AIResume - AI-Powered Resume Tailoring

AIResume is an intelligent resume tailoring application that uses AI to optimize your resume for specific job descriptions. It analyzes the match between your resume and a job posting, then intelligently modifies your resume to improve the match score while preserving dates, structure, and truthfulness.

🌟 Features

• 📤 Multi-Format Support: Upload resumes and job descriptions in PDF, DOCX, or TXT format
• 🔍 Match Score Analysis: Calculate detailed match scores between resume and job description
• 🤖 AI-Powered Tailoring: Uses OpenRouter AI (Claude, GPT, LLaMA) to intelligently rewrite bullet points
• 📊 Before/After Comparison: See your match score improvement side-by-side
• ✅ Smart Preservation: Keeps all dates, personal info, and overall structure intact
• 🎯 Targeted Modifications: Tailors only the most recent 1-2 projects
• ⬇️ Multiple Export Formats: Download tailored resume as PDF or DOCX
• 📝 Change Summary: Detailed explanation of what was modified and why

🎯 How It Works

1. Upload Your Resume: PDF, DOCX, or TXT format
2. Provide Job Description: Upload file or paste text
3. Analyze Match: See your current match score (typically 70-85%)
4. Tailor Resume: AI optimizes your resume for the job
5. Download: Get your tailored resume in PDF or DOCX format

The AI modifies only job responsibilities (bullet points) in your most recent 1-2 projects while:

• Preserving all dates and date ranges
• Maintaining bullet point count (±1)
• Keeping personal information unchanged
• Incorporating relevant keywords from the job description
• Adding quantifiable achievements where possible

📋 Prerequisites

• Python 3.11 or higher
• macOS, Linux, or Windows
• OpenRouter API Key (supports Claude, GPT, LLaMA, and more)

🚀 Installation

1. Clone the Repository

cd /Users/Sri/projects
git clone https://github.com/sthama121-del/AIResume.git
cd AIResume

2. Create Virtual Environment

python3 -m venv venv
source venv/bin/activate  # On macOS/Linux
# OR
venv\Scripts\activate  # On Windows

3. Install Dependencies

pip install -r requirements.txt

4. Set Up Environment Variables

Create a .env file in the project root with your OpenRouter API key:

OPENROUTER_API_KEY=your_openrouter_api_key_here

Note: The .env file is excluded from Git via .gitignore to protect your API key.

To get your API key:

1. Visit OpenRouter
2. Sign up/login and create an API key
3. Add the key to your .env file

🎮 Usage

Running the Application

streamlit run app.py

The application will open in your default browser at http://localhost:8501

Using the Interface

1. Upload Resume (left column)

   • Click "Browse files" or drag and drop
   • Supported formats: PDF, DOCX, TXT

2. Provide Job Description (right column)

   • Option 1: Upload file
   • Option 2: Paste text directly

3. Analyze Match Score

   • Click "🔍 Analyze Match Score"
   • View overall match percentage
   • See matched and missing skills

4. Tailor Resume

   • Click "✨ Tailor Resume to Job Description"
   • Wait 30-60 seconds for AI processing
   • Review the improved match score

5. Download Tailored Resume

   • Download as DOCX (editable)
   • Download as PDF (print-ready)

Configuration Options (Sidebar)

• Select AI Model: Choose from Claude 3.5 Sonnet, GPT-4, GPT-3.5, or LLaMA
• Projects to Tailor: Set how many recent projects to modify (1-3)

📁 Project Structure

AIResume/
├── app.py                        # Streamlit frontend application
├── config.py                     # Configuration and environment setup
├── requirements.txt              # Python dependencies
├── .env                          # Environment variables (API keys)
├── .gitignore                    # Git ignore rules
├── README.md                     # This file
├── backend/
│   ├── __init__.py              # Package initialization
│   ├── file_parser.py           # Extract text from PDF/DOCX/TXT
│   ├── resume_analyzer.py       # Calculate match scores
│   ├── resume_tailor.py         # AI-powered resume tailoring
│   └── document_generator.py    # Generate PDF/DOCX outputs
└── uploads/                      # Temporary file storage (gitignored)

🔧 Configuration

Changing AI Models

Edit config.py to modify the default model:

DEFAULT_MODEL = "anthropic/claude-3.5-sonnet"  # Or any OpenRouter model

Available models:

• anthropic/claude-3.5-sonnet (recommended)
• openai/gpt-4-turbo
• openai/gpt-3.5-turbo
• meta-llama/llama-3.1-70b-instruct

Adjusting Tailoring Parameters

In config.py:

MAX_PROJECTS_TO_TAILOR = 2           # Number of recent projects to modify
BULLET_VARIATION_ALLOWED = 1         # Allow +1 or -1 bullets
TARGET_MATCH_SCORE_MIN = 77          # Minimum target score
TARGET_MATCH_SCORE_MAX = 95          # Maximum realistic score

📊 Match Score Breakdown

The match score is calculated using:

• 60% Technical Skills Match: Programming languages, frameworks, tools, technologies
• 40% General Keywords Match: Job-specific terminology, domain knowledge, soft skills

Target scores:

• 70-75%: Basic match
• 77-86%: Good match (typical result)
• 87-95%: Excellent match (achievable with straightforward requirements)
• 95%+: Rare (only for very specific JDs)

🛠️ Troubleshooting

API Key Issues

Error: "OPENROUTER_API_KEY not found"

Solution: Ensure .env file exists in the project root with:

OPENROUTER_API_KEY=your_key_here

File Upload Issues

Error: "Unsupported file format"

Solution: Ensure files are in PDF, DOCX, or TXT format

PDF Extraction Issues

Error: "Could not extract text from PDF"

Solution: Try these formats in order:

1. Save as text-based PDF (not scanned image)
2. Convert to DOCX
3. Copy text and paste as TXT

Low Match Scores

If initial match score is very low (<50%):

• Ensure job description is complete
• Check that resume contains relevant technical skills
• Verify resume format is being parsed correctly

🤝 Contributing

Contributions are welcome! To contribute:

1. Fork the repository
2. Create a 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.

🙏 Acknowledgments

• OpenRouter for providing unified LLM API access
• Streamlit for the amazing web framework
• Anthropic for Claude AI
• OpenAI for GPT models

📧 Contact

For questions, issues, or suggestions:

• GitHub Issues: github.com/sthama121-del/AIResume/issues
• GitHub: @sthama121-del

🚀 Future Enhancements

Planned features:

• Multi-language support
• Resume templates library
• Cover letter generation
• ATS compatibility checker
• Batch processing for multiple job descriptions
• Resume version history
• LinkedIn profile optimization
• Interview preparation based on tailored resume

📈 Version History

• v1.0.0 (2024-10) - Initial release
  • Multi-format file support
  • AI-powered tailoring with OpenRouter
  • Match score analysis
  • PDF/DOCX export
  • Professional Streamlit UI

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