Update app.py

app.py

@@ -18,9 +18,9 @@ def get_weather_and_insight(city):
     temp = data.get('main', {}).get('temp')
     description = data.get('weather', [{}])[0].get('description')
 
-    # Generating a creative weather summary using LangChain LLM
+    # Generate a creative weather summary using LangChain LLM
     groq_api_key = os.getenv("GROQ_API_KEY")
-    system = f"Today in {city}, it feels like {temp}°C with {humidity}% humidity. The sky is {description}. Can you share a fun fact about {city}?"
+    system = f"Local weather update for {city}: {temp}°C, {description}. Provide a fun fact about {city}."
     human = "{text}"
     prompt = ChatPromptTemplate.from_messages(
         [("system", system), ("human", human)]
@@ -29,11 +29,11 @@ def get_weather_and_insight(city):
     chain = prompt | chat | StrOutputParser()
     output = chain.invoke({"text": city})
 
-    # Adding emojis for visual flair
+    # Add emojis for visual flair
     weather_emoji = "☀️" if "clear" in description else "☁️" if "cloud" in description else "🌧️" if "rain" in description else "❄️" if "snow" in description else "🌫️"
     
-    # Creating the final response string
-    final_response = f"📍 {city.upper()} Update: {output} {weather_emoji}"
+    # Create the final response string, avoiding repetition
+    final_response = f"🌍 Weather Update for {city}: {temp}°C, {humidity}% humidity, described as {description} {weather_emoji}. Insight: {output}"
 
     return final_response
 
@@ -43,7 +43,7 @@ iface = gr.Interface(
     inputs=gr.Textbox(label="Enter City Name", placeholder="Type city here..."),
     outputs=gr.Textbox(label="Weather Report and Insight"),
     title="WeatherAssistantApp",
-    description="Enter a city name to get a concise weather report with an engaging AI-generated city insight."
+    description="Enter a city name to get a concise weather report with an AI-generated insight."
 )
 
 iface.launch()