i am using `QueryFusionRetriever` with

i am using QueryFusionRetriever with CondensePlusContextChatEngine, where i am having 2 retrievers BM25Retriever and VectorStoreIndex.from_vector_store and using langfuse for traces. When using condense plus context chat engine the traces are not well serrated like for multiple retrieverss, multiple queries and then fusion nodes. Just like well separated as in index.as_chat_engine

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def get_chat_engine() -> "CondensePlusContextChatEngine":
    Settings.llm = OpenAI(model="gpt-4o", temperature=0.1)
    index = VectorStoreIndex.from_vector_store(vector_store=vector_store)

    retriever = QueryFusionRetriever(
        [
            index.as_retriever(similarity_top_k=3),
            BM25Retriever.from_defaults(nodes=nodes, similarity_top_k=2, verbose=True),
        ],
        similarity_top_k=2,
        num_queries=2,
        mode="reciprocal_rerank",
        use_async=False,
        verbose=True,
        query_gen_prompt=BOT_QUERY_GEN_PROMPT,
    )
    chat_engine = CondensePlusContextChatEngine.from_defaults(
        retriever=retriever, system_prompt=SUPPORT_BOT_SYSTEM_PROMPT, streaming=True
    )
    return chat_engine

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i am using `QueryFusionRetriever` with