[ENH] Score Documents - Use SBERT embedding instead of FastText

[PrimozGodec]

Issue

SBERT embedding is (in our opinion) more suitable for measuring distances between embeddings of documents and words. The reason for it is that it embeds complete text and not words separately, which leads to a better representation of the whole context of the document.

Description of changes

This PR replaces FastText embedding with SBERT in Score Document. It also better addresses some weaknesses of the widget:

• It implements the option to send the list of documents to the server. It is used when sending words to the server so that each term is not sent in a separate request.
• When embedding fail widget now shows the warning that similarity cannot be computed since some embeddings were unsuccessful. Before, it failed and didn't show any scores; now, it shows other scores except similarity in case of failure.

Includes

• Code changes
• Tests
• Documentation

[PrimozGodec]

Comparison of fastText (first image) and sBERT (second image) similarity for keyword "bicycle". They look similar, but it seems that sBERT is more focused on actual documents with searched content (on the right side of the image, fewer dots are bright green and yellow).

[PrimozGodec]

/rebase