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LangChain / RAG / Vector DBs · Lesson

Memory and State in Agentic RAG

Give your RAG agent short-term and long-term memory so it can hold conversations and recall facts across turns.

Why Agents Need Memory

A stateless agent forgets everything after each call. Memory lets an agent track the conversation, remember user preferences, and avoid repeating retrievals.

Short-Term vs. Long-Term

Short-term memory holds the current conversation in the context window. Long-term memory persists facts across sessions, often in a vector store or database.

All lessons in this course

  1. LangChain Agents and Tool Concepts
  2. Building Multi-Agent RAG Workflows
  3. Integrating External APIs as Tools
  4. Memory and State in Agentic RAG
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