Update core/visual_engine.py

core/visual_engine.py

@@ -12,20 +12,32 @@ import random
 import logging
 
 # --- MoviePy Imports ---
-from moviepy.editor import (ImageClip, VideoFileClip, concatenate_videoclips, TextClip,
-                            CompositeVideoClip, AudioFileClip)
+from moviepy.editor import (
+    ImageClip,
+    VideoFileClip,
+    concatenate_videoclips,
+    TextClip,
+    CompositeVideoClip,
+    AudioFileClip,
+)
 import moviepy.video.fx.all as vfx
 
 # --- MONKEY PATCH for Pillow/MoviePy compatibility ---
 try:
-    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'): # Fallback if no common resampling attributes found
-             print("WARNING: Pillow version lacks common Resampling attributes or ANTIALIAS. MoviePy effects might fail or look different.")
+    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"):  # Fallback if no common resampling attributes found
+        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}")
+    print(
+        f"WARNING: An unexpected error occurred during Pillow ANTIALIAS monkey-patch: {e_monkey_patch}"
+    )
 
 logger = logging.getLogger(__name__)
 # Consider setting level in main app if not already configured:
@@ -39,154 +51,225 @@ 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 successfully.")
 except ImportError:
-    logger.warning("ElevenLabs SDK not found (pip install elevenlabs). Audio generation will be disabled.")
+    logger.warning(
+        "ElevenLabs SDK not found (pip install elevenlabs). Audio generation will be disabled."
+    )
 except Exception as e_eleven_import:
-    logger.warning(f"Error importing ElevenLabs client components: {e_eleven_import}. Audio generation disabled.")
+    logger.warning(
+        f"Error importing ElevenLabs client components: {e_eleven_import}. Audio generation disabled."
+    )
 
 RUNWAYML_SDK_IMPORTED = False
-RunwayMLAPIClient = None # Using a more specific name for the client class
+RunwayMLAPIClient = None  # Using a more specific name for the client class
 try:
-    from runwayml import RunwayML as ImportedRunwayMLClient # Actual SDK import
+    from runwayml import RunwayML as ImportedRunwayMLClient  # Actual SDK import
+
     RunwayMLAPIClient = ImportedRunwayMLClient
     RUNWAYML_SDK_IMPORTED = True
     logger.info("RunwayML SDK imported successfully.")
 except ImportError:
-    logger.warning("RunwayML SDK not found (pip install runwayml). RunwayML video generation will be disabled.")
+    logger.warning(
+        "RunwayML SDK not found (pip install runwayml). RunwayML video generation will be disabled."
+    )
 except Exception as e_runway_sdk_import:
-    logger.warning(f"Error importing RunwayML SDK: {e_runway_sdk_import}. RunwayML features disabled.")
+    logger.warning(
+        f"Error importing RunwayML SDK: {e_runway_sdk_import}. RunwayML features disabled."
+    )
 
 
 class VisualEngine:
-    DEFAULT_FONT_SIZE_PIL = 10 # For default Pillow font
-    PREFERRED_FONT_SIZE_PIL = 20 # For custom font
+    DEFAULT_FONT_SIZE_PIL = 10  # For default Pillow font
+    PREFERRED_FONT_SIZE_PIL = 20  # For custom font
     VIDEO_OVERLAY_FONT_SIZE = 30
-    VIDEO_OVERLAY_FONT_COLOR = 'white'
+    VIDEO_OVERLAY_FONT_COLOR = "white"
     # Standard font names ImageMagick (used by TextClip) is likely to find in Linux containers
-    DEFAULT_MOVIEPY_FONT = 'DejaVu-Sans-Bold'
-    PREFERRED_MOVIEPY_FONT = 'Liberation-Sans-Bold' # Often available
+    DEFAULT_MOVIEPY_FONT = "DejaVu-Sans-Bold"
+    PREFERRED_MOVIEPY_FONT = "Liberation-Sans-Bold"  # Often available
 
-    def __init__(self, output_dir="temp_cinegen_media", default_elevenlabs_voice_id="Rachel"):
+    def __init__(
+        self, output_dir="temp_cinegen_media", default_elevenlabs_voice_id="Rachel"
+    ):
         self.output_dir = output_dir
         os.makedirs(self.output_dir, exist_ok=True)
 
-        self.font_filename_pil = "DejaVuSans-Bold.ttf" # A more standard Linux font
+        self.font_filename_pil = "DejaVuSans-Bold.ttf"  # A more standard Linux font
         font_paths_to_try = [
-            self.font_filename_pil, # If in working dir or PATH
+            self.font_filename_pil,  # If in working dir or PATH
             f"/usr/share/fonts/truetype/dejavu/{self.font_filename_pil}",
-            f"/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf", # Alternative
-            f"/System/Library/Fonts/Supplemental/Arial.ttf", # macOS fallback
-            f"C:/Windows/Fonts/arial.ttf", # Windows fallback
-            f"/usr/local/share/fonts/truetype/mycustomfonts/arial.ttf" # User's previous custom path
+            f"/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf",  # Alternative
+            f"/System/Library/Fonts/Supplemental/Arial.ttf",  # macOS fallback
+            f"C:/Windows/Fonts/arial.ttf",  # Windows fallback
+            f"/usr/local/share/fonts/truetype/mycustomfonts/arial.ttf",  # User's previous custom path
         ]
-        self.font_path_pil_resolved = next((p for p in font_paths_to_try if os.path.exists(p)), None)
-        
-        self.font_pil = ImageFont.load_default() # Default
+        self.font_path_pil_resolved = next(
+            (p for p in font_paths_to_try if os.path.exists(p)), None
+        )
+
+        self.font_pil = ImageFont.load_default()  # Default
         self.current_font_size_pil = self.DEFAULT_FONT_SIZE_PIL
 
         if self.font_path_pil_resolved:
             try:
-                self.font_pil = ImageFont.truetype(self.font_path_pil_resolved, self.PREFERRED_FONT_SIZE_PIL)
+                self.font_pil = ImageFont.truetype(
+                    self.font_path_pil_resolved, self.PREFERRED_FONT_SIZE_PIL
+                )
                 self.current_font_size_pil = self.PREFERRED_FONT_SIZE_PIL
-                logger.info(f"Pillow font loaded: {self.font_path_pil_resolved} at size {self.current_font_size_pil}.")
+                logger.info(
+                    f"Pillow font loaded: {self.font_path_pil_resolved} at size {self.current_font_size_pil}."
+                )
                 # Determine MoviePy font based on loaded PIL font
                 if "dejavu" in self.font_path_pil_resolved.lower():
-                    self.video_overlay_font = 'DejaVu-Sans-Bold'
+                    self.video_overlay_font = "DejaVu-Sans-Bold"
                 elif "liberation" in self.font_path_pil_resolved.lower():
-                    self.video_overlay_font = 'Liberation-Sans-Bold'
-                else: # Fallback if custom font doesn't have an obvious ImageMagick name
+                    self.video_overlay_font = "Liberation-Sans-Bold"
+                else:  # Fallback if custom font doesn't have an obvious ImageMagick name
                     self.video_overlay_font = self.DEFAULT_MOVIEPY_FONT
             except IOError as e_font_load:
-                logger.error(f"Pillow font loading IOError for '{self.font_path_pil_resolved}': {e_font_load}. Using default.")
+                logger.error(
+                    f"Pillow font loading IOError for '{self.font_path_pil_resolved}': {e_font_load}. Using default."
+                )
         else:
             logger.warning("Custom Pillow font not found. Using default.")
 
-        self.openai_api_key = None; self.USE_AI_IMAGE_GENERATION = False
-        self.dalle_model = "dall-e-3"; self.image_size_dalle3 = "1792x1024"
+        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_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.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_ml_client_instance = None # More specific name
+        self.pexels_api_key = None
+        self.USE_PEXELS = False
+        self.runway_api_key = None
+        self.USE_RUNWAYML = False
+        self.runway_ml_client_instance = None  # More specific name
 
         # Attempt to initialize Runway client if SDK is present and env var might be set
-        if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient and os.getenv("RUNWAYML_API_SECRET"):
+        if (
+            RUNWAYML_SDK_IMPORTED
+            and RunwayMLAPIClient
+            and os.getenv("RUNWAYML_API_SECRET")
+        ):
             try:
-                self.runway_ml_client_instance = RunwayMLAPIClient() # SDK uses env var
-                self.USE_RUNWAYML = True # Assume enabled if client initializes
-                logger.info("RunwayML Client initialized from RUNWAYML_API_SECRET env var at startup.")
+                self.runway_ml_client_instance = RunwayMLAPIClient()  # SDK uses env var
+                self.USE_RUNWAYML = True  # Assume enabled if client initializes
+                logger.info(
+                    "RunwayML Client initialized from RUNWAYML_API_SECRET env var at startup."
+                )
             except Exception as e_runway_init_startup:
-                logger.error(f"Initial RunwayML client init failed (env var RUNWAYML_API_SECRET might be invalid): {e_runway_init_startup}")
+                logger.error(
+                    f"Initial RunwayML client init failed (env var RUNWAYML_API_SECRET might be invalid): {e_runway_init_startup}"
+                )
                 self.USE_RUNWAYML = False
-        
+
         logger.info("VisualEngine initialized.")
 
     # --- API Key Setters ---
     def set_openai_api_key(self, api_key):
-        self.openai_api_key = api_key; self.USE_AI_IMAGE_GENERATION = bool(api_key)
-        logger.info(f"DALL-E ({self.dalle_model}) status: {'Ready' if self.USE_AI_IMAGE_GENERATION else 'Disabled'}")
+        self.openai_api_key = api_key
+        self.USE_AI_IMAGE_GENERATION = bool(api_key)
+        logger.info(
+            f"DALL-E ({self.dalle_model}) status: {'Ready' if self.USE_AI_IMAGE_GENERATION 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 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 status: {'Ready' if self.USE_ELEVENLABS else 'Failed Initialization'} (Using Voice ID: {self.elevenlabs_voice_id})")
+                logger.info(
+                    f"ElevenLabs Client status: {'Ready' if self.USE_ELEVENLABS else 'Failed Initialization'} (Using Voice ID: {self.elevenlabs_voice_id})"
+                )
             except Exception as e:
-                logger.error(f"ElevenLabs client initialization error: {e}. Service Disabled.", exc_info=True)
-                self.USE_ELEVENLABS = False; self.elevenlabs_client = None
+                logger.error(
+                    f"ElevenLabs client initialization error: {e}. Service Disabled.",
+                    exc_info=True,
+                )
+                self.USE_ELEVENLABS = False
+                self.elevenlabs_client = None
         else:
             self.USE_ELEVENLABS = False
-            logger.info(f"ElevenLabs Service Disabled (API key not provided or SDK import issue).")
+            logger.info(
+                f"ElevenLabs Service Disabled (API key not provided or SDK import issue)."
+            )
 
     def set_pexels_api_key(self, api_key):
-        self.pexels_api_key = api_key; self.USE_PEXELS = bool(api_key)
-        logger.info(f"Pexels Search status: {'Ready' if self.USE_PEXELS else 'Disabled'}")
+        self.pexels_api_key = api_key
+        self.USE_PEXELS = bool(api_key)
+        logger.info(
+            f"Pexels Search status: {'Ready' if self.USE_PEXELS else 'Disabled'}"
+        )
 
     def set_runway_api_key(self, api_key):
-        self.runway_api_key = api_key # Store key regardless for potential direct HTTP use
+        self.runway_api_key = api_key  # Store key regardless for potential direct HTTP use
         if api_key:
             if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
-                if not self.runway_ml_client_instance: # If not already initialized by env var
+                if not self.runway_ml_client_instance:  # If not already initialized by env var
                     try:
                         # The RunwayML Python SDK expects the API key via the RUNWAYML_API_SECRET env var.
                         # If it's not set, we set it temporarily for client initialization.
                         original_env_secret = os.getenv("RUNWAYML_API_SECRET")
                         if not original_env_secret:
-                            logger.info("Temporarily setting RUNWAYML_API_SECRET from provided key for SDK client init.")
+                            logger.info(
+                                "Temporarily setting RUNWAYML_API_SECRET from provided key for SDK client init."
+                            )
                             os.environ["RUNWAYML_API_SECRET"] = api_key
-                        
+
                         self.runway_ml_client_instance = RunwayMLAPIClient()
-                        self.USE_RUNWAYML = True # SDK client successfully initialized
-                        logger.info("RunwayML Client initialized successfully using provided API key.")
+                        self.USE_RUNWAYML = True  # SDK client successfully initialized
+                        logger.info(
+                            "RunwayML Client initialized successfully using provided API key."
+                        )
 
-                        if not original_env_secret: # Clean up if we set it
+                        if not original_env_secret:  # Clean up if we set it
                             del os.environ["RUNWAYML_API_SECRET"]
-                            logger.info("Cleared temporary RUNWAYML_API_SECRET env var.")
+                            logger.info(
+                                "Cleared temporary RUNWAYML_API_SECRET env var."
+                            )
 
                     except Exception as e_client_init:
-                        logger.error(f"RunwayML Client initialization via set_runway_api_key failed: {e_client_init}", exc_info=True)
-                        self.USE_RUNWAYML = False; self.runway_ml_client_instance = None
-                else: # Client was already initialized (likely via env var during __init__)
+                        logger.error(
+                            f"RunwayML Client initialization via set_runway_api_key failed: {e_client_init}",
+                            exc_info=True,
+                        )
+                        self.USE_RUNWAYML = False
+                        self.runway_ml_client_instance = None
+                else:  # Client was already initialized (likely via env var during __init__)
                     self.USE_RUNWAYML = True
-                    logger.info("RunwayML Client was already initialized (likely from env var). API key stored.")
-            else: # SDK not imported
-                logger.warning("RunwayML SDK not imported. API key stored, but integration requires SDK. Service effectively disabled.")
+                    logger.info(
+                        "RunwayML Client was already initialized (likely from env var). API key stored."
+                    )
+            else:  # SDK not imported
+                logger.warning(
+                    "RunwayML SDK not imported. API key stored, but integration requires SDK. Service effectively disabled."
+                )
                 self.USE_RUNWAYML = False
-        else: # No API key provided
-            self.USE_RUNWAYML = False; self.runway_ml_client_instance = None
+        else:  # No API key provided
+            self.USE_RUNWAYML = False
+            self.runway_ml_client_instance = None
             logger.info("RunwayML Service Disabled (no API key provided).")
 
     # --- Helper Methods ---
@@ -197,91 +280,154 @@ class VisualEngine:
                 ext = os.path.splitext(image_path)[1].lower()
                 mime_map = {".png": "image/png", ".jpg": "image/jpeg", ".jpeg": "image/jpeg"}
                 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}, using default.")
-            
+                if mime_type == "application/octet-stream":
+                    logger.warning(
+                        f"Could not determine MIME type for {image_path}, using default."
+                    )
+
             with open(image_path, "rb") as image_file:
-                encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
+                encoded_string = base64.b64encode(image_file.read()).decode("utf-8")
             data_uri = f"data:{mime_type};base64,{encoded_string}"
-            logger.debug(f"Generated data URI for {os.path.basename(image_path)} (first 100 chars): {data_uri[:100]}...")
+            logger.debug(
+                f"Generated data URI for {os.path.basename(image_path)} (first 100 chars): {data_uri[:100]}..."
+            )
             return data_uri
         except FileNotFoundError:
             logger.error(f"Image file not found at {image_path} for data URI conversion.")
             return None
         except Exception as e:
-            logger.error(f"Error converting image {image_path} to data URI: {e}", exc_info=True)
+            logger.error(
+                f"Error converting image {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}"
         # Gen-4 supports: "1280:720", "720:1280", "1104:832", "832:1104", "960:960", "1584:672"
-        supported_ratios_gen4 = ["1280:720", "720:1280", "1104:832", "832:1104", "960:960", "1584:672"]
+        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
         # Fallback or find closest - for now, strict matching or default
-        logger.warning(f"Resolution {ratio_str} not directly in Gen-4 supported list. Defaulting to 1280:720.")
+        logger.warning(
+            f"Resolution {ratio_str} not directly in Gen-4 supported list. Defaulting to 1280:720."
+        )
         return "1280:720"
 
     def _get_text_dimensions(self, text_content, font_object):
         # (Robust version from before)
-        default_char_height = getattr(font_object, 'size', self.current_font_size_pil)
-        if not text_content: return 0, default_char_height
+        default_char_height = getattr(font_object, "size", self.current_font_size_pil)
+        if not text_content:
+            return 0, default_char_height
         try:
-            if hasattr(font_object,'getbbox'):
-                bbox=font_object.getbbox(text_content);w=bbox[2]-bbox[0];h=bbox[3]-bbox[1]
+            if hasattr(font_object, "getbbox"):
+                bbox = font_object.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_object,'getsize'):
-                w,h=font_object.getsize(text_content)
+            elif hasattr(font_object, "getsize"):
+                w, h = font_object.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.current_font_size_pil*0.6),int(self.current_font_size_pil*1.2)
+            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.current_font_size_pil * 0.6),
+                int(self.current_font_size_pil * 1.2),
+            )
 
     def _create_placeholder_image_content(self, text_description, filename, size=None):
         # (Corrected version from previous response)
-        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_text = ""
+        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_text = ""
         for word_idx, word in enumerate(words):
             prospective_addition = word + (" " if word_idx < len(words) - 1 else "")
             test_line_text = current_line_text + prospective_addition
             current_w, _ = self._get_text_dimensions(test_line_text, self.font_pil)
-            if current_w == 0 and test_line_text.strip(): current_w = len(test_line_text) * (self.current_font_size_pil * 0.6) # Estimate
+            if current_w == 0 and test_line_text.strip():
+                current_w = len(test_line_text) * (self.current_font_size_pil * 0.6)  # Estimate
 
-            if current_w <= max_w: current_line_text = test_line_text
+            if current_w <= max_w:
+                current_line_text = test_line_text
             else:
-                if current_line_text.strip(): lines.append(current_line_text.strip())
-                current_line_text = prospective_addition # Start new line
-        if current_line_text.strip(): lines.append(current_line_text.strip())
+                if current_line_text.strip():
+                    lines.append(current_line_text.strip())
+                current_line_text = prospective_addition  # Start new line
+        if current_line_text.strip():
+            lines.append(current_line_text.strip())
 
         if not lines and text_description:
-            avg_char_w, _ = self._get_text_dimensions("W", self.font_pil); avg_char_w = avg_char_w or (self.current_font_size_pil * 0.6)
+            avg_char_w, _ = self._get_text_dimensions("W", self.font_pil)
+            avg_char_w = avg_char_w or (self.current_font_size_pil * 0.6)
             chars_per_line = int(max_w / avg_char_w) if avg_char_w > 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)")
+            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_pil)
+        single_line_h = single_line_h if single_line_h > 0 else self.current_font_size_pil + 2
+        max_lines = (
+            min(len(lines), (size[1] - (2 * padding)) // (single_line_h + 2))
+            if single_line_h > 0
+            else 1
+        )
+        max_lines = max(1, max_lines)  # Ensure at least one line
 
-        _, single_line_h = self._get_text_dimensions("Ay", self.font_pil); single_line_h = single_line_h if single_line_h > 0 else self.current_font_size_pil + 2
-        max_lines = min(len(lines), (size[1] - (2 * padding)) // (single_line_h + 2)) if single_line_h > 0 else 1
-        max_lines = max(1, max_lines) # Ensure at least one line
-        
         y_pos = padding + (size[1] - (2 * padding) - max_lines * (single_line_h + 2)) / 2.0
         for i in range(max_lines):
-            line_text = lines[i]; line_w, _ = self._get_text_dimensions(line_text, self.font_pil)
-            if line_w == 0 and line_text.strip(): line_w = len(line_text) * (self.current_font_size_pil * 0.6)
+            line_text = lines[i]
+            line_w, _ = self._get_text_dimensions(line_text, self.font_pil)
+            if line_w == 0 and line_text.strip():
+                line_w = len(line_text) * (self.current_font_size_pil * 0.6)
             x_pos = (size[0] - line_w) / 2.0
-            try: d.text((x_pos, y_pos), line_text, font=self.font_pil, fill=(200, 200, 180))
-            except Exception as e_draw: logger.error(f"Pillow d.text error: {e_draw} for '{line_text}'")
+            try:
+                d.text((x_pos, y_pos), line_text, font=self.font_pil, fill=(200, 200, 180))
+            except Exception as e_draw:
+                logger.error(f"Pillow d.text error: {e_draw} for '{line_text}'")
             y_pos += single_line_h + 2
             if i == 6 and max_lines > 7:
-                try: d.text((x_pos, y_pos), "...", font=self.font_pil, fill=(200, 200, 180))
-                except Exception as e_elip: logger.error(f"Pillow d.text ellipsis error: {e_elip}"); break
+                try:
+                    d.text((x_pos, y_pos), "...", font=self.font_pil, fill=(200, 200, 180))
+                except Exception as e_elip:
+                    logger.error(f"Pillow d.text ellipsis error: {e_elip}")
+                    break
+
         filepath = os.path.join(self.output_dir, filename)
-        try: img.save(filepath); return filepath
-        except Exception as e_save: logger.error(f"Saving placeholder image '{filepath}' error: {e_save}", exc_info=True); return None
+        try:
+            img.save(filepath)
+            return filepath
+        except Exception as e_save:
+            logger.error(
+                f"Saving placeholder image '{filepath}' error: {e_save}", exc_info=True
+            )
+            return None
 
     def _search_pexels_image(self, query, output_filename_base):
         # <<< THIS IS THE 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"}
         base_name_for_pexels, _ = os.path.splitext(output_filename_base)
@@ -291,48 +437,77 @@ class VisualEngine:
             logger.info(f"Pexels: Searching for '{query}'")
             effective_query = " ".join(query.split()[:5])
             params["query"] = effective_query
-            response = requests.get("https://api.pexels.com/v1/search", headers=headers, params=params, timeout=20)
+            response = requests.get(
+                "https://api.pexels.com/v1/search", headers=headers, params=params, timeout=20
+            )
             response.raise_for_status()
             data = response.json()
             if data.get("photos") and len(data["photos"]) > 0:
                 photo_details = data["photos"][0]
                 photo_url = photo_details.get("src", {}).get("large2x")
-                if not photo_url: logger.warning(f"Pexels: 'large2x' URL missing for '{effective_query}'. Details: {photo_details}"); return None
-                image_response = requests.get(photo_url, timeout=60); image_response.raise_for_status()
+                if not photo_url:
+                    logger.warning(
+                        f"Pexels: 'large2x' URL missing for '{effective_query}'. Details: {photo_details}"
+                    )
+                    return None
+                image_response = requests.get(photo_url, timeout=60)
+                image_response.raise_for_status()
                 img_data_pil = Image.open(io.BytesIO(image_response.content))
-                if img_data_pil.mode != 'RGB': img_data_pil = img_data_pil.convert('RGB')
-                img_data_pil.save(filepath); logger.info(f"Pexels: Image saved to {filepath}"); return filepath
-            else: logger.info(f"Pexels: No photos for '{effective_query}'."); return None
-        except requests.exceptions.RequestException as e_req: logger.error(f"Pexels: RequestException for '{query}': {e_req}", exc_info=False); return None # Less verbose for network
-        except Exception as e: logger.error(f"Pexels: General error for '{query}': {e}", exc_info=True); return None
+                if img_data_pil.mode != "RGB":
+                    img_data_pil = img_data_pil.convert("RGB")
+                img_data_pil.save(filepath)
+                logger.info(f"Pexels: Image saved to {filepath}")
+                return filepath
+            else:
+                logger.info(f"Pexels: No photos for '{effective_query}'.")
+                return None
+        except requests.exceptions.RequestException as e_req:
+            logger.error(f"Pexels: RequestException for '{query}': {e_req}", exc_info=False)
+            return None  # Less verbose for network
+        except Exception as e:
+            logger.error(f"Pexels: General error for '{query}': {e}", exc_info=True)
+            return None
 
     # --- RunwayML Video Generation (Gen-4 Aligned with SDK) ---
-    def _generate_video_clip_with_runwayml(self, text_prompt_for_motion, input_image_path, scene_identifier_filename_base, target_duration_seconds=5):
+    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_ml_client_instance:
             logger.warning("RunwayML not enabled or client not initialized. Cannot generate video clip.")
             return None
         if not input_image_path or not os.path.exists(input_image_path):
-            logger.error(f"Runway Gen-4 requires an input image. Path not provided or invalid: {input_image_path}")
+            logger.error(
+                f"Runway Gen-4 requires an input image. Path not provided or 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 >= 8 else 5  # Map to 5s or 10s for Gen-4
+        runway_ratio_str = self._map_resolution_to_runway_ratio(
+            self.video_frame_size[0], self.video_frame_size[1]
+        )
 
-        runway_duration = 10 if target_duration_seconds >= 8 else 5 # Map to 5s or 10s for Gen-4
-        runway_ratio_str = self._map_resolution_to_runway_ratio(self.video_frame_size[0], self.video_frame_size[1])
-        
         # Use a more descriptive output filename for Runway videos
         base_name_for_runway, _ = os.path.splitext(scene_identifier_filename_base)
         output_video_filename = base_name_for_runway + f"_runway_gen4_d{runway_duration}s.mp4"
         output_video_filepath = os.path.join(self.output_dir, output_video_filename)
 
-        logger.info(f"Initiating Runway Gen-4 task: motion='{text_prompt_for_motion[:100]}...', image='{os.path.basename(input_image_path)}', dur={runway_duration}s, ratio='{runway_ratio_str}'")
+        logger.info(
+            f"Initiating Runway Gen-4 task: motion='{text_prompt_for_motion[:100]}...', image='{os.path.basename(input_image_path)}', dur={runway_duration}s, ratio='{runway_ratio_str}'"
+        )
         try:
             # Using the RunwayML Python SDK structure
             task_submission = self.runway_ml_client_instance.image_to_video.create(
-                model='gen4_turbo',
+                model="gen4_turbo",
                 prompt_image=image_data_uri,
-                prompt_text=text_prompt_for_motion, # This is the motion prompt
+                prompt_text=text_prompt_for_motion,  # This is the motion prompt
                 duration=runway_duration,
                 ratio=runway_ratio_str,
                 # seed=random.randint(0, 4294967295), # Optional: for reproducibility
@@ -342,7 +517,7 @@ class VisualEngine:
             logger.info(f"Runway Gen-4 task created with ID: {task_id}. Polling for completion...")
 
             poll_interval_seconds = 10
-            max_polling_duration_seconds = 6 * 60 # 6 minutes
+            max_polling_duration_seconds = 6 * 60  # 6 minutes
             start_time = time.time()
 
             while time.time() - start_time < max_polling_duration_seconds:
@@ -350,211 +525,533 @@ class VisualEngine:
                 task_details = self.runway_ml_client_instance.tasks.retrieve(id=task_id)
                 logger.info(f"Runway task {task_id} status: {task_details.status}")
 
-                if task_details.status == 'SUCCEEDED':
+                if task_details.status == "SUCCEEDED":
                     # Determine output URL (this structure might vary based on SDK version)
                     output_url = None
-                    if hasattr(task_details, 'output') and task_details.output and hasattr(task_details.output, 'url'):
+                    if hasattr(task_details, "output") and task_details.output and hasattr(
+                        task_details.output, "url"
+                    ):
                         output_url = task_details.output.url
-                    elif hasattr(task_details, 'artifacts') and task_details.artifacts and isinstance(task_details.artifacts, list) and len(task_details.artifacts) > 0:
+                    elif (
+                        hasattr(task_details, "artifacts")
+                        and task_details.artifacts
+                        and isinstance(task_details.artifacts, list)
+                        and len(task_details.artifacts) > 0
+                    ):
                         first_artifact = task_details.artifacts[0]
-                        if hasattr(first_artifact, 'url'): output_url = first_artifact.url
-                        elif hasattr(first_artifact, 'download_url'): output_url = first_artifact.download_url
-                    
+                        if hasattr(first_artifact, "url"):
+                            output_url = first_artifact.url
+                        elif hasattr(first_artifact, "download_url"):
+                            output_url = first_artifact.download_url
+
                     if not output_url:
-                        logger.error(f"Runway task {task_id} SUCCEEDED, but no output URL found. Details: {vars(task_details) if hasattr(task_details,'__dict__') else str(task_details)}")
+                        logger.error(
+                            f"Runway task {task_id} SUCCEEDED, but no output URL found. Details: {vars(task_details) if hasattr(task_details,'__dict__') else str(task_details)}"
+                        )
                         return None
 
                     logger.info(f"Runway task {task_id} SUCCEEDED. Downloading video from: {output_url}")
                     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 successfully downloaded to: {output_video_filepath}")
+                    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 successfully downloaded to: {output_video_filepath}"
+                    )
                     return output_video_filepath
-                
-                elif task_details.status in ['FAILED', 'ABORTED', 'ERROR']: # Added ERROR
-                    error_msg = getattr(task_details,'error_message',None) or getattr(getattr(task_details,'output',None),'error', "Unknown error from Runway task.")
-                    logger.error(f"Runway task {task_id} final status: {task_details.status}. Error: {error_msg}")
+
+                elif task_details.status in ["FAILED", "ABORTED", "ERROR"]:  # Added ERROR
+                    error_msg = (
+                        getattr(task_details, "error_message", None)
+                        or getattr(getattr(task_details, "output", None), "error", "Unknown error from Runway task.")
+                    )
+                    logger.error(
+                        f"Runway task {task_id} final status: {task_details.status}. Error: {error_msg}"
+                    )
                     return None
-            
-            logger.warning(f"Runway task {task_id} timed out polling after {max_polling_duration_seconds} seconds.")
+
+            logger.warning(
+                f"Runway task {task_id} timed out polling after {max_polling_duration_seconds} seconds."
+            )
             return None
 
-        except AttributeError as ae: # If SDK methods are not as expected
-            logger.error(f"AttributeError with RunwayML SDK: {ae}. Ensure SDK is up to date and methods/attributes match documentation.", exc_info=True)
+        except AttributeError as ae:  # If SDK methods are not as expected
+            logger.error(
+                f"AttributeError with RunwayML SDK: {ae}. Ensure SDK is up to date and methods/attributes match documentation.",
+                exc_info=True,
+            )
             return None
         except Exception as e_runway_call:
-            logger.error(f"General error during Runway Gen-4 API call or processing: {e_runway_call}", exc_info=True)
+            logger.error(
+                f"General error during Runway Gen-4 API call or processing: {e_runway_call}",
+                exc_info=True,
+            )
             return None
 
     def _create_placeholder_video_content(self, text_description, filename, duration=4, size=None):
         # (Keeping as before)
-        if size is None: size = self.video_frame_size; fp = os.path.join(self.output_dir, filename); tc = None
-        try: tc = TextClip(text_description, fontsize=50, color='white', font=self.video_overlay_font, bg_color='black', size=size, method='caption').set_duration(duration); 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 size is None:
+            size = self.video_frame_size
+        fp = os.path.join(self.output_dir, filename)
+        tc = None
+        try:
+            tc = TextClip(
+                text_description,
+                fontsize=50,
+                color="white",
+                font=self.video_overlay_font,
+                bg_color="black",
+                size=size,
+                method="caption",
+            ).set_duration(duration)
+            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()
 
     # --- generate_scene_asset (Main asset generation logic using Runway Gen-4 workflow) ---
-    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,
+    ):
         # (Logic updated for Runway Gen-4 workflow)
         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
         # Use a distinct name for the base image if it's only an intermediate step for video
         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)
-        
+
         # STEP 1: Generate/acquire the base image
         # Try DALL-E
         if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
-            # ... (DALL-E logic as in previous full rewrite - condensed for brevity here)
-            max_r, att_n = 2,0;
+            max_r, att_n = 2, 0
             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.")
-        
-        if asset_info['error'] and self.USE_PEXELS: # Pexels Fallback
-            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); # Use 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']: # Placeholder Fallback
-            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); # Use 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()
+                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:
+            # Pexels Fallback
+            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)  # Use 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"]:
+            # Placeholder Fallback
+            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)  # Use 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()
 
         # STEP 2: If video clip is requested, use the generated base image with RunwayML
         if generate_as_video_clip:
             if not input_image_for_runway_path:
-                logger.error("RunwayML video: base image generation failed entirely. Cannot proceed.");asset_info['error']=True;asset_info['error_message']=(asset_info.get('error_message',"")+" Base img completely failed, Runway abort.").strip();asset_info['type']='none';return asset_info
-            if self.USE_RUNWAYML: # This check is now more about if the service is generally enabled
-                video_path=self._generate_video_clip_with_runwayml(motion_prompt_text_for_video,input_image_for_runway_path,base_name,runway_target_duration) # Pass base_name for runway output filename
-                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 step failed; 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 not enabled/client not ready. 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
+                logger.error("RunwayML video: base image generation failed entirely. Cannot proceed.")
+                asset_info["error"] = True
+                asset_info["error_message"] = (
+                    asset_info.get("error_message", "") + " Base img completely failed, Runway abort."
+                ).strip()
+                asset_info["type"] = "none"
+                return asset_info
+
+            if self.USE_RUNWAYML:
+                # This check is now more about if the service is generally enabled
+                video_path = self._generate_video_clip_with_runwayml(
+                    motion_prompt_text_for_video,
+                    input_image_for_runway_path,
+                    base_name,
+                    runway_target_duration,
+                )  # Pass base_name for runway output filename
+                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 step failed; 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 not enabled/client not ready. 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"):
         # (Keep as before - robust enough)
-        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
+
+            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 we have a streaming method (asm), use it
+            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
 
     # --- assemble_animatic_from_assets (Still contains crucial debug saves for blank video issue) ---
-    def assemble_animatic_from_assets(self, asset_data_list, overall_narration_path=None, output_filename="final_video.mp4", fps=24):
+    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 arrays, debug saves, and pix_fmt)
-        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}")
-                    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)
-                    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 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}")
+                    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)
+                    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}")
                     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
+
+                elif asset_type == "video":
+                    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:
+                        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}")
+                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}"
+                        )