MatchWise: A Resume Matching and Scoring Web Application

MatchWise is an AI-powered web application that helps users analyze and score resumes against job descriptions. It's built with Python, Streamlit, and the Google Gemini API, and it aims to assist job seekers and recruiters in gauging how well a resume matches the desired job criteria.

🎯 Features

• 📄 Upload Resumes: Supports multiple file formats for resume uploads.
• 💼 Upload Job Descriptions: Match resumes with specific job descriptions.
• 🔍 Matching Score: Generates a score indicating the resume's fit for the job.
• 🧠 AI-Powered Analysis: Leverages AI models via the Google Gemini API for resume parsing and matching.
• 🖥️ Streamlit-Based: Simple, intuitive UI for both developers and non-developers.

🚀 Quick Start

Prerequisites

• Python 3.7+
• Google Gemini API Key
• Streamlit

⬇️ Installation

1. Clone the repository:

   git clone https://github.com/bhavsarhem/matchwise.streamlit.app.git

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

   For More info click here 🔗

3. Install the required dependencies:

   pip install -r requirements.txt

4. Add your Google Gemini API key in .env:

   GOOGLE_API_KEY = "YOUR_GOOGLE_GEMINE_API_KEY"

   Generate your own Gemini API-Key from here 🔗

▶️ Running the Application

• Once all dependencies are installed, run the Streamlit application:

  streamlit run app.py

  Write the above code in terminal.

🛠️ Contributing

We welcome contributions from the open-source community! To get started:

1. Fork the repository.

2. Create a new branch:

   git checkout -b feature/your-feature-name

3. Make your changes and commit them:

   git commit -m "Add: your feature or fix description"

4. Push to your branch:

   git push origin feature/your-feature-name

5. Open a Pull Request on GitHub.

Contributions for Hacktoberfest 2024 🏆

We are proud participants in Hacktoberfest! Here’s how you can contribute:

• 📊 New Features: Help us add new features like advanced parsing, custom matching algorithms, or new file formats.
• 🐛 Bug Fixes: Hunt down bugs and suggest improvements.
• 📖 Documentation: Improve this README, write tutorials, or add comments to the code.
• 🎨 UI/UX Improvements: Enhance the web app's design, layout, or accessibility.
• 💡 Open to Ideas: Feel free to propose any new features or improvements.

Guidelines:

• Please ensure your contributions align with the existing coding style.
• Always provide clear commit messages and proper PR descriptions.
• We encourage creating an issue first to discuss your ideas before submitting a PR.

💬 Feedback

If you have any questions or feedback, feel free to reach out by opening an issue or contacting the project maintainers.

🙌 Acknowledgments

Thanks to all our contributors, Hacktoberfest participants, and the open-source community for making this project better!

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✨ Happy Coding! ✨

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Notes:

• Make sure to update the GitHub repository link (https://github.com/bhavsarhem/matchwise.streamlit.app.git) with the actual repo URL.
• Add a requirements.txt file in your project for dependencies.
• The .env file should contain sensitive API keys securely. Don't forget to include instructions or an example .env file.