fix: use model_dump() instead of deprecated dict() in OpenAI output paths

The pydantic v1 .dict() API emits PydanticDeprecatedSince20 on
pydantic v2, which breaks anyone running with DeprecationWarnings as
errors. Every supported openai/openai-agents version requires
pydantic v2, so model_dump() is a drop-in replacement here.

Fixes #7827.

Author: intertermux-code

sentry_sdk/integrations/openai.py

@@ -730,15 +730,15 @@ def _set_common_output_data(
             if record_outputs:
                 for output in response.output:
                     if output.type == "function_call":
-                        output_messages["tool"].append(output.dict())
+                        output_messages["tool"].append(output.model_dump())
                     elif output.type == "message":
                         for output_message in output.content:
                             try:
                                 output_messages["response"].append(output_message.text)  # type: ignore[union-attr]
                             except AttributeError:
                                 # Unknown output message type, just return the json
                                 output_messages["response"].append(
-                                    output_message.dict()
+                                    output_message.model_dump()
                                 )
 
                 if len(output_messages["tool"]) > 0:
@@ -761,14 +761,16 @@ def _set_common_output_data(
         ):
             for output in response.output:
                 if output.type == "function_call":
-                    output_messages["tool"].append(output.dict())
+                    output_messages["tool"].append(output.model_dump())
                 elif output.type == "message":
                     for output_message in output.content:
                         try:
                             output_messages["response"].append(output_message.text)  # type: ignore[union-attr]
                         except AttributeError:
                             # Unknown output message type, just return the json
-                            output_messages["response"].append(output_message.dict())
+                            output_messages["response"].append(
+                                output_message.model_dump()
+                            )
 
             if len(output_messages["tool"]) > 0:
                 set_data_normalized(

sentry_sdk/integrations/openai_agents/utils.py

@@ -226,14 +226,14 @@ def _set_output_data(
 
     for output in result.output:
         if output.type == "function_call":
-            output_messages["tool"].append(output.dict())
+            output_messages["tool"].append(output.model_dump())
         elif output.type == "message":
             for output_message in output.content:
                 try:
                     output_messages["response"].append(output_message.text)
                 except AttributeError:
                     # Unknown output message type, just return the json
-                    output_messages["response"].append(output_message.dict())
+                    output_messages["response"].append(output_message.model_dump())
 
     if record_outputs and len(output_messages["tool"]) > 0:
         if isinstance(span, StreamedSpan):

tests/integrations/openai_agents/test_openai_agents.py

@@ -2,6 +2,8 @@
 import json
 import logging
 import os
+import warnings
+from types import SimpleNamespace
 from unittest import mock
 from unittest.mock import MagicMock, patch
 
@@ -20,6 +22,7 @@
 from agents.items import (
     ResponseFunctionToolCall,
     ResponseOutputMessage,
+    ResponseOutputRefusal,
     ResponseOutputText,
 )
 from agents.models.openai_responses import OpenAIResponsesModel
@@ -72,7 +75,11 @@
 from sentry_sdk.consts import OP, SPANDATA
 from sentry_sdk.integrations.logging import LoggingIntegration
 from sentry_sdk.integrations.openai_agents import OpenAIAgentsIntegration
-from sentry_sdk.integrations.openai_agents.utils import _set_input_data, safe_serialize
+from sentry_sdk.integrations.openai_agents.utils import (
+    _set_input_data,
+    _set_output_data,
+    safe_serialize,
+)
 from sentry_sdk.integrations.stdlib import StdlibIntegration
 from sentry_sdk.utils import package_version, parse_version
 
@@ -7483,3 +7490,45 @@ async def test_runner_run_streamed_with_starting_agent_kwarg(
 
     (transaction,) = events
     assert transaction["transaction"] == "test_agent workflow"
+
+
+def test_set_output_data_tool_calls_no_pydantic_deprecation(sentry_init):
+    """Serializing tool-call output must not use the deprecated pydantic v1 API.
+
+    Regression test for GH-7827: _set_output_data called BaseModel.dict(),
+    which raises PydanticDeprecatedSince20 when DeprecationWarnings are errors.
+    """
+    sentry_init(
+        integrations=[OpenAIAgentsIntegration()],
+        send_default_pii=True,
+        traces_sample_rate=1.0,
+    )
+
+    tool_call = ResponseFunctionToolCall(
+        type="function_call",
+        id="call_1",
+        call_id="call_1",
+        name="get_weather",
+        arguments='{"city": "Berlin"}',
+        status="completed",
+    )
+    refusal = ResponseOutputRefusal(type="refusal", refusal="I cannot help.")
+    message = ResponseOutputMessage(
+        type="message",
+        id="msg_1",
+        role="assistant",
+        content=[refusal],
+        status="completed",
+    )
+    result = SimpleNamespace(output=[tool_call, message])
+
+    with start_span(op="test") as span:
+        with warnings.catch_warnings():
+            warnings.simplefilter("error", DeprecationWarning)
+            _set_output_data(span, result)
+
+    tool_calls = json.loads(span._data[SPANDATA.GEN_AI_RESPONSE_TOOL_CALLS])
+    assert tool_calls[0]["name"] == "get_weather"
+    assert tool_calls[0]["arguments"] == '{"city": "Berlin"}'
+
+    assert "I cannot help." in span._data[SPANDATA.GEN_AI_RESPONSE_TEXT]