AI-Flow is an open-source, visual tool designed for users to build, manage, and monitor complex AI workflows by connecting various AI model APIs. It benefits engineers and power users by simplifying the integration of diverse AI services like GPT-4o, Stable Diffusion, and Claude into repeatable, manageable processes.

How It Works

The project employs a drag-and-drop graphical user interface (GUI) to construct AI workflows. Users visually connect different AI model APIs (e.g., OpenAI, StabilityAI, Replicate) as nodes, allowing for the creation of complex sequences and parallel processing. This approach simplifies the orchestration of multiple AI services, abstracting away much of the underlying API complexity and enabling easier experimentation and deployment of AI-driven applications.

Quick Start & Requirements

Installation options include a Windows-only executable, Docker Compose (`docker-compose up -d` after `cd docker`), or a local installation (cloning the repo, `npm install` for UI, `poetry install` for backend, then running `python server.py` and `npm start`). Key requirements include S3-compatible storage with proper CORS settings for full functionality, and the `REPLICATE_API_KEY` environment variable or App Parameter. Access the application via `http://localhost:80` (Docker) or `http://localhost:3000` (local). Documentation is available via a link in the README.

Highlighted Details

• Supports a wide range of models including OpenAI (GPT-4o, TTS), StabilityAI (SD3.5, SDXL), Claude, Deepseek, and numerous models via Replicate (FLUX, Imagen, Veo, Lyria).
• Features a visual workflow builder with drag-and-drop functionality.
• Includes real-time monitoring of workflow execution and results.
• Supports parallel processing for nodes where possible.
• Workflows can be imported and exported for sharing or backup.
• An optional cloud-based "AI-Flow Pro" offers advanced features like subflows, loops, API triggers, and integrated services.

Maintenance & Community

The README does not provide specific details on notable contributors, community channels (like Discord/Slack), or a public roadmap. Contributions are welcomed via issues and pull requests on GitHub.

Licensing & Compatibility

The project is released under the MIT License, which is permissive and generally allows for commercial use, modification, and distribution without significant restrictions, including use in closed-source applications.

Limitations & Caveats

Full functionality, particularly for features like file uploads and nodes relying on external providers, is contingent on setting up S3-compatible storage with correct CORS configuration. The standalone executable installer is currently limited to Windows users. The project is actively developed, with the latest release being v0.11.3, indicating ongoing feature additions and potential for breaking changes.