Don't lose Azure OpenAI Responses encrypted_content if no summary was included

pydantic_ai_slim/pydantic_ai/models/openai.py

@@ -859,18 +859,28 @@ def _process_response(self, response: responses.Response) -> ModelResponse:
         for item in response.output:
             if isinstance(item, responses.ResponseReasoningItem):
                 signature = item.encrypted_content
-                for summary in item.summary:
-                    # We use the same id for all summaries so that we can merge them on the round trip.
-                    # We only need to store the signature once.
+                if item.summary:
+                    for summary in item.summary:
+                        # We use the same id for all summaries so that we can merge them on the round trip.
+                        items.append(
+                            ThinkingPart(
+                                content=summary.text,
+                                id=item.id,
+                                signature=signature,
+                                provider_name=self.system if signature else None,
+                            )
+                        )
+                        # We only need to store the signature once.
+                        signature = None
+                elif signature:
                     items.append(
                         ThinkingPart(
-                            content=summary.text,
+                            content='',
                             id=item.id,
                             signature=signature,
-                            provider_name=self.system if signature else None,
+                            provider_name=self.system,
                         )
                     )
-                    signature = None
                 # NOTE: We don't currently handle the raw CoT from gpt-oss `reasoning_text`: https://cookbook.openai.com/articles/gpt-oss/handle-raw-cot
                 # If you need this, please file an issue.
             elif isinstance(item, responses.ResponseOutputMessage):
@@ -1122,20 +1132,20 @@ async def _map_messages(  # noqa: C901
                         # We don't currently track built-in tool calls from OpenAI
                         pass
                     elif isinstance(item, ThinkingPart):
-                        if reasoning_item is not None and item.id == reasoning_item['id']:
+                        if reasoning_item is None or reasoning_item['id'] != item.id:
+                            reasoning_item = responses.ResponseReasoningItemParam(
+                                id=item.id or _utils.generate_tool_call_id(),
+                                summary=[],
+                                encrypted_content=item.signature if item.provider_name == self.system else None,
+                                type='reasoning',
+                            )
+                            openai_messages.append(reasoning_item)
+
+                        if item.content:
                             reasoning_item['summary'] = [
                                 *reasoning_item['summary'],
                                 Summary(text=item.content, type='summary_text'),
                             ]
-                            continue
-
-                        reasoning_item = responses.ResponseReasoningItemParam(
-                            id=item.id or _utils.generate_tool_call_id(),
-                            summary=[Summary(text=item.content, type='summary_text')],
-                            encrypted_content=item.signature if item.provider_name == self.system else None,
-                            type='reasoning',
-                        )
-                        openai_messages.append(reasoning_item)
                     else:
                         assert_never(item)
             else:

tests/models/test_openai_responses.py

@@ -38,6 +38,7 @@
 
 with try_import() as imports_successful:
     from openai.types.responses.response_output_message import Content, ResponseOutputMessage, ResponseOutputText
+    from openai.types.responses.response_reasoning_item import ResponseReasoningItem
     from openai.types.responses.response_usage import ResponseUsage
 
     from pydantic_ai.models.openai import OpenAIResponsesModel, OpenAIResponsesModelSettings
@@ -1404,3 +1405,59 @@ def update_plan(plan: str) -> str:
             ),
         ]
     )
+
+
+async def test_openai_responses_thinking_without_summary(allow_model_requests: None):
+    c = response_message(
+        [
+            ResponseReasoningItem(
+                id='reasoning',
+                summary=[],
+                type='reasoning',
+                encrypted_content='123',
+            ),
+            ResponseOutputMessage(
+                id='text',
+                content=cast(list[Content], [ResponseOutputText(text='4', type='output_text', annotations=[])]),
+                role='assistant',
+                status='completed',
+                type='message',
+            ),
+        ],
+    )
+    mock_client = MockOpenAIResponses.create_mock(c)
+    model = OpenAIResponsesModel('gpt-5', provider=OpenAIProvider(openai_client=mock_client))
+
+    agent = Agent(model=model)
+    result = await agent.run('What is 2+2?')
+    assert result.all_messages() == snapshot(
+        [
+            ModelRequest(
+                parts=[
+                    UserPromptPart(
+                        content='What is 2+2?',
+                        timestamp=IsDatetime(),
+                    )
+                ]
+            ),
+            ModelResponse(
+                parts=[
+                    ThinkingPart(content='', id='reasoning', signature='123', provider_name='openai'),
+                    TextPart(content='4'),
+                ],
+                model_name='gpt-4o-123',
+                timestamp=IsDatetime(),
+                provider_name='openai',
+                provider_response_id='123',
+            ),
+        ]
+    )
+
+    _, openai_messages = await model._map_messages(result.all_messages())  # type: ignore[reportPrivateUsage]
+    assert openai_messages == snapshot(
+        [
+            {'role': 'user', 'content': 'What is 2+2?'},
+            {'id': 'reasoning', 'summary': [], 'encrypted_content': '123', 'type': 'reasoning'},
+            {'role': 'assistant', 'content': '4'},
+        ]
+    )