# Copyright 2026 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. from __future__ import annotations from typing import Any from unittest.mock import Mock from google.adk.agents.base_agent import BaseAgent from google.adk.agents.callback_context import CallbackContext from google.adk.models.llm_request import LlmRequest from google.adk.plugins.multimodal_tool_results_plugin import MultimodalToolResultsPlugin from google.adk.plugins.multimodal_tool_results_plugin import PARTS_RETURNED_BY_TOOLS_ID from google.adk.tools.base_tool import BaseTool from google.adk.tools.tool_context import ToolContext from google.genai import types import pytest from .. import testing_utils @pytest.fixture def plugin() -> MultimodalToolResultsPlugin: """Create a default plugin instance for testing.""" return MultimodalToolResultsPlugin() @pytest.fixture def mock_tool() -> MockTool: """Create a mock tool for testing.""" return Mock(spec=BaseTool) @pytest.fixture async def tool_context() -> ToolContext: """Create a mock tool context.""" return ToolContext( invocation_context=await testing_utils.create_invocation_context( agent=Mock(spec=BaseAgent) ) ) @pytest.mark.asyncio async def test_tool_returning_parts_are_added_to_llm_request( plugin: MultimodalToolResultsPlugin, mock_tool: MockTool, tool_context: ToolContext, ): """Test that parts returned by a tool are present in the llm_request later.""" parts = [types.Part(text="part1"), types.Part(text="part2")] result = await plugin.after_tool_callback( tool=mock_tool, tool_args={}, tool_context=tool_context, result=parts, ) assert result == None assert PARTS_RETURNED_BY_TOOLS_ID in tool_context.state assert tool_context.state[PARTS_RETURNED_BY_TOOLS_ID] == parts callback_context = Mock(spec=CallbackContext) callback_context.state = tool_context.state llm_request = LlmRequest(contents=[types.Content(parts=[])]) await plugin.before_model_callback( callback_context=callback_context, llm_request=llm_request ) assert llm_request.contents[-1].parts == parts @pytest.mark.asyncio async def test_tool_returning_non_list_of_parts_is_unchanged( plugin: MultimodalToolResultsPlugin, mock_tool: MockTool, tool_context: ToolContext, ): """Test where tool returning non list of parts, has this result unchanged.""" original_result = {"some": "data"} result = await plugin.after_tool_callback( tool=mock_tool, tool_args={}, tool_context=tool_context, result=original_result, ) assert result == original_result assert PARTS_RETURNED_BY_TOOLS_ID not in tool_context.state callback_context = Mock(spec=CallbackContext) callback_context.state = tool_context.state llm_request = LlmRequest( contents=[types.Content(parts=[types.Part(text="original")])] ) original_parts = list(llm_request.contents[-1].parts) await plugin.before_model_callback( callback_context=callback_context, llm_request=llm_request ) assert llm_request.contents[-1].parts == original_parts @pytest.mark.asyncio async def test_multiple_tools_returning_parts_are_accumulated( plugin: ToolReturningGenAiPartsPlugin, mock_tool: MockTool, tool_context: ToolContext, ): """Test that parts from multiple tool calls are accumulated.""" parts1 = [types.Part(text="part1")] parts2 = [types.Part(text="part2")] await plugin.after_tool_callback( tool=mock_tool, tool_args={}, tool_context=tool_context, result=parts1, ) await plugin.after_tool_callback( tool=mock_tool, tool_args={}, tool_context=tool_context, result=parts2, ) assert PARTS_RETURNED_BY_TOOLS_ID in tool_context.state assert tool_context.state[PARTS_RETURNED_BY_TOOLS_ID] == parts1 + parts2 callback_context = Mock(spec=CallbackContext) callback_context.state = tool_context.state llm_request = LlmRequest(contents=[types.Content(parts=[])]) await plugin.before_model_callback( callback_context=callback_context, llm_request=llm_request ) assert llm_request.contents[-1].parts == parts1 + parts2