app.py

import openai
import requests
import gradio as gr

# Set up your OpenAI API key
openai.api_key = "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"

# Function to get weather data from Open-Meteo API
def get_weather_data(city):
    geocode_url = f"https://geocoding-api.open-meteo.com/v1/search?name={city}&count=1"
    geocode_response = requests.get(geocode_url)
    
    if geocode_response.status_code == 200 and geocode_response.json().get("results"):
        location_data = geocode_response.json()["results"][0]
        latitude = location_data["latitude"]
        longitude = location_data["longitude"]
    else:
        return {"error": "City not found or API issue"}
    
    weather_url = f"https://api.open-meteo.com/v1/forecast?latitude={latitude}&longitude={longitude}&current_weather=true"
    weather_response = requests.get(weather_url)
    
    if weather_response.status_code == 200:
        weather_data = weather_response.json()["current_weather"]
        weather_info = {
            "city": location_data["name"],
            "temperature": weather_data["temperature"],
            "description": "Clear skies" if weather_data["weathercode"] == 0 else "Cloudy or other conditions"
        }
        return weather_info
    else:
        return {"error": "Weather data not available"}

# Function to use GPT Turbo with RAG (external weather data)
def ask_gpt_with_weather_rag(city):
    weather_data = get_weather_data(city)
    
    if "error" in weather_data:
        return weather_data["error"]
    
    weather_info_str = (
        f"The current weather in {weather_data['city']} is "
        f"{weather_data['temperature']}°C with {weather_data['description']}."
    )
    
    prompt = (
        f"You are a helpful assistant. Based on the following weather information:\n\n"
        f"{weather_info_str}\n\n"
        f"Can you recommend an activity suitable for this weather?"
    )
    
    response =  openai.chat.completions.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "system", "content": "You are an assistant knowledgeable about weather and activities."},
            {"role": "user", "content": prompt}
        ]
    )
    
    return response.choices[0].message.content

# Gradio Interface
def weather_activity(city):
    return ask_gpt_with_weather_rag(city)

interface = gr.Interface(
    fn=weather_activity,
    inputs=gr.Textbox(label="Enter City Name"),
    outputs=gr.Textbox(label="Suggested Activity"),
    title="Weather-Based Activity Recommendation",
    description="Enter a city name to get the current weather and GPT-based activity suggestions."
)

# Launch the Gradio interface
if __name__ == "__main__":
    interface.launch(debug=True)