Update core/visual_engine.py

core/visual_engine.py

@@ -1,15 +1,15 @@
 # core/visual_engine.py
 from PIL import Image, ImageDraw, ImageFont, ImageOps
-# --- MONKEY PATCH FOR Image.ANTIALIAS ---
+import base64 # For Data URI conversion
+
+# --- MONKEY PATCH ---
 try:
-    if hasattr(Image, 'Resampling') and hasattr(Image.Resampling, 'LANCZOS'): # Pillow 9+
+    if hasattr(Image, 'Resampling') and hasattr(Image.Resampling, 'LANCZOS'):
         if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.Resampling.LANCZOS
-    elif hasattr(Image, 'LANCZOS'): # Pillow 8
+    elif hasattr(Image, 'LANCZOS'):
          if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.LANCZOS
-    elif not hasattr(Image, 'ANTIALIAS'):
-             print("WARNING: Pillow version lacks common Resampling attributes or ANTIALIAS. Video effects might fail.")
-except Exception as e_mp: print(f"WARNING: ANTIALIAS monkey-patch error: {e_mp}")
-# --- END MONKEY PATCH ---
+    elif not hasattr(Image, 'ANTIALIAS'): print("WARNING: Pillow ANTIALIAS/Resampling issue.")
+except Exception as e_mp: print(f"WARNING: ANTIALIAS patch error: {e_mp}")
 
 from moviepy.editor import (ImageClip, VideoFileClip, concatenate_videoclips, TextClip,
                             CompositeVideoClip, AudioFileClip)
@@ -22,11 +22,12 @@ import io
 import time
 import random
 import logging
+import mimetypes # For Data URI
 
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)
 
-# --- ElevenLabs Client Import ---
+# --- SERVICE CLIENT IMPORTS ---
 ELEVENLABS_CLIENT_IMPORTED = False; ElevenLabsAPIClient = None; Voice = None; VoiceSettings = None
 try:
     from elevenlabs.client import ElevenLabs as ImportedElevenLabsClient
@@ -35,375 +36,462 @@ try:
     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 Client Import (Placeholder) ---
-RUNWAYML_SDK_IMPORTED = False; RunwayMLClient = None
+RUNWAYML_SDK_IMPORTED = False; RunwayMLAPIClient = None # Renamed for clarity
 try:
-    logger.info("RunwayML SDK import is a placeholder.")
-except ImportError: logger.warning("RunwayML SDK (placeholder) not found. RunwayML disabled.")
-except Exception as e_runway_sdk: logger.warning(f"Error importing RunwayML SDK (placeholder): {e_runway_sdk}. RunwayML disabled.")
+    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.")
+except Exception as e_runway_sdk:
+    logger.warning(f"Error importing RunwayML SDK: {e_runway_sdk}. RunwayML features disabled.")
 
 
 class VisualEngine:
     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 = "DejaVuSans-Bold.ttf" # More standard than arial.ttf
-        font_paths_to_try = [
-            self.font_filename,
-            f"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf",
-            f"/usr/share/fonts/truetype/liberation/LiberationSans-Bold.ttf",
-            f"/System/Library/Fonts/Supplemental/Arial.ttf", f"C:/Windows/Fonts/arial.ttf",
-            f"/usr/local/share/fonts/truetype/mycustomfonts/arial.ttf" # Previous custom path
-        ]
+        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"]
         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.video_overlay_font = 'DejaVu-Sans-Bold' # ImageMagick name for DejaVuSans-Bold
-
+        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 loaded: {self.font_path_pil}.")
-            else: logger.warning("Using default Pillow font."); self.font_size_pil = 10
-        except IOError as e_font: logger.error(f"Pillow font loading IOError: {e_font}. Using 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 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"
+        self.video_frame_size = (1280, 720) # Default, will be mapped to Runway ratio
+        
+        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: # Initialize if SDK is available
+            try:
+                # The SDK expects RUNWAYML_API_SECRET env var.
+                # If your key is passed directly, you might need to initialize differently or set the env var.
+                if os.getenv("RUNWAYML_API_SECRET"):
+                    self.runway_client = RunwayMLAPIClient()
+                    logger.info("RunwayML Client initialized using RUNWAYML_API_SECRET env var.")
+                else:
+                    logger.warning("RUNWAYML_API_SECRET env var not set. RunwayML client not initialized here (will try in set_runway_api_key).")
+            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
-        if api_key and ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient:
+        if api_key and ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient: # This API key is for the client
             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).")
+        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 and RUNWAYML_SDK_IMPORTED and RunwayMLClient:
-            try: self.USE_RUNWAYML = True; logger.info(f"RunwayML Client (Placeholder SDK) {'Ready.' if self.USE_RUNWAYML else 'Failed Init.'}")
-            except Exception as e: logger.error(f"RunwayML client (Placeholder SDK) init error: {e}. Disabled.", exc_info=True); self.USE_RUNWAYML = False
-        elif k: self.USE_RUNWAYML = True; logger.info("RunwayML API Key set (direct API or placeholder).")
-        else: self.USE_RUNWAYML = False; logger.info("RunwayML Disabled (no API key).")
+    
+    def set_runway_api_key(self, k): # For RunwayML
+        self.runway_api_key = k # Store the key
+        if k:
+            if RUNWAYML_SDK_IMPORTED and RunwayMLAPIClient:
+                if not self.runway_client: # If not initialized in __init__
+                    try:
+                        # Ensure RUNWAYML_API_SECRET is set if SDK relies on it
+                        if not os.getenv("RUNWAYML_API_SECRET") and k:
+                            logger.info("Setting RUNWAYML_API_SECRET environment variable from provided key for SDK.")
+                            os.environ["RUNWAYML_API_SECRET"] = k # Make key available to SDK
+                        
+                        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 initialization failed in set_runway_api_key: {e_client_init}", exc_info=True)
+                        self.USE_RUNWAYML = False
+                else: # Client was already initialized (e.g., from env var in __init__)
+                    self.USE_RUNWAYML = True
+                    logger.info("RunwayML Client already initialized.")
+            else: # SDK not imported
+                logger.warning("RunwayML SDK not imported. API key set, but direct HTTP calls would be needed (not implemented).")
+                self.USE_RUNWAYML = False # Can't use if SDK is the only implemented path
+        else:
+            self.USE_RUNWAYML = False
+            logger.info("RunwayML Disabled (no API key provided to set_runway_api_key).")
+
+
+    def _image_to_data_uri(self, image_path):
+        try:
+            mime_type, _ = mimetypes.guess_type(image_path)
+            if not mime_type:
+                # Fallback for common image types if mimetypes fails (e.g., on some systems)
+                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:
+                    logger.warning(f"Could not determine MIME type for {image_path}. Defaulting to application/octet-stream.")
+                    mime_type = "application/octet-stream" # Fallback, Runway might reject this
+
+            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"Generated data URI for {image_path} (first 100 chars): {data_uri[:100]}")
+            return data_uri
+        except Exception as e:
+            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):
+        # Gen-4 supports specific ratios. Find the closest supported or default.
+        # Example: 1280x720 -> "1280:720"
+        # This needs to be robust. For now, we'll assume app.py sends a valid W:H string
+        # or we use a default that matches self.video_frame_size if it's standard.
+        if width == 1280 and height == 720: return "1280:720"
+        if width == 720 and height == 1280: return "720:1280"
+        # Add more mappings based on Gen-4 supported ratios if your self.video_frame_size can vary
+        logger.warning(f"Unsupported resolution {width}x{height} for Runway Gen-4 mapping. Defaulting to 1280:720.")
+        return "1280:720" # Default
+
+    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: # Check for initialized client
+            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}")
+            return None
+
+        image_data_uri = self._image_to_data_uri(input_image_path)
+        if not image_data_uri:
+            return None
+
+        runway_duration = 10 if target_duration_seconds > 7 else 5 # Map to 5s or 10s
+        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"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:
+            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, # e.g., "1280:720"
+                # seed=random.randint(0, 4294967295), # Optional
+                # Other Gen-4 params can be added here: motion_score, upscale etc.
+            )
+            logger.info(f"Runway Gen-4 task created with ID: {task.id}. Polling for completion...")
+
+            poll_interval = 10 # seconds
+            max_polls = 36 # Max 6 minutes (36 * 10s)
+            for _ in range(max_polls):
+                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':
+                    # The SDK docs don't explicitly show how to get the output URL from `task_details`.
+                    # Common patterns are `task_details.output.url` or `task_details.artifacts[0].url`.
+                    # This is a GUESS based on typical API structures. You MUST verify this.
+                    output_url = None
+                    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:
+                         # Assuming the first artifact is the video and has a URL
+                        if hasattr(task_details.artifacts[0], 'url'):
+                            output_url = task_details.artifacts[0].url
+                        elif hasattr(task_details.artifacts[0], 'download_url'): # Another common name
+                            output_url = task_details.artifacts[0].download_url
+
+
+                    if not output_url:
+                        logger.error(f"Runway task {task.id} SUCCEEDED, but no output URL found in task details: {task_details}")
+                        # Attempt to log the full task_details object for inspection
+                        try: logger.error(f"Full task details: {vars(task_details)}")
+                        except: pass
+                        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) # 5 min timeout for download
+                    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 and saved to: {output_video_filepath}")
+                    return output_video_filepath
+                
+                elif task_details.status in ['FAILED', 'ABORTED']:
+                    error_message = "Unknown error"
+                    if hasattr(task_details, 'error_message') and task_details.error_message:
+                        error_message = task_details.error_message
+                    elif hasattr(task_details, 'output') and hasattr(task_details.output, 'error') and task_details.output.error:
+                        error_message = task_details.output.error
+                    logger.error(f"Runway task {task.id} status: {task_details.status}. Error: {error_message}")
+                    return None
+            
+            logger.warning(f"Runway task {task.id} timed out after {max_polls * poll_interval} 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 match.", exc_info=True)
+            return None
+        except Exception as e_runway:
+            logger.error(f"Error during Runway Gen-4 API call or processing: {e_runway}", exc_info=True)
+            return None
+
+    # --- Other helper methods (_get_text_dimensions, _create_placeholder_image_content, _search_pexels_image, _create_placeholder_video_content) ---
+    # --- Keep these as they were in the previous full rewrite unless they need minor adjustments for the Gen-4 workflow ---
     def _get_text_dimensions(self,tc,fo): di=fo.size if hasattr(fo,'size') else self.font_size_pil; return (0,di) if not tc else (lambda b:(b[2]-b[0],b[3]-b[1] if b[3]-b[1]>0 else di))(fo.getbbox(tc)) if hasattr(fo,'getbbox') else (lambda s:(s[0],s[1] if s[1]>0 else di))(fo.getsize(tc)) if hasattr(fo,'getsize') else (int(len(tc)*di*0.6),int(di*1.2))
     def _create_placeholder_image_content(self,td,fn,sz=None):
-        # ... (Keeping this method as it was, assuming it's not the source of video corruption) ...
-        if sz is None: sz = self.video_frame_size
-        img=Image.new('RGB',sz,color=(20,20,40));d=ImageDraw.Draw(img);pd=25;mw=sz[0]-(2*pd);ls=[];
-        if not td: td="(Placeholder: No prompt text)"
+        if sz is None: sz = self.video_frame_size; img=Image.new('RGB',sz,color=(20,20,40));d=ImageDraw.Draw(img);pd=25;mw=sz[0]-(2*pd);ls=[];
+        if not td: td="(Placeholder Image)"
         ws=td.split();cl=""
-        for w in ws:
-            tl=cl+w+" ";
-            if self._get_text_dimensions(tl,self.font)[0] <= mw: cl=tl
-            else:
-                if cl: ls.append(cl.strip());
-                cl=w+" "
-        if cl.strip(): ls.append(cl.strip())
-        if not ls and td: ls.append(td[:int(mw//(self._get_text_dimensions("A",self.font)[0] or 10))]+"..." if td else "(Text too long)")
-        elif not ls: ls.append("(Placeholder Text Error)")
-        _,slh=self._get_text_dimensions("Ay",self.font); slh = slh if slh > 0 else self.font_size_pil + 2
-        mld=min(len(ls),(sz[1]-(2*pd))//(slh+2)) if slh > 0 else 1
-        if mld <=0: mld = 1
-        yts = pd + (sz[1]-(2*pd) - mld*(slh+2))/2.0
-        yt = yts
-        for i in range(mld):
-            lc=ls[i];lw,_=self._get_text_dimensions(lc,self.font);xt=(sz[0]-lw)/2.0
-            d.text((xt,yt),lc,font=self.font,fill=(200,200,180));yt+=slh+2
-            if i==6 and mld > 7: d.text((xt,yt),"...",font=self.font,fill=(200,200,180));break
+        for w in ws: tl=cl+w+" ";raw_w,_=self._get_text_dimensions(tl,self.font);check_w=raw_w if raw_w > 0 else len(tl)*(self.font_size_pil*0.6); # Corrected w to check_w
+        if check_w<=mw:cl=tl;else: # Corrected w to check_w
+            if cl:ls.append(cl.strip());cl=w+" "
+        if cl.strip():ls.append(cl.strip())
+        if not ls and td:ls.append(td[:int(mw//(self._get_text_dimensions("A",self.font)[0]or 10))]+"..." if td else "(Text too long)");elif not ls:ls.append("(Placeholder Error)")
+        _,slh=self._get_text_dimensions("Ay",self.font);slh=slh if slh>0 else self.font_size_pil+2;mld=min(len(ls),(sz[1]-(2*pd))//(slh+2)) if slh>0 else 1;
+        if mld<=0:mld=1;yts=pd+(sz[1]-(2*pd)-mld*(slh+2))/2.0;yt=yts
+        for i in range(mld):lc=ls[i];lw,_=self._get_text_dimensions(lc,self.font);xt=(sz[0]-lw)/2.0;d.text((xt,yt),lc,font=self.font,fill=(200,200,180));yt+=slh+2
+        if i==6 and mld>7:d.text((xt,yt),"...",font=self.font,fill=(200,200,180));break
         fp=os.path.join(self.output_dir,fn);
         try:img.save(fp);return fp
-        except Exception as e:logger.error(f"Saving placeholder image {fp}: {e}", exc_info=True);return None
-
+        except Exception as e:logger.error(f"Save placeholder img {fp}: {e}",exc_info=True);return None
     def _search_pexels_image(self, q, ofnb):
-        # ... (Keeping this method as it was) ...
-        if not self.USE_PEXELS or not self.pexels_api_key: return None
-        h = {"Authorization": self.pexels_api_key}; p = {"query": q, "per_page": 1, "orientation": "landscape", "size": "large2x"}
-        pfn = ofnb.replace(".png", f"_pexels_{random.randint(1000,9999)}.jpg").replace(".mp4", f"_pexels_{random.randint(1000,9999)}.jpg")
-        fp = os.path.join(self.output_dir, pfn)
-        try:
-            logger.info(f"Pexels search: '{q}'"); eq = " ".join(q.split()[:5]); p["query"] = eq
-            r = requests.get("https://api.pexels.com/v1/search", headers=h, params=p, timeout=20)
-            r.raise_for_status(); d = r.json()
-            if d.get("photos") and len(d["photos"]) > 0:
-                pu = d["photos"][0]["src"]["large2x"]
-                ir = requests.get(pu, timeout=60); ir.raise_for_status()
-                id = Image.open(io.BytesIO(ir.content))
-                if id.mode != 'RGB': id = id.convert('RGB')
-                id.save(fp); logger.info(f"Pexels image saved: {fp}"); return fp
-            else: logger.info(f"No photos Pexels: '{eq}'")
-        except Exception as e: logger.error(f"Pexels error ('{q}'): {e}", exc_info=True)
-        return None
-
-    def _generate_video_clip_with_runwayml(self, pt, sifnb, tds=4, iip=None):
-        # ... (Keeping placeholder logic) ...
-        if not self.USE_RUNWAYML or not self.runway_api_key: logger.warning("RunwayML disabled."); return None
-        ovfn = sifnb.replace(".png", "_runway.mp4")
-        ovfp = os.path.join(self.output_dir, ovfn)
-        logger.info(f"RunwayML (Placeholder) for: {pt[:100]}... (Dur: {tds}s)")
-        return self._create_placeholder_video_content(f"[RunwayML Placeholder] {pt}", ovfn, duration=tds)
-
-    def _create_placeholder_video_content(self, td, fn, dur=4, sz=None):
-        # ... (Keeping placeholder logic) ...
-        if sz is None: sz = self.video_frame_size
-        fp = os.path.join(self.output_dir, fn)
-        tc = None
+        if not self.USE_PEXELS or not self.pexels_api_key: return None; h={"Authorization":self.pexels_api_key};p={"query":q,"per_page":1,"orientation":"landscape","size":"large2x"}
+        pfn=ofnb.replace(".png",f"_pexels_{random.randint(1000,9999)}.jpg").replace(".mp4",f"_pexels_{random.randint(1000,9999)}.jpg");fp=os.path.join(self.output_dir,pfn)
+        try: logger.info(f"Pexels search: '{q}'");eq=" ".join(q.split()[:5]);p["query"]=eq;r=requests.get("https://api.pexels.com/v1/search",headers=h,params=p,timeout=20)
+        r.raise_for_status();d=r.json()
+        if d.get("photos") and len(d["photos"])>0:pu=d["photos"][0]["src"]["large2x"];ir=requests.get(pu,timeout=60);ir.raise_for_status();id_img=Image.open(io.BytesIO(ir.content)) # Renamed id to id_img
+        if id_img.mode!='RGB':id_img=id_img.convert('RGB');id_img.save(fp);logger.info(f"Pexels saved: {fp}");return fp
+        else: logger.info(f"No Pexels for: '{eq}'")
+        except Exception as e:logger.error(f"Pexels error ('{q}'): {e}",exc_info=True);return None
+    def _create_placeholder_video_content(self, td, fn, dur=4, sz=None): # Generic placeholder
+        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"Placeholder video: {fp}"); return fp
-        except Exception as e: logger.error(f"Placeholder video error {fp}: {e}", exc_info=True); return None
+            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()
 
-    def generate_scene_asset(self, image_prompt_text, scene_data, scene_identifier_filename_base,
-                             generate_as_video_clip=False, runway_target_duration=4, input_image_for_runway=None):
-        # ... (Keeping this method as it was, it calls the above helpers) ...
+
+    # --- generate_scene_asset (Main asset generation logic) ---
+    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_prompt_text, 'error_message': 'Generation not attempted'}
-        if generate_as_video_clip and self.USE_RUNWAYML:
-            video_path = self._generate_video_clip_with_runwayml(image_prompt_text, base_name, runway_target_duration, input_image_for_runway)
-            if video_path and os.path.exists(video_path): return {'path': video_path, 'type': 'video', 'error': False, 'prompt_used': image_prompt_text}
-            else: logger.warning(f"RunwayML failed for {base_name}. Fallback to image."); asset_info['error_message'] = "RunwayML failed."
+        # Default asset_info for error state
+        asset_info = {'path': None, 'type': 'none', 'error': True,
+                      'prompt_used': image_generation_prompt_text, # Default to image prompt
+                      'error_message': 'Asset generation not fully attempted'}
+
+        # STEP 1: Generate/acquire the base image for Runway Gen-4 or for direct image output
+        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)
         
-        image_filename_with_ext = base_name + ".png"; filepath = os.path.join(self.output_dir, image_filename_with_ext); asset_info['type'] = 'image'
+        # Try DALL-E for base image
         if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
             max_r, att_n = 2, 0
             for att_n in range(max_r):
                 try:
-                    logger.info(f"Attempt {att_n+1} DALL-E: {image_prompt_text[:100]}...")
+                    logger.info(f"Attempt {att_n+1} DALL-E (base image): {image_generation_prompt_text[:100]}...")
                     cl = openai.OpenAI(api_key=self.openai_api_key, timeout=90.0)
-                    r = cl.images.generate(model=self.dalle_model, prompt=image_prompt_text, n=1, size=self.image_size_dalle3, quality="hd", response_format="url", style="vivid")
+                    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[:100]}...")
                     ir = requests.get(iu, timeout=120); ir.raise_for_status()
-                    id = Image.open(io.BytesIO(ir.content));
-                    if id.mode != 'RGB': id = id.convert('RGB')
-                    id.save(filepath); logger.info(f"DALL-E saved: {filepath}");
-                    return {'path': filepath, 'type': 'image', 'error': False, 'prompt_used': image_prompt_text, 'revised_prompt': rp}
+                    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 image 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 # DALL-E success
                 except openai.RateLimitError as e: logger.warning(f"OpenAI Rate Limit {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 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. Pexels fallback...")
-
-        if self.USE_PEXELS and (asset_info['error'] or not (self.USE_AI_IMAGE_GENERATION and self.openai_api_key)):
-            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, image_filename_with_ext)
-            if pp: return {'path': pp, 'type': 'image', 'error': False, 'prompt_used': f"Pexels: {pqt}"}
-            cem = asset_info.get('error_message', ""); asset_info['error_message'] = (cem + " Pexels failed.").strip()
-            if not asset_info['error']: logger.warning("Pexels failed (DALL-E not tried).")
+                except Exception as e: logger.error(f"DALL-E base image 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 image.")
         
+        # Try Pexels if DALL-E failed or not used
+        if asset_info['error'] and self.USE_PEXELS:
+            logger.info("Attempting Pexels for base image.")
+            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) # Pass 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 image.").strip()
+
+        # Fallback to placeholder for base image if all above failed
         if asset_info['error']:
-            logger.warning("All methods failed. Placeholder image.")
-            ppt = asset_info.get('prompt_used', image_prompt_text)
-            php = self._create_placeholder_image_content(f"[Fallback Placeholder] {ppt[:100]}...", image_filename_with_ext)
-            if php: return {'path': php, 'type': 'image', 'error': False, 'prompt_used': ppt}
-            else: cem=asset_info.get('error_message',"");asset_info['error_message']=(cem + " Placeholder failed.").strip()
+            logger.warning("Base image (DALL-E/Pexels) failed. Using placeholder for base image.")
+            ppt = asset_info.get('prompt_used', image_generation_prompt_text) # Use the original image prompt
+            php = self._create_placeholder_image_content(f"[Base Img Placeholder] {ppt[:100]}...", 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: # If base image generation totally failed
+                logger.error("Cannot generate RunwayML video: base image path is missing or generation failed.")
+                asset_info['error'] = True # Ensure error state is propagated
+                asset_info['error_message'] = (asset_info.get('error_message',"") + " Base image missing, Runway video aborted.").strip()
+                asset_info['type'] = 'none' # No valid asset produced
+                return asset_info
+
+            if self.USE_RUNWAYML:
+                logger.info(f"Proceeding to Runway Gen-4 video for {base_name} using base image: {input_image_for_runway_path}")
+                video_path = self._generate_video_clip_with_runwayml(
+                    text_prompt_for_motion=motion_prompt_text_for_video,
+                    input_image_path=input_image_for_runway_path,
+                    scene_identifier_filename_base=base_name, # _runway_gen4.mp4 will be appended
+                    target_duration_seconds=runway_target_duration
+                )
+                if video_path and os.path.exists(video_path):
+                    # Success generating video
+                    asset_info = {'path': video_path, 'type': 'video', 'error': False,
+                                  'prompt_used': motion_prompt_text_for_video, # This is the prompt for Runway
+                                  'base_image_path': input_image_for_runway_path}
+                else:
+                    # RunwayML failed, return the base image info but mark video as failed
+                    logger.warning(f"RunwayML video generation failed for {base_name}. Using the base image as fallback.")
+                    asset_info['error'] = True # Video step specifically failed
+                    asset_info['error_message'] = (asset_info.get('error_message', "Base image generated.") + " RunwayML video step failed; using base image instead.").strip()
+                    asset_info['path'] = input_image_for_runway_path # Path of the base image
+                    asset_info['type'] = 'image' # Fallback asset type is image
+                    asset_info['prompt_used'] = image_generation_prompt_text # Prompt for the base image
+            else: # RunwayML not enabled, use base image
+                logger.warning("RunwayML selected but not enabled/configured. Using base image.")
+                asset_info['error'] = True # Mark that video wasn't generated
+                asset_info['error_message'] = (asset_info.get('error_message', "Base image generated.") + " RunwayML disabled; using base image.").strip()
+                asset_info['path'] = input_image_for_runway_path
+                asset_info['type'] = 'image'
+                asset_info['prompt_used'] = image_generation_prompt_text
+        # If not generate_as_video_clip, asset_info already holds the result of image generation
         return asset_info
 
+
+    # --- generate_narration_audio (Keep as before) ---
     def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"):
-        # ... (Keeping this method as it was - robust enough) ...
-        if not self.USE_ELEVENLABS or not self.elevenlabs_client or not text_to_narrate: logger.info("ElevenLabs conditions not met. Skip audio."); return None
-        afp = os.path.join(self.output_dir, output_filename)
-        try:
-            logger.info(f"ElevenLabs audio (Voice: {self.elevenlabs_voice_id}) for: {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() (non-streaming).")
-                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-streamed): {afp}"); return afp
-            else: logger.error("No recognized 11L audio gen 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 chunk in adi:
-                        if chunk: f.write(chunk)
-                logger.info(f"11L audio (streamed): {afp}"); return afp
-        except Exception as e: logger.error(f"11L audio error: {e}", exc_info=True)
-        return None
-
-
-    # =========================================================================
-    # ASSEMBLE ANIMATIC - FOCUS OF CORRUPTION DEBUGGING
-    # =========================================================================
+        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
+
+
+    # --- assemble_animatic_from_assets (Keep robust image processing, C-contiguous, debug saves, pix_fmt) ---
     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 asset data provided for animatic assembly.")
-            return None
-
-        processed_moviepy_clips = []
-        narration_audio_clip = None
-        final_composite_clip_obj = None
-        
-        logger.info(f"Assembling animatic from {len(asset_data_list)} assets. Target frame: {self.video_frame_size}.")
+        if not asset_data_list: logger.warning("No assets for animatic."); return None
+        processed_clips = []; narration_clip = None; final_clip = None # final_composite_clip_obj renamed to final_clip
+        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_info.get('path')
-            asset_type = asset_info.get('type')
-            target_scene_duration = 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"Processing S{scene_num}: Path='{asset_path}', Type='{asset_type}', TargetDur='{target_scene_duration}'s")
+            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', '')
+            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}: Asset not found at '{asset_path}'. Skipping."); continue
-            if target_scene_duration <= 0:
-                logger.warning(f"S{scene_num}: Invalid duration ({target_scene_duration}s). Skipping."); 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_clip = None
+            current_scene_mvpy_clip = None
             try:
                 if asset_type == 'image':
-                    pil_img = Image.open(asset_path)
-                    logger.debug(f"S{scene_num}: Loaded image. Mode: {pil_img.mode}, Size: {pil_img.size}")
-
-                    # --- Robust Image Processing Pipeline for MoviePy ---
-                    # 1. Convert to RGBA for consistent alpha handling
-                    img_rgba_source = pil_img.convert('RGBA') if pil_img.mode != 'RGBA' else pil_img.copy()
-
-                    # 2. Thumbnail
-                    img_thumbnail = img_rgba_source.copy()
-                    resample_filter = Image.Resampling.LANCZOS if hasattr(Image.Resampling, 'LANCZOS') else Image.BILINEAR
-                    img_thumbnail.thumbnail(self.video_frame_size, resample_filter)
-                    logger.debug(f"S{scene_num}: Thumbnailed to: {img_thumbnail.size}")
-
-                    # 3. Create RGBA canvas and paste image onto it (centers and handles transparency)
-                    canvas_rgba = Image.new('RGBA', self.video_frame_size, (0, 0, 0, 0)) # Transparent background
-                    xo = (self.video_frame_size[0] - img_thumbnail.width) // 2
-                    yo = (self.video_frame_size[1] - img_thumbnail.height) // 2
-                    canvas_rgba.paste(img_thumbnail, (xo, yo), img_thumbnail) # Use thumbnail's alpha as mask
-                    
-                    # 4. Convert to final RGB image (flattens alpha against black) for MoviePy
-                    final_rgb_image_for_moviepy = Image.new("RGB", self.video_frame_size, (0, 0, 0)) # Black background
-                    final_rgb_image_for_moviepy.paste(canvas_rgba, mask=canvas_rgba.split()[3]) # Use alpha of canvas_rgba as mask
-
-                    debug_canvas_path = os.path.join(self.output_dir, f"debug_PRE_NUMPY_S{scene_num}.png")
-                    try: final_rgb_image_for_moviepy.save(debug_canvas_path); logger.info(f"DEBUG: Saved PRE-NUMPY image for S{scene_num} to {debug_canvas_path}")
-                    except Exception as e_save: logger.error(f"DEBUG: Error saving PRE-NUMPY image for S{scene_num}: {e_save}")
-                    
-                    # 5. Convert to C-contiguous NumPy array, dtype uint8
-                    frame_np = np.array(final_rgb_image_for_moviepy, 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}: Ensured NumPy array is C-contiguous.")
-                    
-                    logger.debug(f"S{scene_num}: Final NumPy for MoviePy. Shape: {frame_np.shape}, Dtype: {frame_np.dtype}, Contiguous: {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 array shape/size for ImageClip. Shape: {frame_np.shape}. Skipping."); continue
-                    # --- End Robust Image Processing ---
-
-                    current_clip_base = ImageClip(frame_np, transparent=False).set_duration(target_scene_duration)
-                    logger.debug(f"S{scene_num}: Base ImageClip created.")
-
-                    # --- DEBUG: Save frame from MoviePy ImageClip object ---
-                    moviepy_frame_debug_path = os.path.join(self.output_dir, f"debug_MOVIEPY_FRAME_S{scene_num}.png")
-                    try:
-                        current_clip_base.save_frame(moviepy_frame_debug_path, t=0.1) # Save a frame at 0.1s
-                        logger.info(f"DEBUG: Saved frame FROM MOVIEPY ImageClip for S{scene_num} to {moviepy_frame_debug_path}")
-                    except Exception as e_save_mv_frame:
-                        logger.error(f"DEBUG: Error saving frame FROM MOVIEPY ImageClip for S{scene_num}: {e_save_mv_frame}", exc_info=True)
-                    # --- End DEBUG ---
-                    
-                    current_scene_clip_with_fx = current_clip_base
-                    try: # Ken Burns
-                        end_scale = random.uniform(1.03, 1.08)
-                        current_scene_clip_with_fx = current_clip_base.fx(vfx.resize, lambda t: 1 + (end_scale - 1) * (t / target_scene_duration) if target_scene_duration > 0 else 1).set_position('center')
-                    except Exception as e_fx: logger.error(f"S{scene_num}: Ken Burns error: {e_fx}. Using static.", exc_info=False)
-                    current_scene_clip = current_scene_clip_with_fx
-
+                    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)
+                    current_scene_mvpy_clip = clip_fx
                 elif asset_type == 'video':
-                    # ... (Video processing logic - keep as in previous good version) ...
-                    source_video_clip = None
+                    src_clip=None
                     try:
-                        source_video_clip = VideoFileClip(asset_path, target_resolution=(self.video_frame_size[1], self.video_frame_size[0]) if self.video_frame_size else None)
-                        temp_clip = source_video_clip
-                        if source_video_clip.duration != target_scene_duration:
-                            if source_video_clip.duration > target_scene_duration: temp_clip = source_video_clip.subclip(0, target_scene_duration)
-                            else: # Source is shorter
-                                if target_scene_duration / source_video_clip.duration > 1.5 and source_video_clip.duration > 0.1: temp_clip = source_video_clip.loop(duration=target_scene_duration)
-                                else: temp_clip = source_video_clip.set_duration(source_video_clip.duration); logger.info(f"S{scene_num}: Video clip ({source_video_clip.duration:.2f}s) shorter than target ({target_scene_duration:.2f}s).")
-                        current_scene_clip = temp_clip.set_duration(target_scene_duration)
-                        if current_scene_clip.size != list(self.video_frame_size): current_scene_clip = current_scene_clip.resize(self.video_frame_size)
-                    except Exception as e_vid_load: logger.error(f"S{scene_num}: Error loading/processing video '{asset_path}': {e_vid_load}", exc_info=True); continue
+                        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) # Explicitly no audio from source video clips
+                        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
                     finally:
-                        if source_video_clip and source_video_clip is not current_scene_clip and hasattr(source_video_clip, 'close'): source_video_clip.close()
-
-                else: logger.warning(f"S{scene_num}: Unknown asset type '{asset_type}'. Skipping."); 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_clip and key_action: # Add text overlay
+                if current_scene_mvpy_clip and key_action:
                     try:
-                        txt_clip = 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(min(current_scene_clip.duration - 0.5, current_scene_clip.duration * 0.8) if current_scene_clip.duration > 0.5 else current_scene_clip.duration).set_start(0.25).set_position(('center', 0.92), relative=True)
-                        current_scene_clip = CompositeVideoClip([current_scene_clip, txt_clip], size=self.video_frame_size, use_bgclip=True)
-                    except Exception as e_txt: logger.error(f"S{scene_num}: Error with TextClip: {e_txt}. Using clip without text.", exc_info=True)
-                
-                if current_scene_clip: processed_moviepy_clips.append(current_scene_clip); logger.info(f"S{scene_num}: Asset processed. Clip duration: {current_scene_clip.duration:.2f}s.")
-            except Exception as e_asset_proc: logger.error(f"MAJOR Error S{scene_num} ({asset_path}): {e_asset_proc}", exc_info=True)
-            finally: # Close individual clips if an error occurred during their specific processing
-                if current_scene_clip and hasattr(current_scene_clip, 'reader') and current_scene_clip.reader:
-                    if hasattr(current_scene_clip, 'close'): current_scene_clip.close()
-                elif current_scene_clip and hasattr(current_scene_clip, 'close'): current_scene_clip.close()
-
-        if not processed_moviepy_clips: logger.warning("No clips processed. Aborting."); return None
-        
-        transition_duration = 0.75
+                        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 : # Only add text if duration is positive
+                            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 or negative. Skipping text overlay.")
+                    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'): # Check if it's a VideoFileClip instance that needs closing
+                    if hasattr(current_scene_mvpy_clip, 'reader') and current_scene_mvpy_clip.reader: current_scene_mvpy_clip.close()
+                    elif not hasattr(current_scene_mvpy_clip, 'reader'): current_scene_mvpy_clip.close() # For ImageClip if close() is added
+
+        if not processed_clips:logger.warning("No clips processed. Abort.");return None
+        td=0.75
         try:
-            logger.info(f"Concatenating {len(processed_moviepy_clips)} clips.")
-            if len(processed_moviepy_clips) > 1: final_composite_clip_obj = concatenate_videoclips(processed_moviepy_clips, padding = -transition_duration if transition_duration > 0 else 0, method="compose")
-            elif processed_moviepy_clips: final_composite_clip_obj = processed_moviepy_clips[0]
-            if not final_composite_clip_obj: logger.error("Concatenation failed."); return None
-            logger.info(f"Concatenated clip duration: {final_composite_clip_obj.duration:.2f}s")
-
-            if transition_duration > 0 and final_composite_clip_obj.duration > 0:
-                if final_composite_clip_obj.duration > transition_duration * 2: final_composite_clip_obj = final_composite_clip_obj.fx(vfx.fadein, transition_duration).fx(vfx.fadeout, transition_duration)
-                else: final_composite_clip_obj = final_composite_clip_obj.fx(vfx.fadein, min(transition_duration, final_composite_clip_obj.duration/2.0))
-
-            if overall_narration_path and os.path.exists(overall_narration_path) and final_composite_clip_obj.duration > 0:
-                try: narration_audio_clip = AudioFileClip(overall_narration_path); final_composite_clip_obj = final_composite_clip_obj.set_audio(narration_audio_clip); logger.info("Narration added.")
-                except Exception as e_audio: logger.error(f"Adding narration error: {e_audio}", exc_info=True)
-            elif final_composite_clip_obj.duration <= 0 : logger.warning("Video has no duration. Audio not added.")
-            
-            if final_composite_clip_obj and final_composite_clip_obj.duration > 0:
-                output_path = os.path.join(self.output_dir, output_filename)
-                logger.info(f"Writing final video: {output_path} (Duration: {final_composite_clip_obj.duration:.2f}s)")
-                # --- Test different write parameters if corruption persists ---
-                final_composite_clip_obj.write_videofile(
-                    output_path, fps=fps, codec='libx264', 
-                    preset='medium', # Changed from ultrafast for potentially better encoding
-                    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"] # Potentially force pixel format if issues persist
-                )
-                logger.info(f"Video created: {output_path}"); return output_path
-            else: logger.error("Final clip invalid. Not writing."); return None
-        except Exception as e_write: logger.error(f"Video writing error: {e_write}", exc_info=True); 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
         finally:
             logger.debug("Closing all MoviePy clips in `assemble_animatic_from_assets` finally block.")
-            clips_to_close = processed_moviepy_clips + ([narration_audio_clip] if narration_audio_clip else []) + ([final_composite_clip_obj] if final_composite_clip_obj else [])
-            for clip_obj in clips_to_close:
+            all_clips_to_close = processed_clips + ([narration_clip] if narration_clip else []) + ([final_clip] if final_clip else [])
+            for clip_obj in all_clips_to_close: # Use a different name to avoid scope issues
                 if clip_obj and hasattr(clip_obj, 'close'):
                     try: clip_obj.close()
-                    except Exception as e_close: logger.warning(f"Ignoring error while closing a clip: {e_close}")
+                    except Exception as e_close: logger.warning(f"Ignoring error while closing a clip: {type(clip_obj).__name__} - {e_close}")