Weather | Supybot plugin for displaying weather | Frontend Framework library

You are using navigation architecture components, so the navController is the one that should control fragment transactions, you are doing that right with BottomNavigationView.

But within the navDrawer you are doing the transaction through the supportFragmentManager which should be done through the navController instead as both handle the navigation differently.

whenever I select an option on the menu(say settings), it displays the contents of the option along with the bottom navigation view

That is because the BottomNavView is a part of the activity, and you need to move it to a fragment; this requires to change the navigation design of your app; to do that change your app navigation like the below:

Main navigation:

Your usage of computed property is wrong.

You have to bind the computed property status, to each objects inside paints array.

The best option for this one will be creating a seperate component to display the status.

I have refered to this answer for your solution implementation.

Logic

Create a component StatusComponent inside HelloWorld component and pass box, paint and matchingdata as props to it.

So your HelloWorld.vue component will be as below.

template

Because you are using vw in certain places, this unit takes a fixed percentage of browser size of 50vw mean 500px of 1000px screen and 50px of 100px screen, I would suggest to use rem instead also, you can go a bit advanced and use css clamp() to fix width of multiple screen at once.

1. removed /node_modules and yarn.lock file. 2.then reinstalled deleted packages/file using yarn install .

After not getting any further I've posted the same question as an issue in the cfgrib GitHub project, and got a response there: the solution is to add the path of the custom code tables to the ECCODES_DEFINITION_PATH environment variable:

I see you are doing well, you just need to add the API call to a script tag in the same file and then access the input message like this:

Based on your input data, I create my dataframe :

The ZeroShotClassificationPipeline is currently not supported by shap, but you can use a workaround. The workaround is required because:

1. The shap Explainer forwards only one parameter to the model (a pipeline in this case), but the ZeroShotClassificationPipeline requires two parameters, namely text, and labels.
2. The shap Explainer will access the config of your model and use its label2id and id2label properties. They do not match the labels returned from the ZeroShotClassificationPipeline and will result in an error.

Below is a suggestion for one possible workaround. I recommend opening an issue at shap and requesting official support for huggingface's ZeroShotClassificationPipeline.