383 lines
15 KiB
Python
383 lines
15 KiB
Python
"""
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Unit tests to validate UTF-8 encoding in providers
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and integration with language models.
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"""
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import json
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import os
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import unittest
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from unittest.mock import Mock, patch
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import pytest
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from providers.gemini import GeminiModelProvider
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from providers.openai_provider import OpenAIModelProvider
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from providers.shared import ProviderType
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class TestProviderUTF8Encoding(unittest.TestCase):
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"""Tests for UTF-8 encoding in providers."""
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def setUp(self):
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"""Test setup."""
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self.original_locale = os.getenv("LOCALE")
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def tearDown(self):
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"""Cleanup after tests."""
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if self.original_locale is not None:
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os.environ["LOCALE"] = self.original_locale
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else:
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os.environ.pop("LOCALE", None)
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def test_base_provider_utf8_support(self):
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"""Test that the OpenAI provider supports UTF-8."""
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provider = OpenAIModelProvider(api_key="test")
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# Test with UTF-8 characters
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test_text = "Développement en français avec émojis 🚀"
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tokens = provider.count_tokens(test_text, "gpt-4")
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# Should return a valid number (character-based estimate)
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self.assertIsInstance(tokens, int)
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self.assertGreater(tokens, 0)
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@pytest.mark.skip(reason="Requires real Gemini API access")
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@patch("google.generativeai.GenerativeModel")
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def test_gemini_provider_utf8_request(self, mock_model_class):
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"""Test that the Gemini provider handles UTF-8 correctly."""
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# Mock Gemini response
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mock_response = Mock()
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mock_response.text = "Response in French with accents: créé, développé, préféré 🎉"
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mock_response.usage_metadata = Mock()
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mock_response.usage_metadata.prompt_token_count = 10
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mock_response.usage_metadata.candidates_token_count = 15
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mock_response.usage_metadata.total_token_count = 25
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mock_model = Mock()
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mock_model.generate_content.return_value = mock_response
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mock_model_class.return_value = mock_model
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# Test Gemini provider
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provider = GeminiModelProvider(api_key="test-key")
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# Request with UTF-8 characters
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response = provider.generate_content(
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prompt="Can you explain software development?",
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model_name="gemini-2.5-flash",
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system_prompt="Reply in French with emojis.",
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)
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# Checks
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self.assertIsNotNone(response)
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self.assertIn("French", response.content)
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self.assertIn("🎉", response.content)
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# Check that the request contains UTF-8 characters
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mock_model.generate_content.assert_called_once()
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call_args = mock_model.generate_content.call_args
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parts = call_args[0][0] # First argument (parts)
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# Check for UTF-8 content in the request
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request_content = str(parts)
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self.assertIn("développement", request_content)
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@pytest.mark.skip(reason="Requires real OpenAI API access")
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@patch("openai.OpenAI")
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def test_openai_provider_utf8_logging(self, mock_openai_class):
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"""Test that the OpenAI provider logs UTF-8 correctly."""
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# Mock OpenAI response
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mock_response = Mock()
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mock_response.choices = [Mock()]
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mock_response.choices[0].message = Mock()
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mock_response.choices[0].message.content = "Python code created successfully! ✅"
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mock_response.usage = Mock()
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mock_response.usage.prompt_tokens = 20
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mock_response.usage.completion_tokens = 10
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mock_response.usage.total_tokens = 30
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mock_client = Mock()
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mock_client.chat.completions.create.return_value = mock_response
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mock_openai_class.return_value = mock_client # Test OpenAI provider
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provider = OpenAIModelProvider(api_key="test-key")
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# Test with UTF-8 logging
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with patch("logging.info"):
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response = provider.generate_content(
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prompt="Generate Python code to process data",
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model_name="gpt-4",
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system_prompt="You are an expert Python developer.",
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)
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# Response checks
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self.assertIsNotNone(response)
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self.assertIn("created", response.content)
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self.assertIn("✅", response.content)
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@pytest.mark.skip(reason="Requires real OpenAI API access")
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@patch("openai.OpenAI")
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def test_openai_compatible_o3_pro_utf8(self, mock_openai_class):
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"""Test for o3-pro with /responses endpoint and UTF-8."""
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# Mock o3-pro response
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mock_response = Mock()
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mock_response.output = Mock()
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mock_response.output.content = [Mock()]
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mock_response.output.content[0].type = "output_text"
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mock_response.output.content[0].text = "Analysis complete: code is well structured! 🎯"
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mock_response.usage = Mock()
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mock_response.usage.input_tokens = 50
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mock_response.usage.output_tokens = 25
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mock_response.model = "o3-pro"
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mock_response.id = "test-id"
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mock_response.created_at = 1234567890
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mock_client = Mock()
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mock_client.responses.create.return_value = mock_response
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mock_openai_class.return_value = mock_client
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# Test OpenAI Compatible provider with o3-pro
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provider = OpenAIModelProvider(api_key="test-key")
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# Test with UTF-8 logging for o3-pro
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with patch("logging.info") as mock_logging:
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response = provider.generate_content(
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prompt="Analyze this Python code for issues",
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model_name="o3-pro",
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system_prompt="You are a code review expert.",
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)
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# Response checks
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self.assertIsNotNone(response)
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self.assertIn("complete", response.content)
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self.assertIn("🎯", response.content)
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# Check that logging was called with ensure_ascii=False
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mock_logging.assert_called()
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log_calls = [call for call in mock_logging.call_args_list if "API request payload" in str(call)]
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self.assertTrue(len(log_calls) > 0, "No API payload log found")
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def test_provider_type_enum_utf8_safe(self):
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"""Test that ProviderType enum is UTF-8 safe."""
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# Test all provider types
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provider_types = list(ProviderType)
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for provider_type in provider_types:
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# Test JSON serialization
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data = {"provider": provider_type.value, "message": "UTF-8 test: emojis 🚀"}
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json_str = json.dumps(data, ensure_ascii=False)
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# Checks
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self.assertIn(provider_type.value, json_str)
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self.assertIn("emojis", json_str)
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self.assertIn("🚀", json_str)
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# Test deserialization
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parsed = json.loads(json_str)
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self.assertEqual(parsed["provider"], provider_type.value)
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self.assertEqual(parsed["message"], "UTF-8 test: emojis 🚀")
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def test_model_response_utf8_serialization(self):
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"""Test UTF-8 serialization of model responses."""
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from providers.shared import ModelResponse
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response = ModelResponse(
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content="Development successful! Code generated successfully. 🎉✅",
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usage={"input_tokens": 10, "output_tokens": 15, "total_tokens": 25},
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model_name="test-model",
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friendly_name="Test Model",
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provider=ProviderType.OPENAI, # Pass enum, not .value
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metadata={"created": "2024-01-01", "developer": "Test", "emojis": "🚀🎯🔥"},
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)
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response_dict = getattr(response, "to_dict", None)
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if callable(response_dict):
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response_dict = response.to_dict()
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else:
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# Convert ProviderType to string for JSON serialization
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d = response.__dict__.copy()
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if isinstance(d.get("provider"), ProviderType):
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d["provider"] = d["provider"].value
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response_dict = d
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json_str = json.dumps(response_dict, ensure_ascii=False, indent=2)
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# Checks
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self.assertIn("Development", json_str)
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self.assertIn("successful", json_str)
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self.assertIn("generated", json_str)
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self.assertIn("🎉", json_str)
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self.assertIn("✅", json_str)
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self.assertIn("created", json_str)
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self.assertIn("developer", json_str)
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self.assertIn("🚀", json_str)
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# Test deserialization
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parsed = json.loads(json_str)
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self.assertEqual(parsed["content"], response.content)
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self.assertEqual(parsed["friendly_name"], "Test Model")
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def test_error_handling_with_utf8(self):
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"""Test error handling with UTF-8 characters."""
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provider = OpenAIModelProvider(api_key="test")
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# Test validation with UTF-8 error message (no exception expected)
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error_message = None
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try:
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provider.validate_parameters("gpt-4", -1.0) # Invalid temperature
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except Exception as e:
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error_message = str(e)
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# Error message may contain UTF-8 characters or be None
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if error_message:
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self.assertIsInstance(error_message, str)
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else:
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# No exception: test passes (current provider logs a warning only)
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self.assertTrue(True)
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def test_temperature_handling_utf8_locale(self):
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"""Test temperature handling with UTF-8 locale."""
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# Set French locale
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os.environ["LOCALE"] = "fr-FR"
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provider = OpenAIModelProvider(api_key="test")
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# Test different temperatures
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test_temps = [0.0, 0.5, 1.0, 1.5, 2.0]
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for temp in test_temps:
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try:
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provider.validate_parameters("gpt-4", temp)
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# If no exception, temperature is valid
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self.assertLessEqual(temp, 2.0)
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except ValueError:
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# If exception, temperature must be > 2.0
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self.assertGreater(temp, 2.0)
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def test_provider_registry_utf8(self):
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"""Test that the provider registry handles UTF-8."""
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from providers.registry import ModelProviderRegistry
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# Test listing providers with UTF-8 descriptions
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providers = ModelProviderRegistry.get_available_providers()
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# Should contain valid providers
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self.assertGreater(len(providers), 0)
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# Test serialization
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provider_data = {
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"providers": [p.value for p in providers],
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"description": "Available providers for development 🚀",
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}
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json_str = json.dumps(provider_data, ensure_ascii=False)
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# Checks
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self.assertIn("development", json_str)
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self.assertIn("🚀", json_str)
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# Test parsing
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parsed = json.loads(json_str)
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self.assertEqual(parsed["description"], provider_data["description"])
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@pytest.mark.skip(reason="Requires real Gemini API access")
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@patch("google.generativeai.GenerativeModel")
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def test_gemini_provider_handles_api_encoding_error(self, mock_model_class):
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"""Test that the Gemini provider handles a non-UTF-8 API response."""
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from unittest.mock import PropertyMock
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mock_response = Mock()
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type(mock_response).text = PropertyMock(
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side_effect=UnicodeDecodeError("utf-8", b"\xfa", 0, 1, "invalid start byte")
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)
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mock_model = Mock()
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mock_model.generate_content.return_value = mock_response
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mock_model_class.return_value = mock_model
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provider = GeminiModelProvider(api_key="test-key")
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with self.assertRaises(Exception) as context:
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provider.generate_content(
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prompt="Explain something",
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model_name="gemini-2.5-flash",
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system_prompt="Reply in French.",
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)
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# Accept any error message containing UnicodeDecodeError
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self.assertIn("UnicodeDecodeError", str(context.exception))
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class DummyToolForLocaleTest:
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"""Utility class to test language instruction generation."""
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def get_language_instruction(self):
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locale = os.environ.get("LOCALE", "")
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if not locale or not locale.strip():
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return ""
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return f"Always respond in {locale.strip()}.\n\n"
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class TestLocaleModelIntegration(unittest.TestCase):
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"""Integration tests between locale and models."""
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def setUp(self):
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"""Integration test setup."""
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self.original_locale = os.getenv("LOCALE")
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def tearDown(self):
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"""Cleanup after integration tests."""
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if self.original_locale is not None:
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os.environ["LOCALE"] = self.original_locale
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else:
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os.environ.pop("LOCALE", None)
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def test_system_prompt_enhancement_french(self):
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"""Test system prompt enhancement with French locale."""
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os.environ["LOCALE"] = "fr-FR"
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OpenAIModelProvider(api_key="test")
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# Simulate language instruction
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tool = DummyToolForLocaleTest()
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instruction = tool.get_language_instruction()
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self.assertIn("fr-FR", instruction)
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self.assertTrue(instruction.startswith("Always respond in fr-FR"))
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def test_system_prompt_enhancement_multiple_locales(self):
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"""Test enhancement with different locales."""
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OpenAIModelProvider(api_key="test")
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locales = ["fr-FR", "es-ES", "de-DE", "it-IT", "pt-BR", "ja-JP", "zh-CN"]
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for locale in locales:
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os.environ["LOCALE"] = locale
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tool = DummyToolForLocaleTest()
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instruction = tool.get_language_instruction()
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self.assertIn(locale, instruction)
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self.assertTrue(instruction.startswith(f"Always respond in {locale}"))
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prompt_data = {"system_prompt": instruction, "locale": locale}
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json_str = json.dumps(prompt_data, ensure_ascii=False)
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parsed = json.loads(json_str)
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self.assertEqual(parsed["locale"], locale)
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def test_model_name_resolution_utf8(self):
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"""Test model name resolution with UTF-8."""
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provider = OpenAIModelProvider(api_key="test")
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model_names = ["gpt-4", "gemini-2.5-flash", "anthropic/claude-opus-4.1", "o3-pro"]
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for model_name in model_names:
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resolved_model_name = provider._resolve_model_name(model_name)
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self.assertIsInstance(resolved_model_name, str)
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model_data = {
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"model": resolved_model_name,
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"description": f"Model {model_name} - advanced development 🚀",
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"capabilities": ["generation", "review", "creation"],
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}
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json_str = json.dumps(model_data, ensure_ascii=False)
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self.assertIn("development", json_str)
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self.assertIn("generation", json_str)
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self.assertIn("review", json_str)
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self.assertIn("creation", json_str)
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self.assertIn("🚀", json_str)
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def test_system_prompt_enhancement_with_unusual_locale_formats(self):
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"""Test language instruction with various locale formats."""
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test_locales = [
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"fr", # Language only
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"fr_FR", # Language and region with underscore
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"de-DE.UTF-8", # Full locale with encoding
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]
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for locale in test_locales:
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with self.subTest(locale=locale):
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os.environ["LOCALE"] = locale
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tool = DummyToolForLocaleTest()
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instruction = tool.get_language_instruction()
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self.assertTrue(instruction.startswith(f"Always respond in {locale}"))
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