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Contributing to Local CV-JD Evaluator

First off, thank you for considering contributing to Local CV-JD Evaluator! 🎉

The following is a set of guidelines for contributing to this project. These are mostly guidelines, not rules. Use your best judgment, and feel free to propose changes to this document in a pull request.

Table of Contents

Code of Conduct

This project and everyone participating in it is governed by our commitment to creating a welcoming, inclusive, and harassment-free environment for everyone. By participating, you are expected to uphold these standards.

How Can I Contribute?

🐛 Reporting Bugs

Before creating bug reports, please check existing issues to avoid duplicates. When you create a bug report, include as many details as possible:

  • Use a clear and descriptive title
  • Describe the exact steps to reproduce the problem
  • Provide specific examples (input text, model used, etc.)
  • Describe the behavior you observed and what you expected
  • Include screenshots if applicable
  • Specify your environment: OS, browser, LM Studio version, model used

💡 Suggesting Enhancements

Enhancement suggestions are welcome! Please:

  • Use a clear and descriptive title
  • Provide a step-by-step description of the suggested enhancement
  • Explain why this enhancement would be useful
  • Consider the project's scope (privacy-first, standalone, offline-capable)

📝 Improving Documentation

Documentation improvements are always appreciated:

  • Fix typos or clarify confusing sections
  • Add missing information or examples
  • Improve setup instructions
  • Add troubleshooting guides

💻 Code Contributions

We welcome code contributions! Areas that need help:

  • UI/UX Improvements: Better responsive design, accessibility features
  • Analysis Features: New analysis types or improved prompts
  • Export Functionality: Additional export formats or better formatting
  • Performance: Optimization for large inputs or slower devices
  • Browser Compatibility: Ensuring compatibility across different browsers
  • Error Handling: Better error messages and recovery

Development Setup

Prerequisites

  1. Text Editor/IDE: VS Code, Sublime Text, or any editor with HTML/CSS/JavaScript support
  2. LM Studio: For testing the application
  3. Modern Browser: For testing functionality
  4. Git: For version control

Local Development

  1. Fork and Clone

    git clone https://github.com/yourusername/local_jd_cv_evaluator.git
cd local_jd_cv_evaluator

  2. Open the HTML File

    • Open standalone_cv_jd_evaluator.html in your browser
    • Or use a local server for development: 
      # Python 3
python -m http.server 8000

# Python 2
python -m SimpleHTTPServer 8000

# Node.js (with http-server)
npx http-server

  3. Setup LM Studio

    • Install and configure LM Studio
    • Load a test model
    • Start the local server

  4. Test Your Changes

    • Test all functionality thoroughly
    • Try different models and input types
    • Verify export functions work correctly
    • Test error scenarios

Coding Guidelines

HTML Structure

  • Use semantic HTML elements where appropriate
  • Maintain accessibility standards (alt text, ARIA labels)
  • Keep the single-file structure intact

CSS Standards

  • Use CSS custom properties (variables) for consistency
  • Follow the existing naming convention
  • Ensure responsive design principles
  • Test across different screen sizes

JavaScript Guidelines

  • Use ES6+ features consistently
  • Follow existing code style and patterns
  • Add comprehensive error handling
  • Include JSDoc comments for new functions
  • Maintain the class-based architecture

Code Style

// ✅ Good
async function analyzeText(inputText, options) {
    if (!inputText?.trim()) {
        throw new Error('Input text is required');
    }
    
    try {
        const result = await this.processAnalysis(inputText, options);
        return result;
    } catch (error) {
        console.error('Analysis failed:', error);
        throw error;
    }
}

// ❌ Avoid
function analyzeText(inputText,options){
    var result=this.processAnalysis(inputText,options);
    return result;
}

Performance Considerations

  • Optimize for large text inputs
  • Implement proper loading states
  • Use efficient DOM manipulation
  • Consider memory usage with large responses

Privacy & Security

  • Never add external tracking or analytics
  • Ensure all processing remains local
  • Don't log sensitive user data
  • Validate and sanitize user inputs

Pull Request Process

Before Submitting

  1. Test thoroughly on multiple browsers and screen sizes
  2. Verify LM Studio integration works correctly
  3. Check for console errors and fix any issues
  4. Update documentation if your changes affect usage
  5. Follow the existing code style and patterns

Pull Request Template

When submitting a pull request, please:

  1. Use a clear title that describes the change
  2. Reference related issues using GitHub's syntax (fixes #123)
  3. Describe your changes in detail
  4. Include screenshots for UI changes
  5. List testing steps you performed

Review Process

  1. Automated checks will run (when available)
  2. Manual review by maintainers
  3. Testing of functionality
  4. Discussion and potential revision requests
  5. Merge once approved

Issue Reporting

Bug Reports

Use the bug report template and include:

  • Environment details (OS, browser, LM Studio version)
  • Steps to reproduce the issue
  • Expected vs actual behavior
  • Screenshots or error messages
  • Input examples that caused the issue

Feature Requests

Use the feature request template and include:

  • Clear description of the proposed feature
  • Use case and benefits
  • Mockups or examples if applicable
  • Implementation considerations

Questions and Discussions

For questions about usage or general discussions:

  • Use GitHub Discussions for broader topics
  • Use Issues for specific problems or requests
  • Check existing issues and discussions first

Recognition

Contributors will be recognized in the project documentation. Significant contributors may be invited to become maintainers.

Getting Help

If you need help with contributing:

  • Check existing issues and discussions
  • Create a new discussion for questions
  • Reach out through GitHub issues for specific problems

Development Tips

Testing Different Scenarios

Always test with:

  • Various model sizes (7B, 13B, etc.)
  • Different input lengths (short, medium, very long)
  • Edge cases (empty inputs, special characters)
  • Different browsers and devices
  • Network scenarios (offline mode)

Common Pitfalls

  • CORS issues: Test with actual file:// URLs, not just local servers
  • Model compatibility: Different models may respond differently
  • Performance: Large inputs can cause browser slowdowns
  • Memory management: Clean up resources properly

Useful Resources

Thank You! 🙏

Your contributions help make this tool better for everyone while maintaining our commitment to privacy and offline functionality.

Happy contributing! 🚀