🎯 CalibrHire

CalibrHire is an intelligent, automated resume screening tool designed to bridge the gap between recruiters and the perfect candidate. By leveraging advanced parsing and matching algorithms, it streamlines the hiring pipeline, ensuring that the best talent rises to the top efficiently.

🚀 Features

-> Automated Resume Parsing: Effortlessly extract structured data (education, skills, work experience) from unstructured resume documents.

-> Intelligent Matching: Compare candidate profiles directly against job descriptions to identify the strongest matches.

-> Efficient Filtering: Reduce manual screening time by ranking candidates based on relevance and skill alignment.

-> Scalable Architecture: Built to handle large volumes of applications with high accuracy and speed.

🛠 Tech Stack

• Language: Python

• Core Functionality: [Include specific libraries, e.g., spaCy for NLP, PyPDF2/docx2txt for parsing]

• Matching Algorithm: [Specify method, e.g., Cosine Similarity, TF-IDF, or LLM-based embedding]

• Data Handling: [Specify framework, e.g., Pandas/NumPy]

⚙️ Quick Start

1. Clone the Repository

Start by cloning the project to your local machine:

git clone https://github.com/Anisca-hub/CalibrHire.git

cd CalibrHire

2. Set Up Virtual Environment

Create and activate your virtual environment to keep dependencies isolated:

Create the environment

python -m venv venv

Activate it

On macOS/Linux: source venv/bin/activate

On Windows: venv\Scripts\activate

3. Install Dependencies

Once the environment is active, install the required packages: pip install -r requirements.txt

4. Execution

Run the screening tool by providing the paths to your resume directory and the job description file:

streamlit run app.py or python -m streamlit run app.py