# OpenDeepWiki

**Repository Path**: angelwing7/OpenDeepWiki

## Basic Information

- **Project Name**: OpenDeepWiki
- **Description**: OpenDeepWiki 是 DeepWiki 项目的开源版本，旨在提供一个强大的知识管理与协作平台。项目主要使用 C# 和 TypeScript 开发，支持模块化设计，易于扩展和自定义。
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: https://opendeep.wiki
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 15
- **Created**: 2025-05-13
- **Last Updated**: 2025-05-13

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# OpenDeepWiki

[中文](README.zh-CN.md) | [English](README.md)

<div align="center">
  <img src="/img/favicon.png" alt="OpenDeepWiki Logo" width="200" />
  <h3>AI-Driven Code Knowledge Base</h3>
</div>

# Project Introduction

OpenDeepWiki is an open-source project inspired by [DeepWiki](https://deepwiki.com/), developed using .NET 9 and Semantic Kernel. It aims to help developers better understand and utilize codebases by providing features such as code analysis, documentation generation, and knowledge graph creation.
- Analyze code structure
- Understand core concepts of repositories
- Generate code documentation
- Automatically create README.md for code
  MCP Support


OpenDeepWiki supports MCP (Model Context Protocol)
- Supports providing an MCPServer for a single repository and conducting analysis on a single repository.

Usage: The following is the usage of cursor: 
```json
{
  "mcpServers": {
    "OpenDeepWiki":{
      "url": "http://Your OpenDeepWiki service IP:port/sse?owner=AIDotNet&name=OpenDeepWiki"
    }
  }
}
```
- owner: It is the name of the organization or owner of the repository.
- name: It is the name of the repository. 

After adding the repository, test by asking a question (please note that before doing this, the repository must be processed first): What is OpenDeepWiki? The effect is as shown in the picture: ! [](img/mcp.png)


In this way, you can use OpenDeepWiki as an MCPServer, making it available for other AI models to call upon, facilitating the analysis and understanding of an open-source project.

## Features

- **Quick Generation:** Convert all code repositories from Github, Gitlab, Gitee, Gitea, etc., into a knowledge base in just a few minutes.
- **Multi-language Support:** Supports code analysis and documentation generation for all programming languages.
- **Code Structure:** Automatically generate Mermaid charts to understand code structure.
- **Custom Models:** Supports custom models and custom APIs for extension as needed.
- **AI Intelligent Analysis:** AI-based code analysis and understanding of code relationships.
- **Easy SEO:** Generate SEO-friendly documents and knowledge bases using Next.js for better search engine indexing.
- **Conversational Interaction:** Support for conversational interaction with AI to obtain detailed information and usage methods for code, enabling deeper understanding.

## 🚀 Quick Start

1. Clone the repository
```bash
git clone https://github.com/AIDotNet/OpenDeepWiki.git
cd OpenDeepWiki
```

2. Open the `docker-compose.yml` file and modify the following environment variables:

OpenAI:
```yaml
services:
  koalawiki:
    environment:
      - KOALAWIKI_REPOSITORIES=/repositories
      - TASK_MAX_SIZE_PER_USER=5 # Maximum number of parallel document generation tasks per user by AI
      - CHAT_MODEL=DeepSeek-V3 # Model must support functions
      - ANALYSIS_MODEL= # Analysis model used for generating repository directory structure
      - CHAT_API_KEY= # Your API key
      - LANGUAGE= # Set the default language for generation as "Chinese"
      - ENDPOINT=https://api.token-ai.cn/v1
      - DB_TYPE=sqlite
      - MODEL_PROVIDER=OpenAI # Model provider, default is OpenAI, supports AzureOpenAI and Anthropic
      - DB_CONNECTION_STRING=Data Source=/data/KoalaWiki.db
      - EnableSmartFilter=true # Whether intelligent filtering is enabled or not may affect how the AI can obtain the file directory of the repository
      - UPDATE_INTERVAL # Warehouse increment update interval, unit: days
```

AzureOpenAI:
```yaml
services:
  koalawiki:
    environment:
      - KOALAWIKI_REPOSITORIES=/repositories
      - TASK_MAX_SIZE_PER_USER=5 # Maximum number of parallel document generation tasks per user by AI
      - CHAT_MODEL=DeepSeek-V3 # Model must support functions
      - ANALYSIS_MODEL= # Analysis model used for generating repository directory structure
      - CHAT_API_KEY= # Your API key
      - LANGUAGE= # Set the default language for generation as "Chinese"
      - ENDPOINT=https://your-azure-address.openai.azure.com/
      - DB_TYPE=sqlite
      - MODEL_PROVIDER=AzureOpenAI # Model provider, default is OpenAI, supports AzureOpenAI and Anthropic
      - DB_CONNECTION_STRING=Data Source=/data/KoalaWiki.db
      - EnableSmartFilter=true # Whether intelligent filtering is enabled or not may affect how the AI can obtain the file directory of the repository
      - UPDATE_INTERVAL # Warehouse increment update interval, unit: days
```

Anthropic:
```yaml
services:
  koalawiki:
    environment:
      - KOALAWIKI_REPOSITORIES=/repositories
      - TASK_MAX_SIZE_PER_USER=5 # Maximum number of parallel document generation tasks per user by AI
      - CHAT_MODEL=DeepSeek-V3 # Model must support functions
      - ANALYSIS_MODEL= # Analysis model used for generating repository directory structure
      - CHAT_API_KEY= # Your API key
      - LANGUAGE= # Set the default language for generation as "Chinese"
      - ENDPOINT=https://api.anthropic.com/
      - DB_TYPE=sqlite
      - MODEL_PROVIDER=Anthropic # Model provider, default is OpenAI, supports AzureOpenAI and Anthropic
      - DB_CONNECTION_STRING=Data Source=/data/KoalaWiki.db
      - EnableSmartFilter=true # Whether intelligent filtering is enabled or not may affect how the AI can obtain the file directory of the repository
      - UPDATE_INTERVAL # Warehouse increment update interval, unit: days
```

> 💡 **How to get an API Key:**
> - Get Google API key [Google AI Studio](https://makersuite.google.com/app/apikey)
> - Get OpenAI API key [OpenAI Platform](https://platform.openai.com/api-keys)
> - Get CoresHub [CoresHub](https://console.coreshub.cn/xb3/maas/global-keys) [Click here for 50 million free tokens](https://account.coreshub.cn/signup?invite=ZmpMQlZxYVU=)
> - Get TokenAI [TokenAI](https://api.token-ai.cn/)

3. Start the service

You can use the provided Makefile commands to easily manage the application:

```bash
# Build all Docker images
make build

# Start all services in background mode
make up

# Or start in development mode (with logs visible)
make dev
```

Then visit http://localhost:8090 to access the knowledge base.

For more commands:
```bash
make help
```

### For Windows Users (without make)

If you're using Windows and don't have `make` available, you can use these Docker Compose commands directly:

```bash
# Build all Docker images
docker-compose build

# Start all services in background mode
docker-compose up -d

# Start in development mode (with logs visible)
docker-compose up

# Stop all services
docker-compose down

# View logs
docker-compose logs -f
```

For building specific architectures or services, use:

```bash
# Build only backend
docker-compose build koalawiki

# Build only frontend
docker-compose build koalawiki-web

# Build with architecture parameters
docker-compose build --build-arg ARCH=arm64
docker-compose build --build-arg ARCH=amd64
```

## 🔍 How It Works

OpenDeepWiki uses AI to:
 - Clone code repository locally
 - Analyze based on repository README.md
 - Analyze code structure and read code files as needed, then generate directory json data
 - Process tasks according to directory, each task is a document
 - Read code files, analyze code files, generate code documentation, and create Mermaid charts representing code structure dependencies
 - Generate the final knowledge base document
 - Analyze repository through conversational interaction and respond to user inquiries

```mermaid
graph TD
    A[Clone code repository] --> B[Analyze README.md]
    B --> C[Analyze code structure]
    C --> D[Generate directory json data]
    D --> E[Process multiple tasks]
    E --> F[Read code files]
    F --> G[Analyze code files]
    G --> H[Generate code documentation]
    H --> I[Create Mermaid charts]
    I --> J[Generate knowledge base document]
    J --> K[Conversational interaction]
```
## Advanced Configuration

### Environment Variables
  - KOALAWIKI_REPOSITORIES  Path for storing repositories
  - TASK_MAX_SIZE_PER_USER  Maximum parallel tasks for AI document generation per user
  - CHAT_MODEL  Model must support functions
  - ENDPOINT  API Endpoint
  - ANALYSIS_MODEL  Analysis model for generating repository directory structure
  - CHAT_API_KEY  Your API key
  - LANGUAGE  Change the language of the generated documents
  - DB_TYPE  Database type, default is sqlite
  - MODEL_PROVIDER  Model provider, by default OpenAI, supports Azure, OpenAI and Anthropic
  - DB_CONNECTION_STRING  Database connection string
  - EnableSmartFilter Whether intelligent filtering is enabled or not may affect how the AI can obtain the file directory of the repository
  - UPDATE_INTERVAL Warehouse increment update interval, unit: days

### Build for Different Architectures
The Makefile provides commands to build for different CPU architectures:

```bash
# Build for ARM architecture
make build-arm

# Build for AMD architecture
make build-amd

# Build only backend for ARM
make build-backend-arm

# Build only frontend for AMD
make build-frontend-amd
```

## WeChat 

![2e3d38be0544d933e14c64e7de26f307](https://github.com/user-attachments/assets/f2024809-a3b9-44bd-98d9-142573c3206b)

## 📄 License
This project is licensed under the MIT License - see the [LICENSE](./LICENSE) file for details.

## Star History

[![Star History Chart](https://api.star-history.com/svg?repos=AIDotNet/OpenDeepWiki&type=Date)](https://www.star-history.com/#AIDotNet/OpenDeepWiki&Date)