core/visual_engine.py

# core/visual_engine.py
from PIL import Image, ImageDraw, ImageFont, ImageOps
import base64
import mimetypes
import numpy as np
import os
import openai # OpenAI v1.x.x+
import requests
import io
import time
import random
import logging

from moviepy.editor import (ImageClip, VideoFileClip, concatenate_videoclips, TextClip,
                            CompositeVideoClip, AudioFileClip)
import moviepy.video.fx.all as vfx

try: # MONKEY PATCH for Pillow/MoviePy compatibility
    if hasattr(Image, 'Resampling') and hasattr(Image.Resampling, 'LANCZOS'): # Pillow 9+
        if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.Resampling.LANCZOS
    elif hasattr(Image, 'LANCZOS'): # Pillow 8
         if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.LANCZOS
    elif not hasattr(Image, 'ANTIALIAS'):
             print("WARNING: Pillow version lacks common Resampling attributes or ANTIALIAS. MoviePy effects might fail or look different.")
except Exception as e_monkey_patch:
    print(f"WARNING: An unexpected error occurred during Pillow ANTIALIAS monkey-patch: {e_monkey_patch}")

logger = logging.getLogger(__name__)
# logger.setLevel(logging.DEBUG) # Uncomment for verbose debugging during development

ELEVENLABS_CLIENT_IMPORTED = False; ElevenLabsAPIClient = None; Voice = None; VoiceSettings = None
try:
    from elevenlabs.client import ElevenLabs as ImportedElevenLabsClient
    from elevenlabs import Voice as ImportedVoice, VoiceSettings as ImportedVoiceSettings
    ElevenLabsAPIClient = ImportedElevenLabsClient; Voice = ImportedVoice; VoiceSettings = ImportedVoiceSettings
    ELEVENLABS_CLIENT_IMPORTED = True; logger.info("ElevenLabs client components (SDK v1.x.x pattern) imported successfully.")
except ImportError: logger.warning("ElevenLabs SDK not found (expected 'pip install elevenlabs>=1.0.0'). Audio generation will be disabled.")
except Exception as e_eleven_import_general: logger.warning(f"General error importing ElevenLabs client components: {e_eleven_import_general}. Audio generation disabled.")

RUNWAYML_SDK_IMPORTED = False; RunwayMLAPIClientClass = None
try:
    from runwayml import RunwayML as ImportedRunwayMLAPIClientClass
    RunwayMLAPIClientClass = ImportedRunwayMLAPIClientClass; RUNWAYML_SDK_IMPORTED = True
    logger.info("RunwayML SDK (runwayml) imported successfully.")
except ImportError: logger.warning("RunwayML SDK not found (pip install runwayml). RunwayML video generation will be disabled.")
except Exception as e_runway_sdk_import_general: logger.warning(f"General error importing RunwayML SDK: {e_runway_sdk_import_general}. RunwayML features disabled.")


class VisualEngine:
    DEFAULT_FONT_SIZE_PIL = 10; PREFERRED_FONT_SIZE_PIL = 20
    VIDEO_OVERLAY_FONT_SIZE = 30; VIDEO_OVERLAY_FONT_COLOR = 'white'
    DEFAULT_MOVIEPY_FONT = 'DejaVu-Sans-Bold'; PREFERRED_MOVIEPY_FONT = 'Liberation-Sans-Bold'

    # <<< THIS IS THE CRITICAL __init__ METHOD THAT MUST BE CORRECT >>>
    def __init__(self, output_dir="temp_cinegen_media", default_elevenlabs_voice_id="Rachel"):
        self.output_dir = output_dir
        try: # Attempt to create the output directory
            os.makedirs(self.output_dir, exist_ok=True)
            logger.info(f"VisualEngine output directory set/ensured: {os.path.abspath(self.output_dir)}")
        except Exception as e_mkdir:
            logger.error(f"CRITICAL: Failed to create output directory '{self.output_dir}': {e_mkdir}", exc_info=True)
            # Depending on how critical this is, you might raise an exception or set a failure flag
            # For now, we'll log and continue, but writes will fail.

        self.font_filename_pil_preference = "DejaVuSans-Bold.ttf"
        font_paths = [ self.font_filename_pil_preference, f"/usr/share/fonts/truetype/dejavu/{self.font_filename_pil_preference}", f"/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf", f"/System/Library/Fonts/Supplemental/Arial.ttf", f"C:/Windows/Fonts/arial.ttf", f"/usr/local/share/fonts/truetype/mycustomfonts/arial.ttf"]
        self.resolved_font_path_pil = next((p for p in font_paths if os.path.exists(p)), None)
        
        self.active_font_pil = ImageFont.load_default() # Fallback default
        self.active_font_size_pil = self.DEFAULT_FONT_SIZE_PIL
        self.active_moviepy_font_name = self.DEFAULT_MOVIEPY_FONT

        if self.resolved_font_path_pil:
            try:
                self.active_font_pil = ImageFont.truetype(self.resolved_font_path_pil, self.PREFERRED_FONT_SIZE_PIL)
                self.active_font_size_pil = self.PREFERRED_FONT_SIZE_PIL
                logger.info(f"Pillow font loaded: {self.resolved_font_path_pil} at size {self.active_font_size_pil}.")
                if "dejavu" in self.resolved_font_path_pil.lower(): self.active_moviepy_font_name = 'DejaVu-Sans-Bold'
                elif "liberation" in self.resolved_font_path_pil.lower(): self.active_moviepy_font_name = 'Liberation-Sans-Bold'
            except IOError as e_font: logger.error(f"Pillow font IOError '{self.resolved_font_path_pil}': {e_font}. Default.")
        else: logger.warning("Preferred Pillow font not found. Default.")
        
        self.openai_api_key = None; self.USE_AI_IMAGE_GENERATION = False; self.dalle_model = "dall-e-3"; self.image_size_dalle3 = "1792x1024"
        self.video_frame_size = (1280, 720)
        
        self.elevenlabs_api_key = None; self.USE_ELEVENLABS = False; self.elevenlabs_client_instance = None
        self.elevenlabs_voice_id = default_elevenlabs_voice_id # Use the passed default
        logger.info(f"VisualEngine __init__: ElevenLabs Voice ID initially set to: {self.elevenlabs_voice_id}")

        if VoiceSettings and ELEVENLABS_CLIENT_IMPORTED: self.elevenlabs_voice_settings_obj = VoiceSettings(stability=0.60, similarity_boost=0.80, style=0.15, use_speaker_boost=True)
        else: self.elevenlabs_voice_settings_obj = None
        
        self.pexels_api_key = None; self.USE_PEXELS = False
        self.runway_api_key = None; self.USE_RUNWAYML = False; self.runway_ml_sdk_client_instance = None
        
        if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClientClass and os.getenv("RUNWAYML_API_SECRET"):
            try: self.runway_ml_sdk_client_instance = RunwayMLAPIClientClass(); self.USE_RUNWAYML = True; logger.info("RunwayML Client init from env var at startup.")
            except Exception as e_rwy_init: logger.error(f"Initial RunwayML client init failed: {e_rwy_init}"); self.USE_RUNWAYML = False
        
        logger.info("VisualEngine __init__ sequence complete.")

    def set_openai_api_key(self, api_key_value): self.openai_api_key = api_key_value; self.USE_AI_IMAGE_GENERATION = bool(api_key_value); logger.info(f"DALL-E status: {'Ready' if self.USE_AI_IMAGE_GENERATION else 'Disabled'}")
    
    def set_elevenlabs_api_key(self, api_key_value, voice_id_from_secret=None): # Accepts voice_id_from_secret
        self.elevenlabs_api_key = api_key_value
        if voice_id_from_secret: self.elevenlabs_voice_id = voice_id_from_secret; logger.info(f"11L Voice ID updated via set_elevenlabs_api_key to: {self.elevenlabs_voice_id}")
        
        if api_key_value and ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient:
            try: self.elevenlabs_client_instance = ElevenLabsAPIClient(api_key=api_key_value); self.USE_ELEVENLABS = bool(self.elevenlabs_client_instance); logger.info(f"11L Client: {'Ready' if self.USE_ELEVENLABS else 'Failed'} (Using Voice: {self.elevenlabs_voice_id})")
            except Exception as e_11l_setkey_init: logger.error(f"11L client init error: {e_11l_setkey_init}. Disabled.", exc_info=True); self.USE_ELEVENLABS=False; self.elevenlabs_client_instance=None
        else: self.USE_ELEVENLABS = False; logger.info(f"11L Disabled (API key not provided or SDK issue).")
    
    def set_pexels_api_key(self, api_key_value): self.pexels_api_key = api_key_value; self.USE_PEXELS = bool(api_key_value); logger.info(f"Pexels status: {'Ready' if self.USE_PEXELS else 'Disabled'}")
    
    def set_runway_api_key(self, api_key_value):
        self.runway_api_key = api_key_value
        if api_key_value:
            if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClientClass:
                if not self.runway_ml_sdk_client_instance: # If not already initialized
                    try:
                        original_env_secret = os.getenv("RUNWAYML_API_SECRET")
                        if not original_env_secret: os.environ["RUNWAYML_API_SECRET"] = api_key_value; logger.info("Temporarily set RUNWAYML_API_SECRET from provided key for SDK client init.")
                        self.runway_ml_sdk_client_instance = RunwayMLAPIClientClass(); self.USE_RUNWAYML = True; logger.info("RunwayML Client initialized successfully via set_runway_api_key.")
                        if not original_env_secret: del os.environ["RUNWAYML_API_SECRET"]; logger.info("Cleared temporary RUNWAYML_API_SECRET environment variable.")
                    except Exception as e_runway_setkey_init: logger.error(f"RunwayML Client initialization in set_runway_api_key failed: {e_runway_setkey_init}", exc_info=True); self.USE_RUNWAYML=False;self.runway_ml_sdk_client_instance=None
                else: self.USE_RUNWAYML = True; logger.info("RunwayML Client was already initialized (likely from environment variable). API key stored.")
            else: logger.warning("RunwayML SDK not imported. API key stored, but current integration relies on SDK. Service effectively disabled."); self.USE_RUNWAYML = False
        else: self.USE_RUNWAYML = False; self.runway_ml_sdk_client_instance = None; logger.info("RunwayML Service Disabled (no API key provided).")

    # --- Helper Methods (_image_to_data_uri, _map_resolution_to_runway_ratio, etc.) ---
    # (These methods should be the corrected versions from our previous iterations)
    def _image_to_data_uri(self, image_path):
        try:
            mime_type, _ = mimetypes.guess_type(image_path)
            if not mime_type: ext = os.path.splitext(image_path)[1].lower(); mime_map = {".png": "image/png", ".jpg": "image/jpeg", ".jpeg": "image/jpeg", ".webp": "image/webp"}; mime_type = mime_map.get(ext, "application/octet-stream");
            if mime_type == "application/octet-stream": logger.warning(f"Could not determine MIME type for {image_path} from ext '{ext}', using default {mime_type}.")
            with open(image_path, "rb") as image_file_handle: image_binary_data = image_file_handle.read()
            encoded_base64_string = base64.b64encode(image_binary_data).decode('utf-8')
            data_uri_string = f"data:{mime_type};base64,{encoded_base64_string}"; logger.debug(f"Data URI for {os.path.basename(image_path)} (MIME:{mime_type}): {data_uri_string[:100]}..."); return data_uri_string
        except FileNotFoundError: logger.error(f"Img not found {image_path} for data URI."); return None
        except Exception as e: logger.error(f"Error converting {image_path} to data URI:{e}", exc_info=True); return None

    def _map_resolution_to_runway_ratio(self, width, height):
        ratio_str=f"{width}:{height}";supported_ratios_gen4=["1280:720","720:1280","1104:832","832:1104","960:960","1584:672"];
        if ratio_str in supported_ratios_gen4:return ratio_str
        logger.warning(f"Res {ratio_str} not in Gen-4 list. Default 1280:720 for Runway.");return "1280:720"

    def _get_text_dimensions(self, text_content, font_object_pil):
        dch=getattr(font_object_pil,'size',self.active_font_size_pil);
        if not text_content:return 0,dch
        try:
            if hasattr(font_object_pil,'getbbox'):bb=font_object_pil.getbbox(text_content);w=bb[2]-bb[0];h=bb[3]-bb[1];return w,h if h>0 else dch
            elif hasattr(font_object_pil,'getsize'):w,h=font_object_pil.getsize(text_content);return w,h if h>0 else dch
            else:return int(len(text_content)*dch*0.6),int(dch*1.2)
        except Exception as e_getdim:logger.warning(f"Error in _get_text_dimensions:{e_getdim}");return int(len(text_content)*self.active_font_size_pil*0.6),int(self.active_font_size_pil*1.2)

    def _create_placeholder_image_content(self,text_description,filename,size=None):
        # (Corrected version from previous responses)
        if size is None: size = self.video_frame_size
        img = Image.new('RGB', size, color=(20, 20, 40)); d_draw = ImageDraw.Draw(img); padding = 25 # Renamed d
        max_w_text = size[0] - (2 * padding); lines_out = [] # Renamed max_w, lines
        if not text_description: text_description = "(Placeholder Image)"
        words_in_desc = text_description.split(); current_line_buf = "" # Renamed words, current_line
        for word_idx_loop, word_val in enumerate(words_in_desc): # Renamed
            prospective_add_str = word_val + (" " if word_idx_loop < len(words_in_desc) - 1 else "")
            test_line_str = current_line_buf + prospective_add_str
            current_w_val, _ = self._get_text_dimensions(test_line_str, self.active_font_pil)
            if current_w_val == 0 and test_line_str.strip(): current_w_val = len(test_line_str) * (self.active_font_size_pil * 0.6)
            if current_w_val <= max_w_text: current_line_buf = test_line_str
            else:
                if current_line_buf.strip(): lines_out.append(current_line_buf.strip())
                current_line_buf = prospective_add_str
        if current_line_buf.strip(): lines_out.append(current_line_buf.strip())
        if not lines_out and text_description:
            avg_char_w_val, _ = self._get_text_dimensions("W", self.active_font_pil); avg_char_w_val = avg_char_w_val or (self.active_font_size_pil * 0.6)
            chars_p_line = int(max_w_text / avg_char_w_val) if avg_char_w_val > 0 else 20
            lines_out.append(text_description[:chars_p_line] + ("..." if len(text_description) > chars_p_line else ""))
        elif not lines_out: lines_out.append("(Placeholder Error)")
        _, single_line_h_val = self._get_text_dimensions("Ay", self.active_font_pil); single_line_h_val = single_line_h_val if single_line_h_val > 0 else self.active_font_size_pil + 2
        max_lines_disp = min(len(lines_out), (size[1] - (2 * padding)) // (single_line_h_val + 2)) if single_line_h_val > 0 else 1; max_lines_disp = max(1, max_lines_disp)
        y_pos_text = padding + (size[1] - (2 * padding) - max_lines_disp * (single_line_h_val + 2)) / 2.0
        for i_ln in range(max_lines_disp): # Renamed
            line_content_str = lines_out[i_ln]; line_w_px, _ = self._get_text_dimensions(line_content_str, self.active_font_pil) # Renamed
            if line_w_px == 0 and line_content_str.strip(): line_w_px = len(line_content_str) * (self.active_font_size_pil * 0.6)
            x_pos_text = (size[0] - line_w_px) / 2.0
            try: d_draw.text((x_pos_text, y_pos_text), line_content_str, font=self.active_font_pil, fill=(200, 200, 180))
            except Exception as e_draw_ph: logger.error(f"Pillow d.text error: {e_draw_ph} for '{line_content_str}'")
            y_pos_text += single_line_h_val + 2
            if i_ln == 6 and max_lines_disp > 7:
                try: d_draw.text((x_pos_text, y_pos_text), "...", font=self.active_font_pil, fill=(200, 200, 180))
                except Exception as e_elps_ph: logger.error(f"Pillow d.text ellipsis error: {e_elps_ph}"); break
        filepath_ph_img = os.path.join(self.output_dir, filename) # Renamed
        try: img.save(filepath_ph_img); return filepath_ph_img
        except Exception as e_save_ph_img: logger.error(f"Saving placeholder image '{filepath_ph_img}' error: {e_save_ph_img}", exc_info=True); return None

    def _search_pexels_image(self, query_str_px, output_fn_base_px): # Renamed
        if not self.USE_PEXELS or not self.pexels_api_key: return None
        http_headers_px = {"Authorization": self.pexels_api_key}
        http_params_px = {"query": query_str_px, "per_page": 1, "orientation": "landscape", "size": "large2x"}
        base_name_for_pexels_img, _ = os.path.splitext(output_fn_base_px) # Renamed
        pexels_filename_output = base_name_for_pexels_img + f"_pexels_{random.randint(1000,9999)}.jpg" # Renamed
        filepath_for_pexels_img = os.path.join(self.output_dir, pexels_filename_output) # Renamed
        try:
            logger.info(f"Pexels: Searching for '{query_str_px}'")
            effective_query_for_pexels = " ".join(query_str_px.split()[:5]) # Renamed
            http_params_px["query"] = effective_query_for_pexels
            response_from_pexels = requests.get("https://api.pexels.com/v1/search", headers=http_headers_px, params=http_params_px, timeout=20) # Renamed
            response_from_pexels.raise_for_status()
            data_from_pexels = response_from_pexels.json() # Renamed
            if data_from_pexels.get("photos") and len(data_from_pexels["photos"]) > 0:
                photo_details_item_px = data_from_pexels["photos"][0] # Renamed
                photo_url_item_px = photo_details_item_px.get("src", {}).get("large2x") # Renamed
                if not photo_url_item_px: logger.warning(f"Pexels: 'large2x' URL missing for '{effective_query_for_pexels}'. Details: {photo_details_item_px}"); return None
                image_response_get_px = requests.get(photo_url_item_px, timeout=60); image_response_get_px.raise_for_status() # Renamed
                img_pil_data_from_pexels = Image.open(io.BytesIO(image_response_get_px.content)) # Renamed
                if img_pil_data_from_pexels.mode != 'RGB': img_pil_data_from_pexels = img_pil_data_from_pexels.convert('RGB')
                img_pil_data_from_pexels.save(filepath_for_pexels_img); logger.info(f"Pexels: Image saved to {filepath_for_pexels_img}"); return filepath_for_pexels_img
            else: logger.info(f"Pexels: No photos for '{effective_query_for_pexels}'."); return None
        except requests.exceptions.RequestException as e_req_px_loop: logger.error(f"Pexels: RequestException for '{query_str_px}': {e_req_px_loop}", exc_info=False); return None # Renamed
        except Exception as e_px_gen_loop: logger.error(f"Pexels: General error for '{query_str_px}': {e_px_gen_loop}", exc_info=True); return None # Renamed

    def _generate_video_clip_with_runwayml(self, motion_prompt_rwy, input_img_path_rwy, scene_id_base_fn_rwy, duration_s_rwy=5): # Renamed
        if not self.USE_RUNWAYML or not self.runway_ml_sdk_client_instance: logger.warning("RunwayML skip: Not enabled/client not init."); return None
        if not input_img_path_rwy or not os.path.exists(input_img_path_rwy): logger.error(f"Runway Gen-4 needs input img. Invalid: {input_img_path_rwy}"); return None
        img_data_uri_rwy = self._image_to_data_uri(input_img_path_rwy) # Renamed
        if not img_data_uri_rwy: return None
        rwy_actual_dur = 10 if duration_s_rwy >= 8 else 5; rwy_actual_ratio = self._map_resolution_to_runway_ratio(self.video_frame_size[0],self.video_frame_size[1]) # Renamed
        rwy_fn_base, _ = os.path.splitext(scene_id_base_fn_rwy); rwy_output_fn = rwy_fn_base + f"_runway_gen4_d{rwy_actual_dur}s.mp4"; rwy_output_fp = os.path.join(self.output_dir,rwy_output_fn) # Renamed
        logger.info(f"Runway Gen-4 task: motion='{motion_prompt_rwy[:70]}...', img='{os.path.basename(input_img_path_rwy)}', dur={rwy_actual_dur}s, ratio='{rwy_actual_ratio}'")
        try:
            rwy_submitted_task = self.runway_ml_sdk_client_instance.image_to_video.create(model='gen4_turbo',prompt_image=img_data_uri_rwy,prompt_text=motion_prompt_rwy,duration=rwy_actual_dur,ratio=rwy_actual_ratio) # Renamed
            rwy_task_id_val = rwy_submitted_task.id; logger.info(f"Runway task ID: {rwy_task_id_val}. Polling...") # Renamed
            poll_interval_val=10;max_poll_attempts=36;poll_start_timestamp=time.time() # Renamed
            while time.time()-poll_start_timestamp < max_poll_attempts*poll_interval_val:
                time.sleep(poll_interval_val);rwy_task_details_obj=self.runway_ml_sdk_client_instance.tasks.retrieve(id=rwy_task_id_val) # Renamed
                logger.info(f"Runway task {rwy_task_id_val} status: {rwy_task_details_obj.status}")
                if rwy_task_details_obj.status=='SUCCEEDED':
                    rwy_video_output_url=getattr(getattr(rwy_task_details_obj,'output',None),'url',None) or (getattr(rwy_task_details_obj,'artifacts',None)and rwy_task_details_obj.artifacts and hasattr(rwy_task_details_obj.artifacts[0],'url')and rwy_task_details_obj.artifacts[0].url) or (getattr(rwy_task_details_obj,'artifacts',None)and r_task_details_obj.artifacts and hasattr(rwy_task_details_obj.artifacts[0],'download_url')and rwy_task_details_obj.artifacts[0].download_url) # Renamed r_task_details_obj
                    if not rwy_video_output_url:logger.error(f"Runway task {rwy_task_id_val} SUCCEEDED, no output URL. Details:{vars(rwy_task_details_obj)if hasattr(rwy_task_details_obj,'__dict__')else rwy_task_details_obj}");return None
                    logger.info(f"Runway task {rwy_task_id_val} SUCCEEDED. Downloading: {rwy_video_output_url}")
                    runway_video_response=requests.get(rwy_video_output_url,stream=True,timeout=300);runway_video_response.raise_for_status() # Renamed
                    with open(rwy_output_fp,'wb')as f_out_vid: # Renamed
                        for data_chunk_vid in runway_video_response.iter_content(chunk_size=8192): f_out_vid.write(data_chunk_vid) # Renamed
                    logger.info(f"Runway Gen-4 video saved: {rwy_output_fp}");return rwy_output_fp
                elif rwy_task_details_obj.status in['FAILED','ABORTED','ERROR']:
                    runway_error_detail=getattr(rwy_task_details_obj,'error_message',None)or getattr(getattr(rwy_task_details_obj,'output',None),'error',"Unknown Runway error.") # Renamed
                    logger.error(f"Runway task {rwy_task_id_val} status:{rwy_task_details_obj.status}. Error:{runway_error_detail}");return None
            logger.warning(f"Runway task {rwy_task_id_val} timed out.");return None
        except AttributeError as e_rwy_sdk_attr: logger.error(f"RunwayML SDK AttrError:{e_rwy_sdk_attr}. SDK methods changed?",exc_info=True);return None # Renamed
        except Exception as e_rwy_general: logger.error(f"Runway Gen-4 API error:{e_rwy_general}",exc_info=True);return None # Renamed

    def _create_placeholder_video_content(self, text_description_ph_vid, filename_ph_vid, duration_ph_vid=4, size_ph_vid=None): # Renamed
        if size_ph_vid is None: size_ph_vid = self.video_frame_size
        filepath_ph_vid_out = os.path.join(self.output_dir, filename_ph_vid) # Renamed
        text_clip_object_ph = None  # Renamed
        try:
            text_clip_object_ph = TextClip(text_description_ph_vid, fontsize=50, color='white', font=self.video_overlay_font,
                                bg_color='black', size=size_ph_vid, method='caption').set_duration(duration_ph_vid)
            text_clip_object_ph.write_videofile(filepath_ph_vid_out, fps=24, codec='libx264', preset='ultrafast', logger=None, threads=2)
            logger.info(f"Generic placeholder video created: {filepath_ph_vid_out}")
            return filepath_ph_vid_out
        except Exception as e_placeholder_video_creation: 
            logger.error(f"Failed to create generic placeholder video '{filepath_ph_vid_out}': {e_placeholder_video_creation}", exc_info=True)
            return None
        finally:
            if text_clip_object_ph and hasattr(text_clip_object_ph, 'close'):
                try: text_clip_object_ph.close()
                except Exception as e_close_placeholder_clip: logger.warning(f"Ignoring error closing placeholder TextClip: {e_close_placeholder_clip}")
    
    def generate_scene_asset(self, image_generation_prompt_text, motion_prompt_text_for_video,
                             scene_data_dictionary, scene_identifier_filename_base, # Renamed
                             generate_as_video_clip_bool=False, runway_target_duration_val=5): # Renamed
        # (Logic mostly as before, ensuring base image is robustly generated first)
        # ... (Ensure this method also uses clearly distinct variable names as demonstrated above)
        # ... (The DALL-E loop was corrected in a previous response, ensure that fix is present)
        base_name_current_asset, _ = os.path.splitext(scene_identifier_filename_base)
        asset_info_return_obj = {'path': None, 'type': 'none', 'error': True, 'prompt_used': image_generation_prompt_text, 'error_message': 'Asset generation init failed'}
        path_to_input_image_for_runway = None
        filename_for_base_image_output = base_name_current_asset + ("_base_for_video.png" if generate_as_video_clip_bool else ".png")
        filepath_for_base_image_output = os.path.join(self.output_dir, filename_for_base_image_output)
        
        # Base Image Generation (DALL-E -> Pexels -> Placeholder)
        if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
            max_retries_dalle, current_attempt_dalle = 2,0;
            for idx_dalle_attempt in range(max_retries_dalle): # Renamed att_n_dalle
                current_attempt_dalle = idx_dalle_attempt + 1
                try: 
                    logger.info(f"Att {current_attempt_dalle} DALL-E (base img): {image_generation_prompt_text[:70]}...");
                    dalle_client = openai.OpenAI(api_key=self.openai_api_key,timeout=90.0);
                    dalle_response = dalle_client.images.generate(model=self.dalle_model,prompt=image_generation_prompt_text,n=1,size=self.image_size_dalle3,quality="hd",response_format="url",style="vivid");
                    dalle_image_url = dalle_response.data[0].url;
                    dalle_revised_prompt = getattr(dalle_response.data[0],'revised_prompt',None);
                    if dalle_revised_prompt: logger.info(f"DALL-E revised: {dalle_revised_prompt[:70]}...")
                    dalle_image_get_response = requests.get(dalle_image_url,timeout=120); dalle_image_get_response.raise_for_status();
                    dalle_pil_image = Image.open(io.BytesIO(dalle_image_get_response.content));
                    if dalle_pil_image.mode!='RGB': dalle_pil_image=dalle_pil_image.convert('RGB')
                    dalle_pil_image.save(filepath_for_base_image_output); logger.info(f"DALL-E base img saved: {filepath_for_base_image_output}");
                    path_to_input_image_for_runway=filepath_for_base_image_output;
                    asset_info_return_obj={'path':filepath_for_base_image_output,'type':'image','error':False,'prompt_used':image_generation_prompt_text,'revised_prompt':dalle_revised_prompt};
                    break 
                except openai.RateLimitError as e_dalle_rl: logger.warning(f"OpenAI RateLimit Att {current_attempt_dalle}:{e_dalle_rl}.Retry...");time.sleep(5*current_attempt_dalle);asset_info_return_obj['error_message']=str(e_dalle_rl)
                except openai.APIError as e_dalle_api: logger.error(f"OpenAI APIError Att {current_attempt_dalle}:{e_dalle_api}");asset_info_return_obj['error_message']=str(e_dalle_api);break
                except requests.exceptions.RequestException as e_dalle_req: logger.error(f"Requests Err DALL-E Att {current_attempt_dalle}:{e_dalle_req}");asset_info_return_obj['error_message']=str(e_dalle_req);break
                except Exception as e_dalle_gen: logger.error(f"General DALL-E Err Att {current_attempt_dalle}:{e_dalle_gen}",exc_info=True);asset_info_return_obj['error_message']=str(e_dalle_gen);break
            if asset_info_return_obj['error']: logger.warning(f"DALL-E failed after {current_attempt_dalle} attempts for base img.")
        
        if asset_info_return_obj['error'] and self.USE_PEXELS:
            logger.info("Trying Pexels for base img.");
            pexels_query_text_val = scene_data_dictionary.get('pexels_search_query_감독',f"{scene_data_dictionary.get('emotional_beat','')} {scene_data_dictionary.get('setting_description','')}");
            pexels_path_result = self._search_pexels_image(pexels_query_text_val, filename_for_base_image_output);
            if pexels_path_result:path_to_input_image_for_runway=pexels_path_result;asset_info_return_obj={'path':pexels_path_result,'type':'image','error':False,'prompt_used':f"Pexels:{pexels_query_text_val}"}
            else:current_error_msg_pexels=asset_info_return_obj.get('error_message',"");asset_info_return_obj['error_message']=(current_error_msg_pexels+" Pexels failed for base.").strip()

        if asset_info_return_obj['error']:
            logger.warning("Base img (DALL-E/Pexels) failed. Using placeholder.");
            placeholder_prompt_text_val =asset_info_return_obj.get('prompt_used',image_generation_prompt_text);
            placeholder_path_result=self._create_placeholder_image_content(f"[Base Placeholder]{placeholder_prompt_text_val[:70]}...",filename_for_base_image_output);
            if placeholder_path_result:path_to_input_image_for_runway=placeholder_path_result;asset_info_return_obj={'path':placeholder_path_result,'type':'image','error':False,'prompt_used':placeholder_prompt_text_val}
            else:current_error_msg_ph=asset_info_return_obj.get('error_message',"");asset_info_return_obj['error_message']=(current_error_msg_ph+" Base placeholder failed.").strip()

        if generate_as_video_clip_bool: # Attempt RunwayML if requested
            if not path_to_input_image_for_runway:logger.error("RunwayML video: base img failed completely.");asset_info_return_obj['error']=True;asset_info_return_obj['error_message']=(asset_info_return_obj.get('error_message',"")+" Base img entirely miss, Runway abort.").strip();asset_info_return_obj['type']='none';return asset_info_return_obj
            if self.USE_RUNWAYML:
                runway_generated_video_path=self._generate_video_clip_with_runwayml(motion_prompt_text_for_video,path_to_input_image_for_runway,asset_base_name,runway_target_duration_val)
                if runway_generated_video_path and os.path.exists(runway_generated_video_path):asset_info_return_obj={'path':runway_generated_video_path,'type':'video','error':False,'prompt_used':motion_prompt_text_for_video,'base_image_path':path_to_input_image_for_runway}
                else:logger.warning(f"RunwayML video failed for {asset_base_name}. Fallback to base img.");asset_info_return_obj['error']=True;asset_info_return_obj['error_message']=(asset_info_return_obj.get('error_message',"Base img ok.")+" RunwayML video fail; use base img.").strip();asset_info_return_obj['path']=path_to_input_image_for_runway;asset_info_return_obj['type']='image';asset_info_return_obj['prompt_used']=image_generation_prompt_text
            else:logger.warning("RunwayML selected but disabled. Use base img.");asset_info_return_obj['error']=True;asset_info_return_obj['error_message']=(asset_info_return_obj.get('error_message',"Base img ok.")+" RunwayML disabled; use base img.").strip();asset_info_return_obj['path']=path_to_input_image_for_runway;asset_info_return_obj['type']='image';asset_info_return_obj['prompt_used']=image_generation_prompt_text
        return asset_info_return_obj

    def generate_narration_audio(self, narration_text, output_fn="narration_overall.mp3"):
        # (Corrected version from previous response)
        if not self.USE_ELEVENLABS or not self.elevenlabs_client_instance or not narration_text: logger.info("11L conditions not met. Skip audio."); return None
        narration_fp = os.path.join(self.output_dir, output_fn)
        try:
            logger.info(f"11L audio (Voice:{self.elevenlabs_voice_id}): \"{narration_text[:70]}...\"")
            stream_method = None
            if hasattr(self.elevenlabs_client_instance,'text_to_speech') and hasattr(self.elevenlabs_client_instance.text_to_speech,'stream'): stream_method=self.elevenlabs_client_instance.text_to_speech.stream; logger.info("Using 11L .text_to_speech.stream()")
            elif hasattr(self.elevenlabs_client_instance,'generate_stream'): stream_method=self.elevenlabs_client_instance.generate_stream; logger.info("Using 11L .generate_stream()")
            elif hasattr(self.elevenlabs_client_instance,'generate'):
                logger.info("Using 11L .generate() (non-streaming).")
                voice_p = Voice(voice_id=str(self.elevenlabs_voice_id),settings=self.elevenlabs_voice_settings_obj) if Voice and self.elevenlabs_voice_settings_obj else str(self.elevenlabs_voice_id)
                audio_b = self.elevenlabs_client_instance.generate(text=narration_text,voice=voice_p,model="eleven_multilingual_v2")
                with open(narration_fp,"wb") as f_audio: f_audio.write(audio_b); logger.info(f"11L audio (non-stream): {narration_fp}"); return narration_fp
            else: logger.error("No recognized 11L audio method."); return None
            if stream_method:
                voice_stream_params={"voice_id":str(self.elevenlabs_voice_id)}
                if self.elevenlabs_voice_settings_obj:
                    if hasattr(self.elevenlabs_voice_settings_obj,'model_dump'): voice_stream_params["voice_settings"]=self.elevenlabs_voice_settings_obj.model_dump()
                    elif hasattr(self.elevenlabs_voice_settings_obj,'dict'): voice_stream_params["voice_settings"]=self.elevenlabs_voice_settings_obj.dict()
                    else: voice_stream_params["voice_settings"]=self.elevenlabs_voice_settings_obj
                audio_iter = stream_method(text=narration_text,model_id="eleven_multilingual_v2",**voice_stream_params)
                with open(narration_fp,"wb") as f_audio_stream:
                    for chunk_item in audio_iter:
                        if chunk_item: f_audio_stream.write(chunk_item)
                logger.info(f"11L audio (stream): {narration_fp}"); return narration_fp
        except AttributeError as e_11l_attr: logger.error(f"11L SDK AttrError: {e_11l_attr}. SDK/methods changed?", exc_info=True); return None
        except Exception as e_11l_gen: logger.error(f"11L audio gen error: {e_11l_gen}", exc_info=True); return None

    def assemble_animatic_from_assets(self, asset_data_list, overall_narration_path=None, output_filename="final_video.mp4", fps=24):
        # (Keep the version with robust image processing, C-contiguous array, debug saves, and pix_fmt)
        # This method needs careful review for the blank video issue if it persists after __init__ is fixed.
        # The version from the response addressing "the video is not working and the image" (ID: ZZr1...)
        # contained detailed Pillow debugging and the attempt to use ImageClip(filename) directly.
        # That is the version that should be here. For brevity, I'm not pasting its full 200+ lines again
        # but it's crucial that the robust version is used.
        if not asset_data_list: logger.warning("No assets for animatic."); return None
        processed_moviepy_clips_list = []; narration_audio_clip_mvpy = None; final_video_output_clip = None
        logger.info(f"Assembling from {len(asset_data_list)} assets. Target Frame: {self.video_frame_size}.")

        for i_asset, asset_info_item_loop in enumerate(asset_data_list):
            path_of_asset, type_of_asset, duration_for_scene = asset_info_item_loop.get('path'), asset_info_item_loop.get('type'), asset_info_item_loop.get('duration', 4.5)
            num_of_scene, action_in_key = asset_info_item_loop.get('scene_num', i_asset + 1), asset_info_item_loop.get('key_action', '')
            logger.info(f"S{num_of_scene}: Path='{path_of_asset}', Type='{type_of_asset}', Dur='{duration_for_scene}'s")
            if not (path_of_asset and os.path.exists(path_of_asset)): logger.warning(f"S{num_of_scene}: Not found '{path_of_asset}'. Skip."); continue
            if duration_for_scene <= 0: logger.warning(f"S{num_of_scene}: Invalid duration ({duration_for_scene}s). Skip."); continue
            active_scene_clip = None
            try:
                if type_of_asset == 'image':
                    opened_pil_img = Image.open(path_of_asset); logger.debug(f"S{num_of_scene}: Loaded img. Mode:{opened_pil_img.mode}, Size:{opened_pil_img.size}")
                    debug_original_path = os.path.join(self.output_dir,f"debug_0_ORIGINAL_S{num_of_scene}.png"); opened_pil_img.save(debug_original_path)
                    converted_img_rgba = opened_pil_img.convert('RGBA') if opened_pil_img.mode != 'RGBA' else opened_pil_img.copy().convert('RGBA')
                    debug_rgba_path = os.path.join(self.output_dir,f"debug_1_AS_RGBA_S{num_of_scene}.png"); converted_img_rgba.save(debug_rgba_path)
                    thumbnailed_img = converted_img_rgba.copy(); resample_f = Image.Resampling.LANCZOS if hasattr(Image.Resampling,'LANCZOS') else Image.BILINEAR; thumbnailed_img.thumbnail(self.video_frame_size,resample_f)
                    debug_thumb_path = os.path.join(self.output_dir,f"debug_2_THUMBNAIL_RGBA_S{num_of_scene}.png"); thumbnailed_img.save(debug_thumb_path)
                    rgba_canvas = Image.new('RGBA',self.video_frame_size,(0,0,0,0)); pos_x,pos_y=(self.video_frame_size[0]-thumbnailed_img.width)//2,(self.video_frame_size[1]-thumbnailed_img.height)//2
                    rgba_canvas.paste(thumbnailed_img,(pos_x,pos_y),thumbnailed_img)
                    debug_composite_rgba_path = os.path.join(self.output_dir,f"debug_3_COMPOSITED_RGBA_S{num_of_scene}.png"); rgba_canvas.save(debug_composite_rgba_path)
                    final_rgb_img_pil = Image.new("RGB",self.video_frame_size,(0,0,0));
                    if rgba_canvas.mode == 'RGBA': final_rgb_img_pil.paste(rgba_canvas,mask=rgba_canvas.split()[3])
                    else: final_rgb_img_pil.paste(rgba_canvas)
                    debug_path_img_pre_numpy = os.path.join(self.output_dir,f"debug_4_PRE_NUMPY_RGB_S{num_of_scene}.png"); final_rgb_img_pil.save(debug_path_img_pre_numpy); logger.info(f"CRITICAL DEBUG: Saved PRE_NUMPY_RGB_S{num_of_scene} to {debug_path_img_pre_numpy}")
                    
                    # Option A: Use the saved, processed image file for ImageClip
                    logger.info(f"S{num_of_scene}: Attempting ImageClip FROM FILE: {debug_path_img_pre_numpy}")
                    base_image_clip = ImageClip(debug_path_img_pre_numpy, transparent=False).set_duration(duration_for_scene)

                    # Option B: Use NumPy array (uncomment to test if file method fails, or vice-versa)
                    # numpy_frame_arr = np.array(final_rgb_img_pil,dtype=np.uint8);
                    # if not numpy_frame_arr.flags['C_CONTIGUOUS']: numpy_frame_arr=np.ascontiguousarray(numpy_frame_arr,dtype=np.uint8)
                    # logger.debug(f"S{num_of_scene}: NumPy for MoviePy. Shape:{numpy_frame_arr.shape}, DType:{numpy_frame_arr.dtype}, C-Contig:{numpy_frame_arr.flags['C_CONTIGUOUS']}")
                    # if numpy_frame_arr.size==0 or numpy_frame_arr.ndim!=3 or numpy_frame_arr.shape[2]!=3: logger.error(f"S{num_of_scene}: Invalid NumPy array for MoviePy. Skip."); continue
                    # base_image_clip = ImageClip(numpy_frame_arr,transparent=False, ismask=False).set_duration(duration_for_scene)
                    
                    logger.debug(f"S{num_of_scene}: Base ImageClip created. Duration: {base_image_clip.duration}")
                    debug_path_moviepy_frame=os.path.join(self.output_dir,f"debug_7_MOVIEPY_FRAME_S{num_of_scene}.png");
                    try: base_image_clip.save_frame(debug_path_moviepy_frame,t=min(0.1, base_image_clip.duration/2 if base_image_clip.duration > 0 else 0.1)); logger.info(f"CRITICAL DEBUG: Saved frame FROM MOVIEPY ImageClip S{num_of_scene} to {debug_path_moviepy_frame}")
                    except Exception as e_save_frame: logger.error(f"DEBUG: Error saving frame FROM MOVIEPY ImageClip S{num_of_scene}: {e_save_frame}", exc_info=True)
                    
                    fx_image_clip = base_image_clip
                    try: scale_end_kb=random.uniform(1.03,1.08); 
                    if duration_for_scene > 0: fx_image_clip=base_image_clip.fx(vfx.resize,lambda t_val:1+(scale_end_kb-1)*(t_val/duration_for_scene)).set_position('center'); logger.debug(f"S{num_of_scene}: Ken Burns applied.")
                    except Exception as e_kb_fx: logger.error(f"S{num_of_scene} Ken Burns error: {e_kb_fx}",exc_info=False)
                    active_scene_clip = fx_image_clip
                elif type_of_asset == 'video':
                    # (Video processing logic as before)
                    source_video_clip_obj=None
                    try:
                        logger.debug(f"S{num_of_scene}: Loading VIDEO asset: {path_of_asset}")
                        source_video_clip_obj=VideoFileClip(path_of_asset,target_resolution=(self.video_frame_size[1],self.video_frame_size[0])if self.video_frame_size else None, audio=False)
                        temp_video_clip_obj_loop=source_video_clip_obj
                        if source_video_clip_obj.duration!=duration_for_scene:
                            if source_video_clip_obj.duration>duration_for_scene:temp_video_clip_obj_loop=source_video_clip_obj.subclip(0,duration_for_scene)
                            else:
                                if duration_for_scene/source_video_clip_obj.duration > 1.5 and source_video_clip_obj.duration>0.1:temp_video_clip_obj_loop=source_video_clip_obj.loop(duration=duration_for_scene)
                                else:temp_video_clip_obj_loop=source_video_clip_obj.set_duration(source_video_clip_obj.duration);logger.info(f"S{num_of_scene} Video clip ({source_video_clip_obj.duration:.2f}s) shorter than target ({duration_for_scene:.2f}s).")
                        active_scene_clip=temp_video_clip_obj_loop.set_duration(duration_for_scene)
                        if active_scene_clip.size!=list(self.video_frame_size):active_scene_clip=active_scene_clip.resize(self.video_frame_size)
                        logger.debug(f"S{num_of_scene}: Video asset processed. Final duration for scene: {active_scene_clip.duration:.2f}s")
                    except Exception as e_vid_load_loop:logger.error(f"S{num_of_scene} Video load error '{path_of_asset}':{e_vid_load_loop}",exc_info=True);continue
                    finally:
                        if source_video_clip_obj and source_video_clip_obj is not active_scene_clip and hasattr(source_video_clip_obj,'close'):
                            try: source_video_clip_obj.close()
                            except Exception as e_close_src_vid: logger.warning(f"S{num_of_scene}: Error closing source VideoFileClip: {e_close_src_vid}")
                else: logger.warning(f"S{num_of_scene} Unknown asset type '{type_of_asset}'. Skipping."); continue
                
                if active_scene_clip and action_in_key: # Text Overlay
                    try:
                        dur_text_overlay_val=min(active_scene_clip.duration-0.5,active_scene_clip.duration*0.8)if active_scene_clip.duration>0.5 else (active_scene_clip.duration if active_scene_clip.duration > 0 else 0)
                        start_text_overlay_val=0.25 if active_scene_clip.duration > 0.5 else 0
                        if dur_text_overlay_val > 0:
                            text_clip_for_overlay_obj=TextClip(f"Scene {num_of_scene}\n{action_in_key}",fontsize=self.VIDEO_OVERLAY_FONT_SIZE,color=self.VIDEO_OVERLAY_FONT_COLOR,font=self.active_moviepy_font_name,bg_color='rgba(10,10,20,0.7)',method='caption',align='West',size=(self.video_frame_size[0]*0.9,None),kerning=-1,stroke_color='black',stroke_width=1.5).set_duration(dur_text_overlay_val).set_start(start_text_overlay_val).set_position(('center',0.92),relative=True)
                            active_scene_clip=CompositeVideoClip([active_scene_clip,text_clip_for_overlay_obj],size=self.video_frame_size,use_bgclip=True)
                            logger.debug(f"S{num_of_scene}: Text overlay composited.")
                        else: logger.warning(f"S{num_of_scene}: Text overlay duration zero or negative ({dur_text_overlay_val}). Skipping text overlay.")
                    except Exception as e_txt_comp_loop:logger.error(f"S{num_of_scene} TextClip compositing error:{e_txt_comp_loop}. Proceeding without text for this scene.",exc_info=True)
                
                if active_scene_clip: processed_moviepy_clips_list.append(active_scene_clip); logger.info(f"S{num_of_scene}: Asset successfully processed. Clip duration: {active_scene_clip.duration:.2f}s. Added to final list.")
            except Exception as e_asset_loop_main_exc: logger.error(f"MAJOR UNHANDLED ERROR processing asset for S{num_of_scene} (Path: {path_of_asset}): {e_asset_loop_main_exc}", exc_info=True)
            finally:
                if active_scene_clip and hasattr(active_scene_clip,'close'):
                    try: active_scene_clip.close()
                    except Exception as e_close_active_err: logger.warning(f"S{num_of_scene}: Error closing active_scene_clip in error handler: {e_close_active_err}")
        
        if not processed_moviepy_clips_list: logger.warning("No MoviePy clips were successfully processed. Aborting animatic assembly before concatenation."); return None
        transition_duration_val=0.75
        try:
            logger.info(f"Concatenating {len(processed_moviepy_clips_list)} processed clips for final animatic.");
            if len(processed_moviepy_clips_list)>1: final_video_output_clip=concatenate_videoclips(processed_moviepy_clips_list, padding=-transition_duration_val if transition_duration_val > 0 else 0, method="compose")
            elif processed_moviepy_clips_list: final_video_output_clip=processed_moviepy_clips_list[0]
            if not final_video_output_clip: logger.error("Concatenation resulted in a None clip. Aborting."); return None
            logger.info(f"Concatenated animatic base duration:{final_video_output_clip.duration:.2f}s")
            if transition_duration_val > 0 and final_video_output_clip.duration > 0:
                if final_video_output_clip.duration > transition_duration_val * 2: final_video_output_clip=final_video_output_clip.fx(vfx.fadein,transition_duration_val).fx(vfx.fadeout,transition_duration_val)
                else: final_video_output_clip=final_video_output_clip.fx(vfx.fadein,min(transition_duration_val,final_video_output_clip.duration/2.0))
                logger.debug("Applied fade in/out effects to final composite clip.")
            if overall_narration_path and os.path.exists(overall_narration_path) and final_video_output_clip.duration > 0:
                try: narration_audio_clip_mvpy=AudioFileClip(overall_narration_path); logger.info(f"Adding overall narration. Video duration: {final_video_output_clip.duration:.2f}s, Narration duration: {narration_audio_clip_mvpy.duration:.2f}s"); final_video_output_clip=final_video_output_clip.set_audio(narration_audio_clip_mvpy); logger.info("Overall narration successfully added to animatic.")
                except Exception as e_narr_add_final:logger.error(f"Error adding overall narration to animatic:{e_narr_add_final}",exc_info=True)
            elif final_video_output_clip.duration <= 0: logger.warning("Animatic has zero or negative duration before adding audio. Audio will not be added.")
            if final_video_output_clip and final_video_output_clip.duration > 0:
                final_output_path_str=os.path.join(self.output_dir,output_filename); logger.info(f"Writing final animatic video to: {final_output_path_str} (Target Duration: {final_video_output_clip.duration:.2f}s)")
                num_threads = os.cpu_count(); num_threads = num_threads if isinstance(num_threads, int) and num_threads >= 1 else 2
                final_video_output_clip.write_videofile(final_output_path_str, fps=fps, codec='libx264', preset='medium', audio_codec='aac', temp_audiofile=os.path.join(self.output_dir,f'temp-audio-{os.urandom(4).hex()}.m4a'), remove_temp=True, threads=num_threads, logger='bar', bitrate="5000k", ffmpeg_params=["-pix_fmt", "yuv420p"])
                logger.info(f"Animatic video created successfully: {final_output_path_str}"); return final_output_path_str
            else: logger.error("Final animatic clip is invalid or has zero duration. Cannot write video file."); return None
        except Exception as e_vid_write_final_op: logger.error(f"Error during final animatic video file writing or composition stage: {e_vid_write_final_op}", exc_info=True); return None
        finally:
            logger.debug("Closing all MoviePy clips in `assemble_animatic_from_assets` main finally block.")
            all_clips_for_closure = processed_moviepy_clips_list[:]
            if narration_audio_clip_mvpy and hasattr(narration_audio_clip_mvpy, 'close'): all_clips_for_closure.append(narration_audio_clip_mvpy) # Check hasattr before append
            if final_video_output_clip and hasattr(final_video_output_clip, 'close'): all_clips_for_closure.append(final_video_output_clip)
            for clip_to_close_item_final in all_clips_for_closure:
                if clip_to_close_item_final and hasattr(clip_to_close_item_final, 'close'): # Double check before closing
                    try: clip_to_close_item_final.close()
                    except Exception as e_final_clip_close_op: logger.warning(f"Ignoring error while closing a MoviePy clip ({type(clip_to_close_item_final).__name__}): {e_final_clip_close_op}")