annator-atom / backend /middleware /performance.py
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Full stack ATOM backend + AIMONEYFLOW clients (port 7860) (part 5)
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"""
Performance Optimization Middleware
Provides caching, compression, and connection pooling
"""
import asyncio
import hashlib
import json
import logging
import time
from typing import Any, Dict, Optional
from fastapi import Request, Response
from starlette.middleware.base import BaseHTTPMiddleware
from collections import OrderedDict
logger = logging.getLogger(__name__)
class LocalCacheFallback:
"""LRU cache with TTL for Redis fallback scenarios.
Backported from SaaS to ensure parity and fix cross-repo test regressions.
"""
def __init__(self, max_size: int = 1000, default_ttl: int = 60):
self.max_size = max_size
self.default_ttl = default_ttl
self._cache: OrderedDict[str, Dict[str, Any]] = OrderedDict()
self._lock = asyncio.Lock()
# Statistics
self.hits = 0
self.misses = 0
self.evictions = 0
async def get(self, key: str) -> Optional[Any]:
async with self._lock:
if key not in self._cache:
self.misses += 1
return None
entry = self._cache[key]
# Check expiration
if time.time() > entry.get("expires_at", 0):
del self._cache[key]
self.misses += 1
return None
# Move to end (LRU: most recently used)
self._cache.move_to_end(key)
self.hits += 1
return entry["value"]
async def set(self, key: str, value: Any, ttl: Optional[int] = None) -> bool:
async with self._lock:
# Evict oldest if at capacity
if len(self._cache) >= self.max_size and key not in self._cache:
self._cache.popitem(last=False) # Remove oldest (first)
self.evictions += 1
ttl = ttl or self.default_ttl
self._cache[key] = {
"value": value,
"expires_at": time.time() + ttl,
"created_at": time.time()
}
self._cache.move_to_end(key)
return True
async def delete(self, key: str) -> bool:
async with self._lock:
if key in self._cache:
del self._cache[key]
return True
return False
def clear(self):
"""Clear all cache entries"""
self._cache.clear()
self.hits = 0
self.misses = 0
self.evictions = 0
def get_stats(self) -> Dict[str, Any]:
"""Get cache statistics"""
total_requests = self.hits + self.misses
hit_rate = (self.hits / total_requests * 100) if total_requests > 0 else 0
return {
"size": len(self._cache),
"max_size": self.max_size,
"hits": self.hits,
"misses": self.misses,
"evictions": self.evictions,
"hit_rate_percent": round(hit_rate, 2),
"usage_percent": round(len(self._cache) / self.max_size * 100, 2) if self.max_size > 0 else 0,
"entries": list(self._cache.keys())[-10:] # Last 10 keys
}
# Simple in-memory cache for MVP (replace with Redis in production)
class SimpleCache:
"""Simple in-memory cache with TTL"""
def __init__(self):
self.cache: Dict[str, Dict[str, Any]] = {}
self.cleanup_interval = 300 # 5 minutes
self.last_cleanup = time.time()
def get(self, key: str) -> Optional[Any]:
"""Get value from cache"""
if key in self.cache:
entry = self.cache[key]
if time.time() < entry["expires_at"]:
return entry["value"]
else:
del self.cache[key]
return None
def set(self, key: str, value: Any, ttl: int = 300):
"""Set value in cache with TTL"""
self.cache[key] = {
"value": value,
"expires_at": time.time() + ttl,
"created_at": time.time()
}
self._cleanup_expired()
def delete(self, key: str):
"""Delete key from cache"""
if key in self.cache:
del self.cache[key]
def _cleanup_expired(self):
"""Remove expired entries"""
current_time = time.time()
if current_time - self.last_cleanup > self.cleanup_interval:
expired_keys = [
key for key, entry in self.cache.items()
if current_time > entry["expires_at"]
]
for key in expired_keys:
del self.cache[key]
self.last_cleanup = current_time
# Global cache instance
cache = SimpleCache()
class CacheMiddleware(BaseHTTPMiddleware):
"""Response caching middleware for GET requests"""
def __init__(self, app, cache_ttl: int = 300):
super().__init__(app)
self.cache_ttl = cache_ttl
# Don't cache these endpoints
self.no_cache_patterns = [
"/api/agent/",
"/api/ai/",
"/api/workflows/execute",
"/api/v1/workflows/execute",
"/health",
"/metrics"
]
async def dispatch(self, request: Request, call_next):
# Only cache GET requests
if request.method != "GET":
return await call_next(request)
# Check if endpoint should be cached
path = str(request.url.path)
if any(pattern in path for pattern in self.no_cache_patterns):
return await call_next(request)
# Generate cache key
cache_key = self._generate_cache_key(request)
# Try to get from cache
cached_response = cache.get(cache_key)
if cached_response:
# Create response from cached data
response = Response(
content=cached_response["content"],
status_code=cached_response["status_code"],
headers=cached_response["headers"],
media_type=cached_response.get("media_type", "application/json")
)
response.headers["X-Cache"] = "HIT"
return response
# Get response and cache it
response = await call_next(request)
# Only cache successful responses
if 200 <= response.status_code < 300:
# Cache the response
response_body = b""
async for chunk in response.body_iterator:
response_body += chunk
cache_data = {
"content": response_body,
"status_code": response.status_code,
"headers": dict(response.headers),
"media_type": response.media_type
}
cache.set(cache_key, cache_data, self.cache_ttl)
# Create new response with the body
new_response = Response(
content=response_body,
status_code=response.status_code,
headers=dict(response.headers),
media_type=response.media_type
)
new_response.headers["X-Cache"] = "MISS"
return new_response
response.headers["X-Cache"] = "SKIP"
return response
def _generate_cache_key(self, request: Request) -> str:
"""Generate cache key for request"""
# Include path, query params, and headers that affect response
key_data = {
"path": str(request.url.path),
"query": str(request.url.query),
"method": request.method,
# Add relevant headers if needed
}
key_str = json.dumps(key_data, sort_keys=True)
return f"cache:{hashlib.md5(key_str.encode()).hexdigest()}"
class CompressionMiddleware(BaseHTTPMiddleware):
"""Response compression middleware"""
def __init__(self, app, min_size: int = 1024):
super().__init__(app)
self.min_size = min_size
async def dispatch(self, request: Request, call_next):
# Check if client accepts gzip
accept_encoding = request.headers.get("accept-encoding", "")
if "gzip" not in accept_encoding.lower():
return await call_next(request)
response = await call_next(request)
# Only compress responses that are large enough
content_length = response.headers.get("content-length")
if content_length and int(content_length) < self.min_size:
return response
# Only compress certain content types
content_type = response.headers.get("content-type", "")
compressible_types = [
"application/json",
"text/html",
"text/css",
"text/javascript",
"application/javascript"
]
if not any(ct in content_type for ct in compressible_types):
return response
# Compress response
# For MVP, skip actual compression (just add header)
# In production, implement gzip compression
response.headers["content-encoding"] = "gzip"
return response
class DatabaseConnectionPool:
"""Simple database connection pool manager
Note: For database connections, SQLAlchemy already handles connection pooling.
This class is designed for HTTP client connection pooling for external API calls.
"""
def __init__(self, max_connections: int = 10, connection_timeout: float = 30.0):
self.max_connections = max_connections
self.connection_timeout = connection_timeout
self._pool = None
self._initialized = False
async def _get_pool(self):
"""Lazy-initialize HTTP connection pool"""
if not self._initialized:
import httpx
# Create async HTTP client with connection pooling
self._pool = httpx.AsyncClient(
limits=httpx.Limits(
max_connections=self.max_connections,
max_keepalive_connections=self.max_connections // 2
),
timeout=httpx.Timeout(self.connection_timeout),
http2=True, # Enable HTTP/2 for better performance
)
self._initialized = True
logger.info(f"HTTP connection pool initialized: max={self.max_connections} connections")
return self._pool
async def get_connection(self):
"""Get the HTTP client (uses connection pooling internally)"""
pool = await self._get_pool()
return pool
async def release_connection(self, connection):
"""Release is handled automatically by httpx.AsyncClient context manager"""
# httpx.AsyncClient handles connection pooling internally
# No explicit release needed
# This method exists for API compatibility
return
async def close(self):
"""Close the connection pool"""
if self._pool and self._initialized:
await self._pool.aclose()
self._initialized = False
logger.info("HTTP connection pool closed")
async def __aenter__(self):
"""Async context manager support"""
await self._get_pool()
return self
async def __aexit__(self, exc_type, exc_val, exc_tb):
"""Clean up on exit"""
await self.close()
class RequestMetricsMiddleware(BaseHTTPMiddleware):
"""Middleware to collect request metrics"""
def __init__(self, app):
super().__init__(app)
self.metrics = {
"total_requests": 0,
"requests_by_method": {},
"requests_by_path": {},
"response_times": [],
"status_codes": {}
}
self.start_time = datetime.now()
async def dispatch(self, request: Request, call_next):
start_time = time.time()
# Update request count
self.metrics["total_requests"] += 1
# Track by method
method = request.method
self.metrics["requests_by_method"][method] = \
self.metrics["requests_by_method"].get(method, 0) + 1
# Track by path
path = str(request.url.path)
self.metrics["requests_by_path"][path] = \
self.metrics["requests_by_path"].get(path, 0) + 1
# Process request
response = await call_next(request)
# Track response time
response_time = time.time() - start_time
self.metrics["response_times"].append(response_time)
# Track status codes
status = response.status_code
self.metrics["status_codes"][status] = \
self.metrics["status_codes"].get(status, 0) + 1
# Add performance header
response.headers["X-Response-Time"] = f"{response_time:.3f}s"
return response
def get_metrics(self) -> Dict[str, Any]:
"""Get current metrics"""
response_times = self.metrics["response_times"]
avg_response_time = sum(response_times) / len(response_times) if response_times else 0
return {
"uptime_seconds": (datetime.now() - self.start_time).total_seconds(),
"total_requests": self.metrics["total_requests"],
"requests_per_second": self.metrics["total_requests"] / max(
(datetime.now() - self.start_time).total_seconds(), 1
),
"average_response_time": avg_response_time,
"requests_by_method": self.metrics["requests_by_method"],
"top_paths": sorted(
self.metrics["requests_by_path"].items(),
key=lambda x: x[1],
reverse=True
)[:10],
"status_codes": self.metrics["status_codes"]
}
# Connection pool instance
db_pool = DatabaseConnectionPool()
def setup_performance_middleware(app):
"""Setup all performance middleware"""
# Add middleware in reverse order (last added runs first)
app.add_middleware(RequestMetricsMiddleware)
app.add_middleware(CompressionMiddleware)
app.add_middleware(CacheMiddleware, cache_ttl=300) # 5 minutes cache
# Cache decorator for functions
def cached(ttl: int = 300, key_prefix: str = ""):
"""Decorator to cache function results"""
def decorator(func):
@wraps(func)
async def wrapper(*args, **kwargs):
# Generate cache key
key_data = {
"function": func.__name__,
"args": args,
"kwargs": kwargs
}
key_str = f"{key_prefix}:{hashlib.md5(json.dumps(key_data, sort_keys=True, default=str).encode()).hexdigest()}"
# Try to get from cache
result = cache.get(key_str)
if result is not None:
return result
# Execute function and cache result
result = await func(*args, **kwargs)
cache.set(key_str, result, ttl)
return result
return wrapper
return decorator