Update app.py

app.py

@@ -2,16 +2,14 @@ import gradio as gr
 import requests
 from datetime import datetime, timedelta
 
-# Constants
-API_KEY = '91b23cab82ee530b2052c8757e343b0d'
-OPENAI_API_KEY = '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'
+API_KEY = "91b23cab82ee530b2052c8757e343b0d"
 
 def kelvin_to_celsius(temp_kelvin):
     return temp_kelvin - 273.15
 
-def get_weather(city_name, api_key):
+def get_weather(city_name):
     base_url = "http://api.openweathermap.org/data/2.5/weather?"
-    complete_url = base_url + "q=" + city_name + "&appid=" + api_key
+    complete_url = base_url + "q=" + city_name + "&appid=" + API_KEY
     response = requests.get(complete_url)
     data = response.json()
     
@@ -20,59 +18,31 @@ def get_weather(city_name, api_key):
         weather_data = data.get("weather", [{}])[0]
         temperature = kelvin_to_celsius(main_data.get("temp", 0))
         weather_description = weather_data.get("description", "N/A")
-        timezone = data.get("timezone", 0)  # Timezone offset in seconds from UTC
-        
-        # Convert UTC current time to city's local time
-        local_time = datetime.utcnow() + timedelta(seconds=timezone)
-        formatted_time = local_time.strftime('%H:%M:%S')  # 24-hour format
-        
-        return temperature, weather_description, formatted_time
+        timezone = data.get("timezone", 0)
+        local_time = (datetime.utcnow() + timedelta(seconds=timezone)).strftime('%H:%M:%S')
+        return temperature, weather_description, local_time
     else:
         return None
 
-def openai_create(prompt):
-    openai_url = "https://api.openai.com/v1/engines/text-davinci-003/completions"
-    headers = {
-        "Authorization": f"Bearer {OPENAI_API_KEY}",
-        "Content-Type": "application/json"
-    }
-    data = {
-        "prompt": prompt,
-        "temperature": 0.7,
-        "max_tokens": 256,
-        "top_p": 1,
-        "frequency_penalty": 0,
-        "presence_penalty": 0.6,
-        "stop": ["\n"]
-    }
-    response = requests.post(openai_url, headers=headers, json=data)
-    response_data = response.json()
-    summary = response_data['choices'][0]['text'].strip()
-    return summary
-
 def summarize_weather(city1, city2):
-    weather1 = get_weather(city1, API_KEY)
-    weather2 = get_weather(city2, API_KEY)
+    weather1 = get_weather(city1)
+    weather2 = get_weather(city2)
     
     if weather1 and weather2:
-        comparison = f"""
-        Can you provide a concise summary for the following weather information? 
-        In {city1}, the current weather is {weather1[1]} with a temperature of {weather1[0]:.2f}°C. The local time is {weather1[2]}.
-        Meanwhile, in {city2}, it's {weather2[1]} and the temperature is {weather2[0]:.2f}°C. The local time there is {weather2[2]}.
-        """
-        summary = openai_create(comparison)
+        summary = (f"In {city1} it's {weather1[2]} and {weather1[1]} with {weather1[0]:.2f}°C, "
+                   f"while in {city2} it's {weather2[2]} and {weather2[1]} with {weather2[0]:.2f}°C.")
         return summary
     else:
         return "Error fetching weather data for one or both cities."
 
-# Gradio interface
 interface = gr.Interface(
     fn=summarize_weather,
     inputs=[
-        gr.Textbox(placeholder="Enter City 1 (e.g., New York)"),
-        gr.Textbox(placeholder="Enter City 2 (e.g., Los Angeles)")
+        gr.Textbox(placeholder="Enter City 1"),
+        gr.Textbox(placeholder="Enter City 2")
     ],
     outputs="text"
 )
 
-interface.launch()
+if __name__ == "__main__":
+    interface.launch()