Fix typecheck errors

Author: g-eoj

pydantic_ai_slim/pydantic_ai/_output.py

@@ -465,7 +465,7 @@ def __init__(
         self.processor = processor
 
     def dump(self) -> JsonSchema:
-        return self.object_def.json_schema
+        return self.object_def.json_schema # pyright: ignore[reportOptionalMemberAccess]
 
 
 class NativeOutputSchema(StructuredTextOutputSchema[OutputDataT]):
@@ -541,9 +541,9 @@ def mode(self) -> OutputMode:
         return 'tool'
 
     def dump(self) -> JsonSchema:
-        toolset_processors = [self.toolset.processors[k] for k in self.toolset.processors]
-        processors_union = UnionOutputProcessor(toolset_processors).object_def.json_schema
-        return processors_union
+        toolset_processors = [self.toolset.processors[k] for k in self.toolset.processors] # pyright: ignore[reportOptionalMemberAccess]
+        processors_union = UnionOutputProcessor(toolset_processors)
+        return processors_union.object_def.json_schema
 
 
 class BaseOutputProcessor(ABC, Generic[OutputDataT]):
@@ -736,7 +736,7 @@ class UnionOutputProcessor(BaseObjectOutputProcessor[OutputDataT]):
 
     def __init__(
         self,
-        outputs: Sequence[OutputTypeOrFunction[OutputDataT]],
+        outputs: Sequence[OutputTypeOrFunction[OutputDataT]|ObjectOutputProcessor[OutputDataT]],
         *,
         name: str | None = None,
         description: str | None = None,

tests/test_agent.py

@@ -6152,8 +6152,8 @@ def llm(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:
         return ModelResponse(parts=[TextPart('')])
 
     agent = Agent(
-        FunctionModel(llm), 
-        output_type=NativeOutput([bool], name='native_output_name', description='native_output_description')
+        FunctionModel(llm),
+        output_type=NativeOutput([bool], name='native_output_name', description='native_output_description'),
     )
     assert agent.output_json_schema
 
@@ -6163,8 +6163,8 @@ def llm(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:
         return ModelResponse(parts=[TextPart('')])
 
     agent = Agent(
-        FunctionModel(llm), 
-        output_type=PromptedOutput([bool], name='prompted_output_name', description='prompted_output_description')
+        FunctionModel(llm),
+        output_type=PromptedOutput([bool], name='prompted_output_name', description='prompted_output_description'),
     )
     assert agent.output_json_schema
 
@@ -6176,11 +6176,8 @@ def llm(messages: list[ModelMessage], info: AgentInfo) -> ModelResponse:
     HumanDict = StructuredDict(
         {
             'type': 'object',
-            'properties': {
-                'name': {'type': 'string'},
-                'age': {'type': 'integer'}
-            },
-            'required': ['name', 'age']
+            'properties': {'name': {'type': 'string'}, 'age': {'type': 'integer'}},
+            'required': ['name', 'age'],
         },
         name='Human',
         description='A human with a name and age',