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| 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, birth_date): | |
| if not birth_date: | |
| return None, "El campo de fecha de nacimiento es obligatorio." | |
| prompt = f"Tu hor贸scopo de hoy, si naciste el {birth_date}, es:" | |
| response = client.text_generation(prompt, max_new_tokens=180, temperature=0.6) | |
| gpt3_output = response.strip() # Acceso directo al texto generado | |
| personalized_response = f"Tu hor贸scopo {name}, nacido el {birth_date}, es: {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.jpg --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("Or谩culo del Hor贸scopo") | |
| name = st.text_input("Nombre", "Escribe tu nick") | |
| birth_date = st.text_input("Fecha de Nacimiento", "DD/MM/AAAA") | |
| if st.button("Generar Video"): | |
| video_path, error_message = generate_output(name, birth_date) | |
| if error_message: | |
| st.error(f"Error: {error_message}") | |
| else: | |
| video_file = open(video_path, "rb").read() | |
| st.video(video_file) | |