Resume Job Matcher

Overview

Resume Job Matcher is a Python script that automates the process of matching resumes to a job description using AI. It leverages the Anthropic Claude API or OpenAI's GPT API to analyze resumes and provide a match score along with personalized email responses for candidates.

Features

• 🔥 Comprehensive Resume Processing

  • Multiple outputs: PDF and Markdown generation
  • Standardization for fair evaluation
  • Font customization (sans-serif, serif, monospace)
  • Command-line options for flexibility

• 🧠 Advanced AI-Powered Analysis

  • Resume-job comparison using Claude/GPT API
  • Dual AI support with runtime selection
  • Efficient model interaction
  • Structured data handling with Pydantic

• 📊 In-depth Evaluation & Scoring

  • Smart parsing with PyPDF2
  • Multi-factor assessment: skills, experience, education, certifications
  • Visual and content-based quality assessment
  • 🚩 Red flag detection in critical areas
  • Detailed scoring with emoji and color-coded results

• 📈 Comprehensive Analytics & Reporting

  • Statistical insights: top, average, median, standard deviation scores
  • Candidate distribution summary
  • Match analysis with improvement suggestions
  • Job description optimization recommendations

• 🌐 Enhanced Candidate Profiling

  • Website integration for improved matching
  • Personalized email generation

• 🛠️ Robust System Management

  • Advanced logging and error handling
  • Improved user feedback and reliability

Usage

To run the script with the new features:

python resume_matcher.py [--sans-serif|--serif|--mono] [--pdf] [job_desc_file] [pdf_folder]

• Use --sans-serif, --serif, or --mono to select a font preset.
• Use --pdf to generate PDF versions of unified resumes.
• Optionally specify custom paths for the job description file and PDF folder.

Customization

Adjust Logging Level

Modify the logging level at the beginning of the script:

logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

Available levels: DEBUG, INFO, WARNING, ERROR, CRITICAL.

Change Scoring Model

To change the AI model used, update the model parameter in the match_resume_to_job function:

message = client.messages.create(
    model="claude-3-5-sonnet-20240620",
    ...
)

Modify AI Provider

To switch between Anthropic and OpenAI APIs, modify the choose_api function call at the beginning of the script:

def choose_api():
    global chosen_api
    prompt = "Use OpenAI API instead of Anthropic? [y/N]: "
    choice = input(colored(prompt, "cyan")).strip().lower()
    
    if choice in ["y", "yes"]:
        chosen_api = "openai"
    else:
        chosen_api = "anthropic"

Adjust AI Model

To change the AI model used, update the model parameter in the talk_fast function:

response = client.chat.completions.create(
    model="gpt-4o",  # Change this to the desired model
    ...
)

Score Calculation

The final score for each resume is calculated using a combination of two factors:

1. AI-Generated Match Score (75% weight): This score is based on how well the resume matches the job description, considering factors such as skills, experience, education, and other relevant criteria.

2. Resume Quality Score (25% weight): This score assesses the visual appeal and clarity of the resume itself, including formatting, layout, and overall presentation.

The calculation process is as follows:

1. The AI-generated match score and the resume quality score are both normalized to a 0-100 scale.
2. A weighted average is calculated: (AI_Score * 0.75 + Quality_Score * 0.25)
3. The result is clamped to ensure it falls within the 0-100 range.

This combined approach ensures that both the content relevance and the presentation quality of the resume are taken into account in the final score.

Modify Scoring Criteria

Adjust the scoring logic in the match_resume_to_job function's prompt as needed to better fit your specific requirements.

Troubleshooting

Common Issues

• No Resumes Found: Ensure that resume PDFs are placed in the correct directory (src by default).
• Job Description Not Found: Confirm that job_description.txt exists in the script's directory or provide the correct path.
• API Key Errors: Verify that the CLAUDE_API_KEY environment variable is set correctly.
• Dependency Errors: Install all required Python packages using pip.

Adjusting Timeouts and Retries

If you experience network-related errors when fetching personal websites, you may adjust the timeout parameter in the check_website function.

response = requests.get(url, timeout=10)

Best Practices

• Data Privacy: Ensure that all candidate data is handled in compliance with relevant data protection laws and regulations.
• API Usage: Be mindful of API rate limits and usage policies when using the Anthropic Claude API.

Contributing

We welcome contributions! Please follow these steps:

1. Fork the Repository: Create your own fork on GitHub.
2. Create a Feature Branch: Work on your feature or fix in a new branch.
3. Submit a Pull Request: Once your changes are ready, submit a pull request for review.

Acknowledgments

• Anthropic Claude API: For providing advanced AI capabilities.

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Enjoy using the Resume Job Matcher script to streamline your recruitment process!

Python Packages

The following Python packages are required for this project:

• PyPDF2: For extracting text from PDF resumes
• anthropic: To interact with the Anthropic Claude API for AI-powered analysis
• tqdm: For displaying progress bars during processing
• termcolor: To add colored output in the console
• json5: For parsing JSON-like data with added flexibility
• requests: To make HTTP requests for fetching website content
• beautifulsoup4: For parsing HTML content from personal websites
• openai: To interact with the OpenAI API for AI-powered analysis
• pydantic: For data validation and settings management using Python type annotations

To install these packages, you can use pip:

pip install PyPDF2 anthropic openai tqdm termcolor json5 requests beautifulsoup4 pydantic

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