Metadata-Version: 2.4
Name: ai-resume-screener
Version: 0.1.0
Summary: AI-powered resume screening tool using LLMs and Streamlit
Home-page: https://github.com/smrutiranjan1132001/ai-resume-screener
Author: Smruti Ranjan Bhuyan
Author-email: smruti1132001@email.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: streamlit
Requires-Dist: openai
Requires-Dist: PyMuPDF
Requires-Dist: sqlite-utils
Requires-Dist: python-dotenv
Requires-Dist: together
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# 🧠 AI-Powered Resume Screener

A lightweight resume screening app that uses AI to extract key candidate details from PDFs and evaluates them based on skills. Built with **Streamlit**, **SQLite**, and **PyMuPDF**. Ideal for HR teams, devs, or anyone needing a smart CV filter!

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## 📸 Screenshots

![Home Screen](assets/upload_page.jpg)
*Upload resumes and view extracted details*

![Parsed Resume Table](assets/ranked_shortlisting.jpg)
*See candidate info and download PDF*

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## 🚀 Features

- 📄 PDF Resume Upload
- 🧠 LLM-Based Evaluation (GPT or any open-source LLM)
- 🧑‍💻 Name, Email, Skills Extraction
- 🗃 Resume Storage with SQLite
- 📊 Interactive Table View

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## 🛠️ Tech Stack

- **Frontend**: Streamlit
- **Backend**: Python, PyMuPDF, SQLite
- **AI**: OpenAI / GPT-compatible LLMs / Together.ai (pluggable)

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🔄 Pluggable LLM Support
By default, this project uses GPT for resume evaluation.
You can use any open-source LLM model (like Mistral, LLaMA, Gemma, etc.) by simply updating the model name or API in the gpt_evaluator.py file.

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## ⚙️ Getting Started

```bash
git clone https://github.com/your-username/ai-resume-screener.git
cd ai-resume-screener
pip install -r requirements.txt
streamlit run app.py

