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Local CV-JD Evaluator 🔍

https://orand-advisors.com

A privacy-first, standalone AI-powered CV and Job Description analysis tool that runs entirely offline using LM Studio.

License: MIT GitHub release Maintenance

🚀 Features

  • Complete Privacy: All analysis happens locally - no data leaves your computer
  • No API Keys Required: Uses LM Studio for local AI model inference
  • Comprehensive Analysis:
    • Job Description Requirements Analysis
    • CV-Job Fit Assessment
    • Skills Gap Identification
    • CV Optimization Recommendations
    • Corporate Jargon Translation
  • Multiple Export Formats: TXT, DOCX, JSON
  • User-Friendly Interface: Clean, modern web interface
  • Standalone: Single HTML file - no installation required

🔧 Prerequisites

  1. LM Studio: Download and install from lmstudio.ai
  2. Compatible AI Model: Any chat/completion model compatible with OpenAI API format
  3. Modern Web Browser: Chrome, Firefox, Safari, or Edge

🏗️ Setup Instructions

Step 1: Install LM Studio

  1. Download LM Studio from lmstudio.ai
  2. Install and launch the application
  3. Download a compatible model (recommended: Llama 2 7B or similar)

Step 2: Start LM Studio Server

  1. In LM Studio, go to the "Local Server" tab
  2. Load your chosen model
  3. Start the server (default: http://localhost:1234)
  4. Ensure the server is running before using the tool

Step 3: Run the CV-JD Evaluator

  1. Download standalone_cv_jd_evaluator.html
  2. Open the file in your web browser
  3. Click "Test Connection" to verify LM Studio connectivity
  4. Select your model from the dropdown
  5. Start analyzing!

📖 Usage Guide

Basic Workflow

  1. Configure Connection: Test and confirm LM Studio connection
  2. Select Model: Choose from available models in the dropdown
  3. Input Data:
    • Job Description (required): Paste the job posting
    • CV/Resume (optional): Paste your CV for matching analysis
    • Additional Focus (optional): Specify particular areas of interest
  4. Choose Analysis Options:
    • ✅ JD Requirements Analysis
    • ✅ CV Fit Assessment (requires CV input)
    • ✅ Skills Gap Identification (requires CV input)
    • ✅ CV Optimization (requires CV input)
    • ✅ Corporate Jargon Translation
  5. Analyze: Click "Analyze CV-Job Match"
  6. Export Results: Save as TXT, DOCX, or JSON

Analysis Types

📋 JD Requirements Analysis

  • Technical skills breakdown
  • Soft skills requirements
  • Experience and qualifications
  • Role responsibilities analysis
  • Red flags and concerns identification

🎯 CV Fit Assessment

  • Technical skills matching
  • Experience alignment scoring
  • Soft skills evidence evaluation
  • Overall compatibility percentage

🔍 Skills Gap Identification

  • Missing technical skills
  • Experience shortfalls
  • Recommended certifications
  • Improvement suggestions

✨ CV Optimization

  • Keyword incorporation advice
  • Section reorganization tips
  • Achievement highlighting
  • Interview preparation questions

🏢 Corporate Jargon Translation

  • Buzzword decoding
  • Risk assessment (scope creep, burnout potential)
  • Realistic expectation setting
  • Interview clarification questions

🔒 Privacy & Security

  • 100% Local Processing: All analysis happens on your computer
  • No Data Transmission: Nothing is sent to external servers
  • No API Keys: No cloud services or external dependencies
  • Offline Capable: Works without internet connection (after initial model download)

🛠️ Technical Details

System Requirements

  • Operating System: Windows, macOS, or Linux
  • RAM: Minimum 8GB (16GB+ recommended for larger models)
  • Storage: ~4-20GB for AI models (varies by model size)
  • Browser: Modern browser with JavaScript enabled

Supported Model Types

  • LLaMA: All variants (7B, 13B, 70B)
  • Mistral: 7B and larger
  • Code Llama: For technical analysis
  • Custom Models: Any model compatible with OpenAI API format

File Structure

local_jd_cv_evaluator/
├── standalone_cv_jd_evaluator.html    # Main application file
├── README.md                          # This documentation
├── LICENSE                           # MIT license
├── CONTRIBUTING.md                   # Contribution guidelines
├── CHANGELOG.md                      # Version history
└── .github/                         # GitHub templates and workflows
    ├── ISSUE_TEMPLATE/
    └── workflows/

🚧 Troubleshooting

Common Issues

"LM Studio: Not Connected" Error

  • Ensure LM Studio is running
  • Verify the local server is started
  • Check the base URL (default: http://localhost:1234)
  • Confirm a model is loaded in LM Studio

"No Models Found" Message

  • Load a model in LM Studio first
  • Click "Refresh Models" button
  • Restart LM Studio if necessary

Analysis Takes Too Long

  • Use smaller models for faster results
  • Reduce input text length
  • Check LM Studio performance settings

Export Features Not Working

  • Ensure modern browser with JavaScript enabled
  • Check popup blockers for download restrictions
  • For DOCX export, verify html-docx-js library loads correctly

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Setup

  1. Fork this repository
  2. Make your changes to standalone_cv_jd_evaluator.html
  3. Test thoroughly with different models and inputs
  4. Submit a pull request with detailed description

Reporting Issues

Please use the issue templates when reporting bugs or requesting features.

📄 License

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

🙏 Acknowledgments

  • LM Studio: For providing excellent local model inference
  • OpenAI: For the standardized API format
  • FontAwesome: For icons
  • Google Fonts: For Inter font family
  • html-docx-js: For DOCX export functionality

📞 Support

🔄 Version History

See CHANGELOG.md for detailed version history.

🌟 Star History

If you find this tool useful, please consider starring the repository!

Made with ❤️ for privacy-conscious professionals