ResumeParserAI
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.
Install / Use
/learn @rahulapjs/ResumeParserAIREADME
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.
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