We use Keras, Tensorflow and NLTK to recognize the user's intent and generate the appropriate response.
Create a virtual environment and install the requirements:
pip install -r requirements.txt
Train the model:
- Run all the code cells in the notebook 'trainer.ipynb'.
Run the application:
python chat.py
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Greeting: greetings to the user.
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GoodBye: goodbyes to the user.
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ThankYou: appreciation messages to the user.
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Success: response to a successful action relayed by the user.
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About: replies to messages about the chatbot.
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Name: replies to messages about the chatbot's name.
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Help: responses to a user's help request or request for more information on an issue.
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Assistance: replies to a user's request for assistance.
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CreateAccount: helps the user with creating an account.
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Login: messages helping the user login.
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Password: assistance with resetting a forgetten password.
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EmailChange: helps a user with email address changes.
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EmailSupport: gives the user an email for customer support.
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Payout: provides information about vendor payouts.
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Complaint: gives th user a place to complain.