📄 AI Resume Analyser

An AI-powered resume analysis tool that scores your resume against a job description, identifies keyword gaps, highlights strengths, and generates a tailored professional summary — all in seconds.

Built with Python, Streamlit, and the Google Gemini 2.5 Flash API.

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🖥️ Demo

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✨ Features

• ATS Compatibility Score — Get a score out of 100 based on how well your resume matches the job description
• Keyword Analysis — See exactly which keywords from the JD you've matched and which ones are missing
• Strengths Breakdown — Understand what your resume does well for the specific role
• Actionable Improvements — Get specific, targeted suggestions to fix weaknesses
• AI-Rewritten Summary — Receive a tailored professional summary ready to copy-paste directly into your resume
• Dark Mode UI — Clean, modern interface built with custom Streamlit CSS

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🛠️ Tech Stack

Layer	Technology
UI / Frontend	Streamlit
AI / LLM	Google Gemini 2.5 Flash API
Language	Python 3.11+
Config	python-dotenv
Deployment	Streamlit Community Cloud

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🚀 Getting Started

Prerequisites

• Python 3.11 or higher
• A free Google Gemini API key

Installation

1. Clone the repository

   git clone https://github.com/your-username/resume-analyser.git
   cd resume-analyser

2. Create a virtual environment (recommended)

   python -m venv venv
   
   # Windows
   .\venv\Scripts\Activate.ps1
   
   # macOS / Linux
   source venv/bin/activate

3. Install dependencies

   pip install -r requirements.txt

4. Set up your API key

   Create a .env file in the root of the project:

   GEMINI_API_KEY=your_api_key_here

   ⚠️ Never commit your .env file. It is already listed in .gitignore.

5. Run the app

   python -m streamlit run app.py

   The app will open at http://localhost:8501

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📁 Project Structure

resume-analyser/
├── app.py              # Streamlit UI and layout
├── analyzer.py         # Gemini API integration and response parsing
├── prompts.py          # LLM prompt templates
├── requirements.txt    # Python dependencies
├── .env                # API key (not committed)
└── .gitignore

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🔑 Getting a Free Gemini API Key

1. Go to Google AI Studio
2. Sign in with your Google account
3. Click "Get API Key" → "Create API key"
4. Copy the key and add it to your .env file

The free tier includes 250 requests/day with Gemini 2.5 Flash — more than enough for personal use.

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📦 Dependencies

streamlit>=1.32.0
google-generativeai>=0.8.0
python-dotenv>=1.0.0

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☁️ Deployment (Streamlit Community Cloud)

1. Push your project to a public GitHub repository
2. Go to share.streamlit.io and sign in
3. Click "New app" and select your repository
4. Under Advanced settings → Secrets, add:

   GEMINI_API_KEY = "your_api_key_here"

5. Click Deploy — your app will be live at a public URL

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🔮 Planned Features

• PDF resume upload support
• Side-by-side comparison of multiple resume versions
• Analysis history tracking
• Exportable PDF report
• LinkedIn profile URL input

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👤 Author

Ranusha Liyanage
GitHub · LinkedIn