374 lines
15 KiB
Python
374 lines
15 KiB
Python
"""
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Enhanced FastAPI Monitoring Middleware
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Database-backed monitoring for API calls, errors, performance metrics, and usage tracking.
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Includes comprehensive subscription-based usage monitoring and cost tracking.
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"""
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from fastapi import Request, Response
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from fastapi.responses import JSONResponse
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import time
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import json
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from datetime import datetime, timedelta
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from typing import Dict, List, Any, Optional
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from collections import defaultdict, deque
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import asyncio
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from loguru import logger
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from sqlalchemy.orm import Session
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from sqlalchemy import and_, func
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import re
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from models.api_monitoring import APIRequest, APIEndpointStats, SystemHealth, CachePerformance
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from models.subscription_models import APIProvider
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from services.database import get_db
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from .usage_tracking_service import UsageTrackingService
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from .pricing_service import PricingService
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class DatabaseAPIMonitor:
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"""Database-backed API monitoring with usage tracking and subscription management."""
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def __init__(self):
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self.cache_stats = {
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'hits': 0,
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'misses': 0,
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'hit_rate': 0.0
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}
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# API provider detection patterns - Updated to match actual endpoints
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self.provider_patterns = {
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APIProvider.GEMINI: [
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r'gemini', r'google.*ai'
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],
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APIProvider.OPENAI: [r'openai', r'gpt', r'chatgpt'],
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APIProvider.ANTHROPIC: [r'anthropic', r'claude'],
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APIProvider.MISTRAL: [r'mistral'],
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APIProvider.TAVILY: [r'tavily'],
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APIProvider.SERPER: [r'serper'],
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APIProvider.METAPHOR: [r'metaphor', r'/exa'],
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APIProvider.FIRECRAWL: [r'firecrawl']
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}
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def detect_api_provider(self, path: str, user_agent: str = None) -> Optional[APIProvider]:
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"""Detect which API provider is being used based on request details."""
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path_lower = path.lower()
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user_agent_lower = (user_agent or '').lower()
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# Permanently ignore internal route families that must not accrue or check provider usage
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if path_lower.startswith('/api/onboarding/') or path_lower.startswith('/api/subscription/'):
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return None
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for provider, patterns in self.provider_patterns.items():
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for pattern in patterns:
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if re.search(pattern, path_lower) or re.search(pattern, user_agent_lower):
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return provider
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return None
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def extract_usage_metrics(self, request_body: str = None, response_body: str = None) -> Dict[str, Any]:
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"""Extract usage metrics from request/response bodies."""
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metrics = {
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'tokens_input': 0,
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'tokens_output': 0,
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'model_used': None,
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'search_count': 0,
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'image_count': 0,
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'page_count': 0
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}
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try:
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# Try to parse request body for input tokens/content
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if request_body:
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request_data = json.loads(request_body) if isinstance(request_body, str) else request_body
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# Extract model information
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if 'model' in request_data:
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metrics['model_used'] = request_data['model']
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# Estimate input tokens from prompt/content
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if 'prompt' in request_data:
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metrics['tokens_input'] = self._estimate_tokens(request_data['prompt'])
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elif 'messages' in request_data:
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total_content = ' '.join([msg.get('content', '') for msg in request_data['messages']])
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metrics['tokens_input'] = self._estimate_tokens(total_content)
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elif 'input' in request_data:
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metrics['tokens_input'] = self._estimate_tokens(str(request_data['input']))
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# Count specific request types
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if 'query' in request_data or 'search' in request_data:
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metrics['search_count'] = 1
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if 'image' in request_data or 'generate_image' in request_data:
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metrics['image_count'] = 1
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if 'url' in request_data or 'crawl' in request_data:
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metrics['page_count'] = 1
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# Try to parse response body for output tokens
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if response_body:
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response_data = json.loads(response_body) if isinstance(response_body, str) else response_body
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# Extract output content and estimate tokens
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if 'text' in response_data:
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metrics['tokens_output'] = self._estimate_tokens(response_data['text'])
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elif 'content' in response_data:
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metrics['tokens_output'] = self._estimate_tokens(str(response_data['content']))
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elif 'choices' in response_data and response_data['choices']:
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choice = response_data['choices'][0]
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if 'message' in choice and 'content' in choice['message']:
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metrics['tokens_output'] = self._estimate_tokens(choice['message']['content'])
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# Extract actual token usage if provided by API
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if 'usage' in response_data:
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usage = response_data['usage']
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if 'prompt_tokens' in usage:
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metrics['tokens_input'] = usage['prompt_tokens']
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if 'completion_tokens' in usage:
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metrics['tokens_output'] = usage['completion_tokens']
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except (json.JSONDecodeError, KeyError, TypeError) as e:
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logger.debug(f"Could not extract usage metrics: {e}")
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return metrics
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def _estimate_tokens(self, text: str) -> int:
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"""Estimate token count for text (rough approximation)."""
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if not text:
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return 0
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# Rough estimation: 1.3 tokens per word on average
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word_count = len(str(text).split())
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return int(word_count * 1.3)
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async def check_usage_limits_middleware(request: Request, user_id: str, request_body: str = None) -> Optional[JSONResponse]:
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"""Check usage limits before processing request."""
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if not user_id:
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return None
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# No special whitelist; onboarding/subscription are ignored by provider detection
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try:
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path = request.url.path
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except Exception:
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pass
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try:
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db = next(get_db())
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api_monitor = DatabaseAPIMonitor()
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# Detect if this is an API call that should be rate limited
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api_provider = api_monitor.detect_api_provider(request.url.path, request.headers.get('user-agent'))
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if not api_provider:
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return None
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# Use provided request body or read it if not provided
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if request_body is None:
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try:
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if hasattr(request, '_body'):
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request_body = request._body
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else:
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# Try to read body (this might not work in all cases)
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body = await request.body()
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request_body = body.decode('utf-8') if body else None
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except:
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pass
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# Estimate tokens needed
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tokens_requested = 0
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if request_body:
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usage_metrics = api_monitor.extract_usage_metrics(request_body)
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tokens_requested = usage_metrics.get('tokens_input', 0)
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# Check limits
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usage_service = UsageTrackingService(db)
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can_proceed, message, usage_info = await usage_service.enforce_usage_limits(
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user_id=user_id,
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provider=api_provider,
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tokens_requested=tokens_requested
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)
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if not can_proceed:
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logger.warning(f"Usage limit exceeded for {user_id}: {message}")
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return JSONResponse(
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status_code=429,
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content={
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"error": "Usage limit exceeded",
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"message": message,
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"usage_info": usage_info,
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"provider": api_provider.value
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}
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)
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# Warn if approaching limits
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if usage_info.get('call_usage_percentage', 0) >= 80 or usage_info.get('cost_usage_percentage', 0) >= 80:
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logger.warning(f"User {user_id} approaching usage limits: {usage_info}")
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return None
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except Exception as e:
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logger.error(f"Error checking usage limits: {e}")
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# Don't block requests if usage checking fails
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return None
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finally:
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db.close()
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async def monitoring_middleware(request: Request, call_next):
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"""Enhanced FastAPI middleware for monitoring API calls with usage tracking."""
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start_time = time.time()
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# Get database session
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db = next(get_db())
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# Extract request details - Enhanced user identification
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user_id = None
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try:
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# PRIORITY 1: Check request.state.user_id (set by API key injection middleware)
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if hasattr(request.state, 'user_id') and request.state.user_id:
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user_id = request.state.user_id
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logger.debug(f"Monitoring: Using user_id from request.state: {user_id}")
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# PRIORITY 2: Check query parameters
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elif hasattr(request, 'query_params') and 'user_id' in request.query_params:
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user_id = request.query_params['user_id']
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elif hasattr(request, 'path_params') and 'user_id' in request.path_params:
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user_id = request.path_params['user_id']
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# PRIORITY 3: Check headers for user identification
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elif 'x-user-id' in request.headers:
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user_id = request.headers['x-user-id']
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elif 'x-user-email' in request.headers:
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user_id = request.headers['x-user-email'] # Use email as user identifier
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elif 'x-session-id' in request.headers:
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user_id = request.headers['x-session-id'] # Use session as fallback
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# Check for authorization header with user info
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elif 'authorization' in request.headers:
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# Auth middleware should have set request.state.user_id
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# If not, this indicates an authentication failure that should be logged
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user_id = None
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logger.warning("Monitoring: Auth header present but no user_id in state - authentication may have failed")
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# Final fallback: None (skip usage limits for truly anonymous/unauthenticated)
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else:
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user_id = None
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except Exception as e:
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logger.debug(f"Error extracting user ID: {e}")
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user_id = None # On error, skip usage limits
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# Capture request body for usage tracking (read once, safely)
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request_body = None
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try:
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# Only read body for POST/PUT/PATCH requests to avoid issues
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if request.method in ['POST', 'PUT', 'PATCH']:
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if hasattr(request, '_body') and request._body:
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request_body = request._body.decode('utf-8')
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else:
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# Read body only if it hasn't been read yet
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try:
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body = await request.body()
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request_body = body.decode('utf-8') if body else None
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except Exception as body_error:
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logger.debug(f"Could not read request body: {body_error}")
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request_body = None
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except Exception as e:
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logger.debug(f"Error capturing request body: {e}")
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request_body = None
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# Check usage limits before processing
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limit_response = await check_usage_limits_middleware(request, user_id, request_body)
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if limit_response:
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return limit_response
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try:
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response = await call_next(request)
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status_code = response.status_code
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duration = time.time() - start_time
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# Capture response body for usage tracking
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response_body = None
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try:
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if hasattr(response, 'body'):
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response_body = response.body.decode('utf-8') if response.body else None
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elif hasattr(response, '_content'):
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response_body = response._content.decode('utf-8') if response._content else None
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except:
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pass
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# Track API usage if this is an API call to external providers
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api_monitor = DatabaseAPIMonitor()
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api_provider = api_monitor.detect_api_provider(request.url.path, request.headers.get('user-agent'))
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if api_provider and user_id:
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logger.info(f"Detected API call: {request.url.path} -> {api_provider.value} for user: {user_id}")
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try:
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# Extract usage metrics
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usage_metrics = api_monitor.extract_usage_metrics(request_body, response_body)
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# Track usage with the usage tracking service
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usage_service = UsageTrackingService(db)
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await usage_service.track_api_usage(
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user_id=user_id,
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provider=api_provider,
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endpoint=request.url.path,
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method=request.method,
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model_used=usage_metrics.get('model_used'),
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tokens_input=usage_metrics.get('tokens_input', 0),
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tokens_output=usage_metrics.get('tokens_output', 0),
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response_time=duration,
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status_code=status_code,
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request_size=len(request_body) if request_body else None,
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response_size=len(response_body) if response_body else None,
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user_agent=request.headers.get('user-agent'),
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ip_address=request.client.host if request.client else None,
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search_count=usage_metrics.get('search_count', 0),
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image_count=usage_metrics.get('image_count', 0),
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page_count=usage_metrics.get('page_count', 0)
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)
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except Exception as usage_error:
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logger.error(f"Error tracking API usage: {usage_error}")
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# Don't fail the main request if usage tracking fails
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return response
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except Exception as e:
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duration = time.time() - start_time
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status_code = 500
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# Store minimal error info
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logger.error(f"API Error: {request.method} {request.url.path} - {str(e)}")
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return JSONResponse(
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status_code=500,
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content={"error": "Internal server error"}
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)
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finally:
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db.close()
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async def get_monitoring_stats(minutes: int = 5) -> Dict[str, Any]:
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"""Get current monitoring statistics."""
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db = next(get_db())
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try:
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# Placeholder to match old API; heavy stats handled elsewhere
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return {
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'timestamp': datetime.utcnow().isoformat(),
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'overview': {
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'recent_requests': 0,
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'recent_errors': 0,
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},
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'cache_performance': {'hits': 0, 'misses': 0, 'hit_rate': 0.0},
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'recent_errors': [],
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'system_health': {'status': 'healthy', 'error_rate': 0.0}
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}
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finally:
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db.close()
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async def get_lightweight_stats() -> Dict[str, Any]:
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"""Get lightweight stats for dashboard header."""
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db = next(get_db())
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try:
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# Minimal viable placeholder values
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now = datetime.utcnow()
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return {
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'status': 'healthy',
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'icon': '🟢',
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'recent_requests': 0,
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'recent_errors': 0,
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'error_rate': 0.0,
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'timestamp': now.isoformat()
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}
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finally:
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db.close()
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