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116 changes: 116 additions & 0 deletions CLAUDE.md
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# CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

## Project Overview

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It's a full-stack application with:
- Python backend (Flask-based API server)
- React/TypeScript frontend (built with UmiJS)
- Microservices architecture with Docker deployment
- Multiple data stores (MySQL, Elasticsearch/Infinity, Redis, MinIO)

## Architecture

### Backend (`/api/`)
- **Main Server**: `api/ragflow_server.py` - Flask application entry point
- **Apps**: Modular Flask blueprints in `api/apps/` for different functionalities:
- `kb_app.py` - Knowledge base management
- `dialog_app.py` - Chat/conversation handling
- `document_app.py` - Document processing
- `canvas_app.py` - Agent workflow canvas
- `file_app.py` - File upload/management
- **Services**: Business logic in `api/db/services/`
- **Models**: Database models in `api/db/db_models.py`

### Core Processing (`/rag/`)
- **Document Processing**: `deepdoc/` - PDF parsing, OCR, layout analysis
- **LLM Integration**: `rag/llm/` - Model abstractions for chat, embedding, reranking
- **RAG Pipeline**: `rag/flow/` - Chunking, parsing, tokenization
- **Graph RAG**: `graphrag/` - Knowledge graph construction and querying

### Agent System (`/agent/`)
- **Components**: Modular workflow components (LLM, retrieval, categorize, etc.)
- **Templates**: Pre-built agent workflows in `agent/templates/`
- **Tools**: External API integrations (Tavily, Wikipedia, SQL execution, etc.)

### Frontend (`/web/`)
- React/TypeScript with UmiJS framework
- Ant Design + shadcn/ui components
- State management with Zustand
- Tailwind CSS for styling

## Common Development Commands

### Backend Development
```bash
# Install Python dependencies
uv sync --python 3.10 --all-extras
uv run download_deps.py
pre-commit install

# Start dependent services
docker compose -f docker/docker-compose-base.yml up -d

# Run backend (requires services to be running)
source .venv/bin/activate
export PYTHONPATH=$(pwd)
bash docker/launch_backend_service.sh

# Run tests
uv run pytest

# Linting
ruff check
ruff format
```

### Frontend Development
```bash
cd web
npm install
npm run dev # Development server
npm run build # Production build
npm run lint # ESLint
npm run test # Jest tests
```

### Docker Development
```bash
# Full stack with Docker
cd docker
docker compose -f docker-compose.yml up -d

# Check server status
docker logs -f ragflow-server

# Rebuild images
docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
```

## Key Configuration Files

- `docker/.env` - Environment variables for Docker deployment
- `docker/service_conf.yaml.template` - Backend service configuration
- `pyproject.toml` - Python dependencies and project configuration
- `web/package.json` - Frontend dependencies and scripts

## Testing

- **Python**: pytest with markers (p1/p2/p3 priority levels)
- **Frontend**: Jest with React Testing Library
- **API Tests**: HTTP API and SDK tests in `test/` and `sdk/python/test/`

## Database Engines

RAGFlow supports switching between Elasticsearch (default) and Infinity:
- Set `DOC_ENGINE=infinity` in `docker/.env` to use Infinity
- Requires container restart: `docker compose down -v && docker compose up -d`

## Development Environment Requirements

- Python 3.10-3.12
- Node.js >=18.20.4
- Docker & Docker Compose
- uv package manager
- 16GB+ RAM, 50GB+ disk space
2 changes: 1 addition & 1 deletion web/.umirc.ts
Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,7 @@ export default defineConfig({
proxy: [
{
context: ['/api', '/v1'],
target: 'http://127.0.0.1:9380/',
target: 'http://192.161.35.3:50085/',
changeOrigin: true,
ws: true,
logger: console,
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3 changes: 2 additions & 1 deletion web/src/pages/profile-setting/mcp/edit-mcp-dialog.tsx
Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,8 @@ export function EditMcpDialog({
const handleOk = async (values: z.infer<typeof FormSchema>) => {
const nextValues = {
...omit(values, 'authorization_token'),
headers: { authorization_token: values.authorization_token },
variables: { authorization_token: values.authorization_token },
headers: { Authorization: 'Bearer ${authorization_token}' },
};
if (isTriggeredBySaving) {
onOk?.(nextValues);
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