Deployment of PyTorch chatbot with Flask

Related tags

Deep Learning chatbot-deployment
Overview

Chatbot Deployment with Flask and JavaScript

In this tutorial we deploy the chatbot I created in this tutorial with Flask and JavaScript.

This gives 2 deployment options:

  • Deploy within Flask app with jinja2 template
  • Serve only the Flask prediction API. The used html and javascript files can be included in any Frontend application (with only a slight modification) and can run completely separate from the Flask App then.

Initial Setup:

This repo currently contains the starter files.

Create a virtual environment

$ mkdir chatbot-deployment
$ cd chatbot-deployment
$ python3 -m venv venv
$ . venv/bin/activate

Install dependencies

$ (venv) pip install Flask torch torchvision nltk

Install nltk package

$ (venv) python
>>> import nltk
>>> nltk.download('punkt')

Modify intents.json with different intents and responses for your Chatbot

Run

$ (venv) python train.py

This will dump data.pth file. And then run the following command to test it in the console.

$ (venv) python chat.py

Now for deployment follow my tutorial to implement app.py and app.js.

Credits:

This repo was used for the frontend code: https://github.com/hitchcliff/front-end-chatjs

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Patrick Loeber (Python Engineer)
I create free content about Python and Machine Learning on YouTube and my website.
Patrick Loeber (Python Engineer)
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