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6b241f5ef2
Co-authored-by: Xuan Yang <xygoogle@google.com> PiperOrigin-RevId: 854329254
664 lines
21 KiB
Python
664 lines
21 KiB
Python
# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from enum import Enum
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from google.adk.features import FeatureName
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from google.adk.features._feature_registry import temporary_feature_override
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from google.adk.tools import _automatic_function_calling_util
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from google.adk.tools.tool_context import ToolContext
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from google.adk.utils.variant_utils import GoogleLLMVariant
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from google.genai import types
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# TODO: crewai requires python 3.10 as minimum
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# from crewai_tools import FileReadTool
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from pydantic import BaseModel
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import pytest
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def test_string_input():
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def simple_function(input_str: str) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'STRING'
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def test_int_input():
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def simple_function(input_str: int) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'INTEGER'
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def test_float_input():
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def simple_function(input_str: float) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'NUMBER'
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def test_bool_input():
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def simple_function(input_str: bool) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'BOOLEAN'
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def test_array_input():
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def simple_function(input_str: list[str]) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'ARRAY'
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def test_dict_input():
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def simple_function(input_str: dict[str, str]) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'OBJECT'
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def test_basemodel_input():
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class CustomInput(BaseModel):
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input_str: str
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def simple_function(input: CustomInput) -> str:
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return {'result': input}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input'].type == 'OBJECT'
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assert (
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function_decl.parameters.properties['input'].properties['input_str'].type
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== 'STRING'
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)
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def test_toolcontext_ignored():
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def simple_function(input_str: str, tool_context: ToolContext) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function, ignore_params=['tool_context']
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'STRING'
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assert 'tool_context' not in function_decl.parameters.properties
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def test_basemodel():
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class SimpleFunction(BaseModel):
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input_str: str
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custom_input: int
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=SimpleFunction, ignore_params=['custom_input']
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)
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assert function_decl.name == 'SimpleFunction'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'STRING'
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assert 'custom_input' not in function_decl.parameters.properties
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def test_nested_basemodel_input():
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class ChildInput(BaseModel):
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input_str: str
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class CustomInput(BaseModel):
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child: ChildInput
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def simple_function(input: CustomInput) -> str:
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return {'result': input}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input'].type == 'OBJECT'
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assert (
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function_decl.parameters.properties['input'].properties['child'].type
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== 'OBJECT'
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)
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assert (
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function_decl.parameters.properties['input']
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.properties['child']
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.properties['input_str']
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.type
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== 'STRING'
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)
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def test_basemodel_with_nested_basemodel():
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class ChildInput(BaseModel):
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input_str: str
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class CustomInput(BaseModel):
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child: ChildInput
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=CustomInput, ignore_params=['custom_input']
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)
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assert function_decl.name == 'CustomInput'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['child'].type == 'OBJECT'
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assert (
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function_decl.parameters.properties['child'].properties['input_str'].type
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== 'STRING'
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)
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assert 'custom_input' not in function_decl.parameters.properties
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def test_list():
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def simple_function(
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input_str: list[str], input_dir: list[dict[str, str]]
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) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'ARRAY'
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assert function_decl.parameters.properties['input_str'].items.type == 'STRING'
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assert function_decl.parameters.properties['input_dir'].type == 'ARRAY'
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assert function_decl.parameters.properties['input_dir'].items.type == 'OBJECT'
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def test_enums():
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class InputEnum(Enum):
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AGENT = 'agent'
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TOOL = 'tool'
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def simple_function(input: InputEnum = InputEnum.AGENT):
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return input.value
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input'].type == 'STRING'
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assert function_decl.parameters.properties['input'].default == 'agent'
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assert function_decl.parameters.properties['input'].enum == ['agent', 'tool']
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def simple_function_with_wrong_enum(input: InputEnum = 'WRONG_ENUM'):
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return input.value
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with pytest.raises(ValueError):
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_automatic_function_calling_util.build_function_declaration(
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func=simple_function_with_wrong_enum
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)
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def test_basemodel_list():
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class ChildInput(BaseModel):
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input_str: str
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class CustomInput(BaseModel):
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child: ChildInput
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def simple_function(input_str: list[CustomInput]) -> str:
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return {'result': input_str}
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=simple_function
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)
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assert function_decl.name == 'simple_function'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['input_str'].type == 'ARRAY'
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assert function_decl.parameters.properties['input_str'].items.type == 'OBJECT'
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assert (
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function_decl.parameters.properties['input_str']
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.items.properties['child']
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.type
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== 'OBJECT'
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)
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assert (
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function_decl.parameters.properties['input_str']
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.items.properties['child']
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.properties['input_str']
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.type
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== 'STRING'
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)
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# TODO: comment out this test for now as crewai requires python 3.10 as minimum
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# def test_crewai_tool():
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# docs_tool = CrewaiTool(
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# name='directory_read_tool',
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# description='use this to find files for you.',
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# tool=FileReadTool(),
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# )
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# function_decl = docs_tool.get_declaration()
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# assert function_decl.name == 'directory_read_tool'
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# assert function_decl.parameters.type == 'OBJECT'
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# assert function_decl.parameters.properties['file_path'].type == 'STRING'
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def test_function_no_return_annotation_gemini_api():
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"""Test function with no return annotation using GEMINI_API variant."""
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def function_no_return(param: str):
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"""A function with no return annotation."""
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return None
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=function_no_return, variant=GoogleLLMVariant.GEMINI_API
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)
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assert function_decl.name == 'function_no_return'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['param'].type == 'STRING'
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# GEMINI_API should not have response schema
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assert function_decl.response is None
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def test_function_no_return_annotation_vertex_ai():
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"""Test function with no return annotation using VERTEX_AI variant."""
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def function_no_return(param: str):
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"""A function with no return annotation."""
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return None
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=function_no_return, variant=GoogleLLMVariant.VERTEX_AI
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)
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assert function_decl.name == 'function_no_return'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['param'].type == 'STRING'
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# VERTEX_AI should have response schema for functions with no return annotation
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# Changed: Now uses Any type instead of NULL for no return annotation
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assert function_decl.response is not None
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assert function_decl.response.type is None # Any type maps to None in schema
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def test_function_explicit_none_return_vertex_ai():
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"""Test function with explicit None return annotation using VERTEX_AI variant."""
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def function_none_return(param: str) -> None:
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"""A function that explicitly returns None."""
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pass
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=function_none_return, variant=GoogleLLMVariant.VERTEX_AI
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)
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assert function_decl.name == 'function_none_return'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['param'].type == 'STRING'
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# VERTEX_AI should have response schema for explicit None return
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assert function_decl.response is not None
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assert function_decl.response.type == types.Type.NULL
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def test_function_explicit_none_return_gemini_api():
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"""Test function with explicit None return annotation using GEMINI_API variant."""
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def function_none_return(param: str) -> None:
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"""A function that explicitly returns None."""
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pass
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=function_none_return, variant=GoogleLLMVariant.GEMINI_API
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)
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assert function_decl.name == 'function_none_return'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['param'].type == 'STRING'
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# GEMINI_API should not have response schema
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assert function_decl.response is None
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def test_function_regular_return_type_vertex_ai():
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"""Test function with regular return type using VERTEX_AI variant."""
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def function_string_return(param: str) -> str:
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"""A function that returns a string."""
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return param
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=function_string_return, variant=GoogleLLMVariant.VERTEX_AI
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)
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assert function_decl.name == 'function_string_return'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['param'].type == 'STRING'
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# VERTEX_AI should have response schema for string return
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assert function_decl.response is not None
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assert function_decl.response.type == types.Type.STRING
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def test_function_with_no_response_annotations():
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"""Test a function that has no response annotations."""
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def transfer_to_agent(agent_name: str, tool_context: ToolContext):
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"""Transfer the question to another agent."""
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tool_context.actions.transfer_to_agent = agent_name
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function_decl = _automatic_function_calling_util.build_function_declaration(
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func=transfer_to_agent,
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ignore_params=['tool_context'],
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variant=GoogleLLMVariant.VERTEX_AI,
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)
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assert function_decl.name == 'transfer_to_agent'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['agent_name'].type == 'STRING'
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assert 'tool_context' not in function_decl.parameters.properties
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# This function has no return annotation, so it gets Any type instead of NULL
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# Changed: Now uses Any type instead of NULL for no return annotation
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assert function_decl.response is not None
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assert function_decl.response.type is None # Any type maps to None in schema
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def test_transfer_to_agent_tool_with_enum_constraint():
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"""Test TransferToAgentTool adds enum constraint to agent_name."""
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from google.adk.tools.transfer_to_agent_tool import TransferToAgentTool
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agent_names = ['agent_a', 'agent_b', 'agent_c']
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tool = TransferToAgentTool(agent_names=agent_names)
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function_decl = tool._get_declaration()
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assert function_decl.name == 'transfer_to_agent'
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assert function_decl.parameters.type == 'OBJECT'
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assert function_decl.parameters.properties['agent_name'].type == 'STRING'
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assert function_decl.parameters.properties['agent_name'].enum == agent_names
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assert 'tool_context' not in function_decl.parameters.properties
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class TestJsonSchemaFeatureFlagEnabled:
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"""Tests for build_function_declaration when JSON_SCHEMA_FOR_FUNC_DECL is enabled."""
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@pytest.fixture(autouse=True)
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def enable_feature_flag(self):
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"""Enable the JSON_SCHEMA_FOR_FUNC_DECL feature flag for all tests."""
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with temporary_feature_override(
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FeatureName.JSON_SCHEMA_FOR_FUNC_DECL, True
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):
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yield
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def test_basic_string_parameter(self):
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"""Test basic string parameter with feature flag enabled."""
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def greet(name: str) -> str:
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"""Greet someone."""
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return f'Hello, {name}!'
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decl = _automatic_function_calling_util.build_function_declaration(greet)
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assert decl.name == 'greet'
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assert decl.description == 'Greet someone.'
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assert decl.parameters_json_schema == {
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'properties': {'name': {'title': 'Name', 'type': 'string'}},
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'required': ['name'],
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'title': 'greetParams',
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'type': 'object',
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}
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def test_multiple_parameter_types(self):
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"""Test multiple parameter types with feature flag enabled."""
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def create_user(name: str, age: int, active: bool) -> str:
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"""Create a new user."""
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return f'Created {name}'
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decl = _automatic_function_calling_util.build_function_declaration(
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create_user
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)
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schema = decl.parameters_json_schema
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assert schema['properties'] == {
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'name': {'title': 'Name', 'type': 'string'},
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'age': {'title': 'Age', 'type': 'integer'},
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'active': {'title': 'Active', 'type': 'boolean'},
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}
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assert set(schema['required']) == {'name', 'age', 'active'}
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def test_list_parameter(self):
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"""Test list parameter with feature flag enabled."""
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def sum_numbers(numbers: list[int]) -> int:
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"""Sum a list of numbers."""
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return sum(numbers)
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decl = _automatic_function_calling_util.build_function_declaration(
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sum_numbers
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)
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schema = decl.parameters_json_schema
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assert schema['properties']['numbers'] == {
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'items': {'type': 'integer'},
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'title': 'Numbers',
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'type': 'array',
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}
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def test_dict_parameter(self):
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"""Test dict parameter with feature flag enabled."""
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def process_data(data: dict[str, str]) -> str:
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"""Process a dictionary."""
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return str(data)
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decl = _automatic_function_calling_util.build_function_declaration(
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process_data
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)
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schema = decl.parameters_json_schema
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assert schema['properties']['data'] == {
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'additionalProperties': {'type': 'string'},
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'title': 'Data',
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'type': 'object',
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}
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def test_optional_parameter(self):
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"""Test optional parameter with feature flag enabled."""
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def search(query: str, limit: int | None = None) -> str:
|
|
"""Search for something."""
|
|
return query
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(search)
|
|
|
|
schema = decl.parameters_json_schema
|
|
assert schema['required'] == ['query']
|
|
assert 'query' in schema['properties']
|
|
assert 'limit' in schema['properties']
|
|
|
|
def test_enum_parameter(self):
|
|
"""Test enum parameter with feature flag enabled."""
|
|
|
|
class Color(Enum):
|
|
RED = 'red'
|
|
GREEN = 'green'
|
|
BLUE = 'blue'
|
|
|
|
def set_color(color: Color) -> str:
|
|
"""Set the color."""
|
|
return color.value
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(
|
|
set_color
|
|
)
|
|
|
|
schema = decl.parameters_json_schema
|
|
assert schema['properties']['color'] == {
|
|
'$ref': '#/$defs/Color',
|
|
}
|
|
assert schema['$defs']['Color'] == {
|
|
'enum': ['red', 'green', 'blue'],
|
|
'title': 'Color',
|
|
'type': 'string',
|
|
}
|
|
|
|
def test_tool_context_ignored(self):
|
|
"""Test that tool_context is ignored."""
|
|
|
|
def my_tool(query: str, tool_context: ToolContext) -> str:
|
|
"""A tool that uses context."""
|
|
return query
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(
|
|
my_tool, ignore_params=['tool_context']
|
|
)
|
|
|
|
schema = decl.parameters_json_schema
|
|
assert set(schema['properties'].keys()) == {'query'}
|
|
assert 'tool_context' not in schema['properties']
|
|
|
|
def test_gemini_api_no_response_schema(self):
|
|
"""Test that GEMINI_API variant does not include response schema."""
|
|
|
|
def get_data() -> dict[str, int]:
|
|
"""Get some data."""
|
|
return {'count': 42}
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(
|
|
get_data, variant=GoogleLLMVariant.GEMINI_API
|
|
)
|
|
|
|
# GEMINI_API should not have response_json_schema due to bug b/421991354
|
|
assert decl.response_json_schema is None
|
|
|
|
@pytest.mark.parametrize(
|
|
'variant, expect_response_schema',
|
|
[
|
|
(GoogleLLMVariant.GEMINI_API, False),
|
|
(GoogleLLMVariant.VERTEX_AI, True),
|
|
],
|
|
)
|
|
def test_response_schema_by_variant(self, variant, expect_response_schema):
|
|
"""Test response schema generation based on the LLM variant."""
|
|
|
|
def get_data() -> dict[str, int]:
|
|
"""Get some data."""
|
|
return {'count': 42}
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(
|
|
get_data, variant=variant
|
|
)
|
|
|
|
assert (decl.response_json_schema is not None) == expect_response_schema
|
|
|
|
def test_pydantic_model_parameter(self):
|
|
"""Test Pydantic model parameter with feature flag enabled."""
|
|
|
|
class Address(BaseModel):
|
|
street: str
|
|
city: str
|
|
|
|
def save_address(address: Address) -> str:
|
|
"""Save an address."""
|
|
return f'Saved address in {address.city}'
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(
|
|
save_address
|
|
)
|
|
|
|
assert decl.parameters_json_schema is not None
|
|
assert 'address' in decl.parameters_json_schema['properties']
|
|
|
|
def test_no_parameters(self):
|
|
"""Test function with no parameters."""
|
|
|
|
def get_time() -> str:
|
|
"""Get current time."""
|
|
return '12:00'
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(get_time)
|
|
|
|
assert decl.name == 'get_time'
|
|
assert decl.parameters_json_schema is None
|
|
|
|
def test_docstring_preserved(self):
|
|
"""Test that docstring is preserved as description."""
|
|
|
|
def well_documented(x: int) -> int:
|
|
"""This is a well-documented function.
|
|
|
|
It does something useful.
|
|
"""
|
|
return x
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(
|
|
well_documented
|
|
)
|
|
|
|
assert 'well-documented function' in decl.description
|
|
assert 'something useful' in decl.description
|
|
|
|
def test_default_values(self):
|
|
"""Test parameters with default values."""
|
|
|
|
def greet(name: str = 'World') -> str:
|
|
"""Greet someone."""
|
|
return f'Hello, {name}!'
|
|
|
|
decl = _automatic_function_calling_util.build_function_declaration(greet)
|
|
|
|
schema = decl.parameters_json_schema
|
|
assert schema['properties']['name']['default'] == 'World'
|
|
assert 'name' not in schema.get('required', [])
|