No tool output found for function call when chaining responses.

[TaoChenOSU]

• Package Name: azure.ai.projects.aio
• Package Version: 2.01
• Operating System: Windows
• Python Version: 3.12

Describe the bug
When passing a full conversation that includes tool calls/results to create a new response, the API will raise No tool output found for function call for a function call/result pair that already exists in the conversation.

To Reproduce

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())

Expected behavior
The code runs without error.

Additional context
This error cannot be reproduced consistently. I am able to get 7 or 8 times out of 10 runs. When pointing to the OpenAI service, this doesn't seem to happen at all.