Answer (Starts With): 

for route in routes:
    print(f"Processing route {idx}/{len_routes}")

    history = []

    history.append(ChatMessage(
        role='assistant',
        content=("Here is all the details of the route."
                 f"The route is defined in the context of the {route.higher_context} context."
                 f"The route is {route.route} and the method is {route.method}."
                 f"The possible responses are {route.responses}."
                 f"The request body is {route.requestBody}."
                 f"The parameters are {route.parameters}."
                 f"The tags are {route.tags}."
                 f"The additional properties are {route.additional_properties}."),
    ))


    function_llm = OpenAI(model="gpt-3.5-turbo")
    agent = OpenAIAgent.from_tools(
        None,
        llm=function_llm,
        verbose=True,
        system_prompt=(
            PROMPT1
        ),
        chat_history=history,
    )   
    agents[route.title()] = agent

    tool_summary = (
        SUMMARY
    )

    doc_tool = QueryEngineTool(
        query_engine=agents[route.title()],
        metadata=ToolMetadata(
            name=f"tool_{route.title()}",
            description=tool_summary,
        ),
    )

    all_tools.append(doc_tool)


    idx += 1


tool_mapping = SimpleToolNodeMapping.from_objects(all_tools)

if not os.path.exists("index"):
    obj_index = ObjectIndex.from_objects(
        all_tools,
        tool_mapping,
        VectorStoreIndex,
    )

    obj_index.persist("index")
else:
    obj_index = ObjectIndex.from_persist_dir("index", tool_mapping)

top_agent = FnRetrieverOpenAIAgent.from_retriever(
    obj_index.as_retriever(similarity_top_k=3),
    system_prompt=(
        PROMPT
    ),
    verbose=True,
    llm=OpenAI(model="gpt-4"),
)