declare transformer in profiles/anthropic.py to encapsulate dependency

Author: dsfaccini

pydantic_ai_slim/pydantic_ai/profiles/anthropic.py

@@ -1,11 +1,14 @@
 from __future__ import annotations as _annotations
 
-from pydantic_ai.providers.anthropic import AnthropicJsonSchemaTransformer
+from pydantic_ai._json_schema import JsonSchemaTransformer
 
 from . import ModelProfile
 
 
-def anthropic_model_profile(model_name: str) -> ModelProfile | None:
+def anthropic_model_profile(
+    model_name: str,
+    anthropic_json_schema_transformer: type[JsonSchemaTransformer] | None = None,
+) -> ModelProfile | None:
     """Get the model profile for an Anthropic model."""
     models_that_support_json_schema_output = ('claude-sonnet-4-5', 'claude-opus-4-1', 'claude-opus-4-5')
     """These models support both structured outputs and strict tool calling."""
@@ -15,6 +18,6 @@ def anthropic_model_profile(model_name: str) -> ModelProfile | None:
     supports_json_schema_output = model_name.startswith(models_that_support_json_schema_output)
     return ModelProfile(
         thinking_tags=('<thinking>', '</thinking>'),
-        supports_json_schema_output=supports_json_schema_output,
-        json_schema_transformer=AnthropicJsonSchemaTransformer,
+        supports_json_schema_output=supports_json_schema_output and anthropic_json_schema_transformer is not None,
+        json_schema_transformer=anthropic_json_schema_transformer,
     )

pydantic_ai_slim/pydantic_ai/providers/anthropic.py

@@ -25,6 +25,60 @@
 AsyncAnthropicClient: TypeAlias = AsyncAnthropic | AsyncAnthropicBedrock | AsyncAnthropicVertex
 
 
+@dataclass(init=False)
+class AnthropicJsonSchemaTransformer(JsonSchemaTransformer):
+    """Transforms schemas to the subset supported by Anthropic structured outputs.
+
+    Transformation is applied when:
+    - `NativeOutput` is used as the `output_type` of the Agent
+    - `strict=True` is set on the `Tool`
+
+    The behavior of this transformer differs from the OpenAI one in that it sets `Tool.strict=False` by default when not explicitly set to True.
+
+    Example:
+        ```python
+        from pydantic_ai import Agent
+
+        agent = Agent('anthropic:claude-sonnet-4-5')
+
+        @agent.tool_plain  # -> defaults to strict=False
+        def my_tool(x: str) -> dict[str, int]:
+            ...
+        ```
+
+    Anthropic's SDK `transform_schema()` automatically:
+    - Adds `additionalProperties: false` to all objects (required by API)
+    - Removes unsupported constraints (minLength, pattern, etc.)
+    - Moves removed constraints to description field
+    - Removes title and $schema fields
+    """
+
+    def walk(self) -> JsonSchema:
+        from anthropic import transform_schema
+
+        schema = super().walk()
+
+        # The caller (pydantic_ai.models._customize_tool_def or _customize_output_object) coalesces
+        # - output_object.strict = self.is_strict_compatible
+        # - tool_def.strict = self.is_strict_compatible
+        # the reason we don't default to `strict=True` is that the transformation could be lossy
+        # so in order to change the behavior (default to True), we need to come up with logic that will check for lossiness
+        # https://github.com/pydantic/pydantic-ai/issues/3541
+        self.is_strict_compatible = self.strict is True  # not compatible when strict is False/None
+
+        if self.strict is True:
+            from anthropic import transform_schema
+
+            return transform_schema(schema)
+        else:
+            return schema
+
+    def transform(self, schema: JsonSchema) -> JsonSchema:
+        schema.pop('title', None)
+        schema.pop('$schema', None)
+        return schema
+
+
 class AnthropicProvider(Provider[AsyncAnthropicClient]):
     """Provider for Anthropic API."""
 
@@ -41,7 +95,7 @@ def client(self) -> AsyncAnthropicClient:
         return self._client
 
     def model_profile(self, model_name: str) -> ModelProfile | None:
-        return anthropic_model_profile(model_name)
+        return anthropic_model_profile(model_name, AnthropicJsonSchemaTransformer)
 
     @overload
     def __init__(self, *, anthropic_client: AsyncAnthropicClient | None = None) -> None: ...
@@ -85,57 +139,3 @@ def __init__(
             else:
                 http_client = cached_async_http_client(provider='anthropic')
                 self._client = AsyncAnthropic(api_key=api_key, base_url=base_url, http_client=http_client)
-
-
-@dataclass(init=False)
-class AnthropicJsonSchemaTransformer(JsonSchemaTransformer):
-    """Transforms schemas to the subset supported by Anthropic structured outputs.
-
-    Transformation is applied when:
-    - `NativeOutput` is used as the `output_type` of the Agent
-    - `strict=True` is set on the `Tool`
-
-    The behavior of this transformer differs from the OpenAI one in that it sets `Tool.strict=False` by default when not explicitly set to True.
-
-    Example:
-        ```python
-        from pydantic_ai import Agent
-
-        agent = Agent('anthropic:claude-sonnet-4-5')
-
-        @agent.tool_plain  # -> defaults to strict=False
-        def my_tool(x: str) -> dict[str, int]:
-            ...
-        ```
-
-    Anthropic's SDK `transform_schema()` automatically:
-    - Adds `additionalProperties: false` to all objects (required by API)
-    - Removes unsupported constraints (minLength, pattern, etc.)
-    - Moves removed constraints to description field
-    - Removes title and $schema fields
-    """
-
-    def walk(self) -> JsonSchema:
-        from anthropic import transform_schema
-
-        schema = super().walk()
-
-        # The caller (pydantic_ai.models._customize_tool_def or _customize_output_object) coalesces
-        # - output_object.strict = self.is_strict_compatible
-        # - tool_def.strict = self.is_strict_compatible
-        # the reason we don't default to `strict=True` is that the transformation could be lossy
-        # so in order to change the behavior (default to True), we need to come up with logic that will check for lossiness
-        # https://github.com/pydantic/pydantic-ai/issues/3541
-        self.is_strict_compatible = self.strict is True  # not compatible when strict is False/None
-
-        if self.strict is True:
-            from anthropic import transform_schema
-
-            return transform_schema(schema)
-        else:
-            return schema
-
-    def transform(self, schema: JsonSchema) -> JsonSchema:
-        schema.pop('title', None)
-        schema.pop('$schema', None)
-        return schema