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Cannot get the last tool_call_output event in stream_events when MaxTurnsExceeded #526

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MartinDai opened this issue Apr 16, 2025 · 3 comments
Open

Cannot get the last tool_call_output event in stream_events when MaxTurnsExceeded #526

MartinDai opened this issue Apr 16, 2025 · 3 comments
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bug Something isn't working

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@MartinDai
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Please read this first

  • Have you read the docs?Agents SDK docs
  • Have you searched for related issues? Others may have faced similar issues.

Describe the bug

Here is my code

with trace("my-agents", group_id=context_manager.conversation_id):
    context_manager.input_items.append(EasyInputMessageParam(content=message, role="user"))
    result = Runner.run_streamed(
        context_manager.current_agent,
        context_manager.input_items,
        context=context_manager.context,
        max_turns=1,
        run_config=RunConfig(model_provider=MODEL_PROVIDER)
    )

    try:
        async for event in result.stream_events():
            if event.type == "raw_response_event":
                if isinstance(event.data, ResponseTextDeltaEvent):
                    final_chunk = create_chunk(conversation_id=context_manager.conversation_id,
                                               content=event.data.delta,
                                               role="assistant", model=MODEL_NAME)
                    yield f"data: {json.dumps(final_chunk)}\n\n"
                else:
                    continue
            elif event.type == "agent_updated_stream_event":
                logger.info(f"Handed off to {event.new_agent.name}")
            elif event.type == "run_item_stream_event":
                if event.item.type == "tool_call_item":
                    content = f"tool call: {event.item.raw_item.name} arguments: {event.item.raw_item.arguments}"
                    logger.info(content)
                    block = create_block(conversation_id=context_manager.conversation_id,
                                         content=content,
                                         role="agent",
                                         model=MODEL_NAME)
                    yield f"data: {json.dumps(block)}\n\n"
                elif event.item.type == "tool_call_output_item":
                    content = f"tool call output: {event.item.output}"
                    logger.info(content)
                    block = create_block(conversation_id=context_manager.conversation_id,
                                         content=content,
                                         role="tool",
                                         model=MODEL_NAME)
                    yield f"data: {json.dumps(block)}\n\n"
                elif event.item.type == "message_output_item":
                    logger.info(f"AI: {ItemHelpers.text_message_output(event.item)}")
                else:
                    continue
            else:
                continue
    except MaxTurnsExceeded:
        logger.warning(f"Max turns exceeded in conversation {context_manager.conversation_id}")
        error_chunk = create_chunk(
            conversation_id=context_manager.conversation_id,
            content="The session has exceeded the limit. The session has been reset. Please start again.",
            role="assistant",
            model=MODEL_NAME
        )
        yield f"data: {json.dumps(error_chunk)}\n\n"
    except Exception as e:
        logger.error(f"Unexpected error: {str(e)}")
        error_chunk = create_chunk(
            conversation_id=context_manager.conversation_id,
            content="An unknown error occurred during processing. Please try again later.",
            role="assistant",
            model=MODEL_NAME
        )
        yield f"data: {json.dumps(error_chunk)}\n\n"

    context_manager.input_items = result.to_input_list()
    context_manager.current_agent = result.last_agent
    conversation.save_conversation(context_manager)

When i start a conversation and the llm's response with a tool call, the code cannot into event.item.type == "tool_call_output_item": branch, but actually the tool call was invoked, i can find tool call result in result.to_input_list()

Debug information

  • Agents SDK version: 0.0.10
  • Python version 3.12.0

Repro steps

Use the code I provided above

Expected behavior

put tool_call_output event to stream_events before throw MaxTurnsExceeded
@MartinDai MartinDai added the bug Something isn't working label Apr 16, 2025
@MartinDai MartinDai changed the title Cannot get last tool_call_output event in stream_events when MaxTurnsExceeded Cannot get the last tool_call_output event in stream_events when MaxTurnsExceeded Apr 16, 2025
@rm-openai
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Hmm yeah the bug here is within stream_events. Specifically, the new items for tool calls etc are enqueued. But before they are yielded, we check the current_turn and raise an error.

Instead, we should probably push events like turn_updated onto the event queue.

I'll try to get to this soon! PR welcome as well.

@visal1214-debug
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Hi,
Do we have any updates on the issue yet?
I’ve encountered it as well, but it happens intermittently.
I’d prefer not to use a manual workaround yet, as it’s not a viable long-term solution.

@visal1214-debug
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visal1214-debug commented May 26, 2025 •
edited
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But what’s important is that I don’t understand why it decides to run the tool again even though the first run already produced the correct output. This seems to contradict the documentation, which states:

The rule for considering the LLM output as a “final output” is that it produces text output of the desired type and does not invoke any further tool calls.

If you need to see it, here’s a snippet of my agent defined as a tool:
` async def init(self):
self.deep_link_pre = await PrepareDeepLinkAgent.create()

    agent_name = "Deep Link Agent"
    self.deep_link_agent = Agent[AgentContext](
        name=agent_name,
        instructions=self.deep_link_pre.deep_link_prompt["deep_link_system_prompt"],
        output_type=self.deep_link_pre.deep_link_output_model,
        model_settings=ModelSettings(
            temperature=chatbot_settings.openai_config["temperature"]
        ),
        hooks=CustomAgentHooks(display_name=agent_name),
    )

    @function_tool(name_override="deep_link_tool")
    async def deep_link_tool(
        ctx: RunContextWrapper[AgentContext],
    ):

        run_output = await Runner.run(
            starting_agent=self.deep_link_agent,
            input=ctx.context.openai_messages,
            context=ctx,
        )
        result = json.dumps(run_output.final_output.model_dump())
        print("result", result)
        return result

    self.tool = deep_link_tool

def get_tool(self) -> Callable:
    if not self.tool:
        raise RuntimeError("Tool not initialized.")
    return self.tool`

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@MartinDai @rm-openai @visal1214-debug