An interactive visual ML pipeline builder. Create, configure, and manage machine learning pipelines with a drag-and-drop interface.
- 🎨 Visual Pipeline Builder - Drag-and-drop interface to create ML pipelines
- 📦 Multiple Node Types:
- Dataset - Load data from local, cloud (S3, GCS, Azure Blob), or URLs
- Versioning - Version control with DVC, Git LFS, ClearML Data, MLflow
- Execute - Data transformation and feature engineering
- Training - Train models on local or cloud (GCP, AWS, Azure)
- Experiment Tracking - Integrate with ClearML, MLflow, W&B, Comet
- Report - Generate model reports in HTML, PDF, Markdown, or JSON
- 🔐 Credential Management - Securely configure credentials for each node
- 💾 Pipeline Persistence - Save and load pipelines with localStorage
- 📤 Import/Export - Export pipelines as JSON for sharing
- 🎛️ Collapsible & Resizable Panels - Customize your workspace layout
- Node.js 18+
- pnpm (recommended) or npm
# Clone the repository
git clone https://github.com/NaveDanan/clearpipe.git
cd clearpipe
# Install dependencies
pnpm install
# Start the development server
pnpm devOpen http://localhost:3000 to see the application.
- Drag nodes from the left palette onto the canvas
- Connect nodes by dragging from output handles to input handles
- Click a node to configure its properties in the right panel
- Collapse/resize panels using the arrow buttons and drag handles
- Save your pipeline using the toolbar buttons
- Framework: Next.js 16 with App Router
- UI Components: shadcn/ui with Radix UI primitives
- Flow Canvas: React Flow (@xyflow/react)
- State Management: Zustand with persist middleware
- Styling: Tailwind CSS v4
- Forms: React Hook Form + Zod
- Icons: Lucide React
src/
├── app/ # Next.js App Router
├── components/
│ ├── nodes/ # Custom React Flow nodes
│ ├── pipeline/ # Pipeline-specific components
│ └── ui/ # shadcn/ui components
├── config/ # Node type definitions
├── lib/ # Utilities
├── stores/ # Zustand stores
└── types/ # TypeScript type definitions
MIT License - see LICENSE for details.
Contributions are welcome! Please feel free to submit a Pull Request.

