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"""
π€οΈ PENNY Weather Agent - Azure Maps Integration
Provides real-time weather information and weather-aware recommendations
for civic engagement activities.
MISSION: Help residents plan their day with accurate weather data and
smart suggestions for indoor/outdoor activities based on conditions.
ENHANCEMENTS (Phase 1 Complete):
- β
Structured logging with performance tracking
- β
Enhanced error handling with graceful degradation
- β
Type hints for all functions
- β
Health check integration
- β
Response caching for performance
- β
Detailed weather parsing with validation
- β
Penny's friendly voice in all responses
Production-ready for Azure ML deployment.
"""
import os
import logging
import time
from typing import Dict, Any, Optional, List, Tuple
from datetime import datetime, timedelta
import httpx
# --- ENHANCED MODULE IMPORTS ---
from app.logging_utils import log_interaction
# --- LOGGING SETUP ---
logger = logging.getLogger(__name__)
# --- CONFIGURATION ---
AZURE_WEATHER_URL = "https://atlas.microsoft.com/weather/currentConditions/json"
DEFAULT_TIMEOUT = 10.0 # seconds
CACHE_TTL_SECONDS = 300 # 5 minutes - weather doesn't change that fast
# --- CHECK API KEY AVAILABILITY AT MODULE LOAD (NEW - PREVENTS IMPORT FAILURES) ---
AZURE_MAPS_KEY = os.getenv("AZURE_WEATHER_KEY") or os.getenv("AZURE_MAPS_KEY")
if not AZURE_MAPS_KEY:
logger.warning("β οΈ AZURE_MAPS_KEY not configured - weather features will be limited")
_WEATHER_SERVICE_AVAILABLE = False
else:
logger.info("β
AZURE_MAPS_KEY configured")
_WEATHER_SERVICE_AVAILABLE = True
# --- WEATHER CACHE ---
_weather_cache: Dict[str, Tuple[Dict[str, Any], datetime]] = {}
# ============================================================
# WEATHER DATA RETRIEVAL
# ============================================================
async def get_weather_for_location(
lat: float,
lon: float,
use_cache: bool = True
) -> Dict[str, Any]:
"""
π€οΈ Fetches real-time weather from Azure Maps.
Retrieves current weather conditions for a specific location using
Azure Maps Weather API. Includes caching to reduce API calls and
improve response times.
Args:
lat: Latitude coordinate
lon: Longitude coordinate
use_cache: Whether to use cached data if available (default: True)
Returns:
Dictionary containing weather data with keys:
- temperature: {value: float, unit: str}
- phrase: str (weather description)
- iconCode: int
- hasPrecipitation: bool
- isDayTime: bool
- relativeHumidity: int
- cloudCover: int
- etc.
Raises:
RuntimeError: If AZURE_MAPS_KEY is not configured
httpx.HTTPError: If API request fails
Example:
weather = await get_weather_for_location(33.7490, -84.3880)
temp = weather.get("temperature", {}).get("value")
condition = weather.get("phrase", "Unknown")
"""
start_time = time.time()
# Create cache key
cache_key = f"{lat:.4f},{lon:.4f}"
# Check cache first
if use_cache and cache_key in _weather_cache:
cached_data, cached_time = _weather_cache[cache_key]
age = (datetime.now() - cached_time).total_seconds()
if age < CACHE_TTL_SECONDS:
logger.info(
f"π€οΈ Weather cache hit (age: {age:.0f}s, "
f"location: {cache_key})"
)
return cached_data
# Check if service is available (MODIFIED - USES FLAG INSTEAD OF CHECKING ENV VAR)
if not _WEATHER_SERVICE_AVAILABLE:
logger.error("β AZURE_MAPS_KEY not configured")
raise RuntimeError(
"AZURE_MAPS_KEY is required and not set in environment variables."
)
# Build request parameters
params = {
"api-version": "1.0",
"query": f"{lat},{lon}",
"subscription-key": AZURE_MAPS_KEY,
"details": "true",
"language": "en-US",
}
try:
logger.info(f"π€οΈ Fetching weather for location: {cache_key}")
async with httpx.AsyncClient(timeout=DEFAULT_TIMEOUT) as client:
response = await client.get(AZURE_WEATHER_URL, params=params)
response.raise_for_status()
data = response.json()
# Parse response
if "results" in data and len(data["results"]) > 0:
weather_data = data["results"][0]
else:
weather_data = data # Fallback if structure changes
# Validate essential fields
weather_data = _validate_weather_data(weather_data)
# Cache the result
_weather_cache[cache_key] = (weather_data, datetime.now())
# Calculate response time
response_time = (time.time() - start_time) * 1000
# Log successful retrieval
log_interaction(
tenant_id="weather_service",
interaction_type="weather_fetch",
intent="weather",
response_time_ms=response_time,
success=True,
metadata={
"location": cache_key,
"cached": False,
"temperature": weather_data.get("temperature", {}).get("value"),
"condition": weather_data.get("phrase")
}
)
logger.info(
f"β
Weather fetched successfully ({response_time:.0f}ms, "
f"location: {cache_key})"
)
return weather_data
except httpx.TimeoutException as e:
logger.error(f"β±οΈ Weather API timeout: {e}")
raise
except httpx.HTTPStatusError as e:
logger.error(f"β Weather API HTTP error: {e.response.status_code}")
raise
except Exception as e:
logger.error(f"β Weather API error: {e}", exc_info=True)
raise
def _validate_weather_data(data: Dict[str, Any]) -> Dict[str, Any]:
"""
Validates and normalizes weather data from Azure Maps.
Ensures essential fields are present with sensible defaults.
"""
# Ensure temperature exists
if "temperature" not in data:
data["temperature"] = {"value": None, "unit": "F"}
elif isinstance(data["temperature"], (int, float)):
# Handle case where temperature is just a number
data["temperature"] = {"value": data["temperature"], "unit": "F"}
# Ensure phrase exists
if "phrase" not in data or not data["phrase"]:
data["phrase"] = "Conditions unavailable"
# Ensure boolean flags exist
data.setdefault("hasPrecipitation", False)
data.setdefault("isDayTime", True)
# Ensure numeric fields exist
data.setdefault("relativeHumidity", None)
data.setdefault("cloudCover", None)
data.setdefault("iconCode", None)
return data
# ============================================================
# OUTFIT RECOMMENDATIONS
# ============================================================
def recommend_outfit(high_temp: float, condition: str) -> str:
"""
π Recommends what to wear based on weather conditions.
Provides friendly, practical clothing suggestions based on
temperature and weather conditions.
Args:
high_temp: Expected high temperature in Fahrenheit
condition: Weather condition description (e.g., "Sunny", "Rainy")
Returns:
Friendly outfit recommendation string
Example:
outfit = recommend_outfit(85, "Sunny")
# Returns: "Light clothes, sunscreen, and stay hydrated! βοΈ"
"""
condition_lower = condition.lower()
# Check for precipitation first
if "rain" in condition_lower or "storm" in condition_lower:
logger.debug(f"Outfit rec: Rain/Storm (temp: {high_temp}Β°F)")
return "Bring an umbrella or rain jacket! β"
# Temperature-based recommendations
if high_temp >= 85:
logger.debug(f"Outfit rec: Hot (temp: {high_temp}Β°F)")
return "Light clothes, sunscreen, and stay hydrated! βοΈ"
if high_temp >= 72:
logger.debug(f"Outfit rec: Warm (temp: {high_temp}Β°F)")
return "T-shirt and jeans or a casual dress. π"
if high_temp >= 60:
logger.debug(f"Outfit rec: Mild (temp: {high_temp}Β°F)")
return "A hoodie or light jacket should do! π§₯"
logger.debug(f"Outfit rec: Cold (temp: {high_temp}Β°F)")
return "Bundle up β sweater or coat recommended! π§£"
# ============================================================
# EVENT RECOMMENDATIONS BASED ON WEATHER
# ============================================================
def weather_to_event_recommendations(
weather: Dict[str, Any]
) -> List[Dict[str, Any]]:
"""
π
Suggests activity types based on current weather conditions.
Analyzes weather data to provide smart recommendations for
indoor vs outdoor activities, helping residents plan their day.
Args:
weather: Weather data dictionary from get_weather_for_location()
Returns:
List of recommendation dictionaries with keys:
- type: str ("indoor", "outdoor", "neutral")
- suggestions: List[str] (specific activity ideas)
- reason: str (explanation for recommendation)
- priority: int (1-3, added for sorting)
Example:
weather = await get_weather_for_location(33.7490, -84.3880)
recs = weather_to_event_recommendations(weather)
for rec in recs:
print(f"{rec['type']}: {rec['suggestions']}")
"""
condition = (weather.get("phrase") or "").lower()
temp = weather.get("temperature", {}).get("value")
has_precipitation = weather.get("hasPrecipitation", False)
recs = []
# Check for rain or storms (highest priority)
if "rain" in condition or "storm" in condition or has_precipitation:
logger.debug("Event rec: Indoor (precipitation)")
recs.append({
"type": "indoor",
"suggestions": [
"Visit a library π",
"Check out a community center event ποΈ",
"Find an indoor workshop or class π¨",
"Explore a local museum πΌοΈ"
],
"reason": "Rainy weather makes indoor events ideal!",
"priority": 1
})
# Warm weather outdoor activities
elif temp is not None and temp >= 75:
logger.debug(f"Event rec: Outdoor (warm: {temp}Β°F)")
recs.append({
"type": "outdoor",
"suggestions": [
"Visit a park π³",
"Check out a farmers market π₯",
"Look for outdoor concerts or festivals π΅",
"Enjoy a community picnic or BBQ π"
],
"reason": "Beautiful weather for outdoor activities!",
"priority": 1
})
# Cold weather considerations
elif temp is not None and temp < 50:
logger.debug(f"Event rec: Indoor (cold: {temp}Β°F)")
recs.append({
"type": "indoor",
"suggestions": [
"Browse local events at community centers ποΈ",
"Visit a museum or art gallery πΌοΈ",
"Check out indoor markets or shopping ποΈ",
"Warm up at a local cafΓ© or restaurant β"
],
"reason": "Chilly weather β indoor activities are cozy!",
"priority": 1
})
# Mild/neutral weather
else:
logger.debug(f"Event rec: Neutral (mild: {temp}Β°F if temp else 'unknown')")
recs.append({
"type": "neutral",
"suggestions": [
"Browse local events π
",
"Visit a museum or cultural center ποΈ",
"Walk around a local plaza or downtown πΆ",
"Check out both indoor and outdoor activities π"
],
"reason": "Mild weather gives you flexible options!",
"priority": 2
})
return recs
# ============================================================
# HELPER FUNCTIONS
# ============================================================
def format_weather_summary(weather: Dict[str, Any]) -> str:
"""
π Formats weather data into a human-readable summary.
Args:
weather: Weather data dictionary
Returns:
Formatted weather summary string with Penny's friendly voice
Example:
summary = format_weather_summary(weather_data)
# "Currently 72Β°F and Partly Cloudy. Humidity: 65%"
"""
temp_data = weather.get("temperature", {})
temp = temp_data.get("value")
unit = temp_data.get("unit", "F")
phrase = weather.get("phrase", "Conditions unavailable")
humidity = weather.get("relativeHumidity")
# Build summary
parts = []
if temp is not None:
parts.append(f"Currently {int(temp)}Β°{unit}")
parts.append(phrase)
if humidity is not None:
parts.append(f"Humidity: {humidity}%")
summary = " and ".join(parts[:2])
if len(parts) > 2:
summary += f". {parts[2]}"
return summary
def clear_weather_cache():
"""
π§Ή Clears the weather cache.
Useful for testing or if fresh data is needed immediately.
"""
global _weather_cache
cache_size = len(_weather_cache)
_weather_cache.clear()
logger.info(f"π§Ή Weather cache cleared ({cache_size} entries removed)")
def get_cache_stats() -> Dict[str, Any]:
"""
π Returns weather cache statistics.
Returns:
Dictionary with cache statistics:
- entries: int (number of cached locations)
- oldest_entry_age_seconds: float
- newest_entry_age_seconds: float
"""
if not _weather_cache:
return {
"entries": 0,
"oldest_entry_age_seconds": None,
"newest_entry_age_seconds": None
}
now = datetime.now()
ages = [
(now - cached_time).total_seconds()
for _, cached_time in _weather_cache.values()
]
return {
"entries": len(_weather_cache),
"oldest_entry_age_seconds": max(ages) if ages else None,
"newest_entry_age_seconds": min(ages) if ages else None
}
# ============================================================
# HEALTH CHECK
# ============================================================
def get_weather_agent_health() -> Dict[str, Any]:
"""
π Returns weather agent health status.
Used by the main application health check endpoint to monitor
the weather service availability and performance.
Returns:
Dictionary with health information
"""
cache_stats = get_cache_stats()
# MODIFIED - USES FLAG INSTEAD OF CHECKING ENV VAR
return {
"status": "operational" if _WEATHER_SERVICE_AVAILABLE else "degraded",
"service": "azure_maps_weather",
"api_key_configured": _WEATHER_SERVICE_AVAILABLE,
"cache": cache_stats,
"cache_ttl_seconds": CACHE_TTL_SECONDS,
"default_timeout_seconds": DEFAULT_TIMEOUT,
"features": {
"real_time_weather": True,
"outfit_recommendations": True,
"event_recommendations": True,
"response_caching": True
}
}
# ============================================================
# TESTING
# ============================================================
if __name__ == "__main__":
"""π§ͺ Test weather agent functionality"""
import asyncio
print("=" * 60)
print("π§ͺ Testing Weather Agent")
print("=" * 60)
async def run_tests():
# Test location: Atlanta, GA
lat, lon = 33.7490, -84.3880
print(f"\n--- Test 1: Fetch Weather ---")
print(f"Location: {lat}, {lon} (Atlanta, GA)")
try:
weather = await get_weather_for_location(lat, lon)
print(f"β
Weather fetched successfully")
print(f"Temperature: {weather.get('temperature', {}).get('value')}Β°F")
print(f"Condition: {weather.get('phrase')}")
print(f"Precipitation: {weather.get('hasPrecipitation')}")
print(f"\n--- Test 2: Weather Summary ---")
summary = format_weather_summary(weather)
print(f"Summary: {summary}")
print(f"\n--- Test 3: Outfit Recommendation ---")
temp = weather.get('temperature', {}).get('value', 70)
condition = weather.get('phrase', 'Clear')
outfit = recommend_outfit(temp, condition)
print(f"Outfit: {outfit}")
print(f"\n--- Test 4: Event Recommendations ---")
recs = weather_to_event_recommendations(weather)
for rec in recs:
print(f"Type: {rec['type']}")
print(f"Reason: {rec['reason']}")
print(f"Suggestions: {', '.join(rec['suggestions'][:2])}")
print(f"\n--- Test 5: Cache Test ---")
weather2 = await get_weather_for_location(lat, lon, use_cache=True)
print(f"β
Cache working (should be instant)")
print(f"\n--- Test 6: Health Check ---")
health = get_weather_agent_health()
print(f"Status: {health['status']}")
print(f"Cache entries: {health['cache']['entries']}")
except Exception as e:
print(f"β Error: {e}")
asyncio.run(run_tests())
print("\n" + "=" * 60)
print("β
Tests complete") |