AI Interview System - Hackathon Team 7

This project is an intelligent interview system that uses AI to conduct technical interviews with candidates. The system leverages natural language processing, speech recognition, and conversational AI to create a realistic interview experience tailored to specific job descriptions.

🌟 Features

• AI-powered interview bot with natural conversation capabilities
• Job-specific interview questions based on required skills and responsibilities
• Real-time WebRTC audio communication
• Live transcript display during interviews
• Secure authentication and user management
• Candidate and job description management
• Interview scheduling and status tracking

📦 Repository Structure

The project is organized into two main components:

• Frontend: React application with TypeScript, Vite, and TailwindCSS
• Backend: Python FastAPI application with Pipecat for AI conversation

🚀 Getting Started

Prerequisites

• Node.js 16+ and npm/yarn for the frontend
• Python 3.10+ for the backend
• PostgreSQL database
• API keys for Deepgram, Cartesia, and Anthropic Claude

Quick Start

1. Clone the repository:

   git clone https://github.com/your-username/Hackathon-Aug-25-Team7.git
   cd Hackathon-Aug-25-Team7

2. Set up and start the backend:

   cd service
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt
   # Create .env file with required API keys and database URL
   uvicorn main:app --reload

3. Set up and start the frontend:

   cd app
   npm install
   # Create .env file with backend URL
   npm run dev

4. Open your browser and navigate to http://localhost:5173

📚 Documentation

For detailed documentation on each component:

• Frontend Documentation
• Backend Documentation

🧠 How It Works

1. Job Description Analysis: The system analyzes job descriptions to identify required skills and responsibilities.
2. AI-Powered Interviews: Using Anthropic Claude, the system conducts natural conversational interviews.
3. Real-time Audio: WebRTC enables real-time audio communication between the candidate and the AI interviewer.
4. Speech Processing: Deepgram converts speech to text, and Cartesia converts text to speech.
5. Interview Assessment: The conversation is analyzed to assess candidate suitability.

💻 Technologies Used

Frontend

• React
• TypeScript
• WebRTC
• TailwindCSS
• Vite

Backend

• FastAPI
• SQLAlchemy
• Pipecat
• WebRTC
• PostgreSQL
• Anthropic Claude
• Deepgram
• Cartesia

🏆 Hackathon Team 7

This project was developed during the August 2025 Hackathon by Team 7:

• Ashiya Ajare
• Nidhi Soni
• Vishakha Sainani
• Bhushan Nagpure
• Aditya Padekar
• Prajjwalkumar Panzade

🔮 Future Enhancements

• Multi-language support
• Video interview capabilities
• Advanced analytics for interview performance
• Integration with ATS (Applicant Tracking Systems)
• Customizable interview templates