OpenRepoWiki automates the generation of comprehensive wiki documentation for GitHub repositories. It provides quick insights into repository purpose, architecture, and file roles, enabling developers and users to understand projects without extensive code review. The primary benefit is significant time savings in project comprehension.

How It Works

The project employs a fully serverless AWS architecture. A React frontend is served via CloudFront CDN and S3. API Gateway routes requests to Lambda functions, which trigger a Step Functions workflow. This workflow orchestrates an ECS Fargate service powered by LLMs (DeepSeek, Gemini, Ollama) for code analysis and summarization. DynamoDB stores processed data and job statuses, while S3 holds artifacts. This design prioritizes scalability, cost-efficiency, and automated processing.

Quick Start & Requirements

• Prerequisites: AWS CLI, Terraform v1.5+, Node.js 18+, Python 3.11+, Docker.
• Configuration: Set environment variables (LLM_PROVIDER, LLM_APIKEY, GITHUB_TOKEN) in .env.
• Deployment: Deploy infrastructure using Terraform (infra/terraform/env/prod). Build and deploy Lambda services (services/api). Build and deploy the frontend (frontend), configuring VITE_API_URL and VITE_SIGNING_KEY.
• Demo: A live demo is available at openrepowiki.xyz.

Highlighted Details

• Automated Wiki Generation: Creates summaries of repository purpose, functionality, and architecture.
• Codebase Analysis: Identifies key files, functions, and their roles.
• Dependency Graphs: Visualizes file relationships using Mermaid diagrams.
• Security: Features WAF, HMAC-signed requests, restricted CORS, private subnets, and Secrets Manager.
• Cost Optimization: Utilizes Lambda, Fargate Spot, DynamoDB On-Demand, and CloudFront caching.

Maintenance & Community

No specific details regarding maintenance, contributors, or community channels were found in the provided README.

Licensing & Compatibility

The license type is not specified in the provided README. Compatibility for commercial use is undetermined without a license.

Limitations & Caveats

Analyzing large repositories can consume substantial LLM tokens (potentially over 1 million per repo), making the choice of a cost-effective LLM provider, such as DeepSeek, crucial for production use.