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CLAUDE.md
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CLAUDE.md
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# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project Overview
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This is **Langflow** - a low-code app builder for RAG and multi-agent AI applications. It's a Python-based visual IDE that allows users to build, test, and deploy AI workflows through a drag-and-drop interface. The project combines a FastAPI backend with a React frontend.
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## Architecture
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### Backend Structure
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- **Main Backend**: `src/backend/langflow/` - Entry point and versioning
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- **Core Backend**: `src/backend/base/langflow/` - Main application logic with these key modules:
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- `api/` - REST API endpoints and WebSocket handlers
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- `graph/` - Flow graph processing and execution engine
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- `components/` - Custom component definitions and implementations
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- `services/` - Business logic services (database, auth, etc.)
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- `processing/` - Data processing utilities
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- `schema/` - Pydantic models and data structures
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- `serialization/` - Flow import/export functionality
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### Frontend Structure
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- **Main Frontend**: `src/frontend/` - React application with:
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- Modern React 18 with TypeScript
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- Vite build system
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- Tailwind CSS for styling
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- React Flow for workflow visualization
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- Chakra UI and Radix UI components
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### Key Technologies
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- **Backend**: FastAPI, SQLAlchemy, Pydantic, Celery (for async tasks)
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- **Frontend**: React 18, TypeScript, Vite, React Flow, Zustand (state management)
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- **Package Management**: UV (Python), NPM (Node.js)
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## Development Commands
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### Backend Development
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```bash
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# Install backend dependencies
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make install_backend
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# Run backend in development mode
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make backend
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# Run backend with specific settings
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make backend log_level=debug host=0.0.0.0 port=7860
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# Run backend tests
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make unit_tests
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make integration_tests
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make tests
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# Lint and format backend
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make format_backend
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make lint
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```
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### Frontend Development
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```bash
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# Install frontend dependencies
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make install_frontend
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# Run frontend in development mode
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make frontend
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# Build frontend for production
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make build_frontend
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# Run frontend tests
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make tests_frontend
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# Lint and format frontend
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make format_frontend
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```
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### Full Development Workflow
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```bash
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# Initialize the entire development environment
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make init
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# Run both frontend and backend
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make run_frontend
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make run_backend
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# Build and run the complete application
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make build_and_run
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# Format all code
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make format
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```
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### Testing and Quality
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```bash
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# Run all tests with coverage
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make coverage
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# Run linters
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make lint
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# Format code
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make format
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# Check spelling
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make codespell
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```
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## Environment Setup
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1. **Python**: Requires Python 3.10-3.12
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2. **Node.js**: Required for frontend development
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3. **Virtual Environment**: Activated via `.venv/bin/activate`
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4. **Environment Variables**: Copy from `.env.example` to `.env`
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## Database and Storage
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- **Database**: SQLAlchemy with PostgreSQL/SQLite support
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- **Migrations**: Alembic for database migrations
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- **Cache**: Redis for caching and session storage
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## Key Features
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- **Visual IDE**: Drag-and-drop workflow builder using React Flow
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- **Multi-agent Support**: Orchestrates multiple AI agents and conversations
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- **RAG Pipelines**: Complete RAG implementation with various vector stores
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- **API Publish**: Export flows as APIs
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- **Observability**: Integration with LangSmith, LangFuse, LangWatch
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- **Component System**: Extensible component architecture for custom integrations
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## Testing Structure
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- **Unit Tests**: `src/backend/tests/unit/`
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- **Integration Tests**: `src/backend/tests/integration/`
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- **Frontend Tests**: `src/frontend/__tests__/`
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- **Test Framework**: pytest with async support
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- **Coverage**: Generated coverage reports with `make coverage`
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## Custom Components
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The project supports custom components through:
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- `src/backend/base/langflow/custom/` - Custom component definitions
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- Component registry system for dynamic loading
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- Support for Python-based and API-based components
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## Deployment
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- **Docker**: Multi-stage Docker builds for production
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- **Cloud**: DataStax Langflow cloud service integration
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- **Self-hosted**: Complete Docker Compose setup available
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## 数据库
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- 当使用sqlite时，数据库路径为src/backend/base/langflow/langflow.db
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- 数据库路径为src/backend/base/langflow/langflow.db
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- 使用中文回答
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