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