ResuLLMe is a prototype application that leverages Large Language Models (LLMs) to help job candidates improve their résumés. It acts as a smart career advisor, identifying common mistakes and enhancing résumés according to established guidelines. The project is aimed at job seekers looking to optimize their application materials.

How It Works

ResuLLMe processes résumés in PDF or Word format using either OpenAI or Gemini LLMs. The core functionality involves improving the résumé content based on best practices, converting it to the JSON Resume format, and then rendering this structured data into a new PDF using LaTeX. This multi-step process aims to provide a polished and compliant final document.

Quick Start & Requirements

• Docker: docker-compose up -d (available at https://localhost:8501/)
• Native:
  • Install Python dependencies: pip install -r requirements.txt
  • Install LaTeX packages: xargs sudo apt install -y < packages.txt
  • Run: streamlit run src/Main.py
• Prerequisites: Python, Docker, LaTeX.

Highlighted Details

• Supports both OpenAI and Gemini LLMs for résumé enhancement.
• Converts résumés to JSON Resume format.
• Renders enhanced résumés to PDF using LaTeX.
• Live demo available at https://resullme.streamlit.app/.

Maintenance & Community

The project welcomes contributions, particularly for LaTeX template fixes/additions, prompt improvements, and support for additional LLMs (e.g., Bard, Claude, LLaMA).

Licensing & Compatibility

The repository does not explicitly state a license in the provided README.

Limitations & Caveats

The project is described as a prototype. The native installation requires specific system package installations (LaTeX) which may vary by operating system.