mirror of
https://github.com/encounter/adk-python.git
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Xiang (Sean) ZhouandCopybara-Service
a5d6f1e52e
This is to support model path like : projects/265104255505/locations/us-central1/publishers/google/models/gemini-2.0-flash-001" PiperOrigin-RevId: 783413351
321 lines
12 KiB
Python
321 lines
12 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 google.adk.agents.invocation_context import InvocationContext
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from google.adk.agents.sequential_agent import SequentialAgent
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from google.adk.models.llm_request import LlmRequest
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from google.adk.sessions.in_memory_session_service import InMemorySessionService
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from google.adk.tools.tool_context import ToolContext
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from google.adk.tools.vertex_ai_search_tool import VertexAiSearchTool
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from google.adk.utils.model_name_utils import extract_model_name
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from google.adk.utils.model_name_utils import is_gemini_1_model
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from google.adk.utils.model_name_utils import is_gemini_model
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from google.genai import types
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import pytest
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async def _create_tool_context() -> ToolContext:
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session_service = InMemorySessionService()
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session = await session_service.create_session(
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app_name='test_app', user_id='test_user'
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)
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agent = SequentialAgent(name='test_agent')
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invocation_context = InvocationContext(
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invocation_id='invocation_id',
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agent=agent,
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session=session,
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session_service=session_service,
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)
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return ToolContext(invocation_context=invocation_context)
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class TestVertexAiSearchToolHelperFunctions:
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"""Test the helper functions for model name extraction and validation."""
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def test_extract_model_name_simple_model(self):
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"""Test extraction of simple model names."""
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assert extract_model_name('gemini-2.5-pro') == 'gemini-2.5-pro'
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assert extract_model_name('gemini-1.5-flash') == 'gemini-1.5-flash'
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assert extract_model_name('gemini-1.0-pro') == 'gemini-1.0-pro'
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assert extract_model_name('claude-3-sonnet') == 'claude-3-sonnet'
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def test_extract_model_name_path_based_model(self):
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"""Test extraction of path-based model names."""
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path_model = 'projects/265104255505/locations/us-central1/publishers/google/models/gemini-2.0-flash-001'
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assert extract_model_name(path_model) == 'gemini-2.0-flash-001'
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path_model_2 = 'projects/12345/locations/us-east1/publishers/google/models/gemini-1.5-pro-preview'
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assert extract_model_name(path_model_2) == 'gemini-1.5-pro-preview'
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def test_extract_model_name_invalid_path(self):
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"""Test that invalid path formats return the original string."""
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invalid_path = 'projects/invalid/path/format'
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assert extract_model_name(invalid_path) == invalid_path
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def test_is_gemini_model_simple_names(self):
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"""Test Gemini model detection with simple model names."""
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assert is_gemini_model('gemini-2.5-pro') is True
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assert is_gemini_model('gemini-1.5-flash') is True
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assert is_gemini_model('gemini-1.0-pro') is True
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assert is_gemini_model('claude-3-sonnet') is False
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assert is_gemini_model('gpt-4') is False
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assert is_gemini_model('gemini') is False # Must have dash after gemini
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def test_is_gemini_model_path_based_names(self):
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"""Test Gemini model detection with path-based model names."""
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gemini_path = 'projects/265104255505/locations/us-central1/publishers/google/models/gemini-2.0-flash-001'
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assert is_gemini_model(gemini_path) is True
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non_gemini_path = 'projects/265104255505/locations/us-central1/publishers/google/models/claude-3-sonnet'
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assert is_gemini_model(non_gemini_path) is False
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def test_is_gemini_1_model_simple_names(self):
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"""Test Gemini 1.x model detection with simple model names."""
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assert is_gemini_1_model('gemini-1.5-flash') is True
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assert is_gemini_1_model('gemini-1.0-pro') is True
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assert is_gemini_1_model('gemini-1.5-pro-preview') is True
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assert is_gemini_1_model('gemini-2.0-flash') is False
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assert is_gemini_1_model('gemini-2.5-pro') is False
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assert is_gemini_1_model('gemini-10.0-pro') is False # Only 1.x versions
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assert is_gemini_1_model('claude-3-sonnet') is False
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def test_is_gemini_1_model_path_based_names(self):
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"""Test Gemini 1.x model detection with path-based model names."""
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gemini_1_path = 'projects/265104255505/locations/us-central1/publishers/google/models/gemini-1.5-flash-001'
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assert is_gemini_1_model(gemini_1_path) is True
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gemini_2_path = 'projects/265104255505/locations/us-central1/publishers/google/models/gemini-2.0-flash-001'
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assert is_gemini_1_model(gemini_2_path) is False
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def test_edge_cases(self):
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"""Test edge cases for model name validation."""
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# Test with empty string
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assert is_gemini_model('') is False
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assert is_gemini_1_model('') is False
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# Test with model names containing gemini but not starting with it
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assert is_gemini_model('my-gemini-model') is False
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assert is_gemini_1_model('my-gemini-1.5-model') is False
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# Test with model names that have gemini in the middle of the path
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tricky_path = 'projects/265104255505/locations/us-central1/publishers/gemini/models/claude-3-sonnet'
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assert is_gemini_model(tricky_path) is False
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class TestVertexAiSearchTool:
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"""Test the VertexAiSearchTool class."""
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def test_init_with_data_store_id(self):
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"""Test initialization with data store ID."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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assert tool.data_store_id == 'test_data_store'
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assert tool.search_engine_id is None
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def test_init_with_search_engine_id(self):
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"""Test initialization with search engine ID."""
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tool = VertexAiSearchTool(search_engine_id='test_search_engine')
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assert tool.search_engine_id == 'test_search_engine'
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assert tool.data_store_id is None
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def test_init_with_neither_raises_error(self):
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"""Test that initialization without either ID raises ValueError."""
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with pytest.raises(
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ValueError,
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match='Either data_store_id or search_engine_id must be specified',
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):
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VertexAiSearchTool()
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def test_init_with_both_raises_error(self):
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"""Test that initialization with both IDs raises ValueError."""
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with pytest.raises(
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ValueError,
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match='Either data_store_id or search_engine_id must be specified',
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):
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VertexAiSearchTool(
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data_store_id='test_data_store', search_engine_id='test_search_engine'
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)
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@pytest.mark.asyncio
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async def test_process_llm_request_with_simple_gemini_model(self):
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"""Test processing LLM request with simple Gemini model name."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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tool_context = await _create_tool_context()
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llm_request = LlmRequest(
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model='gemini-2.5-pro', config=types.GenerateContentConfig()
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)
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await tool.process_llm_request(
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tool_context=tool_context, llm_request=llm_request
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)
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assert llm_request.config.tools is not None
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assert len(llm_request.config.tools) == 1
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assert llm_request.config.tools[0].retrieval is not None
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assert llm_request.config.tools[0].retrieval.vertex_ai_search is not None
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@pytest.mark.asyncio
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async def test_process_llm_request_with_path_based_gemini_model(self):
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"""Test processing LLM request with path-based Gemini model name."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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tool_context = await _create_tool_context()
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llm_request = LlmRequest(
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model='projects/265104255505/locations/us-central1/publishers/google/models/gemini-2.0-flash-001',
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config=types.GenerateContentConfig(),
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)
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await tool.process_llm_request(
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tool_context=tool_context, llm_request=llm_request
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)
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assert llm_request.config.tools is not None
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assert len(llm_request.config.tools) == 1
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assert llm_request.config.tools[0].retrieval is not None
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assert llm_request.config.tools[0].retrieval.vertex_ai_search is not None
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@pytest.mark.asyncio
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async def test_process_llm_request_with_gemini_1_and_other_tools_raises_error(
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self,
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):
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"""Test that Gemini 1.x with other tools raises ValueError."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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tool_context = await _create_tool_context()
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existing_tool = types.Tool(
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function_declarations=[
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types.FunctionDeclaration(name='test_function', description='test')
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]
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)
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llm_request = LlmRequest(
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model='gemini-1.5-flash',
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config=types.GenerateContentConfig(tools=[existing_tool]),
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)
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with pytest.raises(
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ValueError,
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match=(
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'Vertex AI search tool can not be used with other tools in'
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' Gemini 1.x'
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),
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):
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await tool.process_llm_request(
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tool_context=tool_context, llm_request=llm_request
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)
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@pytest.mark.asyncio
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async def test_process_llm_request_with_path_based_gemini_1_and_other_tools_raises_error(
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self,
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):
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"""Test that path-based Gemini 1.x with other tools raises ValueError."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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tool_context = await _create_tool_context()
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existing_tool = types.Tool(
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function_declarations=[
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types.FunctionDeclaration(name='test_function', description='test')
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]
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)
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llm_request = LlmRequest(
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model='projects/265104255505/locations/us-central1/publishers/google/models/gemini-1.5-pro-preview',
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config=types.GenerateContentConfig(tools=[existing_tool]),
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)
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with pytest.raises(
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ValueError,
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match=(
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'Vertex AI search tool can not be used with other tools in'
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' Gemini 1.x'
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),
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):
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await tool.process_llm_request(
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tool_context=tool_context, llm_request=llm_request
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)
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@pytest.mark.asyncio
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async def test_process_llm_request_with_non_gemini_model_raises_error(self):
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"""Test that non-Gemini model raises ValueError."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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tool_context = await _create_tool_context()
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llm_request = LlmRequest(
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model='claude-3-sonnet', config=types.GenerateContentConfig()
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)
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with pytest.raises(
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ValueError,
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match=(
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'Vertex AI search tool is not supported for model claude-3-sonnet'
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),
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):
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await tool.process_llm_request(
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tool_context=tool_context, llm_request=llm_request
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)
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@pytest.mark.asyncio
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async def test_process_llm_request_with_path_based_non_gemini_model_raises_error(
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self,
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):
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"""Test that path-based non-Gemini model raises ValueError."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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tool_context = await _create_tool_context()
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non_gemini_path = 'projects/265104255505/locations/us-central1/publishers/google/models/claude-3-sonnet'
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llm_request = LlmRequest(
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model=non_gemini_path, config=types.GenerateContentConfig()
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)
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with pytest.raises(
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ValueError,
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match=(
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'Vertex AI search tool is not supported for model'
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f' {non_gemini_path}'
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),
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):
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await tool.process_llm_request(
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tool_context=tool_context, llm_request=llm_request
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)
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@pytest.mark.asyncio
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async def test_process_llm_request_with_gemini_2_and_other_tools_succeeds(
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self,
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):
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"""Test that Gemini 2.x with other tools succeeds."""
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tool = VertexAiSearchTool(data_store_id='test_data_store')
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tool_context = await _create_tool_context()
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existing_tool = types.Tool(
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function_declarations=[
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types.FunctionDeclaration(name='test_function', description='test')
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]
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)
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llm_request = LlmRequest(
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model='gemini-2.5-pro',
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config=types.GenerateContentConfig(tools=[existing_tool]),
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)
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await tool.process_llm_request(
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tool_context=tool_context, llm_request=llm_request
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)
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# Should have both the existing tool and the new vertex AI search tool
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assert llm_request.config.tools is not None
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assert len(llm_request.config.tools) == 2
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assert llm_request.config.tools[0] == existing_tool
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assert llm_request.config.tools[1].retrieval is not None
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assert llm_request.config.tools[1].retrieval.vertex_ai_search is not None
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