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Mock Interview Platform

Project Overview

Our project is a modern, AI-powered platform designed to help users prepare for interviews. It leverages cutting-edge technologies to provide a comprehensive preparation experience, including a real-time chatbot, posture analysis, and interview simulations.

Architecture Overview

The application is built with a modern frontend stack:

  • Framework: React with Vite for a fast development experience.
  • Language: TypeScript for type safety.
  • Styling: Tailwind CSS with shadcn/ui for a beautiful and consistent component-based design.
  • Routing: React Router for navigation within the single-page application.
    • Grok 4.1 api for the intelligent chatbot and interviewer functionality.
    • TensorFlow.js for real-time posture detection and analysis during practice sessions.

The backend consists of a simple Express server to handle requests to the Gemini API securely.

Setup Instructions

  1. Clone the repository:

    git clone https://github.com/ASV-Group/final-one.git
    cd final-one
  2. Install dependencies: This project uses npm as the package manager.

    npm install
  3. Set up environment variables: Create a .env file in the root of the project and add your Google Gemini API key:

    VITE_OPENROUTER_API_KEY=your_api_key_here
    

How to Run Locally

After following the setup instructions, you can run the application in development mode:

npm run dev

APIs or Endpoints

The application communicates with the Grok API.

Example Inputs/Outputs

  • Chatbot:
    • Input: User types a question, e.g., "What are common questions for a software engineer role?"
    • Output: The chatbot provides a detailed answer generated by the Grok API.
  • Posture Analysis:
    • Input: User's webcam video stream during a practice session.
    • Output: Real-time feedback on posture analysis, such as "Sit up straight" or "Look at the camera."

Step for using

  • 1 : Go to interview room
  • 2 : Turn Mic on for speaking and when finished speaking turn mic off.
  • 3 : Turn cam on for realtime posture analysis and body language analysis.
  • 4 : after interview click end interview to check performance.

List of Dependencies

Main Dependencies

  • @openrouter: For interacting with the Gemini API.
  • @tensorflow/tfjs: For running machine learning models in the browser.
  • react: The core UI library.
  • react-router-dom: For routing.
  • tailwindcss: For styling.
  • @radix-ui/*: Foundational components for building the UI.
  • And many more...

Development Dependencies

  • vite: Build tool and dev server.
  • typescript: For type checking.
  • eslint: For code linting.
  • postcss: For CSS processing.

For a complete list, please refer to the package.json file.

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