Predictive intelligence is not working

[Smriti Rastogi]

I have a very simple use case of predicting the category on a change form on the basis of short_description.

It was working fine but suddenly I see no category being predicted.

Error - - Malformed URL.

Any quick help is appreciated.

[Lener Pacania1]

What happens when you re-train the model?  Does it train successfully.  Malformed URL sometimes happens when you moved a PI solution from a different environment and it lost it's connection to the prediction server.   Do you have a support case open for your error?

[Smriti Rastogi]

Hi Lener,

There is an error in taining the solution.

I am getting Malformed URL in dev environment. The solution definition was created in dev itself.

I have opened a HI case last week.

[Lener Pacania1 · Accepted solution]

Thanks for opening a Hi ticket Smriti.  Malformed URL sometimes also mean that the PI infrastructure was down for your data center at the time of prediction/training or the prediction service system property is no longer correct,  we’ll need support to take a look to find out the actual reason.  Can you please send me the case number at lener.pacania@servicenow.com and I’ll keep an eye on the case.

[Smriti Rastogi]

The issue stems from the missing word vector artifact records in the [sys_attachment] table. The training is failing when it is trying to fetch these records from the instance and it returns a null, as these records do not exist.

There is a known issue with preserving solutions in a clone and this could be a cause for the missing word vector model artifacts that prevents the ML Solution training from completing successfully.

KB0861056: Clone does not preserve ML Solutions when setting property [glide.platform_ml.clone_artifacts] to true.

If you set the system property [glide.wordvector.upgrade_time_frame] from 180 [default] to 0, it will regenerate the word vector model each time you submit your ML Solution for training, and it will increase the time it takes to train the solution. However, it will regenerate all the Machine Learning (ML) artifacts, including the word vector artifacts that are missing that prevents it from being trained.

However we did not clone the system recently.