Fix typecheck errors and add coverage tests for file search

- Fix typecheck errors in test_google.py by properly checking event types
- Remove unnecessary comments
- Add tests to cover missing branches in openai.py:
  - Test openai_include_file_search_results setting (line 1334)
  - Test file_search with results (line 2503)
  - Test round-trip status update (line 1697)

Author: gorkachea

tests/models/test_google.py

@@ -4115,7 +4115,6 @@ async def test_google_model_file_search_tool_stream(allow_model_requests: None,
 
 async def test_google_model_file_search_empty_grounding_chunks():
     """Test that file search handles empty grounding_chunks gracefully."""
-    # Create a response with grounding_metadata but empty grounding_chunks
     response = GenerateContentResponse.model_validate(
         {
             'response_id': 'test-123',
@@ -4132,7 +4131,7 @@ async def test_google_model_file_search_empty_grounding_chunks():
                         'parts': [{'text': 'Some text'}],
                     },
                     'grounding_metadata': {
-                        'grounding_chunks': [],  # Empty grounding_chunks
+                        'grounding_chunks': [],
                     },
                 }
             ],
@@ -4150,18 +4149,17 @@ async def response_iterator() -> AsyncIterator[GenerateContentResponse]:
         _provider_name='test-provider',
         _provider_url='',
     )
-    # Set _file_search_tool_call_id to trigger the code path
     streamed_response._file_search_tool_call_id = 'test-tool-call-id'  # pyright: ignore[reportPrivateUsage]
 
     events = [event async for event in streamed_response._get_event_iterator()]  # pyright: ignore[reportPrivateUsage]
-    # Should not crash and should emit text event
     assert len(events) > 0
-    assert any(isinstance(event.part, TextPart) if hasattr(event, 'part') else False for event in events)
+    assert any(
+        isinstance(event, PartStartEvent | PartEndEvent) and isinstance(event.part, TextPart) for event in events
+    )
 
 
 async def test_google_model_file_search_empty_retrieved_contexts():
     """Test that file search handles empty retrieved_contexts gracefully."""
-    # Create a response with grounding_chunks but no retrieved_context
     response = GenerateContentResponse.model_validate(
         {
             'response_id': 'test-123',
@@ -4178,11 +4176,7 @@ async def test_google_model_file_search_empty_retrieved_contexts():
                         'parts': [{'text': 'Some text'}],
                     },
                     'grounding_metadata': {
-                        'grounding_chunks': [
-                            {
-                                # Chunk without retrieved_context
-                            }
-                        ],
+                        'grounding_chunks': [{}],
                     },
                 }
             ],
@@ -4200,13 +4194,13 @@ async def response_iterator() -> AsyncIterator[GenerateContentResponse]:
         _provider_name='test-provider',
         _provider_url='',
     )
-    # Set _file_search_tool_call_id to trigger the code path
     streamed_response._file_search_tool_call_id = 'test-tool-call-id'  # pyright: ignore[reportPrivateUsage]
 
     events = [event async for event in streamed_response._get_event_iterator()]  # pyright: ignore[reportPrivateUsage]
-    # Should not crash and should emit text event
     assert len(events) > 0
-    assert any(isinstance(event.part, TextPart) if hasattr(event, 'part') else False for event in events)
+    assert any(
+        isinstance(event, PartStartEvent | PartEndEvent) and isinstance(event.part, TextPart) for event in events
+    )
 
 
 async def test_cache_point_filtering():

tests/models/test_openai_responses.py

@@ -7759,3 +7759,105 @@ async def test_openai_responses_model_file_search_tool_stream(allow_model_reques
         if vector_store is not None:
             await async_client.vector_stores.delete(vector_store.id)
         await async_client.close()
+
+
+async def test_openai_responses_file_search_include_results_setting():
+    from pydantic_ai.providers.openai import OpenAIProvider
+
+    from .mock_openai import MockOpenAIResponses
+
+    mock_client = MockOpenAIResponses(response=response_message([]))
+    model = OpenAIResponsesModel(
+        'gpt-4o',
+        provider=OpenAIProvider(openai_client=cast(Any, mock_client)),
+        model_settings=OpenAIResponsesModelSettings(openai_include_file_search_results=True),
+    )
+
+    async with model.request_stream(
+        messages=[],
+        model_settings=cast(OpenAIResponsesModelSettings, model.settings or {}),
+        model_request_parameters=ModelRequestParameters(),
+    ):
+        pass
+
+    kwargs_list = get_mock_responses_kwargs(cast(Any, mock_client))
+    assert len(kwargs_list) > 0
+    kwargs = kwargs_list[0]
+    assert 'include' in kwargs
+    assert 'file_search_call.results' in kwargs['include']
+
+
+async def test_openai_responses_file_search_with_results():
+    with try_import():
+        from openai.types.responses.response_file_search_tool_call import (
+            ResponseFileSearchToolCall,
+            ResponseFileSearchToolCallResult,
+        )
+
+        from pydantic_ai.models.openai import _map_file_search_tool_call
+
+        result_obj = ResponseFileSearchToolCallResult(
+            document_name='test.txt',
+            text='Test content',
+            score=0.9,
+        )
+        file_search_item = ResponseFileSearchToolCall(
+            id='fs_test',
+            type='file_search_call',
+            status='completed',
+            queries=['test query'],
+            results=[result_obj],
+        )
+
+        call_part, return_part = _map_file_search_tool_call(file_search_item, 'openai')
+        assert call_part.tool_name == 'file_search'
+        assert return_part.content['status'] == 'completed'
+        assert 'results' in return_part.content
+        assert len(return_part.content['results']) == 1
+
+
+async def test_openai_responses_file_search_round_trip_status_update():
+    from pydantic_ai.builtin_tools import FileSearchTool
+    from pydantic_ai.providers.openai import OpenAIProvider
+
+    model = OpenAIResponsesModel('gpt-4o', provider=OpenAIProvider(api_key='test'))
+    messages = [
+        ModelRequest(
+            parts=[UserPromptPart(content='test', timestamp=IsDatetime())],
+            run_id=IsStr(),
+        ),
+        ModelResponse(
+            parts=[
+                BuiltinToolCallPart(
+                    tool_name=FileSearchTool.kind,
+                    args={'queries': ['test']},
+                    tool_call_id='fs_123',
+                    provider_name='openai',
+                ),
+                BuiltinToolReturnPart(
+                    tool_name=FileSearchTool.kind,
+                    content={'status': 'in_progress'},
+                    tool_call_id='fs_123',
+                    timestamp=IsDatetime(),
+                    provider_name='openai',
+                ),
+            ],
+            usage=RequestUsage(input_tokens=10, output_tokens=5),
+            model_name='gpt-4o',
+            timestamp=IsDatetime(),
+            provider_name='openai',
+            finish_reason='stop',
+            run_id=IsStr(),
+        ),
+    ]
+
+    _, openai_messages = await model._map_messages(  # pyright: ignore[reportPrivateUsage]
+        messages,
+        model_settings=cast(OpenAIResponsesModelSettings, model.settings or {}),
+        model_request_parameters=ModelRequestParameters(),
+    )
+
+    file_search_msgs = [msg for msg in openai_messages if isinstance(msg, dict) and msg.get('type') == 'file_search_call']
+    assert len(file_search_msgs) > 0
+    file_search_msg = file_search_msgs[0]
+    assert file_search_msg.get('status') == 'in_progress'