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| title: AI Code Analyzer | |
| emoji: 🧠 | |
| colorFrom: gray | |
| colorTo: green | |
| sdk: docker | |
| app_port: 7860 | |
| pinned: false | |
| # AI Code Analyzer | |
| A professional AI-powered code analysis tool with a sleek Matrix-inspired interface that leverages multiple Large Language Models (LLMs) to provide comprehensive code reviews, identify issues, and suggest improvements. | |
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| ## ✨ Features | |
| * **🤖 Multi-Model Analysis**: Compare insights from OpenAI GPT-4, Anthropic Claude, DeepSeek, and Hugging Face models | |
| * **🎯 Fine-tuned Code Analyzer**: Custom DeepSeek model trained on 59+ code analysis examples | |
| * **🎨 Matrix-Inspired UI**: Sleek dark theme with neon green accents and cyberpunk aesthetics | |
| * **📊 Comprehensive Code Review**: Get quality scores, identify bugs, security issues, and performance concerns | |
| * **🔍 Language Auto-Detection**: Automatically detects programming language or manually specify | |
| * **📁 File Upload Support**: Upload code files directly with drag & drop functionality | |
| * **⚡ Fast & Responsive**: Optimized for deployment with professional performance | |
| * **🔒 Secure**: API keys are securely managed through environment variables | |
| * **📈 Real-time Metrics**: Track analysis time, quality scores, and model comparisons | |
| * **🌐 Remote Model Support**: Use fine-tuned models hosted on Hugging Face (always available) | |
| ## 🌐 Live Demo | |
| **Local Deployment**: Your AI Code Analyzer is running locally at `http://localhost:8501/` | |
| ## 🛠️ Tech Stack | |
| - **Frontend**: Streamlit with custom Matrix-inspired CSS | |
| - **LLM Integration**: OpenAI, Anthropic, DeepSeek, Hugging Face APIs | |
| - **Fine-tuning**: LoRA/QLoRA with Hugging Face Transformers | |
| - **Model Hosting**: Hugging Face Hub & Spaces | |
| - **Language**: Python 3.11+ | |
| - **Deployment**: Hugging Face Spaces (recommended for ease of use and free tier) | |
| - **Styling**: Custom CSS with Google Fonts (Share Tech Mono, Orbitron) | |
| ## 🎯 Fine-tuned Model | |
| This project includes a custom fine-tuned DeepSeek Coder model trained on 59+ code analysis examples: | |
| - **Base Model**: DeepSeek Coder 1.3B | |
| - **Training Method**: LoRA (Low-Rank Adaptation) | |
| - **Dataset**: 59 high-quality code analysis examples | |
| - **Features**: Quality scores, structured analysis, code improvements | |
| - **Hosting**: Hugging Face Spaces (always online) | |
| ### Model Capabilities | |
| The fine-tuned model provides: | |
| - **Quality Scores**: 1-100 rating for code quality | |
| - **Structured Analysis**: Bugs, Performance, Security sections | |
| - **Code Improvements**: Specific suggestions with examples | |
| - **Professional Output**: Consistent, detailed analysis format | |
| ## 🚀 Quick Start | |
| ### Prerequisites | |
| * Python 3.11 or higher | |
| * API keys for at least one LLM provider: | |
| * OpenAI API Key | |
| * Anthropic API Key | |
| * DeepSeek API Key | |
| * **Hugging Face API Key** (recommended for free usage) | |
| ### Installation | |
| 1. **Clone the repository:** | |
| ```bash | |
| git clone https://github.com/arun3676/ai-code-analyzer.git | |
| cd ai-code-analyzer | |
| ``` | |
| 2. **Create a virtual environment:** | |
| ```bash | |
| python -m venv .venv | |
| source .venv/bin/activate # On Windows: .venv\Scripts\activate | |
| ``` | |
| 3. **Install dependencies:** | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| 4. **Configure environment variables:** | |
| Create a `.env` file in the root directory: | |
| ```env | |
| # API Keys - Replace with your actual API keys | |
| HUGGINGFACE_API_KEY=your_huggingface_api_key_here # Recommended for free usage | |
| OPENAI_API_KEY=your_openai_api_key_here | |
| ANTHROPIC_API_KEY=your_anthropic_api_key_here | |
| DEEPSEEK_API_KEY=your_deepseek_api_key_here | |
| GITHUB_TOKEN=your_github_token_here # Optional, for higher API limits | |
| ``` | |
| **📚 For detailed Hugging Face setup instructions, see: [HUGGINGFACE_SETUP_GUIDE.md](HUGGINGFACE_SETUP_GUIDE.md)** | |
| 5. **Run the application:** | |
| ```bash | |
| # Option 1: Use the startup script (recommended) | |
| python run_app.py | |
| # Option 2: Run directly with Streamlit | |
| python -m streamlit run matrix_final.py --server.port 8501 | |
| ``` | |
| The application will be available at `http://localhost:8501` | |
| ## 📋 Usage | |
| ### Code Analysis | |
| 1. **Upload a file** or **paste your code** in the main panel | |
| 2. **Select a model** from the dropdown (OpenAI, Anthropic, or DeepSeek) | |
| 3. **Choose analysis type**: Code Analysis or Multimodal Analysis | |
| 4. **Click "Analyze Code"** to get comprehensive insights | |
| ### File Upload | |
| - **Drag & drop** code files directly onto the upload area | |
| - **Supported formats**: .py, .js, .java, .cpp, .c, .cs, .go, .rs, .php, .rb, .swift, .kt, .txt | |
| - **File size limit**: 200MB per file | |
| ### Analysis Results | |
| - **Quality Score**: 0-100 rating with color-coded indicators | |
| - **Summary**: Clear description of code functionality | |
| - **Issues & Bugs**: Potential problems identified | |
| - **Improvements**: Actionable suggestions for better code | |
| - **Security**: Security vulnerabilities and concerns | |
| - **Performance**: Optimization recommendations | |
| ## 🏗️ Project Structure | |
| For a detailed explanation of the project structure, architecture, and data flow, please see [PROJECT_STRUCTURE.md](PROJECT_STRUCTURE.md) and [ARCHITECTURE.md](ARCHITECTURE.md). | |
| ``` | |
| ai-code-analyzer/ | |
| ├── .venv/ # Virtual environment directory | |
| ├── analyzer/ # Core analysis engine | |
| │ ├── __init__.py # Package initialization | |
| │ ├── code_analyzer.py # Main analysis engine | |
| │ ├── llm_clients.py # LLM API client implementations | |
| │ ├── prompts.py # Analysis prompt templates | |
| │ └── utils.py # Utility functions | |
| ├── tests/ # Automated tests | |
| │ ├── test_matrix_final.py # Tests for matrix_final.py utilities | |
| │ └── test_prompts.py # Tests for prompt generation | |
| ├── .env # Environment variables (create this) | |
| ├── .gitignore # Git ignore file | |
| ├── ARCHITECTURE.md # Detailed architecture documentation | |
| ├── matrix_final.py # Main Streamlit application | |
| ├── PROJECT_STRUCTURE.md # High-level project structure | |
| ├── README.md # This file | |
| ├── requirements.txt # Python dependencies | |
| ├── run_app.py # Startup script for easy launching | |
| └── TESTING_GUIDE.md # Guide for testing the application | |
| ``` | |
| ## 🔧 Configuration | |
| ### Supported LLM Providers | |
| | Provider | Model | API Key Environment Variable | | |
| | ------------- | ------------------------ | ---------------------------- | | |
| | Hugging Face | Mixtral-8x7B-Instruct | HUGGINGFACE\_API\_KEY | | |
| | OpenAI | GPT-4o-mini | OPENAI\_API\_KEY | | |
| | Anthropic | Claude 3 Haiku | ANTHROPIC\_API\_KEY | | |
| | DeepSeek | DeepSeek Chat | DEEPSEEK\_API\_KEY | | |
| ### Supported Programming Languages | |
| - Python, JavaScript, Java, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin | |
| - **Auto-detection** available for most languages | |
| - **Manual selection** option for specific analysis | |
| ## 🧪 Testing | |
| For detailed instructions on how to test the application, please refer to the [TESTING_GUIDE.md](TESTING_GUIDE.md). | |
| To run the automated tests: | |
| ```bash | |
| pytest | |
| ``` | |
| ## 🚀 Deployment | |
| ### Deploy to Hugging Face Spaces (Recommended) | |
| This project is configured for easy deployment on **Hugging Face Spaces**: | |
| 1. **Fork this repository** to your GitHub account. | |
| 2. **Create a new Space**: Go to [Hugging Face Spaces](https://huggingface.co/spaces/new) and create a new Space. | |
| * Choose "Streamlit" as the Space SDK. | |
| * Select "Public" or "Private" as per your preference. | |
| * Connect your forked GitHub repository. | |
| 3. **Configure Secrets**: In your Hugging Face Space settings, go to "App settings" -> "Secrets". Add your API keys: | |
| * `HUGGINGFACE_API_KEY` (required for Hugging Face models) | |
| * `OPENAI_API_KEY` (optional) | |
| * `ANTHROPIC_API_KEY` (optional) | |
| * `DEEPSEEK_API_KEY` (optional) | |
| * `GITHUB_TOKEN` (optional, for higher GitHub API limits) | |
| 4. **Wait for Deployment**: Hugging Face will automatically detect your `requirements.txt` and `matrix_final.py` and deploy your app. | |
| 5. **Access Your App**: Once deployed, your application will be live on your Hugging Face Space URL. | |
| ### Manual Deployment | |
| If deploying manually, use these settings: | |
| - **Build Command**: `pip install -r requirements.txt` | |
| - **Start Command**: `streamlit run matrix_final.py --server.port=$PORT --server.address=0.0.0.0 --server.headless=true --server.enableCORS=false` | |
| ## 📊 Analysis Output | |
| The tool provides structured analysis including: | |
| - **🎯 Quality Score**: 0-100 rating with visual indicators | |
| - **📋 Summary**: Clear description of code functionality | |
| - **🐛 Issues**: Potential bugs and logical errors | |
| - **💡 Improvements**: Specific actionable suggestions | |
| - **🛡️ Security**: Security vulnerabilities and concerns | |
| - **⚡ Performance**: Optimization opportunities | |
| - **📈 Metrics**: Analysis time, model used, code statistics | |
| ## 🎨 UI Features | |
| - **Matrix Theme**: Dark background with neon green accents | |
| - **Responsive Design**: Works on desktop, tablet, and mobile | |
| - **File Upload**: Drag & drop interface with progress indicators | |
| - **Real-time Analysis**: Live progress updates during analysis | |
| - **Professional Layout**: Clean, organized interface | |
| - **Custom Fonts**: Share Tech Mono and Orbitron for cyberpunk feel | |
| ## 🧪 Development | |
| ### Running Locally | |
| ```bash | |
| # Option 1: Use the startup script (recommended) | |
| python run_app.py | |
| # Option 2: Start the development server directly | |
| python -m streamlit run matrix_final.py --server.port 8501 | |
| # Option 3: With auto-reload for development | |
| python -m streamlit run matrix_final.py --server.port 8501 --server.runOnSave true | |
| ``` | |
| ### Code Structure | |
| - **`matrix_final.py`**: Main Streamlit application with UI and routing | |
| - **`analyzer/`**: Core analysis engine and LLM integrations | |
| - **Custom CSS**: Embedded in the main app for Matrix theme | |
| - **Error Handling**: Comprehensive error handling and user feedback | |
| ## 🤝 Contributing | |
| 1. Fork the repository | |
| 2. Create a feature branch (`git checkout -b feature/amazing-feature`) | |
| 3. Commit your changes (`git commit -m 'Add amazing feature'`) | |
| 4. Push to the branch (`git push origin feature/amazing-feature`) | |
| 5. Open a Pull Request | |
| ## 📝 License | |
| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | |
| ## 🙏 Acknowledgments | |
| * **Streamlit** for the amazing framework | |
| * **OpenAI** for GPT models | |
| * **Anthropic** for Claude | |
| * **DeepSeek** for DeepSeek Coder | |
| * **Render** for seamless deployment | |
| * **Google Fonts** for Share Tech Mono and Orbitron fonts | |
| ## 📞 Support | |
| If you encounter any issues or have questions: | |
| 1. Check the [Issues](https://github.com/arun3676/ai-code-analyzer/issues) page | |
| 2. Create a new issue with detailed information | |
| 3. Contact the maintainers | |
| ## 🔗 Links | |
| - **Live Demo**: *Your Hugging Face Space URL here* | |
| - **Repository**: [github.com/arun3676/ai-code-analyzer](https://github.com/arun3676/ai-code-analyzer) | |
| - **Hugging Face Spaces**: [huggingface.co/spaces](https://huggingface.co/spaces) | |
| --- | |
| **Built with ❤️ by [Arun](https://github.com/arun3676)** |