#!/usr/bin/env python3 """ mem0 Memory Server - Persistent Semantic Memory for Hermes Agent Direct integration with llama-embed on port 4700 """ import os import json import requests from http.server import HTTPServer, BaseHTTPRequestHandler from qdrant_client import QdrantClient, models # Configuration QDRANT_URL = os.environ.get("QDRANT_URL", "http://localhost:6333") EMBEDDING_URL = os.environ.get("EMBEDDING_URL", "http://localhost:4700") PORT = int(os.environ.get("MEM0_PORT", 8080)) USER_ID = "henry_hofmann" # Initialize Qdrant client qdrant_client = QdrantClient(url=QDRANT_URL) # Create collection if it doesn't exist try: qdrant_client.get_collection("hermes_memory") except: qdrant_client.create_collection( collection_name="hermes_memory", vectors_config=models.VectorParams(size=1024, distance=models.Distance.COSINE) ) def get_embedding(text): """Get embedding from llama-embed server""" response = requests.post( f"{EMBEDDING_URL}/v1/embeddings", json={"input": text, "model": "BAAI/bge-m3"}, timeout=30 ) response.raise_for_status() data = response.json() return data["data"][0]["embedding"] class MemoryHandler(BaseHTTPRequestHandler): def log_message(self, format, *args): pass # Suppress logging def do_GET(self): if self.path == "/health": self.send_response(200) self.send_header("Content-Type", "application/json") self.end_headers() self.wfile.write(json.dumps({"status": "ok", "service": "mem0", "user": USER_ID}).encode()) elif self.path == "/memory": # Get recent memories for user try: records = qdrant_client.scroll( collection_name="hermes_memory", limit=10, with_payload=True, with_vectors=False ) memories = [] for record in records[0]: if hasattr(record, 'payload'): memories.append({ "id": record.id, "text": record.payload.get("text", ""), "timestamp": record.payload.get("timestamp", "") }) self.send_response(200) self.send_header("Content-Type", "application/json") self.end_headers() self.wfile.write(json.dumps(memories, default=str).encode()) except Exception as e: self.send_response(500) self.send_header("Content-Type", "application/json") self.end_headers() self.wfile.write(json.dumps({"error": str(e)}).encode()) elif self.path.startswith("/memory/") and self.path.endswith("/search"): # Search memories by query query = self.path.split("/")[2] try: query_vector = get_embedding(query) results = qdrant_client.query_points( collection_name="hermes_memory", query=query_vector, query_filter=models.Filter( must=[models.FieldCondition(key="user_id", match=models.MatchValue(value=USER_ID))] ), limit=5, with_payload=True ) memories = [] for result in results.points: if hasattr(result, 'payload'): memories.append({ "id": result.id, "text": result.payload.get("text", ""), "score": result.score, "timestamp": result.payload.get("timestamp", "") }) self.send_response(200) self.send_header("Content-Type", "application/json") self.end_headers() self.wfile.write(json.dumps(memories, default=str).encode()) except Exception as e: self.send_response(500) self.send_header("Content-Type", "application/json") self.end_headers() self.wfile.write(json.dumps({"error": str(e)}).encode()) else: self.send_response(404) self.end_headers() def do_POST(self): if self.path == "/memory": content_length = int(self.headers["Content-Length"]) post_data = json.loads(self.rfile.read(content_length).decode()) text = post_data.get("text", "") if text: try: # Get embedding embedding = get_embedding(text) # Store in Qdrant qdrant_client.upsert( collection_name="hermes_memory", points=[ models.PointStruct( id=hash(text) % 1000000, vector=embedding, payload={ "text": text, "user_id": USER_ID, "timestamp": str(os.popen("date -Iseconds").read().strip()) } ) ] ) self.send_response(200) self.send_header("Content-Type", "application/json") self.end_headers() self.wfile.write(json.dumps({"status": "ok", "text": text}).encode()) except Exception as e: self.send_response(500) self.send_header("Content-Type", "application/json") self.end_headers() self.wfile.write(json.dumps({"error": str(e)}).encode()) else: self.send_response(400) self.end_headers() else: self.send_response(404) self.end_headers() if __name__ == "__main__": server = HTTPServer(("0.0.0.0", PORT), MemoryHandler) print(f"mem0 server running on port {PORT}") print(f"Qdrant: {QDRANT_URL}") print(f"Embedding: {EMBEDDING_URL}") server.serve_forever()