import gradio as gr  
import os  
import random  
from datetime import datetime  
from huggingface_hub import InferenceClient  

# Configuración  
OUTPUT_DIR = "generated_images"  
os.makedirs(OUTPUT_DIR, exist_ok=True)  

# Usamos el Token de los Secrets del Space
HF_TOKEN = os.getenv("HUGGINGFACE_TOKEN") or os.getenv("HF_TOKEN")
client = InferenceClient(token=HF_TOKEN)  

# Identidad de Sofía Rivera (Optimizada para realismo)
SOFIA_CORE = (  
    "sofia rivera, a beautiful 25-year-old latina cuban-american woman, "  
    "long dark wavy hair, mesmerizing hazel eyes, toned athletic fitness body, "  
    "natural radiant skin, miami influencer aesthetic, hyperrealistic, 8k"  
)  

CATEGORIES = {  
    "Fitness - Gym": {  
        "prompt": f"full body mirror selfie of {SOFIA_CORE}, wearing black sports bra and leggings, modern miami gym background, cinematic lighting",  
        "desc": "### 🏋️ Pilar Fitness\nIdeal para Lunes, Miércoles y Viernes."  
    },  
    "Lifestyle - Beach": {  
        "prompt": f"candid photo of {SOFIA_CORE}, tropical outfit, miami beach sunset, vibrant colors, bokeh background",  
        "desc": "### 🌴 Pilar Lifestyle\nIdeal para Martes y Jueves."  
    },  
    "Lifestyle - Luxury": {  
        "prompt": f"portrait of {SOFIA_CORE}, luxury miami apartment balcony, morning light, natural makeup, authentic vibe",  
        "desc": "### ☕ Pilar Personal\nIdeal para Sábados."  
    },  
    "Premium - Elegant": {  
        "prompt": f"tasteful photography of {SOFIA_CORE}, elegant black lace outfit, soft moody lighting, professional studio aesthetic",  
        "desc": "### 💎 Pilar Premium\nIdeal para Domingos."  
    }  
}  

def generate(category_name, tweak, model_id, steps, cfg, seed):  
    try:  
        if not HF_TOKEN:
            return None, "❌ Error: No se encontró el HUGGINGFACE_TOKEN en los Secrets del Space."

        cat = CATEGORIES[category_name]  
        prompt = f"{cat['prompt']}, {tweak}" if tweak else cat['prompt']  
        
        # Gestión de la Seed
        final_seed = random.randint(0, 2**32 - 1) if seed == -1 else int(seed)  
          
        image = client.text_to_image(  
            prompt=prompt,  
            model=model_id,  
            num_inference_steps=int(steps),  
            guidance_scale=float(cfg),  
            seed=final_seed  
        )  
        return image, f"✅ Generada con {model_id} | Seed: {final_seed}"  
    except Exception as e:  
        return None, f"❌ Error: {str(e)}"  

def create_interface():  
    with gr.Blocks(theme=gr.themes.Soft()) as demo:  
        gr.Markdown("# 🌴 Sofia Rivera AI Workspace")  
        gr.Markdown("Generador de contenido oficial para la agencia de Sofía.")
        
        with gr.Tab("🎨 Generador de Imágenes"):  
            with gr.Row():  
                with gr.Column(scale=1):  
                    cat_drop = gr.Dropdown(choices=list(CATEGORIES.keys()), label="Selecciona el Pilar de Contenido", value="Fitness - Gym")  
                    cat_info = gr.Markdown(CATEGORIES["Fitness - Gym"]["desc"])  
                    tweak = gr.Textbox(label="Detalles extra (opcional)", placeholder="ej: holding a coffee, sunset, smiling...")  
                    
                    with gr.Accordion("Ajustes Técnicos (Avanzado)", open=True):  
                        # CAMBIO CLAVE: 'schnell' es el modelo gratuito y rápido
                        model = gr.Dropdown(
                            choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-dev"], 
                            label="Modelo (Schnell = Gratis)", 
                            value="black-forest-labs/FLUX.1-schnell"
                        )  
                        steps = gr.Slider(1, 12, 4, label="Pasos (Schnell funciona mejor con 4-8)")  
                        cfg = gr.Slider(1, 20, 3.5, label="Guidance Scale")  
                        seed = gr.Number(-1, label="Seed (-1 para aleatorio)")  
                    
                    btn = gr.Button("🚀 Generar Imagen de Sofía", variant="primary")  
                
                with gr.Column(scale=2):  
                    out_img = gr.Image(label="Vista previa de Sofía")  
                    out_log = gr.Textbox(label="Log de Estado", interactive=False)  
          
        cat_drop.change(lambda x: CATEGORIES[x]["desc"], inputs=[cat_drop], outputs=[cat_info])  
        btn.click(generate, [cat_drop, tweak, model, steps, cfg, seed], [out_img, out_log])  
    
    return demo  

if __name__ == "__main__":  
    create_interface().launch()