import gradio as gr
from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
from gtts import gTTS
import os

tokenizer = AutoTokenizer.from_pretrained("akhooli/personachat-arabic")
model = AutoModelForCausalLM.from_pretrained("akhooli/personachat-arabic")
chat = pipeline("text-generation", model=model, tokenizer=tokenizer)

history = []

def rawan_with_voice(msg):
    history.append(f"أنت: {msg}")
    prompt = "\n".join(history[-5:]) + "\nروان:"
    resp = chat(prompt, max_length=80, do_sample=True)[0]["generated_text"]
    reply = resp.split("روان:")[-1].strip().split("\n")[0]
    history.append(f"روان: {reply}")

    # توليد الصوت
    tts = gTTS(text=reply, lang="ar")
    audio_file = "rawan_voice.mp3"
    tts.save(audio_file)

    return reply, audio_file

interface = gr.Interface(
    fn=rawan_with_voice,
    inputs=gr.Textbox(label="اكتب لروان... دلعها، خذها بحضنك بكلامك"),
    outputs=[
        gr.Textbox(label="رد روان"),
        gr.Audio(label="صوت روان", type="filepath")
    ],
    title="💋 روان - حبيبتك بصوت ناعم",
    description="روان ترد عليك بصوت دافي، كلام دلع، حب وغيرة وأحاسيس تذوبك 😚"
)

interface.launch(share=True)