rpa_vision_v3/tests/integration/test_workflow_pipeline_enhanced.py

"""
Tests d'intégration pour WorkflowPipeline avec ExecutionResult amélioré

Auteur: Dom, Alice Kiro - 20 décembre 2024
"""

import pytest
import uuid
from datetime import datetime
from unittest.mock import Mock, patch, MagicMock
from pathlib import Path

from core.pipeline.workflow_pipeline import WorkflowPipeline
from core.pipeline.workflow_pipeline_enhanced import WorkflowPipelineEnhanced, migrate_execute_workflow_step
from core.models.screen_state import ScreenState, WindowContext, RawLevel, PerceptionLevel, ContextLevel, EmbeddingRef
from core.models.execution_result import WorkflowExecutionResult, StepExecutionStatus
from core.models.workflow_graph import Workflow, WorkflowNode, WorkflowEdge, Action
from core.execution.action_executor import ExecutionResult, ExecutionStatus
from core.execution.error_handler import RecoveryResult, RecoveryStrategy


class TestWorkflowPipelineEnhanced:
    """Tests d'intégration pour WorkflowPipeline avec ExecutionResult amélioré"""
    
    @pytest.fixture
    def mock_screen_state(self):
        """Créer un ScreenState mock pour les tests"""
        window = WindowContext(
            app_name="test_app",
            window_title="Test Window",
            screen_resolution=[1920, 1080],
            workspace="main"
        )
        
        raw = RawLevel(
            screenshot_path="/tmp/test_screenshot.png",
            capture_method="test",
            file_size_bytes=1024
        )
        
        perception = PerceptionLevel(
            embedding=EmbeddingRef(
                provider="test",
                vector_id="test_vector",
                dimensions=512
            ),
            detected_text=[],
            text_detection_method="test",
            confidence_avg=0.9
        )
        
        context = ContextLevel(
            current_workflow_candidate="test_workflow",
            workflow_step=None,
            user_id="test_user",
            tags=[],
            business_variables={}
        )
        
        return ScreenState(
            screen_state_id="test_state",
            timestamp=datetime.now(),
            session_id="test_session",
            window=window,
            raw=raw,
            perception=perception,
            context=context,
            ui_elements=[]
        )
    
    @pytest.fixture
    def mock_workflow_pipeline(self):
        """Créer un WorkflowPipeline mock pour les tests"""
        pipeline = Mock(spec=WorkflowPipeline)
        
        # Mock des composants nécessaires
        pipeline.error_handler = Mock()
        pipeline.action_executor = Mock()
        
        # Mock des méthodes nécessaires
        pipeline.match_current_state = Mock()
        pipeline.get_next_action = Mock()
        pipeline.load_workflow = Mock()
        
        return pipeline
    
    def test_execute_workflow_step_enhanced_success_returns_complete_metadata(self, mock_workflow_pipeline, mock_screen_state):
        """Test que execute_workflow_step_enhanced retourne des métadonnées complètes en cas de succès"""
        # Arrange
        workflow_id = "test_workflow"
        
        # Mock du match result
        mock_workflow_pipeline.match_current_state.return_value = {
            "node_id": "node_1",
            "workflow_id": workflow_id,
            "confidence": 0.92
        }
        
        # Mock de l'action suivante
        mock_workflow_pipeline.get_next_action.return_value = {
            "edge_id": "edge_1",
            "action": {"type": "click", "target": "button"},
            "target_node": "node_2",
            "confidence": 0.95
        }
        
        # Mock du workflow
        mock_workflow = Mock(spec=Workflow)
        mock_edge = Mock(spec=WorkflowEdge)
        mock_edge.edge_id = "edge_1"
        mock_edge.from_node = "node_1"
        mock_edge.to_node = "node_2"
        mock_workflow.edges = [mock_edge]
        mock_workflow_pipeline.load_workflow.return_value = mock_workflow
        
        # Mock du résultat d'exécution
        mock_execution_result = Mock(spec=ExecutionResult)
        mock_execution_result.status = ExecutionStatus.SUCCESS
        mock_execution_result.message = "Action executed successfully"
        mock_execution_result.duration_ms = 150.0
        mock_execution_result.target_resolved = None
        mock_execution_result.error = None
        mock_workflow_pipeline.action_executor.execute_edge.return_value = mock_execution_result
        
        # Créer l'instance enhanced
        enhanced = WorkflowPipelineEnhanced()
        
        # Lier les méthodes du pipeline mock
        enhanced.match_current_state = mock_workflow_pipeline.match_current_state
        enhanced.get_next_action = mock_workflow_pipeline.get_next_action
        enhanced.load_workflow = mock_workflow_pipeline.load_workflow
        enhanced.action_executor = mock_workflow_pipeline.action_executor
        enhanced.error_handler = mock_workflow_pipeline.error_handler
        
        # Act
        result = enhanced.execute_workflow_step_enhanced(
            workflow_id=workflow_id,
            current_state=mock_screen_state,
            context={"test_context": "value"}
        )
        
        # Assert
        assert isinstance(result, WorkflowExecutionResult)
        assert result.success is True
        assert result.status == StepExecutionStatus.SUCCESS
        assert result.workflow_id == workflow_id
        assert result.execution_id is not None
        assert result.correlation_id is not None
        assert result.correlation_id != result.execution_id  # Doivent être différents
        
        # Vérifier les métadonnées de performance
        assert result.performance_metrics is not None
        assert result.performance_metrics.total_execution_time_ms > 0
        assert result.performance_metrics.state_matching_time_ms >= 0
        assert result.performance_metrics.action_execution_time_ms >= 0
        
        # Vérifier les détails d'exécution
        assert "action_confidence" in result.execution_details
        assert "match_confidence" in result.execution_details
        assert "execution_context" in result.execution_details
        assert result.execution_details["execution_context"]["test_context"] == "value"
        
        # Vérifier l'action exécutée
        assert result.action_executed is not None
        assert result.action_executed["type"] == "click"
        assert result.action_executed["execution_status"] == ExecutionStatus.SUCCESS.value
        
        # Vérifier le match result
        assert result.match_result is not None
        assert result.match_result["node_id"] == "node_1"
        assert result.match_result["confidence"] == 0.92
    
    def test_execute_workflow_step_enhanced_no_match_returns_recovery_info(self, mock_workflow_pipeline, mock_screen_state):
        """Test que execute_workflow_step_enhanced gère correctement l'absence de match avec récupération"""
        # Arrange
        workflow_id = "test_workflow"
        
        # Mock du match result (pas de match)
        mock_workflow_pipeline.match_current_state.return_value = None
        
        # Mock du workflow pour la récupération
        mock_workflow = Mock(spec=Workflow)
        mock_workflow.nodes = []
        mock_workflow_pipeline.load_workflow.return_value = mock_workflow
        
        # Mock de la récupération
        mock_recovery_result = Mock(spec=RecoveryResult)
        mock_recovery_result.strategy_used = RecoveryStrategy.HIERARCHICAL_MATCHING
        mock_recovery_result.message = "Applied hierarchical matching fallback"
        mock_recovery_result.success = False
        mock_workflow_pipeline.error_handler.handle_matching_failure.return_value = mock_recovery_result
        
        # Créer l'instance enhanced
        enhanced = WorkflowPipelineEnhanced()
        
        # Lier les méthodes du pipeline mock
        enhanced.match_current_state = mock_workflow_pipeline.match_current_state
        enhanced.load_workflow = mock_workflow_pipeline.load_workflow
        enhanced.error_handler = mock_workflow_pipeline.error_handler
        
        # Act
        result = enhanced.execute_workflow_step_enhanced(
            workflow_id=workflow_id,
            current_state=mock_screen_state
        )
        
        # Assert
        assert isinstance(result, WorkflowExecutionResult)
        assert result.success is False
        assert result.status == StepExecutionStatus.NO_MATCH
        assert result.workflow_id == workflow_id
        assert result.execution_id is not None
        assert result.correlation_id is not None
        
        # Vérifier les informations de récupération
        assert result.recovery_applied is not None
        assert result.recovery_applied.strategy == RecoveryStrategy.HIERARCHICAL_MATCHING.value
        assert result.recovery_applied.message == "Applied hierarchical matching fallback"
        assert result.recovery_applied.success is False
        assert result.recovery_applied.attempts == 1
        assert result.recovery_applied.duration_ms >= 0
        
        # Vérifier les métriques de performance
        assert result.performance_metrics is not None
        assert result.performance_metrics.total_execution_time_ms > 0
        assert result.performance_metrics.state_matching_time_ms >= 0
        assert result.performance_metrics.error_handling_time_ms >= 0
        
        # Vérifier que l'état actuel est préservé
        assert result.current_state == mock_screen_state
    
    def test_execute_workflow_step_enhanced_workflow_complete(self, mock_workflow_pipeline, mock_screen_state):
        """Test que execute_workflow_step_enhanced gère correctement la fin de workflow"""
        # Arrange
        workflow_id = "test_workflow"
        
        # Mock du match result
        mock_workflow_pipeline.match_current_state.return_value = {
            "node_id": "final_node",
            "workflow_id": workflow_id,
            "confidence": 0.95
        }
        
        # Mock de l'action suivante (pas d'action = workflow terminé)
        mock_workflow_pipeline.get_next_action.return_value = None
        
        # Créer l'instance enhanced
        enhanced = WorkflowPipelineEnhanced()
        
        # Lier les méthodes du pipeline mock
        enhanced.match_current_state = mock_workflow_pipeline.match_current_state
        enhanced.get_next_action = mock_workflow_pipeline.get_next_action
        
        # Act
        result = enhanced.execute_workflow_step_enhanced(
            workflow_id=workflow_id,
            current_state=mock_screen_state
        )
        
        # Assert
        assert isinstance(result, WorkflowExecutionResult)
        assert result.success is True
        assert result.status == StepExecutionStatus.WORKFLOW_COMPLETE
        assert result.workflow_id == workflow_id
        assert result.current_node == "final_node"
        assert result.execution_id is not None
        assert result.correlation_id is not None
        
        # Vérifier les métriques de performance
        assert result.performance_metrics is not None
        assert result.performance_metrics.total_execution_time_ms > 0
        assert result.performance_metrics.state_matching_time_ms >= 0
        
        # Vérifier le match result
        assert result.match_result is not None
        assert result.match_result["node_id"] == "final_node"
    
    def test_execute_workflow_step_enhanced_exception_handling(self, mock_workflow_pipeline, mock_screen_state):
        """Test que execute_workflow_step_enhanced gère correctement les exceptions"""
        # Arrange
        workflow_id = "test_workflow"
        
        # Mock qui lève une exception
        mock_workflow_pipeline.match_current_state.side_effect = Exception("Test exception")
        
        # Mock de l'error handler
        mock_workflow_pipeline.error_handler.error_history = []
        mock_workflow_pipeline.error_handler._log_error = Mock()
        
        # Créer l'instance enhanced
        enhanced = WorkflowPipelineEnhanced()
        
        # Lier les méthodes du pipeline mock
        enhanced.match_current_state = mock_workflow_pipeline.match_current_state
        enhanced.error_handler = mock_workflow_pipeline.error_handler
        
        # Act
        result = enhanced.execute_workflow_step_enhanced(
            workflow_id=workflow_id,
            current_state=mock_screen_state,
            context={"test": "context"}
        )
        
        # Assert
        assert isinstance(result, WorkflowExecutionResult)
        assert result.success is False
        assert result.status == StepExecutionStatus.EXECUTION_ERROR
        assert result.workflow_id == workflow_id
        assert result.error == "Test exception"
        assert result.execution_id is not None
        assert result.correlation_id is not None
        
        # Vérifier les détails d'exception
        assert "exception_type" in result.execution_details
        assert result.execution_details["exception_type"] == "Exception"
        assert "execution_context" in result.execution_details
        
        # Vérifier que l'error handler a été appelé
        assert len(mock_workflow_pipeline.error_handler.error_history) == 1
        mock_workflow_pipeline.error_handler._log_error.assert_called_once()
    
    def test_migrate_execute_workflow_step_replaces_method(self):
        """Test que migrate_execute_workflow_step remplace correctement la méthode"""
        # Arrange
        mock_pipeline = Mock(spec=WorkflowPipeline)
        original_method = Mock()
        mock_pipeline.execute_workflow_step = original_method
        
        # Act
        migrated_pipeline = migrate_execute_workflow_step(mock_pipeline)
        
        # Assert
        assert migrated_pipeline == mock_pipeline  # Même instance
        assert hasattr(mock_pipeline, '_execute_workflow_step_legacy')
        assert mock_pipeline._execute_workflow_step_legacy == original_method
        assert mock_pipeline.execute_workflow_step != original_method  # Méthode remplacée
    
    def test_serialization_preserves_all_metadata(self, mock_workflow_pipeline, mock_screen_state):
        """Test que la sérialisation préserve toutes les métadonnées"""
        # Arrange
        workflow_id = "test_workflow"
        
        # Mock du match result
        mock_workflow_pipeline.match_current_state.return_value = {
            "node_id": "node_1",
            "workflow_id": workflow_id,
            "confidence": 0.92
        }
        
        # Mock de l'action suivante
        mock_workflow_pipeline.get_next_action.return_value = {
            "edge_id": "edge_1",
            "action": {"type": "click", "target": "button"},
            "target_node": "node_2",
            "confidence": 0.95
        }
        
        # Mock du workflow
        mock_workflow = Mock(spec=Workflow)
        mock_edge = Mock(spec=WorkflowEdge)
        mock_edge.edge_id = "edge_1"
        mock_edge.from_node = "node_1"
        mock_edge.to_node = "node_2"
        mock_workflow.edges = [mock_edge]
        mock_workflow_pipeline.load_workflow.return_value = mock_workflow
        
        # Mock du résultat d'exécution
        mock_execution_result = Mock(spec=ExecutionResult)
        mock_execution_result.status = ExecutionStatus.SUCCESS
        mock_execution_result.message = "Action executed successfully"
        mock_execution_result.duration_ms = 150.0
        mock_execution_result.target_resolved = None
        mock_execution_result.error = None
        mock_workflow_pipeline.action_executor.execute_edge.return_value = mock_execution_result
        
        # Créer l'instance enhanced
        enhanced = WorkflowPipelineEnhanced()
        
        # Lier les méthodes du pipeline mock
        enhanced.match_current_state = mock_workflow_pipeline.match_current_state
        enhanced.get_next_action = mock_workflow_pipeline.get_next_action
        enhanced.load_workflow = mock_workflow_pipeline.load_workflow
        enhanced.action_executor = mock_workflow_pipeline.action_executor
        enhanced.error_handler = mock_workflow_pipeline.error_handler
        
        # Act
        result = enhanced.execute_workflow_step_enhanced(
            workflow_id=workflow_id,
            current_state=mock_screen_state,
            context={"custom_data": "test_value"}
        )
        
        # Sérialiser
        result_dict = result.to_dict()
        
        # Assert - Vérifier que toutes les métadonnées critiques sont présentes
        assert "execution_id" in result_dict
        assert "workflow_id" in result_dict
        assert "correlation_id" in result_dict
        assert "success" in result_dict
        assert "status" in result_dict
        assert "performance_metrics" in result_dict
        assert "match_result" in result_dict
        assert "action_executed" in result_dict
        assert "execution_details" in result_dict
        
        # Vérifier les métriques de performance
        perf_metrics = result_dict["performance_metrics"]
        assert "total_execution_time_ms" in perf_metrics
        assert "state_matching_time_ms" in perf_metrics
        assert "action_execution_time_ms" in perf_metrics
        
        # Vérifier les détails d'exécution personnalisés
        exec_details = result_dict["execution_details"]
        assert "action_confidence" in exec_details
        assert "match_confidence" in exec_details
        assert "execution_context" in exec_details
        assert exec_details["execution_context"]["custom_data"] == "test_value"