Interview Mock Test Generator Web Application

This application allows users to generate interview mock tests based on a specified topic. It generates theory questions and coding problems.

Project Structure

Manas_Android_Research/
├── src/
│   ├── langchain_logic/
│   │   ├── __init__.py
│   │   ├── coding_prompt_template.txt
│   │   ├── question_generator.py
│   │   └── theory_prompt_template.txt
│   ├── static/
│   │   ├── index.html
│   │   ├── script.js
│   │   └── style.css
│   ├── main.py
│   └── pdf_exporter.py
├── requirements.txt
└── README.md 

Setup and Run Instructions

Follow these steps to run the application locally:

1. Prerequisites:

   • Python 3.8 or higher.
   • pip (Python package installer).

2. Clone or Download the Code:

   • Ensure you have all the files from the Manas_Android_Research directory.

3. Navigate to the Project Directory:

   cd path/to/Manas_Android_Research

4. Create and Activate a Python Virtual Environment:

   • It is highly recommended to use a virtual environment to manage dependencies.

   # For Linux/macOS
   python3 -m venv venv
   source venv/bin/activate
   
   # For Windows
   python -m venv venv
   .\venv\Scripts\activate

5. Install Dependencies:

   • Install all required Python packages using the requirements.txt file.

   pip install -r requirements.txt

6. Set Environment Variables:

   • This application requires API keys for Together AI (LLM provider) and Tavily (web search). You need to obtain these keys from their respective websites.
   • Set the following environment variables in your terminal session before running the app:

   # For Linux/macOS
   export TOGETHER_API_KEY="your_together_api_key_here"
   export TAVILY_API_KEY="your_tavily_api_key_here"
   
   # For Windows (PowerShell)
   $env:TOGETHER_API_KEY="your_together_api_key_here"
   $env:TAVILY_API_KEY="your_tavily_api_key_here"
   
   # For Windows (Command Prompt)
   set TOGETHER_API_KEY=your_together_api_key_here
   set TAVILY_API_KEY=your_tavily_api_key_here

   • Replace "your_together_api_key_here" and "your_tavily_api_key_here" with your actual API keys.
   • Note: Without these keys, the question generation will fail or produce limited results.

7. Run the Flask Application:

   • Execute the main Python script to start the Flask development server.

   python src/main.py

   • The application will typically be available at http://127.0.0.1:5000 or http://localhost:5000 in your web browser.

8. Access the Application:

   • Open your web browser and navigate to the URL provided in the terminal output (usually http://127.0.0.1:5000).

Features

• Topic Input: Enter any technical topic for which you want a mock test.
• Theory Questions: Generates 30 theory-based questions (basic to advanced, Bloom's taxonomy variety).
• Coding Questions: Generates 2 coding questions with problem statements, constraints, sample I/O, and difficulty tags.
• Web Search Augmentation: Uses Tavily search to augment LLM knowledge for more relevant theory questions.
• PDF Export: Export the generated mock test as a PDF document.
• Copy to Clipboard: Copy the generated mock test content to your clipboard.

Technologies Used

• Backend: Python, Flask, Langchain, Together AI (LLM), Tavily Search API.
• Frontend: HTML, CSS, JavaScript.
• PDF Generation: WeasyPrint.

Prompt Templates

• src/langchain_logic/theory_prompt_template.txt: Template for generating theory questions.
• src/langchain_logic/coding_prompt_template.txt: Template for generating coding questions.