Filtering on Vocabulary tags does not work for all tags

You can try setting different types, eg integer instead of string and see if it helps, but Views Filtering support is in any case very limited as filtering options directly in providers like Milvus/Zilliz are not nearly as feature rich as Views from Drupal Core.

Moved to Milvus module since filtering support is specific per provider.

Beyond that you can instead combine with database or solr index and use the Boost with AI Search plugins instead for full Filter support. Downgrading priority given this valid workaround.

@scott_euser I can confirm that I am seeing the same kind of random behavior when trying to ai search view using exposed taxonomy terms.
I have added the taxonomy into the search api field list and set "Filterable attributes" as the Indexing option.

This issue however is not confined just to Milvus/Zilliz. I have both a Zilliz account and also a Pinecone account. I am seeing identical behavior using Pinecone. it feel like it is an issue with the search ai module. This issue might be better moved to another thread or at least duplicated in the Pinecone provider.

Scott, I have just watched your video where you discuss the workaround suggested above. https://youtu.be/WZEh4JOGhhM?t=5989 (Great video by the way!) Can you confirm how this approach works? Does it simply prepend results from the ai search to the results of a solr search. If so I don't think that really solves my use case. Any suggestions on how we can help fix this? Can you point to where the exposed filters are handled in the code base?

Filters still work on top of it, but the filtering needs to be in a View using the Search API Database/SOLR backend, not the AI Search backend.

It's impossible maintain (or even achieve in the first place) feature parity with Views Filters, so you really need to use Database or SOLR backend in the first place.

It doesn't prepend, it adds them into the query. Here is a pseudo query example

SELECY *
FROM index
WHERE
( keyword in :search_terms OR entity_id in :results_from_ai_search)
AND status is published
AND exposed filter is example
AND etc
ORDER BY CASE (order from AI Search).., relevance, etc

Ie, keywords it adds an or by filters are still applied. So if you get 10 results from vector database, still 5 of those might get subsequently excluded by filters. BUT those also might not have been found without vector database if there is semantic meaning match but no actual keyword MATCH (solr has a known bug in the queue so isn't 100% like database yet)

In any case if you want to use filterable attributes it does need to be VBD provider issue queue as that's where the code sits for the basic (nowhere near feature parity) of filtering per provider. Pinecone filtering in their API is completely different from Milvus/Zilliz. In Milvus Zilliz code is at MilvusProvider::prepareFilters() attempts to convert the query conditions to Milvus Zilliz API documentation (again, very basic though)