Recursively rebuild models in openai.types

temporalio/contrib/openai_agents/__init__.py

@@ -7,7 +7,6 @@
     This module is experimental and may change in future versions.
     Use with caution in production environments.
 """
-
 from temporalio.contrib.openai_agents._invoke_model_activity import ModelActivity
 from temporalio.contrib.openai_agents._model_parameters import ModelActivityParameters
 from temporalio.contrib.openai_agents._trace_interceptor import (
@@ -30,3 +29,4 @@
     "TestModel",
     "TestModelProvider",
 ]
+

temporalio/contrib/openai_agents/_invoke_model_activity.py

@@ -5,7 +5,7 @@
 
 import enum
 import json
-from dataclasses import dataclass
+from pydantic.dataclasses import dataclass
 from typing import Any, Optional, Union, cast
 
 from agents import (

temporalio/contrib/pydantic.py

@@ -15,6 +15,7 @@
 
 from typing import Any, Optional, Type
 
+import pydantic.dataclasses
 from pydantic import TypeAdapter
 from pydantic_core import to_json
 

tests/contrib/openai_agents/test_openai.py

@@ -45,7 +45,7 @@
 )
 from openai.types.responses.response_function_web_search import ActionSearch
 from openai.types.responses.response_prompt_param import ResponsePromptParam
-from pydantic import ConfigDict, Field
+from pydantic import ConfigDict, Field, TypeAdapter
 
 from temporalio import activity, workflow
 from temporalio.client import Client, WorkflowFailureError, WorkflowHandle
@@ -1736,3 +1736,22 @@ async def test_workflow_method_tools(client: Client):
                 execution_timeout=timedelta(seconds=10),
             )
             await workflow_handle.result()
+
+
+async def test_response_serialization():
+    import json
+
+    from openai.types.responses.response_output_item import ImageGenerationCall
+
+    data = json.loads(
+        b'{"id": "msg_68757ec43348819d86709f0fcb70316301a1194a3e05b38c","type": "image_generation_call","status": "completed"}'
+    )
+    call = TypeAdapter(ImageGenerationCall).validate_python(data)
+    model_response = ModelResponse(
+        output=[
+            call,
+        ],
+        usage=Usage(),
+        response_id="",
+    )
+    encoded = await pydantic_data_converter.encode([model_response])