Resume Analyzer

Deployed Link

Click Here

Project Overview

Resume Analyzer is an AI-powered application that helps job seekers improve their resumes by analyzing skill gaps and providing personalized suggestions based on job descriptions. The application uses large language models to analyze resumes and generate actionable feedback.

Features

• Upload PDF resumes for analysis
• Compare your resume against job descriptions
• Get AI-powered skill gap analysis
• Receive personalized suggestions for resume improvement
• Generate a professionally formatted HTML resume

Technologies Used

• Streamlit: For the web interface
• LangChain: For orchestrating LLM interactions
• Together AI: For LLM inference (Llama-3-70b-chat-hf)
• PyPDF: For PDF text extraction
• Python-dotenv: For environment variable management

Setup Instructions

Prerequisites

• Python 3.8 or higher
• pip package manager

Installation

1. Clone the repository:

   git clone <repository-url>
   cd Resume-Analyzer

2. Create a virtual environment (recommended):

   python -m venv venv
   # On Windows
   venv\Scripts\activate
   # On macOS/Linux
   source venv/bin/activate

3. Install the required dependencies:

   pip install -r requirements.txt

4. Create a .env file in the project root and add your API keys:

   TOGETHER_API_KEY=your_together_api_key_here

Running the Application

To run the Streamlit application:

streamlit run ResumeAnalyzer.py

The application will open in your default web browser.

Usage

1. Upload your resume in PDF format
2. Paste the job description you're applying for
3. Click "Analyze" to get skill gap analysis and suggestions
4. View the generated HTML resume in the "Sample Resume" tab

Project Structure

Resume-Analyzer/
├── ResumeAnalyzer.py    # Main application file
├── requirements.txt     # Project dependencies
├── .env                 # Environment variables (not included in repo)
└── README.md            # This 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.