Hey I could use some help trying to

Hey I could use some help trying to understand the following:

I want to use hybrid search with a weaviate db in a chat engine
I see how I can do that with a query engine with `index.as_query_engine(vector_store_query_mode="hybrid"), but I want to use a chat engine
I'm using the CONDENSE_PLUS_CONTEXT type and I see in the source that it does:

Plain Text

return CondensePlusContextChatEngine.from_defaults(
                retriever=self.as_retriever(**kwargs),
                llm=llm,
                **kwargs,
            )

Would the following work?
`index.as_chat_engine(vector_store_query_mode="hybrid")?

What if I want to do something more complicated like implement this as the retreiver? https://docs.llamaindex.ai/en/stable/examples/retrievers/auto_merging_retriever.html

5 comments

LLogan M

yea that would work, since its passing in the kwargs

AAerk

Thanks!

How would it work if I wanted to do the auto merging retriever?

Are these the steps?

parse my nodes with the hierarchical parser
load into my weaviatevectorstore (WVS)
create a storagecontext (SC) from the WVS
get the leaf nodes from my nodes
put the leaf nodes in a separate WVS (WVS_leaf)
create a retriever from WVS_leaf: RT_leaf=retriever( vector_store_query_mode="hybrid")
create a retriever with RT = AutoMergingRetriever(RT_leaf, SC, vector_store_query_mode="hybrid")
create a chat_engine from WVS index via: index.as_chat_engine(RT, vector_store_query_mode="hybrid")

I appreciate the help!

LLogan M

If you are using an auto merging retriever, you'll need to initialize the chat engine from the class, not the helper function

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CondensePlusContextChatEngine.from_defaults(RT, ...)

AAerk

Got it - so my first set of steps are good, but I just need to pass in retreiver=RT when I make the chat engine?

LLogan M

If you have the retriever, you cant do index.as_chat_engine(), you have to do something similar to the above

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Hey I could use some help trying to