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Resume Analysis Wiki

Welcome to the Resume Analysis project wiki! This documentation will help you understand, set up, and use the Resume Analysis tool effectively.

Overview

Resume Analysis is a powerful Python-based application designed to streamline the resume review process. It automatically extracts and analyzes information from PDF and DOCX resumes using Google's Gemini Large Language Models (LLMs). The system features a flexible plugin architecture that makes it easy to extend its functionality.

Key Features

• Plugin-Based Architecture: Extend functionality by adding new plugins
• Multiple Resume Formats: Support for PDF and DOCX files
• Comprehensive Information Extraction:
  • Basic profile information
  • Skills analysis
  • Education history
  • Work experience
  • Years of experience calculation
• Efficient Processing:
  • Concurrent processing of multiple aspects
  • Structured JSON output
  • Token usage tracking and optimization
• Robust Logging:
  • Separate log files for different purposes
  • Automatic log rotation
  • Configurable log retention

Quick Start

1. Clone the repository
2. Set up your environment:

   python -m venv .venv
   source .venv/bin/activate  # Linux/Mac
   .venv\Scripts\activate     # Windows
   pip install -r requirements.txt

3. Configure your environment:

   cp .env.example .env
   # Edit .env with your API keys and preferences

4. Process resumes:

   python main.py

Documentation Sections

• Installation & Setup - Detailed setup instructions
• User Guide - How to use the tool effectively
• Plugin System - Understanding and extending the plugin architecture
• Technical Documentation - Internal implementation details
• Examples & Tutorials - Practical usage examples
• Contributing - How to contribute to the project
• FAQ & Troubleshooting - Common issues and solutions

Getting Help

• Check the FAQ & Troubleshooting page for common issues
• Review the Examples & Tutorials for usage patterns
• Open an issue on GitHub for bug reports or feature requests
• Join our community discussions

License

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