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import os
import asyncio
import logging
import tempfile
import requests
from datetime import datetime
import edge_tts
import gradio as gr
import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel
from keybert import KeyBERT
from moviepy.editor import VideoFileClip, concatenate_videoclips, AudioFileClip, CompositeAudioClip
import subprocess
import re
import math
from pydub import AudioSegment
from pexelsapi.pexels import Pexels
# Configuraci贸n de logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
# Clave API de Pexels
PEXELS_API_KEY = os.environ.get("PEXELS_API_KEY")
# Inicializaci贸n de modelos
MODEL_NAME = "gpt2"
try:
tokenizer = GPT2Tokenizer.from_pretrained(MODEL_NAME)
model = GPT2LMHeadModel.from_pretrained(MODEL_NAME).eval()
if tokenizer.pad_token is None:
tokenizer.pad_token = tokenizer.eos_token
logger.info(f"Modelo GPT-2 cargado exitosamente.")
except Exception as e:
logger.error(f"Error al cargar modelo GPT-2: {e}")
tokenizer = None
model = None
try:
kw_model = KeyBERT('multi-qa-MiniLM-L6-cos-v1')
logger.info("Modelo KeyBERT cargado exitosamente.")
except Exception as e:
logger.error(f"Error al cargar KeyBERT: {e}")
kw_model = None
def generate_script(prompt, max_length=250):
if not tokenizer or not model:
logger.error("Modelo GPT-2 no disponible")
return "Lo siento, el generador de guiones no est谩 disponible."
logger.info("Generando guion con GPT-2...")
try:
inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=512)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
inputs = {k: v.to(device) for k, v in inputs.items()}
model.to(device)
with torch.no_grad():
outputs = model.generate(
**inputs,
max_length=max_length,
do_sample=True,
top_p=0.95,
top_k=60,
temperature=0.9,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id
)
text = tokenizer.decode(outputs[0], skip_special_tokens=True)
logger.info(f"Guion generado: {text[:200]}...")
return text
except Exception as e:
logger.error(f"Error generando guion: {e}")
return "No se pudo generar el guion. Intenta con otro prompt."
async def text_to_speech(text, voice="es-ES-ElviraNeural", output_path="voz.mp3"):
logger.info(f"Generando audio TTS...")
try:
communicate = edge_tts.Communicate(text, voice)
await communicate.save(output_path)
logger.info(f"Audio TTS guardado")
return True
except Exception as e:
logger.error(f"Error TTS: {e}")
return False
def download_video_file(url, temp_dir):
if not url:
return None
file_name = url.split('/')[-1].split('?')[0]
if not file_name.endswith('.mp4'):
file_name = f"video_temp_{os.getpid()}_{datetime.now().strftime('%f')}.mp4"
output_path = os.path.join(temp_dir, file_name)
logger.info(f"Descargando video: {url}")
try:
response = requests.get(url, stream=True, timeout=30)
response.raise_for_status()
with open(output_path, 'wb') as f:
for chunk in response.iter_content(chunk_size=8192):
if chunk:
f.write(chunk)
logger.info(f"Video descargado")
return output_path
except Exception as e:
logger.error(f"Error descargando video: {e}")
if os.path.exists(output_path):
os.remove(output_path)
return None
def loop_audio_to_length(audio_clip, target_duration):
if audio_clip.duration >= target_duration:
return audio_clip.subclip(0, target_duration)
loops = int(target_duration / audio_clip.duration) + 1
audios = [audio_clip] * loops
concatenated = concatenate_videoclips(audios)
return concatenated.subclip(0, target_duration)
def extract_visual_keywords_from_script(script_text, max_keywords_per_segment=2):
if not kw_model:
logger.warning("KeyBERT no disponible. Usando m茅todo simple.")
return [script_text.split('.')[0].strip().replace(" ", "+")] if script_text.strip() else []
logger.info("Extrayendo palabras clave...")
segments = [s.strip() for s in script_text.split('\n') if s.strip()]
if not segments:
segments = [script_text]
all_keywords = set()
for segment in segments:
if not segment: continue
try:
keywords_with_scores = kw_model.extract_keywords(
segment,
keyphrase_ngram_range=(1, 2),
stop_words='spanish',
top_n=max_keywords_per_segment,
use_mmr=True,
diversity=0.7
)
for kw, score in keywords_with_scores:
all_keywords.add(kw.replace(" ", "+"))
except Exception as e:
logger.warning(f"Error extrayendo keywords: {e}")
all_keywords.add(segment.split(' ')[0].strip().replace(" ", "+"))
return list(all_keywords)
def search_pexels_videos(query_list, num_videos_per_query=5, min_duration_sec=7):
if not PEXELS_API_KEY:
logger.error("ERROR: PEXELS_API_KEY no configurada.")
raise ValueError("Configura PEXELS_API_KEY en los Secrets")
if not query_list:
logger.warning("No hay queries para buscar.")
return []
pexel = Pexels(PEXELS_API_KEY)
all_video_urls = []
for query in query_list:
logger.info(f"Buscando videos para: '{query}'")
try:
results = pexel.search_videos(
query=query,
orientation='landscape',
per_page=num_videos_per_query
)
videos = results.get('videos', [])
if not videos:
logger.info(f"No se encontraron videos para: '{query}'")
continue
for video in videos:
video_files = video.get('video_files', [])
if video_files:
best_quality = max(
video_files,
key=lambda x: x.get('width', 0) * x.get('height', 0)
)
all_video_urls.append(best_quality['link'])
except Exception as e:
logger.error(f"Error buscando videos: {e}")
return all_video_urls
def crear_video(prompt_type, input_text, musica_url=None):
logger.info(f"Iniciando creaci贸n de video: {prompt_type}")
guion = ""
if prompt_type == "Generar Guion con IA":
guion = generate_script(input_text)
if not guion or "No se pudo" in guion:
raise ValueError(guion)
else:
guion = input_text
if not guion.strip():
raise ValueError("Introduce tu guion.")
temp_files = []
downloaded_clip_paths = []
final_clips = []
temp_video_dir = tempfile.mkdtemp()
temp_files.append(temp_video_dir)
try:
voz_archivo = os.path.join(tempfile.gettempdir(), f"voz_temp_{os.getpid()}.mp3")
temp_files.append(voz_archivo)
if not asyncio.run(text_to_speech(guion, output_path=voz_archivo)):
raise ValueError("Error generando voz")
audio_tts = AudioFileClip(voz_archivo)
search_queries = extract_visual_keywords_from_script(guion)
if not search_queries:
raise ValueError("No se pudieron extraer palabras clave")
video_urls = search_pexels_videos(search_queries)
if not video_urls:
raise ValueError(f"Pexels no encontr贸 videos para: {search_queries}")
for url in video_urls:
path = download_video_file(url, temp_video_dir)
if path:
downloaded_clip_paths.append(path)
if not downloaded_clip_paths:
raise ValueError("No se pudo descargar videos")
total_desired_duration = audio_tts.duration * 1.2
current_duration = 0
for path in downloaded_clip_paths:
try:
clip = VideoFileClip(path)
clip_duration = min(clip.duration, 10)
if clip_duration > 1:
final_clips.append(clip.subclip(0, clip_duration))
current_duration += clip_duration
if current_duration >= total_desired_duration:
break
except Exception as e:
logger.warning(f"Error procesando clip: {e}")
if not final_clips:
raise ValueError("No hay clips v谩lidos")
video_base = concatenate_videoclips(final_clips, method="compose")
if video_base.duration < audio_tts.duration:
num_repeats = int(audio_tts.duration / video_base.duration) + 1
video_base = concatenate_videoclips([video_base] * num_repeats)
final_video_duration = audio_tts.duration
mezcla_audio = audio_tts
if musica_url and musica_url.strip():
musica_path = download_video_file(musica_url, temp_video_dir)
if musica_path:
temp_files.append(musica_path)
try:
musica_audio = AudioFileClip(musica_path)
musica_loop = loop_audio_to_length(musica_audio, final_video_duration)
mezcla_audio = CompositeAudioClip([
musica_loop.volumex(0.3),
audio_tts.set_duration(final_video_duration).volumex(1.0)
])
except Exception as e:
logger.warning(f"Error m煤sica: {e}")
video_final = video_base.set_audio(mezcla_audio).subclip(0, final_video_duration)
output_dir = "output_videos"
os.makedirs(output_dir, exist_ok=True)
output_path = os.path.join(output_dir, f"video_{datetime.now().strftime('%Y%m%d_%H%M%S')}.mp4")
video_final.write_videofile(
output_path,
fps=24,
threads=4,
codec="libx264",
audio_codec="aac",
preset="medium",
ffmpeg_params=["-movflags", "+faststart"]
)
return output_path
except Exception as e:
logger.error(f"Error general: {e}")
raise e
finally:
for f in temp_files:
if os.path.exists(f):
if os.path.isdir(f):
import shutil
shutil.rmtree(f)
else:
os.remove(f)
def run_app(prompt_type, prompt_ia, prompt_manual, musica_url):
input_text = ""
if prompt_type == "Generar Guion con IA":
input_text = prompt_ia
if not input_text.strip():
raise gr.Error("Introduce un tema para el guion.")
else:
input_text = prompt_manual
if not input_text.strip():
raise gr.Error("Introduce tu guion.")
try:
video_path = crear_video(prompt_type, input_text, musica_url if musica_url.strip() else None)
if video_path:
return video_path, "隆Video generado exitosamente!"
else:
raise gr.Error("Error desconocido")
except ValueError as ve:
return None, f"Error: {ve}"
except Exception as e:
return None, f"Error grave: {e}"
with gr.Blocks() as app:
gr.Markdown("### 馃幀 Generador de Video con Pexels")
with gr.Tab("Generar Video"):
with gr.Row():
prompt_type = gr.Radio(
["Generar Guion con IA", "Usar Mi Guion"],
label="M茅todo",
value="Generar Guion con IA"
)
with gr.Column(visible=True) as ia_guion_column:
prompt_ia = gr.Textbox(
label="Tema para IA",
lines=2
)
with gr.Column(visible=False) as manual_guion_column:
prompt_manual = gr.Textbox(
label="Tu Guion",
lines=5
)
musica_input = gr.Textbox(
label="URL M煤sica (opcional)",
)
boton = gr.Button("Generar Video")
with gr.Column():
salida_video = gr.Video(label="Video Resultado", interactive=False)
estado_mensaje = gr.Textbox(label="Estado", interactive=False)
prompt_type.change(
fn=lambda value: (gr.update(visible=value == "Generar Guion con IA"),
gr.update(visible=value == "Usar Mi Guion")),
inputs=prompt_type,
outputs=[ia_guion_column, manual_guion_column]
)
boton.click(
fn=lambda: (None, "Procesando..."),
outputs=[salida_video, estado_mensaje],
queue=False
).then(
fn=run_app,
inputs=[prompt_type, prompt_ia, prompt_manual, musica_input],
outputs=[salida_video, estado_mensaje]
)
if __name__ == "__main__":
app.launch(server_name="0.0.0.0", server_port=7860) |