Merge branch 'master' into master

Author: NamitAdhikari

tests/integrations/openai_agents/test_openai_agents.py

@@ -143,6 +143,83 @@ async def EXAMPLE_STREAMED_RESPONSE(*args, **kwargs):
     )
 
 
+async def EXAMPLE_STREAMED_RESPONSE_WITH_DELTA(*args, **kwargs):
+    yield ResponseCreatedEvent(
+        response=Response(
+            id="chat-id",
+            output=[],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="response-model-id",
+            object="response",
+        ),
+        type="response.created",
+        sequence_number=0,
+    )
+
+    yield ResponseTextDeltaEvent(
+        type="response.output_text.delta",
+        item_id="message-id",
+        output_index=0,
+        content_index=0,
+        delta="Hello",
+        logprobs=[],
+        sequence_number=1,
+    )
+
+    yield ResponseTextDeltaEvent(
+        type="response.output_text.delta",
+        item_id="message-id",
+        output_index=0,
+        content_index=0,
+        delta=" world!",
+        logprobs=[],
+        sequence_number=2,
+    )
+
+    yield ResponseCompletedEvent(
+        response=Response(
+            id="chat-id",
+            output=[
+                ResponseOutputMessage(
+                    id="message-id",
+                    content=[
+                        ResponseOutputText(
+                            annotations=[],
+                            text="Hello world!",
+                            type="output_text",
+                        ),
+                    ],
+                    role="assistant",
+                    status="completed",
+                    type="message",
+                ),
+            ],
+            parallel_tool_calls=False,
+            tool_choice="none",
+            tools=[],
+            created_at=10000000,
+            model="response-model-id",
+            object="response",
+            usage=ResponseUsage(
+                input_tokens=20,
+                input_tokens_details=InputTokensDetails(
+                    cached_tokens=5,
+                ),
+                output_tokens=10,
+                output_tokens_details=OutputTokensDetails(
+                    reasoning_tokens=8,
+                ),
+                total_tokens=30,
+            ),
+        ),
+        type="response.completed",
+        sequence_number=3,
+    )
+
+
 @pytest.fixture
 def mock_usage():
     return Usage(
@@ -2692,27 +2769,6 @@ def test_openai_agents_message_truncation(sentry_init, capture_events):
         assert "small message 5" in str(parsed_messages[0])
 
 
-def test_streaming_patches_applied(sentry_init):
-    """
-    Test that the streaming patches are applied correctly.
-    """
-    sentry_init(
-        integrations=[OpenAIAgentsIntegration()],
-        traces_sample_rate=1.0,
-    )
-
-    # Verify that run_streamed is patched (will have __wrapped__ attribute if patched)
-    import agents
-
-    # Check that the method exists and has been modified
-    assert hasattr(agents.run.DEFAULT_AGENT_RUNNER, "run_streamed")
-    assert hasattr(agents.run.AgentRunner, "_run_single_turn_streamed")
-
-    # Verify the patches were applied by checking for our wrapper
-    run_streamed_func = agents.run.DEFAULT_AGENT_RUNNER.run_streamed
-    assert run_streamed_func is not None
-
-
 @pytest.mark.asyncio
 async def test_streaming_span_update_captures_response_data(
     sentry_init, test_agent, mock_usage
@@ -2777,86 +2833,46 @@ async def test_streaming_ttft_on_chat_span(sentry_init, test_agent):
     Events WITHOUT delta (like ResponseCompletedEvent, ResponseCreatedEvent, etc.)
     should NOT trigger TTFT.
     """
-    from sentry_sdk.integrations.openai_agents.patches.models import (
-        _create_get_model_wrapper,
+    client = AsyncOpenAI(api_key="z")
+    client.responses._post = AsyncMock(return_value=EXAMPLE_RESPONSE)
+
+    model = OpenAIResponsesModel(model="gpt-4", openai_client=client)
+
+    agent_with_tool = test_agent.clone(
+        model=model,
     )
 
     sentry_init(
         integrations=[OpenAIAgentsIntegration()],
         traces_sample_rate=1.0,
     )
 
-    # Create a mock model with stream_response and get_response
-    class MockModel:
-        model = "gpt-4"
-
-        async def get_response(self, *args, **kwargs):
-            # Not used in this test, but required by the wrapper
-            pass
-
-        async def stream_response(self, *args, **kwargs):
-            # First event: ResponseCreatedEvent (no delta - should NOT trigger TTFT)
-            created_event = MagicMock(spec=["type", "sequence_number"])
-            created_event.type = "response.created"
-            yield created_event
-
-            # Simulate server-side processing delay before first token
-            await asyncio.sleep(0.05)  # 50ms delay
-
-            # Second event: ResponseTextDeltaEvent (HAS delta - triggers TTFT)
-            text_delta_event = MagicMock(spec=["delta", "type", "content_index"])
-            text_delta_event.delta = "Hello"
-            text_delta_event.type = "response.output_text.delta"
-            yield text_delta_event
-
-            # Third event: more text content (also has delta, but TTFT already recorded)
-            text_delta_event2 = MagicMock(spec=["delta", "type", "content_index"])
-            text_delta_event2.delta = " world!"
-            text_delta_event2.type = "response.output_text.delta"
-            yield text_delta_event2
-
-            # Final event: ResponseCompletedEvent (has response, no delta)
-            completed_event = MagicMock(spec=["response", "type", "sequence_number"])
-            completed_event.response = MagicMock()
-            completed_event.response.model = "gpt-4"
-            completed_event.response.usage = Usage(
-                requests=1,
-                input_tokens=10,
-                output_tokens=5,
-                total_tokens=15,
-            )
-            completed_event.response.output = []
-            yield completed_event
-
-    # Create a mock original _get_model that returns our mock model
-    def mock_get_model(agent, run_config):
-        return MockModel()
-
-    # Wrap it with our integration wrapper
-    wrapped_get_model = _create_get_model_wrapper(mock_get_model)
-
-    with sentry_sdk.start_transaction(name="test_ttft", sampled=True) as transaction:
-        # Get the wrapped model (this applies the stream_response wrapper)
-        wrapped_model = wrapped_get_model(None, test_agent, MagicMock())
-
-        # Call the wrapped stream_response and consume all events
-        async for _event in wrapped_model.stream_response():
-            pass
-
-        # Verify TTFT is recorded on the chat span (must be inside transaction context)
-        chat_spans = [
-            s for s in transaction._span_recorder.spans if s.op == "gen_ai.chat"
-        ]
-        assert len(chat_spans) >= 1
-        chat_span = chat_spans[0]
+    with patch.object(
+        model._client.responses,
+        "create",
+        side_effect=EXAMPLE_STREAMED_RESPONSE_WITH_DELTA,
+    ) as _:
+        with sentry_sdk.start_transaction(
+            name="test_ttft", sampled=True
+        ) as transaction:
+            result = agents.Runner.run_streamed(
+                agent_with_tool,
+                "Please use the simple test tool",
+                run_config=test_run_config,
+            )
 
-        assert SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN in chat_span._data
-        ttft_value = chat_span._data[SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN]
-        # TTFT should be at least 40ms (our simulated delay minus some variance) but reasonable
-        assert 0.04 < ttft_value < 1.0, f"TTFT {ttft_value} should be around 50ms"
+            async for event in result.stream_events():
+                pass
+
+            # Verify TTFT is recorded on the chat span (must be inside transaction context)
+            chat_spans = [
+                s for s in transaction._span_recorder.spans if s.op == "gen_ai.chat"
+            ]
+            assert len(chat_spans) >= 1
+            chat_span = chat_spans[0]
 
-        # Verify streaming flag is set
-        assert chat_span._data.get(SPANDATA.GEN_AI_RESPONSE_STREAMING) is True
+            assert SPANDATA.GEN_AI_RESPONSE_TIME_TO_FIRST_TOKEN in chat_span._data
+            assert chat_span._data.get(SPANDATA.GEN_AI_RESPONSE_STREAMING) is True
 
 
 @pytest.mark.skipif(