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DeepWiki-Open is an innovative AI-powered documentation generator that automatically creates comprehensive, interactive wikis for any GitHub, GitLab, or BitBucket repository. Transform your codebase into beautiful, navigable documentation in seconds.

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What is DeepWiki-Open?

DeepWiki-Open analyzes your repository’s code structure, understands the relationships between components, and generates:

Interactive Documentation

Comprehensive documentation with code analysis and explanations

Visual Diagrams

Automatic Mermaid diagrams showing architecture and data flow

AI-Powered Chat

RAG-powered Q&A system to chat with your repository

Deep Research

Multi-turn AI research for complex code analysis

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Key Features

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🚀 Instant Documentation Generation

Simply enter a repository URL and DeepWiki will analyze the code structure, generate comprehensive documentation, and create visual diagrams to explain how everything works.

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🔐 Private Repository Support

Securely access private repositories with personal access tokens from GitHub, GitLab, or BitBucket.

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🤖 Multiple AI Model Providers

Choose from leading AI providers:
  • Google Gemini (default: gemini-2.0-flash)
  • OpenAI (gpt-4o, o1, o3, o4-mini)
  • OpenRouter (access to Claude, Llama, Mistral, and more)
  • Azure OpenAI (enterprise-grade deployment)
  • Ollama (local open-source models)
  • Amazon Bedrock (AWS-hosted models)
  • DashScope (Alibaba Qwen models)

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💬 Intelligent Q&A System

The Ask Feature uses Retrieval Augmented Generation (RAG) to provide accurate answers based on your repository’s actual code.

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🔍 Advanced Research Capabilities

DeepResearch conducts multi-turn investigations for complex topics, providing comprehensive analysis through multiple research iterations.

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🌍 International Support

Built-in support for 10+ languages including English, Chinese, Japanese, Spanish, Korean, Vietnamese, Portuguese, French, and Russian.

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How It Works

1

Repository Analysis

DeepWiki clones and analyzes your repository structure, including private repos with token authentication.
2

AI Processing

Creates embeddings of the code for smart retrieval and uses AI to generate documentation with context-aware understanding.
3

Visualization

Generates Mermaid diagrams to explain code relationships and system architecture.
4

Interactive Wiki

Organizes everything into a structured, navigable wiki with intelligent Q&A capabilities.

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Architecture Overview

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Project Structure

The DeepWiki-Open project consists of: 
src/
├── app/                  # Next.js app directory
│   ├── page.tsx          # Main application page
│   └── api/              # API routes
├── components/           # React components
│   ├── Ask.tsx           # Q&A interface
│   ├── Mermaid.tsx       # Diagram renderer
│   └── ...
└── utils/               # Utility functions

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Quick Start

Ready to get started? Choose your preferred setup method:

Docker Setup (Recommended)

Get up and running in minutes with Docker Compose

Manual Setup

Install and configure manually for development
You’ll need API keys from your chosen AI provider (Google, OpenAI, etc.) to get started. See the Environment Variables guide for details.

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Next Steps

Quick Start Guide

Get DeepWiki running in under 5 minutes

Configuration

Configure your AI model providers

Features Guide

Learn about all DeepWiki features

API Reference

Explore the REST API endpoints