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RAG is working, but how to directly query an FAISS knowledge bank?
Added on December 6, 2023 4:22PM
Likes: 0
Replies: 2
Neil_B
Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 9 ✭✭✭✭
Hi All,
We're currently running version 12.3.2 and have had some good success setting up an LLM flow using the public preview recipes. I've got a corpus of text going through the embeddings recipe and generating an FAISS knowledge bank. I've been able to use retrieval augmented generation against the knowledge bank using a prompt recipe. All of this is working great.
What I'd like to understand is, how can I simply query against this knowledge bank for nearest neighbors? I know that when i run the prompt recipe, the 5 nearest neighbors are being retrieved and passed to the LLM as context, and are also cited in the output. If I have a new text string and simply want to retrieve and output the 5 nearest neighbors and their associated document chunks from the knowledge bank, without passing them back to the LLM as part of a prompt, how can I do this? Can anyone provide a python example?
Additionally, for the dataiku folks, will we eventually have another recipe allowing us to do this?
Answers
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Hi Neil,
You might want to have a look at the API reference page for LLM Mesh, more precisely on the KnowledgeBank & associated methods: https://developer.dataiku.com/latest/api-reference/python/llm-mesh.html#dataiku.KnowledgeBank
Hope that helps!
Agathe
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Neil_B Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 9 ✭✭✭✭
Thanks for the link. I looked there first before posting, and the section of the documentation in question seems to have been greatly enhanced since I posted my question. That definitely gives me what I need now, thank you.
-Neil
