Update core/visual_engine.py

core/visual_engine.py

@@ -1,16 +1,6 @@
-# core/visual_engine.py
 from PIL import Image, ImageDraw, ImageFont, ImageOps
 import base64
-
-# --- MONKEY PATCH ---
-try:
-    if hasattr(Image, 'Resampling') and hasattr(Image.Resampling, 'LANCZOS'):
-        if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.Resampling.LANCZOS
-    elif hasattr(Image, 'LANCZOS'):
-         if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.LANCZOS
-    elif not hasattr(Image, 'ANTIALIAS'): print("WARNING: Pillow ANTIALIAS/Resampling issue.")
-except Exception as e_mp: print(f"WARNING: ANTIALIAS patch error: {e_mp}")
-
+import json
 from moviepy.editor import (ImageClip, VideoFileClip, concatenate_videoclips, TextClip,
                             CompositeVideoClip, AudioFileClip)
 import moviepy.video.fx.all as vfx
@@ -27,16 +17,37 @@ import mimetypes
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)
 
+# --- MONKEY PATCH ---
+try:
+    if hasattr(Image, 'Resampling') and hasattr(Image.Resampling, 'LANCZOS'):
+        if not hasattr(Image, 'ANTIALIAS'):
+            Image.ANTIALIAS = Image.Resampling.LANCZOS
+    elif hasattr(Image, 'LANCZOS'):
+        if not hasattr(Image, 'ANTIALIAS'):
+            Image.ANTIALIAS = Image.LANCZOS
+    elif not hasattr(Image, 'ANTIALIAS'):
+        print("WARNING: Pillow ANTIALIAS/Resampling issue.")
+except Exception as e_mp:
+    print(f"WARNING: ANTIALIAS patch error: {e_mp}")
+
 # --- SERVICE CLIENT IMPORTS ---
-ELEVENLABS_CLIENT_IMPORTED = False; ElevenLabsAPIClient = None; Voice = None; VoiceSettings = None
+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 imported.")
-except Exception as e_eleven: logger.warning(f"ElevenLabs client import failed: {e_eleven}. Audio disabled.")
+    ElevenLabsAPIClient = ImportedElevenLabsClient
+    Voice = ImportedVoice
+    VoiceSettings = ImportedVoiceSettings
+    ELEVENLABS_CLIENT_IMPORTED = True
+    logger.info("ElevenLabs client components imported.")
+except Exception as e_eleven:
+    logger.warning(f"ElevenLabs client import failed: {e_eleven}. Audio disabled.")
 
-RUNWAYML_SDK_IMPORTED = False; RunwayMLAPIClient = None
+RUNWAYML_SDK_IMPORTED = False
+RunwayMLAPIClient = None
 try:
     from runwayml import RunwayML as ImportedRunwayMLClient
     RunwayMLAPIClient = ImportedRunwayMLClient
@@ -53,129 +64,241 @@ class VisualEngine:
         self.output_dir = output_dir
         os.makedirs(self.output_dir, exist_ok=True)
         self.font_filename = "DejaVuSans-Bold.ttf"
-        font_paths_to_try = [ self.font_filename, "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf", "/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf", "/System/Library/Fonts/Supplemental/Arial.ttf", "C:/Windows/Fonts/arial.ttf", f"/usr/local/share/fonts/truetype/mycustomfonts/arial.ttf"]
+        font_paths_to_try = [
+            self.font_filename,
+            "/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
+            "/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf",
+            "/System/Library/Fonts/Supplemental/Arial.ttf",
+            "C:/Windows/Fonts/arial.ttf",
+            "/usr/local/share/fonts/truetype/mycustomfonts/arial.ttf"
+        ]
         self.font_path_pil = next((p for p in font_paths_to_try if os.path.exists(p)), None)
-        self.font_size_pil = 20; self.video_overlay_font_size = 30; self.video_overlay_font_color = 'white'
+        self.font_size_pil = 20
+        self.video_overlay_font_size = 30
+        self.video_overlay_font_color = 'white'
         self.video_overlay_font = 'DejaVu-Sans-Bold'
         try:
-            self.font = ImageFont.truetype(self.font_path_pil, self.font_size_pil) if self.font_path_pil else ImageFont.load_default()
-            if self.font_path_pil: logger.info(f"Pillow font: {self.font_path_pil}.")
-            else: logger.warning("Default Pillow font."); self.font_size_pil = 10
-        except IOError as e_font: logger.error(f"Pillow font IOError: {e_font}. Default."); self.font = ImageFont.load_default(); self.font_size_pil = 10
-        
-        self.openai_api_key = None; self.USE_AI_IMAGE_GENERATION = False; self.dalle_model = "dall-e-3"; self.image_size_dalle3 = "1792x1024"
+            if self.font_path_pil:
+                self.font = ImageFont.truetype(self.font_path_pil, self.font_size_pil)
+                logger.info(f"Pillow font: {self.font_path_pil}.")
+            else:
+                self.font = ImageFont.load_default()
+                logger.warning("Default Pillow font.")
+                self.font_size_pil = 10
+        except IOError as e_font:
+            logger.error(f"Pillow font IOError: {e_font}. Default.")
+            self.font = ImageFont.load_default()
+            self.font_size_pil = 10
+
+        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 = None; self.elevenlabs_voice_id = default_elevenlabs_voice_id
-        if VoiceSettings and ELEVENLABS_CLIENT_IMPORTED: self.elevenlabs_voice_settings = VoiceSettings(stability=0.60, similarity_boost=0.80, style=0.15, use_speaker_boost=True)
-        else: self.elevenlabs_voice_settings = None
-        
-        self.pexels_api_key = None; self.USE_PEXELS = False
-        
-        self.runway_api_key = None; self.USE_RUNWAYML = False; self.runway_client = None
+
+        self.elevenlabs_api_key = None
+        self.USE_ELEVENLABS = False
+        self.elevenlabs_client = None
+        self.elevenlabs_voice_id = default_elevenlabs_voice_id
+        if VoiceSettings and ELEVENLABS_CLIENT_IMPORTED:
+            self.elevenlabs_voice_settings = VoiceSettings(
+                stability=0.60,
+                similarity_boost=0.80,
+                style=0.15,
+                use_speaker_boost=True
+            )
+        else:
+            self.elevenlabs_voice_settings = None
+
+        self.pexels_api_key = None
+        self.USE_PEXELS = False
+
+        self.runway_api_key = None
+        self.USE_RUNWAYML = False
+        self.runway_client = None
         if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
             try:
-                if os.getenv("RUNWAYML_API_SECRET"): self.runway_client = RunwayMLAPIClient(); logger.info("RunwayML Client initialized using RUNWAYML_API_SECRET env var.")
-            except Exception as e_runway_init: logger.error(f"Failed to initialize RunwayML client during __init__: {e_runway_init}", exc_info=True)
-        
+                if os.getenv("RUNWAYML_API_SECRET"):
+                    self.runway_client = RunwayMLAPIClient()
+                    logger.info("RunwayML Client initialized using RUNWAYML_API_SECRET env var.")
+            except Exception as e_runway_init:
+                logger.error(f"Failed to initialize RunwayML client during __init__: {e_runway_init}", exc_info=True)
+
         logger.info("VisualEngine initialized.")
 
-    def set_openai_api_key(self,k): self.openai_api_key=k; self.USE_AI_IMAGE_GENERATION=bool(k); logger.info(f"DALL-E ({self.dalle_model}) {'Ready.' if k else 'Disabled.'}")
-    def set_elevenlabs_api_key(self,api_key, voice_id_from_secret=None):
-        self.elevenlabs_api_key=api_key
-        if voice_id_from_secret: self.elevenlabs_voice_id = voice_id_from_secret
+    def set_openai_api_key(self, k):
+        self.openai_api_key = k
+        self.USE_AI_IMAGE_GENERATION = bool(k)
+        logger.info(f"DALL-E ({self.dalle_model}) {'Ready.' if k else 'Disabled.'}")
+
+    def set_elevenlabs_api_key(self, api_key, voice_id_from_secret=None):
+        self.elevenlabs_api_key = api_key
+        if voice_id_from_secret:
+            self.elevenlabs_voice_id = voice_id_from_secret
         if api_key and ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient:
-            try: self.elevenlabs_client = ElevenLabsAPIClient(api_key=api_key); self.USE_ELEVENLABS=bool(self.elevenlabs_client); logger.info(f"ElevenLabs Client {'Ready' if self.USE_ELEVENLABS else 'Failed Init'} (Voice ID: {self.elevenlabs_voice_id}).")
-            except Exception as e: logger.error(f"ElevenLabs client init error: {e}. Disabled.", exc_info=True); self.USE_ELEVENLABS=False
-        else: self.USE_ELEVENLABS=False; logger.info("ElevenLabs Disabled (no key or SDK issue).")
-    def set_pexels_api_key(self,k): self.pexels_api_key=k; self.USE_PEXELS=bool(k); logger.info(f"Pexels Search {'Ready.' if k else 'Disabled.'}")
-    
+            try:
+                self.elevenlabs_client = ElevenLabsAPIClient(api_key=api_key)
+                self.USE_ELEVENLABS = bool(self.elevenlabs_client)
+                logger.info(f"ElevenLabs Client {'Ready' if self.USE_ELEVENLABS else 'Failed Init'} (Voice ID: {self.elevenlabs_voice_id}).")
+            except Exception as e:
+                logger.error(f"ElevenLabs client init error: {e}. Disabled.", exc_info=True)
+                self.USE_ELEVENLABS = False
+        else:
+            self.USE_ELEVENLABS = False
+            logger.info("ElevenLabs Disabled (no key or SDK issue).")
+
+    def set_pexels_api_key(self, k):
+        self.pexels_api_key = k
+        self.USE_PEXELS = bool(k)
+        logger.info(f"Pexels Search {'Ready.' if k else 'Disabled.'}")
+
     def set_runway_api_key(self, k):
         self.runway_api_key = k
         if k:
             if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
                 if not self.runway_client:
                     try:
-                        if not os.getenv("RUNWAYML_API_SECRET"): os.environ["RUNWAYML_API_SECRET"] = k; logger.info("Setting RUNWAYML_API_SECRET env var from provided key.")
-                        self.runway_client = RunwayMLAPIClient(); self.USE_RUNWAYML = True; logger.info("RunwayML Client initialized successfully via set_runway_api_key.")
-                    except Exception as e_client_init: logger.error(f"RunwayML Client init failed in set_runway_api_key: {e_client_init}", exc_info=True); self.USE_RUNWAYML = False
-                else: self.USE_RUNWAYML = True; logger.info("RunwayML Client was already initialized.")
-            else: logger.warning("RunwayML SDK not imported. API key set, but integration requires SDK."); self.USE_RUNWAYML = False
-        else: self.USE_RUNWAYML = False; logger.info("RunwayML Disabled (no API key).")
+                        if not os.getenv("RUNWAYML_API_SECRET"):
+                            os.environ["RUNWAYML_API_SECRET"] = k
+                            logger.info("Setting RUNWAYML_API_SECRET env var from provided key.")
+                        self.runway_client = RunwayMLAPIClient()
+                        self.USE_RUNWAYML = True
+                        logger.info("RunwayML Client initialized successfully via set_runway_api_key.")
+                    except Exception as e_client_init:
+                        logger.error(f"RunwayML Client init failed in set_runway_api_key: {e_client_init}", exc_info=True)
+                        self.USE_RUNWAYML = False
+                else:
+                    self.USE_RUNWAYML = True
+                    logger.info("RunwayML Client was already initialized.")
+            else:
+                logger.warning("RunwayML SDK not imported. API key set, but integration requires SDK.")
+                self.USE_RUNWAYML = False
+        else:
+            self.USE_RUNWAYML = False
+            logger.info("RunwayML Disabled (no API key).")
 
     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()
-                if ext == ".png": mime_type = "image/png"
-                elif ext in [".jpg", ".jpeg"]: mime_type = "image/jpeg"
-                else: mime_type = "application/octet-stream"; logger.warning(f"Unknown MIME for {image_path}, using {mime_type}.")
-            with open(image_path, "rb") as image_file: encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
+                if ext == ".png":
+                    mime_type = "image/png"
+                elif ext in [".jpg", ".jpeg"]:
+                    mime_type = "image/jpeg"
+                else:
+                    mime_type = "application/octet-stream"
+                    logger.warning(f"Unknown MIME for {image_path}, using {mime_type}.")
+            with open(image_path, "rb") as image_file:
+                encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
             data_uri = f"data:{mime_type};base64,{encoded_string}"
-            logger.debug(f"Data URI for {image_path} (first 100): {data_uri[:100]}"); return data_uri
-        except Exception as e: logger.error(f"Error converting {image_path} to data URI: {e}", exc_info=True); return None
+            logger.debug(f"Data URI for {image_path} (first 100): {data_uri[:100]}")
+            return data_uri
+        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 = ["1280:720", "720:1280", "1104:832", "832:1104", "960:960", "1584:672"]
-        if ratio_str in supported_ratios: return ratio_str
-        logger.warning(f"Res {ratio_str} not directly Gen-4 supported. Default 1280:720."); return "1280:720"
+        ratio_str = f"{width}:{height}"
+        supported_ratios = ["1280:720", "720:1280", "1104:832", "832:1104", "960:960", "1584:672"]
+        if ratio_str in supported_ratios:
+            return ratio_str
+        logger.warning(f"Res {ratio_str} not directly Gen-4 supported. Default 1280:720.")
+        return "1280:720"
 
-    def _get_text_dimensions(self,text_content,font_obj):
+    def _get_text_dimensions(self, text_content, font_obj):
         default_char_height = getattr(font_obj, 'size', self.font_size_pil)
-        if not text_content: return 0, default_char_height
+        if not text_content:
+            return 0, default_char_height
         try:
-            if hasattr(font_obj,'getbbox'): bbox=font_obj.getbbox(text_content);w=bbox[2]-bbox[0];h=bbox[3]-bbox[1]; return w, h if h > 0 else default_char_height
-            elif hasattr(font_obj,'getsize'): w,h=font_obj.getsize(text_content); return w, h if h > 0 else default_char_height
-            else: return int(len(text_content)*default_char_height*0.6),int(default_char_height*1.2)
-        except Exception as e: logger.warning(f"Error in _get_text_dimensions: {e}"); return int(len(text_content)*self.font_size_pil*0.6),int(self.font_size_pil*1.2)
-
-    def _create_placeholder_image_content(self,text_description,filename,size=None):
-        if size is None: size = self.video_frame_size
-        img=Image.new('RGB',size,color=(20,20,40));d=ImageDraw.Draw(img);padding=25;max_w=size[0]-(2*padding);lines=[];
-        if not text_description: text_description="(Placeholder Image)"
-        words=text_description.split();current_line=""
+            if hasattr(font_obj, 'getbbox'):
+                bbox = font_obj.getbbox(text_content)
+                w = bbox[2] - bbox[0]
+                h = bbox[3] - bbox[1]
+                return w, h if h > 0 else default_char_height
+            elif hasattr(font_obj, 'getsize'):
+                w, h = font_obj.getsize(text_content)
+                return w, h if h > 0 else default_char_height
+            else:
+                return int(len(text_content) * default_char_height * 0.6), int(default_char_height * 1.2)
+        except Exception as e:
+            logger.warning(f"Error in _get_text_dimensions: {e}")
+            return int(len(text_content) * self.font_size_pil * 0.6), int(self.font_size_pil * 1.2)
+
+    def _create_placeholder_image_content(self, text_description, filename, size=None):
+        if size is None:
+            size = self.video_frame_size
+        img = Image.new('RGB', size, color=(20, 20, 40))
+        d = ImageDraw.Draw(img)
+        padding = 25
+        max_w = size[0] - (2 * padding)
+        lines = []
+        if not text_description:
+            text_description = "(Placeholder Image)"
+        words = text_description.split()
+        current_line = ""
         for word_idx, word in enumerate(words):
             prospective_line_addition = word + (" " if word_idx < len(words) - 1 else "")
             test_line = current_line + prospective_line_addition
             current_line_width, _ = self._get_text_dimensions(test_line, self.font)
-            if current_line_width == 0 and test_line.strip(): current_line_width = len(test_line) * (self.font_size_pil * 0.6)
-            if current_line_width <= max_w: current_line = test_line
+            if current_line_width == 0 and test_line.strip():
+                current_line_width = len(test_line) * (self.font_size_pil * 0.6)
+            if current_line_width <= max_w:
+                current_line = test_line
             else:
-                if current_line.strip(): lines.append(current_line.strip())
+                if current_line.strip():
+                    lines.append(current_line.strip())
                 current_line = prospective_line_addition
-        if current_line.strip(): lines.append(current_line.strip())
+        if current_line.strip():
+            lines.append(current_line.strip())
         if not lines and text_description:
             avg_char_width, _ = self._get_text_dimensions("W", self.font)
-            if avg_char_width == 0: avg_char_width = self.font_size_pil * 0.6
+            if avg_char_width == 0:
+                avg_char_width = self.font_size_pil * 0.6
             chars_per_line = int(max_w / avg_char_width) if avg_char_width > 0 else 20
             lines.append(text_description[:chars_per_line] + ("..." if len(text_description) > chars_per_line else ""))
-        elif not lines: lines.append("(Placeholder Error)")
-        _,single_line_h=self._get_text_dimensions("Ay",self.font); single_line_h = single_line_h if single_line_h > 0 else self.font_size_pil + 2
-        max_lines_to_display=min(len(lines),(size[1]-(2*padding))//(single_line_h+2)) if single_line_h > 0 else 1
-        if max_lines_to_display <=0: max_lines_to_display = 1
-        y_text_start = padding + (size[1]-(2*padding) - max_lines_to_display*(single_line_h+2))/2.0; y_text = y_text_start
+        elif not lines:
+            lines.append("(Placeholder Error)")
+        _, single_line_h = self._get_text_dimensions("Ay", self.font)
+        single_line_h = single_line_h if single_line_h > 0 else self.font_size_pil + 2
+        max_lines_to_display = min(len(lines), (size[1] - (2 * padding)) // (single_line_h + 2)) if single_line_h > 0 else 1
+        if max_lines_to_display <= 0:
+            max_lines_to_display = 1
+        y_text_start = padding + (size[1] - (2 * padding) - max_lines_to_display * (single_line_h + 2)) / 2.0
+        y_text = y_text_start
         for i in range(max_lines_to_display):
-            line_content=lines[i]; line_w,_=self._get_text_dimensions(line_content,self.font)
-            if line_w == 0 and line_content.strip(): line_w = len(line_content) * (self.font_size_pil * 0.6)
-            x_text=(size[0]-line_w)/2.0
-            try: d.text((x_text,y_text),line_content,font=self.font,fill=(200,200,180))
-            except Exception as e_draw: logger.error(f"Pillow d.text error: {e_draw} for line '{line_content}'")
-            y_text+=single_line_h+2
-            if i==6 and max_lines_to_display > 7:
-                try: d.text((x_text,y_text),"...",font=self.font,fill=(200,200,180))
-                except Exception as e_ellipsis: logger.error(f"Pillow d.text ellipsis error: {e_ellipsis}")
+            line_content = lines[i]
+            line_w, _ = self._get_text_dimensions(line_content, self.font)
+            if line_w == 0 and line_content.strip():
+                line_w = len(line_content) * (self.font_size_pil * 0.6)
+            x_text = (size[0] - line_w) / 2.0
+            try:
+                d.text((x_text, y_text), line_content, font=self.font, fill=(200, 200, 180))
+            except Exception as e_draw:
+                logger.error(f"Pillow d.text error: {e_draw} for line '{line_content}'")
+            y_text += single_line_h + 2
+            if i == 6 and max_lines_to_display > 7:
+                try:
+                    d.text((x_text, y_text), "...", font=self.font, fill=(200, 200, 180))
+                except Exception as e_ellipsis:
+                    logger.error(f"Pillow d.text ellipsis error: {e_ellipsis}")
                 break
-        filepath=os.path.join(self.output_dir,filename);
-        try:img.save(filepath);return filepath
-        except Exception as e:logger.error(f"Saving placeholder image {filepath}: {e}", exc_info=True);return None
+        filepath = os.path.join(self.output_dir, filename)
+        try:
+            img.save(filepath)
+            return filepath
+        except Exception as e:
+            logger.error(f"Saving placeholder image {filepath}: {e}", exc_info=True)
+            return None
 
     def _search_pexels_image(self, query, output_filename_base):
         # <<< CORRECTED METHOD >>>
-        if not self.USE_PEXELS or not self.pexels_api_key: return None
+        if not self.USE_PEXELS or not self.pexels_api_key:
+            return None
         headers = {"Authorization": self.pexels_api_key}
         params = {"query": query, "per_page": 1, "orientation": "landscape", "size": "large2x"}
-        pexels_filename = output_filename_base.replace(".png", f"_pexels_{random.randint(1000,9999)}.jpg").replace(".mp4", f"_pexels_{random.randint(1000,9999)}.jpg")
+        pexels_filename = output_filename_base.replace(".png", f"_pexels_{random.randint(1000,9999)}.jpg")\
+                                             .replace(".mp4", f"_pexels_{random.randint(1000,9999)}.jpg")
         filepath = os.path.join(self.output_dir, pexels_filename)
         try:
             logger.info(f"Pexels search: '{query}'")
@@ -196,7 +319,7 @@ class VisualEngine:
                 return filepath
             else:
                 logger.info(f"No photos found on Pexels for query: '{effective_query}'")
-                return None # Added explicit return
+                return None
         except requests.exceptions.RequestException as e_req:
             logger.error(f"Pexels request error for query '{query}': {e_req}", exc_info=True)
         except json.JSONDecodeError as e_json:
@@ -205,196 +328,541 @@ class VisualEngine:
             logger.error(f"Pexels image save error for query '{query}': {e_io}", exc_info=True)
         except Exception as e:
             logger.error(f"Unexpected Pexels error for query '{query}': {e}", exc_info=True)
-        return None # Ensure None is returned on any exception
+        return None
 
-    def _generate_video_clip_with_runwayml(self, text_prompt_for_motion, input_image_path, scene_identifier_filename_base, target_duration_seconds=5):
-        if not self.USE_RUNWAYML or not self.runway_client: logger.warning("RunwayML not enabled/client not init. Skip video."); return None
-        if not input_image_path or not os.path.exists(input_image_path): logger.error(f"Runway Gen-4 needs input image. Path invalid: {input_image_path}"); return None
+    def _generate_video_clip_with_runwayml(self, text_prompt_for_motion, input_image_path,
+                                           scene_identifier_filename_base, target_duration_seconds=5):
+        if not self.USE_RUNWAYML or not self.runway_client:
+            logger.warning("RunwayML not enabled/client not init. Skip video.")
+            return None
+        if not input_image_path or not os.path.exists(input_image_path):
+            logger.error(f"Runway Gen-4 needs input image. Path invalid: {input_image_path}")
+            return None
         image_data_uri = self._image_to_data_uri(input_image_path)
-        if not image_data_uri: return None
+        if not image_data_uri:
+            return None
         runway_duration = 10 if target_duration_seconds > 7 else 5
-        runway_ratio_str = self._map_resolution_to_runway_ratio(self.video_frame_size[0], self.video_frame_size[1])
-        output_video_filename = scene_identifier_filename_base.replace(".png", f"_runway_gen4_d{runway_duration}s.mp4")
+        runway_ratio_str = self._map_resolution_to_runway_ratio(
+            self.video_frame_size[0], self.video_frame_size[1]
+        )
+        output_video_filename = scene_identifier_filename_base.replace(
+            ".png", f"_runway_gen4_d{runway_duration}s.mp4"
+        )
         output_video_filepath = os.path.join(self.output_dir, output_video_filename)
-        logger.info(f"Runway Gen-4 task: motion='{text_prompt_for_motion[:100]}...', img='{os.path.basename(input_image_path)}', dur={runway_duration}s, ratio='{runway_ratio_str}'")
+        logger.info(f"Runway Gen-4 task: motion='{text_prompt_for_motion[:100]}...', "
+                    f"img='{os.path.basename(input_image_path)}', dur={runway_duration}s, ratio='{runway_ratio_str}'")
         try:
-            task = self.runway_client.image_to_video.create(model='gen4_turbo', prompt_image=image_data_uri, prompt_text=text_prompt_for_motion, duration=runway_duration, ratio=runway_ratio_str)
+            task = self.runway_client.image_to_video.create(
+                model='gen4_turbo',
+                prompt_image=image_data_uri,
+                prompt_text=text_prompt_for_motion,
+                duration=runway_duration,
+                ratio=runway_ratio_str
+            )
             logger.info(f"Runway Gen-4 task ID: {task.id}. Polling...")
-            poll_interval=10; max_polls=36
+            poll_interval = 10
+            max_polls = 36
             for _ in range(max_polls):
-                time.sleep(poll_interval); task_details = self.runway_client.tasks.retrieve(id=task.id)
+                time.sleep(poll_interval)
+                task_details = self.runway_client.tasks.retrieve(id=task.id)
                 logger.info(f"Runway task {task.id} status: {task_details.status}")
                 if task_details.status == 'SUCCEEDED':
-                    output_url = getattr(getattr(task_details, 'output', None), 'url', None) or \
-                                 (getattr(task_details, 'artifacts', None) and task_details.artifacts[0].url if task_details.artifacts and hasattr(task_details.artifacts[0], 'url') else None) or \
-                                 (getattr(task_details, 'artifacts', None) and task_details.artifacts[0].download_url if task_details.artifacts and hasattr(task_details.artifacts[0], 'download_url') else None)
-                    if not output_url: logger.error(f"Runway task {task.id} SUCCEEDED, but no output URL in details: {vars(task_details) if hasattr(task_details, '__dict__') else task_details}"); return None
+                    output_url = (
+                        getattr(getattr(task_details, 'output', None), 'url', None)
+                        or (
+                            getattr(task_details, 'artifacts', None)
+                            and task_details.artifacts[0].url
+                            if task_details.artifacts and hasattr(task_details.artifacts[0], 'url')
+                            else None
+                        )
+                        or (
+                            getattr(task_details, 'artifacts', None)
+                            and task_details.artifacts[0].download_url
+                            if task_details.artifacts and hasattr(task_details.artifacts[0], 'download_url')
+                            else None
+                        )
+                    )
+                    if not output_url:
+                        logger.error(
+                            f"Runway task {task.id} SUCCEEDED, but no output URL in details: "
+                            f"{vars(task_details) if hasattr(task_details, '__dict__') else task_details}"
+                        )
+                        return None
                     logger.info(f"Runway task {task.id} SUCCEEDED. Downloading from: {output_url}")
-                    video_response = requests.get(output_url, stream=True, timeout=300); video_response.raise_for_status()
+                    video_response = requests.get(output_url, stream=True, timeout=300)
+                    video_response.raise_for_status()
                     with open(output_video_filepath, 'wb') as f:
-                        for chunk in video_response.iter_content(chunk_size=8192): f.write(chunk)
-                    logger.info(f"Runway Gen-4 video saved: {output_video_filepath}"); return output_video_filepath
+                        for chunk in video_response.iter_content(chunk_size=8192):
+                            f.write(chunk)
+                    logger.info(f"Runway Gen-4 video saved: {output_video_filepath}")
+                    return output_video_filepath
                 elif task_details.status in ['FAILED', 'ABORTED']:
-                    em = getattr(task_details,'error_message',None) or getattr(getattr(task_details,'output',None),'error', "Unknown error")
-                    logger.error(f"Runway task {task.id} status: {task_details.status}. Error: {em}"); return None
-            logger.warning(f"Runway task {task.id} timed out."); return None
-        except AttributeError as ae: logger.error(f"RunwayML SDK AttributeError: {ae}. SDK/methods might differ.", exc_info=True); return None
-        except Exception as e: logger.error(f"Runway Gen-4 API error: {e}", exc_info=True); return None
+                    em = (
+                        getattr(task_details, 'error_message', None)
+                        or getattr(getattr(task_details, 'output', None), 'error', "Unknown error")
+                    )
+                    logger.error(f"Runway task {task.id} status: {task_details.status}. Error: {em}")
+                    return None
+            logger.warning(f"Runway task {task.id} timed out.")
+            return None
+        except AttributeError as ae:
+            logger.error(f"RunwayML SDK AttributeError: {ae}. SDK/methods might differ.", exc_info=True)
+            return None
+        except Exception as e:
+            logger.error(f"Runway Gen-4 API error: {e}", exc_info=True)
+            return None
 
     def _create_placeholder_video_content(self, td, fn, dur=4, sz=None):
-        if sz is None: sz = self.video_frame_size; fp = os.path.join(self.output_dir, fn); tc = None
-        try: tc = TextClip(td, fontsize=50, color='white', font=self.video_overlay_font, bg_color='black', size=sz, method='caption').set_duration(dur); tc.write_videofile(fp, fps=24, codec='libx264', preset='ultrafast', logger=None, threads=2); logger.info(f"Generic placeholder video: {fp}"); return fp
-        except Exception as e: logger.error(f"Generic placeholder video error {fp}: {e}", exc_info=True); return None
+        if sz is None:
+            sz = self.video_frame_size
+        fp = os.path.join(self.output_dir, fn)
+        tc = None
+        try:
+            tc = TextClip(
+                td,
+                fontsize=50,
+                color='white',
+                font=self.video_overlay_font,
+                bg_color='black',
+                size=sz,
+                method='caption'
+            ).set_duration(dur)
+            tc.write_videofile(fp, fps=24, codec='libx264', preset='ultrafast', logger=None, threads=2)
+            logger.info(f"Generic placeholder video: {fp}")
+            return fp
+        except Exception as e:
+            logger.error(f"Generic placeholder video error {fp}: {e}", exc_info=True)
+            return None
         finally:
-            if tc and hasattr(tc, 'close'): tc.close()
+            if tc and hasattr(tc, 'close'):
+                tc.close()
 
-    def generate_scene_asset(self, image_generation_prompt_text, motion_prompt_text_for_video,
-                             scene_data, scene_identifier_filename_base,
-                             generate_as_video_clip=False, runway_target_duration=5):
+    def generate_scene_asset(
+        self,
+        image_generation_prompt_text,
+        motion_prompt_text_for_video,
+        scene_data,
+        scene_identifier_filename_base,
+        generate_as_video_clip=False,
+        runway_target_duration=5
+    ):
         base_name, _ = os.path.splitext(scene_identifier_filename_base)
-        asset_info = {'path': None, 'type': 'none', 'error': True, 'prompt_used': image_generation_prompt_text, 'error_message': 'Asset generation init failed'}
+        asset_info = {
+            'path': None,
+            'type': 'none',
+            'error': True,
+            'prompt_used': image_generation_prompt_text,
+            'error_message': 'Asset generation init failed'
+        }
         input_image_for_runway_path = None
         base_image_filename = base_name + ("_base_for_video.png" if generate_as_video_clip else ".png")
         base_image_filepath = os.path.join(self.output_dir, base_image_filename)
-        
+
         if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
-            max_r, att_n = 2,0;
+            max_r = 2
             for att_n in range(max_r):
-                try:logger.info(f"Att {att_n+1} DALL-E (base img): {image_generation_prompt_text[:70]}...");cl=openai.OpenAI(api_key=self.openai_api_key,timeout=90.0);r=cl.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");iu=r.data[0].url;rp=getattr(r.data[0],'revised_prompt',None);
-                if rp:logger.info(f"DALL-E revised: {rp[:70]}...");ir=requests.get(iu,timeout=120);ir.raise_for_status();id_img=Image.open(io.BytesIO(ir.content));
-                if id_img.mode!='RGB':id_img=id_img.convert('RGB');id_img.save(base_image_filepath);logger.info(f"DALL-E base img saved: {base_image_filepath}");input_image_for_runway_path=base_image_filepath;asset_info={'path':base_image_filepath,'type':'image','error':False,'prompt_used':image_generation_prompt_text,'revised_prompt':rp};break
-                except openai.RateLimitError as e:logger.warning(f"OpenAI RateLimit {att_n+1}:{e}.Retry...");time.sleep(5*(att_n+1));asset_info['error_message']=str(e)
-                except Exception as e:logger.error(f"DALL-E base img error:{e}",exc_info=True);asset_info['error_message']=str(e);break
-            if asset_info['error']:logger.warning(f"DALL-E failed after {att_n+1} attempts for base img.")
-        
+                try:
+                    logger.info(f"Att {att_n+1} DALL-E (base img): {image_generation_prompt_text[:70]}...")
+                    cl = openai.OpenAI(api_key=self.openai_api_key, timeout=90.0)
+                    r = cl.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"
+                    )
+                    iu = r.data[0].url
+                    rp = getattr(r.data[0], 'revised_prompt', None)
+                    if rp:
+                        logger.info(f"DALL-E revised: {rp[:70]}...")
+                    ir = requests.get(iu, timeout=120)
+                    ir.raise_for_status()
+                    id_img = Image.open(io.BytesIO(ir.content))
+                    if id_img.mode != 'RGB':
+                        id_img = id_img.convert('RGB')
+                    id_img.save(base_image_filepath)
+                    logger.info(f"DALL-E base img saved: {base_image_filepath}")
+                    input_image_for_runway_path = base_image_filepath
+                    asset_info = {
+                        'path': base_image_filepath,
+                        'type': 'image',
+                        'error': False,
+                        'prompt_used': image_generation_prompt_text,
+                        'revised_prompt': rp
+                    }
+                    break
+                except openai.RateLimitError as e:
+                    logger.warning(f"OpenAI RateLimit {att_n+1}:{e}. Retry...")
+                    time.sleep(5 * (att_n + 1))
+                    asset_info['error_message'] = str(e)
+                except Exception as e:
+                    logger.error(f"DALL-E base img error: {e}", exc_info=True)
+                    asset_info['error_message'] = str(e)
+                    break
+            if asset_info['error']:
+                logger.warning(f"DALL-E failed after {att_n+1} attempts for base img.")
+
         if asset_info['error'] and self.USE_PEXELS:
-            logger.info("Trying Pexels for base img.");pqt=scene_data.get('pexels_search_query_감독',f"{scene_data.get('emotional_beat','')} {scene_data.get('setting_description','')}");pp=self._search_pexels_image(pqt,base_image_filename);
-            if pp:input_image_for_runway_path=pp;asset_info={'path':pp,'type':'image','error':False,'prompt_used':f"Pexels:{pqt}"}
-            else:current_em=asset_info.get('error_message',"");asset_info['error_message']=(current_em+" Pexels failed for base.").strip()
+            logger.info("Trying Pexels for base img.")
+            pqt = scene_data.get('pexels_search_query_감독', f"{scene_data.get('emotional_beat','')} {scene_data.get('setting_description','')}")
+            pp = self._search_pexels_image(pqt, base_image_filename)
+            if pp:
+                input_image_for_runway_path = pp
+                asset_info = {
+                    'path': pp,
+                    'type': 'image',
+                    'error': False,
+                    'prompt_used': f"Pexels:{pqt}"
+                }
+            else:
+                current_em = asset_info.get('error_message', "")
+                asset_info['error_message'] = (current_em + " Pexels failed for base.").strip()
 
         if asset_info['error']:
-            logger.warning("Base img (DALL-E/Pexels) failed. Using placeholder.");ppt=asset_info.get('prompt_used',image_generation_prompt_text);php=self._create_placeholder_image_content(f"[Base Placeholder]{ppt[:70]}...",base_image_filename);
-            if php:input_image_for_runway_path=php;asset_info={'path':php,'type':'image','error':False,'prompt_used':ppt}
-            else:current_em=asset_info.get('error_message',"");asset_info['error_message']=(current_em+" Base placeholder failed.").strip()
+            logger.warning("Base img (DALL-E/Pexels) failed. Using placeholder.")
+            ppt = asset_info.get('prompt_used', image_generation_prompt_text)
+            php = self._create_placeholder_image_content(f"[Base Placeholder]{ppt[:70]}...", base_image_filename)
+            if php:
+                input_image_for_runway_path = php
+                asset_info = {
+                    'path': php,
+                    'type': 'image',
+                    'error': False,
+                    'prompt_used': ppt
+                }
+            else:
+                current_em = asset_info.get('error_message', "")
+                asset_info['error_message'] = (current_em + " Base placeholder failed.").strip()
 
         if generate_as_video_clip:
-            if not input_image_for_runway_path:logger.error("RunwayML video: base img failed.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"")+" Base img miss, Runway abort.").strip();asset_info['type']='none';return asset_info
+            if not input_image_for_runway_path:
+                logger.error("RunwayML video: base img failed.")
+                asset_info['error'] = True
+                asset_info['error_message'] = (asset_info.get('error_message', "") + " Base img miss, Runway abort.").strip()
+                asset_info['type'] = 'none'
+                return asset_info
             if self.USE_RUNWAYML:
                 logger.info(f"Runway Gen-4 video for {base_name} using base: {input_image_for_runway_path}")
-                video_path=self._generate_video_clip_with_runwayml(motion_prompt_text_for_video,input_image_for_runway_path,base_name,runway_target_duration)
-                if video_path and os.path.exists(video_path):asset_info={'path':video_path,'type':'video','error':False,'prompt_used':motion_prompt_text_for_video,'base_image_path':input_image_for_runway_path}
-                else:logger.warning(f"RunwayML video failed for {base_name}. Fallback to base img.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"Base img ok.")+" RunwayML video fail; use base img.").strip();asset_info['path']=input_image_for_runway_path;asset_info['type']='image';asset_info['prompt_used']=image_generation_prompt_text
-            else:logger.warning("RunwayML selected but disabled. Use base img.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"Base img ok.")+" RunwayML disabled; use base img.").strip();asset_info['path']=input_image_for_runway_path;asset_info['type']='image';asset_info['prompt_used']=image_generation_prompt_text
+                video_path = self._generate_video_clip_with_runwayml(
+                    motion_prompt_text_for_video,
+                    input_image_for_runway_path,
+                    base_name,
+                    runway_target_duration
+                )
+                if video_path and os.path.exists(video_path):
+                    asset_info = {
+                        'path': video_path,
+                        'type': 'video',
+                        'error': False,
+                        'prompt_used': motion_prompt_text_for_video,
+                        'base_image_path': input_image_for_runway_path
+                    }
+                else:
+                    logger.warning(f"RunwayML video failed for {base_name}. Fallback to base img.")
+                    asset_info['error'] = True
+                    asset_info['error_message'] = (
+                        asset_info.get('error_message', "Base img ok.") +
+                        " RunwayML video fail; use base img."
+                    ).strip()
+                    asset_info['path'] = input_image_for_runway_path
+                    asset_info['type'] = 'image'
+                    asset_info['prompt_used'] = image_generation_prompt_text
+            else:
+                logger.warning("RunwayML selected but disabled. Use base img.")
+                asset_info['error'] = True
+                asset_info['error_message'] = (
+                    asset_info.get('error_message', "Base img ok.") +
+                    " RunwayML disabled; use base img."
+                ).strip()
+                asset_info['path'] = input_image_for_runway_path
+                asset_info['type'] = 'image'
+                asset_info['prompt_used'] = image_generation_prompt_text
+
         return asset_info
 
     def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"):
-        if not self.USE_ELEVENLABS or not self.elevenlabs_client or not text_to_narrate: logger.info("11L skip."); return None; afp=os.path.join(self.output_dir,output_filename)
-        try: logger.info(f"11L audio (Voice:{self.elevenlabs_voice_id}): {text_to_narrate[:70]}..."); asm=None
-        if hasattr(self.elevenlabs_client,'text_to_speech')and hasattr(self.elevenlabs_client.text_to_speech,'stream'):asm=self.elevenlabs_client.text_to_speech.stream;logger.info("Using 11L .text_to_speech.stream()")
-        elif hasattr(self.elevenlabs_client,'generate_stream'):asm=self.elevenlabs_client.generate_stream;logger.info("Using 11L .generate_stream()")
-        elif hasattr(self.elevenlabs_client,'generate'):logger.info("Using 11L .generate()");vp=Voice(voice_id=str(self.elevenlabs_voice_id),settings=self.elevenlabs_voice_settings)if Voice and self.elevenlabs_voice_settings else str(self.elevenlabs_voice_id);ab=self.elevenlabs_client.generate(text=text_to_narrate,voice=vp,model="eleven_multilingual_v2");
-        with open(afp,"wb")as f:f.write(ab);logger.info(f"11L audio (non-stream): {afp}");return afp
-        else:logger.error("No 11L audio method.");return None
-        if asm:vps={"voice_id":str(self.elevenlabs_voice_id)}
-        if self.elevenlabs_voice_settings:
-            if hasattr(self.elevenlabs_voice_settings,'model_dump'):vps["voice_settings"]=self.elevenlabs_voice_settings.model_dump()
-            elif hasattr(self.elevenlabs_voice_settings,'dict'):vps["voice_settings"]=self.elevenlabs_voice_settings.dict()
-            else:vps["voice_settings"]=self.elevenlabs_voice_settings
-        adi=asm(text=text_to_narrate,model_id="eleven_multilingual_v2",**vps)
-        with open(afp,"wb")as f:
-            for c in adi:
-                if c:f.write(c)
-        logger.info(f"11L audio (stream): {afp}");return afp
-        except Exception as e:logger.error(f"11L audio error: {e}",exc_info=True);return None
+        if not self.USE_ELEVENLABS or not self.elevenlabs_client or not text_to_narrate:
+            logger.info("11L skip.")
+            return None
+
+        afp = os.path.join(self.output_dir, output_filename)
+
+        try:
+            logger.info(f"11L audio (Voice:{self.elevenlabs_voice_id}): {text_to_narrate[:70]}...")
+            asm = None
+
+            # Determine which ElevenLabs streaming/non-streaming method to use
+            if hasattr(self.elevenlabs_client, 'text_to_speech') and \
+               hasattr(self.elevenlabs_client.text_to_speech, 'stream'):
+                asm = self.elevenlabs_client.text_to_speech.stream
+                logger.info("Using 11L .text_to_speech.stream()")
+
+            elif hasattr(self.elevenlabs_client, 'generate_stream'):
+                asm = self.elevenlabs_client.generate_stream
+                logger.info("Using 11L .generate_stream()")
+
+            elif hasattr(self.elevenlabs_client, 'generate'):
+                logger.info("Using 11L .generate()")
+                if Voice and self.elevenlabs_voice_settings:
+                    vp = Voice(
+                        voice_id=str(self.elevenlabs_voice_id),
+                        settings=self.elevenlabs_voice_settings
+                    )
+                else:
+                    vp = str(self.elevenlabs_voice_id)
+
+                ab = self.elevenlabs_client.generate(
+                    text=text_to_narrate,
+                    voice=vp,
+                    model="eleven_multilingual_v2"
+                )
+
+                with open(afp, "wb") as f:
+                    f.write(ab)
+
+                logger.info(f"11L audio (non-stream): {afp}")
+                return afp
+
+            else:
+                logger.error("No 11L audio method.")
+                return None
+
+            # If a streaming method is available:
+            if asm:
+                vps = {"voice_id": str(self.elevenlabs_voice_id)}
+                if self.elevenlabs_voice_settings:
+                    if hasattr(self.elevenlabs_voice_settings, 'model_dump'):
+                        vps["voice_settings"] = self.elevenlabs_voice_settings.model_dump()
+                    elif hasattr(self.elevenlabs_voice_settings, 'dict'):
+                        vps["voice_settings"] = self.elevenlabs_voice_settings.dict()
+                    else:
+                        vps["voice_settings"] = self.elevenlabs_voice_settings
+
+                adi = asm(
+                    text=text_to_narrate,
+                    model_id="eleven_multilingual_v2",
+                    **vps
+                )
+
+                with open(afp, "wb") as f:
+                    for c in adi:
+                        if c:
+                            f.write(c)
+
+                logger.info(f"11L audio (stream): {afp}")
+                return afp
+
+        except Exception as e:
+            logger.error(f"11L audio error: {e}", 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):
-        if not asset_data_list: logger.warning("No assets for animatic."); return None
-        processed_clips = []; narration_clip = None; final_clip = None
+        if not asset_data_list:
+            logger.warning("No assets for animatic.")
+            return None
+
+        processed_clips = []
+        narration_clip = None
+        final_clip = None
         logger.info(f"Assembling from {len(asset_data_list)} assets. Frame: {self.video_frame_size}.")
+
         for i, asset_info in enumerate(asset_data_list):
-            asset_path, asset_type, scene_dur = asset_info.get('path'), asset_info.get('type'), asset_info.get('duration', 4.5)
-            scene_num, key_action = asset_info.get('scene_num', i + 1), asset_info.get('key_action', '')
+            asset_path = asset_info.get('path')
+            asset_type = asset_info.get('type')
+            scene_dur = asset_info.get('duration', 4.5)
+            scene_num = asset_info.get('scene_num', i + 1)
+            key_action = asset_info.get('key_action', '')
             logger.info(f"S{scene_num}: Path='{asset_path}', Type='{asset_type}', Dur='{scene_dur}'s")
-            if not (asset_path and os.path.exists(asset_path)): logger.warning(f"S{scene_num}: Not found '{asset_path}'. Skip."); continue
-            if scene_dur <= 0: logger.warning(f"S{scene_num}: Invalid duration ({scene_dur}s). Skip."); continue
+
+            if not (asset_path and os.path.exists(asset_path)):
+                logger.warning(f"S{scene_num}: Not found '{asset_path}'. Skip.")
+                continue
+            if scene_dur <= 0:
+                logger.warning(f"S{scene_num}: Invalid duration ({scene_dur}s). Skip.")
+                continue
+
             current_scene_mvpy_clip = None
             try:
                 if asset_type == 'image':
-                    pil_img = Image.open(asset_path); logger.debug(f"S{scene_num}: Loaded img. Mode:{pil_img.mode}, Size:{pil_img.size}")
+                    pil_img = Image.open(asset_path)
+                    logger.debug(f"S{scene_num}: Loaded img. Mode:{pil_img.mode}, Size:{pil_img.size}")
                     img_rgba = pil_img.convert('RGBA') if pil_img.mode != 'RGBA' else pil_img.copy()
-                    thumb = img_rgba.copy(); rf = Image.Resampling.LANCZOS if hasattr(Image.Resampling,'LANCZOS') else Image.BILINEAR; thumb.thumbnail(self.video_frame_size,rf)
-                    cv_rgba = Image.new('RGBA',self.video_frame_size,(0,0,0,0)); xo,yo=(self.video_frame_size[0]-thumb.width)//2,(self.video_frame_size[1]-thumb.height)//2
-                    cv_rgba.paste(thumb,(xo,yo),thumb)
-                    final_rgb_pil = Image.new("RGB",self.video_frame_size,(0,0,0)); final_rgb_pil.paste(cv_rgba,mask=cv_rgba.split()[3])
-                    dbg_path = os.path.join(self.output_dir,f"debug_PRE_NUMPY_S{scene_num}.png"); final_rgb_pil.save(dbg_path); logger.info(f"DEBUG: Saved PRE_NUMPY_S{scene_num} to {dbg_path}")
-                    frame_np = np.array(final_rgb_pil,dtype=np.uint8);
-                    if not frame_np.flags['C_CONTIGUOUS']: frame_np=np.ascontiguousarray(frame_np,dtype=np.uint8)
+                    thumb = img_rgba.copy()
+                    rf = Image.Resampling.LANCZOS if hasattr(Image.Resampling, 'LANCZOS') else Image.BILINEAR
+                    thumb.thumbnail(self.video_frame_size, rf)
+
+                    cv_rgba = Image.new('RGBA', self.video_frame_size, (0, 0, 0, 0))
+                    xo = (self.video_frame_size[0] - thumb.width) // 2
+                    yo = (self.video_frame_size[1] - thumb.height) // 2
+                    cv_rgba.paste(thumb, (xo, yo), thumb)
+                    final_rgb_pil = Image.new("RGB", self.video_frame_size, (0, 0, 0))
+                    final_rgb_pil.paste(cv_rgba, mask=cv_rgba.split()[3])
+
+                    dbg_path = os.path.join(self.output_dir, f"debug_PRE_NUMPY_S{scene_num}.png")
+                    final_rgb_pil.save(dbg_path)
+                    logger.info(f"DEBUG: Saved PRE_NUMPY_S{scene_num} to {dbg_path}")
+
+                    frame_np = np.array(final_rgb_pil, dtype=np.uint8)
+                    if not frame_np.flags['C_CONTIGUOUS']:
+                        frame_np = np.ascontiguousarray(frame_np, dtype=np.uint8)
                     logger.debug(f"S{scene_num}: NumPy for MoviePy. Shape:{frame_np.shape}, DType:{frame_np.dtype}, C-Contig:{frame_np.flags['C_CONTIGUOUS']}")
-                    if frame_np.size==0 or frame_np.ndim!=3 or frame_np.shape[2]!=3: logger.error(f"S{scene_num}: Invalid NumPy. Skip."); continue
-                    clip_base = ImageClip(frame_np,transparent=False).set_duration(scene_dur)
-                    mvpy_dbg_path=os.path.join(self.output_dir,f"debug_MOVIEPY_FRAME_S{scene_num}.png"); clip_base.save_frame(mvpy_dbg_path,t=0.1); logger.info(f"DEBUG: Saved MOVIEPY_FRAME_S{scene_num} to {mvpy_dbg_path}")
+
+                    if frame_np.size == 0 or frame_np.ndim != 3 or frame_np.shape[2] != 3:
+                        logger.error(f"S{scene_num}: Invalid NumPy. Skip.")
+                        continue
+
+                    clip_base = ImageClip(frame_np, transparent=False).set_duration(scene_dur)
+                    mvpy_dbg_path = os.path.join(self.output_dir, f"debug_MOVIEPY_FRAME_S{scene_num}.png")
+                    clip_base.save_frame(mvpy_dbg_path, t=0.1)
+                    logger.info(f"DEBUG: Saved MOVIEPY_FRAME_S{scene_num} to {mvpy_dbg_path}")
+
                     clip_fx = clip_base
-                    try: es=random.uniform(1.03,1.08); clip_fx=clip_base.fx(vfx.resize,lambda t:1+(es-1)*(t/scene_dur) if scene_dur>0 else 1).set_position('center')
-                    except Exception as e: logger.error(f"S{scene_num} Ken Burns error: {e}",exc_info=False)
+                    try:
+                        es = random.uniform(1.03, 1.08)
+                        clip_fx = clip_base.fx(
+                            vfx.resize,
+                            lambda t: 1 + (es - 1) * (t / scene_dur) if scene_dur > 0 else 1
+                        ).set_position('center')
+                    except Exception as e:
+                        logger.error(f"S{scene_num} Ken Burns error: {e}", exc_info=False)
+
                     current_scene_mvpy_clip = clip_fx
+
                 elif asset_type == 'video':
-                    src_clip=None
+                    src_clip = None
                     try:
-                        src_clip=VideoFileClip(asset_path,target_resolution=(self.video_frame_size[1],self.video_frame_size[0])if self.video_frame_size else None, audio=False)
-                        tmp_clip=src_clip
-                        if src_clip.duration!=scene_dur:
-                            if src_clip.duration>scene_dur:tmp_clip=src_clip.subclip(0,scene_dur)
+                        src_clip = VideoFileClip(
+                            asset_path,
+                            target_resolution=(self.video_frame_size[1], self.video_frame_size[0]) if self.video_frame_size else None,
+                            audio=False
+                        )
+                        tmp_clip = src_clip
+                        if src_clip.duration != scene_dur:
+                            if src_clip.duration > scene_dur:
+                                tmp_clip = src_clip.subclip(0, scene_dur)
                             else:
-                                if scene_dur/src_clip.duration > 1.5 and src_clip.duration>0.1:tmp_clip=src_clip.loop(duration=scene_dur)
-                                else:tmp_clip=src_clip.set_duration(src_clip.duration);logger.info(f"S{scene_num} Video clip ({src_clip.duration:.2f}s) shorter than target ({scene_dur:.2f}s).")
-                        current_scene_mvpy_clip=tmp_clip.set_duration(scene_dur)
-                        if current_scene_mvpy_clip.size!=list(self.video_frame_size):current_scene_mvpy_clip=current_scene_mvpy_clip.resize(self.video_frame_size)
-                    except Exception as e:logger.error(f"S{scene_num} Video load error '{asset_path}':{e}",exc_info=True);continue
+                                if scene_dur / src_clip.duration > 1.5 and src_clip.duration > 0.1:
+                                    tmp_clip = src_clip.loop(duration=scene_dur)
+                                else:
+                                    tmp_clip = src_clip.set_duration(src_clip.duration)
+                                    logger.info(f"S{scene_num} Video clip ({src_clip.duration:.2f}s) shorter than target ({scene_dur:.2f}s).")
+                        current_scene_mvpy_clip = tmp_clip.set_duration(scene_dur)
+                        if current_scene_mvpy_clip.size != list(self.video_frame_size):
+                            current_scene_mvpy_clip = current_scene_mvpy_clip.resize(self.video_frame_size)
+                    except Exception as e:
+                        logger.error(f"S{scene_num} Video load error '{asset_path}': {e}", exc_info=True)
+                        continue
                     finally:
-                        if src_clip and src_clip is not current_scene_mvpy_clip and hasattr(src_clip,'close'):src_clip.close()
-                else: logger.warning(f"S{scene_num} Unknown asset type '{asset_type}'. Skip."); continue
-                
+                        if src_clip and src_clip is not current_scene_mvpy_clip and hasattr(src_clip, 'close'):
+                            src_clip.close()
+                else:
+                    logger.warning(f"S{scene_num} Unknown asset type '{asset_type}'. Skip.")
+                    continue
+
                 if current_scene_mvpy_clip and key_action:
                     try:
-                        to_dur=min(current_scene_mvpy_clip.duration-0.5,current_scene_mvpy_clip.duration*0.8)if current_scene_mvpy_clip.duration>0.5 else current_scene_mvpy_clip.duration
-                        to_start=0.25
+                        to_dur = min(current_scene_mvpy_clip.duration - 0.5,
+                                     current_scene_mvpy_clip.duration * 0.8) if current_scene_mvpy_clip.duration > 0.5 else current_scene_mvpy_clip.duration
+                        to_start = 0.25
                         if to_dur > 0:
-                            txt_c=TextClip(f"Scene {scene_num}\n{key_action}",fontsize=self.video_overlay_font_size,color=self.video_overlay_font_color,font=self.video_overlay_font,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(to_dur).set_start(to_start).set_position(('center',0.92),relative=True)
-                            current_scene_mvpy_clip=CompositeVideoClip([current_scene_mvpy_clip,txt_c],size=self.video_frame_size,use_bgclip=True)
-                        else: logger.warning(f"S{scene_num}: Text overlay duration is zero. Skip text.")
-                    except Exception as e:logger.error(f"S{scene_num} TextClip error:{e}. No text.",exc_info=True)
-                if current_scene_mvpy_clip:processed_clips.append(current_scene_mvpy_clip);logger.info(f"S{scene_num} Processed. Dur:{current_scene_mvpy_clip.duration:.2f}s.")
-            except Exception as e:logger.error(f"MAJOR Error S{scene_num} ({asset_path}):{e}",exc_info=True)
+                            txt_c = TextClip(
+                                f"Scene {scene_num}\n{key_action}",
+                                fontsize=self.video_overlay_font_size,
+                                color=self.video_overlay_font_color,
+                                font=self.video_overlay_font,
+                                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(to_dur).set_start(to_start).set_position(('center', 0.92), relative=True)
+                            current_scene_mvpy_clip = CompositeVideoClip(
+                                [current_scene_mvpy_clip, txt_c],
+                                size=self.video_frame_size,
+                                use_bgclip=True
+                            )
+                        else:
+                            logger.warning(f"S{scene_num}: Text overlay duration is zero. Skip text.")
+                    except Exception as e:
+                        logger.error(f"S{scene_num} TextClip error: {e}. No text.", exc_info=True)
+
+                if current_scene_mvpy_clip:
+                    processed_clips.append(current_scene_mvpy_clip)
+                    logger.info(f"S{scene_num} Processed. Dur:{current_scene_mvpy_clip.duration:.2f}s.")
+            except Exception as e:
+                logger.error(f"MAJOR Error S{scene_num} ({asset_path}): {e}", exc_info=True)
             finally:
-                if current_scene_mvpy_clip and hasattr(current_scene_mvpy_clip,'close'):
-                    try: current_scene_mvpy_clip.close()
-                    except: pass
+                if current_scene_mvpy_clip and hasattr(current_scene_mvpy_clip, 'close'):
+                    try:
+                        current_scene_mvpy_clip.close()
+                    except Exception:
+                        pass
 
-        if not processed_clips:logger.warning("No clips processed. Abort.");return None
-        td=0.75
+        if not processed_clips:
+            logger.warning("No clips processed. Abort.")
+            return None
+
+        td = 0.75
         try:
-            logger.info(f"Concatenating {len(processed_clips)} clips.");
-            if len(processed_clips)>1:final_clip=concatenate_videoclips(processed_clips,padding=-td if td>0 else 0,method="compose")
-            elif processed_clips:final_clip=processed_clips[0]
-            if not final_clip:logger.error("Concatenation failed.");return None
+            logger.info(f"Concatenating {len(processed_clips)} clips.")
+            if len(processed_clips) > 1:
+                final_clip = concatenate_videoclips(processed_clips, padding=-td if td > 0 else 0, method="compose")
+            elif processed_clips:
+                final_clip = processed_clips[0]
+            if not final_clip:
+                logger.error("Concatenation failed.")
+                return None
             logger.info(f"Concatenated dur:{final_clip.duration:.2f}s")
-            if td>0 and final_clip.duration>0:
-                if final_clip.duration>td*2:final_clip=final_clip.fx(vfx.fadein,td).fx(vfx.fadeout,td)
-                else:final_clip=final_clip.fx(vfx.fadein,min(td,final_clip.duration/2.0))
-            if overall_narration_path and os.path.exists(overall_narration_path) and final_clip.duration>0:
-                try:narration_clip=AudioFileClip(overall_narration_path);final_clip=final_clip.set_audio(narration_clip);logger.info("Narration added.")
-                except Exception as e:logger.error(f"Narration add error:{e}",exc_info=True)
-            elif final_clip.duration<=0:logger.warning("Video no duration. No audio.")
-            if final_clip and final_clip.duration>0:
-                op=os.path.join(self.output_dir,output_filename);logger.info(f"Writing video:{op} (Dur:{final_clip.duration:.2f}s)")
-                final_clip.write_videofile(op,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=os.cpu_count()or 2,logger='bar',bitrate="5000k",ffmpeg_params=["-pix_fmt", "yuv420p"])
-                logger.info(f"Video created:{op}");return op
-            else:logger.error("Final clip invalid. No write.");return None
-        except Exception as e:logger.error(f"Video write error:{e}",exc_info=True);return None
+            if td > 0 and final_clip.duration > 0:
+                if final_clip.duration > td * 2:
+                    final_clip = final_clip.fx(vfx.fadein, td).fx(vfx.fadeout, td)
+                else:
+                    final_clip = final_clip.fx(vfx.fadein, min(td, final_clip.duration / 2.0))
+            if overall_narration_path and os.path.exists(overall_narration_path) and final_clip.duration > 0:
+                try:
+                    narration_clip = AudioFileClip(overall_narration_path)
+                    final_clip = final_clip.set_audio(narration_clip)
+                    logger.info("Narration added.")
+                except Exception as e:
+                    logger.error(f"Narration add error: {e}", exc_info=True)
+            elif final_clip.duration <= 0:
+                logger.warning("Video no duration. No audio.")
+            if final_clip and final_clip.duration > 0:
+                op = os.path.join(self.output_dir, output_filename)
+                logger.info(f"Writing video:{op} (Dur:{final_clip.duration:.2f}s)")
+                final_clip.write_videofile(
+                    op,
+                    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=os.cpu_count() or 2,
+                    logger='bar',
+                    bitrate="5000k",
+                    ffmpeg_params=["-pix_fmt", "yuv420p"]
+                )
+                logger.info(f"Video created:{op}")
+                return op
+            else:
+                logger.error("Final clip invalid. No write.")
+                return None
+        except Exception as e:
+            logger.error(f"Video write error: {e}", exc_info=True)
+            return None
         finally:
             logger.debug("Closing all MoviePy clips in `assemble_animatic_from_assets` finally block.")
             all_clips_to_close = processed_clips + ([narration_clip] if narration_clip else []) + ([final_clip] if final_clip else [])
             for clip_obj_to_close in all_clips_to_close:
                 if clip_obj_to_close and hasattr(clip_obj_to_close, 'close'):
-                    try: clip_obj_to_close.close()
-                    except Exception as e_close: logger.warning(f"Ignoring error while closing a clip: {type(clip_obj_to_close).__name__} - {e_close}")
+                    try:
+                        clip_obj_to_close.close()
+                    except Exception as e_close:
+                        logger.warning(f"Ignoring error while closing a clip: {type(clip_obj_to_close).__name__} - {e_close}")