DeepWiki is my own implementation attempt of DeepWiki, automatically creates beautiful, interactive wikis for any GitHub or GitLab repository! Just enter a repo name, and DeepWiki will:

1. Analyze the code structure
2. Generate comprehensive documentation
3. Create visual diagrams to explain how everything works
4. Organize it all into an easy-to-navigate wiki

• Instant Documentation: Turn any GitHub or GitLab repo into a wiki in seconds
• Private Repository Support: Securely access private repositories with personal access tokens
• Smart Analysis: AI-powered understanding of code structure and relationships
• Beautiful Diagrams: Automatic Mermaid diagrams to visualize architecture and data flow
• Easy Navigation: Simple, intuitive interface to explore the wiki

# Clone the repository
git clone https://github.com/AsyncFuncAI/deepwiki-open.git
cd deepwiki-open

# Create a .env file with your API keys
echo "GOOGLE_API_KEY=your_google_api_key" > .env
echo "OPENAI_API_KEY=your_openai_api_key" >> .env

# Run with Docker Compose
docker-compose up

💡 Where to get these keys:

• Get a Google API key from Google AI Studio
• Get an OpenAI API key from OpenAI Platform

Create a .env file in the project root with these keys:

GOOGLE_API_KEY=your_google_api_key
OPENAI_API_KEY=your_openai_api_key

# Install Python dependencies
pip install -r api/requirements.txt

# Start the API server
python -m api.main

# Install JavaScript dependencies
npm install
# or
yarn install

# Start the web app
npm run dev
# or
yarn dev

1. Open http://localhost:3000 in your browser
2. Enter a GitHub or GitLab repository (like https://github.com/openai/codex, https://github.com/microsoft/autogen, or https://gitlab.com/gitlab-org/gitlab)
3. For private repositories, click "+ Add access tokens" and enter your GitHub or GitLab personal access token
4. Click "Generate Wiki" and watch the magic happen!

DeepWiki uses AI to:

1. Clone and analyze the GitHub or GitLab repository (including private repos with token authentication)
2. Create embeddings of the code for smart retrieval
3. Generate documentation with context-aware AI
4. Create visual diagrams to explain code relationships
5. Organize everything into a structured wiki

graph TD
    A[User inputs GitHub/GitLab repo] --> AA{Private repo?}
    AA -->|Yes| AB[Add access token]
    AA -->|No| B[Clone Repository]
    AB --> B
    B --> C[Analyze Code Structure]
    C --> D[Create Code Embeddings]
    D --> E[Generate Documentation]
    D --> F[Create Visual Diagrams]
    E --> G[Organize as Wiki]
    F --> G
    G --> H[Interactive DeepWiki]

    classDef process stroke-width:2px;
    classDef data stroke-width:2px;
    classDef result stroke-width:2px;
    classDef decision stroke-width:2px;

    class A,D data;
    class AA decision;
    class B,C,E,F,G,AB process;
    class H result;

deepwiki/
├── api/                  # Backend API server
│   ├── main.py           # API entry point
│   ├── api.py            # FastAPI implementation
│   ├── rag.py            # Retrieval Augmented Generation
│   ├── data_pipeline.py  # Data processing utilities
│   └── requirements.txt  # Python dependencies
│
├── src/                  # Frontend Next.js app
│   ├── app/              # Next.js app directory
│   │   └── page.tsx      # Main application page
│   └── components/       # React components
│       └── Mermaid.tsx   # Mermaid diagram renderer
│
├── public/               # Static assets
├── package.json          # JavaScript dependencies
└── .env                  # Environment variables (create this)

You can use Docker to run DeepWiki:

# Pull the image from GitHub Container Registry
docker pull ghcr.io/asyncfuncai/deepwiki-open:latest

# Run the container with environment variables
docker run -p 8001:8001 -p 3000:3000 \
  -e GOOGLE_API_KEY=your_google_api_key \
  -e OPENAI_API_KEY=your_openai_api_key \
  -v ~/.adalflow:/root/.adalflow \
  ghcr.io/asyncfuncai/deepwiki-open:latest

Or use the provided docker-compose.yml file:

# Edit the .env file with your API keys first
docker-compose up

You can also mount a .env file to the container:

# Create a .env file with your API keys
echo "GOOGLE_API_KEY=your_google_api_key" > .env
echo "OPENAI_API_KEY=your_openai_api_key" >> .env

# Run the container with the .env file mounted
docker run -p 8001:8001 -p 3000:3000 \
  -v $(pwd)/.env:/app/.env \
  -v ~/.adalflow:/root/.adalflow \
  ghcr.io/asyncfuncai/deepwiki-open:latest

If you want to build the Docker image locally:

# Clone the repository
git clone https://github.com/AsyncFuncAI/deepwiki-open.git
cd deepwiki-open

# Build the Docker image
docker build -t deepwiki-open .

# Run the container
docker run -p 8001:8001 -p 3000:3000 \
  -e GOOGLE_API_KEY=your_google_api_key \
  -e OPENAI_API_KEY=your_openai_api_key \
  deepwiki-open

The API server provides:

• Repository cloning and indexing
• RAG (Retrieval Augmented Generation)
• Streaming chat completions

For more details, see the API README.

The main interface of DeepWiki

Access private repositories with personal access tokens

Watch DeepWiki in action!

• "Missing environment variables": Make sure your .env file is in the project root and contains both API keys
• "API key not valid": Check that you've copied the full key correctly with no extra spaces

• "Cannot connect to API server": Make sure the API server is running on port 8001
• "CORS error": The API is configured to allow all origins, but if you're having issues, try running both frontend and backend on the same machine

• "Error generating wiki": For very large repositories, try a smaller one first
• "Invalid repository format": Make sure you're using a valid GitHub or GitLab URL format
• "Could not fetch repository structure": For private repositories, ensure you've entered a valid personal access token with appropriate permissions
• "Diagram rendering error": The app will automatically try to fix broken diagrams

1. Restart both servers: Sometimes a simple restart fixes most issues
2. Check console logs: Open browser developer tools to see any JavaScript errors
3. Check API logs: Look at the terminal where the API is running for Python errors

Contributions are welcome! Feel free to:

• Open issues for bugs or feature requests
• Submit pull requests to improve the code
• Share your feedback and ideas

This project is licensed under the MIT License - see the LICENSE file for details.