Lab 6: Memory Persistent Agents

Duration: 15:19 | File: memory_example.py

What You'll Learn

• Build agents with long-term memory capabilities across conversations
• Integrate Mem0 for persistent memory storage and retrieval
• Combine memory with web search for enhanced knowledge
• Implement user-specific memory isolation and relevance scoring

Quick Start

# Memory agent with web search (requires MEM0_API_KEY)
python memory_example.py

Key Concepts

• Memory Backends: FAISS, OpenSearch, Mem0 integration
• Memory Operations: Store, retrieve, and list user memories
• Relevance Scoring: Semantic similarity for memory retrieval
• Knowledge Augmentation: Combine memory with external data sources

Examples

• Personal Assistant: Agent that remembers user preferences
• Web Search Integration: Combine memory with DuckDuckGo search
• User Isolation: Separate memory spaces per user
• Conversation Continuity: Maintain context across sessions

Requirements

• ANTHROPIC_API_KEY in .env file
• MEM0_API_KEY for memory persistence
• Internet connection (for web search)