Resume Recommender

AI-powered resume analysis and candidate recommendation system using Mistral AI. Available as both a web interface (Streamlit) and REST API (FastAPI) for easy integration.

Features

• AI-Powered Analysis: Uses Mistral AI for intelligent resume evaluation
• Structured Output: Returns validated JSON with scores, recommendations, and detailed analysis
• Dual Interface: Web UI for direct use, REST API for integration
• PDF Support: Extracts text from PDF resumes automatically
• Comprehensive Evaluation: Provides scores, strengths, concerns, skills match, and recommendations

Quick Start

Prerequisites

1. Python 3.8+ installed
2. Mistral AI API Key - Get one from Mistral AI

Installation

1. Clone the repository:

   git clone <repository-url>
   cd Resume_Rec_2

2. Create and activate virtual environment:

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

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the project root:

   mistral_api=your_mistral_api_key_here

Usage

Option 1: Web Interface (Streamlit)

Start the Streamlit app:

source venv/bin/activate
streamlit run app.py

Access the app:

• Open your browser and go to: http://localhost:8501
• Upload PDF resumes
• Enter job title, department, and description
• Click "Recommend Candidates" to get AI analysis

Features:

• Easy drag-and-drop PDF upload
• Real-time analysis results
• Structured display with scores and recommendations
• Support for multiple resume analysis

Option 2: REST API (FastAPI)

Start the API server:

source venv/bin/activate
uvicorn main:app --reload

Access the API:

• API Base URL: http://localhost:8888
• Interactive docs: http://localhost:8888/docs
• API documentation: http://localhost:8888/redoc

API Endpoint:

POST /recommend

Request Format (multipart/form-data):

• job_title (string): The job position title
• department (string): Department (Engineering, Marketing, Design, Data, Other)
• job_description (string): Detailed job requirements and description
• resume_file (file): PDF file containing the candidate's resume

Project Structure

Resume_Rec_2/
├── app.py              # Streamlit web interface
├── main.py             # FastAPI backend server
├── mistral_client.py   # Mistral AI integration
├── pdf_extract.py      # PDF text extraction utilities
├── test_api.py         # API testing script
├── requirements.txt    # Python dependencies
├── .env                # Environment variables (create this)
└── README.md          # This file

Dependencies

• FastAPI: REST API framework
• Streamlit: Web interface framework
• Mistral AI: AI model for resume analysis
• pdfminer.six: PDF text extraction
• Pydantic: Data validation and serialization
• uvicorn: ASGI server for FastAPI

Environment Variables

Required environment variables in .env file:

mistral_api=your_mistral_api_key_here

License

MIT License - see LICENSE file for details.