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### Motivation and Context We have some gaps in how we build the JSON schema for function calling related to Union and Optional types. There is also some work to do related to handling `Optional` versus `param | None = None`. <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> ### Description This PR improves the JSON schema building for the Union and Optional types. It adds additional tests and improves some existing tests. - Closes #7297 - Closes #7298 <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [X] The code builds clean without any errors or warnings - [X] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [X] All unit tests pass, and I have added new tests where possible - [X] I didn't break anyone 😄
214 lines
8.5 KiB
Python
214 lines
8.5 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import types
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from enum import Enum
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from typing import Any, Union, get_args, get_origin, get_type_hints
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from semantic_kernel.const import PARSED_ANNOTATION_UNION_DELIMITER
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from semantic_kernel.exceptions.function_exceptions import FunctionInvalidParameterConfiguration
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from semantic_kernel.kernel_pydantic import KernelBaseModel
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TYPE_MAPPING = {
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int: "integer",
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str: "string",
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bool: "boolean",
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float: "number",
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list: "array",
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dict: "object",
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set: "array",
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tuple: "array",
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"int": "integer",
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"str": "string",
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"bool": "boolean",
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"float": "number",
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"list": "array",
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"dict": "object",
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"set": "array",
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"tuple": "array",
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"object": "object",
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"array": "array",
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}
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class KernelJsonSchemaBuilder:
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@classmethod
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def build(cls, parameter_type: type | str, description: str | None = None) -> dict[str, Any]:
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"""Builds the JSON schema for a given parameter type and description.
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Args:
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parameter_type (type | str): The parameter type.
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description (str, optional): The description of the parameter. Defaults to None.
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Returns:
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dict[str, Any]: The JSON schema for the parameter type.
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"""
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if isinstance(parameter_type, str):
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return cls.build_from_type_name(parameter_type, description)
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if isinstance(parameter_type, KernelBaseModel):
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return cls.build_model_schema(parameter_type, description)
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if isinstance(parameter_type, type) and issubclass(parameter_type, Enum):
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return cls.build_enum_schema(parameter_type, description)
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if hasattr(parameter_type, "__annotations__"):
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return cls.build_model_schema(parameter_type, description)
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if hasattr(parameter_type, "__args__"):
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return cls.handle_complex_type(parameter_type, description)
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schema = cls.get_json_schema(parameter_type)
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if description:
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schema["description"] = description
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return schema
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@classmethod
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def build_model_schema(cls, model: type, description: str | None = None) -> dict[str, Any]:
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"""Builds the JSON schema for a given model and description.
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Args:
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model (type): The model type.
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description (str, optional): The description of the model. Defaults to None.
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Returns:
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dict[str, Any]: The JSON schema for the model.
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"""
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# TODO (moonbox3): add support for handling forward references, which is not currently tested
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# https://github.com/microsoft/semantic-kernel/issues/6464
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properties = {}
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required = []
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hints = get_type_hints(model, globals(), locals())
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for field_name, field_type in hints.items():
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field_description = None
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if hasattr(model, "model_fields") and field_name in model.model_fields:
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field_info = model.model_fields[field_name]
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if isinstance(field_info.metadata, dict):
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field_description = field_info.metadata.get("description")
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elif isinstance(field_info.metadata, list) and field_info.metadata:
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field_description = field_info.metadata[0]
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elif hasattr(field_info, "description"):
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field_description = field_info.description
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if not cls._is_optional(field_type):
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required.append(field_name)
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properties[field_name] = cls.build(field_type, field_description)
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schema = {"type": "object", "properties": properties}
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if required:
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schema["required"] = required
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if description:
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schema["description"] = description
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return schema
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@classmethod
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def _is_optional(cls, field_type: Any) -> bool:
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return get_origin(field_type) in {types.UnionType, Union} and type(None) in get_args(field_type)
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@classmethod
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def build_from_type_name(cls, parameter_type: str, description: str | None = None) -> dict[str, Any]:
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"""Builds the JSON schema for a given parameter type name and description.
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Args:
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parameter_type (str): The parameter type name.
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description (str, optional): The description of the parameter. Defaults to None.
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Returns:
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dict[str, Any]: The JSON schema for the parameter type.
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"""
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schema: dict[str, Any] = {}
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if PARSED_ANNOTATION_UNION_DELIMITER in parameter_type:
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# this means it is a Union or | so need to build with "anyOf"
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types = parameter_type.split(PARSED_ANNOTATION_UNION_DELIMITER)
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schemas = [cls.build_from_type_name(t.strip(), description) for t in types]
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schema["anyOf"] = schemas
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else:
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type_name = TYPE_MAPPING.get(parameter_type, "object")
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schema["type"] = type_name
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if description:
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schema["description"] = description
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return schema
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@classmethod
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def get_json_schema(cls, parameter_type: type) -> dict[str, Any]:
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"""Gets JSON schema for a given parameter type.
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Args:
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parameter_type (type): The parameter type.
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Returns:
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dict[str, Any]: The JSON schema for the parameter type.
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"""
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type_name = TYPE_MAPPING.get(parameter_type, "object")
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return {"type": type_name}
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@classmethod
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def handle_complex_type(cls, parameter_type: type, description: str | None = None) -> dict[str, Any]:
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"""Handles building the JSON schema for complex types.
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Args:
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parameter_type (type): The parameter type.
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description (str, optional): The description of the parameter. Defaults to None.
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Returns:
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dict[str, Any]: The JSON schema for the parameter type.
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"""
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origin = get_origin(parameter_type)
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args = get_args(parameter_type)
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schema: dict[str, Any] = {}
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if origin is list or origin is set:
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item_type = args[0]
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schema = {"type": "array", "items": cls.build(item_type)}
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if description:
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schema["description"] = description
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return schema
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if origin is dict:
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_, value_type = args
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additional_properties = cls.build(value_type)
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if additional_properties == {"type": "object"}:
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additional_properties["properties"] = {} # Account for differences in Python 3.10 dict
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schema = {"type": "object", "additionalProperties": additional_properties}
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if description:
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schema["description"] = description
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return schema
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if origin is tuple:
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items = [cls.build(arg) for arg in args]
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schema = {"type": "array", "items": items}
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if description:
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schema["description"] = description
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return schema
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if origin in {Union, types.UnionType}:
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# Handle Optional[T] (Union[T, None]) by making schema nullable
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if len(args) == 2 and type(None) in args:
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non_none_type = args[0] if args[1] is type(None) else args[1]
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schema = cls.build(non_none_type)
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schema["type"] = [schema["type"], "null"]
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if description:
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schema["description"] = description
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return schema
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schemas = [cls.build(arg, description) for arg in args]
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return {"anyOf": schemas}
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schema = cls.get_json_schema(parameter_type)
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if description:
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schema["description"] = description
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return schema
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@classmethod
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def build_enum_schema(cls, enum_type: type, description: str | None = None) -> dict[str, Any]:
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"""Builds the JSON schema for an enum type.
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Args:
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enum_type (type): The enum type.
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description (str, optional): The description of the enum. Defaults to None.
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Returns:
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dict[str, Any]: The JSON schema for the enum type.
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"""
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if not issubclass(enum_type, Enum):
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raise FunctionInvalidParameterConfiguration(f"{enum_type} is not a valid Enum type")
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try:
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enum_values = [item.value for item in enum_type]
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except TypeError as ex:
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raise FunctionInvalidParameterConfiguration(f"Failed to get enum values for {enum_type}") from ex
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schema = {"type": TYPE_MAPPING.get(type(enum_values[0]), "string"), "enum": enum_values}
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if description:
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schema["description"] = description
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return schema
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