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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, concatenate_audioclips, AudioClip
import re
import math
import shutil
import json
from collections import Counter
# Logging configuration
logging.basicConfig(
level=logging.DEBUG,
format='%(asctime)s - %(levelname)s - %(message)s',
handlers=[
logging.StreamHandler(),
logging.FileHandler('video_generator_full.log', encoding='utf-8')
]
)
logger = logging.getLogger(__name__)
logger.info("="*80)
logger.info("STARTING VIDEO GENERATOR EXECUTION")
logger.info("="*80)
# Pexels API Key
PEXELS_API_KEY = os.environ.get("PEXELS_API_KEY")
if not PEXELS_API_KEY:
logger.critical("PEXELS_API_KEY environment variable not found.")
# Uncomment to force fail if not set:
# raise ValueError("Pexels API key not configured")
# Model Initialization
MODEL_NAME = "datificate/gpt2-small-spanish"
logger.info(f"Initializing GPT-2 model: {MODEL_NAME}")
tokenizer = None
model = None
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"GPT-2 model loaded | Vocab size: {len(tokenizer)}")
except Exception as e:
logger.error(f"CRITICAL FAILURE loading GPT-2: {str(e)}", exc_info=True)
tokenizer = model = None
logger.info("Loading KeyBERT model...")
kw_model = None
try:
kw_model = KeyBert('distilbert-base-multilingual-cased')
logger.info("KeyBERT initialized successfully")
except Exception as e:
logger.error(f"FAILURE loading KeyBERT: {str(e)}", exc_info=True)
kw_model = None
def buscar_videos_pexels(query, api_key, per_page=5):
if not api_key:
logger.warning("Cannot search Pexels: API Key not configured.")
return []
logger.debug(f"Searching Pexels: '{query}' | Results per page: {per_page}")
headers = {"Authorization": api_key}
try:
params = {
"query": query,
"per_page": per_page,
"orientation": "landscape",
"size": "medium"
}
response = requests.get(
"https://api.pexels.com/videos/search",
headers=headers,
params=params,
timeout=20
)
response.raise_for_status()
data = response.json()
videos = data.get('videos', [])
logger.info(f"Pexels: Found {len(videos)} videos for '{query}'")
return videos
except requests.exceptions.RequestException as e:
logger.error(f"Pexels connection error for '{query}': {str(e)}")
except json.JSONDecodeError:
logger.error(f"Pexels: Invalid JSON received | Status: {response.status_code} | Response: {response.text[:200]}...")
except Exception as e:
logger.error(f"Unexpected Pexels error for '{query}': {str(e)}", exc_info=True)
return []
def generate_script(prompt, max_length=150):
logger.info(f"Generando guión | Prompt: '{prompt[:50]}...' | Max length: {max_length}")
if not tokenizer or not model:
logger.warning("GPT-2 models not available - Using original prompt as script.")
return prompt
try:
enhanced_prompt = f"Escribe un guion corto, interesante y coherente sobre: {prompt}"
inputs = tokenizer(enhanced_prompt, return_tensors="pt", truncation=True, max_length=512)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
inputs = {k: v.to(device) for k, v in inputs.items()}
outputs = model.generate(
**inputs,
max_length=max_length,
do_sample=True,
top_p=0.9,
top_k=40,
temperature=0.7,
repetition_penalty=1.2,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id,
no_repeat_ngram_size=3
)
text = tokenizer.decode(outputs[0], skip_special_tokens=True)
text = re.sub(r'<[^>]+>', '', text)
text = text.strip()
sentences = text.split('.')
if sentences and sentences[0].strip():
final_text = sentences[0].strip() + '.'
if len(sentences) > 1 and sentences[1].strip() and len(final_text.split()) < max_length * 0.5:
final_text += " " + sentences[1].strip() + "."
final_text = final_text.replace("..", ".")
logger.info(f"Guion generado (Truncado): '{final_text[:100]}...'")
return final_text.strip()
logger.info(f"Guion generado (sin oraciones completas): '{text[:100]}...'")
return text.strip()
except Exception as e:
logger.error(f"Error generating script with GPT-2: {str(e)}", exc_info=True)
logger.warning("Using original prompt as script due to generation error.")
return prompt.strip()
async def text_to_speech(text, output_path, voice="es-ES-ElviraNeural"):
logger.info(f"Converting text to speech | Chars: {len(text)} | Voice: {voice} | Output: {output_path}")
if not text or not text.strip():
logger.warning("Empty text for TTS")
return False
try:
communicate = edge_tts.Communicate(text, voice)
await communicate.save(output_path)
if os.path.exists(output_path) and os.path.getsize(output_path) > 100:
logger.info(f"Audio saved successfully to: {output_path} | Size: {os.path.getsize(output_path)} bytes")
return True
else:
logger.error(f"TTS saved small or empty file to: {output_path}")
return False
except Exception as e:
logger.error(f"Error in TTS: {str(e)}", exc_info=True)
return False
def download_video_file(url, temp_dir):
if not url:
logger.warning("Video URL not provided for download")
return None
try:
logger.info(f"Downloading video from: {url[:80]}...")
os.makedirs(temp_dir, exist_ok=True)
file_name = f"video_dl_{datetime.now().strftime('%Y%m%d_%H%M%S_%f')}.mp4"
output_path = os.path.join(temp_dir, file_name)
with requests.get(url, stream=True, timeout=60) as r:
r.raise_for_status()
with open(output_path, 'wb') as f:
for chunk in r.iter_content(chunk_size=8192):
f.write(chunk)
if os.path.exists(output_path) and os.path.getsize(output_path) > 1000:
logger.info(f"Video downloaded successfully: {output_path} | Size: {os.path.getsize(output_path)} bytes")
return output_path
else:
logger.warning(f"Download seems incomplete or empty for {url[:80]}... File: {output_path} Size: {os.path.getsize(output_path) if os.path.exists(output_path) else 'N/A'} bytes")
if os.path.exists(output_path):
os.remove(output_path)
return None
except requests.exceptions.RequestException as e:
logger.error(f"Download error for {url[:80]}... : {str(e)}")
except Exception as e:
logger.error(f"Unexpected error downloading {url[:80]}... : {str(e)}", exc_info=True)
return None
def loop_audio_to_length(audio_clip, target_duration):
logger.debug(f"Adjusting audio | Current duration: {audio_clip.duration:.2f}s | Target: {target_duration:.2f}s")
# Handle cases where the input audio clip is invalid
if audio_clip is None or audio_clip.duration is None or audio_clip.duration <= 0:
logger.warning("Input audio clip is invalid (None or zero duration), cannot loop.")
# Return a silent clip of target duration as fallback
try:
# Ensure sampling rate is set, default is 44100
sr = getattr(audio_clip, 'fps', 44100) if audio_clip else 44100 # Use fps for audio clips
return AudioClip(lambda t: 0, duration=target_duration, sr=sr)
except Exception as e:
logger.error(f"Could not create silence clip: {e}", exc_info=True)
return AudioFileClip(filename="") # Return empty clip on failure
if audio_clip.duration >= target_duration:
logger.debug("Audio clip already longer or equal to target. Trimming.")
trimmed_clip = audio_clip.subclip(0, target_duration)
# Check trimmed clip validity (should be ok, but good practice)
if trimmed_clip.duration is None or trimmed_clip.duration <= 0:
logger.error("Trimmed audio clip is invalid.")
try: trimmed_clip.close()
except: pass
return AudioFileClip(filename="")
return trimmed_clip
loops = math.ceil(target_duration / audio_clip.duration)
logger.debug(f"Creating {loops} audio loops")
audio_segments = [audio_clip] * loops
looped_audio = None # Initialize for finally block
final_looped_audio = None # Initialize for return value
try:
looped_audio = concatenate_audioclips(audio_segments)
# Verify the concatenated audio clip is valid
if looped_audio.duration is None or looped_audio.duration <= 0:
logger.error("Concatenated audio clip is invalid (None or zero duration).")
raise ValueError("Invalid concatenated audio.")
final_looped_audio = looped_audio.subclip(0, target_duration)
# Verify the final subclipped audio clip is valid
if final_looped_audio.duration is None or final_looped_audio.duration <= 0:
logger.error("Final subclipped audio clip is invalid (None or zero duration).")
raise ValueError("Invalid final subclipped audio.")
return final_looped_audio
except Exception as e:
logger.error(f"Error concatenating/subclipping audio clips for looping: {str(e)}", exc_info=True)
# Fallback: try returning the original clip trimmed if possible
try:
if audio_clip.duration is not None and audio_clip.duration > 0:
logger.warning("Returning original audio clip (may be too short).")
return audio_clip.subclip(0, min(audio_clip.duration, target_duration))
except:
pass # Ignore errors during fallback
logger.error("Fallback to original audio clip failed.")
return AudioFileClip(filename="") # Return empty clip if fallback fails
finally:
# Clean up the temporary concatenated clip if it was created but not returned
if looped_audio is not None and looped_audio is not final_looped_audio:
try: looped_audio.close()
except: pass
def extract_visual_keywords_from_script(script_text):
logger.info("Extracting keywords from script")
if not script_text or not script_text.strip():
logger.warning("Empty script, cannot extract keywords.")
return ["naturaleza", "ciudad", "paisaje"]
clean_text = re.sub(r'[^\w\sáéíóúñÁÉÍÓÚÑ]', '', script_text)
keywords_list = []
if kw_model:
try:
logger.debug("Attempting KeyBERT extraction...")
keywords1 = kw_model.extract_keywords(clean_text, keyphrase_ngram_range=(1, 1), stop_words='spanish', top_n=5)
keywords2 = kw_model.extract_keywords(clean_text, keyphrase_ngram_range=(2, 2), stop_words='spanish', top_n=3)
all_keywords = keywords1 + keywords2
all_keywords.sort(key=lambda item: item[1], reverse=True)
seen_keywords = set()
for keyword, score in all_keywords:
formatted_keyword = keyword.lower().replace(" ", "+")
if formatted_keyword and formatted_keyword not in seen_keywords:
keywords_list.append(formatted_keyword)
seen_keywords.add(formatted_keyword)
if len(keywords_list) >= 5:
break
if keywords_list:
logger.debug(f"KeyBERT extracted keywords: {keywords_list}")
return keywords_list
except Exception as e:
logger.warning(f"KeyBERT failed: {str(e)}. Trying simple method.")
logger.debug("Extracting keywords with simple method...")
words = clean_text.lower().split()
stop_words = {"el", "la", "los", "las", "de", "en", "y", "a", "que", "es", "un", "una", "con", "para", "del", "al", "por", "su", "sus", "se", "lo", "le", "me", "te", "nos", "os", "les", "mi", "tu", "nuestro", "vuestro", "este", "ese", "aquel", "esta", "esa", "aquella", "esto", "eso", "aquello", "mis", "tus", "nuestros", "vuestros", "estas", "esas", "aquellas", "si", "no", "más", "menos", "sin", "sobre", "bajo", "entre", "hasta", "desde", "durante", "mediante", "según", "versus", "via", "cada", "todo", "todos", "toda", "todas", "poco", "pocos", "poca", "pocas", "mucho", "muchos", "mucha", "muchas", "varios", "varias", "otro", "otros", "otra", "otras", "mismo", "misma", "mismos", "mismas", "tan", "tanto", "tanta", "tantos", "tantas", "tal", "tales", "cual", "cuales", "cuyo", "cuya", "cuyos", "cuyas", "quien", "quienes", "cuan", "cuanto", "cuanta", "cuantos", "cuantas", "como", "donde", "cuando", "porque", "aunque", "mientras", "siempre", "nunca", "jamás", "muy", "casi", "solo", "solamente", "incluso", "apenas", "quizás", "tal vez", "acaso", "claro", "cierto", "obvio", "evidentemente", "realmente", "simplemente", "generalmente", "especialmente", "principalmente", "posiblemente", "probablemente", "difícilmente", "fácilmente", "rápidamente", "lentamente", "bien", "mal", "mejor", "peor", "arriba", "abajo", "adelante", "atrás", "cerca", "lejos", "dentro", "fuera", "encima", "debajo", "frente", "detrás", "antes", "después", "luego", "pronto", "tarde", "todavía", "ya", "aun", "aún", "quizá"}
valid_words = [word for word in words if len(word) > 3 and word not in stop_words]
if not valid_words:
logger.warning("No valid keywords found with simple method. Using default keywords.")
return ["naturaleza", "ciudad", "paisaje"]
word_counts = Counter(valid_words)
top_keywords = [word.replace(" ", "+") for word, _ in word_counts.most_common(5)]
if not top_keywords:
logger.warning("Simple method produced no keywords. Using default keywords.")
return ["naturaleza", "ciudad", "paisaje"]
logger.info(f"Final keywords: {top_keywords}")
return top_keywords
def crear_video(prompt_type, input_text, musica_file=None):
logger.info("="*80)
logger.info(f"STARTING VIDEO CREATION | Type: {prompt_type}")
logger.debug(f"Input: '{input_text[:100]}...'")
start_time = datetime.now()
temp_dir_intermediate = None
# Initialize clips and audio objects to None for cleanup in finally
audio_tts_original = None # Keep original TTS clip for cleanup
musica_audio_original = None # Keep original music clip for cleanup
audio_tts = None # This will be the potentially modified/validated TTS clip
musica_audio = None # This will be the potentially modified/validated music clip
video_base = None # This will hold the final video base clip before adding audio
video_final = None # This will hold the final clip with video and audio
source_clips = [] # Clips loaded from downloaded files for proper closing
clips_to_concatenate = [] # Segments extracted from source_clips
try:
# 1. Generate or use script
if prompt_type == "Generar Guion con IA":
guion = generate_script(input_text)
else:
guion = input_text.strip()
logger.info(f"Final script ({len(guion)} chars): '{guion[:100]}...'")
if not guion.strip():
logger.error("Resulting script is empty.")
raise ValueError("The script is empty.")
temp_dir_intermediate = tempfile.mkdtemp(prefix="video_gen_intermediate_")
logger.info(f"Intermediate temporary directory created: {temp_dir_intermediate}")
temp_intermediate_files = []
# 2. Generate voice audio
logger.info("Generating voice audio...")
voz_path = os.path.join(temp_dir_intermediate, "voz.mp3")
if not asyncio.run(text_to_speech(guion, voz_path)):
logger.error("Failed to generate voice audio.")
raise ValueError("Error generating voice audio.")
temp_intermediate_files.append(voz_path)
audio_tts_original = AudioFileClip(voz_path)
# Verify initial TTS audio clip
if audio_tts_original.reader is None or audio_tts_original.duration is None or audio_tts_original.duration <= 0:
logger.critical("Initial TTS audio clip is invalid (reader is None or duration <= 0).")
# Try to close the invalid clip before raising
try: audio_tts_original.close()
except: pass
audio_tts_original = None # Ensure it's None
raise ValueError("Generated voice audio is invalid.")
audio_tts = audio_tts_original # Use the original valid TTS clip
audio_duration = audio_tts.duration
logger.info(f"Voice audio duration: {audio_duration:.2f} seconds")
if audio_duration < 1.0:
logger.error(f"Voice audio duration ({audio_duration:.2f}s) is too short.")
raise ValueError("Generated voice audio is too short (min 1 second required).")
# 3. Extract keywords
logger.info("Extracting keywords...")
try:
keywords = extract_visual_keywords_from_script(guion)
logger.info(f"Identified keywords: {keywords}")
except Exception as e:
logger.error(f"Error extracting keywords: {str(e)}", exc_info=True)
keywords = ["naturaleza", "paisaje"]
if not keywords:
keywords = ["video", "background"]
# 4. Search and download videos
logger.info("Searching videos on Pexels...")
videos_data = []
total_desired_videos = 10
per_page_per_keyword = max(1, total_desired_videos // len(keywords))
for keyword in keywords:
if len(videos_data) >= total_desired_videos: break
try:
videos = buscar_videos_pexels(keyword, PEXELS_API_KEY, per_page=per_page_per_keyword)
if videos:
videos_data.extend(videos)
logger.info(f"Found {len(videos)} videos for '{keyword}'. Total data: {len(videos_data)}")
except Exception as e:
logger.warning(f"Error searching videos for '{keyword}': {str(e)}")
if len(videos_data) < total_desired_videos / 2:
logger.warning(f"Few videos found ({len(videos_data)}). Trying generic keywords.")
generic_keywords = ["nature", "city", "background", "abstract"]
for keyword in generic_keywords:
if len(videos_data) >= total_desired_videos: break
try:
videos = buscar_videos_pexels(keyword, PEXELS_API_KEY, per_page=2)
if videos:
videos_data.extend(videos)
logger.info(f"Found {len(videos)} videos for '{keyword}' (generic). Total data: {len(videos_data)}")
except Exception as e:
logger.warning(f"Error searching generic videos for '{keyword}': {str(e)}")
if not videos_data:
logger.error("No videos found on Pexels for any keyword.")
raise ValueError("No suitable videos found on Pexels.")
video_paths = []
logger.info(f"Attempting to download {len(videos_data)} found videos...")
for video in videos_data:
if 'video_files' not in video or not video['video_files']:
logger.debug(f"Skipping video without video files: {video.get('id')}")
continue
try:
best_quality = None
for vf in sorted(video['video_files'], key=lambda x: x.get('width', 0) * x.get('height', 0), reverse=True):
if 'link' in vf:
best_quality = vf
break
if best_quality and 'link' in best_quality:
path = download_video_file(best_quality['link'], temp_dir_intermediate)
if path:
video_paths.append(path)
temp_intermediate_files.append(path)
logger.info(f"Video downloaded OK from {best_quality['link'][:50]}...")
else:
logger.warning(f"Could not download video from {best_quality['link'][:50]}...")
else:
logger.warning(f"No valid download link found for video {video.get('id')}.")
except Exception as e:
logger.warning(f"Error processing/downloading video {video.get('id')}: {str(e)}")
logger.info(f"Downloaded {len(video_paths)} usable video files.")
if not video_paths:
logger.error("Could not download any usable video file.")
raise ValueError("Could not download any usable video from Pexels.")
# 5. Process and concatenate video clips
logger.info("Processing and concatenating downloaded videos...")
current_duration = 0
min_clip_duration = 0.5
max_clip_segment = 10.0 # Max segment length from one source clip
for i, path in enumerate(video_paths):
# Stop if we have enough duration plus a buffer
if current_duration >= audio_duration + max_clip_segment:
logger.debug(f"Video base sufficient ({current_duration:.1f}s >= {audio_duration:.1f}s + {max_clip_segment:.1f}s buffer). Stopping processing remaining source clips.")
break
clip = None # Initialize for finally block
try:
logger.debug(f"[{i+1}/{len(video_paths)}] Opening clip: {path}")
clip = VideoFileClip(path)
source_clips.append(clip) # Add to list for later cleanup
# Verify the source clip is valid
if clip.reader is None or clip.duration is None or clip.duration <= 0:
logger.warning(f"[{i+1}/{len(video_paths)}] Source clip {path} seems invalid (reader is None or duration <= 0). Skipping.")
continue
# Calculate how much to take from this clip
remaining_needed = audio_duration - current_duration
potential_use_duration = min(clip.duration, max_clip_segment)
if remaining_needed > 0:
segment_duration = min(potential_use_duration, remaining_needed + min_clip_duration)
segment_duration = max(min_clip_duration, segment_duration)
segment_duration = min(segment_duration, clip.duration)
if segment_duration >= min_clip_duration:
try:
# Create a subclip. This creates a *new* clip object.
sub = clip.subclip(0, segment_duration)
# Verify the subclip is valid (it should be a VideoFileClip still)
if sub.reader is None or sub.duration is None or sub.duration <= 0:
logger.warning(f"[{i+1}/{len(video_paths)}] Generated subclip from {path} is invalid. Skipping.")
try: sub.close() # Close the invalid subclip
except: pass
continue
clips_to_concatenate.append(sub)
current_duration += sub.duration
logger.debug(f"[{i+1}/{len(video_paths)}] Segment added: {sub.duration:.1f}s (total video: {current_duration:.1f}/{audio_duration:.1f}s)")
except Exception as sub_e:
logger.warning(f"[{i+1}/{len(video_paths)}] Error creating subclip from {path} ({segment_duration:.1f}s): {str(sub_e)}")
continue
else:
logger.debug(f"[{i+1}/{len(video_paths)}] Clip {path} ({clip.duration:.1f}s) doesn't contribute sufficient segment ({segment_duration:.1f}s needed from it). Skipping.")
else:
logger.debug(f"[{i+1}/{len(video_paths)}] Video base duration already reached. Skipping clip.")
except Exception as e:
logger.warning(f"[{i+1}/{len(video_paths)}] Error processing video {path}: {str(e)}", exc_info=True)
continue
# Source clips are closed in the main finally block
logger.info(f"Source clip processing finished. Obtained {len(clips_to_concatenate)} valid segments.")
if not clips_to_concatenate:
logger.error("No valid video segments available to create the sequence.")
raise ValueError("No valid video segments available to create the video.")
logger.info(f"Concatenating {len(clips_to_concatenate)} video segments.")
concatenated_base = None # Hold the result temporarily
try:
# Concatenate the collected valid segments
concatenated_base = concatenate_videoclips(clips_to_concatenate, method="chain")
logger.info(f"Base video duration after initial concatenation: {concatenated_base.duration:.2f}s")
# Verify the resulting concatenated clip is valid (CompositeVideoClip)
if concatenated_base is None or concatenated_base.duration is None or concatenated_base.duration <= 0:
logger.critical("Concatenated video base clip is invalid after first concatenation (None or zero duration).")
raise ValueError("Failed to create valid video base from segments.")
except Exception as e:
logger.critical(f"Error during initial concatenation: {str(e)}", exc_info=True)
raise ValueError("Failed during initial video concatenation.")
finally:
# IMPORTANT: Close all the individual segments that were concatenated *regardless of success*
for clip_segment in clips_to_concatenate:
try: clip_segment.close()
except: pass
clips_to_concatenate = [] # Clear the list
video_base = concatenated_base # Assign the valid concatenated clip
# --- REVISED REPETITION AND TRIMMING LOGIC ---
final_video_base = video_base # Start with the concatenated base
if final_video_base.duration < audio_duration:
logger.info(f"Base video ({final_video_base.duration:.2f}s) is shorter than audio ({audio_duration:.2f}s). Repeating...")
num_full_repeats = int(audio_duration // final_video_base.duration)
remaining_duration = audio_duration % final_video_base.duration
repeated_clips_list = [final_video_base] * num_full_repeats # List contains the *same* clip object repeated
if remaining_duration > 0:
try:
remaining_clip = final_video_base.subclip(0, remaining_duration)
# Verify remaining clip is valid (should be a CompositeVideoClip from subclip)
if remaining_clip is None or remaining_clip.duration is None or remaining_clip.duration <= 0:
logger.warning(f"Generated subclip for remaining duration {remaining_duration:.2f}s is invalid. Skipping.")
try: remaining_clip.close()
except: pass
else:
repeated_clips_list.append(remaining_clip)
logger.debug(f"Adding remaining segment: {remaining_duration:.2f}s")
except Exception as e:
logger.warning(f"Error creating subclip for remaining duration {remaining_duration:.2f}s: {str(e)}")
if repeated_clips_list:
logger.info(f"Concatenating {len(repeated_clips_list)} parts for repetition.")
video_base_repeated = None # Hold result temporarily
try:
# Concatenate the repeated parts
# If repeated_clips_list contains duplicates of the same object, this is fine for concatenate_videoclips
video_base_repeated = concatenate_videoclips(repeated_clips_list, method="chain")
logger.info(f"Duration of repeated video base: {video_base_repeated.duration:.2f}s")
# Verify the repeated clip is valid
if video_base_repeated is None or video_base_repeated.duration is None or video_base_repeated.duration <= 0:
logger.critical("Concatenated repeated video base clip is invalid.")
raise ValueError("Failed to create valid repeated video base.")
# Close the old base clip *only if it's different from the new one*
if final_video_base is not video_base_repeated:
try: final_video_base.close()
except: pass
# Assign the new valid repeated clip
final_video_base = video_base_repeated
except Exception as e:
logger.critical(f"Error during repetition concatenation: {str(e)}", exc_info=True)
# If repetition fails, the error is raised. The original final_video_base will be closed in main finally.
raise ValueError("Failed during video repetition.")
finally:
# Close the clips in the repeated list, EXCEPT the one assigned to final_video_base
# This needs care as list items might be the same object
if 'repeated_clips_list' in locals():
for clip in repeated_clips_list:
# Only close if it's not the final clip and not already closed (MoviePy tracks this)
if clip is not final_video_base:
try: clip.close()
except: pass
# After repetition (or if no repetition happened), ensure duration matches audio exactly
if final_video_base.duration > audio_duration:
logger.info(f"Trimming video base ({final_video_base.duration:.2f}s) to match audio duration ({audio_duration:.2f}s).")
trimmed_video_base = None # Hold result temporarily
try:
trimmed_video_base = final_video_base.subclip(0, audio_duration)
# Verify the trimmed clip is valid
if trimmed_video_base is None or trimmed_video_base.duration is None or trimmed_video_base.duration <= 0:
logger.critical("Trimmed video base clip is invalid.")
raise ValueError("Failed to create valid trimmed video base.")
# Close the old clip
if final_video_base is not trimmed_video_base:
try: final_video_base.close()
except: pass
# Assign the new valid trimmed clip
final_video_base = trimmed_video_base
except Exception as e:
logger.critical(f"Error during trimming: {str(e)}", exc_info=True)
raise ValueError("Failed during video trimming.")
# Final check on video_base before setting audio/writing
if final_video_base is None or final_video_base.duration is None or final_video_base.duration <= 0:
logger.critical("Final video base clip is invalid before audio/writing (None or zero duration).")
raise ValueError("Final video base clip is invalid.")
# Also check size, as MoviePy needs it for writing
if final_video_base.size is None or final_video_base.size[0] <= 0 or final_video_base.size[1] <= 0:
logger.critical(f"Final video base has invalid size: {final_video_base.size}. Cannot write video.")
raise ValueError("Final video base has invalid size before writing.")
video_base = final_video_base # Use the final adjusted video_base for subsequent steps
# 6. Handle background music
logger.info("Processing audio...")
final_audio = audio_tts # Start with TTS audio
musica_audio_looped = None # Initialize for cleanup
if musica_file:
musica_audio_original = None # Initialize for cleanup
try:
music_path = os.path.join(temp_dir_intermediate, "musica_bg.mp3")
shutil.copyfile(musica_file, music_path)
temp_intermediate_files.append(music_path)
logger.info(f"Background music copied to: {music_path}")
musica_audio_original = AudioFileClip(music_path)
# Verify initial music audio clip
if musica_audio_original.reader is None or musica_audio_original.duration is None or musica_audio_original.duration <= 0:
logger.warning("Background music clip seems invalid or has zero duration. Skipping music.")
# Close the invalid clip before skipping
try: musica_audio_original.close()
except: pass
musica_audio_original = None # Ensure it's None
else:
musica_audio_looped = loop_audio_to_length(musica_audio_original, video_base.duration)
logger.debug(f"Music adjusted to video duration: {musica_audio_looped.duration:.2f}s")
# Verify the looped music clip is valid
if musica_audio_looped is None or musica_audio_looped.duration is None or musica_audio_looped.duration <= 0:
logger.warning("Looped background music clip is invalid. Skipping music.")
# Close the invalid looped clip
try: musica_audio_looped.close()
except: pass
musica_audio_looped = None # Ensure it's None
if musica_audio_looped: # Only proceed if looped music is valid
# CompositeAudioClip uses the *current* audio_tts and musica_audio_looped clips
final_audio = CompositeAudioClip([
musica_audio_looped.volumex(0.2), # Apply effect to the looped clip
audio_tts.volumex(1.0) # Apply effect to the TTS clip (safer than assuming no effects needed)
])
# Verify the resulting composite audio
if final_audio.duration is None or final_audio.duration <= 0:
logger.warning("Composite audio clip is invalid (None or zero duration). Using voice audio only.")
# If CompositeAudioClip fails, need to close its components if they are not the originals
try:
if musica_audio_looped is not musica_audio_original: musica_audio_looped.close()
if audio_tts is not audio_tts_original: audio_tts.close()
# Close the invalid composite audio
try: final_audio.close()
except: pass
except: pass # Ignore errors during cleanup
final_audio = audio_tts_original # Fallback to the original valid TTS
musica_audio = None # Ensure musica_audio variable is None
audio_tts = audio_tts_original # Ensure audio_tts variable points to the original valid TTS
else:
logger.info("Audio mix completed (voice + music).")
# composite audio is valid, set musica_audio variable for later cleanup
musica_audio = musica_audio_looped
# audio_tts variable already points to original which is handled in main finally
except Exception as e:
logger.warning(f"Error processing background music: {str(e)}", exc_info=True)
# Fallback to just TTS audio
final_audio = audio_tts_original
musica_audio = None # Ensure variable is None
audio_tts = audio_tts_original # Ensure variable is original
logger.warning("Using voice audio only due to music processing error.")
# Ensure final_audio duration matches video_base duration if possible
# Check for significant duration mismatch allowing small floating point differences
if final_audio.duration is not None and abs(final_audio.duration - video_base.duration) > 0.2:
logger.warning(f"Final audio duration ({final_audio.duration:.2f}s) differs significantly from video base ({video_base.duration:.2f}s). Attempting trim/extend.")
try:
# Need to create a *new* clip if trimming, and handle closing the old one
if final_audio.duration > video_base.duration:
trimmed_final_audio = final_audio.subclip(0, video_base.duration)
if trimmed_final_audio.duration is None or trimmed_final_audio.duration <= 0:
logger.warning("Trimmed final audio is invalid. Using original final_audio.")
try: trimmed_final_audio.close()
except: pass # Close the invalid trimmed clip
else:
# Safely close the old final_audio if it's different
if final_audio is not trimmed_final_audio:
try: final_audio.close()
except: pass
final_audio = trimmed_final_audio # Use the valid trimmed clip
logger.warning("Trimmed final audio to match video duration.")
# MoviePy often extends audio automatically if it's too short, so we don't explicitly extend here.
except Exception as e:
logger.warning(f"Error adjusting final audio duration: {str(e)}")
# Final check on video_final before writing
# video_final is a composite of video_base and final_audio
video_final = video_base.set_audio(final_audio)
if video_final is None or video_final.duration is None or video_final.duration <= 0:
logger.critical("Final video clip (with audio) is invalid before writing (None or zero duration).")
raise ValueError("Final video clip is invalid before writing.")
output_filename = "final_video.mp4"
output_path = os.path.join(temp_dir_intermediate, output_filename)
logger.info(f"Writing final video to: {output_path}")
video_final.write_videofile(
output_path,
fps=24,
threads=4,
codec="libx264",
audio_codec="aac",
preset="medium",
logger='bar'
)
total_time = (datetime.now() - start_time).total_seconds()
logger.info(f"VIDEO PROCESS FINISHED | Output: {output_path} | Total time: {total_time:.2f}s")
return output_path
except ValueError as ve:
logger.error(f"CONTROLLED ERROR in crear_video: {str(ve)}")
raise ve
except Exception as e:
logger.critical(f"CRITICAL UNHANDLED ERROR in crear_video: {str(e)}", exc_info=True)
raise e
finally:
logger.info("Starting cleanup of clips and intermediate temporary files...")
# Close all initially opened source *video* clips
for clip in source_clips:
try: clip.close()
except Exception as e: logger.warning(f"Error closing source video clip in finally: {str(e)}")
# Close any video segments left in the list (should be empty if successful)
for clip_segment in clips_to_concatenate:
try: clip_segment.close()
except Exception as e: logger.warning(f"Error closing video segment clip in finally: {str(e)}")
# Close the main MoviePy objects if they were successfully created
try:
# Close the audio clips
# Start with the potentially looped/trimmed music clip if it exists
if musica_audio is not None:
try: musica_audio.close()
except Exception as e: logger.warning(f"Error closing musica_audio in finally: {str(e)}")
# Then close the original music audio clip if it exists and is different
if musica_audio_original is not None and musica_audio_original is not musica_audio:
try: musica_audio_original.close()
except Exception as e: logger.warning(f"Error closing musica_audio_original in finally: {str(e)}")
# Close the potentially modified/trimmed TTS clip if it exists and is different from original
if audio_tts is not None and audio_tts is not audio_tts_original:
try: audio_tts.close()
except Exception as e: logger.warning(f"Error closing audio_tts (modified) in finally: {str(e)}")
# Close the original TTS clip if it exists (it's the base)
if audio_tts_original is not None:
try: audio_tts_original.close()
except Exception as e: logger.warning(f"Error closing audio_tts_original in finally: {str(e)}")
# Close video_final first, which should cascade to video_base and final_audio (and their components)
if video_final is not None:
try: video_final.close()
except Exception as e: logger.warning(f"Error closing video_final in finally: {str(e)}")
# If video_final wasn't created but video_base was (due to error before set_audio), close video_base
elif video_base is not None:
try: video_base.close()
except Exception as e: logger.warning(f"Error closing video_base in finally: {str(e)}")
except Exception as e:
logger.warning(f"Error during final clip closing in finally: {str(e)}")
# Clean up intermediate files, but NOT the final video file
if temp_dir_intermediate and os.path.exists(temp_dir_intermediate):
final_output_in_temp = os.path.join(temp_dir_intermediate, "final_video.mp4")
for path in temp_intermediate_files:
try:
if os.path.isfile(path) and path != final_output_in_temp:
logger.debug(f"Deleting temporary file: {path}")
os.remove(path)
except Exception as e:
logger.warning(f"Could not delete temporary file {path}: {str(e)}")
logger.info(f"Intermediate temporary directory {temp_dir_intermediate} will persist for Gradio to read the final video.")
def run_app(prompt_type, prompt_ia, prompt_manual, musica_file):
logger.info("="*80)
logger.info("REQUEST RECEIVED IN INTERFACE")
input_text = prompt_ia if prompt_type == "Generar Guion con IA" else prompt_manual
if not input_text or not input_text.strip():
logger.warning("Empty input text.")
return None, gr.update(value="⚠️ Por favor, ingresa texto para el guion o el tema.")
logger.info(f"Input Type: {prompt_type}")
logger.debug(f"Input Text: '{input_text[:100]}...'")
if musica_file:
logger.info(f"Music file received: {musica_file}")
else:
logger.info("No music file provided.")
try:
logger.info("Calling crear_video...")
video_path = crear_video(prompt_type, input_text, musica_file)
if video_path and os.path.exists(video_path):
logger.info(f"crear_video returned path: {video_path}")
logger.info(f"Size of returned video file: {os.path.getsize(video_path)} bytes")
return video_path, gr.update(value="✅ Video generado exitosamente.", interactive=False)
else:
logger.error(f"crear_video did not return a valid path or file does not exist: {video_path}")
return None, gr.update(value="❌ Error: La generación del video falló o el archivo no se creó correctamente.", interactive=False)
except ValueError as ve:
logger.warning(f"Validation error during video creation: {str(ve)}")
return None, gr.update(value=f"⚠️ Error de validación: {str(ve)}", interactive=False)
except Exception as e:
logger.critical(f"Critical error during video creation: {str(e)}", exc_info=True)
return None, gr.update(value=f"❌ Error inesperado: {str(e)}", interactive=False)
finally:
logger.info("End of run_app handler.")
# Gradio Interface
with gr.Blocks(title="Generador de Videos con IA", theme=gr.themes.Soft(), css="""
.gradio-container {max-width: 800px; margin: auto;}
h1 {text-align: center;}
""") as app:
gr.Markdown("# 🎬 Automatic AI Video Generator")
gr.Markdown("Generate short videos from a topic or script, using stock footage from Pexels and generated voice.")
with gr.Row():
with gr.Column():
prompt_type = gr.Radio(
["Generar Guion con IA", "Usar Mi Guion"],
label="Input Method",
value="Generar Guion con IA"
)
with gr.Column(visible=True) as ia_guion_column:
prompt_ia = gr.Textbox(
label="Topic for AI",
lines=2,
placeholder="Ex: A natural landscape with mountains and rivers at sunrise, showing the beauty of nature...",
max_lines=4,
value=""
)
with gr.Column(visible=False) as manual_guion_column:
prompt_manual = gr.Textbox(
label="Your Full Script",
lines=5,
placeholder="Ex: In this video, we will explore the mysteries of the ocean. We will see fascinating marine life and vibrant coral reefs. Join us on this underwater adventure!",
max_lines=10,
value=""
)
musica_input = gr.Audio(
label="Background Music (optional)",
type="filepath",
interactive=True,
value=None
)
generate_btn = gr.Button("✨ Generate Video", variant="primary")
with gr.Column():
video_output = gr.Video(
label="Generated Video",
interactive=False,
height=400
)
status_output = gr.Textbox(
label="Status",
interactive=False,
show_label=False,
placeholder="Waiting for action...",
value="Waiting for input..."
)
prompt_type.change(
lambda x: (gr.update(visible=x == "Generar Guion con IA"),
gr.update(visible=x == "Usar Mi Guion")),
inputs=prompt_type,
outputs=[ia_guion_column, manual_guion_column]
)
generate_btn.click(
lambda: (None, gr.update(value="⏳ Processing... This can take 2-5 minutes depending on length and resources.", interactive=False)),
outputs=[video_output, status_output],
queue=True,
).then(
run_app,
inputs=[prompt_type, prompt_ia, prompt_manual, musica_input],
outputs=[video_output, status_output]
)
gr.Markdown("### Instructions:")
gr.Markdown("""
1. **Pexels API Key:** Ensure you have set the `PEXELS_API_KEY` environment variable.
2. **Select Input Method**:
- "Generate Script with AI": Describe a topic (e.g., "The beauty of mountains"). AI will generate a short script.
- "Use My Script": Write the full script for your video.
3. **Upload Music** (optional): Select an audio file (MP3, WAV, etc.) for background music.
4. **Click "✨ Generate Video"**.
5. Wait for the video to process. Processing time may vary. Check the status box.
6. If there are errors, check the `video_generator_full.log` file for details.
""")
gr.Markdown("---")
gr.Markdown("Developed by [Your Name/Company/Alias - Optional]")
if __name__ == "__main__":
logger.info("Verifying critical dependencies...")
try:
from moviepy.editor import ColorClip
try:
temp_clip = ColorClip((100,100), color=(255,0,0), duration=0.1) # Use a very short duration
temp_clip.close()
logger.info("MoviePy base clips (like ColorClip) created and closed successfully. FFmpeg seems accessible.")
except Exception as e:
logger.critical(f"Failed to create basic MoviePy clip. Often indicates FFmpeg/ImageMagick issues. Error: {e}", exc_info=True)
except Exception as e:
logger.critical(f"Failed to import MoviePy. Ensure it is installed. Error: {e}", exc_info=True)
logger.info("Starting Gradio app...")
try:
app.launch(server_name="0.0.0.0", server_port=7860, share=False)
except Exception as e:
logger.critical(f"Could not launch app: {str(e)}", exc_info=True)
raise |