This project contains training scripts for machine learning models that are able to classify a sentence into a list of conversation intents that can be defined in src/training/intents.json, and an application loop to interact with the model in src/chatbot.py
Here, I used nltk and numpy to prepare the traning data, and tensorflow to create and train the models.
In future iterations, I plan on integrating with ChatGPT to generate more human responses after classifying the text.
To test this project, you'll need to install the pip dependencies using
pip install -r requirements.txt
In this repo, i've already included a trained model using demonstrative real estate sales conversation intents in portuguese, but if you want to use your own intents
you need to update src/training/intents.json and tailor it to your specific needs, then run the training script.
cd src/training && python train_sequential_network.py
This will generate three files: words.pkl, tags.pkl and chatbot_model.h5 that will be automatically loaded when you run the program.
You only need to train your model when you change the intents.json file.
To interact with the chatbot, navigate to the /src folder and run:
python chatbot.py
