📝 ATS Resume Scanner using Gemini 1.5 Flash

An AI‑powered Applicant Tracking System (ATS) Resume Scanner that evaluates a candidate’s resume against a job description using Gemini 1.5 Flash. The tool simulates how a real ATS or recruiter analyses resumes, offering feedback, skill‑gap suggestions, and a match‑percentage score.

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🚀 Features

• Resume vs JD Comparison – analyses alignment between resume and job description.
• Match Percentage – returns a calculated match score with missing keywords.
• Skill‑Gap Suggestions – recommends improvements to improve alignment.
• PDF → Image Conversion – converts the uploaded PDF to an image for Gemini vision input.
• Streamlit UI – simple web interface for uploading PDFs and pasting job descriptions.

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📌 Use Cases

User	Benefit
Job Seekers	Check fit before applying and tailor resumes accordingly.
Career Coaches	Provide data‑driven feedback to candidates.
HR Teams	Pre‑screen resumes quickly with AI assistance.
Students	Understand industry expectations and enhance resumes.

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❓ Problem Statement

Recruiters use ATS systems to filter resumes based on keyword matches. Candidates rarely know how well their resumes align with a posting.
This project automates that analysis by:

1. Scraping the job description text (user‑supplied).
2. Converting the resume PDF to an image.
3. Feeding both into Gemini 1.5 Flash for multimodal reasoning.
4. Returning professional feedback, skill gaps, and a match percentage.

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⚙️ Tech Stack

• Frontend  : Streamlit
• LLM API  : Google Gemini 1.5 Flash (google-generativeai)
• Image Conversion  : pdf2image + Pillow (Poppler backend)
• Env Management  : python‑dotenv

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🛠️ Getting Started

### 1. Clone the Repository

git clone https://github.com/praphulchandra-nitdgp/ATS-Resume-Scanner.git
cd ATS-Resume-Scanner

### 2. Create and Activate a Virtual Env (optional)

python3 -m venv ats-venv
source ats-venv/bin/activate      # macOS / Linux
# or
ats-venv\Scripts\activate       # Windows

### 3. Install Dependencies

pip install -r requirements.txt

Poppler note (macOS):
brew install poppler

### 4. Add Your Gemini API Key

1. Get a key from Google AI Studio → API Keys.
2. Create a .env file in the project root:

   GOOGLE_API_KEY=your_gemini_key_here

### 5. Run the App

streamlit run app.py

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🔑 How to Generate a Gemini API Key

1. Sign in to https://makersuite.google.com.
2. Go to Settings → API Keys.
3. Click “Create API key” and copy it.
4. Paste it into the .env file as shown above.

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📸 Screenshot

Add a screenshot here once you have one, e.g.

![App UI](screenshots/app.png)

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🧠 Future Ideas

• Export feedback as PDF.
• Support multiple resume pages.
• Integrate auto‑email functionality.
• Add additional AI models for comparison.

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📝 License

MIT

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👤 Author

Made with ❤️ by Ganapathri Praphul Chandra

Setup

For Windows

1. Install Python from python.org.
2. Install Poppler for Windows:
   • Download from: https://github.com/oschwartz10612/poppler-windows/releases/
   • Extract and note the path (e.g., C:\path\to\poppler\bin).
   • Add the bin folder path to your System Environment Variables under Path.
3. Create .env file and follow remaining steps as mentioned above.

For Linux (Debian/Ubuntu)

sudo apt update
sudo apt install poppler-utils

Then continue with the Python virtual environment setup.

For macOS

brew install poppler

Then continue with the Python virtual environment setup.

Ensure you point poppler_path correctly in pdf2image.convert_from_bytes() if needed.