Resume Classification & Details Extraction API

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🔹 Project Overview

This project is an AI-powered Resume Classification and Details Extraction API.
It allows users to upload resumes (.pdf, .docx, .txt), automatically predict the job category, and extract key details such as emails and phone numbers.

The backend is built with FastAPI, using a Random Forest classifier with TF-IDF vectorization, making it ready for integration with frontend applications like React.

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🛠️ Features

• Predicts job category from uploaded resumes
• Extracts emails and phone numbers
• Handles multiple file formats: PDF, DOCX, TXT
• REST API with FastAPI, easy integration with frontend
• Lightweight, fast, and ready for deployment

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📂 Folder Structure

resume-api/
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├── app.py # FastAPI backend
├── model/
│ ├── rf_classifier.pkl # Pre-trained Random Forest model
│ └── tfidf_vectorizer.pkl # TF-IDF vectorizer
├── requirements.txt # Python dependencies
├── data/ # Optional sample resumes
└── README.md # Project description

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⚙️ Installation & Setup

1. Clone the repository:

git clone https://github.com/Bilal-73/Resume-Classification-and-Details-Extraction.git
cd Resume-Classification-and-Details-Extraction

Download Pre-trained Models

• rf_classifier.pkl
• tfidf_vectorizer.pkl

Place them in the model/ folder before running app.py.

🧪 How it works

• Upload resume via /upload-resume endpoint
• Extract text from file using Textract
• Transform text with TF-IDF vectorizer
• Predict category using Random Forest model
• Extract emails and phone numbers
• Returns JSON: