mem0-integration

# mem0-integration Integrate Mem0 (formerly MemGPT) as a universal memory layer for AI agents. Enable persistent memory storage, semantic search across memories, and personalized context retrieval. ## Overview Mem0 provides intelligent memory management for AI applications: - Persistent storage of conversation history and facts - Semantic search across stored memories - User-specific memory isolation - Automatic memory extraction from conversations - Support for local and cloud deployments ## Capabilities ### Memory Operations - Add memories from text or conversations - Search memories semantically - Retrieve relevant context by user/agent - Update and delete memories - Get memory history with timestamps ### Memory Types - Conversation memories (dialogue history) - Fact memories (extracted information) - Preference memories (user preferences) - Entity memories (people, places, things) ### Storage Backends - Local SQLite/JSON storage - PostgreSQL for production - Qdrant vector database integration - Cloud-hosted Mem0 platform ### Integration Patterns - LangChain memory integration - Direct API usage - MCP server connectivity - CrewAI and AutoGen compatibility ## Usage ### Basic Setup ```python from mem0 import Memory # Initialize with default local storage m = Memory() # Or with custom configuration config = { "vector_store": { "provider": "qdrant", "config": { "host": "localhost", "port": 6333, } }, "llm...