Repository: pydantic/pydantic-ai
File: pydantic_ai_slim/pydantic_ai/exceptions.py (Python)

Code before:
            {
                'message': core_schema.typed_dict_field(core_schema.str_schema()),
                'kind': core_schema.typed_dict_field(core_schema.literal_schema(['model-retry'])),
            }
        )
        return core_schema.no_info_after_validator_function(
            lambda dct: ModelRetry(dct['message']),
            schema,
            serialization=core_schema.plain_serializer_function_ser_schema(
                lambda x: {'message': x.message, 'kind': 'model-retry'},
                return_schema=schema,
            ),
        )


class CallDeferred(Exception):
    """Exception to raise when a tool call should be deferred.

    See [tools docs](../deferred-tools.md#deferred-tools) for more information.

    Args:
        metadata: Optional dictionary of metadata to attach to the deferred tool call.
            This metadata will be available in `DeferredToolRequests.metadata` keyed by `tool_call_id`.
    """

    def __init__(self, metadata: dict[str, Any] | None = None):
        self.metadata = metadata or {}
        super().__init__()


class ApprovalRequired(Exception):
    """Exception to raise when a tool call requires human-in-the-loop approval.

    See [tools docs](../deferred-tools.md#human-in-the-loop-tool-approval) for more information.

    Args:
        metadata: Optional dictionary of metadata to attach to the deferred tool call.
            This metadata will be available in `DeferredToolRequests.metadata` keyed by `tool_call_id`.
    """

    def __init__(self, metadata: dict[str, Any] | None = None):
        self.metadata = metadata or {}
        super().__init__()


class UserError(RuntimeError):
    """Error caused by a usage mistake by the application developer — You!"""

    message: str
    """Description of the mistake."""


Review comment (suggestion):
You'll want to update the `TemporalWrapperToolset._{un}wrap_call_tool_result` methods to consider the new metadata arg as well

Code after:
    def __get_pydantic_core_schema__(cls, _: Any, __: Any) -> core_schema.CoreSchema:
        """Pydantic core schema to allow `ModelRetry` to be (de)serialized."""
        schema = core_schema.typed_dict_schema(
            {
                'message': core_schema.typed_dict_field(core_schema.str_schema()),
                'kind': core_schema.typed_dict_field(core_schema.literal_schema(['model-retry'])),
            }
        )
        return core_schema.no_info_after_validator_function(
            lambda dct: ModelRetry(dct['message']),
            schema,
            serialization=core_schema.plain_serializer_function_ser_schema(
                lambda x: {'message': x.message, 'kind': 'model-retry'},
                return_schema=schema,
            ),
        )


class CallDeferred(Exception):
    """Exception to raise when a tool call should be deferred.

    See [tools docs](../deferred-tools.md#deferred-tools) for more information.

    Args:
        metadata: Optional dictionary of metadata to attach to the deferred tool call.
            This metadata will be available in `DeferredToolRequests.metadata` keyed by `tool_call_id`.
    """

    def __init__(self, metadata: dict[str, Any] | None = None):
        self.metadata = metadata
        super().__init__()


class ApprovalRequired(Exception):
    """Exception to raise when a tool call requires human-in-the-loop approval.

    See [tools docs](../deferred-tools.md#human-in-the-loop-tool-approval) for more information.

    Args:
        metadata: Optional dictionary of metadata to attach to the deferred tool call.
            This metadata will be available in `DeferredToolRequests.metadata` keyed by `tool_call_id`.
    """

    def __init__(self, metadata: dict[str, Any] | None = None):
        self.metadata = metadata
        super().__init__()


class UserError(RuntimeError):
    """Error caused by a usage mistake by the application developer — You!"""