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MCQ Generator using OpenAI and Langchain

Steps

Step 1: Setting up the Development Environment

python -m venv env

Step 2: Experimentation in Jupyter Lab

Explore and experiment with the project in Jupyter Lab. This step involves creating and testing various ideas and functionalities.

Step 3: Modular Coding

Convert the experiments and code into modular components for better organization and maintainability.

Step 4: Creating Web API using Streamlit

Utilize Streamlit to create a user-friendly web interface for the MCQ generator.

Step 5: Deploy Application on Cloud Platform (AWS)

Deploy the finalized application on a cloud platform such as AWS to make it accessible to users.

Project Structure

The project follows a modular structure:

  • src/: Contains the main source code for the MCQ generator.

    • mcq_generator/: Package folder containing various files related to the project.
      • ...: Additional subfolders and files as required.

  • experiments/: Holds Jupyter Notebook files for experimentation and development.

Why we created the init.py file

in the src folder there is the folder mcq_generator inside it there are several files regarding the project and to consider it as a package there is a standard to add this file.