An intelligent AI-powered chatbot designed to assist customers in shopping malls seamlessly. Built using Python and TensorFlow, this chatbot understands user queries, predicts their intent using a trained deep learning model, and delivers helpful responses instantly. With an intuitive Tkinter-based interface, it enhances the shopping experience by providing store directions, product information, promotions, and general assistance, making mall navigation effortless and more enjoyable.
Uses NLP techniques for text processing
Deep learning model for intent recognition
GUI built with Tkinter
Supports multiple intents with varied responses
Make sure you have Python installed. You can install the required dependencies using:
pip install numpy tensorflow nltk pickle-mixinAdditionally, download the NLTK resources:
import nltk
nltk.download('punkt')
nltk.download('wordnet')chatbot.py: Core chatbot logic for handling user input, intent prediction, and response generation.
app.py: Tkinter-based GUI application for the chatbot.
intents.json: Defines various intents and corresponding responses.
chatbotmodel.h5: Trained deep learning model for intent classification.
words.pkl and classes.pkl: Preprocessed data used for prediction.
To run the chatbot in the terminal:
python chatbot.pyTo launch the GUI version:
python app.pyIf you need to retrain the chatbot, ensure you have a script that processes the intents.json file, tokenizes text, and trains a neural network. You can create a script like train.py for this purpose.
chatbot-project/
│-- chatbot.py
│-- app.py
│-- intents.json
│-- chatbotmodel.h5
│-- words.pkl
│-- classes.pkl
│-- README.md
│-- .gitignore
To avoid pushing unnecessary files, create a .gitignore file and add:
pycache/
*.pkl
*.h5
venv/
.env
Enhance the NLP pipeline for better intent recognition
Add more intents and responses
Improve the chatbot's conversational abilities with a larger dataset
Feel free to use and modify this project for educational purposes!