How to setup vector search on ai search index

Question

Hi Team,

I want to use AI Search in Microsoft Copilot Studio Bot using Share point online as a data Source.

I created Data Source, Index, Indexer on AI Search using App Registration Keys.

But Copilot Studio expecting AI Search should be vectorized.

Can you give idea / code snippet to vectorize the content.

Also , if user add/ update existing content on sharepoint document library how can i update index via Power Automate / Azure Functions , which is the right approach.

Please guide me.

Thanks,

Balaji

Answer 1

Hi there Balaji Mogadali

Thanks for using QandA platform

Guess you need to vectorize your content and manage updates. For vectorization, try text-embedding-ada-002 model can convert text into embeddings. then be added to your AI Search index by defining a vector field in the index schema using Azure Cognitive Search APIs. For eg, you can store embeddings in a field like contentVector. To handle updates when users cahange content in SharePoint, you can use Azure Functions,

If this helps kindly accept the answer thanks much.

Answer 2

Hi Balaji Mogadali,
Greetings & Welcome to Microsoft Q&A forum! Thanks for posting your query!

You can configure a vectorizer in Azure AI Search by defining it in your search index. This involves specifying the embedding model to use for vectorization. You can use models like text-embedding-ada-002 from Azure OpenAI.

Creating a Vector Index: In Azure AI Search, a vector store has an index schema that defines vector and non-vector fields, a vector configuration for algorithms that create and compress the embedding space, and settings on vector field definitions used in query requests.

Hope this helps. Do let us know if you have any further queries.

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