Reddit Comment Classification App

This project is a Streamlit web application that classifies reddit comments into three categories: "Veterinarian", "Medical Doctor", or "Others". The classification is performed using a fine-tuned BERT model.

Features

• Upload a CSV file containing a column named 'comments'
• Preprocess comments by removing duplicates and preserving order
• Classify each comment into one of three categories
• Download the classified results as a CSV file

Setup Instructions

Prerequisites

• Python 3

Clone the Repository

1. Open your terminal or command prompt.

2. Clone the repository using the following command:

   git clone <your-repo-url>

3. Navigate to the project directory:

   cd <your-repo-name>

Set Up the Virtual Environment

1. Create a virtual environment:

   python3 -m venv myenv

2. Activate the virtual environment:

   • On macOS/Linux:

     source myenv/bin/activate

   • On Windows:

     myenv\Scripts\activate

3. Install the required packages:

   pip install -r requirements.txt

Run the Streamlit App

1. Ensure the virtual environment is activated.

2. Run the Streamlit app:

   streamlit run app.py

3. Open your web browser and navigate to the URL provided by Streamlit (usually http://localhost:8501).

Usage

1. Upload a CSV file containing a column named 'comments'.
2. The app will preprocess and classify each comment.
3. View the classified results in the app.
4. Download the classified results as a CSV file.

Error handling on page

1. In a case where streamlit app throws a 'Cannot import BertTokenizer' error, simply refresh page to get required frontend.