Chatbot Project

This project is a simple chatbot implemented using Python, Flask, Keras, NLTK, and JSON. The chatbot is capable of understanding and responding to predefined intents based on user input.

Project Structure

• App.py: Contains the Flask application setup along with the chatbot logic.
• data.json: Contains the intents for the chatbot, including tags, patterns, and responses.
• labels.pkl and texts.pkl: Store the preprocessed data (words and classes) using pickle.
• model.h5: Stores the trained neural network model using Keras.
• training.ipynb: Jupyter Notebook used for data preprocessing, model training, and saving the trained model.
• static/style.css: Contains the CSS styles for the chatbot interface.
• templates/index.html: Contains the HTML structure for the chatbot interface.

Technologies Used

• Python: Programming language used for the backend logic.
• Flask: Web framework used for building the web application.
• Keras: Deep learning library used for building and training the neural network model.
• NLTK: Natural language processing library used for text preprocessing.
• JSON: Data format used for storing intents and responses.
• HTML/CSS: Used for the frontend interface of the chatbot.

Usage

1. Install the required libraries using pip install -r requirements.txt.
2. Run the Flask application using python app.py.
3. Open your web browser and navigate to http://localhost:5000 to access the chatbot interface.