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test(responses): type the MCP lifecycle test helpers
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5f84e83316
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1 changed files with 9 additions and 5 deletions
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@ -11,7 +11,11 @@ from litellm.responses.mcp.mcp_streaming_iterator import (
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MAX_MCP_TOOL_CALL_ROUNDS,
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MCPEnhancedStreamingIterator,
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)
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from litellm.types.llms.openai import ResponsesAPIResponse, ResponsesAPIStreamEvents
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from litellm.types.llms.openai import (
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BaseLiteLLMOpenAIResponseObject,
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ResponsesAPIResponse,
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ResponsesAPIStreamEvents,
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)
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# `litellm.__init__` re-exports a function named `responses`, which shadows the
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# `litellm.responses` subpackage as an attribute — `import litellm.responses.main`
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@ -57,8 +61,8 @@ def _text_message(text: str):
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return {"type": "message", "role": "assistant", "content": [{"type": "output_text", "text": text}]}
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def _item_type(item) -> str:
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return item["type"] if isinstance(item, dict) else item.type
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def _item_type(item: dict[str, object] | BaseLiteLLMOpenAIResponseObject) -> str:
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return str(item["type"]) if isinstance(item, dict) else str(item.type)
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def _tool_call_stream(call_id: str, tool_name: str, response_id: str = "resp-1") -> _FakeAsyncStream:
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@ -354,11 +358,11 @@ async def test_streaming_follow_up_keeps_previous_response_id_when_stored(monkey
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assert not [item for item in follow_up_kwargs["input"] if item.get("type") == "reasoning"]
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def _event(event_type, **fields):
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def _event(event_type: ResponsesAPIStreamEvents, **fields: object) -> SimpleNamespace:
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return SimpleNamespace(type=event_type, **fields)
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def _lifecycle_round(response_id: str, item: dict, sequence_start: int = 0):
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def _lifecycle_round(response_id: str, item: dict[str, object], sequence_start: int = 0) -> list[SimpleNamespace]:
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"""One upstream Responses round as a provider streams it: its own id, indexes from 0, numbering from 0."""
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return [
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_event(
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