SubZeroSearch 🧊

A lightning-fast, AI-powered Applicant Tracking System built on Snowflake's Data Cloud.

Overview

SubZeroSearch revolutionizes the recruitment process by leveraging Snowflake's Cortex framework and LLM'2 to provide real-time insights from candidate resumes.

Key Features

• Real-time Resume Analysis - Instant parsing and insights extraction
• AI-Powered Search - Natural language queries across your candidate pool
• Interactive Analytics Dashboard - Visual representation of candidate metrics
• Smart Context Retention - Conversation memory for better search results
• Secure Document Management - Enterprise-grade storage on Snowflake

Tech Stack

• Backend: Snowflake Data Cloud, Snowflake Cortex
• Frontend: Streamlit
• AI/ML: Mistral Large v2, Snowpark
• Analytics: Plotly, Pandas
• Data Processing: MarkItDown

Quick Start

1. Configure Snowflake credentials:

AVATAR_URL=
LOGO_URL=

[connections.snowflake]
account =
user =
password =
role =
database =
schema =
warehouse =
client_session_keep_alive = true

2. Install Dependencies:

pip install -r requirements.txt

3. Run the Application:

streamlit run main.py

Installation

1. Clone the Repository:

   git clone https://github.com/yourusername/SubZeroSearch.git
   cd SubZeroSearch

2. Set Up Environment:

   Ensure you have Python 3.9+ installed. Create a virtual environment and activate it:

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

3. Install Required Packages:

   pip install -r requirements.txt

4. Configure Snowflake:

   Update the .env file with your Snowflake credentials.

Usage

• Start the Application: Use the command streamlit run main.py to launch the application.
• Access the Dashboard: Open your browser and navigate to the provided local URL to interact with the dashboard.

Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository.
2. Create a new branch (git checkout -b feature/YourFeature).
3. Commit your changes (git commit -m 'Add some feature').
4. Push to the branch (git push origin feature/YourFeature).
5. Open a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.