Build, execute, and deploy LangGraph agentic workflows through a visual drag-and-drop interface.

• 🎨 Visual Workflow Builder - Drag-and-drop interface powered by ReactFlow
• 🤖 Multi-LLM Support - OpenAI, Anthropic, Google Gemini
• 🔧 Extensible Nodes - LLMs, Tools, APIs, MCPs, Control Flow
• ⚡ Real-time Execution - Watch your workflows run with live visualization
• 🚀 Deploy Anywhere - Export to Docker, Cloud Run, Lambda
• 💾 State Management - Built on LangGraph with checkpointing and memory

• Node.js 18+ and npm/yarn
• Python 3.11+
• Docker and Docker Compose
• PostgreSQL 15+
• Redis 7+

1. Set up environment variables:

# Backend (.env in backend/ directory) cp backend/.env.example backend/.env # Edit backend/.env and add your API keys: # OPENAI_API_KEY=your-key-here # DATABASE_URL=postgresql://flowai:flowai@localhost:5432/flowai # REDIS_URL=redis://localhost:6379/0

2. Clone and install dependencies:

# Install frontend dependencies cd frontend npm install # Install backend dependencies cd ../backend python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt

2. Start infrastructure (PostgreSQL + Redis):

docker-compose up -d

3. Run database migrations:

cd backend alembic upgrade head

4. Start development servers:

# Terminal 1 - Frontend cd frontend npm run dev # Terminal 2 - Backend cd backend uvicorn app.main:app --reload

5. Open your browser:

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000
• API Docs: http://localhost:8000/docs

flowAI/ ├── frontend/ # React + TypeScript + ReactFlow │ ├── src/ │ │ ├── components/ # React components │ │ ├── features/ # Feature modules (workflow, nodes, execution) │ │ ├── lib/ # Utilities and configurations │ │ ├── hooks/ # Custom React hooks │ │ ├── types/ # TypeScript type definitions │ │ └── App.tsx # Main app component │ └── package.json │ ├── backend/ # FastAPI + LangGraph │ ├── app/ │ │ ├── api/ # API endpoints │ │ ├── core/ # Core configuration │ │ ├── models/ # Database models │ │ ├── schemas/ # Pydantic schemas │ │ ├── services/ # Business logic │ │ │ ├── compiler/ # ReactFlow → LangGraph compiler │ │ │ ├── executor/ # Workflow execution engine │ │ │ └── nodes/ # Node type implementations │ │ └── main.py # FastAPI app │ └── requirements.txt │ ├── docker-compose.yml # Local development infrastructure └── DEVELOPMENT_PLAN.md # Detailed development roadmap 

The initial MVP includes:

• ✅ ReactFlow canvas with zoom/pan controls
• ✅ 5 essential node types:
  • Manual Trigger
  • OpenAI LLM
  • HTTP API Call
  • Conditional (if/else)
  • Output
• ✅ Node configuration panel
• ✅ Workflow save/load
• ✅ LangGraph compilation
• ✅ Real-time execution visualization
• ✅ Execution history
• ✅ Dynamic Input Forms - Auto-detect variables ({{var}}) and show input forms
• ✅ Beautiful Output Viewer - Formatted, JSON, and Raw views with Markdown support
• ✅ WebSocket Live Updates - Real-time execution logs and node status updates

• Frontend: React 18, TypeScript, ReactFlow, Tailwind CSS, shadcn/ui
• Backend: FastAPI, LangGraph, LangChain, SQLAlchemy
• Database: PostgreSQL, Redis
• Deployment: Docker, Kubernetes

See DEVELOPMENT_PLAN.md for the detailed roadmap and architecture.

MIT