How do I make an app (Could be a web app) after coding everything in jupyter notebook (which includes rasa library)

After I write down all the code (using jupyter notebook) for a chatbot, how do I make a program, app, web app or any other kind of medium for the users?

Users should just see the interface and converse.

@parshvashah14 are you set on creating your own UI, or would you want to set it up into one of our connected channels? We support lots of channels like facebook messenger and slack, or you can put it on a website. Messaging and Voice Channels

You could do all the training and testing in a jupyter notebook, but for that I would recommend taking the trained model and using the command line interface to run the bot.

@erohmensing I am not set on creating my own UI. The Slack Idea is perfect. Thank you for letting me know.

Do you have a code example for this? : You could do all the training and testing in a jupyter notebook, but for that I would recommend taking the trained model and using the command line interface to run the bot.

or any link through which I could learn about it more?

If you create a jupyter notebook and follow along here: Jupyter Notebooks

Once you train a model, it will end up in your output folder, i.e. models/. Then once you are satisfied with your bot, you should use the rasa run --connector slack command to connect your bot to slack. Before doing so, you’ll have to set up slack integration via the instructions here.

Thank you for all your suggestions. Right now my project is on the embryonic stage.

I am trying to achieve ‘academically productive talk chatbot’ with Rasa (Bazaar Architecture is known for it). If you have any suggestions, I am open to all.

As I am going forward with the Rasa tutorial. I feel that I won’t be needing jupyter notebook, and all the work could be done by editing the project files and coding on command line interface (windows 10).

What are the benefits of using a jupyter notebook with rasa?

@parshvashah14 honestly, I think everyone here at rasa would recommend exactly that – editing the project files and coding on the command line interface. We’ve specifically configured it to make it as easy as possible to use the package in this manner instead of having to know what methods and classes to use to get a bot running in a jupyter notebook (which are also more subject to change than the CLI as the code evolves). In addition, if you want to edit/add your NLU data and stories in a friendlier UI, you can use Rasa X.