9ca954a274
Consolidated salvage from PRs #5301 (qaqcvc), #5339 (lance0), #5058 and #5098 (maymuneth). Mem0 API v2 compatibility (#5301): - All reads use filters={user_id: ...} instead of bare user_id= kwarg - All writes use filters with user_id + agent_id for attribution - Response unwrapping for v2 dict format {results: [...]} - Split _read_filters() vs _write_filters() — reads are user-scoped only for cross-session recall, writes include agent_id - Preserved 'hermes-user' default (no breaking change for existing users) - Omitted run_id scoping from #5301 — cross-session memory is Mem0's core value, session-scoping reads would defeat that purpose Memory prefetch context fencing (#5339): - Wraps prefetched memory in <memory-context> fenced blocks with system note marking content as recalled context, NOT user input - Sanitizes provider output to strip fence-escape sequences, preventing injection where memory content breaks out of the fence - API-call-time only — never persisted to session history Secret redaction (#5058, #5098): - Added prefix patterns for Groq (gsk_), Matrix (syt_), RetainDB (retaindb_), Hindsight (hsk-), Mem0 (mem0_), ByteRover (brv_)
372 lines
14 KiB
Python
372 lines
14 KiB
Python
"""Mem0 memory plugin — MemoryProvider interface.
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Server-side LLM fact extraction, semantic search with reranking, and
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automatic deduplication via the Mem0 Platform API.
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Original PR #2933 by kartik-mem0, adapted to MemoryProvider ABC.
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Config via environment variables:
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MEM0_API_KEY — Mem0 Platform API key (required)
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MEM0_USER_ID — User identifier (default: hermes-user)
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MEM0_AGENT_ID — Agent identifier (default: hermes)
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Or via $HERMES_HOME/mem0.json.
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"""
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from __future__ import annotations
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import json
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import logging
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import os
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import threading
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import time
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from pathlib import Path
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from typing import Any, Dict, List
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from agent.memory_provider import MemoryProvider
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logger = logging.getLogger(__name__)
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# Circuit breaker: after this many consecutive failures, pause API calls
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# for _BREAKER_COOLDOWN_SECS to avoid hammering a down server.
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_BREAKER_THRESHOLD = 5
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_BREAKER_COOLDOWN_SECS = 120
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# ---------------------------------------------------------------------------
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# Config
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# ---------------------------------------------------------------------------
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def _load_config() -> dict:
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"""Load config from env vars, with $HERMES_HOME/mem0.json overrides.
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Environment variables provide defaults; mem0.json (if present) overrides
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individual keys. This avoids a silent failure when the JSON file exists
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but is missing fields like ``api_key`` that the user set in ``.env``.
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"""
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from hermes_constants import get_hermes_home
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config = {
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"api_key": os.environ.get("MEM0_API_KEY", ""),
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"user_id": os.environ.get("MEM0_USER_ID", "hermes-user"),
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"agent_id": os.environ.get("MEM0_AGENT_ID", "hermes"),
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"rerank": True,
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"keyword_search": False,
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}
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config_path = get_hermes_home() / "mem0.json"
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if config_path.exists():
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try:
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file_cfg = json.loads(config_path.read_text(encoding="utf-8"))
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config.update({k: v for k, v in file_cfg.items()
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if v is not None and v != ""})
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except Exception:
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pass
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return config
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# ---------------------------------------------------------------------------
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# Tool schemas
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# ---------------------------------------------------------------------------
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PROFILE_SCHEMA = {
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"name": "mem0_profile",
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"description": (
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"Retrieve all stored memories about the user — preferences, facts, "
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"project context. Fast, no reranking. Use at conversation start."
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),
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"parameters": {"type": "object", "properties": {}, "required": []},
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}
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SEARCH_SCHEMA = {
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"name": "mem0_search",
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"description": (
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"Search memories by meaning. Returns relevant facts ranked by similarity. "
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"Set rerank=true for higher accuracy on important queries."
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),
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"parameters": {
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"type": "object",
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"properties": {
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"query": {"type": "string", "description": "What to search for."},
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"rerank": {"type": "boolean", "description": "Enable reranking for precision (default: false)."},
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"top_k": {"type": "integer", "description": "Max results (default: 10, max: 50)."},
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},
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"required": ["query"],
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},
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}
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CONCLUDE_SCHEMA = {
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"name": "mem0_conclude",
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"description": (
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"Store a durable fact about the user. Stored verbatim (no LLM extraction). "
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"Use for explicit preferences, corrections, or decisions."
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),
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"parameters": {
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"type": "object",
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"properties": {
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"conclusion": {"type": "string", "description": "The fact to store."},
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},
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"required": ["conclusion"],
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},
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}
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# ---------------------------------------------------------------------------
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# MemoryProvider implementation
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# ---------------------------------------------------------------------------
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class Mem0MemoryProvider(MemoryProvider):
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"""Mem0 Platform memory with server-side extraction and semantic search."""
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def __init__(self):
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self._config = None
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self._client = None
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self._client_lock = threading.Lock()
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self._api_key = ""
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self._user_id = "hermes-user"
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self._agent_id = "hermes"
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self._rerank = True
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self._prefetch_result = ""
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self._prefetch_lock = threading.Lock()
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self._prefetch_thread = None
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self._sync_thread = None
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# Circuit breaker state
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self._consecutive_failures = 0
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self._breaker_open_until = 0.0
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@property
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def name(self) -> str:
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return "mem0"
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def is_available(self) -> bool:
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cfg = _load_config()
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return bool(cfg.get("api_key"))
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def save_config(self, values, hermes_home):
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"""Write config to $HERMES_HOME/mem0.json."""
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import json
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from pathlib import Path
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config_path = Path(hermes_home) / "mem0.json"
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existing = {}
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if config_path.exists():
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try:
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existing = json.loads(config_path.read_text())
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except Exception:
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pass
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existing.update(values)
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config_path.write_text(json.dumps(existing, indent=2))
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def get_config_schema(self):
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return [
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{"key": "api_key", "description": "Mem0 Platform API key", "secret": True, "required": True, "env_var": "MEM0_API_KEY", "url": "https://app.mem0.ai"},
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{"key": "user_id", "description": "User identifier", "default": "hermes-user"},
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{"key": "agent_id", "description": "Agent identifier", "default": "hermes"},
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{"key": "rerank", "description": "Enable reranking for recall", "default": "true", "choices": ["true", "false"]},
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]
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def _get_client(self):
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"""Thread-safe client accessor with lazy initialization."""
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with self._client_lock:
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if self._client is not None:
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return self._client
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try:
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from mem0 import MemoryClient
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self._client = MemoryClient(api_key=self._api_key)
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return self._client
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except ImportError:
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raise RuntimeError("mem0 package not installed. Run: pip install mem0ai")
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def _is_breaker_open(self) -> bool:
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"""Return True if the circuit breaker is tripped (too many failures)."""
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if self._consecutive_failures < _BREAKER_THRESHOLD:
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return False
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if time.monotonic() >= self._breaker_open_until:
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# Cooldown expired — reset and allow a retry
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self._consecutive_failures = 0
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return False
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return True
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def _record_success(self):
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self._consecutive_failures = 0
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def _record_failure(self):
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self._consecutive_failures += 1
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if self._consecutive_failures >= _BREAKER_THRESHOLD:
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self._breaker_open_until = time.monotonic() + _BREAKER_COOLDOWN_SECS
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logger.warning(
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"Mem0 circuit breaker tripped after %d consecutive failures. "
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"Pausing API calls for %ds.",
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self._consecutive_failures, _BREAKER_COOLDOWN_SECS,
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)
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def initialize(self, session_id: str, **kwargs) -> None:
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self._config = _load_config()
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self._api_key = self._config.get("api_key", "")
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self._user_id = self._config.get("user_id", "hermes-user")
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self._agent_id = self._config.get("agent_id", "hermes")
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self._rerank = self._config.get("rerank", True)
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def _read_filters(self) -> Dict[str, Any]:
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"""Filters for search/get_all — scoped to user only for cross-session recall."""
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return {"user_id": self._user_id}
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def _write_filters(self) -> Dict[str, Any]:
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"""Filters for add — scoped to user + agent for attribution."""
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return {"user_id": self._user_id, "agent_id": self._agent_id}
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@staticmethod
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def _unwrap_results(response: Any) -> list:
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"""Normalize Mem0 API response — v2 wraps results in {"results": [...]}."""
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if isinstance(response, dict):
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return response.get("results", [])
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if isinstance(response, list):
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return response
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return []
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def system_prompt_block(self) -> str:
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return (
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"# Mem0 Memory\n"
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f"Active. User: {self._user_id}.\n"
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"Use mem0_search to find memories, mem0_conclude to store facts, "
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"mem0_profile for a full overview."
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)
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def prefetch(self, query: str, *, session_id: str = "") -> str:
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if self._prefetch_thread and self._prefetch_thread.is_alive():
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self._prefetch_thread.join(timeout=3.0)
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with self._prefetch_lock:
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result = self._prefetch_result
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self._prefetch_result = ""
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if not result:
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return ""
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return f"## Mem0 Memory\n{result}"
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def queue_prefetch(self, query: str, *, session_id: str = "") -> None:
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if self._is_breaker_open():
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return
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def _run():
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try:
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client = self._get_client()
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results = self._unwrap_results(client.search(
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query=query,
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filters=self._read_filters(),
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rerank=self._rerank,
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top_k=5,
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))
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if results:
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lines = [r.get("memory", "") for r in results if r.get("memory")]
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with self._prefetch_lock:
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self._prefetch_result = "\n".join(f"- {l}" for l in lines)
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self._record_success()
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except Exception as e:
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self._record_failure()
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logger.debug("Mem0 prefetch failed: %s", e)
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self._prefetch_thread = threading.Thread(target=_run, daemon=True, name="mem0-prefetch")
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self._prefetch_thread.start()
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def sync_turn(self, user_content: str, assistant_content: str, *, session_id: str = "") -> None:
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"""Send the turn to Mem0 for server-side fact extraction (non-blocking)."""
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if self._is_breaker_open():
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return
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def _sync():
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try:
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client = self._get_client()
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messages = [
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{"role": "user", "content": user_content},
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{"role": "assistant", "content": assistant_content},
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]
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client.add(messages, **self._write_filters())
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self._record_success()
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except Exception as e:
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self._record_failure()
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logger.warning("Mem0 sync failed: %s", e)
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# Wait for any previous sync before starting a new one
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if self._sync_thread and self._sync_thread.is_alive():
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self._sync_thread.join(timeout=5.0)
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self._sync_thread = threading.Thread(target=_sync, daemon=True, name="mem0-sync")
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self._sync_thread.start()
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def get_tool_schemas(self) -> List[Dict[str, Any]]:
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return [PROFILE_SCHEMA, SEARCH_SCHEMA, CONCLUDE_SCHEMA]
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def handle_tool_call(self, tool_name: str, args: dict, **kwargs) -> str:
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if self._is_breaker_open():
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return json.dumps({
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"error": "Mem0 API temporarily unavailable (multiple consecutive failures). Will retry automatically."
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})
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try:
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client = self._get_client()
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except Exception as e:
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return json.dumps({"error": str(e)})
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if tool_name == "mem0_profile":
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try:
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memories = self._unwrap_results(client.get_all(filters=self._read_filters()))
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self._record_success()
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if not memories:
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return json.dumps({"result": "No memories stored yet."})
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lines = [m.get("memory", "") for m in memories if m.get("memory")]
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return json.dumps({"result": "\n".join(lines), "count": len(lines)})
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except Exception as e:
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self._record_failure()
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return json.dumps({"error": f"Failed to fetch profile: {e}"})
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elif tool_name == "mem0_search":
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query = args.get("query", "")
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if not query:
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return json.dumps({"error": "Missing required parameter: query"})
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rerank = args.get("rerank", False)
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top_k = min(int(args.get("top_k", 10)), 50)
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try:
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results = self._unwrap_results(client.search(
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query=query,
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filters=self._read_filters(),
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rerank=rerank,
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top_k=top_k,
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))
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self._record_success()
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if not results:
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return json.dumps({"result": "No relevant memories found."})
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items = [{"memory": r.get("memory", ""), "score": r.get("score", 0)} for r in results]
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return json.dumps({"results": items, "count": len(items)})
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except Exception as e:
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self._record_failure()
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return json.dumps({"error": f"Search failed: {e}"})
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elif tool_name == "mem0_conclude":
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conclusion = args.get("conclusion", "")
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if not conclusion:
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return json.dumps({"error": "Missing required parameter: conclusion"})
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try:
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client.add(
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[{"role": "user", "content": conclusion}],
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**self._write_filters(),
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infer=False,
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)
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self._record_success()
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return json.dumps({"result": "Fact stored."})
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except Exception as e:
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self._record_failure()
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return json.dumps({"error": f"Failed to store: {e}"})
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return json.dumps({"error": f"Unknown tool: {tool_name}"})
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def shutdown(self) -> None:
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for t in (self._prefetch_thread, self._sync_thread):
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if t and t.is_alive():
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t.join(timeout=5.0)
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with self._client_lock:
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self._client = None
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def register(ctx) -> None:
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"""Register Mem0 as a memory provider plugin."""
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ctx.register_memory_provider(Mem0MemoryProvider())
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