Interview Helper

A comprehensive platform for technical interview preparation and conducting remote interviews with AI assistance.

Features

• Practice Mode: Practice technical interview questions with AI feedback
• Interview Mode: Conduct real-time interviews with video, audio, and chat
• AI-Powered Question Generation: Get relevant technical questions based on job roles
• Vector Search: Find similar questions based on conversation context
• Voice Analysis: Get question suggestions based on voice transcripts
• Performance Analytics: Track your practice performance over time

New Features

• Gemini AI Integration: Replaced Ollama with Google's Gemini API for more reliable AI responses
• Vector Search: Added semantic search using HuggingFace embeddings and FAISS
• Interview Room Questions: Interviewers can now generate relevant questions during interviews
• Voice Analysis: Get question suggestions based on voice transcripts during interviews

Setup

Windows Setup

1. Clone the repository:

   git clone https://github.com/yourusername/interview-helper.git
   cd interview-helper
   

2. Run the setup script:

   setup.bat
   

   This will:

   • Create a virtual environment
   • Install all required packages
   • Download necessary NLTK data

3. Make sure MongoDB is installed and running

   • Download from: https://www.mongodb.com/try/download/community
   • Start the MongoDB service

4. Run the application:

   • In one terminal: run_app.bat
   • In another terminal: run_interview_server.bat

5. Access the application at http://localhost:5001

Manual Setup (Linux/Mac)

1. Clone the repository:

   git clone https://github.com/yourusername/interview-helper.git
   cd interview-helper
   

2. Create a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt
   

3. Initialize NLTK data (for voice analysis):

   python -c "import nltk; nltk.download('punkt'); nltk.download('stopwords')"
   

4. Set up environment variables:

   cp .env.example .env
   

   Edit the .env file and add your:

   • MongoDB connection string
   • Flask secret key
   • Google API key for Gemini (get one from https://makersuite.google.com/app/apikey)

5. Start the application:

   python app.py
   

6. In a separate terminal, start the interview server:

   python interview_server.py
   

7. Access the application at http://localhost:5001

Using the Interview Room

1. Schedule an interview as an interviewer
2. Share the interview key with the interviewee
3. Join the interview room
4. As an interviewer, you can:
   • Use the "Get Interview Question" button to generate relevant questions
   • Select different job roles from the dropdown
   • Click on suggested questions that appear based on the conversation
   • Use voice recognition to get question suggestions based on what's being discussed

Architecture

• Frontend: HTML, CSS (Tailwind), JavaScript
• Backend: Flask, Flask-SocketIO, MongoDB
• AI Components:
  • Google Gemini API for question generation and answer assessment
  • LangChain for prompt engineering and chain management
  • HuggingFace Transformers for embeddings
  • FAISS for vector search
  • NLTK for voice transcript analysis

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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