hi. When building a vector index from a vector store backed by pinecone, how do I specify the number of documents to be returned for a query?

pinecone_index = self.create_index("books") vector_store = PineconeVectorStore(pinecone_index=pinecone_index) self.vector_store = vector_store service_context = ServiceContext.from_defaults(llm=llm) storage_context = StorageContext.from_defaults(vector_store=vector_store) self.index = VectorStoreIndex.from_vector_store(vector_store) self.query_engine = self.index.as_query_engine() print(self.query_engine.query("foo"))

# query("foo") returns as if similarity_top_k is always 2. It's not clear where to change it since I'm not sure when the retriever is being created.

hi. 0.10.0 has been really bad for me because the docs are inconsistent and the module imports are all wrong in the docs. Is this getting fixed? Should I submit PRs to fix the import paths in the docs?

Also, is there a way to access the docs for the 0.9.x releases ? I tried https://docs.llamaindex.ai/en/0.9.46 and https://docs.llamaindex.ai/en/v0.9.46 but that doesn't work.