I am exploring Vertex AI search and conversation to build some usecase within my organization. I am looking for more technical details around vertex AI search and conversation . I have below queries
1. Does Vertex AI search and conversation use RAG for data retrieval?
2. If Yes how RAG works in Vertex AI search and conversation , is it within datastore ?
3. When we create datastore , does it create embedding and load in vector database at the backend?
Please someone help with relevant document/answers.
@xavidop help here please.
Hi @VishalBulbule ,
Yes, vertex AI search and conversations is an no-codeRAG platform. When you create a data store it automatically generates the embeddings using an LLM and store them in a vector database. Then you can use that data store in any Vertex AI search & conversation applications: search, recommendation or chat app.
Best,
Xavi
Thanks @xavidop I am having same understanding. Thanks for confirming !
cool! if you want, you can close this post and setting my comment as the solution!
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