https://github.com/leodeveloper/mcqgen
This project aims to automate the process of generating multiple-choice questions (MCQs) using Generative AI techniques. Users can upload a text file containing relevant content, and our system utilizes Streamlit for the frontend, Python for backend processing, LangChain, LLM (Large Language Model)
https://github.com/leodeveloper/mcqgen
aws-ec2 chatgpt chatgptapi langchain openai python streamlit vector
Last synced: 10 months ago
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This project aims to automate the process of generating multiple-choice questions (MCQs) using Generative AI techniques. Users can upload a text file containing relevant content, and our system utilizes Streamlit for the frontend, Python for backend processing, LangChain, LLM (Large Language Model)
- Host: GitHub
- URL: https://github.com/leodeveloper/mcqgen
- Owner: leodeveloper
- Created: 2024-04-28T03:51:41.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-05-13T05:28:22.000Z (almost 2 years ago)
- Last Synced: 2025-03-31T00:29:48.915Z (about 1 year ago)
- Topics: aws-ec2, chatgpt, chatgptapi, langchain, openai, python, streamlit, vector
- Language: Jupyter Notebook
- Homepage: http://mcq.webhop.me/
- Size: 262 KB
- Stars: 2
- Watchers: 1
- Forks: 4
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# MCQ Generator
## Introduction
This project aims to automate the process of generating multiple-choice questions (MCQs) using Generative AI techniques. Users can upload a text file containing relevant content, and our system utilizes Streamlit for the frontend, Python for backend processing, LangChain, LLM (Large Language Models), ChatGPT, and SequentialChain for generating MCQs. The entire system is deployed on AWS EC2 using MLOps methodologies for seamless integration and deployment.
## Features
- **File Upload**: Users can upload text files containing the content for which MCQs need to be generated.
- **Generative AI**: Leveraging advanced AI models including LangChain, LLM, ChatGPT, and SequentialChain for MCQ generation.
- **Streamlit Interface**: A user-friendly frontend powered by Streamlit for easy interaction.
- **AWS EC2 Deployment**: The system is deployed on AWS EC2 for scalability and reliability.
- **MLOps Integration**: Utilizing MLOps practices for continuous integration and deployment.
## Installation
To run this project locally, follow these steps:
1. Clone the repository:
```bash
git clone https://github.com/your_username/MCQ-Generator.git
Install dependencies:
bash
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cd MCQ-Generator
pip install -r requirements.txt
Run the Streamlit app:
bash
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streamlit run app.py
Usage
Open the web interface by navigating to the provided URL after running the Streamlit app.
Upload a text file containing the content for which you want to generate MCQs.
Wait for the system to process the content and generate MCQs.
Review and use the generated MCQs as needed.
Contributing
Contributions are welcome! If you'd like to contribute to this project, please follow these steps:
Fork the repository.
Create a new branch (git checkout -b feature/my-feature).
Make your changes and commit them (git commit -am 'Add new feature').
Push to the branch (git push origin feature/my-feature).
Create a new Pull Request.
License
This project is licensed under the MIT License.
Acknowledgements
Special thanks to the developers of Streamlit, LangChain, LLM, ChatGPT, SequentialChain, and AWS for their incredible tools and services.
vbnet
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