Knackmore ATS Evaluator

An intelligent resume screening tool that powers Knackmore.com's ATS evaluator. It parses PDF resumes, compares them against target job roles, and returns structured, actionable feedback using AI. Designed for job seekers, recruiters, and developers building smarter hiring workflows.

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✨ Features

• Upload PDF resumes and specify target job roles
• AI-generated ATS score breakdown across 8 categories
• Resume improvement recommendations with examples
• Clean frontend interface built with HTML/CSS/JS
• Flask backend powered by Groq's LLM API
• Markdown-based result formatting
• Support for standalone testing via test.ipynb

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🚀 How It Works

1. User uploads a resume and specifies a job title
2. The PDF is parsed and cleaned using PyMuPDF
3. A prompt is crafted and sent to Groq's llama-3.3-70b-versatile model
4. The AI responds with ATS scores and feedback in JSON/Markdown
5. Results are displayed beautifully in the frontend

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⚙️ Setup Instructions

1. Clone the Repo

git clone https://github.com/your-username/knackmore-ats-evaluator
cd knackmore-ats-evaluator

2. Environment Setup

Create and activate a virtual environment:

conda env create -f environment.yaml
conda activate knackmore

OR using pip:

pip install -r requirements.txt

3. Environment Variables

Create a .env file with:

API_KEY=your-api-key
API_URL=https://api.groq.com/openai/v1/chat/completions
SECRET_KEY=your-flask-secret

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🌐 Running the App

python run.py

Go to: http://localhost:5000

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🔍 File Overview

File	Purpose
run.py	App entry point
config.py	Loads API keys and env vars
test.ipynb	Notebook for standalone score breakdown testing
app/__init__.py	Initializes Flask app and routes
app/routes.py	Handles file upload and result routing
app/resume_evaluator.py	Handles LLM prompt creation and API calls
app/utils.py	PDF parsing and markdown-to-HTML conversion
templates/index.html	Main UI template
static/	Frontend assets (CSS/JS)

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🎓 Powered By

• Flask
• Groq API + LLaMA 3.3 70B
• PyMuPDF (PDF text extraction)
• Markdown + HTML formatting

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🚨 Warning

This tool sends resume data to third-party APIs. Make sure to handle PII responsibly in production environments.

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💼 License

MIT License

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🙏 Acknowledgments

• Groq for lightning-fast LLM responses
• PyMuPDF for reliable PDF parsing
• Markdown for clean UI formatting