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1587faeeb9
* test(unit): wait on the work itself instead of fixed sleeps in 21 flaky files Replace sleeps that raced background logging, cache writes, refreshes and thread work with either awaiting that work directly (logging worker flush, the batch logger's flush_queue, the tasks the call spawned, thread joins) or an Event the test's own fake sets when it runs. Each wait keeps a 5s hang guard that never decides pass or fail. Tests that need a fake clock, real sockets, or measure latency are left unchanged, and no production code moves * test(unit): await the tasks each completion spawns instead of yielding once The logging tests yielded once with asyncio.sleep(0) so the task that enqueues the success log could run before the worker flush. That relied on the enqueue happening before the task's first await. Snapshot the running tasks around each acompletion call and await the ones it spawned, so the guarantee holds however many steps sit before the enqueue
2359 lines
88 KiB
Python
2359 lines
88 KiB
Python
"""Regression tests for LIT-4185 — /v1/responses streaming must stamp
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completion_start_time on the first chunk so downstream TTFT consumers
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(Prometheus, OTEL, SpendLogs completionStartTime) do not fall back to
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completion_start_time = end_time."""
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import asyncio, importlib
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import json
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import threading
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from collections.abc import Callable
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from datetime import datetime
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from typing import Final, Optional
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from unittest.mock import AsyncMock, MagicMock, Mock, patch
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import httpx
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import pytest
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from pydantic_core import PydanticSerializationError
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import litellm
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from litellm.exceptions import MidStreamFallbackError
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from litellm.integrations.custom_logger import CustomLogger
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from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
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from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
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from litellm.responses.streaming_iterator import(
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CachedResponsesAPIStreamingIterator,
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MockResponsesAPIStreamingIterator,
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ResponsesAPIStreamingIterator,
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SyncResponsesAPIStreamingIterator,
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_estimate_usage_from_text,
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)
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from litellm.types.llms.openai import (
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ResponseAPIUsage,
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ResponseCompletedEvent,
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ResponsesAPIResponse,
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ResponsesAPIStreamEvents,
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)
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from contextlib import suppress
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from litellm.responses import streaming_iterator as streaming_module
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from litellm.types.utils import CallTypes
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from tests._vcr_conftest_common import install_live_call_probe, record_vcr_outcome
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from types import SimpleNamespace
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def _sse_event(payload: dict) -> bytes:
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return f"data: {json.dumps(payload)}\n\n".encode("utf-8")
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def _mock_config() -> Mock:
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mock_config = Mock(spec=BaseResponsesAPIConfig)
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mock_responses_api_response = ResponsesAPIResponse(
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id="resp_ttft",
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created_at=0,
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status="completed",
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model="gpt-4o-mini",
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object="response",
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output=[],
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usage=ResponseAPIUsage(input_tokens=1, output_tokens=1, total_tokens=2),
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)
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def _transform(model, parsed_chunk, logging_obj):
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evt_type = parsed_chunk.get("type")
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if evt_type == "response.completed":
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return ResponseCompletedEvent(
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type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
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response=mock_responses_api_response,
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)
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stub = Mock()
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stub.type = evt_type
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return stub
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mock_config.transform_streaming_response.side_effect = _transform
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return mock_config
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def _make_iterator(
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*,
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sse_events: list[bytes],
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logging_obj: LiteLLMLoggingObj,
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trailing_error: Optional[Exception] = None,
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config: Mock | None = None,
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request_data: dict | None = None,
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) -> ResponsesAPIStreamingIterator:
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async def aiter_bytes():
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for evt in sse_events:
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yield evt
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if trailing_error is not None:
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raise trailing_error
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mock_response = Mock()
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mock_response.headers = {}
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mock_response.aiter_bytes = aiter_bytes
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return ResponsesAPIStreamingIterator(
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response=mock_response,
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model="gpt-4o-mini",
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responses_api_provider_config=config or _mock_config(),
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logging_obj=logging_obj,
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litellm_metadata={},
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custom_llm_provider="openai",
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request_data=request_data,
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)
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def _make_sync_iterator(
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*,
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sse_events: list[bytes],
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logging_obj: LiteLLMLoggingObj,
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trailing_error: Optional[Exception] = None,
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) -> SyncResponsesAPIStreamingIterator:
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def iter_bytes():
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for evt in sse_events:
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yield evt
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if trailing_error is not None:
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raise trailing_error
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mock_response = Mock()
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mock_response.headers = {}
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mock_response.iter_bytes = iter_bytes
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return SyncResponsesAPIStreamingIterator(
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response=mock_response,
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model="gpt-4o-mini",
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responses_api_provider_config=_mock_config(),
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logging_obj=logging_obj,
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litellm_metadata={},
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custom_llm_provider="openai",
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)
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def _logging_obj_stub() -> Mock:
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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logging_obj.completion_start_time = None
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logging_obj.model_call_details = {"litellm_params": {}}
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return logging_obj
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@pytest.mark.asyncio
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async def test_responses_streaming_stamps_completion_start_time_on_first_chunk():
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"""Without the fix, `logging_obj.completion_start_time` stays None across the
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entire stream and _success_handler_helper_fn falls back to end_time — collapsing
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the reported TTFT to full generation time."""
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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logging_obj.completion_start_time = None
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logging_obj.model_call_details = {"litellm_params": {}}
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stamped: list[datetime] = []
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def _update(*, completion_start_time):
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stamped.append(completion_start_time)
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logging_obj.completion_start_time = completion_start_time
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logging_obj.model_call_details["completion_start_time"] = completion_start_time
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logging_obj.update_completion_start_time.side_effect = _update
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iterator = _make_iterator(
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sse_events=[
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_sse_event({"type": "response.created"}),
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_sse_event({"type": "response.output_text.delta", "delta": "hi"}),
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_sse_event({"type": "response.completed"}),
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],
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logging_obj=logging_obj,
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)
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async for _ in iterator:
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pass
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assert len(stamped) == 1, (
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f"Expected exactly one first-chunk stamp; got {len(stamped)}. "
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"Later chunks must not re-stamp completion_start_time."
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)
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assert isinstance(stamped[0], datetime)
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@pytest.mark.asyncio
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async def test_responses_streaming_does_not_reset_prior_completion_start_time():
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"""If `completion_start_time` is already set (e.g. by an outer wrapper), the
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iterator must not overwrite it — otherwise TTFT would collapse to
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time-to-last-chunk under contention."""
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prior = datetime(2020, 1, 1, 0, 0, 0)
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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logging_obj.completion_start_time = prior
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logging_obj.model_call_details = {"litellm_params": {}}
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iterator = _make_iterator(
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sse_events=[
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_sse_event({"type": "response.created"}),
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_sse_event({"type": "response.completed"}),
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],
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logging_obj=logging_obj,
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)
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async for _ in iterator:
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pass
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logging_obj.update_completion_start_time.assert_not_called()
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assert logging_obj.completion_start_time == prior
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_COMPLETE_STREAM_EVENTS = [
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_sse_event({"type": "response.created"}),
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_sse_event({"type": "response.output_text.delta", "delta": "hi"}),
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_sse_event({"type": "response.completed"}),
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]
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_TRAILING_ERRORS = [
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httpx.ReadError("Response payload is not completed"),
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httpx.RemoteProtocolError("peer closed connection without sending complete message body"),
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]
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@pytest.mark.asyncio
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@pytest.mark.parametrize("trailing_error", _TRAILING_ERRORS, ids=type)
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async def test_transport_error_after_completed_event_ends_stream_cleanly(trailing_error):
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"""A sloppy connection close after `response.completed` must not turn a
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complete stream into an error (regression guard for the transport no longer
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swallowing ClientPayloadError/TransferEncodingError)."""
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iterator = _make_iterator(
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sse_events=_COMPLETE_STREAM_EVENTS,
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logging_obj=_logging_obj_stub(),
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trailing_error=trailing_error,
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)
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seen = [event.type async for event in iterator]
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assert ResponsesAPIStreamEvents.RESPONSE_COMPLETED in seen
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@pytest.mark.asyncio
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async def test_transport_error_before_completed_event_raises():
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"""A connection lost before any terminal event is a real failure and must
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surface, not end the stream as if it completed."""
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iterator = _make_iterator(
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sse_events=_COMPLETE_STREAM_EVENTS[:-1],
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logging_obj=_logging_obj_stub(),
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trailing_error=httpx.ReadError("Response payload is not completed"),
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)
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with pytest.raises(httpx.ReadError):
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async for _ in iterator:
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pass
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@pytest.mark.parametrize("trailing_error", _TRAILING_ERRORS, ids=type)
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def test_sync_transport_error_after_completed_event_ends_stream_cleanly(trailing_error):
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iterator = _make_sync_iterator(
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sse_events=_COMPLETE_STREAM_EVENTS,
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logging_obj=_logging_obj_stub(),
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trailing_error=trailing_error,
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)
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seen = [event.type for event in iterator]
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assert ResponsesAPIStreamEvents.RESPONSE_COMPLETED in seen
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def test_sync_transport_error_before_completed_event_raises():
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iterator = _make_sync_iterator(
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sse_events=_COMPLETE_STREAM_EVENTS[:-1],
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logging_obj=_logging_obj_stub(),
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trailing_error=httpx.ReadError("Response payload is not completed"),
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)
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with pytest.raises(httpx.ReadError):
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for _ in iterator:
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pass
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_DONE_MARKER: Final = b"data: [DONE]\n\n"
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_CREATED_EVENT: Final = _sse_event({"type": "response.created"})
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_IN_PROGRESS_EVENT: Final = _sse_event({"type": "response.in_progress"})
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_PARTIAL_OUTPUT_EVENTS: Final = _COMPLETE_STREAM_EVENTS[:-1]
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_PRE_OUTPUT_PREFIXES: Final = [
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pytest.param([], True, id="nothing-yielded"),
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pytest.param([_CREATED_EVENT], False, id="created"),
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pytest.param([_CREATED_EVENT, _IN_PROGRESS_EVENT], False, id="created-and-in-progress"),
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]
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def _failure_tracking_logging_obj() -> Mock:
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logging_obj: Final = _logging_obj_stub()
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logging_obj.async_failure_handler = AsyncMock()
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return logging_obj
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def _assert_failure_logged_once(logging_obj: Mock, exception: Exception) -> None:
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assert logging_obj.async_failure_handler.await_count == 1
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assert logging_obj.async_failure_handler.await_args.kwargs["exception"] is exception
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@pytest.mark.asyncio
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@pytest.mark.parametrize("prefix, pre_first_chunk", _PRE_OUTPUT_PREFIXES)
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@pytest.mark.parametrize("trailing_error", _TRAILING_ERRORS, ids=type)
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async def test_transport_error_before_any_output_raises_fallback_error(prefix, pre_first_chunk, trailing_error):
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"""A connection lost while only lifecycle events (response.created / response.in_progress)
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have streamed is fallback-eligible, so it must surface as the MidStreamFallbackError the
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router re-routes, carrying the raw transport error and no generated content."""
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_iterator(sse_events=prefix, logging_obj=logging_obj, trailing_error=trailing_error)
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with pytest.raises(MidStreamFallbackError) as exc_info:
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async for _ in iterator:
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pass
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assert exc_info.value.original_exception is trailing_error
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assert exc_info.value.is_pre_first_chunk is pre_first_chunk
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assert exc_info.value.generated_content == ""
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_assert_failure_logged_once(logging_obj, trailing_error)
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@pytest.mark.asyncio
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async def test_transport_error_after_output_started_is_not_fallback_eligible():
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logging_obj: Final = _failure_tracking_logging_obj()
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trailing_error: Final = httpx.ReadError("Response payload is not completed")
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iterator: Final = _make_iterator(
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sse_events=_PARTIAL_OUTPUT_EVENTS, logging_obj=logging_obj, trailing_error=trailing_error
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)
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with pytest.raises(httpx.ReadError) as exc_info:
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async for _ in iterator:
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pass
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assert exc_info.value is trailing_error
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_assert_failure_logged_once(logging_obj, trailing_error)
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@pytest.mark.asyncio
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@pytest.mark.parametrize("trailer", [[], [_DONE_MARKER]], ids=["eof", "done-marker"])
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async def test_stream_ending_after_partial_output_without_terminal_event_raises(trailer):
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"""A clean EOF or `[DONE]` after output text but with no response.completed /
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response.incomplete / response.failed is a truncated answer: the partial events still
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reach the caller, then an explicit error follows instead of a normal end of stream."""
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_iterator(sse_events=[*_PARTIAL_OUTPUT_EVENTS, *trailer], logging_obj=logging_obj)
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created: Final = await iterator.__anext__()
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delta: Final = await iterator.__anext__()
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with pytest.raises(litellm.APIConnectionError) as exc_info:
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await iterator.__anext__()
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assert (created.type, delta.type) == ("response.created", "response.output_text.delta")
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assert not isinstance(exc_info.value, MidStreamFallbackError)
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assert exc_info.value.llm_provider == "openai"
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_assert_failure_logged_once(logging_obj, exc_info.value)
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@pytest.mark.asyncio
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@pytest.mark.parametrize("prefix, pre_first_chunk", _PRE_OUTPUT_PREFIXES)
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@pytest.mark.parametrize("trailer", [[], [_DONE_MARKER]], ids=["eof", "done-marker"])
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async def test_stream_ending_before_any_output_raises_fallback_error(prefix, pre_first_chunk, trailer):
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_iterator(sse_events=[*prefix, *trailer], logging_obj=logging_obj)
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with pytest.raises(MidStreamFallbackError) as exc_info:
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async for _ in iterator:
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pass
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assert isinstance(exc_info.value.original_exception, litellm.APIConnectionError)
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assert exc_info.value.is_pre_first_chunk is pre_first_chunk
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assert exc_info.value.generated_content == ""
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_assert_failure_logged_once(logging_obj, exc_info.value.original_exception)
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@pytest.mark.asyncio
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@pytest.mark.parametrize("trailer", [[], [_DONE_MARKER]], ids=["eof", "done-marker"])
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async def test_complete_stream_still_ends_normally(trailer):
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_iterator(sse_events=[*_COMPLETE_STREAM_EVENTS, *trailer], logging_obj=logging_obj)
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seen: Final = [event.type async for event in iterator]
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assert seen[-1] == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
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assert logging_obj.async_failure_handler.await_count == 0
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@pytest.mark.parametrize("trailing_error", _TRAILING_ERRORS, ids=type)
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def test_sync_transport_error_before_any_output_raises_fallback_error(trailing_error):
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_sync_iterator(
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sse_events=[_CREATED_EVENT, _IN_PROGRESS_EVENT],
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logging_obj=logging_obj,
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trailing_error=trailing_error,
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)
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with pytest.raises(MidStreamFallbackError) as exc_info:
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for _ in iterator:
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pass
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assert exc_info.value.original_exception is trailing_error
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assert exc_info.value.is_pre_first_chunk is False
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assert exc_info.value.generated_content == ""
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_assert_failure_logged_once(logging_obj, trailing_error)
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@pytest.mark.parametrize("trailer", [[], [_DONE_MARKER]], ids=["eof", "done-marker"])
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def test_sync_stream_ending_after_partial_output_without_terminal_event_raises(trailer):
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_sync_iterator(sse_events=[*_PARTIAL_OUTPUT_EVENTS, *trailer], logging_obj=logging_obj)
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created: Final = next(iterator)
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delta: Final = next(iterator)
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with pytest.raises(litellm.APIConnectionError) as exc_info:
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next(iterator)
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assert (created.type, delta.type) == ("response.created", "response.output_text.delta")
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assert not isinstance(exc_info.value, MidStreamFallbackError)
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_assert_failure_logged_once(logging_obj, exc_info.value)
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def test_sync_stream_ending_before_any_output_raises_fallback_error():
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_sync_iterator(sse_events=[_CREATED_EVENT], logging_obj=logging_obj)
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with pytest.raises(MidStreamFallbackError) as exc_info:
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for _ in iterator:
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pass
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assert isinstance(exc_info.value.original_exception, litellm.APIConnectionError)
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assert exc_info.value.is_pre_first_chunk is False
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_assert_failure_logged_once(logging_obj, exc_info.value.original_exception)
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@pytest.mark.parametrize("trailer", [[], [_DONE_MARKER]], ids=["eof", "done-marker"])
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def test_sync_complete_stream_still_ends_normally(trailer):
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logging_obj: Final = _failure_tracking_logging_obj()
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iterator: Final = _make_sync_iterator(sse_events=[*_COMPLETE_STREAM_EVENTS, *trailer], logging_obj=logging_obj)
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seen: Final = [event.type for event in iterator]
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assert seen[-1] == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
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assert logging_obj.async_failure_handler.await_count == 0
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class _LoopRecordingLogger(CustomLogger):
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def __init__(self) -> None:
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super().__init__()
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self.failure_loop: asyncio.AbstractEventLoop | None = None
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self.failure_deployment_id: str | None = None
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self.failure_finished = False
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self.hook_loop: asyncio.AbstractEventLoop | None = None
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self.hook_finished = False
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async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time):
|
|
self.failure_loop = asyncio.get_running_loop()
|
|
self.failure_deployment_id = kwargs["litellm_params"].get("model_info", {}).get("id")
|
|
await asyncio.sleep(0.05)
|
|
self.failure_finished = True
|
|
|
|
async def async_post_call_success_deployment_hook(self, request_data, response, call_type):
|
|
self.hook_loop = asyncio.get_running_loop()
|
|
await asyncio.sleep(0.05)
|
|
self.hook_finished = True
|
|
return None
|
|
|
|
|
|
class _SyncOnlyRecordingLogger(CustomLogger):
|
|
def __init__(self) -> None:
|
|
super().__init__()
|
|
self.sync_failure_finished = False
|
|
|
|
def log_failure_event(self, kwargs, response_obj, start_time, end_time):
|
|
self.sync_failure_finished = True
|
|
|
|
|
|
class _OrderRecordingSyncLogger(CustomLogger):
|
|
def __init__(self, async_recorder: _LoopRecordingLogger) -> None:
|
|
super().__init__()
|
|
self._async_recorder: Final = async_recorder
|
|
self.async_failure_finished_first: bool | None = None
|
|
|
|
def log_failure_event(self, kwargs, response_obj, start_time, end_time):
|
|
self.async_failure_finished_first = self._async_recorder.failure_finished
|
|
|
|
|
|
def _real_logging_obj(
|
|
*, call_type: str = "aresponses", litellm_params: dict[str, object] | None = None
|
|
) -> LiteLLMLoggingObj:
|
|
logging_obj: Final = LiteLLMLoggingObj(
|
|
model="gpt-4o-mini",
|
|
messages=[{"role": "user", "content": "hi"}],
|
|
stream=True,
|
|
call_type=call_type,
|
|
start_time=datetime.now(),
|
|
litellm_call_id="lit-8678-test",
|
|
function_id="lit-8678-test",
|
|
)
|
|
logging_obj.model_call_details["litellm_params"] = (
|
|
dict(litellm_params) if litellm_params is not None else {"aresponses": True}
|
|
)
|
|
return logging_obj
|
|
|
|
|
|
async def _wait_until(condition: Callable[[], bool]) -> None:
|
|
for _ in range(200):
|
|
if condition():
|
|
return
|
|
await asyncio.sleep(0.01)
|
|
raise AssertionError("condition never became true")
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_transport_error_failure_logging_runs_on_the_iterating_loop(monkeypatch):
|
|
"""LIT-8678: a stream failure used to run async_failure_handler on a helper loop in a
|
|
worker thread and block the iterating loop until it finished, so a callback waiting on
|
|
state bound to that loop (a batch logger's flush lock) stalled the whole proxy."""
|
|
recorder: Final = _LoopRecordingLogger()
|
|
monkeypatch.setattr(litellm, "_async_failure_callback", [recorder])
|
|
monkeypatch.setattr(litellm, "failure_callback", [])
|
|
iterator: Final = _make_iterator(
|
|
sse_events=_PARTIAL_OUTPUT_EVENTS,
|
|
logging_obj=_real_logging_obj(),
|
|
trailing_error=httpx.ReadError("Response payload is not completed"),
|
|
)
|
|
|
|
with pytest.raises(httpx.ReadError):
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
assert recorder.failure_finished is True
|
|
assert recorder.failure_loop is asyncio.get_running_loop()
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_failure_logging_finishes_before_the_error_reaches_the_consumer(monkeypatch):
|
|
"""The router's mid-stream fallback re-enters the same logging object for the next
|
|
deployment as soon as it catches the error, so failure logging that still runs after
|
|
the raise reads the fallback deployment's params and cools down the wrong deployment."""
|
|
recorder: Final = _LoopRecordingLogger()
|
|
monkeypatch.setattr(litellm, "_async_failure_callback", [recorder])
|
|
monkeypatch.setattr(litellm, "failure_callback", [])
|
|
logging_obj: Final = _real_logging_obj(
|
|
litellm_params={"aresponses": True, "model_info": {"id": "primary-deployment"}}
|
|
)
|
|
iterator: Final = _make_iterator(
|
|
sse_events=[],
|
|
logging_obj=logging_obj,
|
|
trailing_error=httpx.ReadError("Response payload is not completed"),
|
|
)
|
|
|
|
with pytest.raises(MidStreamFallbackError):
|
|
async for _ in iterator:
|
|
pass
|
|
logging_obj.model_call_details["litellm_params"]["model_info"] = {"id": "fallback-deployment"}
|
|
await _wait_until(lambda: recorder.failure_finished)
|
|
|
|
assert recorder.failure_deployment_id == "primary-deployment"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_sync_stream_failure_inside_a_running_loop_still_runs_sync_only_callbacks(monkeypatch):
|
|
recorder: Final = _SyncOnlyRecordingLogger()
|
|
monkeypatch.setattr(litellm, "failure_callback", [recorder])
|
|
monkeypatch.setattr(litellm, "_async_failure_callback", [])
|
|
iterator: Final = _make_sync_iterator(
|
|
sse_events=_PARTIAL_OUTPUT_EVENTS,
|
|
logging_obj=_real_logging_obj(call_type="responses", litellm_params={}),
|
|
trailing_error=httpx.ReadError("Response payload is not completed"),
|
|
)
|
|
|
|
with pytest.raises(httpx.ReadError):
|
|
for _ in iterator:
|
|
pass
|
|
|
|
await _wait_until(lambda: recorder.sync_failure_finished)
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_sync_failure_callbacks_run_after_async_failure_logging_finishes(monkeypatch):
|
|
"""Both handlers read the same logging object, so the sync one must not start while the
|
|
async one is still running, which is the ordering the blocking dispatch used to give."""
|
|
async_recorder: Final = _LoopRecordingLogger()
|
|
sync_recorder: Final = _OrderRecordingSyncLogger(async_recorder)
|
|
monkeypatch.setattr(litellm, "_async_failure_callback", [async_recorder])
|
|
monkeypatch.setattr(litellm, "failure_callback", [sync_recorder])
|
|
iterator: Final = _make_sync_iterator(
|
|
sse_events=_PARTIAL_OUTPUT_EVENTS,
|
|
logging_obj=_real_logging_obj(call_type="responses", litellm_params={}),
|
|
trailing_error=httpx.ReadError("Response payload is not completed"),
|
|
)
|
|
|
|
with pytest.raises(httpx.ReadError):
|
|
for _ in iterator:
|
|
pass
|
|
|
|
await _wait_until(lambda: sync_recorder.async_failure_finished_first is not None)
|
|
|
|
assert sync_recorder.async_failure_finished_first is True
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_completed_stream_success_deployment_hook_runs_on_the_iterating_loop(monkeypatch):
|
|
recorder: Final = _LoopRecordingLogger()
|
|
monkeypatch.setattr(litellm, "callbacks", [recorder])
|
|
iterator: Final = _make_iterator(sse_events=_COMPLETE_STREAM_EVENTS, logging_obj=_logging_obj_stub())
|
|
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
assert recorder.hook_finished is True
|
|
assert recorder.hook_loop is asyncio.get_running_loop()
|
|
|
|
|
|
def test_stream_cache_write_completes_when_asyncio_run_closes_the_loop(monkeypatch):
|
|
"""
|
|
Regression test for LIT-6184 on the /v1/responses streaming surface: the
|
|
completed-stream cache write was dispatched as a bare fire-and-forget task,
|
|
so asyncio.run cancelled it at loop close before the write landed. The
|
|
write must survive loop shutdown just like the chat-completions one.
|
|
"""
|
|
import asyncio
|
|
from types import SimpleNamespace
|
|
|
|
import litellm
|
|
from litellm.types.utils import CallTypes
|
|
|
|
writes = []
|
|
|
|
class _SlowWriteCache:
|
|
async def async_add_cache(self, result, dynamic_cache_object=None, **kwargs):
|
|
await asyncio.sleep(0.2)
|
|
writes.append(result)
|
|
|
|
def add_cache(self, *args, **kwargs):
|
|
raise AssertionError("sync write must not run on the async path")
|
|
|
|
caching_handler = SimpleNamespace(
|
|
request_kwargs={
|
|
"model": "test-model",
|
|
"input": "hello",
|
|
"stream": True,
|
|
"caching": True,
|
|
"metadata": None,
|
|
"custom_llm_provider": "openai",
|
|
},
|
|
preset_cache_key="responses-stream-cache-key",
|
|
original_function=litellm.aresponses,
|
|
dual_cache=None,
|
|
_should_store_result_in_cache=lambda original_function, kwargs: True,
|
|
)
|
|
logging_obj = SimpleNamespace(
|
|
model_call_details={"litellm_params": {}},
|
|
llm_caching_handler=caching_handler,
|
|
)
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=Mock(spec=BaseResponsesAPIConfig),
|
|
logging_obj=logging_obj,
|
|
request_data=caching_handler.request_kwargs,
|
|
call_type=CallTypes.aresponses.value,
|
|
)
|
|
iterator.completed_response = ResponseCompletedEvent(
|
|
type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
|
|
response=ResponsesAPIResponse(
|
|
id="resp_lit6184",
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="completed",
|
|
model="test-model",
|
|
object="response",
|
|
output=[
|
|
{
|
|
"type": "message",
|
|
"id": "msg_lit6184",
|
|
"status": "completed",
|
|
"role": "assistant",
|
|
"content": [{"type": "output_text", "text": "cached", "annotations": []}],
|
|
}
|
|
],
|
|
),
|
|
)
|
|
monkeypatch.setattr(litellm, "cache", _SlowWriteCache())
|
|
|
|
async def _short_lived_script():
|
|
iterator._persist_completed_response_to_cache(is_async=True)
|
|
|
|
asyncio.run(_short_lived_script())
|
|
|
|
assert len(writes) == 1
|
|
|
|
|
|
def test_run_post_success_hooks_does_not_report_generation_time_as_overhead():
|
|
"""LIT-5466: the provider call is timed to first byte, so at stream completion the total minus
|
|
that duration is token generation, not LiteLLM overhead."""
|
|
logging_obj = _logging_obj_stub()
|
|
logging_obj.model_call_details = {"litellm_params": {}, "llm_api_duration_ms": 200.0}
|
|
logging_obj.caching_details = None
|
|
|
|
class _CompletedEvent:
|
|
def __init__(self) -> None:
|
|
self._hidden_params: dict = {}
|
|
|
|
iterator = _make_iterator(sse_events=[], logging_obj=logging_obj)
|
|
iterator.completed_response = _CompletedEvent()
|
|
iterator.start_time = datetime(2025, 1, 1, 0, 0, 0)
|
|
|
|
iterator._run_post_success_hooks(datetime(2025, 1, 1, 0, 0, 10))
|
|
|
|
assert iterator.completed_response._hidden_params["_response_ms"] == 10000.0
|
|
assert "litellm_overhead_time_ms" not in iterator.completed_response._hidden_params
|
|
|
|
|
|
def _mock_config_with_completed_response(response: ResponsesAPIResponse) -> Mock:
|
|
mock_config = Mock(spec=BaseResponsesAPIConfig)
|
|
|
|
def _transform(model, parsed_chunk, logging_obj):
|
|
evt_type = parsed_chunk.get("type")
|
|
if evt_type == "response.completed":
|
|
return ResponseCompletedEvent(
|
|
type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
|
|
response=response,
|
|
)
|
|
stub = Mock()
|
|
stub.type = evt_type
|
|
if "delta" in parsed_chunk:
|
|
stub.delta = parsed_chunk.get("delta")
|
|
if "item" in parsed_chunk:
|
|
stub.item = parsed_chunk.get("item")
|
|
return stub
|
|
|
|
mock_config.transform_streaming_response.side_effect = _transform
|
|
return mock_config
|
|
|
|
|
|
def _responses_api_response_without_usage() -> ResponsesAPIResponse:
|
|
return ResponsesAPIResponse(
|
|
id="resp_no_usage",
|
|
created_at=int(datetime(2025, 1, 1).timestamp()),
|
|
status="completed",
|
|
model="gpt-4o-mini",
|
|
object="response",
|
|
output=[],
|
|
usage=None,
|
|
)
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_completed_event_without_usage_gets_text_estimate():
|
|
"""A response.completed event carrying usage: null still bills: the
|
|
iterator estimates usage from the request input and generated text."""
|
|
response = _responses_api_response_without_usage()
|
|
iterator = _make_iterator(
|
|
sse_events=[
|
|
_sse_event({"type": "response.output_text.delta", "delta": "hello world"}),
|
|
_sse_event({"type": "response.completed", "response": {}}),
|
|
],
|
|
logging_obj=_logging_obj_stub(),
|
|
config=_mock_config_with_completed_response(response),
|
|
request_data={"input": "count these input tokens please"},
|
|
)
|
|
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
usage = iterator.completed_response.response.usage
|
|
assert usage is not None
|
|
assert usage.input_tokens > 0
|
|
assert usage.output_tokens > 0
|
|
assert usage.total_tokens == usage.input_tokens + usage.output_tokens
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_completed_event_with_usage_is_left_untouched():
|
|
"""Provider-reported usage on response.completed wins over the estimate."""
|
|
response = _responses_api_response_with_usage()
|
|
iterator = _make_iterator(
|
|
sse_events=[
|
|
_sse_event({"type": "response.output_text.delta", "delta": "hello world"}),
|
|
_sse_event({"type": "response.completed", "response": {}}),
|
|
],
|
|
logging_obj=_logging_obj_stub(),
|
|
config=_mock_config_with_completed_response(response),
|
|
request_data={"input": "count these input tokens please"},
|
|
)
|
|
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
usage = iterator.completed_response.response.usage
|
|
assert usage.input_tokens == 20
|
|
assert usage.output_tokens == 60
|
|
assert usage.total_tokens == 80
|
|
|
|
|
|
def _responses_api_response_with_usage() -> ResponsesAPIResponse:
|
|
return ResponsesAPIResponse(
|
|
id="resp_lit6427",
|
|
created_at=int(datetime(2025, 1, 1).timestamp()),
|
|
status="completed",
|
|
model="mantle-claude",
|
|
object="response",
|
|
output=[],
|
|
usage=ResponseAPIUsage(input_tokens=20, output_tokens=60, total_tokens=80),
|
|
)
|
|
|
|
|
|
def test_stamp_responses_usage_cost_stamps_computed_cost():
|
|
from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
|
|
|
|
response = _responses_api_response_with_usage()
|
|
logging_obj = Mock(spec=LiteLLMLoggingObj)
|
|
logging_obj.response_cost_calculator.return_value = 0.000704
|
|
|
|
_stamp_responses_usage_cost(response, logging_obj)
|
|
|
|
assert getattr(response.usage, "cost", None) == pytest.approx(0.000704)
|
|
logging_obj.response_cost_calculator.assert_called_once_with(result=response)
|
|
|
|
|
|
def test_stamp_responses_usage_cost_keeps_provider_reported_cost():
|
|
from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
|
|
|
|
response = _responses_api_response_with_usage()
|
|
setattr(response.usage, "cost", 0.5)
|
|
logging_obj = Mock(spec=LiteLLMLoggingObj)
|
|
|
|
_stamp_responses_usage_cost(response, logging_obj)
|
|
|
|
assert getattr(response.usage, "cost", None) == pytest.approx(0.5)
|
|
logging_obj.response_cost_calculator.assert_not_called()
|
|
|
|
|
|
def _unvalidated_response_with_dict_usage(usage: dict) -> ResponsesAPIResponse:
|
|
return ResponsesAPIResponse.model_construct(
|
|
id="resp_lit7391",
|
|
created_at=int(datetime(2025, 1, 1).timestamp()),
|
|
status="completed",
|
|
model="perplexity/deepseek-v4-flash-0731",
|
|
object="response",
|
|
output=[],
|
|
truncation="",
|
|
usage=usage,
|
|
)
|
|
|
|
|
|
def test_stamp_responses_usage_cost_keeps_provider_cost_from_dict_usage():
|
|
from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
|
|
response = _unvalidated_response_with_dict_usage(
|
|
{
|
|
"input_tokens": 29,
|
|
"output_tokens": 120,
|
|
"output_tokens_details": {"reasoning_tokens": 117},
|
|
"total_tokens": 149,
|
|
"cost": {"currency": "USD", "input_cost": 0, "output_cost": 3e-05, "total_cost": 3e-05},
|
|
}
|
|
)
|
|
logging_obj = Mock(spec=LiteLLMLoggingObj)
|
|
|
|
_stamp_responses_usage_cost(response, logging_obj)
|
|
|
|
assert isinstance(response.usage, ResponseAPIUsage)
|
|
assert response.usage.cost == pytest.approx(3e-05)
|
|
assert response.usage.output_tokens_details.reasoning_tokens == 117
|
|
logging_obj.response_cost_calculator.assert_not_called()
|
|
|
|
|
|
def test_stamp_responses_usage_cost_computes_cost_for_dict_usage_without_cost():
|
|
from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
|
|
response = _unvalidated_response_with_dict_usage({"input_tokens": 29, "output_tokens": 120, "total_tokens": 149})
|
|
logging_obj = Mock(spec=LiteLLMLoggingObj)
|
|
logging_obj.response_cost_calculator.return_value = 0.000704
|
|
|
|
_stamp_responses_usage_cost(response, logging_obj)
|
|
|
|
assert isinstance(response.usage, ResponseAPIUsage)
|
|
assert response.usage.cost == pytest.approx(0.000704)
|
|
logging_obj.response_cost_calculator.assert_called_once_with(result=response)
|
|
|
|
|
|
def test_stamp_responses_usage_cost_survives_calculator_failure():
|
|
from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
|
|
|
|
response = _responses_api_response_with_usage()
|
|
logging_obj = Mock(spec=LiteLLMLoggingObj)
|
|
logging_obj.response_cost_calculator.side_effect = RuntimeError("cost map unavailable")
|
|
|
|
_stamp_responses_usage_cost(response, logging_obj)
|
|
|
|
assert getattr(response.usage, "cost", None) is None
|
|
|
|
|
|
def _capture_dispatch(logged: list):
|
|
"""Record the object handed to the success handlers.
|
|
|
|
``Mock(spec=LiteLLMLoggingObj).dispatch_success_handlers`` is an AsyncMock whose side effect
|
|
only runs when the coroutine is awaited, so capture with a plain function instead.
|
|
"""
|
|
|
|
async def _noop() -> None:
|
|
return None
|
|
|
|
def _dispatch(result, **kwargs):
|
|
logged.append(result)
|
|
return _noop()
|
|
|
|
return _dispatch
|
|
|
|
|
|
def _headers_config(*, transform_hidden_params: Optional[dict] = None) -> Mock:
|
|
"""Config whose completed event carries a real ResponsesAPIResponse, so the logging copy
|
|
performs a genuine model_dump/model_validate round trip."""
|
|
mock_config = Mock(spec=BaseResponsesAPIConfig)
|
|
|
|
def _transform(model, parsed_chunk, logging_obj):
|
|
evt_type = parsed_chunk.get("type")
|
|
if evt_type != "response.completed":
|
|
stub = Mock()
|
|
stub.type = evt_type
|
|
return stub
|
|
response = ResponsesAPIResponse(
|
|
id="resp_headers",
|
|
created_at=1,
|
|
output=[],
|
|
parallel_tool_calls=False,
|
|
tool_choice="auto",
|
|
tools=[],
|
|
)
|
|
if transform_hidden_params is not None:
|
|
response._hidden_params.update(transform_hidden_params)
|
|
return ResponseCompletedEvent(
|
|
type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
|
|
response=response,
|
|
)
|
|
|
|
mock_config.transform_streaming_response.side_effect = _transform
|
|
return mock_config
|
|
|
|
|
|
def _make_header_iterator(
|
|
*,
|
|
headers: dict,
|
|
config: Mock,
|
|
logging_obj: LiteLLMLoggingObj,
|
|
) -> ResponsesAPIStreamingIterator:
|
|
async def aiter_bytes():
|
|
yield _sse_event({"type": "response.completed"})
|
|
|
|
mock_response = Mock()
|
|
mock_response.headers = headers
|
|
mock_response.aiter_bytes = aiter_bytes
|
|
|
|
return ResponsesAPIStreamingIterator(
|
|
response=mock_response,
|
|
model="gpt-4o-mini",
|
|
responses_api_provider_config=config,
|
|
logging_obj=logging_obj,
|
|
litellm_metadata={},
|
|
custom_llm_provider="azure",
|
|
)
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_streaming_logging_response_carries_provider_response_headers():
|
|
"""LIT-6055: the provider headers the iterator captured must reach the logged response, so
|
|
custom loggers can read Azure's apim-request-id from the callback payload."""
|
|
logging_obj = _logging_obj_stub()
|
|
logged: list[object] = []
|
|
logging_obj.dispatch_success_handlers = _capture_dispatch(logged)
|
|
|
|
logging_obj._on_deferred_stream_complete = None
|
|
|
|
iterator = _make_header_iterator(
|
|
headers={"apim-request-id": "azure-correlation-1", "x-ms-region": "East US 2"},
|
|
config=_headers_config(),
|
|
logging_obj=logging_obj,
|
|
)
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
assert len(logged) == 1
|
|
hidden_params = logged[0].response._hidden_params
|
|
assert hidden_params["additional_headers"]["llm_provider-apim-request-id"] == "azure-correlation-1"
|
|
assert hidden_params["additional_headers"]["llm_provider-x-ms-region"] == "East US 2"
|
|
assert hidden_params["headers"]["apim-request-id"] == "azure-correlation-1"
|
|
# the proxy builds the client's response headers from the iterator's own dict, so the logged
|
|
# response must hold copies rather than alias it
|
|
assert hidden_params["additional_headers"] is not iterator._hidden_params["additional_headers"]
|
|
assert hidden_params["headers"] is not iterator._raw_response_headers
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_streaming_logging_copy_preserves_transform_hidden_params():
|
|
"""LIT-6055: model_validate(model_dump()) drops pydantic private attributes, so headers a
|
|
provider transform already set on the response (fake_stream) must be re-applied."""
|
|
logging_obj = _logging_obj_stub()
|
|
logged: list[object] = []
|
|
logging_obj.dispatch_success_handlers = _capture_dispatch(logged)
|
|
|
|
logging_obj._on_deferred_stream_complete = None
|
|
|
|
iterator = _make_header_iterator(
|
|
headers={},
|
|
config=_headers_config(
|
|
transform_hidden_params={
|
|
"additional_headers": {"llm_provider-apim-request-id": "from-transform"},
|
|
"headers": {"apim-request-id": "from-transform"},
|
|
"response_cost": 0.5,
|
|
}
|
|
),
|
|
logging_obj=logging_obj,
|
|
)
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
assert len(logged) == 1
|
|
hidden_params = logged[0].response._hidden_params
|
|
assert hidden_params["additional_headers"]["llm_provider-apim-request-id"] == "from-transform"
|
|
assert hidden_params["headers"]["apim-request-id"] == "from-transform"
|
|
assert iterator.completed_response is not logged[0]
|
|
# only the header keys travel: response_cost would short-circuit the cost calculator
|
|
assert "response_cost" not in hidden_params
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_streaming_logging_copy_fallback_leaves_caller_event_untouched():
|
|
"""LIT-6055: when the logging copy falls back to the original event, the header restore must
|
|
not stamp logging-only state onto the object the caller is iterating."""
|
|
logging_obj = _logging_obj_stub()
|
|
logged: list[object] = []
|
|
logging_obj.dispatch_success_handlers = _capture_dispatch(logged)
|
|
logging_obj._on_deferred_stream_complete = None
|
|
|
|
iterator = _make_header_iterator(
|
|
headers={"apim-request-id": "azure-correlation-1"},
|
|
config=_headers_config(),
|
|
logging_obj=logging_obj,
|
|
)
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
assert len(logged) == 1
|
|
iterator._completed_response_logged = False
|
|
logged.clear()
|
|
with patch.object(type(iterator.completed_response), "model_dump", side_effect=ValueError("cannot serialize")):
|
|
iterator._log_completed_response(is_async=True)
|
|
|
|
assert len(logged) == 1
|
|
assert logged[0] is not iterator.completed_response
|
|
assert logged[0].response is not iterator.completed_response.response
|
|
assert logged[0].response._hidden_params["headers"]["apim-request-id"] == "azure-correlation-1"
|
|
assert iterator.completed_response.response._hidden_params == {}
|
|
|
|
|
|
def _unvalidated_completed_config() -> Mock:
|
|
"""Config whose completed event carries a Perplexity-style response that fails validation
|
|
(``truncation: ""``) and already holds the stamped ``ResponseAPIUsage``."""
|
|
mock_config = Mock(spec=BaseResponsesAPIConfig)
|
|
|
|
def _transform(model, parsed_chunk, logging_obj):
|
|
response = _unvalidated_response_with_dict_usage(
|
|
ResponseAPIUsage(input_tokens=29, output_tokens=373, total_tokens=402, cost={"total_cost": 0.0001})
|
|
)
|
|
return ResponseCompletedEvent(type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED, response=response)
|
|
|
|
mock_config.transform_streaming_response.side_effect = _transform
|
|
return mock_config
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_streaming_logging_copy_keeps_client_usage_when_response_fails_validation():
|
|
"""LIT-7391: the logging copy cannot round-trip a response that fails validation, and logging
|
|
rewrites the assembled response's usage to chat shape in place, so the event handed to logging
|
|
must never be the one the caller receives."""
|
|
logging_obj = _logging_obj_stub()
|
|
logging_obj.stream = True
|
|
logged: list[object] = []
|
|
logging_obj.dispatch_success_handlers = _capture_dispatch(logged)
|
|
logging_obj._on_deferred_stream_complete = None
|
|
|
|
iterator = _make_header_iterator(headers={}, config=_unvalidated_completed_config(), logging_obj=logging_obj)
|
|
events = [event async for event in iterator]
|
|
|
|
assert len(logged) == 1
|
|
now = datetime.now()
|
|
LiteLLMLoggingObj._get_assembled_streaming_response(
|
|
logging_obj, logged[0], start_time=now, end_time=now, is_async=True, streaming_chunks=[]
|
|
)
|
|
assert logged[0].response.usage["prompt_tokens"] == 29
|
|
|
|
client_usage = events[-1].response.usage
|
|
assert isinstance(client_usage, ResponseAPIUsage)
|
|
assert client_usage.input_tokens == 29
|
|
assert client_usage.cost == pytest.approx(0.0001)
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_completed_event_without_usage_counts_tool_call_arguments():
|
|
"""A function-call-only stream still bills output tokens: streamed
|
|
function_call_arguments deltas feed the text estimate."""
|
|
response = _responses_api_response_without_usage()
|
|
iterator = _make_iterator(
|
|
sse_events=[
|
|
_sse_event(
|
|
{
|
|
"type": "response.output_item.added",
|
|
"item": {"type": "function_call", "name": "get_weather", "call_id": "call_1"},
|
|
}
|
|
),
|
|
_sse_event(
|
|
{
|
|
"type": "response.function_call_arguments.delta",
|
|
"delta": '{"location": "San Francisco", "unit": "celsius"}',
|
|
}
|
|
),
|
|
_sse_event({"type": "response.completed", "response": {}}),
|
|
],
|
|
logging_obj=_logging_obj_stub(),
|
|
config=_mock_config_with_completed_response(response),
|
|
request_data={"input": "what is the weather in san francisco"},
|
|
)
|
|
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
usage = iterator.completed_response.response.usage
|
|
assert usage is not None
|
|
assert usage.output_tokens > 0
|
|
assert usage.total_tokens == usage.input_tokens + usage.output_tokens
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_completed_event_without_usage_counts_multimodal_input_as_messages():
|
|
"""Multimodal request input is counted as chat messages, not as a JSON blob:
|
|
a huge base64 image must not inflate the estimated input tokens."""
|
|
image_input: Final = [
|
|
{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "input_text", "text": "what is in this image"},
|
|
{
|
|
"type": "input_image",
|
|
"image_url": "data:image/png;base64," + "A" * 4000,
|
|
},
|
|
],
|
|
}
|
|
]
|
|
json_count: Final = litellm.token_counter(model="gpt-4o-mini", text=json.dumps(image_input))
|
|
response = _responses_api_response_without_usage()
|
|
iterator = _make_iterator(
|
|
sse_events=[
|
|
_sse_event({"type": "response.output_text.delta", "delta": "it is a cat"}),
|
|
_sse_event({"type": "response.completed", "response": {}}),
|
|
],
|
|
logging_obj=_logging_obj_stub(),
|
|
config=_mock_config_with_completed_response(response),
|
|
request_data={"input": image_input},
|
|
)
|
|
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
usage = iterator.completed_response.response.usage
|
|
assert usage is not None
|
|
assert usage.input_tokens < json_count / 2
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_completed_event_survives_a_failing_usage_estimate():
|
|
"""A malformed request input that makes the message transformer raise must not
|
|
break a stream that previously completed: the estimate is best-effort and
|
|
falls back to usage None."""
|
|
malformed_input: Final = [{"type": "message", "role": "user", "content": 42}]
|
|
with pytest.raises(ValueError, match="Invalid content type"):
|
|
_estimate_usage_from_text("gpt-4o-mini", malformed_input, {"input": malformed_input}, "hello world")
|
|
|
|
response = _responses_api_response_without_usage()
|
|
iterator = _make_iterator(
|
|
sse_events=[
|
|
_sse_event({"type": "response.output_text.delta", "delta": "hello world"}),
|
|
_sse_event({"type": "response.completed", "response": {}}),
|
|
],
|
|
logging_obj=_logging_obj_stub(),
|
|
config=_mock_config_with_completed_response(response),
|
|
request_data={"input": malformed_input},
|
|
)
|
|
|
|
yielded: list = []
|
|
async for chunk in iterator:
|
|
yielded.append(chunk)
|
|
|
|
assert yielded
|
|
assert iterator.completed_response.response.usage is None
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
@pytest.mark.parametrize(
|
|
"tool_delta_event_type",
|
|
["response.custom_tool_call_input.delta", "response.mcp_call_arguments.delta"],
|
|
)
|
|
async def test_completed_event_without_usage_counts_tool_input_deltas(tool_delta_event_type):
|
|
"""Custom-tool and MCP argument deltas feed the streamed usage fallback the
|
|
same way function_call_arguments deltas do."""
|
|
response = _responses_api_response_without_usage()
|
|
iterator = _make_iterator(
|
|
sse_events=[
|
|
_sse_event({"type": tool_delta_event_type, "delta": '{"query": "weather in sf"}'}),
|
|
_sse_event({"type": "response.completed", "response": {}}),
|
|
],
|
|
logging_obj=_logging_obj_stub(),
|
|
config=_mock_config_with_completed_response(response),
|
|
request_data={"input": "what is the weather in san francisco"},
|
|
)
|
|
|
|
async for _ in iterator:
|
|
pass
|
|
|
|
usage = iterator.completed_response.response.usage
|
|
assert usage is not None
|
|
assert usage.output_tokens > 0
|
|
assert usage.total_tokens == usage.input_tokens + usage.output_tokens
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_completed_event_with_a_dict_response_is_typed_and_billed():
|
|
"""transform_streaming_response can model_construct a terminal event whose
|
|
response stays a plain dict; the iterator must type it so the estimated
|
|
usage reaches the cost stamping path."""
|
|
dict_response: Final = {
|
|
"id": "resp_dict",
|
|
"model": "gpt-4o-mini",
|
|
"object": "response",
|
|
"output": [],
|
|
"usage": None,
|
|
}
|
|
|
|
def _transform(model, parsed_chunk, logging_obj):
|
|
if parsed_chunk.get("type") == "response.completed":
|
|
return ResponseCompletedEvent.model_construct(type="response.completed", response=dict_response)
|
|
stub: Final = Mock()
|
|
stub.type = parsed_chunk.get("type")
|
|
if "delta" in parsed_chunk:
|
|
stub.delta = parsed_chunk.get("delta")
|
|
return stub
|
|
|
|
config: Final = Mock(spec=BaseResponsesAPIConfig)
|
|
config.transform_streaming_response.side_effect = _transform
|
|
logging_obj: Final = _logging_obj_stub()
|
|
logging_obj.response_cost_calculator.return_value = 0.000704
|
|
iterator: Final = _make_iterator(
|
|
sse_events=[
|
|
_sse_event({"type": "response.output_text.delta", "delta": "hello world"}),
|
|
_sse_event({"type": "response.completed", "response": {}}),
|
|
],
|
|
logging_obj=logging_obj,
|
|
config=config,
|
|
request_data={"input": "count these input tokens please"},
|
|
)
|
|
|
|
yielded: Final = [chunk async for chunk in iterator]
|
|
|
|
terminal_event: Final = iterator.completed_response
|
|
assert yielded[-1] is terminal_event
|
|
completed_response: Final = terminal_event.response
|
|
assert isinstance(completed_response, ResponsesAPIResponse)
|
|
usage: Final = completed_response.usage
|
|
assert usage is not None
|
|
assert usage.input_tokens > 0
|
|
assert usage.output_tokens > 0
|
|
assert usage.cost == pytest.approx(0.000704)
|
|
logging_obj.response_cost_calculator.assert_any_call(result=completed_response)
|
|
|
|
|
|
def test_billed_terminal_response_keeps_a_response_that_already_has_usage():
|
|
from litellm.responses.streaming_iterator import _billed_terminal_response
|
|
|
|
response: Final = _responses_api_response_with_usage()
|
|
|
|
assert _billed_terminal_response(response, None) is response
|
|
|
|
|
|
def test_billed_terminal_response_copies_when_estimating_and_leaves_the_original_untouched():
|
|
from litellm.responses.streaming_iterator import _billed_terminal_response
|
|
|
|
response: Final = _responses_api_response_without_usage()
|
|
estimated: Final = ResponseAPIUsage(input_tokens=3, output_tokens=4, total_tokens=7)
|
|
|
|
billed: Final = _billed_terminal_response(response, lambda: estimated)
|
|
|
|
assert billed is not response
|
|
assert billed.usage is estimated
|
|
assert response.usage is None
|
|
|
|
|
|
def test_persist_completed_response_to_cache_skips_a_response_without_output(monkeypatch):
|
|
logging_obj: Final = _logging_obj_stub()
|
|
caching_handler: Final = Mock()
|
|
caching_handler.request_kwargs = {"stream": True}
|
|
logging_obj.llm_caching_handler = caching_handler
|
|
iterator: Final = _make_iterator(sse_events=[], logging_obj=logging_obj)
|
|
iterator.completed_response = ResponseCompletedEvent.model_construct(
|
|
type="response.completed",
|
|
response=ResponsesAPIResponse.model_construct(id="resp_empty", output=[], usage=None),
|
|
)
|
|
cache: Final = Mock()
|
|
monkeypatch.setattr(litellm, "cache", cache)
|
|
|
|
iterator._persist_completed_response_to_cache(is_async=False)
|
|
|
|
cache.add_cache.assert_not_called()
|
|
caching_handler.should_store_result_in_cache.assert_not_called()
|
|
|
|
|
|
def test_persist_completed_response_to_cache_survives_an_unserializable_response(monkeypatch):
|
|
bad_response: Final = ResponsesAPIResponse.model_construct(id="r", output=[object()], usage=None)
|
|
with pytest.raises(PydanticSerializationError):
|
|
bad_response.model_dump_json()
|
|
|
|
logging_obj: Final = _logging_obj_stub()
|
|
caching_handler: Final = Mock()
|
|
caching_handler.request_kwargs = {"stream": True}
|
|
logging_obj.llm_caching_handler = caching_handler
|
|
iterator: Final = _make_iterator(sse_events=[], logging_obj=logging_obj)
|
|
iterator.completed_response = ResponseCompletedEvent.model_construct(
|
|
type="response.completed", response=bad_response
|
|
)
|
|
cache: Final = Mock()
|
|
monkeypatch.setattr(litellm, "cache", cache)
|
|
|
|
iterator._persist_completed_response_to_cache(is_async=False)
|
|
|
|
cache.add_cache.assert_not_called()
|
|
|
|
|
|
@pytest.fixture()
|
|
def _vcr_outcome_gate(request, vcr):
|
|
install_live_call_probe(request, vcr)
|
|
yield
|
|
record_vcr_outcome(request, vcr)
|
|
|
|
@pytest.fixture(scope="function")
|
|
def setup_and_teardown():
|
|
"""
|
|
This fixture reloads litellm before every function. To speed up testing by removing callbacks being chained.
|
|
"""
|
|
importlib.reload(litellm)
|
|
try:
|
|
if hasattr(litellm, "proxy") and hasattr(litellm.proxy, "proxy_server"):
|
|
importlib.reload(litellm.proxy.proxy_server)
|
|
except Exception:
|
|
pass
|
|
loop = asyncio.get_event_loop_policy().new_event_loop()
|
|
asyncio.set_event_loop(loop)
|
|
yield
|
|
loop.close()
|
|
asyncio.set_event_loop(None)
|
|
|
|
class _FakeLoggingObj:
|
|
def __init__(self):
|
|
self.success_calls = 0
|
|
self.async_success_calls = 0
|
|
self.failure_calls = 0
|
|
self.async_failure_calls = 0
|
|
self.last_success_kwargs = None
|
|
self.last_async_success_kwargs = None
|
|
self.start_time = datetime.now()
|
|
self.completion_start_time = None
|
|
self.model_call_details = {"litellm_params": {}}
|
|
self.success_logged = threading.Event()
|
|
self.failure_logged = threading.Event()
|
|
|
|
# Signature alignment with Logging handlers
|
|
async def dispatch_success_handlers(self, *args, **kwargs):
|
|
kwargs.pop("prefer_async_handlers", None)
|
|
await self.async_success_handler(*args, **kwargs)
|
|
self.success_handler(*args, **kwargs)
|
|
|
|
def success_handler(self, *args, **kwargs):
|
|
self.success_calls += 1
|
|
self.last_success_kwargs = kwargs
|
|
self.success_logged.set()
|
|
|
|
async def async_success_handler(self, *args, **kwargs):
|
|
self.async_success_calls += 1
|
|
self.last_async_success_kwargs = kwargs
|
|
|
|
def failure_handler(self, *args, **kwargs):
|
|
self.failure_calls += 1
|
|
self.failure_logged.set()
|
|
|
|
async def async_failure_handler(self, *args, **kwargs):
|
|
self.async_failure_calls += 1
|
|
|
|
def update_completion_start_time(self, completion_start_time):
|
|
self.completion_start_time = completion_start_time
|
|
self.model_call_details["completion_start_time"] = completion_start_time
|
|
|
|
async def _await_tasks_spawned_since(existing: set["asyncio.Task[object]"]) -> None:
|
|
spawned: Final = asyncio.all_tasks() - existing
|
|
await asyncio.wait_for(asyncio.gather(*spawned, return_exceptions=True), timeout=5)
|
|
|
|
def _make_completed_response(response_id: str = "resp_test") -> ResponseCompletedEvent:
|
|
return ResponseCompletedEvent(
|
|
type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
|
|
response=ResponsesAPIResponse(
|
|
id=response_id,
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="completed",
|
|
model="test-model",
|
|
object="response",
|
|
output=[
|
|
{
|
|
"type": "message",
|
|
"id": f"msg_{response_id}",
|
|
"status": "completed",
|
|
"role": "assistant",
|
|
"content": [
|
|
{
|
|
"type": "output_text",
|
|
"text": "cached streamed response",
|
|
"annotations": [],
|
|
}
|
|
],
|
|
}
|
|
],
|
|
),
|
|
)
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_log_background_task_failure_logs_task_exceptions(monkeypatch):
|
|
error_logger = MagicMock()
|
|
monkeypatch.setattr(streaming_module.verbose_logger, "error", error_logger)
|
|
|
|
async def _boom():
|
|
raise RuntimeError("boom")
|
|
|
|
task = asyncio.create_task(_boom())
|
|
with suppress(RuntimeError):
|
|
await task
|
|
|
|
streaming_module._log_background_task_failure(task, task_name="cache write")
|
|
|
|
error_logger.assert_called_once()
|
|
assert error_logger.call_args.args == (
|
|
"%s failed: %s",
|
|
"cache write",
|
|
task.exception(),
|
|
)
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_log_background_task_failure_ignores_cancelled_tasks(monkeypatch):
|
|
error_logger = MagicMock()
|
|
monkeypatch.setattr(streaming_module.verbose_logger, "error", error_logger)
|
|
|
|
task = asyncio.create_task(asyncio.sleep(1))
|
|
task.cancel()
|
|
with suppress(asyncio.CancelledError):
|
|
await task
|
|
|
|
streaming_module._log_background_task_failure(task, task_name="cache write")
|
|
|
|
error_logger.assert_not_called()
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_content_part_done_event_supports_refusal_and_reasoning_text():
|
|
refusal_event = streaming_module._build_content_part_done_event(
|
|
item_id="msg_1",
|
|
output_index=0,
|
|
content_index=0,
|
|
part_payload={"type": "refusal", "refusal": "no"},
|
|
)
|
|
reasoning_event = streaming_module._build_content_part_done_event(
|
|
item_id="msg_1",
|
|
output_index=0,
|
|
content_index=1,
|
|
part_payload={"type": "reasoning_text", "reasoning": "because"},
|
|
)
|
|
unsupported_event = streaming_module._build_content_part_done_event(
|
|
item_id="msg_1",
|
|
output_index=0,
|
|
content_index=2,
|
|
part_payload={"type": "image"},
|
|
)
|
|
|
|
assert refusal_event.part.type == "refusal"
|
|
assert refusal_event.part.refusal == "no"
|
|
assert reasoning_event.part.type == "reasoning_text"
|
|
assert reasoning_event.part.reasoning == "because"
|
|
assert unsupported_event is None
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_dump_response_object_handles_model_and_unknown_values():
|
|
response = ResponsesAPIResponse(
|
|
id="resp_dump",
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="completed",
|
|
model="gpt-4.1-mini",
|
|
object="response",
|
|
output=[],
|
|
)
|
|
|
|
assert streaming_module._dump_response_object(response)["id"] == "resp_dump"
|
|
assert streaming_module._dump_response_object({"type": "message"}) == {"type": "message"}
|
|
assert streaming_module._dump_response_object(object()) == {}
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_responses_streaming_triggers_hooks(monkeypatch):
|
|
"""
|
|
Ensure streaming iterator fires success + post-call hooks for responses API.
|
|
"""
|
|
hook_calls = {"post_call": 0, "metadata": 0}
|
|
seen = {}
|
|
|
|
async def fake_post_call(request_data, response, call_type):
|
|
hook_calls["post_call"] += 1
|
|
seen["request_data"] = request_data
|
|
seen["call_type"] = call_type
|
|
|
|
def fake_update_metadata(**kwargs):
|
|
hook_calls["metadata"] += 1
|
|
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"async_post_call_success_deployment_hook",
|
|
fake_post_call,
|
|
)
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"update_response_metadata",
|
|
fake_update_metadata,
|
|
)
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(), # not used in this test
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar", "litellm_params": {}},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
# Simulate completed streaming event
|
|
iterator.completed_response = SimpleNamespace(
|
|
type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED, response=SimpleNamespace()
|
|
)
|
|
|
|
existing_tasks = asyncio.all_tasks()
|
|
iterator._handle_logging_completed_response()
|
|
await _await_tasks_spawned_since(existing_tasks)
|
|
|
|
assert logging_obj.success_calls == 1
|
|
assert logging_obj.async_success_calls == 1
|
|
assert hook_calls["post_call"] == 1
|
|
assert hook_calls["metadata"] == 1
|
|
assert seen["request_data"]["foo"] == "bar"
|
|
assert seen["request_data"].get("litellm_params") is not None
|
|
assert seen["call_type"] == CallTypes.responses
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_responses_streaming_calls_post_streaming_deployment_hook(monkeypatch):
|
|
"""
|
|
Ensure per-chunk streaming deployment hook can modify chunks.
|
|
"""
|
|
|
|
class _HookLogger(CustomLogger):
|
|
async def async_post_call_streaming_deployment_hook(self, request_data, response_chunk, call_type):
|
|
response_chunk.tagged = True
|
|
return response_chunk
|
|
|
|
# Set callbacks to our fake hook
|
|
original_callbacks = litellm.callbacks
|
|
litellm.callbacks = [_HookLogger()]
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
|
|
class _StubConfig:
|
|
def transform_streaming_response(self, **kwargs):
|
|
return SimpleNamespace(type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA, response=None)
|
|
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_StubConfig(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
# Call hook helper directly to verify chunk is modified/flagged
|
|
chunk = SimpleNamespace(type=ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA, response=None)
|
|
chunk = await streaming_module.call_post_streaming_hooks_for_testing(iterator, chunk)
|
|
assert getattr(chunk, "_post_streaming_hooks_ran", False) is True
|
|
assert getattr(chunk, "tagged", False) is True
|
|
|
|
# reset callbacks
|
|
litellm.callbacks = original_callbacks
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_responses_streaming_failure_triggers_failure_handlers():
|
|
"""
|
|
If transform raises, failure handlers should be called.
|
|
"""
|
|
|
|
class _FailConfig:
|
|
def transform_streaming_response(self, **kwargs):
|
|
raise ValueError("boom")
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_FailConfig(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="boom"):
|
|
iterator._process_chunk('{"delta": "chunk"}')
|
|
|
|
assert await asyncio.to_thread(logging_obj.failure_logged.wait, 5)
|
|
assert logging_obj.failure_calls >= 1
|
|
assert logging_obj.async_failure_calls >= 1
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_process_chunk_requires_provider_config():
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=None,
|
|
logging_obj=_FakeLoggingObj(),
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
with pytest.raises(ValueError, match="responses_api_provider_config is required"):
|
|
iterator._process_chunk(json.dumps({"type": "response.completed"}))
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_process_chunk_wraps_encrypted_content_with_model_id():
|
|
openai_types = streaming_module._get_openai_response_types()
|
|
|
|
class _EncryptedConfig:
|
|
def transform_streaming_response(self, **kwargs):
|
|
return openai_types.OutputItemAddedEvent(
|
|
type=openai_types.ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED,
|
|
output_index=0,
|
|
item=openai_types.BaseLiteLLMOpenAIResponseObject(
|
|
id="rs_123",
|
|
type="reasoning",
|
|
encrypted_content="ciphertext",
|
|
),
|
|
)
|
|
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_EncryptedConfig(),
|
|
logging_obj=_FakeLoggingObj(),
|
|
litellm_metadata={
|
|
"encrypted_content_affinity_enabled": True,
|
|
"model_info": {"id": "model-123"},
|
|
},
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
event = iterator._process_chunk(json.dumps({"type": "response.output_item.added"}))
|
|
|
|
assert event.item.encrypted_content.startswith("litellm_enc:")
|
|
assert event.item.encrypted_content.endswith(";ciphertext")
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_process_chunk_completed_response_updates_id_and_usage_cost(monkeypatch):
|
|
original_include_cost = litellm.include_cost_in_streaming_usage
|
|
litellm.include_cost_in_streaming_usage = True
|
|
openai_types = streaming_module._get_openai_response_types()
|
|
|
|
class _CompletedConfig:
|
|
def transform_streaming_response(self, **kwargs):
|
|
return openai_types.ResponseCompletedEvent(
|
|
type=openai_types.ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
|
|
response=ResponsesAPIResponse(
|
|
id="resp_live",
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="completed",
|
|
model="test-model",
|
|
object="response",
|
|
output=[],
|
|
usage=openai_types.ResponseAPIUsage(
|
|
input_tokens=1,
|
|
output_tokens=2,
|
|
total_tokens=3,
|
|
),
|
|
),
|
|
)
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
logging_obj.response_cost_calculator = MagicMock(return_value=1.23)
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_CompletedConfig(),
|
|
logging_obj=logging_obj,
|
|
litellm_metadata={"model_info": {"id": "model-123"}},
|
|
custom_llm_provider="openai",
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
completion_handler = MagicMock()
|
|
monkeypatch.setattr(iterator, "_handle_logging_completed_response", completion_handler)
|
|
|
|
try:
|
|
# Chunk must include a top-level "response" key so BaseResponsesAPIStreamingIterator
|
|
# runs update_responses_api_response_id_with_model_id (see streaming_iterator.py).
|
|
event = iterator._process_chunk(json.dumps({"type": "response.completed", "response": {"id": "resp_live"}}))
|
|
finally:
|
|
litellm.include_cost_in_streaming_usage = original_include_cost
|
|
|
|
assert iterator.completed_response is event
|
|
assert event.response.id != "resp_live"
|
|
assert event.response.id.startswith("resp_")
|
|
assert event.response.usage.cost == 1.23
|
|
completion_handler.assert_called_once()
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_process_chunk_failed_response_triggers_failure_logging(monkeypatch):
|
|
openai_types = streaming_module._get_openai_response_types()
|
|
|
|
class _FailedConfig:
|
|
def transform_streaming_response(self, **kwargs):
|
|
return openai_types.ResponseFailedEvent(
|
|
type=openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED,
|
|
response=ResponsesAPIResponse(
|
|
id="resp_failed",
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="failed",
|
|
model="test-model",
|
|
object="response",
|
|
output=[],
|
|
error={"message": "provider failed"},
|
|
),
|
|
)
|
|
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_FailedConfig(),
|
|
logging_obj=_FakeLoggingObj(),
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
failure_handler = MagicMock()
|
|
monkeypatch.setattr(iterator, "_handle_logging_failed_response", failure_handler)
|
|
|
|
event = iterator._process_chunk(json.dumps({"type": "response.failed"}))
|
|
|
|
assert iterator.completed_response is event
|
|
failure_handler.assert_called_once()
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_handle_logging_failed_response_uses_response_error_message():
|
|
openai_types = streaming_module._get_openai_response_types()
|
|
logging_obj = _FakeLoggingObj()
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
iterator.completed_response = openai_types.ResponseFailedEvent(
|
|
type=openai_types.ResponsesAPIStreamEvents.RESPONSE_FAILED,
|
|
response=ResponsesAPIResponse(
|
|
id="resp_failed_real",
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="failed",
|
|
model="test-model",
|
|
object="response",
|
|
output=[],
|
|
error={"message": "provider failed"},
|
|
),
|
|
)
|
|
|
|
iterator._handle_logging_failed_response()
|
|
assert await asyncio.to_thread(logging_obj.failure_logged.wait, 5)
|
|
|
|
assert logging_obj.failure_calls == 1
|
|
assert logging_obj.async_failure_calls == 1
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_process_chunk_returns_none_for_invalid_json_and_non_dict_payload():
|
|
class _NoopConfig:
|
|
def transform_streaming_response(self, **kwargs):
|
|
raise AssertionError("should not be called")
|
|
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_NoopConfig(),
|
|
logging_obj=_FakeLoggingObj(),
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
assert iterator._process_chunk("not-json") is None
|
|
assert iterator._process_chunk(json.dumps(["not", "a", "dict"])) is None
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_process_chunk_cost_annotation_failure_is_nonfatal(monkeypatch):
|
|
original_include_cost = litellm.include_cost_in_streaming_usage
|
|
litellm.include_cost_in_streaming_usage = True
|
|
openai_types = streaming_module._get_openai_response_types()
|
|
|
|
class _CompletedConfig:
|
|
def transform_streaming_response(self, **kwargs):
|
|
return openai_types.ResponseCompletedEvent(
|
|
type=openai_types.ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
|
|
response=ResponsesAPIResponse(
|
|
id="resp_cost_failure",
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="completed",
|
|
model="test-model",
|
|
object="response",
|
|
output=[],
|
|
usage=openai_types.ResponseAPIUsage(
|
|
input_tokens=1,
|
|
output_tokens=2,
|
|
total_tokens=3,
|
|
),
|
|
),
|
|
)
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
logging_obj.response_cost_calculator = MagicMock(side_effect=RuntimeError("boom"))
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_CompletedConfig(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
completion_handler = MagicMock()
|
|
monkeypatch.setattr(iterator, "_handle_logging_completed_response", completion_handler)
|
|
|
|
try:
|
|
event = iterator._process_chunk(json.dumps({"type": "response.completed"}))
|
|
finally:
|
|
litellm.include_cost_in_streaming_usage = original_include_cost
|
|
|
|
assert iterator.completed_response is event
|
|
assert event.response.usage.cost is None
|
|
completion_handler.assert_called_once()
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_get_completed_response_object_accepts_direct_response():
|
|
logging_obj = _FakeLoggingObj()
|
|
iterator = SyncResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
direct_response = _make_completed_response("resp_direct").response
|
|
iterator.completed_response = direct_response
|
|
|
|
assert iterator._get_completed_response_object() is direct_response
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_responses_streaming_completed_event_persists_async_cache():
|
|
logging_obj = _FakeLoggingObj()
|
|
original_cache = litellm.cache
|
|
litellm.cache = SimpleNamespace(
|
|
async_add_cache=AsyncMock(),
|
|
add_cache=MagicMock(),
|
|
)
|
|
caching_handler = SimpleNamespace(
|
|
request_kwargs={
|
|
"model": "test-model",
|
|
"input": "hello",
|
|
"stream": True,
|
|
"caching": True,
|
|
"cache_key": "stale-request-cache-key",
|
|
"metadata": None,
|
|
"custom_llm_provider": "openai",
|
|
},
|
|
preset_cache_key="responses-stream-cache-key",
|
|
original_function=litellm.aresponses,
|
|
async_set_cache=AsyncMock(),
|
|
_should_store_result_in_cache=lambda original_function, kwargs: True,
|
|
)
|
|
logging_obj.llm_caching_handler = caching_handler
|
|
|
|
iterator = ResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(),
|
|
logging_obj=logging_obj,
|
|
request_data=caching_handler.request_kwargs,
|
|
call_type=CallTypes.aresponses.value,
|
|
)
|
|
iterator.completed_response = _make_completed_response()
|
|
|
|
existing_tasks = asyncio.all_tasks()
|
|
iterator._handle_logging_completed_response()
|
|
await _await_tasks_spawned_since(existing_tasks)
|
|
|
|
litellm.cache.async_add_cache.assert_called_once()
|
|
assert litellm.cache.async_add_cache.call_args.kwargs["stream"] is True
|
|
assert litellm.cache.async_add_cache.call_args.kwargs["cache_key"] == "responses-stream-cache-key"
|
|
assert "metadata" not in litellm.cache.async_add_cache.call_args.kwargs
|
|
assert "custom_llm_provider" not in litellm.cache.async_add_cache.call_args.kwargs
|
|
assert json.loads(litellm.cache.async_add_cache.call_args.args[0])["id"] == iterator.completed_response.response.id
|
|
litellm.cache = original_cache
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_responses_streaming_completed_event_persists_sync_cache():
|
|
logging_obj = _FakeLoggingObj()
|
|
original_cache = litellm.cache
|
|
litellm.cache = SimpleNamespace(
|
|
async_add_cache=AsyncMock(),
|
|
add_cache=MagicMock(),
|
|
)
|
|
caching_handler = SimpleNamespace(
|
|
request_kwargs={
|
|
"model": "test-model",
|
|
"input": "hello",
|
|
"stream": True,
|
|
"caching": True,
|
|
"cache_key": "stale-request-cache-key",
|
|
"metadata": None,
|
|
"custom_llm_provider": "openai",
|
|
},
|
|
preset_cache_key="responses-stream-cache-key",
|
|
original_function=litellm.responses,
|
|
sync_set_cache=MagicMock(),
|
|
_should_store_result_in_cache=lambda original_function, kwargs: True,
|
|
)
|
|
logging_obj.llm_caching_handler = caching_handler
|
|
|
|
iterator = SyncResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(),
|
|
logging_obj=logging_obj,
|
|
request_data=caching_handler.request_kwargs,
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
iterator.completed_response = _make_completed_response("resp_sync")
|
|
|
|
iterator._handle_logging_completed_response()
|
|
|
|
litellm.cache.add_cache.assert_called_once()
|
|
assert litellm.cache.add_cache.call_args.kwargs["stream"] is True
|
|
assert litellm.cache.add_cache.call_args.kwargs["cache_key"] == "responses-stream-cache-key"
|
|
assert "metadata" not in litellm.cache.add_cache.call_args.kwargs
|
|
assert "custom_llm_provider" not in litellm.cache.add_cache.call_args.kwargs
|
|
assert json.loads(litellm.cache.add_cache.call_args.args[0])["id"] == iterator.completed_response.response.id
|
|
litellm.cache = original_cache
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_log_completed_response_sync_direct_path(monkeypatch):
|
|
hook_calls = {"post_call": 0, "metadata": 0}
|
|
|
|
async def fake_post_call(request_data, response, call_type):
|
|
hook_calls["post_call"] += 1
|
|
|
|
def fake_update_metadata(**kwargs):
|
|
hook_calls["metadata"] += 1
|
|
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"async_post_call_success_deployment_hook",
|
|
fake_post_call,
|
|
)
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"update_response_metadata",
|
|
fake_update_metadata,
|
|
)
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
iterator = SyncResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
iterator._persist_completed_response_before_logging = False
|
|
iterator.completed_response = _make_completed_response("resp_log_sync")
|
|
|
|
iterator._log_completed_response(is_async=False)
|
|
assert logging_obj.success_logged.wait(timeout=5)
|
|
|
|
assert logging_obj.success_calls == 1
|
|
assert logging_obj.async_success_calls == 1
|
|
assert hook_calls["post_call"] == 1
|
|
assert hook_calls["metadata"] == 1
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_log_completed_response_falls_back_when_model_validate_fails(monkeypatch):
|
|
class _BadSerializableResponse:
|
|
@classmethod
|
|
def model_validate(cls, value):
|
|
raise RuntimeError("nope")
|
|
|
|
def model_dump(self):
|
|
return {"id": "bad"}
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
iterator = SyncResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
iterator._persist_completed_response_before_logging = False
|
|
iterator.completed_response = _BadSerializableResponse()
|
|
monkeypatch.setattr(iterator, "_run_post_success_hooks", MagicMock())
|
|
|
|
iterator._log_completed_response(is_async=False)
|
|
assert logging_obj.success_logged.wait(timeout=5)
|
|
|
|
assert logging_obj.success_calls == 1
|
|
assert logging_obj.async_success_calls == 1
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.parametrize(
|
|
"scenario",
|
|
[
|
|
"already_cached",
|
|
"not_completed",
|
|
"missing_caching_handler",
|
|
"not_streaming",
|
|
"store_disabled",
|
|
"missing_cache_backend",
|
|
],
|
|
)
|
|
def test_persist_completed_response_to_cache_guard_branches(monkeypatch, scenario):
|
|
logging_obj = _FakeLoggingObj()
|
|
iterator = SyncResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=SimpleNamespace(),
|
|
logging_obj=logging_obj,
|
|
request_data={"foo": "bar"},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
openai_types = streaming_module._get_openai_response_types()
|
|
completed_event = _make_completed_response("resp_guard")
|
|
iterator.completed_response = completed_event
|
|
|
|
if scenario == "already_cached":
|
|
iterator._completed_response_cached = True
|
|
elif scenario == "not_completed":
|
|
iterator.completed_response = openai_types.ResponseIncompleteEvent(
|
|
type=openai_types.ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE,
|
|
response=completed_event.response,
|
|
)
|
|
elif scenario == "missing_caching_handler":
|
|
logging_obj.llm_caching_handler = None
|
|
else:
|
|
logging_obj.llm_caching_handler = SimpleNamespace(
|
|
request_kwargs={
|
|
"model": "test-model",
|
|
"input": "hello",
|
|
"stream": scenario != "not_streaming",
|
|
"cache_key": "request-cache-key",
|
|
"metadata": None,
|
|
"custom_llm_provider": "openai",
|
|
},
|
|
preset_cache_key=None,
|
|
original_function=litellm.responses,
|
|
dual_cache=None,
|
|
_should_store_result_in_cache=lambda original_function, kwargs: scenario != "store_disabled",
|
|
)
|
|
if scenario == "missing_cache_backend":
|
|
monkeypatch.setattr(streaming_module.litellm, "cache", None)
|
|
else:
|
|
monkeypatch.setattr(
|
|
streaming_module.litellm,
|
|
"cache",
|
|
SimpleNamespace(add_cache=MagicMock(), async_add_cache=AsyncMock()),
|
|
)
|
|
|
|
iterator._persist_completed_response_to_cache(is_async=False)
|
|
|
|
expected_cached_flag = scenario == "already_cached"
|
|
assert iterator._completed_response_cached is expected_cached_flag
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_build_synthetic_response_events_covers_annotations_function_calls_and_refusals():
|
|
original_include_cost = litellm.include_cost_in_streaming_usage
|
|
litellm.include_cost_in_streaming_usage = True
|
|
logging_obj = _FakeLoggingObj()
|
|
logging_obj.response_cost_calculator = MagicMock(side_effect=RuntimeError("boom"))
|
|
transformed = ResponsesAPIResponse(
|
|
id="resp_events",
|
|
created_at=int(datetime.now().timestamp()),
|
|
status="completed",
|
|
model="gpt-4.1-mini",
|
|
object="response",
|
|
output=[
|
|
{
|
|
"type": "message",
|
|
"id": "msg_events",
|
|
"status": "completed",
|
|
"role": "assistant",
|
|
"content": [
|
|
{
|
|
"type": "output_text",
|
|
"text": "hello world",
|
|
"annotations": [{"type": "file_citation", "file_id": "file_1"}],
|
|
},
|
|
{
|
|
"type": "refusal",
|
|
"refusal": "no thanks",
|
|
},
|
|
],
|
|
},
|
|
{
|
|
"type": "function_call",
|
|
"id": "fc_events",
|
|
"call_id": "call_123",
|
|
"name": "lookup",
|
|
"arguments": '{"id":1}',
|
|
},
|
|
],
|
|
)
|
|
|
|
try:
|
|
events = streaming_module.build_synthetic_response_events(
|
|
transformed=transformed,
|
|
logging_obj=logging_obj,
|
|
chunk_size=5,
|
|
)
|
|
finally:
|
|
litellm.include_cost_in_streaming_usage = original_include_cost
|
|
|
|
event_types = [event.type.value if hasattr(event.type, "value") else str(event.type) for event in events]
|
|
|
|
assert "response.output_text.annotation.added" in event_types
|
|
assert "response.refusal.delta" in event_types
|
|
assert "response.refusal.done" in event_types
|
|
assert "response.function_call_arguments.delta" in event_types
|
|
assert "response.function_call_arguments.done" in event_types
|
|
assert event_types[-1] == "response.completed"
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_mock_responses_streaming_iterator_async_iteration_logs_completion(
|
|
monkeypatch,
|
|
):
|
|
hook_calls = {"post_call": 0, "metadata": 0}
|
|
|
|
async def fake_post_call(request_data, response, call_type):
|
|
hook_calls["post_call"] += 1
|
|
|
|
def fake_update_metadata(**kwargs):
|
|
hook_calls["metadata"] += 1
|
|
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"async_post_call_success_deployment_hook",
|
|
fake_post_call,
|
|
)
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"update_response_metadata",
|
|
fake_update_metadata,
|
|
)
|
|
|
|
class _MockTransformConfig:
|
|
def transform_response_api_response(self, **kwargs):
|
|
return _make_completed_response("resp_mock").response
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
|
|
iterator = MockResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_MockTransformConfig(),
|
|
logging_obj=logging_obj,
|
|
request_data={"model": "test-model", "stream": True},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
existing_tasks = asyncio.all_tasks()
|
|
streamed_events = [event async for event in iterator]
|
|
await _await_tasks_spawned_since(existing_tasks)
|
|
|
|
assert streamed_events[0].type == ResponsesAPIStreamEvents.RESPONSE_CREATED
|
|
assert streamed_events[-1].type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
|
|
assert logging_obj.success_calls == 1
|
|
assert logging_obj.async_success_calls == 1
|
|
assert hook_calls["post_call"] == 1
|
|
assert hook_calls["metadata"] == 1
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_mock_responses_streaming_iterator_sync_iteration_logs_completion(monkeypatch):
|
|
hook_calls = {"post_call": 0, "metadata": 0}
|
|
|
|
async def fake_post_call(request_data, response, call_type):
|
|
hook_calls["post_call"] += 1
|
|
|
|
def fake_update_metadata(**kwargs):
|
|
hook_calls["metadata"] += 1
|
|
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"async_post_call_success_deployment_hook",
|
|
fake_post_call,
|
|
)
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"update_response_metadata",
|
|
fake_update_metadata,
|
|
)
|
|
|
|
class _MockTransformConfig:
|
|
def transform_response_api_response(self, **kwargs):
|
|
return _make_completed_response("resp_mock_sync").response
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
iterator = MockResponsesAPIStreamingIterator(
|
|
response=httpx.Response(200),
|
|
model="test-model",
|
|
responses_api_provider_config=_MockTransformConfig(),
|
|
logging_obj=logging_obj,
|
|
request_data={"model": "test-model", "stream": True},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
streamed_events = list(iterator)
|
|
assert logging_obj.success_logged.wait(timeout=5)
|
|
|
|
assert streamed_events[0].type == ResponsesAPIStreamEvents.RESPONSE_CREATED
|
|
assert streamed_events[-1].type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
|
|
assert logging_obj.success_calls == 1
|
|
assert logging_obj.async_success_calls == 1
|
|
assert hook_calls["post_call"] == 1
|
|
assert hook_calls["metadata"] == 1
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
@pytest.mark.asyncio
|
|
async def test_cached_responses_stream_async_hit_triggers_success_callbacks(
|
|
monkeypatch,
|
|
):
|
|
hook_calls = {"post_call": 0, "metadata": 0}
|
|
|
|
async def fake_post_call(request_data, response, call_type):
|
|
hook_calls["post_call"] += 1
|
|
|
|
def fake_update_metadata(**kwargs):
|
|
hook_calls["metadata"] += 1
|
|
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"async_post_call_success_deployment_hook",
|
|
fake_post_call,
|
|
)
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"update_response_metadata",
|
|
fake_update_metadata,
|
|
)
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
original_cache = litellm.cache
|
|
litellm.cache = SimpleNamespace(
|
|
async_add_cache=AsyncMock(),
|
|
add_cache=MagicMock(),
|
|
)
|
|
logging_obj.llm_caching_handler = SimpleNamespace(
|
|
request_kwargs={"model": "test-model", "input": "hello", "stream": True},
|
|
preset_cache_key="responses-stream-cache-key",
|
|
original_function=litellm.aresponses,
|
|
_should_store_result_in_cache=lambda original_function, kwargs: True,
|
|
)
|
|
|
|
iterator = CachedResponsesAPIStreamingIterator(
|
|
response=_make_completed_response("resp_cached_async").response,
|
|
logging_obj=logging_obj,
|
|
request_data={"model": "test-model", "input": "hello", "stream": True},
|
|
call_type=CallTypes.aresponses.value,
|
|
)
|
|
|
|
existing_tasks = asyncio.all_tasks()
|
|
streamed_events = [event async for event in iterator]
|
|
await _await_tasks_spawned_since(existing_tasks)
|
|
|
|
assert streamed_events[-1].type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
|
|
assert logging_obj.success_calls == 1
|
|
assert logging_obj.async_success_calls == 1
|
|
assert logging_obj.last_success_kwargs["cache_hit"] is True
|
|
assert logging_obj.last_async_success_kwargs["cache_hit"] is True
|
|
assert hook_calls["post_call"] == 1
|
|
assert hook_calls["metadata"] == 1
|
|
litellm.cache.async_add_cache.assert_not_called()
|
|
litellm.cache.add_cache.assert_not_called()
|
|
litellm.cache = original_cache
|
|
|
|
@pytest.mark.usefixtures("_vcr_outcome_gate", "setup_and_teardown")
|
|
def test_cached_responses_stream_sync_hit_triggers_success_callbacks(monkeypatch):
|
|
hook_calls = {"post_call": 0, "metadata": 0}
|
|
|
|
async def fake_post_call(request_data, response, call_type):
|
|
hook_calls["post_call"] += 1
|
|
|
|
def fake_update_metadata(**kwargs):
|
|
hook_calls["metadata"] += 1
|
|
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"async_post_call_success_deployment_hook",
|
|
fake_post_call,
|
|
)
|
|
monkeypatch.setattr(
|
|
streaming_module,
|
|
"update_response_metadata",
|
|
fake_update_metadata,
|
|
)
|
|
|
|
logging_obj = _FakeLoggingObj()
|
|
original_cache = litellm.cache
|
|
litellm.cache = SimpleNamespace(
|
|
async_add_cache=AsyncMock(),
|
|
add_cache=MagicMock(),
|
|
)
|
|
logging_obj.llm_caching_handler = SimpleNamespace(
|
|
request_kwargs={"model": "test-model", "input": "hello", "stream": True},
|
|
preset_cache_key="responses-stream-cache-key",
|
|
original_function=litellm.responses,
|
|
_should_store_result_in_cache=lambda original_function, kwargs: True,
|
|
)
|
|
|
|
iterator = CachedResponsesAPIStreamingIterator(
|
|
response=_make_completed_response("resp_cached_sync").response,
|
|
logging_obj=logging_obj,
|
|
request_data={"model": "test-model", "input": "hello", "stream": True},
|
|
call_type=CallTypes.responses.value,
|
|
)
|
|
|
|
streamed_events = list(iterator)
|
|
assert logging_obj.success_logged.wait(timeout=5)
|
|
|
|
assert streamed_events[-1].type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
|
|
assert logging_obj.success_calls == 1
|
|
assert logging_obj.async_success_calls == 1
|
|
assert logging_obj.last_success_kwargs["cache_hit"] is True
|
|
assert logging_obj.last_async_success_kwargs["cache_hit"] is True
|
|
assert hook_calls["post_call"] == 1
|
|
assert hook_calls["metadata"] == 1
|
|
litellm.cache.async_add_cache.assert_not_called()
|
|
litellm.cache.add_cache.assert_not_called()
|
|
litellm.cache = original_cache
|