LangGraph-GUI offers a user-friendly graphical interface for designing and executing LangGraph applications, targeting developers and researchers who need to visualize and interact with LLM-powered workflows. It simplifies the creation of complex agents and applications by providing a visual node-edge editor, abstracting away much of the underlying code.

How It Works

The project employs a SvelteFlow-based frontend for interactive graph manipulation and a FastAPI backend to manage application logic and LLM integrations. It supports connecting to local LLM instances, such as Ollama, or external APIs, allowing users to define, test, and run LangGraph state machines directly through the GUI.

Quick Start & Requirements

• Primary install/run command: Docker Compose is the recommended setup.
  • Clone repository: git clone --recurse-submodules https://github.com/LangGraph-GUI/LangGraph-GUI.git && cd LangGraph-GUI
  • Build and run containers: docker compose build && docker compose up
• Prerequisites: Docker Compose is required. Optional dependencies include nv-docker (for NVIDIA GPU acceleration with Ollama) and npm (for potential electron builds).
• Access: The application is accessible via a web browser at http://localhost:3000.
• Links: Official documentation is available at LangGraph-GUI.github.io.

Highlighted Details

• Visual node-edge editor specifically for LangGraph.
• Integration with local LLMs (e.g., Ollama) and online APIs.
• Architecture comprises a SvelteFlow frontend and FastAPI backend.

Maintenance & Community

Contributions and feedback are encouraged through GitHub Discussions and Issues. The README does not specify core maintainers, sponsorships, or dedicated community channels like Discord or Slack.

Licensing & Compatibility

The project is released under the MIT License, which generally allows for broad compatibility, including commercial use and integration into closed-source projects.

Limitations & Caveats

The Docker Compose setup includes a placeholder xxxx for pulling Ollama models, necessitating manual user input to specify the desired model. Details regarding Kubernetes deployment are referenced but not provided within the README.