import os
import gradio as gr
import logging
from datetime import datetime
from dotenv import load_dotenv

# Cargar variables de entorno
load_dotenv()

# Configuración inicial
logging.basicConfig(filename='art_transformer.log', level=logging.INFO)
logger = logging.getLogger(__name__)

# Importaciones internas
from image_processor.analyzer import ImageAnalyzer
from image_processor.framer import FrameGenerator
from image_processor.priority_queue import PriorityQueue
from image_processor.google_auth import GooglePhotosAuth
from image_processor.monitoring import ResourceMonitor

class ArtTransformer:
    def __init__(self):
        self.openai_key = os.getenv("OPENAI_API_KEY")
        self.analyzer = ImageAnalyzer()
        self.framer = FrameGenerator(self.openai_key)
        self.auth = GooglePhotosAuth()
        self.queue = PriorityQueue()
        self.monitor = ResourceMonitor(interval=15)
        self.current_job = None

    def process_album(self, image_paths, priority=2, progress=gr.Progress()):
        try:
            self.monitor.start()
            
            # Autenticación con Google Photos
            credentials = self.auth.authenticate()
            
            # Configurar cola de prioridad
            for idx, path in enumerate(image_paths):
                self.queue.add_task(priority + idx/1000, path)
            
            results = []
            total = len(image_paths)
            
            while not self.queue.is_empty():
                if self.current_job and self.current_job.is_alive():
                    yield gr.Gallery(visible=True), f"⏳ Procesando {self.current_job.name}..."
                
                next_path = self.queue.get_next_task()
                self.current_job = threading.Thread(
                    target=self._process_single_image,
                    args=(next_path, results, progress),
                    name=f"Job-{datetime.now().strftime('%H%M%S')}"
                )
                self.current_job.start()
                self.current_job.join()

            return self._build_output(results), "✅ Proceso completado!"
        
        except Exception as e:
            logger.error(f"Error general: {str(e)}")
            return None, f"❌ Error crítico: {str(e)}"
        
        finally:
            self.monitor.stop()

def create_interface():
    with gr.Blocks(title="Art Transformer", theme=gr.themes.Soft()) as demo:
        gr.Markdown("# 🎨 Transformador Artístico Automático")
        
        with gr.Row():
            with gr.Column(scale=1):
                api_key = gr.Textbox(
                    label="OpenAI API Key",
                    type="password",
                    placeholder="sk-...",
                    info="Necesario para generar marcos"
                )
                priority = gr.Dropdown(
                    label="Prioridad",
                    choices=[("Alta", 0), ("Media", 1), ("Baja", 2)],
                    value=1
                )
                btn_run = gr.Button("Iniciar Procesamiento", variant="primary")
            
            with gr.Column(scale=3):
                gallery = gr.Gallery(
                    label="Resultados",
                    columns=4,
                    height="auto",
                    object_fit="contain"
                )
                status = gr.Textbox(label="Estado", interactive=False)
        
        inputs = gr.File(
            file_count="multiple",
            file_types=["image"],
            label="Subir imágenes"
        )
        
        btn_run.click(
            fn=ArtTransformer().process_album,
            inputs=[inputs, priority],
            outputs=[gallery, status]
        )
    
    return demo

if __name__ == "__main__":
    demo = create_interface()
    demo.queue(concurrency_count=2, max_size=10)
    demo.launch(server_name="0.0.0.0", server_port=7860)