🚀 StreamlitAPP

Currently unavaliable, need to upload all local models

A Streamlit-based web application for AI-powered resume generation and enhancement, utilizing Retrieval-Augmented Generation (RAG) techniques. Seamlessly converts resumes between formats, retrieves best-matching templates, and generates polished, ATS-compliant documents ready for submission.

✨ Features

• 📄 Parse raw resumes from PDF to structured JSON

• 🔎 Retrieve top-matching resume templates based on job descriptions

• 🧠 Generate optimized resume content using AI (RAG framework)

• 📤 Export finalized resumes back into polished PDF format

• 🖥️ Easy-to-use web interface built with Streamlit

• 🛠️ Lightweight, fast, and customizable

🏗️ Project Structure

StreamlitApp/

  ├── app.py                  # Main Streamlit application

  ├── convert_pdf_to_json.py   # Extracts resume content from PDFs

  ├── convert_json_to_pdf.py   # Generates PDFs from structured JSON

  ├── parse_resume.py          # Resume parsing and cleaning logic

  ├── template_retrival.py     # Retrieve templates matching JD

  ├── finetune.py              # Fine-tune prompts for better generation

  ├── resume_schema.py         # JSON schema definition for resumes

  ├── resume_template.html     # HTML template for resume layout

  ├── requirements.txt         # Python package dependencies

  └── packages.txt             # Extra environment setup

🚀 Quick Start

1. Clone the repository

  git clone https://github.com/Kepler22b22/StreamlitAPP.git

  cd StreamlitAPP

2. Install dependencies

  pip install -r requirements.txt

3. Run the Streamlit app

  streamlit run app.py

4. Open in Browser

  Default: http://localhost:8501/

🧠 Technologies Used

• Streamlit

• OpenAI APIs

• Pandas

• Pydantic

• PDFPlumber

🤝 Contributing

Pull requests are welcome!

For major changes, please open an issue first to discuss what you would like to change.

📄 License

This project is licensed under the MIT License. Feel free to use, modify, and distribute it with attribution.

🌟 Acknowledgments

Inspired by the need for faster, smarter resume generation. And thanks to the incredible open-source community. Special thanks to my amazing teammates for their collaboration and dedication:

• Aryan Vats – MS in CS
• Nidhi Choudhary – MS in ADS
• Eben Gunadi – MS in DS (Healthcare)
• Muqi Zhang – MS in CS
• Justin Chen – BS in DS