Traceback (most recent call last):
  File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/runpy.py", line 188, in _run_module_as_main
    mod_name, mod_spec, code = _get_module_details(mod_name, _Error)
  File "/Library/Developer/CommandLineTools/Library/Frameworks/Python3.framework/Versions/3.9/lib/python3.9/runpy.py", line 111, in _get_module_details
    __import__(pkg_name)
  File "/Users/sumved/genia/scm/genia-llamaindex-0.10/test.py", line 81, in <module>
    query_engine = index.as_query_engine()
  File "/Users/sumved/genia/scm/genia-llamaindex-0.10/venv/lib/python3.9/site-packages/llama_index/core/indices/base.py", line 391, in as_query_engine
    return RetrieverQueryEngine.from_args(
  File "/Users/sumved/genia/scm/genia-llamaindex-0.10/venv/lib/python3.9/site-packages/llama_index/core/query_engine/retriever_query_engine.py", line 108, in from_args
    response_synthesizer = response_synthesizer or get_response_synthesizer(
  File "/Users/sumved/genia/scm/genia-llamaindex-0.10/venv/lib/python3.9/site-packages/llama_index/core/response_synthesizers/factory.py", line 66, in get_response_synthesizer
    prompt_helper = prompt_helper or prompt_helper_from_settings_or_context(
  File "/Users/sumved/genia/scm/genia-llamaindex-0.10/venv/lib/python3.9/site-packages/llama_index/core/settings.py", line 306, in prompt_helper_from_settings_or_context
    return settings.prompt_helper
  File "/Users/sumved/genia/scm/genia-llamaindex-0.10/venv/lib/python3.9/site-packages/llama_index/core/settings.py", line 206, in prompt_helper
    self._prompt_helper = PromptHelper.from_llm_metadata(self._llm.metadata)
AttributeError: 'AzureOpenAI' object has no attribute 'metadata'

# Initialize Service Context
service_context = ServiceContext.from_defaults(
    llm=llm,
    embed_model=embed_model,
    chunk_size=256,
    chunk_overlap=10,
    callback_manager=callback_manager,
)

# configure retriever
retriever = VectorIndexRetriever(
    index=index,
    similarity_top_k=1,
)
# configure response synthesizer
response_synthesizer = get_response_synthesizer(
    streaming=False,
    response_mode=ResponseMode.COMPACT,
    # verbose=True,
)
# assemble query engine
query_engine = RetrieverQueryEngine(
    retriever=retriever,
    response_synthesizer=response_synthesizer,
    node_postprocessors=[SimilarityPostprocessor(similarity_cutoff=0.7)],
)
return query_engine

# construct list_index and vector_index from storage_context and service_context
list_index = ListIndex(nodes, service_context=service_context)
vector_index = VectorStoreIndex(nodes, service_context=service_context)

# define list_query_engine and vector_query_engine
list_query_engine = list_index.as_query_engine(
    response_mode="tree_summarize",
    use_async=True,
)
vector_query_engine = vector_index.as_query_engine()

list_tool = QueryEngineTool.from_defaults(
    query_engine=list_query_engine,
    description="Useful for summarization questions related to the data source",
)
vector_tool = QueryEngineTool.from_defaults(
    query_engine=vector_query_engine,
    description="Useful for retrieving specific context related to the data source",
)

# construct RouterQueryEngine
query_engine = RouterQueryEngine(
    # selector=LLMSingleSelector.from_defaults(),
    selector=PydanticSingleSelector.from_defaults(),
    query_engine_tools=[
        list_tool,
        vector_tool,
    ],
)
response_str = query_engine.query(
    "What is the maximum quantity that can be submitted for a First Leg Order in trading?"
).response

HTTP Request: POST https://visdam-labs.openai.azure.com/chat/completions "HTTP/1.1 404 Resource Not Found"