Phase 14: Enhanced performance optimizations with connection pooling and lazy loading

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truetype committed 2026-03-20 20:01:27 +01:00
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@@ -1,18 +1,209 @@
"""
Performance optimizations for MaxClaw Agent
Enhanced with connection pooling, lazy loading, and advanced caching
"""
import os
import sys
import time
import functools
from typing import Dict, Any, Optional, Callable
import threading
from typing import Dict, Any, Optional, Callable, List
from pathlib import Path
import json
from concurrent.futures import ThreadPoolExecutor, as_completed
# Add current directory to path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
class ConnectionPool:
"""Connection pool for managing API connections"""
def __init__(self, max_connections: int = 10):
"""
Initialize connection pool
Args:
max_connections: Maximum number of connections in the pool
"""
self.max_connections = max_connections
self.connections = {}
self.lock = threading.Lock()
def get_connection(self, provider: str, **kwargs):
"""
Get a connection from the pool
Args:
provider: Provider name
**kwargs: Connection parameters
Returns:
Connection object
"""
with self.lock:
key = f"{provider}:{str(sorted(kwargs.items()))}"
if key not in self.connections:
# Create new connection
if provider == "ollama":
import requests
base_url = kwargs.get("base_url", "http://localhost:11434")
session = requests.Session()
session.headers.update({"Content-Type": "application/json"})
self.connections[key] = {
"session": session,
"base_url": base_url,
"last_used": time.time()
}
elif provider in ["openai", "openrouter", "anthropic", "google"]:
import requests
session = requests.Session()
api_key = kwargs.get("api_key", "")
if api_key:
session.headers.update({"Authorization": f"Bearer {api_key}"})
self.connections[key] = {
"session": session,
"last_used": time.time()
}
# Update last used time
if key in self.connections:
self.connections[key]["last_used"] = time.time()
return self.connections.get(key)
def cleanup_idle_connections(self, max_idle_time: int = 300):
"""
Clean up idle connections
Args:
max_idle_time: Maximum idle time in seconds
"""
with self.lock:
current_time = time.time()
keys_to_remove = []
for key, conn in self.connections.items():
if current_time - conn["last_used"] > max_idle_time:
keys_to_remove.append(key)
for key in keys_to_remove:
del self.connections[key]
def get_stats(self) -> Dict[str, Any]:
"""Get connection pool statistics"""
with self.lock:
return {
"total_connections": len(self.connections),
"max_connections": self.max_connections,
"connections": list(self.connections.keys())
}
class LazyLoader:
"""Lazy loading for heavy resources"""
def __init__(self):
self.loaded_modules = {}
self.loaded_tools = {}
self.lock = threading.Lock()
def load_module(self, module_name: str, import_path: str):
"""
Lazily load a module
Args:
module_name: Name to store the module under
import_path: Import path for the module
Returns:
Loaded module
"""
with self.lock:
if module_name not in self.loaded_modules:
try:
module = __import__(import_path, fromlist=[''])
self.loaded_modules[module_name] = module
except ImportError as e:
print(f"Warning: Could not load module {module_name}: {e}")
self.loaded_modules[module_name] = None
return self.loaded_modules.get(module_name)
def load_tool(self, tool_name: str, loader_func: Callable):
"""
Lazily load a tool
Args:
tool_name: Name to store the tool under
loader_func: Function to load the tool
Returns:
Loaded tool
"""
with self.lock:
if tool_name not in self.loaded_tools:
try:
tool = loader_func()
self.loaded_tools[tool_name] = tool
except Exception as e:
print(f"Warning: Could not load tool {tool_name}: {e}")
self.loaded_tools[tool_name] = None
return self.loaded_tools.get(tool_name)
def clear(self):
"""Clear all loaded resources"""
with self.lock:
self.loaded_modules.clear()
self.loaded_tools.clear()
class BatchProcessor:
"""Batch processing for multiple operations"""
def __init__(self, max_workers: int = 5):
"""
Initialize batch processor
Args:
max_workers: Maximum number of worker threads
"""
self.max_workers = max_workers
self.executor = ThreadPoolExecutor(max_workers=max_workers)
def process_batch(self, tasks: List[Callable], timeout: int = 30) -> List[Any]:
"""
Process a batch of tasks in parallel
Args:
tasks: List of callable tasks
timeout: Timeout in seconds
Returns:
List of results
"""
futures = [self.executor.submit(task) for task in tasks]
results = []
try:
for future in as_completed(futures, timeout=timeout):
try:
result = future.result()
results.append(result)
except Exception as e:
results.append({"error": str(e)})
except Exception as e:
print(f"Batch processing error: {e}")
return results
def shutdown(self):
"""Shutdown the executor"""
self.executor.shutdown(wait=True)
class PerformanceMonitor:
"""Monitor and optimize performance"""
@@ -20,6 +211,9 @@ class PerformanceMonitor:
self.metrics = {}
self.cache = {}
self.cache_ttl = 300 # 5 minutes default TTL
self.connection_pool = ConnectionPool()
self.lazy_loader = LazyLoader()
self.batch_processor = BatchProcessor()
def timing(self, func: Callable) -> Callable:
"""Decorator to measure function execution time"""
@@ -90,6 +284,20 @@ class PerformanceMonitor:
def clear_metrics(self):
"""Clear performance metrics"""
self.metrics.clear()
def get_connection_pool_stats(self) -> Dict[str, Any]:
"""Get connection pool statistics"""
return self.connection_pool.get_stats()
def cleanup_resources(self):
"""Clean up resources"""
self.connection_pool.cleanup_idle_connections()
self.clear_cache()
def shutdown(self):
"""Shutdown all resources"""
self.batch_processor.shutdown()
self.cleanup_resources()
# Global performance monitor instance
@@ -288,6 +496,12 @@ def get_performance_report() -> str:
report += f"\nCache Statistics:\n"
report += f" Cached Items: {cache_size}\n"
# Connection pool statistics
pool_stats = performance_monitor.get_connection_pool_stats()
report += f"\nConnection Pool:\n"
report += f" Total Connections: {pool_stats['total_connections']}\n"
report += f" Max Connections: {pool_stats['max_connections']}\n"
return report