import gradio as gr
from huggingface_hub import InferenceClient, HfApi
import os
import tempfile

API_TOKEN = os.environ.get("htoken")
client = InferenceClient(token=API_TOKEN)

def recupera_modelli_reali():
    api = HfApi()
    modelli = api.list_models(
        pipeline_tag="text-to-speech",
        sort="downloads",
        # ❌ direction=-1  <-- rimosso, non esiste più
        limit=30
    )
    return [m.id for m in modelli]

LISTA_MODELLI_DINAMICA = recupera_modelli_reali()

def genera_audio(testo, model_id):
    if not testo.strip():
        return "⚠️ Inserisci del testo.", None
    try:
        audio_bytes = client.text_to_speech(testo, model=model_id)
        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
            f.write(audio_bytes)
            return f"✅ Generato con: {model_id}", f.name
    except Exception as e:
        err = str(e)
        if "loading" in err.lower():
            return "⏳ Modello in caricamento, riprova tra 20s", None
        elif "401" in err or "unauthorized" in err.lower():
            return "❌ Token non valido — controlla il secret 'htoken'", None
        else:
            return f"❌ Errore: {err}", None

with gr.Blocks(theme=gr.themes.Soft()) as interfaccia:
    gr.Markdown("# 🎙️ Browser Modelli Hugging Face TTS")
    gr.Markdown(f"✅ Lista popolata live da Hugging Face — **{len(LISTA_MODELLI_DINAMICA)} modelli trovati**")
    
    with gr.Row():
        testo_input = gr.Textbox(label="Testo", placeholder="Scrivi qualcosa...", value="Hello, this is a test.")
        modello_dropdown = gr.Dropdown(
            choices=LISTA_MODELLI_DINAMICA,
            value=LISTA_MODELLI_DINAMICA[0],
            label="Seleziona Modello"
        )
    
    pulsante = gr.Button("🎵 Genera Audio", variant="primary")
    status = gr.Textbox(label="Console", interactive=False)
    audio = gr.Audio(label="Player")
    
    pulsante.click(fn=genera_audio, inputs=[testo_input, modello_dropdown], outputs=[status, audio])

interfaccia.launch()