CoderAI - AI Integration Platform

CoderAI is a powerful SaaS platform that enables seamless integration with various AI solution providers and development tools. This application allows users to:

• Connect to local Ollama models or external AI providers
• Process and analyze documents using state-of-the-art AI models
• Generate embeddings using Hugging Face models
• Create and manage vector databases for semantic search
• Build custom AI workflows with a user-friendly interface
• Integrate with GitHub for automated code reviews and project management

Features

• Multi-Provider Integration: Connect to Ollama, OpenAI, Anthropic, and other AI providers
• Document Processing: Upload and analyze documents with AI assistance
• Vector Database: Store and search through document embeddings
• Custom Workflows: Create tailored AI workflows for specific use cases
• Analytics Dashboard: Monitor usage and performance metrics
• GitHub Integration: Automated code reviews, pull request analysis, and issue tracking
• Project Management: Built-in tools for managing development workflows and tasks
• Code Review: AI-powered code analysis and improvement suggestions

Technologies Used

Getting Started

1. Install the required dependencies:

   pip install -r requirements.txt
   

2. Set up your environment variables in a .env file:

   OPENAI_API_KEY=your_openai_key_here (optional)
   ANTHROPIC_API_KEY=your_anthropic_key_here (optional)
   HF_TOKEN=your_huggingface_token_here (optional)
   GITHUB_TOKEN=your_github_token_here (required for GitHub integration)
   

3. Run the application:

   streamlit run app.py
   

Requirements

• Python 3.9+
• Ollama installed locally (for local model integration)
• Internet connection (for external API access)

Project Structure

• app.py: Main Streamlit application
• config.py: Configuration settings
• models/: Model integration modules
• utils/: Utility functions
• components/: Streamlit UI components
  • code_review.py: Code review interface and logic
  • github_integration.py: GitHub API integration
  • project_management.py: Project management features
• services/: Core services
  • embedding_service.py: Text embedding generation
  • vector_store_service.py: Vector database management
  • github_service.py: GitHub API service
  • code_analysis_service.py: Code analysis and review
• data/: Data storage directory

GitHub Integration

To use the GitHub integration features:

1. Generate a GitHub Personal Access Token with the following permissions:

   • repo (full access)
   • workflow
   • read:org

2. Add your GitHub token to the .env file

3. Configure your GitHub repositories in the application settings

Code Review Features

• Automated code quality analysis
• Pull request review suggestions
• Security vulnerability scanning
• Best practices recommendations
• Performance optimization tips

Contributing

If you want to contribute to this project:

1. Fork the repository
2. Create a new branch for your feature
3. Submit a pull request with a clear description of your changes

Please make sure to follow the existing code style and guidelines.

License

This project is licensed under the MIT License - see the LICENSE file for details.