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adk-python/tests/unittests/tools/test_set_model_response_tool.py
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# Copyright 2025 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.
"""Tests for SetModelResponseTool."""
from google.adk.agents.invocation_context import InvocationContext
from google.adk.agents.llm_agent import LlmAgent
from google.adk.agents.run_config import RunConfig
from google.adk.sessions.in_memory_session_service import InMemorySessionService
from google.adk.tools.set_model_response_tool import MODEL_JSON_RESPONSE_KEY
from google.adk.tools.set_model_response_tool import SetModelResponseTool
from google.adk.tools.tool_context import ToolContext
from pydantic import BaseModel
from pydantic import Field
from pydantic import ValidationError
import pytest
class PersonSchema(BaseModel):
"""Test schema for structured output."""
name: str = Field(description="A person's name")
age: int = Field(description="A person's age")
city: str = Field(description='The city they live in')
class ComplexSchema(BaseModel):
"""More complex test schema."""
id: int
title: str
tags: list[str] = Field(default_factory=list)
metadata: dict[str, str] = Field(default_factory=dict)
is_active: bool = True
async def _create_invocation_context(agent: LlmAgent) -> InvocationContext:
"""Helper to create InvocationContext for testing."""
session_service = InMemorySessionService()
session = await session_service.create_session(
app_name='test_app', user_id='test_user'
)
return InvocationContext(
invocation_id='test-id',
agent=agent,
session=session,
session_service=session_service,
run_config=RunConfig(),
)
def test_tool_initialization_simple_schema():
"""Test tool initialization with a simple schema."""
tool = SetModelResponseTool(PersonSchema)
assert tool.output_schema == PersonSchema
assert tool.name == 'set_model_response'
assert 'Set your final response' in tool.description
assert tool.func is not None
def test_tool_initialization_complex_schema():
"""Test tool initialization with a complex schema."""
tool = SetModelResponseTool(ComplexSchema)
assert tool.output_schema == ComplexSchema
assert tool.name == 'set_model_response'
assert tool.func is not None
def test_function_signature_generation():
"""Test that function signature is correctly generated from schema."""
tool = SetModelResponseTool(PersonSchema)
import inspect
sig = inspect.signature(tool.func)
# Check that parameters match schema fields
assert 'name' in sig.parameters
assert 'age' in sig.parameters
assert 'city' in sig.parameters
# All parameters should be keyword-only
for param in sig.parameters.values():
assert param.kind == inspect.Parameter.KEYWORD_ONLY
def test_get_declaration():
"""Test that tool declaration is properly generated."""
tool = SetModelResponseTool(PersonSchema)
declaration = tool._get_declaration()
assert declaration is not None
assert declaration.name == 'set_model_response'
assert declaration.description is not None
@pytest.mark.asyncio
async def test_run_async_valid_data():
"""Test tool execution with valid data."""
tool = SetModelResponseTool(PersonSchema)
agent = LlmAgent(name='test_agent', model='gemini-1.5-flash')
invocation_context = await _create_invocation_context(agent)
tool_context = ToolContext(invocation_context)
# Execute with valid data
result = await tool.run_async(
args={'name': 'Alice', 'age': 25, 'city': 'Seattle'},
tool_context=tool_context,
)
# Verify the tool now returns dict directly
assert result is not None
assert result['name'] == 'Alice'
assert result['age'] == 25
assert result['city'] == 'Seattle'
# Verify data is no longer stored in session state (old behavior)
stored_response = invocation_context.session.state.get(
MODEL_JSON_RESPONSE_KEY
)
assert stored_response is None
@pytest.mark.asyncio
async def test_run_async_complex_schema():
"""Test tool execution with complex schema."""
tool = SetModelResponseTool(ComplexSchema)
agent = LlmAgent(name='test_agent', model='gemini-1.5-flash')
invocation_context = await _create_invocation_context(agent)
tool_context = ToolContext(invocation_context)
# Execute with complex data
result = await tool.run_async(
args={
'id': 123,
'title': 'Test Item',
'tags': ['tag1', 'tag2'],
'metadata': {'key': 'value'},
'is_active': False,
},
tool_context=tool_context,
)
# Verify the tool now returns dict directly
assert result is not None
assert result['id'] == 123
assert result['title'] == 'Test Item'
assert result['tags'] == ['tag1', 'tag2']
assert result['metadata'] == {'key': 'value'}
assert result['is_active'] is False
# Verify data is no longer stored in session state (old behavior)
stored_response = invocation_context.session.state.get(
MODEL_JSON_RESPONSE_KEY
)
assert stored_response is None
@pytest.mark.asyncio
async def test_run_async_validation_error():
"""Test tool execution with invalid data raises validation error."""
tool = SetModelResponseTool(PersonSchema)
agent = LlmAgent(name='test_agent', model='gemini-1.5-flash')
invocation_context = await _create_invocation_context(agent)
tool_context = ToolContext(invocation_context)
# Execute with invalid data (wrong type for age)
with pytest.raises(ValidationError):
await tool.run_async(
args={'name': 'Bob', 'age': 'not_a_number', 'city': 'Portland'},
tool_context=tool_context,
)
@pytest.mark.asyncio
async def test_run_async_missing_required_field():
"""Test tool execution with missing required field."""
tool = SetModelResponseTool(PersonSchema)
agent = LlmAgent(name='test_agent', model='gemini-1.5-flash')
invocation_context = await _create_invocation_context(agent)
tool_context = ToolContext(invocation_context)
# Execute with missing required field
with pytest.raises(ValidationError):
await tool.run_async(
args={'name': 'Charlie', 'city': 'Denver'}, # Missing age
tool_context=tool_context,
)
@pytest.mark.asyncio
async def test_session_state_storage_key():
"""Test that response is no longer stored in session state."""
tool = SetModelResponseTool(PersonSchema)
agent = LlmAgent(name='test_agent', model='gemini-1.5-flash')
invocation_context = await _create_invocation_context(agent)
tool_context = ToolContext(invocation_context)
result = await tool.run_async(
args={'name': 'Diana', 'age': 35, 'city': 'Miami'},
tool_context=tool_context,
)
# Verify response is returned directly, not stored in session state
assert result is not None
assert result['name'] == 'Diana'
assert result['age'] == 35
assert result['city'] == 'Miami'
# Verify session state is no longer used
assert MODEL_JSON_RESPONSE_KEY not in invocation_context.session.state
@pytest.mark.asyncio
async def test_multiple_executions_return_latest():
"""Test that multiple executions return latest response independently."""
tool = SetModelResponseTool(PersonSchema)
agent = LlmAgent(name='test_agent', model='gemini-1.5-flash')
invocation_context = await _create_invocation_context(agent)
tool_context = ToolContext(invocation_context)
# First execution
result1 = await tool.run_async(
args={'name': 'First', 'age': 20, 'city': 'City1'},
tool_context=tool_context,
)
# Second execution should return its own response
result2 = await tool.run_async(
args={'name': 'Second', 'age': 30, 'city': 'City2'},
tool_context=tool_context,
)
# Verify each execution returns its own dict
assert result1['name'] == 'First'
assert result1['age'] == 20
assert result1['city'] == 'City1'
assert result2['name'] == 'Second'
assert result2['age'] == 30
assert result2['city'] == 'City2'
# Verify session state is not used
assert MODEL_JSON_RESPONSE_KEY not in invocation_context.session.state
def test_function_return_value_consistency():
"""Test that function return value matches run_async return value."""
tool = SetModelResponseTool(PersonSchema)
# Direct function call
direct_result = tool.func()
# Both should return the same value
assert direct_result == 'Response set successfully.'