#!/usr/bin/env python3
"""
Test Cases for BDR Agent Factory Examples

Comprehensive test suite for text classification, fraud detection,
and integration examples.
"""

import pytest
import json
from datetime import datetime

# Import example implementations
try:
    from text_classification_example import TextClassificationCapability, ClassificationResult
    from fraud_detection_example import FraudDetectionCapability, FraudDetectionResult
    from integration_example import ClaimsProcessingWorkflow, ClaimProcessingResult
    EXAMPLES_AVAILABLE = True
except ImportError:
    EXAMPLES_AVAILABLE = False
    pytest.skip("Example implementations not available", allow_module_level=True)


class TestTextClassification:
    """Test cases for text classification capability"""
    
    @pytest.fixture
    def classifier(self):
        """Create text classifier instance"""
        return TextClassificationCapability(enable_audit=True)
    
    def test_initialization(self, classifier):
        """Test classifier initialization"""
        assert classifier is not None
        assert classifier.CAPABILITY_ID == "cap_text_classification"
        assert classifier.VERSION == "2.1.0"
        assert classifier.enable_audit is True
    
    def test_property_damage_classification(self, classifier):
        """Test classification of property damage claim"""
        text = "Water damage to basement after heavy rain and flooding"
        result = classifier.classify(text=text, explain=True)
        
        assert isinstance(result, ClassificationResult)
        assert result.predicted_class == "property_damage"
        assert result.confidence > 0.7
        assert result.explanation is not None
        assert result.audit_id is not None
    
    def test_auto_accident_classification(self, classifier):
        """Test classification of auto accident claim"""
        text = "Rear-end collision on highway during rush hour traffic"
        result = classifier.classify(text=text, explain=True)
        
        assert result.predicted_class == "auto_accident"
        assert result.confidence > 0.7
        assert 'collision' in text.lower() or 'accident' in text.lower()
    
    def test_health_claim_classification(self, classifier):
        """Test classification of health claim"""
        text = "Patient underwent surgery at hospital for medical treatment"
        result = classifier.classify(text=text, explain=True)
        
        assert result.predicted_class == "health_claim"
        assert result.confidence > 0.7
    
    def test_liability_classification(self, classifier):
        """Test classification of liability claim"""
        text = "Customer slipped and fell in store, sustained injury"
        result = classifier.classify(text=text, explain=True)
        
        assert result.predicted_class == "liability"
        assert result.confidence > 0.7
    
    def test_empty_input_validation(self, classifier):
        """Test that empty input raises ValueError"""
        with pytest.raises(ValueError, match="non-empty string"):
            classifier.classify(text="")
    
    def test_long_input_validation(self, classifier):
        """Test that excessively long input raises ValueError"""
        long_text = "word " * 10000
        with pytest.raises(ValueError, match="maximum length"):
            classifier.classify(text=long_text)
    
    def test_malicious_input_validation(self, classifier):
        """Test that malicious input is rejected"""
        malicious_text = "<script>alert('xss')</script>"
        with pytest.raises(ValueError, match="malicious content"):
            classifier.classify(text=malicious_text)
    
    def test_confidence_threshold(self, classifier):
        """Test confidence threshold filtering"""
        text = "Ambiguous claim description"
        result = classifier.classify(
            text=text,
            confidence_threshold=0.99  # Very high threshold
        )
        
        # With high threshold, uncertain claims should be marked
        assert result is not None
    
    def test_explanation_generation(self, classifier):
        """Test that explanations are generated correctly"""
        text = "Water damage to basement after storm"
        result = classifier.classify(text=text, explain=True)
        
        assert result.explanation is not None
        assert 'method' in result.explanation
        assert 'local_explanation' in result.explanation
        assert 'key_features' in result.explanation['local_explanation']
        assert len(result.explanation['local_explanation']['key_features']) > 0
    
    def test_audit_trail_creation(self, classifier):
        """Test that audit trail is created"""
        text = "Test claim description"
        result = classifier.classify(
            text=text,
            audit_trail=True,
            user_id="test_user"
        )
        
        assert result.audit_id is not None
        
        # Retrieve audit record
        audit_record = classifier.get_audit_record(result.audit_id)
        assert audit_record is not None
        assert audit_record['user_id'] == 'test_user'
        assert audit_record['capability_id'] == 'cap_text_classification'
    
    def test_batch_classification(self, classifier):
        """Test batch classification"""
        texts = [
            "Water damage to property",
            "Car accident on highway",
            "Medical treatment at hospital"
        ]
        
        results = classifier.batch_classify(texts=texts, explain=False)
        
        assert len(results) == 3
        assert all(isinstance(r, ClassificationResult) for r in results)
        assert results[0].predicted_class == "property_damage"
        assert results[1].predicted_class == "auto_accident"
        assert results[2].predicted_class == "health_claim"
    
    def test_metadata_structure(self, classifier):
        """Test that metadata has correct structure"""
        text = "Test claim"
        result = classifier.classify(text=text)
        
        assert result.metadata is not None
        assert 'capability_id' in result.metadata
        assert 'version' in result.metadata
        assert 'processing_time_ms' in result.metadata
        assert 'timestamp' in result.metadata
        assert 'compliance_flags' in result.metadata
    
    def test_compliance_flags(self, classifier):
        """Test that compliance flags are set correctly"""
        text = "Test claim"
        result = classifier.classify(text=text, explain=True, audit_trail=True)
        
        flags = result.metadata['compliance_flags']
        assert flags['explainable'] is True
        assert flags['auditable'] is True
        assert flags['gdpr_compliant'] is True
        assert flags['ifrs17_compliant'] is True
    
    def test_result_serialization(self, classifier):
        """Test that results can be serialized to JSON"""
        text = "Test claim"
        result = classifier.classify(text=text)
        
        result_dict = result.to_dict()
        json_str = json.dumps(result_dict)
        
        assert json_str is not None
        assert len(json_str) > 0


class TestFraudDetection:
    """Test cases for fraud detection capability"""
    
    @pytest.fixture
    def fraud_detector(self):
        """Create fraud detector instance"""
        return FraudDetectionCapability(enable_audit=True)
    
    def test_initialization(self, fraud_detector):
        """Test fraud detector initialization"""
        assert fraud_detector is not None
        assert fraud_detector.CAPABILITY_ID == "cap_fraud_detection"
        assert fraud_detector.VERSION == "1.5.0"
    
    def test_low_risk_claim(self, fraud_detector):
        """Test detection of low-risk claim"""
        claim_data = {
            'claim_id': 'TEST-001',
            'claim_amount': 2000,
            'claim_type': 'auto_accident',
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2023-01-01T00:00:00Z',
            'claimant_history': {
                'previous_claims': 0,
                'years_as_customer': 3
            },
            'witnesses': 2
        }
        
        result = fraud_detector.detect(claim_data=claim_data, explain=True)
        
        assert isinstance(result, FraudDetectionResult)
        assert result.risk_level == 'low'
        assert result.fraud_score < 0.3
        assert result.recommendation == 'approve'
    
    def test_high_risk_claim(self, fraud_detector):
        """Test detection of high-risk claim"""
        claim_data = {
            'claim_id': 'TEST-002',
            'claim_amount': 100000,  # High amount
            'claim_type': 'property_damage',
            'claim_date': '2026-01-03T23:00:00Z',  # Late night
            'policy_start_date': '2025-12-28T00:00:00Z',  # Recent policy
            'claimant_history': {
                'previous_claims': 5,  # Frequent claims
                'years_as_customer': 1
            },
            'witnesses': 0,  # No witnesses
            'incident_details': 'Fire'  # Very short description
        }
        
        result = fraud_detector.detect(claim_data=claim_data, explain=True)
        
        assert result.risk_level in ['high', 'critical']
        assert result.fraud_score > 0.6
        assert result.recommendation in ['escalate', 'reject']
        assert len(result.risk_factors) > 0
    
    def test_medium_risk_claim(self, fraud_detector):
        """Test detection of medium-risk claim"""
        claim_data = {
            'claim_id': 'TEST-003',
            'claim_amount': 25000,
            'claim_type': 'health_claim',
            'claim_date': '2026-01-03T14:00:00Z',
            'policy_start_date': '2024-01-01T00:00:00Z',
            'claimant_history': {
                'previous_claims': 2,
                'years_as_customer': 2
            },
            'witnesses': 1
        }
        
        result = fraud_detector.detect(claim_data=claim_data, explain=True)
        
        assert result.risk_level in ['low', 'medium']
        assert result.recommendation in ['approve', 'review']
    
    def test_missing_required_fields(self, fraud_detector):
        """Test that missing required fields raise ValueError"""
        incomplete_claim = {
            'claim_id': 'TEST-004'
            # Missing claim_amount and claim_type
        }
        
        with pytest.raises(ValueError, match="Missing required field"):
            fraud_detector.detect(claim_data=incomplete_claim)
    
    def test_invalid_claim_amount(self, fraud_detector):
        """Test that invalid claim amount raises ValueError"""
        invalid_claim = {
            'claim_id': 'TEST-005',
            'claim_amount': -1000,  # Negative amount
            'claim_type': 'auto_accident'
        }
        
        with pytest.raises(ValueError, match="cannot be negative"):
            fraud_detector.detect(claim_data=invalid_claim)
    
    def test_risk_factor_detection(self, fraud_detector):
        """Test that risk factors are detected correctly"""
        claim_data = {
            'claim_id': 'TEST-006',
            'claim_amount': 75000,  # Should trigger high_claim_amount
            'claim_type': 'property_damage',
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2025-12-20T00:00:00Z',  # Should trigger recent_policy
            'claimant_history': {
                'previous_claims': 4,  # Should trigger frequent_claims
                'years_as_customer': 1
            }
        }
        
        result = fraud_detector.detect(claim_data=claim_data, explain=True)
        
        # Check that multiple risk factors were detected
        assert len(result.risk_factors) >= 2
        
        # Check for specific risk factors
        factor_types = [f['factor'] for f in result.risk_factors]
        assert 'high_claim_amount' in factor_types
    
    def test_explanation_generation(self, fraud_detector):
        """Test that explanations are generated"""
        claim_data = {
            'claim_id': 'TEST-007',
            'claim_amount': 10000,
            'claim_type': 'auto_accident'
        }
        
        result = fraud_detector.detect(claim_data=claim_data, explain=True)
        
        assert result.explanation is not None
        assert 'human_readable_summary' in result.explanation
        assert 'contributing_factors' in result.explanation
        assert 'recommendations' in result.explanation
    
    def test_audit_trail_creation(self, fraud_detector):
        """Test that audit trail is created"""
        claim_data = {
            'claim_id': 'TEST-008',
            'claim_amount': 5000,
            'claim_type': 'property_damage'
        }
        
        result = fraud_detector.detect(
            claim_data=claim_data,
            audit_trail=True,
            user_id="test_adjuster"
        )
        
        assert result.audit_id is not None
        
        # Retrieve audit record
        audit_record = fraud_detector.get_audit_record(result.audit_id)
        assert audit_record is not None
        assert audit_record['user_id'] == 'test_adjuster'
        assert audit_record['claim_id'] == 'TEST-008'
    
    def test_compliance_flags(self, fraud_detector):
        """Test that compliance flags are set"""
        claim_data = {
            'claim_id': 'TEST-009',
            'claim_amount': 5000,
            'claim_type': 'auto_accident'
        }
        
        result = fraud_detector.detect(claim_data=claim_data, explain=True)
        
        flags = result.metadata['compliance_flags']
        assert flags['aml_compliant'] is True
        assert flags['gdpr_compliant'] is True
    
    def test_result_serialization(self, fraud_detector):
        """Test that results can be serialized to JSON"""
        claim_data = {
            'claim_id': 'TEST-010',
            'claim_amount': 5000,
            'claim_type': 'auto_accident'
        }
        
        result = fraud_detector.detect(claim_data=claim_data)
        
        result_dict = result.to_dict()
        json_str = json.dumps(result_dict)
        
        assert json_str is not None
        assert len(json_str) > 0


class TestIntegration:
    """Test cases for integrated workflow"""
    
    @pytest.fixture
    def workflow(self):
        """Create workflow instance"""
        return ClaimsProcessingWorkflow()
    
    def test_initialization(self, workflow):
        """Test workflow initialization"""
        assert workflow is not None
        assert workflow.text_classifier is not None
        assert workflow.fraud_detector is not None
    
    def test_simple_claim_processing(self, workflow):
        """Test processing of simple claim"""
        claim_data = {
            'claim_id': 'INT-001',
            'description': 'Minor car accident in parking lot',
            'claim_amount': 3000,
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2023-01-01T00:00:00Z',
            'claimant_history': {
                'previous_claims': 0,
                'years_as_customer': 3
            },
            'witnesses': 2,
            'third_party_involved': True
        }
        
        result = workflow.process_claim(claim_data, user_id="test_user")
        
        assert isinstance(result, ClaimProcessingResult)
        assert result.claim_id == 'INT-001'
        assert result.final_decision in ['approve', 'review', 'escalate', 'reject']
        assert len(result.audit_trail) >= 2  # At least classification and fraud detection
    
    def test_high_risk_claim_processing(self, workflow):
        """Test processing of high-risk claim"""
        claim_data = {
            'claim_id': 'INT-002',
            'description': 'Total loss fire damage',
            'claim_amount': 150000,
            'claim_date': '2026-01-03T23:00:00Z',
            'policy_start_date': '2025-12-28T00:00:00Z',
            'claimant_history': {
                'previous_claims': 5,
                'years_as_customer': 1
            },
            'witnesses': 0,
            'third_party_involved': False
        }
        
        result = workflow.process_claim(claim_data, user_id="test_user")
        
        # High-risk claims should be escalated or rejected
        assert result.final_decision in ['escalate', 'reject']
        assert result.fraud_detection['risk_level'] in ['high', 'critical']
    
    def test_batch_processing(self, workflow):
        """Test batch processing of multiple claims"""
        claims = [
            {
                'claim_id': f'BATCH-{i:03d}',
                'description': 'Test claim description',
                'claim_amount': 5000,
                'claim_date': '2026-01-03T10:00:00Z',
                'policy_start_date': '2023-01-01T00:00:00Z',
                'claimant_history': {'previous_claims': 0, 'years_as_customer': 3}
            }
            for i in range(5)
        ]
        
        results = workflow.batch_process_claims(claims, user_id="batch_user")
        
        assert len(results) == 5
        assert all(isinstance(r, ClaimProcessingResult) for r in results)
        assert all(r.final_decision in ['approve', 'review', 'escalate', 'reject'] for r in results)
    
    def test_audit_trail_completeness(self, workflow):
        """Test that audit trail captures all steps"""
        claim_data = {
            'claim_id': 'AUDIT-001',
            'description': 'Test claim for audit trail',
            'claim_amount': 5000,
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2023-01-01T00:00:00Z',
            'claimant_history': {'previous_claims': 0, 'years_as_customer': 3}
        }
        
        result = workflow.process_claim(claim_data, user_id="audit_user")
        
        # Check audit trail has all expected steps
        steps = [entry['step'] for entry in result.audit_trail]
        assert 'classification' in steps
        assert 'fraud_detection' in steps
        assert 'final_decision' in steps
    
    def test_decision_logic_approve(self, workflow):
        """Test that low-risk claims are approved"""
        claim_data = {
            'claim_id': 'DECISION-001',
            'description': 'Minor fender bender',
            'claim_amount': 2000,
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2022-01-01T00:00:00Z',
            'claimant_history': {'previous_claims': 0, 'years_as_customer': 4},
            'witnesses': 2
        }
        
        result = workflow.process_claim(claim_data)
        
        # Low-risk, low-amount claims should be approved
        assert result.final_decision == 'approve'
    
    def test_decision_logic_review(self, workflow):
        """Test that medium-risk claims require review"""
        claim_data = {
            'claim_id': 'DECISION-002',
            'description': 'Medical treatment claim',
            'claim_amount': 60000,  # High amount triggers review
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2023-01-01T00:00:00Z',
            'claimant_history': {'previous_claims': 1, 'years_as_customer': 3}
        }
        
        result = workflow.process_claim(claim_data)
        
        # High-amount claims should require review
        assert result.final_decision in ['review', 'escalate']
    
    def test_metadata_structure(self, workflow):
        """Test that metadata has correct structure"""
        claim_data = {
            'claim_id': 'META-001',
            'description': 'Test claim',
            'claim_amount': 5000,
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2023-01-01T00:00:00Z',
            'claimant_history': {'previous_claims': 0, 'years_as_customer': 3}
        }
        
        result = workflow.process_claim(claim_data)
        
        assert result.metadata is not None
        assert 'workflow_version' in result.metadata
        assert 'processing_time_ms' in result.metadata
        assert 'compliance_flags' in result.metadata
    
    def test_result_serialization(self, workflow):
        """Test that workflow results can be serialized"""
        claim_data = {
            'claim_id': 'SERIAL-001',
            'description': 'Test claim',
            'claim_amount': 5000,
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2023-01-01T00:00:00Z',
            'claimant_history': {'previous_claims': 0, 'years_as_customer': 3}
        }
        
        result = workflow.process_claim(claim_data)
        
        result_dict = result.to_dict()
        json_str = json.dumps(result_dict)
        
        assert json_str is not None
        assert len(json_str) > 0


class TestPerformance:
    """Performance and benchmark tests"""
    
    def test_classification_latency(self):
        """Test that classification meets latency SLA"""
        classifier = TextClassificationCapability()
        
        text = "Test claim description for performance testing"
        result = classifier.classify(text=text)
        
        # Should complete in under 500ms (generous for mock implementation)
        assert result.metadata['processing_time_ms'] < 500
    
    def test_fraud_detection_latency(self):
        """Test that fraud detection meets latency SLA"""
        fraud_detector = FraudDetectionCapability()
        
        claim_data = {
            'claim_id': 'PERF-001',
            'claim_amount': 5000,
            'claim_type': 'auto_accident'
        }
        
        result = fraud_detector.detect(claim_data=claim_data)
        
        # Should complete in under 300ms
        assert result.metadata['processing_time_ms'] < 300
    
    def test_workflow_latency(self):
        """Test that complete workflow meets latency SLA"""
        workflow = ClaimsProcessingWorkflow()
        
        claim_data = {
            'claim_id': 'PERF-002',
            'description': 'Performance test claim',
            'claim_amount': 5000,
            'claim_date': '2026-01-03T10:00:00Z',
            'policy_start_date': '2023-01-01T00:00:00Z',
            'claimant_history': {'previous_claims': 0, 'years_as_customer': 3}
        }
        
        result = workflow.process_claim(claim_data)
        
        # Complete workflow should finish in under 1000ms
        assert result.processing_time_ms < 1000


if __name__ == "__main__":
    # Run tests with pytest
    pytest.main([__file__, "-v", "--tb=short"])