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chore: import upstream snapshot with attribution
2026-07-13 13:25:13 +08:00

144 lines
5.1 KiB
Python

# 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 google.adk import models
from google.adk.models.anthropic_llm import Claude
from google.adk.models.google_llm import Gemini
from google.adk.models.lite_llm import LiteLlm
import pytest
@pytest.mark.parametrize(
'model_name',
[
'gemini-1.5-pro',
'gemini-1.5-pro-001',
'gemini-1.5-pro-002',
'gemini-2.5-flash',
'projects/123456/locations/us-central1/endpoints/123456', # finetuned vertex gemini endpoint
'projects/123456/locations/us-central1/publishers/google/models/gemini-2.5-flash', # vertex gemini long name
],
)
def test_match_gemini_family(model_name):
"""Test that Gemini models are resolved correctly."""
assert models.LLMRegistry.resolve(model_name) is Gemini
@pytest.mark.parametrize(
'model_name',
[
'claude-3-5-haiku@20241022',
'claude-3-5-sonnet-v2@20241022',
'claude-3-5-sonnet@20240620',
'claude-3-haiku@20240307',
'claude-3-opus@20240229',
'claude-3-sonnet@20240229',
'claude-sonnet-4@20250514',
'claude-opus-4@20250514',
],
)
def test_match_claude_family(model_name):
"""Test that Claude models are resolved correctly."""
assert models.LLMRegistry.resolve(model_name) is Claude
@pytest.mark.parametrize(
'model_name',
[
'openai/gpt-4o',
'openai/gpt-4o-mini',
'groq/llama3-70b-8192',
'groq/mixtral-8x7b-32768',
'anthropic/claude-3-opus-20240229',
'anthropic/claude-3-5-sonnet-20241022',
],
)
def test_match_litellm_family(model_name):
"""Test that LiteLLM models are resolved correctly."""
assert models.LLMRegistry.resolve(model_name) is LiteLlm
def test_non_exist_model():
with pytest.raises(ValueError) as e_info:
models.LLMRegistry.resolve('non-exist-model')
assert 'Model non-exist-model not found.' in str(e_info.value)
def test_helpful_error_for_claude_without_extensions():
"""Test that missing Claude models show helpful install instructions.
Note: This test may pass even when anthropic IS installed, because it
only checks the error message format when a model is not found.
"""
# Use a non-existent Claude model variant to trigger error
with pytest.raises(ValueError) as e_info:
models.LLMRegistry.resolve('claude-nonexistent-model-xyz')
error_msg = str(e_info.value)
# The error should mention anthropic package and installation instructions
# These checks work whether or not anthropic is actually installed
assert 'Model claude-nonexistent-model-xyz not found' in error_msg
assert 'anthropic package' in error_msg
assert 'pip install' in error_msg
def test_helpful_error_for_litellm_without_extensions():
"""Test that missing LiteLLM models show helpful install instructions.
Note: This test may pass even when litellm IS installed, because it
only checks the error message format when a model is not found.
"""
# Use a non-existent provider to trigger error
with pytest.raises(ValueError) as e_info:
models.LLMRegistry.resolve('unknown-provider/gpt-4o')
error_msg = str(e_info.value)
# The error should mention litellm package for provider-style models
assert 'Model unknown-provider/gpt-4o not found' in error_msg
assert 'litellm package' in error_msg
assert 'pip install' in error_msg
assert 'Provider-style models' in error_msg
def test_resolve_with_prefix():
"""Test that model resolution can be overridden with a prefix."""
assert models.LLMRegistry.resolve('gemini:gemini-1.5-flash') is Gemini
assert models.LLMRegistry.resolve('Claude:claude-3-opus@20240229') is Claude
assert models.LLMRegistry.resolve('lite:openai/gpt-4o') is LiteLlm
assert models.LLMRegistry.resolve('LiteLlm:openai/gpt-4o') is LiteLlm
def test_new_llm_with_prefix(mocker):
"""Test that new_llm strips prefix when creating instance if it matches class."""
mock_class = mocker.MagicMock()
mock_class.__name__ = 'MockLlm'
mocker.patch.object(models.LLMRegistry, 'resolve', return_value=mock_class)
models.LLMRegistry.new_llm('mock:gpt-4')
mock_class.assert_called_once_with(model='gpt-4')
mock_class.reset_mock()
models.LLMRegistry.new_llm('MockLlm:gpt-4')
mock_class.assert_called_once_with(model='gpt-4')
def test_new_llm_with_non_matching_prefix(mocker):
"""Test that new_llm keeps prefix if it does not match class."""
mock_class = mocker.MagicMock()
mock_class.__name__ = 'MockLlm'
mocker.patch.object(models.LLMRegistry, 'resolve', return_value=mock_class)
models.LLMRegistry.new_llm('custom:gpt-4')
mock_class.assert_called_once_with(model='custom:gpt-4')