# app.py

# from flask import Flask,request,jsonify
# from flask_cors import CORS
# app = Flask(__name__)
# cors = CORS(app, resources={r"*": {"origins": "*"}})
from fastapi import FastAPI
import uvicorn
import logging
import time

# Configure logging
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
logger = logging.getLogger(__name__)

# loading the data from the csv file to apandas dataframe
app = FastAPI(title="Rainwater Harvesting API", version="1.0.0")
from huggingface_hub import login
from huggingface_hub import hf_hub_download
from RoofTopCalculation import RooftTopCalculation
from RainFallModel import calculate_rainfall
import os
# Use /app as primary cache directory for Hugging Face Spaces
cache_dir = '/app/hf_cache'
# Fallback cache directory if /app is not writable
fallback_cache_dir = '/tmp/hf_cache'
os.makedirs(cache_dir, exist_ok=True)
os.makedirs(fallback_cache_dir, exist_ok=True)
repo_id = "Navanihk/rainfallPrediction"
import pandas as pd

@app.get("/")
def read_root():
    return {"message": "Rainwater Harvesting API", "status": "running", "version": "1.0"}

@app.get("/health")
def health_check():
    return {"status": "healthy", "timestamp": pd.Timestamp.now().isoformat()}

@app.get("/logs")
def get_logs():
    return {"logs": "Application is running normally", "status": "ok"}

@app.post('/api/roofTopCalculation')
def roof_top_calculation(data: dict):
    start_time = time.time()
    logger.info(f"Received roof top calculation request for location: {data.get('location', 'Unknown')}")
    
    try:
        # Try to download from Hugging Face Hub with fallback cache directories
        try:
            csv_path = hf_hub_download(repo_id=repo_id, filename="rainfall_updated.csv", cache_dir=cache_dir)
            logger.info("Successfully downloaded rainfall data from Hugging Face Hub")
        except PermissionError:
            # Try fallback cache directory
            csv_path = hf_hub_download(repo_id=repo_id, filename="rainfall_updated.csv", cache_dir=fallback_cache_dir)
            logger.info("Successfully downloaded rainfall data using fallback cache directory")
        
        RainFallData = pd.read_csv(csv_path)
        logger.info(f"Loaded rainfall data with {len(RainFallData)} records")
    except Exception as e:
        logger.error(f"Error downloading from Hugging Face Hub: {e}")
        # Fallback: use a basic DataFrame with essential data for calculations
        # This ensures the API continues to work even if the download fails
        RainFallData = pd.DataFrame({
            'state': ['Delhi', 'Maharashtra', 'Karnataka', 'Tamil Nadu'],
            'district': ['New Delhi', 'Mumbai', 'Bangalore', 'Chennai'],
            'rainfall': [700, 2200, 970, 1400]  # Average rainfall in mm/year
        })
        logger.info("Using fallback rainfall data")
    
    try:
        if not data:
            logger.warning("No data provided in request")
            return {"error": "No data provided"}, 400

        # Perform roof top calculation logic
        result = RooftTopCalculation(data, RainFallData)
        
        end_time = time.time()
        processing_time = round(end_time - start_time, 2)
        logger.info(f"Successfully completed calculation in {processing_time} seconds")
        
        return result

    except Exception as e:
        logger.error(f"Error during calculation: {str(e)}")
        return {"error": str(e)}, 500

# Run the app if the script is executed directly
if __name__ == "__main__":
    import os
    port = int(os.environ.get("PORT", 7860))  # Hugging Face Spaces uses port 7860
    uvicorn.run(app, host="0.0.0.0", port=port)