GitDiagram is an open-source tool that transforms GitHub repository structures into interactive system design diagrams using AI. It was created to help developers quickly understand complex codebases by converting file trees and README content into visually navigable Mermaid.js diagrams. The tool is especially valuable for contributors new to large open-source projects, offering an intuitive way to explore architecture without manually parsing hundreds of files. By leveraging OpenAI o4-mini for prompt-based analysis, GitDiagram extracts meaningful relationships between components and renders them as clickable diagrams that link directly to source files.
Users can generate diagrams for both public and private repositories by providing a GitHub personal access token. The tool is designed with extensibility in mind, offering a full-stack architecture that can be self-hosted for teams needing control over data privacy or rate limits. With a frontend built in Next.js and TypeScript, and a backend powered by FastAPI and PostgreSQL, GitDiagram bridges the gap between raw code and visual comprehension.
What You Get
- Instant Visualization - Convert any GitHub repository’s structure into an interactive Mermaid.js diagram by simply replacing ‘hub’ with ‘diagram’ in any GitHub URL (e.g., github.com/owner/repo → gitdiagram.com/owner/repo)
- Interactivity - Click on any component in the diagram to navigate directly to its corresponding source file or directory in GitHub, enabling seamless exploration without leaving the interface
- Fast Generation with AI - Uses OpenAI o4-mini (previously Claude 3.5 Sonnet) to analyze file trees and README content, then generates accurate architecture diagrams through prompt engineering rather than static parsing
- Customization & Regeneration - Modify diagram generation prompts and regenerate diagrams with custom instructions to refine output based on specific analysis needs
- Private Repository Support - Generate diagrams for private repos by providing a GitHub personal access token with ‘repo’ scope via the UI or environment variables when self-hosting
- Public API Access (WIP) - Integrate diagram generation into other tools via a publicly available API endpoint, with documentation and endpoints planned for future releases
Common Use Cases
- Building a new contribution workflow for large open-source projects - A developer joins a repo with 500+ files and uses GitDiagram to instantly visualize module dependencies, reducing onboarding time from hours to minutes
- Teaching system design in engineering bootcamps - Instructors use GitDiagram to demonstrate real-world architecture patterns by generating diagrams from popular GitHub projects like Next.js or Vue, helping students connect theory with code structure
- Problem: Overwhelmed by unfamiliar codebase → Solution: Generate diagram to map components - A backend engineer needs to debug a microservice in a repo they’ve never seen; they paste the GitHub URL, get an interactive diagram showing service boundaries and data flow, then navigate directly to relevant files
- Team onboarding for distributed DevOps teams - A remote team uses GitDiagram to share visual overviews of microservice architectures before sprint planning, reducing miscommunication about component ownership and dependencies
Under The Hood
This project is a full-stack web application that integrates AI-powered code analysis with interactive visualizations, enabling developers to understand and diagram GitHub repositories through a modern web interface. It combines a TypeScript/Next.js frontend with a Python-based backend API, emphasizing structured development and modern web practices.
Architecture
This project adopts a monolithic architecture with clear separation between frontend and backend components, utilizing a layered design for organization. The system integrates service-oriented backend modules with reusable frontend UI elements.
- Monolithic structure with distinct frontend and backend layers
- Service-oriented backend components for modular functionality
- Layered approach supporting separation of concerns and maintainability
Tech Stack
The project leverages a contemporary full-stack tech stack, integrating TypeScript/Next.js for the frontend and Python/FastAPI for the backend to support AI-driven features.
- TypeScript and Next.js for modern, type-safe frontend development
- Python and FastAPI for scalable, well-documented backend services
- Drizzle ORM, PostHog, and Radix UI for enhanced developer experience
- Prettier and ESLint for consistent code formatting and linting
Code Quality
The project demonstrates a mixed quality level with modern practices in place but lacking formal testing and some consistency across components.
- Extensive use of try/catch blocks for error handling in both frontend and backend
- Limited test coverage with no dedicated testing frameworks or strategies
- Inconsistent code style and naming between frontend and backend modules
- Signs of technical debt including duplicated queries and under-abstraction in services
What Makes It Unique
This project introduces a unique blend of AI-powered code analysis and interactive diagramming, distinguishing itself through intelligent architecture and visualization capabilities.
- Multi-provider LLM integration for enhanced code understanding
- Intelligent caching mechanisms to optimize performance and reduce redundant processing
- Seamless visualization of code structure through Mermaid and Radix UI components
- Bridge between GitHub repository analysis and interactive diagramming tools