HackerQuest

HackerQuest is an AI-powered interview interface with a pair programming feature and a live behavioral question format. It allows technical and behavioral interviews to be conducted via a responsive web interface, leveraging AI to assess code, provide feedback, and manage interviews.

Features

• Code Interview Interface: A pair programming environment with support for dynamic questions and live code review.
• Behavioral Interview Interface: A behavioral interview interface with real-time audio visualizers.
• AI Feedback: Automated feedback for code reviews and behavioral interviews, including grading across key performance metrics.
• Backend Services: APIs to handle behavioral and technical questions, along with PDF document analysis for interview documentation.

Repository Structure

The project is organized into several subdirectories, each containing important components of the system:

• EmotionAI: Handles emotion detection for interviews.
• backend: Contains the core backend server (Flask-based), which provides APIs for fetching coding problems and evaluating code and behavioral interviews.
• bot: AI chatbot-related code and configurations for integration.
• frontend: React-based frontend that contains the behavioral and code interview interfaces.

How to Run Locally

Prerequisites

1. Python 3.x and Node.js installed on your machine.
2. Install Docker if using containerized deployment.

Backend Setup (Flask API)

1. Clone the repository:

   git clone https://github.com/alvina-yang/HackerQuest.git
   cd HackerQuest

2. Navigate to the backend directory:

   cd backend

3. Install the required Python packages:

   pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the backend directory and add your API keys (such as for Cohere AI).

5. Run the Flask server:

   python app.py

   The backend will be available at http://localhost:5678.

Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install the dependencies:

   npm install

3. Start the development server:

   npm run dev

   The frontend will be available at http://localhost:3000.

Running the AI-Powered Interview Interfaces

• Behavioral Interview: Open http://localhost:3000/behavioural-interview to start a behavioral interview session.
• Code Interview: Open http://localhost:3000/code-interview to begin a live coding session.

API Endpoints

The backend provides several API endpoints:

• /api/review_code: Submits code for review during technical interviews.
• /api/evaluate_behavioral: Evaluates performance during behavioral interviews.
• /api/upload_pdf: Uploads a PDF document for analysis.
• /api/find_lc_question: Finds a coding problem by querying a LeetCode-style database.