💼 Resume Readiness Checker

An AI-powered web application that analyzes your resume and provides actionable feedback to improve your job application success. Built with Streamlit and powered by OpenAI's GPT-4.

🌟 Features

• 📄 PDF Resume Upload: Support for PDF resume files with intelligent text extraction
• 🤖 AI-Powered Analysis: Advanced resume analysis using OpenAI's GPT-4 model
• 🎯 Job-Specific Feedback: Tailored recommendations based on target job role and description
• 🔑 Flexible API Key Input: Support for both environment variables and secure frontend input
• 📊 Comprehensive Evaluation: Analysis across multiple dimensions:
  • Content Quality & Impact
  • Skills Alignment
  • Experience Presentation
  • ATS Compatibility
  • Actionable Improvement Areas
• 💾 Downloadable Reports: Export your analysis results for future reference
• 📈 Usage Statistics: Track token usage and analysis metrics
• 🔒 Secure Processing: Local file processing with API-based analysis
• ⚡️ Lightweight Model: Using gpt-4o-mini to keep the analysis cost efficient

🚀 Quick Start

Prerequisites

• Python 3.12 or higher
• OpenAI API Key (can be provided via environment variable or frontend input)

Installation

1. Clone the repository

   git clone https://github.com/rohanpandavv/resumereadiness.git
   cd resumereadiness

2. Set up virtual environment (recommended)

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

3. Install dependencies

   pip install -r requirements.txt

   Or if using uv:

   uv sync

4. Configure OpenAI API Key

   Option 1: Environment Variable (Recommended)

   Create a .env file in the root directory:

   # Optional (will prompt for frontend input if not provided)
   OPENAI_API_KEY=your_openai_api_key_here
   
   # Optional (default values shown)
   STREAMLIT_SERVER_PORT=8501
   STREAMLIT_SERVER_HEADLESS=false

   Option 2: Frontend Input

   If no environment variable is found, the app will prompt you to enter your API key directly in the web interface. This is perfect for:

   • Streamlit Cloud deployments
   • Sharing the app with others
   • Testing without local configuration

5. Run the application

   streamlit run main.py

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

🖥️ Usage

1. Enter API Key (if not set via environment variable): Securely input your OpenAI API key
2. Upload Resume: Select and upload your resume in PDF format (max 5MB)
3. Specify Job Details (Optional):
   • Enter the target job role you're applying for
   • Paste the job description for more targeted feedback
4. Analyze: Click the "🔍 Analyze Resume" button
5. Review Results: Get comprehensive AI-powered feedback
6. Download Report: Save your analysis for future reference

📋 Dependencies

• Streamlit (≥1.45.1) - Web application framework
• OpenAI (≥1.82.0) - AI-powered analysis
• PyPDF2 (≥3.0.1) - PDF text extraction
• python-dotenv (≥1.1.0) - Environment variable management

🔧 Configuration

Environment Variables

Create a .env file with the following variables:

# Optional (will prompt for frontend input if not provided)
OPENAI_API_KEY=your_openai_api_key_here

File Upload Limits

• Maximum file size: 5MB
• Supported formats: PDF only
• Text extraction: Automatic with error handling for corrupted pages

🎯 Analysis Features

The AI provides feedback on six key areas:

1. Content Quality & Impact - How well achievements are showcased
2. Skills Alignment - Relevance to target role
3. Experience Presentation - Use of quantifiable results
4. ATS Compatibility - Applicant Tracking System optimization
5. Areas for Improvement - Specific, actionable recommendations
6. Job Match Analysis - Alignment with provided job requirements

📊 Example Output

The analysis provides structured feedback including:

• ✅ Strengths: What's working well in your resume
• ⚠️ Areas for Improvement: Specific issues to address
• 🎯 Recommendations: Actionable steps to enhance your resume
• 📈 ATS Optimization: Tips for better applicant tracking system compatibility

🛠️ Development

Project Structure

resumereadiness/
├── main.py              # Main Streamlit application
├── pyproject.toml       # Project configuration and dependencies
├── uv.lock             # Dependency lock file
├── .env                # Environment variables (create this)
├── .python-version     # Python version specification
└── README.md           # Project documentation

Running in Development Mode

# Install development dependencies
uv sync --dev

# Run with auto-reload
streamlit run main.py --server.runOnSave true

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

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

🔐 Privacy & Security

• Local Processing: PDF text extraction happens locally
• API Usage: Only extracted text is sent to OpenAI for analysis
• No Storage: No resume data is permanently stored
• Secure API Key Handling:
  • Environment variables are preferred for local development
  • Frontend input uses password-masked fields
  • API keys are session-only and never stored permanently
• Session Security: All data processing happens within your browser session

🆘 Troubleshooting

Common Issues

Issue: "Please enter your OpenAI API key to use the resume analyzer"

• Solution: Either set OPENAI_API_KEY in your .env file or enter it directly in the web interface when prompted

Issue: "Error analyzing resume" (API key related)

• Solution: Verify your API key is valid and has sufficient credits. You can test it at OpenAI Platform

Issue: "Could not extract text from PDF"

• Solution: Ensure your PDF is not image-based or encrypted

Issue: "File size exceeds limit"

• Solution: Compress your PDF or use a smaller file (max 5MB)

Issue: "Empty or unreadable text"

• Solution: Try converting your resume to a text-searchable PDF

Getting Help

If you encounter any issues:

1. Check the troubleshooting section above
2. Review the Issues page
3. Create a new issue with detailed description

🙏 Acknowledgments

• OpenAI for providing the GPT-4 API
• Streamlit team for the excellent web framework
• PyPDF2 contributors for PDF processing capabilities

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Made with ❤️ for job seekers worldwide