#263 · Primary category: AI Chatbots

ChatLearner

beam-search chatbot deep-learning nmt nmt-model python rule-based seq2seq-model sequence-to-sequence tensorflow tensorflow-chatbot

A chatbot implemented in TensorFlow based on the seq2seq model, with certain rules integrated.

Project last updated:11/13/19

GitHub Stars

542

Forks

203

Contributors

2

License

Apache-2.0

Why we included this project

ChatLearner is a good study for anyone who wants to see how a chatbot is assembled from TensorFlow's sequence-to-sequence model, rather than just calling an API. The code is deliberately concise, so the dynamic-RNN architecture is easier to follow than the official tutorial. What stands out is the ChatSession layer, which carries conversational context across turns, and a set of hand-written rules that handle things a pure neural model cannot, like simple arithmetic. That hybrid approach is a practical lesson for anyone building a chatbot that needs both learned responses and deterministic behavior. The bundled Papaya training dataset is also worth a look if you are hunting for clean conversational data to train your own model.

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