An NLP based Chatbot over a simple fully connected neural network architecture using Tensorflow and tflearn. Trained over a custom dataset specified in the JSON file.
Run pip install library in your terminal to install all required libraries
The dataset.json contains the intents on which the model is trained. Each pattern (sentence) and response is given a particular tag. The model classifies each input sentence under a tag and gives out a random answer corresponding to that tag. The json file can be formatted according to the user's requirements.
In Python versions above 3.6 PyAudio is not a supported library and installing PyAudio directly using pip install pyaudio fails and needs to be installed separately.
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Windows For that, individually install the wheel file given (this is for Python 3.7, find suitable wheel files here) writing the following line in your terminal.
pip install <.wh file name> -
Ubuntu/Linux
$ sudo apt-get install python3-pyaudio
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Run
trainModel.pyto train the Fully Connected Network on the dataset. You can change the number of epochs or layers accordingly, the current architecture gave good results with a ~95% accuracy on predicting tags. -
Run
textChatbot.pyfor text based chatbot with GUI incorporated -
Run
voiceBot.pyfor voice recognition based chatbot