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feat: GenAI - Support generating JSON Schema from Python function
The `generate_json_schema_from_function` function generates JSON Schema from a Python function so that it can be used for constructing `Schema` or `FunctionDeclaration` objects (after tweaking the schema with the `adapt_json_schema_to_google_tool_schema` function). PiperOrigin-RevId: 617074433
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| # Copyright 2024 Google LLC | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
| # | ||
| """Shared utilities for working with function schemas.""" | ||
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| import inspect | ||
| import typing | ||
| from typing import Any, Callable, Dict | ||
| import warnings | ||
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| from google.cloud.aiplatform_v1beta1 import types as aiplatform_types | ||
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| Struct = Dict[str, Any] | ||
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| def _generate_json_schema_from_function_using_pydantic( | ||
| func: Callable, | ||
| ) -> Struct: | ||
| """Generates JSON Schema for a callable object. | ||
| The `func` function needs to follow specific rules. | ||
| All parameters must be names explicitly (`*args` and `**kwargs` are not supported). | ||
| Args: | ||
| func: Function for which to generate schema | ||
| Returns: | ||
| The JSON Schema for the function as a dict. | ||
| """ | ||
| import pydantic | ||
|
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||
| try: | ||
| import docstring_parser # pylint: disable=g-import-not-at-top | ||
| except ImportError: | ||
| warnings.warn("Unable to import docstring_parser") | ||
| docstring_parser = None | ||
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| function_description = func.__doc__ | ||
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| # Parse parameter descriptions from the docstring. | ||
| # Also parse the function descripton in a better way. | ||
| parameter_descriptions = {} | ||
| if docstring_parser: | ||
| parsed_docstring = docstring_parser.parse(func.__doc__) | ||
| function_description = ( | ||
| parsed_docstring.long_description or parsed_docstring.short_description | ||
| ) | ||
| for meta in parsed_docstring.meta: | ||
| if isinstance(meta, docstring_parser.DocstringParam): | ||
| parameter_descriptions[meta.arg_name] = meta.description | ||
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| defaults = dict(inspect.signature(func).parameters) | ||
| fields_dict = { | ||
| name: ( | ||
| # 1. We infer the argument type here: use Any rather than None so | ||
| # it will not try to auto-infer the type based on the default value. | ||
| ( | ||
| param.annotation if param.annotation != inspect.Parameter.empty | ||
| else Any | ||
| ), | ||
| pydantic.Field( | ||
| # 2. We do not support default values for now. | ||
| default=( | ||
| param.default if param.default != inspect.Parameter.empty | ||
| # ! Need to use pydantic.Undefined instead of None | ||
| else pydantic.fields.Undefined | ||
| ), | ||
| # 3. We support user-provided descriptions. | ||
| description=parameter_descriptions.get(name, None), | ||
| ) | ||
| ) | ||
| for name, param in defaults.items() | ||
| # We do not support *args or **kwargs | ||
| if param.kind in ( | ||
| inspect.Parameter.POSITIONAL_OR_KEYWORD, | ||
| inspect.Parameter.KEYWORD_ONLY, | ||
| inspect.Parameter.POSITIONAL_ONLY, | ||
| ) | ||
| } | ||
| function_schema = pydantic.create_model(func.__name__, **fields_dict).schema() | ||
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| function_schema["title"] = func.__name__ | ||
| function_schema["description"] = function_description | ||
| # Postprocessing | ||
| for name, property_schema in function_schema.get("properties", {}).items(): | ||
| annotation = defaults[name].annotation | ||
| # 5. Nullable fields: | ||
| # * https://github.com/pydantic/pydantic/issues/1270 | ||
| # * https://stackoverflow.com/a/58841311 | ||
| # * https://github.com/pydantic/pydantic/discussions/4872 | ||
| if ( | ||
| typing.get_origin(annotation) is typing.Union | ||
| and type(None) in typing.get_args(annotation) | ||
| ): | ||
| # for "typing.Optional" arguments, function_arg might be a | ||
| # dictionary like | ||
| # | ||
| # {'anyOf': [{'type': 'integer'}, {'type': 'null'}] | ||
| for schema in property_schema.pop("anyOf", []): | ||
| schema_type = schema.get("type") | ||
| if schema_type and schema_type != "null": | ||
| property_schema["type"] = schema_type | ||
| break | ||
| property_schema["nullable"] = True | ||
| # 6. Annotate required fields. | ||
| function_schema["required"] = [ | ||
| k for k in defaults if ( | ||
| defaults[k].default == inspect.Parameter.empty | ||
| and defaults[k].kind in ( | ||
| inspect.Parameter.POSITIONAL_OR_KEYWORD, | ||
| inspect.Parameter.KEYWORD_ONLY, | ||
| inspect.Parameter.POSITIONAL_ONLY, | ||
| ) | ||
| ) | ||
| ] | ||
| return function_schema | ||
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| def adapt_json_schema_to_google_tool_schema(schema: Struct) -> Struct: | ||
| """Adapts JSON schema to Google tool schema.""" | ||
| fixed_schema = dict(schema) | ||
| # `$schema` is one of the basic/most common fields of the real JSON Schema. | ||
| # But Google's Schema proto does not support it. | ||
| # Common attributes that we remove: | ||
| # $schema, additionalProperties | ||
| for key in list(fixed_schema): | ||
| if not hasattr(aiplatform_types.Schema, key) and not hasattr( | ||
| aiplatform_types.Schema, key + "_" | ||
| ): | ||
| fixed_schema.pop(key, None) | ||
| property_schemas = fixed_schema.get("properties") | ||
| if property_schemas: | ||
| for k, v in property_schemas.items(): | ||
| property_schemas[k] = adapt_json_schema_to_google_tool_schema(v) | ||
| return fixed_schema | ||
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| generate_json_schema_from_function = _generate_json_schema_from_function_using_pydantic |