main.py

# main.py

import os
from dotenv import load_dotenv
from datetime import datetime, timedelta
import json

from config import CITIES
from services.weather import fetch_weather_data
from services.llm import get_weather_analysis

load_dotenv()

def process_data_for_llm(weather_data_list):
    """
    Transforms the raw weather data list into a clean, formatted string for the LLM.
    """
    print("\nProcessing data for LLM...")
    final_report = f"Weather forecast overview for {datetime.now().strftime('%A, %B %d, %Y')}:\n\n"
    
    for data in weather_data_list:
        city_name = data.get('city_name', 'Unknown City')
        final_report += f"--- {city_name} ---\n"
        
        # We only want the forecast for the next 5 days
        for i, daily_forecast in enumerate(data['daily'][:5]):
            # Get the date for the forecast day
            forecast_date = datetime.now() + timedelta(days=i)
            day_of_week = forecast_date.strftime('%A')
            
            # Safely get values from the dictionary
            max_temp = daily_forecast.get('temp', {}).get('max', 'N/A')
            min_temp = daily_forecast.get('temp', {}).get('min', 'N/A')
            weather_desc = daily_forecast.get('weather', [{}])[0].get('description', 'N/A')
            precip_prob = int(daily_forecast.get('pop', 0) * 100)
            final_report += f"{day_of_week}: {weather_desc}, High: {max_temp}°C, Low: {min_temp}°C, Precipitation: {precip_prob}%\n"
        final_report += "\n"
    return final_report


def main():
    """
    The main function to orchestrate the Kairos workflow.
    """
    print("Running Kairos orchestrator...")
    if not os.getenv('OPENWEATHER_API_KEY') or not os.getenv('OPENROUTER_API_KEY'):
        print("Error: Required API keys not found in .env file.")
        return

    all_weather_data = []
    for city in CITIES:
        print(f"Fetching weather for {city['name']}...")
        weather_report = fetch_weather_data(os.getenv('OPENWEATHER_API_KEY'), city['lat'], city['lon'])
        if weather_report:
            weather_report['city_name'] = city['name']
            all_weather_data.append(weather_report)

    if not all_weather_data:
        print("Could not fetch any weather data. Exiting.")
        return
    
    print(f"\nSuccessfully fetched weather data for {len(all_weather_data)} cities.")
    
    llm_ready_data = process_data_for_llm(all_weather_data)
    
    analysis_result = get_weather_analysis(llm_ready_data)
    
    if analysis_result:
        print("\n--- Kairos Recommendation ---")
        print(json.dumps(analysis_result, indent=2))
        print("\nWorkflow complete!")
    else:
        print("\nCould not get weather analysis. Workflow stopped.")

if __name__ == "__main__":
    main()