"""
combined_app.py - A unified approach that runs both FastAPI and Streamlit in a single process.
This is specifically designed for Hugging Face Spaces deployments.
Uses lazy loading to avoid loading models during startup.
"""

import streamlit as st
import os
import sys
import threading
import time
from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
import subprocess

# Use environment variable to determine if we're in Spaces
IS_SPACE = "SPACE_ID" in os.environ

# Import FastAPI app but avoid importing modules that load models
# This is critical to prevent infinite loops during deployment
os.environ["SKIP_MODEL_LOADING"] = "1"

# Now import the FastAPI app
from api_backend import app as fastapi_app

# Add a route for checking if the API is running
@fastapi_app.get("/api-status")
def api_status():
    return {"status": "API is running"}

def run_fastapi():
    """Run the FastAPI app in a separate thread"""
    port = int(os.getenv("API_PORT", 7860))
    # Start the FastAPI server
    uvicorn.run(fastapi_app, host="0.0.0.0", port=port)

def run_streamlit():
    """Run the Streamlit app as a subprocess"""
    streamlit_cmd = [
        "streamlit", "run", "app.py",
        "--server.port", "8501",
        "--server.address", "0.0.0.0"
    ]
    subprocess.run(streamlit_cmd)

def main():
    """Main entry point for the combined app"""
    print("Starting the combined FastAPI + Streamlit app...")
    
    # Start FastAPI in a separate thread
    fastapi_thread = threading.Thread(target=run_fastapi, daemon=True)
    fastapi_thread.start()
    
    # Give FastAPI a moment to start
    time.sleep(2)
    print("FastAPI started, now starting Streamlit...")
    
    # Set environment variable for app.py to use the right API URL
    os.environ["API_URL"] = "http://localhost:7860/process-image"
    
    # Start Streamlit
    run_streamlit()

if __name__ == "__main__":
    main()