Spaces:
Runtime error
Runtime error
File size: 6,421 Bytes
f83b968 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 |
from typing import Dict, Any, Optional
import json
import time
from datetime import datetime
from utils.log_manager import LogManager
class AnalyticsLogger:
"""Handles logging of analytics events and metrics"""
def __init__(self):
self.log_manager = LogManager()
self.logger = self.log_manager.get_analytics_logger("events")
self.metrics_logger = self.log_manager.get_analytics_logger("metrics")
def log_user_interaction(self,
user_id: str,
interaction_type: str,
agent_type: str,
duration: float,
success: bool,
details: Optional[Dict] = None):
"""Log user interaction events"""
event = {
"event_type": "user_interaction",
"user_id": user_id,
"interaction_type": interaction_type,
"agent_type": agent_type,
"duration": duration,
"success": success,
"timestamp": datetime.now().isoformat(),
"details": details or {}
}
self.logger.info(f"User Interaction: {json.dumps(event, indent=2)}")
def log_agent_performance(self,
agent_type: str,
operation: str,
response_time: float,
success: bool,
error: Optional[str] = None):
"""Log agent performance metrics"""
metric = {
"metric_type": "agent_performance",
"agent_type": agent_type,
"operation": operation,
"response_time": response_time,
"success": success,
"error": error,
"timestamp": datetime.now().isoformat()
}
self.metrics_logger.info(f"Agent Performance: {json.dumps(metric, indent=2)}")
def log_system_health(self,
cpu_usage: float,
memory_usage: float,
active_users: int,
active_sessions: int):
"""Log system health metrics"""
metric = {
"metric_type": "system_health",
"cpu_usage": cpu_usage,
"memory_usage": memory_usage,
"active_users": active_users,
"active_sessions": active_sessions,
"timestamp": datetime.now().isoformat()
}
self.metrics_logger.info(f"System Health: {json.dumps(metric, indent=2)}")
def log_error(self,
error_type: str,
error_message: str,
severity: str,
context: Optional[Dict] = None):
"""Log error events"""
event = {
"event_type": "error",
"error_type": error_type,
"error_message": error_message,
"severity": severity,
"context": context or {},
"timestamp": datetime.now().isoformat()
}
self.logger.error(f"Error Event: {json.dumps(event, indent=2)}")
def log_security_event(self,
event_type: str,
user_id: str,
success: bool,
details: Optional[Dict] = None):
"""Log security-related events"""
event = {
"event_type": "security",
"security_event_type": event_type,
"user_id": user_id,
"success": success,
"details": details or {},
"timestamp": datetime.now().isoformat()
}
self.logger.info(f"Security Event: {json.dumps(event, indent=2)}")
def log_model_performance(self,
model_name: str,
operation: str,
input_tokens: int,
output_tokens: int,
response_time: float,
success: bool):
"""Log AI model performance metrics"""
metric = {
"metric_type": "model_performance",
"model_name": model_name,
"operation": operation,
"input_tokens": input_tokens,
"output_tokens": output_tokens,
"response_time": response_time,
"success": success,
"timestamp": datetime.now().isoformat()
}
self.metrics_logger.info(f"Model Performance: {json.dumps(metric, indent=2)}")
def log_user_feedback(self,
user_id: str,
interaction_id: str,
rating: int,
feedback_text: Optional[str] = None):
"""Log user feedback"""
event = {
"event_type": "user_feedback",
"user_id": user_id,
"interaction_id": interaction_id,
"rating": rating,
"feedback_text": feedback_text,
"timestamp": datetime.now().isoformat()
}
self.logger.info(f"User Feedback: {json.dumps(event, indent=2)}")
def log_session_metrics(self,
session_id: str,
user_id: str,
session_type: str,
start_time: str,
end_time: str,
metrics: Dict[str, Any]):
"""Log session-specific metrics"""
session_data = {
"metric_type": "session_metrics",
"session_id": session_id,
"user_id": user_id,
"session_type": session_type,
"start_time": start_time,
"end_time": end_time,
"duration": self._calculate_duration(start_time, end_time),
"metrics": metrics,
"timestamp": datetime.now().isoformat()
}
self.metrics_logger.info(f"Session Metrics: {json.dumps(session_data, indent=2)}")
def _calculate_duration(self, start_time: str, end_time: str) -> float:
"""Calculate duration between two ISO format timestamps"""
start = datetime.fromisoformat(start_time)
end = datetime.fromisoformat(end_time)
return (end - start).total_seconds() |