DeepQA

Why we included this project

DeepQA is a TensorFlow implementation of the seq2seq architecture from Google's 2015 neural conversation paper, and it earns its keep as a learning tool, not a production service. The code walks you through the whole flow: loading and tokenizing dialogue data, training the RNN encoder-decoder on conversation pairs, then chatting in a terminal or a simple web interface. Cornell Movie Dialogs is bundled for immediate training, with OpenSubtitles, Supreme Court transcripts, or your own custom data as drop-in alternatives, and pre-trained word embeddings are supported to cut training time. For anyone trying to understand how chatbots worked before large language models, this is a readable, self-contained reference.