**********
Trace: index_construction
**********

vector_store = AzureAISearchVectorStore(
    search_or_index_client=search_client,
    filterable_metadata_field_keys=metadata_fields,
    index_management=IndexManagement.VALIDATE_INDEX,
    id_field_key="id",
    chunk_field_key="chunk",
    embedding_field_key="embedding",
    embedding_dimensionality=1536,
    metadata_string_field_key="metadata",
    doc_id_field_key="doc_id",
)

storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_documents(
    [],
    storage_context=storage_context,
    callback_manager=callback_manager
)

thread = Thread(target=agent.stream_chat, args=(query))
thread.start()

def query_llama_index(query, agent):
        response = agent.stream_chat(query)

queries = ["riddle me this", riddle me that"]
for query in queries:
  thread = Thread(target=query_llama_index, args=(query, agent))
  thread.start()
  thread.join()

def event_generator():
        queue = agent.callback_manager.handlers[0].queue

        # stream response
        while True:
            next_item = queue.get(True, 60.0)  # set a generous timeout of 60 seconds
            # check type of next_item, if string or not
            if isinstance(next_item, EventObject):
                yield convert_sse(dict(next_item))
            elif isinstance(next_item, StreamingAgentChatResponse):
                response = cast(StreamingAgentChatResponse, next_item)
                for text in response.response_gen:
                    yield convert_sse(text)
                break

        return StreamingResponse(event_generator(), media_type="text/event-stream")

CallbackManager

BaseEventHandler

llama_index.core.instrumentation.event_handlers

RetrieverQueryEngine

query_list = [
    "What is the Front Setback Distance for a lot if the lot is in a R-1 zone (Single Family Residential 15 acres gross area), the lot width is 91.2 ft , the lot area is 0.5 acre and the front of the lot is 15 ft from the nearest road centerline. Check Front Secondary first for the answer. Provide a step by step process with references of how you came to the required distance. Also provide just the final required distance. \n\nDesired format:\nProcess:\nDistance: ",
    "What is the Side Setback Distance for a lot if the lot is in a R-1 zone (Single Family Residential 15 acres gross area), the lot width is 91.2 ft  Make sure the answer is no less or more than what is required. Provide a step by step process with references of how you came to the required distance. Also provide just the final required distance. \n\nDesired format:\nProcess:\nDistance: ",
    "What is the Rear Setback Distance for a lot if the lot is in a R-1 zone (Single Family Residential 15 acres gross area), the lot width is 91.2 ft , the lot area is 0.5 and the rear of the lot has has no road access. Make sure the answer is no less or more than what is required. Provide a step by step process with references of how you came to the required distance. Also provide just the final required distance. \n\nDesired format:\nProcess:\nDistance: "
]
    results = []
    for i in query_list:
        res = query_engine.query(i)
        results.append(res)

from llama_index.indices.query.query_transform.base import HyDEQueryTransform
from llama_index.query_engine.transform_query_engine import TransformQueryEngine

# Initialize your index and query engines
query_engine_1 = YourQueryEngine1()
query_engine_2 = YourQueryEngine2()

# Define your query transformation
hyde = HyDEQueryTransform(include_original=True)

# Create an array of query engines
query_engines = [query_engine_1, query_engine_2]

# Create a TransformQueryEngine with the array of query engines and query transformations
transform_query_engine = TransformQueryEngine(query_engines, query_transforms=[transform_1, transform_2])

# Query the index using the TransformQueryEngine
response = transform_query_engine.query("Your query")

# Process the response
# ...

all tools

/usr/local/lib/python3.10/dist-packages/openai/_base_client.py in _request(self, cast_to, options, remaining_retries, stream, stream_cls)
    991 
    992             log.debug("Re-raising status error")
--> 993             raise self._make_status_error_from_response(err.response) from None
    994 
    995         return self._process_response(

BadRequestError: Error code: 400 - {'error': {'message': "'tool_35.24.020 - Purposes of Commercial Zones_C-2 (Retail Commercial) zone.' does not match '^[a-zA-Z0-9_-]{1,64}$' - 'tools.0.function.name'", 'type': 'invalid_request_error', 'param': None, 'code': None}}