e9c5662b3a
Description: This feature adds support for UTF-8 encoding in JSON responses, allowing for proper handling of special characters and emojis. - Implement unit tests for UTF-8 encoding in various model providers including Gemini, OpenAI, and OpenAI Compatible. - Validate UTF-8 support in token counting, content generation, and error handling. - Introduce tests for JSON serialization ensuring proper handling of French characters and emojis. - Create tests for language instruction generation based on locale settings. - Validate UTF-8 handling in workflow tools including AnalyzeTool, CodereviewTool, and DebugIssueTool. - Ensure that all tests check for correct UTF-8 character preservation and proper JSON formatting. - Add integration tests to verify the interaction between locale settings and model responses.
456 lines
19 KiB
Python
456 lines
19 KiB
Python
"""
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Unit tests to validate UTF-8 encoding in workflow tools
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and the generation of properly encoded JSON responses.
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"""
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import json
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import os
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import tempfile
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import unittest
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from unittest.mock import Mock, patch
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from tools.analyze import AnalyzeTool
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from tools.codereview import CodereviewTool
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from tools.debug import DebugIssueTool
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class TestWorkflowToolsUTF8(unittest.TestCase):
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"""Tests for UTF-8 encoding in workflow tools."""
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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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# Default to French for tests
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os.environ["LOCALE"] = "fr-FR"
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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_workflow_json_response_structure(self):
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"""Test the structure of JSON responses from workflow tools."""
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# Test with analysis tool
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analyze_tool = AnalyzeTool()
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# Mock response with UTF-8 characters
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test_response = {
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"status": "pause_for_analysis",
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"step_number": 1,
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"total_steps": 3,
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"next_step_required": True,
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"findings": "Code analysis reveals performance issues 🔍",
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"files_checked": ["/src/main.py"],
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"relevant_files": ["/src/main.py"],
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"issues_found": [
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{"severity": "high", "description": "Function too complex - refactoring needed"}
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],
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"investigation_required": True,
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"required_actions": ["Review code dependencies", "Analyze architectural patterns"],
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}
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# Test JSON serialization with ensure_ascii=False
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json_str = json.dumps(test_response, indent=2, ensure_ascii=False)
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# UTF-8 checks
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self.assertIn("révèle", json_str)
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self.assertIn("problèmes", json_str)
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self.assertIn("nécessaire", json_str)
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self.assertIn("dépendances", json_str)
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self.assertIn("🔍", json_str)
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# No escaped characters
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self.assertNotIn("\\u", json_str)
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# Test parsing
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parsed = json.loads(json_str)
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self.assertEqual(parsed["findings"], test_response["findings"])
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self.assertEqual(len(parsed["issues_found"]), 1)
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self.assertIn("nécessaire", parsed["issues_found"][0]["description"])
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@patch("tools.shared.base_tool.BaseTool.get_model_provider")
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def test_analyze_tool_utf8_response(self, mock_get_provider):
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"""Test that the analyze tool returns correct UTF-8 responses."""
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# Mock provider
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mock_provider = Mock()
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mock_provider.get_provider_type.return_value = Mock(value="test")
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mock_provider.generate_content.return_value = Mock(
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content="Architectural analysis complete. Recommendations: improve modularity.",
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usage={},
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model_name="test-model",
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metadata={},
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)
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mock_get_provider.return_value = mock_provider
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# Test the tool
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analyze_tool = AnalyzeTool()
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result = analyze_tool.execute(
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{
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"step": "Analyze system architecture to identify issues",
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"step_number": 1,
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"total_steps": 2,
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"next_step_required": True,
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"findings": "Starting architectural analysis of Python code",
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"relevant_files": ["/test/main.py"],
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"model": "test-model",
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}
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)
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# Checks
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self.assertIsNotNone(result)
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self.assertEqual(len(result), 1)
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# Parse the response - must be valid UTF-8 JSON
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response_text = result[0].text
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response_data = json.loads(response_text)
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# Structure checks
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self.assertIn("status", response_data)
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self.assertIn("step_number", response_data)
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# Check that the French instruction was added
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mock_provider.generate_content.assert_called()
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call_args = mock_provider.generate_content.call_args
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system_prompt = call_args.kwargs.get("system_prompt", "")
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self.assertIn("fr-FR", system_prompt)
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@patch("tools.shared.base_tool.BaseTool.get_model_provider")
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def test_codereview_tool_french_findings(self, mock_get_provider):
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"""Test that the codereview tool produces findings in French."""
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# Mock with analysis in French
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mock_provider = Mock()
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mock_provider.get_provider_type.return_value = Mock(value="test")
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mock_provider.supports_thinking_mode.return_value = False
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mock_provider.generate_content.return_value = Mock(
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content=json.dumps(
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{
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"status": "analysis_complete",
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"raw_analysis": """
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🔴 CRITIQUE: Aucun problème critique trouvé.
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🟠 ÉLEVÉ: Fichier example.py:42 - Fonction trop complexe
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→ Problème: La fonction process_data() contient trop de responsabilités
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→ Solution: Décomposer en fonctions plus petites et spécialisées
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🟡 MOYEN: Gestion d'erreurs insuffisante
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→ Problème: Plusieurs fonctions n'ont pas de gestion d'erreurs appropriée
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→ Solution: Ajouter des try-catch et validation des paramètres
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✅ Points positifs:
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• Code bien commenté et lisible
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• Nomenclature cohérente
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• Tests unitaires présents
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""",
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},
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ensure_ascii=False,
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),
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usage={},
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model_name="test-model",
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metadata={},
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)
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mock_get_provider.return_value = mock_provider
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# Test the tool
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codereview_tool = CodereviewTool()
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result = codereview_tool.execute(
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{
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"step": "Complete review of Python code",
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"step_number": 1,
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"total_steps": 1,
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"next_step_required": False,
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"findings": "Code review complete",
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"relevant_files": ["/test/example.py"],
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"model": "test-model",
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}
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)
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# Checks
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self.assertIsNotNone(result)
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response_text = result[0].text
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response_data = json.loads(response_text)
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# Check UTF-8 characters in analysis
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if "expert_analysis" in response_data:
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analysis = response_data["expert_analysis"]["raw_analysis"]
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# Vérification de caractères français
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# Check for French characters
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self.assertIn("ÉLEVÉ", analysis)is)
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self.assertIn("problème", analysis)sis)
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self.assertIn("spécialisées", analysis)
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self.assertIn("appropriée", analysis)
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self.assertIn("paramètres", analysis)
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self.assertIn("présents", analysis)
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# Vérification d'emojis
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# Check for emojislysis)
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self.assertIn("🔴", analysis)
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self.assertIn("🟠", analysis)
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self.assertIn("🟡", analysis)
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self.assertIn("✅", analysis)
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@patch("tools.shared.base_tool.BaseTool.get_model_provider")
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@patch("tools.shared.base_tool.BaseTool.get_model_provider")vider):
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def test_debug_tool_french_error_analysis(self, mock_get_provider):
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"""Test that the debug tool analyzes errors in French."""
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# Mock providerck()
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mock_provider = Mock()ider_type.return_value = Mock(value="test")
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mock_provider.get_provider_type.return_value = Mock(value="test")
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mock_provider.generate_content.return_value = Mock(n définie. Cause probable: import manquant.",
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content="Error analyzed: variable 'données' not defined. Probable cause: missing import.",
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usage={},e="test-model",
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model_name="test-model",
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metadata={},
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)ock_get_provider.return_value = mock_provider
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mock_get_provider.return_value = mock_provider
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# Test de l'outil debug
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# Test the debug toolTool()
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debug_tool = DebugIssueTool()
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result = debug_tool.execute(
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{ "step": "Analyser l'erreur NameError dans le fichier de traitement des données",
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"step": "Analyze NameError in data processing file",
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"step_number": 1,
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"total_steps": 2,ed": True,
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"next_step_required": True,e lors de l'exécution du script",
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"findings": "Error detected during script execution",
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"files_checked": ["/src/data_processor.py"],,
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"relevant_files": ["/src/data_processor.py"], - import manquant",
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"hypothesis": "Variable 'données' not defined - missing import",
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"confidence": "medium",
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"model": "test-model",
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}
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)
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# Vérifications
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# CheckstNone(result)
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self.assertIsNotNone(result)xt
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response_text = result[0].textponse_text)
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response_data = json.loads(response_text)
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# Vérification de la structure de réponse
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# Check response structure
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self.assertIn("status", response_data)response_data)
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self.assertIn("investigation_status", response_data)
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# Vérification que les caractères UTF-8 sont préservés
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# Check that UTF-8 characters are preservedFalse)
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response_str = json.dumps(response_data, ensure_ascii=False)
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self.assertIn("données", response_str))
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self.assertIn("détectée", response_str))
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self.assertIn("exécution", response_str)
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self.assertIn("définie", response_str)
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def test_workflow_mixin_utf8_serialization(self):
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def test_workflow_mixin_utf8_serialization(self):lowMixin."""
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"""Test UTF-8 serialization in BaseWorkflowMixin."""
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# Simulation of a workflow response with UTF-8 characters
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workflow_response = {g_expert_analysis",
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"status": "calling_expert_analysis",
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"step_number": 2,
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"total_steps": 3,ed": True,
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"next_step_required": True,",
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"continuation_id": "test-id",
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"file_context": {y_embedded",
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"type": "fully_embedded",
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"files_embedded": 2,n": "Contexte optimisé pour l'analyse experte",
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"context_optimization": "Context optimized for expert analysis",
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},xpert_analysis": {
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"expert_analysis": {sis_complete",
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"status": "analysis_complete",
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"raw_analysis": """
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Complete system analysis reveals:
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🎯 **Objectif**: Améliorer les performances
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🎯 **Objective**: Improve performancenamique
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🔍 **Methodology**: Static and dynamic analysis
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📊 **Results**: nérale: satisfaisante
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• Overall performance: satisfactoryées
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• Possible optimizations: 3 identifiedlog n)
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• Algorithmic complexity: O(n²) → O(n log n)
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**Recommandations prioritaires**:
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**Priority recommendations**:es données
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1. Optimize the data sorting functionréquentes
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2. Implement a cache for frequent requests
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3. Refactor the report generation module
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🚀 **Impact attendu**: Amélioration de 40% des performances
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🚀 **Expected impact**: 40% improvement in performance
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""", },
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},nvestigation_summary": {
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"investigation_summary": {rc/performance.py", "/src/cache.py"],
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"files_analyzed": ["/src/performance.py", "/src/cache.py"],nt des données",
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"key_findings": "Optimizations identified in data processing",
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"recommendations": "Implement caching and algorithmic improvement",
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},
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}
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# Test de sérialisation avec ensure_ascii=False
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# Test serialization with ensure_ascii=False=2, ensure_ascii=False)
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json_str = json.dumps(workflow_response, indent=2, ensure_ascii=False)
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# Vérifications de préservation UTF-8
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# UTF-8 preservation checks
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utf8_chars = [
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"révèle",ogie",
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"Méthodologie",
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"générale",s",
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"identifiées",,
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"prioritaires",
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"données",s",
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"fréquentes",
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"génération",
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"attendu",ion",
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"Amélioration",
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"identifiées",,
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"amélioration",
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]
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for char_seq in utf8_chars:
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for char_seq in utf8_chars: json_str)
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self.assertIn(char_seq, json_str)
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# Vérifications d'emojis
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# Emoji checks", "🚀"]
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emojis = ["🎯", "🔍", "📊", "🚀"]
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for emoji in emojis:oji, json_str)
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self.assertIn(emoji, json_str)
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# Pas de caractères échappés
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# No escaped characters_str)
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self.assertNotIn("\\u", json_str)
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# Test de parsing
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# Test parsingds(json_str)
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parsed = json.loads(json_str)
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self.assertEqual(t_analysis"]["raw_analysis"], workflow_response["expert_analysis"]["raw_analysis"]
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parsed["expert_analysis"]["raw_analysis"], workflow_response["expert_analysis"]["raw_analysis"]
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)
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def test_file_context_utf8_handling(self):
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def test_file_context_utf8_handling(self):xte de fichiers."""
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"""Test UTF-8 handling in file context."""
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# Create a temporary file with UTF-8 content
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french_code = '''#!/usr/bin/env python3
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"""ule de traitement des données utilisateur.
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Module for processing user data.
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Created by: Development Team
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"""
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class GestionnaireDonnées:
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class DataHandler:e traitement des données utilisateur."""
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"""Handler for processing user data."""
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def __init__(self):
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def __init__(self):{}
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self.data = {}= {}
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self.preferences = {}
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traiter_données(self, données_entrée):
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def process_data(self, input_data):
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"""ite les données d'entrée selon les préférences.
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Processes input data according to preferences.
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Args:
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Args:onnées_entrée: Données à traiter
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input_data: Data to process
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rns:
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Returns:ées traitées et formatées
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Processed and formatted data
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"""ultat = {}
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result = {}
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for clé, valeur in données_entrée.items():
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for key, value in input_data.items():
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if self._validate_data(value):r_données(valeur)
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result[key] = self._format_data(value)
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ésultat
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return result
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_valider_données(self, données):
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def _validate_data(self, data):es."""
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"""Validates the structure of the data."""(données)) > 0
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return data is not None and len(str(data)) > 0
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_formater_données(self, données):
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def _format_data(self, data):règles métier."""
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"""Formats the data according to business rules."""
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return f"Formatted: {data}"
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# Configuration par défaut
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# Default configuration
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DEFAULT_CONFIG = {utf-8",
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"encoding": "utf-8",,
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"language": "French",aris"
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"timezone": "Europe/Paris"
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}
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def créer_gestionnaire():
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def create_handler():du gestionnaire de données."""
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"""Creates an instance of the data handler."""
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return DataHandler()
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'''
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with tempfile.NamedTemporaryFile(mode="w", encoding="utf-8", suffix=".py", delete=False) as f:
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with tempfile.NamedTemporaryFile(mode="w", encoding="utf-8", suffix=".py", delete=False) as f:
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f.write(french_code)
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temp_file = f.name
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try:
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try:# Test de lecture et traitement UTF-8
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# Test reading and processing UTF-8tf-8") as f:
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with open(temp_file, "r", encoding="utf-8") as f:
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content = f.read()
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# Simulation du contexte de fichier pour workflow
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# Simulate file context for workflow
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file_context = { temp_file,
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"file_path": temp_file,
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"content": content,,
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"encoding": "utf-8", Python avec noms de variables en français",
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"analysis": "Python file with variable names in French",
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"metrics": { len(content.split("\n")),
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"lines": len(content.split("\n")),
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"classes": 1,
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"methods": 4,péciaux": ["é", "è", "à", "ç", "ù"],
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"special_characters": ["é", "è", "à", "ç", "ù"],
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},
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}
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# Test de sérialisation du contexte
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# Test context serializationext, ensure_ascii=False, indent=2)
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context_json = json.dumps(file_context, ensure_ascii=False, indent=2)
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# Vérifications UTF-8
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# UTF-8 checksnnaireDonnées", context_json)
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self.assertIn("DataHandler", context_json)
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self.assertIn("data", context_json)son)
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self.assertIn("preferences", context_json)on)
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self.assertIn("input_data", context_json)n)
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self.assertIn("format_data", context_json)n)
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self.assertIn("create_handler", context_json)
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self.assertIn("French", context_json)
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# Test de parsing
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# Test parsingjson.loads(context_json)
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parsed_context = json.loads(context_json)], content)
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self.assertEqual(parsed_context["content"], content))
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self.assertIn("French", parsed_context["analysis"])
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finally:
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finally:ttoyage
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# Cleanupemp_file)
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os.unlink(temp_file)
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def test_error_response_utf8_format(self):
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def test_error_response_utf8_format(self):les réponses workflow."""
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"""Test UTF-8 error format in workflow responses."""
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# Simulation of an error response with UTF-8 characters
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error_response = {or",
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"status": "error",idationError",
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"error_type": "ValidationError",ée invalides: caractères spéciaux non supportés",
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"error_message": "Invalid input data: unsupported special characters",
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"error_details": {rc/données.py",
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"file": "/src/données.py",
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"line": 42,"Encodage UTF-8 requis pour les noms de variables accentuées",
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"issue": "UTF-8 encoding required for accented variable names",
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"solution": "Check file encoding and IDE settings",
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},uggestions": [
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"suggestions": [-*- coding: utf-8 -*- en en-tête",
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"Use # -*- coding: utf-8 -*- at the top",
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"Set IDE to UTF-8 by default",e",
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"Check system locale settings",
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],imestamp": "2024-01-01T12:00:00Z",
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"timestamp": "2024-01-01T12:00:00Z",
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}
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# Test de sérialisation d'erreur
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# Test error serializationsponse, ensure_ascii=False, indent=2)
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error_json = json.dumps(error_response, ensure_ascii=False, indent=2)
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# Vérifications UTF-8
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# UTF-8 checkss", error_json)
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self.assertIn("Données", error_json)
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self.assertIn("entrée", error_json)n)
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self.assertIn("spéciaux", error_json))
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self.assertIn("supportés", error_json))
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self.assertIn("données.py", error_json)
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self.assertIn("problème", error_json)n)
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self.assertIn("accentuées", error_json)
|
|
self.assertIn("Vérifier", error_json)n)
|
|
self.assertIn("paramètres", error_json)
|
|
# Test de parsing
|
|
# Test parsingon.loads(error_json)
|
|
parsed_error = json.loads(error_json)type"], "ValidationError")
|
|
self.assertEqual(parsed_error["error_type"], "ValidationError")lème"])
|
|
self.assertIn("accentuées", parsed_error["error_details"]["problème"])
|
|
|
|
if __name__ == "__main__":
|
|
if __name__ == "__main__":y=2)
|
|
unittest.main(verbosity=2) |