Agent Memory Systems

3 Steps

1. 1

   Setting Up In-Context Working Memory: Implement a basic in-context working memory using a list to store recent interactions. This memory will be used to provide context to the agent for each new input.

2. 2

   Implementing Episodic Memory with Vector Stores: Integrate a vector store (e.g., ChromaDB, Pinecone) to store and retrieve episodic memories. Embeddings will be used to find relevant past interactions.

3. 3

   Building Semantic Memory with Knowledge Graphs: Set up a basic knowledge graph (e.g., using Neo4j) to store semantic information about the agent's world. Use Cypher queries to retrieve relevant facts.