Agent_Memory_Techniques
Agent memory for LLMs: 30 runnable Jupyter notebooks covering conversation buffers, vector stores, knowledge graphs, episodic and semantic memory, MemGPT, Mem0, Letta,.
Category
AI Chatbot
Quality
86/100
Primary source
GitHub
What is Agent_Memory_Techniques?
Agent 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.
Key features
Best fit
Why consider it
- Agent_Memory_Techniques is categorized for ai chatbot workflows and tagged with Support, Sales, Agents.
- The public repository has 613 stars, which gives buyers and builders an extra adoption signal.
- License metadata is available: Apache-2.0.
Source & verification
- Verified on Jun 30, 2026 from public source metadata.
- Primary reference: github.com.
- Repository freshness signal: last commit Jun 6, 2026.
Alternative tools
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka,.
Related tools
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka,.