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CodePapi AI ⚡

Transform your code instantly with local AI power. No cloud, no data leaks—just blazing-fast code translation, migration, and debugging on your machine.

License Ollama React NestJS Biome

What is CodePapi AI?

CodePapi AI is a professional, privacy-focused developer tool that brings the power of Large Language Models (LLMs) directly to your local development workflow. Whether you're translating code between languages, migrating frameworks, reviewing for security issues, or debugging complex logic—all your code stays on your machine.

Why CodePapi AI?

✅ 100% Private — Your code never leaves your machine
✅ Lightning Fast — Runs locally on your hardware
✅ Free — MIT licensed, fully open-source
✅ Extensible — Add languages, frameworks, and custom prompts easily

✨ Core Features

🔄 Smart Code Translation

Effortlessly convert code between 10+ languages including JavaScript, TypeScript, Python, Go, Rust, Java, and more. The system is flexible enough to support any language you add.

🚀 Framework Migration Engine

Pre-built, expert-level migration presets for common transformations:

  • React Class Components → React Functional Components (with Hooks)
  • JavaScript → TypeScript
  • CSS → Tailwind CSS
  • React → Vue.js

🔍 Deep Code Review

Get AI-driven analysis of your code covering:

  • Performance optimization opportunities
  • Security vulnerabilities
  • Best practice violations
  • Code quality improvements

🐞 Interactive Bug Fixer

Fix bugs with confidence. The Diff View shows exactly what the AI changed, side-by-side comparison so you understand every modification before accepting.

🔒 Air-Gapped Privacy

Powered by Qwen2.5-Coder (1.5GB model) running locally through Ollama. Your code never touches the internet.

🚀 Getting Started

Prerequisites

Before you begin, ensure you have the following installed:

Installation (Docker)

# Clone the repository
git clone https://github.com/codepapi/codepapi-ai.git
cd codepapi-ai

# Start the entire stack with one command
docker-compose up -d

First Launch Setup

⚠️ Important: The first startup requires downloading AI models. Ensure you have a stable internet connection.

After starting the containers, pull the required models:

# Pull Qwen2.5 Coder (primary model, ~1.5GB)
docker exec ollama ollama pull qwen2.5-coder:1.5b

# Pull Phi-3 Mini (optional, ~2.3GB alternative model)
docker exec ollama ollama pull phi3:mini

Once the models are downloaded and containers are running:

💻 How to Use

  1. Paste or type your code into the left editor
  2. Select a source language/framework from the dropdown
  3. Choose your action:
    • Translate: Pick a target language
    • Review: Get AI analysis (no target needed)
    • Check Bugs: See a diff view of fixes
  4. Click "Run AI" and watch the magic happen
  5. Copy the result or download your transformed code

🛠 Tech Stack

Component Technology Purpose
AI Engine Ollama + Qwen2.5-Coder Local LLM inference
Orchestration LangChain.js AI workflow management
Backend NestJS (Node.js) REST API & business logic
Frontend React + TailwindCSS + Lucide Modern, responsive UI
Editor Monaco Editor VS Code-powered code editing
Quality Biome Fast linting & formatting

🧑‍💻 Development

Adding New Languages

Want to support more programming languages or migration presets? It's easy!

See the Frontend Documentation for detailed instructions on adding languages to frontend/src/constants/languages.ts.

Code Quality

We use Biome for lightning-fast linting and formatting. Before submitting a PR, run:

npm run biome:lint    # Check for issues
npx @biomejs/biome check --apply .  # Auto-fix issues

Project Structure

codepapi-ai/
├── backend/              # NestJS API server
│   └── src/converter/   # Code conversion logic
├── frontend/            # React UI application
│   └── src/constants/   # Language & migration definitions
├── docker-compose.yml   # Full stack orchestration
└── README.md           # This file

📋 Code of Conduct

We are committed to providing a welcoming and inclusive environment for all contributors. Please read and follow our Code of Conduct:

  • Respect: Treat all community members with respect and dignity
  • Inclusion: Welcome contributors of all backgrounds and experience levels
  • Professionalism: Keep discussions constructive and focused on the project
  • Accountability: If you witness or experience misconduct, report it responsibly

Violations will not be tolerated and may result in removal from the project.

🤝 Contributing Guidelines

We welcome contributions from the community! Whether it's bug fixes, features, documentation, or translations, your help makes CodePapi AI better.

Getting Started

  1. Check existing issues and PRs to avoid duplicate work
  2. Fork the repository and clone it locally
  3. Create a feature branch with a descriptive name: 
    git checkout -b feature/add-kotlin-support
# or
git checkout -b fix/console-error-on-large-files

Development Setup

# Install dependencies
cd backend && npm install && cd ..
cd frontend && npm install && cd ..

# Start development environment
docker-compose up -d

# Or run services individually with npm
npm run dev  # in both backend/ and frontend/

Code Standards

Style & Formatting

  • Linter: We use Biome for all TypeScript/JavaScript code
  • Before every commit, run: 
    npx @biomejs/biome check --apply .
  • No manual formatting — let Biome handle it
  • Line length: Maximum 100 characters (Biome enforces this)

Git Commits

  • Commit messages should be clear and descriptive: 
    ✨ feat: add support for Kotlin language
🐛 fix: resolve console error on large file uploads
📝 docs: update contributing guidelines
♻️ refactor: simplify code translation logic
  • Prefix types: feat, fix, docs, refactor, test, chore, perf
  • Keep commits atomic — one logical change per commit
  • Reference issues: Closes #123 in commit body when applicable

Pull Requests

  • Title: Use the same format as commits (e.g., feat: add Kotlin support)
  • Description: Explain why the change is needed, not just what
  • Linked issues: Reference any related issues (Fixes #123)
  • Testing: Include steps to test your changes
  • Screenshots: For UI changes, include before/after screenshots
  • No WIP PRs: Only open PRs when ready for review

Code Quality Checklist

Before submitting a PR, ensure:

  • ✅ Code passes npm run biome:lint without warnings
  • ✅ All tests pass (if applicable)
  • ✅ No console errors or warnings in development
  • ✅ Comments explain why, not what (code should be self-documenting)
  • ✅ No commented-out code left behind
  • ✅ Variable/function names are descriptive and follow conventions
  • ✅ No hardcoded values (use constants/config instead)
  • ✅ Security: No credentials, secrets, or sensitive data exposed
  • ✅ TypeScript: Avoid any types; use proper typing
  • ✅ Documentation: Update README/docs if behavior changes

Adding Features

New Languages or Migration Presets

  1. Update frontend/src/constants/languages.ts with new entries
  2. Add corresponding backend logic in backend/src/converter/converter.service.ts if needed
  3. Test end-to-end with the UI
  4. Update frontend/README.md if adding complex metadata

Bug Fixes

  1. Add a test case that reproduces the bug (if possible)
  2. Fix the issue
  3. Verify the test now passes
  4. Check for related issues that might have the same root cause

Documentation

  1. Keep docs synchronized with code changes
  2. Add examples for complex features
  3. Update the main README if adding major functionality

Testing

While formal unit tests are encouraged:

  • Manual testing is acceptable for UI changes
  • Test in Docker to ensure consistency across environments
  • Test with the Qwen2.5-Coder model (not a different LLM)
  • Document test steps in your PR

Review Process

  1. Automated checks run on all PRs (Biome linting)
  2. Code review: At least one maintainer must approve
  3. Feedback: Be open to suggestions and iterate
  4. Approval: Once approved, you may merge (or request maintainer to merge)
  5. Closed PRs: If inactive for 30 days, may be closed to keep backlog clean

Areas We Need Help With

  • 🌍 Translations: UI language support
  • 🧪 Testing: Test coverage and edge cases
  • 📚 Documentation: Guides, tutorials, examples
  • 🐛 Bug fixes: Active issues on GitHub
  • ✨ Features: Language support, migration presets, new modes
  • 🎨 UI/UX: Design improvements, accessibility

See the Issues page for tasks labeled good first issue and help wanted.

Recognition

  • All contributors are listed in CONTRIBUTORS.md
  • Significant contributions may be highlighted in release notes
  • Community members can earn roles (Maintainer, Reviewer, etc.)

🤖 Responsible AI Ethics

As an AI-powered tool, CodePapi AI follows these ethical principles:

Privacy First

  • No telemetry: We don't track usage or collect analytics
  • Local processing: All code processing happens on your machine
  • No training data: Your code is never used to train or improve models
  • GDPR compliant: Full control over your data

Transparency

  • Open source: Full code transparency — inspect everything
  • Model disclosure: We explicitly state which LLM is used (Phi-3 Mini)
  • Limitations: We're honest about what the AI can and cannot do
  • Attribution: AI improvements are documented and credited

Responsible Use Guidelines

Do:

  • ✅ Use CodePapi AI for legitimate code improvement
  • ✅ Review AI suggestions before implementing
  • ✅ Report security issues responsibly
  • ✅ Contribute improvements back to the community

Don't:

  • ❌ Use for malicious code generation
  • ❌ Bypass security reviews using AI
  • ❌ Rely solely on AI without code review
  • ❌ Claim AI-generated code as entirely your own without attribution

Security Considerations

  • Always review code generated by AI before committing
  • Run security scanners on translated/migrated code
  • Test thoroughly in safe environments first
  • Report any security concerns to [security@example.com]

🚨 Reporting Issues & Security

Bug Reports

  • Use the bug report template provided in GitHub Issues
  • Include reproduction steps and expected vs. actual behavior
  • Environment info: OS, Docker version, any custom configs
  • No duplicate reports: Search existing issues first

Security Vulnerabilities

  • Don't open public issues for security vulnerabilities
  • Email us privately: [security@example.com]
  • Include: Version, reproduction steps, and potential impact
  • Responsible disclosure: Allow 48 hours before public disclosure

See frontend/README.md for detailed customization guides.

⚠️ System Requirements

  • Docker & Docker Compose (recommended) or
  • Node.js 18+ + Ollama (for local development)
  • Minimum 2GB RAM recommended (Qwen2.5-Coder model size)
  • Stable internet for initial model download
  • macOS, Linux, or Windows (with WSL2)

📚 Documentation

📄 License

Distributed under the MIT License. See LICENSE for details.

💬 Support

Made with ❤️ for developers who value privacy and speed

⭐ Star us on GitHub • 🐛 Report a Bug • 💡 Suggest a Feature