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chore: import upstream snapshot with attribution
2026-07-13 12:37:14 +08:00

451 lines
16 KiB
Python

# 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 the factory module.
Note: This file tests the deprecated registry module which is now an alias
for router. The no-name-in-module warning for providers.registry is expected.
"""
# pylint: disable=no-name-in-module
import os
from unittest import mock
from absl.testing import absltest
from langextract import exceptions
from langextract import factory
from langextract.core import base_model
from langextract.core import types
from langextract.providers import router
class FakeGeminiProvider(base_model.BaseLanguageModel):
"""Fake Gemini provider for testing."""
def __init__(self, model_id, api_key=None, **kwargs):
self.model_id = model_id
self.api_key = api_key
self.kwargs = kwargs
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="gemini")]]
def infer_batch(self, prompts, batch_size=32):
return self.infer(prompts)
class FakeOpenAIProvider(base_model.BaseLanguageModel):
"""Fake OpenAI provider for testing."""
def __init__(self, model_id, api_key=None, **kwargs):
if not api_key:
raise ValueError("API key required")
self.model_id = model_id
self.api_key = api_key
self.kwargs = kwargs
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="openai")]]
def infer_batch(self, prompts, batch_size=32):
return self.infer(prompts)
class FactoryTest(absltest.TestCase): # pylint: disable=too-many-public-methods
def setUp(self):
super().setUp()
router.clear()
import langextract.providers as providers_module # pylint: disable=import-outside-toplevel
providers_module._plugins_loaded = True
# Use direct registration for test providers to avoid module path issues
router.register(r"^gemini", priority=100)(FakeGeminiProvider)
router.register(r"^gpt", r"^o1", priority=100)(FakeOpenAIProvider)
def tearDown(self):
super().tearDown()
router.clear()
import langextract.providers as providers_module # pylint: disable=import-outside-toplevel
providers_module._plugins_loaded = False
def test_create_model_basic(self):
"""Test basic model creation."""
config = factory.ModelConfig(
model_id="gemini-pro", provider_kwargs={"api_key": "test-key"}
)
model = factory.create_model(config)
self.assertIsInstance(model, FakeGeminiProvider)
self.assertEqual(model.model_id, "gemini-pro")
self.assertEqual(model.api_key, "test-key")
def test_create_model_from_id(self):
"""Test convenience function for creating model from ID."""
model = factory.create_model_from_id("gemini-flash", api_key="test-key")
self.assertIsInstance(model, FakeGeminiProvider)
self.assertEqual(model.model_id, "gemini-flash")
self.assertEqual(model.api_key, "test-key")
@mock.patch.dict(os.environ, {"GEMINI_API_KEY": "env-gemini-key"})
def test_uses_gemini_api_key_from_environment(self):
"""Factory should use GEMINI_API_KEY from environment for Gemini models."""
config = factory.ModelConfig(model_id="gemini-pro")
model = factory.create_model(config)
self.assertEqual(model.api_key, "env-gemini-key")
@mock.patch.dict(os.environ, {"OPENAI_API_KEY": "env-openai-key"})
def test_uses_openai_api_key_from_environment(self):
"""Factory should use OPENAI_API_KEY from environment for OpenAI models."""
config = factory.ModelConfig(model_id="gpt-4")
model = factory.create_model(config)
self.assertEqual(model.api_key, "env-openai-key")
@mock.patch.dict(
os.environ, {"LANGEXTRACT_API_KEY": "env-langextract-key"}, clear=True
)
def test_falls_back_to_langextract_api_key_when_provider_key_missing(self):
"""Factory uses LANGEXTRACT_API_KEY when provider-specific key is missing."""
config = factory.ModelConfig(model_id="gemini-pro")
model = factory.create_model(config)
self.assertEqual(model.api_key, "env-langextract-key")
@mock.patch.dict(
os.environ,
{
"GEMINI_API_KEY": "gemini-key",
"LANGEXTRACT_API_KEY": "langextract-key",
},
)
def test_provider_specific_key_takes_priority_over_langextract_key(self):
"""Factory prefers provider-specific API key over LANGEXTRACT_API_KEY."""
config = factory.ModelConfig(model_id="gemini-pro")
model = factory.create_model(config)
self.assertEqual(model.api_key, "gemini-key")
def test_explicit_kwargs_override_env(self):
"""Test that explicit kwargs override environment variables."""
with mock.patch.dict(os.environ, {"GEMINI_API_KEY": "env-key"}):
config = factory.ModelConfig(
model_id="gemini-pro", provider_kwargs={"api_key": "explicit-key"}
)
model = factory.create_model(config)
self.assertEqual(model.api_key, "explicit-key")
@mock.patch.dict(os.environ, {}, clear=True)
def test_wraps_provider_initialization_error_in_inference_config_error(self):
"""Factory should wrap provider errors in InferenceConfigError."""
config = factory.ModelConfig(model_id="gpt-4")
with self.assertRaises(exceptions.InferenceConfigError) as cm:
factory.create_model(config)
self.assertIn("Failed to create provider", str(cm.exception))
self.assertIn("API key required", str(cm.exception))
def test_raises_error_when_no_provider_matches_model_id(self):
"""Factory should raise InferenceConfigError for unregistered model IDs."""
config = factory.ModelConfig(model_id="unknown-model")
with self.assertRaises(exceptions.InferenceConfigError) as cm:
factory.create_model(config)
self.assertIn("No provider registered", str(cm.exception))
def test_additional_kwargs_passed_through(self):
"""Test that additional kwargs are passed to provider."""
config = factory.ModelConfig(
model_id="gemini-pro",
provider_kwargs={
"api_key": "test-key",
"temperature": 0.5,
"max_tokens": 100,
"custom_param": "value",
},
)
model = factory.create_model(config)
self.assertEqual(model.kwargs["temperature"], 0.5)
self.assertEqual(model.kwargs["max_tokens"], 100)
self.assertEqual(model.kwargs["custom_param"], "value")
@mock.patch.dict(os.environ, {"OLLAMA_BASE_URL": "http://custom:11434"})
def test_ollama_uses_base_url_from_environment(self):
"""Factory should use OLLAMA_BASE_URL from environment for Ollama models."""
@router.register(r"^ollama")
class FakeOllamaProvider(base_model.BaseLanguageModel): # pylint: disable=unused-variable
def __init__(self, model_id, base_url=None, **kwargs):
self.model_id = model_id
self.base_url = base_url
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="ollama")]]
def infer_batch(self, prompts, batch_size=32):
return self.infer(prompts)
config = factory.ModelConfig(model_id="ollama/llama2")
model = factory.create_model(config)
self.assertEqual(model.base_url, "http://custom:11434")
def test_ollama_models_select_without_api_keys(self):
"""Test that Ollama models resolve without API keys or explicit type."""
@router.register(r"^llama", r"^gemma", r"^mistral", r"^qwen", priority=100)
class FakeOllamaProvider(base_model.BaseLanguageModel):
def __init__(self, model_id, **kwargs):
self.model_id = model_id
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="test")]]
def infer_batch(self, prompts, batch_size=32):
return self.infer(prompts)
test_models = ["llama3", "gemma2:2b", "mistral:7b", "qwen3:0.6b"]
for model_id in test_models:
with self.subTest(model_id=model_id):
with mock.patch.dict(os.environ, {}, clear=True):
config = factory.ModelConfig(model_id=model_id)
model = factory.create_model(config)
self.assertIsInstance(model, FakeOllamaProvider)
self.assertEqual(model.model_id, model_id)
def test_model_config_fields_are_immutable(self):
"""ModelConfig fields should not be modifiable after creation."""
config = factory.ModelConfig(
model_id="gemini-pro", provider_kwargs={"api_key": "test"}
)
with self.assertRaises(AttributeError):
config.model_id = "different"
def test_model_config_allows_dict_contents_modification(self):
"""ModelConfig allows modification of dict contents (not deeply frozen)."""
config = factory.ModelConfig(
model_id="gemini-pro", provider_kwargs={"api_key": "test"}
)
config.provider_kwargs["new_key"] = "value"
self.assertEqual(config.provider_kwargs["new_key"], "value")
def test_uses_highest_priority_provider_when_multiple_match(self):
"""Factory uses highest priority provider when multiple patterns match."""
@router.register(r"^gemini", priority=90)
class AnotherGeminiProvider(base_model.BaseLanguageModel): # pylint: disable=unused-variable
def __init__(self, model_id=None, **kwargs):
self.model_id = model_id or "default-model"
self.kwargs = kwargs
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="another")]]
def infer_batch(self, prompts, batch_size=32):
return self.infer(prompts)
config = factory.ModelConfig(model_id="gemini-pro")
model = factory.create_model(config)
self.assertIsInstance(model, FakeGeminiProvider) # Priority 100 wins
def test_explicit_provider_overrides_pattern_matching(self):
"""Factory should use explicit provider even when pattern doesn't match."""
@router.register(r"^another", priority=90)
class AnotherProvider(base_model.BaseLanguageModel):
def __init__(self, model_id=None, **kwargs):
self.model_id = model_id or "default-model"
self.kwargs = kwargs
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="another")]]
def infer_batch(self, prompts, batch_size=32):
return self.infer(prompts)
config = factory.ModelConfig(
model_id="gemini-pro", provider="AnotherProvider"
)
model = factory.create_model(config)
self.assertIsInstance(model, AnotherProvider)
self.assertEqual(model.model_id, "gemini-pro")
def test_provider_without_model_id_uses_provider_default(self):
"""Factory should use provider's default model_id when none specified."""
@router.register(r"^default-provider$", priority=50)
class DefaultProvider(base_model.BaseLanguageModel):
def __init__(self, model_id="default-model", **kwargs):
self.model_id = model_id
self.kwargs = kwargs
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="default")]]
def infer_batch(self, prompts, batch_size=32):
return self.infer(prompts)
config = factory.ModelConfig(provider="DefaultProvider")
model = factory.create_model(config)
self.assertIsInstance(model, DefaultProvider)
self.assertEqual(model.model_id, "default-model")
def test_raises_error_when_neither_model_id_nor_provider_specified(self):
"""Factory raises ValueError when config has neither model_id nor provider."""
config = factory.ModelConfig()
with self.assertRaises(ValueError) as cm:
factory.create_model(config)
self.assertIn(
"Either model_id or provider must be specified", str(cm.exception)
)
def test_gemini_vertexai_parameters_accepted(self):
"""Test that Vertex AI parameters are properly passed to Gemini provider."""
original_entries = router._entries.copy() # pylint: disable=protected-access
original_keys = router._entry_keys.copy() # pylint: disable=protected-access
try:
@router.register(r"^gemini", priority=200)
class MockGeminiWithVertexAI(base_model.BaseLanguageModel): # pylint: disable=unused-variable
def __init__(
self,
model_id="gemini-3.5-flash",
api_key=None,
vertexai=False,
credentials=None,
project=None,
location=None,
**kwargs,
):
self.model_id = model_id
self.api_key = api_key
self.vertexai = vertexai
self.credentials = credentials
self.project = project
self.location = location
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="vertexai-test")]]
config = factory.ModelConfig(
model_id="gemini-pro",
provider_kwargs={
"vertexai": True,
"project": "test-project",
"location": "us-central1",
},
)
model = factory.create_model(config)
self.assertTrue(model.vertexai)
self.assertEqual(model.project, "test-project")
self.assertEqual(model.location, "us-central1")
self.assertIsNone(model.api_key)
finally:
router._entries = original_entries # pylint: disable=protected-access
router._entry_keys = original_keys # pylint: disable=protected-access
def test_gemini_vertexai_with_credentials(self):
"""Test that Vertex AI credentials can be passed through."""
original_entries = router._entries.copy() # pylint: disable=protected-access
original_keys = router._entry_keys.copy() # pylint: disable=protected-access
try:
@router.register(r"^gemini", priority=200)
class MockGeminiWithCredentials(base_model.BaseLanguageModel): # pylint: disable=unused-variable
def __init__(
self, model_id="gemini-3.5-flash", credentials=None, **kwargs
):
self.model_id = model_id
self.credentials = credentials
super().__init__()
def infer(self, batch_prompts, **kwargs):
return [[types.ScoredOutput(score=1.0, output="creds-test")]]
mock_credentials = {"type": "service_account"} # Simplified mock
config = factory.ModelConfig(
model_id="gemini-3.5-flash",
provider_kwargs={"credentials": mock_credentials},
)
model = factory.create_model(config)
self.assertEqual(model.credentials, mock_credentials)
finally:
router._entries = original_entries # pylint: disable=protected-access
router._entry_keys = original_keys # pylint: disable=protected-access
def test_explicit_provider_loads_builtins_before_resolution(self):
"""Builtins must be loaded even when provider is specified explicitly."""
config = factory.ModelConfig(
model_id="gemini-pro",
provider="FakeGeminiProvider",
provider_kwargs={"api_key": "test-key"},
)
model = factory.create_model(config)
self.assertIsInstance(model, FakeGeminiProvider)
self.assertEqual(model.model_id, "gemini-pro")
def test_explicit_provider_loads_builtins_with_schema_constraints(self):
"""Builtins must be loaded in the _create_model_with_schema path too."""
config = factory.ModelConfig(
model_id="gemini-pro",
provider="FakeGeminiProvider",
provider_kwargs={"api_key": "test-key"},
)
# This exercises _create_model_with_schema via the fence_output kwarg.
model = factory.create_model(config, fence_output=False)
self.assertIsInstance(model, FakeGeminiProvider)
self.assertEqual(model.model_id, "gemini-pro")
if __name__ == "__main__":
absltest.main()