@iyinoluwaayoola , we explored the use of filters. The filters express conditions on the value of predicates and use the graph traversal (relationships). The similarity using vector embedding introduces a new concept. The similarity is not a materialized relationship and this would cause lot of changes for filters. We found it a good first step to introduce the similarity search at root level with the generated queries. I can see valuable use cases to have similarity in filters for nested level. Please share details when you’ll face those use cases, we will see what can be done.
The two GraphQL queries using vector search open a lot of interesting use cases already. (RAG on Graph, multi-modal search as we support multiple embeddings for the same node, recommendation, semantic search, etc …).
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