fix(llm): keep tool-call ids unique so a recycled id can't erase history

pyproject.toml

@@ -236,6 +236,7 @@ ignore = [
 "strix/interface/auth_cli.py" = ["N802"]
 "tests/test_codex_streaming.py" = ["N802"]
 "tests/test_disable_streaming.py" = ["N802"]
+"tests/test_tool_call_ids.py" = ["N802"]
 "tests/test_unknown_tool_recovery.py" = ["N802"]
 "tests/test_report_pdf.py" = ["S105", "S106"]
 # Stdlib HTTP handler overrides (do_GET/do_POST) and lazy imports that avoid a

strix/config/models.py

@@ -6,7 +6,7 @@ import contextlib
 import inspect
 import os
 import time
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, cast
 
 from agents import (
     set_default_openai_api,
@@ -24,12 +24,18 @@ from agents.retry import (
     RetryPolicyContext,
     retry_policies,
 )
-from openai.types.responses import Response, ResponseCompletedEvent
+from openai.types.responses import (
+    Response,
+    ResponseCompletedEvent,
+    ResponseOutputItemAddedEvent,
+    ResponseOutputItemDoneEvent,
+)
 from openai.types.responses.response_usage import ResponseUsage
 from openai.types.shared import Reasoning
 
 from strix.config import codex
 from strix.config.loader import load_settings
+from strix.config.tool_call_ids import TurnCallIdRewriter, dedupe_input
 
 
 if TYPE_CHECKING:
@@ -229,6 +235,105 @@ class _NonStreamingModel(Model):
         yield _completed_stream_event(response, getattr(self._inner, "model", None))
 
 
+class _UniqueToolCallIdModel(Model):
+    """Keep tool-call ids unique so a recycled id can't invalidate the history.
+
+    Providers that number tool calls per turn (``exec_command:0``, ...) restart
+    the counter each turn, so the same id eventually appears twice in one
+    conversation and strict providers reject every subsequent request. Ids that
+    collide with the history are rewritten before the turn is recorded, and
+    already-corrupted histories are repaired on the way out.
+    """
+
+    def __init__(self, inner: Model) -> None:
+        self._inner = inner
+
+    async def close(self) -> None:
+        await self._inner.close()
+
+    def get_retry_advice(self, request: ModelRetryAdviceRequest) -> ModelRetryAdvice | None:
+        return self._inner.get_retry_advice(request)
+
+    async def get_response(
+        self,
+        system_instructions: str | None,
+        input: str | list[TResponseInputItem],  # noqa: A002
+        model_settings: ModelSettings,
+        tools: list[Tool],
+        output_schema: AgentOutputSchemaBase | None,
+        handoffs: list[Handoff],
+        tracing: ModelTracing,
+        *,
+        previous_response_id: str | None,
+        conversation_id: str | None,
+        prompt: ResponsePromptParam | None,
+    ) -> ModelResponse:
+        sanitized = dedupe_input(input)
+        rewriter = TurnCallIdRewriter(sanitized)
+        response = await self._inner.get_response(
+            system_instructions,
+            cast("str | list[TResponseInputItem]", sanitized),
+            model_settings,
+            tools,
+            output_schema,
+            handoffs,
+            tracing,
+            previous_response_id=previous_response_id,
+            conversation_id=conversation_id,
+            prompt=prompt,
+        )
+        response.output = rewriter.rewrite_items(list(response.output))
+        return response
+
+    async def stream_response(
+        self,
+        system_instructions: str | None,
+        input: str | list[TResponseInputItem],  # noqa: A002
+        model_settings: ModelSettings,
+        tools: list[Tool],
+        output_schema: AgentOutputSchemaBase | None,
+        handoffs: list[Handoff],
+        tracing: ModelTracing,
+        *,
+        previous_response_id: str | None,
+        conversation_id: str | None,
+        prompt: ResponsePromptParam | None,
+    ) -> AsyncIterator[TResponseStreamEvent]:
+        sanitized = dedupe_input(input)
+        rewriter = TurnCallIdRewriter(sanitized)
+        stream = self._inner.stream_response(
+            system_instructions,
+            cast("str | list[TResponseInputItem]", sanitized),
+            model_settings,
+            tools,
+            output_schema,
+            handoffs,
+            tracing,
+            previous_response_id=previous_response_id,
+            conversation_id=conversation_id,
+            prompt=prompt,
+        )
+        async for event in stream:
+            yield _rewrite_event_call_ids(event, rewriter)
+
+
+def _rewrite_event_call_ids(
+    event: TResponseStreamEvent, rewriter: TurnCallIdRewriter
+) -> TResponseStreamEvent:
+    if isinstance(event, ResponseOutputItemAddedEvent | ResponseOutputItemDoneEvent):
+        rewritten = rewriter.rewrite_item(event.item)
+        if rewritten is not event.item:
+            return event.model_copy(update={"item": rewritten})
+        return event
+    if isinstance(event, ResponseCompletedEvent):
+        output = rewriter.rewrite_items(list(event.response.output))
+        if output != list(event.response.output):
+            return event.model_copy(
+                update={"response": event.response.model_copy(update={"output": output})}
+            )
+    return event
+
+
 def _completed_stream_event(
     model_response: ModelResponse, model_name: object | None
 ) -> TResponseStreamEvent:
@@ -305,8 +410,8 @@ class StrixProvider(MultiProvider):
             )
         model = super().get_model(model_name)
         if llm.disable_streaming:
-            return _NonStreamingModel(model)
-        return model
+            model = _NonStreamingModel(model)
+        return _UniqueToolCallIdModel(model)
 
 
 DEFAULT_MODEL_RETRY = ModelRetrySettings(

strix/config/tool_call_ids.py

@@ -0,0 +1,117 @@
+"""Keep tool-call ids unique within a conversation.
+
+Some providers return per-turn tool-call ids (``exec_command:0``,
+``exec_command:1``, ...) whose counter restarts on every turn. Once the same
+id appears twice in one conversation, the request payload has two assistant
+tool calls sharing an id and strict providers reject the whole turn, which
+permanently kills the agent because the malformed history is replayed on
+every retry. Rewriting duplicates to fresh unique ids keeps the history
+valid for any provider.
+"""
+
+from __future__ import annotations
+
+from collections import defaultdict, deque
+from typing import Any
+from uuid import uuid4
+
+from openai.types.responses import ResponseFunctionToolCall
+
+
+def new_call_id() -> str:
+    return f"call_{uuid4().hex}"
+
+
+def collect_call_ids(items: list[Any]) -> set[str]:
+    used: set[str] = set()
+    for item in items:
+        if isinstance(item, dict):
+            call_id = item.get("call_id")
+            if isinstance(call_id, str):
+                used.add(call_id)
+        elif isinstance(item, ResponseFunctionToolCall):
+            used.add(item.call_id)
+    return used
+
+
+def dedupe_history_call_ids(items: list[Any]) -> tuple[list[Any], bool]:
+    """Rewrite duplicate call ids in a conversation history.
+
+    Outputs are paired with their call by order, so parallel calls that share
+    an id keep answering the right call after the rewrite.
+    """
+    used: set[str] = set()
+    pending: dict[str, deque[str]] = defaultdict(deque)
+    rebuilt: list[Any] = []
+    changed = False
+
+    for item in items:
+        if not isinstance(item, dict):
+            rebuilt.append(item)
+            continue
+        call_id = item.get("call_id")
+        if not isinstance(call_id, str):
+            rebuilt.append(item)
+            continue
+
+        kind = item.get("type")
+        if kind == "function_call":
+            effective = call_id
+            if call_id in used:
+                effective = new_call_id()
+                item = {**item, "call_id": effective}  # noqa: PLW2901
+                changed = True
+            used.add(effective)
+            pending[call_id].append(effective)
+        elif kind == "function_call_output":
+            queue = pending.get(call_id)
+            if queue:
+                effective = queue.popleft()
+                if effective != call_id:
+                    item = {**item, "call_id": effective}  # noqa: PLW2901
+                    changed = True
+        rebuilt.append(item)
+
+    return rebuilt, changed
+
+
+def dedupe_input(model_input: str | list[Any]) -> str | list[Any]:
+    if isinstance(model_input, str):
+        return model_input
+    rebuilt, changed = dedupe_history_call_ids(model_input)
+    return rebuilt if changed else model_input
+
+
+class TurnCallIdRewriter:
+    """Rewrite a single turn's tool-call ids that collide with the history.
+
+    A turn's items surface several times (streamed item events, then the
+    completed response), so the same original id must always map to the same
+    replacement within the turn.
+    """
+
+    def __init__(self, model_input: str | list[Any]) -> None:
+        self._used = set() if isinstance(model_input, str) else collect_call_ids(model_input)
+        self._remap: dict[str, str] = {}
+        self._settled: set[str] = set()
+
+    def rewrite_item(self, item: Any) -> Any:
+        if not isinstance(item, ResponseFunctionToolCall):
+            return item
+        original = item.call_id
+        if original in self._settled:
+            return item
+        replacement = self._remap.get(original)
+        if replacement is None:
+            if original not in self._used:
+                self._used.add(original)
+                self._settled.add(original)
+                return item
+            replacement = new_call_id()
+            self._remap[original] = replacement
+            self._used.add(replacement)
+            self._settled.add(replacement)
+        return item.model_copy(update={"call_id": replacement})
+
+    def rewrite_items(self, items: list[Any]) -> list[Any]:
+        return [self.rewrite_item(item) for item in items]

tests/test_disable_streaming.py

@@ -31,7 +31,7 @@ from openai.types.responses import (
 
 from strix.config import codex, loader
 from strix.config.loader import load_settings
-from strix.config.models import StrixProvider, _NonStreamingModel
+from strix.config.models import StrixProvider, _NonStreamingModel, _UniqueToolCallIdModel
 
 
 if TYPE_CHECKING:
@@ -299,10 +299,11 @@ def test_get_model_wraps_when_disabled(
     load_settings()
 
     model = StrixProvider().get_model("openai/gpt-4o-mini")
-    assert isinstance(model, _NonStreamingModel)
+    assert isinstance(model, _UniqueToolCallIdModel)
+    assert isinstance(model._inner, _NonStreamingModel)
 
 
-def test_get_model_unwrapped_by_default(
+def test_get_model_keeps_streaming_by_default(
     monkeypatch: pytest.MonkeyPatch, _reset_settings: None
 ) -> None:
     inner = _DummyModel()
@@ -310,7 +311,8 @@ def test_get_model_unwrapped_by_default(
     load_settings()
 
     model = StrixProvider().get_model("openai/gpt-4o-mini")
-    assert model is inner
+    assert isinstance(model, _UniqueToolCallIdModel)
+    assert model._inner is inner
 
 
 def test_get_model_does_not_wrap_subscription_model(

tests/test_tool_call_ids.py

@@ -0,0 +1,249 @@
+"""Tests for tool-call id uniqueness.
+
+Providers that number tool calls per turn (``exec_command:0``, ``:1``, ...)
+restart the counter on every turn, so the same id eventually appears twice in
+one conversation. Strict providers then reject the whole request, and because
+the history is replayed on every retry the agent can never recover. A gateway
+that validates id uniqueness the way those providers do proves both the
+failure and the fix.
+"""
+
+from __future__ import annotations
+
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, HTTPServer
+from typing import TYPE_CHECKING, Any
+
+import pytest
+from agents import Agent, Runner, function_tool
+from agents.models.interface import Model, ModelProvider
+from agents.models.openai_chatcompletions import OpenAIChatCompletionsModel
+from agents.run import RunConfig
+from openai import AsyncOpenAI
+from openai.types.responses import ResponseFunctionToolCall
+
+from strix.config.models import _NonStreamingModel, _UniqueToolCallIdModel
+from strix.config.tool_call_ids import TurnCallIdRewriter, dedupe_history_call_ids
+
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+
+def _tool_call_completion(call_id: str, n: int = 1) -> dict[str, Any]:
+    return {
+        "id": "chatcmpl-1",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "gw-model",
+        "choices": [
+            {
+                "index": 0,
+                "finish_reason": "tool_calls",
+                "message": {
+                    "role": "assistant",
+                    "content": None,
+                    "tool_calls": [
+                        {
+                            "id": call_id,
+                            "type": "function",
+                            "function": {"name": "do_thing", "arguments": json.dumps({"n": n})},
+                        }
+                    ],
+                },
+            }
+        ],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 2, "total_tokens": 7},
+    }
+
+
+def _text_completion(text: str) -> dict[str, Any]:
+    return {
+        "id": "chatcmpl-2",
+        "object": "chat.completion",
+        "created": 0,
+        "model": "gw-model",
+        "choices": [
+            {"index": 0, "finish_reason": "stop", "message": {"role": "assistant", "content": text}}
+        ],
+        "usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8},
+    }
+
+
+_REQUESTS: list[list[dict[str, Any]]] = []
+
+
+def _assistant_call_ids(messages: list[dict[str, Any]]) -> list[str]:
+    return [str(call.get("id")) for message in messages for call in message.get("tool_calls") or []]
+
+
+def _tool_results(messages: list[dict[str, Any]]) -> list[str]:
+    return [str(m.get("content")) for m in messages if m.get("role") == "tool"]
+
+
+class _StrictHandler(BaseHTTPRequestHandler):
+    """Gateway that rejects a history reusing a tool-call id, like strict providers do."""
+
+    def log_message(self, *args: Any) -> None:
+        pass
+
+    def do_POST(self) -> None:
+        length = int(self.headers.get("Content-Length", 0))
+        body = json.loads(self.rfile.read(length) or b"{}")
+        messages = body.get("messages", [])
+        _REQUESTS.append(messages)
+        call_ids = _assistant_call_ids(messages)
+
+        if len(call_ids) != len(set(call_ids)):
+            self._respond(
+                400,
+                {
+                    "error": {
+                        "message": (
+                            "tool messages need a resolvable tool name: carry `tool`/`name`, "
+                            "or match a preceding assistant tool_call by order"
+                        )
+                    }
+                },
+            )
+            return
+
+        turn = len(_REQUESTS)
+        if turn <= 2:
+            # The provider restarts its per-turn counter, so both turns say ":0".
+            self._respond(200, _tool_call_completion("exec_command:0", n=turn))
+        else:
+            self._respond(200, _text_completion("all done"))
+
+    def _respond(self, status: int, payload: dict[str, Any]) -> None:
+        encoded = json.dumps(payload).encode()
+        self.send_response(status)
+        self.send_header("Content-Type", "application/json")
+        self.send_header("Content-Length", str(len(encoded)))
+        self.end_headers()
+        self.wfile.write(encoded)
+
+
+@pytest.fixture
+def strict_gateway() -> Iterator[str]:
+    _REQUESTS.clear()
+    server = HTTPServer(("127.0.0.1", 0), _StrictHandler)
+    thread = threading.Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    try:
+        yield f"http://127.0.0.1:{server.server_address[1]}/v1"
+    finally:
+        server.shutdown()
+        server.server_close()
+
+
+def _model(base_url: str) -> Model:
+    # The gateway answers plain JSON, so the run loop's streamed turns are
+    # served non-streamed; the ids on the wire are the same either way.
+    client = AsyncOpenAI(api_key="tok", base_url=base_url, max_retries=0)
+    return _NonStreamingModel(OpenAIChatCompletionsModel(model="gw-model", openai_client=client))
+
+
+async def _run_agent(base_url: str, *, wrap: bool) -> Any:
+    @function_tool
+    def do_thing(n: int) -> str:
+        return f"did {n}"
+
+    class _Provider(ModelProvider):
+        def get_model(self, model_name: str | None) -> Model:  # noqa: ARG002
+            model = _model(base_url)
+            return _UniqueToolCallIdModel(model) if wrap else model
+
+    agent = Agent(name="t", instructions="use the tool", tools=[do_thing], model="gw-model")
+    result = Runner.run_streamed(
+        agent, input="please", run_config=RunConfig(model_provider=_Provider())
+    )
+    async for _ in result.stream_events():
+        pass
+    return result
+
+
+@pytest.mark.asyncio
+async def test_recycled_call_id_erases_a_turn_without_the_wrapper(strict_gateway: str) -> None:
+    # Repro: two turns run a tool and both are labelled ``exec_command:0``, so
+    # the colliding call and its result are dropped as duplicates. The agent
+    # ends the run having silently lost a turn of its own work — and a provider
+    # that does not drop them instead rejects the malformed history outright.
+    result = await _run_agent(strict_gateway, wrap=False)
+
+    assert result.final_output == "all done"
+    assert _assistant_call_ids(_REQUESTS[-1]) == ["exec_command:0"]
+    assert _tool_results(_REQUESTS[-1]) == ["did 2"]
+
+
+@pytest.mark.asyncio
+async def test_recycled_call_id_is_rewritten_so_no_turn_is_lost(strict_gateway: str) -> None:
+    result = await _run_agent(strict_gateway, wrap=True)
+
+    assert result.final_output == "all done"
+    call_ids = _assistant_call_ids(_REQUESTS[-1])
+    assert len(call_ids) == len(set(call_ids)) == 2
+    assert call_ids[0] == "exec_command:0"
+    assert call_ids[1].startswith("call_")
+    assert _tool_results(_REQUESTS[-1]) == ["did 1", "did 2"]
+
+
+def test_history_dedupe_keeps_outputs_paired_with_their_call() -> None:
+    items = [
+        {"type": "function_call", "call_id": "exec_command:0", "name": "a", "arguments": "{}"},
+        {"type": "function_call_output", "call_id": "exec_command:0", "output": "first"},
+        {"type": "function_call", "call_id": "exec_command:0", "name": "b", "arguments": "{}"},
+        {"type": "function_call_output", "call_id": "exec_command:0", "output": "second"},
+    ]
+
+    rebuilt, changed = dedupe_history_call_ids(items)
+
+    assert changed
+    ids = [item["call_id"] for item in rebuilt]
+    assert ids[0] == ids[1] == "exec_command:0"
+    assert ids[2] == ids[3] != "exec_command:0"
+    assert rebuilt[3]["output"] == "second"
+
+
+def test_history_dedupe_pairs_parallel_calls_by_order() -> None:
+    items = [
+        {"type": "function_call", "call_id": "dup", "name": "a", "arguments": "{}"},
+        {"type": "function_call", "call_id": "dup", "name": "b", "arguments": "{}"},
+        {"type": "function_call_output", "call_id": "dup", "output": "for-a"},
+        {"type": "function_call_output", "call_id": "dup", "output": "for-b"},
+    ]
+
+    rebuilt, changed = dedupe_history_call_ids(items)
+
+    assert changed
+    assert rebuilt[0]["call_id"] == rebuilt[2]["call_id"] == "dup"
+    assert rebuilt[1]["call_id"] == rebuilt[3]["call_id"]
+    assert rebuilt[1]["call_id"] != "dup"
+
+
+def test_history_dedupe_leaves_unique_ids_alone() -> None:
+    items = [
+        {"type": "function_call", "call_id": "call_a", "name": "a", "arguments": "{}"},
+        {"type": "function_call_output", "call_id": "call_a", "output": "x"},
+        {"type": "function_call", "call_id": "call_b", "name": "b", "arguments": "{}"},
+    ]
+
+    rebuilt, changed = dedupe_history_call_ids(items)
+
+    assert not changed
+    assert rebuilt == items
+
+
+def test_turn_rewriter_is_stable_across_repeated_sightings() -> None:
+    history = [{"type": "function_call", "call_id": "exec_command:0", "name": "a"}]
+    rewriter = TurnCallIdRewriter(history)
+    call = ResponseFunctionToolCall(
+        call_id="exec_command:0", name="a", arguments="{}", type="function_call"
+    )
+
+    first = rewriter.rewrite_item(call)
+    second = rewriter.rewrite_item(first)
+
+    assert first.call_id != "exec_command:0"
+    assert second.call_id == first.call_id