Files
hermes-agent/plugins/memory/hindsight/__init__.py
T
Teknium 55107a196e refactor(memory): restructure plugins, add CLI, clean gateway, migration notice
Plugin restructure:
- Move all memory plugins from plugins/<name>-memory/ to plugins/memory/<name>/
  (byterover, hindsight, holographic, honcho, mem0, openviking, retaindb)
- New plugins/memory/__init__.py discovery module that scans the directory
  directly, loading providers by name without the general plugin system
- run_agent.py uses load_memory_provider() instead of get_plugin_memory_providers()

CLI wiring:
- hermes memory setup — interactive curses picker + config wizard
- hermes memory status — show active provider, config, availability
- hermes memory off — disable external provider (built-in only)
- hermes honcho — now shows migration notice pointing to hermes memory setup

Gateway cleanup:
- Remove _get_or_create_gateway_honcho (already removed in prev commit)
- Remove _shutdown_gateway_honcho and _shutdown_all_gateway_honcho methods
- Remove all calls to shutdown methods (4 call sites)
- Remove _honcho_managers/_honcho_configs dict references

Dead code removal:
- Delete tools/honcho_tools.py (279 lines, import was already commented out)
- Delete tests/gateway/test_honcho_lifecycle.py (131 lines, tested removed methods)
- Remove if False placeholder from run_agent.py

Migration:
- Honcho migration notice on startup: detects existing honcho.json or
  ~/.honcho/config.json, prints guidance to run hermes memory setup.
  Only fires when memory.provider is not set and not in quiet mode.

Full suite: 7203 passed, 4 pre-existing failures. Zero regressions.
2026-03-30 23:46:51 -07:00

343 lines
13 KiB
Python

"""Hindsight memory plugin — MemoryProvider interface.
Long-term memory with knowledge graph, entity resolution, and multi-strategy
retrieval. Supports cloud (API key) and local (embedded PostgreSQL) modes.
Original PR #1811 by benfrank241, adapted to MemoryProvider ABC.
Config via environment variables:
HINDSIGHT_API_KEY — API key for Hindsight Cloud
HINDSIGHT_BANK_ID — memory bank identifier (default: hermes)
HINDSIGHT_BUDGET — recall budget: low/mid/high (default: mid)
HINDSIGHT_API_URL — API endpoint
HINDSIGHT_MODE — cloud or local (default: cloud)
Or via $HERMES_HOME/hindsight/config.json (profile-scoped), falling back to
~/.hindsight/config.json (legacy, shared) for backward compatibility.
"""
from __future__ import annotations
import json
import logging
import os
import queue
import threading
from typing import Any, Dict, List
from agent.memory_provider import MemoryProvider
logger = logging.getLogger(__name__)
_DEFAULT_API_URL = "https://api.hindsight.vectorize.io"
_VALID_BUDGETS = {"low", "mid", "high"}
# ---------------------------------------------------------------------------
# Thread helper (from original PR — avoids aiohttp event loop conflicts)
# ---------------------------------------------------------------------------
def _run_in_thread(fn, timeout: float = 30.0):
result_q: queue.Queue = queue.Queue(maxsize=1)
def _run():
import asyncio
asyncio.set_event_loop(None)
try:
result_q.put(("ok", fn()))
except Exception as exc:
result_q.put(("err", exc))
t = threading.Thread(target=_run, daemon=True, name="hindsight-call")
t.start()
kind, value = result_q.get(timeout=timeout)
if kind == "err":
raise value
return value
# ---------------------------------------------------------------------------
# Tool schemas
# ---------------------------------------------------------------------------
RETAIN_SCHEMA = {
"name": "hindsight_retain",
"description": (
"Store information to long-term memory. Hindsight automatically "
"extracts structured facts, resolves entities, and indexes for retrieval."
),
"parameters": {
"type": "object",
"properties": {
"content": {"type": "string", "description": "The information to store."},
"context": {"type": "string", "description": "Short label (e.g. 'user preference', 'project decision')."},
},
"required": ["content"],
},
}
RECALL_SCHEMA = {
"name": "hindsight_recall",
"description": (
"Search long-term memory. Returns memories ranked by relevance using "
"semantic search, keyword matching, entity graph traversal, and reranking."
),
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string", "description": "What to search for."},
},
"required": ["query"],
},
}
REFLECT_SCHEMA = {
"name": "hindsight_reflect",
"description": (
"Synthesize a reasoned answer from long-term memories. Unlike recall, "
"this reasons across all stored memories to produce a coherent response."
),
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string", "description": "The question to reflect on."},
},
"required": ["query"],
},
}
# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------
def _load_config() -> dict:
"""Load config from profile-scoped path, legacy path, or env vars.
Resolution order:
1. $HERMES_HOME/hindsight/config.json (profile-scoped)
2. ~/.hindsight/config.json (legacy, shared)
3. Environment variables
"""
from pathlib import Path
from hermes_constants import get_hermes_home
# Profile-scoped path (preferred)
profile_path = get_hermes_home() / "hindsight" / "config.json"
if profile_path.exists():
try:
return json.loads(profile_path.read_text(encoding="utf-8"))
except Exception:
pass
# Legacy shared path (backward compat)
legacy_path = Path.home() / ".hindsight" / "config.json"
if legacy_path.exists():
try:
return json.loads(legacy_path.read_text(encoding="utf-8"))
except Exception:
pass
return {
"mode": os.environ.get("HINDSIGHT_MODE", "cloud"),
"apiKey": os.environ.get("HINDSIGHT_API_KEY", ""),
"banks": {
"hermes": {
"bankId": os.environ.get("HINDSIGHT_BANK_ID", "hermes"),
"budget": os.environ.get("HINDSIGHT_BUDGET", "mid"),
"enabled": True,
}
},
}
# ---------------------------------------------------------------------------
# MemoryProvider implementation
# ---------------------------------------------------------------------------
class HindsightMemoryProvider(MemoryProvider):
"""Hindsight long-term memory with knowledge graph and multi-strategy retrieval."""
def __init__(self):
self._config = None
self._api_key = None
self._bank_id = "hermes"
self._budget = "mid"
self._mode = "cloud"
self._prefetch_result = ""
self._prefetch_lock = threading.Lock()
self._prefetch_thread = None
self._sync_thread = None
@property
def name(self) -> str:
return "hindsight"
def is_available(self) -> bool:
try:
cfg = _load_config()
mode = cfg.get("mode", "cloud")
if mode == "local":
embed = cfg.get("embed", {})
return bool(embed.get("llmApiKey") or os.environ.get("HINDSIGHT_LLM_API_KEY"))
api_key = cfg.get("apiKey") or os.environ.get("HINDSIGHT_API_KEY", "")
return bool(api_key)
except Exception:
return False
def get_config_schema(self):
return [
{"key": "mode", "description": "Cloud API or local embedded mode", "default": "cloud", "choices": ["cloud", "local"]},
{"key": "api_key", "description": "Hindsight Cloud API key", "secret": True, "env_var": "HINDSIGHT_API_KEY", "url": "https://app.hindsight.vectorize.io"},
{"key": "bank_id", "description": "Memory bank identifier", "default": "hermes"},
{"key": "budget", "description": "Recall thoroughness", "default": "mid", "choices": ["low", "mid", "high"]},
{"key": "llm_provider", "description": "LLM provider for local mode", "default": "anthropic", "choices": ["anthropic", "openai", "groq", "ollama"]},
{"key": "llm_api_key", "description": "LLM API key for local mode", "secret": True, "env_var": "HINDSIGHT_LLM_API_KEY"},
{"key": "llm_model", "description": "LLM model for local mode", "default": "claude-haiku-4-5-20251001"},
]
def _make_client(self):
"""Create a fresh Hindsight client (thread-safe)."""
if self._mode == "local":
from hindsight import HindsightEmbedded
embed = self._config.get("embed", {})
return HindsightEmbedded(
profile=embed.get("profile", "hermes"),
llm_provider=embed.get("llmProvider", ""),
llm_api_key=embed.get("llmApiKey", ""),
llm_model=embed.get("llmModel", ""),
)
from hindsight_client import Hindsight
return Hindsight(api_key=self._api_key, timeout=30.0)
def initialize(self, session_id: str, **kwargs) -> None:
self._config = _load_config()
self._mode = self._config.get("mode", "cloud")
self._api_key = self._config.get("apiKey") or os.environ.get("HINDSIGHT_API_KEY", "")
banks = self._config.get("banks", {}).get("hermes", {})
self._bank_id = banks.get("bankId", "hermes")
budget = banks.get("budget", "mid")
self._budget = budget if budget in _VALID_BUDGETS else "mid"
# Ensure bank exists
try:
client = _run_in_thread(self._make_client)
_run_in_thread(lambda: client.create_bank(bank_id=self._bank_id, name=self._bank_id))
except Exception:
pass # Already exists
def system_prompt_block(self) -> str:
return (
f"# Hindsight Memory\n"
f"Active. Bank: {self._bank_id}, budget: {self._budget}.\n"
f"Use hindsight_recall to search, hindsight_reflect for synthesis, "
f"hindsight_retain to store facts."
)
def prefetch(self, query: str) -> str:
if self._prefetch_thread and self._prefetch_thread.is_alive():
self._prefetch_thread.join(timeout=3.0)
with self._prefetch_lock:
result = self._prefetch_result
self._prefetch_result = ""
if not result:
return ""
return f"## Hindsight Memory\n{result}"
def queue_prefetch(self, query: str) -> None:
def _run():
try:
client = self._make_client()
resp = client.recall(bank_id=self._bank_id, query=query, budget=self._budget)
if resp.results:
text = "\n".join(r.text for r in resp.results if r.text)
with self._prefetch_lock:
self._prefetch_result = text
except Exception as e:
logger.debug("Hindsight prefetch failed: %s", e)
self._prefetch_thread = threading.Thread(target=_run, daemon=True, name="hindsight-prefetch")
self._prefetch_thread.start()
def sync_turn(self, user_content: str, assistant_content: str) -> None:
"""Retain conversation turn in background (non-blocking)."""
combined = f"User: {user_content}\nAssistant: {assistant_content}"
def _sync():
try:
_run_in_thread(
lambda: self._make_client().retain(
bank_id=self._bank_id, content=combined, context="conversation"
)
)
except Exception as e:
logger.warning("Hindsight sync failed: %s", e)
if self._sync_thread and self._sync_thread.is_alive():
self._sync_thread.join(timeout=5.0)
self._sync_thread = threading.Thread(target=_sync, daemon=True, name="hindsight-sync")
self._sync_thread.start()
def get_tool_schemas(self) -> List[Dict[str, Any]]:
return [RETAIN_SCHEMA, RECALL_SCHEMA, REFLECT_SCHEMA]
def handle_tool_call(self, tool_name: str, args: dict, **kwargs) -> str:
if tool_name == "hindsight_retain":
content = args.get("content", "")
if not content:
return json.dumps({"error": "Missing required parameter: content"})
context = args.get("context")
try:
_run_in_thread(
lambda: self._make_client().retain(
bank_id=self._bank_id, content=content, context=context
)
)
return json.dumps({"result": "Memory stored successfully."})
except Exception as e:
return json.dumps({"error": f"Failed to store memory: {e}"})
elif tool_name == "hindsight_recall":
query = args.get("query", "")
if not query:
return json.dumps({"error": "Missing required parameter: query"})
try:
resp = _run_in_thread(
lambda: self._make_client().recall(
bank_id=self._bank_id, query=query, budget=self._budget
)
)
if not resp.results:
return json.dumps({"result": "No relevant memories found."})
lines = [f"{i}. {r.text}" for i, r in enumerate(resp.results, 1)]
return json.dumps({"result": "\n".join(lines)})
except Exception as e:
return json.dumps({"error": f"Failed to search memory: {e}"})
elif tool_name == "hindsight_reflect":
query = args.get("query", "")
if not query:
return json.dumps({"error": "Missing required parameter: query"})
try:
resp = _run_in_thread(
lambda: self._make_client().reflect(
bank_id=self._bank_id, query=query, budget=self._budget
)
)
return json.dumps({"result": resp.text or "No relevant memories found."})
except Exception as e:
return json.dumps({"error": f"Failed to reflect: {e}"})
return json.dumps({"error": f"Unknown tool: {tool_name}"})
def shutdown(self) -> None:
for t in (self._prefetch_thread, self._sync_thread):
if t and t.is_alive():
t.join(timeout=5.0)
def register(ctx) -> None:
"""Register Hindsight as a memory provider plugin."""
ctx.register_memory_provider(HindsightMemoryProvider())