M4A

Agent Memory

beginner
Core ConceptsLast updated: 2025-01-15
Also known as: AI agent memory, LLM memory

What is Agent Memory?


Agent memory refers to the mechanisms that allow AI agents to store, retrieve, and utilize information across interactions. Unlike stateless chatbots that forget everything after each conversation, agents with memory can build context over time, learn user preferences, and provide personalized experiences.


Why Memory Matters


Without memory, AI agents face several limitations:


  • They cannot remember previous conversations
  • They lose context between sessions
  • They cannot learn user preferences
  • They repeat the same mistakes
  • They cannot build on past interactions

    • Types of Agent Memory


    Agent memory systems typically implement several types of memory:


  • **Working Memory**: Short-term storage for the current conversation context
  • **Episodic Memory**: Records of specific past interactions and events
  • **Semantic Memory**: General knowledge and learned facts
  • **Procedural Memory**: Learned skills and behaviors

    • Implementation Approaches


    Modern agent memory systems use various techniques:


  • Vector databases for semantic similarity search
  • Graph databases for relationship modeling
  • Key-value stores for quick lookups
  • Hybrid approaches combining multiple storage types

    • Popular Memory Frameworks


    Several frameworks provide memory capabilities for AI agents:


  • Mem0 - Memory layer for AI applications
  • Zep - Long-term memory for AI assistants
  • Letta (MemGPT) - Agents with self-editing memory
  • LangChain Memory - Memory modules for LLM chains

    • Related Terms

    Episodic Memory

    Episodic memory stores specific events and experiences. Learn how AI agents use episodic memory to recall past interactions and context.

    Semantic Memory

    Semantic memory stores facts, concepts, and general knowledge. Learn how AI agents use semantic memory for reasoning and knowledge retrieval.

    Working Memory

    Working memory holds information needed for the current task. Learn how AI agents manage context windows and short-term information.

    Long-term Memory

    Long-term memory enables AI agents to retain information across sessions. Learn about persistent memory architectures for intelligent agents.

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