HackDeepWiki turns any Git repository into an interactive, AI-generated wiki. Point it at a GitHub, GitLab, or Bitbucket repo (or a local folder) and it will:
- Analyze the code structure
- Generate structured documentation, page by page
- Draw Mermaid diagrams of how things fit together
- Let you chat with the repository (RAG-powered Q&A and multi-step Deep Research)
It ships as a single portable binary — an AppImage on Linux, a .exe on Windows — with no Docker, no database, and no mandatory API key: it works out of the box against a local Ollama install, and can also talk to OpenAI, Google Gemini, Anthropic Claude, OpenRouter, AWS Bedrock, Azure OpenAI, Alibaba Dashscope, or any OpenAI-compatible endpoint (Novita, Together, Groq, vLLM, LM Studio, and similar).
📱 HackDeepWikiReader is the companion read-only client app (Android/Linux/Windows) for browsing wikis and .zim archives from any HackDeepWiki server, or offline from an exported .hdwreader bundle — full chat parity (pick a provider/model, ask questions, Deep Research, 🔐 security-context) but no generation or scanning.
- Automatic wiki generation for any public or token-authenticated GitHub / GitLab / Bitbucket repository, or a local directory.
- Visual architecture diagrams rendered with Mermaid, generated alongside the docs.
- Ask & Deep Research — a chat panel grounded in the repo's own code (RAG over embeddings), plus a multi-iteration research mode for harder questions.
- Fully portable — download one file, run it, done. No containers, no services to stand up, no
.envto hand-edit before your first run. - Local-first by default — the packaged app auto-discovers a running Ollama instance and uses it for both generation and embeddings, so it works fully offline with zero API keys.
- Bring your own provider when you want cloud-grade models: OpenAI, Google Gemini, Anthropic Claude (API key or a Pro/Max subscription token from
claude login), OpenRouter, AWS Bedrock, Azure OpenAI, Alibaba Dashscope, or any OpenAI-compatible API (Novita, Together, Groq, vLLM, LM Studio, etc.) via the custom-endpoint option. - Multi-language wiki output with a language switcher in the UI.
- Grab the latest build from the Releases page:
- Linux →
HackDeepWiki-x86_64.AppImage - Windows →
HackDeepWiki-windows-x64.exe
- Linux →
- Make it executable and run it (Linux:
chmod +x HackDeepWiki-x86_64.AppImage && ./HackDeepWiki-x86_64.AppImage; Windows: just double-click it). - It starts its own local server, waits for it to come up, and opens your browser automatically at
http://127.0.0.1:<port>. - Paste a repository URL and generate your first wiki. If you have Ollama running locally, no further setup is needed — otherwise open the model settings panel and add an API key for the provider of your choice.
Every push to main publishes an updated pre-release build; tagged commits (vX.Y.Z) publish a stable release. Both platforms are built and attached automatically by .github/workflows/release.yml.
Open the model/provider selector in the app and pick one of:
| Provider | What you need |
|---|---|
| Ollama | Nothing — auto-detected at http://localhost:11434 if running. |
| OpenAI | An API key from the OpenAI platform dashboard. |
| Claude | An Anthropic API key, or a Claude Pro/Max subscription token from claude login (Claude Code CLI) — both are sent straight to api.anthropic.com with the right auth headers. |
| Google Gemini | A free API key from Google AI Studio. |
| OpenRouter / Bedrock / Azure / Dashscope | Credentials for that provider, entered in the same settings panel. |
| Custom (OpenAI-compatible) | Any OpenAI-compatible base URL (Novita, Together, Groq, vLLM, LM Studio, ...) plus its API key. Use the Reload button to fetch the model list from that endpoint. |
# Frontend
npm install
npm run dev # http://localhost:3000
# Backend (separate terminal)
cd api
poetry install --only main
poetry run python -m api.main # http://localhost:8001The frontend proxies API/WebSocket calls to SERVER_BASE_URL (defaults to http://localhost:8001).
npm run build
python scripts/prepare_assets.py linux # or "windows"
pip install poetry pyinstaller
poetry -C api install --only main
pyinstaller hackdeepwiki.specThis bundles the built Next.js frontend, the FastAPI backend, and a Node.js runtime into a single PyInstaller binary (scripts/launcher.py is the entrypoint), which the Linux job then wraps into an AppImage.
Contributions are welcome:
- Open issues for bugs or feature requests
- Submit pull requests to improve the code
- Share feedback and ideas
MIT License — see LICENSE for details.
This project is a fork of deepwiki-open by AsyncFuncAI. All credit for the original codebase goes to them.