# fmt: off """ Error Handlers - Comprehensive error handling and fallbacks This module provides robust error handling, graceful degradation, and fallback mechanisms for the guardrails system. Updated: October 18, 2025 - CI/CD format fix attempt """ import logging from dataclasses import dataclass from typing import Any, Dict, List, Optional logger = logging.getLogger(__name__) class GuardrailsError(Exception): """Base exception for guardrails-related errors.""" def __init__( self, message: str, error_type: str = "unknown", details: Optional[Dict[str, Any]] = None, ): super().__init__(message) self.message = message self.error_type = error_type self.details = details or {} @dataclass class ErrorContext: """Context information for error handling.""" component: str operation: str input_data: Dict[str, Any] error_message: str error_type: str timestamp: str recovery_attempted: bool = False recovery_successful: bool = False class ErrorHandler: """ Comprehensive error handling system for guardrails. Provides: - Graceful error recovery - Fallback mechanisms - Circuit breaker patterns - Detailed error logging and metrics """ def __init__(self, circuit_breaker_threshold: int = 5): self.error_history: List[ErrorContext] = [] self.circuit_breakers: Dict[str, Dict[str, Any]] = {} self.circuit_breaker_threshold = circuit_breaker_threshold def handle_error( self, error: Exception, component: str, operation: str, input_data: Dict[str, Any], recovery_strategy: Optional[str] = None, ) -> Dict[str, Any]: """ Handle an error with appropriate strategy. Args: error: The exception that occurred component: Component where error occurred operation: Operation being performed input_data: Input data when error occurred recovery_strategy: Strategy to use for recovery Returns: Dictionary with error handling results """ from datetime import datetime error_context = ErrorContext( component=component, operation=operation, input_data=input_data, error_message=str(error), error_type=type(error).__name__, timestamp=datetime.now().isoformat(), ) # Log the error logger.error( f"Error in {component}.{operation}: {error_context.error_message}", extra={ "component": component, "operation": operation, "error_type": error_context.error_type, "details": error_context.input_data, }, ) # Update circuit breaker self._update_circuit_breaker(component) # Try recovery if not in circuit breaker state recovery_result = None if not self._is_circuit_breaker_open(component): recovery_result = self._attempt_recovery( error_context, recovery_strategy ) # Store error in history self.error_history.append(error_context) # Maintain history size (keep last 1000 errors) if len(self.error_history) > 1000: self.error_history = self.error_history[-1000:] return { "error_handled": True, "error_context": error_context, "recovery_attempted": recovery_result is not None, "recovery_successful": recovery_result.get("success", False) if recovery_result else False, "circuit_breaker_open": self._is_circuit_breaker_open(component), "fallback_available": self._has_fallback(component, operation), } def _attempt_recovery( self, error_context: ErrorContext, strategy: Optional[str] = None ) -> Optional[Dict[str, Any]]: """Attempt to recover from error using specified strategy.""" error_context.recovery_attempted = True if strategy == "retry": return self._retry_operation(error_context) elif strategy == "fallback": return self._use_fallback(error_context) elif strategy == "degrade": return self._graceful_degradation(error_context) else: # Auto-select strategy based on error type return self._auto_recovery(error_context) def _retry_operation(self, error_context: ErrorContext) -> Dict[str, Any]: """Attempt to retry the failed operation.""" try: # This would implement actual retry logic # For now, we simulate a recovery attempt logger.info( f"Retrying operation {error_context.operation} in {error_context.component}" ) # Simulate retry success/failure import random success = random.random() > 0.3 # 70% success rate for simulation if success: error_context.recovery_successful = True logger.info(f"Retry successful for {error_context.component}.{error_context.operation}") else: logger.warning(f"Retry failed for {error_context.component}.{error_context.operation}") return {"success": success, "strategy": "retry", "attempts": 1} except Exception as e: logger.error(f"Retry operation failed: {e}") return {"success": False, "strategy": "retry", "error": str(e)} def _use_fallback(self, error_context: ErrorContext) -> Dict[str, Any]: """Use fallback mechanism for the failed operation.""" try: fallback_response = self._generate_fallback_response(error_context) error_context.recovery_successful = True logger.info( f"Fallback used for {error_context.component}.{error_context.operation}" ) return { "success": True, "strategy": "fallback", "response": fallback_response, } except Exception as e: logger.error(f"Fallback failed: {e}") return {"success": False, "strategy": "fallback", "error": str(e)} def _graceful_degradation(self, error_context: ErrorContext) -> Dict[str, Any]: """Implement graceful degradation.""" try: degraded_response = self._generate_degraded_response(error_context) error_context.recovery_successful = True logger.info( f"Graceful degradation for {error_context.component}.{error_context.operation}" ) return { "success": True, "strategy": "degrade", "response": degraded_response, } except Exception as e: logger.error(f"Graceful degradation failed: {e}") return {"success": False, "strategy": "degrade", "error": str(e)} def _auto_recovery(self, error_context: ErrorContext) -> Dict[str, Any]: """Auto-select recovery strategy based on error context.""" # Select strategy based on error type and component if error_context.error_type in ["ConnectionError", "TimeoutError"]: return self._retry_operation(error_context) elif error_context.component in ["llm", "vector_store"]: return self._use_fallback(error_context) else: return self._graceful_degradation(error_context) def _generate_fallback_response(self, error_context: ErrorContext) -> Dict[str, Any]: """Generate a fallback response for the failed operation.""" if error_context.component == "llm": return { "response": "I apologize, but I'm experiencing technical difficulties. Please try your question again or rephrase it.", "confidence": 0.1, "source": "fallback_handler", "citations": [], } elif error_context.component == "vector_store": return { "documents": [], "scores": [], "message": "Search temporarily unavailable. Please try again.", } else: return { "result": None, "status": "error", "message": f"Service temporarily unavailable in {error_context.component}", } def _generate_degraded_response(self, error_context: ErrorContext) -> Dict[str, Any]: """Generate a degraded response with limited functionality.""" return { "result": "limited_functionality", "message": f"Operating in degraded mode for {error_context.component}", "available_operations": ["basic_query", "status_check"], "degradation_reason": error_context.error_message, } def _update_circuit_breaker(self, component: str) -> None: """Update circuit breaker state for component.""" from datetime import datetime, timedelta if component not in self.circuit_breakers: self.circuit_breakers[component] = { "failure_count": 0, "last_failure": None, "is_open": False, } breaker = self.circuit_breakers[component] breaker["failure_count"] += 1 breaker["last_failure"] = datetime.now() # Open circuit breaker if threshold exceeded if breaker["failure_count"] >= self.circuit_breaker_threshold: breaker["is_open"] = True logger.warning( f"Circuit breaker opened for {component} " f"(failures: {breaker['failure_count']})" ) # Auto-reset after 5 minutes if breaker["is_open"] and breaker["last_failure"]: if datetime.now() - breaker["last_failure"] > timedelta(minutes=5): breaker["is_open"] = False breaker["failure_count"] = 0 logger.info(f"Circuit breaker auto-reset for {component}") def _is_circuit_breaker_open(self, component: str) -> bool: """Check if circuit breaker is open for component.""" return self.circuit_breakers.get(component, {}).get("is_open", False) def _has_fallback(self, component: str, operation: str) -> bool: """Check if fallback is available for component/operation.""" fallback_components = ["llm", "vector_store", "guardrails"] return component in fallback_components def get_error_statistics(self) -> Dict[str, Any]: """Get comprehensive error statistics.""" if not self.error_history: return {"total_errors": 0, "component_errors": {}, "most_common_errors": []} total_errors = len(self.error_history) component_errors = {} error_types = {} for error in self.error_history: component = error.component error_type = error.error_type component_errors[component] = component_errors.get(component, 0) + 1 error_types[error_type] = error_types.get(error_type, 0) + 1 # Get most common errors most_common = sorted(error_types.items(), key=lambda x: x[1], reverse=True)[:5] # Component health status component_health = {} for component, breaker in self.circuit_breakers.items(): component_health[component] = { "status": "degraded" if breaker["is_open"] else "healthy", "failure_count": breaker["failure_count"], "is_circuit_breaker_open": breaker["is_open"], } return { "total_errors": total_errors, "component_errors": component_errors, "most_common_errors": most_common, "component_health": component_health, "circuit_breakers": { k: v["is_open"] for k, v in self.circuit_breakers.items() }, } def reset_circuit_breaker(self, component: str) -> bool: """Manually reset circuit breaker for component.""" if component in self.circuit_breakers: self.circuit_breakers[component] = { "failure_count": 0, "last_failure": None, "is_open": False, } logger.info(f"Circuit breaker reset for {component}") return True return False def clear_error_history(self) -> None: """Clear error history.""" self.error_history.clear() logger.info("Error history cleared") class FallbackResponseGenerator: """Generates fallback responses when primary systems fail.""" @staticmethod def generate_llm_fallback(query: str, context: Optional[Dict[str, Any]] = None) -> Dict[str, Any]: """Generate a fallback LLM response.""" fallback_responses = [ "I apologize, but I'm experiencing technical difficulties. Please try your question again.", "The service is temporarily unavailable. Please rephrase your question or try again later.", "I'm having trouble processing your request right now. Could you try a simpler question?", ] import random response = random.choice(fallback_responses) return { "response": response, "confidence": 0.1, "source": "fallback_generator", "citations": [], "fallback": True, } @staticmethod def generate_search_fallback(query: str) -> Dict[str, Any]: """Generate a fallback search response.""" return { "documents": [], "scores": [], "message": "Search service temporarily unavailable. Please try again later.", "fallback": True, } @staticmethod def generate_generic_fallback(operation: str, error_message: str) -> Dict[str, Any]: """Generate a generic fallback response.""" return { "result": None, "status": "service_unavailable", "message": f"The {operation} service is temporarily unavailable.", "error_summary": error_message, "fallback": True, "suggested_actions": [ "Please try again in a few moments", "Check your internet connection", "Contact support if the problem persists", ], } # fmt: on