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Python: [Bug]: Re-polling a background response after a failed poll re-runs its function calls, repeating their side effects

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@sophia-ramsey がすでに取り組んでいます。

2026年10月5日 から。

評価

難易度
4/5
見積もり時間
3〜5日
初心者へのやさしさ
48/100
issue の種類
バグ
明瞭さ
おおむね明確
活発さ
活発
技術スタック
python
領域
backend

調査の方向性

Start with the background-response polling and function loop in _chat_client.py, especially the continuation-token handling around the referenced lines. Run repro.py with the listed package versions to observe the repeated payment after the failed output POST. Trace how the caller-held token and executed function calls are represented, then verify that a re-poll does not repeat the side effect or leaves the caller with a way to continue safely.

索引モデルが issue の本文から書いたものです。

説明

python
Description

This is the caller-side sibling of #5394.

With options={"background": True}, the caller holds a continuation token and
polls with it until it is None, as in the background-responses docs. When the
background response completes with function calls, the poll itself:

  1. runs the calls (the function loop);
  2. POSTs their outputs.

If step 2 fails, for example on a sustained 429 or 503 after the SDK's
retries, the poll raises ChatClientException. The token the caller still
holds names the response that requested the calls. Re-polling with it, the
obvious recovery after an exception (the docs present continuation tokens as
the handle for operations "interrupted by network issues or client timeouts"),
retrieves that response again and runs its calls a second time.

The fix for #5394 (#5462, and #8357 for the streaming resume) handled the
in-loop form of this: it pops continuation_token from
the options dict once the response completes (_chat_client.py, around lines
956–963 and 876–883 in agent-framework-openai 1.14.4; the comment there reads
"the tools run again each time"). The caller-held token is the remaining form.
After an exception the caller has no other token to use, and nothing tells it
that the calls behind that token have already run.

Code Sample
# --- repro.py (verbatim) ---
"""Agent Framework (Python): re-polling a background response with the held
continuation token re-runs the function calls of that response.

Self-contained: `pip install agent-framework-core==1.19.0 agent-framework-openai==1.14.4`
then `python repro.py`. No network access and no API key; nothing leaves 127.0.0.1.

- The agent is the documented background-responses flow: `agent.run(...,
  options={"background": True})`, then poll with `continuation_token` until it
  is None.
- A local fake OpenAI Responses endpoint queues the first request and, on
  retrieve, returns it completed with one `pay_invoice` function call.
  Submitting the function output fails with 429 on every attempt (a sustained
  rate limit or outage after the tool ran).
- A local fake payment provider records each payment.
- When a poll raises, the caller polls once more with the token it holds,
  which is the only token it has.
"""

import asyncio
import json
import threading
import time
import urllib.request
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from typing import Annotated

MODEL, LEDGER = ("127.0.0.1", 8963), ("127.0.0.1", 8964)
PAYMENTS = []  # the provider's ledger: one entry per committed payment
STORED = {}  # response id -> the completed response object
ARGS = {"invoice": "INV-1", "payee": "ACME", "amount": "100.00"}


class Ledger(BaseHTTPRequestHandler):
    def do_POST(self):  # noqa: N802
        self.rfile.read(int(self.headers["Content-Length"]))
        PAYMENTS.append(time.time())
        data = json.dumps({"status": "PAID", "payment": len(PAYMENTS)}).encode()
        self.send_response(200)
        self.send_header("Content-Length", str(len(data)))
        self.end_headers()
        self.wfile.write(data)

    def log_message(self, *args):
        pass


class FakeResponsesAPI(BaseHTTPRequestHandler):
    def send(self, status, obj, headers=()):
        data = json.dumps(obj).encode()
        self.send_response(status)
        self.send_header("Content-Type", "application/json")
        self.send_header("Content-Length", str(len(data)))
        for k, v in headers:
            self.send_header(k, v)
        self.end_headers()
        self.wfile.write(data)

    def do_GET(self):  # noqa: N802  retrieve: the stored response, completed
        rid = self.path.split("?")[0].rstrip("/").rsplit("/", 1)[-1]
        self.send(200, STORED[rid]) if rid in STORED else self.send(404, {"error": {"message": "no such response"}})

    def do_POST(self):  # noqa: N802
        body = json.loads(self.rfile.read(int(self.headers["Content-Length"])))
        items = body.get("input") if isinstance(body.get("input"), list) else []
        if any(isinstance(i, dict) and i.get("type") == "function_call_output" for i in items):
            return self.send(429, {"error": {"message": "Rate limit reached", "type": "requests",
                                             "code": "rate_limit_exceeded"}}, [("retry-after-ms", "50")])
        rid = f"resp_{len(STORED) + 1}"
        STORED[rid] = {
            "id": rid, "object": "response", "created_at": int(time.time()), "status": "completed",
            "model": "gpt-4o-mini", "background": bool(body.get("background")), "store": True,
            "output": [{"type": "function_call", "id": "fc_1", "call_id": "call_1", "name": "pay_invoice",
                        "arguments": json.dumps(ARGS), "status": "completed"}],
            "parallel_tool_calls": True, "tool_choice": "auto", "tools": [], "error": None,
            "incomplete_details": None, "instructions": None, "metadata": {},
            "previous_response_id": body.get("previous_response_id"), "text": {"format": {"type": "text"}},
            "usage": {"input_tokens": 1, "output_tokens": 1, "total_tokens": 2,
                      "input_tokens_details": {"cached_tokens": 0}, "output_tokens_details": {"reasoning_tokens": 0}}}
        self.send(200, dict(STORED[rid], status="queued", output=[], usage=None))

    def log_message(self, *args):
        pass


def serve(addr, handler):
    s = ThreadingHTTPServer(addr, handler)
    s.daemon_threads = True
    threading.Thread(target=s.serve_forever, daemon=True).start()


serve(MODEL, FakeResponsesAPI)
serve(LEDGER, Ledger)

from importlib.metadata import version  # noqa: E402

from agent_framework import Agent, tool  # noqa: E402
from agent_framework.openai import OpenAIChatClient  # noqa: E402
from pydantic import Field  # noqa: E402


@tool(approval_mode="never_require")
def pay_invoice(invoice: Annotated[str, Field(description="Invoice number")],
                payee: Annotated[str, Field(description="Payee account")],
                amount: Annotated[str, Field(description="Amount to pay")]) -> str:
    """Pay a vendor invoice. This moves money and cannot be undone."""
    req = urllib.request.Request(f"http://{LEDGER[0]}:{LEDGER[1]}/pay", method="POST",
                                 data=json.dumps({"invoice": invoice, "payee": payee, "amount": amount}).encode())
    with urllib.request.urlopen(req, timeout=10) as r:
        return r.read().decode()


async def main():
    client = OpenAIChatClient(model="gpt-4o-mini", api_key="placeholder",
                              base_url=f"http://{MODEL[0]}:{MODEL[1]}/v1")
    agent = Agent(client=client, name="PayAgent", instructions="You pay vendor invoices.", tools=[pay_invoice])
    session = agent.create_session()
    response = await agent.run(messages="Pay invoice INV-1 to ACME for 100.00.", session=session,
                               options={"background": True})
    token = response.continuation_token
    print(f"started; holding continuation token {dict(token)}")
    for attempt in (1, 2):  # a poll, then one re-poll with the held token after it raised
        await asyncio.sleep(0.2)
        try:
            response = await agent.run(session=session, options={"continuation_token": token})
            token = response.continuation_token
            print(f"poll {attempt}: ok")
            if token is None:
                break
        except Exception as exc:
            print(f"poll {attempt} raised {type(exc).__name__}  (payments so far: {len(PAYMENTS)})")


print(f"agent-framework-core {version('agent-framework-core')}")
asyncio.run(main())
print(f"payments made for one requested payment: {len(PAYMENTS)}")
# --- end repro.py ---
Error Messages / Stack Traces
### Reproduction

_Re-checked on 2026-10-03 against agent-framework-core 1.20.0 and agent-framework-openai 1.15.0, the current releases: same result._

Self-contained script below (`pip install agent-framework-core==1.19.0
agent-framework-openai==1.14.4`, then `python repro.py`). It needs no network
access and no API key. It uses:
- a local fake Responses endpoint that queues the first request and, on
  retrieve, returns it completed with one `pay_invoice` call;
- a POST of the function output that returns 429 every time;
- a local fake payment provider.

Output:


agent-framework-core 1.19.0
started; holding continuation token {'response_id': 'resp_1'}
poll 1 raised ChatClientException  (payments so far: 1)
poll 2 raised ChatClientException  (payments so far: 2)
payments made for one requested payment: 2


The service never received either function output, so it has no record of
either payment.

### Expected

After a poll has run a response's function calls, re-polling with the same
token should not run them again. Failing that, the caller should get a way to
see that they ran.
Package Versions

agent-framework-core 1.19.0, agent-framework-openai 1.14.4, openai 3.20.0

Python Version

Python 3.13.9

Additional Context
Possible changes
  1. Surface the executed calls when the output POST fails. For example,
    return or raise with a token (or an error attribute) that carries the
    function results already produced, so the next poll submits them instead of
    re-running the tools.
  2. Record executed call_ids per response in the session. On a
    re-retrieve of the same response, skip or refuse the calls that already ran.
  3. At least, document it. Say that a failed poll may have run tools, that
    re-polling with the same token runs them again, and that side-effecting
    tools should key on call_id.

Found while testing retry and resume paths across agent frameworks.

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