BobAi dc866e6ce3 MAJOR: Remove all Claude references and rename to Mini-RAG
Complete rebrand for v1.0-simple-search branch:

Directory Changes:
- claude_rag/ → mini_rag/ (preserving git history)

Content Changes:
- Updated all imports: from claude_rag → from mini_rag
- Updated all file paths: .claude-rag → .mini-rag
- Updated documentation and comments
- Updated configuration files and examples
- Updated all tests to use mini_rag imports

This ensures complete independence from Claude/Anthropic
branding while maintaining all functionality and git history.

Simple branch contains the basic RAG system without LLM features.
2025-08-12 19:27:55 +10:00

87 lines
2.6 KiB
Python

"""
Performance monitoring for RAG system.
Track loading times, query times, and resource usage.
"""
import time
import psutil
import os
from contextlib import contextmanager
from typing import Dict, Any, Optional
import logging
logger = logging.getLogger(__name__)
class PerformanceMonitor:
"""Track performance metrics for RAG operations."""
def __init__(self):
self.metrics = {}
self.process = psutil.Process(os.getpid())
@contextmanager
def measure(self, operation: str):
"""Context manager to measure operation time and memory."""
# Get initial state
start_time = time.time()
start_memory = self.process.memory_info().rss / 1024 / 1024 # MB
try:
yield self
finally:
# Calculate metrics
end_time = time.time()
end_memory = self.process.memory_info().rss / 1024 / 1024 # MB
duration = end_time - start_time
memory_delta = end_memory - start_memory
# Store metrics
self.metrics[operation] = {
'duration_seconds': duration,
'memory_delta_mb': memory_delta,
'final_memory_mb': end_memory,
}
logger.info(
f"[PERF] {operation}: {duration:.2f}s, "
f"Memory: {end_memory:.1f}MB (+{memory_delta:+.1f}MB)"
)
def get_summary(self) -> Dict[str, Any]:
"""Get performance summary."""
total_time = sum(m['duration_seconds'] for m in self.metrics.values())
return {
'total_time_seconds': total_time,
'operations': self.metrics,
'current_memory_mb': self.process.memory_info().rss / 1024 / 1024,
}
def print_summary(self):
"""Print a formatted summary."""
print("\n" + "="*50)
print("PERFORMANCE SUMMARY")
print("="*50)
for op, metrics in self.metrics.items():
print(f"\n{op}:")
print(f" Time: {metrics['duration_seconds']:.2f}s")
print(f" Memory: +{metrics['memory_delta_mb']:+.1f}MB")
summary = self.get_summary()
print(f"\nTotal Time: {summary['total_time_seconds']:.2f}s")
print(f"Current Memory: {summary['current_memory_mb']:.1f}MB")
print("="*50)
# Global instance for easy access
_monitor = None
def get_monitor() -> PerformanceMonitor:
"""Get or create global monitor instance."""
global _monitor
if _monitor is None:
_monitor = PerformanceMonitor()
return _monitor