rag_template / src /logging_config.py
Guilherme Favaron
Major update: Add hybrid search, reranking, multiple LLMs, and UI improvements
1b447de
"""
Configuração de logging estruturado
"""
import logging
import sys
import json
from datetime import datetime
from typing import Dict, Any, Optional
from pathlib import Path
class StructuredFormatter(logging.Formatter):
"""Formatter para logs estruturados em JSON"""
def format(self, record: logging.LogRecord) -> str:
"""
Formata log record como JSON estruturado
Args:
record: Registro de log
Returns:
String JSON formatada
"""
log_data = {
"timestamp": datetime.utcnow().isoformat() + "Z",
"level": record.levelname,
"logger": record.name,
"message": record.getMessage(),
"module": record.module,
"function": record.funcName,
"line": record.lineno
}
# Adiciona informações extras se existirem
if hasattr(record, "extra_data"):
log_data["extra"] = record.extra_data
# Adiciona informação de exceção se houver
if record.exc_info:
log_data["exception"] = self.formatException(record.exc_info)
return json.dumps(log_data, ensure_ascii=False)
class HumanReadableFormatter(logging.Formatter):
"""Formatter para logs legíveis por humanos"""
def __init__(self):
super().__init__(
fmt="%(asctime)s | %(levelname)-8s | %(name)s | %(message)s",
datefmt="%Y-%m-%d %H:%M:%S"
)
def setup_logger(
name: str,
level: str = "INFO",
log_file: Optional[str] = None,
structured: bool = False
) -> logging.Logger:
"""
Configura logger com formatação customizada
Args:
name: Nome do logger
level: Nível de log (DEBUG, INFO, WARNING, ERROR, CRITICAL)
log_file: Caminho do arquivo de log (opcional)
structured: Se True, usa formato JSON estruturado
Returns:
Logger configurado
"""
logger = logging.getLogger(name)
logger.setLevel(getattr(logging, level.upper()))
# Remove handlers existentes para evitar duplicação
logger.handlers.clear()
# Handler para console
console_handler = logging.StreamHandler(sys.stdout)
console_handler.setLevel(getattr(logging, level.upper()))
if structured:
console_handler.setFormatter(StructuredFormatter())
else:
console_handler.setFormatter(HumanReadableFormatter())
logger.addHandler(console_handler)
# Handler para arquivo se especificado
if log_file:
log_path = Path(log_file)
log_path.parent.mkdir(parents=True, exist_ok=True)
file_handler = logging.FileHandler(log_file, encoding="utf-8")
file_handler.setLevel(getattr(logging, level.upper()))
if structured:
file_handler.setFormatter(StructuredFormatter())
else:
file_handler.setFormatter(HumanReadableFormatter())
logger.addHandler(file_handler)
return logger
def log_with_context(
logger: logging.Logger,
level: str,
message: str,
**kwargs
) -> None:
"""
Loga mensagem com contexto adicional
Args:
logger: Logger a usar
level: Nível do log
message: Mensagem principal
**kwargs: Contexto adicional (session_id, user_id, etc)
"""
extra_record = type('obj', (object,), {'extra_data': kwargs})()
log_func = getattr(logger, level.lower())
log_func(message, extra={"extra_data": kwargs})
class PerformanceLogger:
"""Logger especializado para métricas de performance"""
def __init__(self, logger: logging.Logger):
self.logger = logger
self.metrics: Dict[str, list] = {}
def log_metric(
self,
operation: str,
duration_ms: float,
metadata: Optional[Dict[str, Any]] = None
) -> None:
"""
Registra métrica de performance
Args:
operation: Nome da operação
duration_ms: Duração em milissegundos
metadata: Informações adicionais
"""
metric_data = {
"operation": operation,
"duration_ms": duration_ms,
"timestamp": datetime.utcnow().isoformat() + "Z"
}
if metadata:
metric_data.update(metadata)
self.logger.info(
f"Performance: {operation} completed in {duration_ms:.2f}ms",
extra={"extra_data": metric_data}
)
# Armazena em memória para análise
if operation not in self.metrics:
self.metrics[operation] = []
self.metrics[operation].append(duration_ms)
def get_stats(self, operation: Optional[str] = None) -> Dict[str, Any]:
"""
Retorna estatísticas de performance
Args:
operation: Operação específica (None = todas)
Returns:
Dicionário com estatísticas
"""
if operation:
if operation not in self.metrics:
return {}
durations = self.metrics[operation]
return {
"operation": operation,
"count": len(durations),
"avg_ms": sum(durations) / len(durations),
"min_ms": min(durations),
"max_ms": max(durations),
"total_ms": sum(durations)
}
# Retorna stats de todas operações
stats = {}
for op, durations in self.metrics.items():
stats[op] = {
"count": len(durations),
"avg_ms": sum(durations) / len(durations),
"min_ms": min(durations),
"max_ms": max(durations),
"total_ms": sum(durations)
}
return stats
def clear_metrics(self) -> None:
"""Limpa todas as métricas armazenadas"""
self.metrics.clear()
# Instâncias globais de logger
app_logger = setup_logger("rag_template", level="INFO")
db_logger = setup_logger("rag_template.database", level="INFO")
llm_logger = setup_logger("rag_template.llm", level="INFO")
embedding_logger = setup_logger("rag_template.embeddings", level="INFO")
# Logger de performance
perf_logger = PerformanceLogger(setup_logger("rag_template.performance", level="INFO"))