
ai-flow
No-code tool for connecting AI models
Stars: 188

AI Flow is an open-source, user-friendly UI application that empowers you to seamlessly connect multiple AI models together, specifically leveraging the capabilities of multiples AI APIs such as OpenAI, StabilityAI and Replicate. In a nutshell, AI Flow provides a visual platform for crafting and managing AI-driven workflows, thereby facilitating diverse and dynamic AI interactions.
README:
Open-source tool to seamlessly connect multiple AI model APIs into repeatable workflows.
π Website β’ π Documentation
New Nodes: Claude 3.7, OpenRouter, Generate Random Number
Configuration can now be done entirely in the UI
AI-Flow is an open-source, user-friendly UI that lets you visually design, manage, and monitor AI-driven workflows by seamlessly connecting multiple AI model APIs (e.g., OpenAI, StabilityAI, Replicate, Claude, Deepseek).
- Visual Workflow Builder: Drag-and-drop interface for crafting AI workflows.
- Real-Time Monitoring: Watch your workflow execute and track results.
- Parallel Processing: Nodes run in parallel whenever possible.
- Model Management: Easily organize and manage diverse AI models.
- Import/Export: Share or back up your workflows effortlessly.
- Replicate: LLaMa, Mistral, FaceSwap, InstantMesh, MusicGen, and more.
- OpenAI: GPT-4o, TTS, o1, o3.
- StabilityAI: Stable Diffusion 3.5, SDXL, Stable Video Diffusion, plus additional tools.
- Others: Claude, Deepseek.
AI-Flow is fully open source and available under the MIT License, empowering you to build and run your AI workflows on your personal machine.
For those seeking enhanced functionality and a polished experience, AI-Flow Pro on our cloud platform (app.ai-flow.net) offers advanced features, including:
- Subflows & Loops: Create complex, nested workflows and iterate tasks effortlessly.
- API-Triggered Flows: Initiate workflows via API calls for seamless automation.
- Integrated Services: Connect with external services such as Google Search, Airtable, Zapier, and Make.
- Simplified Interface: Transform workflows into streamlined tools with an intuitive UI.
The cloud version builds upon the foundation of the open-source project, giving you more power and flexibility while still letting you use your own API keys.
Note: To unlock full functionality, AI-Flow requires S3-compatible storage (with proper CORS settings) to host resources. Without it, features like File Upload or nodes that rely on external providers (e.g., StabilityAI) may not work as expected. Also, set
REPLICATE_API_KEY
in your environment to use the Replicate node.
-
Clone the Repository:
git clone https://github.com/DahnM20/ai-flow.git cd ai-flow
-
UI Setup:
cd packages/ui npm install
-
Backend Setup:
cd ../backend poetry install
-
Windows Users:
poetry shell pip install -r requirements_windows.txt
-
Windows Users:
-
Run the Application:
- Start the backend:
poetry run python server.py
- In a new terminal, start the UI:
cd packages/ui npm start
- Open your browser and navigate to http://localhost:3000.
- Start the backend:
-
Prepare Docker Compose:
- Navigate to the
docker
directory:cd docker
- Update the
REPLICATE_API_KEY
in the YAML file.
- Navigate to the
-
Launch with Docker Compose:
docker-compose up -d
-
Access the Application:
- Open http://localhost:80 in your browser.
- To stop, run:
docker-compose stop
We welcome contributions! If you encounter issues or have feature ideas, please open an issue or submit a pull request.
This project is released under the MIT License.
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