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.

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hi

आपका नाम क्या है

கல்லூரி கட்டண விவரம்

This repo currently contains the starter files.

Clone repo and create a virtual environment

$ gh repo clone Paari1263/team_NTH.exe
$ cd team_NTH.exe
$ 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')

intents.jsoncontains our 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.

Paari.A , Mona Abishek.A, Muralikrishna.S