Conchylicultor/DeepQA

Health v2 · maintenance only

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2910 stars · 1154 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

DeepQA is a TensorFlow implementation of Google's 'A Neural Conversational Model', a seq2seq RNN-based deep learning chatbot. It supports training on several dialog corpora (Cornell Movie Dialogs, OpenSubtitles, Ubuntu, Supreme Court) and includes a Django web chat interface.

Use cases

• train a seq2seq neural chatbot
• reproduce the Google neural conversational model paper
• build a chatbot from movie dialog data
• experiment with RNN conversation models in TensorFlow
• run a web-based chatbot demo
• train a chatbot on custom conversation data

When to choose

• you want a classic seq2seq chatbot implementation for learning or research
• you need to reproduce the 'A Neural Conversational Model' paper results
• you want to train a conversational model on Cornell Movie Dialogs or OpenSubtitles

When to avoid

• you need a production-grade modern LLM chatbot
• you require up-to-date TensorFlow 2.x or PyTorch support
• you need actively maintained code with recent fixes

Facets

library · maturity maintenance

chatbot machine-learning deep-learning nlp llm-training artificial-intelligence deep-learning chatbots python seq2seq tensorflow rnn conversation-model cornell-movie-dialogs research-reproduction natural-language-processing linux docker gpu

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