Python: [Bug]: No tool output found for function call

[TaoChenOSU]

Description

Agent invocation results in error when chained.

Code Sample

# Copyright (c) Microsoft. All rights reserved.

import asyncio
import os

from agent_framework import Agent, tool
from agent_framework.foundry import FoundryChatClient
from azure.identity import AzureCliCredential
from dotenv import load_dotenv

load_dotenv()


@tool(approval_mode="never_require")
def query_data(
    topic: str,
) -> str:
    """Query internal data about a topic."""
    print(f"  [query_data] topic={topic}")
    return f"Data from default: Revenue for {topic} is $10M."


@tool(approval_mode="never_require")
def get_style(format: str = "plain") -> str:
    """Get the output formatting style."""
    print(f"  [get_style] format={format}")
    return f"Use {format} formatting with bullet points."


async def main() -> None:
    client = FoundryChatClient(
        project_endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
        model=os.environ["FOUNDRY_MODEL"],
        credential=AzureCliCredential(),
    )

    agent_a = Agent(
        client=client,
        name="researcher",
        instructions="Call query_data exactly once with the user's topic. Return the raw result.",
        tools=[query_data],
    )

    agent_b = Agent(
        client=client,
        name="writer",
        instructions="Call get_style exactly once, then rewrite the data as a short report.",
        tools=[get_style],
    )

    response = await agent_a.run("Summarize Q3 revenue.")
    response = await agent_b.run(["Summarize Q3 revenue.", *response.messages])

    return


if __name__ == "__main__":
    asyncio.run(main())

Error Messages / Stack Traces

ERROR: ... service failed to complete the prompt: Error code: 400 -
    {'error': {'message': 'No tool output found for function call <call_id>.',
    'type': 'invalid_request_error', 'param': 'input', 'code': None}}

Package Versions

agent-framework

Python Version

Python 3.12

Additional Context

No response

[TaoChenOSU]

This is potentially related to #5023

Eduard van Valkenburg (@eavanvalkenburg) I did some preliminarily analysis:

The input to the service after the tool is executed locally will have to carry a continuation token in order to continue the service-managed conversation.

In the RawOpenAIChatClient, we do check the continuation token:

However, the options passed to the method only carries the conversation_id:

Looking closer at the function loop, it removes messages based on the availability of the conversation_id:

I don't have the full picture yet for why this will happen and it only happens when the response of an agent is used as the input to another agent. Please help take a look. Thanks!

[eavanvalkenburg]

Just tried your exact script with gpt-5-mini, gpt-4o and o3, but with this change:

    response = await agent_a.run("Summarize Q3 revenue.")
    print("response 1: ", response.text)
    response = await agent_b.run(["Summarize Q3 revenue.", *response.messages])
    print("response 2: ", response.text)

and got this output:

  [query_data] topic=Summarize Q3 revenue.
response 1:  Data from default: Revenue for Summarize Q3 revenue. is $10M.
  [get_style] format=plain
response 2:  - Report: Q3 Revenue Summary
  - Total Q3 revenue: $10M.

So closing this as can't reproduce

[TaoChenOSU]

After spending some more time on investigating the issue, I believe the error originates from the Foundry service. Use the following code to reproduce the issue:

import asyncio
import json
import os

from azure.ai.projects.aio import AIProjectClient
from azure.identity.aio import AzureCliCredential
from dotenv import load_dotenv
from openai import AsyncOpenAI

load_dotenv()


async def run_agent_1(client: AsyncOpenAI):
    # Agent 1
    instructions = "Call query_data exactly once with the user's topic. Return the raw result."

    def query_data(
        topic: str,
    ) -> str:
        """Query internal data about a topic."""
        print(f"  [query_data] topic={topic}")
        return f"Data from default: Revenue for {topic} is $10M."

    tools = [
        {
            "type": "function",
            "name": "query_data",
            "parameters": {
                "type": "object",
                "properties": {
                    "topic": {
                        "type": "string",
                    },
                },
                "required": ["topic"],
            },
        },
    ]

    input_message = [{"role": "user", "content": "Summarize Q3 revenue."}]
    conversation = input_message

    agent_1_response_1 = await client.responses.create(
        model="gpt-5.4",
        input=input_message,
        instructions=instructions,
        tools=tools,
    )

    conversation += agent_1_response_1.output

    for item in agent_1_response_1.output:
        if item.type == "function_call" and item.name == "query_data":
            topic = json.loads(item.arguments)["topic"]
            data = query_data(topic)
            print(f"Responding to function call {item.name} with call_id {item.call_id}")
            input_message = [
                {
                    "type": "function_call_output",
                    "call_id": item.call_id,
                    "output": data,
                }
            ]

    conversation.extend(input_message)

    agent_1_response_2 = await client.responses.create(
        model="gpt-5.4",
        instructions=instructions,
        tools=tools,
        input=input_message,
        previous_response_id=agent_1_response_1.id,
    )
    conversation += agent_1_response_2.output
    print(agent_1_response_2.output_text)

    return conversation


async def run_agent_2(client: AsyncOpenAI, conversation):
    instructions = "Call get_style exactly once, then rewrite the data as a short report."

    def get_style(format: str = "plain") -> str:
        """Get the output formatting style."""
        print(f"  [get_style] format={format}")
        return f"Use {format} formatting with bullet points."

    tools = [
        {
            "type": "function",
            "name": "get_style",
            "parameters": {
                "type": "object",
                "properties": {
                    "format": {
                        "type": "string",
                    },
                },
                "required": ["format"],
            },
        },
    ]

    agent_2_response_1 = await client.responses.create(
        model="gpt-5.4",
        input=conversation,
        instructions=instructions,
        tools=tools,
    )

    for item in agent_2_response_1.output:
        if item.type == "function_call" and item.name == "get_style":
            format = json.loads(item.arguments)["format"]
            style = get_style(format)
            print(f"Responding to function call {item.name} with call_id {item.call_id}")
            input_message = [
                {
                    "type": "function_call_output",
                    "call_id": item.call_id,
                    "output": style,
                }
            ]

    agent_2_response_2 = await client.responses.create(
        model="gpt-5.4",
        instructions=instructions,
        tools=tools,
        input=input_message,
        previous_response_id=agent_2_response_1.id,
    )

    print(agent_2_response_2.output_text)


async def main():
    client = AIProjectClient(
        endpoint=os.environ["FOUNDRY_PROJECT_ENDPOINT"],
        model=os.environ["FOUNDRY_MODEL"],
        credential=AzureCliCredential(),
    ).get_openai_client()

    # # Error won't happen when pointing to OpenAI
    # client = AsyncOpenAI(api_key=os.environ["OPENAI_API_KEY"])

    print("=====Run from Agent 1=====")
    conversation = await run_agent_1(client)

    print("\n====Conversation====")
    for item in conversation:
        print(item)

    print("\n=====Run from Agent 2=====")
    await run_agent_2(client, conversation)


if __name__ == "__main__":
    asyncio.run(main())

Note that the script didn't use Agent Framework at all. The function loop is manual. Reopening this issue to track the status of the issue.

[TaoChenOSU]

Issue opened on the Azure Python SDK repo: Azure/azure-sdk-for-python#46092