Grosbeak: AI-Powered Resume Customizer

Overview

This project is an AI-powered resume customization system that tailors a candidate's resume to a specific job description. It utilizes multiple data sources, including the candidate's existing resume, LinkedIn profile, and GitHub profile, to create a comprehensive and tailored resume.

Features

• Asynchronous processing for efficient data gathering and resume generation
• Integration with OpenAI's GPT models for intelligent resume customization
• Web scraping capabilities for job descriptions and LinkedIn profiles
• GitHub profile analysis for additional context
• Multiple AI agents working in parallel:
  • ExistingResumeAgent: Tailors the existing resume to the job description
  • LinkedInAgent: Creates a resume based on LinkedIn profile and job description
  • AggregatorAgent: Combines and refines the output from other agents
• Markdown output format for easy editing and conversion

Prerequisites

• Python 3.10+
• Poetry (for dependency management)
• Logfire (for logging)

Setup

1. Clone the repository:

   git clone https://github.com/JoshuaOliphant/grosbeak.git
   cd grosbeak
   

2. Install dependencies using Poetry:

   poetry install
   

3. Set up environment variables: Create a .env file in the project root and add the following:

   OPENAI_API_KEY=your_openai_api_key
   SERPER_API_KEY=your_serper_api_key
   GITHUB_API_KEY=your_github_api_key
   LOGFIRE_TOKEN=your_logfire_token
   

Usage

1. Prepare your input files:

   • Save your existing resume as a Markdown file (e.g., existing_resume.md)

2. Run the script:

   uvicorn src.main:app --reload
   

3. When prompted, enter the following information:

   • Job posting URL
   • Your LinkedIn profile URL
   • Path to your existing resume file
   • Your GitHub profile URL (optional)

4. The script will process the information and generate a customized resume in Markdown format.

5. Find the output resume in the file specified (default: customized_resume.md).

Configuration

You can modify the following parameters in the main.py file:

• resume_file_path: Path to your existing resume file
• output_file_path: Path where the customized resume will be saved

How It Works

1. The system gathers information from multiple sources:

   • Scrapes the job description from the provided URL
   • Fetches and parses the LinkedIn profile
   • Reads the existing resume file
   • Retrieves GitHub profile information (if provided)

2. Three AI agents process the information concurrently:

   • ExistingResumeAgent tailors the existing resume to the job description
   • LinkedInAgent creates a resume based on the LinkedIn profile and job description
   • AggregatorAgent combines and refines the output from the other two agents

3. The final, customized resume is generated in Markdown format and saved to a file.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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

Acknowledgements

• OpenAI for providing the GPT models
• Serper for web scraping capabilities
• GitHub for API access to user profiles