LLM_Engineering_OLD/week4/community-contributions/ai_docstring_generator

🚀 AI Docstring Generator

An intelligent tool that automatically generates comprehensive docstrings and comments for your code using state-of-the-art AI models (OpenAI GPT, Anthropic Claude, and Google Gemini).

✨ Features

• 🤖 Multi-Model Support: Choose between GPT-4o, Claude Sonnet 4, or Gemini 2.0
• 🌍 Multi-Language Support: Python, JavaScript, Java, C++, Go, and Rust
• ⚡ Real-time Streaming: Watch documentation being generated live
• 📝 Comprehensive Documentation: Generates parameter descriptions, return values, exceptions, and inline comments
• 🎨 Beautiful UI: Clean and intuitive Gradio interface
• 📚 Built-in Examples: Quick start with pre-loaded code examples

🎯 Supported Languages

• Python (PEP 257, Google style)
• JavaScript/TypeScript (JSDoc)
• Java (Javadoc)
• C++ (Doxygen)
• Go (Go conventions)
• Rust (Rust doc comments)

📋 Prerequisites

• Python 3.8 or higher
• API keys for at least one of the following:
  • OpenAI API key
  • Anthropic API key
  • Google API key

🛠️ Installation

1. Clone the repository

git clone {paste-this-repo-link}
cd ai-docstring-generator //navigate to this folder

2. Create a virtual environment (recommended)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies

pip install -r requirements.txt

4. Set up environment variables

Create a .env file in the project root:

OPENAI_API_KEY=sk-your-openai-api-key-here
ANTHROPIC_API_KEY=sk-ant-your-anthropic-api-key-here
GOOGLE_API_KEY=your-google-api-key-here

Note: You only need the API key(s) for the model(s) you plan to use.

🚀 Usage

1. Run the application

python docstring_generator.ipynb

2. Access the interface

   • The app will automatically open in your default browser

3. Generate documentation

   • Select your programming language
   • Choose an AI model (GPT, Claude, or Gemini)
   • Paste your code or load an example
   • Click "✨ Generate Docstrings"
   • Copy the documented code!

📖 Example

Input (Python):

def calculate_pi(iterations, param1, param2):
    result = 1.0
    for i in range(1, iterations+1):
        j = i * param1 - param2
        result -= (1/j)
        j = i * param1 + param2
        result += (1/j)
    return result

Output:

def calculate_pi(iterations, param1, param2):
    """
    Calculate an approximation of pi using the Leibniz formula.
    
    Args:
        iterations (int): Number of iterations to perform in the calculation.
                         Higher values increase accuracy but take longer.
        param1 (int): First parameter for the calculation formula (typically 4).
        param2 (int): Second parameter for the calculation formula (typically 1).
    
    Returns:
        float: Approximation of pi divided by 4. Multiply by 4 to get pi.
    
    Note:
        This uses the Leibniz formula: π/4 = 1 - 1/3 + 1/5 - 1/7 + ...
        Convergence is slow; many iterations needed for good accuracy.
    """
    result = 1.0
    for i in range(1, iterations+1):
        # Calculate denominator for negative term
        j = i * param1 - param2
        result -= (1/j)
        # Calculate denominator for positive term
        j = i * param1 + param2
        result += (1/j)
    return result

🔑 Getting API Keys

OpenAI API Key

1. Visit platform.openai.com
2. Sign up or log in
3. Go to API Keys section
4. Create a new API key

Anthropic API Key

1. Visit console.anthropic.com
2. Sign up or log in
3. Go to API Keys
4. Generate a new key

Google API Key

1. Visit Google AI Studio
2. Sign in with Google account
3. Create an API key

📁 Project Structure

ai-docstring-generator/
│
├── docstring_generator.py   # Main application file
├── requirements.txt          # Python dependencies
├── README.md                # Project documentation

🎨 Customization

You can customize the documentation style by modifying the system_prompt_for_docstring() function in docstring_generator.py.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📝 License

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

🐛 Troubleshooting

Common Issues

Issue: TypeError: Client.__init__() got an unexpected keyword argument 'proxies'

• Solution: Update packages: pip install --upgrade anthropic httpx

Issue: API key not found

• Solution: Ensure your .env file is in the project root and contains valid API keys

Issue: Model not responding

• Solution: Check your API key is valid and you have available credits/quota

Issue: Port 7860 already in use

• Solution: Change the port in the ui.launch() call: server_port=7861

🔮 Future Enhancements

• Support for more AI models (Llama, Mistral, etc.)
• Batch processing for multiple files
• Support for more programming languages
• Custom documentation style templates
• Integration with IDEs (VS Code, PyCharm)
• API endpoint for programmatic access

📧 Contact

For questions or suggestions, please open an issue on GitHub. Or mail me at udayslathia16@gmail.com

🙏 Acknowledgments

• OpenAI for GPT models
• Anthropic for Claude models
• Google for Gemini models
• Gradio for the amazing UI framework

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Made with ❤️ for developers who value good documentation

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⭐ Star History

If you find this project useful, please consider giving it a star!