OpenRepoWiki is a tool that automatically generates a comprehensive wiki page for any given GitHub repository. I hate reading code, but I want to learn how to build stuffs from websites to databases. That's why I built OpenRepoWiki, where we can understand the purpose of that files and folders of a particular repository.

• Automated Wiki Generation: Creates a summarized overview of a repository's purpose, functionality, and core components.
• Codebase Analysis: Analyzes the code structure, identifies key files and functions, and explains their roles within the project.
• Dependency Graph: Shows how files in each folder relate to each other using Mermaid diagrams with labeled arrows (e.g., "provides config to", "transforms data for").
• Link To That Code Block: The sky-blue highlighted code block will point to the Github link where it referenced.

• Either Google AI Studio or Deepseek API Key
• Github API Key (To get more quota requesting the repository data)
• Amazon S3 (You can ignore the parameters if you are going to use it locally. You need to use certificate for your Database if you are going to host it.)
• Docker (If you are hosting locally)

1. Copy .env.example to .env
2. Configure just github token and LLM configurations
3. Run docker compose up or docker compose up -d to hide the output

• It's recommended if you can run bigger LLM than 14b parameter.
• You do not need to provide the API KEY
• Set LLM_PROVIDER to Ollama (It is going to connect to default ollama endpoint)
• Set LLM_MODELNAME to the model name you can see from Ollama using the command ollama ls
• It is recommended to set TOKEN_PROCESSING_CHARACTER_LIMIT between 10000-20000 (Approx 300-600 lines of code) if you are using low param LLM (ex. 8b, 14b)

Example:

LLM_PROVIDER=deepseek LLM_APIKEY=sk-.... LLM_MODELNAME=deepseek-chat 

• If you are going to host it locally, you will only need to configure the Docker PostgreSQL container, Github API Key, and Google AI Studio or Deepseek API Key

Refer Documentation