app.py

import os
import openai
import gradio as gr
import subprocess
from gtts import gTTS
from pydub import AudioSegment

openai.api_key = os.environ.get("openai_api_key")

def generate_output(name, horoscope_type, birth_date):
    prompt = f"Tú horóscopo de hoy, si nacido el {birth_date}, es:"
    response = openai.Completion.create(
        engine="text-davinci-003",
        prompt=prompt,
        max_tokens=180,
        temperature=0.6,
        n=1,
        stop=None,)
    gpt3_output = response.choices[0].text.strip()
    personalized_response = f"Tu horóscopo {name} nacido el {birth_date} es: {gpt3_output}"
    
    if len(response.choices) == 0 or 'text' not in response.choices[0]:
        return None, "No se pudo generar el texto."

    try:
        tts = gTTS(personalized_response, lang='es')
        temp_audio_path = "temp_audio.mp3"
        tts.save(temp_audio_path)
        audio_path = "audio.wav"
        audio = AudioSegment.from_mp3(temp_audio_path)
        audio.export(audio_path, format="wav")
        print("Archivo de audio generado:", audio_path)
    except Exception as e:
        return None, f"No se pudo generar el audio: {str(e)}"

    command = f"python3 inference.py --checkpoint_path checkpoints/wav2lip_gan.pth --face face2.png --audio audio.wav --outfile video.mp4 --nosmooth"
    process = subprocess.run(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    if process.returncode != 0:
        error_message = process.stderr.decode("utf-8")
        return None, f"No se pudo generar el video: {error_message}"

    output_video_path = "video.mp4"
    os.remove(temp_audio_path)

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

name_input = gr.inputs.Textbox(lines=1, placeholder="Escribe tu Nombre Completo", label="Nombre")
birth_date = gr.inputs.Textbox(lines=1, placeholder="Fecha Nacimiento - DD/MM/AAAA", label="Cumpleaños")
output = gr.outputs.Video(label="Resultado").style(width=350)

def generate_and_display_output(name, horoscope_type, birth_date):
    video_path, error_message = generate_output(name, horoscope_type, birth_date)
    if error_message:
        print(f"Error: {error_message}")
    else:
        return video_path

iface = gr.Interface(
    fn=generate_and_display_output,
    inputs=[name_input, birth_date],
    outputs=output,
    layout="vertical",
    theme="darkdefault"
)

iface.launch()