Simplify fix: always remove title, drop customize_request_parameters

Address reviewer feedback from @DouweM:
- Always remove 'title' from all schemas (like OpenAI does)
- Remove unnecessary customize_request_parameters() method
- Remove unused imports (GoogleJsonSchemaTransformer, _customize_tool_def, _customize_output_object)

The original approach of conditionally removing title based on $defs keys
had an edge case where users could customize titles. The simpler approach
of always removing title is safer and cleaner, since the function declaration
name is set separately in ToolDefinition anyway.

Author: conradlee

pydantic_ai_slim/pydantic_ai/models/google.py

@@ -38,16 +38,14 @@
     VideoUrl,
 )
 from ..profiles import ModelProfileSpec
-from ..profiles.google import GoogleJsonSchemaTransformer, GoogleModelProfile
+from ..profiles.google import GoogleModelProfile
 from ..providers import Provider, infer_provider
 from ..settings import ModelSettings
 from ..tools import ToolDefinition
 from . import (
     Model,
     ModelRequestParameters,
     StreamedResponse,
-    _customize_output_object,
-    _customize_tool_def,
     check_allow_model_requests,
     download_item,
     get_user_agent,
@@ -247,48 +245,6 @@ def prepare_request(
                 )
         return super().prepare_request(model_settings, model_request_parameters)
 
-    def customize_request_parameters(self, model_request_parameters: ModelRequestParameters) -> ModelRequestParameters:
-        """Apply schema transformations, using inlining only for tools, not for NativeOutput."""
-        # Transform tools with inlining (default behavior of GoogleJsonSchemaTransformer)
-        model_request_parameters = replace(
-            model_request_parameters,
-            function_tools=[
-                _customize_tool_def(GoogleJsonSchemaTransformer, t) for t in model_request_parameters.function_tools
-            ],
-            output_tools=[
-                _customize_tool_def(GoogleJsonSchemaTransformer, t) for t in model_request_parameters.output_tools
-            ],
-        )
-
-        # For NativeOutput, use GoogleJsonSchemaTransformer with prefer_inlined_defs=False to keep $ref/$defs
-        if output_object := model_request_parameters.output_object:
-            from .._json_schema import JsonSchema
-
-            # Create a subclass that doesn't inline for output objects
-            class GoogleOutputSchemaTransformer(GoogleJsonSchemaTransformer):
-                def __init__(
-                    self,
-                    schema: JsonSchema,
-                    *,
-                    strict: bool | None = None,
-                    simplify_nullable_unions: bool = False,
-                ) -> None:
-                    # Call JsonSchemaTransformer.__init__ directly, skipping GoogleJsonSchemaTransformer.__init__
-                    # to avoid setting prefer_inlined_defs=True
-                    super(GoogleJsonSchemaTransformer, self).__init__(
-                        schema,
-                        strict=strict,
-                        prefer_inlined_defs=False,  # Don't inline for NativeOutput
-                        simplify_nullable_unions=simplify_nullable_unions,
-                    )
-
-            model_request_parameters = replace(
-                model_request_parameters,
-                output_object=_customize_output_object(GoogleOutputSchemaTransformer, output_object),
-            )
-
-        return model_request_parameters
-
     async def request(
         self,
         messages: list[ModelMessage],

pydantic_ai_slim/pydantic_ai/profiles/google.py

@@ -37,10 +37,10 @@ class GoogleJsonSchemaTransformer(JsonSchemaTransformer):
 
     Gemini supports [a subset of OpenAPI v3.0.3](https://ai.google.dev/gemini-api/docs/function-calling#function_declarations).
 
-    Note: Gemini's tool calling system treats 'title' fields in nested schemas as callable function names,
+    Note: Gemini's tool calling system treats 'title' fields as callable function names,
     causing MALFORMED_FUNCTION_CALL errors. This fixes issue #3483 where nested Pydantic models were
-    treated as tool calls instead of structured output schema. We remove 'title' from nested schemas
-    (those defined in $defs) while preserving $ref/$defs structure for better schema organization.
+    treated as tool calls instead of structured output schema. We remove 'title' from all schemas
+    since the function declaration name is set separately in the ToolDefinition.
     """
 
     def transform(self, schema: JsonSchema) -> JsonSchema:
@@ -52,14 +52,10 @@ def transform(self, schema: JsonSchema) -> JsonSchema:
         schema.pop('discriminator', None)
         schema.pop('examples', None)
 
-        # Remove 'title' from nested schemas - Gemini treats these as callable function names
-        # in tool calling mode, causing MALFORMED_FUNCTION_CALL errors for nested objects.
-        # Only keep title at the root level for the function declaration name.
-        # We detect nested schemas by checking if the title matches a key in $defs.
-        if self.defs and 'title' in schema:
-            # Check if this schema's title matches any key in $defs (meaning it's a nested definition)
-            if schema.get('title') in self.defs:
-                schema.pop('title', None)
+        # Remove 'title' - Gemini treats these as callable function names in tool calling mode,
+        # causing MALFORMED_FUNCTION_CALL errors. The title for the function declaration itself
+        # is set separately in the ToolDefinition, so we don't need it in the schema.
+        schema.pop('title', None)
 
         type_ = schema.get('type')
         if type_ == 'string' and (fmt := schema.pop('format', None)):