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Add support for phase param
This commit is contained in:
Sameer Kankute
parent
ba3f30f04d
commit
c3860468fe
2 changed files with 318 additions and 1 deletions
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@ -6,6 +6,7 @@ from typing_extensions import Any, List, Optional, TypedDict
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from litellm.types.llms.base import BaseLiteLLMOpenAIResponseObject
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Phase = Optional[Literal["commentary", "final_answer"]] # TODO: Once openai sdk has updated, we can remove this and use the openai sdk type
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class GenericResponseOutputItemContentAnnotation(BaseLiteLLMOpenAIResponseObject):
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"""Annotation for content in a message"""
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@ -35,6 +36,7 @@ class OutputFunctionToolCall(BaseLiteLLMOpenAIResponseObject):
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type: Optional[str] # "function_call"
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id: Optional[str]
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status: Literal["in_progress", "completed", "incomplete"]
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phase: Phase = None
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class OutputImageGenerationCall(BaseLiteLLMOpenAIResponseObject):
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@ -57,6 +59,7 @@ class GenericResponseOutputItem(BaseLiteLLMOpenAIResponseObject):
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status: str # "completed", "in_progress", etc.
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role: str # "assistant", "user", etc.
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content: List[OutputText]
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phase: Phase = None
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class DeleteResponseResult(BaseLiteLLMOpenAIResponseObject):
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@ -925,4 +925,318 @@ def test_get_supported_openai_params():
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assert "temperature" in params
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assert "stream" in params
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assert "background" in params
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assert "stream" in params
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assert "stream" in params
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class TestPhaseParameter:
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"""Tests for the `phase` parameter on assistant output items (gpt-5.3-codex)."""
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def setup_method(self):
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self.config = OpenAIResponsesAPIConfig()
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self.model = "gpt-5.3-codex"
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self.logging_obj = MagicMock()
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@staticmethod
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def _make_output_text(text: str):
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from litellm.types.responses.main import OutputText
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return OutputText(type="output_text", text=text, annotations=[])
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def test_generic_response_output_item_accepts_phase_commentary(self):
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from litellm.types.responses.main import GenericResponseOutputItem
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item = GenericResponseOutputItem(
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type="message",
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id="msg_001",
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status="completed",
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role="assistant",
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content=[self._make_output_text("Thinking...")],
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phase="commentary",
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)
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assert item.phase == "commentary"
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def test_generic_response_output_item_accepts_phase_final_answer(self):
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from litellm.types.responses.main import GenericResponseOutputItem
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item = GenericResponseOutputItem(
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type="message",
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id="msg_002",
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status="completed",
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role="assistant",
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content=[self._make_output_text("The answer is 42.")],
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phase="final_answer",
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)
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assert item.phase == "final_answer"
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def test_generic_response_output_item_phase_defaults_to_none(self):
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from litellm.types.responses.main import GenericResponseOutputItem
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item = GenericResponseOutputItem(
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type="message",
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id="msg_003",
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status="completed",
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role="assistant",
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content=[self._make_output_text("Hello")],
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)
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assert item.phase is None
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def test_output_function_tool_call_accepts_phase(self):
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from litellm.types.responses.main import OutputFunctionToolCall
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item = OutputFunctionToolCall(
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type="function_call",
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id="fc_001",
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arguments='{"query": "test"}',
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call_id="call_001",
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name="search",
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status="completed",
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phase="commentary",
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)
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assert item.phase == "commentary"
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def test_input_passthrough_dict_preserves_phase(self):
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"""Dict input items (the normal HTTP flow) must preserve phase verbatim."""
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input_items = [
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{
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"type": "message",
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"role": "user",
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"content": [{"type": "input_text", "text": "Hi"}],
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},
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{
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"type": "message",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "Preamble..."}],
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"phase": "commentary",
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},
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{
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"type": "message",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "Done."}],
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"phase": "final_answer",
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},
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{
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"type": "message",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "Neutral."}],
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"phase": None,
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},
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]
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result = self.config._validate_input_param(input_items)
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assert isinstance(result, list)
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assert "phase" not in result[0]
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assert result[1]["phase"] == "commentary"
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assert result[2]["phase"] == "final_answer"
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assert result[3]["phase"] is None
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def test_input_passthrough_pydantic_preserves_non_null_phase(self):
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"""Pydantic input items must preserve non-null phase values."""
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from litellm.types.responses.main import GenericResponseOutputItem
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item = GenericResponseOutputItem(
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type="message",
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id="msg_010",
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status="completed",
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role="assistant",
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content=[self._make_output_text("commentary")],
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phase="commentary",
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)
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result = self.config._validate_input_param([item])
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assert isinstance(result, list)
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assert result[0]["phase"] == "commentary"
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def test_response_parsing_preserves_phase_on_output(self):
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"""Non-streaming response must preserve phase on output items."""
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raw_json = {
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"id": "resp_001",
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"created_at": 1700000000,
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"model": "gpt-5.3-codex",
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"object": "response",
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"status": "completed",
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"output": [
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{
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"type": "message",
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"id": "msg_001",
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"status": "completed",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "preamble"}],
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"phase": "commentary",
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},
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{
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"type": "message",
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"id": "msg_002",
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"status": "completed",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "answer"}],
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"phase": "final_answer",
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},
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],
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"usage": {"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
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}
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response = ResponsesAPIResponse(**raw_json)
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assert len(response.output) == 2
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for idx, output_item in enumerate(response.output):
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if isinstance(output_item, dict):
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phase = output_item.get("phase")
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else:
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phase = getattr(output_item, "phase", None)
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expected = "commentary" if idx == 0 else "final_answer"
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assert phase == expected, (
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f"output[{idx}] phase={phase!r}, expected {expected!r}"
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)
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def test_streaming_output_item_done_preserves_phase(self):
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"""OutputItemDoneEvent must preserve phase on its item."""
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from litellm.types.llms.openai import (
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OutputItemDoneEvent,
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ResponsesAPIStreamEvents,
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)
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chunk = {
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"type": "response.output_item.done",
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"output_index": 0,
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"sequence_number": 3,
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"item": {
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"type": "message",
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"id": "msg_100",
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"status": "completed",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "done"}],
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"phase": "final_answer",
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},
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}
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result = self.config.transform_streaming_response(
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model=self.model, parsed_chunk=chunk, logging_obj=self.logging_obj
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)
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assert isinstance(result, OutputItemDoneEvent)
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assert result.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE
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assert getattr(result.item, "phase", None) == "final_answer"
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def test_streaming_output_item_added_preserves_phase(self):
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"""OutputItemAddedEvent must preserve phase on its item."""
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from litellm.types.llms.openai import (
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OutputItemAddedEvent,
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ResponsesAPIStreamEvents,
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)
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chunk = {
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"type": "response.output_item.added",
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"output_index": 0,
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"item": {
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"type": "message",
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"id": "msg_200",
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"role": "assistant",
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"phase": "commentary",
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},
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}
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result = self.config.transform_streaming_response(
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model=self.model, parsed_chunk=chunk, logging_obj=self.logging_obj
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)
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assert isinstance(result, OutputItemAddedEvent)
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assert result.type == ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED
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assert getattr(result.item, "phase", None) == "commentary"
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def test_streaming_response_completed_preserves_phase(self):
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"""ResponseCompletedEvent must preserve phase on output items inside the response."""
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completed_chunk = {
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"type": "response.completed",
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"response": {
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"id": "resp_300",
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"created_at": 1700000000,
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"model": "gpt-5.3-codex",
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"object": "response",
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"status": "completed",
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"output": [
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{
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"type": "message",
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"id": "msg_300",
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"status": "completed",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "final"}],
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"phase": "final_answer",
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}
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],
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"usage": {
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"input_tokens": 5,
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"output_tokens": 10,
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"total_tokens": 15,
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},
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},
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}
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result = self.config.transform_streaming_response(
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model=self.model,
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parsed_chunk=completed_chunk,
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logging_obj=self.logging_obj,
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)
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assert result.type == ResponsesAPIStreamEvents.RESPONSE_COMPLETED
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output_item = result.response.output[0]
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if isinstance(output_item, dict):
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assert output_item["phase"] == "final_answer"
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else:
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assert getattr(output_item, "phase", None) == "final_answer"
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def test_phase_roundtrip_output_to_input(self):
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"""Simulate full round-trip: parse response output, then send items back as input."""
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raw_json = {
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"id": "resp_rt",
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"created_at": 1700000000,
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"model": "gpt-5.3-codex",
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"object": "response",
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"status": "completed",
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"output": [
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{
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"type": "message",
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"id": "msg_rt1",
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"status": "completed",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "preamble"}],
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"phase": "commentary",
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},
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{
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"type": "message",
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"id": "msg_rt2",
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"status": "completed",
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"role": "assistant",
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"content": [{"type": "output_text", "text": "answer"}],
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"phase": "final_answer",
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},
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],
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"usage": {"input_tokens": 10, "output_tokens": 20, "total_tokens": 30},
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}
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response = ResponsesAPIResponse(**raw_json)
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input_items = []
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for item in response.output:
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if isinstance(item, dict):
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input_items.append(item)
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else:
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input_items.append(
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item.model_dump() if hasattr(item, "model_dump") else dict(item)
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)
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input_items.append(
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{
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"type": "message",
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"role": "user",
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"content": [{"type": "input_text", "text": "next question"}],
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}
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)
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validated = self.config._validate_input_param(input_items)
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assert isinstance(validated, list)
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assert validated[0]["phase"] == "commentary"
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assert validated[1]["phase"] == "final_answer"
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assert "phase" not in validated[2]
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