app.py

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")
    
    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.")
        try:
            sr = getattr(audio_clip, 'fps', 44100) if audio_clip else 44100
            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="")

    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)
        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
    final_looped_audio = None
    try:
       looped_audio = concatenate_audioclips(audio_segments)
       
       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)

       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)
        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
        logger.error("Fallback to original audio clip failed.")
        return AudioFileClip(filename="")

    finally:
        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
    
    audio_tts_original = None
    musica_audio_original = None
    audio_tts = None
    musica_audio = None
    video_base = None
    video_final = None
    source_clips = []
    clips_to_concatenate = []

    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)
        
        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: audio_tts_original.close()
            except: pass
            audio_tts_original = None
            raise ValueError("Generated voice audio is invalid.")

        audio_tts = audio_tts_original
        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

        for i, path in enumerate(video_paths):
            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
            try:
                logger.debug(f"[{i+1}/{len(video_paths)}] Opening clip: {path}")
                clip = VideoFileClip(path)
                source_clips.append(clip)

                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

                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:
                               sub = clip.subclip(0, segment_duration)
                               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()
                                    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

        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
        try:
            concatenated_base = concatenate_videoclips(clips_to_concatenate, method="chain")
            logger.info(f"Base video duration after initial concatenation: {concatenated_base.duration:.2f}s")

            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:
             for clip_segment in clips_to_concatenate:
                  try: clip_segment.close()
                  except: pass
             clips_to_concatenate = []

        video_base = concatenated_base

        final_video_base = video_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
            
            if remaining_duration > 0:
                try:
                    remaining_clip = final_video_base.subclip(0, remaining_duration)
                    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
                 try:
                    video_base_repeated = concatenate_videoclips(repeated_clips_list, method="chain")
                    logger.info(f"Duration of repeated video base: {video_base_repeated.duration:.2f}s")
                    
                    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.")

                    if final_video_base is not video_base_repeated:
                        try: final_video_base.close()
                        except: pass
                    
                    final_video_base = video_base_repeated

                 except Exception as e:
                    logger.critical(f"Error during repetition concatenation: {str(e)}", exc_info=True)
                    raise ValueError("Failed during video repetition.")
                 finally:
                     if 'repeated_clips_list' in locals():
                         for clip in repeated_clips_list:
                              if clip is not final_video_base:
                                   try: clip.close()
                                   except: pass


        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
             try:
                trimmed_video_base = final_video_base.subclip(0, audio_duration)
                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.")

                if final_video_base is not trimmed_video_base:
                     try: final_video_base.close()
                     except: pass

                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.")


        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.")

        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

        # 6. Handle background music
        logger.info("Processing audio...")
        
        final_audio = audio_tts_original

        musica_audio_looped = None

        if musica_file:
            musica_audio_original = None
            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)
                
                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.")
                     try: musica_audio_original.close()
                     except: pass
                     musica_audio_original = 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")

                     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.")
                          try: musica_audio_looped.close()
                          except: pass
                          musica_audio_looped = None


                if musica_audio_looped:
                    composite_audio = CompositeAudioClip([
                        musica_audio_looped.volumex(0.2),
                        audio_tts_original.volumex(1.0)
                    ])
                    
                    if composite_audio.duration is None or composite_audio.duration <= 0:
                        logger.warning("Composite audio clip is invalid (None or zero duration). Using voice audio only.")
                        try: composite_audio.close()
                        except: pass
                        final_audio = audio_tts_original
                    else:
                         logger.info("Audio mix completed (voice + music).")
                         final_audio = composite_audio
                         musica_audio = musica_audio_looped

            except Exception as e:
                logger.warning(f"Error processing background music: {str(e)}", exc_info=True)
                final_audio = audio_tts_original
                musica_audio = None
                logger.warning("Using voice audio only due to music processing error.")


        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.")
            try:
                 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
                      else:
                           if final_audio is not trimmed_final_audio:
                               try: final_audio.close()
                               except: pass
                           final_audio = trimmed_final_audio
                           logger.warning("Trimmed final audio to match video duration.")
            except Exception as e:
                 logger.warning(f"Error adjusting final audio duration: {str(e)}")


        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...")
        
        for clip in source_clips:
            try:
                clip.close()
            except Exception as e:
                logger.warning(f"Error closing source video clip in finally: {str(e)}")
            
        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 audio clips: looped music, original music, then final audio (which might close its components)
        if musica_audio is not None:
            try:
                musica_audio.close()
            except Exception as e:
                logger.warning(f"Error closing musica_audio (processed) in finally: {str(e)}")
        
        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 TTS clips: potentially modified/trimmed TTS, then original TTS
        # Note: audio_tts variable is only assigned audio_tts_original in this code, but keep structure for safety
        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 (processed) in finally: {str(e)}")

        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 clips: final video (should cascade), then video base if it wasn't the final
        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)}")
        # Note: video_base variable is reassigned to final_video_base. Close only if it exists and is different from video_final
        elif video_base is not None and video_base is not video_final: # Check if video_base holds a different clip
             try:
                 video_base.close()
             except Exception as e:
                 logger.warning(f"Error closing video_base 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
    
    output_video = None
    output_file = None
    status_msg = gr.update(value="⏳ Procesando...", interactive=False)

    if not input_text or not input_text.strip():
        logger.warning("Empty input text.")
        return None, None, gr.update(value="⚠️ Por favor, ingresa texto para el guion o el tema.", interactive=False)

    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")
            output_video = video_path
            output_file = video_path
            status_msg = 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}")
            status_msg = 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)}")
        status_msg = 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)
        status_msg = gr.update(value=f"❌ Error inesperado: {str(e)}", interactive=False)
    finally:
        logger.info("End of run_app handler.")
        return output_video, output_file, status_msg


# 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 Preview",
                interactive=False,
                height=400
            )
            file_output = gr.File(
                label="Download Video",
                interactive=False,
                visible=False
            )
            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, None, gr.update(value="⏳ Procesando... Esto puede tomar 2-5 minutos.", interactive=False)),
        outputs=[video_output, file_output, status_output],
        queue=True,
    ).then(
        run_app,
        inputs=[prompt_type, prompt_ia, prompt_manual, musica_input],
        outputs=[video_output, file_output, status_output]
    ).then(
        lambda video_path, file_path: gr.update(visible=video_path is not None or file_path is not None), # Show download if either video or file path is returned
        inputs=[video_output, file_output],
        outputs=[file_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.  The generated video will appear above, and a download link will show if successful.
    7.  If there are errors, check the `video_generator_full.log` file for details.
    """)
    gr.Markdown("---")
    gr.Markdown("Developed by [Your Name/Company/Alias - Opcional]")

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)
            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