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Server-side LLM fact extraction, semantic search with reranking, and
automatic deduplication via the Mem0 Platform API.
Original PR #2933 by kartik-mem0, adapted to MemoryProvider ABC.
Config via environment variables:
MEM0_API_KEY — Mem0 Platform API key (required)
MEM0_USER_ID — User identifier (default: hermes-user)
MEM0_AGENT_ID — Agent identifier (default: hermes)
Or via $HERMES_HOME/mem0.json.
"""
from __future__ import annotations
import json
import logging
import os
import threading
import time
from typing import Any, Dict, List
from agent.memory_provider import MemoryProvider
from tools.registry import tool_error
logger = logging.getLogger(__name__)
# Circuit breaker: after this many consecutive failures, pause API calls
# for _BREAKER_COOLDOWN_SECS to avoid hammering a down server.
_BREAKER_THRESHOLD = 5
_BREAKER_COOLDOWN_SECS = 120
# ---------------------------------------------------------------------------
# Config
# ---------------------------------------------------------------------------
def _load_config() -> dict:
"""Load config from env vars, with $HERMES_HOME/mem0.json overrides.
Environment variables provide defaults; mem0.json (if present) overrides
individual keys. This avoids a silent failure when the JSON file exists
but is missing fields like ``api_key`` that the user set in ``.env``.
"""
from hermes_constants import get_hermes_home
config = {
"api_key": os.environ.get("MEM0_API_KEY", ""),
"user_id": os.environ.get("MEM0_USER_ID", "hermes-user"),
"agent_id": os.environ.get("MEM0_AGENT_ID", "hermes"),
"rerank": True,
"keyword_search": False,
}
config_path = get_hermes_home() / "mem0.json"
if config_path.exists():
try:
file_cfg = json.loads(config_path.read_text(encoding="utf-8"))
config.update({k: v for k, v in file_cfg.items()
if v is not None and v != ""})
except Exception:
pass
return config
# ---------------------------------------------------------------------------
# Tool schemas
# ---------------------------------------------------------------------------
PROFILE_SCHEMA = {
"name": "mem0_profile",
"description": (
"Retrieve all stored memories about the user — preferences, facts, "
"project context. Fast, no reranking. Use at conversation start."
),
"parameters": {"type": "object", "properties": {}, "required": []},
}
SEARCH_SCHEMA = {
"name": "mem0_search",
"description": (
"Search memories by meaning. Returns relevant facts ranked by similarity. "
"Set rerank=true for higher accuracy on important queries."
),
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string", "description": "What to search for."},
"rerank": {"type": "boolean", "description": "Enable reranking for precision (default: false)."},
"top_k": {"type": "integer", "description": "Max results (default: 10, max: 50)."},
},
"required": ["query"],
},
}
CONCLUDE_SCHEMA = {
"name": "mem0_conclude",
"description": (
"Store a durable fact about the user. Stored verbatim (no LLM extraction). "
"Use for explicit preferences, corrections, or decisions."
),
"parameters": {
"type": "object",
"properties": {
"conclusion": {"type": "string", "description": "The fact to store."},
},
"required": ["conclusion"],
},
}
# ---------------------------------------------------------------------------
# MemoryProvider implementation
# ---------------------------------------------------------------------------
class Mem0MemoryProvider(MemoryProvider):
"""Mem0 Platform memory with server-side extraction and semantic search."""
def __init__(self):
self._config = None
self._client = None
self._client_lock = threading.Lock()
self._api_key = ""
self._user_id = "hermes-user"
self._agent_id = "hermes"
self._rerank = True
self._prefetch_result = ""
self._prefetch_lock = threading.Lock()
self._prefetch_thread = None
self._sync_thread = None
# Circuit breaker state
self._consecutive_failures = 0
self._breaker_open_until = 0.0
@property
def name(self) -> str:
return "mem0"
def is_available(self) -> bool:
cfg = _load_config()
return bool(cfg.get("api_key"))
def save_config(self, values, hermes_home):
"""Write config to $HERMES_HOME/mem0.json."""
import json
from pathlib import Path
config_path = Path(hermes_home) / "mem0.json"
existing = {}
if config_path.exists():
try:
existing = json.loads(config_path.read_text())
except Exception:
pass
existing.update(values)
config_path.write_text(json.dumps(existing, indent=2))
def get_config_schema(self):
return [
{"key": "api_key", "description": "Mem0 Platform API key", "secret": True, "required": True, "env_var": "MEM0_API_KEY", "url": "https://app.mem0.ai"},
{"key": "user_id", "description": "User identifier", "default": "hermes-user"},
{"key": "agent_id", "description": "Agent identifier", "default": "hermes"},
{"key": "rerank", "description": "Enable reranking for recall", "default": "true", "choices": ["true", "false"]},
]
def _get_client(self):
"""Thread-safe client accessor with lazy initialization."""
with self._client_lock:
if self._client is not None:
return self._client
try:
from mem0 import MemoryClient
self._client = MemoryClient(api_key=self._api_key)
return self._client
except ImportError:
raise RuntimeError("mem0 package not installed. Run: pip install mem0ai")
def _is_breaker_open(self) -> bool:
"""Return True if the circuit breaker is tripped (too many failures)."""
if self._consecutive_failures < _BREAKER_THRESHOLD:
return False
if time.monotonic() >= self._breaker_open_until:
# Cooldown expired — reset and allow a retry
self._consecutive_failures = 0
return False
return True
def _record_success(self):
self._consecutive_failures = 0
def _record_failure(self):
self._consecutive_failures += 1
if self._consecutive_failures >= _BREAKER_THRESHOLD:
self._breaker_open_until = time.monotonic() + _BREAKER_COOLDOWN_SECS
logger.warning(
"Mem0 circuit breaker tripped after %d consecutive failures. "
"Pausing API calls for %ds.",
self._consecutive_failures, _BREAKER_COOLDOWN_SECS,
)
def initialize(self, session_id: str, **kwargs) -> None:
self._config = _load_config()
self._api_key = self._config.get("api_key", "")
# Prefer gateway-provided user_id for per-user memory scoping;
# fall back to config/env default for CLI (single-user) sessions.
self._user_id = kwargs.get("user_id") or self._config.get("user_id", "hermes-user")
self._agent_id = self._config.get("agent_id", "hermes")
self._rerank = self._config.get("rerank", True)
def _read_filters(self) -> Dict[str, Any]:
"""Filters for search/get_all — scoped to user only for cross-session recall."""
return {"user_id": self._user_id}
def _write_filters(self) -> Dict[str, Any]:
"""Filters for add — scoped to user + agent for attribution."""
return {"user_id": self._user_id, "agent_id": self._agent_id}
@staticmethod
def _unwrap_results(response: Any) -> list:
"""Normalize Mem0 API response — v2 wraps results in {"results": [...]}."""
if isinstance(response, dict):
return response.get("results", [])
if isinstance(response, list):
return response
return []
def system_prompt_block(self) -> str:
return (
"# Mem0 Memory\n"
f"Active. User: {self._user_id}.\n"
"Use mem0_search to find memories, mem0_conclude to store facts, "
"mem0_profile for a full overview."
)
def prefetch(self, query: str, *, session_id: 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"## Mem0 Memory\n{result}"
def queue_prefetch(self, query: str, *, session_id: str = "") -> None:
if self._is_breaker_open():
return
def _run():
try:
client = self._get_client()
results = self._unwrap_results(client.search(
query=query,
filters=self._read_filters(),
rerank=self._rerank,
top_k=5,
))
if results:
lines = [r.get("memory", "") for r in results if r.get("memory")]
with self._prefetch_lock:
self._prefetch_result = "\n".join(f"- {l}" for l in lines)
self._record_success()
except Exception as e:
self._record_failure()
logger.debug("Mem0 prefetch failed: %s", e)
self._prefetch_thread = threading.Thread(target=_run, daemon=True, name="mem0-prefetch")
self._prefetch_thread.start()
def sync_turn(self, user_content: str, assistant_content: str, *, session_id: str = "") -> None:
"""Send the turn to Mem0 for server-side fact extraction (non-blocking)."""
if self._is_breaker_open():
return
def _sync():
try:
client = self._get_client()
messages = [
{"role": "user", "content": user_content},
{"role": "assistant", "content": assistant_content},
]
client.add(messages, **self._write_filters())
self._record_success()
except Exception as e:
self._record_failure()
logger.warning("Mem0 sync failed: %s", e)
# Wait for any previous sync before starting a new one
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="mem0-sync")
self._sync_thread.start()
def get_tool_schemas(self) -> List[Dict[str, Any]]:
return [PROFILE_SCHEMA, SEARCH_SCHEMA, CONCLUDE_SCHEMA]
def handle_tool_call(self, tool_name: str, args: dict, **kwargs) -> str:
if self._is_breaker_open():
return json.dumps({
"error": "Mem0 API temporarily unavailable (multiple consecutive failures). Will retry automatically."
})
try:
client = self._get_client()
except Exception as e:
return tool_error(str(e))
if tool_name == "mem0_profile":
try:
memories = self._unwrap_results(client.get_all(filters=self._read_filters()))
self._record_success()
if not memories:
return json.dumps({"result": "No memories stored yet."})
lines = [m.get("memory", "") for m in memories if m.get("memory")]
return json.dumps({"result": "\n".join(lines), "count": len(lines)})
except Exception as e:
self._record_failure()
return tool_error(f"Failed to fetch profile: {e}")
elif tool_name == "mem0_search":
query = args.get("query", "")
if not query:
return tool_error("Missing required parameter: query")
rerank = args.get("rerank", False)
top_k = min(int(args.get("top_k", 10)), 50)
try:
results = self._unwrap_results(client.search(
query=query,
filters=self._read_filters(),
rerank=rerank,
top_k=top_k,
))
self._record_success()
if not results:
return json.dumps({"result": "No relevant memories found."})
items = [{"memory": r.get("memory", ""), "score": r.get("score", 0)} for r in results]
return json.dumps({"results": items, "count": len(items)})
except Exception as e:
self._record_failure()
return tool_error(f"Search failed: {e}")
elif tool_name == "mem0_conclude":
conclusion = args.get("conclusion", "")
if not conclusion:
return tool_error("Missing required parameter: conclusion")
try:
client.add(
[{"role": "user", "content": conclusion}],
**self._write_filters(),
infer=False,
)
self._record_success()
return json.dumps({"result": "Fact stored."})
except Exception as e:
self._record_failure()
return tool_error(f"Failed to store: {e}")
return tool_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)
with self._client_lock:
self._client = None
def register(ctx) -> None:
"""Register Mem0 as a memory provider plugin."""
ctx.register_memory_provider(Mem0MemoryProvider())
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