GitVizz
Visualize and analyze GitHub or local repositories using LLM-friendly summaries, file structure, and interactive dependency graphs.
Stars: 236
GitVizz is an AI-powered repository analysis tool that helps developers understand and navigate codebases quickly. It transforms complex code structures into interactive documentation, dependency graphs, and intelligent conversations. With features like interactive dependency graphs, AI-powered code conversations, advanced code visualization, and automatic documentation generation, GitVizz offers instant understanding and insights for any repository. The tool is built with modern technologies like Next.js, FastAPI, and OpenAI, making it scalable and efficient for analyzing large codebases. GitVizz also provides a standalone Python library for core code analysis and dependency graph generation, offering multi-language parsing, AST analysis, dependency graphs, visualizations, and extensibility for custom applications.
README:
Understand Any Codebase in Minutes, Not Hours
AI-powered repository analysis that turns complex codebases into interactive documentation, dependency graphs, and intelligent conversations.
GitVizz revolutionizes how developers understand and navigate codebases. Whether you're onboarding to a new project, reviewing code, or exploring open source repositories, GitVizz transforms complex code structures into intuitive, interactive experiences.
https://github.com/user-attachments/assets/52eeb2c1-598b-4173-b0e8-8d4b986dbf64
- Instant Understanding: Analyze any repository in seconds, not hours
- AI-Powered Insights: Get intelligent summaries and explanations
- Visual Code Maps: Interactive dependency graphs and code relationships
- Chat with Code: Ask questions about any codebase and get instant answers
- Auto Documentation: Generate comprehensive docs automatically
- Smart Search: Find functions, classes, and patterns across entire repositories
Visit gitvizz.com and paste any GitHub repository URL to get started instantly!
# Clone the repository
git clone https://github.com/adithya-s-k/gitvizz.git
cd gitvizz
# Copy environment files
cp backend/.env.example backend/.env
cp frontend/.env.example frontend/.env.local
# Start all services
docker-compose up --buildAccess Points:
- Frontend: http://localhost:3000
- Backend API: http://localhost:8003
- Phoenix UI: http://localhost:6006 (LLM observability dashboard)
๐ Phoenix Observability: GitVizz includes Arize Phoenix for comprehensive LLM monitoring and tracing. See Phoenix Setup Guide for detailed configuration options.
Click to expand manual setup instructions
# Create virtual environment
python3 -m venv .venv
source .venv/bin/activate
# Install dependencies
pip install -r backend/requirements.txt
# Configure environment
cp backend/.env.example backend/.env
# Edit backend/.env with your settings
# Start backend server
uvicorn backend.server:app --host 0.0.0.0 --port 8003 --reload# Install dependencies
cd frontend
pnpm install
# Configure environment
cp .env.example .env.local
# Edit .env.local with your settings
# Start development server
pnpm devGitVizz is built with modern, scalable technologies:
โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ
โ Frontend โ โ Backend โ โ AI Services โ
โ โ โ โ โ โ
โ โข Next.js 14 โโโโโบโ โข FastAPI โโโโโบโ โข OpenAI โ
โ โข TypeScript โ โ โข Python 3.9+ โ โ โข Anthropic โ
โ โข Tailwind CSS โ โ โข Async/Await โ โ โข Local LLMs โ
โ โข ShadCN UI โ โ โข Pydantic โ โ โ
โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโ
Frontend:
- Next.js 14 - React framework with App Router
- Tailwind CSS - Utility-first CSS framework
- ShadCN UI - Beautiful, accessible components
- Responsive Design - Works on all devices
Backend:
- FastAPI - High-performance Python API framework
- AST Parsing - Advanced code analysis
- Graph Generation - Dynamic dependency mapping
- LLM Integration - Multiple AI provider support
- Node.js 18+ and pnpm
- Python 3.9+ and pip
- Docker & Docker Compose (for containerized setup)
- MongoDB - For user data and repository metadata storage
- GitHub Personal Access Token - For private repo access
- GitHub App - For advanced GitHub integration
- OpenAI API Key - For AI-powered features
- Anthropic API Key - Alternative AI provider
- Gemini API Key - Google's AI model support
- Groq API Key - Fast inference API
- Phoenix - LLM observability and tracing platform
Backend (.env)
# GitHub Integration
GITHUB_USER_AGENT=gitvizz-cognitivelab
# JWT Authentication
JWT_SECRET=your-jwt-secret-here-use-openssl-rand-base64-32
JWT_ALGORITHM=HS256
JWT_EXPIRE_MINUTES=10080 # 7 days
REFRESH_TOKEN_EXPIRE_DAYS=30 # 30 days
# Database Configuration
MONGO_URI=mongodb://localhost:27017
MONGODB_DB_NAME=gitvizz
# Server Configuration
HOST=0.0.0.0
PORT=8003
# File Storage
FILE_STORAGE_BASEPATH="storage"
# Data Encryption
ENCRYPTION_KEY=your-32-byte-base64-encryption-key-here
FERNET_KEY=your-32-byte-base64-encryption-key-here
# GitHub OAuth App Credentials
GITHUB_CLIENT_ID=your-github-oauth-client-id
GITHUB_CLIENT_SECRET=your-github-oauth-client-secret
# GitHub App Credentials (if using GitHub App instead of OAuth)
GITHUB_APP_ID=your-github-app-id
GITHUB_PRIVATE_KEY="-----BEGIN RSA PRIVATE KEY-----
your-github-app-private-key-here
-----END RSA PRIVATE KEY-----"
# Phoenix Observability (Optional)
PHOENIX_API_KEY=your-phoenix-api-key
PHOENIX_COLLECTOR_ENDPOINT=https://app.phoenix.arize.com
# LLM API Keys (at least one required)
OPENAI_API_KEY=your-openai-api-key-here
ANTHROPIC_API_KEY=your-anthropic-api-key-here
GEMINI_API_KEY=your-gemini-api-key-here
GROQ_API_KEY=your-groq-api-key-hereFrontend (.env.local)
# API base URL for the frontend application
NEXT_PUBLIC_BACKEND_URL=http://localhost:8003
# NextAuth Configuration
NEXTAUTH_URL=http://localhost:3000
AUTH_SECRET="your-auth-secret-here"
# GitHub App Integration
NEXT_PUBLIC_GITHUB_APP_NAME=your-github-app-name
AUTH_GITHUB_ID=your-github-app-client-id
AUTH_GITHUB_SECRET=your-github-app-client-secretStep-by-step guide to create a GitHub Personal Access Token
- Navigate to GitHub: Go to github.com and sign in
- Access Profile Settings: Click your profile picture โ Settings
- Developer Settings: Scroll down and click "Developer settings"
- Personal Access Tokens: Click "Personal access tokens" โ "Tokens (classic)"
- Generate New Token: Click "Generate new token" โ "Generate new token (classic)"
- Authenticate: Use your password to confirm
-
Configure Token:
- Note: Give your token a descriptive name
- Expiration: Set appropriate expiration date
- Scopes: Select required permissions
- Repository Access: Choose "All repositories" for full access
- Generate: Click "Generate token"
Important: Copy and save the token immediately - you won't be able to see it again!
For detailed instructions with screenshots, see docs/github_personal_token.md
Step-by-step guide to create a GitHub App
-
Navigate to GitHub Apps: Go to GitHub Apps settings
-
Create New App: Click "New GitHub App"
-
App Details:
- GitHub App name: Enter your application name
-
Homepage URL:
http://localhost:3000/ -
Callback URL:
http://localhost:3000/api/auth/callback/github - Expire user authorization tokens: Deselect this
-
Setup URL:
http://localhost:3000/ - Webhook: Deselect "Active" to disable webhooks
-
Set Permissions:
- Repository Permissions โ Contents: Read-only
- Account Permissions โ Email addresses: Read-only
-
Create App: Click "Create GitHub App"
-
Get Credentials:
- Copy App ID and Client ID
- Generate and copy Client Secret
-
Generate Private Key:
- Click "Generate a private key"
- Download the
.pemfile - Copy entire contents including BEGIN/END lines
- Wrap in double quotes for
.envfile
For detailed instructions with screenshots, see docs/create_github_app.md
We love contributions! GitVizz is open source and community-driven.
- Report Bugs - Found an issue? Let us know!
- Suggest Features - Have ideas? We'd love to hear them!
- Improve Documentation - Help others understand GitVizz better
- Submit Pull Requests - Code contributions are always welcome!
- Star the Repository - Show your support!
- Fork the repository
-
Create a feature branch (
git checkout -b feature/amazing-feature) -
Commit your changes (
git commit -m 'Add amazing feature') -
Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
We follow Conventional Commits:
-
feat:New features -
fix:Bug fixes -
docs:Documentation changes -
style:Code style changes -
refactor:Code refactoring -
test:Adding tests -
chore:Maintenance tasks
gitvizz/
โโโ frontend/ # Next.js frontend application
โ โโโ app/ # App router pages
โ โโโ components/ # Reusable UI components
โ โโโ api-client/ # Generated API client
โ โโโ public/ # Static assets
โโโ backend/ # FastAPI backend application
โ โโโ controllers/ # API route handlers
โ โโโ documentation_generator/ # AI-powered analysis
โ โโโ models/ # Data models
โ โโโ routes/ # API routes
โ โโโ schemas/ # Request/response schemas
โ โโโ services/ # Business logic
โ โโโ utils/ # Utility functions
โโโ gitvizz/ # ๐ฆ GitVizz Core Library
โ โโโ gitvizz/ # Python package
โ โ โโโ graph_generator.py # Main graph generation engine
โ โ โโโ custom_ast_parser.py # AST parsing with Tree-sitter
โ โ โโโ modal_app.py # Optional Modal integration
โ โโโ pyproject.toml # Package configuration
โ โโโ README.md # Library documentation
โโโ docs/ # Documentation
โโโ docker-compose.yaml # Container orchestration
โโโ README.md # You are here!
GitVizz includes a standalone Python library (gitvizz/) that provides the core code analysis and dependency graph generation functionality. This library can be used independently in your own projects:
- ๐ Multi-language Parsing: Python, JavaScript, TypeScript, React, Next.js
- ๐ณ AST Analysis: Advanced Abstract Syntax Tree parsing with Tree-sitter
- ๐ธ๏ธ Dependency Graphs: Generate detailed code relationship maps
- ๐ Interactive Visualizations: HTML graph outputs with Pyvis
- โก Fast & Efficient: Optimized for large codebases
- ๐ง Extensible: Plugin architecture for new languages
# Install the library
pip install git+https://github.com/adithya-s-k/GitVizz.git#subdirectory=gitvizz
# Use in your Python code
from gitvizz import GraphGenerator
files_data = [{"path": "main.py", "content": "# your code"}]
generator = GraphGenerator(files=files_data)
result = generator.generate()- Code Analysis Tools: Build custom code analysis applications
- Documentation Generation: Auto-generate dependency documentation
- IDE Plugins: Integrate code visualization into development environments
- CI/CD Pipelines: Automated code structure analysis
- Research: Academic research on software architecture
For detailed documentation, see gitvizz/README.md.
-
[ ] Agentic Chat System - Advanced multi-agent conversation system with tool usage and autonomous reasoning
- Context-aware code navigation agents
- Automated refactoring suggestions
- Intelligent bug detection and fix proposals
- Self-healing code recommendations
-
[ ] Enhanced Documentation Generation - Next-generation AI-powered documentation
- Multi-format output (Markdown, HTML, PDF, Confluence)
- Interactive API documentation
- Auto-generated code examples and tutorials
- Version-aware documentation diffing
- Architecture decision records (ADRs) generation
-
[ ] Video Generation from Code - Transform code into visual explanations
- Animated code walkthroughs
- Function execution flow visualizations
- Architecture diagram animations
- Tutorial video generation from codebases
- Code review video summaries
-
[ ] Enhanced AI Models - Support for more LLM providers
- OpenRouter integration for unified model access
- Local LLM support (Ollama, LM Studio)
- Custom model fine-tuning capabilities
- Cost optimization with model routing
-
[ ] PyPI Release - Publish GitVizz core library to PyPI
- Stable v1.0 release
- Comprehensive API documentation
- Usage examples and cookbook
-
[ ] Smart Context Builder - AI-powered retrieval for relevant code
- Semantic code search with embeddings
- Intelligent context pruning for LLM queries
- Multi-hop reasoning across dependencies
- Automated code snippet selection
-
[ ] Code Quality & Security Analysis
- Security vulnerability detection
- Performance bottleneck identification
- Code smell detection and refactoring suggestions
- Test coverage analysis and recommendations
- Technical debt tracking
-
[ ] Advanced Analytics - Comprehensive code quality metrics
- Complexity metrics and visualization
- Code churn analysis
- Developer contribution insights
- Codebase health scoring
-
[ ] Real-time Collaboration - Multi-user code exploration
- Shared analysis sessions
- Collaborative annotations
- Team knowledge bases
- Code review workflow integration
-
[ ] Plugin System - Extensible architecture
- Custom language parsers
- Third-party tool integrations
- Custom visualization plugins
- Export format extensions
-
[ ] VS Code Extension - Native IDE integration
- Inline documentation preview
- Graph visualization in editor
- AI chat sidebar
- Quick analysis commands
-
[ ] JetBrains IDE Plugin - IntelliJ IDEA, PyCharm, WebStorm support
- Native IDE integration
- Context-aware suggestions
- Code navigation enhancements
-
[ ] Mobile App - Code exploration on the go
- iOS and Android native apps
- Offline repository access
- Push notifications for analysis completion
- Mobile-optimized graph visualization
-
[ ] Self-Hosted Enterprise Edition
- On-premise deployment
- LDAP/SAML/SSO authentication
- Advanced security controls
- Audit logging and compliance
-
[ ] Team Collaboration Suite
- Organization-wide knowledge bases
- Team analytics and insights
- Project management integration
- Custom workflows and automations
-
[ ] Multi-Repository Analysis - Cross-project insights
- Microservices dependency mapping
- Shared library usage tracking
- Organization-wide code patterns
-
[ ] Time-Travel Code Analysis - Historical codebase exploration
- Repository evolution visualization
- Regression analysis
- Contributor timeline analysis
- Code archaeology tools
-
[ ] AI Code Generation & Migration
- Automated migration between frameworks
- Legacy code modernization
- Cross-language code translation
- Architecture transformation assistance
-
[ ] Extended Language Support
- Rust, Swift, Kotlin support
- SQL and database schema analysis
- Infrastructure-as-Code (Terraform, CloudFormation)
- Configuration file analysis (YAML, TOML, JSON)
Have an idea? Submit a feature request and help shape the future of GitVizz!
This repository contains multiple components with different licenses:
- Backend & Frontend Applications: Licensed under the GNU Affero General Public License v3.0
- GitVizz Core Library: Licensed under the Apache License 2.0
Please refer to the respective LICENSE files in each component directory for detailed terms and conditions.
- Contributors - Thank you to all our amazing contributors!
- Community - Special thanks to our supportive community
- Open Source - Built on the shoulders of incredible open source projects
- Feedback - Grateful for all user feedback and suggestions
Made with โค๏ธ by CognitiveLab | Powered by Omniparse
Star us on GitHub โ it motivates us a lot!
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PR-Agent is a tool that helps to efficiently review and handle pull requests by providing AI feedbacks and suggestions. It supports various commands such as generating PR descriptions, providing code suggestions, answering questions about the PR, and updating the CHANGELOG.md file. PR-Agent can be used via CLI, GitHub Action, GitHub App, Docker, and supports multiple git providers and models. It emphasizes real-life practical usage, with each tool having a single GPT-4 call for quick and affordable responses. The PR Compression strategy enables effective handling of both short and long PRs, while the JSON prompting strategy allows for modular and customizable tools. PR-Agent Pro, the hosted version by CodiumAI, provides additional benefits such as full management, improved privacy, priority support, and extra features.
shell_gpt
ShellGPT is a command-line productivity tool powered by AI large language models (LLMs). This command-line tool offers streamlined generation of shell commands, code snippets, documentation, eliminating the need for external resources (like Google search). Supports Linux, macOS, Windows and compatible with all major Shells like PowerShell, CMD, Bash, Zsh, etc.
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sweep
Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.
teams-ai
The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.
ai-guide
This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.
classifai
Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.
chatbot-ui
Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.
BricksLLM
BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students
uAgents
uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.
griptape
Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.





