Hello. I have a design question on using

jjma7889

Hello. I have a design question on using Azure AI Search for RAG. I have a large set of document in Azure AI Search that are stored with searchable key doc_id, text chunks, and their embedding. How to use llama index to: query "foo" for embedding only within scope of doc_id="XYZ"? The hybrid mode is not designed for this case. Should I create custom retriever? What is the right approach? Any existing examples? I guess this use case is common to all vector store based RAG. The key is to get the nodes with "XYZ" first then build retreiver with those nodes I guess.

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DDS

I would use a metadata filter

jjma7889

@DS Thank you. I will try that.

jjma7889

@DS metadata filter works for the case, which only works with exact match. It would be great to allow user to pass through more valid ODATA expression, such as

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"filter": "file_id eq 'solicitation 3/GSA.pdf' and search.in(mime_type, 'application/pdf')",

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Hello. I have a design question on using