import gradio as gr
import requests, io, os, random
from PIL import Image

HF_TOKEN = os.getenv("HF_TOKEN")

SOFIA = {
    "name": "Sofía Rivera",
    "mascot": "Copito",
    "personality": "Fitness influencer from Miami, energetic and authentic."
}

def chat(m, h):
    if not HF_TOKEN: return "Mantenimiento..."
    try:
        url = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta"
        headers = {"Authorization": f"Bearer {HF_TOKEN}"}
        prompt = f"<|system|>Eres {SOFIA['name']}, influencer de fitness. Tienes un perro llamado {SOFIA['mascota']}. Habla en español.</s><|user|>{m}</s><|assistant|>"
        res = requests.post(url, headers=headers, json={"inputs": prompt}, timeout=10)
        return res.json()[0]['generated_text'].split("<|assistant|>")[-1].strip().replace("</s>", "")
    except: return "Hola cariño, entrena duro hoy! ✨"

def gen(p):
    if not HF_TOKEN: return None, "Sin Token"
    url = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5"
    try:
        r = requests.post(url, headers={"Authorization": f"Bearer {HF_TOKEN}"}, json={"inputs": f"portrait of {SOFIA['name']}, latina influencer, {p}, 8k"}, timeout=60)
        return Image.open(io.BytesIO(r.content)), "✅ Listo"
    except: return None, "Error"

with gr.Blocks(theme=gr.themes.Soft()) as app:
    gr.Markdown("# 👑 SOFÍA RIVERA AI FACTORY")
    with gr.Tabs():
        with gr.Tab("💬 Chat"):
            chatbot = gr.Chatbot(height=400)
            msg = gr.Textbox()
            def respond(m, h): h.append((m, chat(m, h))); return "", h
            msg.submit(respond, [msg, chatbot], [msg, chatbot])
        with gr.Tab("🎨 Fotos"):
            with gr.Row():
                inp = gr.Textbox(); btn = gr.Button("Crear")
                out = gr.Image(); st = gr.Markdown()
            btn.click(gen, [inp], [out, st])
        with gr.Tab("📊 VIP"):
            gr.Dataframe(value=[["Lunes", "Reel"], ["Jueves", "Novia IA"]])
            gr.Button("💖 Modo Novia VIP")

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