Vibe Coding DiscoverAgent_Memory_Techniques
View on GitHubAgent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta, Zep, Graphiti, LoCoMo benchmarks, and production patterns.
30 runnable Jupyter notebooks teaching agent memory for LLMs: conversation buffers, vector stores, knowledge graphs, episodic/semantic/working memory, plus Mem0, Letta, Zep, Graphiti and LoCoMo benchmarks. A hands-on reference for choosing and building memory in production agents.
Use Cases
teach yourself the 30 major agent memory techniquesadd cross-session memory to a chatbotcompare vector store vs knowledge graph memoryimplement episodic and semantic memory for agentsbuild self-editing memory with MemGPT/Lettapersonalization via Mem0 managed memorytemporal knowledge graph memory with Zep/Graphitibenchmark memory approaches with LoCoMochoose the right memory technique via decision treeproduction memory deployment patterns
Built With
- Language
- Jupyter Notebook
- Frameworks
- LangChain · OpenAI SDK · Anthropic SDK · ChromaDB · FAISS · sentence-transformers · NetworkX · Mem0 · Letta · MemGPT · Zep · Graphiti · Pydantic · pandas · NumPy
Tags
agent-memory · llm-memory · jupyter-notebooks · tutorial · conversation-buffer · vector-store · knowledge-graph · episodic-memory · semantic-memory · working-memory · benchmarks · production-patterns · long-term-memory · context-management