Langchain lets you create "tool" or function, like querying an index or searching the web or whatever and "agents" to use those tools based on "reasoning" that you give it

I’ve got a database of a few hundred email newsletters I’ve sent over the years, including open rates, unsubscribes, etc.
I want to query stuff like “what are the common themes between emails with the highest open rates?”
I can’t do that with the sql index alone or simple vector index. That’s where I’m stuck. I’ve tried using sql and vector as tools in langchain but the agent can’t figure it out. I think I need metadata in my simple vector but can’t that out. Can anyone point me in the right direction? Or have a similar use case?

i keep running into this error trying to define the query config for a pinecone index. what should the query config look like?

ValueError("pinecone_index or pinecone_kwargs is required.")
ValueError: pinecone_index or pinecone_kwargs is required.