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Teknium 1e6285c53d feat: compression eval harness for agent/context_compressor.py
Ships a complete offline eval harness at scripts/compression_eval/. Runs
a real conversation fixture through ContextCompressor.compress(), asks
the compressor model to answer probe questions from the compressed
state, then has a judge model score each answer 0-5 on six dimensions
(accuracy, context_awareness, artifact_trail, completeness, continuity,
instruction_following). Methodology adapted from Factory's Dec 2025
write-up (https://factory.ai/news/evaluating-compression); the
scoreboard framing is not adopted.

Motivation: we edit context_compressor.py prompts and _template_sections
by hand and ship with no automated check that compression still
preserves file paths, error codes, or the active task. Until now there
has been no signal between 'test suite green' and 'a user hits a bad
summary in production.'

What's shipped
- DESIGN.md — full architecture, fixture/probe format, scrubber
  pipeline, grading rubric, open follow-ups
- README.md — usage, cost expectations, when to run it
- scrub_fixtures.py — reproducible pipeline that converts real sessions
  from ~/.hermes/sessions/*.jsonl into public-safe JSON fixtures. Applies
  agent.redact.redact_sensitive_text + username path normalisation +
  personal handle scrubbing + email/git-author normalisation + reasoning
  scratchpad stripping + platform-mention scrubbing + first-user
  paraphrase + system-prompt placeholder + orphan-message pruning + 2KB
  tool-output truncation
- fixtures/ — three scrubbed session snapshots covering three session
  shapes:
    feature-impl-context-priority  (75 msgs / ~17k tokens)
    debug-session-feishu-id-model  (59 msgs / ~13k tokens)
    config-build-competitive-scouts (61 msgs / ~23k tokens)
- probes/ — three probe banks (10-11 probes each) covering all four
  types (recall/artifact/continuation/decision) with expected_facts
  anchors (PR numbers, file paths, error codes, commands)
- rubric.py — six-dimension grading rubric, judge-prompt builder,
  JSON-with-fallback response parser
- compressor_driver.py — thin wrapper around ContextCompressor for
  forced single-shot compression (fixtures are below the default
  100k threshold so we force compress() to attribute score deltas
  to prompt changes, not threshold-fire variance)
- grader.py — two-phase continuation + grading calls via the OpenAI
  SDK directly against the resolved provider endpoint
- report.py — markdown report renderer (paste-ready for PR bodies),
  --compare-to delta mode, per-run JSON dumper
- run_eval.py — fire-style CLI (--fixtures, --runs, --judge-model,
  --compressor-model, --label, --focus-topic, --compare-to, --verbose)
- tests/scripts/test_compression_eval.py — 33 hermetic unit tests
  covering rubric parsing edge cases, judge-prompt building, report
  rendering, summariser medians, per-run JSON roundtrip, fixture and
  probe loading, and a PII smoke check on the checked-in fixtures

Non-LLM paths are covered by the 33-test suite that runs in CI. The
LLM paths (continuation + grading) require credentials and real API
calls, so they're exercised by running the eval itself — not by CI.

Validation
- 33/33 unit tests pass in 0.33s via scripts/run_tests.sh
- 50/50 adjacent tests (tests/agent/test_context_compressor.py) still
  pass — no regression introduced
- End-to-end dry run against debug-session-feishu-id-model with
  openai/gpt-5.4-mini via Nous Portal:
    Compression: 13081 -> 3055 tokens (76.6% ratio), 59 -> 10 messages
    Overall score: 3.25 (artifact_trail 1.50 is the weak spot,
    matching Factory's published observation)
    Specific probe misses surfaced with concrete judge notes

Noise floor (one empirical data point)
Same inputs re-run: overall 3.25 -> 3.17 (delta -0.08). Individual
dimensions varied up to ±0.5 between two single-run medians. Confirms
the DESIGN.md < 0.3 noise guidance is the right order of magnitude
for single-run comparisons. Tighter noise measurement (N=10) is
tracked as an open follow-up in DESIGN.md.

Why scripts/ and not tests/
Requires API credentials, costs ~$0.50-1.50 per run, minutes to
execute, LLM-graded (non-deterministic). Incompatible with
scripts/run_tests.sh which is hermetic, parallel, credential-free.
scripts/sample_and_compress.py is the existing precedent for offline
credentialed tooling.

Open follow-ups (tracked in DESIGN.md, not blocking this PR)
1. Iterative-merge fixture (two chained compressions on one session)
2. Precise noise-floor measurement at N=10
3. Scripted scrubber helpers to lower the cost of fixture #4+
4. Judge model selection policy (pin vs. per-user)
2026-04-25 06:17:44 -07:00
911 changed files with 15223 additions and 117101 deletions
-2
View File
@@ -5,9 +5,7 @@
# Dependencies
node_modules
**/node_modules
.venv
**/.venv
# CI/CD
.github
+1 -7
View File
@@ -13,7 +13,7 @@ concurrency:
cancel-in-progress: true
jobs:
nix-lockfile-check:
check:
runs-on: ubuntu-latest
timeout-minutes: 20
steps:
@@ -36,12 +36,6 @@ jobs:
LINK_SHA: ${{ steps.sha.outputs.full }}
run: nix run .#fix-lockfiles -- --check
- name: Fail if check crashed without reporting
if: steps.check.outputs.stale != 'true' && steps.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)
if: steps.check.outputs.stale == 'true' && github.event_name == 'pull_request'
uses: marocchino/sticky-pull-request-comment@52423e01640425a022ef5fd42c6fb5f633a02728 # v2.9.1
+2 -103
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:
@@ -26,103 +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 --apply 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: ${{ steps.app-token.outputs.token }}
- uses: ./.github/actions/nix-setup
- name: Apply lockfile hashes
id: apply
run: nix run .#fix-lockfiles -- --apply
- name: Commit & push
if: steps.apply.outputs.changed == 'true'
shell: bash
run: |
set -euo pipefail
# Ensure only nix files were modified — prevents accidental
# self-triggering if fix-lockfiles ever touches package files.
unexpected="$(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'
+4 -1
View File
@@ -52,6 +52,10 @@ ignored/
.worktrees/
environments/benchmarks/evals/
# Compression eval run outputs (harness lives in scripts/compression_eval/)
scripts/compression_eval/results/*
!scripts/compression_eval/results/.gitkeep
# Web UI build output
hermes_cli/web_dist/
@@ -69,4 +73,3 @@ mini-swe-agent/
.nix-stamps/
result
website/static/api/skills-index.json
models-dev-upstream/
+1 -14
View File
@@ -38,7 +38,7 @@ hermes-agent/
│ │ # 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)
│ └── builtin_hooks/ # Always-registered gateway hooks (boot-md, ...)
├── plugins/ # Plugin system (see "Plugins" section below)
│ ├── memory/ # Memory-provider plugins (honcho, mem0, supermemory, ...)
│ ├── context_engine/ # Context-engine plugins
@@ -240,19 +240,6 @@ 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
+1 -1
View File
@@ -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
```
+3 -13
View File
@@ -14,7 +14,7 @@ ENV PLAYWRIGHT_BROWSERS_PATH=/opt/hermes/.playwright
# 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 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 openssh-client docker-cli tini && \
rm -rf /var/lib/apt/lists/*
# Non-root user for runtime; UID can be overridden via HERMES_UID at runtime
@@ -30,28 +30,18 @@ WORKDIR /opt/hermes
# unless the lockfiles themselves change.
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/package.json ui-tui/packages/hermes-ink/package-lock.json ui-tui/packages/hermes-ink/
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 && \
rm -rf node_modules/@hermes/ink && \
rm -rf packages/hermes-ink/node_modules && \
cp -R packages/hermes-ink node_modules/@hermes/ink && \
npm install --omit=dev --prefer-offline --no-audit --prefix node_modules/@hermes/ink && \
rm -rf node_modules/@hermes/ink/node_modules/react && \
node --input-type=module -e "await import('@hermes/ink')"
# Build web dashboard (Vite outputs to hermes_cli/web_dist/)
RUN cd web && npm run build
# ---------- Permissions ----------
# Make install dir world-readable so any HERMES_UID can read it at runtime.
-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))
+1 -28
View File
@@ -3,7 +3,6 @@
from __future__ import annotations
import asyncio
import contextvars
import logging
import os
from collections import defaultdict, deque
@@ -575,22 +574,6 @@ 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
@@ -624,19 +607,9 @@ 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)
return PromptResponse(stop_reason="end_turn")
+30 -240
View File
@@ -20,27 +20,12 @@ from pathlib import Path
from hermes_constants import get_hermes_home
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__)
@@ -217,33 +202,19 @@ 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).
@@ -365,88 +336,6 @@ def _is_kimi_coding_endpoint(base_url: str | None) -> bool:
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.
@@ -468,14 +357,9 @@ def _common_betas_for_base_url(base_url: str | None) -> list[str]:
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.
"""
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]
return [b for b in _COMMON_BETAS if b != _TOOL_STREAMING_BETA]
return _COMMON_BETAS
@@ -490,7 +374,6 @@ def build_anthropic_client(api_key: str, base_url: str = None, timeout: float =
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. "
@@ -507,16 +390,7 @@ def build_anthropic_client(api_key: str, base_url: str = None, timeout: float =
"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
kwargs["base_url"] = normalized_base_url
common_betas = _common_betas_for_base_url(normalized_base_url)
if _is_kimi_coding_endpoint(base_url):
@@ -573,16 +447,8 @@ 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. "
@@ -598,7 +464,6 @@ 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)},
)
@@ -614,6 +479,9 @@ def _read_claude_code_credentials_from_keychain() -> Optional[Dict[str, Any]]:
Returns dict with {accessToken, refreshToken?, expiresAt?} or None.
"""
import platform
import subprocess
if platform.system() != "Darwin":
return None
@@ -1118,26 +986,6 @@ 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.
@@ -1145,25 +993,14 @@ 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
@@ -1180,33 +1017,6 @@ 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:
@@ -1217,9 +1027,7 @@ def convert_tools_to_anthropic(tools: List[Dict]) -> List[Dict]:
result.append({
"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
@@ -1350,7 +1158,6 @@ 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.
@@ -1362,12 +1169,6 @@ 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 = []
@@ -1596,16 +1397,7 @@ 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)
)
_is_kimi = _is_kimi_coding_endpoint(base_url)
last_assistant_idx = None
for i in range(len(result) - 1, -1, -1):
@@ -1617,22 +1409,22 @@ 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.
if _is_kimi:
# Kimi's /coding endpoint enables thinking server-side and
# requires unsigned thinking blocks on replayed assistant
# tool-call messages. Strip signed Anthropic blocks (Kimi
# can't validate signatures) but preserve the unsigned ones
# we synthesised from reasoning_content above.
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
# Anthropic-signed block — Kimi can't validate, strip
continue
# Unsigned thinking (synthesised from reasoning_content) —
# keep it: the upstream needs it for message-history validation.
# keep it: Kimi 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:
@@ -1728,9 +1520,7 @@ 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)
@@ -1836,7 +1626,7 @@ def build_anthropic_kwargs(
# 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)
_is_kimi_coding = _is_kimi_coding_endpoint(base_url)
if reasoning_config and isinstance(reasoning_config, dict) and not _is_kimi_coding:
if reasoning_config.get("enabled") is not False and "haiku" not in model.lower():
effort = str(reasoning_config.get("effort", "medium")).lower()
@@ -1862,9 +1652,9 @@ 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)
+62 -538
View File
@@ -41,57 +41,9 @@ import threading
import time
from pathlib import Path # noqa: F401 — used by test mocks
from types import SimpleNamespace
from typing import Any, Dict, List, Optional, Tuple, TYPE_CHECKING
from urllib.parse import urlparse, parse_qs, urlunparse
from typing import Any, Dict, List, Optional, Tuple
# NOTE: `from openai import OpenAI` is deliberately NOT at module top — the
# openai SDK pulls a large type tree (~240 ms cold, including responses/*,
# graders/*). We expose `OpenAI` here as a thin proxy that imports the SDK on
# first call and forwards, so:
# (a) the 15+ in-module `OpenAI(...)` construction sites work unchanged
# (Python's function-scope name lookup resolves `OpenAI` to the proxy
# object bound in module globals here, without triggering any import);
# (b) external code can still do `auxiliary_client.OpenAI` or
# `patch("agent.auxiliary_client.OpenAI", ...)` — tests see the proxy,
# and patch replaces the module attribute as usual;
# (c) `OpenAI` as a type annotation resolves at runtime to the proxy class
# (which is harmless — annotations aren't type-checked at runtime).
# See tests/agent/test_auxiliary_client.py for patch patterns this supports.
if TYPE_CHECKING:
from openai import OpenAI # noqa: F401 — type hints only
_OPENAI_CLS_CACHE: Optional[type] = None
def _load_openai_cls() -> type:
"""Import and cache ``openai.OpenAI``."""
global _OPENAI_CLS_CACHE
if _OPENAI_CLS_CACHE is None:
from openai import OpenAI as _cls
_OPENAI_CLS_CACHE = _cls
return _OPENAI_CLS_CACHE
class _OpenAIProxy:
"""Module-level proxy that looks like the ``openai.OpenAI`` class.
Forwards ``OpenAI(...)`` calls and ``isinstance(x, OpenAI)`` checks to the
real SDK class, importing the SDK lazily on first use.
"""
__slots__ = ()
def __call__(self, *args, **kwargs):
return _load_openai_cls()(*args, **kwargs)
def __instancecheck__(self, obj):
return isinstance(obj, _load_openai_cls())
def __repr__(self):
return "<lazy openai.OpenAI proxy>"
OpenAI = _OpenAIProxy() # module-level name, resolves lazily on call/isinstance
from openai import OpenAI
from agent.credential_pool import load_pool
from hermes_cli.config import get_hermes_home
@@ -100,25 +52,6 @@ from utils import base_url_host_matches, base_url_hostname, normalize_proxy_env_
logger = logging.getLogger(__name__)
def _safe_isinstance(obj: Any, maybe_type: Any) -> bool:
"""Return False instead of raising when a patched symbol is not a type."""
try:
return isinstance(obj, maybe_type)
except TypeError:
return False
def _extract_url_query_params(url: str):
"""Extract query params from URL, return (clean_url, default_query dict or None)."""
parsed = urlparse(url)
if parsed.query:
clean = urlunparse(parsed._replace(query=""))
params = {k: v[0] for k, v in parse_qs(parsed.query).items()}
return clean, params
return url, None
# Module-level flag: only warn once per process about stale OPENAI_BASE_URL.
_stale_base_url_warned = False
@@ -137,8 +70,6 @@ _PROVIDER_ALIASES = {
"moonshot": "kimi-coding",
"kimi-cn": "kimi-coding-cn",
"moonshot-cn": "kimi-coding-cn",
"gmi-cloud": "gmi",
"gmicloud": "gmi",
"minimax-china": "minimax-cn",
"minimax_cn": "minimax-cn",
"claude": "anthropic",
@@ -149,10 +80,6 @@ _PROVIDER_ALIASES = {
"github-models": "copilot",
"github-copilot-acp": "copilot-acp",
"copilot-acp-agent": "copilot-acp",
"tencent": "tencent-tokenhub",
"tokenhub": "tencent-tokenhub",
"tencent-cloud": "tencent-tokenhub",
"tencentmaas": "tencent-tokenhub",
}
@@ -216,9 +143,7 @@ _API_KEY_PROVIDER_AUX_MODELS: Dict[str, str] = {
"kimi-coding": "kimi-k2-turbo-preview",
"stepfun": "step-3.5-flash",
"kimi-coding-cn": "kimi-k2-turbo-preview",
"gmi": "google/gemini-3.1-flash-lite-preview",
"minimax": "MiniMax-M2.7",
"minimax-oauth": "MiniMax-M2.7-highspeed",
"minimax-cn": "MiniMax-M2.7",
"anthropic": "claude-haiku-4-5-20251001",
"ai-gateway": "google/gemini-3-flash",
@@ -226,7 +151,6 @@ _API_KEY_PROVIDER_AUX_MODELS: Dict[str, str] = {
"opencode-go": "glm-5",
"kilocode": "google/gemini-3-flash-preview",
"ollama-cloud": "nemotron-3-nano:30b",
"tencent-tokenhub": "hy3-preview",
}
# Vision-specific model overrides for direct providers.
@@ -238,21 +162,6 @@ _PROVIDER_VISION_MODELS: Dict[str, str] = {
"zai": "glm-5v-turbo",
}
# Providers whose endpoint does not accept image input, even though the
# provider's broader ecosystem has vision models available elsewhere. When
# `auxiliary.vision.provider: auto` sees one of these as the main provider,
# it must skip straight to the aggregator chain instead of returning a client
# that will 404 on every vision request.
#
# kimi-coding / kimi-coding-cn: the Kimi Coding Plan routes through
# api.kimi.com/coding (Anthropic Messages wire) which Kimi's own docs
# describe as having no image_in capability. Vision lives on the separate
# Kimi Platform (api.moonshot.ai, OpenAI-wire, pay-as-you-go). See #17076.
_PROVIDERS_WITHOUT_VISION: frozenset = frozenset({
"kimi-coding",
"kimi-coding-cn",
})
# OpenRouter app attribution headers
_OR_HEADERS = {
"HTTP-Referer": "https://hermes-agent.nousresearch.com",
@@ -481,34 +390,7 @@ class _CodexCompletionsAdapter:
# Note: the Codex endpoint (chatgpt.com/backend-api/codex) does NOT
# support max_output_tokens or temperature — omit to avoid 400 errors.
# Translate extra_body.reasoning (chat.completions shape) into the
# Responses API's top-level reasoning + include fields. Mirrors
# agent/transports/codex.py::build_kwargs() so auxiliary callers
# that configure reasoning via auxiliary.<task>.extra_body get the
# same behavior as the main agent's Codex transport.
extra_body = kwargs.get("extra_body") or {}
if isinstance(extra_body, dict):
reasoning_cfg = extra_body.get("reasoning")
if isinstance(reasoning_cfg, dict):
if reasoning_cfg.get("enabled") is False:
# Reasoning explicitly disabled — do not set reasoning
# or include. The Codex backend still thinks by
# default, but we honor the caller's intent where the
# API allows it.
pass
else:
effort = reasoning_cfg.get("effort", "medium")
# Codex backend rejects "minimal"; clamp to "low" to
# match the main-agent Codex transport behavior.
if effort == "minimal":
effort = "low"
resp_kwargs["reasoning"] = {
"effort": effort,
"summary": "auto",
}
resp_kwargs["include"] = ["reasoning.encrypted_content"]
# Tools support for auxiliary callers (e.g. skills_hub) that pass function schemas
# Tools support for flush_memories and similar callers
tools = kwargs.get("tools")
if tools:
converted = []
@@ -817,116 +699,6 @@ class AsyncAnthropicAuxiliaryClient:
self.base_url = sync_wrapper.base_url
def _endpoint_speaks_anthropic_messages(base_url: str) -> bool:
"""True if the endpoint at ``base_url`` speaks the Anthropic Messages
protocol instead of OpenAI chat.completions.
Mirrors ``hermes_cli.runtime_provider._detect_api_mode_for_url`` so the
auxiliary client and the main agent stay in sync on transport selection.
Covers:
- Any URL ending in ``/anthropic`` (MiniMax, Zhipu GLM, LiteLLM proxies,
Anthropic-compatible gateways).
- ``api.kimi.com/coding`` (Kimi Coding Plan — the /coding route only
speaks Claude-Code's native Anthropic shape; ``chat.completions``
returns 404 on Anthropic-only model aliases like ``kimi-for-coding``).
- ``api.anthropic.com`` (native Anthropic).
"""
normalized = (base_url or "").strip().lower().rstrip("/")
if not normalized:
return False
if normalized.endswith("/anthropic"):
return True
hostname = base_url_hostname(normalized)
if hostname == "api.anthropic.com":
return True
if hostname == "api.kimi.com" and "/coding" in normalized:
return True
return False
def _maybe_wrap_anthropic(
client_obj: Any,
model: str,
api_key: str,
base_url: str,
api_mode: Optional[str] = None,
) -> Any:
"""Rewrap a plain OpenAI client in ``AnthropicAuxiliaryClient`` when
the endpoint actually speaks Anthropic Messages.
This is the single chokepoint for aux-client transport correction.
Runs at the end of every ``resolve_provider_client`` branch so that
api_key providers (Kimi Coding Plan), the ``custom`` endpoint, and
future /anthropic gateways all land on the right wire format
regardless of which branch built the client.
Returns ``client_obj`` unchanged when:
- It's already an Anthropic/Codex/Gemini/CopilotACP wrapper.
- The endpoint is an OpenAI-wire endpoint.
- ``api_mode`` is explicitly set to a non-Anthropic transport.
- The ``anthropic`` SDK is not installed (falls back to OpenAI wire).
"""
# Already wrapped — don't double-wrap.
if _safe_isinstance(client_obj, AnthropicAuxiliaryClient):
return client_obj
# Other specialized adapters we should never re-dispatch.
if _safe_isinstance(client_obj, CodexAuxiliaryClient):
return client_obj
try:
from agent.gemini_native_adapter import GeminiNativeClient
if _safe_isinstance(client_obj, GeminiNativeClient):
return client_obj
except ImportError:
pass
try:
from agent.copilot_acp_client import CopilotACPClient
if _safe_isinstance(client_obj, CopilotACPClient):
return client_obj
except ImportError:
pass
# Explicit non-anthropic api_mode wins over URL heuristics.
if api_mode and api_mode != "anthropic_messages":
return client_obj
should_wrap = (
api_mode == "anthropic_messages"
or _endpoint_speaks_anthropic_messages(base_url)
)
if not should_wrap:
return client_obj
try:
from agent.anthropic_adapter import build_anthropic_client
except ImportError:
logger.warning(
"Endpoint %s speaks Anthropic Messages but the anthropic SDK is "
"not installed — falling back to OpenAI-wire (will likely 404).",
base_url,
)
return client_obj
try:
real_client = build_anthropic_client(api_key, base_url)
except Exception as exc:
logger.warning(
"Failed to build Anthropic client for %s (%s) — falling back to "
"OpenAI-wire client.", base_url, exc,
)
return client_obj
logger.debug(
"Auxiliary transport: wrapping client in AnthropicAuxiliaryClient "
"(model=%s, base_url=%s, api_mode=%s)",
model, base_url[:60] if base_url else "", api_mode or "auto-detected",
)
return AnthropicAuxiliaryClient(
real_client, model, api_key, base_url, is_oauth=False,
)
def _read_nous_auth() -> Optional[dict]:
"""Read and validate ~/.hermes/auth.json for an active Nous provider.
@@ -1097,9 +869,7 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
from hermes_cli.models import copilot_default_headers
extra["default_headers"] = copilot_default_headers()
_client = OpenAI(api_key=api_key, base_url=base_url, **extra)
_client = _maybe_wrap_anthropic(_client, model, api_key, base_url)
return _client, model
return OpenAI(api_key=api_key, base_url=base_url, **extra), model
creds = resolve_api_key_provider_credentials(provider_id)
api_key = str(creds.get("api_key", "")).strip()
@@ -1125,9 +895,7 @@ def _resolve_api_key_provider() -> Tuple[Optional[OpenAI], Optional[str]]:
from hermes_cli.models import copilot_default_headers
extra["default_headers"] = copilot_default_headers()
_client = OpenAI(api_key=api_key, base_url=base_url, **extra)
_client = _maybe_wrap_anthropic(_client, model, api_key, base_url)
return _client, model
return OpenAI(api_key=api_key, base_url=base_url, **extra), model
return None, None
@@ -1389,10 +1157,8 @@ def _try_custom_endpoint() -> Tuple[Optional[Any], Optional[str]]:
return None, None
model = _read_main_model() or "gpt-4o-mini"
logger.debug("Auxiliary client: custom endpoint (%s, api_mode=%s)", model, custom_mode or "chat_completions")
_clean_base, _dq = _extract_url_query_params(custom_base)
_extra = {"default_query": _dq} if _dq else {}
if custom_mode == "codex_responses":
real_client = OpenAI(api_key=custom_key, base_url=_clean_base, **_extra)
real_client = OpenAI(api_key=custom_key, base_url=custom_base)
return CodexAuxiliaryClient(real_client, model), model
if custom_mode == "anthropic_messages":
# Third-party Anthropic-compatible gateway (MiniMax, Zhipu GLM,
@@ -1406,18 +1172,12 @@ def _try_custom_endpoint() -> Tuple[Optional[Any], Optional[str]]:
"Custom endpoint declares api_mode=anthropic_messages but the "
"anthropic SDK is not installed — falling back to OpenAI-wire."
)
return OpenAI(api_key=custom_key, base_url=_clean_base, **_extra), model
return OpenAI(api_key=custom_key, base_url=custom_base), model
return (
AnthropicAuxiliaryClient(real_client, model, custom_key, custom_base, is_oauth=False),
model,
)
# URL-based anthropic detection for custom endpoints that didn't set
# api_mode explicitly (e.g. kimi.com/coding reached via custom config).
_fallback_client = OpenAI(api_key=custom_key, base_url=_clean_base, **_extra)
_fallback_client = _maybe_wrap_anthropic(
_fallback_client, model, custom_key, custom_base, custom_mode,
)
return _fallback_client, model
return OpenAI(api_key=custom_key, base_url=custom_base), model
def _try_codex() -> Tuple[Optional[Any], Optional[str]]:
@@ -1589,49 +1349,6 @@ def _is_auth_error(exc: Exception) -> bool:
return "error code: 401" in err_lower or "authenticationerror" in type(exc).__name__.lower()
def _is_unsupported_parameter_error(exc: Exception, param: str) -> bool:
"""Detect provider 400s for an unsupported request parameter.
Different OpenAI-compatible endpoints phrase the same class of error a few
ways: ``Unsupported parameter: X``, ``unsupported_parameter`` with a
``param`` field, ``X is not supported``, ``unknown parameter: X``,
``unrecognized request argument: X``. We match on both the parameter
name and a generic "unsupported/unknown/unrecognized parameter" marker so
call sites can reactively retry without the offending key instead of
surfacing a noisy auxiliary failure.
Generalizes the temperature-specific detector that originally shipped
with PR #15621 so the same retry strategy can cover ``max_tokens``,
``seed``, ``top_p``, and any future quirk. Credit @nicholasrae (PR #15416)
for the generalization pattern.
"""
param_lower = (param or "").lower()
if not param_lower:
return False
err_lower = str(exc).lower()
if param_lower not in err_lower:
return False
return any(marker in err_lower for marker in (
"unsupported parameter",
"unsupported_parameter",
"not supported",
"does not support",
"unknown parameter",
"unrecognized request argument",
"unrecognized parameter",
"invalid parameter",
))
def _is_unsupported_temperature_error(exc: Exception) -> bool:
"""Back-compat wrapper: detect API errors where the model rejects ``temperature``.
Delegates to :func:`_is_unsupported_parameter_error`; kept as a separate
public symbol because existing tests and call sites import it by name.
"""
return _is_unsupported_parameter_error(exc, "temperature")
def _evict_cached_clients(provider: str) -> None:
"""Drop cached auxiliary clients for a provider so fresh creds are used."""
normalized = _normalize_aux_provider(provider)
@@ -1843,14 +1560,8 @@ def _resolve_auto(main_runtime: Optional[Dict[str, Any]] = None) -> Tuple[Option
# below — never look up auth env vars ad-hoc.
def _to_async_client(sync_client, model: str, is_vision: bool = False):
"""Convert a sync client to its async counterpart, preserving Codex routing.
When ``is_vision=True`` and the underlying base URL is Copilot, the
resulting async client carries the ``Copilot-Vision-Request: true``
header so the request is routed to Copilot's vision-capable
infrastructure (otherwise vision payloads silently time out).
"""
def _to_async_client(sync_client, model: str):
"""Convert a sync client to its async counterpart, preserving Codex routing."""
from openai import AsyncOpenAI
if isinstance(sync_client, CodexAuxiliaryClient):
@@ -1879,11 +1590,9 @@ def _to_async_client(sync_client, model: str, is_vision: bool = False):
if base_url_host_matches(sync_base_url, "openrouter.ai"):
async_kwargs["default_headers"] = dict(_OR_HEADERS)
elif base_url_host_matches(sync_base_url, "api.githubcopilot.com"):
from hermes_cli.copilot_auth import copilot_request_headers
from hermes_cli.models import copilot_default_headers
async_kwargs["default_headers"] = copilot_request_headers(
is_agent_turn=True, is_vision=is_vision
)
async_kwargs["default_headers"] = copilot_default_headers()
elif base_url_host_matches(sync_base_url, "api.kimi.com"):
async_kwargs["default_headers"] = {"User-Agent": "claude-code/0.1.0"}
return AsyncOpenAI(**async_kwargs), model
@@ -1910,7 +1619,6 @@ def resolve_provider_client(
explicit_api_key: str = None,
api_mode: str = None,
main_runtime: Optional[Dict[str, Any]] = None,
is_vision: bool = False,
) -> Tuple[Optional[Any], Optional[str]]:
"""Central router: given a provider name and optional model, return a
configured client with the correct auth, base URL, and API format.
@@ -1968,20 +1676,8 @@ def resolve_provider_client(
return True
return False
def _wrap_if_needed(client_obj, final_model_str: str, base_url_str: str = "",
api_key_str: str = ""):
"""Wrap a plain OpenAI client in the correct transport adapter.
Handles two cases:
- ``CodexAuxiliaryClient`` when the endpoint needs the Responses API
(explicit ``api_mode=codex_responses`` or api.openai.com + codex
model name).
- ``AnthropicAuxiliaryClient`` when the endpoint speaks Anthropic
Messages (explicit ``api_mode=anthropic_messages``, any ``/anthropic``
suffix, ``api.kimi.com/coding``, or ``api.anthropic.com``).
Clients that are already specialized wrappers pass through unchanged.
"""
def _wrap_if_needed(client_obj, final_model_str: str, base_url_str: str = ""):
"""Wrap a plain OpenAI client in CodexAuxiliaryClient if Responses API is needed."""
if _needs_codex_wrap(client_obj, base_url_str, final_model_str):
logger.debug(
"resolve_provider_client: wrapping client in CodexAuxiliaryClient "
@@ -1989,11 +1685,7 @@ def resolve_provider_client(
api_mode or "auto-detected", final_model_str,
base_url_str[:60] if base_url_str else "")
return CodexAuxiliaryClient(client_obj, final_model_str)
# Anthropic-wire endpoints: rewrap plain OpenAI clients so
# chat.completions.create() is translated to /v1/messages.
return _maybe_wrap_anthropic(
client_obj, final_model_str, api_key_str, base_url_str, api_mode,
)
return client_obj
# ── Auto: try all providers in priority order ────────────────────
if provider == "auto":
@@ -2010,7 +1702,7 @@ def resolve_provider_client(
"auxiliary provider (using %r instead)", model, resolved)
model = None
final_model = model or resolved
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
# ── OpenRouter ───────────────────────────────────────────────────
@@ -2023,7 +1715,7 @@ def resolve_provider_client(
)
return None, None
final_model = _normalize_resolved_model(model or default, provider)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
# ── Nous Portal (OAuth) ──────────────────────────────────────────
@@ -2040,7 +1732,7 @@ def resolve_provider_client(
"but Nous Portal not configured (run: hermes auth)")
return None, None
final_model = _normalize_resolved_model(model or default, provider)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
# ── OpenAI Codex (OAuth → Responses API) ─────────────────────────
@@ -2067,13 +1759,13 @@ def resolve_provider_client(
"but no Codex OAuth token found (run: hermes model)")
return None, None
final_model = _normalize_resolved_model(model or default, provider)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
# ── Custom endpoint (OPENAI_BASE_URL + OPENAI_API_KEY) ───────────
if provider == "custom":
if explicit_base_url:
custom_base = _to_openai_base_url(explicit_base_url).strip()
custom_base = explicit_base_url.strip()
custom_key = (
(explicit_api_key or "").strip()
or os.getenv("OPENAI_API_KEY", "").strip()
@@ -2086,23 +1778,18 @@ def resolve_provider_client(
)
return None, None
final_model = _normalize_resolved_model(
model or (main_runtime.get("model") if main_runtime else None) or "gpt-4o-mini",
model or _read_main_model() or "gpt-4o-mini",
provider,
)
extra = {}
_clean_base, _dq = _extract_url_query_params(custom_base)
if _dq:
extra["default_query"] = _dq
if base_url_host_matches(custom_base, "api.kimi.com"):
extra["default_headers"] = {"User-Agent": "claude-code/0.1.0"}
elif base_url_host_matches(custom_base, "api.githubcopilot.com"):
from hermes_cli.copilot_auth import copilot_request_headers
extra["default_headers"] = copilot_request_headers(
is_agent_turn=True, is_vision=is_vision
)
client = OpenAI(api_key=custom_key, base_url=_clean_base, **extra)
client = _wrap_if_needed(client, final_model, custom_base, custom_key)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
from hermes_cli.models import copilot_default_headers
extra["default_headers"] = copilot_default_headers()
client = OpenAI(api_key=custom_key, base_url=custom_base, **extra)
client = _wrap_if_needed(client, final_model, custom_base)
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
# Try custom first, then codex, then API-key providers
for try_fn in (_try_custom_endpoint, _try_codex,
@@ -2111,9 +1798,8 @@ def resolve_provider_client(
if client is not None:
final_model = _normalize_resolved_model(model or default, provider)
_cbase = str(getattr(client, "base_url", "") or "")
_ckey = str(getattr(client, "api_key", "") or "")
client = _wrap_if_needed(client, final_model, _cbase, _ckey)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
client = _wrap_if_needed(client, final_model, _cbase)
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
logger.warning("resolve_provider_client: custom/main requested "
"but no endpoint credentials found")
@@ -2135,23 +1821,9 @@ def resolve_provider_client(
entry_api_mode = (api_mode or custom_entry.get("api_mode") or "").strip()
if custom_base:
final_model = _normalize_resolved_model(
model
or custom_entry.get("model")
or (main_runtime.get("model") if main_runtime else None)
or _read_main_model()
or "gpt-4o-mini",
model or custom_entry.get("model") or _read_main_model() or "gpt-4o-mini",
provider,
)
# anthropic_messages talks to the /anthropic surface directly;
# OpenAI-wire paths (chat_completions / codex_responses) need the
# /v1 equivalent. Rewrite only on the OpenAI-wire path so the
# Anthropic fallback SDK still sees the original URL.
if entry_api_mode == "anthropic_messages":
openai_base = custom_base
else:
openai_base = _to_openai_base_url(custom_base)
_clean_base2, _dq2 = _extract_url_query_params(openai_base)
_extra2 = {"default_query": _dq2} if _dq2 else {}
logger.debug(
"resolve_provider_client: named custom provider %r (%s, api_mode=%s)",
provider, final_model, entry_api_mode or "chat_completions")
@@ -2169,13 +1841,8 @@ def resolve_provider_client(
"installed — falling back to OpenAI-wire.",
provider,
)
# Fallback went OpenAI-wire after all — redo the query
# extraction against the rewritten /v1 URL.
_fallback_base = _to_openai_base_url(custom_base)
_fb_clean, _fb_dq = _extract_url_query_params(_fallback_base)
_fb_extra = {"default_query": _fb_dq} if _fb_dq else {}
client = OpenAI(api_key=custom_key, base_url=_fb_clean, **_fb_extra)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
client = OpenAI(api_key=custom_key, base_url=custom_base)
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
sync_anthropic = AnthropicAuxiliaryClient(
real_client, final_model, custom_key, custom_base, is_oauth=False,
@@ -2183,7 +1850,7 @@ def resolve_provider_client(
if async_mode:
return AsyncAnthropicAuxiliaryClient(sync_anthropic), final_model
return sync_anthropic, final_model
client = OpenAI(api_key=custom_key, base_url=_clean_base2, **_extra2)
client = OpenAI(api_key=custom_key, base_url=custom_base)
# codex_responses or inherited auto-detect (via _wrap_if_needed).
# _wrap_if_needed reads the closed-over `api_mode` (the task-level
# override). Named-provider entry api_mode=codex_responses also
@@ -2193,8 +1860,8 @@ def resolve_provider_client(
):
client = CodexAuxiliaryClient(client, final_model)
else:
client = _wrap_if_needed(client, final_model, openai_base, custom_key)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
client = _wrap_if_needed(client, final_model, custom_base)
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
logger.warning(
"resolve_provider_client: named custom provider %r has no base_url",
@@ -2226,7 +1893,7 @@ def resolve_provider_client(
logger.warning("resolve_provider_client: anthropic requested but no Anthropic credentials found")
return None, None
final_model = _normalize_resolved_model(model or default_model, provider)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode else (client, final_model))
return (_to_async_client(client, final_model) if async_mode else (client, final_model))
creds = resolve_api_key_provider_credentials(provider)
api_key = str(creds.get("api_key", "")).strip()
@@ -2252,7 +1919,7 @@ def resolve_provider_client(
if is_native_gemini_base_url(base_url):
client = GeminiNativeClient(api_key=api_key, base_url=base_url)
logger.debug("resolve_provider_client: %s (%s)", provider, final_model)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
# Provider-specific headers
@@ -2260,11 +1927,9 @@ def resolve_provider_client(
if base_url_host_matches(base_url, "api.kimi.com"):
headers["User-Agent"] = "claude-code/0.1.0"
elif base_url_host_matches(base_url, "api.githubcopilot.com"):
from hermes_cli.copilot_auth import copilot_request_headers
from hermes_cli.models import copilot_default_headers
headers.update(copilot_request_headers(
is_agent_turn=True, is_vision=is_vision
))
headers.update(copilot_default_headers())
client = OpenAI(api_key=api_key, base_url=base_url,
**({"default_headers": headers} if headers else {}))
@@ -2286,24 +1951,16 @@ def resolve_provider_client(
# Honor api_mode for any API-key provider (e.g. direct OpenAI with
# codex-family models). The copilot-specific wrapping above handles
# copilot; this covers the general case (#6800). Also rewraps
# Anthropic-wire endpoints (Kimi Coding Plan api.kimi.com/coding,
# /anthropic-suffixed gateways) so named providers like kimi-coding
# land on the right transport without needing per-provider branches.
client = _wrap_if_needed(client, final_model, base_url, api_key)
# copilot; this covers the general case (#6800).
client = _wrap_if_needed(client, final_model, base_url)
logger.debug("resolve_provider_client: %s (%s)", provider, final_model)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
if pconfig.auth_type == "external_process":
creds = resolve_external_process_provider_credentials(provider)
final_model = _normalize_resolved_model(
model
or (main_runtime.get("model") if main_runtime else None)
or _read_main_model(),
provider,
)
final_model = _normalize_resolved_model(model or _read_main_model(), provider)
if provider == "copilot-acp":
api_key = str(creds.get("api_key", "")).strip()
base_url = str(creds.get("base_url", "")).strip()
@@ -2330,45 +1987,12 @@ def resolve_provider_client(
args=args,
)
logger.debug("resolve_provider_client: %s (%s)", provider, final_model)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
return (_to_async_client(client, final_model) if async_mode
else (client, final_model))
logger.warning("resolve_provider_client: external-process provider %s not "
"directly supported", provider)
return None, None
elif pconfig.auth_type == "aws_sdk":
# AWS SDK providers (Bedrock) — use the Anthropic Bedrock client via
# boto3's credential chain (IAM roles, SSO, env vars, instance metadata).
try:
from agent.bedrock_adapter import has_aws_credentials, resolve_bedrock_region
from agent.anthropic_adapter import build_anthropic_bedrock_client
except ImportError:
logger.warning("resolve_provider_client: bedrock requested but "
"boto3 or anthropic SDK not installed")
return None, None
if not has_aws_credentials():
logger.debug("resolve_provider_client: bedrock requested but "
"no AWS credentials found")
return None, None
region = resolve_bedrock_region()
default_model = "anthropic.claude-haiku-4-5-20251001-v1:0"
final_model = _normalize_resolved_model(model or default_model, provider)
try:
real_client = build_anthropic_bedrock_client(region)
except ImportError as exc:
logger.warning("resolve_provider_client: cannot create Bedrock "
"client: %s", exc)
return None, None
client = AnthropicAuxiliaryClient(
real_client, final_model, api_key="aws-sdk",
base_url=f"https://bedrock-runtime.{region}.amazonaws.com",
)
logger.debug("resolve_provider_client: bedrock (%s, %s)", final_model, region)
return (_to_async_client(client, final_model, is_vision=is_vision) if async_mode
else (client, final_model))
elif pconfig.auth_type in ("oauth_device_code", "oauth_external"):
# OAuth providers — route through their specific try functions
if provider == "nous":
@@ -2441,13 +2065,8 @@ def _normalize_vision_provider(provider: Optional[str]) -> str:
return _normalize_aux_provider(provider)
def _resolve_strict_vision_backend(
provider: str,
model: Optional[str] = None,
) -> Tuple[Optional[Any], Optional[str]]:
def _resolve_strict_vision_backend(provider: str) -> Tuple[Optional[Any], Optional[str]]:
provider = _normalize_vision_provider(provider)
if provider == "copilot":
return resolve_provider_client("copilot", model, is_vision=True)
if provider == "openrouter":
return _try_openrouter()
if provider == "nous":
@@ -2515,7 +2134,7 @@ def resolve_vision_provider_client(
return resolved_provider, None, None
final_model = resolved_model or default_model
if async_mode:
async_client, async_model = _to_async_client(sync_client, final_model, is_vision=True)
async_client, async_model = _to_async_client(sync_client, final_model)
return resolved_provider, async_client, async_model
return resolved_provider, sync_client, final_model
@@ -2547,35 +2166,19 @@ def resolve_vision_provider_client(
main_provider = _read_main_provider()
main_model = _read_main_model()
if main_provider and main_provider not in ("auto", ""):
vision_model = _PROVIDER_VISION_MODELS.get(main_provider, main_model)
if main_provider == "nous":
sync_client, default_model = _resolve_strict_vision_backend(
main_provider, vision_model
)
sync_client, default_model = _resolve_strict_vision_backend(main_provider)
if sync_client is not None:
logger.info(
"Vision auto-detect: using main provider %s (%s)",
main_provider, default_model or resolved_model or main_model,
)
return _finalize(main_provider, sync_client, default_model)
elif main_provider in _PROVIDERS_WITHOUT_VISION:
# Kimi Coding Plan's /coding endpoint (Anthropic Messages wire)
# does not accept image input — Kimi's own docs say "Current
# model does not support image input, switch to a model with
# image_in capability" and vision lives on the separate Kimi
# Platform (api.moonshot.ai). Skip the main provider and fall
# through to the aggregator chain instead of returning a
# client that will 404 on every vision request (#17076).
logger.debug(
"Vision auto-detect: skipping main provider %s (no "
"vision support) — falling through to aggregator chain",
main_provider,
)
else:
vision_model = _PROVIDER_VISION_MODELS.get(main_provider, main_model)
rpc_client, rpc_model = resolve_provider_client(
main_provider, vision_model,
api_mode=resolved_api_mode,
is_vision=True)
api_mode=resolved_api_mode)
if rpc_client is not None:
logger.info(
"Vision auto-detect: using main provider %s (%s)",
@@ -2597,14 +2200,11 @@ def resolve_vision_provider_client(
return None, None, None
if requested in _VISION_AUTO_PROVIDER_ORDER:
sync_client, default_model = _resolve_strict_vision_backend(
requested, resolved_model
)
sync_client, default_model = _resolve_strict_vision_backend(requested)
return _finalize(requested, sync_client, default_model)
client, final_model = _get_cached_client(requested, resolved_model, async_mode,
api_mode=resolved_api_mode,
is_vision=True)
api_mode=resolved_api_mode)
if client is None:
return requested, None, None
return requested, client, final_model
@@ -2668,11 +2268,10 @@ def _client_cache_key(
api_key: Optional[str] = None,
api_mode: Optional[str] = None,
main_runtime: Optional[Dict[str, Any]] = None,
is_vision: bool = False,
) -> tuple:
runtime = _normalize_main_runtime(main_runtime)
runtime_key = tuple(runtime.get(field, "") for field in _MAIN_RUNTIME_FIELDS) if provider == "auto" else ()
return (provider, async_mode, base_url or "", api_key or "", api_mode or "", runtime_key, is_vision)
return (provider, async_mode, base_url or "", api_key or "", api_mode or "", runtime_key)
def _store_cached_client(cache_key: tuple, client: Any, default_model: Optional[str], *, bound_loop: Any = None) -> None:
@@ -2698,7 +2297,6 @@ def _refresh_nous_auxiliary_client(
api_key: Optional[str] = None,
api_mode: Optional[str] = None,
main_runtime: Optional[Dict[str, Any]] = None,
is_vision: bool = False,
) -> Tuple[Optional[Any], Optional[str]]:
"""Refresh Nous runtime creds, rebuild the client, and replace the cache entry."""
runtime = _resolve_nous_runtime_api(force_refresh=True)
@@ -2716,7 +2314,7 @@ def _refresh_nous_auxiliary_client(
current_loop = _aio.get_event_loop()
except RuntimeError:
pass
client, final_model = _to_async_client(sync_client, final_model or "", is_vision=is_vision)
client, final_model = _to_async_client(sync_client, final_model or "")
else:
client = sync_client
@@ -2727,7 +2325,6 @@ def _refresh_nous_auxiliary_client(
api_key=api_key,
api_mode=api_mode,
main_runtime=main_runtime,
is_vision=is_vision,
)
_store_cached_client(cache_key, client, final_model, bound_loop=current_loop)
return client, final_model
@@ -2839,19 +2436,12 @@ def _is_openrouter_client(client: Any) -> bool:
return False
def _cached_client_accepts_slash_models(client: Any, cached_default: Optional[str]) -> bool:
"""Best-effort check for cached clients that accept ``vendor/model`` IDs."""
if _is_openrouter_client(client):
return True
return bool(cached_default and "/" in cached_default)
def _compat_model(client: Any, model: Optional[str], cached_default: Optional[str]) -> Optional[str]:
"""Keep slash-bearing model IDs only for cached clients that support them.
"""Drop OpenRouter-format model slugs (with '/') for non-OpenRouter clients.
Mirrors the guard in resolve_provider_client() which is skipped on cache hits.
"""
if model and "/" in model and not _cached_client_accepts_slash_models(client, cached_default):
if model and "/" in model and not _is_openrouter_client(client):
return cached_default
return model or cached_default
@@ -2864,7 +2454,6 @@ def _get_cached_client(
api_key: str = None,
api_mode: str = None,
main_runtime: Optional[Dict[str, Any]] = None,
is_vision: bool = False,
) -> Tuple[Optional[Any], Optional[str]]:
"""Get or create a cached client for the given provider.
@@ -2901,7 +2490,6 @@ def _get_cached_client(
api_key=api_key,
api_mode=api_mode,
main_runtime=main_runtime,
is_vision=is_vision,
)
with _client_cache_lock:
if cache_key in _client_cache:
@@ -2933,7 +2521,6 @@ def _get_cached_client(
explicit_api_key=api_key,
api_mode=api_mode,
main_runtime=runtime,
is_vision=is_vision,
)
if client is not None:
# For async clients, remember which loop they were created on so we
@@ -3052,7 +2639,7 @@ def _get_task_extra_body(task: str) -> Dict[str, Any]:
# Providers that use Anthropic-compatible endpoints (via OpenAI SDK wrapper).
# Their image content blocks must use Anthropic format, not OpenAI format.
_ANTHROPIC_COMPAT_PROVIDERS = frozenset({"minimax", "minimax-oauth", "minimax-cn"})
_ANTHROPIC_COMPAT_PROVIDERS = frozenset({"minimax", "minimax-cn"})
def _is_anthropic_compat_endpoint(provider: str, base_url: str) -> bool:
@@ -3140,8 +2727,8 @@ def _build_call_kwargs(
temperature = fixed_temperature
# Opus 4.7+ rejects any non-default temperature/top_p/top_k — silently
# drop here so auxiliary callers that hardcode temperature (e.g. 0 on
# structured-JSON extraction) don't 400 the moment
# drop here so auxiliary callers that hardcode temperature (e.g. 0.3 on
# flush_memories, 0 on structured-JSON extraction) don't 400 the moment
# the aux model is flipped to 4.7.
if temperature is not None:
from agent.anthropic_adapter import _forbids_sampling_params
@@ -3229,7 +2816,7 @@ def call_llm(
Args:
task: Auxiliary task name ("compression", "vision", "web_extract",
"session_search", "skills_hub", "mcp", "title_generation").
"session_search", "skills_hub", "mcp", "flush_memories").
Reads provider:model from config/env. Ignored if provider is set.
provider: Explicit provider override.
model: Explicit model override.
@@ -3332,45 +2919,13 @@ def call_llm(
if _is_anthropic_compat_endpoint(resolved_provider, _client_base):
kwargs["messages"] = _convert_openai_images_to_anthropic(kwargs["messages"])
# Handle unsupported temperature, max_tokens vs max_completion_tokens retry,
# then payment fallback.
# Handle max_tokens vs max_completion_tokens retry, then payment fallback.
try:
return _validate_llm_response(
client.chat.completions.create(**kwargs), task)
except Exception as first_err:
if "temperature" in kwargs and _is_unsupported_temperature_error(first_err):
retry_kwargs = dict(kwargs)
retry_kwargs.pop("temperature", None)
logger.info(
"Auxiliary %s: provider rejected temperature; retrying once without it",
task or "call",
)
try:
return _validate_llm_response(
client.chat.completions.create(**retry_kwargs), task)
except Exception as retry_err:
retry_err_str = str(retry_err)
# If retry still fails, fall through to the max_tokens /
# payment / auth chains below using the temperature-stripped
# kwargs. Re-raise only if the retry hit something those
# chains won't handle.
if not (
_is_payment_error(retry_err)
or _is_connection_error(retry_err)
or _is_auth_error(retry_err)
or "max_tokens" in retry_err_str
or "unsupported_parameter" in retry_err_str
):
raise
first_err = retry_err
kwargs = retry_kwargs
err_str = str(first_err)
if max_tokens is not None and (
"max_tokens" in err_str
or "unsupported_parameter" in err_str
or _is_unsupported_parameter_error(first_err, "max_tokens")
):
if "max_tokens" in err_str or "unsupported_parameter" in err_str:
kwargs.pop("max_tokens", None)
kwargs["max_completion_tokens"] = max_tokens
try:
@@ -3397,7 +2952,6 @@ def call_llm(
api_key=resolved_api_key,
api_mode=resolved_api_mode,
main_runtime=main_runtime,
is_vision=(task == "vision"),
)
if refreshed_client is not None:
logger.info("Auxiliary %s: refreshed Nous runtime credentials after 401, retrying",
@@ -3634,35 +3188,8 @@ async def async_call_llm(
return _validate_llm_response(
await client.chat.completions.create(**kwargs), task)
except Exception as first_err:
if "temperature" in kwargs and _is_unsupported_temperature_error(first_err):
retry_kwargs = dict(kwargs)
retry_kwargs.pop("temperature", None)
logger.info(
"Auxiliary %s (async): provider rejected temperature; retrying once without it",
task or "call",
)
try:
return _validate_llm_response(
await client.chat.completions.create(**retry_kwargs), task)
except Exception as retry_err:
retry_err_str = str(retry_err)
if not (
_is_payment_error(retry_err)
or _is_connection_error(retry_err)
or _is_auth_error(retry_err)
or "max_tokens" in retry_err_str
or "unsupported_parameter" in retry_err_str
):
raise
first_err = retry_err
kwargs = retry_kwargs
err_str = str(first_err)
if max_tokens is not None and (
"max_tokens" in err_str
or "unsupported_parameter" in err_str
or _is_unsupported_parameter_error(first_err, "max_tokens")
):
if "max_tokens" in err_str or "unsupported_parameter" in err_str:
kwargs.pop("max_tokens", None)
kwargs["max_completion_tokens"] = max_tokens
try:
@@ -3688,7 +3215,6 @@ async def async_call_llm(
base_url=resolved_base_url,
api_key=resolved_api_key,
api_mode=resolved_api_mode,
is_vision=(task == "vision"),
)
if refreshed_client is not None:
logger.info("Auxiliary %s (async): refreshed Nous runtime credentials after 401, retrying",
@@ -3757,9 +3283,7 @@ async def async_call_llm(
extra_body=effective_extra_body,
base_url=str(getattr(fb_client, "base_url", "") or ""))
# Convert sync fallback client to async
async_fb, async_fb_model = _to_async_client(
fb_client, fb_model or "", is_vision=(task == "vision")
)
async_fb, async_fb_model = _to_async_client(fb_client, fb_model or "")
if async_fb_model and async_fb_model != fb_kwargs.get("model"):
fb_kwargs["model"] = async_fb_model
return _validate_llm_response(
+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:
+5 -128
View File
@@ -61,52 +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.
@@ -337,11 +294,6 @@ 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 +317,6 @@ 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 +389,6 @@ 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."""
@@ -542,7 +475,7 @@ class ContextCompressor(ContextEngine):
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):
@@ -879,12 +812,10 @@ 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.",
@@ -915,57 +846,13 @@ 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)
# 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.",
@@ -1180,9 +1067,8 @@ 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):
@@ -1251,13 +1137,6 @@ 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
@@ -1336,13 +1215,11 @@ 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."
)
+4 -124
View File
@@ -7,13 +7,13 @@ 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
import hermes_cli.auth as auth_mod
from hermes_cli.auth import (
CODEX_ACCESS_TOKEN_REFRESH_SKEW_SECONDS,
@@ -455,70 +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.
@@ -851,18 +787,6 @@ class CredentialPool:
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:
@@ -1299,48 +1223,6 @@ 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
@@ -1391,8 +1273,7 @@ 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":
# Check both os.environ and ~/.hermes/.env file
token = (get_env_value("OPENROUTER_API_KEY") or "").strip()
token = os.getenv("OPENROUTER_API_KEY", "").strip()
if token:
source = "env:OPENROUTER_API_KEY"
if _is_source_suppressed(provider, source):
@@ -1418,7 +1299,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
env_url = ""
if pconfig.base_url_env_var:
env_url = (get_env_value(pconfig.base_url_env_var) or "").strip().rstrip("/")
env_url = os.getenv(pconfig.base_url_env_var, "").strip().rstrip("/")
env_vars = list(pconfig.api_key_env_vars)
if provider == "anthropic":
@@ -1429,8 +1310,7 @@ def _seed_from_env(provider: str, entries: List[PooledCredential]) -> Tuple[bool
]
for env_var in env_vars:
# Check both os.environ and ~/.hermes/.env file
token = (get_env_value(env_var) or "").strip()
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",
-869
View File
@@ -1,869 +0,0 @@
"""Curator — background skill maintenance orchestrator.
The curator is an auxiliary-model task that periodically reviews agent-created
skills and maintains the collection. It runs inactivity-triggered (no cron
daemon): when the agent is idle and the last curator run was longer than
``interval_hours`` ago, ``maybe_run_curator()`` spawns a forked AIAgent to do
the review.
Responsibilities:
- Auto-transition lifecycle states based on last_used_at timestamps
- Spawn a background review agent that can pin / archive / consolidate /
patch agent-created skills via skill_manage
- Persist curator state (last_run_at, paused, etc.) in .curator_state
Strict invariants:
- Only touches agent-created skills (see tools/skill_usage.is_agent_created)
- Never auto-deletes only archives. Archive is recoverable.
- Pinned skills bypass all auto-transitions
- Uses the auxiliary client; never touches the main session's prompt cache
"""
from __future__ import annotations
import json
import logging
import os
import tempfile
import threading
from datetime import datetime, timedelta, timezone
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Set
from hermes_constants import get_hermes_home
from tools import skill_usage
logger = logging.getLogger(__name__)
DEFAULT_INTERVAL_HOURS = 24 * 7 # 7 days
DEFAULT_MIN_IDLE_HOURS = 2
DEFAULT_STALE_AFTER_DAYS = 30
DEFAULT_ARCHIVE_AFTER_DAYS = 90
# ---------------------------------------------------------------------------
# .curator_state — persistent scheduler + status
# ---------------------------------------------------------------------------
def _state_file() -> Path:
return get_hermes_home() / "skills" / ".curator_state"
def _default_state() -> Dict[str, Any]:
return {
"last_run_at": None,
"last_run_duration_seconds": None,
"last_run_summary": None,
"paused": False,
"run_count": 0,
}
def load_state() -> Dict[str, Any]:
path = _state_file()
if not path.exists():
return _default_state()
try:
data = json.loads(path.read_text(encoding="utf-8"))
if isinstance(data, dict):
base = _default_state()
base.update({k: v for k, v in data.items() if k in base or k.startswith("_")})
return base
except (OSError, json.JSONDecodeError) as e:
logger.debug("Failed to read curator state: %s", e)
return _default_state()
def save_state(data: Dict[str, Any]) -> None:
path = _state_file()
try:
path.parent.mkdir(parents=True, exist_ok=True)
fd, tmp = tempfile.mkstemp(dir=str(path.parent), prefix=".curator_state_", suffix=".tmp")
try:
with os.fdopen(fd, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2, sort_keys=True, ensure_ascii=False)
f.flush()
os.fsync(f.fileno())
os.replace(tmp, path)
except BaseException:
try:
os.unlink(tmp)
except OSError:
pass
raise
except Exception as e:
logger.debug("Failed to save curator state: %s", e, exc_info=True)
def set_paused(paused: bool) -> None:
state = load_state()
state["paused"] = bool(paused)
save_state(state)
def is_paused() -> bool:
return bool(load_state().get("paused"))
# ---------------------------------------------------------------------------
# Config access
# ---------------------------------------------------------------------------
def _load_config() -> Dict[str, Any]:
"""Read curator.* config from ~/.hermes/config.yaml. Tolerates missing file."""
try:
from hermes_cli.config import load_config
cfg = load_config()
except Exception as e:
logger.debug("Failed to load config for curator: %s", e)
return {}
if not isinstance(cfg, dict):
return {}
cur = cfg.get("curator") or {}
if not isinstance(cur, dict):
return {}
return cur
def is_enabled() -> bool:
"""Default ON when no config says otherwise."""
cfg = _load_config()
return bool(cfg.get("enabled", True))
def get_interval_hours() -> int:
cfg = _load_config()
try:
return int(cfg.get("interval_hours", DEFAULT_INTERVAL_HOURS))
except (TypeError, ValueError):
return DEFAULT_INTERVAL_HOURS
def get_min_idle_hours() -> float:
cfg = _load_config()
try:
return float(cfg.get("min_idle_hours", DEFAULT_MIN_IDLE_HOURS))
except (TypeError, ValueError):
return DEFAULT_MIN_IDLE_HOURS
def get_stale_after_days() -> int:
cfg = _load_config()
try:
return int(cfg.get("stale_after_days", DEFAULT_STALE_AFTER_DAYS))
except (TypeError, ValueError):
return DEFAULT_STALE_AFTER_DAYS
def get_archive_after_days() -> int:
cfg = _load_config()
try:
return int(cfg.get("archive_after_days", DEFAULT_ARCHIVE_AFTER_DAYS))
except (TypeError, ValueError):
return DEFAULT_ARCHIVE_AFTER_DAYS
# ---------------------------------------------------------------------------
# Idle / interval check
# ---------------------------------------------------------------------------
def _parse_iso(ts: Optional[str]) -> Optional[datetime]:
if not ts:
return None
try:
return datetime.fromisoformat(ts)
except (TypeError, ValueError):
return None
def should_run_now(now: Optional[datetime] = None) -> bool:
"""Return True if the curator should run immediately.
Gates:
- curator.enabled == True
- not paused
- last_run_at missing, OR older than interval_hours
The idle check (min_idle_hours) is applied at the call site where we know
whether an agent is actively running here we only enforce the static
gates.
"""
if not is_enabled():
return False
if is_paused():
return False
state = load_state()
last = _parse_iso(state.get("last_run_at"))
if last is None:
return True
if now is None:
now = datetime.now(timezone.utc)
if last.tzinfo is None:
last = last.replace(tzinfo=timezone.utc)
interval = timedelta(hours=get_interval_hours())
return (now - last) >= interval
# ---------------------------------------------------------------------------
# Automatic state transitions (pure function, no LLM)
# ---------------------------------------------------------------------------
def apply_automatic_transitions(now: Optional[datetime] = None) -> Dict[str, int]:
"""Walk every agent-created skill and move active/stale/archived based on
last_used_at. Pinned skills are never touched. Returns a counter dict
describing what changed."""
from tools import skill_usage as _u
if now is None:
now = datetime.now(timezone.utc)
stale_cutoff = now - timedelta(days=get_stale_after_days())
archive_cutoff = now - timedelta(days=get_archive_after_days())
counts = {"marked_stale": 0, "archived": 0, "reactivated": 0, "checked": 0}
for row in _u.agent_created_report():
counts["checked"] += 1
name = row["name"]
if row.get("pinned"):
continue
last_used = _parse_iso(row.get("last_used_at"))
# If never used, treat as using created_at as the anchor so new skills
# don't immediately archive themselves.
anchor = last_used or _parse_iso(row.get("created_at")) or now
if anchor.tzinfo is None:
anchor = anchor.replace(tzinfo=timezone.utc)
current = row.get("state", _u.STATE_ACTIVE)
if anchor <= archive_cutoff and current != _u.STATE_ARCHIVED:
ok, _msg = _u.archive_skill(name)
if ok:
counts["archived"] += 1
elif anchor <= stale_cutoff and current == _u.STATE_ACTIVE:
_u.set_state(name, _u.STATE_STALE)
counts["marked_stale"] += 1
elif anchor > stale_cutoff and current == _u.STATE_STALE:
# Skill got used again after being marked stale — reactivate.
_u.set_state(name, _u.STATE_ACTIVE)
counts["reactivated"] += 1
return counts
# ---------------------------------------------------------------------------
# Review prompt for the forked agent
# ---------------------------------------------------------------------------
CURATOR_REVIEW_PROMPT = (
"You are running as Hermes' background skill CURATOR. This is an "
"UMBRELLA-BUILDING consolidation pass, not a passive audit and not a "
"duplicate-finder.\n\n"
"The goal of the skill collection is a LIBRARY OF CLASS-LEVEL "
"INSTRUCTIONS AND EXPERIENTIAL KNOWLEDGE. A collection of hundreds of "
"narrow skills where each one captures one session's specific bug is "
"a FAILURE of the library — not a feature. An agent searching skills "
"matches on descriptions, not on exact names; one broad umbrella "
"skill with labeled subsections beats five narrow siblings for "
"discoverability, not the other way around.\n\n"
"The right target shape is CLASS-LEVEL skills with rich SKILL.md "
"bodies + `references/`, `templates/`, and `scripts/` subfiles for "
"session-specific detail — not one-session-one-skill micro-entries.\n\n"
"Hard rules — do not violate:\n"
"1. DO NOT touch bundled or hub-installed skills. The candidate list "
"below is already filtered to agent-created skills only.\n"
"2. DO NOT delete any skill. Archiving (moving the skill's directory "
"into ~/.hermes/skills/.archive/) is the maximum destructive action. "
"Archives are recoverable; deletion is not.\n"
"3. DO NOT touch skills shown as pinned=yes. Skip them entirely.\n"
"4. DO NOT use usage counters as a reason to skip consolidation. The "
"counters are new and often mostly zero. Judge overlap on CONTENT, "
"not on use_count. 'use=0' is not evidence a skill is valuable; it's "
"absence of evidence either way.\n"
"5. DO NOT reject consolidation on the grounds that 'each skill has "
"a distinct trigger'. Pairwise distinctness is the wrong bar. The "
"right bar is: 'would a human maintainer write this as N separate "
"skills, or as one skill with N labeled subsections?' When the "
"answer is the latter, merge.\n\n"
"How to work — not optional:\n"
"1. Scan the full candidate list. Identify PREFIX CLUSTERS (skills "
"sharing a first word or domain keyword). Examples you are likely "
"to find: hermes-config-*, hermes-dashboard-*, gateway-*, codex-*, "
"ollama-*, anthropic-*, gemini-*, mcp-*, salvage-*, pr-*, "
"competitor-*, python-*, security-*, etc. Expect 10-25 clusters.\n"
"2. For each cluster with 2+ members, do NOT ask 'are these pairs "
"overlapping?' — ask 'what is the UMBRELLA CLASS these skills all "
"serve? Would a maintainer name that class and write one skill for "
"it?' If yes, pick (or create) the umbrella and absorb the siblings "
"into it.\n"
"3. Three ways to consolidate — use the right one per cluster:\n"
" a. MERGE INTO EXISTING UMBRELLA — one skill in the cluster is "
"already broad enough to be the umbrella (example: `pr-triage-"
"salvage` for the PR review cluster). Patch it to add a labeled "
"section for each sibling's unique insight, then archive the "
"siblings.\n"
" b. CREATE A NEW UMBRELLA SKILL.md — no existing member is broad "
"enough. Use skill_manage action=create to write a new class-level "
"skill whose SKILL.md covers the shared workflow and has short "
"labeled subsections. Archive the now-absorbed narrow siblings.\n"
" c. DEMOTE TO REFERENCES/TEMPLATES/SCRIPTS — a sibling has "
"narrow-but-valuable session-specific content. Move it into the "
"umbrella's appropriate support directory:\n"
" • `references/<topic>.md` for session-specific detail OR "
"condensed knowledge banks (quoted research, API docs excerpts, "
"domain notes, provider quirks, reproduction recipes)\n"
" • `templates/<name>.<ext>` for starter files meant to be "
"copied and modified\n"
" • `scripts/<name>.<ext>` for statically re-runnable actions "
"(verification scripts, fixture generators, probes)\n"
" Then archive the old sibling. Use `terminal` with `mkdir -p "
"~/.hermes/skills/<umbrella>/references/ && mv ... <umbrella>/"
"references/<topic>.md` (or templates/ / scripts/).\n"
"4. Also flag skills whose NAME is too narrow (contains a PR number, "
"a feature codename, a specific error string, an 'audit' / "
"'diagnosis' / 'salvage' session artifact). These almost always "
"belong as a subsection or support file under a class-level umbrella.\n"
"5. Iterate. After one consolidation round, scan the remaining set "
"and look for the NEXT umbrella opportunity. Don't stop after 3 "
"merges.\n\n"
"Your toolset:\n"
" - skills_list, skill_view — read the current landscape\n"
" - skill_manage action=patch — add sections to the umbrella\n"
" - skill_manage action=create — create a new umbrella SKILL.md\n"
" - skill_manage action=write_file — add a references/, templates/, "
"or scripts/ file under an existing skill (the skill must already "
"exist)\n"
" - terminal — mv a sibling into the archive "
"OR move its content into a support subfile\n\n"
"'keep' is a legitimate decision ONLY when the skill is already a "
"class-level umbrella and none of the proposed merges would improve "
"discoverability. 'This is narrow but distinct from its siblings' "
"is NOT a reason to keep — it's a reason to move it under an "
"umbrella as a subsection or support file.\n\n"
"Expected output: real umbrella-ification. Process every obvious "
"cluster. If you end the pass with fewer than 10 archives, you "
"stopped too early — go back and look at the clusters you left "
"alone.\n\n"
"When done, write a summary with: clusters processed, skills "
"patched/absorbed, skills demoted to references/templates/scripts, "
"skills archived, new umbrellas created, and clusters you "
"deliberately left alone with one line each."
)
# ---------------------------------------------------------------------------
# Per-run reports — {YYYYMMDD-HHMMSS}/run.json + REPORT.md under logs/curator/
# ---------------------------------------------------------------------------
def _reports_root() -> Path:
"""Directory where curator run reports are written.
Lives under the profile-aware logs dir (``~/.hermes/logs/curator/``)
alongside ``agent.log`` and ``gateway.log`` so it's found by anyone
looking for operational telemetry, not mixed in with the user's
authored skill data in ``~/.hermes/skills/``.
"""
return get_hermes_home() / "logs" / "curator"
def _write_run_report(
*,
started_at: datetime,
elapsed_seconds: float,
auto_counts: Dict[str, int],
auto_summary: str,
before_report: List[Dict[str, Any]],
before_names: Set[str],
after_report: List[Dict[str, Any]],
llm_meta: Dict[str, Any],
) -> Optional[Path]:
"""Write run.json + REPORT.md under logs/curator/{YYYYMMDD-HHMMSS}/.
Returns the report directory path on success, None if the write
couldn't happen (caller logs and continues — reporting is best-effort).
"""
root = _reports_root()
try:
root.mkdir(parents=True, exist_ok=True)
except Exception as e:
logger.debug("Curator report dir create failed: %s", e)
return None
stamp = started_at.strftime("%Y%m%d-%H%M%S")
run_dir = root / stamp
# If we crash-reran within the same second, append a disambiguator
suffix = 1
while run_dir.exists():
suffix += 1
run_dir = root / f"{stamp}-{suffix}"
try:
run_dir.mkdir(parents=True, exist_ok=False)
except Exception as e:
logger.debug("Curator run dir create failed: %s", e)
return None
# Diff before/after
after_by_name = {r.get("name"): r for r in after_report if isinstance(r, dict)}
after_names = set(after_by_name.keys())
removed = sorted(before_names - after_names) # archived during this run
added = sorted(after_names - before_names) # new skills this run
before_by_name = {r.get("name"): r for r in before_report if isinstance(r, dict)}
# State transitions between the two snapshots (e.g. active -> stale)
transitions: List[Dict[str, str]] = []
for name in sorted(after_names & before_names):
s_before = (before_by_name.get(name) or {}).get("state")
s_after = (after_by_name.get(name) or {}).get("state")
if s_before and s_after and s_before != s_after:
transitions.append({"name": name, "from": s_before, "to": s_after})
# Classify LLM tool calls
tc_counts: Dict[str, int] = {}
for tc in llm_meta.get("tool_calls", []) or []:
name = tc.get("name", "unknown")
tc_counts[name] = tc_counts.get(name, 0) + 1
payload = {
"started_at": started_at.isoformat(),
"duration_seconds": round(elapsed_seconds, 2),
"model": llm_meta.get("model", ""),
"provider": llm_meta.get("provider", ""),
"auto_transitions": auto_counts,
"counts": {
"before": len(before_names),
"after": len(after_names),
"delta": len(after_names) - len(before_names),
"archived_this_run": len(removed),
"added_this_run": len(added),
"state_transitions": len(transitions),
"tool_calls_total": sum(tc_counts.values()),
},
"tool_call_counts": tc_counts,
"archived": removed,
"added": added,
"state_transitions": transitions,
"llm_final": llm_meta.get("final", ""),
"llm_summary": llm_meta.get("summary", ""),
"llm_error": llm_meta.get("error"),
"tool_calls": llm_meta.get("tool_calls", []),
}
# run.json — machine-readable, full fidelity
try:
(run_dir / "run.json").write_text(
json.dumps(payload, indent=2, ensure_ascii=False) + "\n",
encoding="utf-8",
)
except Exception as e:
logger.debug("Curator run.json write failed: %s", e)
# REPORT.md — human-readable
try:
md = _render_report_markdown(payload)
(run_dir / "REPORT.md").write_text(md, encoding="utf-8")
except Exception as e:
logger.debug("Curator REPORT.md write failed: %s", e)
return run_dir
def _render_report_markdown(p: Dict[str, Any]) -> str:
"""Render the human-readable report."""
lines: List[str] = []
started = p.get("started_at", "")
duration = p.get("duration_seconds", 0) or 0
mins, secs = divmod(int(duration), 60)
dur_label = f"{mins}m {secs}s" if mins else f"{secs}s"
lines.append(f"# Curator run — {started}\n")
model = p.get("model") or "(not resolved)"
prov = p.get("provider") or "(not resolved)"
counts = p.get("counts") or {}
lines.append(
f"Model: `{model}` via `{prov}` · Duration: {dur_label} · "
f"Agent-created skills: {counts.get('before', 0)}{counts.get('after', 0)} "
f"({counts.get('delta', 0):+d})\n"
)
error = p.get("llm_error")
if error:
lines.append(f"> ⚠ LLM pass error: `{error}`\n")
# Auto-transitions (pure, no LLM)
auto = p.get("auto_transitions") or {}
lines.append("## Auto-transitions (pure, no LLM)\n")
lines.append(f"- checked: {auto.get('checked', 0)}")
lines.append(f"- marked stale: {auto.get('marked_stale', 0)}")
lines.append(f"- archived: {auto.get('archived', 0)}")
lines.append(f"- reactivated: {auto.get('reactivated', 0)}")
lines.append("")
# LLM pass numbers
tc_counts = p.get("tool_call_counts") or {}
lines.append("## LLM consolidation pass\n")
lines.append(f"- tool calls: **{counts.get('tool_calls_total', 0)}** "
f"(by name: {', '.join(f'{k}={v}' for k, v in sorted(tc_counts.items())) or 'none'})")
lines.append(f"- archived this run: **{counts.get('archived_this_run', 0)}**")
lines.append(f"- new skills this run: **{counts.get('added_this_run', 0)}**")
lines.append(f"- state transitions (active ↔ stale ↔ archived): "
f"**{counts.get('state_transitions', 0)}**")
lines.append("")
# Archived list
archived = p.get("archived") or []
if archived:
lines.append(f"### Skills archived ({len(archived)})\n")
lines.append("_Archived skills are at `~/.hermes/skills/.archive/`. "
"Restore any via `hermes curator restore <name>`._\n")
# Show first 50 inline, note truncation after that
SHOW = 50
for n in archived[:SHOW]:
lines.append(f"- `{n}`")
if len(archived) > SHOW:
lines.append(f"- … and {len(archived) - SHOW} more (see `run.json` for the full list)")
lines.append("")
# Added list
added = p.get("added") or []
if added:
lines.append(f"### New skills this run ({len(added)})\n")
lines.append("_Usually these are new class-level umbrellas created via `skill_manage action=create`._\n")
for n in added:
lines.append(f"- `{n}`")
lines.append("")
# State transitions
trans = p.get("state_transitions") or []
if trans:
lines.append(f"### State transitions ({len(trans)})\n")
for t in trans:
lines.append(f"- `{t.get('name')}`: {t.get('from')}{t.get('to')}")
lines.append("")
# Full LLM final response
final = (p.get("llm_final") or "").strip()
if final:
lines.append("## LLM final summary\n")
lines.append(final)
lines.append("")
elif not error:
llm_sum = p.get("llm_summary") or ""
if llm_sum:
lines.append("## LLM summary\n")
lines.append(llm_sum)
lines.append("")
# Recovery footer
lines.append("## Recovery\n")
lines.append("- Restore an archived skill: `hermes curator restore <name>`")
lines.append("- All archives live under `~/.hermes/skills/.archive/` and are recoverable by `mv`")
lines.append("- See `run.json` in this directory for the full machine-readable record.")
lines.append("")
return "\n".join(lines)
# ---------------------------------------------------------------------------
# Orchestrator — spawn a forked AIAgent for the LLM review pass
# ---------------------------------------------------------------------------
def _render_candidate_list() -> str:
"""Human/agent-readable list of agent-created skills with usage stats."""
rows = skill_usage.agent_created_report()
if not rows:
return "No agent-created skills to review."
lines = [f"Agent-created skills ({len(rows)}):\n"]
for r in rows:
lines.append(
f"- {r['name']} "
f"state={r['state']} "
f"pinned={'yes' if r.get('pinned') else 'no'} "
f"use={r.get('use_count', 0)} "
f"view={r.get('view_count', 0)} "
f"patches={r.get('patch_count', 0)} "
f"last_used={r.get('last_used_at') or 'never'}"
)
return "\n".join(lines)
def run_curator_review(
on_summary: Optional[Callable[[str], None]] = None,
synchronous: bool = False,
) -> Dict[str, Any]:
"""Execute a single curator review pass.
Steps:
1. Apply automatic state transitions (pure, no LLM).
2. If there are agent-created skills, spawn a forked AIAgent that runs
the LLM review prompt against the current candidate list.
3. Update .curator_state with last_run_at and a one-line summary.
4. Invoke *on_summary* with a user-visible description.
If *synchronous* is True, the LLM review runs in the calling thread; the
default is to spawn a daemon thread so the caller returns immediately.
"""
start = datetime.now(timezone.utc)
counts = apply_automatic_transitions(now=start)
auto_summary_parts = []
if counts["marked_stale"]:
auto_summary_parts.append(f"{counts['marked_stale']} marked stale")
if counts["archived"]:
auto_summary_parts.append(f"{counts['archived']} archived")
if counts["reactivated"]:
auto_summary_parts.append(f"{counts['reactivated']} reactivated")
auto_summary = ", ".join(auto_summary_parts) if auto_summary_parts else "no changes"
# Persist state before the LLM pass so a crash mid-review still records
# the run and doesn't immediately re-trigger.
state = load_state()
state["last_run_at"] = start.isoformat()
state["run_count"] = int(state.get("run_count", 0)) + 1
state["last_run_summary"] = f"auto: {auto_summary}"
save_state(state)
def _llm_pass():
nonlocal auto_summary
# Snapshot skill state BEFORE the LLM pass so the report can diff.
try:
before_report = skill_usage.agent_created_report()
except Exception:
before_report = []
before_names = {r.get("name") for r in before_report if isinstance(r, dict)}
llm_meta: Dict[str, Any] = {}
try:
candidate_list = _render_candidate_list()
if "No agent-created skills" in candidate_list:
final_summary = f"auto: {auto_summary}; llm: skipped (no candidates)"
llm_meta = {
"final": "",
"summary": "skipped (no candidates)",
"model": "",
"provider": "",
"tool_calls": [],
"error": None,
}
else:
prompt = f"{CURATOR_REVIEW_PROMPT}\n\n{candidate_list}"
llm_meta = _run_llm_review(prompt)
final_summary = (
f"auto: {auto_summary}; llm: {llm_meta.get('summary', 'no change')}"
)
except Exception as e:
logger.debug("Curator LLM pass failed: %s", e, exc_info=True)
final_summary = f"auto: {auto_summary}; llm: error ({e})"
llm_meta = {
"final": "",
"summary": f"error ({e})",
"model": "",
"provider": "",
"tool_calls": [],
"error": str(e),
}
elapsed = (datetime.now(timezone.utc) - start).total_seconds()
state2 = load_state()
state2["last_run_duration_seconds"] = elapsed
state2["last_run_summary"] = final_summary
# Write the per-run report. Runs in a best-effort try so a
# reporting bug never breaks the curator itself. Report path is
# recorded in state so `hermes curator status` can point at it.
try:
after_report = skill_usage.agent_created_report()
except Exception:
after_report = []
try:
report_path = _write_run_report(
started_at=start,
elapsed_seconds=elapsed,
auto_counts=counts,
auto_summary=auto_summary,
before_report=before_report,
before_names=before_names,
after_report=after_report,
llm_meta=llm_meta,
)
if report_path is not None:
state2["last_report_path"] = str(report_path)
except Exception as e:
logger.debug("Curator report write failed: %s", e, exc_info=True)
save_state(state2)
if on_summary:
try:
on_summary(f"curator: {final_summary}")
except Exception:
pass
if synchronous:
_llm_pass()
else:
t = threading.Thread(target=_llm_pass, daemon=True, name="curator-review")
t.start()
return {
"started_at": start.isoformat(),
"auto_transitions": counts,
"summary_so_far": auto_summary,
}
def _run_llm_review(prompt: str) -> Dict[str, Any]:
"""Spawn an AIAgent fork to run the curator review prompt.
Returns a dict with:
- final: full (untruncated) final response from the reviewer
- summary: short summary suitable for state file (240-char cap)
- model, provider: what the fork actually ran on
- tool_calls: list of {name, arguments} for every tool call made during
the pass (arguments may be truncated for readability)
- error: set if the pass failed mid-run; final/summary may still be empty
Never raises; callers get a structured failure instead.
"""
import contextlib
result_meta: Dict[str, Any] = {
"final": "",
"summary": "",
"model": "",
"provider": "",
"tool_calls": [],
"error": None,
}
try:
from run_agent import AIAgent
except Exception as e:
result_meta["error"] = f"AIAgent import failed: {e}"
result_meta["summary"] = result_meta["error"]
return result_meta
# Resolve provider + model the same way the CLI does, so the curator
# fork inherits the user's active main config rather than falling
# through to an empty provider/model pair (which sends HTTP 400
# "No models provided"). AIAgent() without explicit provider/model
# arguments hits an auto-resolution path that fails for OAuth-only
# providers and for pool-backed credentials.
_api_key = None
_base_url = None
_api_mode = None
_resolved_provider = None
_model_name = ""
try:
from hermes_cli.config import load_config
from hermes_cli.runtime_provider import resolve_runtime_provider
_cfg = load_config()
_m = _cfg.get("model", {}) if isinstance(_cfg.get("model"), dict) else {}
_provider = _m.get("provider") or "auto"
_model_name = _m.get("default") or _m.get("model") or ""
_rp = resolve_runtime_provider(
requested=_provider, target_model=_model_name
)
_api_key = _rp.get("api_key")
_base_url = _rp.get("base_url")
_api_mode = _rp.get("api_mode")
_resolved_provider = _rp.get("provider") or _provider
except Exception as e:
logger.debug("Curator provider resolution failed: %s", e, exc_info=True)
result_meta["model"] = _model_name
result_meta["provider"] = _resolved_provider or ""
review_agent = None
try:
review_agent = AIAgent(
model=_model_name,
provider=_resolved_provider,
api_key=_api_key,
base_url=_base_url,
api_mode=_api_mode,
# Umbrella-building over a large skill collection is worth a
# high iteration ceiling — the pass typically takes 50-100
# API calls against hundreds of candidate skills. The
# single-session review path caps itself at a much smaller
# number because it's not doing a curation sweep.
max_iterations=9999,
quiet_mode=True,
platform="curator",
skip_context_files=True,
skip_memory=True,
)
# Disable recursive nudges — the curator must never spawn its own review.
review_agent._memory_nudge_interval = 0
review_agent._skill_nudge_interval = 0
# Redirect the forked agent's stdout/stderr to /dev/null while it
# runs so its tool-call chatter doesn't pollute the foreground
# terminal. The background-thread runner also hides it; this
# belt-and-suspenders path matters when a caller invokes
# run_curator_review(synchronous=True) from the CLI.
with open(os.devnull, "w") as _devnull, \
contextlib.redirect_stdout(_devnull), \
contextlib.redirect_stderr(_devnull):
conv_result = review_agent.run_conversation(user_message=prompt)
final = ""
if isinstance(conv_result, dict):
final = str(conv_result.get("final_response") or "").strip()
result_meta["final"] = final
result_meta["summary"] = (final[:240] + "") if len(final) > 240 else (final or "no change")
# Collect tool calls for the report. Walk the forked agent's
# session messages and extract every tool_call made during the
# pass. Truncate argument payloads so a giant skill_manage create
# doesn't blow up the report.
_calls: List[Dict[str, Any]] = []
for msg in getattr(review_agent, "_session_messages", []) or []:
if not isinstance(msg, dict):
continue
tcs = msg.get("tool_calls") or []
for tc in tcs:
if not isinstance(tc, dict):
continue
fn = tc.get("function") or {}
name = fn.get("name") or ""
args_raw = fn.get("arguments") or ""
if isinstance(args_raw, str) and len(args_raw) > 400:
args_raw = args_raw[:400] + ""
_calls.append({"name": name, "arguments": args_raw})
result_meta["tool_calls"] = _calls
except Exception as e:
result_meta["error"] = f"error: {e}"
result_meta["summary"] = result_meta["error"]
finally:
if review_agent is not None:
try:
review_agent.close()
except Exception:
pass
return result_meta
# ---------------------------------------------------------------------------
# Public entrypoint for the session-start hook
# ---------------------------------------------------------------------------
def maybe_run_curator(
*,
idle_for_seconds: Optional[float] = None,
on_summary: Optional[Callable[[str], None]] = None,
) -> Optional[Dict[str, Any]]:
"""Best-effort: run a curator pass if all gates pass. Returns the result
dict if a pass was started, else None. Never raises."""
try:
if not should_run_now():
return None
# Idle gating: only enforce when the caller provided a measurement.
if idle_for_seconds is not None:
min_idle_s = get_min_idle_hours() * 3600.0
if idle_for_seconds < min_idle_s:
return None
return run_curator_review(on_summary=on_summary)
except Exception as e:
logger.debug("maybe_run_curator failed: %s", e, exc_info=True)
return None
-32
View File
@@ -42,7 +42,6 @@ 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
@@ -91,7 +90,6 @@ class ClassifiedError:
_BILLING_PATTERNS = [
"insufficient credits",
"insufficient_quota",
"insufficient balance",
"credit balance",
"credits have been exhausted",
"top up your credits",
@@ -149,20 +147,6 @@ _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",
@@ -687,15 +671,6 @@ 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(
@@ -823,13 +798,6 @@ 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
+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,
+1 -1
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
+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():
-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
+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.
"""
+47 -111
View File
@@ -46,13 +46,11 @@ def _resolve_requests_verify() -> bool | str:
# 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", "stepfun", "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",
@@ -61,9 +59,7 @@ _PROVIDER_PREFIXES: frozenset[str] = frozenset({
"ollama",
"stepfun", "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",
@@ -110,11 +106,9 @@ _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 +143,10 @@ 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-5.5 (launched Apr 23 2026). 400k is the fallback for providers we
# can't probe live. ChatGPT Codex OAuth actually caps lower (272k as of
# Apr 2026) and is resolved via _resolve_codex_oauth_context_length().
"gpt-5.5": 400000,
"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)
@@ -169,17 +162,7 @@ DEFAULT_CONTEXT_LENGTHS = {
"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 +193,6 @@ 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
@@ -313,8 +294,6 @@ _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",
}
@@ -625,6 +604,8 @@ 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
@@ -708,29 +689,6 @@ 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
@@ -1014,7 +972,10 @@ 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}")
@@ -1232,14 +1193,12 @@ 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)
@@ -1253,33 +1212,13 @@ def get_model_context_length(
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
@@ -1298,42 +1237,34 @@ def get_model_context_length(
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
# 2. Active endpoint metadata for truly custom/unknown endpoints.
# Known providers (Copilot, OpenAI, Anthropic, etc.) skip this — their
# /models endpoint may report a provider-imposed limit (e.g. Copilot
# 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 +1282,19 @@ 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,
@@ -1391,12 +1334,6 @@ def get_model_context_length(
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 +1343,7 @@ 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).
@@ -1423,8 +1360,7 @@ 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 — 128K
-1
View File
@@ -149,7 +149,6 @@ PROVIDER_TO_MODELS_DEV: Dict[str, str] = {
"stepfun": "stepfun",
"kimi-coding-cn": "kimi-for-coding",
"minimax": "minimax",
"minimax-oauth": "minimax",
"minimax-cn": "minimax-cn",
"deepseek": "deepseek",
"alibaba": "alibaba",
+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",
]
-38
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. "
@@ -310,10 +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 "
@@ -432,29 +422,6 @@ 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."
),
}
# ---------------------------------------------------------------------------
@@ -858,11 +825,6 @@ 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 "
+6 -58
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:
@@ -309,7 +257,7 @@ 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.
Disabled when security.redact_secrets is false in config.yaml.
"""
if text is None:
return None
+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)
# ---------------------------------------------------------------------------
+109 -10
View File
@@ -7,15 +7,11 @@ can invoke skills via /skill-name commands.
import json
import logging
import re
import subprocess
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__)
@@ -24,6 +20,111 @@ _skill_commands: Dict[str, Dict[str, Any]] = {}
_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)\}")
# 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 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 _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)."""
raw_identifier = (skill_identifier or "").strip()
@@ -42,9 +143,7 @@ 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
@@ -329,7 +428,7 @@ def build_skill_invocation_message(
loaded_skill, skill_dir, skill_name = loaded
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(
@@ -368,7 +467,7 @@ def build_preloaded_skills_prompt(
loaded_skill, skill_dir, skill_name = loaded
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
+1 -9
View File
@@ -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:
+5 -39
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 ""
@@ -59,7 +41,6 @@ def generate_title(
max_tokens=500,
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",
)
+2 -7
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()
+6 -129
View File
@@ -12,84 +12,12 @@ 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
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}
normalized_model = (model or "").strip().lower()
if normalized_model.startswith("google/"):
normalized_model = normalized_model.split("/", 1)[1]
# 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'.
@@ -103,15 +31,15 @@ class ChatCompletionsTransport(ProviderTransport):
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.
Strips Codex Responses API fields (``codex_reasoning_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:
if "codex_reasoning_items" in msg:
needs_sanitize = True
break
tool_calls = msg.get("tool_calls")
@@ -131,7 +59,6 @@ class ChatCompletionsTransport(ProviderTransport):
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:
@@ -173,7 +100,6 @@ class ChatCompletionsTransport(ProviderTransport):
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
@@ -187,7 +113,6 @@ class ChatCompletionsTransport(ProviderTransport):
# 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
@@ -262,7 +187,6 @@ class ChatCompletionsTransport(ProviderTransport):
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:
@@ -294,41 +218,12 @@ class ChatCompletionsTransport(ProviderTransport):
_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:
@@ -344,9 +239,8 @@ class ChatCompletionsTransport(ProviderTransport):
"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):
# Reasoning
if params.get("supports_reasoning", False):
if is_github_models:
gh_reasoning = params.get("github_reasoning_extra")
if gh_reasoning is not None:
@@ -382,23 +276,6 @@ class ChatCompletionsTransport(ProviderTransport):
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:
+3 -21
View File
@@ -8,7 +8,7 @@ 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
from agent.transports.types import NormalizedResponse, ToolCall, Usage
class ResponsesApiTransport(ProviderTransport):
@@ -120,24 +120,6 @@ class ResponsesApiTransport(ProviderTransport):
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
@@ -151,6 +133,8 @@ class ResponsesApiTransport(ProviderTransport):
"""Normalize Codex Responses API response to NormalizedResponse."""
from agent.codex_responses_adapter import (
_normalize_codex_response,
_extract_responses_message_text,
_extract_responses_reasoning_text,
)
# _normalize_codex_response returns (SimpleNamespace, finish_reason_str)
@@ -176,8 +160,6 @@ class ResponsesApiTransport(ProviderTransport):
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
+1 -6
View File
@@ -97,7 +97,7 @@ class NormalizedResponse:
Response-level ``provider_data`` examples:
* Anthropic: ``{"reasoning_details": [...]}``
* Codex: ``{"codex_reasoning_items": [...], "codex_message_items": [...]}``
* Codex: ``{"codex_reasoning_items": [...]}``
* Others: ``None``
"""
@@ -126,11 +126,6 @@ class NormalizedResponse:
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
-21
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")
+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}")
+17 -48
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"
@@ -180,11 +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.
@@ -610,7 +606,6 @@ platform_toolsets:
signal: [hermes-signal]
homeassistant: [hermes-homeassistant]
qqbot: [hermes-qqbot]
yuanbao: [hermes-yuanbao]
# =============================================================================
# Gateway Platform Settings
@@ -795,16 +790,9 @@ 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)
@@ -829,9 +817,7 @@ 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)
@@ -845,19 +831,12 @@ 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).
@@ -873,22 +852,17 @@ 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
# ───────────────────────────────────────────────────────────────────────────
@@ -898,15 +872,10 @@ 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):
@@ -932,7 +901,7 @@ 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
+404 -837
View File
File diff suppressed because it is too large Load Diff
+7 -57
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:
@@ -432,7 +417,6 @@ 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]:
@@ -454,9 +438,6 @@ 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.
@@ -500,14 +481,6 @@ def create_job(
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 = {
"id": job_id,
@@ -519,7 +492,6 @@ 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": {
@@ -713,32 +685,10 @@ 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"
@@ -872,7 +822,7 @@ 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:
+11 -119
View File
@@ -77,7 +77,7 @@ _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
@@ -198,9 +198,7 @@ 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:
@@ -233,32 +231,12 @@ def _resolve_single_delivery_target(job: dict, deliver_value: str) -> Optional[d
}
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:
@@ -359,7 +337,6 @@ def _deliver_result(job: dict, content: str, adapters=None, loop=None) -> Option
"sms": Platform.SMS,
"bluebubbles": Platform.BLUEBUBBLES,
"qqbot": Platform.QQBOT,
"yuanbao": Platform.YUANBAO,
}
# Optionally wrap the content with a header/footer so the user knows this
@@ -694,51 +671,10 @@ 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 "
@@ -774,7 +710,7 @@ def _build_job_prompt(job: dict, prerun_script: Optional[tuple] = None) -> str:
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,
]
@@ -782,7 +718,7 @@ 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)}']"
@@ -844,8 +780,6 @@ 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.
@@ -1033,12 +967,10 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
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.
# When a workdir is configured, inject AGENTS.md / CLAUDE.md /
# .cursorrules from that directory; otherwise preserve the old
# behaviour (don't inject SOUL.md/AGENTS.md from the scheduler cwd).
skip_context_files=not bool(_job_workdir),
load_soul_identity=True,
skip_memory=True, # Cron system prompts would corrupt user representations
platform="cron",
session_id=_cron_session_id,
@@ -1053,18 +985,7 @@ 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)
@@ -1207,24 +1128,6 @@ 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:
@@ -1364,17 +1267,6 @@ def tick(verbose: bool = True, adapters=None, loop=None) -> int:
_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)
return sum(_results)
finally:
if fcntl:
+7 -9
View File
@@ -41,15 +41,6 @@ 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
@@ -76,6 +67,13 @@ if [ ! -f "$HERMES_HOME/config.yaml" ]; then
cp "$INSTALL_DIR/cli-config.yaml.example" "$HERMES_HOME/config.yaml"
fi
# Ensure the main config file remains accessible to the hermes runtime user
# even if it was edited on the host after initial ownership setup.
if [ -f "$HERMES_HOME/config.yaml" ]; then
chown hermes:hermes "$HERMES_HOME/config.yaml"
chmod 640 "$HERMES_HOME/config.yaml"
fi
# SOUL.md
if [ ! -f "$HERMES_HOME/SOUL.md" ]; then
cp "$INSTALL_DIR/docker/SOUL.md" "$HERMES_HOME/SOUL.md"
-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 -67
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)
@@ -136,66 +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]]:
@@ -268,14 +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")
+6 -92
View File
@@ -67,7 +67,6 @@ class Platform(Enum):
WEIXIN = "weixin"
BLUEBUBBLES = "bluebubbles"
QQBOT = "qqbot"
YUANBAO = "yuanbao"
@dataclass
@@ -136,7 +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"),
)
@@ -179,7 +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,
@@ -196,14 +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 {
@@ -212,7 +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
@@ -225,9 +215,6 @@ class StreamingConfig:
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=float(
data.get("fresh_final_after_seconds", 60.0)
),
)
@@ -327,9 +314,6 @@ class GatewayConfig:
# 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)
# Yuanbao uses extra dict for app credentials
elif platform == Platform.YUANBAO and config.extra.get("app_id") and config.extra.get("app_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")
@@ -451,7 +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),
@@ -566,8 +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
@@ -588,8 +570,6 @@ def load_gateway_config() -> GatewayConfig:
)
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:
@@ -604,7 +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"]
@@ -612,21 +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)
@@ -634,8 +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")
@@ -714,11 +687,6 @@ 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()
if "group_allowed_chats" in telegram_cfg and not os.getenv("TELEGRAM_GROUP_ALLOWED_USERS"):
gac = telegram_cfg["group_allowed_chats"]
if isinstance(gac, list):
gac = ",".join(str(v) for v in gac)
os.environ["TELEGRAM_GROUP_ALLOWED_USERS"] = str(gac)
if "disable_link_previews" in telegram_cfg:
plat_data = platforms_data.setdefault(Platform.TELEGRAM.value, {})
if not isinstance(plat_data, dict):
@@ -945,20 +913,8 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
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:
@@ -1315,48 +1271,6 @@ def _apply_env_overrides(config: GatewayConfig) -> None:
name=os.getenv("QQBOT_HOME_CHANNEL_NAME") or os.getenv(qq_home_name_env, "Home"),
)
# 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"),
)
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:
+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,
+12 -6
View File
@@ -52,13 +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:
"""
+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:
-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",
]
+69 -357
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
@@ -589,11 +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
@@ -812,51 +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)
@@ -981,62 +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,
@@ -1044,8 +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,
))
@@ -1160,8 +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])
@@ -1282,12 +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
@@ -1349,60 +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
@@ -1412,7 +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:
@@ -1669,18 +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,
@@ -1693,24 +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
@@ -1726,22 +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
@@ -2371,31 +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
@@ -2460,6 +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")
@@ -2507,49 +2351,17 @@ 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():
r = agent.run_conversation(
user_message=user_message,
@@ -2572,36 +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",
@@ -2617,11 +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:
@@ -2631,21 +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)
@@ -2695,46 +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:
@@ -2749,17 +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
@@ -2779,7 +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)
@@ -2795,9 +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:
+19 -345
View File
@@ -148,102 +148,7 @@ def _detect_macos_system_proxy() -> str | None:
return None
def _split_host_port(value: str) -> tuple[str, int | None]:
raw = str(value or "").strip()
if not raw:
return "", None
if "://" in raw:
parsed = urlsplit(raw)
return (parsed.hostname or "").lower().rstrip("."), parsed.port
if raw.startswith("[") and "]" in raw:
host, _, rest = raw[1:].partition("]")
port = None
if rest.startswith(":") and rest[1:].isdigit():
port = int(rest[1:])
return host.lower().rstrip("."), port
if raw.count(":") == 1:
host, _, maybe_port = raw.rpartition(":")
if maybe_port.isdigit():
return host.lower().rstrip("."), int(maybe_port)
return raw.lower().strip("[]").rstrip("."), None
def _no_proxy_entries() -> list[str]:
entries: list[str] = []
for key in ("NO_PROXY", "no_proxy"):
raw = os.environ.get(key, "")
entries.extend(part.strip() for part in raw.split(",") if part.strip())
return entries
def _no_proxy_entry_matches(entry: str, host: str, port: int | None = None) -> bool:
token = str(entry or "").strip().lower()
if not token:
return False
if token == "*":
return True
token_host, token_port = _split_host_port(token)
if token_port is not None and port is not None and token_port != port:
return False
if token_port is not None and port is None:
return False
if not token_host:
return False
try:
network = ipaddress.ip_network(token_host, strict=False)
try:
return ipaddress.ip_address(host) in network
except ValueError:
return False
except ValueError:
pass
try:
token_ip = ipaddress.ip_address(token_host)
try:
return ipaddress.ip_address(host) == token_ip
except ValueError:
return False
except ValueError:
pass
if token_host.startswith("*."):
suffix = token_host[1:]
return host.endswith(suffix)
if token_host.startswith("."):
return host == token_host[1:] or host.endswith(token_host)
return host == token_host or host.endswith(f".{token_host}")
def should_bypass_proxy(target_hosts: str | list[str] | tuple[str, ...] | set[str] | None) -> bool:
"""Return True when NO_PROXY/no_proxy matches at least one target host.
Supports exact hosts, domain suffixes, wildcard suffixes, IP literals,
CIDR ranges, optional host:port entries, and ``*``.
"""
entries = _no_proxy_entries()
if not entries or not target_hosts:
return False
if isinstance(target_hosts, str):
candidates = [target_hosts]
else:
candidates = list(target_hosts)
for candidate in candidates:
host, port = _split_host_port(str(candidate))
if not host:
continue
if any(_no_proxy_entry_matches(entry, host, port) for entry in entries):
return True
return False
def resolve_proxy_url(
platform_env_var: str | None = None,
*,
target_hosts: str | list[str] | tuple[str, ...] | set[str] | None = None,
) -> str | None:
def resolve_proxy_url(platform_env_var: str | None = None) -> str | None:
"""Return a proxy URL from env vars, or macOS system proxy.
Check order:
@@ -251,26 +156,18 @@ def resolve_proxy_url(
1. HTTPS_PROXY / HTTP_PROXY / ALL_PROXY (and lowercase variants)
2. macOS system proxy via ``scutil --proxy`` (auto-detect)
Returns *None* if no proxy is found, or if NO_PROXY/no_proxy matches one
of ``target_hosts``.
Returns *None* if no proxy is found.
"""
if platform_env_var:
value = (os.environ.get(platform_env_var) or "").strip()
if value:
if should_bypass_proxy(target_hosts):
return None
return normalize_proxy_url(value)
for key in ("HTTPS_PROXY", "HTTP_PROXY", "ALL_PROXY",
"https_proxy", "http_proxy", "all_proxy"):
value = (os.environ.get(key) or "").strip()
if value:
if should_bypass_proxy(target_hosts):
return None
return normalize_proxy_url(value)
detected = normalize_proxy_url(_detect_macos_system_proxy())
if detected and should_bypass_proxy(target_hosts):
return None
return detected
return normalize_proxy_url(_detect_macos_system_proxy())
def proxy_kwargs_for_bot(proxy_url: str | None) -> dict:
@@ -307,14 +204,9 @@ def proxy_kwargs_for_aiohttp(proxy_url: str | None) -> tuple[dict, dict]:
"""Build kwargs for standalone ``aiohttp.ClientSession`` with proxy.
Returns ``(session_kwargs, request_kwargs)`` where:
- With aiohttp-socks ``({"connector": ProxyConnector(...)}, {})``
for *all* proxy schemes (SOCKS **and** HTTP/HTTPS).
- HTTP without aiohttp-socks ``({}, {"proxy": url})``.
- None ``({}, {})``.
Prefer the connector path: it works transparently with libraries
(like mautrix) that call ``session.request()`` without forwarding
per-request ``proxy=`` kwargs.
- SOCKS ``({"connector": ProxyConnector(...)}, {})``
- HTTP ``({}, {"proxy": url})``
- None ``({}, {})``
Usage::
@@ -325,53 +217,20 @@ def proxy_kwargs_for_aiohttp(proxy_url: str | None) -> tuple[dict, dict]:
"""
if not proxy_url:
return {}, {}
try:
from aiohttp_socks import ProxyConnector
if proxy_url.lower().startswith("socks"):
try:
from aiohttp_socks import ProxyConnector
connector = ProxyConnector.from_url(proxy_url, rdns=True)
return {"connector": connector}, {}
except ImportError:
if proxy_url.lower().startswith("socks"):
connector = ProxyConnector.from_url(proxy_url, rdns=True)
return {"connector": connector}, {}
except ImportError:
logger.warning(
"aiohttp_socks not installed — SOCKS proxy %s ignored. "
"Run: pip install aiohttp-socks",
proxy_url,
)
return {}, {}
return {}, {"proxy": proxy_url}
def is_host_excluded_by_no_proxy(hostname: str, no_proxy_value: str | None = None) -> bool:
"""Return True when ``hostname`` matches a ``NO_PROXY`` entry.
Supports comma- or whitespace-separated entries with optional leading dots
and ``*.`` wildcards, which match both the apex domain and subdomains.
"""
raw = no_proxy_value
if raw is None:
raw = os.environ.get("NO_PROXY") or os.environ.get("no_proxy") or ""
raw = raw.strip()
if not raw:
return False
lower_hostname = hostname.lower()
for entry in re.split(r"[\s,]+", raw):
normalized = entry.strip().lower()
if not normalized:
continue
if normalized == "*":
return True
if normalized.startswith("*."):
normalized = normalized[2:]
elif normalized.startswith("."):
normalized = normalized[1:]
if lower_hostname == normalized or lower_hostname.endswith(f".{normalized}"):
return True
return False
return {}, {"proxy": proxy_url}
from dataclasses import dataclass, field
@@ -731,15 +590,7 @@ SUPPORTED_DOCUMENT_TYPES = {
".pdf": "application/pdf",
".md": "text/markdown",
".txt": "text/plain",
".csv": "text/csv",
".log": "text/plain",
".json": "application/json",
".xml": "application/xml",
".yaml": "application/yaml",
".yml": "application/yaml",
".toml": "application/toml",
".ini": "text/plain",
".cfg": "text/plain",
".zip": "application/zip",
".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
@@ -907,41 +758,6 @@ class MessageEvent:
return args
_PLAINTEXT_GATEWAY_RESTART_PATTERNS: tuple[re.Pattern[str], ...] = (
re.compile(r"^(?:please\s+)?restart\s+(?:the\s+)?gateway[.!?\s]*$", re.IGNORECASE),
re.compile(r"^(?:please\s+)?restart\s+(?:the\s+)?hermes\s+gateway[.!?\s]*$", re.IGNORECASE),
re.compile(r"^(?:please\s+)?restart\s+hermes[.!?\s]*$", re.IGNORECASE),
)
def coerce_plaintext_gateway_command(event: "MessageEvent") -> None:
"""Rewrite a tiny set of DM plaintext admin phrases into slash commands.
This keeps high-impact operational phrases like ``restart gateway`` out of
the LLM/tool path, where they can trigger a self-restart from inside the
currently running agent and leave the gateway stuck in ``draining`` while it
waits for that same agent to finish.
Scope is intentionally narrow: DM text messages only, exact restart-style
phrases only. Group chats keep natural-language semantics.
"""
try:
if event is None or event.message_type != MessageType.TEXT:
return
text = (event.text or "").strip()
if not text or text.startswith("/"):
return
source = getattr(event, "source", None)
if getattr(source, "chat_type", None) != "dm":
return
for pattern in _PLAINTEXT_GATEWAY_RESTART_PATTERNS:
if pattern.match(text):
event.text = "/restart"
return
except Exception:
return
@dataclass
class SendResult:
"""Result of sending a message."""
@@ -1063,61 +879,6 @@ def resolve_channel_prompt(
return None
def resolve_channel_skills(
config_extra: dict,
channel_id: str,
parent_id: str | None = None,
) -> list[str] | None:
"""Resolve auto-loaded skill(s) for a channel/thread from platform config.
Looks up ``channel_skill_bindings`` in the adapter's ``config.extra`` dict.
Config format::
channel_skill_bindings:
- id: "C0123" # Slack channel ID or Discord channel/forum ID
skills: ["skill-a", "skill-b"]
- id: "D0ABCDE"
skill: "solo-skill" # single string also accepted
Prefers an exact match on *channel_id*; falls back to *parent_id*
(useful for forum threads / Slack threads inheriting the parent channel's
binding).
Returns a deduplicated list of skill names (order preserved), or None if
no match is found.
"""
bindings = config_extra.get("channel_skill_bindings") or []
if not isinstance(bindings, list) or not bindings:
return None
ids_to_check: set[str] = set()
if channel_id:
ids_to_check.add(str(channel_id))
if parent_id:
ids_to_check.add(str(parent_id))
if not ids_to_check:
return None
for entry in bindings:
if not isinstance(entry, dict):
continue
entry_id = str(entry.get("id", ""))
if entry_id in ids_to_check:
skills = entry.get("skills") or entry.get("skill")
if isinstance(skills, str):
s = skills.strip()
return [s] if s else None
if isinstance(skills, list) and skills:
seen: list[str] = []
for name in skills:
if not isinstance(name, str):
continue
nm = name.strip()
if nm and nm not in seen:
seen.append(nm)
return seen or None
return None
class BasePlatformAdapter(ABC):
"""
Base class for platform adapters.
@@ -1161,20 +922,7 @@ class BasePlatformAdapter(ABC):
self._post_delivery_callbacks: Dict[str, Any] = {}
self._expected_cancelled_tasks: set[asyncio.Task] = set()
self._busy_session_handler: Optional[Callable[[MessageEvent, str], Awaitable[bool]]] = None
# Auto-TTS on voice input: ``_auto_tts_default`` is the global default
# (``voice.auto_tts`` in config.yaml, pushed by GatewayRunner on connect).
# Per-chat overrides live in two sets populated from ``_voice_mode``:
# - ``_auto_tts_enabled_chats``: chat explicitly opted in via ``/voice on``
# or ``/voice tts`` (mode is ``voice_only`` or ``all``). Fires even when
# the global default is False.
# - ``_auto_tts_disabled_chats``: chat explicitly opted out via
# ``/voice off`` (mode is ``off``). Suppresses auto-TTS even when the
# global default is True.
# The gate in _process_message() is:
# fire if chat in _auto_tts_enabled_chats
# OR (_auto_tts_default and chat not in _auto_tts_disabled_chats)
self._auto_tts_default: bool = False
self._auto_tts_enabled_chats: set = set()
# Chats where auto-TTS on voice input is disabled (set by /voice off)
self._auto_tts_disabled_chats: set = set()
# Chats where typing indicator is paused (e.g. during approval waits).
# _keep_typing skips send_typing when the chat_id is in this set.
@@ -1196,21 +944,6 @@ class BasePlatformAdapter(ABC):
def fatal_error_retryable(self) -> bool:
return self._fatal_error_retryable
def _should_auto_tts_for_chat(self, chat_id: str) -> bool:
"""Whether auto-TTS on voice input should fire for ``chat_id``.
Decision layers (Issue #16007):
1. Explicit ``/voice on`` or ``/voice tts`` always fire (even if
``voice.auto_tts`` is False).
2. Explicit ``/voice off`` never fire.
3. Fall back to the global ``voice.auto_tts`` config default.
"""
if chat_id in self._auto_tts_enabled_chats:
return True
if chat_id in self._auto_tts_disabled_chats:
return False
return bool(self._auto_tts_default)
def set_fatal_error_handler(self, handler: Callable[["BasePlatformAdapter"], Awaitable[None] | None]) -> None:
self._fatal_error_handler = handler
@@ -1394,27 +1127,6 @@ class BasePlatformAdapter(ABC):
"""
return SendResult(success=False, error="Not supported")
async def delete_message(
self,
chat_id: str,
message_id: str,
) -> bool:
"""
Delete a previously sent message. Optional platforms that don't
support deletion return ``False`` and callers fall back to leaving
the message in place.
Used by the stream consumer's fresh-final cleanup path (see
openclaw/openclaw#72038) to remove long-lived preview messages
after sending the completed reply as a fresh message so the
platform's visible timestamp reflects completion time.
Returns ``True`` on successful deletion, ``False`` otherwise.
Subclasses should override for platforms with a deletion API
(e.g. Telegram ``deleteMessage``).
"""
return False
async def send_typing(self, chat_id: str, metadata=None) -> None:
"""
Send a typing indicator.
@@ -1742,41 +1454,13 @@ class BasePlatformAdapter(ABC):
the agent is waiting for dangerous-command approval). This is critical
for Slack's Assistant API where ``assistant_threads_setStatus`` disables
the compose box pausing lets the user type ``/approve`` or ``/deny``.
Each ``send_typing`` call is bounded by a ~1.5s timeout so a slow
network round-trip can't stall the refresh cadence. Telegram- and
Discord-side typing expire after ~5s; if any individual send_typing
takes longer than the refresh interval, the bubble would die and
stay dead until that call returns. Abandoning the slow call lets
the next tick fire a fresh send_typing on schedule as long as
one of them succeeds within the 5s platform-side window, the bubble
stays visible across provider stalls / upstream API timeouts.
"""
# Bound each send_typing round-trip so the refresh cadence isn't
# gated on network health. Must stay below ``interval`` so a slow
# call gets abandoned before the next scheduled tick.
_send_typing_timeout = max(0.25, min(1.5, interval - 0.25))
try:
while True:
if stop_event is not None and stop_event.is_set():
return
if chat_id not in self._typing_paused:
try:
await asyncio.wait_for(
self.send_typing(chat_id, metadata=metadata),
timeout=_send_typing_timeout,
)
except asyncio.TimeoutError:
# Slow network — abandon this tick, keep the loop
# on schedule so the next send_typing fires fresh.
pass
except asyncio.CancelledError:
raise
except Exception as typing_err:
logger.debug(
"[%s] send_typing error (non-fatal): %s",
self.name, typing_err,
)
await self.send_typing(chat_id, metadata=metadata)
if stop_event is None:
await asyncio.sleep(interval)
continue
@@ -2228,8 +1912,6 @@ class BasePlatformAdapter(ABC):
"""
if not self._message_handler:
return
coerce_plaintext_gateway_command(event)
session_key = build_session_key(
event.source,
@@ -2429,14 +2111,12 @@ class BasePlatformAdapter(ABC):
logger.info("[%s] extract_local_files found %d file(s) in response", self.name, len(local_files))
# Auto-TTS: if voice message, generate audio FIRST (before sending text)
# Gated via ``_should_auto_tts_for_chat``: fires when the chat has
# an explicit ``/voice on|tts`` opt-in OR when ``voice.auto_tts`` is
# True globally and no ``/voice off`` has been issued.
# Skipped when the chat has voice mode disabled (/voice off)
_tts_path = None
if (self._should_auto_tts_for_chat(event.source.chat_id)
and event.message_type == MessageType.VOICE
if (event.message_type == MessageType.VOICE
and text_content
and not media_files):
and not media_files
and event.source.chat_id not in self._auto_tts_disabled_chats):
try:
from tools.tts_tool import text_to_speech_tool, check_tts_requirements
if check_tts_requirements():
@@ -2760,9 +2440,6 @@ class BasePlatformAdapter(ABC):
user_id_alt: Optional[str] = None,
chat_id_alt: Optional[str] = None,
is_bot: bool = False,
guild_id: Optional[str] = None,
parent_chat_id: Optional[str] = None,
message_id: Optional[str] = None,
) -> SessionSource:
"""Helper to build a SessionSource for this platform."""
# Normalize empty topic to None
@@ -2780,9 +2457,6 @@ class BasePlatformAdapter(ABC):
user_id_alt=user_id_alt,
chat_id_alt=chat_id_alt,
is_bot=is_bot,
guild_id=str(guild_id) if guild_id else None,
parent_chat_id=str(parent_chat_id) if parent_chat_id else None,
message_id=str(message_id) if message_id else None,
)
@abstractmethod
+2 -19
View File
@@ -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):
@@ -392,13 +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,
@@ -406,19 +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)
+23 -21
View File
@@ -305,7 +305,7 @@ class VoiceReceiver:
encrypted = bytes(payload_with_nonce[:-4])
try:
import nacl.secret # noqa: E402 — delayed import, only in voice path
import nacl.secret # noqa: delayed import only in voice path
box = nacl.secret.Aead(self._secret_key)
decrypted = box.decrypt(encrypted, header, bytes(nonce))
except Exception as e:
@@ -813,14 +813,7 @@ class DiscordAdapter(BasePlatformAdapter):
logger.info("[%s] Synced %d slash command(s) via bulk tree sync", self.name, len(synced))
return
# Discord's per-app command-management bucket is ~5 writes / 20 s,
# so a mass-prune-plus-upsert reconcile (e.g. 77 orphans + 30
# desired = 107 writes) takes several minutes of forced waits.
# A flat 30 s budget blew up reliably under bucket pressure and
# left slash commands broken for ~60 min until the bucket fully
# recovered. Use a wide ceiling; the cap still guards against a
# true hang. (#16713)
summary = await asyncio.wait_for(self._safe_sync_slash_commands(), timeout=600)
summary = await asyncio.wait_for(self._safe_sync_slash_commands(), timeout=30)
logger.info(
"[%s] Safely reconciled %d slash command(s): unchanged=%d updated=%d recreated=%d created=%d deleted=%d",
self.name,
@@ -832,11 +825,7 @@ class DiscordAdapter(BasePlatformAdapter):
summary["deleted"],
)
except asyncio.TimeoutError:
logger.warning(
"[%s] Slash command sync timed out — Discord rate-limit bucket "
"may be saturated; will retry on next reconnect",
self.name,
)
logger.warning("[%s] Slash command sync timed out after 30s", self.name)
except asyncio.CancelledError:
raise
except Exception as e: # pragma: no cover - defensive logging
@@ -2326,6 +2315,11 @@ class DiscordAdapter(BasePlatformAdapter):
async def slash_background(interaction: discord.Interaction, prompt: str):
await self._run_simple_slash(interaction, f"/background {prompt}", "Background task started~")
@tree.command(name="btw", description="Ephemeral side question using session context")
@discord.app_commands.describe(question="Your side question (no tools, not persisted)")
async def slash_btw(interaction: discord.Interaction, question: str):
await self._run_simple_slash(interaction, f"/btw {question}")
# ── Auto-register any gateway-available commands not yet on the tree ──
# This ensures new commands added to COMMAND_REGISTRY in
# hermes_cli/commands.py automatically appear as Discord slash
@@ -2690,8 +2684,21 @@ class DiscordAdapter(BasePlatformAdapter):
skills: ["skill-a", "skill-b"]
Also checks parent_id so forum threads inherit the forum's bindings.
"""
from gateway.platforms.base import resolve_channel_skills
return resolve_channel_skills(self.config.extra, channel_id, parent_id)
bindings = self.config.extra.get("channel_skill_bindings", [])
if not bindings:
return None
ids_to_check = {channel_id}
if parent_id:
ids_to_check.add(parent_id)
for entry in bindings:
entry_id = str(entry.get("id", ""))
if entry_id in ids_to_check:
skills = entry.get("skills") or entry.get("skill")
if isinstance(skills, str):
return [skills]
if isinstance(skills, list) and skills:
return list(dict.fromkeys(skills)) # dedup, preserve order
return None
def _resolve_channel_prompt(self, channel_id: str, parent_id: str | None = None) -> str | None:
"""Resolve a Discord per-channel prompt, preferring the exact channel over its parent."""
@@ -3254,7 +3261,6 @@ class DiscordAdapter(BasePlatformAdapter):
if auto_thread and not skip_thread and not is_voice_linked_channel and not is_reply_message:
thread = await self._auto_create_thread(message)
if thread:
parent_channel_id = str(message.channel.id)
is_thread = True
thread_id = str(thread.id)
auto_threaded_channel = thread
@@ -3305,7 +3311,6 @@ class DiscordAdapter(BasePlatformAdapter):
chat_topic = self._get_effective_topic(message.channel, is_thread=is_thread)
# Build source
guild = getattr(message, "guild", None)
source = self.build_source(
chat_id=str(effective_channel.id),
chat_name=chat_name,
@@ -3315,9 +3320,6 @@ class DiscordAdapter(BasePlatformAdapter):
thread_id=thread_id,
chat_topic=chat_topic,
is_bot=getattr(message.author, "bot", False),
guild_id=str(guild.id) if guild else None,
parent_chat_id=parent_channel_id,
message_id=str(message.id),
)
# Build media URLs -- download image attachments to local cache so the
-3
View File
@@ -28,7 +28,6 @@ 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
@@ -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
@@ -588,7 +586,6 @@ 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
+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()
+2 -11
View File
@@ -11,10 +11,10 @@ import logging
import re
import time
from pathlib import Path
from typing import TYPE_CHECKING, Dict
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__)
@@ -57,15 +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):
+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:
+1
View File
@@ -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"
+7 -2
View File
@@ -1957,7 +1957,7 @@ 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
@@ -1970,7 +1970,7 @@ 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
@@ -2135,6 +2135,11 @@ 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
+8 -287
View File
@@ -31,7 +31,6 @@ from gateway.platforms.base import (
BasePlatformAdapter,
MessageEvent,
MessageType,
ProcessingOutcome,
SendResult,
cache_image_from_bytes,
cache_audio_from_bytes,
@@ -163,10 +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)
@@ -493,11 +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 = []
@@ -551,9 +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 "",
@@ -561,9 +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",
@@ -722,159 +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
# ------------------------------------------------------------------
@@ -886,22 +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:
@@ -911,10 +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:
@@ -1138,110 +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)
async def on_processing_start(self, event: MessageEvent) -> None:
"""React with 👀 when processing begins."""
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 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
# ------------------------------------------------------------------
File diff suppressed because it is too large Load Diff
+15 -140
View File
@@ -84,7 +84,6 @@ from gateway.platforms.telegram_network import (
discover_fallback_ips,
parse_fallback_ip_env,
)
from utils import atomic_replace
def check_telegram_requirements() -> bool:
@@ -123,12 +122,12 @@ def _strip_mdv2(text: str) -> str:
# ---------------------------------------------------------------------------
# Markdown table → Telegram-friendly row groups
# Markdown table → code block conversion
# ---------------------------------------------------------------------------
# Telegram's MarkdownV2 has no table syntax — '|' is just an escaped literal,
# so pipe tables render as noisy backslash-pipe text with no alignment.
# Reformating each row into a bold heading plus bullet list keeps the content
# readable on mobile clients while preserving the source data.
# Wrapping the table in a fenced code block makes Telegram render it as
# monospace preformatted text with columns intact.
# Matches a GFM table delimiter row: optional outer pipes, cells containing
# only dashes (with optional leading/trailing colons for alignment) separated
@@ -145,49 +144,13 @@ def _is_table_row(line: str) -> bool:
return bool(stripped) and '|' in stripped
def _split_markdown_table_row(line: str) -> list[str]:
"""Split a simple GFM table row into stripped cell values."""
stripped = line.strip()
if stripped.startswith("|"):
stripped = stripped[1:]
if stripped.endswith("|"):
stripped = stripped[:-1]
return [cell.strip() for cell in stripped.split("|")]
def _render_table_block_for_telegram(table_block: list[str]) -> str:
"""Render a detected GFM table as Telegram-friendly row groups."""
if len(table_block) < 3:
return "\n".join(table_block)
headers = _split_markdown_table_row(table_block[0])
if len(headers) < 2:
return "\n".join(table_block)
rendered_rows: list[str] = []
for index, row in enumerate(table_block[2:], start=1):
cells = _split_markdown_table_row(row)
if len(cells) < len(headers):
cells.extend([""] * (len(headers) - len(cells)))
elif len(cells) > len(headers):
cells = cells[: len(headers)]
heading = next((cell for cell in cells if cell), f"Row {index}")
rendered_rows.append(f"**{heading}**")
rendered_rows.extend(
f"{header}: {value}" for header, value in zip(headers, cells)
)
return "\n\n".join(rendered_rows)
def _wrap_markdown_tables(text: str) -> str:
"""Rewrite GFM-style pipe tables into Telegram-friendly bullet groups.
"""Wrap GFM-style pipe tables in ``` fences so Telegram renders them.
Detected by a row containing '|' immediately followed by a delimiter
row matching :data:`_TABLE_SEPARATOR_RE`. Subsequent pipe-containing
non-blank lines are consumed as the table body and rewritten as
per-row bullet groups. Tables inside existing fenced code blocks are left
non-blank lines are consumed as the table body and included in the
wrapped block. Tables inside existing fenced code blocks are left
alone.
"""
if '|' not in text or '-' not in text:
@@ -224,7 +187,9 @@ def _wrap_markdown_tables(text: str) -> str:
while j < len(lines) and _is_table_row(lines[j]):
table_block.append(lines[j])
j += 1
out.append(_render_table_block_for_telegram(table_block))
out.append('```')
out.extend(table_block)
out.append('```')
i = j
continue
@@ -369,49 +334,6 @@ class TelegramAdapter(BasePlatformAdapter):
return {"link_preview_options": LinkPreviewOptions(is_disabled=True)}
return {"disable_web_page_preview": True}
async def _drain_polling_connections(self) -> None:
"""Reset the httpx connection pool used for getUpdates polling.
Network errors (especially through proxies like sing-box) can leave
httpx connections in a half-closed state that still occupy pool slots.
After enough reconnect cycles the pool fills up entirely, causing
``Pool timeout: All connections in the connection pool are occupied.``
We reset ONLY ``_request[0]`` (the getUpdates request) the general
request (``_request[1]``) is left untouched so concurrent
``send_message`` / ``edit_message`` calls are never interrupted.
Implementation note: accesses ``Bot._request[0]`` which is the
get-updates ``BaseRequest`` in the PTB 22.x internal tuple
``(get_updates_request, general_request)``. There is no public
accessor for the polling request; review if upgrading to PTB 23+.
"""
if not (self._app and self._app.bot):
return
try:
# PTB 22.x: _request is a (get_updates, general) tuple;
# no public accessor exists for the polling request.
polling_req = self._app.bot._request[0] # noqa: SLF001
except Exception:
return
try:
await polling_req.shutdown()
except Exception:
logger.debug(
"[%s] Polling request shutdown failed (non-fatal)",
self.name, exc_info=True,
)
try:
await polling_req.initialize()
logger.debug(
"[%s] Polling request pool drained before reconnect", self.name
)
except Exception:
logger.debug(
"[%s] Polling request re-initialize failed (non-fatal)",
self.name, exc_info=True,
)
async def _handle_polling_network_error(self, error: Exception) -> None:
"""Reconnect polling after a transient network interruption.
@@ -457,8 +379,6 @@ class TelegramAdapter(BasePlatformAdapter):
except Exception:
pass
await self._drain_polling_connections()
try:
await self._app.updater.start_polling(
allowed_updates=Update.ALL_TYPES,
@@ -506,7 +426,6 @@ class TelegramAdapter(BasePlatformAdapter):
except Exception:
pass
await asyncio.sleep(RETRY_DELAY)
await self._drain_polling_connections()
try:
await self._app.updater.start_polling(
allowed_updates=Update.ALL_TYPES,
@@ -635,7 +554,7 @@ class TelegramAdapter(BasePlatformAdapter):
_yaml.dump(config, f, default_flow_style=False, sort_keys=False)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, config_path)
os.replace(tmp_path, config_path)
except BaseException:
try:
os.unlink(tmp_path)
@@ -784,6 +703,7 @@ class TelegramAdapter(BasePlatformAdapter):
"write_timeout": _env_float("HERMES_TELEGRAM_HTTP_WRITE_TIMEOUT", 20.0),
}
proxy_url = resolve_proxy_url("TELEGRAM_PROXY")
disable_fallback = (os.getenv("HERMES_TELEGRAM_DISABLE_FALLBACK_IPS", "").strip().lower() in ("1", "true", "yes", "on"))
fallback_ips = self._fallback_ips()
if not fallback_ips:
@@ -794,8 +714,6 @@ class TelegramAdapter(BasePlatformAdapter):
", ".join(fallback_ips),
)
proxy_targets = ["api.telegram.org", *fallback_ips]
proxy_url = resolve_proxy_url("TELEGRAM_PROXY", target_hosts=proxy_targets)
if fallback_ips and not proxy_url and not disable_fallback:
logger.info(
"[%s] Telegram fallback IPs active: %s",
@@ -1290,31 +1208,6 @@ class TelegramAdapter(BasePlatformAdapter):
)
return SendResult(success=False, error=str(e))
async def delete_message(self, chat_id: str, message_id: str) -> bool:
"""Delete a previously sent Telegram message.
Used by the stream consumer's fresh-final cleanup path (ported
from openclaw/openclaw#72038) to remove long-lived preview
messages after sending the completed reply as a fresh message.
Telegram's Bot API ``deleteMessage`` works for bot-posted
messages in the last 48 hours. Failures are non-fatal the
caller leaves the preview in place and logs at debug level.
"""
if not self._bot:
return False
try:
await self._bot.delete_message(
chat_id=int(chat_id),
message_id=int(message_id),
)
return True
except Exception as e:
logger.debug(
"[%s] Failed to delete Telegram message %s: %s",
self.name, message_id, e,
)
return False
async def send_update_prompt(
self, chat_id: str, prompt: str, default: str = "",
session_key: str = "",
@@ -2161,8 +2054,10 @@ class TelegramAdapter(BasePlatformAdapter):
text = content
# 0) Rewrite GFM-style pipe tables into Telegram-friendly row groups
# before the normal MarkdownV2 conversions run.
# 0) Pre-wrap GFM-style pipe tables in ``` fences. Telegram can't
# render tables natively, but fenced code blocks render as
# monospace preformatted text with columns intact. The wrapped
# tables then flow through step (1) below as protected regions.
text = _wrap_markdown_tables(text)
# 1) Protect fenced code blocks (``` ... ```)
@@ -2432,26 +2327,6 @@ class TelegramAdapter(BasePlatformAdapter):
user = getattr(entity, "user", None)
if user and getattr(user, "id", None) == bot_id:
return True
elif entity_type == "bot_command" and expected:
# Telegram's official group-disambiguation form for slash
# commands (``/cmd@botname``) is emitted as a single
# ``bot_command`` entity covering the whole span — there
# is no accompanying ``mention`` entity. Treat it as a
# direct address to this bot when the ``@botname`` suffix
# matches. This is the form Telegram's own command menu
# autocomplete produces in groups, so dropping it at the
# mention gate would break /new, /reset, /help, ... for
# every group that has ``require_mention`` enabled (#15415).
offset = int(getattr(entity, "offset", -1))
length = int(getattr(entity, "length", 0))
if offset < 0 or length <= 0:
continue
command_text = source_text[offset:offset + length]
at_index = command_text.find("@")
if at_index < 0:
continue
if command_text[at_index:].strip().lower() == expected:
return True
return False
def _message_matches_mention_patterns(self, message: Message) -> bool:
+3 -3
View File
@@ -43,10 +43,10 @@ _DOH_PROVIDERS: list[dict] = [
_SEED_FALLBACK_IPS: list[str] = ["149.154.167.220"]
def _resolve_proxy_url(target_hosts=None) -> str | None:
def _resolve_proxy_url() -> str | None:
# Delegate to shared implementation (env vars + macOS system proxy detection)
from gateway.platforms.base import resolve_proxy_url
return resolve_proxy_url("TELEGRAM_PROXY", target_hosts=target_hosts)
return resolve_proxy_url("TELEGRAM_PROXY")
class TelegramFallbackTransport(httpx.AsyncBaseTransport):
@@ -60,7 +60,7 @@ class TelegramFallbackTransport(httpx.AsyncBaseTransport):
def __init__(self, fallback_ips: Iterable[str], **transport_kwargs):
self._fallback_ips = [ip for ip in dict.fromkeys(_normalize_fallback_ips(fallback_ips))]
proxy_url = _resolve_proxy_url(target_hosts=[_TELEGRAM_API_HOST, *self._fallback_ips])
proxy_url = _resolve_proxy_url()
if proxy_url and "proxy" not in transport_kwargs:
transport_kwargs["proxy"] = proxy_url
self._primary = httpx.AsyncHTTPTransport(**transport_kwargs)
+4 -52
View File
@@ -89,21 +89,8 @@ MAX_CONSECUTIVE_FAILURES = 3
RETRY_DELAY_SECONDS = 2
BACKOFF_DELAY_SECONDS = 30
SESSION_EXPIRED_ERRCODE = -14
RATE_LIMIT_ERRCODE = -2 # iLink frequency limit — backoff and retry
MESSAGE_DEDUP_TTL_SECONDS = 300
def _is_stale_session_ret(
ret: "Optional[int]", errcode: "Optional[int]", errmsg: "Optional[str]",
) -> bool:
"""True when iLink returns ret=-2 / errcode=-2 with 'unknown error',
which is a stale-session signal (same as errcode=-14) rather than
a genuine rate limit."""
if ret != RATE_LIMIT_ERRCODE and errcode != RATE_LIMIT_ERRCODE:
return False
return (errmsg or "").lower() == "unknown error"
MEDIA_IMAGE = 1
MEDIA_VIDEO = 2
MEDIA_FILE = 3
@@ -1126,7 +1113,7 @@ async def qr_login(
class WeixinAdapter(BasePlatformAdapter):
"""Native Hermes adapter for Weixin personal accounts."""
MAX_MESSAGE_LENGTH = 2000
MAX_MESSAGE_LENGTH = 4000
# WeChat does not support editing sent messages — streaming must use the
# fallback "send-final-only" path so the cursor (▉) is never left visible.
@@ -1151,10 +1138,10 @@ class WeixinAdapter(BasePlatformAdapter):
extra.get("cdn_base_url") or os.getenv("WEIXIN_CDN_BASE_URL", WEIXIN_CDN_BASE_URL)
).strip().rstrip("/")
self._send_chunk_delay_seconds = float(
extra.get("send_chunk_delay_seconds") or os.getenv("WEIXIN_SEND_CHUNK_DELAY_SECONDS", "1.5")
extra.get("send_chunk_delay_seconds") or os.getenv("WEIXIN_SEND_CHUNK_DELAY_SECONDS", "0.35")
)
self._send_chunk_retries = int(
extra.get("send_chunk_retries") or os.getenv("WEIXIN_SEND_CHUNK_RETRIES", "4")
extra.get("send_chunk_retries") or os.getenv("WEIXIN_SEND_CHUNK_RETRIES", "2")
)
self._send_chunk_retry_delay_seconds = float(
extra.get("send_chunk_retry_delay_seconds")
@@ -1222,17 +1209,6 @@ class WeixinAdapter(BasePlatformAdapter):
self._mark_connected()
_LIVE_ADAPTERS[self._token] = self
logger.info("[%s] Connected account=%s base=%s", self.name, _safe_id(self._account_id), self._base_url)
if self._group_policy != "disabled":
logger.warning(
"[%s] WEIXIN_GROUP_POLICY=%s is set, but QR-login connects an iLink bot "
"identity (e.g. ...@im.bot) which typically cannot be invited into ordinary "
"WeChat groups. iLink usually does not deliver ordinary-group events for "
"these accounts, so group messages may never reach Hermes regardless of this "
"policy. If group delivery doesn't work, the limitation is on the iLink side, "
"not in Hermes.",
self.name,
self._group_policy,
)
return True
async def disconnect(self) -> None:
@@ -1277,8 +1253,7 @@ class WeixinAdapter(BasePlatformAdapter):
ret = response.get("ret", 0)
errcode = response.get("errcode", 0)
if ret not in (0, None) or errcode not in (0, None):
if (ret == SESSION_EXPIRED_ERRCODE or errcode == SESSION_EXPIRED_ERRCODE
or _is_stale_session_ret(ret, errcode, response.get("errmsg"))):
if ret == SESSION_EXPIRED_ERRCODE or errcode == SESSION_EXPIRED_ERRCODE:
logger.error("[%s] Session expired; pausing for 10 minutes", self.name)
await asyncio.sleep(600)
consecutive_failures = 0
@@ -1543,7 +1518,6 @@ class WeixinAdapter(BasePlatformAdapter):
is_session_expired = (
ret == SESSION_EXPIRED_ERRCODE
or errcode == SESSION_EXPIRED_ERRCODE
or _is_stale_session_ret(ret, errcode, resp.get("errmsg"))
)
# Session expired — strip token and retry once
if is_session_expired and not retried_without_token and context_token:
@@ -1557,28 +1531,6 @@ class WeixinAdapter(BasePlatformAdapter):
self.name, _safe_id(chat_id),
)
continue
# Rate limit (-2) — backoff and retry
is_rate_limited = (
ret == RATE_LIMIT_ERRCODE
or errcode == RATE_LIMIT_ERRCODE
)
if is_rate_limited:
errmsg = resp.get("errmsg") or resp.get("msg") or "rate limited"
# Record the error so we raise a descriptive
# RuntimeError (instead of AssertionError) if the
# loop exhausts with the server still rate-limiting.
last_error = RuntimeError(
f"iLink sendmessage rate limited: ret={ret} errcode={errcode} errmsg={errmsg}"
)
if attempt >= self._send_chunk_retries:
break
wait = self._send_chunk_retry_delay_seconds * 3 # 3x backoff for rate limit
logger.warning(
"[%s] rate limited for %s; backing off %.1fs before retry",
self.name, _safe_id(chat_id), wait,
)
await asyncio.sleep(wait)
continue
errmsg = resp.get("errmsg") or resp.get("msg") or "unknown error"
raise RuntimeError(
f"iLink sendmessage error: ret={ret} errcode={errcode} errmsg={errmsg}"
File diff suppressed because it is too large Load Diff
-645
View File
@@ -1,645 +0,0 @@
"""
yuanbao_media.py 元宝平台媒体处理模块
提供 COS 上传文件下载TIM 媒体消息构建等功能
移植自 TypeScript media.tsyuanbao-openclaw-plugin
使用 httpx 替代 cos-nodejs-sdk-v5避免引入额外 SDK 依赖
COS 上传流程
1. 调用 genUploadInfo 获取临时凭证tmpSecretId/tmpSecretKey/sessionToken
2. 用临时凭证通过 HMAC-SHA1 签名构建 Authorization
3. HTTP PUT 上传到 COS
TIM 消息体构建
- buildImageMsgBody() TIMImageElem
- buildFileMsgBody() TIMFileElem
"""
from __future__ import annotations
import hashlib
import hmac
import logging
import os
import secrets
import struct
import time
import urllib.parse
from typing import Optional, Any
import httpx
logger = logging.getLogger(__name__)
# ============ 常量 ============
UPLOAD_INFO_PATH = "/api/resource/genUploadInfo"
DEFAULT_API_DOMAIN = "yuanbao.tencent.com"
DEFAULT_MAX_SIZE_MB = 50
# COS 加速域名后缀(优先使用全球加速)
COS_USE_ACCELERATE = True
# ============ 类型映射 ============
# MIME → image_format 数字(TIM 协议字段)
_MIME_TO_IMAGE_FORMAT: dict[str, int] = {
"image/jpeg": 1,
"image/jpg": 1,
"image/gif": 2,
"image/png": 3,
"image/bmp": 4,
"image/webp": 255,
"image/heic": 255,
"image/tiff": 255,
}
# 文件扩展名 → MIME
_EXT_TO_MIME: dict[str, str] = {
".jpg": "image/jpeg",
".jpeg": "image/jpeg",
".png": "image/png",
".gif": "image/gif",
".webp": "image/webp",
".bmp": "image/bmp",
".heic": "image/heic",
".tiff": "image/tiff",
".ico": "image/x-icon",
".pdf": "application/pdf",
".doc": "application/msword",
".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
".xls": "application/vnd.ms-excel",
".xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
".ppt": "application/vnd.ms-powerpoint",
".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation",
".txt": "text/plain",
".zip": "application/zip",
".tar": "application/x-tar",
".gz": "application/gzip",
".mp3": "audio/mpeg",
".mp4": "video/mp4",
".wav": "audio/wav",
".ogg": "audio/ogg",
".webm": "video/webm",
}
# ============ 工具函数 ============
def guess_mime_type(filename: str) -> str:
"""根据文件扩展名猜测 MIME 类型。"""
ext = os.path.splitext(filename)[-1].lower()
return _EXT_TO_MIME.get(ext, "application/octet-stream")
def is_image(filename: str, mime_type: str = "") -> bool:
"""判断是否为图片类型。"""
if mime_type.startswith("image/"):
return True
ext = os.path.splitext(filename)[-1].lower()
return ext in {".jpg", ".jpeg", ".png", ".gif", ".webp", ".bmp", ".heic", ".tiff", ".ico"}
def get_image_format(mime_type: str) -> int:
"""获取 TIM 图片格式编号。"""
return _MIME_TO_IMAGE_FORMAT.get(mime_type.lower(), 255)
def md5_hex(data: bytes) -> str:
"""计算 MD5 十六进制摘要。"""
return hashlib.md5(data).hexdigest()
def generate_file_id() -> str:
"""生成随机文件 ID(32 位 hex)。"""
return secrets.token_hex(16)
# ============ 图片尺寸解析(纯 Python,无需 Pillow ============
def parse_image_size(data: bytes) -> Optional[dict[str, int]]:
"""
解析图片宽高支持 JPEG/PNG/GIF/WebP无需第三方依赖
返回 {"width": w, "height": h} None无法识别
"""
return (
_parse_png_size(data)
or _parse_jpeg_size(data)
or _parse_gif_size(data)
or _parse_webp_size(data)
)
def _parse_png_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 24:
return None
if buf[:4] != b"\x89PNG":
return None
w = struct.unpack(">I", buf[16:20])[0]
h = struct.unpack(">I", buf[20:24])[0]
return {"width": w, "height": h}
def _parse_jpeg_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 4 or buf[0] != 0xFF or buf[1] != 0xD8:
return None
i = 2
while i < len(buf) - 9:
if buf[i] != 0xFF:
i += 1
continue
marker = buf[i + 1]
if marker in (0xC0, 0xC2):
h = struct.unpack(">H", buf[i + 5: i + 7])[0]
w = struct.unpack(">H", buf[i + 7: i + 9])[0]
return {"width": w, "height": h}
if i + 3 < len(buf):
i += 2 + struct.unpack(">H", buf[i + 2: i + 4])[0]
else:
break
return None
def _parse_gif_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 10:
return None
sig = buf[:6].decode("ascii", errors="replace")
if sig not in ("GIF87a", "GIF89a"):
return None
w = struct.unpack("<H", buf[6:8])[0]
h = struct.unpack("<H", buf[8:10])[0]
return {"width": w, "height": h}
def _parse_webp_size(buf: bytes) -> Optional[dict[str, int]]:
if len(buf) < 16:
return None
if buf[:4] != b"RIFF" or buf[8:12] != b"WEBP":
return None
chunk = buf[12:16].decode("ascii", errors="replace")
if chunk == "VP8 ":
if len(buf) >= 30 and buf[23] == 0x9D and buf[24] == 0x01 and buf[25] == 0x2A:
w = struct.unpack("<H", buf[26:28])[0] & 0x3FFF
h = struct.unpack("<H", buf[28:30])[0] & 0x3FFF
return {"width": w, "height": h}
elif chunk == "VP8L":
if len(buf) >= 25 and buf[20] == 0x2F:
bits = struct.unpack("<I", buf[21:25])[0]
w = (bits & 0x3FFF) + 1
h = ((bits >> 14) & 0x3FFF) + 1
return {"width": w, "height": h}
elif chunk == "VP8X":
if len(buf) >= 30:
w = (buf[24] | (buf[25] << 8) | (buf[26] << 16)) + 1
h = (buf[27] | (buf[28] << 8) | (buf[29] << 16)) + 1
return {"width": w, "height": h}
return None
# ============ URL 下载 ============
async def download_url(
url: str,
max_size_mb: int = DEFAULT_MAX_SIZE_MB,
) -> tuple[bytes, str]:
"""
下载 URL 内容返回 (bytes, content_type)
Args:
url: HTTP(S) URL
max_size_mb: 最大允许大小MB超过则抛出异常
Returns:
(data_bytes, content_type_string)
Raises:
ValueError: 内容超过大小限制
httpx.HTTPError: 网络/HTTP 错误
"""
max_bytes = max_size_mb * 1024 * 1024
async with httpx.AsyncClient(timeout=30.0, follow_redirects=True) as client:
# 先 HEAD 检查大小
try:
head = await client.head(url)
content_length = int(head.headers.get("content-length", 0) or 0)
if content_length > 0 and content_length > max_bytes:
raise ValueError(
f"文件过大: {content_length / 1024 / 1024:.1f} MB > {max_size_mb} MB"
)
except httpx.HTTPStatusError:
pass # 部分服务器不支持 HEAD,忽略
# GET 下载(流式读取,防止超限)
async with client.stream("GET", url) as resp:
resp.raise_for_status()
content_type = resp.headers.get("content-type", "").split(";")[0].strip()
chunks: list[bytes] = []
downloaded = 0
async for chunk in resp.aiter_bytes(65536):
downloaded += len(chunk)
if downloaded > max_bytes:
raise ValueError(
f"文件过大: 已超过 {max_size_mb} MB 限制"
)
chunks.append(chunk)
data = b"".join(chunks)
return data, content_type
# ============ COS 鉴权(HMAC-SHA1 ============
def _cos_sign(
method: str,
path: str,
params: dict[str, str],
headers: dict[str, str],
secret_id: str,
secret_key: str,
start_time: Optional[int] = None,
expire_seconds: int = 3600,
) -> str:
"""
构建 COS 请求签名q-sign-algorithm=sha1 方案
参考https://cloud.tencent.com/document/product/436/7778
Args:
method: HTTP 方法小写 "put"
path: URL 路径URL encode 后的小写
params: URL 查询参数 dict用于签名
headers: 参与签名的请求头 dictkey 需小写
secret_id: 临时 SecretIdtmpSecretId
secret_key: 临时 SecretKeytmpSecretKey
start_time: 签名起始 Unix 时间戳默认 now
expire_seconds: 签名有效期默认 3600
Returns:
Authorization header 完整字符串
"""
now = int(time.time())
q_sign_time = f"{start_time or now};{(start_time or now) + expire_seconds}"
# Step 1: SignKey = HMAC-SHA1(SecretKey, q-sign-time)
sign_key = hmac.new(
secret_key.encode("utf-8"),
q_sign_time.encode("utf-8"),
hashlib.sha1,
).hexdigest()
# Step 2: HttpString
# 参数和头部需按字典序排列,key 小写
sorted_params = sorted((k.lower(), urllib.parse.quote(str(v), safe="") ) for k, v in params.items())
sorted_headers = sorted((k.lower(), urllib.parse.quote(str(v), safe="") ) for k, v in headers.items())
url_param_list = ";".join(k for k, _ in sorted_params)
url_params = "&".join(f"{k}={v}" for k, v in sorted_params)
header_list = ";".join(k for k, _ in sorted_headers)
header_str = "&".join(f"{k}={v}" for k, v in sorted_headers)
http_string = "\n".join([
method.lower(),
path,
url_params,
header_str,
"",
])
# Step 3: StringToSign = sha1 hash of HttpString
sha1_of_http = hashlib.sha1(http_string.encode("utf-8")).hexdigest()
string_to_sign = "\n".join([
"sha1",
q_sign_time,
sha1_of_http,
"",
])
# Step 4: Signature = HMAC-SHA1(SignKey, StringToSign)
signature = hmac.new(
sign_key.encode("utf-8"),
string_to_sign.encode("utf-8"),
hashlib.sha1,
).hexdigest()
return (
f"q-sign-algorithm=sha1"
f"&q-ak={secret_id}"
f"&q-sign-time={q_sign_time}"
f"&q-key-time={q_sign_time}"
f"&q-header-list={header_list}"
f"&q-url-param-list={url_param_list}"
f"&q-signature={signature}"
)
# ============ 主要公开 API ============
async def get_cos_credentials(
app_key: str,
api_domain: str,
token: str,
filename: str = "file",
file_id: Optional[str] = None,
bot_id: str = "",
route_env: str = "",
) -> dict:
"""
调用 genUploadInfo 接口获取 COS 临时密钥及上传配置
Args:
app_key: 应用 Key用于 X-ID
api_domain: API 域名 https://bot.yuanbao.tencent.com
token: 当前有效的签票 tokenX-Token
filename: 待上传的文件名含扩展名
file_id: 客户端生成的唯一文件 ID不传则自动生成
bot_id: Bot 账号 ID用于 X-ID
Returns:
COS 上传配置 dict包含以下字段
bucketName (str) COS Bucket 名称
region (str) COS 地域
location (str) 上传 Key对象路径
encryptTmpSecretId (str) 临时 SecretId
encryptTmpSecretKey(str) 临时 SecretKey
encryptToken (str) SessionToken
startTime (int) 凭证起始时间戳Unix
expiredTime (int) 凭证过期时间戳Unix
resourceUrl (str) 上传后的公网访问 URL
resourceID (str) 资源 ID可选
Raises:
RuntimeError: 接口返回非 0 code 或字段缺失
"""
if file_id is None:
file_id = generate_file_id()
upload_url = f"{api_domain.rstrip('/')}{UPLOAD_INFO_PATH}"
headers = {
"Content-Type": "application/json",
"X-Token": token,
"X-ID": bot_id or app_key,
"X-Source": "web",
}
if route_env:
headers["X-Route-Env"] = route_env
body = {
"fileName": filename,
"fileId": file_id,
"docFrom": "localDoc",
"docOpenId": "",
}
async with httpx.AsyncClient(timeout=15.0) as client:
resp = await client.post(upload_url, json=body, headers=headers)
resp.raise_for_status()
result: dict[str, Any] = resp.json()
code = result.get("code")
if code != 0 and code is not None:
raise RuntimeError(
f"genUploadInfo 失败: code={code}, msg={result.get('msg', '')}"
)
data = result.get("data") or result
required_fields = ["bucketName", "location"]
missing = [f for f in required_fields if not data.get(f)]
if missing:
raise RuntimeError(
f"genUploadInfo 返回字段不完整: 缺少字段 {missing}"
)
return data
async def upload_to_cos(
file_bytes: bytes,
filename: str,
content_type: str,
credentials: dict,
bucket: str,
region: str,
) -> dict:
"""
通过 httpx PUT 请求将文件上传到 COS
使用临时凭证tmpSecretId/tmpSecretKey/sessionToken构建 HMAC-SHA1 签名
Args:
file_bytes: 文件二进制内容
filename: 文件名用于辅助计算 MIMEUUID
content_type: MIME 类型 "image/jpeg"
credentials: get_cos_credentials() 返回的 dict包含
encryptTmpSecretId tmpSecretId
encryptTmpSecretKey tmpSecretKey
encryptToken sessionToken
location COS key对象路径
resourceUrl 上传后公网 URL
startTime 凭证起始时间Unix
expiredTime 凭证过期时间Unix
bucket: COS Bucket 名称 chatbot-1234567890
region: COS 地域 ap-guangzhou
Returns:
上传结果 dict包含
url (str) COS 公网访问 URL
uuid (str) 文件内容 MD5
size (int) 文件大小字节
width (int, optional) 图片宽度仅图片
height (int, optional) 图片高度仅图片
Raises:
httpx.HTTPStatusError: COS 返回非 2xx 状态
RuntimeError: credentials 字段缺失
"""
secret_id: str = credentials.get("encryptTmpSecretId", "")
secret_key: str = credentials.get("encryptTmpSecretKey", "")
session_token: str = credentials.get("encryptToken", "")
cos_key: str = credentials.get("location", "")
resource_url: str = credentials.get("resourceUrl", "")
start_time: Optional[int] = credentials.get("startTime")
expired_time: Optional[int] = credentials.get("expiredTime")
if not secret_id or not secret_key or not cos_key:
raise RuntimeError(
f"COS credentials 不完整: secretId={bool(secret_id)}, "
f"secretKey={bool(secret_key)}, location={bool(cos_key)}"
)
# 构建 COS 上传 URL(优先使用全球加速域名)
if COS_USE_ACCELERATE:
cos_host = f"{bucket}.cos.accelerate.myqcloud.com"
else:
cos_host = f"{bucket}.cos.{region}.myqcloud.com"
# URL encode cos_key(保留 /
encoded_key = urllib.parse.quote(cos_key, safe="/")
cos_url = f"https://{cos_host}/{encoded_key.lstrip('/')}"
# 确定 Content-Type
if not content_type or content_type == "application/octet-stream":
if is_image(filename):
content_type = guess_mime_type(filename)
else:
content_type = "application/octet-stream"
# 计算文件 MD5 + size
file_uuid = md5_hex(file_bytes)
file_size = len(file_bytes)
# 参与签名的请求头
sign_headers = {
"host": cos_host,
"content-type": content_type,
"x-cos-security-token": session_token,
}
# 计算签名有效期
now = int(time.time())
sign_start = start_time if start_time else now
sign_expire = (expired_time - now) if expired_time and expired_time > now else 3600
authorization = _cos_sign(
method="put",
path=f"/{encoded_key.lstrip('/')}",
params={},
headers=sign_headers,
secret_id=secret_id,
secret_key=secret_key,
start_time=sign_start,
expire_seconds=sign_expire,
)
put_headers = {
"Authorization": authorization,
"Content-Type": content_type,
"x-cos-security-token": session_token,
}
logger.info(
"COS PUT: bucket=%s region=%s key=%s size=%d mime=%s",
bucket, region, cos_key, file_size, content_type,
)
async with httpx.AsyncClient(timeout=120.0) as client:
resp = await client.put(
cos_url,
content=file_bytes,
headers=put_headers,
)
resp.raise_for_status()
# 解析图片尺寸(仅图片类型)
result: dict[str, Any] = {
"url": resource_url or cos_url,
"uuid": file_uuid,
"size": file_size,
}
if content_type.startswith("image/"):
size_info = parse_image_size(file_bytes)
if size_info:
result["width"] = size_info["width"]
result["height"] = size_info["height"]
logger.info(
"COS 上传成功: url=%s size=%d",
result["url"], file_size,
)
return result
# ============ TIM 媒体消息构建 ============
def build_image_msg_body(
url: str,
uuid: Optional[str] = None,
filename: Optional[str] = None,
size: int = 0,
width: int = 0,
height: int = 0,
mime_type: str = "",
) -> list[dict]:
"""
构建腾讯 IM TIMImageElem 消息体
参考https://cloud.tencent.com/document/product/269/2720
Args:
url: 图片公网访问 URLCOS resourceUrl
uuid: 文件 UUIDMD5 或其他唯一标识
filename: 文件名uuid 为空时作为备用
size: 文件大小字节
width: 图片宽度像素
height: 图片高度像素
mime_type: MIME 类型用于确定 image_format
Returns:
TIMImageElem 消息体列表适合直接放入 msg_body
"""
_uuid = uuid or filename or _basename_from_url(url) or "image"
image_format = get_image_format(mime_type) if mime_type else 255
return [
{
"msg_type": "TIMImageElem",
"msg_content": {
"uuid": _uuid,
"image_format": image_format,
"image_info_array": [
{
"type": 1, # 1 = 原图
"size": size,
"width": width,
"height": height,
"url": url,
}
],
},
}
]
def build_file_msg_body(
url: str,
filename: str,
uuid: Optional[str] = None,
size: int = 0,
) -> list[dict]:
"""
构建腾讯 IM TIMFileElem 消息体
参考https://cloud.tencent.com/document/product/269/2720
Args:
url: 文件公网访问 URLCOS resourceUrl
filename: 文件名含扩展名
uuid: 文件 UUIDMD5 或其他唯一标识不传则使用 filename
size: 文件大小字节
Returns:
TIMFileElem 消息体列表适合直接放入 msg_body
"""
_uuid = uuid or filename
return [
{
"msg_type": "TIMFileElem",
"msg_content": {
"uuid": _uuid,
"file_name": filename,
"file_size": size,
"url": url,
},
}
]
# ============ 内部工具 ============
def _basename_from_url(url: str) -> str:
"""从 URL 提取文件名。"""
try:
parsed = urllib.parse.urlparse(url)
return os.path.basename(parsed.path)
except Exception:
return ""
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@@ -1,558 +0,0 @@
"""
Yuanbao sticker (TIMFaceElem) support.
Ported from yuanbao-openclaw-plugin/src/sticker/.
TIMFaceElem wire format:
{
"msg_type": "TIMFaceElem",
"msg_content": {
"index": 0, # always 0 per Yuanbao convention
"data": "<json>", # serialised sticker metadata
}
}
The `data` field carries a JSON string with the sticker's metadata so the
receiver can look up the correct asset in the emoji pack.
"""
from __future__ import annotations
import json
import random
import re
import unicodedata
from typing import Optional
# ---------------------------------------------------------------------------
# Sticker catalogue ported from builtin-stickers.json
# Key : canonical name (Chinese)
# Value : {sticker_id, package_id, name, description, width, height, formats}
# ---------------------------------------------------------------------------
STICKER_MAP: dict[str, dict] = {
"六六六": {
"sticker_id": "278", "package_id": "1003", "name": "六六六",
"description": "666 厉害 牛 棒 绝了 好强 awesome",
"width": 128, "height": 128, "formats": "png",
},
"我想开了": {
"sticker_id": "262", "package_id": "1003", "name": "我想开了",
"description": "想开 佛系 释怀 顿悟 看淡了 无所谓",
"width": 128, "height": 128, "formats": "png",
},
"害羞": {
"sticker_id": "130", "package_id": "1003", "name": "害羞",
"description": "腼腆 不好意思 脸红 娇羞 羞涩 捂脸",
"width": 128, "height": 128, "formats": "png",
},
"比心": {
"sticker_id": "252", "package_id": "1003", "name": "比心",
"description": "笔芯 爱你 爱心手势 love heart 喜欢你",
"width": 128, "height": 128, "formats": "png",
},
"委屈": {
"sticker_id": "125", "package_id": "1003", "name": "委屈",
"description": "难过 想哭 可怜巴巴 瘪嘴 受伤 被欺负",
"width": 128, "height": 128, "formats": "png",
},
"亲亲": {
"sticker_id": "146", "package_id": "1003", "name": "亲亲",
"description": "么么 mua 亲一下 kiss 飞吻 啵",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "131", "package_id": "1003", "name": "",
"description": "帅 墨镜 cool 高冷 有型 swagger",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "145", "package_id": "1003", "name": "",
"description": "睡觉 困 zzZ 打盹 躺平 休眠 sleepy",
"width": 128, "height": 128, "formats": "png",
},
"发呆": {
"sticker_id": "152", "package_id": "1003", "name": "发呆",
"description": "懵 愣住 放空 呆滞 出神 脑子空白",
"width": 128, "height": 128, "formats": "png",
},
"可怜": {
"sticker_id": "157", "package_id": "1003", "name": "可怜",
"description": "卖萌 求饶 委屈巴巴 弱小 拜托 眼巴巴",
"width": 128, "height": 128, "formats": "png",
},
"摊手": {
"sticker_id": "200", "package_id": "1003", "name": "摊手",
"description": "无奈 没办法 耸肩 随便 那咋整 whatever",
"width": 128, "height": 128, "formats": "png",
},
"头大": {
"sticker_id": "213", "package_id": "1003", "name": "头大",
"description": "头疼 烦恼 郁闷 难搞 崩溃 一团乱",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "256", "package_id": "1003", "name": "",
"description": "害怕 惊恐 震惊 吓一跳 恐怖 怂",
"width": 128, "height": 128, "formats": "png",
},
"吐血": {
"sticker_id": "203", "package_id": "1003", "name": "吐血",
"description": "无语 崩溃 被雷 内伤 一口老血 屮",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "185", "package_id": "1003", "name": "",
"description": "傲娇 生气 不满 撇嘴 不理 赌气",
"width": 128, "height": 128, "formats": "png",
},
"嘿嘿": {
"sticker_id": "220", "package_id": "1003", "name": "嘿嘿",
"description": "坏笑 猥琐笑 偷笑 憨笑 得意 你懂的",
"width": 128, "height": 128, "formats": "png",
},
"头秃": {
"sticker_id": "218", "package_id": "1003", "name": "头秃",
"description": "程序员 加班 焦虑 没头发 秃了 肝爆",
"width": 128, "height": 128, "formats": "png",
},
"暗中观察": {
"sticker_id": "221", "package_id": "1003", "name": "暗中观察",
"description": "窥屏 潜水 偷偷看 角落 围观 屏住呼吸",
"width": 128, "height": 128, "formats": "png",
},
"我酸了": {
"sticker_id": "224", "package_id": "1003", "name": "我酸了",
"description": "嫉妒 柠檬精 羡慕 吃柠檬 眼红 恰柠檬",
"width": 128, "height": 128, "formats": "png",
},
"打call": {
"sticker_id": "246", "package_id": "1003", "name": "打call",
"description": "应援 加油 支持 喝彩 助威 call",
"width": 128, "height": 128, "formats": "png",
},
"庆祝": {
"sticker_id": "251", "package_id": "1003", "name": "庆祝",
"description": "祝贺 开心 耶 party 胜利 干杯",
"width": 128, "height": 128, "formats": "png",
},
"奋斗": {
"sticker_id": "151", "package_id": "1003", "name": "奋斗",
"description": "努力 加油 拼搏 冲 干劲 卷起来",
"width": 128, "height": 128, "formats": "png",
},
"惊讶": {
"sticker_id": "143", "package_id": "1003", "name": "惊讶",
"description": "震惊 哇 不敢相信 OMG 居然 这么离谱",
"width": 128, "height": 128, "formats": "png",
},
"疑问": {
"sticker_id": "144", "package_id": "1003", "name": "疑问",
"description": "问号 不懂 啥 为什么 啥情况 懵逼问",
"width": 128, "height": 128, "formats": "png",
},
"仔细分析": {
"sticker_id": "248", "package_id": "1003", "name": "仔细分析",
"description": "思考 推敲 认真 研究 琢磨 让我想想",
"width": 128, "height": 128, "formats": "png",
},
"撅嘴": {
"sticker_id": "184", "package_id": "1003", "name": "撅嘴",
"description": "嘟嘴 卖萌 不高兴 撒娇 嘴翘",
"width": 128, "height": 128, "formats": "png",
},
"泪奔": {
"sticker_id": "199", "package_id": "1003", "name": "泪奔",
"description": "大哭 伤心 破防 感动哭 泪流满面 呜呜",
"width": 128, "height": 128, "formats": "png",
},
"尊嘟假嘟": {
"sticker_id": "276", "package_id": "1003", "name": "尊嘟假嘟",
"description": "真的假的 真假 可爱问 你骗我 是不是",
"width": 128, "height": 128, "formats": "png",
},
"略略略": {
"sticker_id": "113", "package_id": "1003", "name": "略略略",
"description": "调皮 吐舌 不服 略 气死你 鬼脸",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "180", "package_id": "1003", "name": "",
"description": "想睡 倦 打哈欠 睁不开眼 好困啊 sleepy",
"width": 128, "height": 128, "formats": "png",
},
"折磨": {
"sticker_id": "181", "package_id": "1003", "name": "折磨",
"description": "难受 痛苦 煎熬 蚌埠住了 受不了 要命",
"width": 128, "height": 128, "formats": "png",
},
"抠鼻": {
"sticker_id": "182", "package_id": "1003", "name": "抠鼻",
"description": "不屑 无聊 淡定 无所谓 鄙视 挖鼻",
"width": 128, "height": 128, "formats": "png",
},
"鼓掌": {
"sticker_id": "183", "package_id": "1003", "name": "鼓掌",
"description": "拍手 叫好 赞同 666 喝彩 掌声",
"width": 128, "height": 128, "formats": "png",
},
"斜眼笑": {
"sticker_id": "204", "package_id": "1003", "name": "斜眼笑",
"description": "滑稽 坏笑 doge 意味深长 阴阳怪气 嘿嘿嘿",
"width": 128, "height": 128, "formats": "png",
},
"辣眼睛": {
"sticker_id": "216", "package_id": "1003", "name": "辣眼睛",
"description": "看不下去 cringe 毁三观 太丑了 瞎了",
"width": 128, "height": 128, "formats": "png",
},
"哦哟": {
"sticker_id": "217", "package_id": "1003", "name": "哦哟",
"description": "惊讶 起哄 哇哦 有戏 不简单 哟",
"width": 128, "height": 128, "formats": "png",
},
"吃瓜": {
"sticker_id": "222", "package_id": "1003", "name": "吃瓜",
"description": "围观 看戏 八卦 路人 看热闹 板凳",
"width": 128, "height": 128, "formats": "png",
},
"狗头": {
"sticker_id": "225", "package_id": "1003", "name": "狗头",
"description": "doge 保命 开玩笑 滑稽 反讽 懂的都懂",
"width": 128, "height": 128, "formats": "png",
},
"敬礼": {
"sticker_id": "227", "package_id": "1003", "name": "敬礼",
"description": "salute 尊重 收到 遵命 致敬 报告",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "231", "package_id": "1003", "name": "",
"description": "知道了 明白 敷衍 嗯 这样啊 收到",
"width": 128, "height": 128, "formats": "png",
},
"拿到红包": {
"sticker_id": "236", "package_id": "1003", "name": "拿到红包",
"description": "红包 谢谢老板 发财 开心 抢到了 欧气",
"width": 128, "height": 128, "formats": "png",
},
"牛吖": {
"sticker_id": "239", "package_id": "1003", "name": "牛吖",
"description": "牛 厉害 强 666 佩服 大佬",
"width": 128, "height": 128, "formats": "png",
},
"贴贴": {
"sticker_id": "272", "package_id": "1003", "name": "贴贴",
"description": "抱抱 亲昵 蹭蹭 亲密 靠靠 撒娇贴",
"width": 128, "height": 128, "formats": "png",
},
"爱心": {
"sticker_id": "138", "package_id": "1003", "name": "爱心",
"description": "心 love 喜欢你 红心 示爱 么么哒",
"width": 128, "height": 128, "formats": "png",
},
"晚安": {
"sticker_id": "170", "package_id": "1003", "name": "晚安",
"description": "好梦 睡了 night 早点休息 安啦 moon",
"width": 128, "height": 128, "formats": "png",
},
"太阳": {
"sticker_id": "176", "package_id": "1003", "name": "太阳",
"description": "晴天 早上好 阳光 morning 好天气 日",
"width": 128, "height": 128, "formats": "png",
},
"柠檬": {
"sticker_id": "266", "package_id": "1003", "name": "柠檬",
"description": "酸 嫉妒 柠檬精 羡慕 我酸 恰柠檬",
"width": 128, "height": 128, "formats": "png",
},
"大冤种": {
"sticker_id": "267", "package_id": "1003", "name": "大冤种",
"description": "倒霉 吃亏 自嘲 好心没好报 背锅 工具人",
"width": 128, "height": 128, "formats": "png",
},
"吐了": {
"sticker_id": "132", "package_id": "1003", "name": "吐了",
"description": "恶心 yue 受不了 嫌弃 想吐 生理不适",
"width": 128, "height": 128, "formats": "png",
},
"": {
"sticker_id": "134", "package_id": "1003", "name": "",
"description": "生气 愤怒 火大 暴躁 气炸 怼",
"width": 128, "height": 128, "formats": "png",
},
"玫瑰": {
"sticker_id": "165", "package_id": "1003", "name": "玫瑰",
"description": "花 示爱 表白 浪漫 送你花 情人节",
"width": 128, "height": 128, "formats": "png",
},
"凋谢": {
"sticker_id": "119", "package_id": "1003", "name": "凋谢",
"description": "花谢 失恋 难过 枯萎 心碎 凉了",
"width": 128, "height": 128, "formats": "png",
},
"点赞": {
"sticker_id": "159", "package_id": "1003", "name": "点赞",
"description": "赞 认同 好棒 good like 大拇指 顶",
"width": 128, "height": 128, "formats": "png",
},
"握手": {
"sticker_id": "164", "package_id": "1003", "name": "握手",
"description": "合作 你好 商务 hello deal 成交 友好",
"width": 128, "height": 128, "formats": "png",
},
"抱拳": {
"sticker_id": "163", "package_id": "1003", "name": "抱拳",
"description": "谢谢 失敬 江湖 承让 拜托 有礼",
"width": 128, "height": 128, "formats": "png",
},
"ok": {
"sticker_id": "169", "package_id": "1003", "name": "ok",
"description": "好的 收到 没问题 okay 行 可以 懂了",
"width": 128, "height": 128, "formats": "png",
},
"拳头": {
"sticker_id": "174", "package_id": "1003", "name": "拳头",
"description": "加油 干 冲 fight 力量 击拳 硬气",
"width": 128, "height": 128, "formats": "png",
},
"鞭炮": {
"sticker_id": "191", "package_id": "1003", "name": "鞭炮",
"description": "过年 喜庆 爆竹 春节 噼里啪啦 红",
"width": 128, "height": 128, "formats": "png",
},
"烟花": {
"sticker_id": "258", "package_id": "1003", "name": "烟花",
"description": "庆典 漂亮 新年 嘭 绽放 节日快乐",
"width": 128, "height": 128, "formats": "png",
},
}
def get_sticker_by_name(name: str) -> Optional[dict]:
"""
按名称查找贴纸支持模糊匹配
匹配优先级
1. 完全相等name
2. name 包含查询词前缀/子串
3. description 包含查询词同义词搜索
4. 通用模糊评分 sticker-search 同算法命中即返回得分最高的一条
返回 sticker dict找不到返回 None
"""
if not name:
return None
query = name.strip()
if query in STICKER_MAP:
return STICKER_MAP[query]
for key, sticker in STICKER_MAP.items():
if query in key or key in query:
return sticker
for sticker in STICKER_MAP.values():
desc = sticker.get("description", "")
if query in desc:
return sticker
matches = search_stickers(query, limit=1)
return matches[0] if matches else None
def get_random_sticker(category: str = None) -> dict:
"""
随机返回一个贴纸
若指定 category则在 description 中含有该关键词的贴纸里随机选取
category None 时从全表随机
"""
if category:
candidates = [
s for s in STICKER_MAP.values()
if category in s.get("description", "") or category in s.get("name", "")
]
if candidates:
return random.choice(candidates)
return random.choice(list(STICKER_MAP.values()))
def get_sticker_by_id(sticker_id: str) -> Optional[dict]:
"""按 sticker_id 精确查找贴纸。"""
if not sticker_id:
return None
sid = str(sticker_id).strip()
for sticker in STICKER_MAP.values():
if sticker.get("sticker_id") == sid:
return sticker
return None
# ---------------------------------------------------------------------------
# 模糊搜索(对齐 chatbot-web yuanbao-openclaw-plugin/sticker-cache.ts.searchStickers
# ---------------------------------------------------------------------------
_PUNCT_RE = re.compile(r"[\s\u3000\-_·.,,。!?\"“”'‘’、/\\]+")
def _normalize_text(raw: str) -> str:
return unicodedata.normalize("NFKC", str(raw or "")).strip().lower()
def _compact_text(raw: str) -> str:
return _PUNCT_RE.sub("", _normalize_text(raw))
def _multiset_char_hit_ratio(needle: str, haystack: str) -> float:
if not needle:
return 0.0
bag: dict[str, int] = {}
for ch in haystack:
bag[ch] = bag.get(ch, 0) + 1
hits = 0
for ch in needle:
n = bag.get(ch, 0)
if n > 0:
hits += 1
bag[ch] = n - 1
return hits / len(needle)
def _bigram_jaccard(a: str, b: str) -> float:
if len(a) < 2 or len(b) < 2:
return 0.0
A = {a[i:i + 2] for i in range(len(a) - 1)}
B = {b[i:i + 2] for i in range(len(b) - 1)}
inter = len(A & B)
union = len(A) + len(B) - inter
return inter / union if union else 0.0
def _longest_subsequence_ratio(needle: str, haystack: str) -> float:
if not needle:
return 0.0
j = 0
for ch in haystack:
if j >= len(needle):
break
if ch == needle[j]:
j += 1
return j / len(needle)
def _score_field(haystack: str, query: str) -> float:
hay = _normalize_text(haystack)
q = _normalize_text(query)
if not hay or not q:
return 0.0
hay_c = _compact_text(haystack)
q_c = _compact_text(query)
best = 0.0
if hay == q:
best = max(best, 100.0)
if q in hay:
best = max(best, 92 + min(6, len(q)))
if len(q) >= 2 and hay.startswith(q):
best = max(best, 88.0)
if q_c and q_c in hay_c:
best = max(best, 86.0)
best = max(best, _multiset_char_hit_ratio(q_c, hay_c) * 62)
best = max(best, _bigram_jaccard(q_c, hay_c) * 58)
best = max(best, _longest_subsequence_ratio(q_c, hay_c) * 52)
if len(q) == 1 and q in hay:
best = max(best, 68.0)
return best
def search_stickers(query: str, limit: int = 10) -> list[dict]:
"""
在内置贴纸表中按模糊匹配排序返回前 N 条结果
评分综合 name/description 字段的子串字符多重集覆盖bigram Jaccard子序列比例
name 权重略高于 description×0.88 query 时按字典顺序返回前 N
"""
safe_limit = max(1, min(500, int(limit) if limit else 10))
if not query or not _normalize_text(query):
return list(STICKER_MAP.values())[:safe_limit]
scored: list[tuple[float, dict]] = []
for sticker in STICKER_MAP.values():
name_s = _score_field(sticker.get("name", ""), query)
desc_s = _score_field(sticker.get("description", ""), query) * 0.88
sid = str(sticker.get("sticker_id", "")).strip()
q_norm = _normalize_text(query)
id_s = 0.0
if sid and q_norm:
sid_norm = _normalize_text(sid)
if sid_norm == q_norm:
id_s = 100.0
elif q_norm in sid_norm:
id_s = 84.0
scored.append((max(name_s, desc_s, id_s), sticker))
scored.sort(key=lambda x: x[0], reverse=True)
top = scored[0][0] if scored else 0
if top <= 0:
return [s for _, s in scored[:safe_limit]]
if top >= 22:
floor = 18.0
elif top >= 12:
floor = max(10.0, top * 0.5)
else:
floor = max(6.0, top * 0.35)
filtered = [pair for pair in scored if pair[0] >= floor]
out = filtered if filtered else scored
return [s for _, s in out[:safe_limit]]
def build_face_msg_body(
face_index: int,
face_type: int = 1,
data: Optional[str] = None,
) -> list:
"""
构造 TIMFaceElem 消息体
Yuanbao 约定
- index 固定传 0服务端通过 data 字段识别具体表情
- data JSON 字符串包含 sticker_id / package_id 等字段
Args:
face_index: 保留字段暂时不影响 wire formatYuanbao 固定 index=0
face_index > 0 时视为旧版 QQ 表情 ID直接放入 index
face_type: 保留字段兼容旧接口当前未使用
data: 已序列化的 JSON 字符串 None 时仅传 index
Returns:
符合 Yuanbao TIM 协议的 msg_body list::
[{"msg_type": "TIMFaceElem", "msg_content": {"index": 0, "data": "..."}}]
"""
msg_content: dict = {"index": face_index}
if data is not None:
msg_content["data"] = data
return [{"msg_type": "TIMFaceElem", "msg_content": msg_content}]
def build_sticker_msg_body(sticker: dict) -> list:
"""
STICKER_MAP 中的 sticker dict 直接构造 TIMFaceElem 消息体
这是 send_sticker() 的内部辅助确保 data 字段与原始 JS 插件一致
"""
data_payload = json.dumps(
{
"sticker_id": sticker["sticker_id"],
"package_id": sticker["package_id"],
"width": sticker.get("width", 128),
"height": sticker.get("height", 128),
"formats": sticker.get("formats", "png"),
"name": sticker["name"],
},
ensure_ascii=False,
separators=(",", ":"),
)
return build_face_msg_body(face_index=0, data=data_payload)
+568 -1475
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-150
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@@ -1,150 +0,0 @@
"""Gateway runtime-metadata footer.
Renders a compact footer showing runtime state (model, context %, cwd) and
appends it to the FINAL message of an agent turn when enabled. Off by default
to keep replies minimal.
Config (``~/.hermes/config.yaml``)::
display:
runtime_footer:
enabled: true # off by default
fields: [model, context_pct, cwd] # order shown; drop any to hide
Per-platform overrides live under ``display.platforms.<platform>.runtime_footer``.
Users can toggle the global setting with ``/footer on|off`` from both the CLI
and any gateway platform.
The footer is appended to the final response text in ``gateway/run.py`` right
before returning the response to the adapter send path so it only lands on
the final message a user sees, not on tool-progress updates or streaming
partials. When streaming is on and the final text has already been delivered
piecemeal, the footer is sent as a separate trailing message via
``send_trailing_footer()``.
"""
from __future__ import annotations
import os
from pathlib import Path
from typing import Any, Iterable, Optional
_DEFAULT_FIELDS: tuple[str, ...] = ("model", "context_pct", "cwd")
_SEP = " · "
def _home_relative_cwd(cwd: str) -> str:
"""Return *cwd* with ``$HOME`` collapsed to ``~``. Empty string if unset."""
if not cwd:
return ""
try:
home = os.path.expanduser("~")
p = os.path.abspath(cwd)
if home and (p == home or p.startswith(home + os.sep)):
return "~" + p[len(home):]
return p
except Exception:
return cwd
def _model_short(model: Optional[str]) -> str:
"""Drop ``vendor/`` prefix for readability (``openai/gpt-5.4`` → ``gpt-5.4``)."""
if not model:
return ""
return model.rsplit("/", 1)[-1]
def resolve_footer_config(
user_config: dict[str, Any] | None,
platform_key: str | None = None,
) -> dict[str, Any]:
"""Resolve effective runtime-footer config for *platform_key*.
Merge order (later wins):
1. Built-in defaults (enabled=False)
2. ``display.runtime_footer``
3. ``display.platforms.<platform_key>.runtime_footer``
"""
resolved = {"enabled": False, "fields": list(_DEFAULT_FIELDS)}
cfg = (user_config or {}).get("display") or {}
global_cfg = cfg.get("runtime_footer")
if isinstance(global_cfg, dict):
if "enabled" in global_cfg:
resolved["enabled"] = bool(global_cfg.get("enabled"))
if isinstance(global_cfg.get("fields"), list) and global_cfg["fields"]:
resolved["fields"] = [str(f) for f in global_cfg["fields"]]
if platform_key:
platforms = cfg.get("platforms") or {}
plat_cfg = platforms.get(platform_key)
if isinstance(plat_cfg, dict):
plat_footer = plat_cfg.get("runtime_footer")
if isinstance(plat_footer, dict):
if "enabled" in plat_footer:
resolved["enabled"] = bool(plat_footer.get("enabled"))
if isinstance(plat_footer.get("fields"), list) and plat_footer["fields"]:
resolved["fields"] = [str(f) for f in plat_footer["fields"]]
return resolved
def format_runtime_footer(
*,
model: Optional[str],
context_tokens: int,
context_length: Optional[int],
cwd: Optional[str] = None,
fields: Iterable[str] = _DEFAULT_FIELDS,
) -> str:
"""Render the footer line, or return "" if no fields have data.
Fields are skipped silently when their underlying data is missing a
partially-populated footer is better than a line with ``?%`` or empty slots.
"""
parts: list[str] = []
for field in fields:
if field == "model":
m = _model_short(model)
if m:
parts.append(m)
elif field == "context_pct":
if context_length and context_length > 0 and context_tokens >= 0:
pct = max(0, min(100, round((context_tokens / context_length) * 100)))
parts.append(f"{pct}%")
elif field == "cwd":
rel = _home_relative_cwd(cwd or os.environ.get("TERMINAL_CWD", ""))
if rel:
parts.append(rel)
# Unknown field names are silently ignored.
if not parts:
return ""
return _SEP.join(parts)
def build_footer_line(
*,
user_config: dict[str, Any] | None,
platform_key: str | None,
model: Optional[str],
context_tokens: int,
context_length: Optional[int],
cwd: Optional[str] = None,
) -> str:
"""Top-level entry point used by gateway/run.py.
Returns the footer text (empty string when disabled or no data). Callers
append this to the final response themselves, preserving a single blank
line of separation.
"""
cfg = resolve_footer_config(user_config, platform_key)
if not cfg.get("enabled"):
return ""
return format_runtime_footer(
model=model,
context_tokens=context_tokens,
context_length=context_length,
cwd=cwd,
fields=cfg.get("fields") or _DEFAULT_FIELDS,
)
+35 -113
View File
@@ -60,10 +60,6 @@ from .config import (
SessionResetPolicy, # noqa: F401 — re-exported via gateway/__init__.py
HomeChannel,
)
from .whatsapp_identity import (
canonical_whatsapp_identifier,
)
from utils import atomic_replace
@dataclass
@@ -87,9 +83,6 @@ class SessionSource:
user_id_alt: Optional[str] = None # Platform-specific stable alt ID (Signal UUID, Feishu union_id)
chat_id_alt: Optional[str] = None # Signal group internal ID
is_bot: bool = False # True when the message author is a bot/webhook (Discord)
guild_id: Optional[str] = None # Discord guild / Slack workspace / Matrix server scope
parent_chat_id: Optional[str] = None # Parent channel when chat_id refers to a thread
message_id: Optional[str] = None # ID of the triggering message (for pin/reply/react)
@property
def description(self) -> str:
@@ -127,14 +120,8 @@ class SessionSource:
d["user_id_alt"] = self.user_id_alt
if self.chat_id_alt:
d["chat_id_alt"] = self.chat_id_alt
if self.guild_id:
d["guild_id"] = self.guild_id
if self.parent_chat_id:
d["parent_chat_id"] = self.parent_chat_id
if self.message_id:
d["message_id"] = self.message_id
return d
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "SessionSource":
return cls(
@@ -148,9 +135,6 @@ class SessionSource:
chat_topic=data.get("chat_topic"),
user_id_alt=data.get("user_id_alt"),
chat_id_alt=data.get("chat_id_alt"),
guild_id=data.get("guild_id"),
parent_chat_id=data.get("parent_chat_id"),
message_id=data.get("message_id"),
)
@@ -202,31 +186,6 @@ that requires raw IDs). Discord is excluded because mentions use ``<@user_id>``
and the LLM needs the real ID to tag users."""
def _discord_tools_loaded() -> bool:
"""True iff the agent will actually have Discord tools this session.
Two conditions must hold:
1. The `discord` or `discord_admin` toolset is enabled for the
Discord platform via `hermes tools` (opt-in, default OFF).
2. `DISCORD_BOT_TOKEN` is set the tool's `check_fn` gates on it
at registry time, so the toolset being enabled in config is not
enough if the token isn't configured.
Returns False (safe default keeps the stale-API disclaimer) on any
error so a bad config can't silently promise tools the agent lacks.
"""
if not (os.environ.get("DISCORD_BOT_TOKEN") or "").strip():
return False
try:
from hermes_cli.config import load_config
from hermes_cli.tools_config import _get_platform_tools
cfg = load_config()
enabled = _get_platform_tools(cfg, "discord", include_default_mcp_servers=False)
return "discord" in enabled or "discord_admin" in enabled
except Exception:
return False
def build_session_context_prompt(
context: SessionContext,
*,
@@ -310,57 +269,17 @@ def build_session_context_prompt(
"**Platform notes:** You are running inside Slack. "
"You do NOT have access to Slack-specific APIs — you cannot search "
"channel history, pin/unpin messages, manage channels, or list users. "
"Do not promise to perform these actions. The gateway may inline the "
"current message's Slack block/attachment payload when available, but "
"you still cannot call Slack APIs yourself."
"Do not promise to perform these actions. If the user asks, explain "
"that you can only read messages sent directly to you and respond."
)
elif context.source.platform == Platform.DISCORD:
# Inject the Discord IDs block only when the agent actually has
# Discord tools loaded this session — i.e. the user opted into
# `discord` / `discord_admin` via `hermes tools` AND the bot
# token is configured. Otherwise keep the stale-API disclaimer
# honest so we never promise tools the agent lacks.
if _discord_tools_loaded():
src = context.source
id_lines = ["", "**Discord IDs (for the `discord` / `discord_admin` tools):**"]
if src.guild_id:
id_lines.append(f" - Guild: `{src.guild_id}`")
if src.thread_id and src.parent_chat_id:
id_lines.append(f" - Parent channel: `{src.parent_chat_id}`")
id_lines.append(f" - Thread: `{src.thread_id}` (use as `channel_id` for fetch_messages etc.)")
else:
id_lines.append(f" - Channel: `{src.chat_id}`")
if src.message_id:
id_lines.append(f" - Triggering message: `{src.message_id}`")
lines.extend(id_lines)
else:
lines.append("")
lines.append(
"**Platform notes:** You are running inside Discord. "
"You do NOT have access to Discord-specific APIs — you cannot search "
"channel history, pin messages, manage roles, or list server members. "
"Do not promise to perform these actions. If the user asks, explain "
"that you can only read messages sent directly to you and respond."
)
elif context.source.platform == Platform.BLUEBUBBLES:
lines.append("")
lines.append(
"**Platform notes:** You are responding via iMessage. "
"Keep responses short and conversational — think texts, not essays. "
"Structure longer replies as separate short thoughts, each separated "
"by a blank line (double newline). Each block between blank lines "
"will be delivered as its own iMessage bubble, so write accordingly: "
"one idea per bubble, 13 sentences each. "
"If the user needs a detailed answer, give the short version first "
"and offer to elaborate."
)
elif context.source.platform == Platform.YUANBAO:
lines.append("")
lines.append(
"**Platform notes:** You are running inside Yuanbao. "
"You CAN send private (DM) messages via the send_message tool. "
"Use target='yuanbao:direct:<account_id>' for DM "
"and target='yuanbao:group:<group_code>' for group chat."
"**Platform notes:** You are running inside Discord. "
"You do NOT have access to Discord-specific APIs — you cannot search "
"channel history, pin messages, manage roles, or list server members. "
"Do not promise to perform these actions. If the user asks, explain "
"that you can only read messages sent directly to you and respond."
)
# Connected platforms
@@ -448,11 +367,11 @@ class SessionEntry:
auto_reset_reason: Optional[str] = None # "idle" or "daily"
reset_had_activity: bool = False # whether the expired session had any messages
# Set by the background expiry watcher after it finalizes an expired
# session (invoking on_session_finalize hooks and evicting the cached
# agent). Persisted to sessions.json so the flag survives gateway
# restarts — prevents redundant finalization runs.
expiry_finalized: bool = False
# Set by the background expiry watcher after it successfully flushes
# memories for this session. Persisted to sessions.json so the flag
# survives gateway restarts (the old in-memory _pre_flushed_sessions
# set was lost on restart, causing redundant re-flushes).
memory_flushed: bool = False
# When True the next call to get_or_create_session() will auto-reset
# this session (create a new session_id) so the user starts fresh.
@@ -488,7 +407,7 @@ class SessionEntry:
"last_prompt_tokens": self.last_prompt_tokens,
"estimated_cost_usd": self.estimated_cost_usd,
"cost_status": self.cost_status,
"expiry_finalized": self.expiry_finalized,
"memory_flushed": self.memory_flushed,
"suspended": self.suspended,
"resume_pending": self.resume_pending,
"resume_reason": self.resume_reason,
@@ -540,7 +459,7 @@ class SessionEntry:
last_prompt_tokens=data.get("last_prompt_tokens", 0),
estimated_cost_usd=data.get("estimated_cost_usd", 0.0),
cost_status=data.get("cost_status", "unknown"),
expiry_finalized=data.get("expiry_finalized", data.get("memory_flushed", False)),
memory_flushed=data.get("memory_flushed", False),
suspended=data.get("suspended", False),
resume_pending=data.get("resume_pending", False),
resume_reason=data.get("resume_reason"),
@@ -599,24 +518,15 @@ def build_session_key(
"""
platform = source.platform.value
if source.chat_type == "dm":
dm_chat_id = source.chat_id
if source.platform == Platform.WHATSAPP:
dm_chat_id = canonical_whatsapp_identifier(source.chat_id)
if dm_chat_id:
if source.chat_id:
if source.thread_id:
return f"agent:main:{platform}:dm:{dm_chat_id}:{source.thread_id}"
return f"agent:main:{platform}:dm:{dm_chat_id}"
return f"agent:main:{platform}:dm:{source.chat_id}:{source.thread_id}"
return f"agent:main:{platform}:dm:{source.chat_id}"
if source.thread_id:
return f"agent:main:{platform}:dm:{source.thread_id}"
return f"agent:main:{platform}:dm"
participant_id = source.user_id_alt or source.user_id
if participant_id and source.platform == Platform.WHATSAPP:
# Same JID/LID-flip bug as the DM case: without canonicalisation, a
# single group member gets two isolated per-user sessions when the
# bridge reshuffles alias forms.
participant_id = canonical_whatsapp_identifier(str(participant_id)) or participant_id
key_parts = ["agent:main", platform, source.chat_type]
if source.chat_id:
@@ -705,7 +615,7 @@ class SessionStore:
json.dump(data, f, indent=2)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, sessions_file)
os.replace(tmp_path, sessions_file)
except BaseException:
try:
os.unlink(tmp_path)
@@ -1241,7 +1151,6 @@ class SessionStore:
reasoning_content=message.get("reasoning_content") if message.get("role") == "assistant" else None,
reasoning_details=message.get("reasoning_details") if message.get("role") == "assistant" else None,
codex_reasoning_items=message.get("codex_reasoning_items") if message.get("role") == "assistant" else None,
codex_message_items=message.get("codex_message_items") if message.get("role") == "assistant" else None,
)
except Exception as e:
logger.debug("Session DB operation failed: %s", e)
@@ -1257,11 +1166,24 @@ class SessionStore:
Used by /retry, /undo, and /compress to persist modified conversation history.
Rewrites both SQLite and legacy JSONL storage.
"""
# SQLite: replace atomically so a mid-rewrite failure doesn't leave
# the session half-empty in the DB while JSONL still has history.
# SQLite: clear old messages and re-insert
if self._db:
try:
self._db.replace_messages(session_id, messages)
self._db.clear_messages(session_id)
for msg in messages:
role = msg.get("role", "unknown")
self._db.append_message(
session_id=session_id,
role=role,
content=msg.get("content"),
tool_name=msg.get("tool_name"),
tool_calls=msg.get("tool_calls"),
tool_call_id=msg.get("tool_call_id"),
reasoning=msg.get("reasoning") if role == "assistant" else None,
reasoning_content=msg.get("reasoning_content") if role == "assistant" else None,
reasoning_details=msg.get("reasoning_details") if role == "assistant" else None,
codex_reasoning_items=msg.get("codex_reasoning_items") if role == "assistant" else None,
)
except Exception as e:
logger.debug("Failed to rewrite transcript in DB: %s", e)
-145
View File
@@ -44,14 +44,6 @@ class StreamConsumerConfig:
buffer_threshold: int = 40
cursor: str = ""
buffer_only: bool = False
# When >0, the final edit for a streamed response is delivered as a
# fresh message if the original preview has been visible for at least
# this many seconds. This makes the platform's visible timestamp
# reflect completion time instead of first-token time for long-running
# responses (e.g. reasoning models that stream slowly). Ported from
# openclaw/openclaw#72038. Default 0 = always edit in place (legacy
# behavior). The gateway enables this selectively per-platform.
fresh_final_after_seconds: float = 0.0
class GatewayStreamConsumer:
@@ -91,29 +83,14 @@ class GatewayStreamConsumer:
chat_id: str,
config: Optional[StreamConsumerConfig] = None,
metadata: Optional[dict] = None,
on_new_message: Optional[callable] = None,
):
self.adapter = adapter
self.chat_id = chat_id
self.cfg = config or StreamConsumerConfig()
self.metadata = metadata
# Fired whenever a fresh content bubble is created on the platform
# (first-send of a new message, commentary, overflow chunk, or
# fallback continuation). The gateway uses this to linearize the
# tool-progress bubble: when content resumes after a tool batch,
# the next tool.started should open a NEW progress bubble below
# the content, not edit the old bubble above it.
# Called with no arguments. Exceptions are swallowed.
self._on_new_message = on_new_message
self._queue: queue.Queue = queue.Queue()
self._accumulated = ""
self._message_id: Optional[str] = None
# Wall-clock timestamp (time.monotonic) when ``_message_id`` was
# first assigned from a successful first-send. Used by the
# fresh-final logic to detect long-lived previews whose edit
# timestamps would be stale by completion time. Ported from
# openclaw/openclaw#72038.
self._message_created_ts: Optional[float] = None
self._already_sent = False
self._edit_supported = True # Disabled when progressive edits are no longer usable
self._last_edit_time = 0.0
@@ -155,21 +132,10 @@ class GatewayStreamConsumer:
if text:
self._queue.put((_COMMENTARY, text))
def _notify_new_message(self) -> None:
"""Fire the on_new_message callback, swallowing any errors."""
cb = self._on_new_message
if cb is None:
return
try:
cb()
except Exception:
logger.debug("on_new_message callback error", exc_info=True)
def _reset_segment_state(self, *, preserve_no_edit: bool = False) -> None:
if preserve_no_edit and self._message_id == "__no_edit__":
return
self._message_id = None
self._message_created_ts = None
self._accumulated = ""
self._last_sent_text = ""
self._fallback_final_send = False
@@ -548,9 +514,6 @@ class GatewayStreamConsumer:
self._message_id = str(result.message_id)
self._already_sent = True
self._last_sent_text = text
# Fresh content bubble — close off any stale tool bubble
# above so the next tool starts a new bubble below.
self._notify_new_message()
return str(result.message_id)
else:
self._edit_supported = False
@@ -683,9 +646,6 @@ class GatewayStreamConsumer:
sent_any_chunk = True
last_successful_chunk = chunk
last_message_id = result.message_id or last_message_id
# Each fallback chunk is a fresh platform message — notify
# so any stale tool-progress bubble gets closed off.
self._notify_new_message()
self._message_id = last_message_id
self._already_sent = True
@@ -769,91 +729,11 @@ class GatewayStreamConsumer:
# tool..."), not the final response. Setting already_sent would cause
# the final response to be incorrectly suppressed when there are
# multiple tool calls. See: https://github.com/NousResearch/hermes-agent/issues/10454
if result.success:
# Commentary counts as fresh content — close off any
# stale tool bubble above it so the next tool starts a
# new bubble below.
self._notify_new_message()
return result.success
except Exception as e:
logger.error("Commentary send error: %s", e)
return False
def _should_send_fresh_final(self) -> bool:
"""Return True when a long-lived preview should be replaced with a
fresh final message instead of an edit.
Conditions:
- Fresh-final is enabled (``fresh_final_after_seconds > 0``).
- We have a real preview message id (not the ``__no_edit__`` sentinel
and not ``None``).
- The preview has been visible for at least the configured threshold.
Ported from openclaw/openclaw#72038.
"""
threshold = getattr(self.cfg, "fresh_final_after_seconds", 0.0) or 0.0
if threshold <= 0:
return False
if not self._message_id or self._message_id == "__no_edit__":
return False
if self._message_created_ts is None:
return False
age = time.monotonic() - self._message_created_ts
return age >= threshold
async def _try_fresh_final(self, text: str) -> bool:
"""Send ``text`` as a brand-new message (best-effort delete the old
preview) so the platform's visible timestamp reflects completion
time. Returns True on successful delivery, False on any failure so
the caller falls back to the normal edit path.
Ported from openclaw/openclaw#72038.
"""
old_message_id = self._message_id
try:
result = await self.adapter.send(
chat_id=self.chat_id,
content=text,
metadata=self.metadata,
)
except Exception as e:
logger.debug("Fresh-final send failed, falling back to edit: %s", e)
return False
if not getattr(result, "success", False):
return False
# Successful fresh send — try to delete the stale preview so the
# user doesn't see the old edit-stuck message underneath. Cleanup
# is best-effort; platforms that don't implement ``delete_message``
# just leave the preview behind (still an acceptable outcome —
# the visible final timestamp is the important part).
if old_message_id and old_message_id != "__no_edit__":
delete_fn = getattr(self.adapter, "delete_message", None)
if delete_fn is not None:
try:
await delete_fn(self.chat_id, old_message_id)
except Exception as e:
logger.debug(
"Fresh-final preview cleanup failed (%s): %s",
old_message_id, e,
)
# Adopt the new message id as the current message so subsequent
# callers (e.g. overflow split loops, finalize retries) see a
# consistent state.
new_message_id = getattr(result, "message_id", None)
if new_message_id:
self._message_id = new_message_id
self._message_created_ts = time.monotonic()
else:
# Send succeeded but platform didn't return an id — treat the
# delivery as final-only and fall back to "__no_edit__" so we
# don't try to edit something we can't address.
self._message_id = "__no_edit__"
self._message_created_ts = None
self._already_sent = True
self._last_sent_text = text
self._final_response_sent = True
return True
async def _send_or_edit(self, text: str, *, finalize: bool = False) -> bool:
"""Send or edit the streaming message.
@@ -906,22 +786,6 @@ class GatewayStreamConsumer:
finalize and self._adapter_requires_finalize
):
return True
# Fresh-final for long-lived previews: when finalizing
# the last edit in a streaming sequence, if the
# original preview has been visible for at least
# ``fresh_final_after_seconds``, send the completed
# reply as a fresh message so the platform's visible
# timestamp reflects completion time instead of the
# preview creation time. Best-effort cleanup of the
# old preview follows. Ported from
# openclaw/openclaw#72038. Gated by config so the
# legacy edit-in-place path stays the default.
if (
finalize
and self._should_send_fresh_final()
and await self._try_fresh_final(text)
):
return True
# Edit existing message
result = await self.adapter.edit_message(
chat_id=self.chat_id,
@@ -988,10 +852,6 @@ class GatewayStreamConsumer:
if result.success:
if result.message_id:
self._message_id = result.message_id
# Track when the preview first became visible to
# the user so fresh-final logic can detect stale
# preview timestamps on long-running responses.
self._message_created_ts = time.monotonic()
else:
self._edit_supported = False
self._already_sent = True
@@ -1003,11 +863,6 @@ class GatewayStreamConsumer:
# every delta/tool boundary when platforms accept a
# message but do not return an editable message id.
self._message_id = "__no_edit__"
# Notify the gateway that a fresh content bubble was
# created so any accumulated tool-progress bubble above
# gets closed off — the next tool fires into a new
# bubble below, preserving chronological order.
self._notify_new_message()
return True
else:
# Initial send failed — disable streaming for this session
-155
View File
@@ -1,155 +0,0 @@
"""Shared helpers for canonicalising WhatsApp sender identity.
WhatsApp's bridge can surface the same human under two different JID shapes
within a single conversation:
- LID form: ``999999999999999@lid``
- Phone form: ``15551234567@s.whatsapp.net``
Both the authorisation path (:mod:`gateway.run`) and the session-key path
(:mod:`gateway.session`) need to collapse these aliases to a single stable
identity. This module is the single source of truth for that resolution so
the two paths can never drift apart.
Public helpers:
- :func:`normalize_whatsapp_identifier` strip JID/LID/device/plus syntax
down to the bare numeric identifier.
- :func:`canonical_whatsapp_identifier` walk the bridge's
``lid-mapping-*.json`` files and return a stable canonical identity
across phone/LID variants.
- :func:`expand_whatsapp_aliases` return the full alias set for an
identifier. Used by authorisation code that needs to match any known
form of a sender against an allow-list.
Plugins that need per-sender behaviour on WhatsApp (role-based routing,
per-contact authorisation, policy gating in a gateway hook) should use
``canonical_whatsapp_identifier`` so their bookkeeping lines up with
Hermes' own session keys.
"""
from __future__ import annotations
import json
import logging
import re
from typing import Set
logger = logging.getLogger(__name__)
# WhatsApp JIDs are numeric (or plus-prefixed numeric) with optional
# ``@``, ``.`` and ``:`` separators. ``\w`` is pinned to ASCII so
# full-width digits / Unicode word chars can't sneak through.
_SAFE_IDENTIFIER_RE = re.compile(r"^[A-Za-z0-9@.+\-]+$")
from hermes_constants import get_hermes_home
def normalize_whatsapp_identifier(value: str) -> str:
"""Strip WhatsApp JID/LID syntax down to its stable numeric identifier.
Accepts any of the identifier shapes the WhatsApp bridge may emit:
``"60123456789@s.whatsapp.net"``, ``"60123456789:47@s.whatsapp.net"``,
``"60123456789@lid"``, or a bare ``"+601****6789"`` / ``"60123456789"``.
Returns just the numeric identifier (``"60123456789"``) suitable for
equality comparisons.
Useful for plugins that want to match sender IDs against
user-supplied config (phone numbers in ``config.yaml``) without
worrying about which variant the bridge happens to deliver.
"""
return (
str(value or "")
.strip()
.replace("+", "", 1)
.split(":", 1)[0]
.split("@", 1)[0]
)
def expand_whatsapp_aliases(identifier: str) -> Set[str]:
"""Resolve WhatsApp phone/LID aliases via bridge session mapping files.
Returns the set of all identifiers transitively reachable through the
bridge's ``$HERMES_HOME/whatsapp/session/lid-mapping-*.json`` files,
starting from ``identifier``. The result always includes the
normalized input itself, so callers can safely ``in`` check against
the return value without a separate fallback branch.
Returns an empty set if ``identifier`` normalizes to empty.
"""
normalized = normalize_whatsapp_identifier(identifier)
if not normalized:
return set()
session_dir = get_hermes_home() / "whatsapp" / "session"
resolved: Set[str] = set()
queue = [normalized]
while queue:
current = queue.pop(0)
if not current or current in resolved:
continue
# Defense-in-depth: reject identifiers that could sneak path
# separators / traversal segments into the ``lid-mapping-{current}``
# filename below. The hardcoded ``lid-mapping-`` prefix already
# prevents escape via pathlib's component split (an attacker can't
# create ``lid-mapping-..`` as a real directory in session_dir), but
# this keeps the identifier space to the characters WhatsApp JIDs
# actually use and avoids depending on that filesystem-layout
# invariant.
if not _SAFE_IDENTIFIER_RE.match(current):
continue
resolved.add(current)
for suffix in ("", "_reverse"):
mapping_path = session_dir / f"lid-mapping-{current}{suffix}.json"
if not mapping_path.exists():
continue
try:
mapped = normalize_whatsapp_identifier(
json.loads(mapping_path.read_text(encoding="utf-8"))
)
except (OSError, json.JSONDecodeError) as exc:
logger.debug("whatsapp_identity: failed to read %s: %s", mapping_path, exc)
continue
if mapped and mapped not in resolved:
queue.append(mapped)
return resolved
def canonical_whatsapp_identifier(identifier: str) -> str:
"""Return a stable WhatsApp sender identity across phone-JID/LID variants.
WhatsApp may surface the same person under either a phone-format JID
(``60123456789@s.whatsapp.net``) or a LID (``1234567890@lid``). This
applies to a DM ``chat_id`` *and* to the ``participant_id`` of a
member inside a group chat both represent a user identity, and the
bridge may flip between the two for the same human.
This helper reads the bridge's ``whatsapp/session/lid-mapping-*.json``
files, walks the mapping transitively, and picks the shortest
(numeric-preferred) alias as the canonical identity.
:func:`gateway.session.build_session_key` uses this for both WhatsApp
DM chat_ids and WhatsApp group participant_ids, so callers get the
same session-key identity Hermes itself uses.
Plugins that need per-sender behaviour (role-based routing,
authorisation, per-contact policy) should use this so their
bookkeeping lines up with Hermes' session bookkeeping even when
the bridge reshuffles aliases.
Returns an empty string if ``identifier`` normalizes to empty. If no
mapping files exist yet (fresh bridge install), returns the
normalized input unchanged.
"""
normalized = normalize_whatsapp_identifier(identifier)
if not normalized:
return ""
# expand_whatsapp_aliases always includes `normalized` itself in the
# returned set, so the min() below degrades gracefully to `normalized`
# when no lid-mapping files are present.
aliases = expand_whatsapp_aliases(normalized)
return min(aliases, key=lambda candidate: (len(candidate), candidate))
+9 -428
View File
@@ -43,7 +43,6 @@ import yaml
from hermes_cli.config import get_hermes_home, get_config_path, read_raw_config
from hermes_constants import OPENROUTER_BASE_URL
from utils import atomic_replace
logger = logging.getLogger(__name__)
@@ -72,14 +71,6 @@ DEFAULT_AGENT_KEY_MIN_TTL_SECONDS = 30 * 60 # 30 minutes
ACCESS_TOKEN_REFRESH_SKEW_SECONDS = 120 # refresh 2 min before expiry
DEVICE_AUTH_POLL_INTERVAL_CAP_SECONDS = 1 # poll at most every 1s
DEFAULT_CODEX_BASE_URL = "https://chatgpt.com/backend-api/codex"
MINIMAX_OAUTH_CLIENT_ID = "78257093-7e40-4613-99e0-527b14b39113"
MINIMAX_OAUTH_SCOPE = "group_id profile model.completion"
MINIMAX_OAUTH_GRANT_TYPE = "urn:ietf:params:oauth:grant-type:user_code"
MINIMAX_OAUTH_GLOBAL_BASE = "https://api.minimax.io"
MINIMAX_OAUTH_CN_BASE = "https://api.minimaxi.com"
MINIMAX_OAUTH_GLOBAL_INFERENCE = "https://api.minimax.io/anthropic"
MINIMAX_OAUTH_CN_INFERENCE = "https://api.minimaxi.com/anthropic"
MINIMAX_OAUTH_REFRESH_SKEW_SECONDS = 60
DEFAULT_QWEN_BASE_URL = "https://portal.qwen.ai/v1"
DEFAULT_GITHUB_MODELS_BASE_URL = "https://api.githubcopilot.com"
DEFAULT_COPILOT_ACP_BASE_URL = "acp://copilot"
@@ -118,12 +109,6 @@ SERVICE_PROVIDER_NAMES: Dict[str, str] = {
DEFAULT_GEMINI_CLOUDCODE_BASE_URL = "cloudcode-pa://google"
GEMINI_OAUTH_ACCESS_TOKEN_REFRESH_SKEW_SECONDS = 60 # refresh 60s before expiry
# LM Studio's default no-auth mode still requires *some* non-empty bearer for
# the API-key code paths (auxiliary_client, runtime resolver) to treat the
# provider as configured. This sentinel is sent only to LM Studio, never to
# any remote service.
LMSTUDIO_NOAUTH_PLACEHOLDER = "dummy-lm-api-key"
# =============================================================================
# Provider Registry
@@ -134,7 +119,7 @@ class ProviderConfig:
"""Describes a known inference provider."""
id: str
name: str
auth_type: str # "oauth_device_code", "oauth_external", "oauth_minimax", or "api_key"
auth_type: str # "oauth_device_code", "oauth_external", or "api_key"
portal_base_url: str = ""
inference_base_url: str = ""
client_id: str = ""
@@ -174,14 +159,6 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
auth_type="oauth_external",
inference_base_url=DEFAULT_GEMINI_CLOUDCODE_BASE_URL,
),
"lmstudio": ProviderConfig(
id="lmstudio",
name="LM Studio",
auth_type="api_key",
inference_base_url="http://127.0.0.1:1234/v1",
api_key_env_vars=("LM_API_KEY",),
base_url_env_var="LM_BASE_URL",
),
"copilot": ProviderConfig(
id="copilot",
name="GitHub Copilot",
@@ -247,14 +224,6 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
api_key_env_vars=("ARCEEAI_API_KEY",),
base_url_env_var="ARCEE_BASE_URL",
),
"gmi": ProviderConfig(
id="gmi",
name="GMI Cloud",
auth_type="api_key",
inference_base_url="https://api.gmi-serving.com/v1",
api_key_env_vars=("GMI_API_KEY",),
base_url_env_var="GMI_BASE_URL",
),
"minimax": ProviderConfig(
id="minimax",
name="MiniMax",
@@ -263,17 +232,6 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
api_key_env_vars=("MINIMAX_API_KEY",),
base_url_env_var="MINIMAX_BASE_URL",
),
"minimax-oauth": ProviderConfig(
id="minimax-oauth",
name="MiniMax (OAuth \u00b7 minimax.io)",
auth_type="oauth_minimax",
portal_base_url=MINIMAX_OAUTH_GLOBAL_BASE,
inference_base_url=MINIMAX_OAUTH_GLOBAL_INFERENCE,
client_id=MINIMAX_OAUTH_CLIENT_ID,
scope=MINIMAX_OAUTH_SCOPE,
extra={"region": "global", "cn_portal_base_url": MINIMAX_OAUTH_CN_BASE,
"cn_inference_base_url": MINIMAX_OAUTH_CN_INFERENCE},
),
"anthropic": ProviderConfig(
id="anthropic",
name="Anthropic",
@@ -382,14 +340,6 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
api_key_env_vars=("XIAOMI_API_KEY",),
base_url_env_var="XIAOMI_BASE_URL",
),
"tencent-tokenhub": ProviderConfig(
id="tencent-tokenhub",
name="Tencent TokenHub",
auth_type="api_key",
inference_base_url="https://tokenhub.tencentmaas.com/v1",
api_key_env_vars=("TOKENHUB_API_KEY",),
base_url_env_var="TOKENHUB_BASE_URL",
),
"ollama-cloud": ProviderConfig(
id="ollama-cloud",
name="Ollama Cloud",
@@ -406,14 +356,6 @@ PROVIDER_REGISTRY: Dict[str, ProviderConfig] = {
api_key_env_vars=(),
base_url_env_var="BEDROCK_BASE_URL",
),
"azure-foundry": ProviderConfig(
id="azure-foundry",
name="Azure Foundry",
auth_type="api_key",
inference_base_url="", # User-provided endpoint
api_key_env_vars=("AZURE_FOUNDRY_API_KEY",),
base_url_env_var="AZURE_FOUNDRY_BASE_URL",
),
}
@@ -517,27 +459,11 @@ def _resolve_api_key_provider_secret(
pass
return "", ""
from hermes_cli.config import get_env_value
for env_var in pconfig.api_key_env_vars:
# Check both os.environ and ~/.hermes/.env file
val = (get_env_value(env_var) or "").strip()
val = os.getenv(env_var, "").strip()
if has_usable_secret(val):
return val, env_var
# Fallback: try credential pool (e.g. zai key stored via auth.json)
try:
from agent.credential_pool import load_pool
pool = load_pool(provider_id)
if pool and pool.has_credentials():
entry = pool.peek()
if entry:
key = getattr(entry, "access_token", "") or getattr(entry, "runtime_api_key", "")
key = str(key).strip()
if has_usable_secret(key):
return key, f"credential_pool:{provider_id}"
except Exception:
pass
return "", ""
@@ -817,18 +743,7 @@ def _load_auth_store(auth_file: Optional[Path] = None) -> Dict[str, Any]:
try:
raw = json.loads(auth_file.read_text())
except Exception as exc:
corrupt_path = auth_file.with_suffix(".json.corrupt")
try:
import shutil
shutil.copy2(auth_file, corrupt_path)
except Exception:
pass
logger.warning(
"auth: failed to parse %s (%s) — starting with empty store. "
"Corrupt file preserved at %s",
auth_file, exc, corrupt_path,
)
except Exception:
return {"version": AUTH_STORE_VERSION, "providers": {}}
if isinstance(raw, dict) and (
@@ -862,7 +777,7 @@ def _save_auth_store(auth_store: Dict[str, Any]) -> Path:
handle.write(payload)
handle.flush()
os.fsync(handle.fileno())
atomic_replace(tmp_path, auth_file)
os.replace(tmp_path, auth_file)
try:
dir_fd = os.open(str(auth_file.parent), os.O_RDONLY)
except OSError:
@@ -1170,9 +1085,7 @@ def resolve_provider(
"kimi-cn": "kimi-coding-cn", "moonshot-cn": "kimi-coding-cn",
"step": "stepfun", "stepfun-coding-plan": "stepfun",
"arcee-ai": "arcee", "arceeai": "arcee",
"gmi-cloud": "gmi", "gmicloud": "gmi",
"minimax-china": "minimax-cn", "minimax_cn": "minimax-cn",
"minimax-portal": "minimax-oauth", "minimax-global": "minimax-oauth", "minimax_oauth": "minimax-oauth",
"alibaba_coding": "alibaba-coding-plan", "alibaba-coding": "alibaba-coding-plan",
"alibaba_coding_plan": "alibaba-coding-plan",
"claude": "anthropic", "claude-code": "anthropic",
@@ -1184,13 +1097,11 @@ def resolve_provider(
"qwen-portal": "qwen-oauth", "qwen-cli": "qwen-oauth", "qwen-oauth": "qwen-oauth", "google-gemini-cli": "google-gemini-cli", "gemini-cli": "google-gemini-cli", "gemini-oauth": "google-gemini-cli",
"hf": "huggingface", "hugging-face": "huggingface", "huggingface-hub": "huggingface",
"mimo": "xiaomi", "xiaomi-mimo": "xiaomi",
"tencent": "tencent-tokenhub", "tokenhub": "tencent-tokenhub",
"tencent-cloud": "tencent-tokenhub", "tencentmaas": "tencent-tokenhub",
"aws": "bedrock", "aws-bedrock": "bedrock", "amazon-bedrock": "bedrock", "amazon": "bedrock",
"go": "opencode-go", "opencode-go-sub": "opencode-go",
"kilo": "kilocode", "kilo-code": "kilocode", "kilo-gateway": "kilocode",
"lmstudio": "lmstudio", "lm-studio": "lmstudio", "lm_studio": "lmstudio",
# Local server aliases — route through the generic custom provider
"lmstudio": "custom", "lm-studio": "custom", "lm_studio": "custom",
"ollama": "custom", "ollama_cloud": "ollama-cloud",
"vllm": "custom", "llamacpp": "custom",
"llama.cpp": "custom", "llama-cpp": "custom",
@@ -1237,11 +1148,8 @@ def resolve_provider(
continue
# GitHub tokens are commonly present for repo/tool access but should not
# hijack inference auto-selection unless the user explicitly chooses
# Copilot/GitHub Models as the provider. LM Studio is a local server
# whose availability isn't implied by LM_API_KEY presence (it may be
# offline, and the no-auth setup uses a placeholder value), so it
# also requires explicit selection.
if pid in ("copilot", "lmstudio"):
# Copilot/GitHub Models as the provider.
if pid == "copilot":
continue
for env_var in pconfig.api_key_env_vars:
if has_usable_secret(os.getenv(env_var, "")):
@@ -3519,13 +3427,6 @@ def resolve_api_key_provider_credentials(provider_id: str) -> Dict[str, Any]:
key_source = ""
api_key, key_source = _resolve_api_key_provider_secret(provider_id, pconfig)
# No-auth LM Studio: substitute a placeholder so runtime / auxiliary_client
# see the local server as configured. doctor still reports unconfigured
# because get_api_key_provider_status uses the raw secret resolver.
if not api_key and provider_id == "lmstudio":
api_key = LMSTUDIO_NOAUTH_PLACEHOLDER
key_source = key_source or "default"
env_url = ""
if pconfig.base_url_env_var:
env_url = os.getenv(pconfig.base_url_env_var, "").strip()
@@ -4136,326 +4037,6 @@ def _codex_device_code_login() -> Dict[str, Any]:
}
# ==================== MiniMax Portal OAuth ====================
def _minimax_pkce_pair() -> tuple:
"""Generate (code_verifier, code_challenge_S256, state) for MiniMax OAuth."""
import secrets
verifier = secrets.token_urlsafe(64)[:96]
challenge = base64.urlsafe_b64encode(
hashlib.sha256(verifier.encode()).digest()
).decode().rstrip("=")
state = secrets.token_urlsafe(16)
return verifier, challenge, state
def _minimax_request_user_code(
client: httpx.Client, *, portal_base_url: str, client_id: str,
code_challenge: str, state: str,
) -> Dict[str, Any]:
response = client.post(
f"{portal_base_url}/oauth/code",
data={
"response_type": "code",
"client_id": client_id,
"scope": MINIMAX_OAUTH_SCOPE,
"code_challenge": code_challenge,
"code_challenge_method": "S256",
"state": state,
},
headers={
"Content-Type": "application/x-www-form-urlencoded",
"Accept": "application/json",
"x-request-id": str(uuid.uuid4()),
},
)
if response.status_code != 200:
raise AuthError(
f"MiniMax OAuth authorization failed: {response.text or response.reason_phrase}",
provider="minimax-oauth", code="authorization_failed",
)
payload = response.json()
for field in ("user_code", "verification_uri", "expired_in"):
if field not in payload:
raise AuthError(
f"MiniMax OAuth response missing field: {field}",
provider="minimax-oauth", code="authorization_incomplete",
)
if payload.get("state") != state:
raise AuthError(
"MiniMax OAuth state mismatch (possible CSRF).",
provider="minimax-oauth", code="state_mismatch",
)
return payload
def _minimax_poll_token(
client: httpx.Client, *, portal_base_url: str, client_id: str,
user_code: str, code_verifier: str, expired_in: int, interval_ms: Optional[int],
) -> Dict[str, Any]:
# OpenClaw treats expired_in as a unix-ms timestamp (Date.now() < expireTimeMs).
# Defensive parsing: if it's small enough to be a duration, treat as seconds.
import time as _time
now_ms = int(_time.time() * 1000)
if expired_in > now_ms // 2:
# Looks like a unix-ms timestamp.
deadline = expired_in / 1000.0
else:
# Treat as duration in seconds from now.
deadline = _time.time() + max(1, expired_in)
interval = max(2.0, (interval_ms or 2000) / 1000.0)
while _time.time() < deadline:
response = client.post(
f"{portal_base_url}/oauth/token",
data={
"grant_type": MINIMAX_OAUTH_GRANT_TYPE,
"client_id": client_id,
"user_code": user_code,
"code_verifier": code_verifier,
},
headers={
"Content-Type": "application/x-www-form-urlencoded",
"Accept": "application/json",
},
)
try:
payload = response.json() if response.text else {}
except Exception:
payload = {}
if response.status_code != 200:
msg = (payload.get("base_resp", {}) or {}).get("status_msg") or response.text
raise AuthError(
f"MiniMax OAuth error: {msg or 'unknown'}",
provider="minimax-oauth", code="token_exchange_failed",
)
status = payload.get("status")
if status == "error":
raise AuthError(
"MiniMax OAuth reported an error. Please try again later.",
provider="minimax-oauth", code="authorization_denied",
)
if status == "success":
if not all(payload.get(k) for k in ("access_token", "refresh_token", "expired_in")):
raise AuthError(
"MiniMax OAuth success payload missing required token fields.",
provider="minimax-oauth", code="token_incomplete",
)
return payload
# "pending" or any other status -> keep polling
_time.sleep(interval)
raise AuthError(
"MiniMax OAuth timed out before authorization completed.",
provider="minimax-oauth", code="timeout",
)
def _minimax_save_auth_state(auth_state: Dict[str, Any]) -> None:
"""Persist MiniMax OAuth state to Hermes auth store (~/.hermes/auth.json)."""
with _auth_store_lock():
auth_store = _load_auth_store()
_save_provider_state(auth_store, "minimax-oauth", auth_state)
_save_auth_store(auth_store)
def _minimax_oauth_login(
*, region: str = "global", open_browser: bool = True,
timeout_seconds: float = 15.0,
) -> Dict[str, Any]:
"""Run MiniMax OAuth flow, persist tokens, return auth state dict."""
pconfig = PROVIDER_REGISTRY["minimax-oauth"]
if region == "cn":
portal_base_url = pconfig.extra["cn_portal_base_url"]
inference_base_url = pconfig.extra["cn_inference_base_url"]
else:
portal_base_url = pconfig.portal_base_url
inference_base_url = pconfig.inference_base_url
verifier, challenge, state = _minimax_pkce_pair()
if _is_remote_session():
open_browser = False
print(f"Starting Hermes login via MiniMax ({region}) OAuth...")
print(f"Portal: {portal_base_url}")
with httpx.Client(timeout=httpx.Timeout(timeout_seconds),
headers={"Accept": "application/json"}) as client:
code_data = _minimax_request_user_code(
client, portal_base_url=portal_base_url,
client_id=pconfig.client_id,
code_challenge=challenge, state=state,
)
verification_url = str(code_data["verification_uri"])
user_code = str(code_data["user_code"])
print()
print("To continue:")
print(f" 1. Open: {verification_url}")
print(f" 2. If prompted, enter code: {user_code}")
if open_browser:
if webbrowser.open(verification_url):
print(" (Opened browser for verification)")
else:
print(" Could not open browser automatically -- use the URL above.")
interval_raw = code_data.get("interval")
interval_ms = int(interval_raw) if interval_raw is not None else None
print("Waiting for approval...")
token_data = _minimax_poll_token(
client, portal_base_url=portal_base_url,
client_id=pconfig.client_id,
user_code=user_code, code_verifier=verifier,
expired_in=int(code_data["expired_in"]),
interval_ms=interval_ms,
)
now = datetime.now(timezone.utc)
expires_in_s = int(token_data["expired_in"])
expires_at = now.timestamp() + expires_in_s
auth_state = {
"provider": "minimax-oauth",
"region": region,
"portal_base_url": portal_base_url,
"inference_base_url": inference_base_url,
"client_id": pconfig.client_id,
"scope": MINIMAX_OAUTH_SCOPE,
"token_type": token_data.get("token_type", "Bearer"),
"access_token": token_data["access_token"],
"refresh_token": token_data["refresh_token"],
"resource_url": token_data.get("resource_url"),
"obtained_at": now.isoformat(),
"expires_at": datetime.fromtimestamp(expires_at, tz=timezone.utc).isoformat(),
"expires_in": expires_in_s,
}
_minimax_save_auth_state(auth_state)
print("\u2713 MiniMax OAuth login successful.")
if msg := token_data.get("notification_message"):
print(f"Note from MiniMax: {msg}")
return auth_state
def _refresh_minimax_oauth_state(
state: Dict[str, Any], *, timeout_seconds: float = 15.0,
force: bool = False,
) -> Dict[str, Any]:
"""Refresh MiniMax OAuth access token if close to expiry (or forced)."""
if not state.get("refresh_token"):
raise AuthError(
"MiniMax OAuth state has no refresh_token; please re-login.",
provider="minimax-oauth", code="no_refresh_token", relogin_required=True,
)
try:
expires_at = datetime.fromisoformat(state.get("expires_at", "")).timestamp()
except Exception:
expires_at = 0.0
now = time.time()
if not force and (expires_at - now) > MINIMAX_OAUTH_REFRESH_SKEW_SECONDS:
return state
portal_base_url = state["portal_base_url"]
with httpx.Client(timeout=httpx.Timeout(timeout_seconds)) as client:
response = client.post(
f"{portal_base_url}/oauth/token",
data={
"grant_type": "refresh_token",
"client_id": state["client_id"],
"refresh_token": state["refresh_token"],
},
headers={
"Content-Type": "application/x-www-form-urlencoded",
"Accept": "application/json",
},
)
if response.status_code != 200:
body = response.text.lower()
relogin = any(m in body for m in
("invalid_grant", "refresh_token_reused", "invalid_refresh_token"))
raise AuthError(
f"MiniMax OAuth refresh failed: {response.text or response.reason_phrase}",
provider="minimax-oauth", code="refresh_failed",
relogin_required=relogin,
)
payload = response.json()
if payload.get("status") != "success":
raise AuthError(
"MiniMax OAuth refresh did not return success.",
provider="minimax-oauth", code="refresh_failed",
relogin_required=True,
)
now_dt = datetime.now(timezone.utc)
expires_in_s = int(payload["expired_in"])
new_state = dict(state)
new_state.update({
"access_token": payload["access_token"],
"refresh_token": payload.get("refresh_token", state["refresh_token"]),
"obtained_at": now_dt.isoformat(),
"expires_at": datetime.fromtimestamp(now_dt.timestamp() + expires_in_s,
tz=timezone.utc).isoformat(),
"expires_in": expires_in_s,
})
_minimax_save_auth_state(new_state)
return new_state
def resolve_minimax_oauth_runtime_credentials(
*, min_token_ttl_seconds: int = MINIMAX_OAUTH_REFRESH_SKEW_SECONDS,
) -> Dict[str, Any]:
"""Return {provider, api_key, base_url, source} for minimax-oauth."""
state = get_provider_auth_state("minimax-oauth")
if not state or not state.get("access_token"):
raise AuthError(
"Not logged into MiniMax OAuth. Run `hermes model` and select "
"MiniMax (OAuth).",
provider="minimax-oauth", code="not_logged_in", relogin_required=True,
)
state = _refresh_minimax_oauth_state(state)
return {
"provider": "minimax-oauth",
"api_key": state["access_token"],
"base_url": state["inference_base_url"].rstrip("/"),
"source": "oauth",
}
def get_minimax_oauth_auth_status() -> Dict[str, Any]:
"""Return auth status dict for MiniMax OAuth provider."""
state = get_provider_auth_state("minimax-oauth")
if not state or not state.get("access_token"):
return {"logged_in": False, "provider": "minimax-oauth"}
try:
expires_at = datetime.fromisoformat(state.get("expires_at", "")).timestamp()
token_valid = (expires_at - time.time()) > 0
except Exception:
token_valid = bool(state.get("access_token"))
return {
"logged_in": token_valid,
"provider": "minimax-oauth",
"region": state.get("region", "global"),
"expires_at": state.get("expires_at"),
}
def _login_minimax_oauth(args, pconfig: ProviderConfig) -> None:
"""CLI entry for MiniMax OAuth login."""
region = getattr(args, "region", None) or "global"
open_browser = not getattr(args, "no_browser", False)
timeout = getattr(args, "timeout", None) or 15.0
try:
_minimax_oauth_login(
region=region, open_browser=open_browser, timeout_seconds=timeout,
)
except AuthError as exc:
print(format_auth_error(exc))
raise SystemExit(1)
def _nous_device_code_login(
*,
portal_base_url: Optional[str] = None,
@@ -4644,10 +4225,10 @@ def _login_nous(args, pconfig: ProviderConfig) -> None:
)
from hermes_cli.models import (
get_curated_nous_model_ids, get_pricing_for_provider,
_PROVIDER_MODELS, get_pricing_for_provider,
check_nous_free_tier, partition_nous_models_by_tier,
)
model_ids = get_curated_nous_model_ids()
model_ids = _PROVIDER_MODELS.get("nous", [])
print()
unavailable_models: list = []
+2 -23
View File
@@ -33,7 +33,7 @@ from hermes_constants import OPENROUTER_BASE_URL
# Providers that support OAuth login in addition to API keys.
_OAUTH_CAPABLE_PROVIDERS = {"anthropic", "nous", "openai-codex", "qwen-oauth", "google-gemini-cli", "minimax-oauth"}
_OAUTH_CAPABLE_PROVIDERS = {"anthropic", "nous", "openai-codex", "qwen-oauth", "google-gemini-cli"}
def _get_custom_provider_names() -> list:
@@ -170,7 +170,7 @@ def auth_add_command(args) -> None:
if provider.startswith(CUSTOM_POOL_PREFIX):
requested_type = AUTH_TYPE_API_KEY
else:
requested_type = AUTH_TYPE_OAUTH if provider in {"anthropic", "nous", "openai-codex", "qwen-oauth", "google-gemini-cli", "minimax-oauth"} else AUTH_TYPE_API_KEY
requested_type = AUTH_TYPE_OAUTH if provider in {"anthropic", "nous", "openai-codex", "qwen-oauth", "google-gemini-cli"} else AUTH_TYPE_API_KEY
pool = load_pool(provider)
@@ -333,27 +333,6 @@ def auth_add_command(args) -> None:
print(f'Added {provider} OAuth credential #{len(pool.entries())}: "{entry.label}"')
return
if provider == "minimax-oauth":
from hermes_cli.auth import resolve_minimax_oauth_runtime_credentials
creds = resolve_minimax_oauth_runtime_credentials()
label = (getattr(args, "label", None) or "").strip() or label_from_token(
creds["api_key"],
_oauth_default_label(provider, len(pool.entries()) + 1),
)
entry = PooledCredential(
provider=provider,
id=uuid.uuid4().hex[:6],
label=label,
auth_type=AUTH_TYPE_OAUTH,
priority=0,
source=f"{SOURCE_MANUAL}:minimax_oauth",
access_token=creds["api_key"],
base_url=creds.get("base_url"),
)
pool.add_entry(entry)
print(f'Added {provider} OAuth credential #{len(pool.entries())}: "{entry.label}"')
return
raise SystemExit(f"`hermes auth add {provider}` is not implemented for auth type {requested_type} yet.")
-300
View File
@@ -1,300 +0,0 @@
"""Azure Foundry endpoint auto-detection.
Inspect an Azure AI Foundry / Azure OpenAI endpoint to determine:
- API transport (OpenAI-style ``chat_completions`` vs
Anthropic-style ``anthropic_messages``)
- Available models (best effort Azure does not expose a deployment
listing via the inference API key, but Azure OpenAI v1 endpoints
return the resource's model catalog via ``GET /models``)
- Context length for each discovered/entered model, via the existing
:func:`agent.model_metadata.get_model_context_length` resolver.
Rationale:
Azure has no pure-API-key deployment-listing endpoint per Microsoft,
deployment enumeration requires ARM management-plane auth. Azure
OpenAI v1 endpoints ``{resource}.openai.azure.com/openai/v1`` do return
a ``/models`` list, but it reflects the resource's *available* models
rather than the user's *deployed* deployment names. In practice it is
still a useful hint the user picks a familiar model name and we look
up its context length from the catalog.
The detector never crashes on errors (every HTTP call is wrapped in a
broad try/except). Callers get a :class:`DetectionResult` with whatever
information could be gathered, and fall back to manual entry for the
rest.
"""
from __future__ import annotations
import json
import logging
import re
from dataclasses import dataclass, field
from typing import Optional
from urllib import request as urllib_request
from urllib.error import HTTPError, URLError
from urllib.parse import urlparse
logger = logging.getLogger(__name__)
# Default Azure OpenAI ``api-version`` to probe with. The v1 GA endpoint
# accepts requests without ``api-version`` entirely, so this is only used
# as a fallback for pre-v1 resources that still require it.
_AZURE_OPENAI_PROBE_API_VERSIONS = (
"2025-04-01-preview",
"2024-10-21", # oldest GA that supports /models
)
# Default Azure Anthropic ``api-version``. Matches the value used by
# ``agent/anthropic_adapter.py`` when building the Anthropic client.
_AZURE_ANTHROPIC_API_VERSION = "2025-04-15"
@dataclass
class DetectionResult:
"""Everything auto-detection could gather from a base URL + API key."""
#: Detected API transport: ``"chat_completions"``,
#: ``"anthropic_messages"``, or ``None`` when detection failed.
api_mode: Optional[str] = None
#: Deployment / model IDs returned by ``/models`` (best effort).
#: Empty when the endpoint doesn't expose the list with an API key.
models: list[str] = field(default_factory=list)
#: Lowercased host from the base URL (used for display messages).
hostname: str = ""
#: Human-readable reason the detector chose ``api_mode``. Useful
#: for explaining auto-detection to the user in the wizard.
reason: str = ""
#: ``True`` when ``/models`` returned a valid OpenAI-shaped payload.
models_probe_ok: bool = False
#: ``True`` when the URL was determined to be an Anthropic-style
#: endpoint (from path suffix or live probe).
is_anthropic: bool = False
def _http_get_json(url: str, api_key: str, timeout: float = 6.0) -> tuple[int, Optional[dict]]:
"""GET a URL with ``api-key`` + ``Authorization`` headers. Return
``(status_code, parsed_json_or_None)``. Never raises."""
req = urllib_request.Request(url, method="GET")
# Azure OpenAI uses ``api-key``. Some Azure deployments (and
# Anthropic-style routes) use ``Authorization: Bearer``. Send both
# so we probe once per URL rather than twice.
req.add_header("api-key", api_key)
req.add_header("Authorization", f"Bearer {api_key}")
req.add_header("User-Agent", "hermes-agent/azure-detect")
try:
with urllib_request.urlopen(req, timeout=timeout) as resp:
body = resp.read()
try:
return resp.status, json.loads(body.decode("utf-8", errors="replace"))
except Exception:
return resp.status, None
except HTTPError as exc:
return exc.code, None
except (URLError, TimeoutError, OSError) as exc:
logger.debug("azure_detect: GET %s failed: %s", url, exc)
return 0, None
except Exception as exc: # pragma: no cover — defensive
logger.debug("azure_detect: GET %s unexpected error: %s", url, exc)
return 0, None
def _strip_trailing_v1(url: str) -> str:
"""Strip trailing ``/v1`` or ``/v1/`` so we can construct sub-paths."""
return re.sub(r"/v1/?$", "", url.rstrip("/"))
def _looks_like_anthropic_path(url: str) -> bool:
"""Return True when the URL's path ends in ``/anthropic`` or
contains a ``/anthropic/`` segment. Used by Azure Foundry
resources that route Claude traffic through a dedicated path."""
try:
parsed = urlparse(url)
path = (parsed.path or "").lower().rstrip("/")
return path.endswith("/anthropic") or "/anthropic/" in path + "/"
except Exception:
return False
def _extract_model_ids(payload: dict) -> list[str]:
"""Extract a list of model IDs from an OpenAI-shaped ``/models``
response. Returns ``[]`` on any shape mismatch."""
data = payload.get("data") if isinstance(payload, dict) else None
if not isinstance(data, list):
return []
ids: list[str] = []
for item in data:
if not isinstance(item, dict):
continue
# OpenAI shape: {"id": "gpt-5.4", "object": "model", ...}
mid = item.get("id") or item.get("model") or item.get("name")
if isinstance(mid, str) and mid:
ids.append(mid)
return ids
def _probe_openai_models(base_url: str, api_key: str) -> tuple[bool, list[str]]:
"""Probe ``<base>/models`` for an OpenAI-shaped response.
Returns ``(ok, models)``. ``ok`` is True iff the endpoint accepted
us as an OpenAI-style caller (200 OK + OpenAI-shaped JSON body).
"""
base_url = base_url.rstrip("/")
# Azure OpenAI v1: {resource}.openai.azure.com/openai/v1 — no
# api-version required for GA paths, so probe without first.
candidates = [f"{base_url}/models"]
# Fallback: explicit api-version for pre-v1 resources
for v in _AZURE_OPENAI_PROBE_API_VERSIONS:
candidates.append(f"{base_url}/models?api-version={v}")
for url in candidates:
status, body = _http_get_json(url, api_key)
if status == 200 and body is not None:
ids = _extract_model_ids(body)
if ids:
logger.info(
"azure_detect: /models probe OK at %s (%d models)",
url, len(ids),
)
return True, ids
# 200 + empty list still counts as "OpenAI shape, no models
# listed" — let the user proceed with manual entry.
if isinstance(body, dict) and "data" in body:
return True, []
return False, []
def _probe_anthropic_messages(base_url: str, api_key: str) -> bool:
"""Send a zero-token request to ``<base>/v1/messages`` and check
whether the endpoint at least *recognises* the Anthropic Messages
shape (any 4xx that mentions ``messages`` or ``model``, or a 400
``invalid_request`` with an Anthropic error shape). Never completes
a real chat.
"""
base = _strip_trailing_v1(base_url)
url = f"{base}/v1/messages?api-version={_AZURE_ANTHROPIC_API_VERSION}"
payload = json.dumps({
"model": "probe",
"max_tokens": 1,
"messages": [{"role": "user", "content": "ping"}],
}).encode("utf-8")
req = urllib_request.Request(url, method="POST", data=payload)
req.add_header("api-key", api_key)
req.add_header("Authorization", f"Bearer {api_key}")
req.add_header("anthropic-version", "2023-06-01")
req.add_header("content-type", "application/json")
req.add_header("User-Agent", "hermes-agent/azure-detect")
try:
with urllib_request.urlopen(req, timeout=6.0) as resp:
# Should never 200 — "probe" isn't a real deployment. But
# if it does, the endpoint definitely speaks Anthropic.
return resp.status < 500
except HTTPError as exc:
# 4xx with an Anthropic-shaped error body = Anthropic endpoint.
try:
body = exc.read().decode("utf-8", errors="replace")
lowered = body.lower()
if "anthropic" in lowered or '"type"' in lowered and '"error"' in lowered:
return True
# Pre-Azure-v1 Azure Foundry returns a plain 404 for
# Anthropic-style calls on non-Anthropic deployments. A
# 400 "model not found" IS Anthropic though.
if exc.code == 400 and ("messages" in lowered or "model" in lowered):
return True
return False
except Exception:
return False
except (URLError, TimeoutError, OSError):
return False
except Exception: # pragma: no cover
return False
def detect(base_url: str, api_key: str) -> DetectionResult:
"""Inspect an Azure endpoint and describe its transport + models.
Call this from the wizard before asking the user to pick an API
mode manually. The caller should treat the returned
:class:`DetectionResult` as *advisory* if ``api_mode`` is None,
fall back to asking the user.
"""
result = DetectionResult()
try:
parsed = urlparse(base_url)
result.hostname = (parsed.hostname or "").lower()
except Exception:
result.hostname = ""
# 1. Path sniff. Azure Foundry exposes Anthropic-style deployments
# under a dedicated ``/anthropic`` path.
if _looks_like_anthropic_path(base_url):
result.is_anthropic = True
result.api_mode = "anthropic_messages"
result.reason = "URL path ends in /anthropic → Anthropic Messages API"
return result
# 2. Try the OpenAI-style /models probe. If this works, the
# endpoint definitely speaks OpenAI wire.
ok, models = _probe_openai_models(base_url, api_key)
if ok:
result.models_probe_ok = True
result.models = models
result.api_mode = "chat_completions"
result.reason = (
f"GET /models returned {len(models)} model(s) — OpenAI-style endpoint"
if models
else "GET /models returned an OpenAI-shaped empty list — OpenAI-style endpoint"
)
return result
# 3. Fallback: probe the Anthropic Messages shape. Slower and more
# intrusive than /models, so only run it when the OpenAI probe
# failed.
if _probe_anthropic_messages(base_url, api_key):
result.is_anthropic = True
result.api_mode = "anthropic_messages"
result.reason = "Endpoint accepts Anthropic Messages shape"
return result
# Nothing matched. Caller falls back to manual selection.
result.reason = (
"Could not probe endpoint (private network, missing model list, or "
"non-standard path) — falling back to manual API-mode selection"
)
return result
def lookup_context_length(model: str, base_url: str, api_key: str) -> Optional[int]:
"""Thin wrapper around :func:`agent.model_metadata.get_model_context_length`
that returns ``None`` when only the fallback default (128k) would
fire, so the wizard can distinguish "we actually know this" from
"we guessed."""
try:
from agent.model_metadata import (
DEFAULT_FALLBACK_CONTEXT,
get_model_context_length,
)
except Exception:
return None
try:
n = get_model_context_length(model, base_url=base_url, api_key=api_key)
except Exception as exc:
logger.debug("azure_detect: context length lookup failed: %s", exc)
return None
if isinstance(n, int) and n > 0 and n != DEFAULT_FALLBACK_CONTEXT:
return n
return None
__all__ = ["DetectionResult", "detect", "lookup_context_length"]
+1 -272
View File
@@ -36,23 +36,12 @@ _EXCLUDED_DIRS = {
"__pycache__", # bytecode caches — regenerated on import
".git", # nested git dirs (profiles shouldn't have these, but safety)
"node_modules", # js deps if website/ somehow leaks in
"backups", # prior auto-backups — don't nest backups exponentially
"checkpoints", # session-local trajectory caches — regenerated per-session,
# session-hash-keyed so they don't port to another machine anyway
}
# File-name suffixes to skip
_EXCLUDED_SUFFIXES = (
".pyc",
".pyo",
# SQLite sidecar files — the backup takes a consistent snapshot of ``*.db``
# via ``sqlite3.backup()``, so shipping the live WAL / shared-memory /
# rollback-journal alongside would pair a fresh snapshot with stale sidecar
# state and produce a torn restore on the next open. They're transient and
# regenerated on first connection anyway.
".db-wal",
".db-shm",
".db-journal",
)
# File names to skip (runtime state that's meaningless on another machine)
@@ -465,12 +454,6 @@ def run_import(args) -> None:
# Critical state files to include in quick snapshots (relative to HERMES_HOME).
# Everything else is either regeneratable (logs, cache) or managed separately
# (skills, repo, sessions/).
#
# Entries may be individual files OR directories. Directories are captured
# recursively; missing entries are silently skipped. Pairing data lives in
# platform-specific JSON blobs outside state.db, so it's listed here explicitly
# — `hermes update` snapshots this set before pulling so approved-user lists
# are recoverable if anything goes wrong (issue #15733).
_QUICK_STATE_FILES = (
"state.db",
"config.yaml",
@@ -480,10 +463,6 @@ _QUICK_STATE_FILES = (
"gateway_state.json",
"channel_directory.json",
"processes.json",
# Pairing stores (generic + per-platform JSONs outside state.db)
"pairing", # legacy location (gateway/pairing.py)
"platforms/pairing", # new location (gateway/pairing.py)
"feishu_comment_pairing.json", # Feishu comment subscription pairings
)
_QUICK_SNAPSHOTS_DIR = "state-snapshots"
@@ -519,27 +498,7 @@ def create_quick_snapshot(
for rel in _QUICK_STATE_FILES:
src = home / rel
if not src.exists():
continue
if src.is_dir():
# Walk the directory and record each file individually in the
# manifest so restore can treat them uniformly. Empty dirs are
# skipped (nothing to snapshot).
for sub in src.rglob("*"):
if not sub.is_file():
continue
sub_rel = sub.relative_to(home).as_posix()
dst = snap_dir / sub_rel
dst.parent.mkdir(parents=True, exist_ok=True)
try:
shutil.copy2(sub, dst)
manifest[sub_rel] = dst.stat().st_size
except (OSError, PermissionError) as exc:
logger.warning("Could not snapshot %s: %s", sub_rel, exc)
continue
if not src.is_file():
if not src.exists() or not src.is_file():
continue
dst = snap_dir / rel
@@ -694,233 +653,3 @@ def run_quick_backup(args) -> None:
print(f" Restore with: /snapshot restore {snap_id}")
else:
print("No state files found to snapshot.")
# ---------------------------------------------------------------------------
# Shared full-zip backup helper
# ---------------------------------------------------------------------------
def _write_full_zip_backup(out_path: Path, hermes_root: Path) -> Optional[Path]:
"""Write a full zip snapshot of ``hermes_root`` to ``out_path``.
Uses the same exclusion rules and SQLite safe-copy as :func:`run_backup`.
Returns the output path on success, None on failure (nothing to back up,
or write error caller should surface the outcome but not raise).
"""
files_to_add: list[tuple[Path, Path]] = []
try:
for dirpath, dirnames, filenames in os.walk(hermes_root, followlinks=False):
dp = Path(dirpath)
# Prune excluded directories in-place so os.walk doesn't descend
dirnames[:] = [d for d in dirnames if d not in _EXCLUDED_DIRS]
for fname in filenames:
fpath = dp / fname
try:
rel = fpath.relative_to(hermes_root)
except ValueError:
continue
if _should_exclude(rel):
continue
# Skip the output zip itself if it already exists inside root.
try:
if fpath.resolve() == out_path.resolve():
continue
except (OSError, ValueError):
pass
files_to_add.append((fpath, rel))
except OSError as exc:
logger.warning("Full-zip backup: walk failed: %s", exc)
return None
if not files_to_add:
return None
try:
with zipfile.ZipFile(out_path, "w", zipfile.ZIP_DEFLATED, compresslevel=6) as zf:
for abs_path, rel_path in files_to_add:
try:
if abs_path.suffix == ".db":
with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as tmp:
tmp_db = Path(tmp.name)
try:
if _safe_copy_db(abs_path, tmp_db):
zf.write(tmp_db, arcname=str(rel_path))
finally:
tmp_db.unlink(missing_ok=True)
else:
zf.write(abs_path, arcname=str(rel_path))
except (PermissionError, OSError, ValueError) as exc:
logger.debug("Skipping %s in zip backup: %s", rel_path, exc)
continue
except OSError as exc:
logger.warning("Full-zip backup: zip write failed: %s", exc)
# Best-effort cleanup of partial file
try:
out_path.unlink(missing_ok=True)
except OSError:
pass
return None
return out_path
# ---------------------------------------------------------------------------
# Pre-update auto-backup
# ---------------------------------------------------------------------------
_PRE_UPDATE_BACKUPS_DIR = "backups"
_PRE_UPDATE_PREFIX = "pre-update-"
_PRE_UPDATE_DEFAULT_KEEP = 5
def _pre_update_backup_dir(hermes_home: Optional[Path] = None) -> Path:
home = hermes_home or get_hermes_home()
return home / _PRE_UPDATE_BACKUPS_DIR
def _prune_pre_update_backups(backup_dir: Path, keep: int) -> int:
"""Remove oldest pre-update backups beyond the keep limit.
Returns the number of files deleted. Only touches files matching
``pre-update-*.zip`` so hand-made zips dropped in the same directory
are never touched.
"""
if keep < 0:
keep = 0
if not backup_dir.exists():
return 0
backups = sorted(
(p for p in backup_dir.iterdir()
if p.is_file() and p.name.startswith(_PRE_UPDATE_PREFIX) and p.suffix.lower() == ".zip"),
key=lambda p: p.name,
reverse=True,
)
deleted = 0
for p in backups[keep:]:
try:
p.unlink()
deleted += 1
except OSError as exc:
logger.warning("Failed to prune backup %s: %s", p.name, exc)
return deleted
def create_pre_update_backup(
hermes_home: Optional[Path] = None,
keep: int = _PRE_UPDATE_DEFAULT_KEEP,
) -> Optional[Path]:
"""Create a full zip backup of HERMES_HOME under ``backups/``.
Mirrors :func:`run_backup` (same exclusion rules, same SQLite safe-copy)
but writes to ``<HERMES_HOME>/backups/pre-update-<timestamp>.zip`` and
auto-prunes old pre-update backups.
Returns the path to the created zip, or ``None`` if no files were
found or the backup could not be created. Never raises the caller
(``hermes update``) should continue even if the backup fails.
"""
hermes_root = hermes_home or get_default_hermes_root()
if not hermes_root.is_dir():
return None
backup_dir = _pre_update_backup_dir(hermes_root)
try:
backup_dir.mkdir(parents=True, exist_ok=True)
except OSError as exc:
logger.warning("Could not create pre-update backup dir %s: %s", backup_dir, exc)
return None
stamp = datetime.now().strftime("%Y-%m-%d-%H%M%S")
out_path = backup_dir / f"{_PRE_UPDATE_PREFIX}{stamp}.zip"
result = _write_full_zip_backup(out_path, hermes_root)
if result is None:
return None
_prune_pre_update_backups(backup_dir, keep=keep)
return out_path
# ---------------------------------------------------------------------------
# Pre-migration auto-backup (used by `hermes claw migrate`)
# ---------------------------------------------------------------------------
_PRE_MIGRATION_PREFIX = "pre-migration-"
_PRE_MIGRATION_DEFAULT_KEEP = 5
def _prune_pre_migration_backups(backup_dir: Path, keep: int) -> int:
"""Remove oldest pre-migration backups beyond the keep limit.
Only touches files matching ``pre-migration-*.zip`` so other backups in
the same directory are never touched.
"""
if keep < 0:
keep = 0
if not backup_dir.exists():
return 0
backups = sorted(
(p for p in backup_dir.iterdir()
if p.is_file() and p.name.startswith(_PRE_MIGRATION_PREFIX) and p.suffix.lower() == ".zip"),
key=lambda p: p.name,
reverse=True,
)
deleted = 0
for p in backups[keep:]:
try:
p.unlink()
deleted += 1
except OSError as exc:
logger.warning("Failed to prune pre-migration backup %s: %s", p.name, exc)
return deleted
def create_pre_migration_backup(
hermes_home: Optional[Path] = None,
keep: int = _PRE_MIGRATION_DEFAULT_KEEP,
) -> Optional[Path]:
"""Create a full zip backup of HERMES_HOME under ``backups/`` before a
``hermes claw migrate`` apply.
Shares implementation with :func:`create_pre_update_backup` via
``_write_full_zip_backup`` same exclusions, same SQLite safe-copy,
restorable with ``hermes import <archive>``. Writes to
``<HERMES_HOME>/backups/pre-migration-<timestamp>.zip`` and auto-prunes
old pre-migration backups.
Returns the path to the created zip, or ``None`` if nothing was found
to back up (fresh install) or the write failed. Never raises the
caller decides whether to abort or proceed.
"""
hermes_root = hermes_home or get_default_hermes_root()
if not hermes_root.is_dir():
return None
# Reuses the shared backups/ directory so `hermes import` and the
# update-backup listing pick up pre-migration archives too.
backup_dir = _pre_update_backup_dir(hermes_root)
try:
backup_dir.mkdir(parents=True, exist_ok=True)
except OSError as exc:
logger.warning("Could not create pre-migration backup dir %s: %s", backup_dir, exc)
return None
stamp = datetime.now().strftime("%Y-%m-%d-%H%M%S")
out_path = backup_dir / f"{_PRE_MIGRATION_PREFIX}{stamp}.zip"
result = _write_full_zip_backup(out_path, hermes_root)
if result is None:
return None
_prune_pre_migration_backups(backup_dir, keep=keep)
return out_path
+1
View File
@@ -562,6 +562,7 @@ def build_welcome_banner(console: Console, model: str, cwd: str,
right_content = "\n".join(right_lines)
layout_table.add_row(left_content, right_content)
agent_name = _skin_branding("agent_name", "Hermes Agent")
title_color = _skin_color("banner_title", "#FFD700")
border_color = _skin_color("banner_border", "#CD7F32")
version_label = format_banner_version_label()
-138
View File
@@ -1,138 +0,0 @@
"""Shared helpers for attaching Hermes to a local Chrome CDP port."""
from __future__ import annotations
import os
import platform
import shlex
import shutil
import subprocess
from hermes_constants import get_hermes_home
DEFAULT_BROWSER_CDP_PORT = 9222
DEFAULT_BROWSER_CDP_URL = f"http://127.0.0.1:{DEFAULT_BROWSER_CDP_PORT}"
_DARWIN_APPS = (
"/Applications/Google Chrome.app/Contents/MacOS/Google Chrome",
"/Applications/Chromium.app/Contents/MacOS/Chromium",
"/Applications/Brave Browser.app/Contents/MacOS/Brave Browser",
"/Applications/Microsoft Edge.app/Contents/MacOS/Microsoft Edge",
)
_WINDOWS_INSTALL_PARTS = (
("Google", "Chrome", "Application", "chrome.exe"),
("Chromium", "Application", "chrome.exe"),
("Chromium", "Application", "chromium.exe"),
("BraveSoftware", "Brave-Browser", "Application", "brave.exe"),
("Microsoft", "Edge", "Application", "msedge.exe"),
)
_LINUX_BIN_NAMES = (
"google-chrome", "google-chrome-stable", "chromium-browser",
"chromium", "brave-browser", "microsoft-edge",
)
_WINDOWS_BIN_NAMES = (
"chrome.exe", "msedge.exe", "brave.exe", "chromium.exe",
"chrome", "msedge", "brave", "chromium",
)
def get_chrome_debug_candidates(system: str) -> list[str]:
candidates: list[str] = []
seen: set[str] = set()
def add(path: str | None) -> None:
if not path:
return
normalized = os.path.normcase(os.path.normpath(path))
if normalized in seen or not os.path.isfile(path):
return
candidates.append(path)
seen.add(normalized)
def add_install_paths(bases: tuple[str | None, ...]) -> None:
for base in filter(None, bases):
for parts in _WINDOWS_INSTALL_PARTS:
add(os.path.join(base, *parts))
if system == "Darwin":
for app in _DARWIN_APPS:
add(app)
return candidates
if system == "Windows":
for name in _WINDOWS_BIN_NAMES:
add(shutil.which(name))
add_install_paths((
os.environ.get("ProgramFiles"),
os.environ.get("ProgramFiles(x86)"),
os.environ.get("LOCALAPPDATA"),
))
return candidates
for name in _LINUX_BIN_NAMES:
add(shutil.which(name))
add_install_paths(("/mnt/c/Program Files", "/mnt/c/Program Files (x86)"))
return candidates
def chrome_debug_data_dir() -> str:
return str(get_hermes_home() / "chrome-debug")
def _chrome_debug_args(port: int) -> list[str]:
return [
f"--remote-debugging-port={port}",
f"--user-data-dir={chrome_debug_data_dir()}",
"--no-first-run",
"--no-default-browser-check",
]
def manual_chrome_debug_command(port: int = DEFAULT_BROWSER_CDP_PORT, system: str | None = None) -> str | None:
system = system or platform.system()
candidates = get_chrome_debug_candidates(system)
if candidates:
argv = [candidates[0], *_chrome_debug_args(port)]
return subprocess.list2cmdline(argv) if system == "Windows" else shlex.join(argv)
if system == "Darwin":
data_dir = chrome_debug_data_dir()
return (
f'open -a "Google Chrome" --args --remote-debugging-port={port} '
f'--user-data-dir="{data_dir}" --no-first-run --no-default-browser-check'
)
return None
def _detach_kwargs(system: str) -> dict:
if system != "Windows":
return {"start_new_session": True}
flags = getattr(subprocess, "DETACHED_PROCESS", 0) | getattr(
subprocess, "CREATE_NEW_PROCESS_GROUP", 0
)
return {"creationflags": flags} if flags else {}
def try_launch_chrome_debug(port: int = DEFAULT_BROWSER_CDP_PORT, system: str | None = None) -> bool:
system = system or platform.system()
candidates = get_chrome_debug_candidates(system)
if not candidates:
return False
os.makedirs(chrome_debug_data_dir(), exist_ok=True)
try:
subprocess.Popen(
[candidates[0], *_chrome_debug_args(port)],
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL,
**_detach_kwargs(system),
)
return True
except Exception:
return False
+6 -67
View File
@@ -4,8 +4,7 @@ Usage:
hermes claw migrate # Preview then migrate (always shows preview first)
hermes claw migrate --dry-run # Preview only, no changes
hermes claw migrate --yes # Skip confirmation prompt
hermes claw migrate --preset full --overwrite --migrate-secrets # Full run w/ secrets
hermes claw migrate --no-backup # Skip pre-migration snapshot
hermes claw migrate --preset full --overwrite # Full migration, overwrite conflicts
hermes claw cleanup # Archive leftover OpenClaw directories
hermes claw cleanup --dry-run # Preview what would be archived
"""
@@ -16,7 +15,6 @@ import subprocess
import sys
from datetime import datetime
from pathlib import Path
from typing import Optional
from hermes_cli.config import get_hermes_home, get_config_path, load_config, save_config
from hermes_constants import get_optional_skills_dir
@@ -323,13 +321,10 @@ def _cmd_migrate(args):
migrate_secrets = getattr(args, "migrate_secrets", False)
workspace_target = getattr(args, "workspace_target", None)
skill_conflict = getattr(args, "skill_conflict", "skip")
no_backup = getattr(args, "no_backup", False)
# Secrets are never included implicitly — they must be explicitly requested
# via --migrate-secrets, even under --preset full. This mirrors OpenClaw's
# migrate-hermes posture (two-phase: run once without secrets, rerun with
# --include-secrets) and prevents a --preset full invocation from silently
# importing API keys that the user may not have intended to copy.
# If using the "full" preset, secrets are included by default
if preset == "full":
migrate_secrets = True
print()
print(
@@ -436,24 +431,15 @@ def _cmd_migrate(args):
preview_summary = preview_report.get("summary", {})
preview_count = preview_summary.get("migrated", 0)
preview_conflicts = preview_summary.get("conflict", 0)
# "Nothing to migrate" means nothing migrated AND nothing blocked by
# conflicts. If there are conflicts, we still want to show the plan and
# surface the refusal/--overwrite guidance instead of silently bailing.
if preview_count == 0 and preview_conflicts == 0:
if preview_count == 0:
print()
print_info("Nothing to migrate from OpenClaw.")
_print_migration_report(preview_report, dry_run=True)
return
print()
if preview_count > 0:
print_header(f"Migration Preview — {preview_count} item(s) would be imported")
else:
print_header(
f"Migration Preview — {preview_conflicts} conflict(s), nothing would be imported"
)
print_header(f"Migration Preview — {preview_count} item(s) would be imported")
print_info("No changes have been made yet. Review the list below:")
_print_migration_report(preview_report, dry_run=True)
@@ -461,24 +447,6 @@ def _cmd_migrate(args):
if dry_run:
return
# ── Phase 1b: Refuse if the plan has conflicts and --overwrite is not set ─
# Modelled on OpenClaw's assertConflictFreePlan() — apply is a safe no-op
# on conflicts unless the user explicitly opts in to overwriting. Without
# this guard, the user would answer "yes, proceed" and silently end up
# with a migration that skipped every conflicting item.
if preview_conflicts > 0 and not overwrite:
print()
print_error(
f"Plan has {preview_conflicts} conflict(s). Refusing to apply."
)
print_info(
"Each conflict is an item whose target already exists in ~/.hermes/. "
"Re-run with --overwrite to replace conflicting targets (item-level "
"backups are written to the migration report directory)."
)
print_info("Or re-run with --dry-run to review the full plan.")
return
# ── Phase 2: Confirm and execute ───────────────────────────
print()
if not auto_yes:
@@ -490,32 +458,6 @@ def _cmd_migrate(args):
print_info("Migration cancelled.")
return
# ── Phase 2b: Pre-apply backup of the Hermes home ─────────
# Delegates to hermes_cli.backup.create_pre_migration_backup(), which
# shares implementation with the pre-update backup (same exclusion
# rules, same SQLite safe-copy, zip format) so the archive is
# restorable with `hermes import`. Mirrors OpenClaw's
# createPreMigrationBackup posture — one atomic restore point before
# any mutation, auto-pruned to the last 5 pre-migration zips.
backup_archive: Optional[Path] = None
if not no_backup:
try:
from hermes_cli.backup import create_pre_migration_backup, _format_size
backup_archive = create_pre_migration_backup(hermes_home=hermes_home)
if backup_archive:
size_str = _format_size(backup_archive.stat().st_size)
print()
print_success(f"Pre-migration backup: {backup_archive} ({size_str})")
print_info(f"Restore with: hermes import {backup_archive.name}")
except Exception as e:
print()
print_error(f"Could not create pre-migration backup: {e}")
print_info(
"Re-run with --no-backup to skip, or free up disk space under the Hermes home."
)
logger.debug("Pre-migration backup error", exc_info=True)
return
try:
migrator = mod.Migrator(
source_root=source_dir.resolve(),
@@ -534,9 +476,6 @@ def _cmd_migrate(args):
print()
print_error(f"Migration failed: {e}")
logger.debug("OpenClaw migration error", exc_info=True)
if backup_archive:
print_info(f"A pre-migration backup is available at: {backup_archive}")
print_info(f"Restore with: hermes import {backup_archive.name}")
return
# Print results
+6 -176
View File
@@ -62,8 +62,6 @@ COMMAND_REGISTRY: list[CommandDef] = [
aliases=("reset",)),
CommandDef("clear", "Clear screen and start a new session", "Session",
cli_only=True),
CommandDef("redraw", "Force a full UI repaint (recovers from terminal drift)", "Session",
cli_only=True),
CommandDef("history", "Show conversation history", "Session",
cli_only=True),
CommandDef("save", "Save the current conversation", "Session",
@@ -86,7 +84,9 @@ COMMAND_REGISTRY: list[CommandDef] = [
CommandDef("deny", "Deny a pending dangerous command", "Session",
gateway_only=True),
CommandDef("background", "Run a prompt in the background", "Session",
aliases=("bg", "btw"), args_hint="<prompt>"),
aliases=("bg",), args_hint="<prompt>"),
CommandDef("btw", "Ephemeral side question using session context (no tools, not persisted)", "Session",
args_hint="<question>"),
CommandDef("agents", "Show active agents and running tasks", "Session",
aliases=("tasks",)),
CommandDef("queue", "Queue a prompt for the next turn (doesn't interrupt)", "Session",
@@ -103,8 +103,7 @@ COMMAND_REGISTRY: list[CommandDef] = [
# Configuration
CommandDef("config", "Show current configuration", "Configuration",
cli_only=True),
CommandDef("model", "Switch model for this session", "Configuration",
aliases=("provider",), args_hint="[model] [--provider name] [--global]"),
CommandDef("model", "Switch model for this session", "Configuration", args_hint="[model] [--provider name] [--global]"),
CommandDef("gquota", "Show Google Gemini Code Assist quota usage", "Info",
cli_only=True),
@@ -115,9 +114,6 @@ COMMAND_REGISTRY: list[CommandDef] = [
CommandDef("verbose", "Cycle tool progress display: off -> new -> all -> verbose",
"Configuration", cli_only=True,
gateway_config_gate="display.tool_progress_command"),
CommandDef("footer", "Toggle gateway runtime-metadata footer on final replies",
"Configuration", args_hint="[on|off|status]",
subcommands=("on", "off", "status")),
CommandDef("yolo", "Toggle YOLO mode (skip all dangerous command approvals)",
"Configuration"),
CommandDef("reasoning", "Manage reasoning effort and display", "Configuration",
@@ -128,14 +124,8 @@ COMMAND_REGISTRY: list[CommandDef] = [
subcommands=("normal", "fast", "status", "on", "off")),
CommandDef("skin", "Show or change the display skin/theme", "Configuration",
cli_only=True, args_hint="[name]"),
CommandDef("indicator", "Pick the TUI busy-indicator style", "Configuration",
cli_only=True, args_hint="[kaomoji|emoji|unicode|ascii]",
subcommands=("kaomoji", "emoji", "unicode", "ascii")),
CommandDef("voice", "Toggle voice mode", "Configuration",
args_hint="[on|off|tts|status]", subcommands=("on", "off", "tts", "status")),
CommandDef("busy", "Control what Enter does while Hermes is working", "Configuration",
cli_only=True, args_hint="[queue|steer|interrupt|status]",
subcommands=("queue", "steer", "interrupt", "status")),
# Tools & Skills
CommandDef("tools", "Manage tools: /tools [list|disable|enable] [name...]", "Tools & Skills",
@@ -148,9 +138,6 @@ COMMAND_REGISTRY: list[CommandDef] = [
CommandDef("cron", "Manage scheduled tasks", "Tools & Skills",
cli_only=True, args_hint="[subcommand]",
subcommands=("list", "add", "create", "edit", "pause", "resume", "run", "remove")),
CommandDef("curator", "Background skill maintenance (status, run, pin, archive)",
"Tools & Skills", args_hint="[subcommand]",
subcommands=("status", "run", "pause", "resume", "pin", "unpin", "restore")),
CommandDef("reload", "Reload .env variables into the running session", "Tools & Skills",
cli_only=True),
CommandDef("reload-mcp", "Reload MCP servers from config", "Tools & Skills",
@@ -183,8 +170,8 @@ COMMAND_REGISTRY: list[CommandDef] = [
CommandDef("debug", "Upload debug report (system info + logs) and get shareable links", "Info"),
# Exit
CommandDef("quit", "Exit the CLI (use --delete to also remove session history)", "Exit",
cli_only=True, aliases=("exit",), args_hint="[--delete]"),
CommandDef("quit", "Exit the CLI", "Exit",
cli_only=True, aliases=("exit",)),
]
@@ -817,114 +804,6 @@ def discord_skill_commands_by_category(
return trimmed_categories, uncategorized, hidden
# ---------------------------------------------------------------------------
# Slack native slash commands
# ---------------------------------------------------------------------------
# Slack slash command name constraints: lowercase a-z, 0-9, hyphens,
# underscores. Max 32 chars. Slack app manifest accepts up to 50 slash
# commands per app.
_SLACK_MAX_SLASH_COMMANDS = 50
_SLACK_NAME_LIMIT = 32
_SLACK_INVALID_CHARS = re.compile(r"[^a-z0-9_\-]")
def _sanitize_slack_name(raw: str) -> str:
"""Convert a command name to a valid Slack slash command name.
Slack allows lowercase a-z, digits, hyphens, and underscores. Max 32
chars. Uppercase is lowercased; invalid chars are stripped.
"""
name = raw.lower()
name = _SLACK_INVALID_CHARS.sub("", name)
name = name.strip("-_")
return name[:_SLACK_NAME_LIMIT]
def slack_native_slashes() -> list[tuple[str, str, str]]:
"""Return (slash_name, description, usage_hint) triples for Slack.
Every gateway-available command in ``COMMAND_REGISTRY`` is surfaced as
a standalone Slack slash command (e.g. ``/btw``, ``/stop``, ``/model``),
matching Discord's and Telegram's model where every command is a
first-class slash and not a ``/hermes <verb>`` subcommand.
Both canonical names and aliases are included so users can type any
documented form (e.g. ``/background``, ``/bg``, and ``/btw`` all work).
Plugin-registered slash commands are included too.
Results are clamped to Slack's 50-command limit with duplicate-name
avoidance. ``/hermes`` is always reserved as the first entry so the
legacy ``/hermes <subcommand>`` form keeps working for anything that
gets dropped by the clamp or for free-form questions.
"""
overrides = _resolve_config_gates()
entries: list[tuple[str, str, str]] = []
seen: set[str] = set()
# Reserve /hermes as the catch-all top-level command.
entries.append(("hermes", "Talk to Hermes or run a subcommand", "[subcommand] [args]"))
seen.add("hermes")
def _add(name: str, desc: str, hint: str) -> None:
slack_name = _sanitize_slack_name(name)
if not slack_name or slack_name in seen:
return
if len(entries) >= _SLACK_MAX_SLASH_COMMANDS:
return
# Slack description cap is 2000 chars; keep it short.
entries.append((slack_name, desc[:140], hint[:100]))
seen.add(slack_name)
# First pass: canonical names (so they win slots if we hit the cap).
for cmd in COMMAND_REGISTRY:
if not _is_gateway_available(cmd, overrides):
continue
_add(cmd.name, cmd.description, cmd.args_hint or "")
# Second pass: aliases.
for cmd in COMMAND_REGISTRY:
if not _is_gateway_available(cmd, overrides):
continue
for alias in cmd.aliases:
# Skip aliases that only differ from canonical by case/punctuation
# normalization (already covered by _add dedup).
_add(alias, f"Alias for /{cmd.name}{cmd.description}", cmd.args_hint or "")
# Third pass: plugin commands.
for name, description, args_hint in _iter_plugin_command_entries():
_add(name, description, args_hint or "")
return entries
def slack_app_manifest(request_url: str = "https://hermes-agent.local/slack/commands") -> dict[str, Any]:
"""Generate a Slack app manifest with all gateway commands as slashes.
``request_url`` is required by Slack's manifest schema for every slash
command, but in Socket Mode (which we use) Slack ignores it and routes
the command event through the WebSocket. A placeholder URL is fine.
The returned dict is the ``features.slash_commands`` portion only
callers compose it into a full manifest (or merge into an existing
one). Keeping it narrow avoids coupling us to the rest of the manifest
schema (display_information, oauth_config, settings, etc.) which users
set up once in the Slack UI and rarely change.
"""
slashes = []
for name, desc, usage in slack_native_slashes():
entry = {
"command": f"/{name}",
"description": desc or f"Run /{name}",
"should_escape": False,
"url": request_url,
}
if usage:
entry["usage_hint"] = usage
slashes.append(entry)
return {"features": {"slash_commands": slashes}}
def slack_subcommand_map() -> dict[str, str]:
"""Return subcommand -> /command mapping for Slack /hermes handler.
@@ -952,42 +831,6 @@ def slack_subcommand_map() -> dict[str, str]:
# Autocomplete
# ---------------------------------------------------------------------------
# Per-process cache for /model<space> LM Studio autocomplete. Probing on
# every keystroke would block the UI; a short TTL keeps it live without
# hammering the server.
_LMSTUDIO_COMPLETION_CACHE: tuple[float, list[str]] | None = None
def _lmstudio_completion_models() -> list[str]:
"""Locally-loaded LM Studio models for /model autocomplete (cached, gated)."""
global _LMSTUDIO_COMPLETION_CACHE
# Gate: don't probe 127.0.0.1 on every keystroke for users who don't use LM Studio.
if not (os.environ.get("LM_API_KEY") or os.environ.get("LM_BASE_URL")):
try:
from hermes_cli.auth import _load_auth_store
store = _load_auth_store() or {}
if "lmstudio" not in (store.get("providers") or {}) \
and "lmstudio" not in (store.get("credential_pool") or {}):
return []
except Exception:
return []
now = time.time()
if _LMSTUDIO_COMPLETION_CACHE and (now - _LMSTUDIO_COMPLETION_CACHE[0]) < 30.0:
return _LMSTUDIO_COMPLETION_CACHE[1]
try:
from hermes_cli.models import fetch_lmstudio_models
models = fetch_lmstudio_models(
api_key=os.environ.get("LM_API_KEY", ""),
base_url=os.environ.get("LM_BASE_URL") or "http://127.0.0.1:1234/v1",
timeout=0.8,
)
except Exception:
models = []
_LMSTUDIO_COMPLETION_CACHE = (now, models)
return models
class SlashCommandCompleter(Completer):
"""Autocomplete for built-in slash commands, subcommands, and skill commands."""
@@ -1411,19 +1254,6 @@ class SlashCommandCompleter(Completer):
)
except Exception:
pass
# LM Studio: surface locally-loaded models. Gated on the user actually
# having LM Studio configured (env var or auth-store entry) so we
# don't probe 127.0.0.1 on every keystroke for users who don't use it.
for name in _lmstudio_completion_models():
if name in seen:
continue
if name.startswith(sub_lower) and name != sub_lower:
yield Completion(
name,
start_position=-len(sub_text),
display=name,
display_meta="LM Studio",
)
def get_completions(self, document, complete_event):
text = document.text_before_cursor
+53 -552
View File
@@ -30,67 +30,34 @@ logger = logging.getLogger(__name__)
_IS_WINDOWS = platform.system() == "Windows"
_ENV_VAR_NAME_RE = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")
_LAST_EXPANDED_CONFIG_BY_PATH: Dict[str, Any] = {}
# (path, mtime_ns, size) -> cached expanded config dict.
# load_config() returns a deepcopy of the cached value when the file
# hasn't changed since the last load, skipping yaml.safe_load +
# _deep_merge + _normalize_* + _expand_env_vars (~13 ms/call).
# save_config() + migrate_config() write via atomic_yaml_write which
# produces a fresh inode, so stat() sees a new mtime_ns and the next
# load repopulates automatically — no explicit invalidation hook.
_LOAD_CONFIG_CACHE: Dict[str, Tuple[int, int, Dict[str, Any]]] = {}
# (path, mtime_ns, size) -> cached raw yaml dict. Same pattern as
# _LOAD_CONFIG_CACHE but for read_raw_config() — used when callers want
# the user's on-disk values without defaults merged in.
_RAW_CONFIG_CACHE: Dict[str, Tuple[int, int, Dict[str, Any]]] = {}
# Env var names written to .env that aren't in OPTIONAL_ENV_VARS
# (managed by setup/provider flows directly).
_EXTRA_ENV_KEYS = frozenset({
"OPENAI_API_KEY", "OPENAI_BASE_URL",
"ANTHROPIC_API_KEY", "ANTHROPIC_TOKEN",
"DISCORD_HOME_CHANNEL", "DISCORD_HOME_CHANNEL_NAME",
"TELEGRAM_HOME_CHANNEL", "TELEGRAM_HOME_CHANNEL_NAME",
"SLACK_HOME_CHANNEL", "SLACK_HOME_CHANNEL_NAME",
"DISCORD_HOME_CHANNEL", "TELEGRAM_HOME_CHANNEL",
"SIGNAL_ACCOUNT", "SIGNAL_HTTP_URL",
"SIGNAL_ALLOWED_USERS", "SIGNAL_GROUP_ALLOWED_USERS",
"SIGNAL_HOME_CHANNEL", "SIGNAL_HOME_CHANNEL_NAME",
"SMS_HOME_CHANNEL", "SMS_HOME_CHANNEL_NAME",
"DINGTALK_CLIENT_ID", "DINGTALK_CLIENT_SECRET",
"DINGTALK_HOME_CHANNEL", "DINGTALK_HOME_CHANNEL_NAME",
"FEISHU_APP_ID", "FEISHU_APP_SECRET", "FEISHU_ENCRYPT_KEY", "FEISHU_VERIFICATION_TOKEN",
"FEISHU_HOME_CHANNEL", "FEISHU_HOME_CHANNEL_NAME",
"YUANBAO_HOME_CHANNEL", "YUANBAO_HOME_CHANNEL_NAME",
"WECOM_BOT_ID", "WECOM_SECRET",
"WECOM_CALLBACK_CORP_ID", "WECOM_CALLBACK_CORP_SECRET", "WECOM_CALLBACK_AGENT_ID",
"WECOM_CALLBACK_TOKEN", "WECOM_CALLBACK_ENCODING_AES_KEY",
"WECOM_CALLBACK_HOST", "WECOM_CALLBACK_PORT",
"WECOM_HOME_CHANNEL", "WECOM_HOME_CHANNEL_NAME",
"WEIXIN_ACCOUNT_ID", "WEIXIN_TOKEN", "WEIXIN_BASE_URL", "WEIXIN_CDN_BASE_URL",
"WEIXIN_HOME_CHANNEL", "WEIXIN_HOME_CHANNEL_NAME", "WEIXIN_DM_POLICY", "WEIXIN_GROUP_POLICY",
"WEIXIN_ALLOWED_USERS", "WEIXIN_GROUP_ALLOWED_USERS", "WEIXIN_ALLOW_ALL_USERS",
"BLUEBUBBLES_SERVER_URL", "BLUEBUBBLES_PASSWORD",
"BLUEBUBBLES_HOME_CHANNEL", "BLUEBUBBLES_HOME_CHANNEL_NAME",
"QQ_APP_ID", "QQ_CLIENT_SECRET", "QQBOT_HOME_CHANNEL", "QQBOT_HOME_CHANNEL_NAME",
"QQ_HOME_CHANNEL", "QQ_HOME_CHANNEL_NAME", # legacy aliases (pre-rename, still read for back-compat)
"QQ_ALLOWED_USERS", "QQ_GROUP_ALLOWED_USERS", "QQ_ALLOW_ALL_USERS", "QQ_MARKDOWN_SUPPORT",
"QQ_STT_API_KEY", "QQ_STT_BASE_URL", "QQ_STT_MODEL",
"TERMINAL_ENV", "TERMINAL_SSH_KEY", "TERMINAL_SSH_PORT",
"WHATSAPP_MODE", "WHATSAPP_ENABLED",
"MATTERMOST_HOME_CHANNEL", "MATTERMOST_HOME_CHANNEL_NAME", "MATTERMOST_REPLY_MODE",
"MATTERMOST_HOME_CHANNEL", "MATTERMOST_REPLY_MODE",
"MATRIX_PASSWORD", "MATRIX_ENCRYPTION", "MATRIX_DEVICE_ID", "MATRIX_HOME_ROOM",
"MATRIX_REQUIRE_MENTION", "MATRIX_FREE_RESPONSE_ROOMS", "MATRIX_AUTO_THREAD", "MATRIX_DM_AUTO_THREAD",
"MATRIX_REQUIRE_MENTION", "MATRIX_FREE_RESPONSE_ROOMS", "MATRIX_AUTO_THREAD",
"MATRIX_RECOVERY_KEY",
# Langfuse observability plugin — optional tuning keys + standard SDK vars.
# Activation is via plugins.enabled (opt-in through `hermes plugins enable
# observability/langfuse` or `hermes tools → Langfuse`); credentials gate
# the plugin at runtime.
"HERMES_LANGFUSE_ENV",
"HERMES_LANGFUSE_RELEASE",
"HERMES_LANGFUSE_SAMPLE_RATE",
"HERMES_LANGFUSE_MAX_CHARS",
"HERMES_LANGFUSE_DEBUG",
"LANGFUSE_PUBLIC_KEY",
"LANGFUSE_SECRET_KEY",
"LANGFUSE_BASE_URL",
})
import yaml
@@ -239,7 +206,6 @@ def get_container_exec_info() -> Optional[dict]:
# Re-export from hermes_constants — canonical definition lives there.
from hermes_constants import get_hermes_home # noqa: F811,E402
from utils import atomic_replace
def get_config_path() -> Path:
"""Get the main config file path."""
@@ -423,34 +389,6 @@ DEFAULT_CONFIG = {
# (60+ tool iterations with tiny output) before users assume the
# bot is dead and /restart.
"gateway_notify_interval": 180,
# Freshness window for the gateway auto-continue note (seconds).
# After a gateway crash/restart/SIGTERM mid-run, the next user
# message gets a "[System note: your previous turn was
# interrupted — process the unfinished tool result(s) first]"
# prepended so the model picks up where it left off. That's the
# right behaviour while the interruption is fresh, but stale
# markers (transcript last touched hours or days ago) can revive
# an unrelated old task when the user's next message starts new
# work. This window is the max age of the last persisted
# transcript row for which we still inject the continue note.
# Default 3600s comfortably covers a long turn (gateway_timeout
# default is 1800s) plus runtime slack. Set to 0 to disable the
# gate and restore pre-fix behaviour (always inject).
"gateway_auto_continue_freshness": 3600,
# How user-attached images are presented to the main model on each turn.
# "auto" — attach natively when the active model reports
# supports_vision=True AND the user hasn't explicitly
# configured auxiliary.vision.provider. Otherwise fall
# back to text (vision_analyze pre-analysis).
# "native" — always attach natively; non-vision models will either
# error at the provider or get a last-chance text fallback
# (see run_agent._prepare_messages_for_api).
# "text" — always pre-analyze with vision_analyze and prepend the
# description as text; the main model never sees pixels.
# Affects gateway platforms, the TUI, and CLI /attach. vision_analyze
# remains available as a tool regardless of this setting — the routing
# only controls how inbound user images are presented.
"image_input_mode": "auto",
},
"terminal": {
@@ -499,8 +437,7 @@ DEFAULT_CONFIG = {
"singularity_image": "docker://nikolaik/python-nodejs:python3.11-nodejs20",
"modal_image": "nikolaik/python-nodejs:python3.11-nodejs20",
"daytona_image": "nikolaik/python-nodejs:python3.11-nodejs20",
"vercel_runtime": "node24",
# Container resource limits (docker, singularity, modal, daytona, vercel_sandbox — ignored for local/ssh)
# Container resource limits (docker, singularity, modal, daytona — ignored for local/ssh)
"container_cpu": 1,
"container_memory": 5120, # MB (default 5GB)
"container_disk": 51200, # MB (default 50GB)
@@ -516,16 +453,6 @@ DEFAULT_CONFIG = {
# Explicit opt-in: mount the host cwd into /workspace for Docker sessions.
# Default off because passing host directories into a sandbox weakens isolation.
"docker_mount_cwd_to_workspace": False,
# Explicit opt-in: run the Docker container as the host user's uid:gid
# (via `--user`). When enabled, files written into bind-mounted dirs
# (docker_volumes, the persistent workspace, or the auto-mounted cwd)
# are owned by your host user instead of root, which avoids needing
# `sudo chown` after container runs. Default off to preserve behavior
# for images whose entrypoints expect to start as root (e.g. the
# bundled Hermes image, which drops to the `hermes` user via gosu).
# When on, SETUID/SETGID caps are omitted from the container since
# no privilege drop is needed.
"docker_run_as_host_user": False,
# Persistent shell — keep a long-lived bash shell across execute() calls
# so cwd/env vars/shell variables survive between commands.
# Enabled by default for non-local backends (SSH); local is always opt-in
@@ -538,7 +465,6 @@ DEFAULT_CONFIG = {
"command_timeout": 30, # Timeout for browser commands in seconds (screenshot, navigate, etc.)
"record_sessions": False, # Auto-record browser sessions as WebM videos
"allow_private_urls": False, # Allow navigating to private/internal IPs (localhost, 192.168.x.x, etc.)
"auto_local_for_private_urls": True, # When a cloud provider is set, auto-spawn local Chromium for LAN/localhost URLs instead of sending them to the cloud
"cdp_url": "", # Optional persistent CDP endpoint for attaching to an existing Chromium/Chrome
# CDP supervisor — dialog + frame detection via a persistent WebSocket.
# Active only when a CDP-capable backend is attached (Browserbase or
@@ -560,19 +486,6 @@ DEFAULT_CONFIG = {
"checkpoints": {
"enabled": True,
"max_snapshots": 50, # Max checkpoints to keep per directory
# Auto-maintenance: shadow repos accumulate forever under
# ~/.hermes/checkpoints/ (one per cd'd working directory). Field
# reports put the typical offender at 1000+ repos / ~12 GB. When
# auto_prune is on, hermes sweeps at startup (at most once per
# min_interval_hours) and deletes:
# * orphan repos: HERMES_WORKDIR no longer exists on disk
# * stale repos: newest mtime older than retention_days
# Opt-in so users who rely on /rollback against long-ago sessions
# never lose data silently.
"auto_prune": False,
"retention_days": 7,
"delete_orphans": True,
"min_interval_hours": 24,
},
# Maximum characters returned by a single read_file call. Reads that
@@ -605,7 +518,7 @@ DEFAULT_CONFIG = {
"threshold": 0.50, # compress when context usage exceeds this ratio
"target_ratio": 0.20, # fraction of threshold to preserve as recent tail
"protect_last_n": 20, # minimum recent messages to keep uncompressed
"hygiene_hard_message_limit": 400, # gateway session-hygiene force-compress threshold by message count
},
# Anthropic prompt caching (Claude via OpenRouter or native Anthropic API).
@@ -699,6 +612,14 @@ DEFAULT_CONFIG = {
"timeout": 30,
"extra_body": {},
},
"flush_memories": {
"provider": "auto",
"model": "",
"base_url": "",
"api_key": "",
"timeout": 30,
"extra_body": {},
},
"title_generation": {
"provider": "auto",
"model": "",
@@ -713,12 +634,7 @@ DEFAULT_CONFIG = {
"compact": False,
"personality": "kawaii",
"resume_display": "full",
"busy_input_mode": "interrupt", # interrupt | queue | steer
# When true, `hermes --tui` auto-resumes the most recent human-
# facing session on launch instead of forging a fresh one.
# Mirrors `hermes -c` muscle memory. Default off so existing
# users aren't surprised. HERMES_TUI_RESUME=<id> always wins.
"tui_auto_resume_recent": False,
"busy_input_mode": "interrupt",
"bell_on_complete": False,
"show_reasoning": False,
"streaming": False,
@@ -726,9 +642,6 @@ DEFAULT_CONFIG = {
"inline_diffs": True, # Show inline diff previews for write actions (write_file, patch, skill_manage)
"show_cost": False, # Show $ cost in the status bar (off by default)
"skin": "default",
# TUI busy indicator style: kaomoji (default), emoji, unicode (braille
# spinner), or ascii. Live-swappable via `/indicator <style>`.
"tui_status_indicator": "kaomoji",
"user_message_preview": { # CLI: how many submitted user-message lines to echo back in scrollback
"first_lines": 2,
"last_lines": 2,
@@ -738,14 +651,6 @@ DEFAULT_CONFIG = {
"tool_progress_overrides": {}, # DEPRECATED — use display.platforms instead
"tool_preview_length": 0, # Max chars for tool call previews (0 = no limit, show full paths/commands)
"platforms": {}, # Per-platform display overrides: {"telegram": {"tool_progress": "all"}, "slack": {"tool_progress": "off"}}
# Gateway runtime-metadata footer appended to the FINAL message of a turn
# (disabled by default to keep replies minimal). When enabled, renders
# e.g. `model · 68% · ~/projects/hermes`. Per-platform overrides go under
# display.platforms.<platform>.runtime_footer.
"runtime_footer": {
"enabled": False,
"fields": ["model", "context_pct", "cwd"], # Order shown; drop any to hide
},
},
# Web dashboard settings
@@ -878,15 +783,6 @@ DEFAULT_CONFIG = {
# warning log if out of range.
"max_spawn_depth": 1, # depth cap (1 = flat [default], 2 = orchestrator→leaf, 3 = three-level)
"orchestrator_enabled": True, # kill switch for role="orchestrator"
# When a subagent hits a dangerous-command approval prompt, the parent's
# prompt_toolkit TUI owns stdin — a thread-local input() call from the
# subagent worker would deadlock the parent UI. To avoid the deadlock,
# subagent threads ALWAYS resolve approvals non-interactively:
# false (default) → auto-deny with a logger.warning audit line (safe)
# true → auto-approve "once" with a logger.warning audit line
# Flip to true only if you trust delegated work to run dangerous cmds
# without human review (cron pipelines, batch automation, etc.).
"subagent_auto_approve": False,
},
# Ephemeral prefill messages file — JSON list of {role, content} dicts
@@ -926,35 +822,6 @@ DEFAULT_CONFIG = {
"guard_agent_created": False,
},
# Curator — background skill maintenance.
#
# Periodically reviews AGENT-CREATED skills (never bundled or
# hub-installed) and keeps the collection tidy: marks long-unused skills
# as stale, archives genuinely obsolete ones (archive only, never
# deletes), and spawns a forked aux-model agent to consolidate overlaps
# and patch drift. Runs inactivity-triggered from session start — no
# cron daemon.
#
# See `hermes curator status` for the last run summary.
"curator": {
"enabled": True,
# How long to wait between curator runs (hours). Default: 7 days.
"interval_hours": 24 * 7,
# Only run when the agent has been idle at least this long (hours).
"min_idle_hours": 2,
# Mark a skill as "stale" after this many days without use.
"stale_after_days": 30,
# Archive a skill (move to skills/.archive/) after this many days
# without use. Archived skills are recoverable — no auto-deletion.
"archive_after_days": 90,
# Optional per-task override for the curator's aux model. Leave null
# to use Hermes' main auxiliary client resolution.
"auxiliary": {
"provider": None,
"model": None,
},
},
# Honcho AI-native memory -- reads ~/.honcho/config.json as single source of truth.
# This section is only needed for hermes-specific overrides; everything else
# (apiKey, workspace, peerName, sessions, enabled) comes from the global config.
@@ -972,7 +839,7 @@ DEFAULT_CONFIG = {
"auto_thread": True, # Auto-create threads on @mention in channels (like Slack)
"reactions": True, # Add 👀/✅/❌ reactions to messages during processing
"channel_prompts": {}, # Per-channel ephemeral system prompts (forum parents apply to child threads)
# discord / discord_admin tools: restrict which actions the agent may call.
# discord_server tool: restrict which actions the agent may call.
# Default (empty) = all actions allowed (subject to bot privileged intents).
# Accepts comma-separated string ("list_guilds,list_channels,fetch_messages")
# or YAML list. Unknown names are dropped with a warning at load time.
@@ -992,7 +859,6 @@ DEFAULT_CONFIG = {
# Telegram platform settings (gateway mode)
"telegram": {
"reactions": False, # Add 👀/✅/❌ reactions to messages during processing
"channel_prompts": {}, # Per-chat/topic ephemeral system prompts (topics inherit from parent group)
},
@@ -1047,7 +913,7 @@ DEFAULT_CONFIG = {
# Pre-exec security scanning via tirith
"security": {
"allow_private_urls": False, # Allow requests to private/internal IPs (for OpenWrt, proxies, VPNs)
"redact_secrets": False,
"redact_secrets": True,
"tirith_enabled": True,
"tirith_path": "tirith",
"tirith_timeout": 5,
@@ -1092,27 +958,6 @@ DEFAULT_CONFIG = {
"backup_count": 3, # Number of rotated backup files to keep
},
# Remotely-hosted model catalog manifest. When enabled, the CLI fetches
# curated model lists for OpenRouter and Nous Portal from this URL,
# falling back to the in-repo snapshot on network failure. Lets us
# update model picker lists without shipping a hermes-agent release.
# The default URL is served by the docs site GitHub Pages deploy.
"model_catalog": {
"enabled": True,
"url": "https://hermes-agent.nousresearch.com/docs/api/model-catalog.json",
# Disk cache TTL in hours. Beyond this, the CLI refetches on the
# next /model or `hermes model` invocation; network failures
# silently fall back to the stale cache.
"ttl_hours": 24,
# Optional per-provider override URLs for third parties that want
# to self-host their own curation list using the same schema.
# Example:
# providers:
# openrouter:
# url: https://example.com/my-curation.json
"providers": {},
},
# Network settings — workarounds for connectivity issues.
"network": {
# Force IPv4 connections. On servers with broken or unreachable IPv6,
@@ -1149,27 +994,6 @@ DEFAULT_CONFIG = {
"min_interval_hours": 24,
},
# Contextual first-touch onboarding hints (see agent/onboarding.py).
# Each hint is shown once per install and then latched here so it
# never fires again. Users can wipe the section to re-see all hints.
"onboarding": {
"seen": {},
},
# ``hermes update`` behaviour.
"updates": {
# Run a full ``hermes backup``-style zip of HERMES_HOME before every
# ``hermes update``. Backups land in ``<HERMES_HOME>/backups/`` and
# can be restored with ``hermes import <path>``. Off by default —
# on large HERMES_HOME directories the zip can add minutes to every
# update. Set to true to re-enable, or pass ``--backup`` to opt in
# for a single update run.
"pre_update_backup": False,
# How many pre-update backup zips to retain. Older ones are pruned
# automatically after each successful backup.
"backup_keep": 5,
},
# Config schema version - bump this when adding new required fields
"_config_version": 22,
}
@@ -1271,22 +1095,6 @@ OPTIONAL_ENV_VARS = {
"category": "provider",
"advanced": True,
},
"LM_API_KEY": {
"description": "LM Studio bearer token for auth-enabled local servers",
"prompt": "LM Studio API key / bearer token",
"url": None,
"password": True,
"category": "provider",
"advanced": True,
},
"LM_BASE_URL": {
"description": "LM Studio base URL override",
"prompt": "LM Studio base URL (leave empty for default)",
"url": None,
"password": False,
"category": "provider",
"advanced": True,
},
"GLM_API_KEY": {
"description": "Z.AI / GLM API key (also recognized as ZAI_API_KEY / Z_AI_API_KEY)",
"prompt": "Z.AI / GLM API key",
@@ -1375,22 +1183,6 @@ OPTIONAL_ENV_VARS = {
"category": "provider",
"advanced": True,
},
"GMI_API_KEY": {
"description": "GMI Cloud API key",
"prompt": "GMI Cloud API key",
"url": "https://www.gmicloud.ai/",
"password": True,
"category": "provider",
"advanced": True,
},
"GMI_BASE_URL": {
"description": "GMI Cloud base URL override",
"prompt": "GMI Cloud base URL (leave empty for default)",
"url": None,
"password": False,
"category": "provider",
"advanced": True,
},
"MINIMAX_API_KEY": {
"description": "MiniMax API key (international)",
"prompt": "MiniMax API key",
@@ -1578,21 +1370,6 @@ OPTIONAL_ENV_VARS = {
"category": "provider",
"advanced": True,
},
"AZURE_FOUNDRY_API_KEY": {
"description": "Azure Foundry API key for custom Azure endpoints",
"prompt": "Azure Foundry API Key",
"url": "https://ai.azure.com/",
"password": True,
"category": "provider",
},
"AZURE_FOUNDRY_BASE_URL": {
"description": "Azure Foundry base URL (set via 'hermes model' for endpoint-specific config)",
"prompt": "Azure Foundry base URL",
"url": None,
"password": False,
"category": "provider",
"advanced": True,
},
# ── Tool API keys ──
"EXA_API_KEY": {
@@ -1760,44 +1537,6 @@ OPTIONAL_ENV_VARS = {
"category": "tool",
},
# ── Bundled skills (opt-in: only needed if the user uses that skill) ──
# These use category="skill" (distinct from "tool") so the sandbox
# env blocklist in tools/environments/local.py does NOT rewrite them —
# skills legitimately need these passed through to curl via
# tools/env_passthrough.py when the user's skill calls out.
"NOTION_API_KEY": {
"description": "Notion integration token (used by the `notion` skill)",
"prompt": "Notion API key",
"url": "https://www.notion.so/my-integrations",
"password": True,
"category": "skill",
"advanced": True,
},
"LINEAR_API_KEY": {
"description": "Linear personal API key (used by the `linear` skill)",
"prompt": "Linear API key",
"url": "https://linear.app/settings/api",
"password": True,
"category": "skill",
"advanced": True,
},
"AIRTABLE_API_KEY": {
"description": "Airtable personal access token (used by the `airtable` skill)",
"prompt": "Airtable API key",
"url": "https://airtable.com/create/tokens",
"password": True,
"category": "skill",
"advanced": True,
},
"TENOR_API_KEY": {
"description": "Tenor API key for GIF search (used by the `gif-search` skill)",
"prompt": "Tenor API key",
"url": "https://developers.google.com/tenor/guides/quickstart",
"password": True,
"category": "skill",
"advanced": True,
},
# ── Honcho ──
"HONCHO_API_KEY": {
"description": "Honcho API key for AI-native persistent memory",
@@ -1813,30 +1552,6 @@ OPTIONAL_ENV_VARS = {
"category": "tool",
},
# ── Langfuse observability ──
"HERMES_LANGFUSE_PUBLIC_KEY": {
"description": "Langfuse project public key (pk-lf-...)",
"prompt": "Langfuse public key",
"url": "https://cloud.langfuse.com",
"password": False,
"category": "tool",
},
"HERMES_LANGFUSE_SECRET_KEY": {
"description": "Langfuse project secret key (sk-lf-...)",
"prompt": "Langfuse secret key",
"url": "https://cloud.langfuse.com",
"password": True,
"category": "tool",
},
"HERMES_LANGFUSE_BASE_URL": {
"description": "Langfuse server URL (default: https://cloud.langfuse.com)",
"prompt": "Langfuse server URL (leave empty for cloud.langfuse.com)",
"url": None,
"password": False,
"category": "tool",
"advanced": True,
},
# ── Messaging platforms ──
"TELEGRAM_BOT_TOKEN": {
"description": "Telegram bot token from @BotFather",
@@ -1984,14 +1699,6 @@ OPTIONAL_ENV_VARS = {
"category": "messaging",
"advanced": True,
},
"MATRIX_DM_AUTO_THREAD": {
"description": "Auto-create threads for DM messages in Matrix (default: false)",
"prompt": "Auto-create threads in DMs (true/false)",
"url": None,
"password": False,
"category": "messaging",
"advanced": True,
},
"MATRIX_DEVICE_ID": {
"description": "Stable Matrix device ID for E2EE persistence across restarts (e.g. HERMES_BOT)",
"prompt": "Matrix device ID (stable across restarts)",
@@ -2333,21 +2040,14 @@ def _normalize_custom_provider_entry(
"baseUrl": "base_url",
"apiMode": "api_mode",
"keyEnv": "key_env",
"apiKeyEnv": "key_env", # alias — OpenClaw-compatible + docs variant
"defaultModel": "default_model",
"contextLength": "context_length",
"rateLimitDelay": "rate_limit_delay",
}
# api_key_env is a documented snake_case alias for key_env (see
# website/docs/guides/azure-foundry.md). Normalize it up front so the
# rest of the normalizer treats it as the canonical field.
if "api_key_env" in entry and "key_env" not in entry:
entry["key_env"] = entry["api_key_env"]
_KNOWN_KEYS = {
"name", "api", "url", "base_url", "api_key", "key_env", "api_key_env",
"name", "api", "url", "base_url", "api_key", "key_env",
"api_mode", "transport", "model", "default_model", "models",
"context_length", "rate_limit_delay",
"request_timeout_seconds", "stale_timeout_seconds",
}
for camel, snake in _CAMEL_ALIASES.items():
if camel in entry and snake not in entry:
@@ -2505,71 +2205,6 @@ def get_compatible_custom_providers(
return compatible
def get_custom_provider_context_length(
model: str,
base_url: str,
custom_providers: Optional[List[Dict[str, Any]]] = None,
config: Optional[Dict[str, Any]] = None,
) -> Optional[int]:
"""Look up a per-model ``context_length`` override from ``custom_providers``.
Matches any entry whose ``base_url`` equals ``base_url`` (trailing-slash
insensitive) and returns ``custom_providers[i].models.<model>.context_length``
if present and valid. Returns ``None`` when no override applies.
This is the single source of truth for custom-provider context overrides,
used by:
* ``AIAgent.__init__`` (startup resolution)
* ``AIAgent.switch_model`` (mid-session ``/model`` switch)
* ``hermes_cli.model_switch.resolve_display_context_length`` (``/model`` confirmation display)
* ``gateway.run._format_session_info`` (``/info`` display)
* ``agent.model_metadata.get_model_context_length`` (when custom_providers is threaded through)
Before this helper existed, the lookup was duplicated in ``run_agent.py``'s
startup path only; every other path (notably ``/model`` switch) fell back
to the 128K default. See #15779.
"""
if not model or not base_url:
return None
if custom_providers is None:
try:
custom_providers = get_compatible_custom_providers(config)
except Exception:
if config is None:
return None
raw = config.get("custom_providers")
custom_providers = raw if isinstance(raw, list) else []
if not isinstance(custom_providers, list):
return None
target_url = (base_url or "").rstrip("/")
if not target_url:
return None
for entry in custom_providers:
if not isinstance(entry, dict):
continue
entry_url = (entry.get("base_url") or "").rstrip("/")
if not entry_url or entry_url != target_url:
continue
models = entry.get("models")
if not isinstance(models, dict):
continue
model_cfg = models.get(model)
if not isinstance(model_cfg, dict):
continue
raw_ctx = model_cfg.get("context_length")
if raw_ctx is None:
continue
try:
ctx = int(raw_ctx)
except (TypeError, ValueError):
continue
if ctx > 0:
return ctx
return None
def check_config_version() -> Tuple[int, int]:
"""
Check config version.
@@ -2599,9 +2234,6 @@ _KNOWN_ROOT_KEYS = {
_VALID_CUSTOM_PROVIDER_FIELDS = {
"name", "base_url", "api_key", "api_mode", "model", "models",
"context_length", "rate_limit_delay",
# key_env is read at runtime by runtime_provider.py and auxiliary_client.py
# — include it here so the set accurately describes the supported schema.
"key_env",
}
# Fields that look like they should be inside custom_providers, not at root
@@ -2678,32 +2310,10 @@ def validate_config_structure(config: Optional[Dict[str, Any]] = None) -> List["
"Add the API endpoint URL, e.g.: base_url: https://api.example.com/v1",
))
# ── fallback_model: single dict OR list of dicts (chain) ─────────────
# ── fallback_model must be a top-level dict with provider + model ────
fb = config.get("fallback_model")
if fb is not None:
if isinstance(fb, list):
# Chain fallback — validate each entry
for i, entry in enumerate(fb):
if not isinstance(entry, dict):
issues.append(ConfigIssue(
"error",
f"fallback_model[{i}] should be a dict, got {type(entry).__name__}",
"Each entry needs provider + model",
))
else:
if not entry.get("provider"):
issues.append(ConfigIssue(
"warning",
f"fallback_model[{i}] is missing 'provider' field",
"Add: provider: openrouter (or another provider)",
))
if not entry.get("model"):
issues.append(ConfigIssue(
"warning",
f"fallback_model[{i}] is missing 'model' field",
"Add: model: <model-name>",
))
elif not isinstance(fb, dict):
if not isinstance(fb, dict):
issues.append(ConfigIssue(
"error",
f"fallback_model should be a dict with 'provider' and 'model', got {type(fb).__name__}",
@@ -3488,52 +3098,6 @@ def _normalize_max_turns_config(config: Dict[str, Any]) -> Dict[str, Any]:
return config
def cfg_get(cfg: Optional[Dict[str, Any]], *keys: str, default: Any = None) -> Any:
"""Traverse nested dict keys safely, returning ``default`` on any miss.
Canonical helper for the ``cfg.get("X", {}).get("Y", default)`` pattern
that appears 50+ times across the codebase. Handles three common gotchas
in one place:
1. Missing intermediate keys (returns ``default``, no KeyError).
2. An intermediate value that's not a dict (e.g. a user wrote a string
where a section was expected). Returns ``default`` instead of
AttributeError on ``.get()``.
3. ``cfg is None`` (callers sometimes pass ``load_config() or None``).
Named ``cfg_get`` rather than ``cfg_path`` to avoid shadowing the
ubiquitous ``cfg_path = _hermes_home / "config.yaml"`` local variable
that appears in gateway/run.py, cron/scheduler.py, main.py, etc.
Explicit ``None`` values are returned as-is (matches ``dict.get(key,
default)`` semantics ``default`` is only returned when the key is
*absent*, not when it's present but set to ``None``).
Examples:
>>> cfg_get({"agent": {"reasoning_effort": "high"}}, "agent", "reasoning_effort")
'high'
>>> cfg_get({}, "agent", "reasoning_effort", default="medium")
'medium'
>>> cfg_get({"agent": "oops_a_string"}, "agent", "reasoning_effort", default="low")
'low'
>>> cfg_get(None, "anything", default=42)
42
>>> cfg_get({"a": {"b": None}}, "a", "b", default="def") # explicit None preserved
>>> cfg_get({"a": {"b": False}}, "a", "b", default=True) # falsy values preserved
False
"""
if not isinstance(cfg, dict):
return default
node: Any = cfg
for key in keys:
if not isinstance(node, dict):
return default
if key not in node:
return default
node = node[key]
return node
def read_raw_config() -> Dict[str, Any]:
"""Read ~/.hermes/config.yaml as-is, without merging defaults or migrating.
@@ -3542,62 +3106,25 @@ def read_raw_config() -> Dict[str, Any]:
be parsed. Use this for lightweight config reads where you just need a
single value and don't want the overhead of ``load_config()``'s deep-merge
+ migration pipeline.
Cached on the config file's (mtime_ns, size) — same strategy as
``load_config()``. Returns a deepcopy on every call since some callers
mutate the result before passing to ``save_config()``.
"""
try:
config_path = get_config_path()
st = config_path.stat()
cache_key = (st.st_mtime_ns, st.st_size)
except (FileNotFoundError, OSError):
return {}
path_key = str(config_path)
cached = _RAW_CONFIG_CACHE.get(path_key)
if cached is not None and cached[:2] == cache_key:
return copy.deepcopy(cached[2])
try:
with open(config_path, encoding="utf-8") as f:
data = yaml.safe_load(f) or {}
if config_path.exists():
with open(config_path, encoding="utf-8") as f:
return yaml.safe_load(f) or {}
except Exception:
return {}
if not isinstance(data, dict):
data = {}
_RAW_CONFIG_CACHE[path_key] = (cache_key[0], cache_key[1], copy.deepcopy(data))
return data
pass
return {}
def load_config() -> Dict[str, Any]:
"""Load configuration from ~/.hermes/config.yaml.
Cached on the config file's (mtime_ns, size). Returns a deepcopy of
the cached value when unchanged, since most call sites mutate the
result (e.g. ``cfg["model"]["default"] = ...`` before ``save_config``).
The cache is keyed on ``str(config_path)`` so profile switches
(which change ``HERMES_HOME`` and therefore ``get_config_path()``)
don't collide.
"""
"""Load configuration from ~/.hermes/config.yaml."""
ensure_hermes_home()
config_path = get_config_path()
path_key = str(config_path)
try:
st = config_path.stat()
cache_key: Optional[Tuple[int, int]] = (st.st_mtime_ns, st.st_size)
except FileNotFoundError:
cache_key = None
cached = _LOAD_CONFIG_CACHE.get(path_key)
if cached is not None and cache_key is not None and cached[:2] == cache_key:
return copy.deepcopy(cached[2])
config = copy.deepcopy(DEFAULT_CONFIG)
if cache_key is not None:
if config_path.exists():
try:
with open(config_path, encoding="utf-8") as f:
user_config = yaml.safe_load(f) or {}
@@ -3615,26 +3142,20 @@ def load_config() -> Dict[str, Any]:
normalized = _normalize_root_model_keys(_normalize_max_turns_config(config))
expanded = _expand_env_vars(normalized)
_LAST_EXPANDED_CONFIG_BY_PATH[path_key] = copy.deepcopy(expanded)
if cache_key is not None:
_LOAD_CONFIG_CACHE[path_key] = (cache_key[0], cache_key[1], copy.deepcopy(expanded))
else:
_LOAD_CONFIG_CACHE.pop(path_key, None)
_LAST_EXPANDED_CONFIG_BY_PATH[str(config_path)] = copy.deepcopy(expanded)
return expanded
_SECURITY_COMMENT = """
# ── Security ──────────────────────────────────────────────────────────
# Secret redaction is OFF by default — tool output (terminal stdout,
# read_file results, web content) passes through unmodified. Set
# redact_secrets to true to mask strings that look like API keys, tokens,
# and passwords before they enter the model context and logs.
# API keys, tokens, and passwords are redacted from tool output by default.
# Set to false to see full values (useful for debugging auth issues).
# tirith pre-exec scanning is enabled by default when the tirith binary
# is available. Configure via security.tirith_* keys or env vars
# (TIRITH_ENABLED, TIRITH_BIN, TIRITH_TIMEOUT, TIRITH_FAIL_OPEN).
#
# security:
# redact_secrets: true
# redact_secrets: false
# tirith_enabled: true
# tirith_path: "tirith"
# tirith_timeout: 5
@@ -3667,11 +3188,11 @@ _FALLBACK_COMMENT = """
_COMMENTED_SECTIONS = """
# ── Security ──────────────────────────────────────────────────────────
# Secret redaction is OFF by default. Set to true to mask strings that
# look like API keys, tokens, and passwords in tool output and logs.
# API keys, tokens, and passwords are redacted from tool output by default.
# Set to false to see full values (useful for debugging auth issues).
#
# security:
# redact_secrets: true
# redact_secrets: false
# ── Fallback Model ────────────────────────────────────────────────────
# Automatic provider failover when primary is unavailable.
@@ -3722,12 +3243,7 @@ def save_config(config: Dict[str, Any]):
if not sec or sec.get("redact_secrets") is None:
parts.append(_SECURITY_COMMENT)
fb = normalized.get("fallback_model", {})
fb_is_valid = False
if isinstance(fb, list):
fb_is_valid = any(isinstance(e, dict) and e.get("provider") and e.get("model") for e in fb)
elif isinstance(fb, dict):
fb_is_valid = bool(fb.get("provider") and fb.get("model"))
if not fb_is_valid:
if not fb or not isinstance(fb, dict) or not (fb.get("provider") and fb.get("model")):
parts.append(_FALLBACK_COMMENT)
atomic_yaml_write(
@@ -3796,27 +3312,18 @@ def _sanitize_env_lines(lines: list) -> list:
# Detect concatenated KEY=VALUE pairs on one line.
# Search for known KEY= patterns at any position in the line.
# We collect full needle ranges so we can drop matches that are
# fully contained within a longer overlapping needle. Without this,
# suffix collisions corrupt the file: e.g. LM_API_KEY= inside
# GLM_API_KEY= would otherwise split the line into "G\nLM_API_KEY=...".
match_ranges: list[tuple[int, int]] = []
split_positions = []
for key_name in known_keys:
needle = key_name + "="
idx = stripped.find(needle)
while idx >= 0:
match_ranges.append((idx, idx + len(needle)))
split_positions.append(idx)
idx = stripped.find(needle, idx + len(needle))
split_positions = sorted({
s for s, e in match_ranges
if not any(
s2 <= s and e2 >= e and (s2, e2) != (s, e)
for s2, e2 in match_ranges
)
})
if len(split_positions) > 1:
split_positions.sort()
# Deduplicate (shouldn't happen, but be safe)
split_positions = sorted(set(split_positions))
for i, pos in enumerate(split_positions):
end = split_positions[i + 1] if i + 1 < len(split_positions) else len(stripped)
part = stripped[pos:end].strip()
@@ -3862,7 +3369,7 @@ def sanitize_env_file() -> int:
f.writelines(sanitized)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, env_path)
os.replace(tmp_path, env_path)
except BaseException:
try:
os.unlink(tmp_path)
@@ -3925,7 +3432,7 @@ def save_env_value(key: str, value: str):
value = _check_non_ascii_credential(key, value)
ensure_hermes_home()
env_path = get_env_path()
# On Windows, open() defaults to the system locale (cp1252) which can
# cause OSError errno 22 on UTF-8 .env files.
read_kw = {"encoding": "utf-8", "errors": "replace"} if _IS_WINDOWS else {}
@@ -3937,7 +3444,7 @@ def save_env_value(key: str, value: str):
lines = f.readlines()
# Sanitize on every read: split concatenated keys, drop stale placeholders
lines = _sanitize_env_lines(lines)
# Find and update or append
found = False
for i, line in enumerate(lines):
@@ -3945,7 +3452,7 @@ def save_env_value(key: str, value: str):
lines[i] = f"{key}={value}\n"
found = True
break
if not found:
# Ensure there's a newline at the end of the file before appending
if lines and not lines[-1].endswith("\n"):
@@ -3965,7 +3472,7 @@ def save_env_value(key: str, value: str):
f.writelines(lines)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, env_path)
os.replace(tmp_path, env_path)
# Restore original permissions before _secure_file may tighten them.
if original_mode is not None:
try:
@@ -4021,7 +3528,7 @@ def remove_env_value(key: str) -> bool:
f.writelines(new_lines)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, env_path)
os.replace(tmp_path, env_path)
if original_mode is not None:
try:
os.chmod(env_path, original_mode)
@@ -4108,13 +3615,12 @@ def get_env_value(key: str) -> Optional[str]:
# =============================================================================
def redact_key(key: str) -> str:
"""Redact an API key for display.
Thin wrapper over :func:`agent.redact.mask_secret` preserves the
"(not set)" placeholder in dim color for the empty case.
"""
from agent.redact import mask_secret
return mask_secret(key, empty=color("(not set)", Colors.DIM))
"""Redact an API key for display."""
if not key:
return color("(not set)", Colors.DIM)
if len(key) < 12:
return "***"
return key[:4] + "..." + key[-4:]
def show_config():
@@ -4194,9 +3700,6 @@ def show_config():
print(f" Daytona image: {terminal.get('daytona_image', 'nikolaik/python-nodejs:python3.11-nodejs20')}")
daytona_key = get_env_value('DAYTONA_API_KEY')
print(f" API key: {'configured' if daytona_key else '(not set)'}")
elif terminal.get('backend') == 'vercel_sandbox':
print(f" Vercel runtime: {terminal.get('vercel_runtime', 'node24')}")
print(f" Vercel auth: {'configured' if get_env_value('VERCEL_OIDC_TOKEN') or (get_env_value('VERCEL_TOKEN') and get_env_value('VERCEL_PROJECT_ID') and get_env_value('VERCEL_TEAM_ID')) else '(not set)'}")
elif terminal.get('backend') == 'ssh':
ssh_host = get_env_value('TERMINAL_SSH_HOST')
ssh_user = get_env_value('TERMINAL_SSH_USER')
@@ -4389,9 +3892,7 @@ def set_config_value(key: str, value: str):
"terminal.singularity_image": "TERMINAL_SINGULARITY_IMAGE",
"terminal.modal_image": "TERMINAL_MODAL_IMAGE",
"terminal.daytona_image": "TERMINAL_DAYTONA_IMAGE",
"terminal.vercel_runtime": "TERMINAL_VERCEL_RUNTIME",
"terminal.docker_mount_cwd_to_workspace": "TERMINAL_DOCKER_MOUNT_CWD_TO_WORKSPACE",
"terminal.docker_run_as_host_user": "TERMINAL_DOCKER_RUN_AS_HOST_USER",
"terminal.cwd": "TERMINAL_CWD",
"terminal.timeout": "TERMINAL_TIMEOUT",
"terminal.sandbox_dir": "TERMINAL_SANDBOX_DIR",
-235
View File
@@ -1,235 +0,0 @@
"""CLI subcommand: `hermes curator <subcommand>`.
Thin shell around agent/curator.py and tools/skill_usage.py. Renders a status
table, triggers a run, pauses/resumes, and pins/unpins skills.
This module intentionally has no side effects at import time main.py wires
the argparse subparsers on demand.
"""
from __future__ import annotations
import argparse
import sys
from datetime import datetime, timezone
from typing import Optional
def _fmt_ts(ts: Optional[str]) -> str:
if not ts:
return "never"
try:
dt = datetime.fromisoformat(ts)
except (TypeError, ValueError):
return str(ts)
if dt.tzinfo is None:
dt = dt.replace(tzinfo=timezone.utc)
delta = datetime.now(timezone.utc) - dt
secs = int(delta.total_seconds())
if secs < 60:
return f"{secs}s ago"
if secs < 3600:
return f"{secs // 60}m ago"
if secs < 86400:
return f"{secs // 3600}h ago"
return f"{secs // 86400}d ago"
def _cmd_status(args) -> int:
from agent import curator
from tools import skill_usage
state = curator.load_state()
enabled = curator.is_enabled()
paused = state.get("paused", False)
last_run = state.get("last_run_at")
summary = state.get("last_run_summary") or "(none)"
runs = state.get("run_count", 0)
status_line = (
"ENABLED" if enabled and not paused else
"PAUSED" if paused else
"DISABLED"
)
print(f"curator: {status_line}")
print(f" runs: {runs}")
print(f" last run: {_fmt_ts(last_run)}")
print(f" last summary: {summary}")
_report = state.get("last_report_path")
if _report:
print(f" last report: {_report}")
_ih = curator.get_interval_hours()
_interval_label = (
f"{_ih // 24}d" if _ih % 24 == 0 and _ih >= 24
else f"{_ih}h"
)
print(f" interval: every {_interval_label}")
print(f" stale after: {curator.get_stale_after_days()}d unused")
print(f" archive after: {curator.get_archive_after_days()}d unused")
rows = skill_usage.agent_created_report()
if not rows:
print("\nno agent-created skills")
return 0
by_state = {"active": [], "stale": [], "archived": []}
pinned = []
for r in rows:
state_name = r.get("state", "active")
by_state.setdefault(state_name, []).append(r)
if r.get("pinned"):
pinned.append(r["name"])
print(f"\nagent-created skills: {len(rows)} total")
for state_name in ("active", "stale", "archived"):
bucket = by_state.get(state_name, [])
print(f" {state_name:10s} {len(bucket)}")
if pinned:
print(f"\npinned ({len(pinned)}): {', '.join(pinned)}")
# Show top 5 least-recently-used active skills
active = sorted(
by_state.get("active", []),
key=lambda r: r.get("last_used_at") or r.get("created_at") or "",
)[:5]
if active:
print("\nleast recently used (top 5):")
for r in active:
last = _fmt_ts(r.get("last_used_at"))
print(f" {r['name']:40s} use={r.get('use_count', 0):3d} last_used={last}")
return 0
def _cmd_run(args) -> int:
from agent import curator
if not curator.is_enabled():
print("curator: disabled via config; enable with `curator.enabled: true`")
return 1
print("curator: running review pass...")
def _on_summary(msg: str) -> None:
print(msg)
result = curator.run_curator_review(
on_summary=_on_summary,
synchronous=bool(args.synchronous),
)
auto = result.get("auto_transitions", {})
if auto:
print(
f"auto: checked={auto.get('checked', 0)} "
f"stale={auto.get('marked_stale', 0)} "
f"archived={auto.get('archived', 0)} "
f"reactivated={auto.get('reactivated', 0)}"
)
if not args.synchronous:
print("llm pass running in background — check `hermes curator status` later")
return 0
def _cmd_pause(args) -> int:
from agent import curator
curator.set_paused(True)
print("curator: paused")
return 0
def _cmd_resume(args) -> int:
from agent import curator
curator.set_paused(False)
print("curator: resumed")
return 0
def _cmd_pin(args) -> int:
from tools import skill_usage
if not skill_usage.is_agent_created(args.skill):
print(
f"curator: '{args.skill}' is bundled or hub-installed — cannot pin "
"(only agent-created skills participate in curation)"
)
return 1
skill_usage.set_pinned(args.skill, True)
print(f"curator: pinned '{args.skill}' (will bypass auto-transitions)")
return 0
def _cmd_unpin(args) -> int:
from tools import skill_usage
if not skill_usage.is_agent_created(args.skill):
print(
f"curator: '{args.skill}' is bundled or hub-installed — "
"there's nothing to unpin (curator only tracks agent-created skills)"
)
return 1
skill_usage.set_pinned(args.skill, False)
print(f"curator: unpinned '{args.skill}'")
return 0
def _cmd_restore(args) -> int:
from tools import skill_usage
ok, msg = skill_usage.restore_skill(args.skill)
print(f"curator: {msg}")
return 0 if ok else 1
# ---------------------------------------------------------------------------
# argparse wiring (called from hermes_cli.main)
# ---------------------------------------------------------------------------
def register_cli(parent: argparse.ArgumentParser) -> None:
"""Attach `curator` subcommands to *parent*.
main.py calls this with the ArgumentParser returned by
``subparsers.add_parser("curator", ...)``.
"""
parent.set_defaults(func=lambda a: (parent.print_help(), 0)[1])
subs = parent.add_subparsers(dest="curator_command")
p_status = subs.add_parser("status", help="Show curator status and skill stats")
p_status.set_defaults(func=_cmd_status)
p_run = subs.add_parser("run", help="Trigger a curator review now")
p_run.add_argument(
"--sync", "--synchronous", dest="synchronous", action="store_true",
help="Wait for the LLM review pass to finish (default: background thread)",
)
p_run.set_defaults(func=_cmd_run)
p_pause = subs.add_parser("pause", help="Pause the curator until resumed")
p_pause.set_defaults(func=_cmd_pause)
p_resume = subs.add_parser("resume", help="Resume a paused curator")
p_resume.set_defaults(func=_cmd_resume)
p_pin = subs.add_parser("pin", help="Pin a skill so the curator never auto-transitions it")
p_pin.add_argument("skill", help="Skill name")
p_pin.set_defaults(func=_cmd_pin)
p_unpin = subs.add_parser("unpin", help="Unpin a skill")
p_unpin.add_argument("skill", help="Skill name")
p_unpin.set_defaults(func=_cmd_unpin)
p_restore = subs.add_parser("restore", help="Restore an archived skill")
p_restore.add_argument("skill", help="Skill name")
p_restore.set_defaults(func=_cmd_restore)
def cli_main(argv=None) -> int:
"""Standalone entry (also usable by hermes_cli.main fallthrough)."""
parser = argparse.ArgumentParser(prog="hermes curator")
register_cli(parser)
args = parser.parse_args(argv)
fn = getattr(args, "func", None)
if fn is None:
parser.print_help()
return 0
return int(fn(args) or 0)
if __name__ == "__main__": # pragma: no cover
sys.exit(cli_main())
+7 -13
View File
@@ -7,6 +7,7 @@ Currently supports:
import io
import json
import os
import sys
import time
import urllib.error
@@ -17,7 +18,6 @@ from pathlib import Path
from typing import Optional
from hermes_constants import get_hermes_home
from utils import atomic_replace
# ---------------------------------------------------------------------------
@@ -45,13 +45,8 @@ def _pending_file() -> Path:
Each entry: ``{"url": "...", "expire_at": <unix_ts>}``. Scheduled
DELETEs used to be handled by spawning a detached Python process per
paste that slept for 6 hours; those accumulated forever if the user
ran ``hermes debug share`` repeatedly.
Deletion is now driven by the gateway's cron ticker
(``gateway/run.py::_start_cron_ticker``) which calls
``_sweep_expired_pastes`` once per hour. ``hermes debug share`` also
runs an opportunistic sweep on entry as a fallback for CLI-only users
who never start the gateway.
ran ``hermes debug share`` repeatedly. We now persist the schedule
to disk and sweep expired entries on the next debug invocation.
"""
return get_hermes_home() / "pastes" / "pending.json"
@@ -79,7 +74,7 @@ def _save_pending(entries: list[dict]) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
tmp = path.with_suffix(".json.tmp")
tmp.write_text(json.dumps(entries, indent=2), encoding="utf-8")
atomic_replace(tmp, path)
os.replace(tmp, path)
except OSError:
# Non-fatal — worst case the user has to run ``hermes debug delete``
# manually.
@@ -228,10 +223,9 @@ def _schedule_auto_delete(urls: list[str], delay_seconds: int = _AUTO_DELETE_SEC
interpreters that never exited until the sleep completed.
The replacement is stateless: we append to ``~/.hermes/pastes/pending.json``
and the gateway's cron ticker sweeps expired entries once per hour.
``hermes debug share`` also runs an opportunistic sweep as a fallback
for CLI-only users. If neither runs again, paste.rs's own retention
policy handles cleanup.
and rely on opportunistic sweeps (``_sweep_expired_pastes``) called from
every ``hermes debug`` invocation. If the user never runs ``hermes debug``
again, paste.rs's own retention policy handles cleanup.
"""
_record_pending(urls, delay_seconds=delay_seconds)
+1
View File
@@ -13,6 +13,7 @@ automatically.
from __future__ import annotations
import io
import os
import sys
import time
+14 -137
View File
@@ -8,7 +8,6 @@ import os
import sys
import subprocess
import shutil
import importlib.util
from pathlib import Path
from hermes_cli.config import get_project_root, get_hermes_home, get_env_path
@@ -31,7 +30,6 @@ load_dotenv(PROJECT_ROOT / ".env", override=False, encoding="utf-8")
from hermes_cli.colors import Colors, color
from hermes_cli.models import _HERMES_USER_AGENT
from hermes_cli.vercel_auth import describe_vercel_auth
from hermes_constants import OPENROUTER_MODELS_URL
from utils import base_url_host_matches
@@ -48,7 +46,6 @@ _PROVIDER_ENV_HINTS = (
"Z_AI_API_KEY",
"KIMI_API_KEY",
"KIMI_CN_API_KEY",
"GMI_API_KEY",
"MINIMAX_API_KEY",
"MINIMAX_CN_API_KEY",
"KILOCODE_API_KEY",
@@ -59,7 +56,6 @@ _PROVIDER_ENV_HINTS = (
"OPENCODE_ZEN_API_KEY",
"OPENCODE_GO_API_KEY",
"XIAOMI_API_KEY",
"TOKENHUB_API_KEY",
)
@@ -295,23 +291,15 @@ def run_doctor(args):
known_providers: set = set()
try:
from hermes_cli.auth import (
PROVIDER_REGISTRY,
resolve_provider as _resolve_auth_provider,
)
from hermes_cli.auth import PROVIDER_REGISTRY
known_providers = set(PROVIDER_REGISTRY.keys()) | {"openrouter", "custom", "auto"}
except Exception:
_resolve_auth_provider = None
pass
try:
from hermes_cli.config import get_compatible_custom_providers as _compatible_custom_providers
from hermes_cli.providers import (
normalize_provider as _normalize_catalog_provider,
resolve_provider_full as _resolve_provider_full,
)
from hermes_cli.providers import resolve_provider_full as _resolve_provider_full
except Exception:
_compatible_custom_providers = None
_normalize_catalog_provider = None
_resolve_provider_full = None
custom_providers = []
@@ -331,43 +319,13 @@ def run_doctor(args):
if name:
known_providers.add("custom:" + name.lower().replace(" ", "-"))
valid_provider_ids = set(known_providers)
provider_ids_to_accept = {provider} if provider else set()
if _normalize_catalog_provider is not None:
for known_provider in known_providers:
try:
valid_provider_ids.add(_normalize_catalog_provider(known_provider))
except Exception:
continue
runtime_provider = provider
if (
provider
and _resolve_auth_provider is not None
and provider not in ("auto", "custom")
):
try:
runtime_provider = _resolve_auth_provider(provider)
provider_ids_to_accept.add(runtime_provider)
except Exception:
runtime_provider = provider
catalog_provider = provider
if (
provider
and _resolve_provider_full is not None
and provider not in ("auto", "custom")
):
canonical_provider = provider
if provider and _resolve_provider_full is not None and provider != "auto":
provider_def = _resolve_provider_full(provider, user_providers, custom_providers)
catalog_provider = provider_def.id if provider_def is not None else None
if catalog_provider is not None:
provider_ids_to_accept.add(catalog_provider)
canonical_provider = provider_def.id if provider_def is not None else None
if provider and provider != "auto":
if catalog_provider is None or (
known_providers
and not (provider_ids_to_accept & valid_provider_ids)
):
if canonical_provider is None or (known_providers and canonical_provider not in known_providers):
known_list = ", ".join(sorted(known_providers)) if known_providers else "(unavailable)"
check_fail(
f"model.provider '{provider_raw}' is not a recognised provider",
@@ -380,24 +338,7 @@ def run_doctor(args):
)
# Warn if model is set to a provider-prefixed name on a provider that doesn't use them
provider_for_policy = runtime_provider or catalog_provider
providers_accepting_vendor_slugs = {
"openrouter",
"custom",
"auto",
"ai-gateway",
"kilocode",
"opencode-zen",
"huggingface",
"lmstudio",
"nous",
}
if (
default_model
and "/" in default_model
and provider_for_policy
and provider_for_policy not in providers_accepting_vendor_slugs
):
if default_model and "/" in default_model and canonical_provider and canonical_provider not in ("openrouter", "custom", "auto", "ai-gateway", "kilocode", "opencode-zen", "huggingface", "nous"):
check_warn(
f"model.default '{default_model}' uses a vendor/model slug but provider is '{provider_raw}'",
"(vendor-prefixed slugs belong to aggregators like openrouter)",
@@ -413,24 +354,20 @@ def run_doctor(args):
# own env-var checks elsewhere in doctor, and get_auth_status()
# returns a bare {logged_in: False} for anything it doesn't
# explicitly dispatch, which would produce false positives.
if runtime_provider and runtime_provider not in ("auto", "custom", "openrouter"):
if canonical_provider and canonical_provider not in ("auto", "custom", "openrouter"):
try:
from hermes_cli.auth import PROVIDER_REGISTRY, get_auth_status
pconfig = PROVIDER_REGISTRY.get(runtime_provider)
pconfig = PROVIDER_REGISTRY.get(canonical_provider)
if pconfig and getattr(pconfig, "auth_type", "") == "api_key":
status = get_auth_status(runtime_provider) or {}
configured = bool(
status.get("configured")
or status.get("logged_in")
or status.get("api_key")
)
status = get_auth_status(canonical_provider) or {}
configured = bool(status.get("configured") or status.get("logged_in") or status.get("api_key"))
if not configured:
check_fail(
f"model.provider '{runtime_provider}' is set but no API key is configured",
f"model.provider '{canonical_provider}' is set but no API key is configured",
"(check ~/.hermes/.env or run 'hermes setup')",
)
issues.append(
f"No credentials found for provider '{runtime_provider}'. "
f"No credentials found for provider '{canonical_provider}'. "
f"Run 'hermes setup' or set the provider's API key in {_DHH}/.env, "
f"or switch providers with 'hermes config set model.provider <name>'"
)
@@ -539,7 +476,6 @@ def run_doctor(args):
get_nous_auth_status,
get_codex_auth_status,
get_gemini_oauth_auth_status,
get_minimax_oauth_auth_status,
)
nous_status = get_nous_auth_status()
@@ -569,27 +505,13 @@ def run_doctor(args):
check_ok("Google Gemini OAuth", f"(logged in{suffix})")
else:
check_warn("Google Gemini OAuth", "(not logged in)")
minimax_status = get_minimax_oauth_auth_status()
if minimax_status.get("logged_in"):
region = minimax_status.get("region", "global")
check_ok("MiniMax OAuth", f"(logged in, region={region})")
else:
check_warn("MiniMax OAuth", "(not logged in)")
except Exception as e:
check_warn("Auth provider status", f"(could not check: {e})")
if shutil.which("codex"):
check_ok("codex CLI")
else:
# Native OAuth uses Hermes' own device-code flow — the Codex CLI is
# only needed if you want to import existing tokens from
# ~/.codex/auth.json. Downgrade to info so users running
# `hermes auth openai-codex` aren't told they're missing something.
check_info(
"codex CLI not installed "
"(optional — only required to import tokens from an existing Codex CLI login)"
)
check_warn("codex CLI not found", "(required for openai-codex login)")
# =========================================================================
# Check: Directory structure
@@ -873,50 +795,6 @@ def run_doctor(args):
check_fail("daytona SDK not installed", "(pip install daytona)")
issues.append("Install daytona SDK: pip install daytona")
# Vercel Sandbox (if using vercel_sandbox backend)
if terminal_env == "vercel_sandbox":
runtime = os.getenv("TERMINAL_VERCEL_RUNTIME", "node24").strip() or "node24"
from tools.terminal_tool import _SUPPORTED_VERCEL_RUNTIMES
if runtime in _SUPPORTED_VERCEL_RUNTIMES:
check_ok("Vercel runtime", f"({runtime})")
else:
supported = ", ".join(_SUPPORTED_VERCEL_RUNTIMES)
check_fail("Vercel runtime unsupported", f"({runtime}; use {supported})")
issues.append(f"Set TERMINAL_VERCEL_RUNTIME to one of: {supported}")
disk = os.getenv("TERMINAL_CONTAINER_DISK", "51200").strip()
if disk in ("", "0", "51200"):
check_ok("Vercel disk setting", "(uses platform default)")
else:
check_fail("Vercel custom disk unsupported", "(reset terminal.container_disk to 51200)")
issues.append("Vercel Sandbox does not support custom container_disk; use the shared default 51200")
if importlib.util.find_spec("vercel") is not None:
check_ok("vercel SDK", "(installed)")
else:
check_fail("vercel SDK not installed", "(pip install 'hermes-agent[vercel]')")
issues.append("Install the Vercel optional dependency: pip install 'hermes-agent[vercel]'")
auth_status = describe_vercel_auth()
if auth_status.ok:
check_ok("Vercel auth", f"({auth_status.label})")
elif auth_status.label.startswith("partial"):
check_fail("Vercel auth incomplete", f"({auth_status.label})")
issues.append("Set VERCEL_TOKEN, VERCEL_PROJECT_ID, and VERCEL_TEAM_ID together")
else:
check_fail("Vercel auth not configured", f"({auth_status.label})")
issues.append(
"Configure Vercel Sandbox auth with VERCEL_TOKEN, VERCEL_PROJECT_ID, and VERCEL_TEAM_ID"
)
for line in auth_status.detail_lines:
check_info(f"Vercel auth {line}")
persistent = os.getenv("TERMINAL_CONTAINER_PERSISTENT", "true").lower() in ("1", "true", "yes", "on")
if persistent:
check_info("Vercel persistence: snapshot filesystem only; live processes do not survive sandbox recreation")
else:
check_info("Vercel persistence: ephemeral filesystem")
# Node.js + agent-browser (for browser automation tools)
if shutil.which("node"):
check_ok("Node.js")
@@ -1055,7 +933,6 @@ def run_doctor(args):
("StepFun Step Plan", ("STEPFUN_API_KEY",), "https://api.stepfun.ai/step_plan/v1/models", "STEPFUN_BASE_URL", True),
("Kimi / Moonshot (China)", ("KIMI_CN_API_KEY",), "https://api.moonshot.cn/v1/models", None, True),
("Arcee AI", ("ARCEEAI_API_KEY",), "https://api.arcee.ai/api/v1/models", "ARCEE_BASE_URL", True),
("GMI Cloud", ("GMI_API_KEY",), "https://api.gmi-serving.com/v1/models", "GMI_BASE_URL", True),
("DeepSeek", ("DEEPSEEK_API_KEY",), "https://api.deepseek.com/v1/models", "DEEPSEEK_BASE_URL", True),
("Hugging Face", ("HF_TOKEN",), "https://router.huggingface.co/v1/models", "HF_BASE_URL", True),
("NVIDIA NIM", ("NVIDIA_API_KEY",), "https://integrate.api.nvidia.com/v1/models", "NVIDIA_BASE_URL", True),
+6 -8
View File
@@ -33,14 +33,12 @@ def _get_git_commit(project_root: Path) -> str:
def _redact(value: str) -> str:
"""Redact all but first 4 and last 4 chars.
Thin wrapper over :func:`agent.redact.mask_secret`. Returns ``""`` for
an empty value (matches the historical behavior of this helper
``hermes dump`` formats empty values as blank, not as ``"(not set)"``).
"""
from agent.redact import mask_secret
return mask_secret(value)
"""Redact all but first 4 and last 4 chars."""
if not value:
return ""
if len(value) < 12:
return "***"
return value[:4] + "..." + value[-4:]
def _gateway_status() -> str:
+1 -2
View File
@@ -7,7 +7,6 @@ import sys
from pathlib import Path
from dotenv import load_dotenv
from utils import atomic_replace
# Env var name suffixes that indicate credential values. These are the
@@ -128,7 +127,7 @@ def _sanitize_env_file_if_needed(path: Path) -> None:
f.writelines(sanitized)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp, path)
os.replace(tmp, path)
except BaseException:
try:
os.unlink(tmp)
-361
View File
@@ -1,361 +0,0 @@
"""
hermes fallback manage the fallback provider chain.
Fallback providers are tried in order when the primary model fails with
rate-limit, overload, or connection errors. See:
https://hermes-agent.nousresearch.com/docs/user-guide/features/fallback-providers
Subcommands:
hermes fallback [list] Show the current fallback chain (default when no subcommand)
hermes fallback add Pick provider + model via the same picker as `hermes model`,
then append the selection to the chain
hermes fallback remove Pick an entry to delete from the chain
hermes fallback clear Remove all fallback entries
Storage: ``fallback_providers`` in ``~/.hermes/config.yaml`` (top-level, list of
``{provider, model, base_url?, api_mode?}`` dicts). The legacy single-dict
``fallback_model`` format is migrated to the new list format on first add.
"""
from __future__ import annotations
import copy
from typing import Any, Dict, List, Optional
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
def _read_chain(config: Dict[str, Any]) -> List[Dict[str, Any]]:
"""Return the normalized fallback chain as a list of dicts.
Accepts both the new list format (``fallback_providers``) and the legacy
single-dict format (``fallback_model``). The returned list is always a
fresh copy callers can mutate without touching the config dict.
"""
chain = config.get("fallback_providers") or []
if isinstance(chain, list):
result = [dict(e) for e in chain if isinstance(e, dict) and e.get("provider") and e.get("model")]
if result:
return result
legacy = config.get("fallback_model")
if isinstance(legacy, dict) and legacy.get("provider") and legacy.get("model"):
return [dict(legacy)]
if isinstance(legacy, list):
return [dict(e) for e in legacy if isinstance(e, dict) and e.get("provider") and e.get("model")]
return []
def _write_chain(config: Dict[str, Any], chain: List[Dict[str, Any]]) -> None:
"""Persist the chain to ``fallback_providers`` and clear legacy key."""
config["fallback_providers"] = chain
# Drop the legacy single-dict key on write so there's only one source of truth.
if "fallback_model" in config:
config.pop("fallback_model", None)
def _format_entry(entry: Dict[str, Any]) -> str:
"""One-line human-readable rendering of a fallback entry."""
provider = entry.get("provider", "?")
model = entry.get("model", "?")
base = entry.get("base_url")
suffix = f" [{base}]" if base else ""
return f"{model} (via {provider}){suffix}"
def _extract_fallback_from_model_cfg(model_cfg: Any) -> Optional[Dict[str, Any]]:
"""Pull the ``{provider, model, base_url?, api_mode?}`` dict from a ``config["model"]`` snapshot."""
if not isinstance(model_cfg, dict):
return None
provider = (model_cfg.get("provider") or "").strip()
# The picker writes the selected model to ``model.default``.
model = (model_cfg.get("default") or model_cfg.get("model") or "").strip()
if not provider or not model:
return None
entry: Dict[str, Any] = {"provider": provider, "model": model}
base_url = (model_cfg.get("base_url") or "").strip()
if base_url:
entry["base_url"] = base_url
api_mode = (model_cfg.get("api_mode") or "").strip()
if api_mode:
entry["api_mode"] = api_mode
return entry
def _snapshot_auth_active_provider() -> Any:
"""Return the current ``active_provider`` in auth.json, or a sentinel if unavailable."""
try:
from hermes_cli.auth import _load_auth_store
store = _load_auth_store()
return store.get("active_provider")
except Exception:
return None
def _restore_auth_active_provider(value: Any) -> None:
"""Write back a previously snapshotted ``active_provider`` value."""
try:
from hermes_cli.auth import _auth_store_lock, _load_auth_store, _save_auth_store
with _auth_store_lock():
store = _load_auth_store()
store["active_provider"] = value
_save_auth_store(store)
except Exception:
# Best-effort — if auth.json can't be restored, the user's primary
# provider may have been deactivated by the picker. They can re-run
# `hermes model` to fix it. Don't fail the fallback add.
pass
# ---------------------------------------------------------------------------
# Subcommand handlers
# ---------------------------------------------------------------------------
def cmd_fallback_list(args) -> None: # noqa: ARG001
"""Print the current fallback chain."""
from hermes_cli.config import load_config
config = load_config()
chain = _read_chain(config)
print()
if not chain:
print(" No fallback providers configured.")
print()
print(" Add one with: hermes fallback add")
print()
return
primary = _describe_primary(config)
if primary:
print(f" Primary: {primary}")
print()
print(f" Fallback chain ({len(chain)} {'entry' if len(chain) == 1 else 'entries'}):")
for i, entry in enumerate(chain, 1):
print(f" {i}. {_format_entry(entry)}")
print()
print(" Tried in order when the primary fails (rate-limit, 5xx, connection errors).")
print(" Docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/fallback-providers")
print()
def _describe_primary(config: Dict[str, Any]) -> Optional[str]:
"""One-line description of the primary model for display purposes."""
model_cfg = config.get("model")
if isinstance(model_cfg, dict):
provider = (model_cfg.get("provider") or "?").strip() or "?"
model = (model_cfg.get("default") or model_cfg.get("model") or "?").strip() or "?"
return f"{model} (via {provider})"
if isinstance(model_cfg, str) and model_cfg.strip():
return model_cfg.strip()
return None
def cmd_fallback_add(args) -> None:
"""Launch the same picker as `hermes model`, then append the selection to the chain."""
from hermes_cli.main import _require_tty, select_provider_and_model
from hermes_cli.config import load_config, save_config
_require_tty("fallback add")
# Snapshot BEFORE the picker runs so we can distinguish "user actually
# picked something" from "user cancelled" by comparing before/after.
before_cfg = load_config()
model_before = copy.deepcopy(before_cfg.get("model"))
active_provider_before = _snapshot_auth_active_provider()
print()
print(" Adding a fallback provider. The picker below is the same one used by")
print(" `hermes model` — select the provider + model you want as a fallback.")
print()
try:
select_provider_and_model(args=args)
except SystemExit:
# Some provider flows exit on auth failure — restore state and re-raise.
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
raise
# Read the post-picker state to see what the user selected.
after_cfg = load_config()
model_after = after_cfg.get("model")
new_entry = _extract_fallback_from_model_cfg(model_after)
if not new_entry:
# Picker didn't complete (user cancelled or flow bailed). Nothing to do.
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
print()
print(" No fallback added.")
return
# Picker picked the same thing that's already the primary → nothing changed,
# and there's nothing useful to add as a fallback to itself.
primary_entry = _extract_fallback_from_model_cfg(model_before)
if primary_entry and primary_entry["provider"] == new_entry["provider"] \
and primary_entry["model"] == new_entry["model"]:
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
print()
print(f" Selected model matches the current primary ({_format_entry(new_entry)}).")
print(" A provider cannot be a fallback for itself — no change.")
return
# Reload the config with the primary restored, then append the new entry
# to ``fallback_providers``. We deliberately re-load (rather than mutating
# ``after_cfg``) because the picker may have touched other top-level keys
# (custom_providers, providers credentials) that we want to keep.
_restore_model_cfg(model_before)
_restore_auth_active_provider(active_provider_before)
final_cfg = load_config()
chain = _read_chain(final_cfg)
# Reject exact-duplicate fallback entries.
for existing in chain:
if existing.get("provider") == new_entry["provider"] \
and existing.get("model") == new_entry["model"]:
print()
print(f" {_format_entry(new_entry)} is already in the fallback chain — skipped.")
return
chain.append(new_entry)
_write_chain(final_cfg, chain)
save_config(final_cfg)
print()
print(f" Added fallback: {_format_entry(new_entry)}")
print(f" Chain is now {len(chain)} {'entry' if len(chain) == 1 else 'entries'} long.")
print()
print(" Run `hermes fallback list` to view, or `hermes fallback remove` to delete.")
def _restore_model_cfg(model_before: Any) -> None:
"""Restore ``config["model"]`` to a previously-captured snapshot."""
from hermes_cli.config import load_config, save_config
cfg = load_config()
if model_before is None:
cfg.pop("model", None)
else:
cfg["model"] = copy.deepcopy(model_before)
save_config(cfg)
def cmd_fallback_remove(args) -> None: # noqa: ARG001
"""Pick an entry from the chain and remove it."""
from hermes_cli.config import load_config, save_config
config = load_config()
chain = _read_chain(config)
if not chain:
print()
print(" No fallback providers configured — nothing to remove.")
print()
return
choices = [_format_entry(e) for e in chain]
choices.append("Cancel")
try:
from hermes_cli.setup import _curses_prompt_choice
idx = _curses_prompt_choice("Select a fallback to remove:", choices, 0)
except Exception:
idx = _numbered_pick("Select a fallback to remove:", choices)
if idx is None or idx < 0 or idx >= len(chain):
print()
print(" Cancelled — no change.")
return
removed = chain.pop(idx)
_write_chain(config, chain)
save_config(config)
print()
print(f" Removed fallback: {_format_entry(removed)}")
if chain:
print(f" Chain is now {len(chain)} {'entry' if len(chain) == 1 else 'entries'} long.")
else:
print(" Fallback chain is now empty.")
print()
def cmd_fallback_clear(args) -> None: # noqa: ARG001
"""Remove all fallback entries (with confirmation)."""
from hermes_cli.config import load_config, save_config
config = load_config()
chain = _read_chain(config)
if not chain:
print()
print(" No fallback providers configured — nothing to clear.")
print()
return
print()
print(f" Current fallback chain ({len(chain)} {'entry' if len(chain) == 1 else 'entries'}):")
for i, entry in enumerate(chain, 1):
print(f" {i}. {_format_entry(entry)}")
print()
try:
resp = input(" Clear all entries? [y/N]: ").strip().lower()
except (KeyboardInterrupt, EOFError):
print()
print(" Cancelled.")
return
if resp not in ("y", "yes"):
print(" Cancelled — no change.")
return
_write_chain(config, [])
save_config(config)
print()
print(" Fallback chain cleared.")
print()
def _numbered_pick(question: str, choices: List[str]) -> Optional[int]:
"""Fallback numbered-list picker when curses is unavailable."""
print(question)
for i, c in enumerate(choices, 1):
print(f" {i}. {c}")
print()
while True:
try:
val = input(f"Choice [1-{len(choices)}]: ").strip()
if not val:
return None
idx = int(val) - 1
if 0 <= idx < len(choices):
return idx
print(f"Please enter 1-{len(choices)}")
except ValueError:
print("Please enter a number")
except (KeyboardInterrupt, EOFError):
print()
return None
# ---------------------------------------------------------------------------
# Dispatch
# ---------------------------------------------------------------------------
def cmd_fallback(args) -> None:
"""Top-level dispatcher for ``hermes fallback [subcommand]``."""
sub = getattr(args, "fallback_command", None)
if sub in (None, "", "list", "ls"):
cmd_fallback_list(args)
elif sub == "add":
cmd_fallback_add(args)
elif sub in ("remove", "rm"):
cmd_fallback_remove(args)
elif sub == "clear":
cmd_fallback_clear(args)
else:
print(f"Unknown fallback subcommand: {sub}")
print("Use one of: list, add, remove, clear")
raise SystemExit(2)
+20 -65
View File
@@ -279,11 +279,9 @@ def _scan_gateway_pids(exclude_pids: set[int], all_profiles: bool = False) -> li
["wmic", "process", "get", "ProcessId,CommandLine", "/FORMAT:LIST"],
capture_output=True,
text=True,
encoding="utf-8",
errors="ignore",
timeout=10,
)
if result.returncode != 0 or result.stdout is None:
if result.returncode != 0:
return []
current_cmd = ""
for line in result.stdout.split("\n"):
@@ -832,22 +830,6 @@ def _user_dbus_socket_path() -> Path:
return Path(xdg) / "bus"
def _user_systemd_private_socket_path() -> Path:
"""Return the per-user systemd private socket path (regardless of existence)."""
xdg = os.environ.get("XDG_RUNTIME_DIR") or f"/run/user/{os.getuid()}"
return Path(xdg) / "systemd" / "private"
def _user_systemd_socket_ready() -> bool:
"""Return True when user-scope systemd has a reachable control socket.
Some distros expose only the per-user systemd private socket even when the
D-Bus session bus socket is absent. ``systemctl --user`` can still work in
that configuration, so preflight checks must treat either socket as valid.
"""
return _user_dbus_socket_path().exists() or _user_systemd_private_socket_path().exists()
def _ensure_user_systemd_env() -> None:
"""Ensure DBUS_SESSION_BUS_ADDRESS and XDG_RUNTIME_DIR are set for systemctl --user.
@@ -871,29 +853,28 @@ def _ensure_user_systemd_env() -> None:
def _wait_for_user_dbus_socket(timeout: float = 3.0) -> bool:
"""Poll for the user systemd runtime socket(s), up to ``timeout`` seconds.
"""Poll for the user D-Bus socket to appear, up to ``timeout`` seconds.
Linger-enabled user@.service can take a second or two to spawn its control
socket(s) after ``loginctl enable-linger`` runs. Returns True once either
the user D-Bus socket or the per-user systemd private socket exists.
Linger-enabled user@.service can take a second or two to spawn the socket
after ``loginctl enable-linger`` runs. Returns True once the socket exists.
"""
import time
deadline = time.monotonic() + timeout
while time.monotonic() < deadline:
if _user_systemd_socket_ready():
if _user_dbus_socket_path().exists():
_ensure_user_systemd_env()
return True
time.sleep(0.2)
return _user_systemd_socket_ready()
return _user_dbus_socket_path().exists()
def _preflight_user_systemd(*, auto_enable_linger: bool = True) -> None:
"""Ensure ``systemctl --user`` will reach the user-scope systemd instance.
"""Ensure ``systemctl --user`` will reach the user D-Bus session bus.
No-op when the user D-Bus socket or per-user systemd private socket is
already there (the common case on desktops and linger-enabled servers). On
fresh SSH sessions where both are missing:
No-op when the bus socket is already there (the common case on desktops
and linger-enabled servers). On fresh SSH sessions where the socket is
missing:
* If linger is already enabled, wait briefly for user@.service to spawn
the socket.
@@ -907,7 +888,8 @@ def _preflight_user_systemd(*, auto_enable_linger: bool = True) -> None:
systemd operations and surface the message to the user.
"""
_ensure_user_systemd_env()
if _user_systemd_socket_ready():
bus_path = _user_dbus_socket_path()
if bus_path.exists():
return
import getpass
@@ -921,7 +903,7 @@ def _preflight_user_systemd(*, auto_enable_linger: bool = True) -> None:
# Linger is on but socket still missing — unusual; fall through to error.
_raise_user_systemd_unavailable(
username,
reason="User systemd control sockets are missing even though linger is enabled.",
reason="User D-Bus socket is missing even though linger is enabled.",
fix_hint=(
f" systemctl start user@{os.getuid()}.service\n"
" (may require sudo; try again after the command succeeds)"
@@ -2742,24 +2724,6 @@ _PLATFORMS = [
"help": "OpenID to deliver cron results and notifications to."},
],
},
{
"key": "yuanbao",
"label": "Yuanbao",
"emoji": "💎",
"token_var": "YUANBAO_APP_ID",
"setup_instructions": [
"1. Download the Yuanbao app from https://yuanbao.tencent.com/",
"2. In the app, go to PAI → My Bot and create a new bot",
"3. After the bot is created, copy the App ID and App Secret",
"4. Enter them below and Hermes will connect automatically over WebSocket",
],
"vars": [
{"name": "YUANBAO_APP_ID", "prompt": "App ID", "password": False,
"help": "The App ID from your Yuanbao IM Bot credentials."},
{"name": "YUANBAO_APP_SECRET", "prompt": "App Secret", "password": True,
"help": "The App Secret (used for HMAC signing) from your Yuanbao IM Bot."},
],
},
]
@@ -2971,7 +2935,7 @@ def _setup_sms():
def _setup_dingtalk():
"""Configure DingTalk — QR scan (recommended) or manual credential entry."""
from hermes_cli.setup import (
prompt_choice, prompt_yes_no, print_success, print_warning,
prompt_choice, prompt_yes_no, print_info, print_success, print_warning,
)
dingtalk_platform = next(p for p in _PLATFORMS if p["key"] == "dingtalk")
@@ -3144,12 +3108,6 @@ def _setup_wecom():
print_success("💬 WeCom configured!")
def _setup_yuanbao():
"""Configure Yuanbao via the standard platform setup."""
yuanbao_platform = next(p for p in _PLATFORMS if p["key"] == "yuanbao")
_setup_standard_platform(yuanbao_platform)
def _is_service_installed() -> bool:
"""Check if the gateway is installed as a system service."""
if supports_systemd_services():
@@ -3295,12 +3253,6 @@ def _setup_weixin():
print_warning(" Direct messages disabled.")
print()
print_info(" Note: QR login connects an iLink bot identity (e.g. ...@im.bot), not a")
print_info(" scriptable personal WeChat account. Ordinary WeChat groups typically cannot")
print_info(" invite an @im.bot identity, and iLink does not deliver ordinary-group events")
print_info(" to most bot accounts. The settings below only apply when iLink actually")
print_info(" delivers group events for your account type — otherwise DM remains the only")
print_info(" working channel regardless of this choice.")
group_choices = [
"Disable group chats (recommended)",
"Allow all group chats",
@@ -3314,12 +3266,12 @@ def _setup_weixin():
elif group_idx == 1:
save_env_value("WEIXIN_GROUP_POLICY", "open")
save_env_value("WEIXIN_GROUP_ALLOWED_USERS", "")
print_warning(" All group chats enabled (only takes effect if iLink delivers group events).")
print_warning(" All group chats enabled.")
else:
allow_groups = prompt(" Allowed group chat IDs (comma-separated, not member user IDs)", "", password=False).replace(" ", "")
allow_groups = prompt(" Allowed group chat IDs (comma-separated)", "", password=False).replace(" ", "")
save_env_value("WEIXIN_GROUP_POLICY", "allowlist")
save_env_value("WEIXIN_GROUP_ALLOWED_USERS", allow_groups)
print_success(" Group allowlist saved (only takes effect if iLink delivers group events).")
print_success(" Group allowlist saved.")
if user_id:
print()
@@ -3528,6 +3480,7 @@ def _setup_qqbot():
method_idx = prompt_choice(" How would you like to set up QQ Bot?", method_choices, 0)
credentials = None
used_qr = False
if method_idx == 0:
# ── QR scan-to-configure ──
@@ -3538,6 +3491,8 @@ def _setup_qqbot():
print()
print_warning(" QQ Bot setup cancelled.")
return
if credentials:
used_qr = True
if not credentials:
print_info(" QR setup did not complete. Continuing with manual input.")
+2 -2
View File
@@ -19,8 +19,9 @@ format) lives there.
from __future__ import annotations
import json
import os
from pathlib import Path
from typing import Any, Dict, List
from typing import Any, Dict, List, Optional
def hooks_command(args) -> None:
@@ -124,7 +125,6 @@ _DEFAULT_PAYLOADS = {
"task_id": "test-task",
"tool_call_id": "test-call",
"result": '{"output": "hello"}',
"duration_ms": 42,
},
"pre_llm_call": {
"session_id": "test-session",
+97 -1377
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