This repository provides a ReAct-style agent with memory persistence capabilities, designed for developers and researchers building conversational AI applications that require stateful interactions. It enables agents to learn user preferences and recall past information across different conversation threads by saving memories to a configurable store.

How It Works

The agent utilizes LangGraph to manage conversational flow and memory. When the agent calls a tool, LangGraph routes the execution to a store_memory node, which saves extracted information to a memory graph's Store. This approach allows for efficient retrieval and reuse of contextual data, enhancing the agent's ability to maintain long-term memory and personalized interactions.

Quick Start & Requirements

• Install/Run: Deploy on LangGraph Cloud. Requires setting up a .env file with API keys.
• Prerequisites: API keys for Anthropic or OpenAI.
• Links: LangGraph Studio

Highlighted Details

• Implements a ReAct-style agent with a dedicated memory saving tool.
• Memories are scoped by user_id for cross-thread persistence.
• Customizable memory structure, additional tools, models, and prompts.
• Integrates with LangSmith for evaluation and optimization using @unit decorator.

Maintenance & Community

The project is associated with langchain-ai. Further community and roadmap details are not explicitly provided in the README.

Licensing & Compatibility

The repository's license is not specified in the README. Compatibility for commercial use or closed-source linking is not detailed.

Limitations & Caveats

The README does not specify the license, making commercial use and closed-source integration uncertain. Evaluating and tuning memory management, especially with multiple tools, is noted as a potential challenge.