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630 lines
22 KiB
Python
630 lines
22 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 json
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from datetime import datetime
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from typing import Optional
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from unittest.mock import Mock, patch
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import httpx
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import pytest
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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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ResponsesAPIStreamingIterator,
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SyncResponsesAPIStreamingIterator,
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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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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 = Mock(spec=ResponsesAPIResponse)
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mock_responses_api_response.id = "resp_ttft"
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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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completed = Mock(spec=ResponseCompletedEvent)
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completed.type = ResponsesAPIStreamEvents.RESPONSE_COMPLETED
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completed.response = mock_responses_api_response
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return completed
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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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) -> 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=_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 _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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def test_stream_cache_write_completes_when_asyncio_run_closes_the_loop(monkeypatch):
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"""
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Regression test for LIT-6184 on the /v1/responses streaming surface: the
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completed-stream cache write was dispatched as a bare fire-and-forget task,
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so asyncio.run cancelled it at loop close before the write landed. The
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write must survive loop shutdown just like the chat-completions one.
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"""
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import asyncio
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from types import SimpleNamespace
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import litellm
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from litellm.types.utils import CallTypes
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writes = []
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class _SlowWriteCache:
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async def async_add_cache(self, result, dynamic_cache_object=None, **kwargs):
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await asyncio.sleep(0.2)
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writes.append(result)
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def add_cache(self, *args, **kwargs):
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raise AssertionError("sync write must not run on the async path")
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caching_handler = SimpleNamespace(
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request_kwargs={
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"model": "test-model",
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"input": "hello",
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"stream": True,
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"caching": True,
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"metadata": None,
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"custom_llm_provider": "openai",
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},
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preset_cache_key="responses-stream-cache-key",
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original_function=litellm.aresponses,
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dual_cache=None,
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_should_store_result_in_cache=lambda original_function, kwargs: True,
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)
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logging_obj = SimpleNamespace(
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model_call_details={"litellm_params": {}},
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_llm_caching_handler=caching_handler,
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)
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iterator = ResponsesAPIStreamingIterator(
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response=httpx.Response(200),
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model="test-model",
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responses_api_provider_config=Mock(spec=BaseResponsesAPIConfig),
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logging_obj=logging_obj,
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request_data=caching_handler.request_kwargs,
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call_type=CallTypes.aresponses.value,
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)
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iterator.completed_response = ResponseCompletedEvent(
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type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
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response=ResponsesAPIResponse(
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id="resp_lit6184",
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created_at=int(datetime.now().timestamp()),
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status="completed",
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model="test-model",
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object="response",
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output=[],
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),
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)
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monkeypatch.setattr(litellm, "cache", _SlowWriteCache())
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async def _short_lived_script():
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iterator._persist_completed_response_to_cache(is_async=True)
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asyncio.run(_short_lived_script())
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assert len(writes) == 1
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def test_run_post_success_hooks_does_not_report_generation_time_as_overhead():
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"""LIT-5466: the provider call is timed to first byte, so at stream completion the total minus
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that duration is token generation, not LiteLLM overhead."""
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logging_obj = _logging_obj_stub()
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logging_obj.model_call_details = {"litellm_params": {}, "llm_api_duration_ms": 200.0}
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logging_obj.caching_details = None
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class _CompletedEvent:
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def __init__(self) -> None:
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self._hidden_params: dict = {}
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iterator = _make_iterator(sse_events=[], logging_obj=logging_obj)
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iterator.completed_response = _CompletedEvent()
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iterator.start_time = datetime(2025, 1, 1, 0, 0, 0)
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iterator._run_post_success_hooks(datetime(2025, 1, 1, 0, 0, 10))
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assert iterator.completed_response._hidden_params["_response_ms"] == 10000.0
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assert "litellm_overhead_time_ms" not in iterator.completed_response._hidden_params
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def _responses_api_response_with_usage() -> ResponsesAPIResponse:
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return ResponsesAPIResponse(
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id="resp_lit6427",
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created_at=int(datetime(2025, 1, 1).timestamp()),
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status="completed",
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model="mantle-claude",
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object="response",
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output=[],
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usage=ResponseAPIUsage(input_tokens=20, output_tokens=60, total_tokens=80),
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)
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def test_stamp_responses_usage_cost_stamps_computed_cost():
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from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
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response = _responses_api_response_with_usage()
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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logging_obj._response_cost_calculator.return_value = 0.000704
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_stamp_responses_usage_cost(response, logging_obj)
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assert getattr(response.usage, "cost", None) == pytest.approx(0.000704)
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logging_obj._response_cost_calculator.assert_called_once_with(result=response)
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def test_stamp_responses_usage_cost_keeps_provider_reported_cost():
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from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
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response = _responses_api_response_with_usage()
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setattr(response.usage, "cost", 0.5)
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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_stamp_responses_usage_cost(response, logging_obj)
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assert getattr(response.usage, "cost", None) == pytest.approx(0.5)
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logging_obj._response_cost_calculator.assert_not_called()
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def _unvalidated_response_with_dict_usage(usage: dict) -> ResponsesAPIResponse:
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return ResponsesAPIResponse.model_construct(
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id="resp_lit7391",
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created_at=int(datetime(2025, 1, 1).timestamp()),
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status="completed",
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model="perplexity/deepseek-v4-flash-0731",
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object="response",
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output=[],
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truncation="",
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usage=usage,
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)
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def test_stamp_responses_usage_cost_keeps_provider_cost_from_dict_usage():
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from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
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response = _unvalidated_response_with_dict_usage(
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{
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"input_tokens": 29,
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"output_tokens": 120,
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"output_tokens_details": {"reasoning_tokens": 117},
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"total_tokens": 149,
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"cost": {"currency": "USD", "input_cost": 0, "output_cost": 3e-05, "total_cost": 3e-05},
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}
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)
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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_stamp_responses_usage_cost(response, logging_obj)
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assert isinstance(response.usage, ResponseAPIUsage)
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assert response.usage.cost == pytest.approx(3e-05)
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assert response.usage.output_tokens_details.reasoning_tokens == 117
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logging_obj._response_cost_calculator.assert_not_called()
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def test_stamp_responses_usage_cost_computes_cost_for_dict_usage_without_cost():
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from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
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response = _unvalidated_response_with_dict_usage({"input_tokens": 29, "output_tokens": 120, "total_tokens": 149})
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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logging_obj._response_cost_calculator.return_value = 0.000704
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_stamp_responses_usage_cost(response, logging_obj)
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assert isinstance(response.usage, ResponseAPIUsage)
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assert response.usage.cost == pytest.approx(0.000704)
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logging_obj._response_cost_calculator.assert_called_once_with(result=response)
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def test_stamp_responses_usage_cost_survives_calculator_failure():
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from litellm.responses.streaming_iterator import _stamp_responses_usage_cost
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response = _responses_api_response_with_usage()
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logging_obj = Mock(spec=LiteLLMLoggingObj)
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logging_obj._response_cost_calculator.side_effect = RuntimeError("cost map unavailable")
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_stamp_responses_usage_cost(response, logging_obj)
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assert getattr(response.usage, "cost", None) is None
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def _capture_dispatch(logged: list):
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"""Record the object handed to the success handlers.
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``Mock(spec=LiteLLMLoggingObj).dispatch_success_handlers`` is an AsyncMock whose side effect
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only runs when the coroutine is awaited, so capture with a plain function instead.
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"""
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async def _noop() -> None:
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return None
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def _dispatch(result, **kwargs):
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logged.append(result)
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return _noop()
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return _dispatch
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def _headers_config(*, transform_hidden_params: Optional[dict] = None) -> Mock:
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"""Config whose completed event carries a real ResponsesAPIResponse, so the logging copy
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performs a genuine model_dump/model_validate round trip."""
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mock_config = Mock(spec=BaseResponsesAPIConfig)
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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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stub = Mock()
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stub.type = evt_type
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return stub
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response = ResponsesAPIResponse(
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id="resp_headers",
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created_at=1,
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output=[],
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parallel_tool_calls=False,
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tool_choice="auto",
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tools=[],
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)
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if transform_hidden_params is not None:
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response._hidden_params.update(transform_hidden_params)
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return ResponseCompletedEvent(
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type=ResponsesAPIStreamEvents.RESPONSE_COMPLETED,
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response=response,
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)
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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_header_iterator(
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*,
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headers: dict,
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config: Mock,
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logging_obj: LiteLLMLoggingObj,
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) -> ResponsesAPIStreamingIterator:
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async def aiter_bytes():
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yield _sse_event({"type": "response.completed"})
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mock_response = Mock()
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mock_response.headers = 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,
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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)
|