Update app.py

app.py

@@ -32,22 +32,6 @@ def get_current_time_in_timezone(timezone: str = "UTC") -> str:
 
 @tool
 def get_weather_forecast(city: str = "New York", days: int = 7) -> str:
-    """
-    A tool to fetch a weekly weather forecast for a specified city.
-    
-    This function first checks for a cached forecast for the given city. If the cached
-    data is older than 10 minutes, it attempts to fetch new data from OpenWeatherMap.
-    
-    If a valid API key is not provided or an error occurs during the API call,
-    a mock forecast is generated.
-    
-    Args:
-        city (str): The city name for which to get the weather.
-        days (int): Number of days to forecast (maximum of 7).
-    
-    Returns:
-        str: A formatted summary forecast with daily averages.
-    """
     global cached_forecasts
     now_ms = int(time.time() * 1000)
 
@@ -55,100 +39,61 @@ def get_weather_forecast(city: str = "New York", days: int = 7) -> str:
     if city in cached_forecasts and now_ms - cached_forecasts[city]["timestamp"] < CACHE_DURATION_MS:
         return cached_forecasts[city]["data"]
 
-    # Your API key for OpenWeatherMap (if available); replace with a valid key if possible.
+    # Use a real API key in production
     api_key = "OPENWEATHER_API"
+    
+    # Validate API key before proceeding
+    if not api_key or api_key == "OPENWEATHER_API":
+        return "Error: Invalid or missing OpenWeather API key. Please configure a valid API key."
 
-    forecast_data = None
-
-    if api_key == "OPENWEATHER_API":
-        # No valid API key provided: generate mock forecast data.
-        forecast_lines = []
-        today = datetime.datetime.now()
-        for i in range(min(days, 7)):
-            date_obj = today + datetime.timedelta(days=i)
+    url = f"http://api.openweathermap.org/data/2.5/forecast?q={city}&appid={api_key}&units=metric"
+    try:
+        response = requests.get(url)
+        data = response.json()
+        if data.get("cod") != "200":
+            raise ValueError(data.get("message", "Error fetching weather data"))
+
+        # Process and group forecast items by day (format: YYYY-MM-DD)
+        forecast_by_day = {}
+        for item in data.get("list", []):
+            dt = datetime.datetime.utcfromtimestamp(item["dt"])
+            day_str = dt.strftime("%Y-%m-%d")
+            forecast_by_day.setdefault(day_str, []).append(item)
+
+        # Build forecast for up to 'days' days
+        sorted_days = sorted(forecast_by_day.keys())[:min(days, 7)]
+        daily_forecasts = []
+        for day_str in sorted_days:
+            day_items = forecast_by_day[day_str]
+            date_obj = datetime.datetime.strptime(day_str, "%Y-%m-%d")
             day_name = date_obj.strftime("%A")
             date_display = date_obj.strftime("%b %d")
-            temp = 15 + random.randint(0, 5)
-            humidity = 65 + random.randint(0, 15)
-            pressure = 1010 + random.randint(0, 10)
-            wind_speed = 8 + random.randint(0, 7)
-            conditions = ['partly cloudy', 'sunny', 'rain', 'overcast', 'light showers', 'clear skies', 'scattered clouds']
-            condition = conditions[i % len(conditions)]
-            forecast_lines.append(
-                f"{day_name}, {date_display}: {temp}°C, {condition} | Humidity: {humidity}% | Pressure: {pressure} hPa | Wind: {wind_speed} km/h"
+
+            total_temp = total_humidity = total_pressure = total_wind = 0
+            condition_counts = {}
+            for item in day_items:
+                total_temp += item["main"]["temp"]
+                total_humidity += item["main"]["humidity"]
+                total_pressure += item["main"]["pressure"]
+                total_wind += item["wind"]["speed"]
+                condition = item["weather"][0]["description"]
+                condition_counts[condition] = condition_counts.get(condition, 0) + 1
+
+            count = len(day_items)
+            avg_temp = round(total_temp / count)
+            avg_humidity = round(total_humidity / count)
+            avg_pressure = round(total_pressure / count)
+            avg_wind = round((total_wind / count) * 3.6)  # Convert m/s to km/h
+            most_common_condition = max(condition_counts.items(), key=lambda x: x[1])[0]
+
+            daily_forecasts.append(
+                f"{day_name}, {date_display}: {avg_temp}°C, {most_common_condition} | Humidity: {avg_humidity}% | Pressure: {avg_pressure} hPa | Wind: {avg_wind} km/h"
             )
-        forecast_data = "\n".join(forecast_lines)
-    else:
-        # Valid API key provided: fetch forecast from OpenWeatherMap.
-        url = f"http://api.openweathermap.org/data/2.5/forecast?q={city}&appid={api_key}&units=metric"
-        try:
-            response = requests.get(url)
-            data = response.json()
-            if data.get("cod") != "200":
-                raise ValueError(data.get("message", "Error fetching weather data"))
-
-            # Group forecast items by day (format: YYYY-MM-DD)
-            forecast_by_day = {}
-            for item in data.get("list", []):
-                dt = datetime.datetime.utcfromtimestamp(item["dt"])
-                day_str = dt.strftime("%Y-%m-%d")
-                forecast_by_day.setdefault(day_str, []).append(item)
-
-            # Get forecast for up to 'days' days (maximum 7)
-            sorted_days = sorted(forecast_by_day.keys())[:min(days, 7)]
-            daily_forecasts = []
-            for day_str in sorted_days:
-                day_items = forecast_by_day[day_str]
-                # Convert the day string to a date to extract day name and formatted date.
-                date_obj = datetime.datetime.strptime(day_str, "%Y-%m-%d")
-                day_name = date_obj.strftime("%A")
-                date_display = date_obj.strftime("%b %d")
-
-                total_temp = 0
-                total_humidity = 0
-                total_pressure = 0
-                total_wind = 0
-                condition_counts = {}
-
-                for item in day_items:
-                    total_temp += item["main"]["temp"]
-                    total_humidity += item["main"]["humidity"]
-                    total_pressure += item["main"]["pressure"]
-                    total_wind += item["wind"]["speed"]
-                    condition = item["weather"][0]["description"]
-                    condition_counts[condition] = condition_counts.get(condition, 0) + 1
-
-                count = len(day_items)
-                avg_temp = round(total_temp / count)
-                avg_humidity = round(total_humidity / count)
-                avg_pressure = round(total_pressure / count)
-                # Convert wind speed from m/s to km/h (approximately).
-                avg_wind = round((total_wind / count) * 3.6)
-                most_common_condition = max(condition_counts.items(), key=lambda x: x[1])[0]
-
-                daily_forecasts.append(
-                    f"{day_name}, {date_display}: {avg_temp}°C, {most_common_condition} | Humidity: {avg_humidity}% | Pressure: {avg_pressure} hPa | Wind: {avg_wind} km/h"
-                )
-            forecast_data = "\n".join(daily_forecasts)
-        except Exception as error:
-            print("Error fetching forecast from API:", error)
-            # Fallback to generating mock forecast data in case of error
-            forecast_lines = []
-            today = datetime.datetime.now()
-            for i in range(min(days, 7)):
-                date_obj = today + datetime.timedelta(days=i)
-                day_name = date_obj.strftime("%A")
-                date_display = date_obj.strftime("%b %d")
-                temp = 15 + random.randint(0, 5)
-                humidity = 65 + random.randint(0, 15)
-                pressure = 1010 + random.randint(0, 10)
-                wind_speed = 8 + random.randint(0, 7)
-                conditions = ['partly cloudy', 'sunny', 'rain', 'overcast', 'light showers', 'clear skies', 'scattered clouds']
-                condition = conditions[i % len(conditions)]
-                forecast_lines.append(
-                    f"{day_name}, {date_display}: {temp}°C, {condition} | Humidity: {humidity}% | Pressure: {pressure} hPa | Wind: {wind_speed} km/h"
-                )
-            forecast_data = "\n".join(forecast_lines)
+        forecast_data = "\n".join(daily_forecasts)
+    except Exception as error:
+        # Log the error and return an error message
+        print("Error fetching forecast from API:", error)
+        return f"Error: Unable to fetch weather data. Reason: {error}"
 
     # Cache the forecast data
     cached_forecasts[city] = {