Intelligent Conversational Chatbot

Project Description

This project is an intelligent conversational chatbot implemented using BERT (Bidirectional Encoder Representations from Transformers). The chatbot is designed to understand and respond to various user intents in a conversational manner. The different intents include greetings, questions about the time, identity of the user, chatbot, jokes, queries, and more.

Training the Model

Preparing the Training Data

The training data consists of various user queries and their corresponding intents. The data is preprocessed and tokenized to be compatible with the BERT model.

Training Process

1. Open the Jupyter notebook Intent_Classification_Chatbot.ipynb.
2. Follow the steps in the notebook to preprocess the data, train the model, and save the trained model as a .pth file.
3. The trained model will be saved as data.pth.

Running the Gradio App

Gradio is used to create a user-friendly web interface for interacting with the chatbot.

Steps to Run the Gradio App

1. Ensure you have all the required dependencies installed:

   pip install -r requirements.txt

2. Run the Gradio app:

   python run.py

3. Open the provided URL in your web browser to interact with the chatbot.

Further Extensions

• Additional Intents: Add more intents to make the chatbot more versatile.
• Improved Responses: Enhance the response generation to make the chatbot more engaging.
• Deployment: Deploy the chatbot on a cloud platform for wider accessibility.

Contributing Guidelines

1. Fork the repository.
2. Create a new branch for your feature or bugfix:

   git checkout -b feature-name

3. Commit your changes:

   git commit -m "Description of your changes"

4. Push to the branch:

   git push origin feature-name

5. Create a pull request.

Contact Information

For any questions or suggestions, please contact:

• Name: Mehul Mathur
• Email: [email protected]