def create_wrapped_function(
        self,
        *,
        primary_func: Callable[..., Any],
        functions: list[Callable[..., Any]],
        catalog: str,
        schema: str,
        replace=False,
        dependencies: Optional[list[str]] = None,
        environment_version: str = "None",
    ) -> "FunctionInfo":
        """
        Create a wrapped function comprised of a `primary_func` function and in-lined wrapped `functions` within the `primary_func` body.

        Note: `databricks-connect` is required to use this function, make sure its version is 15.1.0 or above to use
            serverless compute.

        Args:
            primary_func: The primary function to be wrapped.
            functions: A list of functions to be wrapped inline within the body of `primary_func`.
            catalog: The catalog name.
            schema: The schema name.
            replace: Whether to replace the function if it already exists. Defaults to False.
            dependencies: A list of external dependencies required by the function. Defaults to an empty list. Note that the
                `dependencies` parameter is not supported in all runtimes. Ensure that you are using a runtime that supports environment
                and dependency declaration prior to creating a function that defines dependencies.
                Standard PyPI package declarations are supported (i.e., `requests>=2.25.1`).
            environment_version: The version of the environment in which the function will be executed. Defaults to 'None'. Note
                that the `environment_version` parameter is not supported in all runtimes. Ensure that you are using a runtime that
                supports environment and dependency declaration prior to creating a function that declares an environment verison.

        Returns:
            FunctionInfo: Metadata about the created function, including its name and signature.
        """
        if not callable(primary_func):
            raise ValueError("The provided primary function is not callable.")

        sql_function_body = generate_wrapped_sql_function_body(
            primary_func=primary_func,
            functions=functions,
            catalog=catalog,
            schema=schema,
            replace=replace,
            dependencies=dependencies,
            environment_version=environment_version,
        )

        return self.create_function(sql_function_body=sql_function_body)

        Create a wrapped function comprised of a `primary_func` function and in-lined wrapped `functions` within the `primary_func` body.

        Note: `databricks-connect` is required to use this function, make sure its version is 15.1.0 or above to use
            serverless compute.

        Args:
            primary_func: The primary function to be wrapped.
            functions: A list of functions to be wrapped inline within the body of `primary_func`.
            catalog: The catalog name.
            schema: The schema name.
            replace: Whether to replace the function if it already exists. Defaults to False.
            dependencies: A list of external dependencies required by the function. Defaults to an empty list. Note that the
                `dependencies` parameter is not supported in all runtimes. Ensure that you are using a runtime that supports environment
                and dependency declaration prior to creating a function that defines dependencies.
                Standard PyPI package declarations are supported (i.e., `requests>=2.25.1`).
            environment_version: The version of the environment in which the function will be executed. Defaults to 'None'. Note
                that the `environment_version` parameter is not supported in all runtimes. Ensure that you are using a runtime that
                supports environment and dependency declaration prior to creating a function that declares an environment verison.

        Returns:
            FunctionInfo: Metadata about the created function, including its name and signature.
        
ai/core/src/unitycatalog/ai/core/databricks.py