import os
import streamlit as st
import subprocess
from gtts import gTTS
import cv2
from huggingface_hub import InferenceClient

client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")

def generate_output(name, ingredients):
    if not ingredients:
        return None, "El campo de ingredientes es obligatorio."

    prompt = f"La respuesta a tu pregunta {ingredients}, es:"
    response = client.text_generation(prompt, max_new_tokens=50, temperature=0.6)
    gpt3_output = response.strip()
    personalized_response = f"{gpt3_output}"
    
    try:
        tts = gTTS(personalized_response, lang='es')
        audio_path = "audio.mp3"
        tts.save(audio_path)
    except Exception as e:
        return None, f"No se pudo generar el audio: {str(e)}"

    video_path = "video.mp4"
    command = f"python3 inference.py --checkpoint_path checkpoints/wav2lip_gan.pth --face face.png --audio {audio_path} --outfile {video_path} --nosmooth"
    process = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
    if process.returncode != 0:
        error_message = process.stderr
        return None, f"No se pudo generar el video: {error_message}"

    if os.path.isfile(video_path):
        return video_path, None
    return None, "No se pudo generar el video"

st.title("Lypsinc +Inteligencia Artificial")

name = st.text_input("Nombre", "Escribe tu nick")
ingredients = st.text_input("Pregunta")

if st.button("Generar Video"):
    video_path, error_message = generate_output(name, ingredients)
    if error_message:
        st.error(f"Error: {error_message}")
    else:
        video_file = open(video_path, "rb").read()
        st.video(video_file)