Hybrid search-indexer
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aradhanachaturvedi commented
Hi I want to know this-
I am not using vectorized integration because its still in preview mode. So without this I want to build RAG for my client.
I have below query
- Indexer can Pull data from ADLS , but in case I want to perform hybrid search which requires embedding this will not work. Until and unless I put json which has both text + Embedding in my ADLS
- my source data is in ADLS . So now I need to write separate code for doing chunk+embedding using Azure openAI model (lets say I am using Databricks notebook)
- Whenever any new data comes up in ADLS , I need to call this databricks notebook . So which one will you suggest using Azure function or ADF which will call notebook and create chunks and index it in AI search?
- is there any other better approach ?can we have custom web api skill in indexer to call embedding model endpoint?is that possible