COMM061 - NATURAL LANGUAGE PROCESSING - GROUP 43

Overview

This project is designed to deploy a Flask application that utilizes the SciBERT model for various NLP tasks. The project includes a Jupyter notebook, app.ipynb, which is converted to a Python script during the CI/CD pipeline. The application is deployed using a CI/CD pipeline configured in GitLab.

Table of Contents

• Project Structure
• Requirements
• Setup
• Usage
• License

Project Structure

.
├── app.ipynb                # Jupyter notebook for the application
├── requirements.txt         # List of dependencies
├── pipeline.sh              # Shell script for building the project
├── .gitlab-ci.yml           # GitLab CI/CD pipeline configuration
└── README.md                # Project documentation

Requirements

• Python 3.8+
• Flask
• Gunicorn
• Jupyter
• nbconvert
• PyTorch
• NumPy
• Transformers
• Datasets
• Evaluate
• Seqeval

You can find all required packages listed in requirements.txt.

Setup

1. Clone the repository:

   git clone <repository-url>
   cd <repository-directory>

2. Set up a virtual environment and install dependencies:

   python3 -m venv .venv
   source .venv/bin/activate
   pip install -r requirements.txt

3. Run the application:

   nohup python3 app.py &

Usage

1. Converting the Jupyter Notebook:

   Convert app.ipynb to a Python script:

   jupyter nbconvert --to script app.ipynb

2. Running the Flask Application:

   Ensure that app.py is present in the project directory after conversion. Then, start the Flask application:

   python3 app.py

3. Access the Application:

   By default, the Flask application runs on http://127.0.0.1:8080. Open this URL in your web browser to access the application.

License

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