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app/weather_agent.py
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# app/weather_agent.py
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"""
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🌤️ PENNY Weather Agent - Azure Maps Integration
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Provides real-time weather information and weather-aware recommendations
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for civic engagement activities.
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MISSION: Help residents plan their day with accurate weather data and
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smart suggestions for indoor/outdoor activities based on conditions.
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ENHANCEMENTS (Phase 1 Complete):
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- ✅ Structured logging with performance tracking
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- ✅ Enhanced error handling with graceful degradation
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- ✅ Type hints for all functions
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- ✅ Health check integration
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- ✅ Response caching for performance
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- ✅ Detailed weather parsing with validation
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- ✅ Penny's friendly voice in all responses
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Production-ready for Azure ML deployment.
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"""
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import os
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import logging
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import time
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from typing import Dict, Any, Optional, List, Tuple
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from datetime import datetime, timedelta
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import httpx
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# --- ENHANCED MODULE IMPORTS ---
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from app.logging_utils import log_interaction
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# --- LOGGING SETUP ---
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logger = logging.getLogger(__name__)
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# --- CONFIGURATION ---
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AZURE_WEATHER_URL = "https://atlas.microsoft.com/weather/currentConditions/json"
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DEFAULT_TIMEOUT = 10.0 # seconds
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CACHE_TTL_SECONDS = 300 # 5 minutes - weather doesn't change that fast
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# --- CHECK API KEY AVAILABILITY AT MODULE LOAD (NEW - PREVENTS IMPORT FAILURES) ---
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AZURE_MAPS_KEY = os.getenv("AZURE_MAPS_KEY")
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if not AZURE_MAPS_KEY:
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logger.warning("⚠️ AZURE_MAPS_KEY not configured - weather features will be limited")
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_WEATHER_SERVICE_AVAILABLE = False
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else:
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logger.info("✅ AZURE_MAPS_KEY configured")
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_WEATHER_SERVICE_AVAILABLE = True
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# --- WEATHER CACHE ---
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_weather_cache: Dict[str, Tuple[Dict[str, Any], datetime]] = {}
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# ============================================================
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# WEATHER DATA RETRIEVAL
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# ============================================================
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async def get_weather_for_location(
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lat: float,
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lon: float,
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use_cache: bool = True
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) -> Dict[str, Any]:
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"""
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🌤️ Fetches real-time weather from Azure Maps.
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Retrieves current weather conditions for a specific location using
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Azure Maps Weather API. Includes caching to reduce API calls and
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improve response times.
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Args:
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lat: Latitude coordinate
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lon: Longitude coordinate
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use_cache: Whether to use cached data if available (default: True)
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Returns:
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Dictionary containing weather data with keys:
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- temperature: {value: float, unit: str}
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- phrase: str (weather description)
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- iconCode: int
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- hasPrecipitation: bool
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- isDayTime: bool
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- relativeHumidity: int
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- cloudCover: int
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- etc.
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Raises:
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RuntimeError: If AZURE_MAPS_KEY is not configured
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httpx.HTTPError: If API request fails
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Example:
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weather = await get_weather_for_location(33.7490, -84.3880)
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temp = weather.get("temperature", {}).get("value")
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condition = weather.get("phrase", "Unknown")
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"""
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start_time = time.time()
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# Create cache key
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cache_key = f"{lat:.4f},{lon:.4f}"
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# Check cache first
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if use_cache and cache_key in _weather_cache:
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cached_data, cached_time = _weather_cache[cache_key]
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age = (datetime.now() - cached_time).total_seconds()
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if age < CACHE_TTL_SECONDS:
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logger.info(
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f"🌤️ Weather cache hit (age: {age:.0f}s, "
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f"location: {cache_key})"
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)
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return cached_data
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# Check if service is available (MODIFIED - USES FLAG INSTEAD OF CHECKING ENV VAR)
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if not _WEATHER_SERVICE_AVAILABLE:
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logger.error("❌ AZURE_MAPS_KEY not configured")
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raise RuntimeError(
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"AZURE_MAPS_KEY is required and not set in environment variables."
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)
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# Build request parameters
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params = {
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"api-version": "1.0",
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"query": f"{lat},{lon}",
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"subscription-key": AZURE_MAPS_KEY,
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"details": "true",
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"language": "en-US",
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}
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try:
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logger.info(f"🌤️ Fetching weather for location: {cache_key}")
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async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as client:
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response = await client.get(AZURE_WEATHER_URL, params=params)
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response.raise_for_status()
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data = response.json()
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# Parse response
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if "results" in data and len(data["results"]) > 0:
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weather_data = data["results"][0]
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else:
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weather_data = data # Fallback if structure changes
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# Validate essential fields
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weather_data = _validate_weather_data(weather_data)
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# Cache the result
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_weather_cache[cache_key] = (weather_data, datetime.now())
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# Calculate response time
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response_time = (time.time() - start_time) * 1000
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# Log successful retrieval
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log_interaction(
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tenant_id="weather_service",
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interaction_type="weather_fetch",
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intent="weather",
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response_time_ms=response_time,
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success=True,
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metadata={
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"location": cache_key,
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"cached": False,
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"temperature": weather_data.get("temperature", {}).get("value"),
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"condition": weather_data.get("phrase")
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}
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)
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logger.info(
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f"✅ Weather fetched successfully ({response_time:.0f}ms, "
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f"location: {cache_key})"
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)
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return weather_data
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except httpx.TimeoutException as e:
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logger.error(f"⏱️ Weather API timeout: {e}")
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raise
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except httpx.HTTPStatusError as e:
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logger.error(f"❌ Weather API HTTP error: {e.response.status_code}")
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raise
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except Exception as e:
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logger.error(f"❌ Weather API error: {e}", exc_info=True)
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raise
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def _validate_weather_data(data: Dict[str, Any]) -> Dict[str, Any]:
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"""
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Validates and normalizes weather data from Azure Maps.
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Ensures essential fields are present with sensible defaults.
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"""
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# Ensure temperature exists
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if "temperature" not in data:
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data["temperature"] = {"value": None, "unit": "F"}
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elif isinstance(data["temperature"], (int, float)):
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# Handle case where temperature is just a number
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data["temperature"] = {"value": data["temperature"], "unit": "F"}
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# Ensure phrase exists
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if "phrase" not in data or not data["phrase"]:
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data["phrase"] = "Conditions unavailable"
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# Ensure boolean flags exist
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data.setdefault("hasPrecipitation", False)
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data.setdefault("isDayTime", True)
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# Ensure numeric fields exist
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data.setdefault("relativeHumidity", None)
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data.setdefault("cloudCover", None)
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data.setdefault("iconCode", None)
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return data
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# ============================================================
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# OUTFIT RECOMMENDATIONS
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# ============================================================
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def recommend_outfit(high_temp: float, condition: str) -> str:
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"""
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👕 Recommends what to wear based on weather conditions.
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Provides friendly, practical clothing suggestions based on
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temperature and weather conditions.
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Args:
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high_temp: Expected high temperature in Fahrenheit
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condition: Weather condition description (e.g., "Sunny", "Rainy")
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Returns:
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Friendly outfit recommendation string
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Example:
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outfit = recommend_outfit(85, "Sunny")
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# Returns: "Light clothes, sunscreen, and stay hydrated! ☀️"
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"""
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condition_lower = condition.lower()
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# Check for precipitation first
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if "rain" in condition_lower or "storm" in condition_lower:
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logger.debug(f"Outfit rec: Rain/Storm (temp: {high_temp}°F)")
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return "Bring an umbrella or rain jacket! ☔"
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# Temperature-based recommendations
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if high_temp >= 85:
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logger.debug(f"Outfit rec: Hot (temp: {high_temp}°F)")
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return "Light clothes, sunscreen, and stay hydrated! ☀️"
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if high_temp >= 72:
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logger.debug(f"Outfit rec: Warm (temp: {high_temp}°F)")
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return "T-shirt and jeans or a casual dress. 👕"
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if high_temp >= 60:
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logger.debug(f"Outfit rec: Mild (temp: {high_temp}°F)")
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return "A hoodie or light jacket should do! 🧥"
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logger.debug(f"Outfit rec: Cold (temp: {high_temp}°F)")
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return "Bundle up — sweater or coat recommended! 🧣"
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# ============================================================
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# EVENT RECOMMENDATIONS BASED ON WEATHER
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# ============================================================
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def weather_to_event_recommendations(
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weather: Dict[str, Any]
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) -> List[Dict[str, Any]]:
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"""
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📅 Suggests activity types based on current weather conditions.
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Analyzes weather data to provide smart recommendations for
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indoor vs outdoor activities, helping residents plan their day.
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Args:
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weather: Weather data dictionary from get_weather_for_location()
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Returns:
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List of recommendation dictionaries with keys:
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- type: str ("indoor", "outdoor", "neutral")
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- suggestions: List[str] (specific activity ideas)
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- reason: str (explanation for recommendation)
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- priority: int (1-3, added for sorting)
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Example:
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weather = await get_weather_for_location(33.7490, -84.3880)
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recs = weather_to_event_recommendations(weather)
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for rec in recs:
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print(f"{rec['type']}: {rec['suggestions']}")
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"""
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condition = (weather.get("phrase") or "").lower()
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temp = weather.get("temperature", {}).get("value")
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has_precipitation = weather.get("hasPrecipitation", False)
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recs = []
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# Check for rain or storms (highest priority)
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if "rain" in condition or "storm" in condition or has_precipitation:
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logger.debug("Event rec: Indoor (precipitation)")
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recs.append({
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"type": "indoor",
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"suggestions": [
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"Visit a library 📚",
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"Check out a community center event 🏛️",
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"Find an indoor workshop or class 🎨",
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"Explore a local museum 🖼️"
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],
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"reason": "Rainy weather makes indoor events ideal!",
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"priority": 1
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})
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# Warm weather outdoor activities
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elif temp is not None and temp >= 75:
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logger.debug(f"Event rec: Outdoor (warm: {temp}°F)")
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recs.append({
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"type": "outdoor",
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"suggestions": [
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"Visit a park 🌳",
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"Check out a farmers market 🥕",
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"Look for outdoor concerts or festivals 🎵",
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"Enjoy a community picnic or BBQ 🍔"
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],
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"reason": "Beautiful weather for outdoor activities!",
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"priority": 1
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})
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# Cold weather considerations
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elif temp is not None and temp < 50:
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logger.debug(f"Event rec: Indoor (cold: {temp}°F)")
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recs.append({
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"type": "indoor",
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"suggestions": [
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"Browse local events at community centers 🏛️",
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"Visit a museum or art gallery 🖼️",
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"Check out indoor markets or shopping 🛍️",
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"Warm up at a local café or restaurant ☕"
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],
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"reason": "Chilly weather — indoor activities are cozy!",
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"priority": 1
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})
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# Mild/neutral weather
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else:
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logger.debug(f"Event rec: Neutral (mild: {temp}°F if temp else 'unknown')")
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recs.append({
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"type": "neutral",
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"suggestions": [
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"Browse local events 📅",
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"Visit a museum or cultural center 🏛️",
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"Walk around a local plaza or downtown 🚶",
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"Check out both indoor and outdoor activities 🌍"
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],
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"reason": "Mild weather gives you flexible options!",
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"priority": 2
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})
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return recs
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# ============================================================
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# HELPER FUNCTIONS
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# ============================================================
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def format_weather_summary(weather: Dict[str, Any]) -> str:
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"""
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📝 Formats weather data into a human-readable summary.
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Args:
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weather: Weather data dictionary
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Returns:
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Formatted weather summary string with Penny's friendly voice
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Example:
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summary = format_weather_summary(weather_data)
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# "Currently 72°F and Partly Cloudy. Humidity: 65%"
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"""
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temp_data = weather.get("temperature", {})
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temp = temp_data.get("value")
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unit = temp_data.get("unit", "F")
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phrase = weather.get("phrase", "Conditions unavailable")
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humidity = weather.get("relativeHumidity")
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# Build summary
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parts = []
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if temp is not None:
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parts.append(f"Currently {int(temp)}°{unit}")
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parts.append(phrase)
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if humidity is not None:
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parts.append(f"Humidity: {humidity}%")
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summary = " and ".join(parts[:2])
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if len(parts) > 2:
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summary += f". {parts[2]}"
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return summary
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def clear_weather_cache():
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"""
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🧹 Clears the weather cache.
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| 405 |
-
|
| 406 |
-
Useful for testing or if fresh data is needed immediately.
|
| 407 |
-
"""
|
| 408 |
-
global _weather_cache
|
| 409 |
-
cache_size = len(_weather_cache)
|
| 410 |
-
_weather_cache.clear()
|
| 411 |
-
logger.info(f"🧹 Weather cache cleared ({cache_size} entries removed)")
|
| 412 |
-
|
| 413 |
-
|
| 414 |
-
def get_cache_stats() -> Dict[str, Any]:
|
| 415 |
-
"""
|
| 416 |
-
📊 Returns weather cache statistics.
|
| 417 |
-
|
| 418 |
-
Returns:
|
| 419 |
-
Dictionary with cache statistics:
|
| 420 |
-
- entries: int (number of cached locations)
|
| 421 |
-
- oldest_entry_age_seconds: float
|
| 422 |
-
- newest_entry_age_seconds: float
|
| 423 |
-
"""
|
| 424 |
-
if not _weather_cache:
|
| 425 |
-
return {
|
| 426 |
-
"entries": 0,
|
| 427 |
-
"oldest_entry_age_seconds": None,
|
| 428 |
-
"newest_entry_age_seconds": None
|
| 429 |
-
}
|
| 430 |
-
|
| 431 |
-
now = datetime.now()
|
| 432 |
-
ages = [
|
| 433 |
-
(now - cached_time).total_seconds()
|
| 434 |
-
for _, cached_time in _weather_cache.values()
|
| 435 |
-
]
|
| 436 |
-
|
| 437 |
-
return {
|
| 438 |
-
"entries": len(_weather_cache),
|
| 439 |
-
"oldest_entry_age_seconds": max(ages) if ages else None,
|
| 440 |
-
"newest_entry_age_seconds": min(ages) if ages else None
|
| 441 |
-
}
|
| 442 |
-
|
| 443 |
-
|
| 444 |
-
# ============================================================
|
| 445 |
-
# HEALTH CHECK
|
| 446 |
-
# ============================================================
|
| 447 |
-
|
| 448 |
-
def get_weather_agent_health() -> Dict[str, Any]:
|
| 449 |
-
"""
|
| 450 |
-
📊 Returns weather agent health status.
|
| 451 |
-
|
| 452 |
-
Used by the main application health check endpoint to monitor
|
| 453 |
-
the weather service availability and performance.
|
| 454 |
-
|
| 455 |
-
Returns:
|
| 456 |
-
Dictionary with health information
|
| 457 |
-
"""
|
| 458 |
-
cache_stats = get_cache_stats()
|
| 459 |
-
|
| 460 |
-
# MODIFIED - USES FLAG INSTEAD OF CHECKING ENV VAR
|
| 461 |
-
return {
|
| 462 |
-
"status": "operational" if _WEATHER_SERVICE_AVAILABLE else "degraded",
|
| 463 |
-
"service": "azure_maps_weather",
|
| 464 |
-
"api_key_configured": _WEATHER_SERVICE_AVAILABLE,
|
| 465 |
-
"cache": cache_stats,
|
| 466 |
-
"cache_ttl_seconds": CACHE_TTL_SECONDS,
|
| 467 |
-
"default_timeout_seconds": DEFAULT_TIMEOUT,
|
| 468 |
-
"features": {
|
| 469 |
-
"real_time_weather": True,
|
| 470 |
-
"outfit_recommendations": True,
|
| 471 |
-
"event_recommendations": True,
|
| 472 |
-
"response_caching": True
|
| 473 |
-
}
|
| 474 |
-
}
|
| 475 |
-
|
| 476 |
-
|
| 477 |
-
# ============================================================
|
| 478 |
-
# TESTING
|
| 479 |
-
# ============================================================
|
| 480 |
-
|
| 481 |
-
if __name__ == "__main__":
|
| 482 |
-
"""🧪 Test weather agent functionality"""
|
| 483 |
-
import asyncio
|
| 484 |
-
|
| 485 |
-
print("=" * 60)
|
| 486 |
-
print("🧪 Testing Weather Agent")
|
| 487 |
-
print("=" * 60)
|
| 488 |
-
|
| 489 |
-
async def run_tests():
|
| 490 |
-
# Test location: Atlanta, GA
|
| 491 |
-
lat, lon = 33.7490, -84.3880
|
| 492 |
-
|
| 493 |
-
print(f"\n--- Test 1: Fetch Weather ---")
|
| 494 |
-
print(f"Location: {lat}, {lon} (Atlanta, GA)")
|
| 495 |
-
|
| 496 |
-
try:
|
| 497 |
-
weather = await get_weather_for_location(lat, lon)
|
| 498 |
-
print(f"✅ Weather fetched successfully")
|
| 499 |
-
print(f"Temperature: {weather.get('temperature', {}).get('value')}°F")
|
| 500 |
-
print(f"Condition: {weather.get('phrase')}")
|
| 501 |
-
print(f"Precipitation: {weather.get('hasPrecipitation')}")
|
| 502 |
-
|
| 503 |
-
print(f"\n--- Test 2: Weather Summary ---")
|
| 504 |
-
summary = format_weather_summary(weather)
|
| 505 |
-
print(f"Summary: {summary}")
|
| 506 |
-
|
| 507 |
-
print(f"\n--- Test 3: Outfit Recommendation ---")
|
| 508 |
-
temp = weather.get('temperature', {}).get('value', 70)
|
| 509 |
-
condition = weather.get('phrase', 'Clear')
|
| 510 |
-
outfit = recommend_outfit(temp, condition)
|
| 511 |
-
print(f"Outfit: {outfit}")
|
| 512 |
-
|
| 513 |
-
print(f"\n--- Test 4: Event Recommendations ---")
|
| 514 |
-
recs = weather_to_event_recommendations(weather)
|
| 515 |
-
for rec in recs:
|
| 516 |
-
print(f"Type: {rec['type']}")
|
| 517 |
-
print(f"Reason: {rec['reason']}")
|
| 518 |
-
print(f"Suggestions: {', '.join(rec['suggestions'][:2])}")
|
| 519 |
-
|
| 520 |
-
print(f"\n--- Test 5: Cache Test ---")
|
| 521 |
-
weather2 = await get_weather_for_location(lat, lon, use_cache=True)
|
| 522 |
-
print(f"✅ Cache working (should be instant)")
|
| 523 |
-
|
| 524 |
-
print(f"\n--- Test 6: Health Check ---")
|
| 525 |
-
health = get_weather_agent_health()
|
| 526 |
-
print(f"Status: {health['status']}")
|
| 527 |
-
print(f"Cache entries: {health['cache']['entries']}")
|
| 528 |
-
|
| 529 |
-
except Exception as e:
|
| 530 |
-
print(f"❌ Error: {e}")
|
| 531 |
-
|
| 532 |
-
asyncio.run(run_tests())
|
| 533 |
-
|
| 534 |
-
print("\n" + "=" * 60)
|
| 535 |
-
print("✅ Tests complete")
|
|
|
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