# dennybritz/chatbot-retrieval

Dual LSTM Encoder for Dialog Response Generation

Repository: https://github.com/dennybritz/chatbot-retrieval
Canonical: https://ross.abutalabs.com/products/chatbot-retrieval
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2022-11-21T20:51:04+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3789, "days_push": 1381, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1570, forks 665 (observed 2026-08-28T04:05:05.388197+00:00)

## What it is
A reference implementation of the Dual LSTM Encoder model for retrieval-based dialog response selection, built in TensorFlow and trained on the Ubuntu Dialogue Corpus. It accompanies a WildML blog post on deep learning for chatbots and includes scripts for training, evaluation, and prediction.

## Use cases
- learn how to build a retrieval-based chatbot with deep learning
- implement a dual LSTM encoder for dialog response selection
- train a response ranking model on the Ubuntu Dialog Corpus
- understand how to evaluate a next-utterance classification model
- study a worked TensorFlow example for conversational AI

## When to choose
- you want to learn retrieval-based dialog models from a well-known tutorial implementation
- you need a baseline dual encoder architecture for response selection research
- you are working through the Ubuntu Dialogue Corpus paper experiments

## When to avoid
- you need a production-ready chatbot framework or maintained library
- you require modern TensorFlow 2.x or PyTorch compatibility, since the code targets TensorFlow 0.9-era APIs
- you want a generative conversational model rather than retrieval-based response ranking

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: machine-learning, deep-learning, rag, chatbot
- domain: deep-learning, chatbots, machine-learning, tutorials
- platform: python, cross-platform
- tags: dual-lstm-encoder, tensorflow, ubuntu-dialog-corpus, retrieval-based-chatbot, response-selection, reference-implementation, jupyter-notebook, natural-language-processing

## Member repositories
- dennybritz/chatbot-retrieval (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:05.388197+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:58:28.485386+00:00, confidence not recorded.
  - readme: https://github.com/dennybritz/chatbot-retrieval (fetched 2026-08-28T04:05:05.388197+00:00, sha b2a214b7093d)
- Data as of 2026-08-30T08:39:29.467469+00:00.