Update app.py

app.py

@@ -618,16 +618,27 @@ def weather_agent_tool(query: str) -> str:
         hour_str = closest_hour["time"].split(" ")[1]
 
         summary_prompt = f"""
-        Summarise this weather forecast naturally:
-        Location: {location}
-        Time: {target_dt.strftime('%Y-%m-%d')} at {hour_str}
-        Condition: {condition}
-        Temp: {temp}°C (Feels like {feels}°C)
-        Humidity: {humidity}%
-        Chance of rain: {chance_rain}%
-
-        Make it short, friendly, and human-style.
-        """
+You are a weather analyst. Below is detailed weather data for a specific time and location.
+
+Your task: Based on the user's question, **reason step-by-step** which information is most relevant, then provide a concise, human-readable answer in British English.
+
+--- Weather Data ---
+Location: {location}
+Time: {target_dt.strftime('%Y-%m-%d')} at {hour_str}
+Condition: {condition}
+Temperature: {temp}°C (Feels like {feels}°C)
+Humidity: {humidity}%
+Chance of rain: {chance_rain}%
+Chance of snow: {closest_hour.get("chance_of_snow", 0)}%
+Wind speed: {closest_hour.get("wind_kph", 'N/A')} kph
+UV index: {closest_hour.get("uv", 'N/A')}
+Cloud cover: {closest_hour.get("cloud", 'N/A')}%
+
+--- User Query ---
+"{query}"
+
+Step-by-step reasoning and final answer:
+"""
         response = llm_gpt4.invoke(summary_prompt)
         return response.content.strip() if isinstance(response, AIMessage) else str(response)
 
@@ -715,16 +726,27 @@ def weather_tool(query: str) -> str:
         hour_str = closest_hour["time"].split(" ")[1]
 
         summary_prompt = f"""
-        Summarise this weather forecast naturally:
-        Location: {location}
-        Time: {target_dt.strftime('%Y-%m-%d')} at {hour_str}
-        Condition: {condition}
-        Temp: {temp}°C (Feels like {feels}°C)
-        Humidity: {humidity}%
-        Chance of rain: {chance_rain}%
-
-        Make it short, friendly, and human-style.
-        """
+You are a weather analyst. Below is detailed weather data for a specific time and location.
+
+Your task: Based on the user's question, **reason step-by-step** which information is most relevant, then provide a concise, human-readable answer in British English.
+
+--- Weather Data ---
+Location: {location}
+Time: {target_dt.strftime('%Y-%m-%d')} at {hour_str}
+Condition: {condition}
+Temperature: {temp}°C (Feels like {feels}°C)
+Humidity: {humidity}%
+Chance of rain: {chance_rain}%
+Chance of snow: {closest_hour.get("chance_of_snow", 0)}%
+Wind speed: {closest_hour.get("wind_kph", 'N/A')} kph
+UV index: {closest_hour.get("uv", 'N/A')}
+Cloud cover: {closest_hour.get("cloud", 'N/A')}%
+
+--- User Query ---
+"{query}"
+
+Step-by-step reasoning and final answer:
+"""
         response = llm_gpt4.invoke(summary_prompt)
         return response.content.strip() if isinstance(response, AIMessage) else str(response)