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This is the Reasoning and Learning Lab participation to The Conversational Intelligence Challenge - NIPS 2017 Live Competition (
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  1. Python 98.8%
  2. Other 1.2%
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NIPS Challenge Docker container

This repository contains the Dockerfile and setup code to run chat bot in docker instance.

Live Deployment

Telegram bot @conv_test. Make sure to have an username registered in Telegram, and then start conversation with \begin.

File description

  • : Main entry point of the chat bot, message selection logic can be implemented here.
  • models/ : Folder where model code is stored
  • data/ : Folder where data files are stored
  • : Configuration script, which has the location of data files as well as bot tokens. Replace the bot token with your ones to test.
  • models/ - Wrapper function which calls the models. Must implement get_response def.
  • models/setup - shell script to download the models
  • data/setup - shell script to download the data files and saved model files
  • - Selection logic for best answer

Running Docker

  • After installing docker, build the image from this directory using the following command: docker build -t convai .
  • Docker will create a virtual container with all the dependencies needed.
  • Docker will autostart the bot whenever the container is run: docker run convai

Adding your own models

  • In models/setup, add the repository of your model (should be a public repository for now) to clone.
  • In data/setup, add the data location to download your saved model data
  • Change the with the endpoint of the data
  • Create a wrapper in models/ for your model
  • Modify the to call your model.


Feel free to open an issue or submit a PR.


Nips ConvAI Challenge McGill RLLDialog Team

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