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ResumeParserAI is a Streamlit-based AI application that parses PDF resumes using Google Gemini to extract structured data and generate professional summaries. Docker-ready for easy deployment.

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ResumeParserAI

A Streamlit-based application that parses resumes (PDF) using Google Gemini AI to generate professional summaries and extract structured data.

Features

  • PDF Upload: Upload your resume in PDF format.
  • AI Analysis: Uses Google Gemini Pro/Flash to analyze the content.
  • Structured Extraction: Extracts Name, Email, Location, Work Experience, Projects, Skills, and Education.
  • Professional Summary: Generates an engaging first-person summary.

Prerequisites

  • Docker and Docker Compose installed on your machine.
  • A Google Gemini API Key.

Getting Started

1. Clone the repository

git clone <repository-url>
cd ResumeParserAI

2. Environment Setup

Create a .env file from the example:

cp .env.example .env

Open .env and add your Gemini API key:

GEMINI_API_KEY=your_actual_api_key_here

3. Run with Docker Compose

Start the application:

docker-compose up --build

Access the application at http://localhost:8501.

4. Run Locally (Optional)

If you prefer running without Docker:

pip install -r requirements.txt
streamlit run main.py

Project Structure

  • main.py: Main application logic.
  • requirements.txt: Python dependencies.
  • Dockerfile: Docker construction instructions.
  • docker-compose.yml: Container orchestration.

About

ResumeParserAI is a Streamlit-based AI application that parses PDF resumes using Google Gemini to extract structured data and generate professional summaries. Docker-ready for easy deployment.

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