chore: import upstream snapshot with attribution

2026-07-13 12:39:17 +08:00
commit 4ed4e9ff99
1368 changed files with 334957 additions and 0 deletions
@@ -0,0 +1,165 @@
+import pytest
+from openai.types.chat import ChatCompletion, ChatCompletionMessage
+from openai.types.chat.chat_completion import Choice
+from openai.types.responses.response_usage import InputTokensDetails, OutputTokensDetails
+
+from agents import (
+    ModelSettings,
+    ModelTracing,
+    OpenAIChatCompletionsModel,
+    OpenAIResponsesModel,
+)
+
+
+class DummyResponses:
+    async def create(self, **kwargs):
+        self.kwargs = kwargs
+
+        class DummyResponse:
+            id = "dummy"
+            output = []
+            usage = type(
+                "Usage",
+                (),
+                {
+                    "input_tokens": 0,
+                    "output_tokens": 0,
+                    "total_tokens": 0,
+                    "input_tokens_details": InputTokensDetails.model_validate(
+                        {"cache_write_tokens": 0, "cached_tokens": 0}
+                    ),
+                    "output_tokens_details": OutputTokensDetails(reasoning_tokens=0),
+                },
+            )()
+
+        return DummyResponse()
+
+
+class DummyClient:
+    def __init__(self):
+        self.responses = DummyResponses()
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_top_logprobs_param_passed():
+    client = DummyClient()
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)  # type: ignore
+    await model.get_response(
+        system_instructions=None,
+        input="hi",
+        model_settings=ModelSettings(top_logprobs=2),
+        tools=[],
+        output_schema=None,
+        handoffs=[],
+        tracing=ModelTracing.DISABLED,
+        previous_response_id=None,
+    )
+    assert client.responses.kwargs["top_logprobs"] == 2
+    assert "message.output_text.logprobs" in client.responses.kwargs["include"]
+
+
+class DummyChatCompletions:
+    async def create(self, **kwargs):
+        self.kwargs = kwargs
+        return ChatCompletion(
+            id="dummy",
+            created=0,
+            model="gpt-4",
+            object="chat.completion",
+            choices=[
+                Choice(
+                    index=0,
+                    finish_reason="stop",
+                    message=ChatCompletionMessage(role="assistant", content="hi"),
+                )
+            ],
+            usage=None,
+        )
+
+
+class DummyChatClient:
+    def __init__(self):
+        self.chat = type("_Chat", (), {"completions": DummyChatCompletions()})()
+        self.base_url = "https://api.openai.com/v1"
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_chat_completions_top_logprobs_sets_logprobs_flag():
+    client = DummyChatClient()
+    model = OpenAIChatCompletionsModel(model="gpt-4", openai_client=client)  # type: ignore
+    await model.get_response(
+        system_instructions=None,
+        input="hi",
+        model_settings=ModelSettings(top_logprobs=2),
+        tools=[],
+        output_schema=None,
+        handoffs=[],
+        tracing=ModelTracing.DISABLED,
+        previous_response_id=None,
+    )
+    kwargs = client.chat.completions.kwargs
+    # The Chat Completions API rejects top_logprobs unless logprobs is set to True.
+    assert kwargs["top_logprobs"] == 2
+    assert kwargs["logprobs"] is True
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_chat_completions_omits_logprobs_when_top_logprobs_unset():
+    client = DummyChatClient()
+    model = OpenAIChatCompletionsModel(model="gpt-4", openai_client=client)  # type: ignore
+    await model.get_response(
+        system_instructions=None,
+        input="hi",
+        model_settings=ModelSettings(),
+        tools=[],
+        output_schema=None,
+        handoffs=[],
+        tracing=ModelTracing.DISABLED,
+        previous_response_id=None,
+    )
+    assert "logprobs" not in client.chat.completions.kwargs
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_chat_completions_extra_args_logprobs_passthrough():
+    client = DummyChatClient()
+    model = OpenAIChatCompletionsModel(model="gpt-4", openai_client=client)  # type: ignore
+    await model.get_response(
+        system_instructions=None,
+        input="hi",
+        model_settings=ModelSettings(extra_args={"logprobs": True}),
+        tools=[],
+        output_schema=None,
+        handoffs=[],
+        tracing=ModelTracing.DISABLED,
+        previous_response_id=None,
+    )
+    # With top_logprobs unset, a user can still request plain logprobs via extra_args;
+    # the SDK must not reserve the key and collide with it.
+    assert client.chat.completions.kwargs["logprobs"] is True
+
+
+@pytest.mark.allow_call_model_methods
+@pytest.mark.asyncio
+async def test_chat_completions_top_logprobs_with_extra_args_logprobs_does_not_collide():
+    client = DummyChatClient()
+    model = OpenAIChatCompletionsModel(model="gpt-4", openai_client=client)  # type: ignore
+    await model.get_response(
+        system_instructions=None,
+        input="hi",
+        model_settings=ModelSettings(top_logprobs=2, extra_args={"logprobs": True}),
+        tools=[],
+        output_schema=None,
+        handoffs=[],
+        tracing=ModelTracing.DISABLED,
+        previous_response_id=None,
+    )
+    # Setting both top_logprobs and extra_args["logprobs"] was already a working workaround;
+    # the SDK must defer to the caller's logprobs rather than adding a duplicate that collides.
+    kwargs = client.chat.completions.kwargs
+    assert kwargs["top_logprobs"] == 2
+    assert kwargs["logprobs"] is True