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1 Commits

Author SHA1 Message Date
Brooklyn Nicholson c275423d0d feat(tui): add /mouse [on|off|toggle] runtime slash command
Toggle SGR mouse tracking (DEC 1000/1002/1003/1006) at runtime without
restart or env-var spelunking. Fix path when a terminal doesn't honor raw
mode / no-echo and echoes mouse events as visible escape sequences (e.g.
`<35;111;133M` scrolling up the transcript on every mouse move).

- New `/mouse [on|off|toggle]` slash command (persists via config.set key=mouse
  → display.tui_mouse in ~/.hermes/config.yaml).
- New hermes-ink export `setAltScreenMouseTracking(enabled)` that writes
  ENABLE/DISABLE bytes and updates the instance flag without re-entering
  the alt-screen — so live toggles are flicker-free.
- `<AlternateScreen>` mouseTracking prop is frozen at initial value (from
  `HERMES_TUI_DISABLE_MOUSE` env); runtime state lives in `$uiState` and is
  applied via useEffect. Env-var opt-out wins over config so explicit
  HERMES_TUI_DISABLE_MOUSE=1 stays off regardless of persisted state.
- Server: folds `mouse` into the existing compact/statusbar branch in
  config.set/get, defaulting to on.
2026-04-21 17:31:01 -05:00
1549 changed files with 20777 additions and 303796 deletions
-11
View File
@@ -5,15 +5,7 @@
# Dependencies
node_modules
**/node_modules
.venv
**/.venv
# Built artifacts that are regenerated inside the image. Excluded so local
# rebuilds on the developer's machine don't invalidate the npm-install layer
# that now depends on the full ui-tui/packages/hermes-ink/ tree being present.
ui-tui/dist/
ui-tui/packages/hermes-ink/dist/
# CI/CD
.github
@@ -22,6 +14,3 @@ ui-tui/packages/hermes-ink/dist/
.env
*.md
# Runtime data (bind-mounted at /opt/data; must not leak into build context)
data/
-16
View File
@@ -398,19 +398,3 @@ IMAGE_TOOLS_DEBUG=false
# Override STT provider endpoints (for proxies or self-hosted instances)
# GROQ_BASE_URL=https://api.groq.com/openai/v1
# STT_OPENAI_BASE_URL=https://api.openai.com/v1
# =============================================================================
# MICROSOFT TEAMS INTEGRATION
# =============================================================================
# Register a Bot in Azure: https://dev.botframework.com/ → "Register a bot"
# Or use Azure Portal: Azure Active Directory → App registrations → New registration
# Then add the bot to Teams via the Bot Framework or App Studio.
#
# TEAMS_CLIENT_ID= # Azure AD App (client) ID
# TEAMS_CLIENT_SECRET= # Azure AD client secret value
# TEAMS_TENANT_ID= # Azure AD tenant ID (or "common" for multi-tenant)
# TEAMS_ALLOWED_USERS= # Comma-separated AAD object IDs or UPNs
# TEAMS_ALLOW_ALL_USERS=false # Set true to skip the allowlist
# TEAMS_HOME_CHANNEL= # Default channel/chat ID for cron delivery
# TEAMS_HOME_CHANNEL_NAME= # Display name for the home channel
# TEAMS_PORT=3978 # Webhook listen port (Bot Framework default)
+2 -12
View File
@@ -1,18 +1,8 @@
name: 'Setup Nix'
description: 'Install Nix and configure Cachix binary cache'
inputs:
cachix-auth-token:
description: 'Cachix auth token (enables push). Omit for read-only.'
required: false
default: ''
description: 'Install Nix with DeterminateSystems and enable magic-nix-cache'
runs:
using: composite
steps:
- uses: DeterminateSystems/nix-installer-action@ef8a148080ab6020fd15196c2084a2eea5ff2d25 # v22
- uses: cachix/cachix-action@1eb2ef646ac0255473d23a5907ad7b04ce94065c # v17
with:
name: hermes-agent
authToken: ${{ inputs.cachix-auth-token }}
continue-on-error: true
- uses: DeterminateSystems/magic-nix-cache-action@565684385bcd71bad329742eefe8d12f2e765b39 # v13
-13
View File
@@ -53,9 +53,6 @@ jobs:
- name: Extract skill metadata for dashboard
run: python3 website/scripts/extract-skills.py
- name: Regenerate per-skill docs pages + catalogs
run: python3 website/scripts/generate-skill-docs.py
- name: Build skills index (if not already present)
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -76,16 +73,6 @@ jobs:
run: |
mkdir -p _site/docs
cp -r website/build/* _site/docs/
# llms.txt / llms-full.txt are also published at the site root
# (https://hermes-agent.nousresearch.com/llms.txt) because some
# agents and IDE plugins probe the classic root-level path rather
# than /docs/llms.txt. Same file, two URLs, one source of truth.
if [ -f website/build/llms.txt ]; then
cp website/build/llms.txt _site/llms.txt
fi
if [ -f website/build/llms-full.txt ]; then
cp website/build/llms-full.txt _site/llms-full.txt
fi
- name: Upload artifact
uses: actions/upload-pages-artifact@56afc609e74202658d3ffba0e8f6dda462b719fa # v3
-3
View File
@@ -36,9 +36,6 @@ jobs:
- name: Extract skill metadata for dashboard
run: python3 website/scripts/extract-skills.py
- name: Regenerate per-skill docs pages + catalogs
run: python3 website/scripts/generate-skill-docs.py
- name: Lint docs diagrams
run: npm run lint:diagrams
working-directory: website
+68
View File
@@ -0,0 +1,68 @@
name: Nix Lockfile Check
on:
pull_request:
workflow_dispatch:
permissions:
contents: read
pull-requests: write
concurrency:
group: nix-lockfile-check-${{ github.ref }}
cancel-in-progress: true
jobs:
check:
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
- uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4
- uses: ./.github/actions/nix-setup
- name: Resolve head SHA
id: sha
shell: bash
run: |
FULL="${{ github.event.pull_request.head.sha || github.sha }}"
echo "full=$FULL" >> "$GITHUB_OUTPUT"
echo "short=${FULL:0:7}" >> "$GITHUB_OUTPUT"
- name: Check lockfile hashes
id: check
continue-on-error: true
env:
LINK_SHA: ${{ steps.sha.outputs.full }}
run: nix run .#fix-lockfiles -- --check
- name: Post sticky PR comment (stale)
if: steps.check.outputs.stale == 'true' && github.event_name == 'pull_request'
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
message: |
### ⚠️ npm lockfile hash out of date
Checked against commit [`${{ steps.sha.outputs.short }}`](${{ github.server_url }}/${{ github.repository }}/commit/${{ steps.sha.outputs.full }}) (PR head at check time).
The `hash = "sha256-..."` line in these nix files no longer matches the committed `package-lock.json`:
${{ steps.check.outputs.report }}
#### Apply the fix
- [ ] **Apply lockfile fix** — tick to push a commit with the correct hashes to this PR branch
- Or [run the Nix Lockfile Fix workflow](${{ github.server_url }}/${{ github.repository }}/actions/workflows/nix-lockfile-fix.yml) manually (pass PR `#${{ github.event.pull_request.number }}`)
- Or locally: `nix run .#fix-lockfiles -- --apply` and commit the diff
- name: Clear sticky PR comment (resolved)
if: steps.check.outputs.stale == 'false' && github.event_name == 'pull_request'
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
delete: true
- name: Fail if stale
if: steps.check.outputs.stale == 'true'
run: exit 1
+3 -108
View File
@@ -1,13 +1,6 @@
name: Nix Lockfile Fix
on:
push:
branches: [main]
paths:
- 'ui-tui/package-lock.json'
- 'ui-tui/package.json'
- 'web/package-lock.json'
- 'web/package.json'
workflow_dispatch:
inputs:
pr_number:
@@ -26,105 +19,9 @@ concurrency:
cancel-in-progress: false
jobs:
# ── Auto-fix on main ───────────────────────────────────────────────
# Fires when a push to main touches package.json or package-lock.json
# in ui-tui/ or web/. Runs fix-lockfiles and pushes the hash
# update commit directly to main so Nix builds never stay broken.
#
# Safety invariants:
# 1. The fix commit only touches nix/*.nix files, which are NOT in
# the paths filter above, so this cannot re-trigger itself.
# 2. An explicit file-whitelist check before commit aborts if
# fix-lockfiles ever modifies unexpected files.
# 3. Job-level concurrency with cancel-in-progress: true ensures
# back-to-back pushes collapse to the newest; ref: main checkout
# always operates on the latest branch state.
# 4. Uses a GitHub App token (not GITHUB_TOKEN) so the fix commit
# triggers downstream nix.yml verification.
auto-fix-main:
if: github.event_name == 'push'
runs-on: ubuntu-latest
timeout-minutes: 25
concurrency:
group: auto-fix-main
cancel-in-progress: true
steps:
- name: Generate GitHub App token
id: app-token
uses: actions/create-github-app-token@7bfa3a4717ef143a604ee0a99d859b8886a96d00 # v1.9.3
with:
app-id: ${{ secrets.APP_ID }}
private-key: ${{ secrets.APP_PRIVATE_KEY }}
- uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4
with:
ref: main
token: ${{ steps.app-token.outputs.token }}
- uses: ./.github/actions/nix-setup
with:
cachix-auth-token: ${{ secrets.CACHIX_AUTH_TOKEN }}
- name: Apply lockfile hashes
id: apply
run: nix run .#fix-lockfiles -- --apply
- name: Commit & push
if: steps.apply.outputs.changed == 'true'
shell: bash
run: |
set -euo pipefail
# Ensure only nix files were modified — prevents accidental
# self-triggering if fix-lockfiles ever touches package files.
unexpected="$(git diff --name-only | grep -Ev '^nix/(tui|web)\.nix$' || true)"
if [ -n "$unexpected" ]; then
echo "::error::Unexpected modified files: $unexpected"
exit 1
fi
# Record the base SHA before committing — used to detect package
# file changes if we need to rebase after a non-fast-forward push.
BASE_SHA="$(git rev-parse HEAD)"
git config user.name 'github-actions[bot]'
git config user.email '41898282+github-actions[bot]@users.noreply.github.com'
git add nix/tui.nix nix/web.nix
git commit -m "fix(nix): auto-refresh npm lockfile hashes" \
-m "Source: $GITHUB_SHA" \
-m "Run: $GITHUB_SERVER_URL/$GITHUB_REPOSITORY/actions/runs/$GITHUB_RUN_ID"
# Retry push with rebase in case main advanced with an unrelated
# commit during the nix build. Without this, a non-fast-forward
# rejection silently loses the fix. If package files changed during
# the rebase, abort — a fresh auto-fix run will handle the new state.
for attempt in 1 2 3; do
if git push origin HEAD:main; then
exit 0
fi
echo "::warning::Push attempt $attempt failed (non-fast-forward?), rebasing…"
git fetch origin main
# If package files changed between our base and the new main,
# our computed hashes are stale. Abort and let the next triggered
# run recompute from the correct package-lock state.
pkg_changed="$(git diff --name-only "$BASE_SHA"..origin/main -- \
'ui-tui/package-lock.json' 'ui-tui/package.json' \
'web/package-lock.json' 'web/package.json' || true)"
if [ -n "$pkg_changed" ]; then
echo "::warning::Package files changed since hash computation — aborting; a fresh run will recompute"
exit 0
fi
git rebase origin/main
done
echo "::error::Failed to push after 3 rebase attempts"
exit 1
# ── PR fix (manual / checkbox) ─────────────────────────────────────
# Existing behavior: run on manual dispatch OR when a task-list
# checkbox in the sticky lockfile-check comment flips from [ ] to [x].
fix:
# Run on manual dispatch OR when a task-list checkbox in the sticky
# lockfile-check comment flips from `[ ]` to `[x]`.
if: |
github.event_name == 'workflow_dispatch' ||
(github.event_name == 'issue_comment'
@@ -202,12 +99,10 @@ jobs:
fetch-depth: 0
- uses: ./.github/actions/nix-setup
with:
cachix-auth-token: ${{ secrets.CACHIX_AUTH_TOKEN }}
- name: Apply lockfile hashes
id: apply
run: nix run .#fix-lockfiles
run: nix run .#fix-lockfiles -- --apply
- name: Commit & push
if: steps.apply.outputs.changed == 'true'
-84
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@@ -7,7 +7,6 @@ on:
permissions:
contents: read
pull-requests: write
concurrency:
group: nix-${{ github.ref }}
@@ -23,95 +22,12 @@ jobs:
steps:
- uses: actions/checkout@34e114876b0b11c390a56381ad16ebd13914f8d5 # v4
- uses: ./.github/actions/nix-setup
with:
cachix-auth-token: ${{ secrets.CACHIX_AUTH_TOKEN }}
- name: Resolve head SHA
if: github.event_name == 'pull_request'
id: sha
shell: bash
run: |
FULL="${{ github.event.pull_request.head.sha || github.sha }}"
echo "full=$FULL" >> "$GITHUB_OUTPUT"
echo "short=${FULL:0:7}" >> "$GITHUB_OUTPUT"
- name: Check flake
id: flake
if: runner.os == 'Linux'
continue-on-error: true
run: nix flake check --print-build-logs
- name: Build package
id: build
if: runner.os == 'Linux'
continue-on-error: true
run: nix build --print-build-logs
# When the real Nix build fails, run a targeted diagnostic to see if
# the failure is specifically a stale npm lockfile hash in one of the
# known npm subpackages (tui / web). This avoids surfacing a generic
# "build failed" message when the fix is a single known command.
- name: Diagnose npm lockfile hashes
id: hash_check
if: (steps.flake.outcome == 'failure' || steps.build.outcome == 'failure') && runner.os == 'Linux'
continue-on-error: true
env:
LINK_SHA: ${{ steps.sha.outputs.full }}
run: nix run .#fix-lockfiles -- --check
# If fix-lockfiles itself crashes (infrastructure blip, cache throttle,
# etc.) it won't set stale=true/false. Treat that as a distinct failure
# mode rather than silently ignoring it.
- name: Fail if hash check crashed without reporting
if: steps.hash_check.outcome == 'failure' && steps.hash_check.outputs.stale != 'true' && steps.hash_check.outputs.stale != 'false'
run: |
echo "::error::fix-lockfiles exited without reporting stale status — likely an infrastructure or script failure"
exit 1
- name: Post sticky PR comment (stale hashes)
if: steps.hash_check.outputs.stale == 'true' && github.event_name == 'pull_request'
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
message: |
### ⚠️ npm lockfile hash out of date
Checked against commit [`${{ steps.sha.outputs.short }}`](${{ github.server_url }}/${{ github.repository }}/commit/${{ steps.sha.outputs.full }}) (PR head at check time).
The `hash = "sha256-..."` line in these nix files no longer matches the committed `package-lock.json`:
${{ steps.hash_check.outputs.report }}
#### Apply the fix
- [ ] **Apply lockfile fix** — tick to push a commit with the correct hashes to this PR branch
- Or [run the Nix Lockfile Fix workflow](${{ github.server_url }}/${{ github.repository }}/actions/workflows/nix-lockfile-fix.yml) manually (pass PR `#${{ github.event.pull_request.number }}`)
- Or locally: `nix run .#fix-lockfiles` and commit the diff
# Clear the sticky comment when either the build passed outright (no
# hash check needed) or the hash check explicitly returned stale=false
# (build failed for a non-hash reason).
- name: Clear sticky PR comment (resolved)
if: |
github.event_name == 'pull_request' &&
runner.os == 'Linux' &&
(steps.hash_check.outputs.stale == 'false' ||
(steps.flake.outcome == 'success' && steps.build.outcome == 'success'))
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
with:
header: nix-lockfile-check
delete: true
- name: Final fail if build or flake failed
if: steps.flake.outcome == 'failure' || steps.build.outcome == 'failure'
run: |
if [ "${{ steps.hash_check.outputs.stale }}" == "true" ]; then
echo "::error::Nix build failed due to stale npm lockfile hash. Run: nix run .#fix-lockfiles"
else
echo "::error::Nix build/flake check failed. See logs above."
fi
exit 1
- name: Evaluate flake (macOS)
if: runner.os == 'macOS'
run: nix flake show --json > /dev/null
-2
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@@ -1,4 +1,3 @@
.DS_Store
/venv/
/_pycache/
*.pyc*
@@ -69,4 +68,3 @@ mini-swe-agent/
.nix-stamps/
result
website/static/api/skills-index.json
models-dev-upstream/
+77 -224
View File
@@ -5,61 +5,78 @@ Instructions for AI coding assistants and developers working on the hermes-agent
## Development Environment
```bash
# Prefer .venv; fall back to venv if that's what your checkout has.
source .venv/bin/activate # or: source venv/bin/activate
source venv/bin/activate # ALWAYS activate before running Python
```
`scripts/run_tests.sh` probes `.venv` first, then `venv`, then
`$HOME/.hermes/hermes-agent/venv` (for worktrees that share a venv with the
main checkout).
## Project Structure
File counts shift constantly — don't treat the tree below as exhaustive.
The canonical source is the filesystem. The notes call out the load-bearing
entry points you'll actually edit.
```
hermes-agent/
├── run_agent.py # AIAgent class — core conversation loop (~12k LOC)
├── run_agent.py # AIAgent class — core conversation loop
├── model_tools.py # Tool orchestration, discover_builtin_tools(), handle_function_call()
├── toolsets.py # Toolset definitions, _HERMES_CORE_TOOLS list
├── cli.py # HermesCLI class — interactive CLI orchestrator (~11k LOC)
├── cli.py # HermesCLI class — interactive CLI orchestrator
├── hermes_state.py # SessionDB — SQLite session store (FTS5 search)
├── hermes_constants.py # get_hermes_home(), display_hermes_home() — profile-aware paths
├── hermes_logging.py # setup_logging() — agent.log / errors.log / gateway.log (profile-aware)
├── batch_runner.py # Parallel batch processing
├── agent/ # Agent internals (provider adapters, memory, caching, compression, etc.)
├── hermes_cli/ # CLI subcommands, setup wizard, plugins loader, skin engine
├── tools/ # Tool implementations — auto-discovered via tools/registry.py
├── agent/ # Agent internals
│ ├── prompt_builder.py # System prompt assembly
│ ├── context_compressor.py # Auto context compression
│ ├── prompt_caching.py # Anthropic prompt caching
│ ├── auxiliary_client.py # Auxiliary LLM client (vision, summarization)
│ ├── model_metadata.py # Model context lengths, token estimation
│ ├── models_dev.py # models.dev registry integration (provider-aware context)
│ ├── display.py # KawaiiSpinner, tool preview formatting
│ ├── skill_commands.py # Skill slash commands (shared CLI/gateway)
│ └── trajectory.py # Trajectory saving helpers
├── hermes_cli/ # CLI subcommands and setup
│ ├── main.py # Entry point — all `hermes` subcommands
│ ├── config.py # DEFAULT_CONFIG, OPTIONAL_ENV_VARS, migration
│ ├── commands.py # Slash command definitions + SlashCommandCompleter
│ ├── callbacks.py # Terminal callbacks (clarify, sudo, approval)
│ ├── setup.py # Interactive setup wizard
│ ├── skin_engine.py # Skin/theme engine — CLI visual customization
│ ├── skills_config.py # `hermes skills` — enable/disable skills per platform
│ ├── tools_config.py # `hermes tools` — enable/disable tools per platform
│ ├── skills_hub.py # `/skills` slash command (search, browse, install)
│ ├── models.py # Model catalog, provider model lists
│ ├── model_switch.py # Shared /model switch pipeline (CLI + gateway)
│ └── auth.py # Provider credential resolution
├── tools/ # Tool implementations (one file per tool)
│ ├── registry.py # Central tool registry (schemas, handlers, dispatch)
│ ├── approval.py # Dangerous command detection
│ ├── terminal_tool.py # Terminal orchestration
│ ├── process_registry.py # Background process management
│ ├── file_tools.py # File read/write/search/patch
│ ├── web_tools.py # Web search/extract (Parallel + Firecrawl)
│ ├── browser_tool.py # Browserbase browser automation
│ ├── code_execution_tool.py # execute_code sandbox
│ ├── delegate_tool.py # Subagent delegation
│ ├── mcp_tool.py # MCP client (~1050 lines)
│ └── environments/ # Terminal backends (local, docker, ssh, modal, daytona, singularity)
├── gateway/ # Messaging gateway — run.py + session.py + platforms/
│ ├── platforms/ # Adapter per platform (telegram, discord, slack, whatsapp,
│ # homeassistant, signal, matrix, mattermost, email, sms,
│ # dingtalk, wecom, weixin, feishu, qqbot, bluebubbles,
│ │ # webhook, api_server, ...). See ADDING_A_PLATFORM.md.
│ └── builtin_hooks/ # Extension point for always-registered gateway hooks (none shipped)
├── plugins/ # Plugin system (see "Plugins" section below)
│ ├── memory/ # Memory-provider plugins (honcho, mem0, supermemory, ...)
│ ├── context_engine/ # Context-engine plugins
│ └── <others>/ # Dashboard, image-gen, disk-cleanup, examples, ...
├── optional-skills/ # Heavier/niche skills shipped but NOT active by default
├── skills/ # Built-in skills bundled with the repo
├── gateway/ # Messaging platform gateway
│ ├── run.py # Main loop, slash commands, message dispatch
├── session.py # SessionStore — conversation persistence
└── platforms/ # Adapters: telegram, discord, slack, whatsapp, homeassistant, signal, qqbot
├── ui-tui/ # Ink (React) terminal UI — `hermes --tui`
── src/ # entry.tsx, app.tsx, gatewayClient.ts + app/components/hooks/lib
── src/entry.tsx # TTY gate + render()
│ ├── src/app.tsx # Main state machine and UI
│ ├── src/gatewayClient.ts # Child process + JSON-RPC bridge
│ ├── src/app/ # Decomposed app logic (event handler, slash handler, stores, hooks)
│ ├── src/components/ # Ink components (branding, markdown, prompts, pickers, etc.)
│ ├── src/hooks/ # useCompletion, useInputHistory, useQueue, useVirtualHistory
│ └── src/lib/ # Pure helpers (history, osc52, text, rpc, messages)
├── tui_gateway/ # Python JSON-RPC backend for the TUI
│ ├── entry.py # stdio entrypoint
│ ├── server.py # RPC handlers and session logic
│ ├── render.py # Optional rich/ANSI bridge
│ └── slash_worker.py # Persistent HermesCLI subprocess for slash commands
├── acp_adapter/ # ACP server (VS Code / Zed / JetBrains integration)
├── cron/ # Scheduler jobs.py, scheduler.py
├── cron/ # Scheduler (jobs.py, scheduler.py)
├── environments/ # RL training environments (Atropos)
├── scripts/ # run_tests.sh, release.py, auxiliary scripts
── website/ # Docusaurus docs site
└── tests/ # Pytest suite (~15k tests across ~700 files as of Apr 2026)
├── tests/ # Pytest suite (~3000 tests)
── batch_runner.py # Parallel batch processing
```
**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys only).
**Logs:** `~/.hermes/logs/``agent.log` (INFO+), `errors.log` (WARNING+),
`gateway.log` when running the gateway. Profile-aware via `get_hermes_home()`.
Browse with `hermes logs [--follow] [--level ...] [--session ...]`.
**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys)
## File Dependency Chain
@@ -77,30 +94,20 @@ run_agent.py, cli.py, batch_runner.py, environments/
## AIAgent Class (run_agent.py)
The real `AIAgent.__init__` takes ~60 parameters (credentials, routing, callbacks,
session context, budget, credential pool, etc.). The signature below is the
minimum subset you'll usually touch — read `run_agent.py` for the full list.
```python
class AIAgent:
def __init__(self,
base_url: str = None,
api_key: str = None,
provider: str = None,
api_mode: str = None, # "chat_completions" | "codex_responses" | ...
model: str = "", # empty → resolved from config/provider later
max_iterations: int = 90, # tool-calling iterations (shared with subagents)
model: str = "anthropic/claude-opus-4.6",
max_iterations: int = 90,
enabled_toolsets: list = None,
disabled_toolsets: list = None,
quiet_mode: bool = False,
save_trajectories: bool = False,
platform: str = None, # "cli", "telegram", etc.
platform: str = None, # "cli", "telegram", etc.
session_id: str = None,
skip_context_files: bool = False,
skip_memory: bool = False,
credential_pool=None,
# ... plus callbacks, thread/user/chat IDs, iteration_budget, fallback_model,
# checkpoints config, prefill_messages, service_tier, reasoning_config, etc.
# ... plus provider, api_mode, callbacks, routing params
): ...
def chat(self, message: str) -> str:
@@ -113,13 +120,10 @@ class AIAgent:
### Agent Loop
The core loop is inside `run_conversation()` — entirely synchronous, with
interrupt checks, budget tracking, and a one-turn grace call:
The core loop is inside `run_conversation()` — entirely synchronous:
```python
while (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) \
or self._budget_grace_call:
if self._interrupt_requested: break
while api_call_count < self.max_iterations and self.iteration_budget.remaining > 0:
response = client.chat.completions.create(model=model, messages=messages, tools=tool_schemas)
if response.tool_calls:
for tool_call in response.tool_calls:
@@ -130,8 +134,7 @@ while (api_call_count < self.max_iterations and self.iteration_budget.remaining
return response.content
```
Messages follow OpenAI format: `{"role": "system/user/assistant/tool", ...}`.
Reasoning content is stored in `assistant_msg["reasoning"]`.
Messages follow OpenAI format: `{"role": "system/user/assistant/tool", ...}`. Reasoning content is stored in `assistant_msg["reasoning"]`.
---
@@ -240,19 +243,6 @@ npm run fmt # prettier
npm test # vitest
```
### TUI in the Dashboard (`hermes dashboard` → `/chat`)
The dashboard embeds the real `hermes --tui`**not** a rewrite. See `hermes_cli/pty_bridge.py` + the `@app.websocket("/api/pty")` endpoint in `hermes_cli/web_server.py`.
- Browser loads `web/src/pages/ChatPage.tsx`, which mounts xterm.js's `Terminal` with the WebGL renderer, `@xterm/addon-fit` for container-driven resize, and `@xterm/addon-unicode11` for modern wide-character widths.
- `/api/pty?token=…` upgrades to a WebSocket; auth uses the same ephemeral `_SESSION_TOKEN` as REST, via query param (browsers can't set `Authorization` on WS upgrade).
- The server spawns whatever `hermes --tui` would spawn, through `ptyprocess` (POSIX PTY — WSL works, native Windows does not).
- Frames: raw PTY bytes each direction; resize via `\x1b[RESIZE:<cols>;<rows>]` intercepted on the server and applied with `TIOCSWINSZ`.
**Do not re-implement the primary chat experience in React.** The main transcript, composer/input flow (including slash-command behavior), and PTY-backed terminal belong to the embedded `hermes --tui` — anything new you add to Ink shows up in the dashboard automatically. If you find yourself rebuilding the transcript or composer for the dashboard, stop and extend Ink instead.
**Structured React UI around the TUI is allowed when it is not a second chat surface.** Sidebar widgets, inspectors, summaries, status panels, and similar supporting views (e.g. `ChatSidebar`, `ModelPickerDialog`, `ToolCall`) are fine when they complement the embedded TUI rather than replacing the transcript / composer / terminal. Keep their state independent of the PTY child's session and surface their failures non-destructively so the terminal pane keeps working unimpaired.
---
## Adding New Tools
@@ -290,7 +280,7 @@ The registry handles schema collection, dispatch, availability checking, and err
**State files**: If a tool stores persistent state (caches, logs, checkpoints), use `get_hermes_home()` for the base directory — never `Path.home() / ".hermes"`. This ensures each profile gets its own state.
**Agent-level tools** (todo, memory): intercepted by `run_agent.py` before `handle_function_call()`. See `tools/todo_tool.py` for the pattern.
**Agent-level tools** (todo, memory): intercepted by `run_agent.py` before `handle_function_call()`. See `todo_tool.py` for the pattern.
---
@@ -298,13 +288,9 @@ The registry handles schema collection, dispatch, availability checking, and err
### config.yaml options:
1. Add to `DEFAULT_CONFIG` in `hermes_cli/config.py`
2. Bump `_config_version` (check the current value at the top of `DEFAULT_CONFIG`)
ONLY if you need to actively migrate/transform existing user config
(renaming keys, changing structure). Adding a new key to an existing
section is handled automatically by the deep-merge and does NOT require
a version bump.
2. Bump `_config_version` (currently 5) to trigger migration for existing users
### .env variables (SECRETS ONLY — API keys, tokens, passwords):
### .env variables:
1. Add to `OPTIONAL_ENV_VARS` in `hermes_cli/config.py` with metadata:
```python
"NEW_API_KEY": {
@@ -316,29 +302,13 @@ The registry handles schema collection, dispatch, availability checking, and err
},
```
Non-secret settings (timeouts, thresholds, feature flags, paths, display
preferences) belong in `config.yaml`, not `.env`. If internal code needs an
env var mirror for backward compatibility, bridge it from `config.yaml` to
the env var in code (see `gateway_timeout`, `terminal.cwd``TERMINAL_CWD`).
### Config loaders (three paths — know which one you're in):
### Config loaders (two separate systems):
| Loader | Used by | Location |
|--------|---------|----------|
| `load_cli_config()` | CLI mode | `cli.py` — merges CLI-specific defaults + user YAML |
| `load_config()` | `hermes tools`, `hermes setup`, most CLI subcommands | `hermes_cli/config.py` — merges `DEFAULT_CONFIG` + user YAML |
| Direct YAML load | Gateway runtime | `gateway/run.py` + `gateway/config.py` — reads user YAML raw |
If you add a new key and the CLI sees it but the gateway doesn't (or vice
versa), you're on the wrong loader. Check `DEFAULT_CONFIG` coverage.
### Working directory:
- **CLI** — uses the process's current directory (`os.getcwd()`).
- **Messaging** — uses `terminal.cwd` from `config.yaml`. The gateway bridges this
to the `TERMINAL_CWD` env var for child tools. **`MESSAGING_CWD` has been
removed** — the config loader prints a deprecation warning if it's set in
`.env`. Same for `TERMINAL_CWD` in `.env`; the canonical setting is
`terminal.cwd` in `config.yaml`.
| `load_cli_config()` | CLI mode | `cli.py` |
| `load_config()` | `hermes tools`, `hermes setup` | `hermes_cli/config.py` |
| Direct YAML load | Gateway | `gateway/run.py` |
---
@@ -431,95 +401,7 @@ Activate with `/skin cyberpunk` or `display.skin: cyberpunk` in config.yaml.
---
## Plugins
Hermes has two plugin surfaces. Both live under `plugins/` in the repo so
repo-shipped plugins can be discovered alongside user-installed ones in
`~/.hermes/plugins/` and pip-installed entry points.
### General plugins (`hermes_cli/plugins.py` + `plugins/<name>/`)
`PluginManager` discovers plugins from `~/.hermes/plugins/`, `./.hermes/plugins/`,
and pip entry points. Each plugin exposes a `register(ctx)` function that
can:
- Register Python-callback lifecycle hooks:
`pre_tool_call`, `post_tool_call`, `pre_llm_call`, `post_llm_call`,
`on_session_start`, `on_session_end`
- Register new tools via `ctx.register_tool(...)`
- Register CLI subcommands via `ctx.register_cli_command(...)` — the
plugin's argparse tree is wired into `hermes` at startup so
`hermes <pluginname> <subcmd>` works with no change to `main.py`
Hooks are invoked from `model_tools.py` (pre/post tool) and `run_agent.py`
(lifecycle). **Discovery timing pitfall:** `discover_plugins()` only runs
as a side effect of importing `model_tools.py`. Code paths that read plugin
state without importing `model_tools.py` first must call `discover_plugins()`
explicitly (it's idempotent).
### Memory-provider plugins (`plugins/memory/<name>/`)
Separate discovery system for pluggable memory backends. Current built-in
providers include **honcho, mem0, supermemory, byterover, hindsight,
holographic, openviking, retaindb**.
Each provider implements the `MemoryProvider` ABC (see `agent/memory_provider.py`)
and is orchestrated by `agent/memory_manager.py`. Lifecycle hooks include
`sync_turn(turn_messages)`, `prefetch(query)`, `shutdown()`, and optional
`post_setup(hermes_home, config)` for setup-wizard integration.
**CLI commands via `plugins/memory/<name>/cli.py`:** if a memory plugin
defines `register_cli(subparser)`, `discover_plugin_cli_commands()` finds
it at argparse setup time and wires it into `hermes <plugin>`. The
framework only exposes CLI commands for the **currently active** memory
provider (read from `memory.provider` in config.yaml), so disabled
providers don't clutter `hermes --help`.
**Rule (Teknium, May 2026):** plugins MUST NOT modify core files
(`run_agent.py`, `cli.py`, `gateway/run.py`, `hermes_cli/main.py`, etc.).
If a plugin needs a capability the framework doesn't expose, expand the
generic plugin surface (new hook, new ctx method) — never hardcode
plugin-specific logic into core. PR #5295 removed 95 lines of hardcoded
honcho argparse from `main.py` for exactly this reason.
### Dashboard / context-engine / image-gen plugin directories
`plugins/context_engine/`, `plugins/image_gen/`, `plugins/example-dashboard/`,
etc. follow the same pattern (ABC + orchestrator + per-plugin directory).
Context engines plug into `agent/context_engine.py`; image-gen providers
into `agent/image_gen_provider.py`.
---
## Skills
Two parallel surfaces:
- **`skills/`** — built-in skills shipped and loadable by default.
Organized by category directories (e.g. `skills/github/`, `skills/mlops/`).
- **`optional-skills/`** — heavier or niche skills shipped with the repo but
NOT active by default. Installed explicitly via
`hermes skills install official/<category>/<skill>`. Adapter lives in
`tools/skills_hub.py` (`OptionalSkillSource`). Categories include
`autonomous-ai-agents`, `blockchain`, `communication`, `creative`,
`devops`, `email`, `health`, `mcp`, `migration`, `mlops`, `productivity`,
`research`, `security`, `web-development`.
When reviewing skill PRs, check which directory they target — heavy-dep or
niche skills belong in `optional-skills/`.
### SKILL.md frontmatter
Standard fields: `name`, `description`, `version`, `platforms`
(OS-gating list: `[macos]`, `[linux, macos]`, ...),
`metadata.hermes.tags`, `metadata.hermes.category`,
`metadata.hermes.config` (config.yaml settings the skill needs — stored
under `skills.config.<key>`, prompted during setup, injected at load time).
---
## Important Policies
### Prompt Caching Must Not Break
Hermes-Agent ensures caching remains valid throughout a conversation. **Do NOT implement changes that would:**
@@ -529,10 +411,9 @@ Hermes-Agent ensures caching remains valid throughout a conversation. **Do NOT i
Cache-breaking forces dramatically higher costs. The ONLY time we alter context is during context compression.
Slash commands that mutate system-prompt state (skills, tools, memory, etc.)
must be **cache-aware**: default to deferred invalidation (change takes
effect next session), with an opt-in `--now` flag for immediate
invalidation. See `/skills install --now` for the canonical pattern.
### Working Directory Behavior
- **CLI**: Uses current directory (`.``os.getcwd()`)
- **Messaging**: Uses `MESSAGING_CWD` env var (default: home directory)
### Background Process Notifications (Gateway)
@@ -554,7 +435,7 @@ Hermes supports **profiles** — multiple fully isolated instances, each with it
`HERMES_HOME` directory (config, API keys, memory, sessions, skills, gateway, etc.).
The core mechanism: `_apply_profile_override()` in `hermes_cli/main.py` sets
`HERMES_HOME` before any module imports. All `get_hermes_home()` references
`HERMES_HOME` before any module imports. All 119+ references to `get_hermes_home()`
automatically scope to the active profile.
### Rules for profile-safe code
@@ -611,12 +492,8 @@ Use `get_hermes_home()` from `hermes_constants` for code paths. Use `display_her
for user-facing print/log messages. Hardcoding `~/.hermes` breaks profiles — each profile
has its own `HERMES_HOME` directory. This was the source of 5 bugs fixed in PR #3575.
### DO NOT introduce new `simple_term_menu` usage
Existing call sites in `hermes_cli/main.py` remain for legacy fallback only;
the preferred UI is curses (stdlib) because `simple_term_menu` has
ghost-duplication rendering bugs in tmux/iTerm2 with arrow keys. New
interactive menus must use `hermes_cli/curses_ui.py` — see
`hermes_cli/tools_config.py` for the canonical pattern.
### DO NOT use `simple_term_menu` for interactive menus
Rendering bugs in tmux/iTerm2 — ghosting on scroll. Use `curses` (stdlib) instead. See `hermes_cli/tools_config.py` for the pattern.
### DO NOT use `\033[K` (ANSI erase-to-EOL) in spinner/display code
Leaks as literal `?[K` text under `prompt_toolkit`'s `patch_stdout`. Use space-padding: `f"\r{line}{' ' * pad}"`.
@@ -627,30 +504,6 @@ Leaks as literal `?[K` text under `prompt_toolkit`'s `patch_stdout`. Use space-p
### DO NOT hardcode cross-tool references in schema descriptions
Tool schema descriptions must not mention tools from other toolsets by name (e.g., `browser_navigate` saying "prefer web_search"). Those tools may be unavailable (missing API keys, disabled toolset), causing the model to hallucinate calls to non-existent tools. If a cross-reference is needed, add it dynamically in `get_tool_definitions()` in `model_tools.py` — see the `browser_navigate` / `execute_code` post-processing blocks for the pattern.
### The gateway has TWO message guards — both must bypass approval/control commands
When an agent is running, messages pass through two sequential guards:
(1) **base adapter** (`gateway/platforms/base.py`) queues messages in
`_pending_messages` when `session_key in self._active_sessions`, and
(2) **gateway runner** (`gateway/run.py`) intercepts `/stop`, `/new`,
`/queue`, `/status`, `/approve`, `/deny` before they reach
`running_agent.interrupt()`. Any new command that must reach the runner
while the agent is blocked (e.g. approval prompts) MUST bypass BOTH
guards and be dispatched inline, not via `_process_message_background()`
(which races session lifecycle).
### Squash merges from stale branches silently revert recent fixes
Before squash-merging a PR, ensure the branch is up to date with `main`
(`git fetch origin main && git reset --hard origin/main` in the worktree,
then re-apply the PR's commits). A stale branch's version of an unrelated
file will silently overwrite recent fixes on main when squashed. Verify
with `git diff HEAD~1..HEAD` after merging — unexpected deletions are a
red flag.
### Don't wire in dead code without E2E validation
Unused code that was never shipped was dead for a reason. Before wiring an
unused module into a live code path, E2E test the real resolution chain
with actual imports (not mocks) against a temp `HERMES_HOME`.
### Tests must not write to `~/.hermes/`
The `_isolate_hermes_home` autouse fixture in `tests/conftest.py` redirects `HERMES_HOME` to a temp dir. Never hardcode `~/.hermes/` paths in tests.
@@ -706,7 +559,7 @@ If you can't use the wrapper (e.g. on Windows or inside an IDE that shells
pytest directly), at minimum activate the venv and pass `-n 4`:
```bash
source .venv/bin/activate # or: source venv/bin/activate
source venv/bin/activate
python -m pytest tests/ -q -n 4
```
+7 -7
View File
@@ -9,7 +9,7 @@ Thank you for contributing to Hermes Agent! This guide covers everything you nee
We value contributions in this order:
1. **Bug fixes** — crashes, incorrect behavior, data loss. Always top priority.
2. **Cross-platform compatibility** — macOS, different Linux distros, and WSL2 on Windows. We want Hermes to work everywhere.
2. **Cross-platform compatibility** Windows, macOS, different Linux distros, different terminal emulators. We want Hermes to work everywhere.
3. **Security hardening** — shell injection, prompt injection, path traversal, privilege escalation. See [Security](#security-considerations).
4. **Performance and robustness** — retry logic, error handling, graceful degradation.
5. **New skills** — but only broadly useful ones. See [Should it be a Skill or a Tool?](#should-it-be-a-skill-or-a-tool)
@@ -55,10 +55,10 @@ If your skill is specialized, community-contributed, or niche, it's better suite
| Requirement | Notes |
|-------------|-------|
| **Git** | With `--recurse-submodules` support, and the `git-lfs` extension installed |
| **Git** | With `--recurse-submodules` support |
| **Python 3.11+** | uv will install it if missing |
| **uv** | Fast Python package manager ([install](https://docs.astral.sh/uv/)) |
| **Node.js 20+** | Optional — needed for browser tools and WhatsApp bridge (matches root `package.json` engines) |
| **Node.js 18+** | Optional — needed for browser tools and WhatsApp bridge |
### Clone and install
@@ -88,7 +88,7 @@ cp cli-config.yaml.example ~/.hermes/config.yaml
touch ~/.hermes/.env
# Add at minimum an LLM provider key:
echo "OPENROUTER_API_KEY=***" >> ~/.hermes/.env
echo 'OPENROUTER_API_KEY=sk-or-v1-your-key' >> ~/.hermes/.env
```
### Run
@@ -494,7 +494,7 @@ branding:
agent_name: "My Agent"
welcome: "Welcome message"
response_label: " ⚔ Agent "
prompt_symbol: "⚔"
prompt_symbol: "⚔ "
tool_prefix: "╎" # Tool output line prefix
```
@@ -515,7 +515,7 @@ See `hermes_cli/skin_engine.py` for the full schema and existing skins as exampl
## Cross-Platform Compatibility
Hermes runs on Linux, macOS, and WSL2 on Windows. When writing code that touches the OS:
Hermes runs on Linux, macOS, and Windows. When writing code that touches the OS:
### Critical rules
@@ -597,7 +597,7 @@ refactor/description # Code restructuring
1. **Run tests**: `pytest tests/ -v`
2. **Test manually**: Run `hermes` and exercise the code path you changed
3. **Check cross-platform impact**: If you touch file I/O, process management, or terminal handling, consider macOS, Linux, and WSL2
3. **Check cross-platform impact**: If you touch file I/O, process management, or terminal handling, consider Windows and macOS
4. **Keep PRs focused**: One logical change per PR. Don't mix a bug fix with a refactor with a new feature.
### PR description
+6 -35
View File
@@ -10,11 +10,9 @@ ENV PYTHONUNBUFFERED=1
ENV PLAYWRIGHT_BROWSERS_PATH=/opt/hermes/.playwright
# Install system dependencies in one layer, clear APT cache
# tini reaps orphaned zombie processes (MCP stdio subprocesses, git, bun, etc.)
# that would otherwise accumulate when hermes runs as PID 1. See #15012.
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential curl nodejs npm python3 ripgrep ffmpeg gcc python3-dev libffi-dev procps git openssh-client docker-cli tini && \
build-essential nodejs npm python3 ripgrep ffmpeg gcc python3-dev libffi-dev procps git && \
rm -rf /var/lib/apt/lists/*
# Non-root user for runtime; UID can be overridden via HERMES_UID at runtime
@@ -28,56 +26,29 @@ WORKDIR /opt/hermes
# ---------- Layer-cached dependency install ----------
# Copy only package manifests first so npm install + Playwright are cached
# unless the lockfiles themselves change.
#
# ui-tui/packages/hermes-ink/ is copied IN FULL (not just its manifests)
# because it is referenced as a `file:` workspace dependency from
# ui-tui/package.json. Copying the tree up front lets npm resolve the
# workspace to real content instead of stopping at a bare package.json.
COPY package.json package-lock.json ./
COPY web/package.json web/package-lock.json web/
COPY ui-tui/package.json ui-tui/package-lock.json ui-tui/
COPY ui-tui/packages/hermes-ink/ ui-tui/packages/hermes-ink/
# `npm_config_install_links=false` forces npm to install `file:` deps as
# symlinks (the npm 10+ default) even on Debian's older bundled npm 9.x,
# which defaults to `install-links=true` and installs file deps as *copies*.
# The host-side package-lock.json is generated with a newer npm that uses
# symlinks, so an install-as-copy produces a hidden node_modules/.package-lock.json
# that permanently disagrees with the root lock on the @hermes/ink entry.
# That disagreement trips the TUI launcher's `_tui_need_npm_install()`
# check on every startup and triggers a runtime `npm install` that then
# fails with EACCES (node_modules/ is root-owned from build time).
ENV npm_config_install_links=false
RUN npm install --prefer-offline --no-audit && \
npx playwright install --with-deps chromium --only-shell && \
(cd web && npm install --prefer-offline --no-audit) && \
(cd ui-tui && npm install --prefer-offline --no-audit) && \
npm cache clean --force
# ---------- Source code ----------
# .dockerignore excludes node_modules, so the installs above survive.
COPY --chown=hermes:hermes . .
# Build browser dashboard and terminal UI assets.
RUN cd web && npm run build && \
cd ../ui-tui && npm run build
# ---------- Permissions ----------
# Make install dir world-readable so any HERMES_UID can read it at runtime.
# The venv needs to be traversable too.
USER root
RUN chmod -R a+rX /opt/hermes
# Start as root so the entrypoint can usermod/groupmod + gosu.
# If HERMES_UID is unset, the entrypoint drops to the default hermes user (10000).
# Build web dashboard (Vite outputs to hermes_cli/web_dist/)
RUN cd web && npm run build
# ---------- Python virtualenv ----------
RUN chown hermes:hermes /opt/hermes
USER hermes
RUN uv venv && \
uv pip install --no-cache-dir -e ".[all]"
# ---------- Runtime ----------
ENV HERMES_WEB_DIST=/opt/hermes/hermes_cli/web_dist
ENV HERMES_HOME=/opt/data
ENV PATH="/opt/data/.local/bin:${PATH}"
VOLUME [ "/opt/data" ]
ENTRYPOINT [ "/usr/bin/tini", "-g", "--", "/opt/hermes/docker/entrypoint.sh" ]
ENTRYPOINT [ "/opt/hermes/docker/entrypoint.sh" ]
+8 -3
View File
@@ -76,7 +76,7 @@ Hermes has two entry points: start the terminal UI with `hermes`, or run the gat
| Set a personality | `/personality [name]` | `/personality [name]` |
| Retry or undo the last turn | `/retry`, `/undo` | `/retry`, `/undo` |
| Compress context / check usage | `/compress`, `/usage`, `/insights [--days N]` | `/compress`, `/usage`, `/insights [days]` |
| Browse skills | `/skills` or `/<skill-name>` | `/<skill-name>` |
| Browse skills | `/skills` or `/<skill-name>` | `/skills` or `/<skill-name>` |
| Interrupt current work | `Ctrl+C` or send a new message | `/stop` or send a new message |
| Platform-specific status | `/platforms` | `/status`, `/sethome` |
@@ -157,10 +157,14 @@ curl -LsSf https://astral.sh/uv/install.sh | sh
uv venv venv --python 3.11
source venv/bin/activate
uv pip install -e ".[all,dev]"
scripts/run_tests.sh
python -m pytest tests/ -q
```
> **RL Training (optional):** The RL/Atropos integration (`environments/`) ships via the `atroposlib` and `tinker` dependencies pulled in by `.[all,dev]` — no submodule setup required.
> **RL Training (optional):** To work on the RL/Tinker-Atropos integration:
> ```bash
> git submodule update --init tinker-atropos
> uv pip install -e "./tinker-atropos"
> ```
---
@@ -169,6 +173,7 @@ scripts/run_tests.sh
- 💬 [Discord](https://discord.gg/NousResearch)
- 📚 [Skills Hub](https://agentskills.io)
- 🐛 [Issues](https://github.com/NousResearch/hermes-agent/issues)
- 💡 [Discussions](https://github.com/NousResearch/hermes-agent/discussions)
- 🔌 [HermesClaw](https://github.com/AaronWong1999/hermesclaw) — Community WeChat bridge: Run Hermes Agent and OpenClaw on the same WeChat account.
---
-453
View File
@@ -1,453 +0,0 @@
# Hermes Agent v0.11.0 (v2026.4.23)
**Release Date:** April 23, 2026
**Since v0.9.0:** 1,556 commits · 761 merged PRs · 1,314 files changed · 224,174 insertions · 29 community contributors (290 including co-authors)
> The Interface release — a full React/Ink rewrite of the interactive CLI, a pluggable transport architecture underneath every provider, native AWS Bedrock support, five new inference paths, a 17th messaging platform (QQBot), a dramatically expanded plugin surface, and GPT-5.5 via Codex OAuth.
This release also folds in all the highlights deferred from v0.10.0 (which shipped only the Nous Tool Gateway) — so it covers roughly two weeks of work across the whole stack.
---
## ✨ Highlights
- **New Ink-based TUI** — `hermes --tui` is now a full React/Ink rewrite of the interactive CLI, with a Python JSON-RPC backend (`tui_gateway`). Sticky composer, live streaming with OSC-52 clipboard support, stable picker keys, status bar with per-turn stopwatch and git branch, `/clear` confirm, light-theme preset, and a subagent spawn observability overlay. ~310 commits to `ui-tui/` + `tui_gateway/`. (@OutThisLife + Teknium)
- **Transport ABC + Native AWS Bedrock** — Format conversion and HTTP transport were extracted from `run_agent.py` into a pluggable `agent/transports/` layer. `AnthropicTransport`, `ChatCompletionsTransport`, `ResponsesApiTransport`, and `BedrockTransport` each own their own format conversion and API shape. Native AWS Bedrock support via the Converse API ships on top of the new abstraction. ([#10549](https://github.com/NousResearch/hermes-agent/pull/10549), [#13347](https://github.com/NousResearch/hermes-agent/pull/13347), [#13366](https://github.com/NousResearch/hermes-agent/pull/13366), [#13430](https://github.com/NousResearch/hermes-agent/pull/13430), [#13805](https://github.com/NousResearch/hermes-agent/pull/13805), [#13814](https://github.com/NousResearch/hermes-agent/pull/13814) — @kshitijk4poor + Teknium)
- **Five new inference paths** — Native NVIDIA NIM ([#11774](https://github.com/NousResearch/hermes-agent/pull/11774)), Arcee AI ([#9276](https://github.com/NousResearch/hermes-agent/pull/9276)), Step Plan ([#13893](https://github.com/NousResearch/hermes-agent/pull/13893)), Google Gemini CLI OAuth ([#11270](https://github.com/NousResearch/hermes-agent/pull/11270)), and Vercel ai-gateway with pricing + dynamic discovery ([#13223](https://github.com/NousResearch/hermes-agent/pull/13223) — @jerilynzheng). Plus Gemini routed through the native AI Studio API for better performance ([#12674](https://github.com/NousResearch/hermes-agent/pull/12674)).
- **GPT-5.5 over Codex OAuth** — OpenAI's new GPT-5.5 reasoning model is now available through your ChatGPT Codex OAuth, with live model discovery wired into the model picker so new OpenAI releases show up without catalog updates. ([#14720](https://github.com/NousResearch/hermes-agent/pull/14720))
- **QQBot — 17th supported platform** — Native QQBot adapter via QQ Official API v2, with QR scan-to-configure setup wizard, streaming cursor, emoji reactions, and DM/group policy gating that matches WeCom/Weixin parity. ([#9364](https://github.com/NousResearch/hermes-agent/pull/9364), [#11831](https://github.com/NousResearch/hermes-agent/pull/11831))
- **Plugin surface expanded** — Plugins can now register slash commands (`register_command`), dispatch tools directly (`dispatch_tool`), block tool execution from hooks (`pre_tool_call` can veto), rewrite tool results (`transform_tool_result`), transform terminal output (`transform_terminal_output`), ship image_gen backends, and add custom dashboard tabs. The bundled disk-cleanup plugin is opt-in by default as a reference implementation. ([#9377](https://github.com/NousResearch/hermes-agent/pull/9377), [#10626](https://github.com/NousResearch/hermes-agent/pull/10626), [#10763](https://github.com/NousResearch/hermes-agent/pull/10763), [#10951](https://github.com/NousResearch/hermes-agent/pull/10951), [#12929](https://github.com/NousResearch/hermes-agent/pull/12929), [#12944](https://github.com/NousResearch/hermes-agent/pull/12944), [#12972](https://github.com/NousResearch/hermes-agent/pull/12972), [#13799](https://github.com/NousResearch/hermes-agent/pull/13799), [#14175](https://github.com/NousResearch/hermes-agent/pull/14175))
- **`/steer` — mid-run agent nudges** — `/steer <prompt>` injects a note that the running agent sees after its next tool call, without interrupting the turn or breaking prompt cache. For when you want to course-correct an agent in-flight. ([#12116](https://github.com/NousResearch/hermes-agent/pull/12116))
- **Shell hooks** — Wire any shell script as a Hermes lifecycle hook (pre_tool_call, post_tool_call, on_session_start, etc.) without writing a Python plugin. ([#13296](https://github.com/NousResearch/hermes-agent/pull/13296))
- **Webhook direct-delivery mode** — Webhook subscriptions can now forward payloads straight to a platform chat without going through the agent — zero-LLM push notifications for alerting, uptime checks, and event streams. ([#12473](https://github.com/NousResearch/hermes-agent/pull/12473))
- **Smarter delegation** — Subagents now have an explicit `orchestrator` role that can spawn their own workers, with configurable `max_spawn_depth` (default flat). Concurrent sibling subagents share filesystem state through a file-coordination layer so they don't clobber each other's edits. ([#13691](https://github.com/NousResearch/hermes-agent/pull/13691), [#13718](https://github.com/NousResearch/hermes-agent/pull/13718))
- **Auxiliary models — configurable UI + main-model-first** — `hermes model` has a dedicated "Configure auxiliary models" screen for per-task overrides (compression, vision, session_search, title_generation). `auto` routing now defaults to the main model for side tasks across all users (previously aggregator users were silently routed to a cheap provider-side default). ([#11891](https://github.com/NousResearch/hermes-agent/pull/11891), [#11900](https://github.com/NousResearch/hermes-agent/pull/11900))
- **Dashboard plugin system + live theme switching** — The web dashboard is now extensible. Third-party plugins can add custom tabs, widgets, and views without forking. Paired with a live-switching theme system — themes now control colors, fonts, layout, and density — so users can hot-swap the dashboard look without a reload. Same theming discipline the CLI has, now on the web. ([#10951](https://github.com/NousResearch/hermes-agent/pull/10951), [#10687](https://github.com/NousResearch/hermes-agent/pull/10687), [#14725](https://github.com/NousResearch/hermes-agent/pull/14725))
- **Dashboard polish** — i18n (English + Chinese), react-router sidebar layout, mobile-responsive, Vercel deployment, real per-session API call tracking, and one-click update + gateway restart buttons. ([#9228](https://github.com/NousResearch/hermes-agent/pull/9228), [#9370](https://github.com/NousResearch/hermes-agent/pull/9370), [#9453](https://github.com/NousResearch/hermes-agent/pull/9453), [#10686](https://github.com/NousResearch/hermes-agent/pull/10686), [#13526](https://github.com/NousResearch/hermes-agent/pull/13526), [#14004](https://github.com/NousResearch/hermes-agent/pull/14004) — @austinpickett + @DeployFaith + Teknium)
---
## 🏗️ Core Agent & Architecture
### Transport Layer (NEW)
- **Transport ABC** abstracts format conversion and HTTP transport from `run_agent.py` into `agent/transports/` ([#13347](https://github.com/NousResearch/hermes-agent/pull/13347))
- **AnthropicTransport** — Anthropic Messages API path ([#13366](https://github.com/NousResearch/hermes-agent/pull/13366), @kshitijk4poor)
- **ChatCompletionsTransport** — default path for OpenAI-compatible providers ([#13805](https://github.com/NousResearch/hermes-agent/pull/13805))
- **ResponsesApiTransport** — OpenAI Responses API + Codex build_kwargs wiring ([#13430](https://github.com/NousResearch/hermes-agent/pull/13430), @kshitijk4poor)
- **BedrockTransport** — AWS Bedrock Converse API transport ([#13814](https://github.com/NousResearch/hermes-agent/pull/13814))
### Provider & Model Support
- **Native AWS Bedrock provider** via Converse API ([#10549](https://github.com/NousResearch/hermes-agent/pull/10549))
- **NVIDIA NIM native provider** (salvage of #11703) ([#11774](https://github.com/NousResearch/hermes-agent/pull/11774))
- **Arcee AI direct provider** ([#9276](https://github.com/NousResearch/hermes-agent/pull/9276))
- **Step Plan provider** (salvage #6005) ([#13893](https://github.com/NousResearch/hermes-agent/pull/13893), @kshitijk4poor)
- **Google Gemini CLI OAuth** inference provider ([#11270](https://github.com/NousResearch/hermes-agent/pull/11270))
- **Vercel ai-gateway** with pricing, attribution, and dynamic discovery ([#13223](https://github.com/NousResearch/hermes-agent/pull/13223), @jerilynzheng)
- **GPT-5.5 over Codex OAuth** with live model discovery in the picker ([#14720](https://github.com/NousResearch/hermes-agent/pull/14720))
- **Gemini routed through native AI Studio API** ([#12674](https://github.com/NousResearch/hermes-agent/pull/12674))
- **xAI Grok upgraded to Responses API** ([#10783](https://github.com/NousResearch/hermes-agent/pull/10783))
- **Ollama improvements** — Cloud provider support, GLM continuation, `think=false` control, surrogate sanitization, `/v1` hint ([#10782](https://github.com/NousResearch/hermes-agent/pull/10782))
- **Kimi K2.6** across OpenRouter, Nous Portal, native Kimi, and HuggingFace ([#13148](https://github.com/NousResearch/hermes-agent/pull/13148), [#13152](https://github.com/NousResearch/hermes-agent/pull/13152), [#13169](https://github.com/NousResearch/hermes-agent/pull/13169))
- **Kimi K2.5** promoted to first position in all model suggestion lists ([#11745](https://github.com/NousResearch/hermes-agent/pull/11745), @kshitijk4poor)
- **Xiaomi MiMo v2.5-pro + v2.5** on OpenRouter, Nous Portal, and native ([#14184](https://github.com/NousResearch/hermes-agent/pull/14184), [#14635](https://github.com/NousResearch/hermes-agent/pull/14635), @kshitijk4poor)
- **GLM-5V-Turbo** for coding plan ([#9907](https://github.com/NousResearch/hermes-agent/pull/9907))
- **Claude Opus 4.7** in Nous Portal catalog ([#11398](https://github.com/NousResearch/hermes-agent/pull/11398))
- **OpenRouter elephant-alpha** in curated lists ([#9378](https://github.com/NousResearch/hermes-agent/pull/9378))
- **OpenCode-Go** — Kimi K2.6 and Qwen3.5/3.6 Plus in curated catalog ([#13429](https://github.com/NousResearch/hermes-agent/pull/13429))
- **minimax/minimax-m2.5:free** in OpenRouter catalog ([#13836](https://github.com/NousResearch/hermes-agent/pull/13836))
- **`/model` merges models.dev entries** for lesser-loved providers ([#14221](https://github.com/NousResearch/hermes-agent/pull/14221))
- **Per-provider + per-model `request_timeout_seconds`** config ([#12652](https://github.com/NousResearch/hermes-agent/pull/12652))
- **Configurable API retry count** via `agent.api_max_retries` ([#14730](https://github.com/NousResearch/hermes-agent/pull/14730))
- **ctx_size context length key** for Lemonade server (salvage #8536) ([#14215](https://github.com/NousResearch/hermes-agent/pull/14215))
- **Custom provider display name prompt** ([#9420](https://github.com/NousResearch/hermes-agent/pull/9420))
- **Recommendation badges** on tool provider selection ([#9929](https://github.com/NousResearch/hermes-agent/pull/9929))
- Fix: correct GPT-5 family context lengths in fallback defaults ([#9309](https://github.com/NousResearch/hermes-agent/pull/9309))
- Fix: clamp `minimal` reasoning effort to `low` on Responses API ([#9429](https://github.com/NousResearch/hermes-agent/pull/9429))
- Fix: strip reasoning item IDs from Responses API input when `store=False` ([#10217](https://github.com/NousResearch/hermes-agent/pull/10217))
- Fix: OpenViking correct account default + commit session on `/new` and compress ([#10463](https://github.com/NousResearch/hermes-agent/pull/10463))
- Fix: Kimi `/coding` thinking block survival + empty reasoning_content + block ordering (multiple PRs)
- Fix: don't send Anthropic thinking to api.kimi.com/coding ([#13826](https://github.com/NousResearch/hermes-agent/pull/13826))
- Fix: send `max_tokens`, `reasoning_effort`, and `thinking` for Kimi/Moonshot
- Fix: stream reasoning content through OpenAI-compatible providers that emit it
### Agent Loop & Conversation
- **`/steer <prompt>`** — mid-run agent nudges after next tool call ([#12116](https://github.com/NousResearch/hermes-agent/pull/12116))
- **Orchestrator role + configurable spawn depth** for `delegate_task` (default flat) ([#13691](https://github.com/NousResearch/hermes-agent/pull/13691))
- **Cross-agent file state coordination** for concurrent subagents ([#13718](https://github.com/NousResearch/hermes-agent/pull/13718))
- **Compressor smart collapse, dedup, anti-thrashing**, template upgrade, hardening ([#10088](https://github.com/NousResearch/hermes-agent/pull/10088))
- **Compression summaries respect the conversation's language** ([#12556](https://github.com/NousResearch/hermes-agent/pull/12556))
- **Compression model falls back to main model** on permanent 503/404 ([#10093](https://github.com/NousResearch/hermes-agent/pull/10093))
- **Auto-continue interrupted agent work** after gateway restart ([#9934](https://github.com/NousResearch/hermes-agent/pull/9934))
- **Activity heartbeats** prevent false gateway inactivity timeouts ([#10501](https://github.com/NousResearch/hermes-agent/pull/10501))
- **Auxiliary models UI** — dedicated screen for per-task overrides ([#11891](https://github.com/NousResearch/hermes-agent/pull/11891))
- **Auxiliary auto routing defaults to main model** for all users ([#11900](https://github.com/NousResearch/hermes-agent/pull/11900))
- **PLATFORM_HINTS for Matrix, Mattermost, Feishu** ([#14428](https://github.com/NousResearch/hermes-agent/pull/14428), @alt-glitch)
- Fix: reset retry counters after compression; stop poisoning conversation history ([#10055](https://github.com/NousResearch/hermes-agent/pull/10055))
- Fix: break compression-exhaustion infinite loop and auto-reset session ([#10063](https://github.com/NousResearch/hermes-agent/pull/10063))
- Fix: stale agent timeout, uv venv detection, empty response after tools ([#10065](https://github.com/NousResearch/hermes-agent/pull/10065))
- Fix: prevent premature loop exit when weak models return empty after substantive tool calls ([#10472](https://github.com/NousResearch/hermes-agent/pull/10472))
- Fix: preserve pre-start terminal interrupts ([#10504](https://github.com/NousResearch/hermes-agent/pull/10504))
- Fix: improve interrupt responsiveness during concurrent tool execution ([#10935](https://github.com/NousResearch/hermes-agent/pull/10935))
- Fix: word-wrap spinner, interruptable agent join, and delegate_task interrupt ([#10940](https://github.com/NousResearch/hermes-agent/pull/10940))
- Fix: `/stop` no longer resets the session ([#9224](https://github.com/NousResearch/hermes-agent/pull/9224))
- Fix: honor interrupts during MCP tool waits ([#9382](https://github.com/NousResearch/hermes-agent/pull/9382), @helix4u)
- Fix: break stuck session resume loops after repeated restarts ([#9941](https://github.com/NousResearch/hermes-agent/pull/9941))
- Fix: empty response nudge crash + placeholder leak to cron targets ([#11021](https://github.com/NousResearch/hermes-agent/pull/11021))
- Fix: streaming cursor sanitization to prevent message truncation (multiple PRs)
- Fix: resolve `context_length` for plugin context engines ([#9238](https://github.com/NousResearch/hermes-agent/pull/9238))
### Session & Memory
- **Auto-prune old sessions + VACUUM state.db** at startup ([#13861](https://github.com/NousResearch/hermes-agent/pull/13861))
- **Honcho overhaul** — context injection, 5-tool surface, cost safety, session isolation ([#10619](https://github.com/NousResearch/hermes-agent/pull/10619))
- **Hindsight richer session-scoped retain metadata** (salvage of #6290) ([#13987](https://github.com/NousResearch/hermes-agent/pull/13987))
- Fix: deduplicate memory provider tools to prevent 400 on strict providers ([#10511](https://github.com/NousResearch/hermes-agent/pull/10511))
- Fix: discover user-installed memory providers from `$HERMES_HOME/plugins/` ([#10529](https://github.com/NousResearch/hermes-agent/pull/10529))
- Fix: add `on_memory_write` bridge to sequential tool execution path ([#10507](https://github.com/NousResearch/hermes-agent/pull/10507))
- Fix: preserve `session_id` across `previous_response_id` chains in `/v1/responses` ([#10059](https://github.com/NousResearch/hermes-agent/pull/10059))
---
## 🖥️ New Ink-based TUI
A full React/Ink rewrite of the interactive CLI — invoked via `hermes --tui` or `HERMES_TUI=1`. Shipped across ~310 commits to `ui-tui/` and `tui_gateway/`.
### TUI Foundations
- New TUI based on Ink + Python JSON-RPC backend
- Prettier + ESLint + vitest tooling for `ui-tui/`
- Entry split between `src/entry.tsx` (TTY gate) and `src/app.tsx` (state machine)
- Persistent `_SlashWorker` subprocess for slash command dispatch
### UX & Features
- **Stable picker keys, /clear confirm, light-theme preset** ([#12312](https://github.com/NousResearch/hermes-agent/pull/12312), @OutThisLife)
- **Git branch in status bar** cwd label ([#12305](https://github.com/NousResearch/hermes-agent/pull/12305), @OutThisLife)
- **Per-turn elapsed stopwatch in FaceTicker + done-in sys line** ([#13105](https://github.com/NousResearch/hermes-agent/pull/13105), @OutThisLife)
- **Subagent spawn observability overlay** ([#14045](https://github.com/NousResearch/hermes-agent/pull/14045), @OutThisLife)
- **Per-prompt elapsed stopwatch in status bar** ([#12948](https://github.com/NousResearch/hermes-agent/pull/12948))
- Sticky composer that freezes during scroll
- OSC-52 clipboard support for copy across SSH sessions
- Virtualized history rendering for performance
- Slash command autocomplete via `complete.slash` RPC
- Path autocomplete via `complete.path` RPC
- Dozens of resize/ghosting/sticky-prompt fixes landed through the week
### Structural Refactors
- Decomposed `app.tsx` into `app/event-handler`, `app/slash-handler`, `app/stores`, `app/hooks` ([#14640](https://github.com/NousResearch/hermes-agent/pull/14640) and surrounding)
- Component split: `branding.tsx`, `markdown.tsx`, `prompts.tsx`, `sessionPicker.tsx`, `messageLine.tsx`, `thinking.tsx`, `maskedPrompt.tsx`
- Hook split: `useCompletion`, `useInputHistory`, `useQueue`, `useVirtualHistory`
---
## 📱 Messaging Platforms (Gateway)
### New Platforms
- **QQBot (17th platform)** — QQ Official API v2 adapter with QR setup, streaming, package split ([#9364](https://github.com/NousResearch/hermes-agent/pull/9364), [#11831](https://github.com/NousResearch/hermes-agent/pull/11831))
### Telegram
- **Dedicated `TELEGRAM_PROXY` env var + config.yaml proxy support** (closes #9414, #6530, #9074, #7786) ([#10681](https://github.com/NousResearch/hermes-agent/pull/10681))
- **`ignored_threads` config** for Telegram groups ([#9530](https://github.com/NousResearch/hermes-agent/pull/9530))
- **Config option to disable link previews** (closes #8728) ([#10610](https://github.com/NousResearch/hermes-agent/pull/10610))
- **Auto-wrap markdown tables** in code blocks ([#11794](https://github.com/NousResearch/hermes-agent/pull/11794))
- Fix: prevent duplicate replies when stream task is cancelled ([#9319](https://github.com/NousResearch/hermes-agent/pull/9319))
- Fix: prevent streaming cursor (▉) from appearing as standalone messages ([#9538](https://github.com/NousResearch/hermes-agent/pull/9538))
- Fix: retry transient tool sends + cold-boot budget ([#10947](https://github.com/NousResearch/hermes-agent/pull/10947))
- Fix: Markdown special char escaping in `send_exec_approval`
- Fix: parentheses in URLs during MarkdownV2 link conversion
- Fix: Unicode dash normalization in model switch (closes iOS smart-punctuation issue)
- Many platform hint / streaming / session-key fixes
### Discord
- **Forum channel support** (salvage of #10145 + media + polish) ([#11920](https://github.com/NousResearch/hermes-agent/pull/11920))
- **`DISCORD_ALLOWED_ROLES`** for role-based access control ([#11608](https://github.com/NousResearch/hermes-agent/pull/11608))
- **Config option to disable slash commands** (salvage #13130) ([#14315](https://github.com/NousResearch/hermes-agent/pull/14315))
- **Native `send_animation`** for inline GIF playback ([#10283](https://github.com/NousResearch/hermes-agent/pull/10283))
- **`send_message` Discord media attachments** ([#10246](https://github.com/NousResearch/hermes-agent/pull/10246))
- **`/skill` command group** with category subcommands ([#9909](https://github.com/NousResearch/hermes-agent/pull/9909))
- **Extract reply text from message references** ([#9781](https://github.com/NousResearch/hermes-agent/pull/9781))
### Feishu
- **Intelligent reply on document comments** with 3-tier access control ([#11898](https://github.com/NousResearch/hermes-agent/pull/11898))
- **Show processing state via reactions** on user messages ([#12927](https://github.com/NousResearch/hermes-agent/pull/12927))
- **Preserve @mention context for agent consumption** (salvage #13874) ([#14167](https://github.com/NousResearch/hermes-agent/pull/14167))
### DingTalk
- **`require_mention` + `allowed_users` gating** (parity with Slack/Telegram/Discord) ([#11564](https://github.com/NousResearch/hermes-agent/pull/11564))
- **QR-code device-flow authorization** for setup wizard ([#11574](https://github.com/NousResearch/hermes-agent/pull/11574))
- **AI Cards streaming, emoji reactions, and media handling** (salvage of #10985) ([#11910](https://github.com/NousResearch/hermes-agent/pull/11910))
### WhatsApp
- **`send_voice`** — native audio message delivery ([#13002](https://github.com/NousResearch/hermes-agent/pull/13002))
- **`dm_policy` and `group_policy`** parity with WeCom/Weixin/QQ adapters ([#13151](https://github.com/NousResearch/hermes-agent/pull/13151))
### WeCom / Weixin
- **WeCom QR-scan bot creation + interactive setup wizard** (salvage #13923) ([#13961](https://github.com/NousResearch/hermes-agent/pull/13961))
### Signal
- **Media delivery support** via `send_message` ([#13178](https://github.com/NousResearch/hermes-agent/pull/13178))
### Slack
- **Per-thread sessions for DMs by default** ([#10987](https://github.com/NousResearch/hermes-agent/pull/10987))
### BlueBubbles (iMessage)
- Group chat session separation, webhook registration & auth fixes ([#9806](https://github.com/NousResearch/hermes-agent/pull/9806))
### Gateway Core
- **Gateway proxy mode** — forward messages to a remote API server ([#9787](https://github.com/NousResearch/hermes-agent/pull/9787))
- **Per-channel ephemeral prompts** (Discord, Telegram, Slack, Mattermost) ([#10564](https://github.com/NousResearch/hermes-agent/pull/10564))
- **Surface plugin slash commands** natively on all platforms + decision-capable command hook ([#14175](https://github.com/NousResearch/hermes-agent/pull/14175))
- **Support document/archive extensions in MEDIA: tag extraction** (salvage #8255) ([#14307](https://github.com/NousResearch/hermes-agent/pull/14307))
- **Recognize `.pdf` in MEDIA: tag extraction** ([#13683](https://github.com/NousResearch/hermes-agent/pull/13683))
- **`--all` flag for `gateway start` and `restart`** ([#10043](https://github.com/NousResearch/hermes-agent/pull/10043))
- **Notify active sessions on gateway shutdown** + update health check ([#9850](https://github.com/NousResearch/hermes-agent/pull/9850))
- **Block agent from self-destructing the gateway** via terminal (closes #6666) ([#9895](https://github.com/NousResearch/hermes-agent/pull/9895))
- Fix: suppress duplicate replies on interrupt and streaming flood control ([#10235](https://github.com/NousResearch/hermes-agent/pull/10235))
- Fix: close temporary agents after one-off tasks ([#11028](https://github.com/NousResearch/hermes-agent/pull/11028), @kshitijk4poor)
- Fix: busy-session ack when user messages during active agent run ([#10068](https://github.com/NousResearch/hermes-agent/pull/10068))
- Fix: route watch-pattern notifications to the originating session ([#10460](https://github.com/NousResearch/hermes-agent/pull/10460))
- Fix: preserve notify context in executor threads ([#10921](https://github.com/NousResearch/hermes-agent/pull/10921), @kshitijk4poor)
- Fix: avoid duplicate replies after interrupted long tasks ([#11018](https://github.com/NousResearch/hermes-agent/pull/11018))
- Fix: unlink stale PID + lock files on cleanup
- Fix: force-unlink stale PID file after `--replace` takeover
---
## 🔧 Tool System
### Plugin Surface (major expansion)
- **`register_command()`** — plugins can now add slash commands ([#10626](https://github.com/NousResearch/hermes-agent/pull/10626))
- **`dispatch_tool()`** — plugins can invoke tools from their code ([#10763](https://github.com/NousResearch/hermes-agent/pull/10763))
- **`pre_tool_call` blocking** — plugins can veto tool execution ([#9377](https://github.com/NousResearch/hermes-agent/pull/9377))
- **`transform_tool_result`** — plugins rewrite tool results generically ([#12972](https://github.com/NousResearch/hermes-agent/pull/12972))
- **`transform_terminal_output`** — plugins rewrite terminal tool output ([#12929](https://github.com/NousResearch/hermes-agent/pull/12929))
- **Namespaced skill registration** for plugin skill bundles ([#9786](https://github.com/NousResearch/hermes-agent/pull/9786))
- **Opt-in-by-default + bundled disk-cleanup plugin** (salvage #12212) ([#12944](https://github.com/NousResearch/hermes-agent/pull/12944))
- **Pluggable `image_gen` backends + OpenAI provider** ([#13799](https://github.com/NousResearch/hermes-agent/pull/13799))
- **`openai-codex` image_gen plugin** (gpt-image-2 via Codex OAuth) ([#14317](https://github.com/NousResearch/hermes-agent/pull/14317))
- **Shell hooks** — wire shell scripts as hook callbacks ([#13296](https://github.com/NousResearch/hermes-agent/pull/13296))
### Browser
- **`browser_cdp` raw DevTools Protocol passthrough** ([#12369](https://github.com/NousResearch/hermes-agent/pull/12369))
- Camofox hardening + connection stability across the window
### Execute Code
- **Project/strict execution modes** (default: project) ([#11971](https://github.com/NousResearch/hermes-agent/pull/11971))
### Image Generation
- **Multi-model FAL support** with picker in `hermes tools` ([#11265](https://github.com/NousResearch/hermes-agent/pull/11265))
- **Recraft V3 → V4 Pro, Nano Banana → Pro upgrades** ([#11406](https://github.com/NousResearch/hermes-agent/pull/11406))
- **GPT Image 2** in FAL catalog ([#13677](https://github.com/NousResearch/hermes-agent/pull/13677))
- **xAI image generation provider** (grok-imagine-image) ([#14765](https://github.com/NousResearch/hermes-agent/pull/14765))
### TTS / STT / Voice
- **Google Gemini TTS provider** ([#11229](https://github.com/NousResearch/hermes-agent/pull/11229))
- **xAI Grok STT provider** ([#14473](https://github.com/NousResearch/hermes-agent/pull/14473))
- **xAI TTS** (shipped with Responses API upgrade) ([#10783](https://github.com/NousResearch/hermes-agent/pull/10783))
- **KittenTTS local provider** (salvage of #2109) ([#13395](https://github.com/NousResearch/hermes-agent/pull/13395))
- **CLI record beep toggle** ([#13247](https://github.com/NousResearch/hermes-agent/pull/13247), @helix4u)
### Webhook / Cron
- **Webhook direct-delivery mode** — zero-LLM push notifications ([#12473](https://github.com/NousResearch/hermes-agent/pull/12473))
- **Cron `wakeAgent` gate** — scripts can skip the agent entirely ([#12373](https://github.com/NousResearch/hermes-agent/pull/12373))
- **Cron per-job `enabled_toolsets`** — cap token overhead + cost per job ([#14767](https://github.com/NousResearch/hermes-agent/pull/14767))
### Delegate
- **Orchestrator role** + configurable spawn depth (default flat) ([#13691](https://github.com/NousResearch/hermes-agent/pull/13691))
- **Cross-agent file state coordination** ([#13718](https://github.com/NousResearch/hermes-agent/pull/13718))
### File / Patch
- **`patch` — "did you mean?" feedback** when patch fails to match ([#13435](https://github.com/NousResearch/hermes-agent/pull/13435))
### API Server
- **Stream `/v1/responses` SSE tool events** (salvage #9779) ([#10049](https://github.com/NousResearch/hermes-agent/pull/10049))
- **Inline image inputs** on `/v1/chat/completions` and `/v1/responses` ([#12969](https://github.com/NousResearch/hermes-agent/pull/12969))
### Docker / Podman
- **Entry-level Podman support** — `find_docker()` + rootless entrypoint ([#10066](https://github.com/NousResearch/hermes-agent/pull/10066))
- **Add docker-cli to Docker image** (salvage #10096) ([#14232](https://github.com/NousResearch/hermes-agent/pull/14232))
- **File-sync back to host on teardown** (salvage of #8189 + hardening) ([#11291](https://github.com/NousResearch/hermes-agent/pull/11291))
### MCP
- 12 MCP improvements across the window (status, timeout handling, tool-call forwarding, etc.)
---
## 🧩 Skills Ecosystem
### Skill System
- **Namespaced skill registration** for plugin bundles ([#9786](https://github.com/NousResearch/hermes-agent/pull/9786))
- **`hermes skills reset`** to un-stick bundled skills ([#11468](https://github.com/NousResearch/hermes-agent/pull/11468))
- **Skills guard opt-in** — `config.skills.guard_agent_created` (default off) ([#14557](https://github.com/NousResearch/hermes-agent/pull/14557))
- **Bundled skill scripts runnable out of the box** ([#13384](https://github.com/NousResearch/hermes-agent/pull/13384))
- **`xitter` replaced with `xurl`** — the official X API CLI ([#12303](https://github.com/NousResearch/hermes-agent/pull/12303))
- **MiniMax-AI/cli as default skill tap** (salvage #7501) ([#14493](https://github.com/NousResearch/hermes-agent/pull/14493))
- **Fuzzy `@` file completions + mtime sorting** ([#9467](https://github.com/NousResearch/hermes-agent/pull/9467))
### New Skills
- **concept-diagrams** (salvage of #11045, @v1k22) ([#11363](https://github.com/NousResearch/hermes-agent/pull/11363))
- **architecture-diagram** (Cocoon AI port) ([#9906](https://github.com/NousResearch/hermes-agent/pull/9906))
- **pixel-art** with hardware palettes and video animation ([#12663](https://github.com/NousResearch/hermes-agent/pull/12663), [#12725](https://github.com/NousResearch/hermes-agent/pull/12725))
- **baoyu-comic** ([#13257](https://github.com/NousResearch/hermes-agent/pull/13257), @JimLiu)
- **baoyu-infographic** — 21 layouts × 21 styles (salvage #9901) ([#12254](https://github.com/NousResearch/hermes-agent/pull/12254))
- **page-agent** — embed Alibaba's in-page GUI agent in your webapp ([#13976](https://github.com/NousResearch/hermes-agent/pull/13976))
- **fitness-nutrition** optional skill + optional env var support ([#9355](https://github.com/NousResearch/hermes-agent/pull/9355))
- **drug-discovery** — ChEMBL, PubChem, OpenFDA, ADMET ([#9443](https://github.com/NousResearch/hermes-agent/pull/9443))
- **touchdesigner-mcp** (salvage of #10081) ([#12298](https://github.com/NousResearch/hermes-agent/pull/12298))
- **adversarial-ux-test** optional skill (salvage of #2494, @omnissiah-comelse) ([#13425](https://github.com/NousResearch/hermes-agent/pull/13425))
- **maps** — added `guest_house`, `camp_site`, and dual-key bakery lookup ([#13398](https://github.com/NousResearch/hermes-agent/pull/13398))
- **llm-wiki** — port provenance markers, source hashing, and quality signals ([#13700](https://github.com/NousResearch/hermes-agent/pull/13700))
---
## 📊 Web Dashboard
- **i18n (English + Chinese) language switcher** ([#9453](https://github.com/NousResearch/hermes-agent/pull/9453))
- **Live-switching theme system** ([#10687](https://github.com/NousResearch/hermes-agent/pull/10687))
- **Dashboard plugin system** — extend the web UI with custom tabs ([#10951](https://github.com/NousResearch/hermes-agent/pull/10951))
- **react-router, sidebar layout, sticky header, dropdown component** ([#9370](https://github.com/NousResearch/hermes-agent/pull/9370), @austinpickett)
- **Responsive for mobile** ([#9228](https://github.com/NousResearch/hermes-agent/pull/9228), @DeployFaith)
- **Vercel deployment** ([#10686](https://github.com/NousResearch/hermes-agent/pull/10686), [#11061](https://github.com/NousResearch/hermes-agent/pull/11061), @austinpickett)
- **Context window config support** ([#9357](https://github.com/NousResearch/hermes-agent/pull/9357))
- **HTTP health probe for cross-container gateway detection** ([#9894](https://github.com/NousResearch/hermes-agent/pull/9894))
- **Update + restart gateway buttons** ([#13526](https://github.com/NousResearch/hermes-agent/pull/13526), @austinpickett)
- **Real API call count per session** (salvages #10140) ([#14004](https://github.com/NousResearch/hermes-agent/pull/14004))
---
## 🖱️ CLI & User Experience
- **Dynamic shell completion for bash, zsh, and fish** ([#9785](https://github.com/NousResearch/hermes-agent/pull/9785))
- **Light-mode skins + skin-aware completion menus** ([#9461](https://github.com/NousResearch/hermes-agent/pull/9461))
- **Numbered keyboard shortcuts** on approval and clarify prompts ([#13416](https://github.com/NousResearch/hermes-agent/pull/13416))
- **Markdown stripping, compact multiline previews, external editor** ([#12934](https://github.com/NousResearch/hermes-agent/pull/12934))
- **`--ignore-user-config` and `--ignore-rules` flags** (port codex#18646) ([#14277](https://github.com/NousResearch/hermes-agent/pull/14277))
- **Account limits section in `/usage`** ([#13428](https://github.com/NousResearch/hermes-agent/pull/13428))
- **Doctor: Command Installation check** for `hermes` bin symlink ([#10112](https://github.com/NousResearch/hermes-agent/pull/10112))
- **ESC cancels secret/sudo prompts**, clearer skip messaging ([#9902](https://github.com/NousResearch/hermes-agent/pull/9902))
- Fix: agent-facing text uses `display_hermes_home()` instead of hardcoded `~/.hermes` ([#10285](https://github.com/NousResearch/hermes-agent/pull/10285))
- Fix: enforce `config.yaml` as sole CWD source + deprecate `.env` CWD vars + add `hermes memory reset` ([#11029](https://github.com/NousResearch/hermes-agent/pull/11029))
---
## 🔒 Security & Reliability
- **Global toggle to allow private/internal URL resolution** ([#14166](https://github.com/NousResearch/hermes-agent/pull/14166))
- **Block agent from self-destructing the gateway** via terminal (closes #6666) ([#9895](https://github.com/NousResearch/hermes-agent/pull/9895))
- **Telegram callback authorization** on update prompts ([#10536](https://github.com/NousResearch/hermes-agent/pull/10536))
- **SECURITY.md** added ([#10532](https://github.com/NousResearch/hermes-agent/pull/10532), @I3eg1nner)
- **Warn about legacy hermes.service units** during `hermes update` ([#11918](https://github.com/NousResearch/hermes-agent/pull/11918))
- **Complete ASCII-locale UnicodeEncodeError recovery** for `api_messages`/`reasoning_content` (closes #6843) ([#10537](https://github.com/NousResearch/hermes-agent/pull/10537))
- **Prevent stale `os.environ` leak** after `clear_session_vars` ([#10527](https://github.com/NousResearch/hermes-agent/pull/10527))
- **Prevent agent hang when backgrounding processes** via terminal tool ([#10584](https://github.com/NousResearch/hermes-agent/pull/10584))
- Many smaller session-resume, interrupt, streaming, and memory-race fixes throughout the window
---
## 🐛 Notable Bug Fixes
The `fix:` category in this window covers 482 PRs. Highlights:
- Streaming cursor artifacts filtered from Matrix, Telegram, WhatsApp, Discord (multiple PRs)
- `<think>` and `<thought>` blocks filtered from gateway stream consumers ([#9408](https://github.com/NousResearch/hermes-agent/pull/9408))
- Gateway display.streaming root-config override regression ([#9799](https://github.com/NousResearch/hermes-agent/pull/9799))
- Context `session_search` coerces limit to int (prevents TypeError) ([#10522](https://github.com/NousResearch/hermes-agent/pull/10522))
- Memory tool stays available when `fcntl` is unavailable (Windows) ([#9783](https://github.com/NousResearch/hermes-agent/pull/9783))
- Trajectory compressor credentials load from `HERMES_HOME/.env` ([#9632](https://github.com/NousResearch/hermes-agent/pull/9632), @Dusk1e)
- `@_context_completions` no longer crashes on `@` mention ([#9683](https://github.com/NousResearch/hermes-agent/pull/9683), @kshitijk4poor)
- Group session `user_id` no longer treated as `thread_id` in shutdown notifications ([#10546](https://github.com/NousResearch/hermes-agent/pull/10546))
- Telegram `platform_hint` — markdown is supported (closes #8261) ([#10612](https://github.com/NousResearch/hermes-agent/pull/10612))
- Doctor checks for Kimi China credentials fixed
- Streaming: don't suppress final response when commentary message is sent ([#10540](https://github.com/NousResearch/hermes-agent/pull/10540))
- Rapid Telegram follow-ups no longer get cut off
---
## 🧪 Testing & CI
- **Contributor attribution CI check** on PRs ([#9376](https://github.com/NousResearch/hermes-agent/pull/9376))
- Hermetic test parity (`scripts/run_tests.sh`) held across this window
- Test count stabilized post-Transport refactor; CI matrix held green through the transport rollout
---
## 📚 Documentation
- Atropos + wandb links in user guide
- ACP / VS Code / Zed / JetBrains integration docs refresh
- Webhook subscription docs updated for direct-delivery mode
- Plugin author guide expanded for new hooks (`register_command`, `dispatch_tool`, `transform_tool_result`)
- Transport layer developer guide added
- Website removed Discussions link from README
---
## 👥 Contributors
### Core
- **@teknium1** (Teknium)
### Top Community Contributors (by merged PR count)
- **@kshitijk4poor** — 49 PRs · Transport refactor (AnthropicTransport, ResponsesApiTransport), Step Plan provider, Xiaomi MiMo v2.5 support, numerous gateway fixes, promoted Kimi K2.5, @ mention crash fix
- **@OutThisLife** (Brooklyn) — 31 PRs · TUI polish, git branch in status bar, per-turn stopwatch, stable picker keys, `/clear` confirm, light-theme preset, subagent spawn observability overlay
- **@helix4u** — 11 PRs · Voice CLI record beep, MCP tool interrupt handling, assorted stability fixes
- **@austinpickett** — 8 PRs · Dashboard react-router + sidebar + sticky header + dropdown, Vercel deployment, update + restart buttons
- **@alt-glitch** — 8 PRs · PLATFORM_HINTS for Matrix/Mattermost/Feishu, Matrix fixes
- **@ethernet8023** — 3 PRs
- **@benbarclay** — 3 PRs
- **@Aslaaen** — 2 PRs
### Also contributing
@jerilynzheng (ai-gateway pricing), @JimLiu (baoyu-comic skill), @Dusk1e (trajectory compressor credentials), @DeployFaith (mobile-responsive dashboard), @LeonSGP43, @v1k22 (concept-diagrams), @omnissiah-comelse (adversarial-ux-test), @coekfung (Telegram MarkdownV2 expandable blockquotes), @liftaris (TUI provider resolution), @arihantsethia (skill analytics dashboard), @topcheer + @xing8star (QQBot foundation), @kovyrin, @I3eg1nner (SECURITY.md), @PeterBerthelsen, @lengxii, @priveperfumes, @sjz-ks, @cuyua9, @Disaster-Terminator, @leozeli, @LehaoLin, @trevthefoolish, @loongfay, @MrNiceRicee, @WideLee, @bluefishs, @malaiwah, @bobashopcashier, @dsocolobsky, @iamagenius00, @IAvecilla, @aniruddhaadak80, @Es1la, @asheriif, @walli, @jquesnelle (original Tool Gateway work).
### All Contributors (alphabetical)
@0xyg3n, @10ishq, @A-afflatus, @Abnertheforeman, @admin28980, @adybag14-cyber, @akhater, @alexzhu0,
@AllardQuek, @alt-glitch, @aniruddhaadak80, @anna-oake, @anniesurla, @anthhub, @areu01or00, @arihantsethia,
@arthurbr11, @asheriif, @Aslaaen, @Asunfly, @austinpickett, @AviArora02-commits, @AxDSan, @azhengbot, @Bartok9,
@benbarclay, @bennytimz, @bernylinville, @bingo906, @binhnt92, @bkadish, @bluefishs, @bobashopcashier,
@brantzh6, @BrennerSpear, @brianclemens, @briandevans, @brooklynnicholson, @bugkill3r, @buray, @burtenshaw,
@cdanis, @cgarwood82, @ChimingLiu, @chongweiliu, @christopherwoodall, @coekfung, @cola-runner, @corazzione,
@counterposition, @cresslank, @cuyua9, @cypres0099, @danieldoderlein, @davetist, @davidvv, @DeployFaith,
@Dev-Mriganka, @devorun, @dieutx, @Disaster-Terminator, @dodo-reach, @draix, @DrStrangerUJN, @dsocolobsky,
@Dusk1e, @dyxushuai, @elkimek, @elmatadorgh, @emozilla, @entropidelic, @Erosika, @erosika, @Es1la, @etcircle,
@etherman-os, @ethernet8023, @fancydirty, @farion1231, @fatinghenji, @Fatty911, @fengtianyu88, @Feranmi10,
@flobo3, @francip, @fuleinist, @g-guthrie, @GenKoKo, @gianfrancopiana, @gnanam1990, @GuyCui, @haileymarshall,
@haimu0x, @handsdiff, @hansnow, @hedgeho9X, @helix4u, @hengm3467, @HenkDz, @heykb, @hharry11, @HiddenPuppy,
@honghua, @houko, @houziershi, @hsy5571616, @huangke19, @hxp-plus, @Hypn0sis, @I3eg1nner, @iacker,
@iamagenius00, @IAvecilla, @iborazzi, @Ifkellx, @ifrederico, @imink, @isaachuangGMICLOUD, @ismell0992-afk,
@j0sephz, @Jaaneek, @jackjin1997, @JackTheGit, @jaffarkeikei, @jerilynzheng, @JiaDe-Wu, @Jiawen-lee, @JimLiu,
@jinzheng8115, @jneeee, @jplew, @jquesnelle, @Julientalbot, @Junass1, @jvcl, @kagura-agent, @keifergu,
@kevinskysunny, @keyuyuan, @konsisumer, @kovyrin, @kshitijk4poor, @leeyang1990, @LehaoLin, @lengxii,
@LeonSGP43, @leozeli, @li0near, @liftaris, @Lind3ey, @Linux2010, @liujinkun2025, @LLQWQ, @Llugaes, @lmoncany,
@longsizhuo, @lrawnsley, @Lubrsy706, @lumenradley, @luyao618, @lvnilesh, @LVT382009, @m0n5t3r, @Magaav,
@MagicRay1217, @malaiwah, @manuelschipper, @Marvae, @MassiveMassimo, @mavrickdeveloper, @maxchernin, @memosr,
@meng93, @mengjian-github, @MestreY0d4-Uninter, @Mibayy, @MikeFac, @mikewaters, @milkoor, @minorgod,
@MrNiceRicee, @ms-alan, @mvanhorn, @n-WN, @N0nb0at, @Nan93, @NIDNASSER-Abdelmajid, @nish3451, @niyoh120,
@nocoo, @nosleepcassette, @NousResearch, @ogzerber, @omnissiah-comelse, @Only-Code-A, @opriz, @OwenYWT, @pedh,
@pefontana, @PeterBerthelsen, @phpoh, @pinion05, @plgonzalezrx8, @pradeep7127, @priveperfumes,
@projectadmin-dev, @PStarH, @rnijhara, @Roy-oss1, @roytian1217, @RucchiZ, @Ruzzgar, @RyanLee-Dev, @Salt-555,
@Sanjays2402, @sgaofen, @sharziki, @shenuu, @shin4, @SHL0MS, @shushuzn, @sicnuyudidi, @simon-gtcl,
@simon-marcus, @sirEven, @Sisyphus, @sjz-ks, @snreynolds, @Societus, @Somme4096, @sontianye, @sprmn24,
@StefanIsMe, @stephenschoettler, @Swift42, @taeng0204, @taeuk178, @tannerfokkens-maker, @TaroballzChen,
@ten-ltw, @teyrebaz33, @Tianworld, @topcheer, @Tranquil-Flow, @trevthefoolish, @TroyMitchell911, @UNLINEARITY,
@v1k22, @vivganes, @vominh1919, @vrinek, @VTRiot, @WadydX, @walli, @wenhao7, @WhiteWorld, @WideLee, @wujhsu,
@WuTianyi123, @Wysie, @xandersbell, @xiaoqiang243, @xiayh0107, @xinpengdr, @Xowiek, @ycbai, @yeyitech, @ygd58,
@youngDoo, @yudaiyan, @Yukipukii1, @yule975, @yyq4193, @yzx9, @ZaynJarvis, @zhang9w0v5, @zhanggttry,
@zhangxicen, @zhongyueming1121, @zhouxiaoya12, @zons-zhaozhy
Also: @maelrx, @Marco Rutsch, @MaxsolcuCrypto, @Mind-Dragon, @Paul Bergeron, @say8hi, @whitehatjr1001.
---
**Full Changelog**: [v2026.4.13...v2026.4.23](https://github.com/NousResearch/hermes-agent/compare/v2026.4.13...v2026.4.23)
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# Hermes Agent v0.12.0 (v2026.4.30)
**Release Date:** April 30, 2026
**Since v0.11.0:** 1,096 commits · 550 merged PRs · 1,270 files changed · 217,776 insertions · 213 community contributors (including co-authors)
> The Curator release — Hermes Agent now maintains itself. An autonomous background Curator grades, prunes, and consolidates your skill library on its own schedule. The self-improvement loop that reviews what to save got a substantial upgrade. Four new inference providers, a 18th messaging platform, a 19th via Teams plugin, native Spotify + Google Meet integrations, ComfyUI and TouchDesigner-MCP moved from optional to bundled-by-default, and a ~57% cut to visible TUI cold start.
---
## ✨ Highlights
- **Autonomous Curator** — `hermes curator` runs as a background agent on the gateway's cron ticker (7-day cycle default). It grades your skill library, consolidates related skills, prunes dead ones, and writes per-run reports to `logs/curator/run.json` + `REPORT.md`. Archived skills are classified consolidated-vs-pruned via model + heuristic. Defense-in-depth gates protect bundled/hub skills from mutation. Unified under `auxiliary.curator` — pick the curator's model in `hermes model`, manage it from the dashboard. `hermes curator status` ranks skills by usage (most-used / least-used). ([#17277](https://github.com/NousResearch/hermes-agent/pull/17277), [#17307](https://github.com/NousResearch/hermes-agent/pull/17307), [#17941](https://github.com/NousResearch/hermes-agent/pull/17941), [#17868](https://github.com/NousResearch/hermes-agent/pull/17868), [#18033](https://github.com/NousResearch/hermes-agent/pull/18033))
- **Self-improvement loop — substantially upgraded** — The background review fork (the core of Hermes' self-improvement: after each turn it decides what memories/skills to save or update) is now class-first (rubric-based rather than free-form), active-update biased (prefers the skill the agent just loaded), handles `references/`/`templates/` sub-files, and properly inherits the parent's live runtime (provider, model, credentials actually propagate). Restricted to memory + skills toolsets so it can't sprawl. Memory providers shut down cleanly. Prior-turn tool messages excluded from the summary so the fork sees a clean context. ([#16026](https://github.com/NousResearch/hermes-agent/pull/16026), [#17213](https://github.com/NousResearch/hermes-agent/pull/17213), [#16099](https://github.com/NousResearch/hermes-agent/pull/16099), [#16569](https://github.com/NousResearch/hermes-agent/pull/16569), [#16204](https://github.com/NousResearch/hermes-agent/pull/16204), [#15057](https://github.com/NousResearch/hermes-agent/pull/15057))
- **Skill integrations — major expansion** — **ComfyUI v5** with official CLI + REST + hardware-gated local install, moved from optional to **built-in by default** ([#17610](https://github.com/NousResearch/hermes-agent/pull/17610), [#17631](https://github.com/NousResearch/hermes-agent/pull/17631), [#17734](https://github.com/NousResearch/hermes-agent/pull/17734)). **TouchDesigner-MCP** bundled by default, expanded with GLSL, post-FX, audio, geometry, and 9 new reference docs ([#16753](https://github.com/NousResearch/hermes-agent/pull/16753), [#16624](https://github.com/NousResearch/hermes-agent/pull/16624), [#16768](https://github.com/NousResearch/hermes-agent/pull/16768) — @kshitijk4poor + @SHL0MS). **Humanizer** skill ports a text-cleaner that strips AI-isms ([#16787](https://github.com/NousResearch/hermes-agent/pull/16787)). **claude-design** HTML artifact skill + design-md (Google DESIGN.md spec) + airtable salvage + `skill_manage` edits in `external_dirs` + direct-URL skill install + `/reload-skills` slash command. ([#16358](https://github.com/NousResearch/hermes-agent/pull/16358), [#14876](https://github.com/NousResearch/hermes-agent/pull/14876), [#16291](https://github.com/NousResearch/hermes-agent/pull/16291), [#17512](https://github.com/NousResearch/hermes-agent/pull/17512), [#16323](https://github.com/NousResearch/hermes-agent/pull/16323), [#17744](https://github.com/NousResearch/hermes-agent/pull/17744))
- **LM Studio — first-class provider** — upgraded from a custom-endpoint alias to a full-blown native provider: dedicated auth, `hermes doctor` checks, reasoning transport, live `/models` listing. (Salvage of @kshitijk4poor's #17061.) ([#17102](https://github.com/NousResearch/hermes-agent/pull/17102))
- **Four more new inference providers** — **GMI Cloud** (first-class, salvage of #11955@isaachuangGMICLOUD), **Azure AI Foundry** with auto-detection, **MiniMax OAuth** with PKCE browser flow (salvage #15203), **Tencent Tokenhub** (salvage of #16860). ([#16663](https://github.com/NousResearch/hermes-agent/pull/16663), [#15845](https://github.com/NousResearch/hermes-agent/pull/15845), [#17524](https://github.com/NousResearch/hermes-agent/pull/17524), [#16960](https://github.com/NousResearch/hermes-agent/pull/16960))
- **Pluggable gateway platforms + Microsoft Teams** — the gateway is now a plugin host. Drop-in messaging adapters live outside the core, and Microsoft Teams is the first plugin-shipped platform. (Salvage of #17664.) ([#17751](https://github.com/NousResearch/hermes-agent/pull/17751), [#17828](https://github.com/NousResearch/hermes-agent/pull/17828))
- **Tencent 元宝 (Yuanbao) — 18th messaging platform** — native gateway adapter with text + media delivery. ([#16298](https://github.com/NousResearch/hermes-agent/pull/16298), [#17424](https://github.com/NousResearch/hermes-agent/pull/17424))
- **Spotify — native tools + bundled skill + wizard** — 7 tools (play, search, queue, playlists, devices) behind PKCE OAuth, interactive setup wizard, bundled skill, surfacing in `hermes tools`, cron usage documented. ([#15121](https://github.com/NousResearch/hermes-agent/pull/15121), [#15130](https://github.com/NousResearch/hermes-agent/pull/15130), [#15154](https://github.com/NousResearch/hermes-agent/pull/15154), [#15180](https://github.com/NousResearch/hermes-agent/pull/15180))
- **Google Meet plugin** — join calls, transcribe, speak, follow up. Realtime OpenAI transport + Node bot server, full pipeline bundled as a plugin. ([#16364](https://github.com/NousResearch/hermes-agent/pull/16364))
- **`hermes -z` one-shot mode + `hermes update --check`** — non-interactive `hermes -z <prompt>` with `--model`/`--provider`/`HERMES_INFERENCE_MODEL`. `hermes update --check` preflight. Opt-in pre-update HERMES_HOME backup. ([#15702](https://github.com/NousResearch/hermes-agent/pull/15702), [#15704](https://github.com/NousResearch/hermes-agent/pull/15704), [#15841](https://github.com/NousResearch/hermes-agent/pull/15841), [#16539](https://github.com/NousResearch/hermes-agent/pull/16539), [#16566](https://github.com/NousResearch/hermes-agent/pull/16566))
- **Models dashboard tab + in-browser model config** — rich per-model analytics, switch main + auxiliary models from the dashboard. ([#17745](https://github.com/NousResearch/hermes-agent/pull/17745), [#17802](https://github.com/NousResearch/hermes-agent/pull/17802))
- **Remote model catalog manifest** — OpenRouter + Nous Portal model catalogs are now pulled from a remote manifest so new models show up without a release. ([#16033](https://github.com/NousResearch/hermes-agent/pull/16033))
- **Native multimodal image routing** — images now route based on the model's actual vision capability rather than provider defaults. ([#16506](https://github.com/NousResearch/hermes-agent/pull/16506))
- **Gateway media parity** — native multi-image sending across Telegram, Discord, Slack, Mattermost, Email, and Signal; centralized audio routing with FLAC support + Telegram document fallback. ([#17909](https://github.com/NousResearch/hermes-agent/pull/17909), [#17833](https://github.com/NousResearch/hermes-agent/pull/17833))
- **TUI catches up to (and past) the classic CLI** — LaTeX rendering (@austinpickett), `/reload` .env hot-reload, pluggable busy-indicator styles (@OutThisLife, #13610), opt-in auto-resume of last session, expanded light-terminal auto-detection, session delete from `/resume` picker with `d`, modified mouse-wheel line scroll, and a `/mouse` toggle that kills ConPTY's phantom mouse injection (@kevin-ho). ([#17175](https://github.com/NousResearch/hermes-agent/pull/17175), [#17286](https://github.com/NousResearch/hermes-agent/pull/17286), [#17150](https://github.com/NousResearch/hermes-agent/pull/17150), [#17130](https://github.com/NousResearch/hermes-agent/pull/17130), [#17113](https://github.com/NousResearch/hermes-agent/pull/17113), [#17668](https://github.com/NousResearch/hermes-agent/pull/17668), [#17669](https://github.com/NousResearch/hermes-agent/pull/17669), [#15488](https://github.com/NousResearch/hermes-agent/pull/15488))
- **Observability + achievements plugins** — bundled Langfuse observability plugin (salvage #16845) + bundled hermes-achievements plugin that scans full session history. ([#16917](https://github.com/NousResearch/hermes-agent/pull/16917), [#17754](https://github.com/NousResearch/hermes-agent/pull/17754))
- **TTS provider registry + Piper local TTS** — pluggable `tts.providers.<name>` registry; Piper ships as a native local TTS provider. (Closes #8508.) ([#17843](https://github.com/NousResearch/hermes-agent/pull/17843), [#17885](https://github.com/NousResearch/hermes-agent/pull/17885))
- **Vercel Sandbox backend** — Vercel sandboxes as an execute_code/terminal backend (@kshitijk4poor). ([#17445](https://github.com/NousResearch/hermes-agent/pull/17445))
- **Secret redaction off by default** — default flipped to off. Prevents the long-standing patch-corruption incidents where fake secret-shaped substrings mangled tool outputs. Opt in via `redaction.enabled: true` when you need it. ([#16794](https://github.com/NousResearch/hermes-agent/pull/16794))
- **Cold-start performance** — visible TUI cold start cut **~57%** via lazy agent init (@OutThisLife), lazy imports of OpenAI / Anthropic / Firecrawl / account_usage, mtime-cached `load_config()`, memoized `get_tool_definitions()` with TTL-cached `check_fn` results, precompiled dangerous-command patterns. ([#17190](https://github.com/NousResearch/hermes-agent/pull/17190), [#17046](https://github.com/NousResearch/hermes-agent/pull/17046), [#17041](https://github.com/NousResearch/hermes-agent/pull/17041), [#17098](https://github.com/NousResearch/hermes-agent/pull/17098), [#17206](https://github.com/NousResearch/hermes-agent/pull/17206))
- **Configurable prompt cache TTL** — `prompt_caching.cache_ttl` (5m default, 1h opt-in — cost savings for bursty sessions that keep cache warm). Salvage of #12659. ([#15065](https://github.com/NousResearch/hermes-agent/pull/15065))
---
## 🧠 Autonomous Curator & Self-Improvement Loop
### Curator — autonomous skill maintenance
- **`hermes curator` as a background agent** — runs on the gateway's cron ticker, 7-day cycle by default, umbrella-first prompt, inherits parent config, unbounded iterations ([#17277](https://github.com/NousResearch/hermes-agent/pull/17277) — issue #7816)
- **Per-run reports** — `logs/curator/run.json` + `REPORT.md` per cycle ([#17307](https://github.com/NousResearch/hermes-agent/pull/17307))
- **Consolidated vs pruned classification** — archived skills split with model + heuristic ([#17941](https://github.com/NousResearch/hermes-agent/pull/17941))
- **`hermes curator status`** — ranks skills by usage, shows most-used and least-used ([#18033](https://github.com/NousResearch/hermes-agent/pull/18033))
- **Unified under `auxiliary.curator`** — pick the model in `hermes model`, configure from the dashboard ([#17868](https://github.com/NousResearch/hermes-agent/pull/17868))
- **Documentation** — dedicated curator feature page on the docs site ([#17563](https://github.com/NousResearch/hermes-agent/pull/17563))
- Fix: seed defaults on update, create `logs/curator/` directory, defer fire import ([#17927](https://github.com/NousResearch/hermes-agent/pull/17927))
- Fix: scan nested archive subdirs in `restore_skill` (@0xDevNinja) ([#17951](https://github.com/NousResearch/hermes-agent/pull/17951))
- Fix: use actual skill activity in curator status (@y0shua1ee) ([#17953](https://github.com/NousResearch/hermes-agent/pull/17953))
- Fix: `skill_manage` refuses writes on pinned skills; pinning now blocks curator writes ([#17562](https://github.com/NousResearch/hermes-agent/pull/17562), [#17578](https://github.com/NousResearch/hermes-agent/pull/17578))
- Fix: `bump_use()` wired into skill invocation + preload + skill_view (salvage #17782) ([#17932](https://github.com/NousResearch/hermes-agent/pull/17932))
### Self-improvement loop (background review fork)
- **Class-first skill-review prompt** — rubric-based grading rather than free-form "should this update" ([#16026](https://github.com/NousResearch/hermes-agent/pull/16026))
- **Active-update bias** — prefers updating skills the agent just loaded, handles `references/` + `templates/` sub-files ([#17213](https://github.com/NousResearch/hermes-agent/pull/17213))
- **Fork inherits parent's live runtime** — provider, model, credentials actually propagate now ([#16099](https://github.com/NousResearch/hermes-agent/pull/16099))
- **Scoped toolsets** — review fork restricted to memory + skills (no shell, no web) ([#16569](https://github.com/NousResearch/hermes-agent/pull/16569))
- **Clean shutdown** — background review memory providers exit properly (salvage #15289) ([#16204](https://github.com/NousResearch/hermes-agent/pull/16204))
- **Clean context** — prior-history tool messages excluded from review summary (salvage #14967) ([#15057](https://github.com/NousResearch/hermes-agent/pull/15057))
---
## 🧩 Skills Ecosystem
### Skill integrations — newly bundled or promoted
- **ComfyUI v5** — official CLI + REST + hardware-gated local install; **moved from optional to built-in** ([#17610](https://github.com/NousResearch/hermes-agent/pull/17610), [#17631](https://github.com/NousResearch/hermes-agent/pull/17631), [#17734](https://github.com/NousResearch/hermes-agent/pull/17734), [#17612](https://github.com/NousResearch/hermes-agent/pull/17612))
- **TouchDesigner-MCP** — **bundled by default** ([#16753](https://github.com/NousResearch/hermes-agent/pull/16753) — @kshitijk4poor), expanded with GLSL, post-FX, audio, geometry references ([#16624](https://github.com/NousResearch/hermes-agent/pull/16624)), 9 new reference docs ([#16768](https://github.com/NousResearch/hermes-agent/pull/16768) — @SHL0MS)
- **Humanizer** — strips AI-isms from text ([#16787](https://github.com/NousResearch/hermes-agent/pull/16787))
- **claude-design** — HTML artifact skill with disambiguation from other design skills ([#16358](https://github.com/NousResearch/hermes-agent/pull/16358))
- **design-md** — Google's DESIGN.md spec skill ([#14876](https://github.com/NousResearch/hermes-agent/pull/14876))
- **airtable** — salvaged skill + skill API keys wired into `.env` (#15838) ([#16291](https://github.com/NousResearch/hermes-agent/pull/16291))
- **pretext** — creative browser demos with @chenglou/pretext ([#17259](https://github.com/NousResearch/hermes-agent/pull/17259))
- **spike** + **sketch** — throwaway experiments + HTML mockups, adapted from gsd-build ([#17421](https://github.com/NousResearch/hermes-agent/pull/17421))
### Skills UX
- **Install skills from a direct HTTP(S) URL** — `hermes skills install <url>` ([#16323](https://github.com/NousResearch/hermes-agent/pull/16323))
- **`/reload-skills`** slash command (salvage #17670) ([#17744](https://github.com/NousResearch/hermes-agent/pull/17744))
- **`hermes skills list`** shows enabled/disabled status ([#16129](https://github.com/NousResearch/hermes-agent/pull/16129))
- **`skill_manage` refuses writes on pinned skills** ([#17562](https://github.com/NousResearch/hermes-agent/pull/17562))
- **`skill_manage` edits external_dirs skills in place** (salvage #9966) ([#17512](https://github.com/NousResearch/hermes-agent/pull/17512), [#17289](https://github.com/NousResearch/hermes-agent/pull/17289))
- Fix: inline-shell rendering in `skill_view` ([#15376](https://github.com/NousResearch/hermes-agent/pull/15376))
- Fix: exclude `.archive/` from skill index walk (salvage #17639) ([#17931](https://github.com/NousResearch/hermes-agent/pull/17931))
- Fix: dedicated docs page per bundled + optional skill ([#14929](https://github.com/NousResearch/hermes-agent/pull/14929))
- Fix: `google-workspace` shared HERMES_HOME helper + ship deps as optional extra ([#15405](https://github.com/NousResearch/hermes-agent/pull/15405))
- Fix: auto-wrap ASCII-art code blocks in generated skill pages ([#16497](https://github.com/NousResearch/hermes-agent/pull/16497))
- Point agent at `hermes-agent` skill + docs site for Hermes questions ([#16535](https://github.com/NousResearch/hermes-agent/pull/16535))
---
## 🏗️ Core Agent & Architecture
### Provider & Model Support
#### New providers
- **GMI Cloud** — first-class API-key provider on par with Arcee/Kilocode/Xiaomi (salvage of #11955@isaachuangGMICLOUD) ([#16663](https://github.com/NousResearch/hermes-agent/pull/16663))
- **Azure AI Foundry** — auto-detection, full wiring ([#15845](https://github.com/NousResearch/hermes-agent/pull/15845))
- **LM Studio** — upgraded from custom-endpoint alias to first-class provider: dedicated auth, doctor checks, reasoning transport, live `/models` (salvage of #17061@kshitijk4poor) ([#17102](https://github.com/NousResearch/hermes-agent/pull/17102))
- **MiniMax OAuth** — PKCE browser flow with full OAuth integration (salvage #15203) ([#17524](https://github.com/NousResearch/hermes-agent/pull/17524))
- **Tencent Tokenhub** — new provider (salvage of #16860) ([#16960](https://github.com/NousResearch/hermes-agent/pull/16960))
#### Model catalog
- **Remote model catalog manifest** — OpenRouter + Nous Portal catalogs pulled from remote manifest so new models show up without a release ([#16033](https://github.com/NousResearch/hermes-agent/pull/16033))
- `openai/gpt-5.5` and `gpt-5.5-pro` added to OpenRouter + Nous Portal ([#15343](https://github.com/NousResearch/hermes-agent/pull/15343))
- `deepseek-v4-pro` and `deepseek-v4-flash` added ([#14934](https://github.com/NousResearch/hermes-agent/pull/14934))
- `qwen3.6-plus` added to Alibaba-supported models ([#16896](https://github.com/NousResearch/hermes-agent/pull/16896))
- Gemini free-tier keys blocked at setup with 429 guidance surfacing ([#15100](https://github.com/NousResearch/hermes-agent/pull/15100))
#### Model configuration
- **Configurable `prompt_caching.cache_ttl`** — 5m default, 1h opt-in (salvage #12659) ([#15065](https://github.com/NousResearch/hermes-agent/pull/15065))
- `/fast` whitelist broadened to all OpenAI + Anthropic models ([#16883](https://github.com/NousResearch/hermes-agent/pull/16883))
- `auxiliary.extra_body.reasoning` translates into Codex Responses API ([#17004](https://github.com/NousResearch/hermes-agent/pull/17004))
- `hermes fallback` command for managing fallback providers ([#16052](https://github.com/NousResearch/hermes-agent/pull/16052))
### Agent Loop & Conversation
- **Native multimodal image routing** — based on model vision capability, not provider defaults ([#16506](https://github.com/NousResearch/hermes-agent/pull/16506))
- **Delegate `child_timeout_seconds` default bumped to 600s** ([#14809](https://github.com/NousResearch/hermes-agent/pull/14809))
- **Diagnostic dump when subagent times out with 0 API calls** ([#15105](https://github.com/NousResearch/hermes-agent/pull/15105))
- **Gateway busts cached agent on compression/context_length config edits** ([#17008](https://github.com/NousResearch/hermes-agent/pull/17008))
- **Opt-in runtime-metadata footer on final replies** ([#17026](https://github.com/NousResearch/hermes-agent/pull/17026))
- `/reload-mcp` awareness — rebuild cached agents + prompt-cache cost confirmation ([#17729](https://github.com/NousResearch/hermes-agent/pull/17729))
- Fix: repair CamelCase + `_tool` suffix tool-call emissions ([#15124](https://github.com/NousResearch/hermes-agent/pull/15124))
- Fix: retry on `json.JSONDecodeError` instead of treating as local validation error ([#15107](https://github.com/NousResearch/hermes-agent/pull/15107))
- Fix: handle unescaped control chars in `tool_call.arguments` ([#15356](https://github.com/NousResearch/hermes-agent/pull/15356))
- Fix: ordering fix in `_copy_reasoning_content_for_api` — cross-provider reasoning isolation (@Zjianru) ([#15749](https://github.com/NousResearch/hermes-agent/pull/15749))
- Fix: inject empty `reasoning_content` for DeepSeek/Kimi `tool_calls` unconditionally (@Zjianru) ([#15762](https://github.com/NousResearch/hermes-agent/pull/15762))
- Fix: persist streamed `reasoning_content` on assistant turns (#16844) ([#16892](https://github.com/NousResearch/hermes-agent/pull/16892))
- Fix: cancel coroutine on timeout so worker thread exits; full traceback on tool failure ([#17428](https://github.com/NousResearch/hermes-agent/pull/17428))
- Fix: isolate `get_tool_definitions` quiet_mode cache + dedup LCM injection (#17335) ([#17889](https://github.com/NousResearch/hermes-agent/pull/17889))
- Fix: serialize concurrent `hermes_tools` RPC calls from `execute_code` (#17770) ([#17894](https://github.com/NousResearch/hermes-agent/pull/17894), [#17902](https://github.com/NousResearch/hermes-agent/pull/17902))
- Fix: rename `[SYSTEM:``[IMPORTANT:` in all user-injected markers (dodges Azure content filter) ([#16114](https://github.com/NousResearch/hermes-agent/pull/16114))
### Compression
- **Retry summary on main model for unknown errors before giving up** ([#16774](https://github.com/NousResearch/hermes-agent/pull/16774))
- **Notify users when configured aux model fails even if main-model fallback recovers** ([#16775](https://github.com/NousResearch/hermes-agent/pull/16775))
- `/compress` wrapped in `_busy_command` to block input during compression ([#15388](https://github.com/NousResearch/hermes-agent/pull/15388))
- Fix: reserve system + tools headroom when aux binds threshold ([#15631](https://github.com/NousResearch/hermes-agent/pull/15631))
- Fix: use text-char sum for multimodal token estimation in `_find_tail_cut_by_tokens` ([#16369](https://github.com/NousResearch/hermes-agent/pull/16369))
### Session, Memory & State
- **Trigram FTS5 index for CJK search, replace LIKE fallback** (@alt-glitch) ([#16651](https://github.com/NousResearch/hermes-agent/pull/16651))
- **Index `tool_name` + `tool_calls` in FTS5, with repair + migration** (salvages #16866) ([#16914](https://github.com/NousResearch/hermes-agent/pull/16914))
- **Checkpoints: auto-prune orphan and stale shadow repos at startup** ([#16303](https://github.com/NousResearch/hermes-agent/pull/16303))
- **Memory providers notified on mid-process session_id rotation** (#6672) ([#17409](https://github.com/NousResearch/hermes-agent/pull/17409))
- Fix: quote underscored terms in FTS5 query sanitization ([#16915](https://github.com/NousResearch/hermes-agent/pull/16915))
- Fix: resolve viking_read 500/412 on file URIs + pseudo-summary URIs (salvage #5886) ([#17869](https://github.com/NousResearch/hermes-agent/pull/17869))
- Fix: skip external-provider sync on interrupted turns ([#15395](https://github.com/NousResearch/hermes-agent/pull/15395))
- Fix: close embedded Hindsight async client cleanly (salvage #14605) ([#16209](https://github.com/NousResearch/hermes-agent/pull/16209))
- Fix: pass session transcript to `shutdown_memory_provider` on gateway + CLI (#15165) ([#16571](https://github.com/NousResearch/hermes-agent/pull/16571))
- Fix: write-origin metadata seam ([#15346](https://github.com/NousResearch/hermes-agent/pull/15346))
- Fix: preserve symlinks during atomic file writes ([#16980](https://github.com/NousResearch/hermes-agent/pull/16980))
- Refactor: remove `flush_memories` entirely ([#15696](https://github.com/NousResearch/hermes-agent/pull/15696))
### Auxiliary models
- Fix: surface auxiliary failures in UI (previously silent) ([#15324](https://github.com/NousResearch/hermes-agent/pull/15324))
- Fix: surface title-gen auxiliary failures instead of silently dropping ([#16371](https://github.com/NousResearch/hermes-agent/pull/16371))
- Fix: generalize unsupported-parameter detector and harden `max_tokens` retry ([#15633](https://github.com/NousResearch/hermes-agent/pull/15633))
---
## 📱 Messaging Platforms (Gateway)
### New Platforms
- **Microsoft Teams (19th platform)** — as a plugin, + xdist collision guard ([#17828](https://github.com/NousResearch/hermes-agent/pull/17828))
- **Yuanbao (Tencent 元宝, 18th platform)** — native adapter with text + media delivery ([#16298](https://github.com/NousResearch/hermes-agent/pull/16298), [#17424](https://github.com/NousResearch/hermes-agent/pull/17424), [#16880](https://github.com/NousResearch/hermes-agent/pull/16880))
### Pluggable Gateway Platforms
- **Drop-in messaging adapters** — the gateway is now a plugin host for platforms (salvage of #17664) ([#17751](https://github.com/NousResearch/hermes-agent/pull/17751))
### Telegram
- **Chat allowlists for groups and forums** (@web3blind) ([#15027](https://github.com/NousResearch/hermes-agent/pull/15027))
- **Send fresh finals for stale preview streams** (port openclaw#72038) ([#16261](https://github.com/NousResearch/hermes-agent/pull/16261))
- **Render markdown tables as row-group bullets + prompt hint** ([#16997](https://github.com/NousResearch/hermes-agent/pull/16997))
- Document fallback in centralized audio routing ([#17833](https://github.com/NousResearch/hermes-agent/pull/17833))
- Native multi-image sending ([#17909](https://github.com/NousResearch/hermes-agent/pull/17909))
### Discord
- **Opt-in toolsets + ID injection + tool split + Feishu wiring** (salvage #15457, #15458) ([#15610](https://github.com/NousResearch/hermes-agent/pull/15610), [#15613](https://github.com/NousResearch/hermes-agent/pull/15613))
- Fix: coerce `limit` parameter to int before `min()` call ([#16319](https://github.com/NousResearch/hermes-agent/pull/16319))
### Slack
- **Register every gateway command as a native slash (Discord/Telegram parity)** ([#16164](https://github.com/NousResearch/hermes-agent/pull/16164))
- **`strict_mention` config** — prevents thread auto-engagement ([#16193](https://github.com/NousResearch/hermes-agent/pull/16193))
- **`channel_skill_bindings`** — bind specific skills to specific Slack channels ([#16283](https://github.com/NousResearch/hermes-agent/pull/16283))
### Signal
- **Native formatting** — markdown → bodyRanges, reply quotes, reactions ([#17417](https://github.com/NousResearch/hermes-agent/pull/17417))
- Native multi-image sending ([#17909](https://github.com/NousResearch/hermes-agent/pull/17909))
### Feishu / Mattermost / Email / Signal
- All participate in **native multi-image sending** ([#17909](https://github.com/NousResearch/hermes-agent/pull/17909))
### Gateway Core
- **Centralized audio routing + FLAC support + Telegram doc fallback** ([#17833](https://github.com/NousResearch/hermes-agent/pull/17833))
- **Native multi-image sending** across Telegram, Discord, Slack, Mattermost, Email, Signal ([#17909](https://github.com/NousResearch/hermes-agent/pull/17909))
- **Make hygiene hard message limit configurable** ([#17000](https://github.com/NousResearch/hermes-agent/pull/17000))
- **Opt-in runtime-metadata footer on final replies** ([#17026](https://github.com/NousResearch/hermes-agent/pull/17026))
- **`pre_gateway_dispatch` hook** — plugins can intercept before dispatch ([#15050](https://github.com/NousResearch/hermes-agent/pull/15050))
- **`pre_approval_request` / `post_approval_response` hooks** ([#16776](https://github.com/NousResearch/hermes-agent/pull/16776))
- Fix: timeouts — guard `load_config()` call against runtime exceptions ([#16318](https://github.com/NousResearch/hermes-agent/pull/16318))
- Fix: support passing handler tools via registry ([#15613](https://github.com/NousResearch/hermes-agent/pull/15613))
---
## 🔧 Tool System
### Plugin-first architecture
- **Pluggable gateway platforms** — platforms can ship as plugins ([#17751](https://github.com/NousResearch/hermes-agent/pull/17751))
- **Microsoft Teams as first plugin-shipped platform** ([#17828](https://github.com/NousResearch/hermes-agent/pull/17828))
- **`pre_gateway_dispatch` hook** ([#15050](https://github.com/NousResearch/hermes-agent/pull/15050))
- **`pre_approval_request` + `post_approval_response` hooks** ([#16776](https://github.com/NousResearch/hermes-agent/pull/16776))
- **`duration_ms` on `post_tool_call`** (inspired by Claude Code 2.1.119) ([#15429](https://github.com/NousResearch/hermes-agent/pull/15429))
- **Bundled plugins**: Spotify ([#15174](https://github.com/NousResearch/hermes-agent/pull/15174)), Google Meet ([#16364](https://github.com/NousResearch/hermes-agent/pull/16364)), Langfuse observability ([#16917](https://github.com/NousResearch/hermes-agent/pull/16917)), hermes-achievements ([#17754](https://github.com/NousResearch/hermes-agent/pull/17754))
- **Page-scoped plugin slots for built-in dashboard pages** ([#15658](https://github.com/NousResearch/hermes-agent/pull/15658))
- **Declarative plugin installation for NixOS module** (@alt-glitch) ([#15953](https://github.com/NousResearch/hermes-agent/pull/15953))
### Browser
- **CDP supervisor** — dialog detection + response + cross-origin iframe eval ([#14540](https://github.com/NousResearch/hermes-agent/pull/14540))
- **Auto-spawn local Chromium for LAN/localhost URLs** when cloud provider is configured ([#16136](https://github.com/NousResearch/hermes-agent/pull/16136))
### Execute code / Terminal
- **Vercel Sandbox backend** for `execute_code` / terminal (@kshitijk4poor) ([#17445](https://github.com/NousResearch/hermes-agent/pull/17445))
- **Collapse subagent `task_id`s to shared container** ([#16177](https://github.com/NousResearch/hermes-agent/pull/16177))
- **Docker: run container as host user** to avoid root-owned bind mounts (@benbarclay) ([#17305](https://github.com/NousResearch/hermes-agent/pull/17305))
- Fix: safely quote `~/` subpaths in wrapped `cd` commands ([#15394](https://github.com/NousResearch/hermes-agent/pull/15394))
- Fix: close file descriptor in `LocalEnvironment._update_cwd` ([#17300](https://github.com/NousResearch/hermes-agent/pull/17300))
- Fix: SSH — prevent tar from overwriting remote home dir permissions ([#17898](https://github.com/NousResearch/hermes-agent/pull/17898), [#17867](https://github.com/NousResearch/hermes-agent/pull/17867))
### Image generation
- See Provider section for updates; no new image providers this window.
### TTS / Voice
- **Pluggable TTS provider registry** under `tts.providers.<name>` ([#17843](https://github.com/NousResearch/hermes-agent/pull/17843))
- **Piper** as native local TTS provider (closes #8508) ([#17885](https://github.com/NousResearch/hermes-agent/pull/17885))
- **Voice mode CLI parity in the TUI** — VAD loop + TTS + crash forensics ([#14810](https://github.com/NousResearch/hermes-agent/pull/14810))
- Fix: vision — use HERMES_HOME-based cache dir instead of cwd ([#17719](https://github.com/NousResearch/hermes-agent/pull/17719))
### Cron
- **Honor `hermes tools` config for the cron platform** ([#14798](https://github.com/NousResearch/hermes-agent/pull/14798))
- **Per-job `workdir`** — project-aware cron runs ([#15110](https://github.com/NousResearch/hermes-agent/pull/15110))
- **`context_from` field** — chain cron job outputs ([#15606](https://github.com/NousResearch/hermes-agent/pull/15606))
- Fix: promote `croniter` to a core dependency ([#17577](https://github.com/NousResearch/hermes-agent/pull/17577))
### Web search
- **Expose `limit` for `web_search`** ([#16934](https://github.com/NousResearch/hermes-agent/pull/16934))
### Maps
- Fix: include seconds in timezone UTC offset output ([#16300](https://github.com/NousResearch/hermes-agent/pull/16300))
### Approvals
- **Hardline blocklist for unrecoverable commands** ([#15878](https://github.com/NousResearch/hermes-agent/pull/15878))
- Perf: precompile DANGEROUS_PATTERNS and HARDLINE_PATTERNS ([#17206](https://github.com/NousResearch/hermes-agent/pull/17206))
### ACP
- **Advertise and forward image prompts** ([#18030](https://github.com/NousResearch/hermes-agent/pull/18030))
### API Server
- **POST `/v1/runs/{run_id}/stop`** (salvage of #15656) ([#15842](https://github.com/NousResearch/hermes-agent/pull/15842))
- **Expose run status for external UIs** (#17085) ([#17458](https://github.com/NousResearch/hermes-agent/pull/17458))
### Nix
- **Declarative plugin installation for NixOS module** (@alt-glitch) ([#15953](https://github.com/NousResearch/hermes-agent/pull/15953))
- Fix: use `--rebuild` in fix-lockfiles to bypass cached FOD store paths ([#15444](https://github.com/NousResearch/hermes-agent/pull/15444))
- Fix: `extraPackages` now actually works via per-user profile ([#17047](https://github.com/NousResearch/hermes-agent/pull/17047))
- Fix: refresh web/ npm-deps hash to unblock main builds ([#17174](https://github.com/NousResearch/hermes-agent/pull/17174))
- Fix: replace magic-nix-cache with Cachix ([#17928](https://github.com/NousResearch/hermes-agent/pull/17928))
---
## 🖥️ TUI
### New features
- **LaTeX rendering** (@austinpickett) ([#17175](https://github.com/NousResearch/hermes-agent/pull/17175))
- **`/reload` .env hot-reload** — ported from the classic CLI ([#17286](https://github.com/NousResearch/hermes-agent/pull/17286))
- **Pluggable busy-indicator styles** (@OutThisLife, #13610) ([#17150](https://github.com/NousResearch/hermes-agent/pull/17150))
- **Opt-in auto-resume of the most recent session** (@OutThisLife) ([#17130](https://github.com/NousResearch/hermes-agent/pull/17130))
- **Expanded light-terminal auto-detection** — `HERMES_TUI_THEME` + background hex (@OutThisLife) ([#17113](https://github.com/NousResearch/hermes-agent/pull/17113))
- **Delete sessions from `/resume` picker with `d`** (@OutThisLife) ([#17668](https://github.com/NousResearch/hermes-agent/pull/17668))
- **Line-by-line scroll on modified mouse wheel** (@OutThisLife) ([#17669](https://github.com/NousResearch/hermes-agent/pull/17669))
- **Delete queued message while editing with ctrl-x / cancel with esc** (@OutThisLife) ([#16707](https://github.com/NousResearch/hermes-agent/pull/16707))
- **Per-section visibility for the details accordion** (@OutThisLife) ([#14968](https://github.com/NousResearch/hermes-agent/pull/14968))
- **Voice mode CLI parity** — VAD loop + TTS + crash forensics ([#14810](https://github.com/NousResearch/hermes-agent/pull/14810))
- **Contextual first-touch hints ported to TUI** — `/busy`, `/verbose` ([#16054](https://github.com/NousResearch/hermes-agent/pull/16054))
- **Mini help menu on `?` in the input field** (@ethernet8023) ([#18043](https://github.com/NousResearch/hermes-agent/pull/18043))
### Fixes
- Fix: proactive mouse disable on ConPTY + `/mouse` toggle command (@kevin-ho, WSL2 ghost-mouse fix) ([#15488](https://github.com/NousResearch/hermes-agent/pull/15488))
- Fix: restore skills search RPC ([#15870](https://github.com/NousResearch/hermes-agent/pull/15870))
- Perf: cache text measurements across yoga flex re-passes ([#14818](https://github.com/NousResearch/hermes-agent/pull/14818))
- Perf: stabilize long-session scrolling ([#15926](https://github.com/NousResearch/hermes-agent/pull/15926))
- Perf: lazily seed virtual history heights ([#16523](https://github.com/NousResearch/hermes-agent/pull/16523))
- Perf: cut visible cold start ~57% with lazy agent init ([#17190](https://github.com/NousResearch/hermes-agent/pull/17190))
---
## 🖱️ CLI & User Experience
### New commands
- **`hermes -z <prompt>`** — non-interactive one-shot mode ([#15702](https://github.com/NousResearch/hermes-agent/pull/15702))
- **`hermes -z` with `--model` / `--provider` / `HERMES_INFERENCE_MODEL`** ([#15704](https://github.com/NousResearch/hermes-agent/pull/15704))
- **`hermes update --check`** preflight flag ([#15841](https://github.com/NousResearch/hermes-agent/pull/15841))
- **`hermes fallback`** command for managing fallback providers ([#16052](https://github.com/NousResearch/hermes-agent/pull/16052))
- **`/busy`** slash command for busy input mode ([#15382](https://github.com/NousResearch/hermes-agent/pull/15382))
- **`/busy` input mode 'steer'** as a third option ([#16279](https://github.com/NousResearch/hermes-agent/pull/16279))
- **`/btw` as alias for `/background`** ([#16053](https://github.com/NousResearch/hermes-agent/pull/16053))
- **`/reload-skills`** slash command (salvage #17670) ([#17744](https://github.com/NousResearch/hermes-agent/pull/17744))
- **Surface `/queue`, `/bg`, `/steer` in agent-running placeholder** ([#16118](https://github.com/NousResearch/hermes-agent/pull/16118))
### Setup / onboarding
- **Auto-reconfigure on existing installs** ([#15879](https://github.com/NousResearch/hermes-agent/pull/15879))
- **Contextual first-touch hints for `/busy` and `/verbose`** ([#16046](https://github.com/NousResearch/hermes-agent/pull/16046))
- **Cost-saving tips from the April 30 tip-of-the-day** ([#17841](https://github.com/NousResearch/hermes-agent/pull/17841))
- **Hyperlink startup banner title to the latest GitHub Release** ([#14945](https://github.com/NousResearch/hermes-agent/pull/14945))
### Update / backup
- **Snapshot pairing data before `git pull`** ([#16383](https://github.com/NousResearch/hermes-agent/pull/16383))
- **Auto-backup HERMES_HOME before `hermes update`** (opt-in, off by default) ([#16539](https://github.com/NousResearch/hermes-agent/pull/16539), [#16566](https://github.com/NousResearch/hermes-agent/pull/16566))
- **Exclude `checkpoints/` from backups** ([#16572](https://github.com/NousResearch/hermes-agent/pull/16572))
- **Exclude SQLite WAL/SHM/journal sidecars from backups** ([#16576](https://github.com/NousResearch/hermes-agent/pull/16576))
- **Installer FHS layout for root installs on Linux** ([#15608](https://github.com/NousResearch/hermes-agent/pull/15608))
- Fix: kill stale dashboards instead of warning ([#17832](https://github.com/NousResearch/hermes-agent/pull/17832))
- Fix: show correct update status on nix-built hermes ([#17550](https://github.com/NousResearch/hermes-agent/pull/17550))
### Slash-command housekeeping
- Refactor: drop `/provider`, `/plan` handler, and clean up slash registry ([#15047](https://github.com/NousResearch/hermes-agent/pull/15047))
- Refactor: drop `persist_session` plumbing + fix broken `/btw` mid-turn bypass ([#16075](https://github.com/NousResearch/hermes-agent/pull/16075))
### OpenClaw migration (for folks coming from OpenClaw)
- **Hardened OpenClaw import** — plan-first apply, redaction, pre-migration backup ([#16911](https://github.com/NousResearch/hermes-agent/pull/16911))
- Fix: case-preserving brand rewrite + one-time `~/.openclaw` residue banner ([#16327](https://github.com/NousResearch/hermes-agent/pull/16327))
- Fix: resolve `openclaw` workspace files from `agents.defaults.workspace` ([#16879](https://github.com/NousResearch/hermes-agent/pull/16879))
- Fix: resolve model aliases against real OpenClaw catalog schema (salvage #16778) ([#16977](https://github.com/NousResearch/hermes-agent/pull/16977))
---
## 📊 Web Dashboard
- **Models tab** — rich per-model analytics ([#17745](https://github.com/NousResearch/hermes-agent/pull/17745))
- **Configure main + auxiliary models from the Models page** ([#17802](https://github.com/NousResearch/hermes-agent/pull/17802))
- **Dashboard Chat tab — xterm.js + JSON-RPC sidecar** (supersedes #12710 + #13379, @OutThisLife) ([#14890](https://github.com/NousResearch/hermes-agent/pull/14890))
- **Dashboard layout refresh** (@austinpickett) ([#14899](https://github.com/NousResearch/hermes-agent/pull/14899))
- **`--stop` and `--status` flags** on the dashboard CLI ([#17840](https://github.com/NousResearch/hermes-agent/pull/17840))
- **Page-scoped plugin slots for built-in pages** ([#15658](https://github.com/NousResearch/hermes-agent/pull/15658))
- Fix: replace all buttons for design system buttons ([#17007](https://github.com/NousResearch/hermes-agent/pull/17007))
---
## ⚡ Performance
- **TUI visible cold start cut ~57%** via lazy agent init ([#17190](https://github.com/NousResearch/hermes-agent/pull/17190))
- **Lazy-import OpenAI, Anthropic, Firecrawl, account_usage** ([#17046](https://github.com/NousResearch/hermes-agent/pull/17046))
- **mtime-cache `load_config()` and `read_raw_config()`** ([#17041](https://github.com/NousResearch/hermes-agent/pull/17041))
- **Memoize `get_tool_definitions()` + TTL-cache `check_fn` results** ([#17098](https://github.com/NousResearch/hermes-agent/pull/17098))
- **Precompile DANGEROUS_PATTERNS and HARDLINE_PATTERNS** ([#17206](https://github.com/NousResearch/hermes-agent/pull/17206))
- **Cache Ink text measurements across yoga flex re-passes** ([#14818](https://github.com/NousResearch/hermes-agent/pull/14818))
- **Stabilize long-session scrolling** ([#15926](https://github.com/NousResearch/hermes-agent/pull/15926))
- **Lazily seed virtual history heights** ([#16523](https://github.com/NousResearch/hermes-agent/pull/16523))
---
## 🔒 Security & Reliability
- **Secret redaction off by default** — stops corrupting patches / API payloads with fake-key substitutions. Opt in via `redaction.enabled: true` ([#16794](https://github.com/NousResearch/hermes-agent/pull/16794))
- **`[SYSTEM:``[IMPORTANT:`** in all user-injected markers (Azure content filter dodge) ([#16114](https://github.com/NousResearch/hermes-agent/pull/16114))
- **Hardline blocklist for unrecoverable commands** ([#15878](https://github.com/NousResearch/hermes-agent/pull/15878))
- **Canonical `mask_secret` helper; fix status.py DIM drift** ([#17207](https://github.com/NousResearch/hermes-agent/pull/17207))
- **Sweep expired paste.rs uploads on a real timer** ([#16431](https://github.com/NousResearch/hermes-agent/pull/16431))
- **Preserve symlinks during atomic file writes** ([#16980](https://github.com/NousResearch/hermes-agent/pull/16980))
- **Probe `/dev/tty` by opening it, not bare existence** ([#17024](https://github.com/NousResearch/hermes-agent/pull/17024))
---
## 🐛 Notable Bug Fixes
This window includes 360 `fix:` PRs. Selected highlights from across the stack:
- **Background review fork inherits parent's live runtime** — provider/model/creds now propagate correctly ([#16099](https://github.com/NousResearch/hermes-agent/pull/16099))
- **Hindsight configurable `HINDSIGHT_TIMEOUT` env var** ([#15077](https://github.com/NousResearch/hermes-agent/pull/15077))
- **Tools: normalize numeric entries + clear stale `no_mcp` in `_save_platform_tools`** ([#15607](https://github.com/NousResearch/hermes-agent/pull/15607))
- **MCP: rewrite `definitions` refs to `$defs` in input schemas** — closes provider-side 400s
- **Azure content filter compatibility** — renamed `[SYSTEM:` markers so Azure's content filter stops flagging them ([#16114](https://github.com/NousResearch/hermes-agent/pull/16114))
- **Vision cache uses HERMES_HOME instead of cwd** ([#17719](https://github.com/NousResearch/hermes-agent/pull/17719))
- **FTS5 search** — tool_name + tool_calls indexing with repair + migration ([#16914](https://github.com/NousResearch/hermes-agent/pull/16914))
- **Streaming reasoning persists on assistant turns** ([#16892](https://github.com/NousResearch/hermes-agent/pull/16892))
- **execute_code concurrent RPC serialization** (#17770) ([#17894](https://github.com/NousResearch/hermes-agent/pull/17894), [#17902](https://github.com/NousResearch/hermes-agent/pull/17902))
- **Background reviewer scoped to memory + skills toolsets** — no more accidental web/shell escapes ([#16569](https://github.com/NousResearch/hermes-agent/pull/16569))
- **Compression recovery** — retry on main before giving up; notify user when aux fails ([#16774](https://github.com/NousResearch/hermes-agent/pull/16774), [#16775](https://github.com/NousResearch/hermes-agent/pull/16775))
- **`croniter` promoted to a core dependency** ([#17577](https://github.com/NousResearch/hermes-agent/pull/17577))
- **Discord tool `limit` parameter coerced to int** before `min()` call ([#16319](https://github.com/NousResearch/hermes-agent/pull/16319))
- **Yuanbao messaging platform entrance fix** ([#16880](https://github.com/NousResearch/hermes-agent/pull/16880))
- **ACP advertise and forward image prompts** ([#18030](https://github.com/NousResearch/hermes-agent/pull/18030))
- **DeepSeek / Kimi reasoning content isolation** across cross-provider histories (@Zjianru) ([#15749](https://github.com/NousResearch/hermes-agent/pull/15749), [#15762](https://github.com/NousResearch/hermes-agent/pull/15762))
- **Preserve reasoning_content replay on DeepSeek v4 + Kimi/Moonshot thinking** ([#18045](https://github.com/NousResearch/hermes-agent/pull/18045))
The vast majority of the 360 fixes landed in the streaming/compression/tool-calling paths across all providers — DeepSeek, Kimi, Moonshot, GLM, Qwen, MiniMax, Gemini, Anthropic, OpenAI — alongside TUI polish (resize, scroll, sticky-prompt) and gateway platform-specific edge cases.
---
## 🧪 Testing & CI
- Hermetic test parity (`scripts/run_tests.sh`) held across this window
- **Microsoft Teams xdist collision guard** — prevents worker collisions when Teams platform tests run in parallel ([#17828](https://github.com/NousResearch/hermes-agent/pull/17828))
- Chore: remove unused imports and dead locals (ruff F401, F841) ([#17010](https://github.com/NousResearch/hermes-agent/pull/17010))
---
## 📚 Documentation
- **Curator feature page** added to docs site ([#17563](https://github.com/NousResearch/hermes-agent/pull/17563))
- **Document pin also blocking `skill_manage` writes** ([#17578](https://github.com/NousResearch/hermes-agent/pull/17578))
- **Direct-URL skill install documented** across features, reference, guide, and `hermes-agent` skill ([#16355](https://github.com/NousResearch/hermes-agent/pull/16355))
- **Hooks tutorial — build a BOOT.md startup checklist** (replaces the removed built-in hook) ([#17202](https://github.com/NousResearch/hermes-agent/pull/17202))
- **ComfyUI docs: ask local vs cloud FIRST before hardware check** ([#17612](https://github.com/NousResearch/hermes-agent/pull/17612))
- **Obliteratus skill: link YouTube video guide in SKILL.md** ([#15808](https://github.com/NousResearch/hermes-agent/pull/15808))
- Per-skill docs pages generated for bundled + optional skills; ASCII art code blocks auto-wrapped ([#14929](https://github.com/NousResearch/hermes-agent/pull/14929), [#16497](https://github.com/NousResearch/hermes-agent/pull/16497))
---
## ⚖️ Removed / Reverted
- **Kanban multi-profile collaboration board** — landed in #16081, reverted in ([#16098](https://github.com/NousResearch/hermes-agent/pull/16098)) while the design is reworked
- **computer-use cua-driver** — 3 preparatory PRs landed then were reverted in ([#16927](https://github.com/NousResearch/hermes-agent/pull/16927))
- **BOOT.md built-in hook** removed ([#17093](https://github.com/NousResearch/hermes-agent/pull/17093)); the hooks tutorial ([#17202](https://github.com/NousResearch/hermes-agent/pull/17202)) shows how to build the same workflow yourself with a shell hook
- **`/provider` + `/plan` slash commands dropped** ([#15047](https://github.com/NousResearch/hermes-agent/pull/15047))
- **`flush_memories` removed entirely** ([#15696](https://github.com/NousResearch/hermes-agent/pull/15696))
---
## 👥 Contributors
### Core
- **@teknium1** (Teknium)
### Top Community Contributors (by merged PR count since v0.11.0)
- **@OutThisLife** (Brooklyn) — 52 PRs · TUI — light-terminal detection + pluggable busy styles + auto-resume + session-delete from /resume + mouse-wheel scrolling + xterm.js dashboard Chat tab + cold-start cut + accordion polish
- **@kshitijk4poor** — 12 PRs · LM Studio first-class provider (salvage), Vercel Sandbox backend, GMI Cloud salvage, bundled-by-default touchdesigner-mcp, many tool-call / reasoning fixes
- **@helix4u** — 10 PRs · MCP schema robustness, assorted stability fixes
- **@alt-glitch** — 8 PRs · trigram FTS5 CJK search, declarative Nix plugin install, matrix/feishu hints and fixes
- **@ethernet8023** — 4 PRs
- **@austinpickett** — 4 PRs · LaTeX rendering in TUI, dashboard layout refresh
- **@benbarclay** — 3 PRs · Docker run-as-host-user so bind mounts don't get root-owned
- **@vominh1919** — 2 PRs
- **@stephenschoettler** — 2 PRs
- **@kevin-ho** — ConPTY mouse-injection fix (#15488)
- **@Zjianru** — cross-provider reasoning_content isolation + DeepSeek/Kimi empty-reasoning injection (#15749, #15762)
- **@web3blind** — Telegram chat allowlists for groups and forums (#15027)
- **@SHL0MS** — 9 new TouchDesigner-MCP reference docs (#16768)
- **@0xDevNinja** — curator `restore_skill` nested-archive fix (#17951)
- **@y0shua1ee** — curator `use` activity fix (#17953)
### Also contributing
Salvaged or co-authored work from **@isaachuangGMICLOUD** (GMI Cloud), earlier upstream PRs from the original author of each salvage chain, and a long tail of one-shot fixes, documentation nudges, and skill contributions from the community.
### All Contributors (alphabetical, excluding @teknium1)
@0xbyt4, @0xharryriddle, @0xDevNinja, @0z1-ghb, @5park1e, @A-FdL-Prog, @aj-nt, @akhater, @alblez, @alexg0bot,
@alexzhu0, @AllardQuek, @alt-glitch, @amanning3390, @amanuel2, @AndreKurait, @andrewhosf, @Andy283, @andyylin,
@angel12, @AntAISecurityLab, @ash, @austinpickett, @badgerbees, @BadTechBandit, @Bartok9, @beenherebefore,
@beesrsj2500, @BeliefanX, @benbarclay, @benjaminsehl, @BlackishGreen33, @bloodcarter, @BlueBirdBack,
@briandevans, @brooklynnicholson, @bsgdigital, @buray, @bwjoke, @camaragon, @cdanis, @cgarwood82,
@charles-brooks, @chen1749144759, @chengoak, @ching-kaching, @Contentment003111, @crayfish-ai, @CruxExperts,
@cyclingwithelephants, @dandaka, @danklynn, @ddupont808, @dhabibi, @difujia, @dimitrovi, @dlkakbs,
@dontcallmejames, @EKKOLearnAI, @emozilla, @ericnicolaides, @Erosika, @ethernet8023, @exiao, @Feranmi10,
@flobo3, @foxion37, @georgeglessner, @georgex8001, @ghostmfr, @H-Ali13381, @HangGlidersRule, @harryplusplus,
@haru398801, @heathley, @hejuntt1014, @hekaru-agent, @helix4u, @Heltman, @HenkDz, @heyitsaamir, @hharry11,
@hhhonzik, @hhuang91, @HiddenPuppy, @htsh, @iamagenius00, @in-liberty420, @innocarpe, @irispillars, @iRonin,
@isaachuangGMICLOUD, @Ito-69, @j3ffffff, @jackjin1997, @jakubkrcmar, @Jason2031, @JayGwod, @jerome-benoit,
@johnncenae, @Kailigithub, @keiravoss94, @kevin-ho, @knockyai, @konsisumer, @kshitijk4poor, @kunlabs, @l0hde,
@Leihb, @leoneparise, @LeonSGP43, @liizfq, @liuhao1024, @loongzhao, @lsdsjy, @luyao618, @ma-pony, @Magaav,
@MagicRay1217, @math0r-be, @MattMaximo, @maxims-oss, @MaxyMoos, @maymuneth, @mcndjxlefnd, @memosr,
@MestreY0d4-Uninter, @mewwts, @Mirac1eSky, @MorAlekss, @mrhwick, @mrunmayee17, @mssteuer, @Nanako0129,
@nazirulhafiy, @Nerijusas, @Nicecsh, @nicoloboschi, @nightq, @ningfangbin, @octo-patch, @Octopus,
@OutThisLife, @Paperclip, @pein892, @perlowja, @prasadus92, @qike-ms, @qiyin-code, @Readon, @ReginaldasR,
@revaraver, @rfilgueiras, @rmoen, @romanornr, @rugvedS07, @rylena, @samrusani, @Sanjays2402, @sasha-id,
@Satoshi-agi, @scheidti, @scotttrinh, @season179, @SeeYangZhi, @sgaofen, @shamork, @shannonsands, @SHL0MS,
@simbam99, @Societus, @socrates1024, @Sonoyunchu, @sprmn24, @stephenschoettler, @tangyuanjc, @TechPrototyper,
@tekgnosis-net, @ThomassJonax, @tmimmanuel, @tochukwuada, @Tosko4, @Tranquil-Flow, @twozle, @txbxxx,
@UgwujaGeorge, @Versun, @vlwkaos, @voidborne-d, @vominh1919, @Wang-tianhao, @Wangshengyang2004, @web3blind,
@westers, @Wysie, @xandersbell, @xiahu88988, @XieNBi, @xinbenlv, @xnbi, @y0shua1ee, @yatesjalex, @yes999zc,
@yeyitech, @Yoimex, @YueLich, @Yukipukii1, @zhiyanliu, @zicochaos, @Zjianru, @zkl2333, @zons-zhaozhy,
@ztexydt-cqh.
Also: @Siddharth Balyan, @YuShu.
---
**Full Changelog**: [v2026.4.23...v2026.4.30](https://github.com/NousResearch/hermes-agent/compare/v2026.4.23...v2026.4.30)
-11
View File
@@ -112,17 +112,6 @@ def main() -> None:
import acp
from .server import HermesACPAgent
# MCP tool discovery from config.yaml — run before asyncio.run() so
# it's safe to use blocking waits. (ACP also registers per-session
# MCP servers dynamically via asyncio.to_thread inside the event
# loop; that path is unaffected.) Moved from model_tools.py module
# scope to avoid freezing the gateway's loop on lazy import (#16856).
try:
from tools.mcp_tool import discover_mcp_tools
discover_mcp_tools()
except Exception:
logger.debug("MCP tool discovery failed at ACP startup", exc_info=True)
agent = HermesACPAgent()
try:
asyncio.run(acp.run_agent(agent, use_unstable_protocol=True))
+24 -546
View File
@@ -3,8 +3,6 @@
from __future__ import annotations
import asyncio
import contextvars
import json
import logging
import os
from collections import defaultdict, deque
@@ -14,7 +12,6 @@ from typing import Any, Deque, Optional
import acp
from acp.schema import (
AgentCapabilities,
AgentMessageChunk,
AuthenticateResponse,
AvailableCommand,
AvailableCommandsUpdate,
@@ -32,7 +29,6 @@ from acp.schema import (
McpServerStdio,
ModelInfo,
NewSessionResponse,
PromptCapabilities,
PromptResponse,
ResumeSessionResponse,
SetSessionConfigOptionResponse,
@@ -48,8 +44,6 @@ from acp.schema import (
TextContentBlock,
UnstructuredCommandInput,
Usage,
UsageUpdate,
UserMessageChunk,
)
# AuthMethodAgent was renamed from AuthMethod in agent-client-protocol 0.9.0
@@ -66,8 +60,7 @@ from acp_adapter.events import (
make_tool_progress_cb,
)
from acp_adapter.permissions import make_approval_callback
from acp_adapter.session import SessionManager, SessionState, _expand_acp_enabled_toolsets
from acp_adapter.tools import build_tool_complete, build_tool_start
from acp_adapter.session import SessionManager, SessionState
logger = logging.getLogger(__name__)
@@ -94,69 +87,17 @@ def _extract_text(
| EmbeddedResourceContentBlock
],
) -> str:
"""Extract plain text from ACP content blocks for display/commands."""
"""Extract plain text from ACP content blocks."""
parts: list[str] = []
for block in prompt:
if isinstance(block, TextContentBlock):
parts.append(block.text)
elif hasattr(block, "text"):
parts.append(str(block.text))
# Non-text blocks are ignored for now.
return "\n".join(parts)
def _image_block_to_openai_part(block: ImageContentBlock) -> dict[str, Any] | None:
"""Convert an ACP image content block to OpenAI-style multimodal content."""
data = str(getattr(block, "data", "") or "").strip()
uri = str(getattr(block, "uri", "") or "").strip()
mime_type = str(getattr(block, "mime_type", "") or "image/png").strip() or "image/png"
if data:
url = data if data.startswith("data:") else f"data:{mime_type};base64,{data}"
elif uri:
url = uri
else:
return None
return {"type": "image_url", "image_url": {"url": url}}
def _content_blocks_to_openai_user_content(
prompt: list[
TextContentBlock
| ImageContentBlock
| AudioContentBlock
| ResourceContentBlock
| EmbeddedResourceContentBlock
],
) -> str | list[dict[str, Any]]:
"""Convert ACP prompt blocks into a Hermes/OpenAI-compatible user content payload."""
parts: list[dict[str, Any]] = []
text_parts: list[str] = []
for block in prompt:
if isinstance(block, TextContentBlock):
if block.text:
parts.append({"type": "text", "text": block.text})
text_parts.append(block.text)
continue
if isinstance(block, ImageContentBlock):
image_part = _image_block_to_openai_part(block)
if image_part is not None:
parts.append(image_part)
continue
if not parts:
return _extract_text(prompt)
# Keep pure text prompts as strings so slash-command handling and text-only
# providers keep the exact legacy path. Switch to structured content only
# when an actual non-text block is present.
if all(part.get("type") == "text" for part in parts):
return "\n".join(text_parts)
return parts
class HermesACPAgent(acp.Agent):
"""ACP Agent implementation wrapping Hermes AIAgent."""
@@ -167,8 +108,6 @@ class HermesACPAgent(acp.Agent):
"context": "Show conversation context info",
"reset": "Clear conversation history",
"compact": "Compress conversation context",
"steer": "Inject guidance into the currently running agent turn",
"queue": "Queue a prompt to run after the current turn finishes",
"version": "Show Hermes version",
}
@@ -198,16 +137,6 @@ class HermesACPAgent(acp.Agent):
"name": "compact",
"description": "Compress conversation context",
},
{
"name": "steer",
"description": "Inject guidance into the currently running agent turn",
"input_hint": "guidance for the active turn",
},
{
"name": "queue",
"description": "Queue a prompt to run after the current turn finishes",
"input_hint": "prompt to run next",
},
{
"name": "version",
"description": "Show Hermes version",
@@ -318,66 +247,6 @@ class HermesACPAgent(acp.Agent):
return target_provider, new_model
@staticmethod
def _build_usage_update(state: SessionState) -> UsageUpdate | None:
"""Build ACP native context-usage data for clients like Zed.
Zed's circular context indicator is driven by ACP ``usage_update``
session updates: ``size`` is the model context window and ``used`` is
the current request pressure. Hermes estimates ``used`` from the same
buckets it sends to providers: system prompt, conversation history, and
tool schemas.
"""
agent = state.agent
compressor = getattr(agent, "context_compressor", None)
size = int(getattr(compressor, "context_length", 0) or 0)
if size <= 0:
return None
try:
from agent.model_metadata import estimate_request_tokens_rough
used = estimate_request_tokens_rough(
state.history,
system_prompt=getattr(agent, "_cached_system_prompt", "") or "",
tools=getattr(agent, "tools", None) or None,
)
except Exception:
logger.debug("Could not estimate ACP native context usage", exc_info=True)
used = int(getattr(compressor, "last_prompt_tokens", 0) or 0)
return UsageUpdate(
session_update="usage_update",
size=max(size, 0),
used=max(used, 0),
)
async def _send_usage_update(self, state: SessionState) -> None:
"""Send ACP native context usage to the connected client."""
if not self._conn:
return
update = self._build_usage_update(state)
if update is None:
return
try:
await self._conn.session_update(
session_id=state.session_id,
update=update,
)
except Exception:
logger.warning(
"Failed to send ACP usage update for session %s",
state.session_id,
exc_info=True,
)
def _schedule_usage_update(self, state: SessionState) -> None:
"""Schedule native context indicator refresh after ACP responses."""
if not self._conn:
return
loop = asyncio.get_running_loop()
loop.call_soon(asyncio.create_task, self._send_usage_update(state))
async def _register_session_mcp_servers(
self,
state: SessionState,
@@ -418,11 +287,7 @@ class HermesACPAgent(acp.Agent):
try:
from model_tools import get_tool_definitions
enabled_toolsets = _expand_acp_enabled_toolsets(
getattr(state.agent, "enabled_toolsets", None) or ["hermes-acp"],
mcp_server_names=[server.name for server in mcp_servers],
)
state.agent.enabled_toolsets = enabled_toolsets
enabled_toolsets = getattr(state.agent, "enabled_toolsets", None) or ["hermes-acp"]
disabled_toolsets = getattr(state.agent, "disabled_toolsets", None)
state.agent.tools = get_tool_definitions(
enabled_toolsets=enabled_toolsets,
@@ -482,7 +347,6 @@ class HermesACPAgent(acp.Agent):
agent_info=Implementation(name="hermes-agent", version=HERMES_VERSION),
agent_capabilities=AgentCapabilities(
load_session=True,
prompt_capabilities=PromptCapabilities(image=True),
session_capabilities=SessionCapabilities(
fork=SessionForkCapabilities(),
list=SessionListCapabilities(),
@@ -508,140 +372,6 @@ class HermesACPAgent(acp.Agent):
# ---- Session management -------------------------------------------------
@staticmethod
def _history_message_text(message: dict[str, Any]) -> str:
"""Extract displayable text from a persisted OpenAI-style message."""
content = message.get("content")
if isinstance(content, str):
return content.strip()
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, dict):
text = item.get("text")
if isinstance(text, str):
parts.append(text)
elif item.get("type") == "text" and isinstance(item.get("content"), str):
parts.append(item["content"])
elif isinstance(item, str):
parts.append(item)
return "\n".join(part.strip() for part in parts if part and part.strip()).strip()
return ""
@staticmethod
def _history_message_update(
*,
role: str,
text: str,
) -> UserMessageChunk | AgentMessageChunk | None:
"""Build an ACP history replay update for a user/assistant message."""
block = TextContentBlock(type="text", text=text)
if role == "user":
return UserMessageChunk(
session_update="user_message_chunk",
content=block,
)
if role == "assistant":
return AgentMessageChunk(
session_update="agent_message_chunk",
content=block,
)
return None
@staticmethod
def _history_tool_call_name_args(tool_call: dict[str, Any]) -> tuple[str, dict[str, Any]]:
"""Extract function name/arguments from an OpenAI-style tool_call."""
function = tool_call.get("function") if isinstance(tool_call.get("function"), dict) else {}
name = str(function.get("name") or tool_call.get("name") or "unknown_tool")
raw_args = function.get("arguments") or tool_call.get("arguments") or tool_call.get("args") or {}
if isinstance(raw_args, str):
try:
parsed = json.loads(raw_args)
except Exception:
parsed = {"raw": raw_args}
raw_args = parsed
if not isinstance(raw_args, dict):
raw_args = {}
return name, raw_args
@staticmethod
def _history_tool_call_id(tool_call: dict[str, Any]) -> str:
"""Return the stable provider tool call id for ACP history replay."""
return str(
tool_call.get("id")
or tool_call.get("call_id")
or tool_call.get("tool_call_id")
or ""
).strip()
async def _replay_session_history(self, state: SessionState) -> None:
"""Send persisted user/assistant history to clients during session/load.
Zed's ACP history UI calls ``session/load`` after the user picks an item
from the Agents sidebar. The agent must then replay the full conversation
as user/assistant chunks plus reconstructed tool-call start/completion
notifications; merely restoring server-side state makes Hermes remember
context, but leaves the editor looking like a clean thread.
"""
if not self._conn or not state.history:
return
active_tool_calls: dict[str, tuple[str, dict[str, Any]]] = {}
async def _send(update: Any) -> bool:
try:
await self._conn.session_update(session_id=state.session_id, update=update)
return True
except Exception:
logger.warning(
"Failed to replay ACP history for session %s",
state.session_id,
exc_info=True,
)
return False
for message in state.history:
role = str(message.get("role") or "")
if role in {"user", "assistant"}:
text = self._history_message_text(message)
if text:
update = self._history_message_update(role=role, text=text)
if update is not None and not await _send(update):
return
if role == "assistant" and isinstance(message.get("tool_calls"), list):
for tool_call in message["tool_calls"]:
if not isinstance(tool_call, dict):
continue
tool_call_id = self._history_tool_call_id(tool_call)
if not tool_call_id:
continue
tool_name, args = self._history_tool_call_name_args(tool_call)
active_tool_calls[tool_call_id] = (tool_name, args)
if not await _send(build_tool_start(tool_call_id, tool_name, args)):
return
continue
if role == "tool":
tool_call_id = str(message.get("tool_call_id") or "").strip()
tool_name = str(message.get("tool_name") or "").strip()
function_args: dict[str, Any] | None = None
if tool_call_id in active_tool_calls:
tool_name, function_args = active_tool_calls.pop(tool_call_id)
if not tool_call_id or not tool_name:
continue
result = message.get("content")
if not await _send(
build_tool_complete(
tool_call_id,
tool_name,
result=result if isinstance(result, str) else None,
function_args=function_args,
)
):
return
async def new_session(
self,
cwd: str,
@@ -652,24 +382,11 @@ class HermesACPAgent(acp.Agent):
await self._register_session_mcp_servers(state, mcp_servers)
logger.info("New session %s (cwd=%s)", state.session_id, cwd)
self._schedule_available_commands_update(state.session_id)
self._schedule_usage_update(state)
return NewSessionResponse(
session_id=state.session_id,
models=self._build_model_state(state),
)
def _schedule_history_replay(self, state: SessionState) -> None:
"""Replay persisted history after session/load or session/resume returns.
Zed only attaches streamed transcript/tool updates once the load/resume
response has completed. Sending replay notifications while the request is
still in-flight can make the server look correct in logs while the editor
drops or fails to attach the tool-call history.
"""
loop = asyncio.get_running_loop()
replay_coro = self._replay_session_history(state)
loop.call_soon(asyncio.create_task, replay_coro)
async def load_session(
self,
cwd: str,
@@ -683,9 +400,7 @@ class HermesACPAgent(acp.Agent):
return None
await self._register_session_mcp_servers(state, mcp_servers)
logger.info("Loaded session %s", session_id)
self._schedule_history_replay(state)
self._schedule_available_commands_update(session_id)
self._schedule_usage_update(state)
return LoadSessionResponse(models=self._build_model_state(state))
async def resume_session(
@@ -701,17 +416,12 @@ class HermesACPAgent(acp.Agent):
state = self.session_manager.create_session(cwd=cwd)
await self._register_session_mcp_servers(state, mcp_servers)
logger.info("Resumed session %s", state.session_id)
self._schedule_history_replay(state)
self._schedule_available_commands_update(state.session_id)
self._schedule_usage_update(state)
return ResumeSessionResponse(models=self._build_model_state(state))
async def cancel(self, session_id: str, **kwargs: Any) -> None:
state = self.session_manager.get_session(session_id)
if state and state.cancel_event:
with state.runtime_lock:
if state.is_running and state.current_prompt_text:
state.interrupted_prompt_text = state.current_prompt_text
state.cancel_event.set()
try:
if getattr(state, "agent", None) and hasattr(state.agent, "interrupt"):
@@ -802,77 +512,18 @@ class HermesACPAgent(acp.Agent):
return PromptResponse(stop_reason="refusal")
user_text = _extract_text(prompt).strip()
user_content = _content_blocks_to_openai_user_content(prompt)
has_content = bool(user_text) or (
isinstance(user_content, list) and bool(user_content)
)
if not has_content:
if not user_text:
return PromptResponse(stop_reason="end_turn")
# /steer on an idle session has no in-flight tool call to inject into.
# Rewrite it so the payload runs as a normal user prompt, matching the
# gateway's behavior (gateway/run.py ~L4898). Two sub-cases:
# 1. Zed-interrupt salvage — a prior prompt was cancelled by the
# client right before /steer arrived; replay it with the steer
# text attached as explicit correction/guidance so the user's
# in-flight work isn't lost.
# 2. Plain idle — no prior work to salvage; just run the steer
# payload as a regular prompt. Without this, _cmd_steer would
# silently append to state.queued_prompts and respond with
# "No active turn — queued for the next turn", which looks like
# /queue even though the user never typed /queue.
if isinstance(user_content, str) and user_text.startswith("/steer"):
steer_text = user_text.split(maxsplit=1)[1].strip() if len(user_text.split(maxsplit=1)) > 1 else ""
interrupted_prompt = ""
rewrite_idle = False
with state.runtime_lock:
if not state.is_running and steer_text:
if state.interrupted_prompt_text:
interrupted_prompt = state.interrupted_prompt_text
state.interrupted_prompt_text = ""
else:
rewrite_idle = True
if interrupted_prompt:
user_text = (
f"{interrupted_prompt}\n\n"
f"User correction/guidance after interrupt: {steer_text}"
)
user_content = user_text
elif rewrite_idle:
user_text = steer_text
user_content = steer_text
# Intercept slash commands — handle locally without calling the LLM.
# Slash commands are text-only; if the client included images/resources,
# send the whole multimodal prompt to the agent instead of treating it as
# an ACP command.
if isinstance(user_content, str) and user_text.startswith("/"):
# Intercept slash commands — handle locally without calling the LLM
if user_text.startswith("/"):
response_text = self._handle_slash_command(user_text, state)
if response_text is not None:
if self._conn:
update = acp.update_agent_message_text(response_text)
await self._conn.session_update(session_id, update)
await self._send_usage_update(state)
return PromptResponse(stop_reason="end_turn")
# If Zed sends another regular prompt while the same ACP session is
# still running, queue it instead of racing two AIAgent loops against
# the same state.history. /steer and /queue are handled above and can
# land immediately.
with state.runtime_lock:
if state.is_running:
queued_text = user_text or "[Image attachment]"
state.queued_prompts.append(queued_text)
depth = len(state.queued_prompts)
if self._conn:
update = acp.update_agent_message_text(
f"Queued for the next turn. ({depth} queued)"
)
await self._conn.session_update(session_id, update)
return PromptResponse(stop_reason="end_turn")
state.is_running = True
state.current_prompt_text = user_text or "[Image attachment]"
logger.info("Prompt on session %s: %s", session_id, user_text[:100])
conn = self._conn
@@ -885,37 +536,24 @@ class HermesACPAgent(acp.Agent):
tool_call_meta: dict[str, dict[str, Any]] = {}
previous_approval_cb = None
streamed_message = False
if conn:
tool_progress_cb = make_tool_progress_cb(conn, session_id, loop, tool_call_ids, tool_call_meta)
reasoning_cb = make_thinking_cb(conn, session_id, loop)
thinking_cb = make_thinking_cb(conn, session_id, loop)
step_cb = make_step_cb(conn, session_id, loop, tool_call_ids, tool_call_meta)
message_cb = make_message_cb(conn, session_id, loop)
def stream_delta_cb(text: str) -> None:
nonlocal streamed_message
if text:
streamed_message = True
message_cb(text)
approval_cb = make_approval_callback(conn.request_permission, loop, session_id)
else:
tool_progress_cb = None
reasoning_cb = None
thinking_cb = None
step_cb = None
stream_delta_cb = None
message_cb = None
approval_cb = None
agent = state.agent
agent.tool_progress_callback = tool_progress_cb
# ACP thought panes should not receive Hermes' local kawaii waiting/status
# updates. Route provider/model reasoning deltas instead; if the provider
# emits no reasoning, Zed should not get a fake "thinking" accordion.
agent.thinking_callback = None
agent.reasoning_callback = reasoning_cb
agent.thinking_callback = thinking_cb
agent.step_callback = step_cb
agent.stream_delta_callback = stream_delta_cb
agent.message_callback = message_cb
# Approval callback is per-thread (thread-local, GHSA-qg5c-hvr5-hjgr).
# Set it INSIDE _run_agent so the TLS write happens in the executor
@@ -932,22 +570,6 @@ class HermesACPAgent(acp.Agent):
def _run_agent() -> dict:
nonlocal previous_approval_cb, previous_interactive
# Bind HERMES_SESSION_KEY for this session so per-session caches
# (e.g. the interactive sudo password cache in tools.terminal_tool)
# scope to the ACP session rather than leaking across sessions
# that land on the same reused executor thread. This call runs
# inside a contextvars.copy_context() below, so the ContextVar
# write is isolated from other concurrent ACP sessions.
try:
from gateway.session_context import (
clear_session_vars,
set_session_vars,
)
session_tokens = set_session_vars(session_key=session_id)
except Exception:
session_tokens = None
clear_session_vars = None # type: ignore[assignment]
logger.debug("Could not set ACP session context", exc_info=True)
if approval_cb:
try:
from tools import terminal_tool as _terminal_tool
@@ -961,10 +583,9 @@ class HermesACPAgent(acp.Agent):
os.environ["HERMES_INTERACTIVE"] = "1"
try:
result = agent.run_conversation(
user_message=user_content,
user_message=user_text,
conversation_history=state.history,
task_id=session_id,
persist_user_message=user_text or "[Image attachment]",
)
return result
except Exception as e:
@@ -982,24 +603,11 @@ class HermesACPAgent(acp.Agent):
_terminal_tool.set_approval_callback(previous_approval_cb)
except Exception:
logger.debug("Could not restore approval callback", exc_info=True)
if session_tokens is not None and clear_session_vars is not None:
try:
clear_session_vars(session_tokens)
except Exception:
logger.debug("Could not clear ACP session context", exc_info=True)
try:
# Wrap the executor call in a fresh copy of the current context so
# concurrent ACP sessions on the shared ThreadPoolExecutor don't
# stomp on each other's ContextVar writes (HERMES_SESSION_KEY in
# particular — used by the interactive sudo password cache scope).
ctx = contextvars.copy_context()
result = await loop.run_in_executor(_executor, ctx.run, _run_agent)
result = await loop.run_in_executor(_executor, _run_agent)
except Exception:
logger.exception("Executor error for session %s", session_id)
with state.runtime_lock:
state.is_running = False
state.current_prompt_text = ""
return PromptResponse(stop_reason="end_turn")
if result.get("messages"):
@@ -1021,32 +629,10 @@ class HermesACPAgent(acp.Agent):
)
except Exception:
logger.debug("Failed to auto-title ACP session %s", session_id, exc_info=True)
if final_response and conn and not streamed_message:
if final_response and conn:
update = acp.update_agent_message_text(final_response)
await conn.session_update(session_id, update)
# Mark this turn idle before draining queued work so recursive prompt()
# calls can acquire the session. Queued turns are intentionally run as
# normal follow-up user prompts, preserving role alternation and history.
with state.runtime_lock:
state.is_running = False
state.current_prompt_text = ""
while True:
with state.runtime_lock:
if not state.queued_prompts:
break
next_prompt = state.queued_prompts.pop(0)
if conn:
await conn.session_update(
session_id,
acp.update_user_message_text(next_prompt),
)
await self.prompt(
prompt=[TextContentBlock(type="text", text=next_prompt)],
session_id=session_id,
)
usage = None
if any(result.get(key) is not None for key in ("prompt_tokens", "completion_tokens", "total_tokens")):
usage = Usage(
@@ -1057,8 +643,6 @@ class HermesACPAgent(acp.Agent):
cached_read_tokens=result.get("cache_read_tokens"),
)
await self._send_usage_update(state)
stop_reason = "cancelled" if state.cancel_event and state.cancel_event.is_set() else "end_turn"
return PromptResponse(stop_reason=stop_reason, usage=usage)
@@ -1126,8 +710,6 @@ class HermesACPAgent(acp.Agent):
"context": self._cmd_context,
"reset": self._cmd_reset,
"compact": self._cmd_compact,
"steer": self._cmd_steer,
"queue": self._cmd_queue,
"version": self._cmd_version,
}.get(cmd)
@@ -1172,9 +754,7 @@ class HermesACPAgent(acp.Agent):
def _cmd_tools(self, args: str, state: SessionState) -> str:
try:
from model_tools import get_tool_definitions
toolsets = _expand_acp_enabled_toolsets(
getattr(state.agent, "enabled_toolsets", None) or ["hermes-acp"]
)
toolsets = getattr(state.agent, "enabled_toolsets", None) or ["hermes-acp"]
tools = get_tool_definitions(enabled_toolsets=toolsets, quiet_mode=True)
if not tools:
return "No tools available."
@@ -1191,84 +771,22 @@ class HermesACPAgent(acp.Agent):
return f"Could not list tools: {e}"
def _cmd_context(self, args: str, state: SessionState) -> str:
"""Show ACP session context pressure and compression guidance."""
n_messages = len(state.history)
# Count by role.
if n_messages == 0:
return "Conversation is empty (no messages yet)."
# Count by role
roles: dict[str, int] = {}
for msg in state.history:
role = msg.get("role", "unknown")
roles[role] = roles.get(role, 0) + 1
agent = state.agent
model = state.model or getattr(agent, "model", "")
provider = getattr(agent, "provider", None) or "auto"
compressor = getattr(agent, "context_compressor", None)
context_length = int(getattr(compressor, "context_length", 0) or 0)
threshold_tokens = int(getattr(compressor, "threshold_tokens", 0) or 0)
try:
from agent.model_metadata import estimate_request_tokens_rough
system_prompt = getattr(agent, "_cached_system_prompt", "") or ""
tools = getattr(agent, "tools", None) or None
approx_tokens = estimate_request_tokens_rough(
state.history,
system_prompt=system_prompt,
tools=tools,
)
except Exception:
logger.debug("Could not estimate ACP context usage", exc_info=True)
approx_tokens = 0
if threshold_tokens <= 0 and context_length > 0:
threshold_tokens = int(context_length * 0.80)
lines = [
f"Conversation: {n_messages} messages"
if n_messages
else "Conversation is empty (no messages yet).",
f"Conversation: {n_messages} messages",
f" user: {roles.get('user', 0)}, assistant: {roles.get('assistant', 0)}, "
f"tool: {roles.get('tool', 0)}, system: {roles.get('system', 0)}",
]
model = state.model or getattr(state.agent, "model", "")
if model:
lines.append(f"Model: {model}")
lines.append(f"Provider: {provider}")
if approx_tokens > 0:
if context_length > 0:
usage_pct = (approx_tokens / context_length) * 100
lines.append(
f"Context usage: ~{approx_tokens:,} / {context_length:,} tokens ({usage_pct:.1f}%)"
)
else:
lines.append(f"Context usage: ~{approx_tokens:,} tokens")
if threshold_tokens > 0:
if approx_tokens > 0:
threshold_pct = (threshold_tokens / context_length) * 100 if context_length > 0 else 0
remaining = max(threshold_tokens - approx_tokens, 0)
if approx_tokens >= threshold_tokens:
lines.append(
f"Compression: due now (threshold ~{threshold_tokens:,}"
+ (f", {threshold_pct:.0f}%" if threshold_pct else "")
+ "). Run /compact."
)
else:
lines.append(
f"Compression: ~{remaining:,} tokens until threshold "
f"(~{threshold_tokens:,}"
+ (f", {threshold_pct:.0f}%" if threshold_pct else "")
+ ")."
)
else:
lines.append(f"Compression threshold: ~{threshold_tokens:,} tokens")
if getattr(agent, "compression_enabled", True) is False:
lines.append("Compression is disabled for this agent.")
else:
lines.append("Tip: run /compact to compress manually before the threshold.")
return "\n".join(lines)
def _cmd_reset(self, args: str, state: SessionState) -> str:
@@ -1286,16 +804,10 @@ class HermesACPAgent(acp.Agent):
if not hasattr(agent, "_compress_context"):
return "Context compression not available for this agent."
from agent.model_metadata import estimate_request_tokens_rough
from agent.model_metadata import estimate_messages_tokens_rough
original_count = len(state.history)
# Include system prompt + tool schemas so the figure reflects real
# request pressure, not a transcript-only underestimate (#6217).
_sys_prompt = getattr(agent, "_cached_system_prompt", "") or ""
_tools = getattr(agent, "tools", None) or None
approx_tokens = estimate_request_tokens_rough(
state.history, system_prompt=_sys_prompt, tools=_tools
)
approx_tokens = estimate_messages_tokens_rough(state.history)
original_session_db = getattr(agent, "_session_db", None)
try:
@@ -1315,13 +827,7 @@ class HermesACPAgent(acp.Agent):
self.session_manager.save_session(state.session_id)
new_count = len(state.history)
_sys_prompt_after = getattr(agent, "_cached_system_prompt", "") or _sys_prompt
_tools_after = getattr(agent, "tools", None) or _tools
new_tokens = estimate_request_tokens_rough(
state.history,
system_prompt=_sys_prompt_after,
tools=_tools_after,
)
new_tokens = estimate_messages_tokens_rough(state.history)
return (
f"Context compressed: {original_count} -> {new_count} messages\n"
f"~{approx_tokens:,} -> ~{new_tokens:,} tokens"
@@ -1329,34 +835,6 @@ class HermesACPAgent(acp.Agent):
except Exception as e:
return f"Compression failed: {e}"
def _cmd_steer(self, args: str, state: SessionState) -> str:
steer_text = args.strip()
if not steer_text:
return "Usage: /steer <guidance>"
if state.is_running and hasattr(state.agent, "steer"):
try:
if state.agent.steer(steer_text):
preview = steer_text[:80] + ("..." if len(steer_text) > 80 else "")
return f"⏩ Steer queued for the active turn: {preview}"
except Exception as exc:
logger.warning("ACP steer failed for session %s: %s", state.session_id, exc)
return f"⚠️ Steer failed: {exc}"
with state.runtime_lock:
state.queued_prompts.append(steer_text)
depth = len(state.queued_prompts)
return f"No active turn — queued for the next turn. ({depth} queued)"
def _cmd_queue(self, args: str, state: SessionState) -> str:
queued_text = args.strip()
if not queued_text:
return "Usage: /queue <prompt>"
with state.runtime_lock:
state.queued_prompts.append(queued_text)
depth = len(state.queued_prompts)
return f"Queued for the next turn. ({depth} queued)"
def _cmd_version(self, args: str, state: SessionState) -> str:
return f"Hermes Agent v{HERMES_VERSION}"
+8 -74
View File
@@ -26,33 +26,6 @@ from typing import Any, Dict, List, Optional
logger = logging.getLogger(__name__)
def _win_path_to_wsl(path: str) -> str | None:
"""Convert a Windows drive path to its WSL /mnt/<drive>/... equivalent."""
match = re.match(r"^([A-Za-z]):[\\/](.*)$", path)
if not match:
return None
drive = match.group(1).lower()
tail = match.group(2).replace("\\", "/")
return f"/mnt/{drive}/{tail}"
def _translate_acp_cwd(cwd: str) -> str:
"""Translate Windows ACP cwd values when Hermes itself is running in WSL.
Windows ACP clients can launch ``hermes acp`` inside WSL while still sending
editor workspaces as Windows drive paths such as ``E:\\Projects``. Store
and execute against the WSL mount path so agents, tools, and persisted ACP
sessions all agree on the usable workspace. Native Linux/macOS keeps the
original cwd unchanged.
"""
from hermes_constants import is_wsl
if not is_wsl():
return cwd
translated = _win_path_to_wsl(str(cwd))
return translated if translated is not None else cwd
def _normalize_cwd_for_compare(cwd: str | None) -> str:
raw = str(cwd or ".").strip()
if not raw:
@@ -61,9 +34,11 @@ def _normalize_cwd_for_compare(cwd: str | None) -> str:
# Normalize Windows drive paths into the equivalent WSL mount form so
# ACP history filters match the same workspace across Windows and WSL.
translated = _win_path_to_wsl(expanded)
if translated is not None:
expanded = translated
match = re.match(r"^([A-Za-z]):[\\/](.*)$", expanded)
if match:
drive = match.group(1).lower()
tail = match.group(2).replace("\\", "/")
expanded = f"/mnt/{drive}/{tail}"
elif re.match(r"^/mnt/[A-Za-z]/", expanded):
expanded = f"/mnt/{expanded[5].lower()}/{expanded[7:]}"
@@ -121,40 +96,16 @@ def _acp_stderr_print(*args, **kwargs) -> None:
def _register_task_cwd(task_id: str, cwd: str) -> None:
"""Bind a task/session id to the editor's working directory for tools.
Zed can launch Hermes from a Windows workspace while the ACP process runs
inside WSL. In that case ACP sends cwd as e.g. ``E:\\Projects\\POTI``;
local tools need the WSL mount equivalent or subprocess creation fails
before the command can run.
"""
"""Bind a task/session id to the editor's working directory for tools."""
if not task_id:
return
try:
from tools.terminal_tool import register_task_env_overrides
register_task_env_overrides(task_id, {"cwd": _translate_acp_cwd(cwd)})
register_task_env_overrides(task_id, {"cwd": cwd})
except Exception:
logger.debug("Failed to register ACP task cwd override", exc_info=True)
def _expand_acp_enabled_toolsets(
toolsets: List[str] | None = None,
mcp_server_names: List[str] | None = None,
) -> List[str]:
"""Return ACP toolsets plus explicit MCP server toolsets for this session."""
expanded: List[str] = []
for name in list(toolsets or ["hermes-acp"]):
if name and name not in expanded:
expanded.append(name)
for server_name in list(mcp_server_names or []):
toolset_name = f"mcp-{server_name}"
if server_name and toolset_name not in expanded:
expanded.append(toolset_name)
return expanded
def _clear_task_cwd(task_id: str) -> None:
"""Remove task-specific cwd overrides for an ACP session."""
if not task_id:
@@ -176,11 +127,6 @@ class SessionState:
model: str = ""
history: List[Dict[str, Any]] = field(default_factory=list)
cancel_event: Any = None # threading.Event
is_running: bool = False
queued_prompts: List[str] = field(default_factory=list)
runtime_lock: Any = field(default_factory=Lock)
current_prompt_text: str = ""
interrupted_prompt_text: str = ""
class SessionManager:
@@ -211,7 +157,6 @@ class SessionManager:
"""Create a new session with a unique ID and a fresh AIAgent."""
import threading
cwd = _translate_acp_cwd(cwd)
session_id = str(uuid.uuid4())
agent = self._make_agent(session_id=session_id, cwd=cwd)
state = SessionState(
@@ -254,7 +199,6 @@ class SessionManager:
"""Deep-copy a session's history into a new session."""
import threading
cwd = _translate_acp_cwd(cwd)
original = self.get_session(session_id) # checks DB too
if original is None:
return None
@@ -356,7 +300,6 @@ class SessionManager:
def update_cwd(self, session_id: str, cwd: str) -> Optional[SessionState]:
"""Update the working directory for a session and its tool overrides."""
cwd = _translate_acp_cwd(cwd)
state = self.get_session(session_id) # checks DB too
if state is None:
return None
@@ -594,18 +537,9 @@ class SessionManager:
elif isinstance(model_cfg, str) and model_cfg.strip():
default_model = model_cfg.strip()
configured_mcp_servers = [
name
for name, cfg in (config.get("mcp_servers") or {}).items()
if not isinstance(cfg, dict) or cfg.get("enabled", True) is not False
]
kwargs = {
"platform": "acp",
"enabled_toolsets": _expand_acp_enabled_toolsets(
["hermes-acp"],
mcp_server_names=configured_mcp_servers,
),
"enabled_toolsets": ["hermes-acp"],
"quiet_mode": True,
"session_id": session_id,
"model": model or default_model,
+21 -822
View File
@@ -28,11 +28,6 @@ TOOL_KIND_MAP: Dict[str, ToolKind] = {
"terminal": "execute",
"process": "execute",
"execute_code": "execute",
# Session/meta tools
"todo": "other",
"skill_view": "read",
"skills_list": "read",
"skill_manage": "edit",
# Web / fetch
"web_search": "fetch",
"web_extract": "fetch",
@@ -56,28 +51,6 @@ TOOL_KIND_MAP: Dict[str, ToolKind] = {
}
_POLISHED_TOOLS = {
# Core operator loop
"todo", "memory", "session_search", "delegate_task",
# Files / execution
"read_file", "write_file", "patch", "search_files", "terminal", "process", "execute_code",
# Skills / web / browser / media
"skill_view", "skills_list", "skill_manage", "web_search", "web_extract",
"browser_navigate", "browser_click", "browser_type", "browser_press", "browser_scroll",
"browser_back", "browser_snapshot", "browser_console", "browser_get_images", "browser_vision",
"vision_analyze", "image_generate", "text_to_speech",
# Schedulers / platform integrations
"cronjob", "send_message", "clarify", "discord", "discord_admin",
"ha_list_entities", "ha_get_state", "ha_list_services", "ha_call_service",
"feishu_doc_read", "feishu_drive_list_comments", "feishu_drive_list_comment_replies",
"feishu_drive_reply_comment", "feishu_drive_add_comment",
"kanban_create", "kanban_show", "kanban_comment", "kanban_complete",
"kanban_block", "kanban_link", "kanban_heartbeat",
"yb_query_group_info", "yb_query_group_members", "yb_search_sticker",
"yb_send_dm", "yb_send_sticker", "mixture_of_agents",
}
def get_tool_kind(tool_name: str) -> ToolKind:
"""Return the ACP ToolKind for a hermes tool, defaulting to 'other'."""
return TOOL_KIND_MAP.get(tool_name, "other")
@@ -112,645 +85,18 @@ def build_tool_title(tool_name: str, args: Dict[str, Any]) -> str:
if urls:
return f"extract: {urls[0]}" + (f" (+{len(urls)-1})" if len(urls) > 1 else "")
return "web extract"
if tool_name == "process":
action = str(args.get("action") or "").strip() or "manage"
sid = str(args.get("session_id") or "").strip()
return f"process {action}: {sid}" if sid else f"process {action}"
if tool_name == "delegate_task":
tasks = args.get("tasks")
if isinstance(tasks, list) and tasks:
return f"delegate batch ({len(tasks)} tasks)"
goal = args.get("goal", "")
if goal and len(goal) > 60:
goal = goal[:57] + "..."
return f"delegate: {goal}" if goal else "delegate task"
if tool_name == "session_search":
query = str(args.get("query") or "").strip()
return f"session search: {query}" if query else "recent sessions"
if tool_name == "memory":
action = str(args.get("action") or "manage").strip() or "manage"
target = str(args.get("target") or "memory").strip() or "memory"
return f"memory {action}: {target}"
if tool_name == "execute_code":
code = str(args.get("code") or "").strip()
first_line = next((line.strip() for line in code.splitlines() if line.strip()), "")
if first_line:
if len(first_line) > 70:
first_line = first_line[:67] + "..."
return f"python: {first_line}"
return "python code"
if tool_name == "todo":
items = args.get("todos")
if isinstance(items, list):
return f"todo ({len(items)} item{'s' if len(items) != 1 else ''})"
return "todo"
if tool_name == "skill_view":
name = str(args.get("name") or "?").strip() or "?"
file_path = str(args.get("file_path") or "").strip()
suffix = f"/{file_path}" if file_path else ""
return f"skill view ({name}{suffix})"
if tool_name == "skills_list":
category = str(args.get("category") or "").strip()
return f"skills list ({category})" if category else "skills list"
if tool_name == "skill_manage":
action = str(args.get("action") or "manage").strip() or "manage"
name = str(args.get("name") or "?").strip() or "?"
file_path = str(args.get("file_path") or "").strip()
target = f"{name}/{file_path}" if file_path else name
if len(target) > 64:
target = target[:61] + "..."
return f"skill {action}: {target}"
if tool_name == "browser_navigate":
return f"navigate: {args.get('url', '?')}"
if tool_name == "browser_snapshot":
return "browser snapshot"
if tool_name == "browser_vision":
return f"browser vision: {str(args.get('question', '?'))[:50]}"
if tool_name == "browser_get_images":
return "browser images"
return "execute code"
if tool_name == "vision_analyze":
return f"analyze image: {str(args.get('question', '?'))[:50]}"
if tool_name == "image_generate":
prompt = str(args.get("prompt") or args.get("description") or "").strip()
return f"generate image: {prompt[:50]}" if prompt else "generate image"
if tool_name == "cronjob":
action = str(args.get("action") or "manage").strip() or "manage"
job_id = str(args.get("job_id") or args.get("id") or "").strip()
return f"cron {action}: {job_id}" if job_id else f"cron {action}"
return f"analyze image: {args.get('question', '?')[:50]}"
return tool_name
def _text(content: str) -> Any:
return acp.tool_content(acp.text_block(content))
def _json_loads_maybe(value: Optional[str]) -> Any:
if not isinstance(value, str):
return value
try:
return json.loads(value)
except Exception:
pass
# Some Hermes tools append a human hint after a JSON payload, e.g.
# ``{...}\n\n[Hint: Results truncated...]``. Keep the structured rendering path
# by decoding the first JSON value instead of falling back to raw text.
try:
decoded, _ = json.JSONDecoder().raw_decode(value.lstrip())
return decoded
except Exception:
return None
def _truncate_text(text: str, limit: int = 5000) -> str:
if len(text) <= limit:
return text
return text[: max(0, limit - 100)] + f"\n... ({len(text)} chars total, truncated)"
def _fenced_text(text: str, language: str = "") -> str:
"""Return a Markdown fence that cannot be broken by backticks in text."""
longest = max((len(run) for run in text.split("`")[1::2]), default=0)
fence = "`" * max(3, longest + 1)
return f"{fence}{language}\n{text}\n{fence}"
def _format_todo_result(result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict) or not isinstance(data.get("todos"), list):
return None
summary = data.get("summary") if isinstance(data.get("summary"), dict) else {}
icon = {
"completed": "",
"in_progress": "🔄",
"pending": "",
"cancelled": "",
}
lines = ["**Todo list**", ""]
for item in data["todos"]:
if not isinstance(item, dict):
continue
status = str(item.get("status") or "pending")
content = str(item.get("content") or item.get("id") or "").strip()
if content:
lines.append(f"- {icon.get(status, '')} {content}")
if summary:
cancelled = summary.get("cancelled", 0)
lines.extend([
"",
"**Progress:** "
f"{summary.get('completed', 0)} completed, "
f"{summary.get('in_progress', 0)} in progress, "
f"{summary.get('pending', 0)} pending"
+ (f", {cancelled} cancelled" if cancelled else ""),
])
return "\n".join(lines)
def _format_read_file_result(result: Optional[str], args: Optional[Dict[str, Any]]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
if data.get("error") and not data.get("content"):
return f"Read failed: {data.get('error')}"
content = data.get("content")
if not isinstance(content, str):
return None
path = str((args or {}).get("path") or data.get("path") or "file").strip()
offset = (args or {}).get("offset")
limit = (args or {}).get("limit")
range_bits = []
if offset:
range_bits.append(f"from line {offset}")
if limit:
range_bits.append(f"limit {limit}")
suffix = f" ({', '.join(range_bits)})" if range_bits else ""
header = f"Read {path}{suffix}"
if data.get("total_lines") is not None:
header += f"{data.get('total_lines')} total lines"
# Hermes read_file output is line-numbered with `|`. If we send it as raw
# Markdown, Zed can interpret pipes as tables and collapse the layout.
# Fence the payload so file lines stay readable and literal.
return _truncate_text(f"{header}\n\n{_fenced_text(content)}")
def _format_search_files_result(result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
matches = data.get("matches")
if not isinstance(matches, list):
return None
total = data.get("total_count", len(matches))
shown = min(len(matches), 12)
truncated = bool(data.get("truncated")) or len(matches) > shown
lines = [
"Search results",
f"Found {total} match{'es' if total != 1 else ''}; showing {shown}.",
"",
]
for match in matches[:shown]:
if not isinstance(match, dict):
lines.append(f"- {match}")
continue
path = str(match.get("path") or match.get("file") or match.get("filename") or "?")
line = match.get("line") or match.get("line_number")
content = str(match.get("content") or match.get("text") or "").strip()
loc = f"{path}:{line}" if line else path
lines.append(f"- {loc}")
if content:
snippet = _truncate_text(" ".join(content.split()), 300)
lines.append(f" {snippet}")
if truncated:
lines.extend([
"",
"Results truncated. Narrow the search, add file_glob, or use offset to page.",
])
return _truncate_text("\n".join(lines), limit=7000)
def _format_execute_code_result(result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return result if isinstance(result, str) and result.strip() else None
output = str(data.get("output") or "")
error = str(data.get("error") or "")
exit_code = data.get("exit_code")
parts = [f"Exit code: {exit_code}" if exit_code is not None else "Execution complete"]
if output:
parts.extend(["", "Output:", output])
if error:
parts.extend(["", "Error:", error])
return _truncate_text("\n".join(parts))
def _extract_markdown_headings(content: str, limit: int = 8) -> list[str]:
headings: list[str] = []
for line in content.splitlines():
stripped = line.strip()
if stripped.startswith("#"):
heading = stripped.lstrip("#").strip()
if heading:
headings.append(heading)
if len(headings) >= limit:
break
return headings
def _format_skill_view_result(result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
if data.get("success") is False:
return f"Skill view failed: {data.get('error', 'unknown error')}"
name = str(data.get("name") or "skill")
file_path = str(data.get("file") or data.get("path") or "SKILL.md")
description = str(data.get("description") or "").strip()
content = str(data.get("content") or "")
linked = data.get("linked_files") if isinstance(data.get("linked_files"), dict) else None
lines = ["**Skill loaded**", "", f"- **Name:** `{name}`", f"- **File:** `{file_path}`"]
if description:
lines.append(f"- **Description:** {description}")
if content:
lines.append(f"- **Content:** {len(content):,} chars loaded into agent context")
if linked:
linked_count = sum(len(v) for v in linked.values() if isinstance(v, list))
lines.append(f"- **Linked files:** {linked_count}")
headings = _extract_markdown_headings(content)
if headings:
lines.extend(["", "**Sections**"])
lines.extend(f"- {heading}" for heading in headings)
lines.extend([
"",
"_Full skill content is available to the agent but hidden here to keep ACP readable._",
])
return "\n".join(lines)
def _format_skill_manage_result(result: Optional[str], args: Optional[Dict[str, Any]]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
action = str((args or {}).get("action") or "manage").strip() or "manage"
name = str((args or {}).get("name") or data.get("name") or "skill").strip() or "skill"
file_path = str((args or {}).get("file_path") or data.get("file_path") or "SKILL.md").strip() or "SKILL.md"
success = data.get("success")
status = "✅ Skill updated" if success is not False else "✗ Skill update failed"
lines = [f"**{status}**", "", f"- **Action:** `{action}`", f"- **Skill:** `{name}`"]
if action not in {"delete"}:
lines.append(f"- **File:** `{file_path}`")
message = str(data.get("message") or data.get("error") or "").strip()
if message:
lines.append(f"- **Result:** {message}")
replacements = data.get("replacements") or data.get("replacement_count")
if replacements is not None:
lines.append(f"- **Replacements:** {replacements}")
path = str(data.get("path") or "").strip()
if path:
lines.append(f"- **Path:** `{path}`")
return "\n".join(lines)
def _format_web_search_result(result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
web = data.get("data", {}).get("web") if isinstance(data.get("data"), dict) else data.get("web")
if not isinstance(web, list):
return None
lines = [f"Web results: {len(web)}"]
for item in web[:10]:
if not isinstance(item, dict):
continue
title = str(item.get("title") or item.get("url") or "result").strip()
url = str(item.get("url") or "").strip()
desc = str(item.get("description") or "").strip()
lines.append(f"{title}" + (f"{url}" if url else ""))
if desc:
lines.append(f" {desc}")
return _truncate_text("\n".join(lines))
def _format_web_extract_result(result: Optional[str]) -> Optional[str]:
"""Return only web_extract errors for ACP; success stays compact via title."""
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
if data.get("success") is False and data.get("error"):
return f"Web extract failed: {data.get('error')}"
results = data.get("results")
if not isinstance(results, list):
return None
failures: list[str] = []
for item in results[:10]:
if not isinstance(item, dict):
continue
error = str(item.get("error") or "").strip()
if not error or error in {"None", "null"}:
continue
url = str(item.get("url") or "").strip()
title = str(item.get("title") or url or "Untitled").strip()
failures.append(
f"- {title}" + (f"{url}" if url and url != title else "") + f"\n Error: {_truncate_text(error, limit=500)}"
)
if not failures:
return None
lines = [f"Web extract failed for {len(failures)} URL{'s' if len(failures) != 1 else ''}"]
lines.extend(failures)
return "\n".join(lines)
def _format_process_result(result: Optional[str], args: Optional[Dict[str, Any]]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return result if isinstance(result, str) and result.strip() else None
if data.get("success") is False and data.get("error"):
return f"Process error: {data.get('error')}"
action = str((args or {}).get("action") or "process").strip() or "process"
if isinstance(data.get("processes"), list):
processes = data["processes"]
lines = [f"Processes: {len(processes)}"]
for proc in processes[:20]:
if not isinstance(proc, dict):
lines.append(f"- {proc}")
continue
sid = str(proc.get("session_id") or proc.get("id") or "?")
status = str(proc.get("status") or ("exited" if proc.get("exited") else "running"))
cmd = str(proc.get("command") or "").strip()
pid = proc.get("pid")
code = proc.get("exit_code")
bits = [status]
if pid is not None:
bits.append(f"pid {pid}")
if code is not None:
bits.append(f"exit {code}")
lines.append(f"- `{sid}` — {', '.join(bits)}" + (f"{cmd[:120]}" if cmd else ""))
if len(processes) > 20:
lines.append(f"... {len(processes) - 20} more process(es)")
return "\n".join(lines)
status = str(data.get("status") or data.get("state") or action).strip()
sid = str(data.get("session_id") or (args or {}).get("session_id") or "").strip()
lines = [f"Process {action}: {status}" + (f" (`{sid}`)" if sid else "")]
for key, label in (("command", "Command"), ("pid", "PID"), ("exit_code", "Exit code"), ("returncode", "Exit code"), ("lines", "Lines")):
if data.get(key) is not None:
lines.append(f"- **{label}:** {data.get(key)}")
output = data.get("output") or data.get("new_output") or data.get("log") or data.get("stdout")
error = data.get("error") or data.get("stderr")
if output:
lines.extend(["", "Output:", _truncate_text(str(output), limit=5000)])
if error:
lines.extend(["", "Error:", _truncate_text(str(error), limit=2000)])
msg = data.get("message")
if msg and not output and not error:
lines.append(str(msg))
return _truncate_text("\n".join(lines), limit=7000)
def _format_delegate_result(result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
if data.get("error") and not isinstance(data.get("results"), list):
return f"Delegation failed: {data.get('error')}"
results = data.get("results")
if not isinstance(results, list):
return None
total = data.get("total_duration_seconds")
lines = [f"Delegation results: {len(results)} task{'s' if len(results) != 1 else ''}" + (f" in {total}s" if total is not None else "")]
icon = {"completed": "", "failed": "", "error": "", "timeout": "", "interrupted": ""}
for item in results:
if not isinstance(item, dict):
lines.append(f"- {item}")
continue
idx = item.get("task_index")
status = str(item.get("status") or "unknown")
model = item.get("model")
dur = item.get("duration_seconds")
role = item.get("_child_role")
header = f"{icon.get(status, '')} Task {idx + 1 if isinstance(idx, int) else '?'}: {status}"
bits = []
if model:
bits.append(str(model))
if role:
bits.append(f"role={role}")
if dur is not None:
bits.append(f"{dur}s")
if bits:
header += " (" + ", ".join(bits) + ")"
lines.extend(["", header])
summary = str(item.get("summary") or "").strip()
error = str(item.get("error") or "").strip()
if summary:
lines.append(_truncate_text(summary, limit=1200))
if error:
lines.append("Error: " + _truncate_text(error, limit=800))
trace = item.get("tool_trace")
if isinstance(trace, list) and trace:
names = [str(t.get("tool") or "?") for t in trace if isinstance(t, dict)]
if names:
lines.append("Tools: " + ", ".join(names[:12]) + (f" (+{len(names)-12})" if len(names) > 12 else ""))
return _truncate_text("\n".join(lines), limit=8000)
def _format_session_search_result(result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
if data.get("success") is False:
return f"Session search failed: {data.get('error', 'unknown error')}"
results = data.get("results")
if not isinstance(results, list):
return None
mode = data.get("mode") or "search"
query = data.get("query")
lines = ["Recent sessions" if mode == "recent" else f"Session search results" + (f" for `{query}`" if query else "")]
if not results:
lines.append(str(data.get("message") or "No matching sessions found."))
return "\n".join(lines)
for item in results:
if not isinstance(item, dict):
continue
sid = str(item.get("session_id") or "?")
title = str(item.get("title") or item.get("when") or "Untitled session").strip()
when = str(item.get("last_active") or item.get("started_at") or item.get("when") or "").strip()
count = item.get("message_count")
source = str(item.get("source") or "").strip()
meta = ", ".join(str(x) for x in [when, source, f"{count} msgs" if count is not None else ""] if x)
lines.append(f"- **{title}** (`{sid}`)" + (f"{meta}" if meta else ""))
summary = str(item.get("summary") or item.get("preview") or "").strip()
if summary:
lines.append(" " + _truncate_text(" ".join(summary.split()), limit=500))
return _truncate_text("\n".join(lines), limit=7000)
def _format_memory_result(result: Optional[str], args: Optional[Dict[str, Any]]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return None
action = str((args or {}).get("action") or "memory").strip() or "memory"
target = str(data.get("target") or (args or {}).get("target") or "memory")
if data.get("success") is False:
lines = [f"✗ Memory {action} failed ({target})", str(data.get("error") or "unknown error")]
matches = data.get("matches")
if isinstance(matches, list) and matches:
lines.append("Matches:")
lines.extend(f"- {_truncate_text(str(m), 160)}" for m in matches[:5])
return "\n".join(lines)
lines = [f"✅ Memory {action} saved ({target})"]
if data.get("message"):
lines.append(str(data.get("message")))
if data.get("entry_count") is not None:
lines.append(f"Entries: {data.get('entry_count')}")
if data.get("usage"):
lines.append(f"Usage: {data.get('usage')}")
# Avoid dumping all memory entries into ACP UI; show only the explicit new value preview.
preview = str((args or {}).get("content") or (args or {}).get("old_text") or "").strip()
if preview:
lines.append("Preview: " + _truncate_text(preview, limit=300))
return "\n".join(lines)
def _format_edit_result(tool_name: str, result: Optional[str], args: Optional[Dict[str, Any]]) -> Optional[str]:
data = _json_loads_maybe(result)
path = str((args or {}).get("path") or "file").strip()
if isinstance(data, dict):
if data.get("success") is False or data.get("error"):
return f"{tool_name} failed for {path}: {data.get('error', 'unknown error')}"
message = str(data.get("message") or "").strip()
replacements = data.get("replacements") or data.get("replacement_count")
lines = [f"{tool_name} completed" + (f" for `{path}`" if path else "")]
if message:
lines.append(message)
if replacements is not None:
lines.append(f"Replacements: {replacements}")
if data.get("files_modified"):
files = data.get("files_modified")
if isinstance(files, list):
lines.append("Files: " + ", ".join(f"`{f}`" for f in files[:8]))
return "\n".join(lines)
if isinstance(result, str) and result.strip():
return _truncate_text(result, limit=3000)
return f"{tool_name} completed" + (f" for `{path}`" if path else "")
def _format_browser_result(tool_name: str, result: Optional[str], args: Optional[Dict[str, Any]]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return result if isinstance(result, str) and result.strip() else None
if data.get("success") is False or data.get("error"):
return f"{tool_name} failed: {data.get('error', 'unknown error')}"
if tool_name == "browser_get_images":
images = data.get("images") or data.get("data")
if isinstance(images, list):
lines = [f"Images found: {len(images)}"]
for img in images[:12]:
if isinstance(img, dict):
alt = str(img.get("alt") or "").strip()
url = str(img.get("url") or img.get("src") or "").strip()
lines.append(f"- {alt or 'image'}" + (f"{url}" if url else ""))
return _truncate_text("\n".join(lines), limit=5000)
title = str(data.get("title") or data.get("url") or data.get("status") or tool_name)
text = str(data.get("text") or data.get("content") or data.get("snapshot") or data.get("analysis") or data.get("message") or "").strip()
lines = [title]
if data.get("url") and data.get("url") != title:
lines.append(str(data.get("url")))
if text:
lines.extend(["", _truncate_text(text, limit=5000)])
return _truncate_text("\n".join(lines), limit=7000)
def _format_media_or_cron_result(tool_name: str, result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, dict):
return result if isinstance(result, str) and result.strip() else None
if data.get("success") is False or data.get("error"):
return f"{tool_name} failed: {data.get('error', 'unknown error')}"
lines = [f"{tool_name} completed"]
for key in ("file_path", "path", "url", "image_url", "job_id", "id", "status", "message", "next_run"):
if data.get(key):
lines.append(f"- **{key}:** {data.get(key)}")
return "\n".join(lines)
def _format_generic_structured_result(tool_name: str, result: Optional[str]) -> Optional[str]:
data = _json_loads_maybe(result)
if not isinstance(data, (dict, list)):
return result if isinstance(result, str) and result.strip() else None
if isinstance(data, list):
lines = [f"{tool_name}: {len(data)} item{'s' if len(data) != 1 else ''}"]
for item in data[:12]:
lines.append(f"- {_truncate_text(str(item), limit=240)}")
return _truncate_text("\n".join(lines), limit=5000)
if data.get("success") is False or data.get("error"):
return f"{tool_name} failed: {data.get('error', 'unknown error')}"
lines = [f"{tool_name} completed" if data.get("success") is True else f"{tool_name} result"]
priority_keys = (
"message", "status", "id", "task_id", "issue_id", "title", "name", "entity_id",
"state", "service", "url", "path", "file_path", "count", "total", "next_run",
)
seen = set()
for key in priority_keys:
value = data.get(key)
if value in (None, "", [], {}):
continue
seen.add(key)
lines.append(f"- **{key}:** {_truncate_text(str(value), limit=500)}")
for key, value in data.items():
if key in seen or key in {"success", "raw", "content", "entries"}:
continue
if value in (None, "", [], {}):
continue
if isinstance(value, (dict, list)):
preview = json.dumps(value, ensure_ascii=False, default=str)
else:
preview = str(value)
lines.append(f"- **{key}:** {_truncate_text(preview, limit=500)}")
if len(lines) >= 14:
break
content = data.get("content")
if isinstance(content, str) and content.strip():
lines.extend(["", _truncate_text(content.strip(), limit=1500)])
return _truncate_text("\n".join(lines), limit=7000)
def _build_polished_completion_content(
tool_name: str,
result: Optional[str],
function_args: Optional[Dict[str, Any]],
) -> Optional[List[Any]]:
formatter = {
"todo": lambda: _format_todo_result(result),
"read_file": lambda: _format_read_file_result(result, function_args),
"write_file": lambda: _format_edit_result(tool_name, result, function_args),
"patch": lambda: _format_edit_result(tool_name, result, function_args),
"search_files": lambda: _format_search_files_result(result),
"execute_code": lambda: _format_execute_code_result(result),
"process": lambda: _format_process_result(result, function_args),
"delegate_task": lambda: _format_delegate_result(result),
"session_search": lambda: _format_session_search_result(result),
"memory": lambda: _format_memory_result(result, function_args),
"skill_view": lambda: _format_skill_view_result(result),
"skill_manage": lambda: _format_skill_manage_result(result, function_args),
"web_search": lambda: _format_web_search_result(result),
"web_extract": lambda: _format_web_extract_result(result),
"browser_navigate": lambda: _format_browser_result(tool_name, result, function_args),
"browser_snapshot": lambda: _format_browser_result(tool_name, result, function_args),
"browser_vision": lambda: _format_browser_result(tool_name, result, function_args),
"browser_get_images": lambda: _format_browser_result(tool_name, result, function_args),
"vision_analyze": lambda: _format_media_or_cron_result(tool_name, result),
"image_generate": lambda: _format_media_or_cron_result(tool_name, result),
"cronjob": lambda: _format_media_or_cron_result(tool_name, result),
}.get(tool_name)
if formatter is None and tool_name in _POLISHED_TOOLS:
formatter = lambda: _format_generic_structured_result(tool_name, result)
if formatter is None:
return None
text = formatter()
if not text:
return None
return [_text(text)]
def _build_patch_mode_content(patch_text: str) -> List[Any]:
"""Parse V4A patch mode input into ACP diff blocks when possible."""
if not patch_text:
@@ -912,11 +258,7 @@ def _build_tool_complete_content(
except Exception:
pass
polished_content = _build_polished_completion_content(tool_name, result, function_args)
if polished_content:
return polished_content
return [_text(display_result)]
return [acp.tool_content(acp.text_block(display_result))]
# ---------------------------------------------------------------------------
@@ -946,6 +288,7 @@ def build_tool_start(
content = _build_patch_mode_content(patch_text)
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
raw_input=arguments,
)
if tool_name == "write_file":
@@ -954,172 +297,32 @@ def build_tool_start(
content = [acp.tool_diff_content(path=path, new_text=file_content)]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
raw_input=arguments,
)
if tool_name == "terminal":
command = arguments.get("command", "")
content = [_text(f"$ {command}")]
content = [acp.tool_content(acp.text_block(f"$ {command}"))]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
raw_input=arguments,
)
if tool_name == "read_file":
# The title and location already identify the file. Sending a synthetic
# "Reading ..." content block makes Zed render an unhelpful Output
# section before the real file contents arrive on completion.
path = arguments.get("path", "")
content = [acp.tool_content(acp.text_block(f"Reading {path}"))]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=None, locations=locations,
tool_call_id, title, kind=kind, content=content, locations=locations,
raw_input=arguments,
)
if tool_name == "search_files":
pattern = arguments.get("pattern", "")
target = arguments.get("target", "content")
search_path = arguments.get("path")
where = f" in {search_path}" if search_path else ""
content = [_text(f"Searching for '{pattern}' ({target}){where}")]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "todo":
items = arguments.get("todos")
if isinstance(items, list):
preview_lines = ["Updating todo list", ""]
for item in items[:8]:
if isinstance(item, dict):
preview_lines.append(f"- {item.get('status', 'pending')}: {item.get('content', item.get('id', ''))}")
if len(items) > 8:
preview_lines.append(f"... {len(items) - 8} more")
content = [_text("\n".join(preview_lines))]
else:
content = [_text("Reading todo list")]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "skill_view":
name = str(arguments.get("name") or "?").strip() or "?"
file_path = str(arguments.get("file_path") or "SKILL.md").strip() or "SKILL.md"
content = [_text(f"Loading skill '{name}' ({file_path})")]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "skill_manage":
action = str(arguments.get("action") or "manage").strip() or "manage"
name = str(arguments.get("name") or "?").strip() or "?"
file_path = str(arguments.get("file_path") or "SKILL.md").strip() or "SKILL.md"
path = f"skills/{name}/{file_path}" if file_path else f"skills/{name}"
if action == "patch":
old = str(arguments.get("old_string") or "")
new = str(arguments.get("new_string") or "")
content = [acp.tool_diff_content(path=path, old_text=old or None, new_text=new)]
elif action in {"edit", "create"}:
content = [
acp.tool_diff_content(
path=path,
new_text=str(arguments.get("content") or ""),
)
]
elif action == "write_file":
target = str(arguments.get("file_path") or "file")
content = [
acp.tool_diff_content(
path=f"skills/{name}/{target}",
new_text=str(arguments.get("file_content") or ""),
)
]
elif action in {"delete", "remove_file"}:
target = str(arguments.get("file_path") or file_path or name)
content = [_text(f"Removing {target} from skill '{name}'")]
else:
content = [_text(f"Running skill_manage action '{action}' on skill '{name}' ({file_path})")]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "execute_code":
code = str(arguments.get("code") or "").strip()
preview = code[:1200] + (f"\n... ({len(code)} chars total, truncated)" if len(code) > 1200 else "")
content = [_text(f"Running Python helper script:\n\n```python\n{preview}\n```" if preview else "Running Python helper script")]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "web_search":
query = str(arguments.get("query") or "").strip()
content = [_text(f"Searching the web for: {query}" if query else "Searching the web")]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "web_extract":
# The title identifies the URL(s). Avoid a duplicate content block so
# Zed renders this like read_file: compact start, concise completion.
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=None, locations=locations,
)
if tool_name == "process":
action = str(arguments.get("action") or "").strip() or "manage"
sid = str(arguments.get("session_id") or "").strip()
data_preview = str(arguments.get("data") or "").strip()
text = f"Process action: {action}" + (f"\nSession: {sid}" if sid else "")
if data_preview:
text += "\nInput: " + _truncate_text(data_preview, limit=500)
content = [_text(text)]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "delegate_task":
tasks = arguments.get("tasks")
if isinstance(tasks, list) and tasks:
lines = [f"Delegating {len(tasks)} tasks", ""]
for i, task in enumerate(tasks[:8], 1):
if isinstance(task, dict):
goal = str(task.get("goal") or "").strip()
role = str(task.get("role") or "").strip()
lines.append(f"{i}. " + _truncate_text(goal, limit=160) + (f" ({role})" if role else ""))
if len(tasks) > 8:
lines.append(f"... {len(tasks) - 8} more")
content = [_text("\n".join(lines))]
else:
goal = str(arguments.get("goal") or "").strip()
content = [_text("Delegating task" + (f":\n{_truncate_text(goal, limit=800)}" if goal else ""))]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "session_search":
query = str(arguments.get("query") or "").strip()
content = [_text(f"Searching past sessions for: {query}" if query else "Loading recent sessions")]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name == "memory":
action = str(arguments.get("action") or "manage").strip() or "manage"
target = str(arguments.get("target") or "memory").strip() or "memory"
preview = str(arguments.get("content") or arguments.get("old_text") or "").strip()
text = f"Memory {action} ({target})"
if preview:
text += "\nPreview: " + _truncate_text(preview, limit=500)
content = [_text(text)]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
)
if tool_name in _POLISHED_TOOLS:
try:
args_text = json.dumps(arguments, indent=2, default=str)
except (TypeError, ValueError):
args_text = str(arguments)
content = [_text(_truncate_text(args_text, limit=1200))]
content = [acp.tool_content(acp.text_block(f"Searching for '{pattern}' ({target})"))]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
raw_input=arguments,
)
# Generic fallback
@@ -1131,7 +334,7 @@ def build_tool_start(
content = [acp.tool_content(acp.text_block(args_text))]
return acp.start_tool_call(
tool_call_id, title, kind=kind, content=content, locations=locations,
raw_input=None if tool_name in _POLISHED_TOOLS else arguments,
raw_input=arguments,
)
@@ -1144,22 +347,18 @@ def build_tool_complete(
) -> ToolCallProgress:
"""Create a ToolCallUpdate (progress) event for a completed tool call."""
kind = get_tool_kind(tool_name)
if tool_name == "web_extract":
error_text = _format_web_extract_result(result)
content = [_text(error_text)] if error_text else None
else:
content = _build_tool_complete_content(
tool_name,
result,
function_args=function_args,
snapshot=snapshot,
)
content = _build_tool_complete_content(
tool_name,
result,
function_args=function_args,
snapshot=snapshot,
)
return acp.update_tool_call(
tool_call_id,
kind=kind,
status="completed",
content=content,
raw_output=None if tool_name in _POLISHED_TOOLS else result,
raw_output=result,
)
+137 -502
View File
@@ -14,33 +14,17 @@ import copy
import json
import logging
import os
import platform
import subprocess
from pathlib import Path
from hermes_constants import get_hermes_home
from types import SimpleNamespace
from typing import Any, Dict, List, Optional, Tuple
from utils import base_url_host_matches, normalize_proxy_env_vars
from utils import normalize_proxy_env_vars
# NOTE: `import anthropic` is deliberately NOT at module top — the SDK pulls
# ~220 ms of imports (anthropic.types, anthropic.lib.tools._beta_runner, etc.)
# and the 3 usage sites (build_anthropic_client, build_anthropic_bedrock_client,
# read_claude_code_credentials_from_keychain) are all on cold user-triggered
# paths. Access via the `_get_anthropic_sdk()` accessor below, which caches
# the module after the first call and returns None on ImportError.
_anthropic_sdk: Any = ... # sentinel — None means "tried and missing"
def _get_anthropic_sdk():
"""Return the ``anthropic`` SDK module, importing lazily. None if not installed."""
global _anthropic_sdk
if _anthropic_sdk is ...:
try:
import anthropic as _sdk
_anthropic_sdk = _sdk
except ImportError:
_anthropic_sdk = None
return _anthropic_sdk
try:
import anthropic as _anthropic_sdk
except ImportError:
_anthropic_sdk = None # type: ignore[assignment]
logger = logging.getLogger(__name__)
@@ -133,63 +117,6 @@ def _get_anthropic_max_output(model: str) -> int:
return best_val
def _resolve_positive_anthropic_max_tokens(value) -> Optional[int]:
"""Return ``value`` floored to a positive int, or ``None`` if it is not a
finite positive number. Ported from openclaw/openclaw#66664.
Anthropic's Messages API rejects ``max_tokens`` values that are 0,
negative, non-integer, or non-finite with HTTP 400. Python's ``or``
idiom (``max_tokens or fallback``) correctly catches ``0`` but lets
negative ints and fractional floats (``-1``, ``0.5``) through to the
API, producing a user-visible failure instead of a local error.
"""
# Booleans are a subclass of int — exclude explicitly so ``True`` doesn't
# silently become 1 and ``False`` doesn't become 0.
if isinstance(value, bool):
return None
if not isinstance(value, (int, float)):
return None
try:
import math
if not math.isfinite(value):
return None
except Exception:
return None
floored = int(value) # truncates toward zero for floats
return floored if floored > 0 else None
def _resolve_anthropic_messages_max_tokens(
requested,
model: str,
context_length: Optional[int] = None,
) -> int:
"""Resolve the ``max_tokens`` budget for an Anthropic Messages call.
Prefers ``requested`` when it is a positive finite number; otherwise
falls back to the model's output ceiling. Raises ``ValueError`` if no
positive budget can be resolved (should not happen with current model
table defaults, but guards against a future regression where
``_get_anthropic_max_output`` could return ``0``).
Separately, callers apply a context-window clamp — this resolver does
not, to keep the positive-value contract independent of endpoint
specifics.
Ported from openclaw/openclaw#66664 (resolveAnthropicMessagesMaxTokens).
"""
resolved = _resolve_positive_anthropic_max_tokens(requested)
if resolved is not None:
return resolved
fallback = _get_anthropic_max_output(model)
if fallback > 0:
return fallback
raise ValueError(
f"Anthropic Messages adapter requires a positive max_tokens value for "
f"model {model!r}; got {requested!r} and no model default resolved."
)
def _supports_adaptive_thinking(model: str) -> bool:
"""Return True for Claude 4.6+ models that support adaptive thinking."""
return any(v in model for v in _ADAPTIVE_THINKING_SUBSTRINGS)
@@ -217,33 +144,19 @@ def _forbids_sampling_params(model: str) -> bool:
# Beta headers for enhanced features (sent with ALL auth types).
# As of Opus 4.7 (2026-04-16), the first two are GA on Claude 4.6+ — the
# As of Opus 4.7 (2026-04-16), both of these are GA on Claude 4.6+ — the
# beta headers are still accepted (harmless no-op) but not required. Kept
# here so older Claude (4.5, 4.1) + third-party Anthropic-compat endpoints
# that still gate on the headers continue to get the enhanced features.
#
# ``context-1m-2025-08-07`` unlocks the 1M context window on Claude Opus 4.6/4.7
# and Sonnet 4.6 when served via AWS Bedrock or Azure AI Foundry. 1M is GA on
# native Anthropic (api.anthropic.com) for Opus 4.6+, but Bedrock/Azure still
# gate it behind this beta header as of 2026-04 — without it Bedrock caps Opus
# at 200K even though model_metadata.py advertises 1M. The header is a harmless
# no-op on endpoints where 1M is GA.
#
# Migration guide: remove these if you no longer support ≤4.5 models or once
# Bedrock/Azure promote 1M to GA.
# Migration guide: remove these if you no longer support ≤4.5 models.
_COMMON_BETAS = [
"interleaved-thinking-2025-05-14",
"fine-grained-tool-streaming-2025-05-14",
"context-1m-2025-08-07",
]
# MiniMax's Anthropic-compatible endpoints fail tool-use requests when
# the fine-grained tool streaming beta is present. Omit it so tool calls
# fall back to the provider's default response path.
_TOOL_STREAMING_BETA = "fine-grained-tool-streaming-2025-05-14"
# 1M context beta — see comment on _COMMON_BETAS above. Stripped for
# Bearer-auth (MiniMax) endpoints since they host their own models and
# unknown Anthropic beta headers risk request rejection.
_CONTEXT_1M_BETA = "context-1m-2025-08-07"
# Fast mode beta — enables the ``speed: "fast"`` request parameter for
# significantly higher output token throughput on Opus 4.6 (~2.5x).
@@ -308,9 +221,8 @@ def _is_oauth_token(key: str) -> bool:
Positively identifies Anthropic OAuth tokens by their key format:
- ``sk-ant-`` prefix (but NOT ``sk-ant-api``) → setup tokens, managed keys
- ``eyJ`` prefix → JWTs from the Anthropic OAuth flow
- ``cc-`` prefix → Claude Code OAuth access tokens (from CLAUDE_CODE_OAUTH_TOKEN)
Non-Anthropic keys (MiniMax, Alibaba, etc.) don't match any pattern
Non-Anthropic keys (MiniMax, Alibaba, etc.) don't match either pattern
and correctly return False.
"""
if not key:
@@ -324,9 +236,6 @@ def _is_oauth_token(key: str) -> bool:
# JWTs from Anthropic OAuth flow
if key.startswith("eyJ"):
return True
# Claude Code OAuth access tokens (opaque, from CLAUDE_CODE_OAUTH_TOKEN)
if key.startswith("cc-"):
return True
return False
@@ -357,96 +266,6 @@ def _is_third_party_anthropic_endpoint(base_url: str | None) -> bool:
return True # Any other endpoint is a third-party proxy
def _is_kimi_coding_endpoint(base_url: str | None) -> bool:
"""Return True for Kimi's /coding endpoint that requires claude-code UA."""
normalized = _normalize_base_url_text(base_url)
if not normalized:
return False
return normalized.rstrip("/").lower().startswith("https://api.kimi.com/coding")
# Model-name prefixes that identify the Kimi / Moonshot family. Covers
# - official slugs: ``kimi-k2.5``, ``kimi_thinking``, ``moonshot-v1-8k``
# - common release lines: ``k1.5-...``, ``k2-thinking``, ``k25-...``, ``k2.5-...``
# Matched case-insensitively against the post-``normalize_model_name`` form,
# so a caller's ``provider/vendor/model`` slug is handled the same as a
# bare name.
_KIMI_FAMILY_MODEL_PREFIXES = (
"kimi-", "kimi_",
"moonshot-", "moonshot_",
"k1.", "k1-",
"k2.", "k2-",
"k25", "k2.5",
)
def _model_name_is_kimi_family(model: str | None) -> bool:
if not isinstance(model, str):
return False
m = model.strip().lower()
if not m:
return False
# Strip vendor prefix (e.g. ``moonshotai/kimi-k2.5`` → ``kimi-k2.5``)
if "/" in m:
m = m.rsplit("/", 1)[-1]
return m.startswith(_KIMI_FAMILY_MODEL_PREFIXES)
def _is_kimi_family_endpoint(base_url: str | None, model: str | None = None) -> bool:
"""Return True for any Kimi / Moonshot Anthropic-Messages-speaking endpoint.
Broader than ``_is_kimi_coding_endpoint`` — matches:
- Kimi's official ``/coding`` URL (legacy check, preserved)
- Any ``api.kimi.com`` / ``moonshot.ai`` / ``moonshot.cn`` host
- Custom or proxied endpoints whose *model* name is in the Kimi / Moonshot
family (``kimi-*``, ``moonshot-*``, ``k1.*``, ``k2.*``, …). Users with
``api_mode: anthropic_messages`` on a private gateway fronting Kimi
fall into this branch — the upstream still enforces Kimi's thinking
semantics (reasoning_content required on every replayed tool-call
message) regardless of the gateway's hostname.
Used to decide whether to drop Anthropic's ``thinking`` kwarg and to
preserve unsigned reasoning_content-derived thinking blocks on replay.
See hermes-agent#13848, #17057.
"""
if _is_kimi_coding_endpoint(base_url):
return True
for _domain in ("api.kimi.com", "moonshot.ai", "moonshot.cn"):
if base_url_host_matches(base_url or "", _domain):
return True
if _model_name_is_kimi_family(model):
return True
return False
def _is_deepseek_anthropic_endpoint(base_url: str | None) -> bool:
"""Return True for DeepSeek's Anthropic-compatible endpoint.
DeepSeek's ``/anthropic`` route speaks the Anthropic Messages protocol
but, when thinking mode is enabled, requires the ``thinking`` blocks
from prior assistant turns to round-trip on subsequent requests — the
generic third-party path strips them and triggers HTTP 400::
The content[].thinking in the thinking mode must be passed back
to the API.
Per DeepSeek's published compatibility matrix the blocks are unsigned
(no Anthropic-proprietary signature, no ``redacted_thinking`` support),
so this endpoint is handled with the same strip-signed / keep-unsigned
policy used for Kimi's ``/coding`` endpoint. The match is pinned to
the ``/anthropic`` path so the OpenAI-compatible ``api.deepseek.com``
base URL (which never reaches this adapter) is not misclassified.
See hermes-agent#16748.
"""
if not base_url_host_matches(base_url or "", "api.deepseek.com"):
return False
normalized = _normalize_base_url_text(base_url)
if not normalized:
return False
return "/anthropic" in normalized.rstrip("/").lower()
def _requires_bearer_auth(base_url: str | None) -> bool:
"""Return True for Anthropic-compatible providers that require Bearer auth.
@@ -461,45 +280,20 @@ def _requires_bearer_auth(base_url: str | None) -> bool:
return normalized.startswith(("https://api.minimax.io/anthropic", "https://api.minimaxi.com/anthropic"))
def _common_betas_for_base_url(
base_url: str | None,
*,
drop_context_1m_beta: bool = False,
) -> list[str]:
def _common_betas_for_base_url(base_url: str | None) -> list[str]:
"""Return the beta headers that are safe for the configured endpoint.
MiniMax's Anthropic-compatible endpoints (Bearer-auth) reject requests
that include Anthropic's ``fine-grained-tool-streaming`` beta — every
tool-use message triggers a connection error. Strip that beta for
Bearer-auth endpoints while keeping all other betas intact.
The ``context-1m-2025-08-07`` beta is also stripped for Bearer-auth
endpoints — MiniMax hosts its own models, not Claude, so the header is
irrelevant at best and risks request rejection at worst.
``drop_context_1m_beta=True`` additionally strips the 1M-context beta on
otherwise-unrelated endpoints. The OAuth retry path flips this flag after
a subscription rejects the beta with
"The long context beta is not yet available for this subscription" so
subsequent requests in the same session don't repeat the probe. See the
reactive recovery loop in ``run_agent.py`` and issue-comment history on
PR #17680 for the full rationale.
"""
if _requires_bearer_auth(base_url):
_stripped = {_TOOL_STREAMING_BETA, _CONTEXT_1M_BETA}
return [b for b in _COMMON_BETAS if b not in _stripped]
if drop_context_1m_beta:
return [b for b in _COMMON_BETAS if b != _CONTEXT_1M_BETA]
return [b for b in _COMMON_BETAS if b != _TOOL_STREAMING_BETA]
return _COMMON_BETAS
def build_anthropic_client(
api_key: str,
base_url: str = None,
timeout: float = None,
*,
drop_context_1m_beta: bool = False,
):
def build_anthropic_client(api_key: str, base_url: str = None, timeout: float = None):
"""Create an Anthropic client, auto-detecting setup-tokens vs API keys.
If *timeout* is provided it overrides the default 900s read timeout. The
@@ -508,15 +302,8 @@ def build_anthropic_client(
Anthropic-compatible providers respect the same knob as OpenAI-wire
providers.
``drop_context_1m_beta=True`` strips ``context-1m-2025-08-07`` from the
client-level ``anthropic-beta`` header. Used by the reactive OAuth retry
path in ``run_agent.py`` when a subscription rejects the beta; leave at
its default on fresh clients so 1M-capable subscriptions keep the
capability.
Returns an anthropic.Anthropic instance.
"""
_anthropic_sdk = _get_anthropic_sdk()
if _anthropic_sdk is None:
raise ImportError(
"The 'anthropic' package is required for the Anthropic provider. "
@@ -533,33 +320,12 @@ def build_anthropic_client(
"timeout": Timeout(timeout=float(_read_timeout), connect=10.0),
}
if normalized_base_url:
# Azure Anthropic endpoints require an ``api-version`` query parameter.
# Pass it via default_query so the SDK appends it to every request URL
# without corrupting the base_url (appending it directly produces
# malformed paths like /anthropic?api-version=.../v1/messages).
_is_azure_endpoint = "azure.com" in normalized_base_url.lower()
if _is_azure_endpoint and "api-version" not in normalized_base_url:
kwargs["base_url"] = normalized_base_url.rstrip("/")
kwargs["default_query"] = {"api-version": "2025-04-15"}
else:
kwargs["base_url"] = normalized_base_url
common_betas = _common_betas_for_base_url(
normalized_base_url,
drop_context_1m_beta=drop_context_1m_beta,
)
kwargs["base_url"] = normalized_base_url
common_betas = _common_betas_for_base_url(normalized_base_url)
if _is_kimi_coding_endpoint(base_url):
# Kimi's /coding endpoint requires User-Agent: claude-code/0.1.0
# to be recognized as a valid Coding Agent. Without it, returns 403.
# Check this BEFORE _requires_bearer_auth since both match api.kimi.com/coding.
kwargs["api_key"] = api_key
kwargs["default_headers"] = {
"User-Agent": "claude-code/0.1.0",
**( {"anthropic-beta": ",".join(common_betas)} if common_betas else {} )
}
elif _requires_bearer_auth(normalized_base_url):
if _requires_bearer_auth(normalized_base_url):
# Some Anthropic-compatible providers (e.g. MiniMax) expect the API key in
# Authorization: Bearer *** for regular API keys. Route those endpoints
# Authorization: Bearer even for regular API keys. Route those endpoints
# through auth_token so the SDK sends Bearer auth instead of x-api-key.
# Check this before OAuth token shape detection because MiniMax secrets do
# not use Anthropic's sk-ant-api prefix and would otherwise be misread as
@@ -602,16 +368,8 @@ def build_anthropic_bedrock_client(region: str):
Claude feature parity: prompt caching, thinking budgets, adaptive
thinking, fast mode — features not available via the Converse API.
Attaches the common Anthropic beta headers as client-level defaults so
that Bedrock-hosted Claude models get the same enhanced features as
native Anthropic. The ``context-1m-2025-08-07`` beta in particular
unlocks the 1M context window for Opus 4.6/4.7 on Bedrock — without
it, Bedrock caps these models at 200K even though the Anthropic API
serves them with 1M natively.
Auth uses the boto3 default credential chain (IAM roles, SSO, env vars).
"""
_anthropic_sdk = _get_anthropic_sdk()
if _anthropic_sdk is None:
raise ImportError(
"The 'anthropic' package is required for the Bedrock provider. "
@@ -627,73 +385,11 @@ def build_anthropic_bedrock_client(region: str):
return _anthropic_sdk.AnthropicBedrock(
aws_region=region,
timeout=Timeout(timeout=900.0, connect=10.0),
default_headers={"anthropic-beta": ",".join(_COMMON_BETAS)},
)
def _read_claude_code_credentials_from_keychain() -> Optional[Dict[str, Any]]:
"""Read Claude Code OAuth credentials from the macOS Keychain.
Claude Code >=2.1.114 stores credentials in the macOS Keychain under the
service name "Claude Code-credentials" rather than (or in addition to)
the JSON file at ~/.claude/.credentials.json.
The password field contains a JSON string with the same claudeAiOauth
structure as the JSON file.
Returns dict with {accessToken, refreshToken?, expiresAt?} or None.
"""
if platform.system() != "Darwin":
return None
try:
# Read the "Claude Code-credentials" generic password entry
result = subprocess.run(
["security", "find-generic-password",
"-s", "Claude Code-credentials",
"-w"],
capture_output=True,
text=True,
timeout=5,
)
except (OSError, subprocess.TimeoutExpired):
logger.debug("Keychain: security command not available or timed out")
return None
if result.returncode != 0:
logger.debug("Keychain: no entry found for 'Claude Code-credentials'")
return None
raw = result.stdout.strip()
if not raw:
return None
try:
data = json.loads(raw)
except json.JSONDecodeError:
logger.debug("Keychain: credentials payload is not valid JSON")
return None
oauth_data = data.get("claudeAiOauth")
if oauth_data and isinstance(oauth_data, dict):
access_token = oauth_data.get("accessToken", "")
if access_token:
return {
"accessToken": access_token,
"refreshToken": oauth_data.get("refreshToken", ""),
"expiresAt": oauth_data.get("expiresAt", 0),
"source": "macos_keychain",
}
return None
def read_claude_code_credentials() -> Optional[Dict[str, Any]]:
"""Read refreshable Claude Code OAuth credentials.
Checks two sources in order:
1. macOS Keychain (Darwin only) — "Claude Code-credentials" entry
2. ~/.claude/.credentials.json file
"""Read refreshable Claude Code OAuth credentials from ~/.claude/.credentials.json.
This intentionally excludes ~/.claude.json primaryApiKey. Opencode's
subscription flow is OAuth/setup-token based with refreshable credentials,
@@ -702,12 +398,6 @@ def read_claude_code_credentials() -> Optional[Dict[str, Any]]:
Returns dict with {accessToken, refreshToken?, expiresAt?} or None.
"""
# Try macOS Keychain first (covers Claude Code >=2.1.114)
kc_creds = _read_claude_code_credentials_from_keychain()
if kc_creds:
return kc_creds
# Fall back to JSON file
cred_path = Path.home() / ".claude" / ".credentials.json"
if cred_path.exists():
try:
@@ -878,9 +568,7 @@ def _write_claude_code_credentials(
existing["claudeAiOauth"] = oauth_data
cred_path.parent.mkdir(parents=True, exist_ok=True)
_tmp_cred = cred_path.with_suffix(".tmp")
_tmp_cred.write_text(json.dumps(existing, indent=2), encoding="utf-8")
_tmp_cred.replace(cred_path)
cred_path.write_text(json.dumps(existing, indent=2), encoding="utf-8")
# Restrict permissions (credentials file)
cred_path.chmod(0o600)
except (OSError, IOError) as e:
@@ -1147,26 +835,6 @@ def read_hermes_oauth_credentials() -> Optional[Dict[str, Any]]:
# ---------------------------------------------------------------------------
def _is_bedrock_model_id(model: str) -> bool:
"""Detect AWS Bedrock model IDs that use dots as namespace separators.
Bedrock model IDs come in two forms:
- Bare: ``anthropic.claude-opus-4-7``
- Regional (inference profiles): ``us.anthropic.claude-sonnet-4-5-v1:0``
In both cases the dots separate namespace components, not version
numbers, and must be preserved verbatim for the Bedrock API.
"""
lower = model.lower()
# Regional inference-profile prefixes
if any(lower.startswith(p) for p in ("global.", "us.", "eu.", "ap.", "jp.")):
return True
# Bare Bedrock model IDs: provider.model-family
if lower.startswith("anthropic."):
return True
return False
def normalize_model_name(model: str, preserve_dots: bool = False) -> str:
"""Normalize a model name for the Anthropic API.
@@ -1174,25 +842,14 @@ def normalize_model_name(model: str, preserve_dots: bool = False) -> str:
- Converts dots to hyphens in version numbers (OpenRouter uses dots,
Anthropic uses hyphens: claude-opus-4.6 → claude-opus-4-6), unless
preserve_dots is True (e.g. for Alibaba/DashScope: qwen3.5-plus).
- Preserves Bedrock model IDs (``anthropic.claude-opus-4-7``) and
regional inference profiles (``us.anthropic.claude-*``) whose dots
are namespace separators, not version separators.
"""
lower = model.lower()
if lower.startswith("anthropic/"):
model = model[len("anthropic/"):]
if not preserve_dots:
# Bedrock model IDs use dots as namespace separators
# (e.g. "anthropic.claude-opus-4-7", "us.anthropic.claude-*").
# These must not be converted to hyphens. See issue #12295.
if _is_bedrock_model_id(model):
return model
# Only convert dots to hyphens for Anthropic/Claude models.
# Non-Anthropic models (gpt-5.4, gemini-2.5, etc.) use dots
# as part of their canonical names. See issue #17171.
_lower = model.lower()
if _lower.startswith("claude-") or _lower.startswith("anthropic/"):
model = model.replace(".", "-")
# OpenRouter uses dots for version separators (claude-opus-4.6),
# Anthropic uses hyphens (claude-opus-4-6). Convert dots to hyphens.
model = model.replace(".", "-")
return model
@@ -1209,60 +866,17 @@ def _sanitize_tool_id(tool_id: str) -> str:
return sanitized or "tool_0"
def _normalize_tool_input_schema(schema: Any) -> Dict[str, Any]:
"""Normalize tool schemas before sending them to Anthropic.
Anthropic's tool schema validator rejects nullable unions such as
``anyOf: [{"type": "string"}, {"type": "null"}]`` that Pydantic/MCP
commonly emits for optional fields. Tool optionality is represented by
the parent ``required`` array, so we delegate to the shared
``strip_nullable_unions`` helper to collapse nullable unions to the
non-null branch while preserving metadata like description/default.
``keep_nullable_hint=False`` because the Anthropic validator does not
recognize the OpenAPI-style ``nullable: true`` extension and strict
schema-to-grammar converters may reject unknown keywords.
"""
if not schema:
return {"type": "object", "properties": {}}
from tools.schema_sanitizer import strip_nullable_unions
normalized = strip_nullable_unions(schema, keep_nullable_hint=False)
if not isinstance(normalized, dict):
return {"type": "object", "properties": {}}
if normalized.get("type") == "object" and not isinstance(normalized.get("properties"), dict):
normalized = {**normalized, "properties": {}}
return normalized
def convert_tools_to_anthropic(tools: List[Dict]) -> List[Dict]:
"""Convert OpenAI tool definitions to Anthropic format."""
if not tools:
return []
result = []
seen_names: set = set()
for t in tools:
fn = t.get("function", {})
name = fn.get("name", "")
# Defensive dedup: Anthropic rejects requests with duplicate tool
# names. Upstream injection paths already dedup, but this guard
# converts a hard API failure into a warning. See: #18478
if name and name in seen_names:
logger.warning(
"convert_tools_to_anthropic: duplicate tool name '%s' "
"— dropping second occurrence",
name,
)
continue
if name:
seen_names.add(name)
result.append({
"name": name,
"name": fn.get("name", ""),
"description": fn.get("description", ""),
"input_schema": _normalize_tool_input_schema(
fn.get("parameters", {"type": "object", "properties": {}})
),
"input_schema": fn.get("parameters", {"type": "object", "properties": {}}),
})
return result
@@ -1393,7 +1007,6 @@ def _convert_content_to_anthropic(content: Any) -> Any:
def convert_messages_to_anthropic(
messages: List[Dict],
base_url: str | None = None,
model: str | None = None,
) -> Tuple[Optional[Any], List[Dict]]:
"""Convert OpenAI-format messages to Anthropic format.
@@ -1405,12 +1018,6 @@ def convert_messages_to_anthropic(
endpoint, all thinking block signatures are stripped. Signatures are
Anthropic-proprietary — third-party endpoints cannot validate them and will
reject them with HTTP 400 "Invalid signature in thinking block".
When *model* is provided and matches the Kimi / Moonshot family (or
*base_url* is a Kimi / Moonshot host), unsigned thinking blocks
synthesised from ``reasoning_content`` are preserved on replayed
assistant tool-call messages — Kimi requires the field to exist, even
if empty.
"""
system = None
result = []
@@ -1459,31 +1066,6 @@ def convert_messages_to_anthropic(
"name": fn.get("name", ""),
"input": parsed_args,
})
# Kimi's /coding endpoint (Anthropic protocol) requires assistant
# tool-call messages to carry reasoning_content when thinking is
# enabled server-side. Preserve it as a thinking block so Kimi
# can validate the message history. See hermes-agent#13848.
#
# Accept empty string "" — _copy_reasoning_content_for_api()
# injects "" as a tier-3 fallback for Kimi tool-call messages
# that had no reasoning. Kimi requires the field to exist, even
# if empty.
#
# Prepend (not append): Anthropic protocol requires thinking
# blocks before text and tool_use blocks.
#
# Guard: only add when reasoning_details didn't already contribute
# thinking blocks. On native Anthropic, reasoning_details produces
# signed thinking blocks — adding another unsigned one from
# reasoning_content would create a duplicate (same text) that gets
# downgraded to a spurious text block on the last assistant message.
reasoning_content = m.get("reasoning_content")
_already_has_thinking = any(
isinstance(b, dict) and b.get("type") in ("thinking", "redacted_thinking")
for b in blocks
)
if isinstance(reasoning_content, str) and not _already_has_thinking:
blocks.insert(0, {"type": "thinking", "thinking": reasoning_content})
# Anthropic rejects empty assistant content
effective = blocks or content
if not effective or effective == "":
@@ -1639,16 +1221,6 @@ def convert_messages_to_anthropic(
# cache markers can interfere with signature validation.
_THINKING_TYPES = frozenset(("thinking", "redacted_thinking"))
_is_third_party = _is_third_party_anthropic_endpoint(base_url)
# Kimi /coding and DeepSeek /anthropic share a contract: both speak the
# Anthropic Messages protocol upstream but require that thinking blocks
# synthesised from reasoning_content round-trip on subsequent turns when
# thinking is enabled. Signed Anthropic blocks still have to be stripped
# (neither endpoint can validate Anthropic's signatures); unsigned blocks
# are preserved. See hermes-agent#13848 (Kimi) and #16748 (DeepSeek).
_preserve_unsigned_thinking = (
_is_kimi_family_endpoint(base_url, model)
or _is_deepseek_anthropic_endpoint(base_url)
)
last_assistant_idx = None
for i in range(len(result) - 1, -1, -1):
@@ -1660,25 +1232,7 @@ def convert_messages_to_anthropic(
if m.get("role") != "assistant" or not isinstance(m.get("content"), list):
continue
if _preserve_unsigned_thinking:
# Kimi's /coding and DeepSeek's /anthropic endpoints both enable
# thinking server-side and require unsigned thinking blocks on
# replayed assistant tool-call messages. Strip signed Anthropic
# blocks (neither upstream can validate Anthropic signatures) but
# preserve the unsigned ones we synthesised from reasoning_content.
new_content = []
for b in m["content"]:
if not isinstance(b, dict) or b.get("type") not in _THINKING_TYPES:
new_content.append(b)
continue
if b.get("signature") or b.get("data"):
# Anthropic-signed block — upstream can't validate, strip
continue
# Unsigned thinking (synthesised from reasoning_content) —
# keep it: the upstream needs it for message-history validation.
new_content.append(b)
m["content"] = new_content or [{"type": "text", "text": "(empty)"}]
elif _is_third_party or idx != last_assistant_idx:
if _is_third_party or idx != last_assistant_idx:
# Third-party endpoint: strip ALL thinking blocks from every
# assistant message — signatures are Anthropic-proprietary.
# Direct Anthropic: strip from non-latest assistant messages only.
@@ -1732,7 +1286,6 @@ def build_anthropic_kwargs(
context_length: Optional[int] = None,
base_url: str | None = None,
fast_mode: bool = False,
drop_context_1m_beta: bool = False,
) -> Dict[str, Any]:
"""Build kwargs for anthropic.messages.create().
@@ -1772,19 +1325,12 @@ def build_anthropic_kwargs(
Currently only supported on native Anthropic endpoints (not third-party
compatible ones).
"""
system, anthropic_messages = convert_messages_to_anthropic(
messages, base_url=base_url, model=model
)
system, anthropic_messages = convert_messages_to_anthropic(messages, base_url=base_url)
anthropic_tools = convert_tools_to_anthropic(tools) if tools else []
model = normalize_model_name(model, preserve_dots=preserve_dots)
# effective_max_tokens = output cap for this call (≠ total context window)
# Use the resolver helper so non-positive values (negative ints,
# fractional floats, NaN, non-numeric) fail locally with a clear error
# rather than 400-ing at the Anthropic API. See openclaw/openclaw#66664.
effective_max_tokens = _resolve_anthropic_messages_max_tokens(
max_tokens, model, context_length=context_length
)
effective_max_tokens = max_tokens or _get_anthropic_max_output(model)
# Clamp output cap to fit inside the total context window.
# Only matters for small custom endpoints where context_length < native
@@ -1863,25 +1409,11 @@ def build_anthropic_kwargs(
# MiniMax Anthropic-compat endpoints support thinking (manual mode only,
# not adaptive). Haiku does NOT support extended thinking — skip entirely.
#
# Kimi's /coding endpoint speaks the Anthropic Messages protocol but has
# its own thinking semantics: when ``thinking.enabled`` is sent, Kimi
# validates the message history and requires every prior assistant
# tool-call message to carry OpenAI-style ``reasoning_content``. The
# Anthropic path never populates that field, and
# ``convert_messages_to_anthropic`` strips all Anthropic thinking blocks
# on third-party endpoints — so the request fails with HTTP 400
# "thinking is enabled but reasoning_content is missing in assistant
# tool call message at index N". Kimi's reasoning is driven server-side
# on the /coding route, so skip Anthropic's thinking parameter entirely
# for that host. (Kimi on chat_completions enables thinking via
# extra_body in the ChatCompletionsTransport — see #13503.)
#
# On 4.7+ the `thinking.display` field defaults to "omitted", which
# silently hides reasoning text that Hermes surfaces in its CLI. We
# request "summarized" so the reasoning blocks stay populated — matching
# 4.6 behavior and preserving the activity-feed UX during long tool runs.
_is_kimi_coding = _is_kimi_family_endpoint(base_url, model)
if reasoning_config and isinstance(reasoning_config, dict) and not _is_kimi_coding:
if reasoning_config and isinstance(reasoning_config, dict):
if reasoning_config.get("enabled") is not False and "haiku" not in model.lower():
effort = str(reasoning_config.get("effort", "medium")).lower()
budget = THINKING_BUDGET.get(effort, 8000)
@@ -1906,9 +1438,9 @@ def build_anthropic_kwargs(
# ── Strip sampling params on 4.7+ ─────────────────────────────────
# Opus 4.7 rejects any non-default temperature/top_p/top_k with a 400.
# Callers (auxiliary_client, etc.) may set these for older models;
# drop them here as a safety net so upstream 4.6 → 4.7 migrations
# don't require coordinated edits everywhere.
# Callers (auxiliary_client, flush_memories, etc.) may set these for
# older models; drop them here as a safety net so upstream 4.6 → 4.7
# migrations don't require coordinated edits everywhere.
if _forbids_sampling_params(model):
for _sampling_key in ("temperature", "top_p", "top_k"):
kwargs.pop(_sampling_key, None)
@@ -1921,10 +1453,7 @@ def build_anthropic_kwargs(
kwargs.setdefault("extra_body", {})["speed"] = "fast"
# Build extra_headers with ALL applicable betas (the per-request
# extra_headers override the client-level anthropic-beta header).
betas = list(_common_betas_for_base_url(
base_url,
drop_context_1m_beta=drop_context_1m_beta,
))
betas = list(_common_betas_for_base_url(base_url))
if is_oauth:
betas.extend(_OAUTH_ONLY_BETAS)
betas.append(_FAST_MODE_BETA)
@@ -1933,3 +1462,109 @@ def build_anthropic_kwargs(
return kwargs
def normalize_anthropic_response(
response,
strip_tool_prefix: bool = False,
) -> Tuple[SimpleNamespace, str]:
"""Normalize Anthropic response to match the shape expected by AIAgent.
Returns (assistant_message, finish_reason) where assistant_message has
.content, .tool_calls, and .reasoning attributes.
When *strip_tool_prefix* is True, removes the ``mcp_`` prefix that was
added to tool names for OAuth Claude Code compatibility.
"""
text_parts = []
reasoning_parts = []
reasoning_details = []
tool_calls = []
for block in response.content:
if block.type == "text":
text_parts.append(block.text)
elif block.type == "thinking":
reasoning_parts.append(block.thinking)
block_dict = _to_plain_data(block)
if isinstance(block_dict, dict):
reasoning_details.append(block_dict)
elif block.type == "tool_use":
name = block.name
if strip_tool_prefix and name.startswith(_MCP_TOOL_PREFIX):
name = name[len(_MCP_TOOL_PREFIX):]
tool_calls.append(
SimpleNamespace(
id=block.id,
type="function",
function=SimpleNamespace(
name=name,
arguments=json.dumps(block.input),
),
)
)
# Map Anthropic stop_reason to OpenAI finish_reason.
# Newer stop reasons added in Claude 4.5+ / 4.7:
# - refusal: the model declined to answer (cyber safeguards, CSAM, etc.)
# - model_context_window_exceeded: hit context limit (not max_tokens)
# Both need distinct handling upstream — a refusal should surface to the
# user with a clear message, and a context-window overflow should trigger
# compression/truncation rather than be treated as normal end-of-turn.
stop_reason_map = {
"end_turn": "stop",
"tool_use": "tool_calls",
"max_tokens": "length",
"stop_sequence": "stop",
"refusal": "content_filter",
"model_context_window_exceeded": "length",
}
finish_reason = stop_reason_map.get(response.stop_reason, "stop")
return (
SimpleNamespace(
content="\n".join(text_parts) if text_parts else None,
tool_calls=tool_calls or None,
reasoning="\n\n".join(reasoning_parts) if reasoning_parts else None,
reasoning_content=None,
reasoning_details=reasoning_details or None,
),
finish_reason,
)
def normalize_anthropic_response_v2(
response,
strip_tool_prefix: bool = False,
) -> "NormalizedResponse":
"""Normalize Anthropic response to NormalizedResponse.
Wraps the existing normalize_anthropic_response() and maps its output
to the shared transport types. This allows incremental migration —
one call site at a time — without changing the original function.
"""
from agent.transports.types import NormalizedResponse, build_tool_call
assistant_msg, finish_reason = normalize_anthropic_response(response, strip_tool_prefix)
tool_calls = None
if assistant_msg.tool_calls:
tool_calls = [
build_tool_call(
id=tc.id,
name=tc.function.name,
arguments=tc.function.arguments,
)
for tc in assistant_msg.tool_calls
]
provider_data = {}
if getattr(assistant_msg, "reasoning_details", None):
provider_data["reasoning_details"] = assistant_msg.reasoning_details
return NormalizedResponse(
content=assistant_msg.content,
tool_calls=tool_calls,
finish_reason=finish_reason,
reasoning=getattr(assistant_msg, "reasoning", None),
usage=None, # Anthropic usage is on the raw response, not the normaliser
provider_data=provider_data or None,
)
+144 -996
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+5 -171
View File
@@ -87,114 +87,6 @@ def reset_client_cache():
_bedrock_control_client_cache.clear()
def invalidate_runtime_client(region: str) -> bool:
"""Evict the cached ``bedrock-runtime`` client for a single region.
Per-region counterpart to :func:`reset_client_cache`. Used by the converse
call wrappers to discard clients whose underlying HTTP connection has
gone stale, so the next call allocates a fresh client (with a fresh
connection pool) instead of reusing a dead socket.
Returns True if a cached entry was evicted, False if the region was not
cached.
"""
existed = region in _bedrock_runtime_client_cache
_bedrock_runtime_client_cache.pop(region, None)
return existed
# ---------------------------------------------------------------------------
# Stale-connection detection
# ---------------------------------------------------------------------------
#
# boto3 caches its HTTPS connection pool inside the client object. When a
# pooled connection is killed out from under us (NAT timeout, VPN flap,
# server-side TCP RST, proxy idle cull, etc.), the next use surfaces as
# one of a handful of low-level exceptions — most commonly
# ``botocore.exceptions.ConnectionClosedError`` or
# ``urllib3.exceptions.ProtocolError``. urllib3 also trips an internal
# ``assert`` in a couple of paths (connection pool state checks, chunked
# response readers) which bubbles up as a bare ``AssertionError`` with an
# empty ``str(exc)``.
#
# In all of these cases the client is the problem, not the request: retrying
# with the same cached client reproduces the failure until the process
# restarts. The fix is to evict the region's cached client so the next
# attempt builds a new one.
_STALE_LIB_MODULE_PREFIXES = (
"urllib3.",
"botocore.",
"boto3.",
)
def _traceback_frames_modules(exc: BaseException):
"""Yield ``__name__``-style module strings for each frame in exc's traceback."""
tb = getattr(exc, "__traceback__", None)
while tb is not None:
frame = tb.tb_frame
module = frame.f_globals.get("__name__", "")
yield module or ""
tb = tb.tb_next
def is_stale_connection_error(exc: BaseException) -> bool:
"""Return True if ``exc`` indicates a dead/stale Bedrock HTTP connection.
Matches:
* ``botocore.exceptions.ConnectionError`` and subclasses
(``ConnectionClosedError``, ``EndpointConnectionError``,
``ReadTimeoutError``, ``ConnectTimeoutError``).
* ``urllib3.exceptions.ProtocolError`` / ``NewConnectionError`` /
``ConnectionError`` (best-effort import — urllib3 is a transitive
dependency of botocore so it is always available in practice).
* Bare ``AssertionError`` raised from a frame inside urllib3, botocore,
or boto3. These are internal-invariant failures (typically triggered
by corrupted connection-pool state after a dropped socket) and are
recoverable by swapping the client.
Non-library ``AssertionError``s (from application code or tests) are
intentionally not matched — only library-internal asserts signal stale
connection state.
"""
# botocore: the canonical signal — HTTPClientError is the umbrella for
# ConnectionClosedError, ReadTimeoutError, EndpointConnectionError,
# ConnectTimeoutError, and ProxyConnectionError. ConnectionError covers
# the same family via a different branch of the hierarchy.
try:
from botocore.exceptions import (
ConnectionError as BotoConnectionError,
HTTPClientError,
)
botocore_errors: tuple = (BotoConnectionError, HTTPClientError)
except ImportError: # pragma: no cover — botocore always present with boto3
botocore_errors = ()
if botocore_errors and isinstance(exc, botocore_errors):
return True
# urllib3: low-level transport failures
try:
from urllib3.exceptions import (
ProtocolError,
NewConnectionError,
ConnectionError as Urllib3ConnectionError,
)
urllib3_errors = (ProtocolError, NewConnectionError, Urllib3ConnectionError)
except ImportError: # pragma: no cover
urllib3_errors = ()
if urllib3_errors and isinstance(exc, urllib3_errors):
return True
# Library-internal AssertionError (urllib3 / botocore / boto3)
if isinstance(exc, AssertionError):
for module in _traceback_frames_modules(exc):
if any(module.startswith(prefix) for prefix in _STALE_LIB_MODULE_PREFIXES):
return True
return False
# ---------------------------------------------------------------------------
# AWS credential detection
# ---------------------------------------------------------------------------
@@ -291,52 +183,14 @@ def has_aws_credentials(env: Optional[Dict[str, str]] = None) -> bool:
def resolve_bedrock_region(env: Optional[Dict[str, str]] = None) -> str:
"""Resolve the AWS region for Bedrock API calls.
Priority:
1. AWS_REGION env var
2. AWS_DEFAULT_REGION env var
3. boto3/botocore configured region (from ~/.aws/config or SSO profile)
4. us-east-1 (hard fallback)
The boto3 fallback is critical for EU/AP users who configure their region
in ~/.aws/config via a named profile rather than env vars — without it,
live model discovery would always return us.* profile IDs regardless of
the user's actual region.
Priority: AWS_REGION → AWS_DEFAULT_REGION → us-east-1 (fallback).
"""
env = env if env is not None else os.environ
explicit = (
return (
env.get("AWS_REGION", "").strip()
or env.get("AWS_DEFAULT_REGION", "").strip()
or "us-east-1"
)
if explicit:
return explicit
try:
import botocore.session
region = botocore.session.get_session().get_config_variable("region")
if region:
return region
except Exception:
pass
return "us-east-1"
def bedrock_model_ids_or_none() -> Optional[List[str]]:
"""Live-discover Bedrock model IDs for the active region.
Returns a list of model ID strings if discovery succeeds and yields
at least one model, or ``None`` on failure / empty result. Callers
should fall back to the static curated list when ``None`` is returned.
This helper consolidates the discover → extract-ids → fallback
pattern that was previously duplicated across ``provider_model_ids``,
``list_authenticated_providers`` section 2, and section 3.
"""
try:
discovered = discover_bedrock_models(resolve_bedrock_region())
if discovered:
return [m["id"] for m in discovered]
except Exception:
pass
return None
# ---------------------------------------------------------------------------
@@ -933,17 +787,7 @@ def call_converse(
guardrail_config=guardrail_config,
)
try:
response = client.converse(**kwargs)
except Exception as exc:
if is_stale_connection_error(exc):
logger.warning(
"bedrock: stale-connection error on converse(region=%s, model=%s): "
"%s — evicting cached client so the next call reconnects.",
region, model, type(exc).__name__,
)
invalidate_runtime_client(region)
raise
response = client.converse(**kwargs)
return normalize_converse_response(response)
@@ -975,17 +819,7 @@ def call_converse_stream(
guardrail_config=guardrail_config,
)
try:
response = client.converse_stream(**kwargs)
except Exception as exc:
if is_stale_connection_error(exc):
logger.warning(
"bedrock: stale-connection error on converse_stream(region=%s, "
"model=%s): %s — evicting cached client so the next call reconnects.",
region, model, type(exc).__name__,
)
invalidate_runtime_client(region)
raise
response = client.converse_stream(**kwargs)
return normalize_converse_stream_events(response)
+11 -197
View File
@@ -23,52 +23,26 @@ from agent.prompt_builder import DEFAULT_AGENT_IDENTITY
logger = logging.getLogger(__name__)
# Matches Codex/Harmony tool-call serialization that occasionally leaks into
# assistant-message content when the model fails to emit a structured
# ``function_call`` item. Accepts the common forms:
#
# to=functions.exec_command
# assistant to=functions.exec_command
# <|channel|>commentary to=functions.exec_command
#
# ``to=functions.<name>`` is the stable marker — the optional ``assistant`` or
# Harmony channel prefix varies by degeneration mode. Case-insensitive to
# cover lowercase/uppercase ``assistant`` variants.
_TOOL_CALL_LEAK_PATTERN = re.compile(
r"(?:^|[\s>|])to=functions\.[A-Za-z_][\w.]*",
re.IGNORECASE,
)
# ---------------------------------------------------------------------------
# Multimodal content helpers
# ---------------------------------------------------------------------------
def _chat_content_to_responses_parts(content: Any, *, role: str = "user") -> List[Dict[str, Any]]:
def _chat_content_to_responses_parts(content: Any) -> List[Dict[str, Any]]:
"""Convert chat-style multimodal content to Responses API input parts.
Input: ``[{"type":"text"|"image_url", ...}]`` (native OpenAI Chat format)
Output: ``[{"type":"input_text"|"output_text"|"input_image", ...}]`` (Responses format)
The ``role`` parameter controls the text content type:
- ``"user"`` (default) → ``"input_text"``
- ``"assistant"`` → ``"output_text"``
The Responses API rejects ``input_text`` inside assistant messages and
``output_text`` inside user messages, so callers MUST pass the correct
role for the message being converted.
Output: ``[{"type":"input_text"|"input_image", ...}]`` (Responses format)
Returns an empty list when ``content`` is not a list or contains no
recognized parts — callers fall back to the string path.
"""
text_type = "output_text" if role == "assistant" else "input_text"
if not isinstance(content, list):
return []
converted: List[Dict[str, Any]] = []
for part in content:
if isinstance(part, str):
if part:
converted.append({"type": text_type, "text": part})
converted.append({"type": "input_text", "text": part})
continue
if not isinstance(part, dict):
continue
@@ -76,7 +50,7 @@ def _chat_content_to_responses_parts(content: Any, *, role: str = "user") -> Lis
if ptype in {"text", "input_text", "output_text"}:
text = part.get("text")
if isinstance(text, str) and text:
converted.append({"type": text_type, "text": text})
converted.append({"type": "input_text", "text": text})
continue
if ptype in {"image_url", "input_image"}:
image_ref = part.get("image_url")
@@ -227,23 +201,6 @@ def _responses_tools(tools: Optional[List[Dict[str, Any]]] = None) -> Optional[L
# Message format conversion
# ---------------------------------------------------------------------------
_RESPONSE_MESSAGE_STATUSES = {"completed", "incomplete", "in_progress"}
def _normalize_responses_message_status(value: Any, *, default: str = "completed") -> str:
"""Normalize a Responses assistant message status for replay.
The API accepts completed/incomplete/in_progress on replayed assistant
output messages. Preserve those exactly (modulo case/hyphen spelling) so
incomplete Codex continuation turns don't get falsely marked completed.
"""
if isinstance(value, str):
status = value.strip().lower().replace("-", "_").replace(" ", "_")
if status in _RESPONSE_MESSAGE_STATUSES:
return status
return default
def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Convert internal chat-style messages to Responses input items."""
items: List[Dict[str, Any]] = []
@@ -259,10 +216,9 @@ def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Di
if role in {"user", "assistant"}:
content = msg.get("content", "")
if isinstance(content, list):
content_parts = _chat_content_to_responses_parts(content, role=role)
text_type = "output_text" if role == "assistant" else "input_text"
content_parts = _chat_content_to_responses_parts(content)
content_text = "".join(
p.get("text", "") for p in content_parts if p.get("type") == text_type
p.get("text", "") for p in content_parts if p.get("type") == "input_text"
)
else:
content_parts = []
@@ -289,57 +245,7 @@ def _chat_messages_to_responses_input(messages: List[Dict[str, Any]]) -> List[Di
seen_item_ids.add(item_id)
has_codex_reasoning = True
# Replay exact assistant message items (with id/phase) from
# previous turns so the API can maintain prefix-cache hits.
# OpenAI docs: "preserve and resend phase on all assistant
# messages — dropping it can degrade performance."
codex_message_items = msg.get("codex_message_items")
replayed_message_items = 0
if isinstance(codex_message_items, list):
for raw_item in codex_message_items:
if not isinstance(raw_item, dict):
continue
if raw_item.get("type") != "message" or raw_item.get("role") != "assistant":
continue
raw_content_parts = raw_item.get("content")
if not isinstance(raw_content_parts, list):
continue
normalized_content_parts = []
for part in raw_content_parts:
if not isinstance(part, dict):
continue
part_type = str(part.get("type") or "").strip()
if part_type not in {"output_text", "text"}:
continue
text = part.get("text", "")
if text is None:
text = ""
if not isinstance(text, str):
text = str(text)
normalized_content_parts.append({"type": "output_text", "text": text})
if not normalized_content_parts:
continue
replay_item = {
"type": "message",
"role": "assistant",
"status": _normalize_responses_message_status(raw_item.get("status")),
"content": normalized_content_parts,
}
item_id = raw_item.get("id")
if isinstance(item_id, str) and item_id.strip():
replay_item["id"] = item_id.strip()
phase = raw_item.get("phase")
if isinstance(phase, str) and phase.strip():
replay_item["phase"] = phase.strip()
items.append(replay_item)
replayed_message_items += 1
if replayed_message_items > 0:
pass
elif content_parts:
if content_parts:
items.append({"role": "assistant", "content": content_parts})
elif content_text.strip():
items.append({"role": "assistant", "content": content_text})
@@ -499,47 +405,6 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
normalized.append(reasoning_item)
continue
if item_type == "message":
role = item.get("role")
if role != "assistant":
raise ValueError(f"Codex Responses input[{idx}] message items must have role='assistant'.")
content = item.get("content")
if not isinstance(content, list):
raise ValueError(f"Codex Responses input[{idx}] message item must have content list.")
normalized_content = []
for part_idx, part in enumerate(content):
if not isinstance(part, dict):
raise ValueError(
f"Codex Responses input[{idx}] message content[{part_idx}] must be an object."
)
part_type = part.get("type")
if part_type not in {"output_text", "text"}:
raise ValueError(
f"Codex Responses input[{idx}] message content[{part_idx}] has unsupported type {part_type!r}."
)
text = part.get("text", "")
if text is None:
text = ""
if not isinstance(text, str):
text = str(text)
normalized_content.append({"type": "output_text", "text": text})
if not normalized_content:
raise ValueError(f"Codex Responses input[{idx}] message item must contain at least one text part.")
normalized_item: Dict[str, Any] = {
"type": "message",
"role": "assistant",
"status": _normalize_responses_message_status(item.get("status")),
"content": normalized_content,
}
item_id = item.get("id")
if isinstance(item_id, str) and item_id.strip():
normalized_item["id"] = item_id.strip()
phase = item.get("phase")
if isinstance(phase, str) and phase.strip():
normalized_item["phase"] = phase.strip()
normalized.append(normalized_item)
continue
role = item.get("role")
if role in {"user", "assistant"}:
content = item.get("content", "")
@@ -547,16 +412,13 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
content = ""
if isinstance(content, list):
# Multimodal content from ``_chat_messages_to_responses_input``
# is already in Responses format (``input_text`` / ``output_text``
# / ``input_image``). Validate each part and pass through.
# Use the correct text type for the role — ``output_text`` for
# assistant messages, ``input_text`` for user messages.
text_type = "output_text" if role == "assistant" else "input_text"
# is already in Responses format (``input_text`` / ``input_image``).
# Validate each part and pass through.
validated: List[Dict[str, Any]] = []
for part_idx, part in enumerate(content):
if isinstance(part, str):
if part:
validated.append({"type": text_type, "text": part})
validated.append({"type": "input_text", "text": part})
continue
if not isinstance(part, dict):
raise ValueError(
@@ -567,7 +429,7 @@ def _preflight_codex_input_items(raw_items: Any) -> List[Dict[str, Any]]:
text = part.get("text", "")
if not isinstance(text, str):
text = str(text or "")
validated.append({"type": text_type, "text": text})
validated.append({"type": "input_text", "text": text})
elif ptype in {"input_image", "image_url"}:
image_ref = part.get("image_url", "")
detail = part.get("detail")
@@ -824,7 +686,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
content_parts: List[str] = []
reasoning_parts: List[str] = []
reasoning_items_raw: List[Dict[str, Any]] = []
message_items_raw: List[Dict[str, Any]] = []
tool_calls: List[Any] = []
has_incomplete_items = response_status in {"queued", "in_progress", "incomplete"}
saw_commentary_phase = False
@@ -843,7 +704,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
if item_type == "message":
item_phase = getattr(item, "phase", None)
normalized_phase = None
if isinstance(item_phase, str):
normalized_phase = item_phase.strip().lower()
if normalized_phase in {"commentary", "analysis"}:
@@ -853,18 +713,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
message_text = _extract_responses_message_text(item)
if message_text:
content_parts.append(message_text)
raw_message_item: Dict[str, Any] = {
"type": "message",
"role": "assistant",
"status": _normalize_responses_message_status(item_status),
"content": [{"type": "output_text", "text": message_text}],
}
item_id = getattr(item, "id", None)
if isinstance(item_id, str) and item_id:
raw_message_item["id"] = item_id
if normalized_phase:
raw_message_item["phase"] = normalized_phase
message_items_raw.append(raw_message_item)
elif item_type == "reasoning":
reasoning_text = _extract_responses_reasoning_text(item)
if reasoning_text:
@@ -939,37 +787,6 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
if isinstance(out_text, str):
final_text = out_text.strip()
# ── Tool-call leak recovery ──────────────────────────────────
# gpt-5.x on the Codex Responses API sometimes degenerates and emits
# what should be a structured `function_call` item as plain assistant
# text using the Harmony/Codex serialization (``to=functions.foo
# {json}`` or ``assistant to=functions.foo {json}``). The model
# intended to call a tool, but the intent never made it into
# ``response.output`` as a ``function_call`` item, so ``tool_calls``
# is empty here. If we pass this through, the parent sees a
# confident-looking summary with no audit trail (empty ``tool_trace``)
# and no tools actually ran — the Taiwan-embassy-email incident.
#
# Detection: leaked tokens always contain ``to=functions.<name>`` and
# the assistant message has no real tool calls. Treat it as incomplete
# so the existing Codex-incomplete continuation path (3 retries,
# handled in run_agent.py) gets a chance to re-elicit a proper
# ``function_call`` item. The existing loop already handles message
# append, dedup, and retry budget.
leaked_tool_call_text = False
if final_text and not tool_calls and _TOOL_CALL_LEAK_PATTERN.search(final_text):
leaked_tool_call_text = True
logger.warning(
"Codex response contains leaked tool-call text in assistant content "
"(no structured function_call items). Treating as incomplete so the "
"continuation path can re-elicit a proper tool call. Leaked snippet: %r",
final_text[:300],
)
# Clear the text so downstream code doesn't surface the garbage as
# a summary. The encrypted reasoning items (if any) are preserved
# so the model keeps its chain-of-thought on the retry.
final_text = ""
assistant_message = SimpleNamespace(
content=final_text,
tool_calls=tool_calls,
@@ -977,13 +794,10 @@ def _normalize_codex_response(response: Any) -> tuple[Any, str]:
reasoning_content=None,
reasoning_details=None,
codex_reasoning_items=reasoning_items_raw or None,
codex_message_items=message_items_raw or None,
)
if tool_calls:
finish_reason = "tool_calls"
elif leaked_tool_call_text:
finish_reason = "incomplete"
elif has_incomplete_items or (saw_commentary_phase and not saw_final_answer_phase):
finish_reason = "incomplete"
elif reasoning_items_raw and not final_text:
+15 -202
View File
@@ -61,93 +61,9 @@ _PRUNED_TOOL_PLACEHOLDER = "[Old tool output cleared to save context space]"
# Chars per token rough estimate
_CHARS_PER_TOKEN = 4
# Flat token cost per attached image part. Real cost varies by provider and
# dimensions (Anthropic ≈ width×height/750, GPT-4o up to ~1700 for
# high-detail 2048×2048, Gemini 258/tile), but 1600 is a realistic ceiling
# that keeps compression budgeting honest for multi-image conversations.
# Matches Claude Code's IMAGE_TOKEN_ESTIMATE constant.
_IMAGE_TOKEN_ESTIMATE = 1600
# Same figure expressed in the char-budget currency the rest of the
# compressor speaks in. Used when accumulating message "content length"
# for tail-cut decisions.
_IMAGE_CHAR_EQUIVALENT = _IMAGE_TOKEN_ESTIMATE * _CHARS_PER_TOKEN
_SUMMARY_FAILURE_COOLDOWN_SECONDS = 600
def _content_length_for_budget(raw_content: Any) -> int:
"""Return the effective char-length of a message's content for token budgeting.
Plain strings: ``len(content)``. Multimodal lists: sum of text-part
``len(text)`` plus a flat ``_IMAGE_CHAR_EQUIVALENT`` per image part
(``image_url`` / ``input_image`` / Anthropic-style ``image``). This
keeps the compressor from treating a turn with 5 attached images as
near-zero tokens just because the text part is empty.
"""
if isinstance(raw_content, str):
return len(raw_content)
if not isinstance(raw_content, list):
return len(str(raw_content or ""))
total = 0
for p in raw_content:
if isinstance(p, str):
total += len(p)
continue
if not isinstance(p, dict):
total += len(str(p))
continue
ptype = p.get("type")
if ptype in {"image_url", "input_image", "image"}:
total += _IMAGE_CHAR_EQUIVALENT
else:
# text / input_text / tool_result-with-text / anything else with
# a text field. Ignore the raw base64 payload inside image_url
# dicts — dimensions don't matter, only whether it's an image.
total += len(p.get("text", "") or "")
return total
def _content_text_for_contains(content: Any) -> str:
"""Return a best-effort text view of message content.
Used only for substring checks when we need to know whether we've already
appended a note to a message. Keeps multimodal lists intact elsewhere.
"""
if content is None:
return ""
if isinstance(content, str):
return content
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, str):
parts.append(item)
elif isinstance(item, dict):
text = item.get("text")
if isinstance(text, str):
parts.append(text)
return "\n".join(part for part in parts if part)
return str(content)
def _append_text_to_content(content: Any, text: str, *, prepend: bool = False) -> Any:
"""Append or prepend plain text to message content safely.
Compression sometimes needs to add a note or merge a summary into an
existing message. Message content may be plain text or a multimodal list of
blocks, so direct string concatenation is not always safe.
"""
if content is None:
return text
if isinstance(content, str):
return text + content if prepend else content + text
if isinstance(content, list):
text_block = {"type": "text", "text": text}
return [text_block, *content] if prepend else [*content, text_block]
rendered = str(content)
return text + rendered if prepend else rendered + text
def _truncate_tool_call_args_json(args: str, head_chars: int = 200) -> str:
"""Shrink long string values inside a tool-call arguments JSON blob while
preserving JSON validity.
@@ -337,11 +253,6 @@ class ContextCompressor(ContextEngine):
self._context_probed = False
self._context_probe_persistable = False
self._previous_summary = None
self._last_summary_error = None
self._last_summary_dropped_count = 0
self._last_summary_fallback_used = False
self._last_aux_model_failure_error = None
self._last_aux_model_failure_model = None
self._last_compression_savings_pct = 100.0
self._ineffective_compression_count = 0
@@ -365,13 +276,6 @@ class ContextCompressor(ContextEngine):
int(context_length * self.threshold_percent),
MINIMUM_CONTEXT_LENGTH,
)
# Recalculate token budgets for the new context length so the
# compressor stays calibrated after a model switch (e.g. 200K → 32K).
target_tokens = int(self.threshold_tokens * self.summary_target_ratio)
self.tail_token_budget = target_tokens
self.max_summary_tokens = min(
int(context_length * 0.05), _SUMMARY_TOKENS_CEILING,
)
def __init__(
self,
@@ -444,18 +348,6 @@ class ContextCompressor(ContextEngine):
self._last_compression_savings_pct: float = 100.0
self._ineffective_compression_count: int = 0
self._summary_failure_cooldown_until: float = 0.0
self._last_summary_error: Optional[str] = None
# When summary generation fails and a static fallback is inserted,
# record how many turns were unrecoverably dropped so callers
# (gateway hygiene, /compress) can surface a visible warning.
self._last_summary_dropped_count: int = 0
self._last_summary_fallback_used: bool = False
# When a user-configured summary model fails and we recover by
# retrying on the main model, record the failure so gateway /
# CLI callers can still warn the user even though compression
# succeeded. Silent recovery would hide the broken config.
self._last_aux_model_failure_error: Optional[str] = None
self._last_aux_model_failure_model: Optional[str] = None
def update_from_response(self, usage: Dict[str, Any]):
"""Update tracked token usage from API response."""
@@ -538,11 +430,11 @@ class ContextCompressor(ContextEngine):
# Token-budget approach: walk backward accumulating tokens
accumulated = 0
boundary = len(result)
min_protect = min(protect_tail_count, len(result))
min_protect = min(protect_tail_count, len(result) - 1)
for i in range(len(result) - 1, -1, -1):
msg = result[i]
raw_content = msg.get("content") or ""
content_len = _content_length_for_budget(raw_content)
content_len = sum(len(p.get("text", "")) for p in raw_content) if isinstance(raw_content, list) else len(raw_content)
msg_tokens = content_len // _CHARS_PER_TOKEN + 10
for tc in msg.get("tool_calls") or []:
if isinstance(tc, dict):
@@ -569,8 +461,6 @@ class ContextCompressor(ContextEngine):
# Skip multimodal content (list of content blocks)
if isinstance(content, list):
continue
if not isinstance(content, str):
continue
if len(content) < 200:
continue
h = hashlib.md5(content.encode("utf-8", errors="replace")).hexdigest()[:12]
@@ -881,12 +771,10 @@ The user has requested that this compaction PRIORITISE preserving all informatio
self._previous_summary = summary
self._summary_failure_cooldown_until = 0.0
self._summary_model_fallen_back = False
self._last_summary_error = None
return self._with_summary_prefix(summary)
except RuntimeError:
# No provider configured — long cooldown, unlikely to self-resolve
self._summary_failure_cooldown_until = time.monotonic() + _SUMMARY_FAILURE_COOLDOWN_SECONDS
self._last_summary_error = "no auxiliary LLM provider configured"
logging.warning("Context compression: no provider available for "
"summary. Middle turns will be dropped without summary "
"for %d seconds.",
@@ -917,57 +805,13 @@ The user has requested that this compaction PRIORITISE preserving all informatio
"Falling back to main model '%s' for compression.",
self.summary_model, e, self.model,
)
# Record the aux-model failure so callers can warn the user
# even if the retry-on-main succeeds — a misconfigured aux
# model is something the user needs to fix.
_err_text = str(e).strip() or e.__class__.__name__
if len(_err_text) > 220:
_err_text = _err_text[:217].rstrip() + "..."
self._last_aux_model_failure_error = _err_text
self._last_aux_model_failure_model = self.summary_model
self.summary_model = "" # empty = use main model
self._summary_failure_cooldown_until = 0.0 # no cooldown
return self._generate_summary(turns_to_summarize, focus_topic=focus_topic) # retry immediately
# Unknown-error best-effort retry on main model. Losing N turns of
# context is almost always worse than one extra summary attempt, so
# if we haven't already fallen back and the summary model differs
# from the main model, try once more on main before entering
# cooldown. Errors that DID match _is_model_not_found above are
# already handled by the fast-path retry; this branch catches
# everything else (400s, provider-specific "no route" strings,
# aggregator rejections, etc.) where auto-retry is still safer
# than dropping the turns.
if (
self.summary_model
and self.summary_model != self.model
and not getattr(self, "_summary_model_fallen_back", False)
):
self._summary_model_fallen_back = True
logging.warning(
"Summary model '%s' failed (%s). "
"Retrying on main model '%s' before giving up.",
self.summary_model, e, self.model,
)
# Record the aux-model failure (see 404 branch above) — user
# should know their configured model is broken even if main
# recovers the call.
_err_text = str(e).strip() or e.__class__.__name__
if len(_err_text) > 220:
_err_text = _err_text[:217].rstrip() + "..."
self._last_aux_model_failure_error = _err_text
self._last_aux_model_failure_model = self.summary_model
self.summary_model = "" # empty = use main model
self._summary_failure_cooldown_until = 0.0
return self._generate_summary(turns_to_summarize, focus_topic=focus_topic)
return self._generate_summary(turns_to_summarize) # retry immediately
# Transient errors (timeout, rate limit, network) — shorter cooldown
_transient_cooldown = 60
self._summary_failure_cooldown_until = time.monotonic() + _transient_cooldown
err_text = str(e).strip() or e.__class__.__name__
if len(err_text) > 220:
err_text = err_text[:217].rstrip() + "..."
self._last_summary_error = err_text
logging.warning(
"Failed to generate context summary: %s. "
"Further summary attempts paused for %d seconds.",
@@ -994,8 +838,8 @@ The user has requested that this compaction PRIORITISE preserving all informatio
def _get_tool_call_id(tc) -> str:
"""Extract the call ID from a tool_call entry (dict or SimpleNamespace)."""
if isinstance(tc, dict):
return tc.get("call_id", "") or tc.get("id", "") or ""
return getattr(tc, "call_id", "") or getattr(tc, "id", "") or ""
return tc.get("id", "")
return getattr(tc, "id", "") or ""
def _sanitize_tool_pairs(self, messages: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Fix orphaned tool_call / tool_result pairs after compression.
@@ -1182,9 +1026,8 @@ The user has requested that this compaction PRIORITISE preserving all informatio
for i in range(n - 1, head_end - 1, -1):
msg = messages[i]
raw_content = msg.get("content") or ""
content_len = _content_length_for_budget(raw_content)
msg_tokens = content_len // _CHARS_PER_TOKEN + 10 # +10 for role/metadata
content = msg.get("content") or ""
msg_tokens = len(content) // _CHARS_PER_TOKEN + 10 # +10 for role/metadata
# Include tool call arguments in estimate
for tc in msg.get("tool_calls") or []:
if isinstance(tc, dict):
@@ -1215,21 +1058,6 @@ The user has requested that this compaction PRIORITISE preserving all informatio
return max(cut_idx, head_end + 1)
# ------------------------------------------------------------------
# ContextEngine: manual /compress preflight
# ------------------------------------------------------------------
def has_content_to_compress(self, messages: List[Dict[str, Any]]) -> bool:
"""Return True if there is a non-empty middle region to compact.
Overrides the ABC default so the gateway ``/compress`` guard can
skip the LLM call when the transcript is still entirely inside
the protected head/tail.
"""
compress_start = self._align_boundary_forward(messages, self.protect_first_n)
compress_end = self._find_tail_cut_by_tokens(messages, compress_start)
return compress_start < compress_end
# ------------------------------------------------------------------
# Main compression entry point
# ------------------------------------------------------------------
@@ -1253,13 +1081,6 @@ The user has requested that this compaction PRIORITISE preserving all informatio
related to this topic and be more aggressive about compressing
everything else. Inspired by Claude Code's ``/compact``.
"""
# Reset per-call summary failure state — callers inspect these fields
# after compress() returns to decide whether to surface a warning.
self._last_summary_dropped_count = 0
self._last_summary_fallback_used = False
self._last_summary_error = None
self._last_aux_model_failure_error = None
self._last_aux_model_failure_model = None
n_messages = len(messages)
# Only need head + 3 tail messages minimum (token budget decides the real tail size)
_min_for_compress = self.protect_first_n + 3 + 1
@@ -1323,13 +1144,10 @@ The user has requested that this compaction PRIORITISE preserving all informatio
for i in range(compress_start):
msg = messages[i].copy()
if i == 0 and msg.get("role") == "system":
existing = msg.get("content")
existing = msg.get("content") or ""
_compression_note = "[Note: Some earlier conversation turns have been compacted into a handoff summary to preserve context space. The current session state may still reflect earlier work, so build on that summary and state rather than re-doing work.]"
if _compression_note not in _content_text_for_contains(existing):
msg["content"] = _append_text_to_content(
existing,
"\n\n" + _compression_note if isinstance(existing, str) and existing else _compression_note,
)
if _compression_note not in existing:
msg["content"] = existing + "\n\n" + _compression_note
compressed.append(msg)
# If LLM summary failed, insert a static fallback so the model
@@ -1338,13 +1156,11 @@ The user has requested that this compaction PRIORITISE preserving all informatio
if not self.quiet_mode:
logger.warning("Summary generation failed — inserting static fallback context marker")
n_dropped = compress_end - compress_start
self._last_summary_dropped_count = n_dropped
self._last_summary_fallback_used = True
summary = (
f"{SUMMARY_PREFIX}\n"
f"Summary generation was unavailable. {n_dropped} message(s) were "
f"Summary generation was unavailable. {n_dropped} conversation turns were "
f"removed to free context space but could not be summarized. The removed "
f"messages contained earlier work in this session. Continue based on the "
f"turns contained earlier work in this session. Continue based on the "
f"recent messages below and the current state of any files or resources."
)
@@ -1375,15 +1191,12 @@ The user has requested that this compaction PRIORITISE preserving all informatio
for i in range(compress_end, n_messages):
msg = messages[i].copy()
if _merge_summary_into_tail and i == compress_end:
merged_prefix = (
original = msg.get("content") or ""
msg["content"] = (
summary
+ "\n\n--- END OF CONTEXT SUMMARY — "
"respond to the message below, not the summary above ---\n\n"
)
msg["content"] = _append_text_to_content(
msg.get("content"),
merged_prefix,
prepend=True,
+ original
)
_merge_summary_into_tail = False
compressed.append(msg)
-22
View File
@@ -78,7 +78,6 @@ class ContextEngine(ABC):
self,
messages: List[Dict[str, Any]],
current_tokens: int = None,
focus_topic: str = None,
) -> List[Dict[str, Any]]:
"""Compact the message list and return the new message list.
@@ -87,12 +86,6 @@ class ContextEngine(ABC):
context budget. The implementation is free to summarize, build a
DAG, or do anything else as long as the returned list is a valid
OpenAI-format message sequence.
Args:
focus_topic: Optional topic string from manual ``/compress <focus>``.
Engines that support guided compression should prioritise
preserving information related to this topic. Engines that
don't support it may simply ignore this argument.
"""
# -- Optional: pre-flight check ----------------------------------------
@@ -105,21 +98,6 @@ class ContextEngine(ABC):
"""
return False
# -- Optional: manual /compress preflight ------------------------------
def has_content_to_compress(self, messages: List[Dict[str, Any]]) -> bool:
"""Quick check: is there anything in ``messages`` that can be compacted?
Used by the gateway ``/compress`` command as a preflight guard
returning False lets the gateway report "nothing to compress yet"
without making an LLM call.
Default returns True (always attempt). Engines with a cheap way
to introspect their own head/tail boundaries should override this
to return False when the transcript is still entirely protected.
"""
return True
# -- Optional: session lifecycle ---------------------------------------
def on_session_start(self, session_id: str, **kwargs) -> None:
+1 -43
View File
@@ -46,47 +46,6 @@ def _resolve_args() -> list[str]:
return shlex.split(raw)
def _resolve_home_dir() -> str:
"""Return a stable HOME for child ACP processes."""
try:
from hermes_constants import get_subprocess_home
profile_home = get_subprocess_home()
if profile_home:
return profile_home
except Exception:
pass
home = os.environ.get("HOME", "").strip()
if home:
return home
expanded = os.path.expanduser("~")
if expanded and expanded != "~":
return expanded
try:
import pwd
resolved = pwd.getpwuid(os.getuid()).pw_dir.strip()
if resolved:
return resolved
except Exception:
pass
# Last resort: /tmp (writable on any POSIX system). Avoids crashing the
# subprocess with no HOME; callers can set HERMES_HOME explicitly if they
# need a different writable dir.
return "/tmp"
def _build_subprocess_env() -> dict[str, str]:
env = os.environ.copy()
env["HOME"] = _resolve_home_dir()
return env
def _jsonrpc_error(message_id: Any, code: int, message: str) -> dict[str, Any]:
return {
"jsonrpc": "2.0",
@@ -423,7 +382,6 @@ class CopilotACPClient:
text=True,
bufsize=1,
cwd=self._acp_cwd,
env=_build_subprocess_env(),
)
except FileNotFoundError as exc:
raise RuntimeError(
@@ -608,7 +566,7 @@ class CopilotACPClient:
end = start + limit if isinstance(limit, int) and limit > 0 else None
content = "".join(lines[start:end])
if content:
content = redact_sensitive_text(content, force=True)
content = redact_sensitive_text(content)
response = {
"jsonrpc": "2.0",
"id": message_id,
+7 -243
View File
@@ -3,18 +3,17 @@
from __future__ import annotations
import logging
import os
import random
import threading
import time
import uuid
import os
import re
from dataclasses import dataclass, fields, replace
from datetime import datetime
from typing import Any, Dict, List, Optional, Set, Tuple
from hermes_constants import OPENROUTER_BASE_URL
from hermes_cli.config import get_env_value, load_env
import hermes_cli.auth as auth_mod
from hermes_cli.auth import (
CODEX_ACCESS_TOKEN_REFRESH_SKEW_SECONDS,
@@ -456,125 +455,6 @@ class CredentialPool:
logger.debug("Failed to sync from credentials file: %s", exc)
return entry
def _sync_codex_entry_from_auth_store(self, entry: PooledCredential) -> PooledCredential:
"""Sync a Codex device_code pool entry from auth.json if tokens differ.
When a Codex OAuth access token expires (or the ChatGPT account hits
its 5h/weekly quota), the pool entry gets marked ``STATUS_EXHAUSTED``
with a ``last_error_reset_at`` that can be many hours in the future.
Meanwhile the user may run ``hermes model`` / ``hermes auth`` which
performs a fresh device-code login and writes new tokens to
``auth.json`` under ``_auth_store_lock``. Without this sync the pool
entry stays frozen until ``last_error_reset_at`` elapses even
though fresh credentials are sitting on disk and every request
fails with "no available entries (all exhausted or empty)".
Mirrors the Nous/Anthropic resync paths above. Only applies to
device_code-sourced entries; env/API-key-sourced entries have no
auth.json shadow to sync from.
"""
if self.provider != "openai-codex" or entry.source != "device_code":
return entry
try:
with _auth_store_lock():
auth_store = _load_auth_store()
state = _load_provider_state(auth_store, "openai-codex")
if not isinstance(state, dict):
return entry
tokens = state.get("tokens")
if not isinstance(tokens, dict):
return entry
store_access = tokens.get("access_token", "")
store_refresh = tokens.get("refresh_token", "")
# Adopt auth.json tokens when either side differs. Codex refresh
# tokens are single-use too, so a fresh refresh_token from
# another process means our entry's pair is consumed/stale.
entry_access = entry.access_token or ""
entry_refresh = entry.refresh_token or ""
if store_access and (
store_access != entry_access
or (store_refresh and store_refresh != entry_refresh)
):
logger.debug(
"Pool entry %s: syncing Codex tokens from auth.json "
"(refreshed by another process)",
entry.id,
)
field_updates: Dict[str, Any] = {
"access_token": store_access,
"refresh_token": store_refresh or entry.refresh_token,
"last_status": None,
"last_status_at": None,
"last_error_code": None,
"last_error_reason": None,
"last_error_message": None,
"last_error_reset_at": None,
}
if state.get("last_refresh"):
field_updates["last_refresh"] = state["last_refresh"]
updated = replace(entry, **field_updates)
self._replace_entry(entry, updated)
self._persist()
return updated
except Exception as exc:
logger.debug("Failed to sync Codex entry from auth.json: %s", exc)
return entry
def _sync_nous_entry_from_auth_store(self, entry: PooledCredential) -> PooledCredential:
"""Sync a Nous pool entry from auth.json if tokens differ.
Nous OAuth refresh tokens are single-use. When another process
(e.g. a concurrent cron) refreshes the token via
``resolve_nous_runtime_credentials``, it writes fresh tokens to
auth.json under ``_auth_store_lock``. The pool entry's tokens
become stale. This method detects that and adopts the newer pair,
avoiding a "refresh token reuse" revocation on the Nous Portal.
"""
if self.provider != "nous" or entry.source != "device_code":
return entry
try:
with _auth_store_lock():
auth_store = _load_auth_store()
state = _load_provider_state(auth_store, "nous")
if not state:
return entry
store_refresh = state.get("refresh_token", "")
store_access = state.get("access_token", "")
if store_refresh and store_refresh != entry.refresh_token:
logger.debug(
"Pool entry %s: syncing tokens from auth.json (Nous refresh token changed)",
entry.id,
)
field_updates: Dict[str, Any] = {
"access_token": store_access,
"refresh_token": store_refresh,
"last_status": None,
"last_status_at": None,
"last_error_code": None,
}
if state.get("expires_at"):
field_updates["expires_at"] = state["expires_at"]
if state.get("agent_key"):
field_updates["agent_key"] = state["agent_key"]
if state.get("agent_key_expires_at"):
field_updates["agent_key_expires_at"] = state["agent_key_expires_at"]
if state.get("inference_base_url"):
field_updates["inference_base_url"] = state["inference_base_url"]
extra_updates = dict(entry.extra)
for extra_key in ("obtained_at", "expires_in", "agent_key_id",
"agent_key_expires_in", "agent_key_reused",
"agent_key_obtained_at"):
val = state.get(extra_key)
if val is not None:
extra_updates[extra_key] = val
updated = replace(entry, extra=extra_updates, **field_updates)
self._replace_entry(entry, updated)
self._persist()
return updated
except Exception as exc:
logger.debug("Failed to sync Nous entry from auth.json: %s", exc)
return entry
def _sync_device_code_entry_to_auth_store(self, entry: PooledCredential) -> None:
"""Write refreshed pool entry tokens back to auth.json providers.
@@ -681,9 +561,6 @@ class CredentialPool:
last_refresh=refreshed.get("last_refresh"),
)
elif self.provider == "nous":
synced = self._sync_nous_entry_from_auth_store(entry)
if synced is not entry:
entry = synced
nous_state = {
"access_token": entry.access_token,
"refresh_token": entry.refresh_token,
@@ -758,26 +635,6 @@ class CredentialPool:
# Credentials file had a valid (non-expired) token — use it directly
logger.debug("Credentials file has valid token, using without refresh")
return synced
# For nous: another process may have consumed the refresh token
# between our proactive sync and the HTTP call. Re-sync from
# auth.json and adopt the fresh tokens if available.
if self.provider == "nous":
synced = self._sync_nous_entry_from_auth_store(entry)
if synced.refresh_token != entry.refresh_token:
logger.debug("Nous refresh failed but auth.json has newer tokens — adopting")
updated = replace(
synced,
last_status=STATUS_OK,
last_status_at=None,
last_error_code=None,
last_error_reason=None,
last_error_message=None,
last_error_reset_at=None,
)
self._replace_entry(synced, updated)
self._persist()
self._sync_device_code_entry_to_auth_store(updated)
return updated
self._mark_exhausted(entry, None)
return None
@@ -841,29 +698,6 @@ class CredentialPool:
if synced is not entry:
entry = synced
cleared_any = True
# For nous entries, sync from auth.json before status checks.
# Another process may have successfully refreshed via
# resolve_nous_runtime_credentials(), making this entry's
# exhausted status stale.
if (self.provider == "nous"
and entry.source == "device_code"
and entry.last_status == STATUS_EXHAUSTED):
synced = self._sync_nous_entry_from_auth_store(entry)
if synced is not entry:
entry = synced
cleared_any = True
# For openai-codex entries, same pattern: the user may have
# re-authed via `hermes model` / `hermes auth` after a 429/401,
# leaving fresh tokens on disk while the pool entry is still
# frozen behind last_error_reset_at (can be hours in the
# future for ChatGPT weekly windows).
if (self.provider == "openai-codex"
and entry.source == "device_code"
and entry.last_status == STATUS_EXHAUSTED):
synced = self._sync_codex_entry_from_auth_store(entry)
if synced is not entry:
entry = synced
cleared_any = True
if entry.last_status == STATUS_EXHAUSTED:
exhausted_until = _exhausted_until(entry)
if exhausted_until is not None and now < exhausted_until:
@@ -905,11 +739,8 @@ class CredentialPool:
if self._strategy == STRATEGY_LEAST_USED and len(available) > 1:
entry = min(available, key=lambda e: e.request_count)
# Increment usage counter so subsequent selections distribute load
updated = replace(entry, request_count=entry.request_count + 1)
self._replace_entry(entry, updated)
self._current_id = entry.id
return updated
return entry
if self._strategy == STRATEGY_ROUND_ROBIN and len(available) > 1:
entry = available[0]
@@ -1225,18 +1056,6 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
"inference_base_url": state.get("inference_base_url"),
"agent_key": state.get("agent_key"),
"agent_key_expires_at": state.get("agent_key_expires_at"),
# Carry the mint/refresh timestamps into the pool so
# freshness-sensitive consumers (self-heal hooks, pool
# pruning by age) can distinguish just-minted credentials
# from stale ones. Without these, fresh device_code
# entries get obtained_at=None and look older than they
# are (#15099).
"obtained_at": state.get("obtained_at"),
"expires_in": state.get("expires_in"),
"agent_key_id": state.get("agent_key_id"),
"agent_key_expires_in": state.get("agent_key_expires_in"),
"agent_key_reused": state.get("agent_key_reused"),
"agent_key_obtained_at": state.get("agent_key_obtained_at"),
"tls": state.get("tls") if isinstance(state.get("tls"), dict) else None,
"label": seeded_label,
},
@@ -1247,10 +1066,9 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
# env vars (COPILOT_GITHUB_TOKEN / GH_TOKEN). They don't live in
# the auth store or credential pool, so we resolve them here.
try:
from hermes_cli.copilot_auth import resolve_copilot_token, get_copilot_api_token
from hermes_cli.copilot_auth import resolve_copilot_token
token, source = resolve_copilot_token()
if token:
api_token = get_copilot_api_token(token)
source_name = "gh_cli" if "gh" in source.lower() else f"env:{source}"
if not _is_suppressed(provider, source_name):
active_sources.add(source_name)
@@ -1262,7 +1080,7 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
{
"source": source_name,
"auth_type": AUTH_TYPE_API_KEY,
"access_token": api_token,
"access_token": token,
"base_url": pconfig.inference_base_url if pconfig else "",
"label": source,
},
@@ -1300,48 +1118,6 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
except Exception as exc:
logger.debug("Qwen OAuth token seed failed: %s", exc)
elif provider == "minimax-oauth":
# MiniMax OAuth tokens live in ~/.hermes/auth.json providers.minimax-oauth.
# Seed the pool so `/auth list` reflects the logged-in state and the
# standard `hermes auth remove minimax-oauth <N>` flow works.
# Use refresh_if_expiring=False equivalent: resolve_minimax_oauth_runtime_credentials
# always refreshes on expiry, so instead read raw state here to avoid
# surprise network calls during provider discovery.
try:
from hermes_cli.auth import get_provider_auth_state
state = get_provider_auth_state("minimax-oauth")
if state and state.get("access_token"):
source_name = "oauth"
if not _is_suppressed(provider, source_name):
active_sources.add(source_name)
expires_at_ms = None
try:
from datetime import datetime as _dt
raw = state.get("expires_at", "")
if raw:
expires_at_ms = int(_dt.fromisoformat(raw).timestamp() * 1000)
except Exception:
expires_at_ms = None
base_url = str(state.get("inference_base_url", "") or "").rstrip("/")
changed |= _upsert_entry(
entries,
provider,
source_name,
{
"source": source_name,
"auth_type": AUTH_TYPE_OAUTH,
"access_token": state["access_token"],
"refresh_token": state.get("refresh_token"),
"expires_at_ms": expires_at_ms,
"base_url": base_url,
"label": state.get("label", "") or label_from_token(
state.get("access_token", ""), source_name
),
},
)
except Exception as exc:
logger.debug("MiniMax OAuth token seed failed: %s", exc)
elif provider == "openai-codex":
# Respect user suppression — `hermes auth remove openai-codex` marks
# the device_code source as suppressed so it won't be re-seeded from
@@ -1381,16 +1157,6 @@ def _seed_from_singletons(provider: str, entries: List[PooledCredential]) -> Tup
def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool, Set[str]]:
changed = False
active_sources: Set[str] = set()
# Prefer ~/.hermes/.env over os.environ — the user's config file is the
# authoritative source for Hermes credentials. Stale env vars from parent
# processes (Codex CLI, test scripts, etc.) should not override deliberate
# changes to the .env file.
def _get_env_prefer_dotenv(key: str) -> str:
env_file = load_env()
val = env_file.get(key) or os.environ.get(key) or ""
return val.strip()
# Honour user suppression — `hermes auth remove <provider> <N>` for an
# env-seeded credential marks the env:<VAR> source as suppressed so it
# won't be re-seeded from the user's shell environment or ~/.hermes/.env.
@@ -1402,8 +1168,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
def _is_source_suppressed(_p, _s): # type: ignore[misc]
return False
if provider == "openrouter":
# Prefer ~/.hermes/.env over os.environ
token = _get_env_prefer_dotenv("OPENROUTER_API_KEY")
token = os.getenv("OPENROUTER_API_KEY", "").strip()
if token:
source = "env:OPENROUTER_API_KEY"
if _is_source_suppressed(provider, source):
@@ -1429,7 +1194,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
env_url = ""
if pconfig.base_url_env_var:
env_url = _get_env_prefer_dotenv(pconfig.base_url_env_var).rstrip("/")
env_url = os.getenv(pconfig.base_url_env_var, "").strip().rstrip("/")
env_vars = list(pconfig.api_key_env_vars)
if provider == "anthropic":
@@ -1440,8 +1205,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
]
for env_var in env_vars:
# Prefer ~/.hermes/.env over os.environ
token = _get_env_prefer_dotenv(env_var)
token = os.getenv(env_var, "").strip()
if not token:
continue
source = f"env:{env_var}"
+1 -18
View File
@@ -47,6 +47,7 @@ from __future__ import annotations
import os
from dataclasses import dataclass, field
from pathlib import Path
from typing import Callable, List, Optional
@@ -252,19 +253,6 @@ def _remove_nous_device_code(provider: str, removed) -> RemovalResult:
return result
def _remove_minimax_oauth(provider: str, removed) -> RemovalResult:
"""MiniMax OAuth lives in auth.json providers.minimax-oauth — clear it.
Same pattern as Nous: single-source OAuth state with refresh tokens.
Suppression of the `oauth` source ensures the pool reseed path
(_seed_from_singletons) doesn't instantly undo the removal.
"""
result = RemovalResult()
if _clear_auth_store_provider(provider):
result.cleaned.append(f"Cleared {provider} OAuth tokens from auth store")
return result
def _remove_codex_device_code(provider: str, removed) -> RemovalResult:
"""Codex tokens live in TWO places: our auth store AND ~/.codex/auth.json.
@@ -402,11 +390,6 @@ def _register_all_sources() -> None:
remove_fn=_remove_qwen_cli,
description="~/.qwen/oauth_creds.json",
))
register(RemovalStep(
provider="minimax-oauth", source_id="oauth",
remove_fn=_remove_minimax_oauth,
description="auth.json providers.minimax-oauth",
))
register(RemovalStep(
provider="*", source_id="config:",
match_fn=lambda src: src.startswith("config:") or src == "model_config",
-1674
View File
File diff suppressed because it is too large Load Diff
-693
View File
@@ -1,693 +0,0 @@
"""Curator snapshot + rollback.
A pre-run snapshot of ``~/.hermes/skills/`` (excluding ``.curator_backups/``
itself) is taken before any mutating curator pass. Snapshots are tar.gz
files under ``~/.hermes/skills/.curator_backups/<utc-iso>/`` with a
companion ``manifest.json`` describing the snapshot (reason, time, size,
counted skill files). Rollback picks a snapshot, moves the current
``skills/`` tree aside into another snapshot so even the rollback itself
is undoable, then extracts the chosen snapshot into place.
The snapshot does NOT include:
- ``.curator_backups/`` (would recurse)
- ``.hub/`` (hub-installed skills managed by the hub, not us)
It DOES include:
- all SKILL.md files + their directories (``scripts/``, ``references/``,
``templates/``, ``assets/``)
- ``.usage.json`` (usage telemetry needed to rehydrate state cleanly)
- ``.archive/`` (so rollback restores previously-archived skills too)
- ``.curator_state`` (so rolling back also restores the last-run-at
pointer otherwise the curator would immediately re-fire on the next
tick)
- ``.bundled_manifest`` (so protection markers stay consistent)
Alongside the skills tarball, each snapshot also captures a copy of
``~/.hermes/cron/jobs.json`` as ``cron-jobs.json`` when it exists. Cron
jobs reference skills by name in their ``skills``/``skill`` fields; the
curator's consolidation pass rewrites those in place via
``cron.jobs.rewrite_skill_refs()``. Without capturing the pre-run state,
rolling back the skills tree would leave cron jobs pointing at the
umbrella skills even though the narrow skills they were originally
configured with have been restored. We store the whole jobs.json for
fidelity but rollback only touches the ``skills``/``skill`` fields the
rest (schedule, next_run_at, enabled, prompt, etc.) is live state and
we leave it alone.
"""
from __future__ import annotations
import json
import logging
import os
import re
import shutil
import tarfile
import tempfile
import time
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from hermes_constants import get_hermes_home
logger = logging.getLogger(__name__)
DEFAULT_KEEP = 5
# Entries under skills/ that should NEVER be rolled up into a snapshot.
# .hub/ is managed by the skills hub; rolling it back would break lockfile
# invariants. .curator_backups is the backup dir itself — recursion bomb.
_EXCLUDE_TOP_LEVEL = {".curator_backups", ".hub"}
# Snapshot id regex: UTC ISO with colons replaced by dashes so the filename
# is portable (Windows-safe). An optional ``-NN`` suffix handles two
# snapshots landing in the same wallclock second.
_ID_RE = re.compile(r"^\d{4}-\d{2}-\d{2}T\d{2}-\d{2}-\d{2}Z(-\d{2})?$")
def _backups_dir() -> Path:
return get_hermes_home() / "skills" / ".curator_backups"
def _skills_dir() -> Path:
return get_hermes_home() / "skills"
def _cron_jobs_file() -> Path:
"""Source path for the live cron jobs store (``~/.hermes/cron/jobs.json``)."""
return get_hermes_home() / "cron" / "jobs.json"
CRON_JOBS_FILENAME = "cron-jobs.json"
def _backup_cron_jobs_into(dest: Path) -> Dict[str, Any]:
"""Copy the live cron jobs.json into ``dest`` as ``cron-jobs.json``.
Returns a small dict describing what was captured so the caller can
fold it into the manifest. Never raises if the cron file is missing
or unreadable, the return dict has ``backed_up=False`` and the reason,
and the snapshot proceeds without cron data (the snapshot is still
useful for rolling back skills).
"""
src = _cron_jobs_file()
info: Dict[str, Any] = {"backed_up": False, "jobs_count": 0}
if not src.exists():
info["reason"] = "no cron/jobs.json present"
return info
try:
raw = src.read_text(encoding="utf-8")
except OSError as e:
logger.debug("Failed to read cron/jobs.json for backup: %s", e)
info["reason"] = f"read error: {e}"
return info
# Count jobs as a nice diagnostic — but don't fail the snapshot if the
# file is unparseable; just store the raw text and let rollback deal
# with it (or not, if it's corrupted). jobs.json wraps the list as
# `{"jobs": [...], "updated_at": ...}` — we count via that shape, and
# fall back to bare-list shape just in case the format ever changes.
try:
parsed = json.loads(raw)
if isinstance(parsed, dict):
inner = parsed.get("jobs")
if isinstance(inner, list):
info["jobs_count"] = len(inner)
elif isinstance(parsed, list):
info["jobs_count"] = len(parsed)
except (json.JSONDecodeError, TypeError):
info["jobs_count"] = 0
info["parse_warning"] = "jobs.json was not valid JSON at snapshot time"
try:
(dest / CRON_JOBS_FILENAME).write_text(raw, encoding="utf-8")
except OSError as e:
logger.debug("Failed to write cron backup file: %s", e)
info["reason"] = f"write error: {e}"
return info
info["backed_up"] = True
return info
def _utc_id(now: Optional[datetime] = None) -> str:
"""UTC ISO-ish filesystem-safe timestamp: ``2026-05-01T13-05-42Z``."""
if now is None:
now = datetime.now(timezone.utc)
# isoformat → "2026-05-01T13:05:42.123456+00:00"; strip subseconds and tz.
s = now.replace(microsecond=0).isoformat()
if s.endswith("+00:00"):
s = s[:-6]
return s.replace(":", "-") + "Z"
def _load_config() -> Dict[str, Any]:
try:
from hermes_cli.config import load_config
cfg = load_config()
except Exception as e:
logger.debug("Failed to load config for curator backup: %s", e)
return {}
if not isinstance(cfg, dict):
return {}
cur = cfg.get("curator") or {}
if not isinstance(cur, dict):
return {}
bk = cur.get("backup") or {}
return bk if isinstance(bk, dict) else {}
def is_enabled() -> bool:
"""Default ON — the whole point of the backup is safety by default."""
return bool(_load_config().get("enabled", True))
def get_keep() -> int:
cfg = _load_config()
try:
n = int(cfg.get("keep", DEFAULT_KEEP))
except (TypeError, ValueError):
n = DEFAULT_KEEP
return max(1, n)
# ---------------------------------------------------------------------------
# Snapshot
# ---------------------------------------------------------------------------
def _count_skill_files(base: Path) -> int:
try:
return sum(1 for _ in base.rglob("SKILL.md"))
except OSError:
return 0
def _write_manifest(dest: Path, reason: str, archive_path: Path,
skills_counted: int,
cron_info: Optional[Dict[str, Any]] = None) -> None:
manifest = {
"id": dest.name,
"reason": reason,
"created_at": datetime.now(timezone.utc).isoformat(),
"archive": archive_path.name,
"archive_bytes": archive_path.stat().st_size,
"skill_files": skills_counted,
}
if cron_info is not None:
manifest["cron_jobs"] = {
"backed_up": bool(cron_info.get("backed_up", False)),
"jobs_count": int(cron_info.get("jobs_count", 0)),
}
if not cron_info.get("backed_up"):
manifest["cron_jobs"]["reason"] = cron_info.get("reason", "not captured")
if cron_info.get("parse_warning"):
manifest["cron_jobs"]["parse_warning"] = cron_info["parse_warning"]
(dest / "manifest.json").write_text(
json.dumps(manifest, indent=2, sort_keys=True), encoding="utf-8"
)
def snapshot_skills(reason: str = "manual") -> Optional[Path]:
"""Create a tar.gz snapshot of ``~/.hermes/skills/`` and prune old ones.
Returns the snapshot directory path, or ``None`` if the snapshot was
skipped (backup disabled, skills dir missing, or an IO error occurred
in which case we log at debug and return None so the curator never
aborts a pass because of a backup failure).
"""
if not is_enabled():
logger.debug("Curator backup disabled by config; skipping snapshot")
return None
skills = _skills_dir()
if not skills.exists():
logger.debug("No ~/.hermes/skills/ directory — nothing to back up")
return None
backups = _backups_dir()
try:
backups.mkdir(parents=True, exist_ok=True)
except OSError as e:
logger.debug("Failed to create backups dir %s: %s", backups, e)
return None
# Uniquify: if a snapshot with the same second already exists (can
# happen if two curator runs fire in the same second), append a short
# counter. Avoids clobbering and avoids timestamp collisions.
base_id = _utc_id()
snap_id = base_id
counter = 1
while (backups / snap_id).exists():
snap_id = f"{base_id}-{counter:02d}"
counter += 1
dest = backups / snap_id
try:
dest.mkdir(parents=True, exist_ok=False)
except OSError as e:
logger.debug("Failed to create snapshot dir %s: %s", dest, e)
return None
archive = dest / "skills.tar.gz"
try:
# Stream into the tarball — no tempdir copy needed.
with tarfile.open(archive, "w:gz", compresslevel=6) as tf:
for entry in sorted(skills.iterdir()):
if entry.name in _EXCLUDE_TOP_LEVEL:
continue
# arcname: store paths relative to skills/ so extraction
# drops cleanly back into the skills dir.
tf.add(str(entry), arcname=entry.name, recursive=True)
# Capture cron/jobs.json alongside the tarball. Never fails the
# snapshot — the skills side is the core guarantee; cron is
# additive. We still record in the manifest whether it was
# captured so rollback can surface "no cron data in this snapshot".
cron_info = _backup_cron_jobs_into(dest)
_write_manifest(dest, reason, archive,
_count_skill_files(skills),
cron_info=cron_info)
except (OSError, tarfile.TarError) as e:
logger.debug("Curator snapshot failed: %s", e, exc_info=True)
# Clean up partial snapshot
try:
shutil.rmtree(dest, ignore_errors=True)
except OSError:
pass
return None
_prune_old(keep=get_keep())
logger.info("Curator snapshot created: %s (%s)", snap_id, reason)
return dest
def _prune_old(keep: int) -> List[str]:
"""Delete regular snapshots beyond the newest *keep*. Returns deleted
ids. Staging dirs (``.rollback-staging-*``) are implementation detail
and pruned independently on every call."""
backups = _backups_dir()
if not backups.exists():
return []
entries: List[Tuple[str, Path]] = []
stale_staging: List[Path] = []
for child in backups.iterdir():
if not child.is_dir():
continue
if child.name.startswith(".rollback-staging-"):
# Staging dirs are only supposed to exist briefly during a
# rollback. If we find one here (e.g. from a crashed rollback),
# clean it up opportunistically.
stale_staging.append(child)
continue
if _ID_RE.match(child.name):
entries.append((child.name, child))
# Newest first (lexicographic works because the id is UTC ISO).
entries.sort(key=lambda t: t[0], reverse=True)
deleted: List[str] = []
for _, path in entries[keep:]:
try:
shutil.rmtree(path)
deleted.append(path.name)
except OSError as e:
logger.debug("Failed to prune %s: %s", path, e)
for path in stale_staging:
try:
shutil.rmtree(path)
except OSError as e:
logger.debug("Failed to clean stale staging dir %s: %s", path, e)
return deleted
# ---------------------------------------------------------------------------
# List + rollback
# ---------------------------------------------------------------------------
def _read_manifest(snap_dir: Path) -> Dict[str, Any]:
mf = snap_dir / "manifest.json"
if not mf.exists():
return {}
try:
return json.loads(mf.read_text(encoding="utf-8"))
except (OSError, json.JSONDecodeError):
return {}
def list_backups() -> List[Dict[str, Any]]:
"""Return all restorable snapshots, newest first. Only entries with a
real ``skills.tar.gz`` tarball are listed transient
``.rollback-staging-*`` directories created mid-rollback are
implementation detail and not shown."""
backups = _backups_dir()
if not backups.exists():
return []
out: List[Dict[str, Any]] = []
for child in sorted(backups.iterdir(), reverse=True):
if not child.is_dir():
continue
if not _ID_RE.match(child.name):
continue
if not (child / "skills.tar.gz").exists():
continue
mf = _read_manifest(child)
mf.setdefault("id", child.name)
mf.setdefault("path", str(child))
if "archive_bytes" not in mf:
arc = child / "skills.tar.gz"
try:
mf["archive_bytes"] = arc.stat().st_size
except OSError:
mf["archive_bytes"] = 0
out.append(mf)
return out
def _resolve_backup(backup_id: Optional[str]) -> Optional[Path]:
"""Return the path of the requested backup, or the newest one if
*backup_id* is None. Returns None if no match."""
backups = _backups_dir()
if not backups.exists():
return None
if backup_id:
target = backups / backup_id
if (
target.is_dir()
and _ID_RE.match(backup_id)
and (target / "skills.tar.gz").exists()
):
return target
return None
candidates = [
c for c in sorted(backups.iterdir(), reverse=True)
if c.is_dir() and _ID_RE.match(c.name) and (c / "skills.tar.gz").exists()
]
return candidates[0] if candidates else None
def _restore_cron_skill_links(snapshot_dir: Path) -> Dict[str, Any]:
"""Reconcile backed-up cron skill links into the live ``cron/jobs.json``.
We do NOT overwrite the whole cron file. Only the ``skills`` and
``skill`` fields are restored, and only on jobs that still exist in the
current file (matched by ``id``). Everything else about the job
schedule, next_run_at, last_run_at, enabled, prompt, workdir, hooks
is live state that the user/scheduler has modified since the snapshot;
overwriting it would regress unrelated cron activity.
Rules:
- Jobs present in backup AND live, with differing skills skills restored.
- Jobs present in backup AND live, with matching skills no-op.
- Jobs present in backup but gone from live (user deleted the job
after the snapshot) skipped, noted in the return report.
- Jobs present in live but not in backup (user created a new cron
job after the snapshot) left untouched.
Never raises; failures are captured in the return dict. Writes through
``cron.jobs`` to pick up the same lock + atomic-write path that tick()
uses, so we don't race the scheduler.
"""
report: Dict[str, Any] = {
"attempted": False,
"restored": [],
"skipped_missing": [],
"unchanged": 0,
"error": None,
}
backup_file = snapshot_dir / CRON_JOBS_FILENAME
if not backup_file.exists():
report["error"] = f"snapshot has no {CRON_JOBS_FILENAME}"
return report
try:
backup_text = backup_file.read_text(encoding="utf-8")
backup_parsed = json.loads(backup_text)
except (OSError, json.JSONDecodeError) as e:
report["error"] = f"failed to load backed-up jobs: {e}"
return report
# jobs.json on disk is `{"jobs": [...], "updated_at": ...}`; accept both
# that shape and a bare list for forward compat.
if isinstance(backup_parsed, dict):
backup_jobs = backup_parsed.get("jobs")
elif isinstance(backup_parsed, list):
backup_jobs = backup_parsed
else:
backup_jobs = None
if not isinstance(backup_jobs, list):
report["error"] = "backed-up cron-jobs.json has no jobs list"
return report
# Build a lookup of the backed-up skill state keyed by job id.
# We only need the two skill-ish fields (legacy single and modern list).
backup_by_id: Dict[str, Dict[str, Any]] = {}
for job in backup_jobs:
if not isinstance(job, dict):
continue
jid = job.get("id")
if not isinstance(jid, str) or not jid:
continue
backup_by_id[jid] = {
"skills": job.get("skills"),
"skill": job.get("skill"),
"name": job.get("name") or jid,
}
if not backup_by_id:
report["attempted"] = True # we tried but there was nothing to do
return report
# Load and rewrite the live jobs under the scheduler's lock.
try:
from cron.jobs import load_jobs, save_jobs, _jobs_file_lock
except ImportError as e:
report["error"] = f"cron module unavailable: {e}"
return report
report["attempted"] = True
try:
with _jobs_file_lock:
live_jobs = load_jobs()
changed = False
live_ids = set()
for live in live_jobs:
if not isinstance(live, dict):
continue
jid = live.get("id")
if not isinstance(jid, str) or not jid:
continue
live_ids.add(jid)
backup = backup_by_id.get(jid)
if backup is None:
continue # live job didn't exist at snapshot time
cur_skills = live.get("skills")
cur_skill = live.get("skill")
bkp_skills = backup.get("skills")
bkp_skill = backup.get("skill")
if cur_skills == bkp_skills and cur_skill == bkp_skill:
report["unchanged"] += 1
continue
# Restore. Preserve absence (don't force the key to appear
# if the backup didn't have it either).
if bkp_skills is None:
live.pop("skills", None)
else:
live["skills"] = bkp_skills
if bkp_skill is None:
live.pop("skill", None)
else:
live["skill"] = bkp_skill
report["restored"].append({
"job_id": jid,
"job_name": backup.get("name") or jid,
"from": {"skills": cur_skills, "skill": cur_skill},
"to": {"skills": bkp_skills, "skill": bkp_skill},
})
changed = True
# Jobs in backup but not in live = user deleted them after snapshot
for jid, backup in backup_by_id.items():
if jid not in live_ids:
report["skipped_missing"].append({
"job_id": jid,
"job_name": backup.get("name") or jid,
})
if changed:
save_jobs(live_jobs)
except Exception as e: # noqa: BLE001 — rollback must not die mid-restore
logger.debug("Cron skill-link restore failed: %s", e, exc_info=True)
report["error"] = f"restore failed mid-flight: {e}"
return report
def rollback(backup_id: Optional[str] = None) -> Tuple[bool, str, Optional[Path]]:
"""Restore ``~/.hermes/skills/`` from a snapshot.
Strategy:
1. Resolve the target snapshot (explicit id or newest regular).
2. Take a safety snapshot of the CURRENT skills tree under
``.curator_backups/pre-rollback-<ts>/`` so the rollback itself is
undoable.
3. Move all current top-level entries (except ``.curator_backups``
and ``.hub``) into a tempdir.
4. Extract the chosen snapshot into ``~/.hermes/skills/``.
5. On failure during 4, move the tempdir contents back (best-effort)
and return failure.
Returns ``(ok, message, snapshot_path)``.
"""
target = _resolve_backup(backup_id)
if target is None:
return (
False,
f"no matching backup found"
+ (f" for id '{backup_id}'" if backup_id else "")
+ " (use `hermes curator rollback --list` to see available snapshots)",
None,
)
archive = target / "skills.tar.gz"
if not archive.exists():
return (False, f"snapshot {target.name} has no skills.tar.gz — corrupted?", None)
skills = _skills_dir()
skills.mkdir(parents=True, exist_ok=True)
backups = _backups_dir()
backups.mkdir(parents=True, exist_ok=True)
# Step 2: safety snapshot of current state FIRST. If this fails we bail
# out before touching anything — otherwise a failed extract could leave
# the user with no skills.
try:
snapshot_skills(reason=f"pre-rollback to {target.name}")
except Exception as e:
return (False, f"pre-rollback safety snapshot failed: {e}", None)
# Additionally move current entries into an internal staging dir so
# the extract happens into an empty skills tree (predictable result).
# This dir is implementation detail — not listed as a restorable
# backup. The safety snapshot above is the user-facing undo handle.
staged = backups / f".rollback-staging-{_utc_id()}"
try:
staged.mkdir(parents=True, exist_ok=False)
except OSError as e:
return (False, f"failed to create staging dir: {e}", None)
moved: List[Tuple[Path, Path]] = []
try:
for entry in list(skills.iterdir()):
if entry.name in _EXCLUDE_TOP_LEVEL:
continue
dest = staged / entry.name
shutil.move(str(entry), str(dest))
moved.append((entry, dest))
except OSError as e:
# Best-effort rollback of the move
for orig, dest in moved:
try:
shutil.move(str(dest), str(orig))
except OSError:
pass
try:
shutil.rmtree(staged, ignore_errors=True)
except OSError:
pass
return (False, f"failed to stage current skills: {e}", None)
# Step 4: extract the snapshot into skills/
try:
with tarfile.open(archive, "r:gz") as tf:
# Python 3.12+ supports filter='data' for safer extraction.
# Fall back to the unfiltered call for older interpreters but
# still reject absolute paths and .. components defensively.
for member in tf.getmembers():
name = member.name
if name.startswith("/") or ".." in Path(name).parts:
raise tarfile.TarError(
f"refusing to extract unsafe path: {name!r}"
)
try:
tf.extractall(str(skills), filter="data") # type: ignore[call-arg]
except TypeError:
# Python < 3.12 — no filter kwarg
tf.extractall(str(skills))
except (OSError, tarfile.TarError) as e:
# Best-effort recover: move staged contents back
for orig, dest in moved:
try:
shutil.move(str(dest), str(orig))
except OSError:
pass
try:
shutil.rmtree(staged, ignore_errors=True)
except OSError:
pass
return (False, f"snapshot extract failed (state restored): {e}", None)
# Extract succeeded — the staging dir has served its purpose. The
# user's undo handle is the safety snapshot tarball we took earlier.
try:
shutil.rmtree(staged, ignore_errors=True)
except OSError:
pass
# Reconcile cron skill-links. Surgical: only the skills/skill fields
# on jobs matched by id. Everything else in jobs.json is live state
# (schedule, next_run_at, enabled, prompt, etc.) and we leave it
# alone. Failures here don't fail the overall rollback — the skills
# tree is already restored, which is the main guarantee.
cron_report = _restore_cron_skill_links(target)
summary_bits = [f"restored from snapshot {target.name}"]
if cron_report.get("attempted"):
restored_n = len(cron_report.get("restored") or [])
skipped_n = len(cron_report.get("skipped_missing") or [])
if cron_report.get("error"):
summary_bits.append(f"cron links: error — {cron_report['error']}")
elif restored_n == 0 and skipped_n == 0 and cron_report.get("unchanged", 0) == 0:
# Attempted but nothing matched — empty snapshot or no overlapping ids.
pass
else:
parts = []
if restored_n:
parts.append(f"{restored_n} job(s) had skill links restored")
if skipped_n:
parts.append(f"{skipped_n} backed-up job(s) no longer exist (skipped)")
if cron_report.get("unchanged"):
parts.append(f"{cron_report['unchanged']} already matched")
summary_bits.append("cron links: " + ", ".join(parts))
logger.info("Curator rollback: restored from %s (cron_report=%s)",
target.name, cron_report)
return (True, "; ".join(summary_bits), target)
# ---------------------------------------------------------------------------
# Human-readable summary for CLI
# ---------------------------------------------------------------------------
def format_size(n: int) -> str:
for unit in ("B", "KB", "MB", "GB"):
if n < 1024 or unit == "GB":
return f"{n:.1f} {unit}" if unit != "B" else f"{n} B"
n /= 1024
return f"{n:.1f} GB"
def summarize_backups() -> str:
rows = list_backups()
if not rows:
return "No curator snapshots yet."
lines = [f"{'id':<24} {'reason':<40} {'skills':>6} {'size':>8}"]
lines.append("" * len(lines[0]))
for r in rows:
lines.append(
f"{r.get('id','?'):<24} "
f"{(r.get('reason','?') or '?')[:40]:<40} "
f"{r.get('skill_files', 0):>6} "
f"{format_size(int(r.get('archive_bytes', 0))):>8}"
)
return "\n".join(lines)
+10 -181
View File
@@ -42,11 +42,9 @@ class FailoverReason(enum.Enum):
# Context / payload
context_overflow = "context_overflow" # Context too large — compress, not failover
payload_too_large = "payload_too_large" # 413 — compress payload
image_too_large = "image_too_large" # Native image part exceeds provider's per-image limit — shrink and retry
# Model
model_not_found = "model_not_found" # 404 or invalid model — fallback to different model
provider_policy_blocked = "provider_policy_blocked" # Aggregator (e.g. OpenRouter) blocked the only endpoint due to account data/privacy policy
# Request format
format_error = "format_error" # 400 bad request — abort or strip + retry
@@ -54,7 +52,6 @@ class FailoverReason(enum.Enum):
# Provider-specific
thinking_signature = "thinking_signature" # Anthropic thinking block sig invalid
long_context_tier = "long_context_tier" # Anthropic "extra usage" tier gate
oauth_long_context_beta_forbidden = "oauth_long_context_beta_forbidden" # Anthropic OAuth subscription rejects 1M context beta — disable beta and retry
# Catch-all
unknown = "unknown" # Unclassifiable — retry with backoff
@@ -92,7 +89,6 @@ class ClassifiedError:
_BILLING_PATTERNS = [
"insufficient credits",
"insufficient_quota",
"insufficient balance",
"credit balance",
"credits have been exhausted",
"top up your credits",
@@ -150,20 +146,6 @@ _PAYLOAD_TOO_LARGE_PATTERNS = [
"error code: 413",
]
# Image-size patterns. Matched against 400 bodies (not 413) because most
# providers return a 400 with a specific image-too-big message before the
# whole request hits the 413 size limit. Anthropic's wording is the most
# important here (hard 5 MB per image, returned as
# "messages.N.content.K.image.source.base64: image exceeds 5 MB maximum").
_IMAGE_TOO_LARGE_PATTERNS = [
"image exceeds", # Anthropic: "image exceeds 5 MB maximum"
"image too large", # generic
"image_too_large", # error_code variant
"image size exceeds", # variant
# "request_too_large" on a request known to contain an image → image is
# the likely culprit; we still try the shrink path before giving up.
]
# Context overflow patterns
_CONTEXT_OVERFLOW_PATTERNS = [
"context length",
@@ -212,29 +194,6 @@ _MODEL_NOT_FOUND_PATTERNS = [
"unsupported model",
]
# OpenRouter aggregator policy-block patterns.
#
# When a user's OpenRouter account privacy setting (or a per-request
# `provider.data_collection: deny` preference) excludes the only endpoint
# serving a model, OpenRouter returns 404 with a *specific* message that is
# distinct from "model not found":
#
# "No endpoints available matching your guardrail restrictions and
# data policy. Configure: https://openrouter.ai/settings/privacy"
#
# We classify this as `provider_policy_blocked` rather than
# `model_not_found` because:
# - The model *exists* — model_not_found is misleading in logs
# - Provider fallback won't help: the account-level setting applies to
# every call on the same OpenRouter account
# - The error body already contains the fix URL, so the user gets
# actionable guidance without us rewriting the message
_PROVIDER_POLICY_BLOCKED_PATTERNS = [
"no endpoints available matching your guardrail",
"no endpoints available matching your data policy",
"no endpoints found matching your data policy",
]
# Auth patterns (non-status-code signals)
_AUTH_PATTERNS = [
"invalid api key",
@@ -261,25 +220,12 @@ _TRANSPORT_ERROR_TYPES = frozenset({
"ConnectionAbortedError", "BrokenPipeError",
"TimeoutError", "ReadError",
"ServerDisconnectedError",
# SSL/TLS transport errors — transient mid-stream handshake/record
# failures that should retry rather than surface as a stalled session.
# ssl.SSLError subclasses OSError (caught by isinstance) but we list
# the type names here so provider-wrapped SSL errors (e.g. when the
# SDK re-raises without preserving the exception chain) still classify
# as transport rather than falling through to the unknown bucket.
"SSLError", "SSLZeroReturnError", "SSLWantReadError",
"SSLWantWriteError", "SSLEOFError", "SSLSyscallError",
# OpenAI SDK errors (not subclasses of Python builtins)
"APIConnectionError",
"APITimeoutError",
})
# Server disconnect patterns (no status code, but transport-level).
# These are the "ambiguous" patterns — a plain connection close could be
# transient transport hiccup OR server-side context overflow rejection
# (common when the API gateway disconnects instead of returning an HTTP
# error for oversized requests). A large session + one of these patterns
# triggers the context-overflow-with-compression recovery path.
# Server disconnect patterns (no status code, but transport-level)
_SERVER_DISCONNECT_PATTERNS = [
"server disconnected",
"peer closed connection",
@@ -290,40 +236,6 @@ _SERVER_DISCONNECT_PATTERNS = [
"incomplete chunked read",
]
# SSL/TLS transient failure patterns — intentionally distinct from
# _SERVER_DISCONNECT_PATTERNS above.
#
# An SSL alert mid-stream is almost always a transport-layer hiccup
# (flaky network, mid-session TLS renegotiation failure, load balancer
# dropping the connection) — NOT a server-side context overflow signal.
# So we want the retry path but NOT the compression path; lumping these
# into _SERVER_DISCONNECT_PATTERNS would trigger unnecessary (and
# expensive) context compression on any large-session SSL hiccup.
#
# The OpenSSL library constructs error codes by prepending a format string
# to the uppercased alert reason; OpenSSL 3.x changed the separator
# (e.g. `SSLV3_ALERT_BAD_RECORD_MAC` → `SSL/TLS_ALERT_BAD_RECORD_MAC`),
# which silently stopped matching anything explicit. Matching on the
# stable substrings (`bad record mac`, `ssl alert`, `tls alert`, etc.)
# survives future OpenSSL format churn without code changes.
_SSL_TRANSIENT_PATTERNS = [
# Space-separated (human-readable form, Python ssl module, most SDKs)
"bad record mac",
"ssl alert",
"tls alert",
"ssl handshake failure",
"tlsv1 alert",
"sslv3 alert",
# Underscore-separated (OpenSSL error code tokens, e.g.
# `ERR_SSL_SSL/TLS_ALERT_BAD_RECORD_MAC`, `SSLV3_ALERT_BAD_RECORD_MAC`)
"bad_record_mac",
"ssl_alert",
"tls_alert",
"tls_alert_internal_error",
# Python ssl module prefix, e.g. "[SSL: BAD_RECORD_MAC]"
"[ssl:",
]
# ── Classification pipeline ─────────────────────────────────────────────
@@ -343,10 +255,9 @@ def classify_api_error(
2. HTTP status code + message-aware refinement
3. Error code classification (from body)
4. Message pattern matching (billing vs rate_limit vs context vs auth)
5. SSL/TLS transient alert patterns retry as timeout
5. Transport error heuristics
6. Server disconnect + large session context overflow
7. Transport error heuristics
8. Fallback: unknown (retryable with backoff)
7. Fallback: unknown (retryable with backoff)
Args:
error: The exception from the API call.
@@ -360,11 +271,6 @@ def classify_api_error(
"""
status_code = _extract_status_code(error)
error_type = type(error).__name__
# Copilot/GitHub Models RateLimitError may not set .status_code; force 429
# so downstream rate-limit handling (classifier reason, pool rotation,
# fallback gating) fires correctly instead of misclassifying as generic.
if status_code is None and error_type == "RateLimitError":
status_code = 429
body = _extract_error_body(error)
error_code = _extract_error_code(body)
@@ -451,25 +357,6 @@ def classify_api_error(
should_compress=True,
)
# Anthropic OAuth subscription rejects the 1M-context beta header.
# Observed error body: "The long context beta is not yet available for
# this subscription." Returned as HTTP 400 from native Anthropic when
# the subscription doesn't include 1M context, even though the request
# carries ``anthropic-beta: context-1m-2025-08-07``. The recovery path
# in run_agent.py rebuilds the Anthropic client with the beta stripped
# and retries once. Pattern is narrow enough that it won't collide with
# the 429 tier-gate pattern above (different status, different phrase).
if (
status_code == 400
and "long context beta" in error_msg
and "not yet available" in error_msg
):
return _result(
FailoverReason.oauth_long_context_beta_forbidden,
retryable=True,
should_compress=False,
)
# ── 2. HTTP status code classification ──────────────────────────
if status_code is not None:
@@ -501,18 +388,7 @@ def classify_api_error(
if classified is not None:
return classified
# ── 5. SSL/TLS transient errors → retry as timeout (not compression) ──
# SSL alerts mid-stream are transport hiccups, not server-side context
# overflow signals. Classify before the disconnect check so a large
# session doesn't incorrectly trigger context compression when the real
# cause is a flaky TLS handshake. Also matches when the error is
# wrapped in a generic exception whose message string carries the SSL
# alert text but the type isn't ssl.SSLError (happens with some SDKs
# that re-raise without chaining).
if any(p in error_msg for p in _SSL_TRANSIENT_PATTERNS):
return _result(FailoverReason.timeout, retryable=True)
# ── 6. Server disconnect + large session → context overflow ─────
# ── 5. Server disconnect + large session → context overflow ─────
# Must come BEFORE generic transport error catch — a disconnect on
# a large session is more likely context overflow than a transient
# transport hiccup. Without this ordering, RemoteProtocolError
@@ -529,12 +405,12 @@ def classify_api_error(
)
return _result(FailoverReason.timeout, retryable=True)
# ── 7. Transport / timeout heuristics ───────────────────────────
# ── 6. Transport / timeout heuristics ───────────────────────────
if error_type in _TRANSPORT_ERROR_TYPES or isinstance(error, (TimeoutError, ConnectionError, OSError)):
return _result(FailoverReason.timeout, retryable=True)
# ── 8. Fallback: unknown ────────────────────────────────────────
# ── 7. Fallback: unknown ────────────────────────────────────────
return _result(FailoverReason.unknown, retryable=True)
@@ -588,33 +464,17 @@ def _classify_by_status(
return _classify_402(error_msg, result_fn)
if status_code == 404:
# OpenRouter policy-block 404 — distinct from "model not found".
# The model exists; the user's account privacy setting excludes the
# only endpoint serving it. Falling back to another provider won't
# help (same account setting applies). The error body already
# contains the fix URL, so just surface it.
if any(p in error_msg for p in _PROVIDER_POLICY_BLOCKED_PATTERNS):
return result_fn(
FailoverReason.provider_policy_blocked,
retryable=False,
should_fallback=False,
)
if any(p in error_msg for p in _MODEL_NOT_FOUND_PATTERNS):
return result_fn(
FailoverReason.model_not_found,
retryable=False,
should_fallback=True,
)
# Generic 404 with no "model not found" signal — could be a wrong
# endpoint path (common with local llama.cpp / Ollama / vLLM when
# the URL is slightly misconfigured), a proxy routing glitch, or
# a transient backend issue. Classifying these as model_not_found
# silently falls back to a different provider and tells the model
# the model is missing, which is wrong and wastes a turn. Treat
# as unknown so the retry loop surfaces the real error instead.
# Generic 404 — could be model or endpoint
return result_fn(
FailoverReason.unknown,
retryable=True,
FailoverReason.model_not_found,
retryable=False,
should_fallback=True,
)
if status_code == 413:
@@ -707,15 +567,6 @@ def _classify_400(
) -> ClassifiedError:
"""Classify 400 Bad Request — context overflow, format error, or generic."""
# Image-too-large from 400 (Anthropic's 5 MB per-image check fires this way).
# Must be checked BEFORE context_overflow because messages can trip both
# patterns ("exceeds" + "image") and image-shrink is a cheaper recovery.
if any(p in error_msg for p in _IMAGE_TOO_LARGE_PATTERNS):
return result_fn(
FailoverReason.image_too_large,
retryable=True,
)
# Context overflow from 400
if any(p in error_msg for p in _CONTEXT_OVERFLOW_PATTERNS):
return result_fn(
@@ -725,12 +576,6 @@ def _classify_400(
)
# Some providers return model-not-found as 400 instead of 404 (e.g. OpenRouter).
if any(p in error_msg for p in _PROVIDER_POLICY_BLOCKED_PATTERNS):
return result_fn(
FailoverReason.provider_policy_blocked,
retryable=False,
should_fallback=False,
)
if any(p in error_msg for p in _MODEL_NOT_FOUND_PATTERNS):
return result_fn(
FailoverReason.model_not_found,
@@ -843,13 +688,6 @@ def _classify_by_message(
should_compress=True,
)
# Image-too-large patterns (from message text when no status_code)
if any(p in error_msg for p in _IMAGE_TOO_LARGE_PATTERNS):
return result_fn(
FailoverReason.image_too_large,
retryable=True,
)
# Usage-limit patterns need the same disambiguation as 402: some providers
# surface "usage limit" errors without an HTTP status code. A transient
# signal ("try again", "resets at", …) means it's a periodic quota, not
@@ -910,15 +748,6 @@ def _classify_by_message(
should_fallback=True,
)
# Provider policy-block (aggregator-side guardrail) — check before
# model_not_found so we don't mis-label as a missing model.
if any(p in error_msg for p in _PROVIDER_POLICY_BLOCKED_PATTERNS):
return result_fn(
FailoverReason.provider_policy_blocked,
retryable=False,
should_fallback=False,
)
# Model not found patterns
if any(p in error_msg for p in _MODEL_NOT_FOUND_PATTERNS):
return result_fn(
+2
View File
@@ -30,6 +30,7 @@ from __future__ import annotations
import json
import logging
import os
import time
import uuid
from types import SimpleNamespace
@@ -41,6 +42,7 @@ from agent import google_oauth
from agent.gemini_schema import sanitize_gemini_tool_parameters
from agent.google_code_assist import (
CODE_ASSIST_ENDPOINT,
FREE_TIER_ID,
CodeAssistError,
ProjectContext,
resolve_project_context,
-104
View File
@@ -44,97 +44,6 @@ def is_native_gemini_base_url(base_url: str) -> bool:
return not normalized.endswith("/openai")
def probe_gemini_tier(
api_key: str,
base_url: str = DEFAULT_GEMINI_BASE_URL,
*,
model: str = "gemini-2.5-flash",
timeout: float = 10.0,
) -> str:
"""Probe a Google AI Studio API key and return its tier.
Returns one of:
- ``"free"`` -- key is on the free tier (unusable with Hermes)
- ``"paid"`` -- key is on a paid tier
- ``"unknown"`` -- probe failed; callers should proceed without blocking.
"""
key = (api_key or "").strip()
if not key:
return "unknown"
normalized_base = str(base_url or DEFAULT_GEMINI_BASE_URL).strip().rstrip("/")
if not normalized_base:
normalized_base = DEFAULT_GEMINI_BASE_URL
if normalized_base.lower().endswith("/openai"):
normalized_base = normalized_base[: -len("/openai")]
url = f"{normalized_base}/models/{model}:generateContent"
payload = {
"contents": [{"role": "user", "parts": [{"text": "hi"}]}],
"generationConfig": {"maxOutputTokens": 1},
}
try:
with httpx.Client(timeout=timeout) as client:
resp = client.post(
url,
params={"key": key},
json=payload,
headers={"Content-Type": "application/json"},
)
except Exception as exc:
logger.debug("probe_gemini_tier: network error: %s", exc)
return "unknown"
headers_lower = {k.lower(): v for k, v in resp.headers.items()}
rpd_header = headers_lower.get("x-ratelimit-limit-requests-per-day")
if rpd_header:
try:
rpd_val = int(rpd_header)
except (TypeError, ValueError):
rpd_val = None
# Published free-tier daily caps (Dec 2025):
# gemini-2.5-pro: 100, gemini-2.5-flash: 250, flash-lite: 1000
# Tier 1 starts at ~1500+ for Flash. We treat <= 1000 as free.
if rpd_val is not None and rpd_val <= 1000:
return "free"
if rpd_val is not None and rpd_val > 1000:
return "paid"
if resp.status_code == 429:
body_text = ""
try:
body_text = resp.text or ""
except Exception:
body_text = ""
if "free_tier" in body_text.lower():
return "free"
return "paid"
if 200 <= resp.status_code < 300:
return "paid"
return "unknown"
def is_free_tier_quota_error(error_message: str) -> bool:
"""Return True when a Gemini 429 message indicates free-tier exhaustion."""
if not error_message:
return False
return "free_tier" in error_message.lower()
_FREE_TIER_GUIDANCE = (
"\n\nYour Google API key is on the free tier (<= 250 requests/day for "
"gemini-2.5-flash). Hermes typically makes 3-10 API calls per user turn, "
"so the free tier is exhausted in a handful of messages and cannot sustain "
"an agent session. Enable billing on your Google Cloud project and "
"regenerate the key in a billing-enabled project: "
"https://aistudio.google.com/apikey"
)
class GeminiAPIError(Exception):
"""Error shape compatible with Hermes retry/error classification."""
@@ -741,12 +650,6 @@ def gemini_http_error(response: httpx.Response) -> GeminiAPIError:
else:
message = f"Gemini returned HTTP {status}: {body_text[:500]}"
# Free-tier quota exhaustion -> append actionable guidance so users who
# bypassed the setup wizard (direct GOOGLE_API_KEY in .env) still learn
# that the free tier cannot sustain an agent session.
if status == 429 and is_free_tier_quota_error(err_message or body_text):
message = message + _FREE_TIER_GUIDANCE
return GeminiAPIError(
message,
code=code,
@@ -801,13 +704,6 @@ class GeminiNativeClient:
http_client: Optional[httpx.Client] = None,
**_: Any,
) -> None:
if not (api_key or "").strip():
raise RuntimeError(
"Gemini native client requires an API key, but none was provided. "
"Set GOOGLE_API_KEY or GEMINI_API_KEY in your environment / ~/.hermes/.env "
"(get one at https://aistudio.google.com/app/apikey), or run `hermes setup` "
"to configure the Google provider."
)
self.api_key = api_key
normalized_base = (base_url or DEFAULT_GEMINI_BASE_URL).rstrip("/")
if normalized_base.endswith("/openai"):
+1 -15
View File
@@ -2,7 +2,7 @@
from __future__ import annotations
from typing import Any, Dict
from typing import Any, Dict, List
# Gemini's ``FunctionDeclaration.parameters`` field accepts the ``Schema``
# object, which is only a subset of OpenAPI 3.0 / JSON Schema. Strip fields
@@ -73,20 +73,6 @@ def sanitize_gemini_schema(schema: Any) -> Dict[str, Any]:
]
continue
cleaned[key] = value
# Gemini's Schema validator requires every ``enum`` entry to be a string,
# even when the parent ``type`` is ``integer`` / ``number`` / ``boolean``.
# OpenAI / OpenRouter / Anthropic accept typed enums (e.g. Discord's
# ``auto_archive_duration: {type: integer, enum: [60, 1440, 4320, 10080]}``),
# so we only drop the ``enum`` when it would collide with Gemini's rule.
# Keeping ``type: integer`` plus the human-readable description gives the
# model enough guidance; the tool handler still validates the value.
enum_val = cleaned.get("enum")
type_val = cleaned.get("type")
if isinstance(enum_val, list) and type_val in {"integer", "number", "boolean"}:
if any(not isinstance(item, str) for item in enum_val):
cleaned.pop("enum", None)
return cleaned
+1
View File
@@ -29,6 +29,7 @@ from __future__ import annotations
import json
import logging
import os
import time
import urllib.error
import urllib.parse
+3 -3
View File
@@ -49,13 +49,14 @@ import json
import logging
import os
import secrets
import socket
import stat
import threading
import time
import urllib.error
import urllib.parse
import urllib.request
from dataclasses import dataclass
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Dict, Optional, Tuple
@@ -97,7 +98,6 @@ _DEFAULT_CLIENT_SECRET = f"GOCSPX-{_PUBLIC_CLIENT_SECRET_SUFFIX}"
# Regex patterns for fallback scraping from an installed gemini-cli.
import re as _re
from utils import atomic_replace
_CLIENT_ID_PATTERN = _re.compile(
r"OAUTH_CLIENT_ID\s*=\s*['\"]([0-9]+-[a-z0-9]+\.apps\.googleusercontent\.com)['\"]"
)
@@ -499,7 +499,7 @@ def save_credentials(creds: GoogleCredentials) -> Path:
fh.flush()
os.fsync(fh.fileno())
os.chmod(tmp_path, stat.S_IRUSR | stat.S_IWUSR)
atomic_replace(tmp_path, path)
os.replace(tmp_path, path)
finally:
try:
if tmp_path.exists():
-242
View File
@@ -1,242 +0,0 @@
"""
Image Generation Provider ABC
=============================
Defines the pluggable-backend interface for image generation. Providers register
instances via ``PluginContext.register_image_gen_provider()``; the active one
(selected via ``image_gen.provider`` in ``config.yaml``) services every
``image_generate`` tool call.
Providers live in ``<repo>/plugins/image_gen/<name>/`` (built-in, auto-loaded
as ``kind: backend``) or ``~/.hermes/plugins/image_gen/<name>/`` (user, opt-in
via ``plugins.enabled``).
Response shape
--------------
All providers return a dict that :func:`success_response` / :func:`error_response`
produce. The tool wrapper JSON-serializes it. Keys:
success bool
image str | None URL or absolute file path
model str provider-specific model identifier
prompt str echoed prompt
aspect_ratio str "landscape" | "square" | "portrait"
provider str provider name (for diagnostics)
error str only when success=False
error_type str only when success=False
"""
from __future__ import annotations
import abc
import base64
import datetime
import logging
import uuid
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
VALID_ASPECT_RATIOS: Tuple[str, ...] = ("landscape", "square", "portrait")
DEFAULT_ASPECT_RATIO = "landscape"
# ---------------------------------------------------------------------------
# ABC
# ---------------------------------------------------------------------------
class ImageGenProvider(abc.ABC):
"""Abstract base class for an image generation backend.
Subclasses must implement :meth:`generate`. Everything else has sane
defaults override only what your provider needs.
"""
@property
@abc.abstractmethod
def name(self) -> str:
"""Stable short identifier used in ``image_gen.provider`` config.
Lowercase, no spaces. Examples: ``fal``, ``openai``, ``replicate``.
"""
@property
def display_name(self) -> str:
"""Human-readable label shown in ``hermes tools``. Defaults to ``name.title()``."""
return self.name.title()
def is_available(self) -> bool:
"""Return True when this provider can service calls.
Typically checks for a required API key. Default: True
(providers with no external dependencies are always available).
"""
return True
def list_models(self) -> List[Dict[str, Any]]:
"""Return catalog entries for ``hermes tools`` model picker.
Each entry::
{
"id": "gpt-image-1.5", # required
"display": "GPT Image 1.5", # optional; defaults to id
"speed": "~10s", # optional
"strengths": "...", # optional
"price": "$...", # optional
}
Default: empty list (provider has no user-selectable models).
"""
return []
def get_setup_schema(self) -> Dict[str, Any]:
"""Return provider metadata for the ``hermes tools`` picker.
Used by ``tools_config.py`` to inject this provider as a row in
the Image Generation provider list. Shape::
{
"name": "OpenAI", # picker label
"badge": "paid", # optional short tag
"tag": "One-line description...", # optional subtitle
"env_vars": [ # keys to prompt for
{"key": "OPENAI_API_KEY",
"prompt": "OpenAI API key",
"url": "https://platform.openai.com/api-keys"},
],
}
Default: minimal entry derived from ``display_name``. Override to
expose API key prompts and custom badges.
"""
return {
"name": self.display_name,
"badge": "",
"tag": "",
"env_vars": [],
}
def default_model(self) -> Optional[str]:
"""Return the default model id, or None if not applicable."""
models = self.list_models()
if models:
return models[0].get("id")
return None
@abc.abstractmethod
def generate(
self,
prompt: str,
aspect_ratio: str = DEFAULT_ASPECT_RATIO,
**kwargs: Any,
) -> Dict[str, Any]:
"""Generate an image.
Implementations should return the dict from :func:`success_response`
or :func:`error_response`. ``kwargs`` may contain forward-compat
parameters future versions of the schema will expose implementations
should ignore unknown keys.
"""
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def resolve_aspect_ratio(value: Optional[str]) -> str:
"""Clamp an aspect_ratio value to the valid set, defaulting to landscape.
Invalid values are coerced rather than rejected so the tool surface is
forgiving of agent mistakes.
"""
if not isinstance(value, str):
return DEFAULT_ASPECT_RATIO
v = value.strip().lower()
if v in VALID_ASPECT_RATIOS:
return v
return DEFAULT_ASPECT_RATIO
def _images_cache_dir() -> Path:
"""Return ``$HERMES_HOME/cache/images/``, creating parents as needed."""
from hermes_constants import get_hermes_home
path = get_hermes_home() / "cache" / "images"
path.mkdir(parents=True, exist_ok=True)
return path
def save_b64_image(
b64_data: str,
*,
prefix: str = "image",
extension: str = "png",
) -> Path:
"""Decode base64 image data and write it under ``$HERMES_HOME/cache/images/``.
Returns the absolute :class:`Path` to the saved file.
Filename format: ``<prefix>_<YYYYMMDD_HHMMSS>_<short-uuid>.<ext>``.
"""
raw = base64.b64decode(b64_data)
ts = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
short = uuid.uuid4().hex[:8]
path = _images_cache_dir() / f"{prefix}_{ts}_{short}.{extension}"
path.write_bytes(raw)
return path
def success_response(
*,
image: str,
model: str,
prompt: str,
aspect_ratio: str,
provider: str,
extra: Optional[Dict[str, Any]] = None,
) -> Dict[str, Any]:
"""Build a uniform success response dict.
``image`` may be an HTTP URL or an absolute filesystem path (for b64
providers like OpenAI). Callers that need to pass through additional
backend-specific fields can supply ``extra``.
"""
payload: Dict[str, Any] = {
"success": True,
"image": image,
"model": model,
"prompt": prompt,
"aspect_ratio": aspect_ratio,
"provider": provider,
}
if extra:
for k, v in extra.items():
payload.setdefault(k, v)
return payload
def error_response(
*,
error: str,
error_type: str = "provider_error",
provider: str = "",
model: str = "",
prompt: str = "",
aspect_ratio: str = DEFAULT_ASPECT_RATIO,
) -> Dict[str, Any]:
"""Build a uniform error response dict."""
return {
"success": False,
"image": None,
"error": error,
"error_type": error_type,
"model": model,
"prompt": prompt,
"aspect_ratio": aspect_ratio,
"provider": provider,
}
-120
View File
@@ -1,120 +0,0 @@
"""
Image Generation Provider Registry
==================================
Central map of registered providers. Populated by plugins at import-time via
``PluginContext.register_image_gen_provider()``; consumed by the
``image_generate`` tool to dispatch each call to the active backend.
Active selection
----------------
The active provider is chosen by ``image_gen.provider`` in ``config.yaml``.
If unset, :func:`get_active_provider` applies fallback logic:
1. If exactly one provider is registered, use it.
2. Otherwise if a provider named ``fal`` is registered, use it (legacy
default matches pre-plugin behavior).
3. Otherwise return ``None`` (the tool surfaces a helpful error pointing
the user at ``hermes tools``).
"""
from __future__ import annotations
import logging
import threading
from typing import Dict, List, Optional
from agent.image_gen_provider import ImageGenProvider
logger = logging.getLogger(__name__)
_providers: Dict[str, ImageGenProvider] = {}
_lock = threading.Lock()
def register_provider(provider: ImageGenProvider) -> None:
"""Register an image generation provider.
Re-registration (same ``name``) overwrites the previous entry and logs
a debug message this makes hot-reload scenarios (tests, dev loops)
behave predictably.
"""
if not isinstance(provider, ImageGenProvider):
raise TypeError(
f"register_provider() expects an ImageGenProvider instance, "
f"got {type(provider).__name__}"
)
name = provider.name
if not isinstance(name, str) or not name.strip():
raise ValueError("Image gen provider .name must be a non-empty string")
with _lock:
existing = _providers.get(name)
_providers[name] = provider
if existing is not None:
logger.debug("Image gen provider '%s' re-registered (was %r)", name, type(existing).__name__)
else:
logger.debug("Registered image gen provider '%s' (%s)", name, type(provider).__name__)
def list_providers() -> List[ImageGenProvider]:
"""Return all registered providers, sorted by name."""
with _lock:
items = list(_providers.values())
return sorted(items, key=lambda p: p.name)
def get_provider(name: str) -> Optional[ImageGenProvider]:
"""Return the provider registered under *name*, or None."""
if not isinstance(name, str):
return None
with _lock:
return _providers.get(name.strip())
def get_active_provider() -> Optional[ImageGenProvider]:
"""Resolve the currently-active provider.
Reads ``image_gen.provider`` from config.yaml; falls back per the
module docstring.
"""
configured: Optional[str] = None
try:
from hermes_cli.config import load_config
cfg = load_config()
section = cfg.get("image_gen") if isinstance(cfg, dict) else None
if isinstance(section, dict):
raw = section.get("provider")
if isinstance(raw, str) and raw.strip():
configured = raw.strip()
except Exception as exc:
logger.debug("Could not read image_gen.provider from config: %s", exc)
with _lock:
snapshot = dict(_providers)
if configured:
provider = snapshot.get(configured)
if provider is not None:
return provider
logger.debug(
"image_gen.provider='%s' configured but not registered; falling back",
configured,
)
# Fallback: single-provider case
if len(snapshot) == 1:
return next(iter(snapshot.values()))
# Fallback: prefer legacy FAL for backward compat
if "fal" in snapshot:
return snapshot["fal"]
return None
def _reset_for_tests() -> None:
"""Clear the registry. **Test-only.**"""
with _lock:
_providers.clear()
-236
View File
@@ -1,236 +0,0 @@
"""Routing helpers for inbound user-attached images.
Two modes:
native attach images as OpenAI-style ``image_url`` content parts on the
user turn. Provider adapters (Anthropic, Gemini, Bedrock, Codex,
OpenAI chat.completions) already translate these into their
vendor-specific multimodal formats.
text run ``vision_analyze`` on each image up-front and prepend the
description to the user's text. The model never sees the pixels;
it only sees a lossy text summary. This is the pre-existing
behaviour and still the right choice for non-vision models.
The decision is made once per message turn by :func:`decide_image_input_mode`.
It reads ``agent.image_input_mode`` from config.yaml (``auto`` | ``native``
| ``text``, default ``auto``) and the active model's capability metadata.
In ``auto`` mode:
- If the user has explicitly configured ``auxiliary.vision.provider``
(i.e. not ``auto`` and not empty), we assume they want the text pipeline
regardless of the main model they've opted in to a specific vision
backend for a reason (cost, quality, local-only, etc.).
- Otherwise, if the active model reports ``supports_vision=True`` in its
models.dev metadata, we attach natively.
- Otherwise (non-vision model, no explicit override), we fall back to text.
This keeps ``vision_analyze`` surfaced as a tool in every session skills
and agent flows that chain it (browser screenshots, deeper inspection of
URL-referenced images, style-gating loops) keep working. The routing only
affects *how user-attached images on the current turn* are presented to the
main model.
"""
from __future__ import annotations
import base64
import logging
import mimetypes
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
_VALID_MODES = frozenset({"auto", "native", "text"})
def _coerce_mode(raw: Any) -> str:
"""Normalize a config value into one of the valid modes."""
if not isinstance(raw, str):
return "auto"
val = raw.strip().lower()
if val in _VALID_MODES:
return val
return "auto"
def _explicit_aux_vision_override(cfg: Optional[Dict[str, Any]]) -> bool:
"""True when the user configured a specific auxiliary vision backend.
An explicit override means the user *wants* the text pipeline (they're
paying for a dedicated vision model), so we don't silently bypass it.
"""
if not isinstance(cfg, dict):
return False
aux = cfg.get("auxiliary") or {}
if not isinstance(aux, dict):
return False
vision = aux.get("vision") or {}
if not isinstance(vision, dict):
return False
provider = str(vision.get("provider") or "").strip().lower()
model = str(vision.get("model") or "").strip()
base_url = str(vision.get("base_url") or "").strip()
# "auto" / "" / blank = not explicit
if provider in ("", "auto") and not model and not base_url:
return False
return True
def _lookup_supports_vision(provider: str, model: str) -> Optional[bool]:
"""Return True/False if we can resolve caps, None if unknown."""
if not provider or not model:
return None
try:
from agent.models_dev import get_model_capabilities
caps = get_model_capabilities(provider, model)
except Exception as exc: # pragma: no cover - defensive
logger.debug("image_routing: caps lookup failed for %s:%s%s", provider, model, exc)
return None
if caps is None:
return None
return bool(caps.supports_vision)
def decide_image_input_mode(
provider: str,
model: str,
cfg: Optional[Dict[str, Any]],
) -> str:
"""Return ``"native"`` or ``"text"`` for the given turn.
Args:
provider: active inference provider ID (e.g. ``"anthropic"``, ``"openrouter"``).
model: active model slug as it would be sent to the provider.
cfg: loaded config.yaml dict, or None. When None, behaves as auto.
"""
mode_cfg = "auto"
if isinstance(cfg, dict):
agent_cfg = cfg.get("agent") or {}
if isinstance(agent_cfg, dict):
mode_cfg = _coerce_mode(agent_cfg.get("image_input_mode"))
if mode_cfg == "native":
return "native"
if mode_cfg == "text":
return "text"
# auto
if _explicit_aux_vision_override(cfg):
return "text"
supports = _lookup_supports_vision(provider, model)
if supports is True:
return "native"
return "text"
# Image size handling is REACTIVE rather than proactive: we attempt native
# attachment at full size regardless of provider, and rely on
# ``run_agent._try_shrink_image_parts_in_messages`` to shrink + retry if
# the provider rejects the request (e.g. Anthropic's hard 5 MB per-image
# ceiling returned as HTTP 400 "image exceeds 5 MB maximum").
#
# Why reactive: our knowledge of provider ceilings is partial and evolving
# (OpenAI accepts 49 MB+, Anthropic 5 MB, Gemini 100 MB, others unknown).
# A proactive per-provider table would be stale the moment a provider raises
# or lowers its limit, and silently degrading quality for users on providers
# that would have accepted the full image is the worse failure mode.
# The shrink-on-reject path loses 1 API call + maybe 1s of Pillow work when
# it fires, which is cheaper than permanent quality loss.
def _guess_mime(path: Path) -> str:
mime, _ = mimetypes.guess_type(str(path))
if mime and mime.startswith("image/"):
return mime
# mimetypes on some Linux distros mis-maps .jpg; default to jpeg when
# the suffix looks imagey.
suffix = path.suffix.lower()
return {
".jpg": "image/jpeg",
".jpeg": "image/jpeg",
".png": "image/png",
".gif": "image/gif",
".webp": "image/webp",
".bmp": "image/bmp",
}.get(suffix, "image/jpeg")
def _file_to_data_url(path: Path) -> Optional[str]:
"""Encode a local image as a base64 data URL at its native size.
Size limits are NOT enforced here the agent retry loop
(``run_agent._try_shrink_image_parts_in_messages``) shrinks on the
provider's first rejection. Keeping this simple means providers that
accept large images (OpenAI 49 MB+, Gemini 100 MB) don't pay a silent
quality tax just because one other provider is stricter.
Returns None only if the file can't be read (missing, permission
denied, etc.); the caller reports those paths in ``skipped``.
"""
try:
raw = path.read_bytes()
except Exception as exc:
logger.warning("image_routing: failed to read %s%s", path, exc)
return None
mime = _guess_mime(path)
b64 = base64.b64encode(raw).decode("ascii")
return f"data:{mime};base64,{b64}"
def build_native_content_parts(
user_text: str,
image_paths: List[str],
) -> Tuple[List[Dict[str, Any]], List[str]]:
"""Build an OpenAI-style ``content`` list for a user turn.
Shape:
[{"type": "text", "text": "..."},
{"type": "image_url", "image_url": {"url": "data:image/png;base64,..."}},
...]
Images are attached at their native size. If a provider rejects the
request because an image is too large (e.g. Anthropic's 5 MB per-image
ceiling), the agent's retry loop transparently shrinks and retries
once see ``run_agent._try_shrink_image_parts_in_messages``.
Returns (content_parts, skipped_paths). Skipped paths are files that
couldn't be read from disk.
"""
parts: List[Dict[str, Any]] = []
skipped: List[str] = []
text = (user_text or "").strip()
if text:
parts.append({"type": "text", "text": text})
for raw_path in image_paths:
p = Path(raw_path)
if not p.exists() or not p.is_file():
skipped.append(str(raw_path))
continue
data_url = _file_to_data_url(p)
if not data_url:
skipped.append(str(raw_path))
continue
parts.append({
"type": "image_url",
"image_url": {"url": data_url},
})
# If the text was empty, add a neutral prompt so the turn isn't just images.
if not text and any(p.get("type") == "image_url" for p in parts):
parts.insert(0, {"type": "text", "text": "What do you see in this image?"})
return parts, skipped
__all__ = [
"decide_image_input_mode",
"build_native_content_parts",
]
-48
View File
@@ -1,48 +0,0 @@
"""LM Studio reasoning-effort resolution shared by the chat-completions
transport and run_agent's iteration-limit summary path.
LM Studio publishes per-model ``capabilities.reasoning.allowed_options`` (e.g.
``["off","on"]`` for toggle-style models, ``["off","minimal","low"]`` for
graduated models). We map the user's ``reasoning_config`` onto LM Studio's
OpenAI-compatible vocabulary, then clamp against the model's allowed set so
the server doesn't 400 on an unsupported effort.
"""
from __future__ import annotations
from typing import List, Optional
# LM Studio accepts these top-level reasoning_effort values via its
# OpenAI-compatible chat.completions endpoint.
_LM_VALID_EFFORTS = {"none", "minimal", "low", "medium", "high", "xhigh"}
# Toggle-style models publish allowed_options as ["off","on"] in /api/v1/models.
# Map them onto the OpenAI-compatible request vocabulary.
_LM_EFFORT_ALIASES = {"off": "none", "on": "medium"}
def resolve_lmstudio_effort(
reasoning_config: Optional[dict],
allowed_options: Optional[List[str]],
) -> Optional[str]:
"""Return the ``reasoning_effort`` string to send to LM Studio, or ``None``.
``None`` means "omit the field": the user picked a level the model can't
honor, so let LM Studio fall back to the model's declared default rather
than silently substituting a different effort. When ``allowed_options`` is
falsy (probe failed), skip clamping and send the resolved effort anyway.
"""
effort = "medium"
if reasoning_config and isinstance(reasoning_config, dict):
if reasoning_config.get("enabled") is False:
effort = "none"
else:
raw = (reasoning_config.get("effort") or "").strip().lower()
raw = _LM_EFFORT_ALIASES.get(raw, raw)
if raw in _LM_VALID_EFFORTS:
effort = raw
if allowed_options:
allowed = {_LM_EFFORT_ALIASES.get(opt, opt) for opt in allowed_options}
if effort not in allowed:
return None
return effort
+5 -5
View File
@@ -20,25 +20,25 @@ def summarize_manual_compression(
headline = f"No changes from compression: {before_count} messages"
if after_tokens == before_tokens:
token_line = (
f"Approx request size: ~{before_tokens:,} tokens (unchanged)"
f"Rough transcript estimate: ~{before_tokens:,} tokens (unchanged)"
)
else:
token_line = (
f"Approx request size: ~{before_tokens:,}"
f"Rough transcript estimate: ~{before_tokens:,}"
f"~{after_tokens:,} tokens"
)
else:
headline = f"Compressed: {before_count}{after_count} messages"
token_line = (
f"Approx request size: ~{before_tokens:,}"
f"Rough transcript estimate: ~{before_tokens:,}"
f"~{after_tokens:,} tokens"
)
note = None
if not noop and after_count < before_count and after_tokens > before_tokens:
note = (
"Note: fewer messages can still raise this estimate when "
"compression rewrites the transcript into denser summaries."
"Note: fewer messages can still raise this rough transcript estimate "
"when compression rewrites the transcript into denser summaries."
)
return {
+8 -192
View File
@@ -28,9 +28,9 @@ Usage in run_agent.py:
from __future__ import annotations
import json
import logging
import re
import inspect
from typing import Any, Dict, List, Optional
from agent.memory_provider import MemoryProvider
@@ -62,124 +62,15 @@ def sanitize_context(text: str) -> str:
return text
class StreamingContextScrubber:
"""Stateful scrubber for streaming text that may contain split memory-context spans.
The one-shot ``sanitize_context`` regex cannot survive chunk boundaries:
a ``<memory-context>`` opened in one delta and closed in a later delta
leaks its payload to the UI because the non-greedy block regex needs
both tags in one string. This scrubber runs a small state machine
across deltas, holding back partial-tag tails and discarding
everything inside a span (including the system-note line).
Usage::
scrubber = StreamingContextScrubber()
for delta in stream:
visible = scrubber.feed(delta)
if visible:
emit(visible)
trailing = scrubber.flush() # at end of stream
if trailing:
emit(trailing)
The scrubber is re-entrant per agent instance. Callers building new
top-level responses (new turn) should create a fresh scrubber or call
``reset()``.
"""
_OPEN_TAG = "<memory-context>"
_CLOSE_TAG = "</memory-context>"
def __init__(self) -> None:
self._in_span: bool = False
self._buf: str = ""
def reset(self) -> None:
self._in_span = False
self._buf = ""
def feed(self, text: str) -> str:
"""Return the visible portion of ``text`` after scrubbing.
Any trailing fragment that could be the start of an open/close tag
is held back in the internal buffer and surfaced on the next
``feed()`` call or discarded/emitted by ``flush()``.
"""
if not text:
return ""
buf = self._buf + text
self._buf = ""
out: list[str] = []
while buf:
if self._in_span:
idx = buf.lower().find(self._CLOSE_TAG)
if idx == -1:
# Hold back a potential partial close tag; drop the rest
held = self._max_partial_suffix(buf, self._CLOSE_TAG)
self._buf = buf[-held:] if held else ""
return "".join(out)
# Found close — skip span content + tag, continue
buf = buf[idx + len(self._CLOSE_TAG):]
self._in_span = False
else:
idx = buf.lower().find(self._OPEN_TAG)
if idx == -1:
# No open tag — hold back a potential partial open tag
held = self._max_partial_suffix(buf, self._OPEN_TAG)
if held:
out.append(buf[:-held])
self._buf = buf[-held:]
else:
out.append(buf)
return "".join(out)
# Emit text before the tag, enter span
if idx > 0:
out.append(buf[:idx])
buf = buf[idx + len(self._OPEN_TAG):]
self._in_span = True
return "".join(out)
def flush(self) -> str:
"""Emit any held-back buffer at end-of-stream.
If we're still inside an unterminated span the remaining content is
discarded (safer: leaking partial memory context is worse than a
truncated answer). Otherwise the held-back partial-tag tail is
emitted verbatim (it turned out not to be a real tag).
"""
if self._in_span:
self._buf = ""
self._in_span = False
return ""
tail = self._buf
self._buf = ""
return tail
@staticmethod
def _max_partial_suffix(buf: str, tag: str) -> int:
"""Return the length of the longest buf-suffix that is a tag-prefix.
Case-insensitive. Returns 0 if no suffix could start the tag.
"""
tag_lower = tag.lower()
buf_lower = buf.lower()
max_check = min(len(buf_lower), len(tag_lower) - 1)
for i in range(max_check, 0, -1):
if tag_lower.startswith(buf_lower[-i:]):
return i
return 0
def build_memory_context_block(raw_context: str) -> str:
"""Wrap prefetched memory in a fenced block with system note."""
"""Wrap prefetched memory in a fenced block with system note.
The fence prevents the model from treating recalled context as user
discourse. Injected at API-call time only never persisted.
"""
if not raw_context or not raw_context.strip():
return ""
clean = sanitize_context(raw_context)
if clean != raw_context:
logger.warning("memory provider returned pre-wrapped context; stripped")
return (
"<memory-context>\n"
"[System note: The following is recalled memory context, "
@@ -402,41 +293,6 @@ class MemoryManager:
provider.name, e,
)
def on_session_switch(
self,
new_session_id: str,
*,
parent_session_id: str = "",
reset: bool = False,
**kwargs,
) -> None:
"""Notify all providers that the agent's session_id has rotated.
Fires on ``/resume``, ``/branch``, ``/reset``, ``/new``, and
context compression any path that reassigns
``AIAgent.session_id`` without tearing the provider down.
Providers keep running; they only need to refresh cached
per-session state so subsequent writes land in the correct
session's record. See ``MemoryProvider.on_session_switch`` for
the full contract.
"""
if not new_session_id:
return
for provider in self._providers:
try:
provider.on_session_switch(
new_session_id,
parent_session_id=parent_session_id,
reset=reset,
**kwargs,
)
except Exception as e:
logger.debug(
"Memory provider '%s' on_session_switch failed: %s",
provider.name, e,
)
def on_pre_compress(self, messages: List[Dict[str, Any]]) -> str:
"""Notify all providers before context compression.
@@ -456,39 +312,7 @@ class MemoryManager:
)
return "\n\n".join(parts)
@staticmethod
def _provider_memory_write_metadata_mode(provider: MemoryProvider) -> str:
"""Return how to pass metadata to a provider's memory-write hook."""
try:
signature = inspect.signature(provider.on_memory_write)
except (TypeError, ValueError):
return "keyword"
params = list(signature.parameters.values())
if any(p.kind == inspect.Parameter.VAR_KEYWORD for p in params):
return "keyword"
if "metadata" in signature.parameters:
return "keyword"
accepted = [
p for p in params
if p.kind in (
inspect.Parameter.POSITIONAL_ONLY,
inspect.Parameter.POSITIONAL_OR_KEYWORD,
inspect.Parameter.KEYWORD_ONLY,
)
]
if len(accepted) >= 4:
return "positional"
return "legacy"
def on_memory_write(
self,
action: str,
target: str,
content: str,
metadata: Optional[Dict[str, Any]] = None,
) -> None:
def on_memory_write(self, action: str, target: str, content: str) -> None:
"""Notify external providers when the built-in memory tool writes.
Skips the builtin provider itself (it's the source of the write).
@@ -497,15 +321,7 @@ class MemoryManager:
if provider.name == "builtin":
continue
try:
metadata_mode = self._provider_memory_write_metadata_mode(provider)
if metadata_mode == "keyword":
provider.on_memory_write(
action, target, content, metadata=dict(metadata or {})
)
elif metadata_mode == "positional":
provider.on_memory_write(action, target, content, dict(metadata or {}))
else:
provider.on_memory_write(action, target, content)
provider.on_memory_write(action, target, content)
except Exception as e:
logger.debug(
"Memory provider '%s' on_memory_write failed: %s",
+3 -52
View File
@@ -25,9 +25,8 @@ Lifecycle (called by MemoryManager, wired in run_agent.py):
Optional hooks (override to opt in):
on_turn_start(turn, message, **kwargs) per-turn tick with runtime context
on_session_end(messages) end-of-session extraction
on_session_switch(new_session_id, **kwargs) mid-process session_id rotation
on_pre_compress(messages) -> str extract before context compression
on_memory_write(action, target, content, metadata=None) mirror built-in memory writes
on_memory_write(action, target, content) mirror built-in memory writes
on_delegation(task, result, **kwargs) parent-side observation of subagent work
"""
@@ -35,7 +34,7 @@ from __future__ import annotations
import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
from typing import Any, Dict, List
logger = logging.getLogger(__name__)
@@ -161,45 +160,6 @@ class MemoryProvider(ABC):
(CLI exit, /reset, gateway session expiry).
"""
def on_session_switch(
self,
new_session_id: str,
*,
parent_session_id: str = "",
reset: bool = False,
**kwargs,
) -> None:
"""Called when the agent switches session_id mid-process.
Fires on ``/resume``, ``/branch``, ``/reset``, ``/new`` (CLI), the
gateway equivalents, and context compression any path that
reassigns ``AIAgent.session_id`` without tearing the provider down.
Providers that cache per-session state in ``initialize()``
(``_session_id``, ``_document_id``, accumulated turn buffers,
counters) should update or reset that state here so subsequent
writes land in the correct session's record.
Parameters
----------
new_session_id:
The session_id the agent just switched to.
parent_session_id:
The previous session_id, if meaningful set for ``/branch``
(fork lineage), context compression (continuation lineage),
and ``/resume`` (the session we're leaving). Empty string
when no lineage applies.
reset:
``True`` when this is a genuinely new conversation, not a
resumption of an existing one. Fired by ``/reset`` / ``/new``.
Providers should flush accumulated per-session buffers
(``_session_turns``, ``_turn_counter``, etc.) when this is
set. ``False`` for ``/resume`` / ``/branch`` / compression
where the logical conversation continues under the new id.
Default is no-op for backward compatibility.
"""
def on_pre_compress(self, messages: List[Dict[str, Any]]) -> str:
"""Called before context compression discards old messages.
@@ -260,21 +220,12 @@ class MemoryProvider(ABC):
should all have ``env_var`` set and this method stays no-op).
"""
def on_memory_write(
self,
action: str,
target: str,
content: str,
metadata: Optional[Dict[str, Any]] = None,
) -> None:
def on_memory_write(self, action: str, target: str, content: str) -> None:
"""Called when the built-in memory tool writes an entry.
action: 'add', 'replace', or 'remove'
target: 'memory' or 'user'
content: the entry content
metadata: structured provenance for the write, when available. Common
keys include ``write_origin``, ``execution_context``, ``session_id``,
``parent_session_id``, ``platform``, and ``tool_name``.
Use to mirror built-in memory writes to your backend.
"""
+60 -341
View File
@@ -4,9 +4,7 @@ Pure utility functions with no AIAgent dependency. Used by ContextCompressor
and run_agent.py for pre-flight context checks.
"""
import ipaddress
import logging
import os
import re
import time
from pathlib import Path
@@ -22,48 +20,25 @@ from hermes_constants import OPENROUTER_MODELS_URL
logger = logging.getLogger(__name__)
def _resolve_requests_verify() -> bool | str:
"""Resolve SSL verify setting for `requests` calls from env vars.
The `requests` library only honours REQUESTS_CA_BUNDLE / CURL_CA_BUNDLE
by default. Hermes also honours HERMES_CA_BUNDLE (its own convention)
and SSL_CERT_FILE (used by the stdlib `ssl` module and by httpx), so
that a single env var can cover both `requests` and `httpx` callsites
inside the same process.
Returns either a filesystem path to a CA bundle, or True to defer to
the requests default (certifi).
"""
for env_var in ("HERMES_CA_BUNDLE", "REQUESTS_CA_BUNDLE", "SSL_CERT_FILE"):
val = os.getenv(env_var)
if val and os.path.isfile(val):
return val
return True
# Provider names that can appear as a "provider:" prefix before a model ID.
# Only these are stripped — Ollama-style "model:tag" colons (e.g. "qwen3.5:27b")
# are preserved so the full model name reaches cache lookups and server queries.
_PROVIDER_PREFIXES: frozenset[str] = frozenset({
"openrouter", "nous", "openai-codex", "copilot", "copilot-acp",
"gemini", "ollama-cloud", "zai", "kimi-coding", "kimi-coding-cn", "stepfun", "minimax", "minimax-oauth", "minimax-cn", "anthropic", "deepseek",
"gemini", "ollama-cloud", "zai", "kimi-coding", "kimi-coding-cn", "minimax", "minimax-cn", "anthropic", "deepseek",
"opencode-zen", "opencode-go", "ai-gateway", "kilocode", "alibaba",
"qwen-oauth",
"xiaomi",
"arcee",
"gmi",
"tencent-tokenhub",
"custom", "local",
# Common aliases
"google", "google-gemini", "google-ai-studio",
"glm", "z-ai", "z.ai", "zhipu", "github", "github-copilot",
"github-models", "kimi", "moonshot", "kimi-cn", "moonshot-cn", "claude", "deep-seek",
"ollama",
"stepfun", "opencode", "zen", "go", "vercel", "kilo", "dashscope", "aliyun", "qwen",
"opencode", "zen", "go", "vercel", "kilo", "dashscope", "aliyun", "qwen",
"mimo", "xiaomi-mimo",
"tencent", "tokenhub", "tencent-cloud", "tencentmaas",
"arcee-ai", "arceeai",
"gmi-cloud", "gmicloud",
"xai", "x-ai", "x.ai", "grok",
"nvidia", "nim", "nvidia-nim", "nemotron",
"qwen-portal",
@@ -76,13 +51,6 @@ _OLLAMA_TAG_PATTERN = re.compile(
)
# Tailscale's CGNAT range (RFC 6598). `ipaddress.is_private` excludes this
# block, so without an explicit check Ollama reached over Tailscale (e.g.
# `http://100.77.243.5:11434`) wouldn't be treated as local and its stream
# read / stale timeouts wouldn't get auto-bumped. Built once at import time.
_TAILSCALE_CGNAT = ipaddress.IPv4Network("100.64.0.0/10")
def _strip_provider_prefix(model: str) -> str:
"""Strip a recognised provider prefix from a model string.
@@ -110,11 +78,9 @@ _endpoint_model_metadata_cache_time: Dict[str, float] = {}
_ENDPOINT_MODEL_CACHE_TTL = 300
# Descending tiers for context length probing when the model is unknown.
# We start at 256K (covers GPT-5.x, many current large-context models) and
# step down on context-length errors until one works. Tier[0] is also the
# default fallback when no detection method succeeds.
# We start at 128K (a safe default for most modern models) and step down
# on context-length errors until one works.
CONTEXT_PROBE_TIERS = [
256_000,
128_000,
64_000,
32_000,
@@ -149,11 +115,6 @@ DEFAULT_CONTEXT_LENGTHS = {
"claude": 200000,
# OpenAI — GPT-5 family (most have 400k; specific overrides first)
# Source: https://developers.openai.com/api/docs/models
# GPT-5.5 (launched Apr 23 2026) is 1.05M on the direct OpenAI API and
# ChatGPT Codex OAuth caps it at 272K; both paths resolve via their own
# provider-aware branches (_resolve_codex_oauth_context_length + models.dev).
# This hardcoded value is only reached when every probe misses.
"gpt-5.5": 1050000,
"gpt-5.4-nano": 400000, # 400k (not 1.05M like full 5.4)
"gpt-5.4-mini": 400000, # 400k (not 1.05M like full 5.4)
"gpt-5.4": 1050000, # GPT-5.4, GPT-5.4 Pro (1.05M context)
@@ -164,22 +125,10 @@ DEFAULT_CONTEXT_LENGTHS = {
# Google
"gemini": 1048576,
# Gemma (open models served via AI Studio)
"gemma-4": 256000, # Gemma 4 family
"gemma4": 256000, # Ollama-style naming (e.g. gemma4:31b-cloud)
"gemma-4-31b": 256000,
"gemma-3": 131072,
"gemma": 8192, # fallback for older gemma models
# DeepSeek — V4 family ships with a 1M context window. The legacy
# aliases ``deepseek-chat`` / ``deepseek-reasoner`` are server-side
# mapped to the non-thinking / thinking modes of ``deepseek-v4-flash``
# and inherit the same 1M window. The ``deepseek`` substring entry
# below remains as a 128K fallback for older / unknown DeepSeek model
# ids (e.g. via custom endpoints).
# https://api-docs.deepseek.com/zh-cn/quick_start/pricing
"deepseek-v4-pro": 1_000_000,
"deepseek-v4-flash": 1_000_000,
"deepseek-chat": 1_000_000,
"deepseek-reasoner": 1_000_000,
# DeepSeek
"deepseek": 128000,
# Meta
"llama": 131072,
@@ -210,8 +159,6 @@ DEFAULT_CONTEXT_LENGTHS = {
"grok": 131072, # catch-all (grok-beta, unknown grok-*)
# Kimi
"kimi": 262144,
# Tencent — Hy3 Preview (Hunyuan) with 256K context window
"hy3-preview": 256000,
# Nemotron — NVIDIA's open-weights series (128K context across all sizes)
"nemotron": 131072,
# Arcee
@@ -226,12 +173,10 @@ DEFAULT_CONTEXT_LENGTHS = {
"moonshotai/Kimi-K2.6": 262144,
"moonshotai/Kimi-K2-Thinking": 262144,
"MiniMaxAI/MiniMax-M2.5": 204800,
"XiaomiMiMo/MiMo-V2-Flash": 262144,
"mimo-v2-pro": 1048576,
"mimo-v2.5-pro": 1048576,
"mimo-v2.5": 1048576,
"mimo-v2-omni": 262144,
"mimo-v2-flash": 262144,
"XiaomiMiMo/MiMo-V2-Flash": 256000,
"mimo-v2-pro": 1000000,
"mimo-v2-omni": 256000,
"mimo-v2-flash": 256000,
"zai-org/GLM-5": 202752,
}
@@ -246,7 +191,6 @@ _CONTEXT_LENGTH_KEYS = (
"max_seq_len",
"n_ctx_train",
"n_ctx",
"ctx_size",
)
_MAX_COMPLETION_KEYS = (
@@ -290,12 +234,9 @@ _URL_TO_PROVIDER: Dict[str, str] = {
"chatgpt.com": "openai",
"api.anthropic.com": "anthropic",
"api.z.ai": "zai",
"open.bigmodel.cn": "zai",
"api.moonshot.ai": "kimi-coding",
"api.moonshot.cn": "kimi-coding-cn",
"api.kimi.com": "kimi-coding",
"api.stepfun.ai": "stepfun",
"api.stepfun.com": "stepfun",
"api.arcee.ai": "arcee",
"api.minimax": "minimax",
"dashscope.aliyuncs.com": "alibaba",
@@ -313,8 +254,6 @@ _URL_TO_PROVIDER: Dict[str, str] = {
"integrate.api.nvidia.com": "nvidia",
"api.xiaomimimo.com": "xiaomi",
"xiaomimimo.com": "xiaomi",
"api.gmi-serving.com": "gmi",
"tokenhub.tencentmaas.com": "tencent-tokenhub",
"ollama.com": "ollama-cloud",
}
@@ -342,15 +281,7 @@ def _is_known_provider_base_url(base_url: str) -> bool:
def is_local_endpoint(base_url: str) -> bool:
"""Return True if base_url points to a local machine.
Recognises loopback (``localhost``, ``127.0.0.0/8``, ``::1``),
container-internal DNS names (``host.docker.internal`` et al.),
RFC-1918 private ranges (``10/8``, ``172.16/12``, ``192.168/16``),
link-local, and Tailscale CGNAT (``100.64.0.0/10``). Tailscale CGNAT
is included so remote-but-trusted Ollama boxes reached over a
Tailscale mesh get the same timeout auto-bumps as localhost Ollama.
"""
"""Return True if base_url points to a local machine (localhost / RFC-1918 / WSL)."""
normalized = _normalize_base_url(base_url)
if not normalized:
return False
@@ -365,17 +296,14 @@ def is_local_endpoint(base_url: str) -> bool:
# Docker / Podman / Lima internal DNS names (e.g. host.docker.internal)
if any(host.endswith(suffix) for suffix in _CONTAINER_LOCAL_SUFFIXES):
return True
# RFC-1918 private ranges, link-local, and Tailscale CGNAT
# RFC-1918 private ranges and link-local
import ipaddress
try:
addr = ipaddress.ip_address(host)
if addr.is_private or addr.is_loopback or addr.is_link_local:
return True
if isinstance(addr, ipaddress.IPv4Address) and addr in _TAILSCALE_CGNAT:
return True
return addr.is_private or addr.is_loopback or addr.is_link_local
except ValueError:
pass
# Bare IP that looks like a private range (e.g. 172.26.x.x for WSL)
# or Tailscale CGNAT (100.64.x.x100.127.x.x).
parts = host.split(".")
if len(parts) == 4:
try:
@@ -386,8 +314,6 @@ def is_local_endpoint(base_url: str) -> bool:
return True
if first == 192 and second == 168:
return True
if first == 100 and 64 <= second <= 127:
return True
except ValueError:
pass
return False
@@ -536,7 +462,7 @@ def fetch_model_metadata(force_refresh: bool = False) -> Dict[str, Dict[str, Any
return _model_metadata_cache
try:
response = requests.get(OPENROUTER_MODELS_URL, timeout=10, verify=_resolve_requests_verify())
response = requests.get(OPENROUTER_MODELS_URL, timeout=10)
response.raise_for_status()
data = response.json()
@@ -603,7 +529,6 @@ def fetch_endpoint_model_metadata(
server_url.rstrip("/") + "/api/v1/models",
headers=headers,
timeout=10,
verify=_resolve_requests_verify(),
)
response.raise_for_status()
payload = response.json()
@@ -625,6 +550,8 @@ def fetch_endpoint_model_metadata(
if isinstance(ctx, int) and ctx > 0:
context_length = ctx
break
if context_length is None:
context_length = _extract_context_length(model)
if context_length is not None:
entry["context_length"] = context_length
@@ -650,7 +577,7 @@ def fetch_endpoint_model_metadata(
for candidate in candidates:
url = candidate.rstrip("/") + "/models"
try:
response = requests.get(url, headers=headers, timeout=10, verify=_resolve_requests_verify())
response = requests.get(url, headers=headers, timeout=10)
response.raise_for_status()
payload = response.json()
cache: Dict[str, Dict[str, Any]] = {}
@@ -681,10 +608,9 @@ def fetch_endpoint_model_metadata(
try:
# Try /v1/props first (current llama.cpp); fall back to /props for older builds
base = candidate.rstrip("/").replace("/v1", "")
_verify = _resolve_requests_verify()
props_resp = requests.get(base + "/v1/props", headers=headers, timeout=5, verify=_verify)
props_resp = requests.get(base + "/v1/props", headers=headers, timeout=5)
if not props_resp.ok:
props_resp = requests.get(base + "/props", headers=headers, timeout=5, verify=_verify)
props_resp = requests.get(base + "/props", headers=headers, timeout=5)
if props_resp.ok:
props = props_resp.json()
gen_settings = props.get("default_generation_settings", {})
@@ -708,29 +634,6 @@ def fetch_endpoint_model_metadata(
return {}
def _resolve_endpoint_context_length(
model: str,
base_url: str,
api_key: str = "",
) -> Optional[int]:
"""Resolve context length from an endpoint's live ``/models`` metadata."""
endpoint_metadata = fetch_endpoint_model_metadata(base_url, api_key=api_key)
matched = endpoint_metadata.get(model)
if not matched:
if len(endpoint_metadata) == 1:
matched = next(iter(endpoint_metadata.values()))
else:
for key, entry in endpoint_metadata.items():
if model in key or key in model:
matched = entry
break
if matched:
context_length = matched.get("context_length")
if isinstance(context_length, int):
return context_length
return None
def _get_context_cache_path() -> Path:
"""Return path to the persistent context length cache file."""
from hermes_constants import get_hermes_home
@@ -779,22 +682,6 @@ def get_cached_context_length(model: str, base_url: str) -> Optional[int]:
return cache.get(key)
def _invalidate_cached_context_length(model: str, base_url: str) -> None:
"""Drop a stale cache entry so it gets re-resolved on the next lookup."""
key = f"{model}@{base_url}"
cache = _load_context_cache()
if key not in cache:
return
del cache[key]
path = _get_context_cache_path()
try:
path.parent.mkdir(parents=True, exist_ok=True)
with open(path, "w") as f:
yaml.dump({"context_lengths": cache}, f, default_flow_style=False)
except Exception as e:
logger.debug("Failed to invalidate context length cache entry %s: %s", key, e)
def get_next_probe_tier(current_length: int) -> Optional[int]:
"""Return the next lower probe tier, or None if already at minimum."""
for tier in CONTEXT_PROBE_TIERS:
@@ -1014,7 +901,10 @@ def _query_local_context_length(model: str, base_url: str, api_key: str = "") ->
ctx = cfg.get("context_length")
if ctx and isinstance(ctx, (int, float)):
return int(ctx)
break
# Fall back to max_context_length (theoretical model max)
ctx = m.get("max_context_length") or m.get("context_length")
if ctx and isinstance(ctx, (int, float)):
return int(ctx)
# LM Studio / vLLM / llama.cpp: try /v1/models/{model}
resp = client.get(f"{server_url}/v1/models/{model}")
@@ -1069,7 +959,7 @@ def _query_anthropic_context_length(model: str, base_url: str, api_key: str) ->
"x-api-key": api_key,
"anthropic-version": "2023-06-01",
}
resp = requests.get(url, headers=headers, timeout=10, verify=_resolve_requests_verify())
resp = requests.get(url, headers=headers, timeout=10)
if resp.status_code != 200:
return None
data = resp.json()
@@ -1083,116 +973,6 @@ def _query_anthropic_context_length(model: str, base_url: str, api_key: str) ->
return None
# Known ChatGPT Codex OAuth context windows (observed via live
# chatgpt.com/backend-api/codex/models probe, Apr 2026). These are the
# `context_window` values, which are what Codex actually enforces — the
# direct OpenAI API has larger limits for the same slugs, but Codex OAuth
# caps lower (e.g. gpt-5.5 is 1.05M on the API, 272K on Codex).
#
# Used as a fallback when the live probe fails (no token, network error).
# Longest keys first so substring match picks the most specific entry.
_CODEX_OAUTH_CONTEXT_FALLBACK: Dict[str, int] = {
"gpt-5.1-codex-max": 272_000,
"gpt-5.1-codex-mini": 272_000,
"gpt-5.3-codex": 272_000,
"gpt-5.2-codex": 272_000,
"gpt-5.4-mini": 272_000,
"gpt-5.5": 272_000,
"gpt-5.4": 272_000,
"gpt-5.2": 272_000,
"gpt-5": 272_000,
}
_codex_oauth_context_cache: Dict[str, int] = {}
_codex_oauth_context_cache_time: float = 0.0
_CODEX_OAUTH_CONTEXT_CACHE_TTL = 3600 # 1 hour
def _fetch_codex_oauth_context_lengths(access_token: str) -> Dict[str, int]:
"""Probe the ChatGPT Codex /models endpoint for per-slug context windows.
Codex OAuth imposes its own context limits that differ from the direct
OpenAI API (e.g. gpt-5.5 is 1.05M on the API, 272K on Codex). The
`context_window` field in each model entry is the authoritative source.
Returns a ``{slug: context_window}`` dict. Empty on failure.
"""
global _codex_oauth_context_cache, _codex_oauth_context_cache_time
now = time.time()
if (
_codex_oauth_context_cache
and now - _codex_oauth_context_cache_time < _CODEX_OAUTH_CONTEXT_CACHE_TTL
):
return _codex_oauth_context_cache
try:
resp = requests.get(
"https://chatgpt.com/backend-api/codex/models?client_version=1.0.0",
headers={"Authorization": f"Bearer {access_token}"},
timeout=10,
verify=_resolve_requests_verify(),
)
if resp.status_code != 200:
logger.debug(
"Codex /models probe returned HTTP %s; falling back to hardcoded defaults",
resp.status_code,
)
return {}
data = resp.json()
except Exception as exc:
logger.debug("Codex /models probe failed: %s", exc)
return {}
entries = data.get("models", []) if isinstance(data, dict) else []
result: Dict[str, int] = {}
for item in entries:
if not isinstance(item, dict):
continue
slug = item.get("slug")
ctx = item.get("context_window")
if isinstance(slug, str) and isinstance(ctx, int) and ctx > 0:
result[slug.strip()] = ctx
if result:
_codex_oauth_context_cache = result
_codex_oauth_context_cache_time = now
return result
def _resolve_codex_oauth_context_length(
model: str, access_token: str = ""
) -> Optional[int]:
"""Resolve a Codex OAuth model's real context window.
Prefers a live probe of chatgpt.com/backend-api/codex/models (when we
have a bearer token), then falls back to ``_CODEX_OAUTH_CONTEXT_FALLBACK``.
"""
model_bare = _strip_provider_prefix(model).strip()
if not model_bare:
return None
if access_token:
live = _fetch_codex_oauth_context_lengths(access_token)
if model_bare in live:
return live[model_bare]
# Case-insensitive match in case casing drifts
model_lower = model_bare.lower()
for slug, ctx in live.items():
if slug.lower() == model_lower:
return ctx
# Fallback: longest-key-first substring match over hardcoded defaults.
model_lower = model_bare.lower()
for slug, ctx in sorted(
_CODEX_OAUTH_CONTEXT_FALLBACK.items(), key=lambda x: len(x[0]), reverse=True
):
if slug in model_lower:
return ctx
return None
def _resolve_nous_context_length(model: str) -> Optional[int]:
"""Resolve Nous Portal model context length via OpenRouter metadata.
@@ -1232,14 +1012,12 @@ def get_model_context_length(
api_key: str = "",
config_context_length: int | None = None,
provider: str = "",
custom_providers: list | None = None,
) -> int:
"""Get the context length for a model.
Resolution order:
0. Explicit config override (model.context_length or custom_providers per-model)
1. Persistent cache (previously discovered via probing)
1b. AWS Bedrock static table (must precede custom-endpoint probe)
2. Active endpoint metadata (/models for explicit custom endpoints)
3. Local server query (for local endpoints)
4. Anthropic /v1/models API (API-key users only, not OAuth)
@@ -1247,76 +1025,22 @@ def get_model_context_length(
6. Nous suffix-match via OpenRouter cache
7. models.dev registry lookup (provider-aware)
8. Thin hardcoded defaults (broad family patterns)
9. Default fallback (256K)
9. Default fallback (128K)
"""
# 0. Explicit config override — user knows best
if config_context_length is not None and isinstance(config_context_length, int) and config_context_length > 0:
return config_context_length
# 0b. custom_providers per-model override — check before any probe.
# This closes the gap where /model switch and display paths used to fall
# back to 128K despite the user having a per-model context_length set.
# See #15779.
if custom_providers and base_url and model:
try:
from hermes_cli.config import get_custom_provider_context_length
cp_ctx = get_custom_provider_context_length(
model=model,
base_url=base_url,
custom_providers=custom_providers,
)
if cp_ctx:
return cp_ctx
except Exception:
pass # fall through to probing
# Normalise provider-prefixed model names (e.g. "local:model-name" →
# "model-name") so cache lookups and server queries use the bare ID that
# local servers actually know about. Ollama "model:tag" colons are preserved.
model = _strip_provider_prefix(model)
# 1. Check persistent cache (model+provider)
# LM Studio is excluded — its loaded context length is transient (the
# user can reload the model with a different context_length at any time
# via /api/v1/models/load), so a stale cached value would mask reloads.
if base_url and provider != "lmstudio":
if base_url:
cached = get_cached_context_length(model, base_url)
if cached is not None:
# Invalidate stale Codex OAuth cache entries: pre-PR #14935 builds
# resolved gpt-5.x to the direct-API value (e.g. 1.05M) via
# models.dev and persisted it. Codex OAuth caps at 272K for every
# slug, so any cached Codex entry at or above 400K is a leftover
# from the old resolution path. Drop it and fall through to the
# live /models probe in step 5 below.
if provider == "openai-codex" and cached >= 400_000:
logger.info(
"Dropping stale Codex cache entry %s@%s -> %s (pre-fix value); "
"re-resolving via live /models probe",
model, base_url, f"{cached:,}",
)
_invalidate_cached_context_length(model, base_url)
else:
return cached
# 1b. AWS Bedrock — use static context length table.
# Bedrock's ListFoundationModels API doesn't expose context window sizes,
# so we maintain a curated table in bedrock_adapter.py that reflects
# AWS-imposed limits (e.g. 200K for Claude models vs 1M on the native
# Anthropic API). This must run BEFORE the custom-endpoint probe at
# step 2 — bedrock-runtime.<region>.amazonaws.com is not in
# _URL_TO_PROVIDER, so it would otherwise be treated as a custom endpoint,
# fail the /models probe (Bedrock doesn't expose that shape), and fall
# back to the 128K default before reaching the original step 4b branch.
if provider == "bedrock" or (
base_url
and base_url_hostname(base_url).startswith("bedrock-runtime.")
and base_url_host_matches(base_url, "amazonaws.com")
):
try:
from agent.bedrock_adapter import get_bedrock_context_length
return get_bedrock_context_length(model)
except ImportError:
pass # boto3 not installed — fall through to generic resolution
return cached
# 2. Active endpoint metadata for truly custom/unknown endpoints.
# Known providers (Copilot, OpenAI, Anthropic, etc.) skip this — their
@@ -1324,16 +1048,28 @@ def get_model_context_length(
# returns 128k) instead of the model's full context (400k). models.dev
# has the correct per-provider values and is checked at step 5+.
if _is_custom_endpoint(base_url) and not _is_known_provider_base_url(base_url):
context_length = _resolve_endpoint_context_length(model, base_url, api_key=api_key)
if context_length is not None:
return context_length
endpoint_metadata = fetch_endpoint_model_metadata(base_url, api_key=api_key)
matched = endpoint_metadata.get(model)
if not matched:
# Single-model servers: if only one model is loaded, use it
if len(endpoint_metadata) == 1:
matched = next(iter(endpoint_metadata.values()))
else:
# Fuzzy match: substring in either direction
for key, entry in endpoint_metadata.items():
if model in key or key in model:
matched = entry
break
if matched:
context_length = matched.get("context_length")
if isinstance(context_length, int):
return context_length
if not _is_known_provider_base_url(base_url):
# 3. Try querying local server directly
if is_local_endpoint(base_url):
local_ctx = _query_local_context_length(model, base_url, api_key=api_key)
if local_ctx and local_ctx > 0:
if provider != "lmstudio":
save_context_length(model, base_url, local_ctx)
save_context_length(model, base_url, local_ctx)
return local_ctx
logger.info(
"Could not detect context length for model %r at %s"
@@ -1351,7 +1087,19 @@ def get_model_context_length(
if ctx:
return ctx
# 4b. (Bedrock handled earlier at step 1b — before custom-endpoint probe.)
# 4b. AWS Bedrock — use static context length table.
# Bedrock's ListFoundationModels doesn't expose context window sizes,
# so we maintain a curated table in bedrock_adapter.py.
if provider == "bedrock" or (
base_url
and base_url_hostname(base_url).startswith("bedrock-runtime.")
and base_url_host_matches(base_url, "amazonaws.com")
):
try:
from agent.bedrock_adapter import get_bedrock_context_length
return get_bedrock_context_length(model)
except ImportError:
pass # boto3 not installed — fall through to generic resolution
# 5. Provider-aware lookups (before generic OpenRouter cache)
# These are provider-specific and take priority over the generic OR cache,
@@ -1365,38 +1113,10 @@ def get_model_context_length(
if inferred:
effective_provider = inferred
# 5a. Copilot live /models API — max_prompt_tokens from the user's account.
# This catches account-specific models (e.g. claude-opus-4.6-1m) that
# don't exist in models.dev. For models that ARE in models.dev, this
# returns the provider-enforced limit which is what users can actually use.
if effective_provider in ("copilot", "copilot-acp", "github-copilot"):
try:
from hermes_cli.models import get_copilot_model_context
ctx = get_copilot_model_context(model, api_key=api_key)
if ctx:
return ctx
except Exception:
pass # Fall through to models.dev
if effective_provider == "nous":
ctx = _resolve_nous_context_length(model)
if ctx:
return ctx
if effective_provider == "openai-codex":
# Codex OAuth enforces lower context limits than the direct OpenAI
# API for the same slug (e.g. gpt-5.5 is 1.05M on the API but 272K
# on Codex). Authoritative source is Codex's own /models endpoint.
codex_ctx = _resolve_codex_oauth_context_length(model, access_token=api_key or "")
if codex_ctx:
if base_url:
save_context_length(model, base_url, codex_ctx)
return codex_ctx
if effective_provider == "gmi" and base_url:
# GMI exposes authoritative context_length via /models, but it is not
# in models.dev yet. Preserve that higher-fidelity endpoint lookup.
ctx = _resolve_endpoint_context_length(model, base_url, api_key=api_key)
if ctx is not None:
return ctx
if effective_provider:
from agent.models_dev import lookup_models_dev_context
ctx = lookup_models_dev_context(effective_provider, model)
@@ -1406,7 +1126,7 @@ def get_model_context_length(
# 6. OpenRouter live API metadata (provider-unaware fallback)
metadata = fetch_model_metadata()
if model in metadata:
return metadata[model].get("context_length", DEFAULT_FALLBACK_CONTEXT)
return metadata[model].get("context_length", 128000)
# 8. Hardcoded defaults (fuzzy match — longest key first for specificity)
# Only check `default_model in model` (is the key a substring of the input).
@@ -1423,11 +1143,10 @@ def get_model_context_length(
if base_url and is_local_endpoint(base_url):
local_ctx = _query_local_context_length(model, base_url, api_key=api_key)
if local_ctx and local_ctx > 0:
if provider != "lmstudio":
save_context_length(model, base_url, local_ctx)
save_context_length(model, base_url, local_ctx)
return local_ctx
# 10. Default fallback — 256K
# 10. Default fallback — 128K
return DEFAULT_FALLBACK_CONTEXT
-5
View File
@@ -146,10 +146,8 @@ PROVIDER_TO_MODELS_DEV: Dict[str, str] = {
"openai-codex": "openai",
"zai": "zai",
"kimi-coding": "kimi-for-coding",
"stepfun": "stepfun",
"kimi-coding-cn": "kimi-for-coding",
"minimax": "minimax",
"minimax-oauth": "minimax",
"minimax-cn": "minimax-cn",
"deepseek": "deepseek",
"alibaba": "alibaba",
@@ -419,9 +417,6 @@ def list_provider_models(provider: str) -> List[str]:
Returns an empty list if the provider is unknown or has no data.
"""
from hermes_cli.models import normalize_provider
provider = normalize_provider(provider) or provider
models = _get_provider_models(provider)
if models is None:
return []
-231
View File
@@ -1,231 +0,0 @@
"""Helpers for translating OpenAI-style tool schemas to Moonshot's schema subset.
Moonshot (Kimi) accepts a stricter subset of JSON Schema than standard OpenAI
tool calling. Requests that violate it fail with HTTP 400:
tools.function.parameters is not a valid moonshot flavored json schema,
details: <...>
Known rejection modes documented at
https://forum.moonshot.ai/t/tool-calling-specification-violation-on-moonshot-api/102
and MoonshotAI/kimi-cli#1595:
1. Every property schema must carry a ``type``. Standard JSON Schema allows
type to be omitted (the value is then unconstrained); Moonshot refuses.
2. When ``anyOf`` is used, ``type`` must be on the ``anyOf`` children, not
the parent. Presence of both causes "type should be defined in anyOf
items instead of the parent schema".
The ``#/definitions/...`` → ``#/$defs/...`` rewrite for draft-07 refs is
handled separately in ``tools/mcp_tool._normalize_mcp_input_schema`` so it
applies at MCP registration time for all providers.
"""
from __future__ import annotations
import copy
from typing import Any, Dict, List
# Keys whose values are maps of name → schema (not schemas themselves).
# When we recurse, we walk the values of these maps as schemas, but we do
# NOT apply the missing-type repair to the map itself.
_SCHEMA_MAP_KEYS = frozenset({"properties", "patternProperties", "$defs", "definitions"})
# Keys whose values are lists of schemas.
_SCHEMA_LIST_KEYS = frozenset({"anyOf", "oneOf", "allOf", "prefixItems"})
# Keys whose values are a single nested schema.
_SCHEMA_NODE_KEYS = frozenset({"items", "contains", "not", "additionalProperties", "propertyNames"})
def _repair_schema(node: Any, is_schema: bool = True) -> Any:
"""Recursively apply Moonshot repairs to a schema node.
``is_schema=True`` means this dict is a JSON Schema node and gets the
missing-type + anyOf-parent repairs applied. ``is_schema=False`` means
it's a container map (e.g. the value of ``properties``) and we only
recurse into its values.
"""
if isinstance(node, list):
# Lists only show up under schema-list keys (anyOf/oneOf/allOf), so
# every element is itself a schema.
return [_repair_schema(item, is_schema=True) for item in node]
if not isinstance(node, dict):
return node
# Walk the dict, deciding per-key whether recursion is into a schema
# node, a container map, or a scalar.
repaired: Dict[str, Any] = {}
for key, value in node.items():
if key in _SCHEMA_MAP_KEYS and isinstance(value, dict):
# Map of name → schema. Don't treat the map itself as a schema
# (it has no type / properties of its own), but each value is.
repaired[key] = {
sub_key: _repair_schema(sub_val, is_schema=True)
for sub_key, sub_val in value.items()
}
elif key in _SCHEMA_LIST_KEYS and isinstance(value, list):
repaired[key] = [_repair_schema(v, is_schema=True) for v in value]
elif key in _SCHEMA_NODE_KEYS:
# items / not / additionalProperties: single nested schema.
# additionalProperties can also be a bool — leave those alone.
if isinstance(value, dict):
repaired[key] = _repair_schema(value, is_schema=True)
else:
repaired[key] = value
else:
# Scalars (description, title, format, enum values, etc.) pass through.
repaired[key] = value
if not is_schema:
return repaired
# Rule 2: when anyOf is present, type belongs only on the children.
# Additionally, Moonshot rejects null-type branches inside anyOf
# (enum value (<nil>) does not match any type in [string]).
# Collapse the anyOf to the first non-null branch and infer its type.
if "anyOf" in repaired and isinstance(repaired["anyOf"], list):
repaired.pop("type", None)
non_null = [b for b in repaired["anyOf"]
if isinstance(b, dict) and b.get("type") != "null"]
if non_null and len(non_null) < len(repaired["anyOf"]):
# Drop the anyOf wrapper — keep only the non-null branch.
# If there's a single non-null branch, promote it and fall
# through to Rules 1/3 so nullable/enum cleanup still applies
# to the merged node.
if len(non_null) == 1:
merge = {k: v for k, v in repaired.items() if k != "anyOf"}
merge.update(non_null[0])
repaired = merge
else:
repaired["anyOf"] = non_null
return repaired
else:
# Nothing to collapse — parent type stripped, children already
# repaired by the recursive walk above.
return repaired
# Moonshot also rejects non-standard keywords like ``nullable`` on
# parameter schemas — strip it.
repaired.pop("nullable", None)
# Rule 1: property schemas without type need one. $ref nodes are exempt
# — their type comes from the referenced definition.
# Fill missing type BEFORE Rule 3 so enum cleanup can check the type.
if "$ref" not in repaired:
repaired = _fill_missing_type(repaired)
# Rule 3: Moonshot rejects null/empty-string values inside enum arrays
# when the parent type is a scalar (string, integer, etc.). The error:
# "enum value (<nil>) does not match any type in [string]"
# Strip null and empty-string from enum values, and if the enum becomes
# empty, drop it entirely.
if "enum" in repaired and isinstance(repaired["enum"], list):
node_type = repaired.get("type")
if node_type in ("string", "integer", "number", "boolean"):
cleaned = [v for v in repaired["enum"]
if v is not None and v != ""]
if cleaned:
repaired["enum"] = cleaned
else:
repaired.pop("enum")
return repaired
def _fill_missing_type(node: Dict[str, Any]) -> Dict[str, Any]:
"""Infer a reasonable ``type`` if this schema node has none."""
if "type" in node and node["type"] not in (None, ""):
return node
# Heuristic: presence of ``properties`` → object, ``items`` → array, ``enum``
# → type of first enum value, else fall back to ``string`` (safest scalar).
if "properties" in node or "required" in node or "additionalProperties" in node:
inferred = "object"
elif "items" in node or "prefixItems" in node:
inferred = "array"
elif "enum" in node and isinstance(node["enum"], list) and node["enum"]:
sample = node["enum"][0]
if isinstance(sample, bool):
inferred = "boolean"
elif isinstance(sample, int):
inferred = "integer"
elif isinstance(sample, float):
inferred = "number"
else:
inferred = "string"
else:
inferred = "string"
return {**node, "type": inferred}
def sanitize_moonshot_tool_parameters(parameters: Any) -> Dict[str, Any]:
"""Normalize tool parameters to a Moonshot-compatible object schema.
Returns a deep-copied schema with the two flavored-JSON-Schema repairs
applied. Input is not mutated.
"""
if not isinstance(parameters, dict):
return {"type": "object", "properties": {}}
repaired = _repair_schema(copy.deepcopy(parameters), is_schema=True)
if not isinstance(repaired, dict):
return {"type": "object", "properties": {}}
# Top-level must be an object schema
if repaired.get("type") != "object":
repaired["type"] = "object"
if "properties" not in repaired:
repaired["properties"] = {}
return repaired
def sanitize_moonshot_tools(tools: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Apply ``sanitize_moonshot_tool_parameters`` to every tool's parameters."""
if not tools:
return tools
sanitized: List[Dict[str, Any]] = []
any_change = False
for tool in tools:
if not isinstance(tool, dict):
sanitized.append(tool)
continue
fn = tool.get("function")
if not isinstance(fn, dict):
sanitized.append(tool)
continue
params = fn.get("parameters")
repaired = sanitize_moonshot_tool_parameters(params)
if repaired is not params:
any_change = True
new_fn = {**fn, "parameters": repaired}
sanitized.append({**tool, "function": new_fn})
else:
sanitized.append(tool)
return sanitized if any_change else tools
def is_moonshot_model(model: str | None) -> bool:
"""True for any Kimi / Moonshot model slug, regardless of aggregator prefix.
Matches bare names (``kimi-k2.6``, ``moonshotai/Kimi-K2.6``) and aggregator-
prefixed slugs (``nous/moonshotai/kimi-k2.6``, ``openrouter/moonshotai/...``).
Detection by model name covers Nous / OpenRouter / other aggregators that
route to Moonshot's inference, where the base URL is the aggregator's, not
``api.moonshot.ai``.
"""
if not model:
return False
bare = model.strip().lower()
# Last path segment (covers aggregator-prefixed slugs)
tail = bare.rsplit("/", 1)[-1]
if tail.startswith("kimi-") or tail == "kimi":
return True
# Vendor-prefixed forms commonly used on aggregators
if "moonshot" in bare or "/kimi" in bare or bare.startswith("kimi"):
return True
return False
+1 -144
View File
@@ -18,7 +18,6 @@ import os
import tempfile
import time
from typing import Any, Mapping, Optional
from utils import atomic_replace
logger = logging.getLogger(__name__)
@@ -119,7 +118,7 @@ def record_nous_rate_limit(
try:
with os.fdopen(fd, "w") as f:
json.dump(state, f)
atomic_replace(tmp_path, path)
os.replace(tmp_path, path)
except Exception:
# Clean up temp file on failure
try:
@@ -181,145 +180,3 @@ def format_remaining(seconds: float) -> str:
h, remainder = divmod(s, 3600)
m = remainder // 60
return f"{h}h {m}m" if m else f"{h}h"
# Buckets with reset windows shorter than this are treated as transient
# (upstream jitter, secondary throttling) rather than a genuine quota
# exhaustion worth a cross-session breaker trip.
_MIN_RESET_FOR_BREAKER_SECONDS = 60.0
def is_genuine_nous_rate_limit(
*,
headers: Optional[Mapping[str, str]] = None,
last_known_state: Optional[Any] = None,
) -> bool:
"""Decide whether a 429 from Nous Portal is a real account rate limit.
Nous Portal multiplexes multiple upstream providers (DeepSeek, Kimi,
MiMo, Hermes, ...) behind one endpoint. A 429 can mean either:
(a) The caller's own RPM / RPH / TPM / TPH bucket on Nous is
exhausted a genuine rate limit that will last until the
bucket resets.
(b) The upstream provider is out of capacity for a specific model
transient, clears in seconds, and has nothing to do with
the caller's quota on Nous.
Tripping the cross-session breaker on (b) blocks ALL Nous requests
(and all models, since Nous is one provider key) for minutes even
though the caller's account is healthy and a different model would
have worked. That's the bug users hit when DeepSeek V4 Pro 429s
trigger a breaker that then blocks Kimi 2.6 and MiMo V2.5 Pro.
We tell the two apart by looking at:
1. The 429 response's own ``x-ratelimit-*`` headers. Nous emits
the full suite on every response including 429s. An exhausted
bucket (``remaining == 0`` with a reset window >= 60s) is
proof of (a).
2. The last-known-good rate-limit state captured by
``_capture_rate_limits()`` on the previous successful
response. If any bucket there was already near-exhausted with
a substantial reset window, the current 429 is almost
certainly (a) continuing from that condition.
If neither signal fires, we treat the 429 as (b): fail the single
request, let the retry loop or model-switch proceed, and do NOT
write the cross-session breaker file.
Returns True when the evidence points at (a).
"""
# Signal 1: current 429 response headers.
state = _parse_buckets_from_headers(headers)
if _has_exhausted_bucket(state):
return True
# Signal 2: last-known-good state from a recent successful response.
# Accepts either a RateLimitState (dataclass from rate_limit_tracker)
# or a dict of bucket snapshots.
if last_known_state is not None and _has_exhausted_bucket_in_object(last_known_state):
return True
return False
def _parse_buckets_from_headers(
headers: Optional[Mapping[str, str]],
) -> dict[str, tuple[Optional[int], Optional[float]]]:
"""Extract (remaining, reset_seconds) per bucket from x-ratelimit-* headers.
Returns empty dict when no rate-limit headers are present.
"""
if not headers:
return {}
lowered = {k.lower(): v for k, v in headers.items()}
if not any(k.startswith("x-ratelimit-") for k in lowered):
return {}
def _maybe_int(raw: Optional[str]) -> Optional[int]:
if raw is None:
return None
try:
return int(float(raw))
except (TypeError, ValueError):
return None
def _maybe_float(raw: Optional[str]) -> Optional[float]:
if raw is None:
return None
try:
return float(raw)
except (TypeError, ValueError):
return None
result: dict[str, tuple[Optional[int], Optional[float]]] = {}
for tag in ("requests", "requests-1h", "tokens", "tokens-1h"):
remaining = _maybe_int(lowered.get(f"x-ratelimit-remaining-{tag}"))
reset = _maybe_float(lowered.get(f"x-ratelimit-reset-{tag}"))
if remaining is not None or reset is not None:
result[tag] = (remaining, reset)
return result
def _has_exhausted_bucket(
buckets: Mapping[str, tuple[Optional[int], Optional[float]]],
) -> bool:
"""Return True when any bucket has remaining == 0 AND a meaningful reset window."""
for remaining, reset in buckets.values():
if remaining is None or remaining > 0:
continue
if reset is None:
continue
if reset >= _MIN_RESET_FOR_BREAKER_SECONDS:
return True
return False
def _has_exhausted_bucket_in_object(state: Any) -> bool:
"""Check a RateLimitState-like object for an exhausted bucket.
Accepts the dataclass from ``agent.rate_limit_tracker`` (buckets
exposed as attributes ``requests_min``, ``requests_hour``,
``tokens_min``, ``tokens_hour``) and falls back gracefully for any
object missing those attributes.
"""
for attr in ("requests_min", "requests_hour", "tokens_min", "tokens_hour"):
bucket = getattr(state, attr, None)
if bucket is None:
continue
limit = getattr(bucket, "limit", 0) or 0
remaining = getattr(bucket, "remaining", 0) or 0
# Prefer the adjusted "remaining_seconds_now" property when present;
# fall back to raw reset_seconds.
reset = getattr(bucket, "remaining_seconds_now", None)
if reset is None:
reset = getattr(bucket, "reset_seconds", 0.0) or 0.0
if limit <= 0:
continue
if remaining > 0:
continue
if reset >= _MIN_RESET_FOR_BREAKER_SECONDS:
return True
return False
-193
View File
@@ -1,193 +0,0 @@
"""
Contextual first-touch onboarding hints.
Instead of blocking first-run questionnaires, show a one-time hint the *first*
time a user hits a behavior fork message-while-running, first long-running
tool, etc. Each hint is shown once per install (tracked in ``config.yaml`` under
``onboarding.seen.<flag>``) and then never again.
Keep this module tiny and dependency-free so both the CLI and gateway can import
it without pulling in heavy modules.
"""
from __future__ import annotations
import logging
from pathlib import Path
from typing import Any, Mapping, Optional
logger = logging.getLogger(__name__)
# -------------------------------------------------------------------------
# Flag names (stable — used as config.yaml keys under onboarding.seen)
# -------------------------------------------------------------------------
BUSY_INPUT_FLAG = "busy_input_prompt"
TOOL_PROGRESS_FLAG = "tool_progress_prompt"
OPENCLAW_RESIDUE_FLAG = "openclaw_residue_cleanup"
# -------------------------------------------------------------------------
# Hint content
# -------------------------------------------------------------------------
def busy_input_hint_gateway(mode: str) -> str:
"""Hint shown the first time a user messages while the agent is busy.
``mode`` is the effective busy_input_mode that was just applied, so the
message matches reality ("I just interrupted…" vs "I just queued…").
"""
if mode == "queue":
return (
"💡 First-time tip — I queued your message instead of interrupting. "
"Send `/busy interrupt` to make new messages stop the current task "
"immediately, or `/busy status` to check. This notice won't appear again."
)
if mode == "steer":
return (
"💡 First-time tip — I steered your message into the current run; "
"it will arrive after the next tool call instead of interrupting. "
"Send `/busy interrupt` or `/busy queue` to change this, or "
"`/busy status` to check. This notice won't appear again."
)
return (
"💡 First-time tip — I just interrupted my current task to answer you. "
"Send `/busy queue` to queue follow-ups for after the current task instead, "
"`/busy steer` to inject them mid-run without interrupting, or "
"`/busy status` to check. This notice won't appear again."
)
def busy_input_hint_cli(mode: str) -> str:
"""CLI version of the busy-input hint (plain text, no markdown)."""
if mode == "queue":
return (
"(tip) Your message was queued for the next turn. "
"Use /busy interrupt to make Enter stop the current run instead, "
"or /busy steer to inject mid-run. This tip only shows once."
)
if mode == "steer":
return (
"(tip) Your message was steered into the current run; it arrives "
"after the next tool call. Use /busy interrupt or /busy queue to "
"change this. This tip only shows once."
)
return (
"(tip) Your message interrupted the current run. "
"Use /busy queue to queue messages for the next turn instead, "
"or /busy steer to inject mid-run. This tip only shows once."
)
def tool_progress_hint_gateway() -> str:
return (
"💡 First-time tip — that tool took a while and I'm streaming every step. "
"If the progress messages feel noisy, send `/verbose` to cycle modes "
"(all → new → off). This notice won't appear again."
)
def tool_progress_hint_cli() -> str:
return (
"(tip) That tool ran for a while. Use /verbose to cycle tool-progress "
"display modes (all -> new -> off -> verbose). This tip only shows once."
)
def openclaw_residue_hint_cli() -> str:
"""Banner shown the first time Hermes starts and finds ``~/.openclaw/``.
Points users at ``hermes claw migrate`` (non-destructive port of config,
memory, and skills) first. ``hermes claw cleanup`` is mentioned as the
follow-up step for users who have already migrated and want to archive
the old directory with a warning that archiving breaks OpenClaw.
"""
return (
"A legacy OpenClaw directory was detected at ~/.openclaw/.\n"
"To port your config, memory, and skills over to Hermes, run "
"`hermes claw migrate`.\n"
"If you've already migrated and want to archive the old directory, "
"run `hermes claw cleanup` (renames it to ~/.openclaw.pre-migration — "
"OpenClaw will stop working after this).\n"
"This tip only shows once."
)
def detect_openclaw_residue(home: Optional[Path] = None) -> bool:
"""Return True if an OpenClaw workspace directory is present in ``$HOME``.
Pure filesystem check no side effects. ``home`` override exists for tests.
"""
base = home or Path.home()
try:
return (base / ".openclaw").is_dir()
except OSError:
return False
# -------------------------------------------------------------------------
# State read / write
# -------------------------------------------------------------------------
def _get_seen_dict(config: Mapping[str, Any]) -> Mapping[str, Any]:
onboarding = config.get("onboarding") if isinstance(config, Mapping) else None
if not isinstance(onboarding, Mapping):
return {}
seen = onboarding.get("seen")
return seen if isinstance(seen, Mapping) else {}
def is_seen(config: Mapping[str, Any], flag: str) -> bool:
"""Return True if the user has already been shown this first-touch hint."""
return bool(_get_seen_dict(config).get(flag))
def mark_seen(config_path: Path, flag: str) -> bool:
"""Persist ``onboarding.seen.<flag> = True`` to ``config_path``.
Uses the atomic YAML writer so a concurrent process can't observe a
partially-written file. Returns True on success, False on any error
(including the config file being absent onboarding is best-effort).
"""
try:
import yaml
from utils import atomic_yaml_write
except Exception as e: # pragma: no cover — dependency issue
logger.debug("onboarding: failed to import yaml/utils: %s", e)
return False
try:
cfg: dict = {}
if config_path.exists():
with open(config_path, encoding="utf-8") as f:
cfg = yaml.safe_load(f) or {}
if not isinstance(cfg.get("onboarding"), dict):
cfg["onboarding"] = {}
seen = cfg["onboarding"].get("seen")
if not isinstance(seen, dict):
seen = {}
cfg["onboarding"]["seen"] = seen
if seen.get(flag) is True:
return True # already marked — nothing to do
seen[flag] = True
atomic_yaml_write(config_path, cfg)
return True
except Exception as e:
logger.debug("onboarding: failed to mark flag %s: %s", flag, e)
return False
__all__ = [
"BUSY_INPUT_FLAG",
"TOOL_PROGRESS_FLAG",
"OPENCLAW_RESIDUE_FLAG",
"busy_input_hint_gateway",
"busy_input_hint_cli",
"tool_progress_hint_gateway",
"tool_progress_hint_cli",
"openclaw_residue_hint_cli",
"detect_openclaw_residue",
"is_seen",
"mark_seen",
]
+1 -129
View File
@@ -141,12 +141,6 @@ DEFAULT_AGENT_IDENTITY = (
"Be targeted and efficient in your exploration and investigations."
)
HERMES_AGENT_HELP_GUIDANCE = (
"If the user asks about configuring, setting up, or using Hermes Agent "
"itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') "
"before answering. Docs: https://hermes-agent.nousresearch.com/docs"
)
MEMORY_GUIDANCE = (
"You have persistent memory across sessions. Save durable facts using the memory "
"tool: user preferences, environment details, tool quirks, and stable conventions. "
@@ -182,64 +176,6 @@ SKILLS_GUIDANCE = (
"Skills that aren't maintained become liabilities."
)
KANBAN_GUIDANCE = (
"# Kanban task execution protocol\n"
"You have been assigned ONE task from "
"the shared board at `~/.hermes/kanban.db`. Your task id is in "
"`$HERMES_KANBAN_TASK`; your workspace is `$HERMES_KANBAN_WORKSPACE`. "
"The `kanban_*` tools in your schema are your primary coordination surface — "
"they write directly to the shared SQLite DB and work regardless of terminal "
"backend (local/docker/modal/ssh).\n"
"\n"
"## Lifecycle\n"
"\n"
"1. **Orient.** Call `kanban_show()` first (no args — it defaults to your "
"task). The response includes title, body, parent-task handoffs (summary + "
"metadata), any prior attempts on this task if you're a retry, the full "
"comment thread, and a pre-formatted `worker_context` you can treat as "
"ground truth.\n"
"2. **Work inside the workspace.** `cd $HERMES_KANBAN_WORKSPACE` before "
"any file operations. The workspace is yours for this run. Don't modify "
"files outside it unless the task explicitly asks.\n"
"3. **Heartbeat on long operations.** Call `kanban_heartbeat(note=...)` "
"every few minutes during long subprocesses (training, encoding, crawling). "
"Skip heartbeats for short tasks.\n"
"4. **Block on genuine ambiguity.** If you need a human decision you cannot "
"infer (missing credentials, UX choice, paywalled source, peer output you "
"need first), call `kanban_block(reason=\"...\")` and stop. Don't guess. "
"The user will unblock with context and the dispatcher will respawn you.\n"
"5. **Complete with structured handoff.** Call `kanban_complete(summary=..., "
"metadata=...)`. `summary` is 13 human-readable sentences naming concrete "
"artifacts. `metadata` is machine-readable facts "
"(`{changed_files: [...], tests_run: N, decisions: [...]}`). Downstream "
"workers read both via their own `kanban_show`. Never put secrets / "
"tokens / raw PII in either field — run rows are durable forever.\n"
"6. **If follow-up work appears, create it; don't do it.** Use "
"`kanban_create(title=..., assignee=<right-profile>, parents=[your-task-id])` "
"to spawn a child task for the appropriate specialist profile instead of "
"scope-creeping into the next thing.\n"
"\n"
"## Orchestrator mode\n"
"\n"
"If your task is itself a decomposition task (e.g. a planner profile given "
"a high-level goal), use `kanban_create` to fan out into child tasks — one "
"per specialist, each with an explicit `assignee` and `parents=[...]` to "
"express dependencies. Then `kanban_complete` your own task with a summary "
"of the decomposition. Do NOT execute the work yourself; your job is "
"routing, not implementation.\n"
"\n"
"## Do NOT\n"
"\n"
"- Do not shell out to `hermes kanban <verb>` for board operations. Use "
"the `kanban_*` tools — they work across all terminal backends.\n"
"- Do not complete a task you didn't actually finish. Block it.\n"
"- Do not assign follow-up work to yourself. Assign it to the right "
"specialist profile.\n"
"- Do not call `delegate_task` as a board substitute. `delegate_task` is "
"for short reasoning subtasks inside your own run; board tasks are for "
"cross-agent handoffs that outlive one API loop."
)
TOOL_USE_ENFORCEMENT_GUIDANCE = (
"# Tool-use enforcement\n"
"You MUST use your tools to take action — do not describe what you would do "
@@ -368,10 +304,6 @@ PLATFORM_HINTS = {
"Standard markdown is automatically converted to Telegram format. "
"Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, "
"`inline code`, ```code blocks```, [links](url), and ## headers. "
"Telegram has NO table syntax — prefer bullet lists or labeled "
"key: value pairs over pipe tables (any tables you do emit are "
"auto-rewritten into row-group bullets, which you can produce "
"directly for cleaner output). "
"You can send media files natively: to deliver a file to the user, "
"include MEDIA:/absolute/path/to/file in your response. Images "
"(.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice "
@@ -418,13 +350,7 @@ PLATFORM_HINTS = {
),
"cli": (
"You are a CLI AI Agent. Try not to use markdown but simple text "
"renderable inside a terminal. "
"File delivery: there is no attachment channel — the user reads your "
"response directly in their terminal. Do NOT emit MEDIA:/path tags "
"(those are only intercepted on messaging platforms like Telegram, "
"Discord, Slack, etc.; on the CLI they render as literal text). "
"When referring to a file you created or changed, just state its "
"absolute path in plain text; the user can open it from there."
"renderable inside a terminal."
),
"sms": (
"You are communicating via SMS. Keep responses concise and use plain text "
@@ -438,32 +364,6 @@ PLATFORM_HINTS = {
"MEDIA:/absolute/path/to/file in your response. Images (.jpg, .png, "
".heic) appear as photos and other files arrive as attachments."
),
"mattermost": (
"You are in a Mattermost workspace communicating with your user. "
"Mattermost renders standard Markdown — headings, bold, italic, code "
"blocks, and tables all work. "
"You can send media files natively: include MEDIA:/absolute/path/to/file "
"in your response. Images (.jpg, .png, .webp) are uploaded as photo "
"attachments, audio and video as file attachments. "
"Image URLs in markdown format ![alt](url) are rendered as inline previews automatically."
),
"matrix": (
"You are in a Matrix room communicating with your user. "
"Matrix renders Markdown — bold, italic, code blocks, and links work; "
"the adapter converts your Markdown to HTML for rich display. "
"You can send media files natively: include MEDIA:/absolute/path/to/file "
"in your response. Images (.jpg, .png, .webp) are sent as inline photos, "
"audio (.ogg, .mp3) as voice/audio messages, video (.mp4) inline, "
"and other files as downloadable attachments."
),
"feishu": (
"You are in a Feishu (Lark) workspace communicating with your user. "
"Feishu renders Markdown in messages — bold, italic, code blocks, and "
"links are supported. "
"You can send media files natively: include MEDIA:/absolute/path/to/file "
"in your response. Images (.jpg, .png, .webp) are uploaded and displayed "
"inline, audio files as voice messages, and other files as attachments."
),
"weixin": (
"You are on Weixin/WeChat. Markdown formatting is supported, so you may use it when "
"it improves readability, but keep the message compact and chat-friendly. You can send media files natively: "
@@ -490,29 +390,6 @@ PLATFORM_HINTS = {
"your response. Images are sent as native photos, and other files arrive as downloadable "
"documents."
),
"yuanbao": (
"You are on Yuanbao (腾讯元宝), a Chinese AI assistant platform. "
"Markdown formatting is supported (code blocks, tables, bold/italic). "
"You CAN send media files natively — to deliver a file to the user, include "
"MEDIA:/absolute/path/to/file in your response. The file will be sent as a native "
"Yuanbao attachment: images (.jpg, .png, .webp, .gif) are sent as photos, "
"and other files (.pdf, .docx, .txt, .zip, etc.) arrive as downloadable documents "
"(max 50 MB). You can also include image URLs in markdown format ![alt](url) and "
"they will be downloaded and sent as native photos. "
"Do NOT tell the user you lack file-sending capability — use MEDIA: syntax "
"whenever a file delivery is appropriate.\n\n"
"Stickers (贴纸 / 表情包 / TIM face): Yuanbao has a built-in sticker catalogue. "
"When the user sends a sticker (you see '[emoji: 名称]' in their message) or asks "
"you to send/reply-with a 贴纸/表情/表情包, you MUST use the sticker tools:\n"
" 1. Call yb_search_sticker with a Chinese keyword (e.g. '666', '比心', '吃瓜', "
" '捂脸', '合十') to discover matching sticker_ids.\n"
" 2. Call yb_send_sticker with the chosen sticker_id or name — this sends a real "
" TIMFaceElem that renders as a native sticker in the chat.\n"
"DO NOT draw sticker-like PNGs with execute_code/Pillow/matplotlib and then send "
"them via MEDIA: or send_image_file. That produces a fake low-quality 'sticker' "
"image and is the WRONG path. Bare Unicode emoji in text is also not a substitute "
"— when a sticker is the right response, use yb_send_sticker."
),
}
# ---------------------------------------------------------------------------
@@ -916,11 +793,6 @@ def build_skills_system_prompt(
"Skills also encode the user's preferred approach, conventions, and quality standards "
"for tasks like code review, planning, and testing — load them even for tasks you "
"already know how to do, because the skill defines how it should be done here.\n"
"Whenever the user asks you to configure, set up, install, enable, disable, modify, "
"or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, "
"skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill "
"first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, "
"`hermes setup`) so you don't have to guess or invent workarounds.\n"
"If a skill has issues, fix it with skill_manage(action='patch').\n"
"After difficult/iterative tasks, offer to save as a skill. "
"If a skill you loaded was missing steps, had wrong commands, or needed "
+8 -62
View File
@@ -56,12 +56,8 @@ _SENSITIVE_BODY_KEYS = frozenset({
})
# Snapshot at import time so runtime env mutations (e.g. LLM-generated
# `export HERMES_REDACT_SECRETS=true`) cannot enable/disable redaction
# mid-session. OFF by default — user must opt in via
# `security.redact_secrets: true` in config.yaml (bridged to this env var
# in hermes_cli/main.py and gateway/run.py) or `HERMES_REDACT_SECRETS=true`
# in ~/.hermes/.env.
_REDACT_ENABLED = os.getenv("HERMES_REDACT_SECRETS", "").lower() in ("1", "true", "yes", "on")
# `export HERMES_REDACT_SECRETS=false`) cannot disable redaction mid-session.
_REDACT_ENABLED = os.getenv("HERMES_REDACT_SECRETS", "").lower() not in ("0", "false", "no", "off")
# Known API key prefixes -- match the prefix + contiguous token chars
_PREFIX_PATTERNS = [
@@ -184,59 +180,11 @@ _PREFIX_RE = re.compile(
)
def mask_secret(
value: str,
*,
head: int = 4,
tail: int = 4,
floor: int = 12,
placeholder: str = "***",
empty: str = "",
) -> str:
"""Mask a secret for display, preserving ``head`` and ``tail`` characters.
Canonical helper for display-time redaction across Hermes used by
``hermes config``, ``hermes status``, ``hermes dump``, and anywhere
a secret needs to be shown truncated for debuggability while still
keeping the bulk hidden.
Args:
value: The secret to mask. ``None``/empty returns ``empty``.
head: Leading characters to preserve. Default 4.
tail: Trailing characters to preserve. Default 4.
floor: Values shorter than ``head + tail + floor_margin`` are
fully masked (returns ``placeholder``). Default 12
matches the existing config/status/dump convention.
placeholder: Value returned for too-short inputs. Default ``"***"``.
empty: Value returned when ``value`` is falsy (None, ""). The
caller can override this to e.g. ``color("(not set)",
Colors.DIM)`` for user-facing display.
Examples:
>>> mask_secret("sk-proj-abcdef1234567890")
'sk-p...7890'
>>> mask_secret("short") # fully masked
'***'
>>> mask_secret("") # empty default
''
>>> mask_secret("", empty="(not set)") # empty override
'(not set)'
>>> mask_secret("long-token", head=6, tail=4, floor=18)
'***'
"""
if not value:
return empty
if len(value) < floor:
return placeholder
return f"{value[:head]}...{value[-tail:]}"
def _mask_token(token: str) -> str:
"""Mask a log token — conservative 18-char floor, preserves 6 prefix / 4 suffix."""
# Empty input: historically this returned "***" rather than "". Preserve.
if not token:
"""Mask a token, preserving prefix for long tokens."""
if len(token) < 18:
return "***"
return mask_secret(token, head=6, tail=4, floor=18)
return f"{token[:6]}...{token[-4:]}"
def _redact_query_string(query: str) -> str:
@@ -305,13 +253,11 @@ def _redact_form_body(text: str) -> str:
return _redact_query_string(text.strip())
def redact_sensitive_text(text: str, *, force: bool = False) -> str:
def redact_sensitive_text(text: str) -> str:
"""Apply all redaction patterns to a block of text.
Safe to call on any string -- non-matching text passes through unchanged.
Disabled by default enable via security.redact_secrets: true in config.yaml.
Set force=True for safety boundaries that must never return raw secrets
regardless of the user's global logging redaction preference.
Disabled when security.redact_secrets is false in config.yaml.
"""
if text is None:
return None
@@ -319,7 +265,7 @@ def redact_sensitive_text(text: str, *, force: bool = False) -> str:
text = str(text)
if not text:
return text
if not (force or _REDACT_ENABLED):
if not _REDACT_ENABLED:
return text
# Known prefixes (sk-, ghp_, etc.)
+2 -7
View File
@@ -76,7 +76,6 @@ except ImportError: # pragma: no cover
fcntl = None # type: ignore[assignment]
from hermes_constants import get_hermes_home
from utils import atomic_replace
logger = logging.getLogger(__name__)
@@ -569,7 +568,7 @@ def save_allowlist(data: Dict[str, Any]) -> None:
try:
with os.fdopen(fd, "w") as fh:
fh.write(json.dumps(data, indent=2, sort_keys=True))
atomic_replace(tmp_path, p)
os.replace(tmp_path, p)
except Exception:
try:
os.unlink(tmp_path)
@@ -755,11 +754,7 @@ def _resolve_effective_accept(
if env in ("1", "true", "yes", "on"):
return True
cfg_val = cfg.get("hooks_auto_accept", False)
if isinstance(cfg_val, bool):
return cfg_val
if isinstance(cfg_val, str):
return cfg_val.strip().lower() in ("1", "true", "yes", "on")
return False
return bool(cfg_val)
# ---------------------------------------------------------------------------
+134 -127
View File
@@ -1,54 +1,153 @@
"""Shared slash command helpers for skills.
"""Shared slash command helpers for skills and built-in prompt-style modes.
Shared between CLI (cli.py) and gateway (gateway/run.py) so both surfaces
can invoke skills via /skill-name commands.
can invoke skills via /skill-name commands and prompt-only built-ins like
/plan.
"""
import json
import logging
import os
import re
import subprocess
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, Optional
from hermes_constants import display_hermes_home
from agent.skill_preprocessing import (
expand_inline_shell as _expand_inline_shell,
load_skills_config as _load_skills_config,
substitute_template_vars as _substitute_template_vars,
)
logger = logging.getLogger(__name__)
_skill_commands: Dict[str, Dict[str, Any]] = {}
_skill_commands_platform: Optional[str] = None
_PLAN_SLUG_RE = re.compile(r"[^a-z0-9]+")
# Patterns for sanitizing skill names into clean hyphen-separated slugs.
_SKILL_INVALID_CHARS = re.compile(r"[^a-z0-9-]")
_SKILL_MULTI_HYPHEN = re.compile(r"-{2,}")
# Matches ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} tokens in SKILL.md.
# Tokens that don't resolve (e.g. ${HERMES_SESSION_ID} with no session) are
# left as-is so the user can debug them.
_SKILL_TEMPLATE_RE = re.compile(r"\$\{(HERMES_SKILL_DIR|HERMES_SESSION_ID)\}")
def _resolve_skill_commands_platform() -> Optional[str]:
"""Return the current platform scope used for disabled-skill filtering.
# Matches inline shell snippets like: !`date +%Y-%m-%d`
# Non-greedy, single-line only — no newlines inside the backticks.
_INLINE_SHELL_RE = re.compile(r"!`([^`\n]+)`")
Used to detect when the active platform has shifted so
:func:`get_skill_commands` can drop a stale cache that was populated
for a different platform's ``skills.platform_disabled`` view (#14536).
# Cap inline-shell output so a runaway command can't blow out the context.
_INLINE_SHELL_MAX_OUTPUT = 4000
Resolves from (in order) ``HERMES_PLATFORM`` env var and
``HERMES_SESSION_PLATFORM`` from the gateway session context. Returns
``None`` when no platform scope is active (e.g. classic CLI, RL
rollouts, standalone scripts).
def _load_skills_config() -> dict:
"""Load the ``skills`` section of config.yaml (best-effort)."""
try:
from hermes_cli.config import load_config
cfg = load_config() or {}
skills_cfg = cfg.get("skills")
if isinstance(skills_cfg, dict):
return skills_cfg
except Exception:
logger.debug("Could not read skills config", exc_info=True)
return {}
def _substitute_template_vars(
content: str,
skill_dir: Path | None,
session_id: str | None,
) -> str:
"""Replace ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} in skill content.
Only substitutes tokens for which a concrete value is available
unresolved tokens are left in place so the author can spot them.
"""
if not content:
return content
skill_dir_str = str(skill_dir) if skill_dir else None
def _replace(match: re.Match) -> str:
token = match.group(1)
if token == "HERMES_SKILL_DIR" and skill_dir_str:
return skill_dir_str
if token == "HERMES_SESSION_ID" and session_id:
return str(session_id)
return match.group(0)
return _SKILL_TEMPLATE_RE.sub(_replace, content)
def _run_inline_shell(command: str, cwd: Path | None, timeout: int) -> str:
"""Execute a single inline-shell snippet and return its stdout (trimmed).
Failures return a short ``[inline-shell error: ...]`` marker instead of
raising, so one bad snippet can't wreck the whole skill message.
"""
try:
from gateway.session_context import get_session_env
resolved_platform = (
os.getenv("HERMES_PLATFORM")
or get_session_env("HERMES_SESSION_PLATFORM")
completed = subprocess.run(
["bash", "-c", command],
cwd=str(cwd) if cwd else None,
capture_output=True,
text=True,
timeout=max(1, int(timeout)),
check=False,
)
except Exception:
resolved_platform = os.getenv("HERMES_PLATFORM")
return resolved_platform or None
except subprocess.TimeoutExpired:
return f"[inline-shell timeout after {timeout}s: {command}]"
except FileNotFoundError:
return f"[inline-shell error: bash not found]"
except Exception as exc:
return f"[inline-shell error: {exc}]"
output = (completed.stdout or "").rstrip("\n")
if not output and completed.stderr:
output = completed.stderr.rstrip("\n")
if len(output) > _INLINE_SHELL_MAX_OUTPUT:
output = output[:_INLINE_SHELL_MAX_OUTPUT] + "…[truncated]"
return output
def _expand_inline_shell(
content: str,
skill_dir: Path | None,
timeout: int,
) -> str:
"""Replace every !`cmd` snippet in ``content`` with its stdout.
Runs each snippet with the skill directory as CWD so relative paths in
the snippet work the way the author expects.
"""
if "!`" not in content:
return content
def _replace(match: re.Match) -> str:
cmd = match.group(1).strip()
if not cmd:
return ""
return _run_inline_shell(cmd, skill_dir, timeout)
return _INLINE_SHELL_RE.sub(_replace, content)
def build_plan_path(
user_instruction: str = "",
*,
now: datetime | None = None,
) -> Path:
"""Return the default workspace-relative markdown path for a /plan invocation.
Relative paths are intentional: file tools are task/backend-aware and resolve
them against the active working directory for local, docker, ssh, modal,
daytona, and similar terminal backends. That keeps the plan with the active
workspace instead of the Hermes host's global home directory.
"""
slug_source = (user_instruction or "").strip().splitlines()[0] if user_instruction else ""
slug = _PLAN_SLUG_RE.sub("-", slug_source.lower()).strip("-")
if slug:
slug = "-".join(part for part in slug.split("-")[:8] if part)[:48].strip("-")
slug = slug or "conversation-plan"
timestamp = (now or datetime.now()).strftime("%Y-%m-%d_%H%M%S")
return Path(".hermes") / "plans" / f"{timestamp}-{slug}.md"
def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tuple[dict[str, Any], Path | None, str] | None:
"""Load a skill by name/path and return (loaded_payload, skill_dir, display_name)."""
@@ -68,9 +167,7 @@ def _load_skill_payload(skill_identifier: str, task_id: str | None = None) -> tu
else:
normalized = raw_identifier.lstrip("/")
loaded_skill = json.loads(
skill_view(normalized, task_id=task_id, preprocess=False)
)
loaded_skill = json.loads(skill_view(normalized, task_id=task_id))
except Exception:
return None
@@ -244,12 +341,11 @@ def scan_skill_commands() -> Dict[str, Dict[str, Any]]:
Returns:
Dict mapping "/skill-name" to {name, description, skill_md_path, skill_dir}.
"""
global _skill_commands, _skill_commands_platform
_skill_commands_platform = _resolve_skill_commands_platform()
global _skill_commands
_skill_commands = {}
try:
from tools.skills_tool import SKILLS_DIR, _parse_frontmatter, skill_matches_platform, _get_disabled_skill_names
from agent.skill_utils import get_external_skills_dirs, iter_skill_index_files
from agent.skill_utils import get_external_skills_dirs
disabled = _get_disabled_skill_names()
seen_names: set = set()
@@ -260,8 +356,8 @@ def scan_skill_commands() -> Dict[str, Dict[str, Any]]:
dirs_to_scan.extend(get_external_skills_dirs())
for scan_dir in dirs_to_scan:
for skill_md in iter_skill_index_files(scan_dir, "SKILL.md"):
if any(part in ('.git', '.github', '.hub', '.archive') for part in skill_md.parts):
for skill_md in scan_dir.rglob("SKILL.md"):
if any(part in ('.git', '.github', '.hub') for part in skill_md.parts):
continue
try:
content = skill_md.read_text(encoding='utf-8')
@@ -305,85 +401,12 @@ def scan_skill_commands() -> Dict[str, Dict[str, Any]]:
def get_skill_commands() -> Dict[str, Dict[str, Any]]:
"""Return the current skill commands mapping (scan first if empty).
Rescans when the active platform scope changes (e.g. a gateway
process serving Telegram and Discord concurrently) so each platform
sees its own ``skills.platform_disabled`` view (#14536).
"""
if (
not _skill_commands
or _skill_commands_platform != _resolve_skill_commands_platform()
):
"""Return the current skill commands mapping (scan first if empty)."""
if not _skill_commands:
scan_skill_commands()
return _skill_commands
def reload_skills() -> Dict[str, Any]:
"""Re-scan the skills directory and return a diff of what changed.
Rescans ``~/.hermes/skills/`` and any ``skills.external_dirs`` so the
slash-command map (``agent.skill_commands._skill_commands``) reflects
skills added or removed on disk.
This does NOT invalidate the skills system-prompt cache. Skills are
called by name via ``/skill-name``, ``skills_list``, or ``skill_view``
they don't need to be in the system prompt for the model to use them.
Keeping the prompt cache intact preserves prefix caching across the
reload, so a user invoking ``/reload-skills`` pays no cache-reset cost.
Returns:
Dict with keys::
{
"added": [{"name": str, "description": str}, ...],
"removed": [{"name": str, "description": str}, ...],
"unchanged": [skill names present before and after],
"total": total skill count after rescan,
"commands": total /slash-skill count after rescan,
}
``description`` is the skill's full SKILL.md frontmatter
``description:`` field the same string the system prompt renders
as `` - name: description`` for pre-existing skills.
"""
# Snapshot pre-reload state (name -> description) from the current
# slash-command cache. Using dicts lets the post-rescan diff carry
# descriptions for newly-visible or just-removed skills without a
# second disk walk.
def _snapshot(cmds: Dict[str, Dict[str, Any]]) -> Dict[str, str]:
out: Dict[str, str] = {}
for slash_key, info in cmds.items():
bare = slash_key.lstrip("/")
out[bare] = (info or {}).get("description") or ""
return out
before = _snapshot(_skill_commands)
# Rescan the skills dir. ``scan_skill_commands`` resets
# ``_skill_commands = {}`` internally and repopulates it.
new_commands = scan_skill_commands()
after = _snapshot(new_commands)
added_names = sorted(set(after) - set(before))
removed_names = sorted(set(before) - set(after))
unchanged = sorted(set(after) & set(before))
added = [{"name": n, "description": after[n]} for n in added_names]
# For removed skills, use the description we had cached pre-rescan
# (the skill file is gone so we can't re-read it).
removed = [{"name": n, "description": before[n]} for n in removed_names]
return {
"added": added,
"removed": removed,
"unchanged": unchanged,
"total": len(after),
"commands": len(new_commands),
}
def resolve_skill_command_key(command: str) -> Optional[str]:
"""Resolve a user-typed /command to its canonical skill_cmds key.
@@ -428,16 +451,8 @@ def build_skill_invocation_message(
return f"[Failed to load skill: {skill_info['name']}]"
loaded_skill, skill_dir, skill_name = loaded
# Track active usage for Curator lifecycle management (#17782)
try:
from tools.skill_usage import bump_use
bump_use(skill_name)
except Exception:
pass # Non-critical — skill invocation proceeds regardless
activation_note = (
f'[IMPORTANT: The user has invoked the "{skill_name}" skill, indicating they want '
f'[SYSTEM: The user has invoked the "{skill_name}" skill, indicating they want '
"you to follow its instructions. The full skill content is loaded below.]"
)
return _build_skill_message(
@@ -475,16 +490,8 @@ def build_preloaded_skills_prompt(
continue
loaded_skill, skill_dir, skill_name = loaded
# Track active usage for Curator lifecycle management (#17782)
try:
from tools.skill_usage import bump_use
bump_use(skill_name)
except Exception:
pass # Non-critical
activation_note = (
f'[IMPORTANT: The user launched this CLI session with the "{skill_name}" skill '
f'[SYSTEM: The user launched this CLI session with the "{skill_name}" skill '
"preloaded. Treat its instructions as active guidance for the duration of this "
"session unless the user overrides them.]"
)
-131
View File
@@ -1,131 +0,0 @@
"""Shared SKILL.md preprocessing helpers."""
import logging
import re
import subprocess
from pathlib import Path
logger = logging.getLogger(__name__)
# Matches ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} tokens in SKILL.md.
# Tokens that don't resolve (e.g. ${HERMES_SESSION_ID} with no session) are
# left as-is so the user can debug them.
_SKILL_TEMPLATE_RE = re.compile(r"\$\{(HERMES_SKILL_DIR|HERMES_SESSION_ID)\}")
# Matches inline shell snippets like: !`date +%Y-%m-%d`
# Non-greedy, single-line only -- no newlines inside the backticks.
_INLINE_SHELL_RE = re.compile(r"!`([^`\n]+)`")
# Cap inline-shell output so a runaway command can't blow out the context.
_INLINE_SHELL_MAX_OUTPUT = 4000
def load_skills_config() -> dict:
"""Load the ``skills`` section of config.yaml (best-effort)."""
try:
from hermes_cli.config import load_config
cfg = load_config() or {}
skills_cfg = cfg.get("skills")
if isinstance(skills_cfg, dict):
return skills_cfg
except Exception:
logger.debug("Could not read skills config", exc_info=True)
return {}
def substitute_template_vars(
content: str,
skill_dir: Path | None,
session_id: str | None,
) -> str:
"""Replace ${HERMES_SKILL_DIR} / ${HERMES_SESSION_ID} in skill content.
Only substitutes tokens for which a concrete value is available --
unresolved tokens are left in place so the author can spot them.
"""
if not content:
return content
skill_dir_str = str(skill_dir) if skill_dir else None
def _replace(match: re.Match) -> str:
token = match.group(1)
if token == "HERMES_SKILL_DIR" and skill_dir_str:
return skill_dir_str
if token == "HERMES_SESSION_ID" and session_id:
return str(session_id)
return match.group(0)
return _SKILL_TEMPLATE_RE.sub(_replace, content)
def run_inline_shell(command: str, cwd: Path | None, timeout: int) -> str:
"""Execute a single inline-shell snippet and return its stdout (trimmed).
Failures return a short ``[inline-shell error: ...]`` marker instead of
raising, so one bad snippet can't wreck the whole skill message.
"""
try:
completed = subprocess.run(
["bash", "-c", command],
cwd=str(cwd) if cwd else None,
capture_output=True,
text=True,
timeout=max(1, int(timeout)),
check=False,
)
except subprocess.TimeoutExpired:
return f"[inline-shell timeout after {timeout}s: {command}]"
except FileNotFoundError:
return "[inline-shell error: bash not found]"
except Exception as exc:
return f"[inline-shell error: {exc}]"
output = (completed.stdout or "").rstrip("\n")
if not output and completed.stderr:
output = completed.stderr.rstrip("\n")
if len(output) > _INLINE_SHELL_MAX_OUTPUT:
output = output[:_INLINE_SHELL_MAX_OUTPUT] + "...[truncated]"
return output
def expand_inline_shell(
content: str,
skill_dir: Path | None,
timeout: int,
) -> str:
"""Replace every !`cmd` snippet in ``content`` with its stdout.
Runs each snippet with the skill directory as CWD so relative paths in
the snippet work the way the author expects.
"""
if "!`" not in content:
return content
def _replace(match: re.Match) -> str:
cmd = match.group(1).strip()
if not cmd:
return ""
return run_inline_shell(cmd, skill_dir, timeout)
return _INLINE_SHELL_RE.sub(_replace, content)
def preprocess_skill_content(
content: str,
skill_dir: Path | None,
session_id: str | None = None,
skills_cfg: dict | None = None,
) -> str:
"""Apply configured SKILL.md template and inline-shell preprocessing."""
if not content:
return content
cfg = skills_cfg if isinstance(skills_cfg, dict) else load_skills_config()
if cfg.get("template_vars", True):
content = substitute_template_vars(content, skill_dir, session_id)
if cfg.get("inline_shell", False):
timeout = int(cfg.get("inline_shell_timeout", 10) or 10)
content = expand_inline_shell(content, skill_dir, timeout)
return content
+4 -12
View File
@@ -24,7 +24,7 @@ PLATFORM_MAP = {
"windows": "win32",
}
EXCLUDED_SKILL_DIRS = frozenset((".git", ".github", ".hub", ".archive"))
EXCLUDED_SKILL_DIRS = frozenset((".git", ".github", ".hub"))
# ── Lazy YAML loader ─────────────────────────────────────────────────────
@@ -200,9 +200,6 @@ def get_external_skills_dirs() -> List[Path]:
if not isinstance(raw_dirs, list):
return []
from hermes_constants import get_hermes_home
hermes_home = get_hermes_home()
local_skills = get_skills_dir().resolve()
seen: Set[Path] = set()
result: List[Path] = []
@@ -213,12 +210,7 @@ def get_external_skills_dirs() -> List[Path]:
continue
# Expand ~ and environment variables
expanded = os.path.expanduser(os.path.expandvars(entry))
p = Path(expanded)
# Resolve relative paths against HERMES_HOME, not cwd
if not p.is_absolute():
p = (hermes_home / p).resolve()
else:
p = p.resolve()
p = Path(expanded).resolve()
if p == local_skills:
continue
if p in seen:
@@ -440,10 +432,10 @@ def extract_skill_description(frontmatter: Dict[str, Any]) -> str:
def iter_skill_index_files(skills_dir: Path, filename: str):
"""Walk skills_dir yielding sorted paths matching *filename*.
Excludes ``.git``, ``.github``, ``.hub``, ``.archive`` directories.
Excludes ``.git``, ``.github``, ``.hub`` directories.
"""
matches = []
for root, dirs, files in os.walk(skills_dir, followlinks=True):
for root, dirs, files in os.walk(skills_dir):
dirs[:] = [d for d in dirs if d not in EXCLUDED_SKILL_DIRS]
if filename in files:
matches.append(Path(root) / filename)
+6 -40
View File
@@ -6,18 +6,12 @@ adds latency to the user-facing reply.
import logging
import threading
from typing import Callable, Optional
from typing import Optional
from agent.auxiliary_client import call_llm
logger = logging.getLogger(__name__)
# Callback signature: (task_name, exception) -> None. Used to surface
# auxiliary failures to the user through AIAgent._emit_auxiliary_failure
# so silent-drops (e.g. OpenRouter 402 exhausting the fallback chain)
# become visible instead of piling up as NULL session titles.
FailureCallback = Callable[[str, BaseException], None]
_TITLE_PROMPT = (
"Generate a short, descriptive title (3-7 words) for a conversation that starts with the "
"following exchange. The title should capture the main topic or intent. "
@@ -25,23 +19,11 @@ _TITLE_PROMPT = (
)
def generate_title(
user_message: str,
assistant_response: str,
timeout: float = 30.0,
failure_callback: Optional[FailureCallback] = None,
main_runtime: dict = None,
) -> Optional[str]:
def generate_title(user_message: str, assistant_response: str, timeout: float = 30.0) -> Optional[str]:
"""Generate a session title from the first exchange.
Uses the main runtime's model when available, falling back to the
auxiliary LLM client (cheapest/fastest available model).
Uses the auxiliary LLM client (cheapest/fastest available model).
Returns the title string or None on failure.
``failure_callback`` is invoked with ``(task, exception)`` when the
auxiliary call raises the caller typically wires this to
``AIAgent._emit_auxiliary_failure`` so the user sees a warning instead
of silently accumulating untitled sessions.
"""
# Truncate long messages to keep the request small
user_snippet = user_message[:500] if user_message else ""
@@ -56,10 +38,9 @@ def generate_title(
response = call_llm(
task="title_generation",
messages=messages,
max_tokens=500,
max_tokens=30,
temperature=0.3,
timeout=timeout,
main_runtime=main_runtime,
)
title = (response.choices[0].message.content or "").strip()
# Clean up: remove quotes, trailing punctuation, prefixes like "Title: "
@@ -71,15 +52,7 @@ def generate_title(
title = title[:77] + "..."
return title if title else None
except Exception as e:
# Log at WARNING so this shows up in agent.log without debug mode.
# Full detail at debug level for operators who need the stack.
logger.warning("Title generation failed: %s", e)
logger.debug("Title generation traceback", exc_info=True)
if failure_callback is not None:
try:
failure_callback("title generation", e)
except Exception:
logger.debug("Title generation failure_callback raised", exc_info=True)
logger.debug("Title generation failed: %s", e)
return None
@@ -88,8 +61,6 @@ def auto_title_session(
session_id: str,
user_message: str,
assistant_response: str,
failure_callback: Optional[FailureCallback] = None,
main_runtime: dict = None,
) -> None:
"""Generate and set a session title if one doesn't already exist.
@@ -110,9 +81,7 @@ def auto_title_session(
except Exception:
return
title = generate_title(
user_message, assistant_response, failure_callback=failure_callback, main_runtime=main_runtime
)
title = generate_title(user_message, assistant_response)
if not title:
return
@@ -129,8 +98,6 @@ def maybe_auto_title(
user_message: str,
assistant_response: str,
conversation_history: list,
failure_callback: Optional[FailureCallback] = None,
main_runtime: dict = None,
) -> None:
"""Fire-and-forget title generation after the first exchange.
@@ -152,7 +119,6 @@ def maybe_auto_title(
thread = threading.Thread(
target=auto_title_session,
args=(session_db, session_id, user_message, assistant_response),
kwargs={"failure_callback": failure_callback, "main_runtime": main_runtime},
daemon=True,
name="auto-title",
)
-455
View File
@@ -1,455 +0,0 @@
"""Pure tool-call loop guardrail primitives.
The controller in this module is intentionally side-effect free: it tracks
per-turn tool-call observations and returns decisions. Runtime code owns whether
those decisions become warning guidance, synthetic tool results, or controlled
turn halts.
"""
from __future__ import annotations
import hashlib
import json
from dataclasses import dataclass, field
from typing import Any, Mapping
from utils import safe_json_loads
IDEMPOTENT_TOOL_NAMES = frozenset(
{
"read_file",
"search_files",
"web_search",
"web_extract",
"session_search",
"browser_snapshot",
"browser_console",
"browser_get_images",
"mcp_filesystem_read_file",
"mcp_filesystem_read_text_file",
"mcp_filesystem_read_multiple_files",
"mcp_filesystem_list_directory",
"mcp_filesystem_list_directory_with_sizes",
"mcp_filesystem_directory_tree",
"mcp_filesystem_get_file_info",
"mcp_filesystem_search_files",
}
)
MUTATING_TOOL_NAMES = frozenset(
{
"terminal",
"execute_code",
"write_file",
"patch",
"todo",
"memory",
"skill_manage",
"browser_click",
"browser_type",
"browser_press",
"browser_scroll",
"browser_navigate",
"send_message",
"cronjob",
"delegate_task",
"process",
}
)
@dataclass(frozen=True)
class ToolCallGuardrailConfig:
"""Thresholds for per-turn tool-call loop detection.
Warnings are enabled by default and never prevent tool execution. Hard stops
are explicit opt-in so interactive CLI/TUI sessions get a gentle nudge unless
the user enables circuit-breaker behavior in config.yaml.
"""
warnings_enabled: bool = True
hard_stop_enabled: bool = False
exact_failure_warn_after: int = 2
exact_failure_block_after: int = 5
same_tool_failure_warn_after: int = 3
same_tool_failure_halt_after: int = 8
no_progress_warn_after: int = 2
no_progress_block_after: int = 5
idempotent_tools: frozenset[str] = field(default_factory=lambda: IDEMPOTENT_TOOL_NAMES)
mutating_tools: frozenset[str] = field(default_factory=lambda: MUTATING_TOOL_NAMES)
@classmethod
def from_mapping(cls, data: Mapping[str, Any] | None) -> "ToolCallGuardrailConfig":
"""Build config from the `tool_loop_guardrails` config.yaml section."""
if not isinstance(data, Mapping):
return cls()
warn_after = data.get("warn_after")
if not isinstance(warn_after, Mapping):
warn_after = {}
hard_stop_after = data.get("hard_stop_after")
if not isinstance(hard_stop_after, Mapping):
hard_stop_after = {}
defaults = cls()
return cls(
warnings_enabled=_as_bool(data.get("warnings_enabled"), defaults.warnings_enabled),
hard_stop_enabled=_as_bool(data.get("hard_stop_enabled"), defaults.hard_stop_enabled),
exact_failure_warn_after=_positive_int(
warn_after.get("exact_failure", data.get("exact_failure_warn_after")),
defaults.exact_failure_warn_after,
),
same_tool_failure_warn_after=_positive_int(
warn_after.get("same_tool_failure", data.get("same_tool_failure_warn_after")),
defaults.same_tool_failure_warn_after,
),
no_progress_warn_after=_positive_int(
warn_after.get("idempotent_no_progress", data.get("no_progress_warn_after")),
defaults.no_progress_warn_after,
),
exact_failure_block_after=_positive_int(
hard_stop_after.get("exact_failure", data.get("exact_failure_block_after")),
defaults.exact_failure_block_after,
),
same_tool_failure_halt_after=_positive_int(
hard_stop_after.get("same_tool_failure", data.get("same_tool_failure_halt_after")),
defaults.same_tool_failure_halt_after,
),
no_progress_block_after=_positive_int(
hard_stop_after.get("idempotent_no_progress", data.get("no_progress_block_after")),
defaults.no_progress_block_after,
),
)
@dataclass(frozen=True)
class ToolCallSignature:
"""Stable, non-reversible identity for a tool name plus canonical args."""
tool_name: str
args_hash: str
@classmethod
def from_call(cls, tool_name: str, args: Mapping[str, Any] | None) -> "ToolCallSignature":
canonical = canonical_tool_args(args or {})
return cls(tool_name=tool_name, args_hash=_sha256(canonical))
def to_metadata(self) -> dict[str, str]:
"""Return public metadata without raw argument values."""
return {"tool_name": self.tool_name, "args_hash": self.args_hash}
@dataclass(frozen=True)
class ToolGuardrailDecision:
"""Decision returned by the tool-call guardrail controller."""
action: str = "allow" # allow | warn | block | halt
code: str = "allow"
message: str = ""
tool_name: str = ""
count: int = 0
signature: ToolCallSignature | None = None
@property
def allows_execution(self) -> bool:
return self.action in {"allow", "warn"}
@property
def should_halt(self) -> bool:
return self.action in {"block", "halt"}
def to_metadata(self) -> dict[str, Any]:
data: dict[str, Any] = {
"action": self.action,
"code": self.code,
"message": self.message,
"tool_name": self.tool_name,
"count": self.count,
}
if self.signature is not None:
data["signature"] = self.signature.to_metadata()
return data
def canonical_tool_args(args: Mapping[str, Any]) -> str:
"""Return sorted compact JSON for parsed tool arguments."""
if not isinstance(args, Mapping):
raise TypeError(f"tool args must be a mapping, got {type(args).__name__}")
return json.dumps(
args,
ensure_ascii=False,
sort_keys=True,
separators=(",", ":"),
default=str,
)
def classify_tool_failure(tool_name: str, result: str | None) -> tuple[bool, str]:
"""Safety-fallback classifier used only when callers don't pass ``failed``.
Mirrors ``agent.display._detect_tool_failure`` exactly so the guardrail
never disagrees with the CLI's user-visible ``[error]`` tag. Production
callers in ``run_agent.py`` always pass an explicit ``failed=`` derived
from ``_detect_tool_failure``; this function exists so standalone callers
(tests, tooling) still get consistent behavior.
"""
if result is None:
return False, ""
if tool_name == "terminal":
data = safe_json_loads(result)
if isinstance(data, dict):
exit_code = data.get("exit_code")
if exit_code is not None and exit_code != 0:
return True, f" [exit {exit_code}]"
return False, ""
if tool_name == "memory":
data = safe_json_loads(result)
if isinstance(data, dict):
if data.get("success") is False and "exceed the limit" in data.get("error", ""):
return True, " [full]"
lower = result[:500].lower()
if '"error"' in lower or '"failed"' in lower or result.startswith("Error"):
return True, " [error]"
return False, ""
class ToolCallGuardrailController:
"""Per-turn controller for repeated failed/non-progressing tool calls."""
def __init__(self, config: ToolCallGuardrailConfig | None = None):
self.config = config or ToolCallGuardrailConfig()
self.reset_for_turn()
def reset_for_turn(self) -> None:
self._exact_failure_counts: dict[ToolCallSignature, int] = {}
self._same_tool_failure_counts: dict[str, int] = {}
self._no_progress: dict[ToolCallSignature, tuple[str, int]] = {}
self._halt_decision: ToolGuardrailDecision | None = None
@property
def halt_decision(self) -> ToolGuardrailDecision | None:
return self._halt_decision
def before_call(self, tool_name: str, args: Mapping[str, Any] | None) -> ToolGuardrailDecision:
signature = ToolCallSignature.from_call(tool_name, _coerce_args(args))
if not self.config.hard_stop_enabled:
return ToolGuardrailDecision(tool_name=tool_name, signature=signature)
exact_count = self._exact_failure_counts.get(signature, 0)
if exact_count >= self.config.exact_failure_block_after:
decision = ToolGuardrailDecision(
action="block",
code="repeated_exact_failure_block",
message=(
f"Blocked {tool_name}: the same tool call failed {exact_count} "
"times with identical arguments. Stop retrying it unchanged; "
"change strategy or explain the blocker."
),
tool_name=tool_name,
count=exact_count,
signature=signature,
)
self._halt_decision = decision
return decision
if self._is_idempotent(tool_name):
record = self._no_progress.get(signature)
if record is not None:
_result_hash, repeat_count = record
if repeat_count >= self.config.no_progress_block_after:
decision = ToolGuardrailDecision(
action="block",
code="idempotent_no_progress_block",
message=(
f"Blocked {tool_name}: this read-only call returned the same "
f"result {repeat_count} times. Stop repeating it unchanged; "
"use the result already provided or try a different query."
),
tool_name=tool_name,
count=repeat_count,
signature=signature,
)
self._halt_decision = decision
return decision
return ToolGuardrailDecision(tool_name=tool_name, signature=signature)
def after_call(
self,
tool_name: str,
args: Mapping[str, Any] | None,
result: str | None,
*,
failed: bool | None = None,
) -> ToolGuardrailDecision:
args = _coerce_args(args)
signature = ToolCallSignature.from_call(tool_name, args)
if failed is None:
failed, _ = classify_tool_failure(tool_name, result)
if failed:
exact_count = self._exact_failure_counts.get(signature, 0) + 1
self._exact_failure_counts[signature] = exact_count
self._no_progress.pop(signature, None)
same_count = self._same_tool_failure_counts.get(tool_name, 0) + 1
self._same_tool_failure_counts[tool_name] = same_count
if self.config.hard_stop_enabled and same_count >= self.config.same_tool_failure_halt_after:
decision = ToolGuardrailDecision(
action="halt",
code="same_tool_failure_halt",
message=(
f"Stopped {tool_name}: it failed {same_count} times this turn. "
"Stop retrying the same failing tool path and choose a different approach."
),
tool_name=tool_name,
count=same_count,
signature=signature,
)
self._halt_decision = decision
return decision
if self.config.warnings_enabled and exact_count >= self.config.exact_failure_warn_after:
return ToolGuardrailDecision(
action="warn",
code="repeated_exact_failure_warning",
message=(
f"{tool_name} has failed {exact_count} times with identical arguments. "
"This looks like a loop; inspect the error and change strategy "
"instead of retrying it unchanged."
),
tool_name=tool_name,
count=exact_count,
signature=signature,
)
if self.config.warnings_enabled and same_count >= self.config.same_tool_failure_warn_after:
return ToolGuardrailDecision(
action="warn",
code="same_tool_failure_warning",
message=(
f"{tool_name} has failed {same_count} times this turn. "
"This looks like a loop; change approach before retrying."
),
tool_name=tool_name,
count=same_count,
signature=signature,
)
return ToolGuardrailDecision(tool_name=tool_name, count=exact_count, signature=signature)
self._exact_failure_counts.pop(signature, None)
self._same_tool_failure_counts.pop(tool_name, None)
if not self._is_idempotent(tool_name):
self._no_progress.pop(signature, None)
return ToolGuardrailDecision(tool_name=tool_name, signature=signature)
result_hash = _result_hash(result)
previous = self._no_progress.get(signature)
repeat_count = 1
if previous is not None and previous[0] == result_hash:
repeat_count = previous[1] + 1
self._no_progress[signature] = (result_hash, repeat_count)
if self.config.warnings_enabled and repeat_count >= self.config.no_progress_warn_after:
return ToolGuardrailDecision(
action="warn",
code="idempotent_no_progress_warning",
message=(
f"{tool_name} returned the same result {repeat_count} times. "
"Use the result already provided or change the query instead of "
"repeating it unchanged."
),
tool_name=tool_name,
count=repeat_count,
signature=signature,
)
return ToolGuardrailDecision(tool_name=tool_name, count=repeat_count, signature=signature)
def _is_idempotent(self, tool_name: str) -> bool:
if tool_name in self.config.mutating_tools:
return False
return tool_name in self.config.idempotent_tools
def toolguard_synthetic_result(decision: ToolGuardrailDecision) -> str:
"""Build a synthetic role=tool content string for a blocked tool call."""
return json.dumps(
{
"error": decision.message,
"guardrail": decision.to_metadata(),
},
ensure_ascii=False,
)
def append_toolguard_guidance(result: str, decision: ToolGuardrailDecision) -> str:
"""Append runtime guidance to the current tool result content."""
if decision.action not in {"warn", "halt"} or not decision.message:
return result
label = "Tool loop hard stop" if decision.action == "halt" else "Tool loop warning"
suffix = (
f"\n\n[{label}: "
f"{decision.code}; count={decision.count}; {decision.message}]"
)
return (result or "") + suffix
def _coerce_args(args: Mapping[str, Any] | None) -> Mapping[str, Any]:
return args if isinstance(args, Mapping) else {}
def _result_hash(result: str | None) -> str:
parsed = safe_json_loads(result or "")
if parsed is not None:
try:
canonical = json.dumps(
parsed,
ensure_ascii=False,
sort_keys=True,
separators=(",", ":"),
default=str,
)
except TypeError:
canonical = str(parsed)
else:
canonical = result or ""
return _sha256(canonical)
def _as_bool(value: Any, default: bool) -> bool:
if value is None:
return default
if isinstance(value, bool):
return value
if isinstance(value, (int, float)):
return bool(value)
if isinstance(value, str):
lowered = value.strip().lower()
if lowered in {"1", "true", "yes", "on", "enabled"}:
return True
if lowered in {"0", "false", "no", "off", "disabled"}:
return False
return default
def _positive_int(value: Any, default: int) -> int:
if value is None:
return default
try:
parsed = int(value)
except (TypeError, ValueError):
return default
return parsed if parsed >= 1 else default
def _sha256(value: str) -> str:
return hashlib.sha256(value.encode("utf-8")).hexdigest()
+2 -19
View File
@@ -23,14 +23,9 @@ def get_transport(api_mode: str):
This allows gradual migration call sites can check for None
and fall back to the legacy code path.
"""
cls = _REGISTRY.get(api_mode)
if cls is None:
# The registry can be partially populated when a specific transport
# module was imported directly (for example chat_completions before
# codex). Discover on misses, not only when the registry is empty, so
# test/order-dependent imports do not make valid api_modes unavailable.
if not _REGISTRY:
_discover_transports()
cls = _REGISTRY.get(api_mode)
cls = _REGISTRY.get(api_mode)
if cls is None:
return None
return cls()
@@ -42,15 +37,3 @@ def _discover_transports() -> None:
import agent.transports.anthropic # noqa: F401
except ImportError:
pass
try:
import agent.transports.codex # noqa: F401
except ImportError:
pass
try:
import agent.transports.chat_completions # noqa: F401
except ImportError:
pass
try:
import agent.transports.bedrock # noqa: F401
except ImportError:
pass
+6 -56
View File
@@ -58,7 +58,6 @@ class AnthropicTransport(ProviderTransport):
context_length: int | None
base_url: str | None
fast_mode: bool
drop_context_1m_beta: bool
"""
from agent.anthropic_adapter import build_anthropic_kwargs
@@ -74,77 +73,28 @@ class AnthropicTransport(ProviderTransport):
context_length=params.get("context_length"),
base_url=params.get("base_url"),
fast_mode=params.get("fast_mode", False),
drop_context_1m_beta=params.get("drop_context_1m_beta", False),
)
def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
"""Normalize Anthropic response to NormalizedResponse.
Parses content blocks (text, thinking, tool_use), maps stop_reason
to OpenAI finish_reason, and collects reasoning_details in provider_data.
kwargs:
strip_tool_prefix: bool strip 'mcp_mcp_' prefixes from tool names.
"""
import json
from agent.anthropic_adapter import _to_plain_data
from agent.transports.types import ToolCall
from agent.anthropic_adapter import normalize_anthropic_response_v2
strip_tool_prefix = kwargs.get("strip_tool_prefix", False)
_MCP_PREFIX = "mcp_"
text_parts = []
reasoning_parts = []
reasoning_details = []
tool_calls = []
for block in response.content:
if block.type == "text":
text_parts.append(block.text)
elif block.type == "thinking":
reasoning_parts.append(block.thinking)
block_dict = _to_plain_data(block)
if isinstance(block_dict, dict):
reasoning_details.append(block_dict)
elif block.type == "tool_use":
name = block.name
if strip_tool_prefix and name.startswith(_MCP_PREFIX):
name = name[len(_MCP_PREFIX):]
tool_calls.append(
ToolCall(
id=block.id,
name=name,
arguments=json.dumps(block.input),
)
)
finish_reason = self._STOP_REASON_MAP.get(response.stop_reason, "stop")
provider_data = {}
if reasoning_details:
provider_data["reasoning_details"] = reasoning_details
return NormalizedResponse(
content="\n".join(text_parts) if text_parts else None,
tool_calls=tool_calls or None,
finish_reason=finish_reason,
reasoning="\n\n".join(reasoning_parts) if reasoning_parts else None,
usage=None,
provider_data=provider_data or None,
)
return normalize_anthropic_response_v2(response, strip_tool_prefix=strip_tool_prefix)
def validate_response(self, response: Any) -> bool:
"""Check Anthropic response structure is valid.
An empty content list is legitimate when ``stop_reason == "end_turn"``
the model's canonical way of signalling "nothing more to add" after
a tool turn that already delivered the user-facing text. Treating it
as invalid falsely retries a completed response.
"""
"""Check Anthropic response structure is valid."""
if response is None:
return False
content_blocks = getattr(response, "content", None)
if not isinstance(content_blocks, list):
return False
if not content_blocks:
return getattr(response, "stop_reason", None) == "end_turn"
return False
return True
def extract_cache_stats(self, response: Any) -> Optional[Dict[str, int]]:
-154
View File
@@ -1,154 +0,0 @@
"""AWS Bedrock Converse API transport.
Delegates to the existing adapter functions in agent/bedrock_adapter.py.
Bedrock uses its own boto3 client (not the OpenAI SDK), so the transport
owns format conversion and normalization, while client construction and
boto3 calls stay on AIAgent.
"""
from typing import Any, Dict, List, Optional
from agent.transports.base import ProviderTransport
from agent.transports.types import NormalizedResponse, ToolCall, Usage
class BedrockTransport(ProviderTransport):
"""Transport for api_mode='bedrock_converse'."""
@property
def api_mode(self) -> str:
return "bedrock_converse"
def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> Any:
"""Convert OpenAI messages to Bedrock Converse format."""
from agent.bedrock_adapter import convert_messages_to_converse
return convert_messages_to_converse(messages)
def convert_tools(self, tools: List[Dict[str, Any]]) -> Any:
"""Convert OpenAI tool schemas to Bedrock Converse toolConfig."""
from agent.bedrock_adapter import convert_tools_to_converse
return convert_tools_to_converse(tools)
def build_kwargs(
self,
model: str,
messages: List[Dict[str, Any]],
tools: Optional[List[Dict[str, Any]]] = None,
**params,
) -> Dict[str, Any]:
"""Build Bedrock converse() kwargs.
Calls convert_messages and convert_tools internally.
params:
max_tokens: int output token limit (default 4096)
temperature: float | None
guardrail_config: dict | None Bedrock guardrails
region: str AWS region (default 'us-east-1')
"""
from agent.bedrock_adapter import build_converse_kwargs
region = params.get("region", "us-east-1")
guardrail = params.get("guardrail_config")
kwargs = build_converse_kwargs(
model=model,
messages=messages,
tools=tools,
max_tokens=params.get("max_tokens", 4096),
temperature=params.get("temperature"),
guardrail_config=guardrail,
)
# Sentinel keys for dispatch — agent pops these before the boto3 call
kwargs["__bedrock_converse__"] = True
kwargs["__bedrock_region__"] = region
return kwargs
def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
"""Normalize Bedrock response to NormalizedResponse.
Handles two shapes:
1. Raw boto3 dict (from direct converse() calls)
2. Already-normalized SimpleNamespace with .choices (from dispatch site)
"""
from agent.bedrock_adapter import normalize_converse_response
# Normalize to OpenAI-compatible SimpleNamespace
if hasattr(response, "choices") and response.choices:
# Already normalized at dispatch site
ns = response
else:
# Raw boto3 dict
ns = normalize_converse_response(response)
choice = ns.choices[0]
msg = choice.message
finish_reason = choice.finish_reason or "stop"
tool_calls = None
if msg.tool_calls:
tool_calls = [
ToolCall(
id=tc.id,
name=tc.function.name,
arguments=tc.function.arguments,
)
for tc in msg.tool_calls
]
usage = None
if hasattr(ns, "usage") and ns.usage:
u = ns.usage
usage = Usage(
prompt_tokens=getattr(u, "prompt_tokens", 0) or 0,
completion_tokens=getattr(u, "completion_tokens", 0) or 0,
total_tokens=getattr(u, "total_tokens", 0) or 0,
)
reasoning = getattr(msg, "reasoning", None) or getattr(msg, "reasoning_content", None)
return NormalizedResponse(
content=msg.content,
tool_calls=tool_calls,
finish_reason=finish_reason,
reasoning=reasoning,
usage=usage,
)
def validate_response(self, response: Any) -> bool:
"""Check Bedrock response structure.
After normalize_converse_response, the response has OpenAI-compatible
.choices same check as chat_completions.
"""
if response is None:
return False
# Raw Bedrock dict response — check for 'output' key
if isinstance(response, dict):
return "output" in response
# Already-normalized SimpleNamespace
if hasattr(response, "choices"):
return bool(response.choices)
return False
def map_finish_reason(self, raw_reason: str) -> str:
"""Map Bedrock stop reason to OpenAI finish_reason.
The adapter already does this mapping inside normalize_converse_response,
so this is only used for direct access to raw responses.
"""
_MAP = {
"end_turn": "stop",
"tool_use": "tool_calls",
"max_tokens": "length",
"stop_sequence": "stop",
"guardrail_intervened": "content_filter",
"content_filtered": "content_filter",
}
return _MAP.get(raw_reason, "stop")
# Auto-register on import
from agent.transports import register_transport # noqa: E402
register_transport("bedrock_converse", BedrockTransport)
-529
View File
@@ -1,529 +0,0 @@
"""OpenAI Chat Completions transport.
Handles the default api_mode ('chat_completions') used by ~16 OpenAI-compatible
providers (OpenRouter, Nous, NVIDIA, Qwen, Ollama, DeepSeek, xAI, Kimi, etc.).
Messages and tools are already in OpenAI format convert_messages and
convert_tools are near-identity. The complexity lives in build_kwargs
which has provider-specific conditionals for max_tokens defaults,
reasoning configuration, temperature handling, and extra_body assembly.
"""
import copy
from typing import Any, Dict, List, Optional
from agent.lmstudio_reasoning import resolve_lmstudio_effort
from agent.moonshot_schema import is_moonshot_model, sanitize_moonshot_tools
from agent.prompt_builder import DEVELOPER_ROLE_MODELS
from agent.transports.base import ProviderTransport
from agent.transports.types import NormalizedResponse, ToolCall, Usage
def _build_gemini_thinking_config(model: str, reasoning_config: dict | None) -> dict | None:
"""Translate Hermes/OpenRouter-style reasoning config to Gemini thinkingConfig."""
if reasoning_config is None or not isinstance(reasoning_config, dict):
return None
normalized_model = (model or "").strip().lower()
if normalized_model.startswith("google/"):
normalized_model = normalized_model.split("/", 1)[1]
# ``thinking_config`` is a Gemini-only request parameter. The same
# ``gemini`` provider also serves Gemma (and historically PaLM/Bard);
# those reject the field with HTTP 400 "Unknown name 'thinking_config':
# Cannot find field" — including the polite ``{"includeThoughts": False}``
# form. Omit the field entirely on non-Gemini models. (#17426)
if not normalized_model.startswith("gemini"):
return None
if reasoning_config.get("enabled") is False:
# Gemini can hide thought parts even when internal thinking still
# happens; omit thinkingLevel to avoid model-specific validation quirks.
return {"includeThoughts": False}
effort = str(reasoning_config.get("effort", "medium") or "medium").strip().lower()
if effort == "none":
return {"includeThoughts": False}
thinking_config: Dict[str, Any] = {"includeThoughts": True}
# Gemini 2.5 accepts thinkingBudget; don't guess a budget from Hermes'
# coarse effort levels. ``includeThoughts`` alone is enough to surface
# thought parts without risking request validation errors.
if normalized_model.startswith("gemini-2.5-"):
return thinking_config
if effort not in {"minimal", "low", "medium", "high", "xhigh"}:
effort = "medium"
# Gemini 3 Flash documents low/medium/high thinking levels; Gemini 3 Pro
# is stricter (low/high). Clamp Hermes' wider effort set to what each
# family accepts so we never forward an undocumented level verbatim.
if normalized_model.startswith(("gemini-3", "gemini-3.1")):
if "flash" in normalized_model:
if effort in {"minimal", "low"}:
thinking_config["thinkingLevel"] = "low"
elif effort in {"high", "xhigh"}:
thinking_config["thinkingLevel"] = "high"
else:
thinking_config["thinkingLevel"] = "medium"
elif "pro" in normalized_model:
thinking_config["thinkingLevel"] = (
"high" if effort in {"high", "xhigh"} else "low"
)
return thinking_config
def _snake_case_gemini_thinking_config(config: dict | None) -> dict | None:
"""Convert Gemini thinking config keys to the OpenAI-compat field names."""
if not isinstance(config, dict) or not config:
return None
translated: Dict[str, Any] = {}
if isinstance(config.get("includeThoughts"), bool):
translated["include_thoughts"] = config["includeThoughts"]
if isinstance(config.get("thinkingLevel"), str) and config["thinkingLevel"].strip():
translated["thinking_level"] = config["thinkingLevel"].strip().lower()
if isinstance(config.get("thinkingBudget"), (int, float)):
translated["thinking_budget"] = int(config["thinkingBudget"])
return translated or None
def _is_gemini_openai_compat_base_url(base_url: Any) -> bool:
normalized = str(base_url or "").strip().rstrip("/").lower()
if not normalized:
return False
if "generativelanguage.googleapis.com" not in normalized:
return False
return normalized.endswith("/openai")
class ChatCompletionsTransport(ProviderTransport):
"""Transport for api_mode='chat_completions'.
The default path for OpenAI-compatible providers.
"""
@property
def api_mode(self) -> str:
return "chat_completions"
def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> List[Dict[str, Any]]:
"""Messages are already in OpenAI format — sanitize Codex leaks only.
Strips Codex Responses API fields (``codex_reasoning_items`` /
``codex_message_items`` on the message, ``call_id``/``response_item_id``
on tool_calls) that strict chat-completions providers reject with 400/422.
"""
needs_sanitize = False
for msg in messages:
if not isinstance(msg, dict):
continue
if "codex_reasoning_items" in msg or "codex_message_items" in msg:
needs_sanitize = True
break
tool_calls = msg.get("tool_calls")
if isinstance(tool_calls, list):
for tc in tool_calls:
if isinstance(tc, dict) and ("call_id" in tc or "response_item_id" in tc):
needs_sanitize = True
break
if needs_sanitize:
break
if not needs_sanitize:
return messages
sanitized = copy.deepcopy(messages)
for msg in sanitized:
if not isinstance(msg, dict):
continue
msg.pop("codex_reasoning_items", None)
msg.pop("codex_message_items", None)
tool_calls = msg.get("tool_calls")
if isinstance(tool_calls, list):
for tc in tool_calls:
if isinstance(tc, dict):
tc.pop("call_id", None)
tc.pop("response_item_id", None)
return sanitized
def convert_tools(self, tools: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
"""Tools are already in OpenAI format — identity."""
return tools
def build_kwargs(
self,
model: str,
messages: List[Dict[str, Any]],
tools: Optional[List[Dict[str, Any]]] = None,
**params,
) -> Dict[str, Any]:
"""Build chat.completions.create() kwargs.
This is the most complex transport method it handles ~16 providers
via params rather than subclasses.
params:
timeout: float API call timeout
max_tokens: int | None user-configured max tokens
ephemeral_max_output_tokens: int | None one-shot override (error recovery)
max_tokens_param_fn: callable returns {max_tokens: N} or {max_completion_tokens: N}
reasoning_config: dict | None
request_overrides: dict | None
session_id: str | None
qwen_session_metadata: dict | None {sessionId, promptId} precomputed
model_lower: str lowercase model name for pattern matching
# Provider detection flags (all optional, default False)
is_openrouter: bool
is_nous: bool
is_qwen_portal: bool
is_github_models: bool
is_nvidia_nim: bool
is_kimi: bool
is_lmstudio: bool
is_custom_provider: bool
ollama_num_ctx: int | None
# Provider routing
provider_preferences: dict | None
# Qwen-specific
qwen_prepare_fn: callable | None runs AFTER codex sanitization
qwen_prepare_inplace_fn: callable | None in-place variant for deepcopied lists
# Temperature
fixed_temperature: Any from _fixed_temperature_for_model()
omit_temperature: bool
# Reasoning
supports_reasoning: bool
github_reasoning_extra: dict | None
lmstudio_reasoning_options: list[str] | None # raw allowed_options from /api/v1/models
# Claude on OpenRouter/Nous max output
anthropic_max_output: int | None
# Extra
extra_body_additions: dict | None pre-built extra_body entries
"""
# Codex sanitization: drop reasoning_items / call_id / response_item_id
sanitized = self.convert_messages(messages)
# Qwen portal prep AFTER codex sanitization. If sanitize already
# deepcopied, reuse that copy via the in-place variant to avoid a
# second deepcopy.
is_qwen = params.get("is_qwen_portal", False)
if is_qwen:
qwen_prep = params.get("qwen_prepare_fn")
qwen_prep_inplace = params.get("qwen_prepare_inplace_fn")
if sanitized is messages:
if qwen_prep is not None:
sanitized = qwen_prep(sanitized)
else:
# Already deepcopied — transform in place
if qwen_prep_inplace is not None:
qwen_prep_inplace(sanitized)
elif qwen_prep is not None:
sanitized = qwen_prep(sanitized)
# Developer role swap for GPT-5/Codex models
model_lower = params.get("model_lower", (model or "").lower())
if (
sanitized
and isinstance(sanitized[0], dict)
and sanitized[0].get("role") == "system"
and any(p in model_lower for p in DEVELOPER_ROLE_MODELS)
):
sanitized = list(sanitized)
sanitized[0] = {**sanitized[0], "role": "developer"}
api_kwargs: Dict[str, Any] = {
"model": model,
"messages": sanitized,
}
timeout = params.get("timeout")
if timeout is not None:
api_kwargs["timeout"] = timeout
# Temperature
fixed_temp = params.get("fixed_temperature")
omit_temp = params.get("omit_temperature", False)
if omit_temp:
api_kwargs.pop("temperature", None)
elif fixed_temp is not None:
api_kwargs["temperature"] = fixed_temp
# Qwen metadata (caller precomputes {sessionId, promptId})
qwen_meta = params.get("qwen_session_metadata")
if qwen_meta and is_qwen:
api_kwargs["metadata"] = qwen_meta
# Tools
if tools:
# Moonshot/Kimi uses a stricter flavored JSON Schema. Rewriting
# tool parameters here keeps aggregator routes (Nous, OpenRouter,
# etc.) compatible, in addition to direct moonshot.ai endpoints.
if is_moonshot_model(model):
tools = sanitize_moonshot_tools(tools)
api_kwargs["tools"] = tools
# max_tokens resolution — priority: ephemeral > user > provider default
max_tokens_fn = params.get("max_tokens_param_fn")
ephemeral = params.get("ephemeral_max_output_tokens")
max_tokens = params.get("max_tokens")
anthropic_max_out = params.get("anthropic_max_output")
is_nvidia_nim = params.get("is_nvidia_nim", False)
is_kimi = params.get("is_kimi", False)
is_tokenhub = params.get("is_tokenhub", False)
reasoning_config = params.get("reasoning_config")
if ephemeral is not None and max_tokens_fn:
api_kwargs.update(max_tokens_fn(ephemeral))
elif max_tokens is not None and max_tokens_fn:
api_kwargs.update(max_tokens_fn(max_tokens))
elif is_nvidia_nim and max_tokens_fn:
api_kwargs.update(max_tokens_fn(16384))
elif is_qwen and max_tokens_fn:
api_kwargs.update(max_tokens_fn(65536))
elif is_kimi and max_tokens_fn:
# Kimi/Moonshot: 32000 matches Kimi CLI's default
api_kwargs.update(max_tokens_fn(32000))
elif anthropic_max_out is not None:
api_kwargs["max_tokens"] = anthropic_max_out
# Kimi: top-level reasoning_effort (unless thinking disabled)
if is_kimi:
_kimi_thinking_off = bool(
reasoning_config
and isinstance(reasoning_config, dict)
and reasoning_config.get("enabled") is False
)
if not _kimi_thinking_off:
_kimi_effort = "medium"
if reasoning_config and isinstance(reasoning_config, dict):
_e = (reasoning_config.get("effort") or "").strip().lower()
if _e in ("low", "medium", "high"):
_kimi_effort = _e
api_kwargs["reasoning_effort"] = _kimi_effort
# Tencent TokenHub: top-level reasoning_effort (unless thinking disabled)
if is_tokenhub:
_tokenhub_thinking_off = bool(
reasoning_config
and isinstance(reasoning_config, dict)
and reasoning_config.get("enabled") is False
)
if not _tokenhub_thinking_off:
_tokenhub_effort = "high"
if reasoning_config and isinstance(reasoning_config, dict):
_e = (reasoning_config.get("effort") or "").strip().lower()
if _e in ("low", "medium", "high"):
_tokenhub_effort = _e
api_kwargs["reasoning_effort"] = _tokenhub_effort
# LM Studio: top-level reasoning_effort. Only emit when the model
# declares reasoning support via /api/v1/models capabilities (gated
# upstream by params["supports_reasoning"]). resolve_lmstudio_effort
# is shared with run_agent's summary path so both stay in sync.
if params.get("is_lmstudio", False) and params.get("supports_reasoning", False):
_lm_effort = resolve_lmstudio_effort(
reasoning_config,
params.get("lmstudio_reasoning_options"),
)
if _lm_effort is not None:
api_kwargs["reasoning_effort"] = _lm_effort
# extra_body assembly
extra_body: Dict[str, Any] = {}
is_openrouter = params.get("is_openrouter", False)
is_nous = params.get("is_nous", False)
is_github_models = params.get("is_github_models", False)
provider_name = str(params.get("provider_name") or "").strip().lower()
base_url = params.get("base_url")
provider_prefs = params.get("provider_preferences")
if provider_prefs and is_openrouter:
extra_body["provider"] = provider_prefs
# Kimi extra_body.thinking
if is_kimi:
_kimi_thinking_enabled = True
if reasoning_config and isinstance(reasoning_config, dict):
if reasoning_config.get("enabled") is False:
_kimi_thinking_enabled = False
extra_body["thinking"] = {
"type": "enabled" if _kimi_thinking_enabled else "disabled",
}
# Reasoning. LM Studio is handled above via top-level reasoning_effort,
# so skip emitting extra_body.reasoning for it.
if params.get("supports_reasoning", False) and not params.get("is_lmstudio", False):
if is_github_models:
gh_reasoning = params.get("github_reasoning_extra")
if gh_reasoning is not None:
extra_body["reasoning"] = gh_reasoning
else:
if reasoning_config is not None:
rc = dict(reasoning_config)
if is_nous and rc.get("enabled") is False:
pass # omit for Nous when disabled
else:
extra_body["reasoning"] = rc
else:
extra_body["reasoning"] = {"enabled": True, "effort": "medium"}
if is_nous:
extra_body["tags"] = ["product=hermes-agent"]
# Ollama num_ctx
ollama_ctx = params.get("ollama_num_ctx")
if ollama_ctx:
options = extra_body.get("options", {})
options["num_ctx"] = ollama_ctx
extra_body["options"] = options
# Ollama/custom think=false
if params.get("is_custom_provider", False):
if reasoning_config and isinstance(reasoning_config, dict):
_effort = (reasoning_config.get("effort") or "").strip().lower()
_enabled = reasoning_config.get("enabled", True)
if _effort == "none" or _enabled is False:
extra_body["think"] = False
if is_qwen:
extra_body["vl_high_resolution_images"] = True
if provider_name == "gemini":
raw_thinking_config = _build_gemini_thinking_config(model, reasoning_config)
if _is_gemini_openai_compat_base_url(base_url):
thinking_config = _snake_case_gemini_thinking_config(raw_thinking_config)
if thinking_config:
openai_compat_extra = extra_body.get("extra_body", {})
google_extra = openai_compat_extra.get("google", {})
google_extra["thinking_config"] = thinking_config
openai_compat_extra["google"] = google_extra
extra_body["extra_body"] = openai_compat_extra
elif raw_thinking_config:
extra_body["thinking_config"] = raw_thinking_config
elif provider_name == "google-gemini-cli":
thinking_config = _build_gemini_thinking_config(model, reasoning_config)
if thinking_config:
extra_body["thinking_config"] = thinking_config
# Merge any pre-built extra_body additions
additions = params.get("extra_body_additions")
if additions:
extra_body.update(additions)
if extra_body:
api_kwargs["extra_body"] = extra_body
# Request overrides last (service_tier etc.)
overrides = params.get("request_overrides")
if overrides:
api_kwargs.update(overrides)
return api_kwargs
def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
"""Normalize OpenAI ChatCompletion to NormalizedResponse.
For chat_completions, this is near-identity the response is already
in OpenAI format. extra_content on tool_calls (Gemini thought_signature)
is preserved via ToolCall.provider_data. reasoning_details (OpenRouter
unified format) and reasoning_content (DeepSeek/Moonshot) are also
preserved for downstream replay.
"""
choice = response.choices[0]
msg = choice.message
finish_reason = choice.finish_reason or "stop"
tool_calls = None
if msg.tool_calls:
tool_calls = []
for tc in msg.tool_calls:
# Preserve provider-specific extras on the tool call.
# Gemini 3 thinking models attach extra_content with
# thought_signature — without replay on the next turn the API
# rejects the request with 400.
tc_provider_data: Dict[str, Any] = {}
extra = getattr(tc, "extra_content", None)
if extra is None and hasattr(tc, "model_extra"):
extra = (tc.model_extra or {}).get("extra_content")
if extra is not None:
if hasattr(extra, "model_dump"):
try:
extra = extra.model_dump()
except Exception:
pass
tc_provider_data["extra_content"] = extra
tool_calls.append(ToolCall(
id=tc.id,
name=tc.function.name,
arguments=tc.function.arguments,
provider_data=tc_provider_data or None,
))
usage = None
if hasattr(response, "usage") and response.usage:
u = response.usage
usage = Usage(
prompt_tokens=getattr(u, "prompt_tokens", 0) or 0,
completion_tokens=getattr(u, "completion_tokens", 0) or 0,
total_tokens=getattr(u, "total_tokens", 0) or 0,
)
# Preserve reasoning fields separately. DeepSeek/Moonshot use
# ``reasoning_content``; others use ``reasoning``. Downstream code
# (_extract_reasoning, thinking-prefill retry) reads both distinctly,
# so keep them apart in provider_data rather than merging.
reasoning = getattr(msg, "reasoning", None)
reasoning_content = getattr(msg, "reasoning_content", None)
if reasoning_content is None and hasattr(msg, "model_extra"):
model_extra = getattr(msg, "model_extra", None) or {}
if isinstance(model_extra, dict) and "reasoning_content" in model_extra:
reasoning_content = model_extra["reasoning_content"]
provider_data: Dict[str, Any] = {}
if reasoning_content is not None:
provider_data["reasoning_content"] = reasoning_content
rd = getattr(msg, "reasoning_details", None)
if rd:
provider_data["reasoning_details"] = rd
return NormalizedResponse(
content=msg.content,
tool_calls=tool_calls,
finish_reason=finish_reason,
reasoning=reasoning,
usage=usage,
provider_data=provider_data or None,
)
def validate_response(self, response: Any) -> bool:
"""Check that response has valid choices."""
if response is None:
return False
if not hasattr(response, "choices") or response.choices is None:
return False
if not response.choices:
return False
return True
def extract_cache_stats(self, response: Any) -> Optional[Dict[str, int]]:
"""Extract OpenRouter/OpenAI cache stats from prompt_tokens_details."""
usage = getattr(response, "usage", None)
if usage is None:
return None
details = getattr(usage, "prompt_tokens_details", None)
if details is None:
return None
cached = getattr(details, "cached_tokens", 0) or 0
written = getattr(details, "cache_write_tokens", 0) or 0
if cached or written:
return {"cached_tokens": cached, "creation_tokens": written}
return None
# Auto-register on import
from agent.transports import register_transport # noqa: E402
register_transport("chat_completions", ChatCompletionsTransport)
-246
View File
@@ -1,246 +0,0 @@
"""OpenAI Responses API (Codex) transport.
Delegates to the existing adapter functions in agent/codex_responses_adapter.py.
This transport owns format conversion and normalization NOT client lifecycle,
streaming, or the _run_codex_stream() call path.
"""
from typing import Any, Dict, List, Optional
from agent.transports.base import ProviderTransport
from agent.transports.types import NormalizedResponse, ToolCall
class ResponsesApiTransport(ProviderTransport):
"""Transport for api_mode='codex_responses'.
Wraps the functions extracted into codex_responses_adapter.py (PR 1).
"""
@property
def api_mode(self) -> str:
return "codex_responses"
def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> Any:
"""Convert OpenAI chat messages to Responses API input items."""
from agent.codex_responses_adapter import _chat_messages_to_responses_input
return _chat_messages_to_responses_input(messages)
def convert_tools(self, tools: List[Dict[str, Any]]) -> Any:
"""Convert OpenAI tool schemas to Responses API function definitions."""
from agent.codex_responses_adapter import _responses_tools
return _responses_tools(tools)
def build_kwargs(
self,
model: str,
messages: List[Dict[str, Any]],
tools: Optional[List[Dict[str, Any]]] = None,
**params,
) -> Dict[str, Any]:
"""Build Responses API kwargs.
Calls convert_messages and convert_tools internally.
params:
instructions: str system prompt (extracted from messages[0] if not given)
reasoning_config: dict | None {effort, enabled}
session_id: str | None used for prompt_cache_key + xAI conv header
max_tokens: int | None max_output_tokens
request_overrides: dict | None extra kwargs merged in
provider: str | None provider name for backend-specific logic
base_url: str | None endpoint URL
base_url_hostname: str | None hostname for backend detection
is_github_responses: bool Copilot/GitHub models backend
is_codex_backend: bool chatgpt.com/backend-api/codex
is_xai_responses: bool xAI/Grok backend
github_reasoning_extra: dict | None Copilot reasoning params
"""
from agent.codex_responses_adapter import (
_chat_messages_to_responses_input,
_responses_tools,
)
from run_agent import DEFAULT_AGENT_IDENTITY
instructions = params.get("instructions", "")
payload_messages = messages
if not instructions:
if messages and messages[0].get("role") == "system":
instructions = str(messages[0].get("content") or "").strip()
payload_messages = messages[1:]
if not instructions:
instructions = DEFAULT_AGENT_IDENTITY
is_github_responses = params.get("is_github_responses", False)
is_codex_backend = params.get("is_codex_backend", False)
is_xai_responses = params.get("is_xai_responses", False)
# Resolve reasoning effort
reasoning_effort = "medium"
reasoning_enabled = True
reasoning_config = params.get("reasoning_config")
if reasoning_config and isinstance(reasoning_config, dict):
if reasoning_config.get("enabled") is False:
reasoning_enabled = False
elif reasoning_config.get("effort"):
reasoning_effort = reasoning_config["effort"]
_effort_clamp = {"minimal": "low"}
reasoning_effort = _effort_clamp.get(reasoning_effort, reasoning_effort)
kwargs = {
"model": model,
"instructions": instructions,
"input": _chat_messages_to_responses_input(payload_messages),
"tools": _responses_tools(tools),
"tool_choice": "auto",
"parallel_tool_calls": True,
"store": False,
}
session_id = params.get("session_id")
if not is_github_responses and session_id:
kwargs["prompt_cache_key"] = session_id
if reasoning_enabled and is_xai_responses:
kwargs["include"] = ["reasoning.encrypted_content"]
elif reasoning_enabled:
if is_github_responses:
github_reasoning = params.get("github_reasoning_extra")
if github_reasoning is not None:
kwargs["reasoning"] = github_reasoning
else:
kwargs["reasoning"] = {"effort": reasoning_effort, "summary": "auto"}
kwargs["include"] = ["reasoning.encrypted_content"]
elif not is_github_responses and not is_xai_responses:
kwargs["include"] = []
request_overrides = params.get("request_overrides")
if request_overrides:
kwargs.update(request_overrides)
if is_codex_backend:
prompt_cache_key = kwargs.get("prompt_cache_key")
cache_scope_id = str(prompt_cache_key or session_id or "").strip()
if cache_scope_id:
existing_extra_headers = kwargs.get("extra_headers")
merged_extra_headers: Dict[str, str] = {}
if isinstance(existing_extra_headers, dict):
merged_extra_headers.update(
{
str(key): str(value)
for key, value in existing_extra_headers.items()
if key and value is not None
}
)
merged_extra_headers["session_id"] = cache_scope_id
merged_extra_headers["x-client-request-id"] = cache_scope_id
kwargs["extra_headers"] = merged_extra_headers
max_tokens = params.get("max_tokens")
if max_tokens is not None and not is_codex_backend:
kwargs["max_output_tokens"] = max_tokens
if is_xai_responses and session_id:
existing_extra_headers = kwargs.get("extra_headers")
merged_extra_headers: Dict[str, str] = {}
if isinstance(existing_extra_headers, dict):
merged_extra_headers.update(
{
str(key): str(value)
for key, value in existing_extra_headers.items()
if key and value is not None
}
)
merged_extra_headers["x-grok-conv-id"] = session_id
kwargs["extra_headers"] = merged_extra_headers
return kwargs
def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
"""Normalize Codex Responses API response to NormalizedResponse."""
from agent.codex_responses_adapter import (
_normalize_codex_response,
)
# _normalize_codex_response returns (SimpleNamespace, finish_reason_str)
msg, finish_reason = _normalize_codex_response(response)
tool_calls = None
if msg and msg.tool_calls:
tool_calls = []
for tc in msg.tool_calls:
provider_data = {}
if hasattr(tc, "call_id") and tc.call_id:
provider_data["call_id"] = tc.call_id
if hasattr(tc, "response_item_id") and tc.response_item_id:
provider_data["response_item_id"] = tc.response_item_id
tool_calls.append(ToolCall(
id=tc.id if hasattr(tc, "id") else (tc.function.name if hasattr(tc, "function") else None),
name=tc.function.name if hasattr(tc, "function") else getattr(tc, "name", ""),
arguments=tc.function.arguments if hasattr(tc, "function") else getattr(tc, "arguments", "{}"),
provider_data=provider_data or None,
))
# Extract reasoning items for provider_data
provider_data = {}
if msg and hasattr(msg, "codex_reasoning_items") and msg.codex_reasoning_items:
provider_data["codex_reasoning_items"] = msg.codex_reasoning_items
if msg and hasattr(msg, "codex_message_items") and msg.codex_message_items:
provider_data["codex_message_items"] = msg.codex_message_items
if msg and hasattr(msg, "reasoning_details") and msg.reasoning_details:
provider_data["reasoning_details"] = msg.reasoning_details
return NormalizedResponse(
content=msg.content if msg else None,
tool_calls=tool_calls,
finish_reason=finish_reason or "stop",
reasoning=msg.reasoning if msg and hasattr(msg, "reasoning") else None,
usage=None, # Codex usage is extracted separately in normalize_usage()
provider_data=provider_data or None,
)
def validate_response(self, response: Any) -> bool:
"""Check Codex Responses API response has valid output structure.
Returns True only if response.output is a non-empty list.
Does NOT check output_text fallback the caller handles that
with diagnostic logging for stream backfill recovery.
"""
if response is None:
return False
output = getattr(response, "output", None)
if not isinstance(output, list) or not output:
return False
return True
def preflight_kwargs(self, api_kwargs: Any, *, allow_stream: bool = False) -> dict:
"""Validate and sanitize Codex API kwargs before the call.
Normalizes input items, strips unsupported fields, validates structure.
"""
from agent.codex_responses_adapter import _preflight_codex_api_kwargs
return _preflight_codex_api_kwargs(api_kwargs, allow_stream=allow_stream)
def map_finish_reason(self, raw_reason: str) -> str:
"""Map Codex response.status to OpenAI finish_reason.
Codex uses response.status ('completed', 'incomplete') +
response.incomplete_details.reason for granular mapping.
This method handles the simple status string; the caller
should check incomplete_details separately for 'max_output_tokens'.
"""
_MAP = {
"completed": "stop",
"incomplete": "length",
"failed": "stop",
"cancelled": "stop",
}
return _MAP.get(raw_reason, "stop")
# Auto-register on import
from agent.transports import register_transport # noqa: E402
register_transport("codex_responses", ResponsesApiTransport)
+1 -62
View File
@@ -37,44 +37,6 @@ class ToolCall:
arguments: str # JSON string
provider_data: Optional[Dict[str, Any]] = field(default=None, repr=False)
# ── Backward compatibility ──────────────────────────────────
# The agent loop reads tc.function.name / tc.function.arguments
# throughout run_agent.py (45+ sites). These properties let
# NormalizedResponse pass through without the _nr_to_assistant_message
# shim, while keeping ToolCall's canonical fields flat.
@property
def type(self) -> str:
return "function"
@property
def function(self) -> "ToolCall":
"""Return self so tc.function.name / tc.function.arguments work."""
return self
@property
def call_id(self) -> Optional[str]:
"""Codex call_id from provider_data, accessed via getattr by _build_assistant_message."""
return (self.provider_data or {}).get("call_id")
@property
def response_item_id(self) -> Optional[str]:
"""Codex response_item_id from provider_data."""
return (self.provider_data or {}).get("response_item_id")
@property
def extra_content(self) -> Optional[Dict[str, Any]]:
"""Gemini extra_content (thought_signature) from provider_data.
Gemini 3 thinking models attach ``extra_content`` with a
``thought_signature`` to each tool call. This signature must be
replayed on subsequent API calls without it the API rejects the
request with HTTP 400. The chat_completions transport stores this
in ``provider_data["extra_content"]``; this property exposes it so
``_build_assistant_message`` can ``getattr(tc, "extra_content")``
uniformly.
"""
return (self.provider_data or {}).get("extra_content")
@dataclass
class Usage:
@@ -97,7 +59,7 @@ class NormalizedResponse:
Response-level ``provider_data`` examples:
* Anthropic: ``{"reasoning_details": [...]}``
* Codex: ``{"codex_reasoning_items": [...], "codex_message_items": [...]}``
* Codex: ``{"codex_reasoning_items": [...]}``
* Others: ``None``
"""
@@ -108,29 +70,6 @@ class NormalizedResponse:
usage: Optional[Usage] = None
provider_data: Optional[Dict[str, Any]] = field(default=None, repr=False)
# ── Backward compatibility ──────────────────────────────────
# The shim _nr_to_assistant_message() mapped these from provider_data.
# These properties let NormalizedResponse pass through directly.
@property
def reasoning_content(self) -> Optional[str]:
pd = self.provider_data or {}
return pd.get("reasoning_content")
@property
def reasoning_details(self):
pd = self.provider_data or {}
return pd.get("reasoning_details")
@property
def codex_reasoning_items(self):
pd = self.provider_data or {}
return pd.get("codex_reasoning_items")
@property
def codex_message_items(self):
pd = self.provider_data or {}
return pd.get("codex_message_items")
# ---------------------------------------------------------------------------
# Factory helpers
-33
View File
@@ -359,25 +359,6 @@ _OFFICIAL_DOCS_PRICING: Dict[tuple[str, str], PricingEntry] = {
source_url="https://aws.amazon.com/bedrock/pricing/",
pricing_version="bedrock-pricing-2026-04",
),
# MiniMax
(
"minimax",
"minimax-m2.7",
): PricingEntry(
input_cost_per_million=Decimal("0.30"),
output_cost_per_million=Decimal("1.20"),
source="official_docs_snapshot",
pricing_version="minimax-pricing-2026-04",
),
(
"minimax-cn",
"minimax-m2.7",
): PricingEntry(
input_cost_per_million=Decimal("0.30"),
output_cost_per_million=Decimal("1.20"),
source="official_docs_snapshot",
pricing_version="minimax-pricing-2026-04",
),
}
@@ -419,8 +400,6 @@ def resolve_billing_route(
return BillingRoute(provider="anthropic", model=model.split("/")[-1], base_url=base_url or "", billing_mode="official_docs_snapshot")
if provider_name == "openai":
return BillingRoute(provider="openai", model=model.split("/")[-1], base_url=base_url or "", billing_mode="official_docs_snapshot")
if provider_name in {"minimax", "minimax-cn"}:
return BillingRoute(provider=provider_name, model=model.split("/")[-1], base_url=base_url or "", billing_mode="official_docs_snapshot")
if provider_name in {"custom", "local"} or (base and "localhost" in base):
return BillingRoute(provider=provider_name or "custom", model=model, base_url=base_url or "", billing_mode="unknown")
return BillingRoute(provider=provider_name or "unknown", model=model.split("/")[-1] if model else "", base_url=base_url or "", billing_mode="unknown")
@@ -554,22 +533,10 @@ def normalize_usage(
prompt_total = _to_int(getattr(response_usage, "prompt_tokens", 0))
output_tokens = _to_int(getattr(response_usage, "completion_tokens", 0))
details = getattr(response_usage, "prompt_tokens_details", None)
# Primary: OpenAI-style prompt_tokens_details. Fallback: Anthropic-style
# top-level fields that some OpenAI-compatible proxies (OpenRouter, Vercel
# AI Gateway, Cline) expose when routing Claude models — without this
# fallback, cache writes are undercounted as 0 and cache reads can be
# missed when the proxy only surfaces them at the top level.
# Port of cline/cline#10266.
cache_read_tokens = _to_int(getattr(details, "cached_tokens", 0) if details else 0)
if not cache_read_tokens:
cache_read_tokens = _to_int(getattr(response_usage, "cache_read_input_tokens", 0))
cache_write_tokens = _to_int(
getattr(details, "cache_write_tokens", 0) if details else 0
)
if not cache_write_tokens:
cache_write_tokens = _to_int(
getattr(response_usage, "cache_creation_input_tokens", 0)
)
input_tokens = max(0, prompt_total - cache_read_tokens - cache_write_tokens)
reasoning_tokens = 0
+6 -2
View File
@@ -951,9 +951,13 @@ class BatchRunner:
root_logger.setLevel(original_level)
# Aggregate all batch statistics and update checkpoint
all_completed_prompts = list(completed_prompts_set)
total_reasoning_stats = {"total_assistant_turns": 0, "turns_with_reasoning": 0, "turns_without_reasoning": 0}
for batch_result in results:
# Add newly completed prompts
all_completed_prompts.extend(batch_result.get("completed_prompts", []))
# Aggregate tool stats
for tool_name, stats in batch_result.get("tool_stats", {}).items():
if tool_name not in total_tool_stats:
@@ -973,7 +977,7 @@ class BatchRunner:
# Save final checkpoint (best-effort; incremental writes already happened)
try:
checkpoint_data["completed_prompts"] = sorted(completed_prompts_set)
checkpoint_data["completed_prompts"] = all_completed_prompts
self._save_checkpoint(checkpoint_data, lock=checkpoint_lock)
except Exception as ckpt_err:
print(f"⚠️ Warning: Failed to save final checkpoint: {ckpt_err}")
+18 -100
View File
@@ -30,13 +30,14 @@ model:
# "ollama-cloud" - Ollama Cloud (requires: OLLAMA_API_KEY — https://ollama.com/settings)
# "kilocode" - KiloCode gateway (requires: KILOCODE_API_KEY)
# "ai-gateway" - Vercel AI Gateway (requires: AI_GATEWAY_API_KEY)
# "lmstudio" - LM Studio local server (optional: LM_API_KEY, defaults to http://127.0.0.1:1234/v1)
#
# Local servers (LM Studio, Ollama, vLLM, llama.cpp):
# "custom" - Any other OpenAI-compatible endpoint. Set base_url below.
# Aliases: "ollama", "vllm", "llamacpp" all map to "custom".
# LM Studio is first-class and uses provider: "lmstudio".
# It works with both no-auth and auth-enabled server modes.
# "custom" - Any OpenAI-compatible endpoint. Set base_url below.
# Aliases: "lmstudio", "ollama", "vllm", "llamacpp" all map to "custom".
# Example for LM Studio:
# provider: "lmstudio"
# base_url: "http://localhost:1234/v1"
# No API key needed — local servers typically ignore auth.
#
# Can also be overridden with --provider flag or HERMES_INFERENCE_PROVIDER env var.
provider: "auto"
@@ -121,18 +122,6 @@ model:
# # Data policy: "allow" (default) or "deny" to exclude providers that may store data
# # data_collection: "deny"
# =============================================================================
# OpenRouter Response Caching (only applies when using OpenRouter)
# =============================================================================
# Cache identical API responses at the OpenRouter edge for free instant replays.
# When enabled, identical requests (same model, messages, parameters) return
# cached responses with zero billing. Separate from Anthropic prompt caching.
# See: https://openrouter.ai/docs/guides/features/response-caching
#
# openrouter:
# response_cache: true # Enable response caching (default: true)
# response_cache_ttl: 300 # Cache TTL in seconds, 1-86400 (default: 300)
# =============================================================================
# Git Worktree Isolation
# =============================================================================
@@ -192,11 +181,6 @@ terminal:
# lifetime_seconds: 300
# docker_image: "nikolaik/python-nodejs:python3.11-nodejs20"
# docker_mount_cwd_to_workspace: true # Explicit opt-in: mount your launch cwd into /workspace
# # Optional: run the container as your host user's uid:gid so files written
# # into bind-mounted dirs are owned by you, not root. Drops SETUID/SETGID
# # caps too since no gosu privilege drop is needed. Leave off if your
# # chosen docker_image expects to start as root.
# docker_run_as_host_user: true
# # Optional: explicitly forward selected env vars into Docker.
# # These values come from your current shell first, then ~/.hermes/.env.
# # Warning: anything forwarded here is visible to commands run in the container.
@@ -301,25 +285,6 @@ browser:
# after this period of no activity between agent loops (default: 120 = 2 minutes)
inactivity_timeout: 120
# =============================================================================
# Tool Loop Guardrails
# =============================================================================
# Soft warnings are enabled by default. They append guidance to repeated failed
# or non-progressing tool results but still let the tool execute. Hard stops are
# opt-in circuit breakers for autonomous/cron sessions where stopping a loop is
# preferable to spending the full iteration budget.
tool_loop_guardrails:
warnings_enabled: true
hard_stop_enabled: false
warn_after:
exact_failure: 2
same_tool_failure: 3
idempotent_no_progress: 2
hard_stop_after:
exact_failure: 5
same_tool_failure: 8
idempotent_no_progress: 5
# =============================================================================
# Context Compression (Auto-shrinks long conversations)
# =============================================================================
@@ -361,16 +326,6 @@ compression:
# To pin a specific model/provider for compression summaries, use the
# auxiliary section below (auxiliary.compression.provider / model).
# =============================================================================
# Anthropic prompt caching TTL
# =============================================================================
# When prompt caching is active (Claude via OpenRouter or native Anthropic),
# Anthropic supports two TTL tiers for cached prefixes: "5m" (default) and
# "1h". Other values are ignored and "5m" is used.
#
prompt_caching:
cache_ttl: "5m" # use "1h" for long sessions with pauses between turns
# =============================================================================
# Auxiliary Models (Advanced — Experimental)
# =============================================================================
@@ -552,13 +507,6 @@ agent:
# finish, then interrupts anything still running after this timeout.
# 0 = no drain, interrupt immediately.
# restart_drain_timeout: 60
# Max app-level retry attempts for API errors (connection drops, provider
# timeouts, 5xx, etc.) before the agent surfaces the failure. Lower this
# to 1 if you use fallback providers and want fast failover on flaky
# primaries (default 3). The OpenAI SDK does its own low-level retries
# underneath this wrapper — this is the Hermes-level loop.
# api_max_retries: 3
# Enable verbose logging
verbose: false
@@ -601,7 +549,7 @@ agent:
# - A preset like "hermes-cli" or "hermes-telegram" (curated tool set)
# - A list of individual toolsets to compose your own (see list below)
#
# Supported platform keys: cli, telegram, discord, whatsapp, slack, qqbot, teams
# Supported platform keys: cli, telegram, discord, whatsapp, slack, qqbot
#
# Examples:
#
@@ -631,7 +579,6 @@ agent:
# signal: hermes-signal (same as telegram)
# homeassistant: hermes-homeassistant (same as telegram)
# qqbot: hermes-qqbot (same as telegram)
# teams: hermes-teams (same as telegram)
#
platform_toolsets:
cli: [hermes-cli]
@@ -642,8 +589,6 @@ platform_toolsets:
signal: [hermes-signal]
homeassistant: [hermes-homeassistant]
qqbot: [hermes-qqbot]
yuanbao: [hermes-yuanbao]
teams: [hermes-teams]
# =============================================================================
# Gateway Platform Settings
@@ -828,17 +773,9 @@ code_execution:
# Supports single tasks and batch mode (default 3 parallel, configurable).
delegation:
max_iterations: 50 # Max tool-calling turns per child (default: 50)
# max_concurrent_children: 3 # Max parallel child agents per batch (default: 3, floor: 1, no ceiling).
# WARNING: values above 10 multiply API cost linearly.
# max_spawn_depth: 1 # Delegation tree depth cap (range: 1-3, default: 1 = flat).
# Raise to 2 to allow workers to spawn their own subagents.
# Requires role="orchestrator" on intermediate agents.
# max_concurrent_children: 3 # Max parallel child agents (default: 3)
# max_spawn_depth: 1 # Tree depth cap (1-3, default: 1 = flat). Raise to 2 or 3 to allow orchestrator children to spawn their own workers.
# orchestrator_enabled: true # Kill switch for role="orchestrator" children (default: true).
# subagent_auto_approve: false # When a subagent hits a dangerous-command approval prompt, auto-deny (default: false)
# or auto-approve "once" (true) instead of blocking on stdin.
# The parent TUI owns stdin, so blocking would deadlock; non-interactive resolution is required.
# Both choices emit a logger.warning audit line. Flip to true only for cron/batch pipelines.
# inherit_mcp_toolsets: true # When explicit child toolsets are narrowed, also keep the parent's MCP toolsets (default: true). Set false for strict intersection.
# model: "google/gemini-3-flash-preview" # Override model for subagents (empty = inherit parent)
# provider: "openrouter" # Override provider for subagents (empty = inherit parent)
# # Resolves full credentials (base_url, api_key) automatically.
@@ -862,9 +799,7 @@ delegation:
# Display
# =============================================================================
display:
# Use compact banner mode (hides the ASCII-art banner, shows a single line).
# true: Compact single-line banner
# false: Full ASCII banner with tool/skill summary (default)
# Use compact banner mode
compact: false
# Tool progress display level (CLI and gateway)
@@ -878,19 +813,12 @@ display:
# Gateway-only natural mid-turn assistant updates.
# When true, completed assistant status messages are sent as separate chat
# messages. This is independent of tool_progress and gateway streaming.
# true: Send mid-turn assistant updates as separate messages (default)
# false: Only send the final response
interim_assistant_messages: true
# What Enter does when Hermes is already busy (CLI and gateway platforms).
# What Enter does when Hermes is already busy in the CLI.
# interrupt: Interrupt the current run and redirect Hermes (default)
# queue: Queue your message for the next turn
# steer: Inject your message mid-run via /steer, arriving at the agent
# after the next tool call — no interrupt, no role violation.
# Falls back to 'queue' if the agent isn't running yet or if
# images are attached (steer only carries text).
# Ctrl+C (or /stop in gateway) always interrupts regardless of this setting.
# Toggle at runtime with /busy <interrupt|queue|steer>.
# Ctrl+C always interrupts regardless of this setting.
busy_input_mode: interrupt
# Background process notifications (gateway/messaging only).
@@ -906,22 +834,17 @@ display:
# Play terminal bell when agent finishes a response.
# Useful for long-running tasks — your terminal will ding when the agent is done.
# Works over SSH. Most terminals can be configured to flash the taskbar or play a sound.
# true: Ring the terminal bell on each response
# false: Silent (default)
bell_on_complete: false
# Show model reasoning/thinking before each response.
# When enabled, a dim box shows the model's thought process above the response.
# Toggle at runtime with /reasoning show or /reasoning hide.
# true: Show the reasoning box
# false: Hide reasoning (default)
show_reasoning: false
# Stream tokens to the terminal as they arrive instead of waiting for the
# full response. The response box opens on first token and text appears
# line-by-line. Tool calls are still captured silently.
# true: Stream tokens as they arrive (default)
# false: Wait for the full response before rendering
# Stream tokens to the terminal in real-time. Disable to wait for full responses.
streaming: true
# ───────────────────────────────────────────────────────────────────────────
@@ -931,15 +854,10 @@ display:
# response box label, and branding text. Change at runtime with /skin <name>.
#
# Built-in skins:
# default — Classic Hermes gold/kawaii
# ares — Crimson/bronze war-god theme with spinner wings
# mono — Clean grayscale monochrome
# slate — Cool blue developer-focused
# daylight — Bright light-mode theme
# warm-lightmode — Warm paper-tone light-mode theme
# poseidon — Sea-green/teal Olympian theme
# sisyphus — Earthy stone-and-moss theme
# charizard — Fiery orange dragon theme
# default — Classic Hermes gold/kawaii
# ares — Crimson/bronze war-god theme with spinner wings
# mono — Clean grayscale monochrome
# slate — Cool blue developer-focused
#
# Custom skins: drop a YAML file in ~/.hermes/skins/<name>.yaml
# Schema (all fields optional, missing values inherit from default):
@@ -965,7 +883,7 @@ display:
# agent_name: "My Agent" # Banner title and branding
# welcome: "Welcome message" # Shown at CLI startup
# response_label: " ⚔ Agent " # Response box header label
# prompt_symbol: "⚔" # Prompt symbol (bare token; renderers add trailing space)
# prompt_symbol: "⚔ " # Prompt symbol
# tool_prefix: "╎" # Tool output line prefix (default: ┊)
#
skin: default
+561 -1590
View File
File diff suppressed because it is too large Load Diff
+9 -252
View File
@@ -16,12 +16,11 @@ import uuid
from datetime import datetime, timedelta
from pathlib import Path
from hermes_constants import get_hermes_home
from typing import Optional, Dict, List, Any, Union
from typing import Optional, Dict, List, Any
logger = logging.getLogger(__name__)
from hermes_time import now as _hermes_now
from utils import atomic_replace
try:
from croniter import croniter
@@ -312,22 +311,8 @@ def compute_next_run(schedule: Dict[str, Any], last_run_at: Optional[str] = None
elif schedule["kind"] == "cron":
if not HAS_CRONITER:
logger.warning(
"Cannot compute next run for cron schedule %r: 'croniter' is "
"not installed. croniter is a core dependency as of v0.9.x; "
"reinstall hermes-agent or run 'pip install croniter' in your "
"runtime env.",
schedule.get("expr"),
)
return None
# Use last_run_at as the croniter base when available, consistent
# with interval jobs. This ensures that after a crash/restart,
# the next run is anchored to the actual last execution time
# rather than to an arbitrary restart time.
base_time = now
if last_run_at:
base_time = _ensure_aware(datetime.fromisoformat(last_run_at))
cron = croniter(schedule["expr"], base_time)
cron = croniter(schedule["expr"], now)
next_run = cron.get_next(datetime)
return next_run.isoformat()
@@ -376,7 +361,7 @@ def save_jobs(jobs: List[Dict[str, Any]]):
json.dump({"jobs": jobs, "updated_at": _hermes_now().isoformat()}, f, indent=2)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, JOBS_FILE)
os.replace(tmp_path, JOBS_FILE)
_secure_file(JOBS_FILE)
except BaseException:
try:
@@ -386,39 +371,6 @@ def save_jobs(jobs: List[Dict[str, Any]]):
raise
def _normalize_workdir(workdir: Optional[str]) -> Optional[str]:
"""Normalize and validate a cron job workdir.
Rules:
- Empty / None None (feature off, preserves old behaviour).
- ``~`` is expanded. Relative paths are rejected cron jobs run detached
from any shell cwd, so relative paths have no stable meaning.
- The path must exist and be a directory at create/update time. We do
NOT re-check at run time (a user might briefly unmount the dir; the
scheduler will just fall back to old behaviour with a logged warning).
Returns the absolute path string, or None when disabled.
Raises ValueError on invalid input.
"""
if workdir is None:
return None
raw = str(workdir).strip()
if not raw:
return None
expanded = Path(raw).expanduser()
if not expanded.is_absolute():
raise ValueError(
f"Cron workdir must be an absolute path (got {raw!r}). "
f"Cron jobs run detached from any shell cwd, so relative paths are ambiguous."
)
resolved = expanded.resolve()
if not resolved.exists():
raise ValueError(f"Cron workdir does not exist: {resolved}")
if not resolved.is_dir():
raise ValueError(f"Cron workdir is not a directory: {resolved}")
return str(resolved)
def create_job(
prompt: str,
schedule: str,
@@ -432,9 +384,6 @@ def create_job(
provider: Optional[str] = None,
base_url: Optional[str] = None,
script: Optional[str] = None,
context_from: Optional[Union[str, List[str]]] = None,
enabled_toolsets: Optional[List[str]] = None,
workdir: Optional[str] = None,
) -> Dict[str, Any]:
"""
Create a new cron job.
@@ -454,18 +403,6 @@ def create_job(
script: Optional path to a Python script whose stdout is injected into the
prompt each run. The script runs before the agent turn, and its output
is prepended as context. Useful for data collection / change detection.
context_from: Optional job ID (or list of job IDs) whose most recent output
is injected into the prompt as context before each run.
Useful for chaining cron jobs: job A finds data, job B processes it.
enabled_toolsets: Optional list of toolset names to restrict the agent to.
When set, only tools from these toolsets are loaded, reducing
token overhead. When omitted, all default tools are loaded.
workdir: Optional absolute path. When set, the job runs as if launched
from that directory: AGENTS.md / CLAUDE.md / .cursorrules from
that directory are injected into the system prompt, and the
terminal/file/code_exec tools use it as their working directory
(via TERMINAL_CWD). When unset, the old behaviour is preserved
(no context files injected, tools use the scheduler's cwd).
Returns:
The created job dict
@@ -496,17 +433,6 @@ def create_job(
normalized_base_url = normalized_base_url or None
normalized_script = str(script).strip() if isinstance(script, str) else None
normalized_script = normalized_script or None
normalized_toolsets = [str(t).strip() for t in enabled_toolsets if str(t).strip()] if enabled_toolsets else None
normalized_toolsets = normalized_toolsets or None
normalized_workdir = _normalize_workdir(workdir)
# Normalize context_from: accept str or list of str, store as list or None
if isinstance(context_from, str):
context_from = [context_from.strip()] if context_from.strip() else None
elif isinstance(context_from, list):
context_from = [str(j).strip() for j in context_from if str(j).strip()] or None
else:
context_from = None
label_source = (prompt or (normalized_skills[0] if normalized_skills else None)) or "cron job"
job = {
@@ -519,7 +445,6 @@ def create_job(
"provider": normalized_provider,
"base_url": normalized_base_url,
"script": normalized_script,
"context_from": context_from,
"schedule": parsed_schedule,
"schedule_display": parsed_schedule.get("display", schedule),
"repeat": {
@@ -539,8 +464,6 @@ def create_job(
# Delivery configuration
"deliver": deliver,
"origin": origin, # Tracks where job was created for "origin" delivery
"enabled_toolsets": normalized_toolsets,
"workdir": normalized_workdir,
}
jobs = load_jobs()
@@ -574,15 +497,6 @@ def update_job(job_id: str, updates: Dict[str, Any]) -> Optional[Dict[str, Any]]
if job["id"] != job_id:
continue
# Validate / normalize workdir if present in updates. Empty string or
# None both mean "clear the field" (restore old behaviour).
if "workdir" in updates:
_wd = updates["workdir"]
if _wd in (None, "", False):
updates["workdir"] = None
else:
updates["workdir"] = _normalize_workdir(_wd)
updated = _apply_skill_fields({**job, **updates})
schedule_changed = "schedule" in updates
@@ -713,32 +627,10 @@ def mark_job_run(job_id: str, success: bool, error: Optional[str] = None,
# Compute next run
job["next_run_at"] = compute_next_run(job["schedule"], now)
# If no next run, decide whether this is terminal completion
# (one-shot) or a transient failure (recurring schedule couldn't
# compute — e.g. 'croniter' missing from the runtime env).
# Recurring jobs must NEVER be silently disabled: that turns a
# missing runtime dep into "job completed" and the user's
# schedule quietly goes off. See issue #16265.
# If no next run (one-shot completed), disable
if job["next_run_at"] is None:
kind = job.get("schedule", {}).get("kind")
if kind in ("cron", "interval"):
job["state"] = "error"
if not job.get("last_error"):
job["last_error"] = (
"Failed to compute next run for recurring "
"schedule (is the 'croniter' package "
"installed in the gateway's Python env?)"
)
logger.error(
"Job '%s' (%s) could not compute next_run_at; "
"leaving enabled and marking state=error so the "
"job is not silently disabled.",
job.get("name", job["id"]),
kind,
)
else:
job["enabled"] = False
job["state"] = "completed"
job["enabled"] = False
job["state"] = "completed"
elif job.get("state") != "paused":
job["state"] = "scheduled"
@@ -797,36 +689,19 @@ def get_due_jobs() -> List[Dict[str, Any]]:
next_run = job.get("next_run_at")
if not next_run:
schedule = job.get("schedule", {})
kind = schedule.get("kind")
# One-shot jobs use a small grace window via the dedicated helper.
recovered_next = _recoverable_oneshot_run_at(
schedule,
job.get("schedule", {}),
now,
last_run_at=job.get("last_run_at"),
)
recovery_kind = "one-shot" if recovered_next else None
# Recurring jobs reach here only when something — typically a
# direct jobs.json edit that bypassed add_job() — left
# next_run_at unset. Without this branch, such jobs are
# silently skipped forever; recompute next_run_at from the
# schedule so they pick up at their next scheduled tick.
if not recovered_next and kind in ("cron", "interval"):
recovered_next = compute_next_run(schedule, now.isoformat())
if recovered_next:
recovery_kind = kind
if not recovered_next:
continue
job["next_run_at"] = recovered_next
next_run = recovered_next
logger.info(
"Job '%s' had no next_run_at; recovering %s run at %s",
"Job '%s' had no next_run_at; recovering one-shot run at %s",
job.get("name", job["id"]),
recovery_kind,
recovered_next,
)
for rj in raw_jobs:
@@ -889,7 +764,7 @@ def save_job_output(job_id: str, output: str):
f.write(output)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, output_file)
os.replace(tmp_path, output_file)
_secure_file(output_file)
except BaseException:
try:
@@ -899,121 +774,3 @@ def save_job_output(job_id: str, output: str):
raise
return output_file
# =============================================================================
# Skill reference rewriting (curator integration)
# =============================================================================
def rewrite_skill_refs(
consolidated: Optional[Dict[str, str]] = None,
pruned: Optional[List[str]] = None,
) -> Dict[str, Any]:
"""Rewrite cron job skill references after a curator consolidation pass.
When the curator consolidates a skill X into umbrella Y (or archives X
as pruned), any cron job that lists ``X`` in its ``skills`` field will
fail to load ``X`` at run time the scheduler logs a warning and
skips the skill, so the job runs without the instructions it was
scheduled to follow. See cron/scheduler.py where ``skill_view`` is
called per skill name.
This function repairs cron jobs in-place:
- A skill listed in ``consolidated`` is replaced with its umbrella
target (the ``into`` value). If the umbrella is already in the
job's skill list, the stale name is dropped without duplication.
- A skill listed in ``pruned`` is dropped outright there is no
forwarding target.
- Ordering and other skills in the list are preserved.
- The legacy ``skill`` field is realigned via ``_apply_skill_fields``.
Args:
consolidated: mapping of ``old_skill_name -> umbrella_skill_name``.
pruned: list of skill names that were archived with no forwarding
target.
Returns a report dict::
{
"rewrites": [
{
"job_id": ...,
"job_name": ...,
"before": [...],
"after": [...],
"mapped": {"old": "new", ...},
"dropped": ["old", ...],
},
...
],
"jobs_updated": N,
"jobs_scanned": M,
}
Best-effort: exceptions from loading/saving propagate to the caller so
tests can assert behaviour; the curator invocation site wraps this
call in a try/except so a failure here never breaks the curator.
"""
consolidated = dict(consolidated or {})
pruned_set = set(pruned or [])
# A skill listed in both wins as "consolidated" — it has a target,
# which is the more useful of the two outcomes.
pruned_set -= set(consolidated.keys())
if not consolidated and not pruned_set:
return {"rewrites": [], "jobs_updated": 0, "jobs_scanned": 0}
with _jobs_file_lock:
jobs = load_jobs()
rewrites: List[Dict[str, Any]] = []
changed = False
for job in jobs:
skills_before = _normalize_skill_list(job.get("skill"), job.get("skills"))
if not skills_before:
continue
mapped: Dict[str, str] = {}
dropped: List[str] = []
new_skills: List[str] = []
for name in skills_before:
if name in consolidated:
target = consolidated[name]
mapped[name] = target
if target and target not in new_skills:
new_skills.append(target)
elif name in pruned_set:
dropped.append(name)
else:
if name not in new_skills:
new_skills.append(name)
if not mapped and not dropped:
continue
job["skills"] = new_skills
job["skill"] = new_skills[0] if new_skills else None
changed = True
rewrites.append({
"job_id": job.get("id"),
"job_name": job.get("name") or job.get("id"),
"before": list(skills_before),
"after": list(new_skills),
"mapped": mapped,
"dropped": dropped,
})
if changed:
save_jobs(jobs)
logger.info(
"Curator rewrote skill references in %d cron job(s)", len(rewrites)
)
return {
"rewrites": rewrites,
"jobs_updated": len(rewrites),
"jobs_scanned": len(jobs),
}
+58 -334
View File
@@ -40,44 +40,13 @@ from hermes_time import now as _hermes_now
logger = logging.getLogger(__name__)
def _resolve_cron_enabled_toolsets(job: dict, cfg: dict) -> list[str] | None:
"""Resolve the toolset list for a cron job.
Precedence:
1. Per-job ``enabled_toolsets`` (set via ``cronjob`` tool on create/update).
Keeps the agent's job-scoped toolset override intact — #6130.
2. Per-platform ``hermes tools`` config for the ``cron`` platform.
Mirrors gateway behavior (``_get_platform_tools(cfg, platform_key)``)
so users can gate cron toolsets globally without recreating every job.
3. ``None`` on any lookup failure AIAgent loads the full default set
(legacy behavior before this change, preserved as the safety net).
_DEFAULT_OFF_TOOLSETS ({moa, homeassistant, rl}) are removed by
``_get_platform_tools`` for unconfigured platforms, so fresh installs
get cron WITHOUT ``moa`` by default (issue reported by Norbert
surprise $4.63 run).
"""
per_job = job.get("enabled_toolsets")
if per_job:
return per_job
try:
from hermes_cli.tools_config import _get_platform_tools # lazy: avoid heavy import at cron module load
return sorted(_get_platform_tools(cfg or {}, "cron"))
except Exception as exc:
logger.warning(
"Cron toolset resolution failed, falling back to full default toolset: %s",
exc,
)
return None
# Valid delivery platforms — used to validate user-supplied platform names
# in cron delivery targets, preventing env var enumeration via crafted names.
_KNOWN_DELIVERY_PLATFORMS = frozenset({
"telegram", "discord", "slack", "whatsapp", "signal",
"matrix", "mattermost", "homeassistant", "dingtalk", "feishu",
"wecom", "wecom_callback", "weixin", "sms", "email", "webhook", "bluebubbles",
"qqbot", "yuanbao",
"qqbot",
})
# Platforms that support a configured cron/notification home target, mapped to
@@ -123,19 +92,9 @@ _LOCK_FILE = _LOCK_DIR / ".tick.lock"
def _resolve_origin(job: dict) -> Optional[dict]:
"""Extract origin info from a job, preserving any extra routing metadata.
Treats non-dict origins (free-form provenance strings, ints, lists from
migration scripts or hand-edited jobs.json) as missing instead of
crashing with ``AttributeError`` on ``origin.get(...)``. Without this
guard, a job tagged with e.g. ``"combined-digest-replaces-x-and-y"``
crashed every fire attempt with
``'str' object has no attribute 'get'`` ``mark_job_run`` recorded the
failure, but the next tick re-loaded the same poisoned origin and
crashed identically until the field was patched manually (#18722).
"""
"""Extract origin info from a job, preserving any extra routing metadata."""
origin = job.get("origin")
if not isinstance(origin, dict):
if not origin:
return None
platform = origin.get("platform")
chat_id = origin.get("chat_id")
@@ -157,19 +116,6 @@ def _get_home_target_chat_id(platform_name: str) -> str:
return value
def _get_home_target_thread_id(platform_name: str) -> Optional[str]:
"""Return the optional thread/topic ID for a platform home target."""
env_var = _HOME_TARGET_ENV_VARS.get(platform_name.lower())
if not env_var:
return None
value = os.getenv(f"{env_var}_THREAD_ID", "").strip()
if not value:
legacy = _LEGACY_HOME_TARGET_ENV_VARS.get(env_var)
if legacy:
value = os.getenv(f"{legacy}_THREAD_ID", "").strip()
return value or None
def _resolve_single_delivery_target(job: dict, deliver_value: str) -> Optional[dict]:
"""Resolve one concrete auto-delivery target for a cron job."""
@@ -198,7 +144,7 @@ def _resolve_single_delivery_target(job: dict, deliver_value: str) -> Optional[d
return {
"platform": platform_name,
"chat_id": chat_id,
"thread_id": _get_home_target_thread_id(platform_name),
"thread_id": None,
}
return None
@@ -221,9 +167,7 @@ def _resolve_single_delivery_target(job: dict, deliver_value: str) -> Optional[d
if resolved:
parsed_chat_id, parsed_thread_id, resolved_is_explicit = _parse_target_ref(platform_key, resolved)
if resolved_is_explicit:
chat_id = parsed_chat_id
if parsed_thread_id is not None:
thread_id = parsed_thread_id
chat_id, thread_id = parsed_chat_id, parsed_thread_id
else:
chat_id = resolved
except Exception:
@@ -252,36 +196,16 @@ def _resolve_single_delivery_target(job: dict, deliver_value: str) -> Optional[d
return {
"platform": platform_name,
"chat_id": chat_id,
"thread_id": _get_home_target_thread_id(platform_name),
"thread_id": None,
}
def _normalize_deliver_value(deliver) -> str:
"""Normalize a stored/submitted ``deliver`` value to its canonical string form.
The contract is that ``deliver`` is a string (``"local"``, ``"origin"``,
``"telegram"``, ``"telegram:-1001:17"``, or comma-separated combinations).
Historically some callers MCP clients passing an array, direct edits of
``jobs.json``, or stale code paths have stored a list/tuple like
``["telegram"]``. ``str(["telegram"])`` would serialize to the literal
string ``"['telegram']"``, which is not a known platform and fails
resolution silently. Flatten lists/tuples into a comma-separated string
so both forms work. Returns ``"local"`` for anything falsy.
"""
if deliver is None or deliver == "":
return "local"
if isinstance(deliver, (list, tuple)):
parts = [str(p).strip() for p in deliver if str(p).strip()]
return ",".join(parts) if parts else "local"
return str(deliver)
def _resolve_delivery_targets(job: dict) -> List[dict]:
"""Resolve all concrete auto-delivery targets for a cron job (supports comma-separated deliver)."""
deliver = _normalize_deliver_value(job.get("deliver", "local"))
deliver = job.get("deliver", "local")
if deliver == "local":
return []
parts = [p.strip() for p in deliver.split(",") if p.strip()]
parts = [p.strip() for p in str(deliver).split(",") if p.strip()]
seen = set()
targets = []
for part in parts:
@@ -300,21 +224,13 @@ def _resolve_delivery_target(job: dict) -> Optional[dict]:
return targets[0] if targets else None
# Media extension sets — audio routing is centralized in gateway.platforms.base
# via should_send_media_as_audio() so Telegram-specific rules stay in one place.
# Media extension sets — keep in sync with gateway/platforms/base.py:_process_message_background
_AUDIO_EXTS = frozenset({'.ogg', '.opus', '.mp3', '.wav', '.m4a'})
_VIDEO_EXTS = frozenset({'.mp4', '.mov', '.avi', '.mkv', '.webm', '.3gp'})
_IMAGE_EXTS = frozenset({'.jpg', '.jpeg', '.png', '.webp', '.gif'})
def _send_media_via_adapter(
adapter,
chat_id: str,
media_files: list,
metadata: dict | None,
loop,
job: dict,
platform=None,
) -> None:
def _send_media_via_adapter(adapter, chat_id: str, media_files: list, metadata: dict | None, loop, job: dict) -> None:
"""Send extracted MEDIA files as native platform attachments via a live adapter.
Routes each file to the appropriate adapter method (send_voice, send_image_file,
@@ -323,13 +239,10 @@ def _send_media_via_adapter(
"""
from pathlib import Path
from gateway.platforms.base import should_send_media_as_audio
for media_path, _is_voice in media_files:
try:
ext = Path(media_path).suffix.lower()
route_platform = platform if platform is not None else getattr(adapter, "platform", None)
if should_send_media_as_audio(route_platform, ext, is_voice=_is_voice):
if ext in _AUDIO_EXTS:
coro = adapter.send_voice(chat_id=chat_id, audio_path=media_path, metadata=metadata)
elif ext in _VIDEO_EXTS:
coro = adapter.send_video(chat_id=chat_id, video_path=media_path, metadata=metadata)
@@ -375,6 +288,26 @@ def _deliver_result(job: dict, content: str, adapters=None, loop=None) -> Option
from tools.send_message_tool import _send_to_platform
from gateway.config import load_gateway_config, Platform
platform_map = {
"telegram": Platform.TELEGRAM,
"discord": Platform.DISCORD,
"slack": Platform.SLACK,
"whatsapp": Platform.WHATSAPP,
"signal": Platform.SIGNAL,
"matrix": Platform.MATRIX,
"mattermost": Platform.MATTERMOST,
"homeassistant": Platform.HOMEASSISTANT,
"dingtalk": Platform.DINGTALK,
"feishu": Platform.FEISHU,
"wecom": Platform.WECOM,
"wecom_callback": Platform.WECOM_CALLBACK,
"weixin": Platform.WEIXIN,
"email": Platform.EMAIL,
"sms": Platform.SMS,
"bluebubbles": Platform.BLUEBUBBLES,
"qqbot": Platform.QQBOT,
}
# Optionally wrap the content with a header/footer so the user knows this
# is a cron delivery. Wrapping is on by default; set cron.wrap_response: false
# in config.yaml for clean output.
@@ -417,7 +350,7 @@ def _deliver_result(job: dict, content: str, adapters=None, loop=None) -> Option
thread_id = target.get("thread_id")
# Diagnostic: log thread_id for topic-aware delivery debugging
origin = _resolve_origin(job) or {}
origin = job.get("origin") or {}
origin_thread = origin.get("thread_id")
if origin_thread and not thread_id:
logger.warning(
@@ -431,23 +364,13 @@ def _deliver_result(job: dict, content: str, adapters=None, loop=None) -> Option
job["id"], platform_name, chat_id, thread_id,
)
# Built-in names resolve to their enum member; plugin platform names
# create dynamic members via Platform._missing_().
try:
platform = Platform(platform_name.lower())
except (ValueError, KeyError):
platform = platform_map.get(platform_name.lower())
if not platform:
msg = f"unknown platform '{platform_name}'"
logger.warning("Job '%s': %s", job["id"], msg)
delivery_errors.append(msg)
continue
pconfig = config.platforms.get(platform)
if not pconfig or not pconfig.enabled:
msg = f"platform '{platform_name}' not configured/enabled"
logger.warning("Job '%s': %s", job["id"], msg)
delivery_errors.append(msg)
continue
# Prefer the live adapter when the gateway is running — this supports E2EE
# rooms (e.g. Matrix) where the standalone HTTP path cannot encrypt.
runtime_adapter = (adapters or {}).get(platform)
@@ -478,15 +401,7 @@ def _deliver_result(job: dict, content: str, adapters=None, loop=None) -> Option
# Send extracted media files as native attachments via the live adapter
if adapter_ok and media_files:
_send_media_via_adapter(
runtime_adapter,
chat_id,
media_files,
send_metadata,
loop,
job,
platform=platform,
)
_send_media_via_adapter(runtime_adapter, chat_id, media_files, send_metadata, loop, job)
if adapter_ok:
logger.info("Job '%s': delivered to %s:%s via live adapter", job["id"], platform_name, chat_id)
@@ -498,6 +413,13 @@ def _deliver_result(job: dict, content: str, adapters=None, loop=None) -> Option
)
if not delivered:
pconfig = config.platforms.get(platform)
if not pconfig or not pconfig.enabled:
msg = f"platform '{platform_name}' not configured/enabled"
logger.warning("Job '%s': %s", job["id"], msg)
delivery_errors.append(msg)
continue
# Standalone path: run the async send in a fresh event loop (safe from any thread)
coro = _send_to_platform(platform, pconfig, chat_id, cleaned_delivery_content, thread_id=thread_id, media_files=media_files)
try:
@@ -718,51 +640,10 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
f"{prompt}"
)
# Inject output from referenced cron jobs as context.
context_from = job.get("context_from")
if context_from:
from cron.jobs import OUTPUT_DIR
if isinstance(context_from, str):
context_from = [context_from]
for source_job_id in context_from:
# Guard against path traversal — valid job IDs are 12-char hex strings
if not source_job_id or not all(c in "0123456789abcdef" for c in source_job_id):
logger.warning("context_from: skipping invalid job_id %r", source_job_id)
continue
try:
job_output_dir = OUTPUT_DIR / source_job_id
if not job_output_dir.exists():
continue # silent skip — no output yet
output_files = sorted(
job_output_dir.glob("*.md"),
key=lambda f: f.stat().st_mtime,
reverse=True,
)
if not output_files:
continue # silent skip — no output yet
latest_output = output_files[0].read_text(encoding="utf-8").strip()
# Truncate to 8K characters to avoid prompt bloat
_MAX_CONTEXT_CHARS = 8000
if len(latest_output) > _MAX_CONTEXT_CHARS:
latest_output = latest_output[:_MAX_CONTEXT_CHARS] + "\n\n[... output truncated ...]"
if latest_output:
prompt = (
f"## Output from job '{source_job_id}'\n"
"The following is the most recent output from a preceding "
"cron job. Use it as context for your analysis.\n\n"
f"```\n{latest_output}\n```\n\n"
f"{prompt}"
)
else:
continue # silent skip — empty output
except (OSError, PermissionError) as e:
logger.warning("context_from: failed to read output for job %r: %s", source_job_id, e)
# silent skip — do not pollute the prompt with error messages
# Always prepend cron execution guidance so the agent knows how
# delivery works and can suppress delivery when appropriate.
cron_hint = (
"[IMPORTANT: You are running as a scheduled cron job. "
"[SYSTEM: You are running as a scheduled cron job. "
"DELIVERY: Your final response will be automatically delivered "
"to the user — do NOT use send_message or try to deliver "
"the output yourself. Just produce your report/output as your "
@@ -782,7 +663,6 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
return prompt
from tools.skills_tool import skill_view
from tools.skill_usage import bump_use
parts = []
skipped: list[str] = []
@@ -794,18 +674,12 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
skipped.append(skill_name)
continue
# Bump usage so the curator sees this skill as actively used.
try:
bump_use(skill_name)
except Exception:
logger.debug("Cron job: failed to bump skill usage for '%s'", skill_name, exc_info=True)
content = str(loaded.get("content") or "").strip()
if parts:
parts.append("")
parts.extend(
[
f'[IMPORTANT: The user has invoked the "{skill_name}" skill, indicating they want you to follow its instructions. The full skill content is loaded below.]',
f'[SYSTEM: The user has invoked the "{skill_name}" skill, indicating they want you to follow its instructions. The full skill content is loaded below.]',
"",
content,
]
@@ -813,7 +687,7 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
if skipped:
notice = (
f"[IMPORTANT: The following skill(s) were listed for this job but could not be found "
f"[SYSTEM: The following skill(s) were listed for this job but could not be found "
f"and were skipped: {', '.join(skipped)}. "
f"Start your response with a brief notice so the user is aware, e.g.: "
f"'⚠️ Skill(s) not found and skipped: {', '.join(skipped)}']"
@@ -875,8 +749,6 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
logger.info("Running job '%s' (ID: %s)", job_name, job_id)
logger.info("Prompt: %s", prompt[:100])
agent = None
# Mark this as a cron session so the approval system can apply cron_mode.
# This env var is process-wide and persists for the lifetime of the
# scheduler process — every job this process runs is a cron job.
@@ -891,37 +763,6 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
chat_id=str(origin["chat_id"]) if origin else "",
chat_name=origin.get("chat_name", "") if origin else "",
)
_cron_delivery_vars = (
"HERMES_CRON_AUTO_DELIVER_PLATFORM",
"HERMES_CRON_AUTO_DELIVER_CHAT_ID",
"HERMES_CRON_AUTO_DELIVER_THREAD_ID",
)
for _var_name in _cron_delivery_vars:
_VAR_MAP[_var_name].set("")
# Per-job working directory. When set (and validated at create/update
# time), we point TERMINAL_CWD at it so:
# - build_context_files_prompt() picks up AGENTS.md / CLAUDE.md /
# .cursorrules from the job's project dir, AND
# - the terminal, file, and code-exec tools run commands from there.
#
# tick() serializes workdir-jobs outside the parallel pool, so mutating
# os.environ["TERMINAL_CWD"] here is safe for those jobs. For workdir-less
# jobs we leave TERMINAL_CWD untouched — preserves the original behaviour
# (skip_context_files=True, tools use whatever cwd the scheduler has).
_job_workdir = (job.get("workdir") or "").strip() or None
if _job_workdir and not Path(_job_workdir).is_dir():
# Directory was removed between create-time validation and now. Log
# and drop back to old behaviour rather than crashing the job.
logger.warning(
"Job '%s': configured workdir %r no longer exists — running without it",
job_id, _job_workdir,
)
_job_workdir = None
_prior_terminal_cwd = os.environ.get("TERMINAL_CWD", "_UNSET_")
if _job_workdir:
os.environ["TERMINAL_CWD"] = _job_workdir
logger.info("Job '%s': using workdir %s", job_id, _job_workdir)
try:
# Re-read .env and config.yaml fresh every run so provider/key
@@ -936,11 +777,8 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
if delivery_target:
_VAR_MAP["HERMES_CRON_AUTO_DELIVER_PLATFORM"].set(delivery_target["platform"])
_VAR_MAP["HERMES_CRON_AUTO_DELIVER_CHAT_ID"].set(str(delivery_target["chat_id"]))
_VAR_MAP["HERMES_CRON_AUTO_DELIVER_THREAD_ID"].set(
""
if delivery_target.get("thread_id") is None
else str(delivery_target["thread_id"])
)
if delivery_target.get("thread_id") is not None:
_VAR_MAP["HERMES_CRON_AUTO_DELIVER_THREAD_ID"].set(str(delivery_target["thread_id"]))
model = job.get("model") or os.getenv("HERMES_MODEL") or ""
@@ -1002,7 +840,6 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
resolve_runtime_provider,
format_runtime_provider_error,
)
from hermes_cli.auth import AuthError
try:
runtime_kwargs = {
"requested": job.get("provider") or os.getenv("HERMES_INFERENCE_PROVIDER"),
@@ -1010,28 +847,6 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
if job.get("base_url"):
runtime_kwargs["explicit_base_url"] = job.get("base_url")
runtime = resolve_runtime_provider(**runtime_kwargs)
except AuthError as auth_exc:
# Primary provider auth failed — try fallback chain before giving up.
logger.warning("Job '%s': primary auth failed (%s), trying fallback", job_id, auth_exc)
fb = _cfg.get("fallback_providers") or _cfg.get("fallback_model")
fb_list = (fb if isinstance(fb, list) else [fb]) if fb else []
runtime = None
for entry in fb_list:
if not isinstance(entry, dict):
continue
try:
fb_kwargs = {"requested": entry.get("provider")}
if entry.get("base_url"):
fb_kwargs["explicit_base_url"] = entry["base_url"]
if entry.get("api_key"):
fb_kwargs["explicit_api_key"] = entry["api_key"]
runtime = resolve_runtime_provider(**fb_kwargs)
logger.info("Job '%s': fallback resolved to %s", job_id, runtime.get("provider"))
break
except Exception as fb_exc:
logger.debug("Job '%s': fallback %s failed: %s", job_id, entry.get("provider"), fb_exc)
if runtime is None:
raise RuntimeError(format_runtime_provider_error(auth_exc)) from auth_exc
except Exception as exc:
message = format_runtime_provider_error(exc)
raise RuntimeError(message) from exc
@@ -1071,15 +886,9 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
providers_ignored=pr.get("ignore"),
providers_order=pr.get("order"),
provider_sort=pr.get("sort"),
enabled_toolsets=_resolve_cron_enabled_toolsets(job, _cfg),
disabled_toolsets=["cronjob", "messaging", "clarify"],
quiet_mode=True,
# Cron jobs should always inherit the user's SOUL.md identity from
# HERMES_HOME. When a workdir is configured, also inject project
# context files (AGENTS.md / CLAUDE.md / .cursorrules) from there.
# Without a workdir, keep cwd context discovery disabled.
skip_context_files=not bool(_job_workdir),
load_soul_identity=True,
skip_context_files=True, # Don't inject SOUL.md/AGENTS.md from scheduler cwd
skip_memory=True, # Cron system prompts would corrupt user representations
platform="cron",
session_id=_cron_session_id,
@@ -1094,18 +903,7 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
#
# Uses the agent's built-in activity tracker (updated by
# _touch_activity() on every tool call, API call, and stream delta).
_raw_cron_timeout = os.getenv("HERMES_CRON_TIMEOUT", "").strip()
if _raw_cron_timeout:
try:
_cron_timeout = float(_raw_cron_timeout)
except (ValueError, TypeError):
logger.warning(
"Invalid HERMES_CRON_TIMEOUT=%r; using default 600s",
_raw_cron_timeout,
)
_cron_timeout = 600.0
else:
_cron_timeout = 600.0
_cron_timeout = float(os.getenv("HERMES_CRON_TIMEOUT", 600))
_cron_inactivity_limit = _cron_timeout if _cron_timeout > 0 else None
_POLL_INTERVAL = 5.0
_cron_pool = concurrent.futures.ThreadPoolExecutor(max_workers=1)
@@ -1174,27 +972,6 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
f"— last activity: {_last_desc}"
)
# Guard against non-dict returns from run_conversation under error conditions
if not isinstance(result, dict):
raise RuntimeError(
f"agent.run_conversation returned {type(result).__name__} instead of dict: {result!r}"
)
# If the agent itself reported failure (e.g. all retries exhausted on
# API errors, model abort, mid-run interrupt), do not silently mark the
# job as successful. run_agent populates `failed=True`/`completed=False`
# on these paths and may put the error into `final_response`, which
# would otherwise be delivered as if it were the agent's reply and the
# job's `last_status` set to "ok". Raise so the except handler below
# builds the proper failure tuple. (issue #17855)
if result.get("failed") is True or result.get("completed") is False:
_err_text = (
result.get("error")
or (result.get("final_response") or "").strip()
or "agent reported failure"
)
raise RuntimeError(_err_text)
final_response = result.get("final_response", "") or ""
# Strip leaked placeholder text that upstream may inject on empty completions.
if final_response.strip() == "(No response generated)":
@@ -1244,18 +1021,8 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
return False, output, "", error_msg
finally:
# Restore TERMINAL_CWD to whatever it was before this job ran. We
# only ever mutate it when the job has a workdir; see the setup block
# at the top of run_job for the serialization guarantee.
if _job_workdir:
if _prior_terminal_cwd == "_UNSET_":
os.environ.pop("TERMINAL_CWD", None)
else:
os.environ["TERMINAL_CWD"] = _prior_terminal_cwd
# Clean up ContextVar session/delivery state for this job.
clear_session_vars(_ctx_tokens)
for _var_name in _cron_delivery_vars:
_VAR_MAP[_var_name].set("")
if _session_db:
try:
_session_db.end_session(_cron_session_id, "cron_complete")
@@ -1265,24 +1032,6 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
_session_db.close()
except (Exception, KeyboardInterrupt) as e:
logger.debug("Job '%s': failed to close SQLite session store: %s", job_id, e)
# Release subprocesses, terminal sandboxes, browser daemons, and the
# main OpenAI/httpx client held by this ephemeral cron agent. Without
# this, a gateway that ticks cron every N minutes leaks fds per job
# until it hits EMFILE (#10200 / "too many open files").
try:
if agent is not None:
agent.close()
except (Exception, KeyboardInterrupt) as e:
logger.debug("Job '%s': failed to close agent resources: %s", job_id, e)
# Each cron run spins up a short-lived worker thread whose event loop
# dies as soon as the ``ThreadPoolExecutor`` shuts down. Any async
# httpx clients cached under that loop are now unusable — reap them
# so their transports don't accumulate in the process-global cache.
try:
from agent.auxiliary_client import cleanup_stale_async_clients
cleanup_stale_async_clients()
except Exception as e:
logger.debug("Job '%s': failed to reap stale auxiliary clients: %s", job_id, e)
def tick(verbose: bool = True, adapters=None, loop=None) -> int:
@@ -1399,39 +1148,14 @@ def tick(verbose: bool = True, adapters=None, loop=None) -> int:
mark_job_run(job["id"], False, str(e))
return False
# Partition due jobs: those with a per-job workdir mutate
# os.environ["TERMINAL_CWD"] inside run_job, which is process-global —
# so they MUST run sequentially to avoid corrupting each other. Jobs
# without a workdir leave env untouched and stay parallel-safe.
workdir_jobs = [j for j in due_jobs if (j.get("workdir") or "").strip()]
parallel_jobs = [j for j in due_jobs if not (j.get("workdir") or "").strip()]
_results: list = []
# Sequential pass for workdir jobs.
for job in workdir_jobs:
_ctx = contextvars.copy_context()
_results.append(_ctx.run(_process_job, job))
# Parallel pass for the rest — same behaviour as before.
if parallel_jobs:
with concurrent.futures.ThreadPoolExecutor(max_workers=_max_workers) as _tick_pool:
_futures = []
for job in parallel_jobs:
_ctx = contextvars.copy_context()
_futures.append(_tick_pool.submit(_ctx.run, _process_job, job))
_results.extend(f.result() for f in _futures)
# Best-effort sweep of MCP stdio subprocesses that survived their
# session teardown during this tick. Runs AFTER every job has
# finished so active sessions (including live user chats) are
# never touched — only PIDs explicitly detected as orphans in
# tools.mcp_tool._run_stdio's finally block are reaped.
try:
from tools.mcp_tool import _kill_orphaned_mcp_children
_kill_orphaned_mcp_children()
except Exception as _e:
logger.debug("Post-tick MCP orphan cleanup failed: %s", _e)
# Run all due jobs concurrently, each in its own ContextVar copy
# so session/delivery state stays isolated per-thread.
with concurrent.futures.ThreadPoolExecutor(max_workers=_max_workers) as _tick_pool:
_futures = []
for job in due_jobs:
_ctx = contextvars.copy_context()
_futures.append(_tick_pool.submit(_ctx.run, _process_job, job))
_results = [f.result() for f in _futures]
return sum(_results)
finally:
-59
View File
@@ -1,59 +0,0 @@
#
# docker-compose.yml for Hermes Agent
#
# Usage:
# HERMES_UID=$(id -u) HERMES_GID=$(id -g) docker compose up -d
#
# Set HERMES_UID / HERMES_GID to the host user that owns ~/.hermes so
# files created inside the container stay readable/writable on the host.
# The entrypoint remaps the internal `hermes` user to these values via
# usermod/groupmod + gosu.
#
# Security notes:
# - The dashboard service binds to 127.0.0.1 by default. It stores API
# keys; exposing it on LAN without auth is unsafe. If you want remote
# access, use an SSH tunnel or put it behind a reverse proxy that
# adds authentication — do NOT pass --insecure --host 0.0.0.0.
# - The gateway's API server is off unless you uncomment API_SERVER_KEY
# and API_SERVER_HOST. See docs/user-guide/api-server.md before doing
# this on an internet-facing host.
#
services:
gateway:
build: .
image: hermes-agent
container_name: hermes
restart: unless-stopped
network_mode: host
volumes:
- ~/.hermes:/opt/data
environment:
- HERMES_UID=${HERMES_UID:-10000}
- HERMES_GID=${HERMES_GID:-10000}
# To expose the OpenAI-compatible API server beyond localhost,
# uncomment BOTH lines (API_SERVER_KEY is mandatory for auth):
# - API_SERVER_HOST=0.0.0.0
# - API_SERVER_KEY=${API_SERVER_KEY}
# Microsoft Teams — uncomment and fill in to enable Teams gateway.
# Register your bot at https://dev.botframework.com/ to get these values.
# - TEAMS_CLIENT_ID=${TEAMS_CLIENT_ID}
# - TEAMS_CLIENT_SECRET=${TEAMS_CLIENT_SECRET}
# - TEAMS_TENANT_ID=${TEAMS_TENANT_ID}
# - TEAMS_ALLOWED_USERS=${TEAMS_ALLOWED_USERS}
# - TEAMS_PORT=${TEAMS_PORT:-3978}
command: ["gateway", "run"]
dashboard:
image: hermes-agent
container_name: hermes-dashboard
restart: unless-stopped
network_mode: host
depends_on:
- gateway
volumes:
- ~/.hermes:/opt/data
environment:
- HERMES_UID=${HERMES_UID:-10000}
- HERMES_GID=${HERMES_GID:-10000}
# Localhost-only. For remote access, tunnel via `ssh -L 9119:localhost:9119`.
command: ["dashboard", "--host", "127.0.0.1", "--no-open"]
+2 -70
View File
@@ -22,18 +22,9 @@ if [ "$(id -u)" = "0" ]; then
groupmod -o -g "$HERMES_GID" hermes 2>/dev/null || true
fi
# Fix ownership of the data volume. When HERMES_UID remaps the hermes user,
# files created by previous runs (under the old UID) become inaccessible.
# Always chown -R when UID was remapped; otherwise only if top-level is wrong.
actual_hermes_uid=$(id -u hermes)
needs_chown=false
if [ -n "$HERMES_UID" ] && [ "$HERMES_UID" != "10000" ]; then
needs_chown=true
elif [ "$(stat -c %u "$HERMES_HOME" 2>/dev/null)" != "$actual_hermes_uid" ]; then
needs_chown=true
fi
if [ "$needs_chown" = true ]; then
echo "Fixing ownership of $HERMES_HOME to hermes ($actual_hermes_uid)"
if [ "$(stat -c %u "$HERMES_HOME" 2>/dev/null)" != "$actual_hermes_uid" ]; then
echo "$HERMES_HOME is not owned by $actual_hermes_uid, fixing"
# In rootless Podman the container's "root" is mapped to an unprivileged
# host UID — chown will fail. That's fine: the volume is already owned
# by the mapped user on the host side.
@@ -41,15 +32,6 @@ if [ "$(id -u)" = "0" ]; then
echo "Warning: chown failed (rootless container?) — continuing anyway"
fi
# Ensure config.yaml is readable by the hermes runtime user even if it was
# edited on the host after initial ownership setup. Must run here (as root)
# rather than after the gosu drop, otherwise a non-root caller like
# `docker run -u $(id -u):$(id -g)` hits "Operation not permitted" (#15865).
if [ -f "$HERMES_HOME/config.yaml" ]; then
chown hermes:hermes "$HERMES_HOME/config.yaml" 2>/dev/null || true
chmod 640 "$HERMES_HOME/config.yaml" 2>/dev/null || true
fi
echo "Dropping root privileges"
exec gosu hermes "$0" "$@"
fi
@@ -86,54 +68,4 @@ if [ -d "$INSTALL_DIR/skills" ]; then
python3 "$INSTALL_DIR/tools/skills_sync.py"
fi
# Optionally start `hermes dashboard` as a side-process.
#
# Toggled by HERMES_DASHBOARD=1 (also accepts "true"/"yes", case-insensitive).
# Host/port/TUI can be overridden via:
# HERMES_DASHBOARD_HOST (default 0.0.0.0 — exposed outside the container)
# HERMES_DASHBOARD_PORT (default 9119, matches `hermes dashboard` default)
# HERMES_DASHBOARD_TUI (already honored by `hermes dashboard` itself)
#
# The dashboard is a long-lived server. We background it *before* the final
# `exec hermes "$@"` so the user's chosen foreground command (chat, gateway,
# sleep infinity, …) remains PID-of-interest for the container runtime. When
# the container stops the whole process tree is torn down, so no explicit
# cleanup is needed.
case "${HERMES_DASHBOARD:-}" in
1|true|TRUE|True|yes|YES|Yes)
dash_host="${HERMES_DASHBOARD_HOST:-0.0.0.0}"
dash_port="${HERMES_DASHBOARD_PORT:-9119}"
dash_args=(--host "$dash_host" --port "$dash_port" --no-open)
# Binding to anything other than localhost requires --insecure — the
# dashboard refuses otherwise because it exposes API keys. Inside a
# container this is the expected deployment (host reaches it via
# published port), so opt in automatically.
if [ "$dash_host" != "127.0.0.1" ] && [ "$dash_host" != "localhost" ]; then
dash_args+=(--insecure)
fi
echo "Starting hermes dashboard on ${dash_host}:${dash_port} (background)"
# Prefix dashboard output so it's distinguishable from the main
# process in `docker logs`. stdbuf keeps the pipe line-buffered.
(
stdbuf -oL -eL hermes dashboard "${dash_args[@]}" 2>&1 \
| sed -u 's/^/[dashboard] /'
) &
;;
esac
# Final exec: two supported invocation patterns.
#
# docker run <image> -> exec `hermes` with no args (legacy default)
# docker run <image> chat -q "..." -> exec `hermes chat -q "..."` (legacy wrap)
# docker run <image> sleep infinity -> exec `sleep infinity` directly
# docker run <image> bash -> exec `bash` directly
#
# If the first positional arg resolves to an executable on PATH, we assume the
# caller wants to run it directly (needed by the launcher which runs long-lived
# `sleep infinity` sandbox containers — see tools/environments/docker.py).
# Otherwise we treat the args as a hermes subcommand and wrap with `hermes`,
# preserving the documented `docker run <image> <subcommand>` behavior.
if [ $# -gt 0 ] && command -v "$1" >/dev/null 2>&1; then
exec "$@"
fi
exec hermes "$@"
Binary file not shown.
-1
View File
@@ -36,7 +36,6 @@
imports = [
./nix/packages.nix
./nix/overlays.nix
./nix/nixosModules.nix
./nix/checks.nix
./nix/devShell.nix
+85
View File
@@ -0,0 +1,85 @@
"""Built-in boot-md hook — run ~/.hermes/BOOT.md on gateway startup.
This hook is always registered. It silently skips if no BOOT.md exists.
To activate, create ``~/.hermes/BOOT.md`` with instructions for the
agent to execute on every gateway restart.
Example BOOT.md::
# Startup Checklist
1. Check if any cron jobs failed overnight
2. Send a status update to Discord #general
3. If there are errors in /opt/app/deploy.log, summarize them
The agent runs in a background thread so it doesn't block gateway
startup. If nothing needs attention, it replies with [SILENT] to
suppress delivery.
"""
import logging
import threading
logger = logging.getLogger("hooks.boot-md")
from hermes_constants import get_hermes_home
HERMES_HOME = get_hermes_home()
BOOT_FILE = HERMES_HOME / "BOOT.md"
def _build_boot_prompt(content: str) -> str:
"""Wrap BOOT.md content in a system-level instruction."""
return (
"You are running a startup boot checklist. Follow the BOOT.md "
"instructions below exactly.\n\n"
"---\n"
f"{content}\n"
"---\n\n"
"Execute each instruction. If you need to send a message to a "
"platform, use the send_message tool.\n"
"If nothing needs attention and there is nothing to report, "
"reply with ONLY: [SILENT]"
)
def _run_boot_agent(content: str) -> None:
"""Spawn a one-shot agent session to execute the boot instructions."""
try:
from run_agent import AIAgent
prompt = _build_boot_prompt(content)
agent = AIAgent(
quiet_mode=True,
skip_context_files=True,
skip_memory=True,
max_iterations=20,
)
result = agent.run_conversation(prompt)
response = result.get("final_response", "")
if response and "[SILENT]" not in response:
logger.info("boot-md completed: %s", response[:200])
else:
logger.info("boot-md completed (nothing to report)")
except Exception as e:
logger.error("boot-md agent failed: %s", e)
async def handle(event_type: str, context: dict) -> None:
"""Gateway startup handler — run BOOT.md if it exists."""
if not BOOT_FILE.exists():
return
content = BOOT_FILE.read_text(encoding="utf-8").strip()
if not content:
return
logger.info("Running BOOT.md (%d chars)", len(content))
# Run in a background thread so we don't block gateway startup.
thread = threading.Thread(
target=_run_boot_agent,
args=(content,),
name="boot-md",
daemon=True,
)
thread.start()
+14 -77
View File
@@ -57,7 +57,7 @@ def _session_entry_name(origin: Dict[str, Any]) -> str:
# Build / refresh
# ---------------------------------------------------------------------------
async def build_channel_directory(adapters: Dict[Any, Any]) -> Dict[str, Any]:
def build_channel_directory(adapters: Dict[Any, Any]) -> Dict[str, Any]:
"""
Build a channel directory from connected platform adapters and session data.
@@ -72,7 +72,7 @@ async def build_channel_directory(adapters: Dict[Any, Any]) -> Dict[str, Any]:
if platform == Platform.DISCORD:
platforms["discord"] = _build_discord(adapter)
elif platform == Platform.SLACK:
platforms["slack"] = await _build_slack(adapter)
platforms["slack"] = _build_slack(adapter)
except Exception as e:
logger.warning("Channel directory: failed to build %s: %s", platform.value, e)
@@ -86,16 +86,6 @@ async def build_channel_directory(adapters: Dict[Any, Any]) -> Dict[str, Any]:
continue
platforms[plat_name] = _build_from_sessions(plat_name)
# Include plugin-registered platforms (dynamic enum members aren't in
# Platform.__members__, so the loop above misses them).
try:
from gateway.platform_registry import platform_registry
for entry in platform_registry.plugin_entries():
if entry.name not in _SKIP_SESSION_DISCOVERY and entry.name not in platforms:
platforms[entry.name] = _build_from_sessions(entry.name)
except Exception:
pass
directory = {
"updated_at": datetime.now().isoformat(),
"platforms": platforms,
@@ -146,66 +136,21 @@ def _build_discord(adapter) -> List[Dict[str, str]]:
return channels
async def _build_slack(adapter) -> List[Dict[str, Any]]:
"""List Slack channels the bot has joined across all workspaces.
Uses ``users.conversations`` against each workspace's web client. Pulls
public + private channels the bot is a member of, then merges in DMs
discovered from session history (IMs aren't useful to enumerate
proactively).
"""
team_clients = getattr(adapter, "_team_clients", None) or {}
if not team_clients:
def _build_slack(adapter) -> List[Dict[str, str]]:
"""List Slack channels the bot has joined."""
# Slack adapter may expose a web client
client = getattr(adapter, "_app", None) or getattr(adapter, "_client", None)
if not client:
return _build_from_sessions("slack")
channels: List[Dict[str, Any]] = []
seen_ids: set = set()
try:
from tools.send_message_tool import _send_slack # noqa: F401
# Use the Slack Web API directly if available
except Exception:
pass
for team_id, client in team_clients.items():
try:
cursor: Optional[str] = None
for _page in range(20): # safety cap on pagination
response = await client.users_conversations(
types="public_channel,private_channel",
exclude_archived=True,
limit=200,
cursor=cursor,
)
if not response.get("ok"):
logger.warning(
"Channel directory: users.conversations not ok for team %s: %s",
team_id,
response.get("error", "unknown"),
)
break
for ch in response.get("channels", []):
cid = ch.get("id")
name = ch.get("name")
if not cid or not name or cid in seen_ids:
continue
seen_ids.add(cid)
channels.append({
"id": cid,
"name": name,
"type": "private" if ch.get("is_private") else "channel",
})
cursor = (response.get("response_metadata") or {}).get("next_cursor")
if not cursor:
break
except Exception as e:
logger.warning(
"Channel directory: failed to list Slack channels for team %s: %s",
team_id, e,
)
continue
# Merge in DM/group entries discovered from session history.
for entry in _build_from_sessions("slack"):
if entry.get("id") not in seen_ids:
channels.append(entry)
seen_ids.add(entry.get("id"))
return channels
# Fallback to session data
return _build_from_sessions("slack")
def _build_from_sessions(platform_name: str) -> List[Dict[str, str]]:
@@ -278,14 +223,6 @@ def resolve_channel_name(platform_name: str, name: str) -> Optional[str]:
if not channels:
return None
# 0. Exact ID match — case-sensitive, no normalization. Lets callers pass
# raw platform IDs (e.g. Slack "C0B0QV5434G") even when the format guard
# in _parse_target_ref hasn't recognized them as explicit.
raw = name.strip()
for ch in channels:
if ch.get("id") == raw:
return ch["id"]
query = _normalize_channel_query(name)
# 1. Exact name match, including the display labels shown by send_message(action="list")
+66 -386
View File
@@ -13,7 +13,7 @@ import os
import json
from pathlib import Path
from dataclasses import dataclass, field
from typing import Dict, List, Optional, Any, Callable
from typing import Dict, List, Optional, Any
from enum import Enum
from hermes_cli.config import get_hermes_home
@@ -36,26 +36,6 @@ def _coerce_bool(value: Any, default: bool = True) -> bool:
return is_truthy_value(value, default=default)
def _coerce_float(value: Any, default: float) -> float:
"""Coerce numeric config values, falling back on malformed input."""
if value is None:
return default
try:
return float(value)
except (TypeError, ValueError):
return default
def _coerce_int(value: Any, default: int) -> int:
"""Coerce integer config values, falling back on malformed input."""
if value is None:
return default
try:
return int(value)
except (TypeError, ValueError):
return default
def _normalize_unauthorized_dm_behavior(value: Any, default: str = "pair") -> str:
"""Normalize unauthorized DM behavior to a supported value."""
if isinstance(value, str):
@@ -65,28 +45,8 @@ def _normalize_unauthorized_dm_behavior(value: Any, default: str = "pair") -> st
return default
def _normalize_notice_delivery(value: Any, default: str = "public") -> str:
"""Normalize notice delivery mode to a supported value."""
if isinstance(value, str):
normalized = value.strip().lower()
if normalized in {"public", "private"}:
return normalized
return default
# Module-level cache for bundled platform plugin names (lives outside the
# enum so it doesn't become an accidental enum member).
_Platform__bundled_plugin_names: Optional[set] = None
class Platform(Enum):
"""Supported messaging platforms.
Built-in platforms have explicit members. Plugin platforms use dynamic
members created on-demand by ``_missing_()`` so that
``Platform("irc")`` works without modifying this enum. Dynamic members
are cached in ``_value2member_map_`` for identity-stable comparisons.
"""
"""Supported messaging platforms."""
LOCAL = "local"
TELEGRAM = "telegram"
DISCORD = "discord"
@@ -107,77 +67,6 @@ class Platform(Enum):
WEIXIN = "weixin"
BLUEBUBBLES = "bluebubbles"
QQBOT = "qqbot"
YUANBAO = "yuanbao"
@classmethod
def _missing_(cls, value):
"""Accept unknown platform names only for known plugin adapters.
Creates a pseudo-member cached in ``_value2member_map_`` so that
``Platform("irc") is Platform("irc")`` holds True (identity-stable).
Arbitrary strings are rejected to prevent enum pollution.
"""
if not isinstance(value, str) or not value.strip():
return None
# Normalise to lowercase to avoid case mismatches in config
value = value.strip().lower()
# Check cache first (another call may have created it already)
if value in cls._value2member_map_:
return cls._value2member_map_[value]
# Only create pseudo-members for bundled plugin platforms (discovered
# via filesystem scan) or runtime-registered plugin platforms.
global _Platform__bundled_plugin_names
if _Platform__bundled_plugin_names is None:
_Platform__bundled_plugin_names = cls._scan_bundled_plugin_platforms()
if value in _Platform__bundled_plugin_names:
pseudo = object.__new__(cls)
pseudo._value_ = value
pseudo._name_ = value.upper().replace("-", "_").replace(" ", "_")
cls._value2member_map_[value] = pseudo
cls._member_map_[pseudo._name_] = pseudo
return pseudo
# Runtime-registered plugins (e.g. user-installed, discovered after
# the enum was defined).
try:
from gateway.platform_registry import platform_registry
if platform_registry.is_registered(value):
pseudo = object.__new__(cls)
pseudo._value_ = value
pseudo._name_ = value.upper().replace("-", "_").replace(" ", "_")
cls._value2member_map_[value] = pseudo
cls._member_map_[pseudo._name_] = pseudo
return pseudo
except Exception:
pass
return None
@classmethod
def _scan_bundled_plugin_platforms(cls) -> set:
"""Return names of bundled platform plugins under ``plugins/platforms/``."""
names: set = set()
try:
platforms_dir = Path(__file__).parent.parent / "plugins" / "platforms"
if platforms_dir.is_dir():
for child in platforms_dir.iterdir():
if (
child.is_dir()
and (child / "__init__.py").exists()
and (
(child / "plugin.yaml").exists()
or (child / "plugin.yml").exists()
)
):
names.add(child.name.lower())
except Exception:
pass
return names
# Snapshot of built-in platform values before any dynamic _missing_ lookups.
# Used to distinguish real platforms from arbitrary strings.
_BUILTIN_PLATFORM_VALUES = frozenset(m.value for m in Platform.__members__.values())
@dataclass
@@ -186,24 +75,18 @@ class HomeChannel:
Default destination for a platform.
When a cron job specifies deliver="telegram" without a specific chat ID,
messages are sent to this home channel. Thread-aware platforms may also
store a thread/topic ID so the bare platform target routes to the exact
conversation where /sethome was run.
messages are sent to this home channel.
"""
platform: Platform
chat_id: str
name: str # Human-readable name for display
thread_id: Optional[str] = None
def to_dict(self) -> Dict[str, Any]:
result = {
return {
"platform": self.platform.value,
"chat_id": self.chat_id,
"name": self.name,
}
if self.thread_id:
result["thread_id"] = self.thread_id
return result
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "HomeChannel":
@@ -211,7 +94,6 @@ class HomeChannel:
platform=Platform(data["platform"]),
chat_id=str(data["chat_id"]),
name=data.get("name", "Home"),
thread_id=str(data["thread_id"]) if data.get("thread_id") else None,
)
@@ -253,7 +135,7 @@ class SessionResetPolicy:
mode=mode if mode is not None else "both",
at_hour=at_hour if at_hour is not None else 4,
idle_minutes=idle_minutes if idle_minutes is not None else 1440,
notify=_coerce_bool(notify, True),
notify=notify if notify is not None else True,
notify_exclude_platforms=tuple(exclude) if exclude is not None else ("api_server", "webhook"),
)
@@ -296,7 +178,7 @@ class PlatformConfig:
home_channel = HomeChannel.from_dict(data["home_channel"])
return cls(
enabled=_coerce_bool(data.get("enabled"), False),
enabled=data.get("enabled", False),
token=data.get("token"),
api_key=data.get("api_key"),
home_channel=home_channel,
@@ -313,14 +195,6 @@ class StreamingConfig:
edit_interval: float = 1.0 # Seconds between message edits (Telegram rate-limits at ~1/s)
buffer_threshold: int = 40 # Chars before forcing an edit
cursor: str = "" # Cursor shown during streaming
# Ported from openclaw/openclaw#72038. When >0, the final edit for
# a long-running streamed response is delivered as a fresh message
# if the original preview has been visible for at least this many
# seconds, so the platform's visible timestamp reflects completion
# time instead of the preview creation time. Currently applied to
# Telegram only (other platforms ignore the setting). Default 60s
# matches the OpenClaw rollout. Set to 0 to disable.
fresh_final_after_seconds: float = 60.0
def to_dict(self) -> Dict[str, Any]:
return {
@@ -329,7 +203,6 @@ class StreamingConfig:
"edit_interval": self.edit_interval,
"buffer_threshold": self.buffer_threshold,
"cursor": self.cursor,
"fresh_final_after_seconds": self.fresh_final_after_seconds,
}
@classmethod
@@ -337,55 +210,14 @@ class StreamingConfig:
if not data:
return cls()
return cls(
enabled=_coerce_bool(data.get("enabled"), False),
enabled=data.get("enabled", False),
transport=data.get("transport", "edit"),
edit_interval=_coerce_float(data.get("edit_interval"), 1.0),
buffer_threshold=_coerce_int(data.get("buffer_threshold"), 40),
edit_interval=float(data.get("edit_interval", 1.0)),
buffer_threshold=int(data.get("buffer_threshold", 40)),
cursor=data.get("cursor", ""),
fresh_final_after_seconds=_coerce_float(
data.get("fresh_final_after_seconds"), 60.0
),
)
# -----------------------------------------------------------------------------
# Built-in platform connection checkers
# -----------------------------------------------------------------------------
# Each callable receives a ``PlatformConfig`` and returns ``True`` when the
# platform is sufficiently configured to be considered "connected". Platforms
# that rely on the generic ``token or api_key`` check (Telegram, Discord,
# Slack, Matrix, Mattermost, HomeAssistant) do not need an entry here.
_PLATFORM_CONNECTED_CHECKERS: dict[Platform, Callable[[PlatformConfig], bool]] = {
Platform.WEIXIN: lambda cfg: bool(
cfg.extra.get("account_id") and (cfg.token or cfg.extra.get("token"))
),
Platform.WHATSAPP: lambda cfg: True, # bridge handles auth
Platform.SIGNAL: lambda cfg: bool(cfg.extra.get("http_url")),
Platform.EMAIL: lambda cfg: bool(cfg.extra.get("address")),
Platform.SMS: lambda cfg: bool(os.getenv("TWILIO_ACCOUNT_SID")),
Platform.API_SERVER: lambda cfg: True,
Platform.WEBHOOK: lambda cfg: True,
Platform.FEISHU: lambda cfg: bool(cfg.extra.get("app_id")),
Platform.WECOM: lambda cfg: bool(cfg.extra.get("bot_id")),
Platform.WECOM_CALLBACK: lambda cfg: bool(
cfg.extra.get("corp_id") or cfg.extra.get("apps")
),
Platform.BLUEBUBBLES: lambda cfg: bool(
cfg.extra.get("server_url") and cfg.extra.get("password")
),
Platform.QQBOT: lambda cfg: bool(
cfg.extra.get("app_id") and cfg.extra.get("client_secret")
),
Platform.YUANBAO: lambda cfg: bool(
cfg.extra.get("app_id") and cfg.extra.get("app_secret")
),
Platform.DINGTALK: lambda cfg: bool(
(cfg.extra.get("client_id") or os.getenv("DINGTALK_CLIENT_ID"))
and (cfg.extra.get("client_secret") or os.getenv("DINGTALK_CLIENT_SECRET"))
),
}
@dataclass
class GatewayConfig:
"""
@@ -439,43 +271,58 @@ class GatewayConfig:
for platform, config in self.platforms.items():
if not config.enabled:
continue
if self._is_platform_connected(platform, config):
# Weixin requires both a token and an account_id
if platform == Platform.WEIXIN:
if config.extra.get("account_id") and (config.token or config.extra.get("token")):
connected.append(platform)
continue
# Platforms that use token/api_key auth
if config.token or config.api_key:
connected.append(platform)
# WhatsApp uses enabled flag only (bridge handles auth)
elif platform == Platform.WHATSAPP:
connected.append(platform)
# Signal uses extra dict for config (http_url + account)
elif platform == Platform.SIGNAL and config.extra.get("http_url"):
connected.append(platform)
# Email uses extra dict for config (address + imap_host + smtp_host)
elif platform == Platform.EMAIL and config.extra.get("address"):
connected.append(platform)
# SMS uses api_key (Twilio auth token) — SID checked via env
elif platform == Platform.SMS and os.getenv("TWILIO_ACCOUNT_SID"):
connected.append(platform)
# API Server uses enabled flag only (no token needed)
elif platform == Platform.API_SERVER:
connected.append(platform)
# Webhook uses enabled flag only (secrets are per-route)
elif platform == Platform.WEBHOOK:
connected.append(platform)
# Feishu uses extra dict for app credentials
elif platform == Platform.FEISHU and config.extra.get("app_id"):
connected.append(platform)
# WeCom bot mode uses extra dict for bot credentials
elif platform == Platform.WECOM and config.extra.get("bot_id"):
connected.append(platform)
# WeCom callback mode uses corp_id or apps list
elif platform == Platform.WECOM_CALLBACK and (
config.extra.get("corp_id") or config.extra.get("apps")
):
connected.append(platform)
# BlueBubbles uses extra dict for local server config
elif platform == Platform.BLUEBUBBLES and config.extra.get("server_url") and config.extra.get("password"):
connected.append(platform)
# QQBot uses extra dict for app credentials
elif platform == Platform.QQBOT and config.extra.get("app_id") and config.extra.get("client_secret"):
connected.append(platform)
# DingTalk uses client_id/client_secret from config.extra or env vars
elif platform == Platform.DINGTALK and (
config.extra.get("client_id") or os.getenv("DINGTALK_CLIENT_ID")
) and (
config.extra.get("client_secret") or os.getenv("DINGTALK_CLIENT_SECRET")
):
connected.append(platform)
return connected
def _is_platform_connected(self, platform: Platform, config: PlatformConfig) -> bool:
"""Check whether a single platform is sufficiently configured."""
# Weixin requires both a token and an account_id (checked first so
# the generic token branch doesn't let it through without account_id).
if platform == Platform.WEIXIN:
return bool(
config.extra.get("account_id")
and (config.token or config.extra.get("token"))
)
# Generic token/api_key auth covers Telegram, Discord, Slack, etc.
if config.token or config.api_key:
return True
# Platform-specific check
checker = _PLATFORM_CONNECTED_CHECKERS.get(platform)
if checker is not None:
return checker(config)
# Plugin-registered platforms
try:
from gateway.platform_registry import platform_registry
entry = platform_registry.get(platform.value)
if entry:
if entry.is_connected is not None:
return entry.is_connected(config)
if entry.validate_config is not None:
return entry.validate_config(config)
return True
except Exception:
pass # Registry not yet initialised during early import
return False
def get_home_channel(self, platform: Platform) -> Optional[HomeChannel]:
"""Get the home channel for a platform."""
@@ -588,7 +435,7 @@ class GatewayConfig:
reset_triggers=data.get("reset_triggers", ["/new", "/reset"]),
quick_commands=quick_commands,
sessions_dir=sessions_dir,
always_log_local=_coerce_bool(data.get("always_log_local"), True),
always_log_local=data.get("always_log_local", True),
stt_enabled=_coerce_bool(stt_enabled, True),
group_sessions_per_user=_coerce_bool(group_sessions_per_user, True),
thread_sessions_per_user=_coerce_bool(thread_sessions_per_user, False),
@@ -608,17 +455,6 @@ class GatewayConfig:
)
return self.unauthorized_dm_behavior
def get_notice_delivery(self, platform: Optional[Platform] = None) -> str:
"""Return the effective notice-delivery mode for a platform."""
if platform:
platform_cfg = self.platforms.get(platform)
if platform_cfg and "notice_delivery" in platform_cfg.extra:
return _normalize_notice_delivery(
platform_cfg.extra.get("notice_delivery"),
"public",
)
return "public"
def load_gateway_config() -> GatewayConfig:
"""
@@ -714,8 +550,6 @@ def load_gateway_config() -> GatewayConfig:
existing = {}
# Deep-merge extra dicts so gateway.json defaults survive
merged_extra = {**existing.get("extra", {}), **plat_block.get("extra", {})}
if plat_name == Platform.SLACK.value and "enabled" in plat_block:
merged_extra["_enabled_explicit"] = True
merged = {**existing, **plat_block}
if merged_extra:
merged["extra"] = merged_extra
@@ -734,15 +568,8 @@ def load_gateway_config() -> GatewayConfig:
platform_cfg.get("unauthorized_dm_behavior"),
gw_data.get("unauthorized_dm_behavior", "pair"),
)
if "notice_delivery" in platform_cfg:
bridged["notice_delivery"] = _normalize_notice_delivery(
platform_cfg.get("notice_delivery"),
"public",
)
if "reply_prefix" in platform_cfg:
bridged["reply_prefix"] = platform_cfg["reply_prefix"]
if "reply_in_thread" in platform_cfg:
bridged["reply_in_thread"] = platform_cfg["reply_in_thread"]
if "require_mention" in platform_cfg:
bridged["require_mention"] = platform_cfg["require_mention"]
if "free_response_channels" in platform_cfg:
@@ -757,7 +584,7 @@ def load_gateway_config() -> GatewayConfig:
bridged["group_policy"] = platform_cfg["group_policy"]
if "group_allow_from" in platform_cfg:
bridged["group_allow_from"] = platform_cfg["group_allow_from"]
if plat in (Platform.DISCORD, Platform.SLACK) and "channel_skill_bindings" in platform_cfg:
if plat == Platform.DISCORD and "channel_skill_bindings" in platform_cfg:
bridged["channel_skill_bindings"] = platform_cfg["channel_skill_bindings"]
if "channel_prompts" in platform_cfg:
channel_prompts = platform_cfg["channel_prompts"]
@@ -765,21 +592,16 @@ def load_gateway_config() -> GatewayConfig:
bridged["channel_prompts"] = {str(k): v for k, v in channel_prompts.items()}
else:
bridged["channel_prompts"] = channel_prompts
enabled_was_explicit = "enabled" in platform_cfg
if not bridged and not enabled_was_explicit:
if not bridged:
continue
plat_data = platforms_data.setdefault(plat.value, {})
if not isinstance(plat_data, dict):
plat_data = {}
platforms_data[plat.value] = plat_data
if enabled_was_explicit:
plat_data["enabled"] = platform_cfg["enabled"]
extra = plat_data.setdefault("extra", {})
if not isinstance(extra, dict):
extra = {}
plat_data["extra"] = extra
if plat == Platform.SLACK and enabled_was_explicit:
extra["_enabled_explicit"] = True
extra.update(bridged)
# Slack settings → env vars (env vars take precedence)
@@ -787,8 +609,6 @@ def load_gateway_config() -> GatewayConfig:
if isinstance(slack_cfg, dict):
if "require_mention" in slack_cfg and not os.getenv("SLACK_REQUIRE_MENTION"):
os.environ["SLACK_REQUIRE_MENTION"] = str(slack_cfg["require_mention"]).lower()
if "strict_mention" in slack_cfg and not os.getenv("SLACK_STRICT_MENTION"):
os.environ["SLACK_STRICT_MENTION"] = str(slack_cfg["strict_mention"]).lower()
if "allow_bots" in slack_cfg and not os.getenv("SLACK_ALLOW_BOTS"):
os.environ["SLACK_ALLOW_BOTS"] = str(slack_cfg["allow_bots"]).lower()
frc = slack_cfg.get("free_response_channels")
@@ -796,8 +616,6 @@ def load_gateway_config() -> GatewayConfig:
if isinstance(frc, list):
frc = ",".join(str(v) for v in frc)
os.environ["SLACK_FREE_RESPONSE_CHANNELS"] = str(frc)
if "reactions" in slack_cfg and not os.getenv("SLACK_REACTIONS"):
os.environ["SLACK_REACTIONS"] = str(slack_cfg["reactions"]).lower()
# Discord settings → env vars (env vars take precedence)
discord_cfg = yaml_cfg.get("discord", {})
@@ -846,25 +664,11 @@ def load_gateway_config() -> GatewayConfig:
if yaml_key in allow_mentions_cfg and not os.getenv(env_key):
os.environ[env_key] = str(allow_mentions_cfg[yaml_key]).lower()
# Bridge top-level require_mention to Telegram when the telegram: section
# does not already provide one. Users often write "require_mention: true"
# at the top level alongside group_sessions_per_user, expecting it to work
# the same way (#3979).
_tl_require_mention = yaml_cfg.get("require_mention")
if _tl_require_mention is not None:
_tg_section = yaml_cfg.get("telegram") or {}
if "require_mention" not in _tg_section:
_tg_plat = platforms_data.setdefault(Platform.TELEGRAM.value, {})
_tg_extra = _tg_plat.setdefault("extra", {})
_tg_extra.setdefault("require_mention", _tl_require_mention)
# Telegram settings → env vars (env vars take precedence)
telegram_cfg = yaml_cfg.get("telegram", {})
if isinstance(telegram_cfg, dict):
# Prefer telegram.require_mention; fall back to the top-level shorthand.
_effective_rm = telegram_cfg.get("require_mention", yaml_cfg.get("require_mention"))
if _effective_rm is not None and not os.getenv("TELEGRAM_REQUIRE_MENTION"):
os.environ["TELEGRAM_REQUIRE_MENTION"] = str(_effective_rm).lower()
if "require_mention" in telegram_cfg and not os.getenv("TELEGRAM_REQUIRE_MENTION"):
os.environ["TELEGRAM_REQUIRE_MENTION"] = str(telegram_cfg["require_mention"]).lower()
if "mention_patterns" in telegram_cfg and not os.getenv("TELEGRAM_MENTION_PATTERNS"):
os.environ["TELEGRAM_MENTION_PATTERNS"] = json.dumps(telegram_cfg["mention_patterns"])
frc = telegram_cfg.get("free_response_chats")
@@ -881,21 +685,6 @@ def load_gateway_config() -> GatewayConfig:
os.environ["TELEGRAM_REACTIONS"] = str(telegram_cfg["reactions"]).lower()
if "proxy_url" in telegram_cfg and not os.getenv("TELEGRAM_PROXY"):
os.environ["TELEGRAM_PROXY"] = str(telegram_cfg["proxy_url"]).strip()
allowed_users = telegram_cfg.get("allow_from")
if allowed_users is not None and not os.getenv("TELEGRAM_ALLOWED_USERS"):
if isinstance(allowed_users, list):
allowed_users = ",".join(str(v) for v in allowed_users)
os.environ["TELEGRAM_ALLOWED_USERS"] = str(allowed_users)
group_allowed_users = telegram_cfg.get("group_allow_from")
if group_allowed_users is not None and not os.getenv("TELEGRAM_GROUP_ALLOWED_USERS"):
if isinstance(group_allowed_users, list):
group_allowed_users = ",".join(str(v) for v in group_allowed_users)
os.environ["TELEGRAM_GROUP_ALLOWED_USERS"] = str(group_allowed_users)
group_allowed_chats = telegram_cfg.get("group_allowed_chats")
if group_allowed_chats is not None and not os.getenv("TELEGRAM_GROUP_ALLOWED_CHATS"):
if isinstance(group_allowed_chats, list):
group_allowed_chats = ",".join(str(v) for v in group_allowed_chats)
os.environ["TELEGRAM_GROUP_ALLOWED_CHATS"] = str(group_allowed_chats)
if "disable_link_previews" in telegram_cfg:
plat_data = platforms_data.setdefault(Platform.TELEGRAM.value, {})
if not isinstance(plat_data, dict):
@@ -966,12 +755,6 @@ def load_gateway_config() -> GatewayConfig:
if "dm_mention_threads" in matrix_cfg and not os.getenv("MATRIX_DM_MENTION_THREADS"):
os.environ["MATRIX_DM_MENTION_THREADS"] = str(matrix_cfg["dm_mention_threads"]).lower()
# Feishu settings → env vars (env vars take precedence)
feishu_cfg = yaml_cfg.get("feishu", {})
if isinstance(feishu_cfg, dict):
if "allow_bots" in feishu_cfg and not os.getenv("FEISHU_ALLOW_BOTS"):
os.environ["FEISHU_ALLOW_BOTS"] = str(feishu_cfg["allow_bots"]).lower()
except Exception as e:
logger.warning(
"Failed to process config.yaml — falling back to .env / gateway.json values. "
@@ -1092,7 +875,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.TELEGRAM,
chat_id=telegram_home,
name=os.getenv("TELEGRAM_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("TELEGRAM_HOME_CHANNEL_THREAD_ID") or None,
)
# Discord
@@ -1109,7 +891,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.DISCORD,
chat_id=discord_home,
name=os.getenv("DISCORD_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("DISCORD_HOME_CHANNEL_THREAD_ID") or None,
)
# Reply threading mode for Discord (off/first/all)
@@ -1125,33 +906,13 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
if Platform.WHATSAPP not in config.platforms:
config.platforms[Platform.WHATSAPP] = PlatformConfig()
config.platforms[Platform.WHATSAPP].enabled = True
whatsapp_home = os.getenv("WHATSAPP_HOME_CHANNEL")
if whatsapp_home and Platform.WHATSAPP in config.platforms:
config.platforms[Platform.WHATSAPP].home_channel = HomeChannel(
platform=Platform.WHATSAPP,
chat_id=whatsapp_home,
name=os.getenv("WHATSAPP_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("WHATSAPP_HOME_CHANNEL_THREAD_ID") or None,
)
# Slack
slack_token = os.getenv("SLACK_BOT_TOKEN")
if slack_token:
if Platform.SLACK not in config.platforms:
# No yaml config for Slack — env-only setup, enable it
config.platforms[Platform.SLACK] = PlatformConfig()
config.platforms[Platform.SLACK].enabled = True
else:
slack_config = config.platforms[Platform.SLACK]
enabled_was_explicit = bool(slack_config.extra.pop("_enabled_explicit", False))
if not slack_config.enabled and not enabled_was_explicit:
# Top-level Slack settings such as channel prompts should not
# turn an env-token setup into a disabled platform. Only an
# explicit slack.enabled/platforms.slack.enabled false should.
slack_config.enabled = True
# If yaml config exists, respect its enabled flag (don't override
# explicit enabled: false). Token is still stored so skills that
# send Slack messages can use it without activating the gateway adapter.
config.platforms[Platform.SLACK].enabled = True
config.platforms[Platform.SLACK].token = slack_token
slack_home = os.getenv("SLACK_HOME_CHANNEL")
if slack_home and Platform.SLACK in config.platforms:
@@ -1159,7 +920,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.SLACK,
chat_id=slack_home,
name=os.getenv("SLACK_HOME_CHANNEL_NAME", ""),
thread_id=os.getenv("SLACK_HOME_CHANNEL_THREAD_ID") or None,
)
# Signal
@@ -1180,7 +940,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.SIGNAL,
chat_id=signal_home,
name=os.getenv("SIGNAL_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("SIGNAL_HOME_CHANNEL_THREAD_ID") or None,
)
# Mattermost
@@ -1200,7 +959,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.MATTERMOST,
chat_id=mattermost_home,
name=os.getenv("MATTERMOST_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("MATTERMOST_HOME_CHANNEL_THREAD_ID") or None,
)
# Matrix
@@ -1232,7 +990,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.MATRIX,
chat_id=matrix_home,
name=os.getenv("MATRIX_HOME_ROOM_NAME", "Home"),
thread_id=os.getenv("MATRIX_HOME_ROOM_THREAD_ID") or None,
)
# Home Assistant
@@ -1266,7 +1023,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.EMAIL,
chat_id=email_home,
name=os.getenv("EMAIL_HOME_ADDRESS_NAME", "Home"),
thread_id=os.getenv("EMAIL_HOME_ADDRESS_THREAD_ID") or None,
)
# SMS (Twilio)
@@ -1282,7 +1038,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.SMS,
chat_id=sms_home,
name=os.getenv("SMS_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("SMS_HOME_CHANNEL_THREAD_ID") or None,
)
# API Server
@@ -1345,7 +1100,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.DINGTALK,
chat_id=dingtalk_home,
name=os.getenv("DINGTALK_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("DINGTALK_HOME_CHANNEL_THREAD_ID") or None,
)
# Feishu / Lark
@@ -1373,7 +1127,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.FEISHU,
chat_id=feishu_home,
name=os.getenv("FEISHU_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("FEISHU_HOME_CHANNEL_THREAD_ID") or None,
)
# WeCom (Enterprise WeChat)
@@ -1396,7 +1149,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.WECOM,
chat_id=wecom_home,
name=os.getenv("WECOM_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("WECOM_HOME_CHANNEL_THREAD_ID") or None,
)
# WeCom callback mode (self-built apps)
@@ -1455,7 +1207,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.WEIXIN,
chat_id=weixin_home,
name=os.getenv("WEIXIN_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("WEIXIN_HOME_CHANNEL_THREAD_ID") or None,
)
# BlueBubbles (iMessage)
@@ -1479,7 +1230,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.BLUEBUBBLES,
chat_id=bluebubbles_home,
name=os.getenv("BLUEBUBBLES_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("BLUEBUBBLES_HOME_CHANNEL_THREAD_ID") or None,
)
# QQ (Official Bot API v2)
@@ -1517,56 +1267,8 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
platform=Platform.QQBOT,
chat_id=qq_home,
name=os.getenv("QQBOT_HOME_CHANNEL_NAME") or os.getenv(qq_home_name_env, "Home"),
thread_id=(
os.getenv("QQBOT_HOME_CHANNEL_THREAD_ID")
or os.getenv("QQ_HOME_CHANNEL_THREAD_ID")
or None
),
)
# Yuanbao — YUANBAO_APP_ID preferred
yuanbao_app_id = os.getenv("YUANBAO_APP_ID") or os.getenv("YUANBAO_APP_KEY")
yuanbao_app_secret = os.getenv("YUANBAO_APP_SECRET")
if yuanbao_app_id and yuanbao_app_secret:
if Platform.YUANBAO not in config.platforms:
config.platforms[Platform.YUANBAO] = PlatformConfig()
config.platforms[Platform.YUANBAO].enabled = True
extra = config.platforms[Platform.YUANBAO].extra
extra["app_id"] = yuanbao_app_id
extra["app_secret"] = yuanbao_app_secret
yuanbao_bot_id = os.getenv("YUANBAO_BOT_ID")
if yuanbao_bot_id:
extra["bot_id"] = yuanbao_bot_id
yuanbao_ws_url = os.getenv("YUANBAO_WS_URL")
if yuanbao_ws_url:
extra["ws_url"] = yuanbao_ws_url
yuanbao_api_domain = os.getenv("YUANBAO_API_DOMAIN")
if yuanbao_api_domain:
extra["api_domain"] = yuanbao_api_domain
yuanbao_route_env = os.getenv("YUANBAO_ROUTE_ENV")
if yuanbao_route_env:
extra["route_env"] = yuanbao_route_env
yuanbao_home = os.getenv("YUANBAO_HOME_CHANNEL")
if yuanbao_home:
config.platforms[Platform.YUANBAO].home_channel = HomeChannel(
platform=Platform.YUANBAO,
chat_id=yuanbao_home,
name=os.getenv("YUANBAO_HOME_CHANNEL_NAME", "Home"),
thread_id=os.getenv("YUANBAO_HOME_CHANNEL_THREAD_ID") or None,
)
yuanbao_dm_policy = os.getenv("YUANBAO_DM_POLICY")
if yuanbao_dm_policy:
extra["dm_policy"] = yuanbao_dm_policy.strip().lower()
yuanbao_dm_allow_from = os.getenv("YUANBAO_DM_ALLOW_FROM")
if yuanbao_dm_allow_from:
extra["dm_allow_from"] = yuanbao_dm_allow_from
yuanbao_group_policy = os.getenv("YUANBAO_GROUP_POLICY")
if yuanbao_group_policy:
extra["group_policy"] = yuanbao_group_policy.strip().lower()
yuanbao_group_allow_from = os.getenv("YUANBAO_GROUP_ALLOW_FROM")
if yuanbao_group_allow_from:
extra["group_allow_from"] = yuanbao_group_allow_from
# Session settings
idle_minutes = os.getenv("SESSION_IDLE_MINUTES")
if idle_minutes:
@@ -1581,25 +1283,3 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
config.default_reset_policy.at_hour = int(reset_hour)
except ValueError:
pass
# Registry-driven enable for plugin platforms. Built-ins have explicit
# blocks above; plugins expose check_fn() which is the single source of
# truth for "are my env vars set?". When it returns True, ensure the
# platform is enabled so start() will create its adapter.
try:
from hermes_cli.plugins import discover_plugins
discover_plugins() # idempotent
from gateway.platform_registry import platform_registry
for entry in platform_registry.plugin_entries():
try:
if not entry.check_fn():
continue
except Exception as e:
logger.debug("check_fn for %s raised: %s", entry.name, e)
continue
platform = Platform(entry.name)
if platform not in config.platforms:
config.platforms[platform] = PlatformConfig()
config.platforms[platform].enabled = True
except Exception as e:
logger.debug("Plugin platform enable pass failed: %s", e)
+7 -9
View File
@@ -53,10 +53,9 @@ class DeliveryTarget:
- "telegram" Telegram home channel
- "telegram:123456" specific Telegram chat
"""
target_stripped = target.strip()
target_lower = target_stripped.lower()
target = target.strip().lower()
if target_lower == "origin":
if target == "origin":
if origin:
return cls(
platform=origin.platform,
@@ -68,14 +67,13 @@ class DeliveryTarget:
# Fallback to local if no origin
return cls(platform=Platform.LOCAL, is_origin=True)
if target_lower == "local":
if target == "local":
return cls(platform=Platform.LOCAL)
# Check for platform:chat_id or platform:chat_id:thread_id format
# Use the original case for chat_id/thread_id to preserve case-sensitive IDs
if ":" in target_stripped:
parts = target_stripped.split(":", 2)
platform_str = parts[0].lower() # Platform names are case-insensitive
if ":" in target:
parts = target.split(":", 2)
platform_str = parts[0]
chat_id = parts[1] if len(parts) > 1 else None
thread_id = parts[2] if len(parts) > 2 else None
try:
@@ -87,7 +85,7 @@ class DeliveryTarget:
# Just a platform name (use home channel)
try:
platform = Platform(target_lower)
platform = Platform(target)
return cls(platform=platform)
except ValueError:
# Unknown platform, treat as local
+1 -3
View File
@@ -79,9 +79,7 @@ _PLATFORM_DEFAULTS: dict[str, dict[str, Any]] = {
"discord": _TIER_HIGH,
# Tier 2 — edit support, often customer/workspace channels
# Slack: tool_progress off by default — Bolt posts cannot be edited like CLI;
# "new"/"all" spam permanent lines in channels (hermes-agent#14663).
"slack": {**_TIER_MEDIUM, "tool_progress": "off"},
"slack": _TIER_MEDIUM,
"mattermost": _TIER_MEDIUM,
"matrix": _TIER_MEDIUM,
"feishu": _TIER_MEDIUM,
+26 -66
View File
@@ -21,7 +21,6 @@ Errors in hooks are caught and logged but never block the main pipeline.
import asyncio
import importlib.util
import sys
from typing import Any, Callable, Dict, List, Optional
import yaml
@@ -53,13 +52,19 @@ class HookRegistry:
return list(self._loaded_hooks)
def _register_builtin_hooks(self) -> None:
"""Register built-in hooks that are always active.
"""Register built-in hooks that are always active."""
try:
from gateway.builtin_hooks.boot_md import handle as boot_md_handle
Currently empty no shipped built-in hooks. Kept as the extension
point for future always-on gateway hooks so they drop in without
re-plumbing discover_and_load().
"""
return
self._handlers.setdefault("gateway:startup", []).append(boot_md_handle)
self._loaded_hooks.append({
"name": "boot-md",
"description": "Run ~/.hermes/BOOT.md on gateway startup",
"events": ["gateway:startup"],
"path": "(builtin)",
})
except Exception as e:
print(f"[hooks] Could not load built-in boot-md hook: {e}", flush=True)
def discover_and_load(self) -> None:
"""
@@ -98,28 +103,16 @@ class HookRegistry:
print(f"[hooks] Skipping {hook_name}: no events declared", flush=True)
continue
# Dynamically load the handler module.
# Register in sys.modules BEFORE exec_module so Pydantic /
# dataclasses / typing introspection can resolve forward
# references (triggered by `from __future__ import annotations`
# in the handler). Without this, a handler that declares a
# Pydantic BaseModel for webhook/event payloads fails at first
# dispatch with "TypeAdapter ... is not fully defined".
module_name = f"hermes_hook_{hook_name}"
# Dynamically load the handler module
spec = importlib.util.spec_from_file_location(
module_name, handler_path
f"hermes_hook_{hook_name}", handler_path
)
if spec is None or spec.loader is None:
print(f"[hooks] Skipping {hook_name}: could not load handler.py", flush=True)
continue
module = importlib.util.module_from_spec(spec)
sys.modules[module_name] = module
try:
spec.loader.exec_module(module)
except Exception:
sys.modules.pop(module_name, None)
raise
spec.loader.exec_module(module)
handle_fn = getattr(module, "handle", None)
if handle_fn is None:
@@ -142,22 +135,9 @@ class HookRegistry:
except Exception as e:
print(f"[hooks] Error loading hook {hook_dir.name}: {e}", flush=True)
def _resolve_handlers(self, event_type: str) -> List[Callable]:
"""Return all handlers that should fire for ``event_type``.
Exact matches fire first, followed by wildcard matches (e.g.
``command:*`` matches ``command:reset``).
"""
handlers = list(self._handlers.get(event_type, []))
if ":" in event_type:
base = event_type.split(":")[0]
wildcard_key = f"{base}:*"
handlers.extend(self._handlers.get(wildcard_key, []))
return handlers
async def emit(self, event_type: str, context: Optional[Dict[str, Any]] = None) -> None:
"""
Fire all handlers registered for an event, discarding return values.
Fire all handlers registered for an event.
Supports wildcard matching: handlers registered for "command:*" will
fire for any "command:..." event. Handlers registered for a base type
@@ -171,7 +151,16 @@ class HookRegistry:
if context is None:
context = {}
for fn in self._resolve_handlers(event_type):
# Collect handlers: exact match + wildcard match
handlers = list(self._handlers.get(event_type, []))
# Check for wildcard patterns (e.g., "command:*" matches "command:reset")
if ":" in event_type:
base = event_type.split(":")[0]
wildcard_key = f"{base}:*"
handlers.extend(self._handlers.get(wildcard_key, []))
for fn in handlers:
try:
result = fn(event_type, context)
# Support both sync and async handlers
@@ -179,32 +168,3 @@ class HookRegistry:
await result
except Exception as e:
print(f"[hooks] Error in handler for '{event_type}': {e}", flush=True)
async def emit_collect(
self,
event_type: str,
context: Optional[Dict[str, Any]] = None,
) -> List[Any]:
"""Fire handlers and return their non-None return values in order.
Like :meth:`emit` but captures each handler's return value. Used for
decision-style hooks (e.g. ``command:<name>`` policies that want to
allow/deny/rewrite the command before normal dispatch).
Exceptions from individual handlers are logged but do not abort the
remaining handlers.
"""
if context is None:
context = {}
results: List[Any] = []
for fn in self._resolve_handlers(event_type):
try:
result = fn(event_type, context)
if asyncio.iscoroutine(result):
result = await result
if result is not None:
results.append(result)
except Exception as e:
print(f"[hooks] Error in handler for '{event_type}': {e}", flush=True)
return results
+11 -57
View File
@@ -28,7 +28,6 @@ def mirror_to_session(
message_text: str,
source_label: str = "cli",
thread_id: Optional[str] = None,
user_id: Optional[str] = None,
) -> bool:
"""
Append a delivery-mirror message to the target session's transcript.
@@ -40,20 +39,9 @@ def mirror_to_session(
All errors are caught -- this is never fatal.
"""
try:
session_id = _find_session_id(
platform,
str(chat_id),
thread_id=thread_id,
user_id=user_id,
)
session_id = _find_session_id(platform, str(chat_id), thread_id=thread_id)
if not session_id:
logger.debug(
"Mirror: no session found for %s:%s:%s:%s",
platform,
chat_id,
thread_id,
user_id,
)
logger.debug("Mirror: no session found for %s:%s:%s", platform, chat_id, thread_id)
return False
mirror_msg = {
@@ -71,33 +59,17 @@ def mirror_to_session(
return True
except Exception as e:
logger.debug(
"Mirror failed for %s:%s:%s:%s: %s",
platform,
chat_id,
thread_id,
user_id,
e,
)
logger.debug("Mirror failed for %s:%s:%s: %s", platform, chat_id, thread_id, e)
return False
def _find_session_id(
platform: str,
chat_id: str,
thread_id: Optional[str] = None,
user_id: Optional[str] = None,
) -> Optional[str]:
def _find_session_id(platform: str, chat_id: str, thread_id: Optional[str] = None) -> Optional[str]:
"""
Find the active session_id for a platform + chat_id pair.
Scans sessions.json entries and matches where origin.chat_id == chat_id
on the right platform. DM session keys don't embed the chat_id
(e.g. "agent:main:telegram:dm"), so we check the origin dict.
When *user_id* is provided, prefer exact sender matches. If multiple
same-chat candidates exist and none matches the user, return None instead
of guessing and contaminating another participant's session.
"""
if not _SESSIONS_INDEX.exists():
return None
@@ -109,7 +81,8 @@ def _find_session_id(
return None
platform_lower = platform.lower()
candidates = []
best_match = None
best_updated = ""
for _key, entry in data.items():
origin = entry.get("origin") or {}
@@ -123,31 +96,12 @@ def _find_session_id(
origin_thread_id = origin.get("thread_id")
if thread_id is not None and str(origin_thread_id or "") != str(thread_id):
continue
candidates.append(entry)
updated = entry.get("updated_at", "")
if updated > best_updated:
best_updated = updated
best_match = entry.get("session_id")
if not candidates:
return None
if user_id:
exact_user_matches = [
entry for entry in candidates
if str((entry.get("origin") or {}).get("user_id") or "") == str(user_id)
]
if exact_user_matches:
candidates = exact_user_matches
elif len(candidates) > 1:
return None
elif len(candidates) > 1:
distinct_user_ids = {
str((entry.get("origin") or {}).get("user_id") or "").strip()
for entry in candidates
if str((entry.get("origin") or {}).get("user_id") or "").strip()
}
if len(distinct_user_ids) > 1:
return None
best_entry = max(candidates, key=lambda entry: entry.get("updated_at", ""))
return best_entry.get("session_id")
return best_match
def _append_to_jsonl(session_id: str, message: dict) -> None:
+1 -2
View File
@@ -28,7 +28,6 @@ from pathlib import Path
from typing import Optional
from hermes_constants import get_hermes_dir
from utils import atomic_replace
# Unambiguous alphabet -- excludes 0/O, 1/I to prevent confusion
@@ -60,7 +59,7 @@ def _secure_write(path: Path, data: str) -> None:
f.write(data)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, path)
os.replace(tmp_path, str(path))
try:
os.chmod(path, 0o600)
except OSError:
-212
View File
@@ -1,212 +0,0 @@
"""
Platform Adapter Registry
Allows platform adapters (built-in and plugin) to self-register so the gateway
can discover and instantiate them without hardcoded if/elif chains.
Built-in adapters continue to use the existing if/elif in _create_adapter()
for now. Plugin adapters register here via PluginContext.register_platform()
and are looked up first -- if nothing is found the gateway falls through to
the legacy code path.
Usage (plugin side):
from gateway.platform_registry import platform_registry, PlatformEntry
platform_registry.register(PlatformEntry(
name="irc",
label="IRC",
adapter_factory=lambda cfg: IRCAdapter(cfg),
check_fn=check_requirements,
validate_config=lambda cfg: bool(cfg.extra.get("server")),
required_env=["IRC_SERVER"],
install_hint="pip install irc",
))
Usage (gateway side):
adapter = platform_registry.create_adapter("irc", platform_config)
"""
import logging
from dataclasses import dataclass, field
from typing import Any, Callable, Optional
logger = logging.getLogger(__name__)
@dataclass
class PlatformEntry:
"""Metadata and factory for a single platform adapter."""
# Identifier used in config.yaml (e.g. "irc", "viber").
name: str
# Human-readable label (e.g. "IRC", "Viber").
label: str
# Factory callable: receives a PlatformConfig, returns an adapter instance.
# Using a factory instead of a bare class lets plugins do custom init
# (e.g. passing extra kwargs, wrapping in try/except).
adapter_factory: Callable[[Any], Any]
# Returns True when the platform's dependencies are available.
check_fn: Callable[[], bool]
# Optional: given a PlatformConfig, is it properly configured?
# If None, the registry skips config validation and lets the adapter
# fail at connect() time with a descriptive error.
validate_config: Optional[Callable[[Any], bool]] = None
# Optional: given a PlatformConfig, is the platform connected/enabled?
# Used by ``GatewayConfig.get_connected_platforms()`` and setup UI status.
# If None, falls back to ``validate_config`` or ``check_fn``.
is_connected: Optional[Callable[[Any], bool]] = None
# Env vars this platform needs (for ``hermes setup`` display).
required_env: list = field(default_factory=list)
# Hint shown when check_fn returns False.
install_hint: str = ""
# Optional setup function for interactive configuration.
# Signature: () -> None (prompts user, saves env vars).
# If None, falls back to _setup_standard_platform (needs token_var + vars)
# or a generic "set these env vars" display.
setup_fn: Optional[Callable[[], None]] = None
# "builtin" or "plugin"
source: str = "plugin"
# Name of the plugin manifest that registered this entry (empty for
# built-ins). Used by ``hermes gateway setup`` to auto-enable the
# owning plugin when the user configures its platform.
plugin_name: str = ""
# ── Auth env var names (for _is_user_authorized integration) ──
# E.g. "IRC_ALLOWED_USERS" — checked for comma-separated user IDs.
allowed_users_env: str = ""
# E.g. "IRC_ALLOW_ALL_USERS" — if truthy, all users authorized.
allow_all_env: str = ""
# ── Message limits ──
# Max message length for smart-chunking. 0 = no limit.
max_message_length: int = 0
# ── Privacy ──
# If True, session descriptions redact PII (phone numbers, etc.)
pii_safe: bool = False
# ── Display ──
# Emoji for CLI/gateway display (e.g. "💬")
emoji: str = "🔌"
# Whether this platform should appear in _UPDATE_ALLOWED_PLATFORMS
# (allows /update command from this platform).
allow_update_command: bool = True
# ── LLM guidance ──
# Platform hint injected into the system prompt (e.g. "You are on IRC.
# Do not use markdown."). Empty string = no hint.
platform_hint: str = ""
class PlatformRegistry:
"""Central registry of platform adapters.
Thread-safe for reads (dict lookups are atomic under GIL).
Writes happen at startup during sequential discovery.
"""
def __init__(self) -> None:
self._entries: dict[str, PlatformEntry] = {}
def register(self, entry: PlatformEntry) -> None:
"""Register a platform adapter entry.
If an entry with the same name exists, it is replaced (last writer
wins -- this lets plugins override built-in adapters if desired).
"""
if entry.name in self._entries:
prev = self._entries[entry.name]
logger.info(
"Platform '%s' re-registered (was %s, now %s)",
entry.name,
prev.source,
entry.source,
)
self._entries[entry.name] = entry
logger.debug("Registered platform adapter: %s (%s)", entry.name, entry.source)
def unregister(self, name: str) -> bool:
"""Remove a platform entry. Returns True if it existed."""
return self._entries.pop(name, None) is not None
def get(self, name: str) -> Optional[PlatformEntry]:
"""Look up a platform entry by name."""
return self._entries.get(name)
def all_entries(self) -> list[PlatformEntry]:
"""Return all registered platform entries."""
return list(self._entries.values())
def plugin_entries(self) -> list[PlatformEntry]:
"""Return only plugin-registered platform entries."""
return [e for e in self._entries.values() if e.source == "plugin"]
def is_registered(self, name: str) -> bool:
return name in self._entries
def create_adapter(self, name: str, config: Any) -> Optional[Any]:
"""Create an adapter instance for the given platform name.
Returns None if:
- No entry registered for *name*
- check_fn() returns False (missing deps)
- validate_config() returns False (misconfigured)
- The factory raises an exception
"""
entry = self._entries.get(name)
if entry is None:
return None
if not entry.check_fn():
hint = f" ({entry.install_hint})" if entry.install_hint else ""
logger.warning(
"Platform '%s' requirements not met%s",
entry.label,
hint,
)
return None
if entry.validate_config is not None:
try:
if not entry.validate_config(config):
logger.warning(
"Platform '%s' config validation failed",
entry.label,
)
return None
except Exception as e:
logger.warning(
"Platform '%s' config validation error: %s",
entry.label,
e,
)
return None
try:
adapter = entry.adapter_factory(config)
return adapter
except Exception as e:
logger.error(
"Failed to create adapter for platform '%s': %s",
entry.label,
e,
exc_info=True,
)
return None
# Module-level singleton
platform_registry = PlatformRegistry()
+4 -25
View File
@@ -1,30 +1,9 @@
# Adding a New Messaging Platform
There are two ways to add a platform to the Hermes gateway:
## Plugin Path (Recommended for Community/Third-Party)
Create a plugin directory in `~/.hermes/plugins/` with a `PLUGIN.yaml` and
`adapter.py`. The adapter inherits from `BasePlatformAdapter` and registers
via `ctx.register_platform()` in the `register(ctx)` entry point. This
requires **zero changes to core Hermes code**.
The plugin system automatically handles: adapter creation, config parsing,
user authorization, cron delivery, send_message routing, system prompt hints,
status display, gateway setup, and more.
See `plugins/platforms/irc/` for a complete reference implementation, and
`website/docs/developer-guide/adding-platform-adapters.md` for the full
plugin guide with code examples.
---
## Built-in Path (Core Contributors Only)
Checklist for integrating a platform directly into the Hermes core.
Use this as a reference when building a built-in adapter — every item here
is a real integration point. Missing any of them will cause broken
functionality, missing features, or inconsistent behavior.
Checklist for integrating a new messaging platform into the Hermes gateway.
Use this as a reference when building a new adapter — every item here is a
real integration point that exists in the codebase. Missing any of them will
cause broken functionality, missing features, or inconsistent behavior.
---
-2
View File
@@ -10,12 +10,10 @@ Each adapter handles:
from .base import BasePlatformAdapter, MessageEvent, SendResult
from .qqbot import QQAdapter
from .yuanbao import YuanbaoAdapter
__all__ = [
"BasePlatformAdapter",
"MessageEvent",
"SendResult",
"QQAdapter",
"YuanbaoAdapter",
]
-84
View File
@@ -1,84 +0,0 @@
"""Shared HTTP client factory for long-lived platform adapters.
Gateway messaging platforms (QQ Bot, Feishu, WeCom, DingTalk, Signal,
BlueBubbles, WeCom-callback) keep a persistent ``httpx.AsyncClient``
alive for the adapter's lifetime. That amortises TLS/connection setup
across many API calls, but it also means the process's file-descriptor
pressure is sensitive to how aggressively the pool recycles idle keep-
alive connections.
httpx's default ``keepalive_expiry`` is 5 seconds. On macOS behind
Cloudflare Warp (and other transparent proxies), peer-initiated FIN can
sit in ``CLOSE_WAIT`` longer than that before the local socket actually
drains which, multiplied across 7 long-lived adapters plus the LLM
client and MCP clients, walks straight into the default 256 fd limit.
See #18451.
``platform_httpx_limits()`` returns a tighter ``httpx.Limits`` the
adapter factories use instead of the httpx default. The values chosen:
* ``max_keepalive_connections=10`` plenty for any single adapter;
platform APIs rarely parallelise beyond this.
* ``keepalive_expiry=2.0`` close idle sockets aggressively so a
proxy's lingering CLOSE_WAIT window can't starve the process.
Override via ``HERMES_GATEWAY_HTTPX_KEEPALIVE_EXPIRY`` /
``HERMES_GATEWAY_HTTPX_MAX_KEEPALIVE`` env vars when tuning under load.
"""
from __future__ import annotations
import os
try:
import httpx
except ImportError: # pragma: no cover — optional dep
httpx = None # type: ignore[assignment]
_DEFAULT_KEEPALIVE_EXPIRY_S = 2.0
_DEFAULT_MAX_KEEPALIVE = 10
def platform_httpx_limits() -> "httpx.Limits | None":
"""Return ``httpx.Limits`` tuned for persistent platform-adapter clients.
Returns ``None`` when httpx isn't importable, so callers can fall
back to httpx's built-in default without a hard dependency on this
helper being reachable.
"""
if httpx is None:
return None
def _env_float(name: str, default: float) -> float:
raw = os.environ.get(name, "").strip()
if not raw:
return default
try:
val = float(raw)
except (TypeError, ValueError):
return default
return val if val > 0 else default
def _env_int(name: str, default: int) -> int:
raw = os.environ.get(name, "").strip()
if not raw:
return default
try:
val = int(raw)
except (TypeError, ValueError):
return default
return val if val > 0 else default
keepalive_expiry = _env_float(
"HERMES_GATEWAY_HTTPX_KEEPALIVE_EXPIRY", _DEFAULT_KEEPALIVE_EXPIRY_S
)
max_keepalive = _env_int(
"HERMES_GATEWAY_HTTPX_MAX_KEEPALIVE", _DEFAULT_MAX_KEEPALIVE
)
return httpx.Limits(
max_keepalive_connections=max_keepalive,
# Leave max_connections at httpx default (100) — plenty of headroom.
keepalive_expiry=keepalive_expiry,
)
+74 -376
View File
@@ -7,11 +7,8 @@ Exposes an HTTP server with endpoints:
- GET /v1/responses/{response_id} Retrieve a stored response
- DELETE /v1/responses/{response_id} Delete a stored response
- GET /v1/models lists hermes-agent as an available model
- GET /v1/capabilities machine-readable API capabilities for external UIs
- POST /v1/runs start a run, returns run_id immediately (202)
- GET /v1/runs/{run_id} retrieve current run status
- GET /v1/runs/{run_id}/events SSE stream of structured lifecycle events
- POST /v1/runs/{run_id}/stop interrupt a running agent
- GET /health health check
- GET /health/detailed rich status for cross-container dashboard probing
@@ -62,14 +59,6 @@ MAX_NORMALIZED_TEXT_LENGTH = 65_536 # 64 KB cap for normalized content parts
MAX_CONTENT_LIST_SIZE = 1_000 # Max items when content is an array
def _coerce_port(value: Any, default: int = DEFAULT_PORT) -> int:
"""Parse a listen port without letting malformed env/config values crash startup."""
try:
return int(value)
except (TypeError, ValueError):
return default
def _normalize_chat_content(
content: Any, *, _max_depth: int = 10, _depth: int = 0,
) -> str:
@@ -581,10 +570,7 @@ class APIServerAdapter(BasePlatformAdapter):
super().__init__(config, Platform.API_SERVER)
extra = config.extra or {}
self._host: str = extra.get("host", os.getenv("API_SERVER_HOST", DEFAULT_HOST))
raw_port = extra.get("port")
if raw_port is None:
raw_port = os.getenv("API_SERVER_PORT", str(DEFAULT_PORT))
self._port: int = _coerce_port(raw_port, DEFAULT_PORT)
self._port: int = int(extra.get("port", os.getenv("API_SERVER_PORT", str(DEFAULT_PORT))))
self._api_key: str = extra.get("key", os.getenv("API_SERVER_KEY", ""))
self._cors_origins: tuple[str, ...] = self._parse_cors_origins(
extra.get("cors_origins", os.getenv("API_SERVER_CORS_ORIGINS", "")),
@@ -600,11 +586,6 @@ class APIServerAdapter(BasePlatformAdapter):
self._run_streams: Dict[str, "asyncio.Queue[Optional[Dict]]"] = {}
# Creation timestamps for orphaned-run TTL sweep
self._run_streams_created: Dict[str, float] = {}
# Active run agent/task references for stop support
self._active_run_agents: Dict[str, Any] = {}
self._active_run_tasks: Dict[str, "asyncio.Task"] = {}
# Pollable run status for dashboards and external control-plane UIs.
self._run_statuses: Dict[str, Dict[str, Any]] = {}
self._session_db: Optional[Any] = None # Lazy-init SessionDB for session continuity
@staticmethod
@@ -738,11 +719,10 @@ class APIServerAdapter(BasePlatformAdapter):
gateway platforms), falling back to the hermes-api-server default.
"""
from run_agent import AIAgent
from gateway.run import _resolve_runtime_agent_kwargs, _resolve_gateway_model, _load_gateway_config, GatewayRunner
from gateway.run import _resolve_runtime_agent_kwargs, _resolve_gateway_model, _load_gateway_config
from hermes_cli.tools_config import _get_platform_tools
runtime_kwargs = _resolve_runtime_agent_kwargs()
reasoning_config = GatewayRunner._load_reasoning_config()
model = _resolve_gateway_model()
user_config = _load_gateway_config()
@@ -752,6 +732,7 @@ class APIServerAdapter(BasePlatformAdapter):
# Load fallback provider chain so the API server platform has the
# same fallback behaviour as Telegram/Discord/Slack (fixes #4954).
from gateway.run import GatewayRunner
fallback_model = GatewayRunner._load_fallback_model()
agent = AIAgent(
@@ -770,7 +751,6 @@ class APIServerAdapter(BasePlatformAdapter):
tool_complete_callback=tool_complete_callback,
session_db=self._ensure_session_db(),
fallback_model=fallback_model,
reasoning_config=reasoning_config,
)
return agent
@@ -824,51 +804,6 @@ class APIServerAdapter(BasePlatformAdapter):
],
})
async def _handle_capabilities(self, request: "web.Request") -> "web.Response":
"""GET /v1/capabilities — advertise the stable API surface.
External UIs and orchestrators use this endpoint to discover the API
server's plugin-safe contract without scraping docs or assuming that
every Hermes version exposes the same endpoints.
"""
auth_err = self._check_auth(request)
if auth_err:
return auth_err
return web.json_response({
"object": "hermes.api_server.capabilities",
"platform": "hermes-agent",
"model": self._model_name,
"auth": {
"type": "bearer",
"required": bool(self._api_key),
},
"features": {
"chat_completions": True,
"chat_completions_streaming": True,
"responses_api": True,
"responses_streaming": True,
"run_submission": True,
"run_status": True,
"run_events_sse": True,
"run_stop": True,
"tool_progress_events": True,
"session_continuity_header": "X-Hermes-Session-Id",
"cors": bool(self._cors_origins),
},
"endpoints": {
"health": {"method": "GET", "path": "/health"},
"health_detailed": {"method": "GET", "path": "/health/detailed"},
"models": {"method": "GET", "path": "/v1/models"},
"chat_completions": {"method": "POST", "path": "/v1/chat/completions"},
"responses": {"method": "POST", "path": "/v1/responses"},
"runs": {"method": "POST", "path": "/v1/runs"},
"run_status": {"method": "GET", "path": "/v1/runs/{run_id}"},
"run_events": {"method": "GET", "path": "/v1/runs/{run_id}/events"},
"run_stop": {"method": "POST", "path": "/v1/runs/{run_id}/stop"},
},
})
async def _handle_chat_completions(self, request: "web.Request") -> "web.Response":
"""POST /v1/chat/completions — OpenAI Chat Completions format."""
auth_err = self._check_auth(request)
@@ -993,62 +928,39 @@ class APIServerAdapter(BasePlatformAdapter):
if delta is not None:
_stream_q.put(delta)
# Track which tool_call_ids we've emitted a "running" lifecycle
# event for, so a "completed" event without a matching "running"
# (e.g. internal/filtered tools) is silently dropped instead of
# producing an orphaned event clients can't correlate.
_started_tool_call_ids: set[str] = set()
def _on_tool_progress(event_type, name, preview, args, **kwargs):
"""Send tool progress as a separate SSE event.
def _on_tool_start(tool_call_id, function_name, function_args):
"""Emit ``hermes.tool.progress`` with ``status: running``.
Previously, progress markers like `` list`` were injected
directly into ``delta.content``. OpenAI-compatible frontends
(Open WebUI, LobeChat, ) store ``delta.content`` verbatim as
the assistant message and send it back on subsequent requests.
After enough turns the model learns to *emit* the markers as
plain text instead of issuing real tool calls silently
hallucinating tool results. See #6972.
Replaces the old ``tool_progress_callback("tool.started",
...)`` emit so SSE consumers receive a single event per
tool start, carrying both the legacy ``tool``/``emoji``/
``label`` payload (for #6972 frontends) and the new
``toolCallId``/``status`` correlation fields (#16588).
Skips tools whose names start with ``_`` so internal
events (``_thinking``, ) stay off the wire matching
the prior ``_on_tool_progress`` filter exactly.
The fix: push a tagged tuple ``("__tool_progress__", payload)``
onto the stream queue. The SSE writer emits it as a custom
``event: hermes.tool.progress`` line that compliant frontends
can render for UX but will *not* persist into conversation
history. Clients that don't understand the custom event type
silently ignore it per the SSE specification.
"""
if not tool_call_id or function_name.startswith("_"):
if event_type != "tool.started":
return
_started_tool_call_ids.add(tool_call_id)
from agent.display import build_tool_preview, get_tool_emoji
label = build_tool_preview(function_name, function_args) or function_name
if name.startswith("_"):
return
from agent.display import get_tool_emoji
emoji = get_tool_emoji(name)
label = preview or name
_stream_q.put(("__tool_progress__", {
"tool": function_name,
"emoji": get_tool_emoji(function_name),
"tool": name,
"emoji": emoji,
"label": label,
"toolCallId": tool_call_id,
"status": "running",
}))
def _on_tool_complete(tool_call_id, function_name, function_args, function_result):
"""Emit the matching ``status: completed`` event.
Dropped if the start was filtered (internal tool, missing
id, or never seen) so clients never get an orphaned
``completed`` they can't correlate to a prior ``running``.
"""
if not tool_call_id or tool_call_id not in _started_tool_call_ids:
return
_started_tool_call_ids.discard(tool_call_id)
_stream_q.put(("__tool_progress__", {
"tool": function_name,
"toolCallId": tool_call_id,
"status": "completed",
}))
# Start agent in background. agent_ref is a mutable container
# so the SSE writer can interrupt the agent on client disconnect.
#
# ``tool_progress_callback`` is intentionally not wired here:
# it would duplicate every emit because ``run_agent`` fires it
# side-by-side with ``tool_start_callback``/``tool_complete_callback``.
# The structured callbacks are strictly richer (they carry the
# tool_call id), so they own the chat-completions SSE channel.
agent_ref = [None]
agent_task = asyncio.ensure_future(self._run_agent(
user_message=user_message,
@@ -1056,8 +968,7 @@ class APIServerAdapter(BasePlatformAdapter):
ephemeral_system_prompt=system_prompt,
session_id=session_id,
stream_delta_callback=_on_delta,
tool_start_callback=_on_tool_start,
tool_complete_callback=_on_tool_complete,
tool_progress_callback=_on_tool_progress,
agent_ref=agent_ref,
))
@@ -1172,8 +1083,7 @@ class APIServerAdapter(BasePlatformAdapter):
Tagged tuples ``("__tool_progress__", payload)`` are sent
as a custom ``event: hermes.tool.progress`` SSE event so
frontends can display them without storing the markers in
conversation history. See #6972 for the original event,
#16588 for the ``toolCallId``/``status`` lifecycle fields.
conversation history. See #6972.
"""
if isinstance(item, tuple) and len(item) == 2 and item[0] == "__tool_progress__":
event_data = json.dumps(item[1])
@@ -1294,12 +1204,10 @@ class APIServerAdapter(BasePlatformAdapter):
If the client disconnects mid-stream, ``agent.interrupt()`` is
called so the agent stops issuing upstream LLM calls, then the
asyncio task is cancelled. When ``store=True`` an initial
``in_progress`` snapshot is persisted immediately after
``response.created`` and disconnects update it to an
``incomplete`` snapshot so GET /v1/responses/{id} and
``previous_response_id`` chaining still have something to
recover from.
asyncio task is cancelled. When ``store=True`` the full response
is persisted to the ResponseStore in a ``finally`` block so GET
/v1/responses/{id} and ``previous_response_id`` chaining work the
same as the batch path.
"""
import queue as _q
@@ -1361,60 +1269,6 @@ class APIServerAdapter(BasePlatformAdapter):
final_response_text = ""
agent_error: Optional[str] = None
usage: Dict[str, int] = {"input_tokens": 0, "output_tokens": 0, "total_tokens": 0}
terminal_snapshot_persisted = False
def _persist_response_snapshot(
response_env: Dict[str, Any],
*,
conversation_history_snapshot: Optional[List[Dict[str, Any]]] = None,
) -> None:
if not store:
return
if conversation_history_snapshot is None:
conversation_history_snapshot = list(conversation_history)
conversation_history_snapshot.append({"role": "user", "content": user_message})
self._response_store.put(response_id, {
"response": response_env,
"conversation_history": conversation_history_snapshot,
"instructions": instructions,
"session_id": session_id,
})
if conversation:
self._response_store.set_conversation(conversation, response_id)
def _persist_incomplete_if_needed() -> None:
"""Persist an ``incomplete`` snapshot if no terminal one was written.
Called from both the client-disconnect (``ConnectionResetError``)
and server-cancellation (``asyncio.CancelledError``) paths so
GET /v1/responses/{id} and ``previous_response_id`` chaining keep
working after abrupt stream termination.
"""
if not store or terminal_snapshot_persisted:
return
incomplete_text = "".join(final_text_parts) or final_response_text
incomplete_items: List[Dict[str, Any]] = list(emitted_items)
if incomplete_text:
incomplete_items.append({
"type": "message",
"role": "assistant",
"content": [{"type": "output_text", "text": incomplete_text}],
})
incomplete_env = _envelope("incomplete")
incomplete_env["output"] = incomplete_items
incomplete_env["usage"] = {
"input_tokens": usage.get("input_tokens", 0),
"output_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
}
incomplete_history = list(conversation_history)
incomplete_history.append({"role": "user", "content": user_message})
if incomplete_text:
incomplete_history.append({"role": "assistant", "content": incomplete_text})
_persist_response_snapshot(
incomplete_env,
conversation_history_snapshot=incomplete_history,
)
try:
# response.created — initial envelope, status=in_progress
@@ -1424,7 +1278,6 @@ class APIServerAdapter(BasePlatformAdapter):
"type": "response.created",
"response": created_env,
})
_persist_response_snapshot(created_env)
last_activity = time.monotonic()
async def _open_message_item() -> None:
@@ -1681,18 +1534,6 @@ class APIServerAdapter(BasePlatformAdapter):
"output_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
}
_failed_history = list(conversation_history)
_failed_history.append({"role": "user", "content": user_message})
if final_response_text or agent_error:
_failed_history.append({
"role": "assistant",
"content": final_response_text or agent_error,
})
_persist_response_snapshot(
failed_env,
conversation_history_snapshot=_failed_history,
)
terminal_snapshot_persisted = True
await _write_event("response.failed", {
"type": "response.failed",
"response": failed_env,
@@ -1705,24 +1546,30 @@ class APIServerAdapter(BasePlatformAdapter):
"output_tokens": usage.get("output_tokens", 0),
"total_tokens": usage.get("total_tokens", 0),
}
full_history = list(conversation_history)
full_history.append({"role": "user", "content": user_message})
if isinstance(result, dict) and result.get("messages"):
full_history.extend(result["messages"])
else:
full_history.append({"role": "assistant", "content": final_response_text})
_persist_response_snapshot(
completed_env,
conversation_history_snapshot=full_history,
)
terminal_snapshot_persisted = True
await _write_event("response.completed", {
"type": "response.completed",
"response": completed_env,
})
# Persist for future chaining / GET retrieval, mirroring
# the batch path behavior.
if store:
full_history = list(conversation_history)
full_history.append({"role": "user", "content": user_message})
if isinstance(result, dict) and result.get("messages"):
full_history.extend(result["messages"])
else:
full_history.append({"role": "assistant", "content": final_response_text})
self._response_store.put(response_id, {
"response": completed_env,
"conversation_history": full_history,
"instructions": instructions,
"session_id": session_id,
})
if conversation:
self._response_store.set_conversation(conversation, response_id)
except (ConnectionResetError, ConnectionAbortedError, BrokenPipeError, OSError):
_persist_incomplete_if_needed()
# Client disconnected — interrupt the agent so it stops
# making upstream LLM calls, then cancel the task.
agent = agent_ref[0] if agent_ref else None
@@ -1738,22 +1585,6 @@ class APIServerAdapter(BasePlatformAdapter):
except (asyncio.CancelledError, Exception):
pass
logger.info("SSE client disconnected; interrupted agent task %s", response_id)
except asyncio.CancelledError:
# Server-side cancellation (e.g. shutdown, request timeout) —
# persist an incomplete snapshot so GET /v1/responses/{id} and
# previous_response_id chaining still work, then re-raise so the
# runtime's cancellation semantics are respected.
_persist_incomplete_if_needed()
agent = agent_ref[0] if agent_ref else None
if agent is not None:
try:
agent.interrupt("SSE task cancelled")
except Exception:
pass
if not agent_task.done():
agent_task.cancel()
logger.info("SSE task cancelled; persisted incomplete snapshot for %s", response_id)
raise
return response
@@ -2363,11 +2194,10 @@ class APIServerAdapter(BasePlatformAdapter):
)
if agent_ref is not None:
agent_ref[0] = agent
effective_task_id = session_id or str(uuid.uuid4())
result = agent.run_conversation(
user_message=user_message,
conversation_history=conversation_history,
task_id=effective_task_id,
task_id="default",
)
usage = {
"input_tokens": getattr(agent, "session_prompt_tokens", 0) or 0,
@@ -2384,31 +2214,10 @@ class APIServerAdapter(BasePlatformAdapter):
_MAX_CONCURRENT_RUNS = 10 # Prevent unbounded resource allocation
_RUN_STREAM_TTL = 300 # seconds before orphaned runs are swept
_RUN_STATUS_TTL = 3600 # seconds to retain terminal run status for polling
def _set_run_status(self, run_id: str, status: str, **fields: Any) -> Dict[str, Any]:
"""Update pollable run status without exposing private agent objects."""
now = time.time()
current = self._run_statuses.get(run_id, {})
current.update({
"object": "hermes.run",
"run_id": run_id,
"status": status,
"updated_at": now,
})
current.setdefault("created_at", fields.pop("created_at", now))
current.update(fields)
self._run_statuses[run_id] = current
return current
def _make_run_event_callback(self, run_id: str, loop: "asyncio.AbstractEventLoop"):
"""Return a tool_progress_callback that pushes structured events to the run's SSE queue."""
def _push(event: Dict[str, Any]) -> None:
self._set_run_status(
run_id,
self._run_statuses.get(run_id, {}).get("status", "running"),
last_event=event.get("event"),
)
q = self._run_streams.get(run_id)
if q is None:
return
@@ -2473,6 +2282,28 @@ class APIServerAdapter(BasePlatformAdapter):
if not user_message:
return web.json_response(_openai_error("No user message found in input"), status=400)
run_id = f"run_{uuid.uuid4().hex}"
loop = asyncio.get_running_loop()
q: "asyncio.Queue[Optional[Dict]]" = asyncio.Queue()
self._run_streams[run_id] = q
self._run_streams_created[run_id] = time.time()
event_cb = self._make_run_event_callback(run_id, loop)
# Also wire stream_delta_callback so message.delta events flow through
def _text_cb(delta: Optional[str]) -> None:
if delta is None:
return
try:
loop.call_soon_threadsafe(q.put_nowait, {
"event": "message.delta",
"run_id": run_id,
"timestamp": time.time(),
"delta": delta,
})
except Exception:
pass
instructions = body.get("instructions")
previous_response_id = body.get("previous_response_id")
@@ -2520,55 +2351,22 @@ class APIServerAdapter(BasePlatformAdapter):
)
conversation_history.append({"role": msg["role"], "content": str(content)})
run_id = f"run_{uuid.uuid4().hex}"
session_id = body.get("session_id") or stored_session_id or run_id
ephemeral_system_prompt = instructions
loop = asyncio.get_running_loop()
q: "asyncio.Queue[Optional[Dict]]" = asyncio.Queue()
created_at = time.time()
self._run_streams[run_id] = q
self._run_streams_created[run_id] = created_at
event_cb = self._make_run_event_callback(run_id, loop)
# Also wire stream_delta_callback so message.delta events flow through.
def _text_cb(delta: Optional[str]) -> None:
if delta is None:
return
try:
loop.call_soon_threadsafe(q.put_nowait, {
"event": "message.delta",
"run_id": run_id,
"timestamp": time.time(),
"delta": delta,
})
except Exception:
pass
self._set_run_status(
run_id,
"queued",
created_at=created_at,
session_id=session_id,
model=body.get("model", self._model_name),
)
async def _run_and_close():
try:
self._set_run_status(run_id, "running")
agent = self._create_agent(
ephemeral_system_prompt=ephemeral_system_prompt,
session_id=session_id,
stream_delta_callback=_text_cb,
tool_progress_callback=event_cb,
)
self._active_run_agents[run_id] = agent
def _run_sync():
effective_task_id = session_id or run_id
r = agent.run_conversation(
user_message=user_message,
conversation_history=conversation_history,
task_id=effective_task_id,
task_id="default",
)
u = {
"input_tokens": getattr(agent, "session_prompt_tokens", 0) or 0,
@@ -2586,36 +2384,8 @@ class APIServerAdapter(BasePlatformAdapter):
"output": final_response,
"usage": usage,
})
self._set_run_status(
run_id,
"completed",
output=final_response,
usage=usage,
last_event="run.completed",
)
except asyncio.CancelledError:
self._set_run_status(
run_id,
"cancelled",
last_event="run.cancelled",
)
try:
q.put_nowait({
"event": "run.cancelled",
"run_id": run_id,
"timestamp": time.time(),
})
except Exception:
pass
raise
except Exception as exc:
logger.exception("[api_server] run %s failed", run_id)
self._set_run_status(
run_id,
"failed",
error=str(exc),
last_event="run.failed",
)
try:
q.put_nowait({
"event": "run.failed",
@@ -2631,11 +2401,8 @@ class APIServerAdapter(BasePlatformAdapter):
q.put_nowait(None)
except Exception:
pass
self._active_run_agents.pop(run_id, None)
self._active_run_tasks.pop(run_id, None)
task = asyncio.create_task(_run_and_close())
self._active_run_tasks[run_id] = task
try:
self._background_tasks.add(task)
except TypeError:
@@ -2645,21 +2412,6 @@ class APIServerAdapter(BasePlatformAdapter):
return web.json_response({"run_id": run_id, "status": "started"}, status=202)
async def _handle_get_run(self, request: "web.Request") -> "web.Response":
"""GET /v1/runs/{run_id} — return pollable run status for external UIs."""
auth_err = self._check_auth(request)
if auth_err:
return auth_err
run_id = request.match_info["run_id"]
status = self._run_statuses.get(run_id)
if status is None:
return web.json_response(
_openai_error(f"Run not found: {run_id}", code="run_not_found"),
status=404,
)
return web.json_response(status)
async def _handle_run_events(self, request: "web.Request") -> "web.StreamResponse":
"""GET /v1/runs/{run_id}/events — SSE stream of structured agent lifecycle events."""
auth_err = self._check_auth(request)
@@ -2709,46 +2461,6 @@ class APIServerAdapter(BasePlatformAdapter):
return response
async def _handle_stop_run(self, request: "web.Request") -> "web.Response":
"""POST /v1/runs/{run_id}/stop — interrupt a running agent."""
auth_err = self._check_auth(request)
if auth_err:
return auth_err
run_id = request.match_info["run_id"]
agent = self._active_run_agents.get(run_id)
task = self._active_run_tasks.get(run_id)
if agent is None and task is None:
return web.json_response(_openai_error(f"Run not found: {run_id}", code="run_not_found"), status=404)
self._set_run_status(run_id, "stopping", last_event="run.stopping")
if agent is not None:
try:
agent.interrupt("Stop requested via API")
except Exception:
pass
if task is not None and not task.done():
task.cancel()
# Bounded wait: run_conversation() executes in the default
# executor thread which task.cancel() cannot preempt — we rely on
# agent.interrupt() above to break the loop. Cap the wait so a
# slow/unresponsive interrupt can't hang this handler.
try:
await asyncio.wait_for(asyncio.shield(task), timeout=5.0)
except asyncio.TimeoutError:
logger.warning(
"[api_server] stop for run %s timed out after 5s; "
"agent may still be finishing the current step",
run_id,
)
except (asyncio.CancelledError, Exception):
pass
return web.json_response({"run_id": run_id, "status": "stopping"})
async def _sweep_orphaned_runs(self) -> None:
"""Periodically clean up run streams that were never consumed."""
while True:
@@ -2763,17 +2475,6 @@ class APIServerAdapter(BasePlatformAdapter):
logger.debug("[api_server] sweeping orphaned run %s", run_id)
self._run_streams.pop(run_id, None)
self._run_streams_created.pop(run_id, None)
self._active_run_agents.pop(run_id, None)
self._active_run_tasks.pop(run_id, None)
stale_statuses = [
run_id
for run_id, status in list(self._run_statuses.items())
if status.get("status") in {"completed", "failed", "cancelled"}
and now - float(status.get("updated_at", 0) or 0) > self._RUN_STATUS_TTL
]
for run_id in stale_statuses:
self._run_statuses.pop(run_id, None)
# ------------------------------------------------------------------
# BasePlatformAdapter interface
@@ -2793,7 +2494,6 @@ class APIServerAdapter(BasePlatformAdapter):
self._app.router.add_get("/health/detailed", self._handle_health_detailed)
self._app.router.add_get("/v1/health", self._handle_health)
self._app.router.add_get("/v1/models", self._handle_models)
self._app.router.add_get("/v1/capabilities", self._handle_capabilities)
self._app.router.add_post("/v1/chat/completions", self._handle_chat_completions)
self._app.router.add_post("/v1/responses", self._handle_responses)
self._app.router.add_get("/v1/responses/{response_id}", self._handle_get_response)
@@ -2809,9 +2509,7 @@ class APIServerAdapter(BasePlatformAdapter):
self._app.router.add_post("/api/jobs/{job_id}/run", self._handle_run_job)
# Structured event streaming
self._app.router.add_post("/v1/runs", self._handle_runs)
self._app.router.add_get("/v1/runs/{run_id}", self._handle_get_run)
self._app.router.add_get("/v1/runs/{run_id}/events", self._handle_run_events)
self._app.router.add_post("/v1/runs/{run_id}/stop", self._handle_stop_run)
# Start background sweep to clean up orphaned (unconsumed) run streams
sweep_task = asyncio.create_task(self._sweep_orphaned_runs())
try:
+128 -1128
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+3 -22
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@@ -99,7 +99,6 @@ def _normalize_server_url(raw: str) -> str:
class BlueBubblesAdapter(BasePlatformAdapter):
platform = Platform.BLUEBUBBLES
SUPPORTS_MESSAGE_EDITING = False
MAX_MESSAGE_LENGTH = MAX_TEXT_LENGTH
def __init__(self, config: PlatformConfig):
@@ -162,9 +161,7 @@ class BlueBubblesAdapter(BasePlatformAdapter):
return False
from aiohttp import web
# Tighter keepalive so idle CLOSE_WAIT drains promptly (#18451).
from gateway.platforms._http_client_limits import platform_httpx_limits
self.client = httpx.AsyncClient(timeout=30.0, limits=platform_httpx_limits())
self.client = httpx.AsyncClient(timeout=30.0)
try:
await self._api_get("/api/v1/ping")
info = await self._api_get("/api/v1/server/info")
@@ -394,13 +391,6 @@ class BlueBubblesAdapter(BasePlatformAdapter):
# Text sending
# ------------------------------------------------------------------
@staticmethod
def truncate_message(content: str, max_length: int = MAX_TEXT_LENGTH) -> List[str]:
# Use the base splitter but skip pagination indicators — iMessage
# bubbles flow naturally without "(1/3)" suffixes.
chunks = BasePlatformAdapter.truncate_message(content, max_length)
return [re.sub(r"\s*\(\d+/\d+\)$", "", c) for c in chunks]
async def send(
self,
chat_id: str,
@@ -408,19 +398,10 @@ class BlueBubblesAdapter(BasePlatformAdapter):
reply_to: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> SendResult:
text = self.format_message(content)
text = strip_markdown(content or "")
if not text:
return SendResult(success=False, error="BlueBubbles send requires text")
# Split on paragraph breaks first (double newlines) so each thought
# becomes its own iMessage bubble, then truncate any that are still
# too long.
paragraphs = [p.strip() for p in re.split(r'\n\s*\n', text) if p.strip()]
chunks: List[str] = []
for para in (paragraphs or [text]):
if len(para) <= self.MAX_MESSAGE_LENGTH:
chunks.append(para)
else:
chunks.extend(self.truncate_message(para, max_length=self.MAX_MESSAGE_LENGTH))
chunks = self.truncate_message(text, max_length=self.MAX_MESSAGE_LENGTH)
last = SendResult(success=True)
for chunk in chunks:
guid = await self._resolve_chat_guid(chat_id)
+1 -5
View File
@@ -228,11 +228,7 @@ class DingTalkAdapter(BasePlatformAdapter):
return False
try:
# Tighter keepalive so idle CLOSE_WAIT drains promptly (#18451).
from gateway.platforms._http_client_limits import platform_httpx_limits
self._http_client = httpx.AsyncClient(
timeout=30.0, limits=platform_httpx_limits(),
)
self._http_client = httpx.AsyncClient(timeout=30.0)
credential = dingtalk_stream.Credential(
self._client_id, self._client_secret
+114 -1090
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+1 -112
View File
@@ -28,10 +28,9 @@ from email.header import decode_header
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
from email.utils import formatdate
from email import encoders
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from typing import Any, Dict, List, Optional
from gateway.platforms.base import (
BasePlatformAdapter,
@@ -505,7 +504,6 @@ class EmailAdapter(BasePlatformAdapter):
msg["In-Reply-To"] = original_msg_id
msg["References"] = original_msg_id
msg["Date"] = formatdate(localtime=True)
msg_id = f"<hermes-{uuid.uuid4().hex[:12]}@{self._address.split('@')[1]}>"
msg["Message-ID"] = msg_id
@@ -540,113 +538,6 @@ class EmailAdapter(BasePlatformAdapter):
text += f"\n\nImage: {image_url}"
return await self.send(chat_id, text.strip(), reply_to)
async def send_multiple_images(
self,
chat_id: str,
images: List[Tuple[str, str]],
metadata: Optional[Dict[str, Any]] = None,
human_delay: float = 0.0,
) -> None:
"""Send a batch of images as a single email with multiple MIME attachments.
Local files are attached directly. URL images have their URL
appended to the body (email adapter does not download remote
images). No hard cap email clients handle dozens of
attachments fine, subject to SMTP message size limits.
"""
if not images:
return
from urllib.parse import unquote as _unquote
body_parts: List[str] = []
local_paths: List[str] = []
for image_url, alt_text in images:
if alt_text:
body_parts.append(alt_text)
if image_url.startswith("file://"):
local_path = _unquote(image_url[7:])
if Path(local_path).exists():
local_paths.append(local_path)
else:
logger.warning("[Email] Skipping missing image: %s", local_path)
else:
# Remote URLs just get linked in the body (parity with send_image)
body_parts.append(f"Image: {image_url}")
if not local_paths and not body_parts:
return
body = "\n\n".join(body_parts)
try:
loop = asyncio.get_running_loop()
await loop.run_in_executor(
None,
self._send_email_with_attachments,
chat_id,
body,
local_paths,
)
except Exception as e:
logger.error("[Email] Multi-image send failed, falling back: %s", e, exc_info=True)
await super().send_multiple_images(chat_id, images, metadata, human_delay)
def _send_email_with_attachments(
self,
to_addr: str,
body: str,
file_paths: List[str],
) -> str:
"""Send an email with multiple file attachments via SMTP."""
msg = MIMEMultipart()
msg["From"] = self._address
msg["To"] = to_addr
ctx = self._thread_context.get(to_addr, {})
subject = ctx.get("subject", "Hermes Agent")
if not subject.startswith("Re:"):
subject = f"Re: {subject}"
msg["Subject"] = subject
original_msg_id = ctx.get("message_id")
if original_msg_id:
msg["In-Reply-To"] = original_msg_id
msg["References"] = original_msg_id
msg["Date"] = formatdate(localtime=True)
msg_id = f"<hermes-{uuid.uuid4().hex[:12]}@{self._address.split('@')[1]}>"
msg["Message-ID"] = msg_id
if body:
msg.attach(MIMEText(body, "plain", "utf-8"))
for file_path in file_paths:
p = Path(file_path)
try:
with open(p, "rb") as f:
part = MIMEBase("application", "octet-stream")
part.set_payload(f.read())
encoders.encode_base64(part)
part.add_header("Content-Disposition", f"attachment; filename={p.name}")
msg.attach(part)
except Exception as e:
logger.warning("[Email] Failed to attach %s: %s", file_path, e)
smtp = smtplib.SMTP(self._smtp_host, self._smtp_port, timeout=30)
try:
smtp.starttls(context=ssl.create_default_context())
smtp.login(self._address, self._password)
smtp.send_message(msg)
finally:
try:
smtp.quit()
except Exception:
smtp.close()
logger.info("[Email] Sent multi-attachment email to %s (%d files)", to_addr, len(file_paths))
return msg_id
async def send_document(
self,
chat_id: str,
@@ -654,7 +545,6 @@ class EmailAdapter(BasePlatformAdapter):
caption: Optional[str] = None,
file_name: Optional[str] = None,
reply_to: Optional[str] = None,
**kwargs,
) -> SendResult:
"""Send a file as an email attachment."""
try:
@@ -695,7 +585,6 @@ class EmailAdapter(BasePlatformAdapter):
msg["In-Reply-To"] = original_msg_id
msg["References"] = original_msg_id
msg["Date"] = formatdate(localtime=True)
msg_id = f"<hermes-{uuid.uuid4().hex[:12]}@{self._address.split('@')[1]}>"
msg["Message-ID"] = msg_id
File diff suppressed because it is too large Load Diff
+1
View File
@@ -974,6 +974,7 @@ def build_whole_comment_prompt(
def _resolve_model_and_runtime() -> Tuple[str, dict]:
"""Resolve model and provider credentials, same as gateway message handling."""
import os
from gateway.run import _load_gateway_config, _resolve_gateway_model
user_config = _load_gateway_config()
+4 -14
View File
@@ -11,12 +11,10 @@ import logging
import re
import time
from pathlib import Path
from typing import TYPE_CHECKING, Dict
from utils import atomic_json_write
from typing import TYPE_CHECKING, Dict, Optional
if TYPE_CHECKING:
from gateway.platforms.base import MessageEvent
from gateway.platforms.base import BasePlatformAdapter, MessageEvent
logger = logging.getLogger(__name__)
@@ -59,15 +57,6 @@ class MessageDeduplicator:
if len(self._seen) > self._max_size:
cutoff = now - self._ttl
self._seen = {k: v for k, v in self._seen.items() if v > cutoff}
if len(self._seen) > self._max_size:
# TTL pruning alone does not cap the cache when every entry is
# still fresh. Keep the newest entries so the helper's
# max_size bound is enforced under sustained traffic.
newest = sorted(
self._seen.items(),
key=lambda item: item[1],
)[-self._max_size:]
self._seen = dict(newest)
return False
def clear(self):
@@ -239,11 +228,12 @@ class ThreadParticipationTracker:
def _save(self) -> None:
path = self._state_path()
path.parent.mkdir(parents=True, exist_ok=True)
thread_list = list(self._threads)
if len(thread_list) > self._max_tracked:
thread_list = thread_list[-self._max_tracked:]
self._threads = set(thread_list)
atomic_json_write(path, thread_list, indent=None)
path.write_text(json.dumps(thread_list), encoding="utf-8")
def mark(self, thread_id: str) -> None:
"""Mark *thread_id* as participated and persist."""
+1 -1
View File
@@ -139,7 +139,7 @@ class HomeAssistantAdapter(BasePlatformAdapter):
async def _ws_connect(self) -> bool:
"""Establish WebSocket connection and authenticate."""
ws_url = self._hass_url.replace("https://", "wss://").replace("http://", "ws://")
ws_url = self._hass_url.replace("http://", "ws://").replace("https://", "wss://")
ws_url = f"{ws_url}/api/websocket"
self._session = aiohttp.ClientSession(
+47 -507
View File
@@ -11,7 +11,6 @@ Environment variables:
MATRIX_PASSWORD Password (alternative to access token)
MATRIX_ENCRYPTION Set "true" to enable E2EE
MATRIX_DEVICE_ID Stable device ID for E2EE persistence across restarts
MATRIX_PROXY HTTP(S) or SOCKS proxy URL for Matrix traffic
MATRIX_ALLOWED_USERS Comma-separated Matrix user IDs (@user:server)
MATRIX_HOME_ROOM Room ID for cron/notification delivery
MATRIX_REACTIONS Set "false" to disable processing lifecycle reactions
@@ -19,7 +18,6 @@ Environment variables:
MATRIX_REQUIRE_MENTION Require @mention in rooms (default: true)
MATRIX_FREE_RESPONSE_ROOMS Comma-separated room IDs exempt from mention requirement
MATRIX_AUTO_THREAD Auto-create threads for room messages (default: true)
MATRIX_DM_AUTO_THREAD Auto-create threads for DM messages (default: false)
MATRIX_RECOVERY_KEY Recovery key for cross-signing verification after device key rotation
MATRIX_DM_MENTION_THREADS Create a thread when bot is @mentioned in a DM (default: false)
"""
@@ -32,8 +30,6 @@ import mimetypes
import os
import re
import time
from dataclasses import dataclass
from html import escape as _html_escape
from pathlib import Path
from typing import Any, Dict, Optional, Set
@@ -99,25 +95,11 @@ from gateway.platforms.base import (
MessageType,
ProcessingOutcome,
SendResult,
resolve_proxy_url,
proxy_kwargs_for_aiohttp,
)
from gateway.platforms.helpers import ThreadParticipationTracker
logger = logging.getLogger(__name__)
@dataclass
class _MatrixApprovalPrompt:
"""Tracks a pending Matrix reaction-based exec approval prompt."""
def __init__(self, session_key: str, chat_id: str, message_id: str, resolved: bool = False):
self.session_key = session_key
self.chat_id = chat_id
self.message_id = message_id
self.resolved = resolved
self.bot_reaction_events: dict[str, str] = {} # emoji -> event_id
# Matrix message size limit (4000 chars practical, spec has no hard limit
# but clients render poorly above this).
MAX_MESSAGE_LENGTH = 4000
@@ -132,85 +114,11 @@ _CRYPTO_DB_PATH = _STORE_DIR / "crypto.db"
# Grace period: ignore messages older than this many seconds before startup.
_STARTUP_GRACE_SECONDS = 5
_OUTBOUND_MENTION_RE = re.compile(
r"(?<![\w/])(@[0-9A-Za-z._=/-]+:[0-9A-Za-z.-]+(?::\d+)?)"
)
_E2EE_INSTALL_HINT = (
"Install with: pip install 'mautrix[encryption]' (requires libolm C library)"
)
_MATRIX_IMAGE_FILENAME_EXTS = frozenset({
".jpg",
".jpeg",
".png",
".gif",
".webp",
".bmp",
".svg",
".heic",
".heif",
".avif",
})
def _looks_like_matrix_image_filename(text: str) -> bool:
"""Return True when Matrix image body text is probably just a transport filename.
Matrix ``m.image`` events commonly populate ``content.body`` with the uploaded
filename when the user did not add a caption. Treating that raw filename as
user-authored text confuses downstream vision enrichment.
"""
candidate = str(text or "").strip()
if not candidate or "\n" in candidate or candidate.endswith("/"):
return False
name = Path(candidate).name
if not name or name != candidate:
return False
suffix = Path(name).suffix.lower()
if not suffix:
return False
guessed_type, _ = mimetypes.guess_type(name)
if guessed_type and guessed_type.startswith("image/"):
return True
return suffix in _MATRIX_IMAGE_FILENAME_EXTS
def _create_matrix_session(proxy_url: str | None):
"""Create an ``aiohttp.ClientSession`` whose proxy applies to *all* requests.
mautrix's ``HTTPAPI._send()`` calls ``session.request()`` without forwarding
per-request ``proxy=`` kwargs. For HTTP(S) proxies we use aiohttp's native
``proxy=`` session parameter which sets a default for every request. For SOCKS
we use ``aiohttp_socks.ProxyConnector`` (connector-level).
When no proxy is configured we enable ``trust_env`` so standard env vars
(``HTTP_PROXY`` / ``HTTPS_PROXY``) are honoured automatically.
"""
import aiohttp
if not proxy_url:
return aiohttp.ClientSession(trust_env=True)
if proxy_url.split("://")[0].lower().startswith("socks"):
try:
from aiohttp_socks import ProxyConnector
return aiohttp.ClientSession(
connector=ProxyConnector.from_url(proxy_url, rdns=True),
)
except ImportError:
logger.warning(
"aiohttp_socks not installed — SOCKS proxy %s ignored. "
"Run: pip install aiohttp-socks",
proxy_url,
)
return aiohttp.ClientSession(trust_env=True)
return aiohttp.ClientSession(proxy=proxy_url)
def _check_e2ee_deps() -> bool:
"""Return True if mautrix E2EE dependencies (python-olm) are available."""
@@ -352,9 +260,6 @@ class MatrixAdapter(BasePlatformAdapter):
"1",
"yes",
)
self._dm_auto_thread: bool = os.getenv(
"MATRIX_DM_AUTO_THREAD", "false"
).lower() in ("true", "1", "yes")
self._dm_mention_threads: bool = os.getenv(
"MATRIX_DM_MENTION_THREADS", "false"
).lower() in ("true", "1", "yes")
@@ -365,11 +270,6 @@ class MatrixAdapter(BasePlatformAdapter):
).lower() not in ("false", "0", "no")
self._pending_reactions: dict[tuple[str, str], str] = {}
# Proxy support — resolve once at init, reuse for all HTTP traffic.
self._proxy_url: str | None = resolve_proxy_url(platform_env_var="MATRIX_PROXY")
if self._proxy_url:
logger.info("Matrix: proxy configured — %s", self._proxy_url)
# Text batching: merge rapid successive messages (Telegram-style).
# Matrix clients split long messages around 4000 chars.
self._text_batch_delay_seconds = float(
@@ -381,18 +281,6 @@ class MatrixAdapter(BasePlatformAdapter):
self._pending_text_batches: Dict[str, MessageEvent] = {}
self._pending_text_batch_tasks: Dict[str, asyncio.Task] = {}
# Matrix reaction-based dangerous command approvals.
self._approval_reaction_map = {
"": "once",
"": "deny",
}
self._approval_prompts_by_event: Dict[str, _MatrixApprovalPrompt] = {}
self._approval_prompt_by_session: Dict[str, str] = {}
allowed_users_raw = os.getenv("MATRIX_ALLOWED_USERS", "")
self._allowed_user_ids: Set[str] = {
u.strip() for u in allowed_users_raw.split(",") if u.strip()
}
def _is_duplicate_event(self, event_id) -> bool:
"""Return True if this event was already processed. Tracks the ID otherwise."""
if not event_id:
@@ -438,7 +326,7 @@ class MatrixAdapter(BasePlatformAdapter):
)
return False
except Exception as exc:
logger.error("Matrix: post-upload key verification failed: %s", exc, exc_info=True)
logger.error("Matrix: post-upload key verification failed: %s", exc)
return False
return True
@@ -454,7 +342,6 @@ class MatrixAdapter(BasePlatformAdapter):
logger.error(
"Matrix: cannot verify device keys on server: %s — refusing E2EE",
exc,
exc_info=True,
)
return False
@@ -469,7 +356,7 @@ class MatrixAdapter(BasePlatformAdapter):
try:
await olm.share_keys()
except Exception as exc:
logger.error("Matrix: failed to re-upload device keys: %s", exc, exc_info=True)
logger.error("Matrix: failed to re-upload device keys: %s", exc)
return False
return await self._reverify_keys_after_upload(client, local_ed25519)
@@ -509,7 +396,6 @@ class MatrixAdapter(BasePlatformAdapter):
"Try generating a new access token to get a fresh device.",
client.device_id,
exc,
exc_info=True,
)
return False
return await self._reverify_keys_after_upload(client, local_ed25519)
@@ -534,11 +420,9 @@ class MatrixAdapter(BasePlatformAdapter):
_STORE_DIR.mkdir(parents=True, exist_ok=True)
# Create the HTTP API layer.
client_session = _create_matrix_session(self._proxy_url)
api = HTTPAPI(
base_url=self._homeserver,
token=self._access_token or "",
client_session=client_session,
)
# Create the client.
@@ -581,7 +465,6 @@ class MatrixAdapter(BasePlatformAdapter):
logger.error(
"Matrix: whoami failed — check MATRIX_ACCESS_TOKEN and MATRIX_HOMESERVER: %s",
exc,
exc_info=True,
)
await api.session.close()
return False
@@ -649,20 +532,6 @@ class MatrixAdapter(BasePlatformAdapter):
)
await crypto_store.open()
# Bind the store to the runtime device_id before any
# put_account() runs. PgCryptoStore defaults _device_id
# to "" and its crypto_account UPSERT never updates the
# device_id column on conflict — so once put_account
# writes blank, it stays blank forever. That breaks
# every downstream device-scoped olm operation: peer
# to-device ciphertext can't find our identity key and
# no megolm sessions ever land. Setting _device_id here
# (in-memory; the on-disk row may not exist yet) makes
# the first put_account write the correct value.
# DeviceID is a NewType(str) so plain str works at runtime.
if client.device_id:
await crypto_store.put_device_id(client.device_id)
crypto_state = _CryptoStateStore(state_store, self._joined_rooms)
olm = OlmMachine(client, crypto_store, crypto_state)
@@ -724,44 +593,6 @@ class MatrixAdapter(BasePlatformAdapter):
logger.warning(
"Matrix: recovery key verification failed: %s", exc
)
else:
# No recovery key — bootstrap cross-signing if the bot
# has none yet. Without this, Element shows "Encrypted
# by a device not verified by its owner" on every
# message from this bot, indefinitely. mautrix's
# generate_recovery_key does the full flow: generates
# MSK/SSK/USK, uploads private keys to SSSS, publishes
# public keys to the homeserver, and signs the current
# device with the new SSK. Some homeservers require UIA
# for /keys/device_signing/upload — those will need an
# alternate path; Continuwuity and Synapse-with-shared-
# secret accept the unauthenticated upload.
try:
own_xsign = await olm.get_own_cross_signing_public_keys()
except Exception as exc:
own_xsign = None
logger.warning(
"Matrix: cross-signing key lookup failed: %s", exc
)
if own_xsign is None:
try:
new_recovery_key = await olm.generate_recovery_key()
logger.warning(
"Matrix: bootstrapped cross-signing for %s. "
"SAVE THIS RECOVERY KEY — set "
"MATRIX_RECOVERY_KEY for future restarts so "
"the bot can re-sign its device after key "
"rotation: %s",
client.mxid,
new_recovery_key,
)
except Exception as exc:
logger.warning(
"Matrix: cross-signing bootstrap failed "
"(non-fatal — Element will show 'not "
"verified by its owner'): %s",
exc,
)
client.crypto = olm
logger.info(
@@ -819,7 +650,6 @@ class MatrixAdapter(BasePlatformAdapter):
await asyncio.gather(*tasks)
except Exception as exc:
logger.warning("Matrix: initial sync event dispatch error: %s", exc)
await self._join_pending_invites(sync_data)
else:
logger.warning(
"Matrix: initial sync returned unexpected type %s",
@@ -883,8 +713,17 @@ class MatrixAdapter(BasePlatformAdapter):
chunks = self.truncate_message(formatted, MAX_MESSAGE_LENGTH)
last_event_id = None
for i, chunk in enumerate(chunks):
msg_content = self._build_text_message_content(chunk)
for chunk in chunks:
msg_content: Dict[str, Any] = {
"msgtype": "m.text",
"body": chunk,
}
# Convert markdown to HTML for rich rendering.
html = self._markdown_to_html(chunk)
if html and html != chunk:
msg_content["format"] = "org.matrix.custom.html"
msg_content["formatted_body"] = html
# Reply-to support.
if reply_to:
@@ -991,21 +830,25 @@ class MatrixAdapter(BasePlatformAdapter):
"""Edit an existing message (via m.replace)."""
formatted = self.format_message(content)
new_content = self._build_text_message_content(formatted)
msg_content: Dict[str, Any] = {
"msgtype": "m.text",
"body": f"* {formatted}",
"m.new_content": new_content,
"m.new_content": {
"msgtype": "m.text",
"body": formatted,
},
"m.relates_to": {
"rel_type": "m.replace",
"event_id": message_id,
},
}
if "m.mentions" in new_content:
msg_content["m.mentions"] = new_content["m.mentions"]
if "formatted_body" in new_content:
html = self._markdown_to_html(formatted)
if html and html != formatted:
msg_content["m.new_content"]["format"] = "org.matrix.custom.html"
msg_content["m.new_content"]["formatted_body"] = html
msg_content["format"] = "org.matrix.custom.html"
msg_content["formatted_body"] = f'* {new_content["formatted_body"]}'
msg_content["m.relates_to"] = {
"rel_type": "m.replace",
"event_id": message_id,
}
msg_content["formatted_body"] = f"* {html}"
try:
event_id = await self._client.send_message_event(
@@ -1038,12 +881,10 @@ class MatrixAdapter(BasePlatformAdapter):
# Try aiohttp first (always available), fall back to httpx
try:
import aiohttp as _aiohttp
_sess_kw, _req_kw = proxy_kwargs_for_aiohttp(self._proxy_url)
async with _aiohttp.ClientSession(**_sess_kw) as http:
async with _aiohttp.ClientSession(trust_env=True) as http:
async with http.get(
image_url,
timeout=_aiohttp.ClientTimeout(total=30),
**_req_kw,
image_url, timeout=_aiohttp.ClientTimeout(total=30)
) as resp:
resp.raise_for_status()
data = await resp.read()
@@ -1053,10 +894,8 @@ class MatrixAdapter(BasePlatformAdapter):
)
except ImportError:
import httpx
_httpx_kw: dict = {}
if self._proxy_url:
_httpx_kw["proxy"] = self._proxy_url
async with httpx.AsyncClient(**_httpx_kw) as http:
async with httpx.AsyncClient() as http:
resp = await http.get(image_url, follow_redirects=True, timeout=30)
resp.raise_for_status()
data = resp.content
@@ -1131,56 +970,6 @@ class MatrixAdapter(BasePlatformAdapter):
chat_id, video_path, "m.video", caption, reply_to, metadata=metadata
)
async def send_exec_approval(
self,
chat_id: str,
command: str,
session_key: str,
description: str = "dangerous command",
metadata: Optional[dict] = None,
) -> SendResult:
"""Send a reaction-based exec approval prompt for Matrix."""
if not self._client:
return SendResult(success=False, error="Not connected")
cmd_preview = command[:2000] + "..." if len(command) > 2000 else command
text = (
"⚠️ **Dangerous command requires approval**\n"
f"```\n{cmd_preview}\n```\n"
f"Reason: {description}\n\n"
"Reply `/approve` to execute, `/approve session` to approve this pattern for the session, "
"`/approve always` to approve permanently, or `/deny` to cancel.\n\n"
"You can also click the reaction to approve:\n"
"✅ = /approve\n"
"❎ = /deny"
)
result = await self.send(chat_id, text, metadata=metadata)
if not result.success or not result.message_id:
return result
prompt = _MatrixApprovalPrompt(
session_key=session_key,
chat_id=chat_id,
message_id=result.message_id,
)
old_event = self._approval_prompt_by_session.get(session_key)
if old_event:
self._approval_prompts_by_event.pop(old_event, None)
self._approval_prompts_by_event[result.message_id] = prompt
self._approval_prompt_by_session[session_key] = result.message_id
for emoji in ("", ""):
try:
reaction_result = await self._send_reaction(chat_id, result.message_id, emoji)
# Save the bot's reaction event_id for later cleanup
if reaction_result:
prompt.bot_reaction_events[emoji] = str(reaction_result)
except Exception as exc:
logger.debug("Matrix: failed to add approval reaction %s: %s", emoji, exc)
return result
def format_message(self, content: str) -> str:
"""Pass-through — Matrix supports standard Markdown natively."""
# Strip image markdown; media is uploaded separately.
@@ -1312,15 +1101,9 @@ class MatrixAdapter(BasePlatformAdapter):
next_batch = await client.sync_store.get_next_batch()
while not self._closing:
try:
# Wrap in asyncio.wait_for to guard against TCP-level hangs
# that the Matrix long-poll timeout cannot catch. Long-poll
# is 30s, so 45s gives 15s slack for network drain.
sync_data = await asyncio.wait_for(
client.sync(
since=next_batch,
timeout=30000,
),
timeout=45.0,
sync_data = await client.sync(
since=next_batch,
timeout=30000,
)
# nio returns SyncError objects (not exceptions) for auth
@@ -1356,7 +1139,6 @@ class MatrixAdapter(BasePlatformAdapter):
await asyncio.gather(*tasks)
except Exception as exc:
logger.warning("Matrix: sync event dispatch error: %s", exc)
await self._join_pending_invites(sync_data)
except asyncio.CancelledError:
return
@@ -1382,92 +1164,13 @@ class MatrixAdapter(BasePlatformAdapter):
# Event callbacks
# ------------------------------------------------------------------
def _is_self_sender(self, sender: str) -> bool:
"""Return True if the sender refers to the bot's own account.
Matrix user IDs are byte-compared after trimming whitespace and
lowercasing some homeservers normalize the localpart case
differently at different API surfaces, and the reply-loop tail
of the "hall of mirrors" bug (#15763) has been observed with the
bot's own account bypassing a case-sensitive equality check.
When ``self._user_id`` is empty (whoami hasn't resolved yet, or
login failed), we cannot prove a sender is NOT us, so we return
True defensively an unidentified bot dropping its own events
is always preferable to falling into an echo loop.
"""
own = (self._user_id or "").strip().lower()
if not own:
return True
return sender.strip().lower() == own
@staticmethod
def _is_system_or_bridge_sender(sender: str) -> bool:
"""Return True if the sender looks like a system / bridge / appservice
identity rather than a real user.
Appservice namespaces on Matrix conventionally prefix bot / puppet
user IDs with an underscore (e.g. ``@_telegram_12345:server``,
``@_discord_999:server``, ``@_slack_...:server``). Server-notices
bots and bridge-controller bots on many homeservers use the same
pattern.
We treat these as system identities for pairing purposes: they
should never be offered a pairing code, because an operator
approving the code would hand the bridge itself permanent
authorization and every outbound message relayed by the bridge
would then loop back into the agent as an "authorized user
message", which is the root of issue #15763.
Matches:
``@_something:server`` appservice namespace convention
``@:server`` malformed / empty localpart
``:server`` malformed, no leading ``@``
"""
s = (sender or "").strip()
if not s:
return True
# Localpart is everything between leading '@' and ':'
if s.startswith("@"):
s = s[1:]
if ":" in s:
localpart, _, _ = s.partition(":")
else:
localpart = s
if not localpart:
return True
return localpart.startswith("_")
async def _on_room_message(self, event: Any) -> None:
"""Handle incoming room message events (text, media)."""
room_id = str(getattr(event, "room_id", ""))
sender = str(getattr(event, "sender", ""))
# Diagnostic: confirm the callback is firing at all when DEBUG is on.
# Helps users troubleshoot silent inbound issues like #5819, #7914, #12614.
logger.debug(
"Matrix: callback fired — event %s from %s in %s",
getattr(event, "event_id", "?"),
sender,
room_id,
)
# Ignore own messages (case-insensitive; also drops when our own
# user_id hasn't been resolved yet — see _is_self_sender docstring
# and issue #15763).
if self._is_self_sender(sender):
return
# Ignore appservice / bridge / system identities so they never
# trigger the pairing flow. Once a bridge user is paired, every
# outbound message it relays would loop back as an authorized
# user message (the "hall of mirrors" in #15763).
if self._is_system_or_bridge_sender(sender):
logger.debug(
"Matrix: ignoring system/bridge sender %s in %s",
sender,
room_id,
)
# Ignore own messages.
if sender == self._user_id:
return
# Deduplicate by event ID.
@@ -1563,12 +1266,6 @@ class MatrixAdapter(BasePlatformAdapter):
in_bot_thread = bool(thread_id and thread_id in self._threads)
if self._require_mention and not is_free_room and not in_bot_thread:
if not is_mentioned:
logger.debug(
"Matrix: ignoring message %s in %s — no @mention "
"(set MATRIX_REQUIRE_MENTION=false to disable)",
event_id,
room_id,
)
return None
# DM mention-thread.
@@ -1581,7 +1278,7 @@ class MatrixAdapter(BasePlatformAdapter):
body = self._strip_mention(body)
# Auto-thread.
if not thread_id and ((not is_dm and self._auto_thread) or (is_dm and self._dm_auto_thread)):
if not is_dm and not thread_id and self._auto_thread:
thread_id = event_id
self._threads.mark(thread_id)
@@ -1823,9 +1520,6 @@ class MatrixAdapter(BasePlatformAdapter):
return
body, is_dm, chat_type, thread_id, display_name, source = ctx
if msgtype == "m.image" and _looks_like_matrix_image_filename(body):
body = ""
allow_http_fallback = bool(http_url) and not is_encrypted_media
media_urls = (
[cached_path]
@@ -1855,35 +1549,13 @@ class MatrixAdapter(BasePlatformAdapter):
"Matrix: invited to %s — joining",
room_id,
)
await self._join_room_by_id(room_id)
async def _join_room_by_id(self, room_id: str) -> bool:
"""Join a room by ID and refresh local caches on success."""
if not room_id:
return False
if room_id in self._joined_rooms:
return True
try:
await self._client.join_room(RoomID(room_id))
self._joined_rooms.add(room_id)
logger.info("Matrix: joined %s", room_id)
await self._refresh_dm_cache()
return True
except Exception as exc:
logger.warning("Matrix: error joining %s: %s", room_id, exc)
return False
async def _join_pending_invites(self, sync_data: Dict[str, Any]) -> None:
"""Join rooms still present in rooms.invite after sync processing."""
rooms = sync_data.get("rooms", {}) if isinstance(sync_data, dict) else {}
invites = rooms.get("invite", {})
if not isinstance(invites, dict):
return
for room_id in invites:
if room_id in self._joined_rooms:
continue
logger.info("Matrix: reconciling pending invite for %s", room_id)
await self._join_room_by_id(str(room_id))
# ------------------------------------------------------------------
# Reactions (send, receive, processing lifecycle)
@@ -1968,7 +1640,7 @@ class MatrixAdapter(BasePlatformAdapter):
async def _on_reaction(self, event: Any) -> None:
"""Handle incoming reaction events."""
sender = str(getattr(event, "sender", ""))
if self._is_self_sender(sender):
if sender == self._user_id:
return
event_id = str(getattr(event, "event_id", ""))
if self._is_duplicate_event(event_id):
@@ -1998,51 +1670,6 @@ class MatrixAdapter(BasePlatformAdapter):
room_id,
)
# Check if this reaction resolves a pending approval prompt.
prompt = self._approval_prompts_by_event.get(reacts_to)
if prompt and not prompt.resolved:
if room_id != prompt.chat_id:
return
if self._allowed_user_ids and sender not in self._allowed_user_ids:
logger.info(
"Matrix: ignoring approval reaction from unauthorized user %s on %s",
sender, reacts_to,
)
return
choice = self._approval_reaction_map.get(key)
if not choice:
return
try:
from tools.approval import resolve_gateway_approval
count = resolve_gateway_approval(prompt.session_key, choice)
if count:
prompt.resolved = True
self._approval_prompts_by_event.pop(reacts_to, None)
self._approval_prompt_by_session.pop(prompt.session_key, None)
logger.info(
"Matrix reaction resolved %d approval(s) for session %s "
"(choice=%s, user=%s)",
count, prompt.session_key, choice, sender,
)
# Redact bot's seed reactions, leaving only the user's
await self._redact_bot_approval_reactions(room_id, prompt)
except Exception as exc:
logger.error("Failed to resolve gateway approval from Matrix reaction: %s", exc)
async def _redact_bot_approval_reactions(
self,
room_id: str,
prompt: "_MatrixApprovalPrompt",
) -> None:
"""Redact the bot's seed ✅/❎ reactions, leaving only the user's reaction."""
for emoji, evt_id in prompt.bot_reaction_events.items():
try:
await self.redact_message(room_id, evt_id, "approval resolved")
logger.debug("Matrix: redacted bot reaction %s (%s)", emoji, evt_id)
except Exception as exc:
logger.debug("Matrix: failed to redact bot reaction %s: %s", emoji, exc)
# ------------------------------------------------------------------
# Text message aggregation (handles Matrix client-side splits)
# ------------------------------------------------------------------
@@ -2268,7 +1895,11 @@ class MatrixAdapter(BasePlatformAdapter):
if not self._client or not text:
return SendResult(success=False, error="No client or empty text")
msg_content = self._build_text_message_content(text, msgtype=msgtype)
msg_content: Dict[str, Any] = {"msgtype": msgtype, "body": text}
html = self._markdown_to_html(text)
if html and html != text:
msg_content["format"] = "org.matrix.custom.html"
msg_content["formatted_body"] = html
try:
event_id = await self._client.send_message_event(
@@ -2331,77 +1962,6 @@ class MatrixAdapter(BasePlatformAdapter):
# Mention detection helpers
# ------------------------------------------------------------------
def _build_text_message_content(self, text: str, msgtype: str = "m.text") -> Dict[str, Any]:
"""Build Matrix text content with HTML and outbound mention metadata."""
msg_content: Dict[str, Any] = {"msgtype": msgtype, "body": text}
mention_user_ids = self._extract_outbound_mentions(text)
if mention_user_ids:
msg_content["m.mentions"] = {"user_ids": mention_user_ids}
html_source = self._inject_outbound_mention_links(text)
html = self._markdown_to_html(html_source)
if html and html != text:
msg_content["format"] = "org.matrix.custom.html"
msg_content["formatted_body"] = html
return msg_content
def _extract_outbound_mentions(self, text: str) -> list[str]:
"""Return unique Matrix user IDs mentioned in outbound text."""
protected, _ = self._protect_outbound_mention_regions(text)
seen: Set[str] = set()
mentions: list[str] = []
for match in _OUTBOUND_MENTION_RE.finditer(protected):
user_id = match.group(1)
if user_id not in seen:
seen.add(user_id)
mentions.append(user_id)
return mentions
def _inject_outbound_mention_links(self, text: str) -> str:
"""Wrap outbound Matrix mentions in markdown links outside code spans."""
if not text:
return text
protected, placeholders = self._protect_outbound_mention_regions(text)
linked = _OUTBOUND_MENTION_RE.sub(
lambda match: f"[{match.group(1)}](https://matrix.to/#/{match.group(1)})",
protected,
)
for idx, original in enumerate(placeholders):
linked = linked.replace(f"\x00MENTION_PROTECTED{idx}\x00", original)
return linked
def _protect_outbound_mention_regions(self, text: str) -> tuple[str, list[str]]:
"""Protect markdown regions where outbound mentions should stay literal."""
placeholders: list[str] = []
def _protect(fragment: str) -> str:
idx = len(placeholders)
placeholders.append(fragment)
return f"\x00MENTION_PROTECTED{idx}\x00"
protected = re.sub(
r"```[\s\S]*?```",
lambda match: _protect(match.group(0)),
text or "",
)
protected = re.sub(
r"`[^`\n]+`",
lambda match: _protect(match.group(0)),
protected,
)
protected = re.sub(
r"\[[^\]]+\]\([^)]+\)",
lambda match: _protect(match.group(0)),
protected,
)
return protected, placeholders
def _is_bot_mentioned(
self,
body: str,
@@ -2436,33 +1996,13 @@ class MatrixAdapter(BasePlatformAdapter):
return False
def _strip_mention(self, body: str) -> str:
"""Remove explicit bot mentions from message body.
"""Strip the bot's full MXID (``@user:server``) from *body*.
Important: only strip explicit mention tokens (``@user:server`` or
``@localpart``). Do NOT strip bare words matching the bot localpart,
otherwise normal phrases like "Hermes Agent" become "Agent".
The bare localpart is intentionally *not* stripped it would
mangle file paths like ``/home/hermes/media/file.png``.
"""
if not body:
return ""
# Strip explicit full MXID mentions.
if self._user_id:
body = body.replace(self._user_id, "")
# Strip explicit @localpart mentions only (not bare localpart words).
if self._user_id and ":" in self._user_id:
localpart = self._user_id.split(":")[0].lstrip("@")
if localpart:
body = re.sub(
r'(?<![\w])@' + re.escape(localpart) + r'\b',
'',
body,
flags=re.IGNORECASE,
)
# Normalize spacing after mention removal.
body = re.sub(r'[ \t]{2,}', ' ', body)
body = re.sub(r'\s+([,.;:!?])', r'\1', body)
return body.strip()
async def _get_display_name(self, room_id: str, user_id: str) -> str:
+2 -95
View File
@@ -19,7 +19,7 @@ import logging
import os
import re
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from typing import Any, Dict, List, Optional
from gateway.config import Platform, PlatformConfig
from gateway.platforms.helpers import MessageDeduplicator
@@ -412,6 +412,7 @@ class MattermostAdapter(BasePlatformAdapter):
import aiohttp
last_exc = None
file_data = None
ct = "application/octet-stream"
fname = url.rsplit("/", 1)[-1].split("?")[0] or f"{kind}.png"
@@ -496,100 +497,6 @@ class MattermostAdapter(BasePlatformAdapter):
return SendResult(success=False, error="Failed to post with file")
return SendResult(success=True, message_id=data["id"])
async def send_multiple_images(
self,
chat_id: str,
images: List[Tuple[str, str]],
metadata: Optional[Dict[str, Any]] = None,
human_delay: float = 0.0,
) -> None:
"""Send a batch of images as a single Mattermost post with multiple attachments.
Mattermost supports up to 5 ``file_ids`` per post. Each image is
uploaded individually (Mattermost's file API is one-at-a-time),
then a single post is created referencing all uploaded file_ids
at once. Batches larger than 5 are chunked. Falls back to the
base per-image loop on total failure.
"""
if not images:
return
import mimetypes
import aiohttp
from urllib.parse import unquote as _unquote
CHUNK = 5 # Mattermost post file_ids cap
chunks = [images[i:i + CHUNK] for i in range(0, len(images), CHUNK)]
for chunk_idx, chunk in enumerate(chunks):
if human_delay > 0 and chunk_idx > 0:
await asyncio.sleep(human_delay)
file_ids: List[str] = []
caption_parts: List[str] = []
try:
for image_url, alt_text in chunk:
if alt_text:
caption_parts.append(alt_text)
if image_url.startswith("file://"):
local_path = _unquote(image_url[7:])
p = Path(local_path)
if not p.exists():
logger.warning("Mattermost: skipping missing image %s", local_path)
continue
fname = p.name
ct = mimetypes.guess_type(fname)[0] or "image/png"
file_data = p.read_bytes()
else:
from tools.url_safety import is_safe_url
if not is_safe_url(image_url):
logger.warning("Mattermost: blocked unsafe image URL in batch")
continue
try:
async with self._session.get(
image_url, timeout=aiohttp.ClientTimeout(total=30)
) as resp:
if resp.status >= 400:
logger.warning(
"Mattermost: failed to download image (HTTP %d): %s",
resp.status, image_url[:80],
)
continue
file_data = await resp.read()
ct = resp.content_type or "image/png"
except Exception as dl_err:
logger.warning("Mattermost: download failed for %s: %s", image_url[:80], dl_err)
continue
fname = image_url.rsplit("/", 1)[-1].split("?")[0] or f"image_{len(file_ids)}.png"
fid = await self._upload_file(chat_id, file_data, fname, ct)
if fid:
file_ids.append(fid)
if not file_ids:
continue
payload: Dict[str, Any] = {
"channel_id": chat_id,
"message": "\n".join(caption_parts),
"file_ids": file_ids,
}
logger.info(
"Mattermost: sending %d image(s) as single post (chunk %d/%d)",
len(file_ids), chunk_idx + 1, len(chunks),
)
data = await self._api_post("posts", payload)
if not data or "id" not in data:
logger.warning("Mattermost: multi-image post failed, falling back")
await super().send_multiple_images(chat_id, chunk, metadata, human_delay=human_delay)
except Exception as e:
logger.warning(
"Mattermost: multi-image send failed (chunk %d/%d), falling back: %s",
chunk_idx + 1, len(chunks), e, exc_info=True,
)
await super().send_multiple_images(chat_id, chunk, metadata, human_delay=human_delay)
# ------------------------------------------------------------------
# WebSocket
# ------------------------------------------------------------------
+4 -2
View File
@@ -26,8 +26,9 @@ from .adapter import ( # noqa: F401
# -- Onboard (QR-code scan-to-configure) -----------------------------------
from .onboard import ( # noqa: F401
BindStatus,
create_bind_task,
poll_bind_result,
build_connect_url,
qr_register,
)
from .crypto import decrypt_secret, generate_bind_key # noqa: F401
@@ -43,8 +44,9 @@ __all__ = [
"_ssrf_redirect_guard",
# onboard
"BindStatus",
"create_bind_task",
"poll_bind_result",
"build_connect_url",
"qr_register",
# crypto
"decrypt_secret",
"generate_bind_key",
+7 -32
View File
@@ -243,14 +243,10 @@ class QQAdapter(BasePlatformAdapter):
return False
try:
# Tighter keepalive pool so idle CLOSE_WAIT sockets drain
# faster behind proxies like Cloudflare Warp (#18451).
from gateway.platforms._http_client_limits import platform_httpx_limits
self._http_client = httpx.AsyncClient(
timeout=30.0,
follow_redirects=True,
event_hooks={"response": [_ssrf_redirect_guard]},
limits=platform_httpx_limits(),
)
# 1. Get access token
@@ -539,9 +535,6 @@ class QQAdapter(BasePlatformAdapter):
quick_disconnect_count = 0
else:
backoff_idx += 1
if backoff_idx >= MAX_RECONNECT_ATTEMPTS:
logger.error("[%s] Max reconnect attempts reached (QQCloseError)", self._log_tag)
return
except Exception as exc:
if not self._running:
@@ -980,18 +973,6 @@ class QQAdapter(BasePlatformAdapter):
if not channel_id:
return
# Apply group_policy ACL — guild channels are group-like contexts.
# Without this check any member of any guild the bot is in could
# bypass the configured allowlist.
guild_id = str(d.get("guild_id", ""))
author_id = str(author.get("id", ""))
if not self._is_group_allowed(guild_id or channel_id, author_id):
logger.debug(
"[%s] Guild message blocked by ACL: channel=%s user=%s",
self._log_tag, channel_id, author_id,
)
return
member = d.get("member") if isinstance(d.get("member"), dict) else {}
nick = str(member.get("nick", "")) or str(author.get("username", ""))
@@ -1048,17 +1029,6 @@ class QQAdapter(BasePlatformAdapter):
if not guild_id:
return
# Apply dm_policy ACL — guild DMs were previously unauthenticated.
# Without this check any member of any guild the bot is in could
# bypass the configured allowlist via direct messages.
author_id = str(author.get("id", ""))
if not self._is_dm_allowed(author_id):
logger.debug(
"[%s] Guild DM blocked by ACL: guild=%s user=%s",
self._log_tag, guild_id, author_id,
)
return
text = content
att_result = await self._process_attachments(d.get("attachments"))
image_urls = att_result["image_urls"]
@@ -1984,7 +1954,7 @@ class QQAdapter(BasePlatformAdapter):
self, openid: str, content: str, reply_to: Optional[str] = None
) -> SendResult:
"""Send text to a C2C user via REST API."""
self._next_msg_seq(reply_to or openid)
msg_seq = self._next_msg_seq(reply_to or openid)
body = self._build_text_body(content, reply_to)
if reply_to:
body["msg_id"] = reply_to
@@ -1997,7 +1967,7 @@ class QQAdapter(BasePlatformAdapter):
self, group_openid: str, content: str, reply_to: Optional[str] = None
) -> SendResult:
"""Send text to a group via REST API."""
self._next_msg_seq(reply_to or group_openid)
msg_seq = self._next_msg_seq(reply_to or group_openid)
body = self._build_text_body(content, reply_to)
if reply_to:
body["msg_id"] = reply_to
@@ -2162,6 +2132,11 @@ class QQAdapter(BasePlatformAdapter):
# Route
chat_type = self._guess_chat_type(chat_id)
target_path = (
f"/v2/users/{chat_id}/files"
if chat_type == "c2c"
else f"/v2/groups/{chat_id}/files"
)
if chat_type == "guild":
# Guild channels don't support native media upload in the same way
+21 -117
View File
@@ -1,10 +1,6 @@
"""
QQBot scan-to-configure (QR code onboard) module.
Mirrors the Feishu onboarding pattern: synchronous HTTP + a single public
entry-point ``qr_register()`` that handles the full flow (create task
display QR code poll decrypt credentials).
Calls the ``q.qq.com`` ``create_bind_task`` / ``poll_bind_result`` APIs to
generate a QR-code URL and poll for scan completion. On success the caller
receives the bot's *app_id*, *client_secret* (decrypted locally), and the
@@ -16,20 +12,18 @@ Reference: https://bot.q.qq.com/wiki/develop/api-v2/
from __future__ import annotations
import logging
import time
from enum import IntEnum
from typing import Optional, Tuple
from typing import Tuple
from urllib.parse import quote
from .constants import (
ONBOARD_API_TIMEOUT,
ONBOARD_CREATE_PATH,
ONBOARD_POLL_INTERVAL,
ONBOARD_POLL_PATH,
PORTAL_HOST,
QR_URL_TEMPLATE,
)
from .crypto import decrypt_secret, generate_bind_key
from .crypto import generate_bind_key
from .utils import get_api_headers
logger = logging.getLogger(__name__)
@@ -41,7 +35,7 @@ logger = logging.getLogger(__name__)
class BindStatus(IntEnum):
"""Status codes returned by ``_poll_bind_result``."""
"""Status codes returned by ``poll_bind_result``."""
NONE = 0
PENDING = 1
@@ -50,40 +44,18 @@ class BindStatus(IntEnum):
# ---------------------------------------------------------------------------
# QR rendering
# ---------------------------------------------------------------------------
try:
import qrcode as _qrcode_mod
except (ImportError, TypeError):
_qrcode_mod = None # type: ignore[assignment]
def _render_qr(url: str) -> bool:
"""Try to render a QR code in the terminal. Returns True if successful."""
if _qrcode_mod is None:
return False
try:
qr = _qrcode_mod.QRCode(
error_correction=_qrcode_mod.constants.ERROR_CORRECT_M,
border=2,
)
qr.add_data(url)
qr.make(fit=True)
qr.print_ascii(invert=True)
return True
except Exception:
return False
# ---------------------------------------------------------------------------
# Synchronous HTTP helpers (mirrors Feishu _post_registration pattern)
# Public API
# ---------------------------------------------------------------------------
def _create_bind_task(timeout: float = ONBOARD_API_TIMEOUT) -> Tuple[str, str]:
async def create_bind_task(
timeout: float = ONBOARD_API_TIMEOUT,
) -> Tuple[str, str]:
"""Create a bind task and return *(task_id, aes_key_base64)*.
The AES key is generated locally and sent to the server so it can
encrypt the bot credentials before returning them.
Raises:
RuntimeError: If the API returns a non-zero ``retcode``.
"""
@@ -92,8 +64,8 @@ def _create_bind_task(timeout: float = ONBOARD_API_TIMEOUT) -> Tuple[str, str]:
url = f"https://{PORTAL_HOST}{ONBOARD_CREATE_PATH}"
key = generate_bind_key()
with httpx.Client(timeout=timeout, follow_redirects=True) as client:
resp = client.post(url, json={"key": key}, headers=get_api_headers())
async with httpx.AsyncClient(timeout=timeout, follow_redirects=True) as client:
resp = await client.post(url, json={"key": key}, headers=get_api_headers())
resp.raise_for_status()
data = resp.json()
@@ -108,7 +80,7 @@ def _create_bind_task(timeout: float = ONBOARD_API_TIMEOUT) -> Tuple[str, str]:
return task_id, key
def _poll_bind_result(
async def poll_bind_result(
task_id: str,
timeout: float = ONBOARD_API_TIMEOUT,
) -> Tuple[BindStatus, str, str, str]:
@@ -117,6 +89,12 @@ def _poll_bind_result(
Returns:
A 4-tuple of ``(status, bot_appid, bot_encrypt_secret, user_openid)``.
* ``bot_encrypt_secret`` is AES-256-GCM encrypted decrypt it with
:func:`~gateway.platforms.qqbot.crypto.decrypt_secret` using the
key from :func:`create_bind_task`.
* ``user_openid`` is the OpenID of the person who scanned the code
(available when ``status == COMPLETED``).
Raises:
RuntimeError: If the API returns a non-zero ``retcode``.
"""
@@ -124,8 +102,8 @@ def _poll_bind_result(
url = f"https://{PORTAL_HOST}{ONBOARD_POLL_PATH}"
with httpx.Client(timeout=timeout, follow_redirects=True) as client:
resp = client.post(url, json={"task_id": task_id}, headers=get_api_headers())
async with httpx.AsyncClient(timeout=timeout, follow_redirects=True) as client:
resp = await client.post(url, json={"task_id": task_id}, headers=get_api_headers())
resp.raise_for_status()
data = resp.json()
@@ -144,77 +122,3 @@ def _poll_bind_result(
def build_connect_url(task_id: str) -> str:
"""Build the QR-code target URL for a given *task_id*."""
return QR_URL_TEMPLATE.format(task_id=quote(task_id))
# ---------------------------------------------------------------------------
# Public entry-point
# ---------------------------------------------------------------------------
_MAX_REFRESHES = 3
def qr_register(timeout_seconds: int = 600) -> Optional[dict]:
"""Run the QQBot scan-to-configure QR registration flow.
Mirrors ``feishu.qr_register()``: handles create display poll
decrypt in one call. Unexpected errors propagate to the caller.
:returns:
``{"app_id": ..., "client_secret": ..., "user_openid": ...}`` on
success, or ``None`` on failure / expiry / cancellation.
"""
deadline = time.monotonic() + timeout_seconds
for refresh_count in range(_MAX_REFRESHES + 1):
# ── Create bind task ──
try:
task_id, aes_key = _create_bind_task()
except Exception as exc:
logger.warning("[QQBot onboard] Failed to create bind task: %s", exc)
return None
url = build_connect_url(task_id)
# ── Display QR code + URL ──
print()
if _render_qr(url):
print(f" Scan the QR code above, or open this URL directly:\n {url}")
else:
print(f" Open this URL in QQ on your phone:\n {url}")
print(" Tip: pip install qrcode to display a scannable QR code here")
print()
# ── Poll loop ──
while time.monotonic() < deadline:
try:
status, app_id, encrypted_secret, user_openid = _poll_bind_result(task_id)
except Exception:
time.sleep(ONBOARD_POLL_INTERVAL)
continue
if status == BindStatus.COMPLETED:
client_secret = decrypt_secret(encrypted_secret, aes_key)
print()
print(f" QR scan complete! (App ID: {app_id})")
if user_openid:
print(f" Scanner's OpenID: {user_openid}")
return {
"app_id": app_id,
"client_secret": client_secret,
"user_openid": user_openid,
}
if status == BindStatus.EXPIRED:
if refresh_count >= _MAX_REFRESHES:
logger.warning("[QQBot onboard] QR code expired %d times — giving up", _MAX_REFRESHES)
return None
print(f"\n QR code expired, refreshing... ({refresh_count + 1}/{_MAX_REFRESHES})")
break # next for-loop iteration creates a new task
time.sleep(ONBOARD_POLL_INTERVAL)
else:
# deadline reached without completing
logger.warning("[QQBot onboard] Poll timed out after %ds", timeout_seconds)
return None
return None
+13 -536
View File
@@ -21,7 +21,7 @@ import time
import uuid
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from typing import Dict, List, Optional, Any
from urllib.parse import quote, unquote
import httpx
@@ -31,7 +31,6 @@ from gateway.platforms.base import (
BasePlatformAdapter,
MessageEvent,
MessageType,
ProcessingOutcome,
SendResult,
cache_image_from_bytes,
cache_audio_from_bytes,
@@ -39,17 +38,6 @@ from gateway.platforms.base import (
cache_image_from_url,
)
from gateway.platforms.helpers import redact_phone
from gateway.platforms.signal_rate_limit import (
SIGNAL_BATCH_PACING_NOTICE_THRESHOLD,
SIGNAL_MAX_ATTACHMENTS_PER_MSG,
SIGNAL_RATE_LIMIT_MAX_ATTEMPTS,
SignalRateLimitError,
_extract_retry_after_seconds,
_format_wait,
_is_signal_rate_limit_error,
_signal_send_timeout,
get_scheduler,
)
logger = logging.getLogger(__name__)
@@ -64,7 +52,6 @@ SSE_RETRY_DELAY_MAX = 60.0
HEALTH_CHECK_INTERVAL = 30.0 # seconds between health checks
HEALTH_CHECK_STALE_THRESHOLD = 120.0 # seconds without SSE activity before concern
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
@@ -175,10 +162,6 @@ class SignalAdapter(BasePlatformAdapter):
"""Signal messenger adapter using signal-cli HTTP daemon."""
platform = Platform.SIGNAL
# Signal has no real edit API for already-sent messages. Mark it explicitly
# so streaming suppresses the visible cursor instead of leaving a stale tofu
# square behind in chat clients when edit attempts fail.
SUPPORTS_MESSAGE_EDITING = False
def __init__(self, config: PlatformConfig):
super().__init__(config, Platform.SIGNAL)
@@ -192,15 +175,6 @@ class SignalAdapter(BasePlatformAdapter):
group_allowed_str = os.getenv("SIGNAL_GROUP_ALLOWED_USERS", "")
self.group_allow_from = set(_parse_comma_list(group_allowed_str))
# DM allowlist — mirrors SIGNAL_ALLOWED_USERS checked by run.py.
# Stored here so the reaction hooks can skip unauthorized senders
# (reactions fire before run.py's auth gate, so without this check
# every inbound DM from any contact gets a 👀 reaction).
# "*" means all users allowed (open mode); empty means no restriction
# recorded at adapter level (run.py still enforces auth separately).
dm_allowed_str = os.getenv("SIGNAL_ALLOWED_USERS", "*")
self.dm_allow_from = set(_parse_comma_list(dm_allowed_str))
# HTTP client
self.client: Optional[httpx.AsyncClient] = None
@@ -257,9 +231,7 @@ class SignalAdapter(BasePlatformAdapter):
except Exception as e:
logger.warning("Signal: Could not acquire phone lock (non-fatal): %s", e)
# Tighter keepalive so idle CLOSE_WAIT drains promptly (#18451).
from gateway.platforms._http_client_limits import platform_httpx_limits
self.client = httpx.AsyncClient(timeout=30.0, limits=platform_httpx_limits())
self.client = httpx.AsyncClient(timeout=30.0)
try:
# Health check — verify signal-cli daemon is reachable
try:
@@ -516,11 +488,6 @@ class SignalAdapter(BasePlatformAdapter):
if text and mentions:
text = _render_mentions(text, mentions)
# Extract quote (reply-to) context from Signal dataMessage
quote_data = data_message.get("quote") or {}
reply_to_id = str(quote_data.get("id")) if quote_data.get("id") else None
reply_to_text = quote_data.get("text")
# Process attachments
attachments_data = data_message.get("attachments", [])
media_urls = []
@@ -545,18 +512,6 @@ class SignalAdapter(BasePlatformAdapter):
except Exception:
logger.exception("Signal: failed to fetch attachment %s", att_id)
# Skip envelopes with no meaningful content (no text, no attachments).
# Catches profile key updates, empty messages, and other metadata-only
# envelopes that still carry a dataMessage wrapper but have nothing
# worth processing. See issue: signal-cli logs "Profile key update" +
# Hermes receives msg='' triggering a full agent turn for nothing.
if (not text or not text.strip()) and not media_urls:
logger.debug(
"Signal: skipping contentless envelope from %s (%d attachments)",
redact_phone(sender), len(media_urls) if media_urls else 0,
)
return
# Build session source
source = self.build_source(
chat_id=chat_id,
@@ -586,9 +541,7 @@ class SignalAdapter(BasePlatformAdapter):
else:
timestamp = datetime.now(tz=timezone.utc)
# Build and dispatch event.
# Store raw envelope data in raw_message so on_processing_start/complete
# can extract targetAuthor + targetTimestamp for sendReaction.
# Build and dispatch event
event = MessageEvent(
source=source,
text=text or "",
@@ -596,9 +549,6 @@ class SignalAdapter(BasePlatformAdapter):
media_urls=media_urls,
media_types=media_types,
timestamp=timestamp,
raw_message={"sender": sender, "timestamp_ms": ts_ms},
reply_to_message_id=reply_to_id,
reply_to_text=reply_to_text,
)
logger.debug("Signal: message from %s in %s: %s",
@@ -709,8 +659,6 @@ class SignalAdapter(BasePlatformAdapter):
rpc_id: str = None,
*,
log_failures: bool = True,
raise_on_rate_limit: bool = False,
timeout: float = 30.0,
) -> Any:
"""Send a JSON-RPC 2.0 request to signal-cli daemon.
@@ -719,11 +667,6 @@ class SignalAdapter(BasePlatformAdapter):
repeated NETWORK_FAILURE spam for unreachable recipients while
still preserving visibility for the first occurrence and for
unrelated RPCs.
When ``raise_on_rate_limit=True``, a Signal ``[429]`` /
``RateLimitException`` response raises ``SignalRateLimitError``
instead of being swallowed lets callers (multi-attachment send)
opt into backoff-retry without changing default behaviour.
"""
if not self.client:
logger.warning("Signal: RPC called but client not connected")
@@ -743,28 +686,20 @@ class SignalAdapter(BasePlatformAdapter):
resp = await self.client.post(
f"{self.http_url}/api/v1/rpc",
json=payload,
timeout=timeout,
timeout=30.0,
)
resp.raise_for_status()
data = resp.json()
if "error" in data:
err = data["error"]
if raise_on_rate_limit:
if _is_signal_rate_limit_error(err):
err_msg = str(err.get("message", "")) if isinstance(err, dict) else str(err)
retry_after = _extract_retry_after_seconds(err)
raise SignalRateLimitError(err_msg, retry_after=retry_after)
if log_failures:
logger.warning("Signal RPC error (%s): %s", method, err)
logger.warning("Signal RPC error (%s): %s", method, data["error"])
else:
logger.debug("Signal RPC error (%s): %s", method, err)
logger.debug("Signal RPC error (%s): %s", method, data["error"])
return None
return data.get("result")
except SignalRateLimitError:
raise
except Exception as e:
if log_failures:
logger.warning("Signal RPC %s failed: %s", method, e)
@@ -772,159 +707,6 @@ class SignalAdapter(BasePlatformAdapter):
logger.debug("Signal RPC %s failed: %s", method, e)
return None
# ------------------------------------------------------------------
# Formatting — markdown → Signal body ranges
# ------------------------------------------------------------------
@staticmethod
def _markdown_to_signal(text: str) -> tuple:
"""Convert markdown to plain text + Signal textStyles list.
Signal doesn't render markdown. Instead it uses ``bodyRanges``
(exposed by signal-cli as ``textStyle`` / ``textStyles`` params)
with the format ``start:length:STYLE``.
Positions are measured in **UTF-16 code units** (not Python code
points) because that's what the Signal protocol uses.
Supported styles: BOLD, ITALIC, STRIKETHROUGH, MONOSPACE.
(Signal's SPOILER style is not currently mapped — no standard
markdown syntax for it; would need ``||spoiler||`` parsing.)
Returns ``(plain_text, styles_list)`` where *styles_list* may be
empty if there's nothing to format.
"""
import re
def _utf16_len(s: str) -> int:
"""Length of *s* in UTF-16 code units."""
return len(s.encode("utf-16-le")) // 2
# Pre-process: normalize whitespace before any position tracking
# so later operations don't invalidate recorded offsets.
text = re.sub(r"\n{3,}", "\n\n", text)
text = text.strip()
styles: list = []
# --- Phase 1: fenced code blocks ```...``` → MONOSPACE ---
_CB = re.compile(r"```[a-zA-Z0-9_+-]*\n?(.*?)```", re.DOTALL)
while m := _CB.search(text):
inner = m.group(1).rstrip("\n")
start = m.start()
text = text[: m.start()] + inner + text[m.end() :]
styles.append((start, len(inner), "MONOSPACE"))
# --- Phase 2: heading markers # Foo → Foo (BOLD) ---
_HEADING = re.compile(r"^#{1,6}\s+", re.MULTILINE)
new_text = ""
last_end = 0
for m in _HEADING.finditer(text):
new_text += text[last_end : m.start()]
last_end = m.end()
eol = text.find("\n", m.end())
if eol == -1:
eol = len(text)
heading_text = text[m.end() : eol]
start = len(new_text)
new_text += heading_text
styles.append((start, len(heading_text), "BOLD"))
last_end = eol
new_text += text[last_end:]
text = new_text
# --- Phase 3: inline patterns (single-pass to avoid offset drift) ---
# The old code processed each pattern sequentially, stripping markers
# and recording positions per-pass. Later passes shifted text without
# adjusting earlier positions → bold/italic landed mid-word.
#
# Fix: collect ALL non-overlapping matches first, then strip every
# marker in one pass so positions are computed against the final text.
_PATTERNS = [
(re.compile(r"\*\*(.+?)\*\*", re.DOTALL), "BOLD"),
(re.compile(r"__(.+?)__", re.DOTALL), "BOLD"),
(re.compile(r"~~(.+?)~~", re.DOTALL), "STRIKETHROUGH"),
(re.compile(r"`(.+?)`"), "MONOSPACE"),
(re.compile(r"(?<!\*)\*(?!\*| )(.+?)(?<!\*)\*(?!\*)"), "ITALIC"),
(re.compile(r"(?<!\w)_(?!_)(.+?)(?<!_)_(?!\w)"), "ITALIC"),
]
# Collect all non-overlapping matches (earlier patterns win ties).
all_matches: list = [] # (start, end, g1_start, g1_end, style)
occupied: list = [] # (start, end) intervals already claimed
for pat, style in _PATTERNS:
for m in pat.finditer(text):
ms, me = m.start(), m.end()
if not any(ms < oe and me > os for os, oe in occupied):
all_matches.append((ms, me, m.start(1), m.end(1), style))
occupied.append((ms, me))
all_matches.sort()
# Build removal list so we can adjust Phase 1/2 styles.
# Each match removes its prefix markers (start..g1_start) and
# suffix markers (g1_end..end).
removals: list = [] # (position, length) sorted
for ms, me, g1s, g1e, _ in all_matches:
if g1s > ms:
removals.append((ms, g1s - ms))
if me > g1e:
removals.append((g1e, me - g1e))
removals.sort()
# Adjust Phase 1/2 styles for characters about to be removed.
def _adj(pos: int) -> int:
shift = 0
for rp, rl in removals:
if rp < pos:
shift += min(rl, pos - rp)
else:
break
return pos - shift
adjusted_prior: list = []
for s, l, st in styles:
ns = _adj(s)
ne = _adj(s + l)
if ne > ns:
adjusted_prior.append((ns, ne - ns, st))
# Strip all inline markers in one pass → positions are correct.
result = ""
last_end = 0
inline_styles: list = []
for ms, me, g1s, g1e, sty in all_matches:
result += text[last_end:ms]
pos = len(result)
inner = text[g1s:g1e]
result += inner
inline_styles.append((pos, len(inner), sty))
last_end = me
result += text[last_end:]
text = result
styles = adjusted_prior + inline_styles
# Convert code-point offsets → UTF-16 code-unit offsets
style_strings = []
for cp_start, cp_len, stype in sorted(styles):
# Safety: skip any out-of-bounds styles
if cp_start < 0 or cp_start + cp_len > len(text):
continue
u16_start = _utf16_len(text[:cp_start])
u16_len = _utf16_len(text[cp_start : cp_start + cp_len])
style_strings.append(f"{u16_start}:{u16_len}:{stype}")
return text, style_strings
def format_message(self, content: str) -> str:
"""Strip markdown for plain-text fallback (used by base class).
The actual rich formatting happens in send() via _markdown_to_signal().
"""
# This is only called if someone uses the base-class send path.
# Our send() override bypasses this entirely.
return content
# ------------------------------------------------------------------
# Sending
# ------------------------------------------------------------------
@@ -936,22 +718,14 @@ class SignalAdapter(BasePlatformAdapter):
reply_to: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
) -> SendResult:
"""Send a text message with native Signal formatting."""
"""Send a text message."""
await self._stop_typing_indicator(chat_id)
plain_text, text_styles = self._markdown_to_signal(content)
params: Dict[str, Any] = {
"account": self.account,
"message": plain_text,
"message": content,
}
if text_styles:
if len(text_styles) == 1:
params["textStyle"] = text_styles[0]
else:
params["textStyles"] = text_styles
if chat_id.startswith("group:"):
params["groupId"] = chat_id[6:]
else:
@@ -961,10 +735,11 @@ class SignalAdapter(BasePlatformAdapter):
if result is not None:
self._track_sent_timestamp(result)
# Signal has no editable message identifier. Returning None keeps the
# stream consumer on the non-edit fallback path instead of pretending
# future edits can remove an in-progress cursor from the chat thread.
return SendResult(success=True, message_id=None)
# Use the timestamp from the RPC result as a pseudo message_id.
# Signal doesn't have real message IDs, but the stream consumer
# needs a truthy value to follow its edit→fallback path correctly.
_msg_id = str(result.get("timestamp", "")) if isinstance(result, dict) else None
return SendResult(success=True, message_id=_msg_id or None)
return SendResult(success=False, error="RPC send failed")
def _track_sent_timestamp(self, rpc_result) -> None:
@@ -1028,178 +803,6 @@ class SignalAdapter(BasePlatformAdapter):
self._typing_failures.pop(chat_id, None)
self._typing_skip_until.pop(chat_id, None)
async def send_multiple_images(
self,
chat_id: str,
images: List[Tuple[str, str]],
metadata: Optional[Dict[str, Any]] = None,
human_delay: float = 0.0,
) -> None:
"""Send a batch of images via chunked Signal RPC calls.
Per-image alt texts are dropped Signal's send RPC only carries
one shared message body. Bad images (download failure, missing
file, oversize) are skipped with a warning so one bad URL
doesn't lose the rest of the batch. ``human_delay`` is ignored:
the rate-limit scheduler handles inter-batch pacing.
"""
if not images:
return
scheduler = get_scheduler()
logger.info(
"Signal send_multiple_images: received %d image(s) for %s"
"scheduler state: %s",
len(images), chat_id[:30], scheduler.state(),
)
await self._stop_typing_indicator(chat_id)
attachments: List[str] = []
skipped_download = 0
skipped_missing = 0
skipped_oversize = 0
for image_url, _alt_text in images:
if image_url.startswith("file://"):
file_path = unquote(image_url[7:])
else:
try:
file_path = await cache_image_from_url(image_url)
except Exception as e:
logger.warning("Signal: failed to download image %s: %s", image_url, e)
skipped_download += 1
continue
if not file_path or not Path(file_path).exists():
logger.warning("Signal: image file not found for %s", image_url)
skipped_missing += 1
continue
file_size = Path(file_path).stat().st_size
if file_size > SIGNAL_MAX_ATTACHMENT_SIZE:
logger.warning(
"Signal: image too large (%d bytes), skipping %s", file_size, image_url
)
skipped_oversize += 1
continue
attachments.append(file_path)
if not attachments:
logger.error(
"Signal: no valid images in batch of %d "
"(download=%d missing=%d oversize=%d)",
len(images), skipped_download, skipped_missing, skipped_oversize,
)
return
logger.info(
"Signal send_multiple_images: %d/%d images valid, sending in chunks",
len(attachments), len(images),
)
base_params: Dict[str, Any] = {
"account": self.account,
"message": "",
}
if chat_id.startswith("group:"):
base_params["groupId"] = chat_id[6:]
else:
base_params["recipient"] = [await self._resolve_recipient(chat_id)]
att_batches = [
attachments[i:i + SIGNAL_MAX_ATTACHMENTS_PER_MSG]
for i in range(0, len(attachments), SIGNAL_MAX_ATTACHMENTS_PER_MSG)
]
for idx, att_batch in enumerate(att_batches):
n = len(att_batch)
estimated = scheduler.estimate_wait(n)
logger.debug(
"Signal batch %d/%d: %d attachments, estimated wait=%.1fs",
idx + 1, len(att_batches), n, estimated,
)
if estimated >= SIGNAL_BATCH_PACING_NOTICE_THRESHOLD:
await self._notify_batch_pacing(
chat_id, idx + 1, len(att_batches), estimated
)
params = dict(base_params, attachments=att_batch)
send_timeout = _signal_send_timeout(n)
for attempt in range(1, SIGNAL_RATE_LIMIT_MAX_ATTEMPTS + 1):
await scheduler.acquire(n)
try:
_rpc_t0 = time.monotonic()
result = await self._rpc(
"send", params, raise_on_rate_limit=True, timeout=send_timeout,
)
_rpc_duration = time.monotonic() - _rpc_t0
if result is not None:
self._track_sent_timestamp(result)
await scheduler.report_rpc_duration(_rpc_duration, n)
logger.info(
"Signal batch %d/%d: %d attachments sent in %.1fs "
"(attempt %d/%d)",
idx + 1, len(att_batches), n, _rpc_duration,
attempt, SIGNAL_RATE_LIMIT_MAX_ATTEMPTS,
)
else:
# Assume the server didn't accept the batch, don't deduce tokens
logger.error(
"Signal: RPC send failed for batch %d/%d (%d attachments, "
"attempt %d/%d, rpc_duration=%.1fs)",
idx + 1, len(att_batches), n,
attempt, SIGNAL_RATE_LIMIT_MAX_ATTEMPTS,
_rpc_duration,
)
# Retry transient (non-rate-limit) failures once
if attempt < SIGNAL_RATE_LIMIT_MAX_ATTEMPTS:
backoff = 2.0 ** attempt
logger.info(
"Signal: retrying batch %d/%d after %.1fs backoff",
idx + 1, len(att_batches), backoff,
)
await asyncio.sleep(backoff)
continue
break
except SignalRateLimitError as e:
scheduler.feedback(e.retry_after, n)
if attempt >= SIGNAL_RATE_LIMIT_MAX_ATTEMPTS:
logger.error(
"Signal: rate-limit retries exhausted on batch %d/%d "
"(%d attachments lost, server retry_after=%s)",
idx + 1, len(att_batches), n,
f"{e.retry_after:.0f}s" if e.retry_after else "unknown",
)
break
logger.warning(
"Signal: rate-limited on batch %d/%d "
"(attempt %d/%d, server retry_after=%s); "
"scheduler will pace the retry",
idx + 1, len(att_batches),
attempt, SIGNAL_RATE_LIMIT_MAX_ATTEMPTS,
f"{e.retry_after:.0f}s" if e.retry_after else "unknown",
)
async def _notify_batch_pacing(
self,
chat_id: str,
next_batch_idx: int,
total_batches: int,
wait_s: float,
) -> None:
"""Inform the user when an inter-batch pacing wait crosses the
notice threshold. Best-effort; logs and continues on failure."""
try:
await self.send(
chat_id,
f"(More images coming — pausing ~{_format_wait(wait_s)} "
f"for Signal rate limit, batch {next_batch_idx}/{total_batches}.)",
)
except Exception as e:
logger.warning("Signal: failed to send pacing notice: %s", e)
async def send_image(
self,
chat_id: str,
@@ -1360,132 +963,6 @@ class SignalAdapter(BasePlatformAdapter):
_keep_typing finally block to clean up platform-level typing tasks."""
await self._stop_typing_indicator(chat_id)
# ------------------------------------------------------------------
# Reactions
# ------------------------------------------------------------------
async def send_reaction(
self,
chat_id: str,
emoji: str,
target_author: str,
target_timestamp: int,
) -> bool:
"""Send a reaction emoji to a specific message via signal-cli RPC.
Args:
chat_id: The chat (phone number or "group:<id>")
emoji: Reaction emoji string (e.g. "👀", "")
target_author: Phone number / UUID of the message author
target_timestamp: Signal timestamp (ms) of the message to react to
"""
params: Dict[str, Any] = {
"account": self.account,
"emoji": emoji,
"targetAuthor": target_author,
"targetTimestamp": target_timestamp,
}
if chat_id.startswith("group:"):
params["groupId"] = chat_id[6:]
else:
params["recipient"] = [chat_id]
result = await self._rpc("sendReaction", params)
if result is not None:
return True
logger.debug("Signal: sendReaction failed (chat=%s, emoji=%s)", chat_id[:20], emoji)
return False
async def remove_reaction(
self,
chat_id: str,
target_author: str,
target_timestamp: int,
) -> bool:
"""Remove a reaction by sending an empty-string emoji."""
params: Dict[str, Any] = {
"account": self.account,
"emoji": "",
"targetAuthor": target_author,
"targetTimestamp": target_timestamp,
"remove": True,
}
if chat_id.startswith("group:"):
params["groupId"] = chat_id[6:]
else:
params["recipient"] = [chat_id]
result = await self._rpc("sendReaction", params)
return result is not None
# ------------------------------------------------------------------
# Processing Lifecycle Hooks (reactions as progress indicators)
# ------------------------------------------------------------------
def _extract_reaction_target(self, event: MessageEvent) -> Optional[tuple]:
"""Extract (target_author, target_timestamp) from a MessageEvent.
Returns None if the event doesn't carry the raw Signal envelope data
needed for sendReaction.
"""
raw = event.raw_message
if not isinstance(raw, dict):
return None
author = raw.get("sender")
ts = raw.get("timestamp_ms")
if not author or not ts:
return None
return (author, ts)
def _reactions_enabled(self, event: "MessageEvent" = None) -> bool:
"""Check if message reactions are enabled for this event.
Two gates:
1. SIGNAL_REACTIONS env var set to false/0/no to disable globally.
2. DM allowlist if SIGNAL_ALLOWED_USERS is set, only react to
messages from senders in that list. This prevents unauthorized
contacts from seeing the 👀 reaction (which fires before run.py's
auth gate and would otherwise reveal that a bot is listening).
"""
if os.getenv("SIGNAL_REACTIONS", "true").lower() in ("false", "0", "no"):
return False
if event is not None:
sender = getattr(getattr(event, "source", None), "user_id", None)
if sender and "*" not in self.dm_allow_from and sender not in self.dm_allow_from:
return False
return True
async def on_processing_start(self, event: MessageEvent) -> None:
"""React with 👀 when processing begins."""
if not self._reactions_enabled(event):
return
target = self._extract_reaction_target(event)
if target:
await self.send_reaction(event.source.chat_id, "👀", *target)
async def on_processing_complete(self, event: MessageEvent, outcome: "ProcessingOutcome") -> None:
"""Swap the 👀 reaction for ✅ (success) or ❌ (failure).
On CANCELLED we leave the 👀 in place no terminal outcome means
the reaction should keep reflecting "in progress" (matches Telegram).
"""
if not self._reactions_enabled(event):
return
if outcome == ProcessingOutcome.CANCELLED:
return
target = self._extract_reaction_target(event)
if not target:
return
chat_id = event.source.chat_id
# Remove the in-progress reaction, then add the final one
await self.remove_reaction(chat_id, *target)
if outcome == ProcessingOutcome.SUCCESS:
await self.send_reaction(chat_id, "", *target)
elif outcome == ProcessingOutcome.FAILURE:
await self.send_reaction(chat_id, "", *target)
# ------------------------------------------------------------------
# Chat Info
# ------------------------------------------------------------------

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