Update core/visual_engine.py

core/visual_engine.py

@@ -24,315 +24,225 @@ import random
 import logging
 
 logger = logging.getLogger(__name__)
-logger.setLevel(logging.INFO) # Set default logging level for this module
+logger.setLevel(logging.INFO)
 
 # --- ElevenLabs Client Import ---
-ELEVENLABS_CLIENT_IMPORTED = False
-ElevenLabsAPIClient = None
-Voice = None
-VoiceSettings = None
+ELEVENLABS_CLIENT_IMPORTED = False; ElevenLabsAPIClient = None; Voice = None; VoiceSettings = None
 try:
     from elevenlabs.client import ElevenLabs as ImportedElevenLabsClient
     from elevenlabs import Voice as ImportedVoice, VoiceSettings as ImportedVoiceSettings
-    ElevenLabsAPIClient = ImportedElevenLabsClient
-    Voice = ImportedVoice
-    VoiceSettings = ImportedVoiceSettings
-    ELEVENLABS_CLIENT_IMPORTED = True
-    logger.info("ElevenLabs client components imported successfully.")
-except Exception as e_eleven:
-    logger.warning(f"ElevenLabs client import failed: {e_eleven}. Audio generation will be disabled.")
+    ElevenLabsAPIClient = ImportedElevenLabsClient; Voice = ImportedVoice; VoiceSettings = ImportedVoiceSettings
+    ELEVENLABS_CLIENT_IMPORTED = True; logger.info("ElevenLabs client components imported.")
+except Exception as e_eleven: logger.warning(f"ElevenLabs client import failed: {e_eleven}. Audio disabled.")
 
 # --- RunwayML Client Import (Placeholder) ---
-RUNWAYML_SDK_IMPORTED = False
-RunwayMLClient = None # Placeholder for the actual RunwayML client class
+RUNWAYML_SDK_IMPORTED = False; RunwayMLClient = None
 try:
-    # Example: from runwayml import RunwayClient as ImportedRunwayMLClient
-    # RunwayMLClient = ImportedRunwayMLClient
-    # RUNWAYML_SDK_IMPORTED = True
-    logger.info("RunwayML SDK import is a placeholder. Actual SDK needed for Runway features.")
-except ImportError:
-    logger.warning("RunwayML SDK (placeholder) not found. RunwayML video generation will be disabled.")
-except Exception as e_runway_sdk:
-    logger.warning(f"Error importing RunwayML SDK (placeholder): {e_runway_sdk}. RunwayML features disabled.")
+    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.")
 
 
 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 = "arial.ttf" # Or a more reliably found font like "DejaVuSans-Bold.ttf"
+        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", # macOS
-            f"C:/Windows/Fonts/arial.ttf", # Windows
-            f"/usr/local/share/fonts/truetype/mycustomfonts/{self.font_filename}"
+            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_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'
-        # For MoviePy TextClip, use font names ImageMagick knows. Check with `convert -list font`.
-        # 'Liberation-Sans-Bold' is a good default if available.
-        self.video_overlay_font = 'DejaVuSans-Bold' if 'dejavu' in (self.font_path_pil or '').lower() else 'Liberation-Sans-Bold'
-
+        self.video_overlay_font = 'DejaVu-Sans-Bold' # ImageMagick name for DejaVuSans-Bold
 
         try:
-            if self.font_path_pil:
-                self.font = ImageFont.truetype(self.font_path_pil, self.font_size_pil)
-                logger.info(f"Pillow font loaded: {self.font_path_pil}.")
-            else:
-                self.font = ImageFont.load_default()
-                logger.warning("Custom Pillow font not found. Using default. Text rendering for placeholders might be basic.")
-                self.font_size_pil = 10 # Default Pillow font is small
-        except IOError as e_font:
-            logger.error(f"Pillow font loading IOError for '{self.font_path_pil or 'default'}': {e_font}. Using default.")
-            self.font = ImageFont.load_default()
-            self.font_size_pil = 10
+            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_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)
+        if VoiceSettings and ELEVENLABS_CLIENT_IMPORTED: self.elevenlabs_voice_settings = VoiceSettings(stability=0.60, similarity_boost=0.80, style=0.15, use_speaker_boost=True)
         else: self.elevenlabs_voice_settings = None
-
         self.pexels_api_key = None; self.USE_PEXELS = False
-        self.runway_api_key = None; self.USE_RUNWAYML = False
-        self.runway_client = None
-
+        self.runway_api_key = None; self.USE_RUNWAYML = False; self.runway_client = None
         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_openai_api_key(self,k): self.openai_api_key=k; self.USE_AI_IMAGE_GENERATION=bool(k); logger.info(f"DALL-E ({self.dalle_model}) {'Ready.' if k else 'Disabled.'}")
     def set_elevenlabs_api_key(self,api_key, voice_id_from_secret=None):
         self.elevenlabs_api_key=api_key
         if voice_id_from_secret: self.elevenlabs_voice_id = voice_id_from_secret
         if api_key and ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient:
-            try:
-                self.elevenlabs_client = ElevenLabsAPIClient(api_key=api_key)
-                self.USE_ELEVENLABS=bool(self.elevenlabs_client)
-                logger.info(f"ElevenLabs Client {'Ready' if self.USE_ELEVENLABS else 'Failed Init'} (Voice ID: {self.elevenlabs_voice_id}).")
+            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).")
-
-    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_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.runway_client = RunwayMLClient(api_key=k) # Actual initialization
-                self.USE_RUNWAYML = True
-                logger.info(f"RunwayML Client (Placeholder with SDK) {'Ready.' if self.USE_RUNWAYML else 'Failed Init.'}")
-            except Exception as e: logger.error(f"RunwayML client (Placeholder with SDK) init error: {e}. Disabled.", exc_info=True); self.USE_RUNWAYML = False
-        elif k:
-            self.USE_RUNWAYML = True
-            logger.info("RunwayML API Key set. Using direct API calls or placeholder (SDK not fully integrated/imported).")
+            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 _get_text_dimensions(self,text_content,font_obj):
-        if not text_content: return 0, (self.font.size if hasattr(self.font, 'size') else self.font_size_pil)
-        try:
-            if hasattr(font_obj,'getbbox'):
-                bbox=font_obj.getbbox(text_content);w=bbox[2]-bbox[0];h=bbox[3]-bbox[1]
-                return w, h if h > 0 else font_obj.size
-            elif hasattr(font_obj,'getsize'):
-                w,h=font_obj.getsize(text_content)
-                return w, h if h > 0 else font_obj.size
-            else: return int(len(text_content)*font_obj.size*0.6), int(font_obj.size*1.2)
-        except Exception as e: logger.warning(f"Error in _get_text_dimensions for '{text_content[:20]}...': {e}"); return int(len(text_content)*self.font_size_pil*0.6),int(self.font_size_pil*1.2)
-
-    def _create_placeholder_image_content(self,text_description,filename,size=None):
-        if size is None: size = self.video_frame_size
-        img=Image.new('RGB',size,color=(20,20,40));d=ImageDraw.Draw(img);padding=25;max_w=size[0]-(2*padding);lines=[];
-        if not text_description: text_description="(Placeholder: No prompt text)"
-        words=text_description.split();current_line=""
-        for word in words:
-            test_line=current_line+word+" ";
-            if self._get_text_dimensions(test_line,self.font)[0] <= max_w: current_line=test_line
+    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)"
+        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 current_line: lines.append(current_line.strip());
-                current_line=word+" "
-        if current_line.strip(): lines.append(current_line.strip())
-        if not lines and text_description: lines.append(text_description[:int(max_w//(self._get_text_dimensions("A",self.font)[0] or 10))]+"..." if text_description else "(Text too long)")
-        elif not lines: lines.append("(Placeholder Text Error)")
-        _,single_line_h=self._get_text_dimensions("Ay",self.font); single_line_h = single_line_h if single_line_h > 0 else self.font_size_pil + 2
-        max_lines_to_display=min(len(lines),(size[1]-(2*padding))//(single_line_h+2)) if single_line_h > 0 else 1
-        if max_lines_to_display <=0: max_lines_to_display = 1
-        y_text_start = padding + (size[1]-(2*padding) - max_lines_to_display*(single_line_h+2))/2.0
-        y_text = y_text_start
-        for i in range(max_lines_to_display):
-            line_content=lines[i];line_w,_=self._get_text_dimensions(line_content,self.font);x_text=(size[0]-line_w)/2.0
-            d.text((x_text,y_text),line_content,font=self.font,fill=(200,200,180));y_text+=single_line_h+2
-            if i==6 and max_lines_to_display > 7: d.text((x_text,y_text),"...",font=self.font,fill=(200,200,180));break
-        filepath=os.path.join(self.output_dir,filename);
-        try:img.save(filepath);return filepath
-        except Exception as e:logger.error(f"Saving placeholder image {filepath}: {e}", exc_info=True);return None
-
-    def _search_pexels_image(self, query, output_filename_base):
+                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
+        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
+
+    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
-        headers = {"Authorization": self.pexels_api_key}; params = {"query": query, "per_page": 1, "orientation": "landscape", "size": "large2x"} # Request higher quality
-        pexels_filename = output_filename_base.replace(".png", f"_pexels_{random.randint(1000,9999)}.jpg").replace(".mp4", f"_pexels_{random.randint(1000,9999)}.jpg")
-        filepath = os.path.join(self.output_dir, pexels_filename)
+        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"Searching Pexels 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.raise_for_status(); data = response.json()
-            if data.get("photos") and len(data["photos"]) > 0:
-                photo_url = data["photos"][0]["src"]["large2x"]
-                image_response = requests.get(photo_url, timeout=60); image_response.raise_for_status()
-                img_data = Image.open(io.BytesIO(image_response.content))
-                if img_data.mode != 'RGB': img_data = img_data.convert('RGB')
-                img_data.save(filepath); logger.info(f"Pexels image saved: {filepath}"); return filepath
-            else: logger.info(f"No photos found on Pexels for query: '{effective_query}'")
-        except Exception as e: logger.error(f"Pexels search/download for query '{query}': {e}", exc_info=True)
+            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, prompt_text, scene_identifier_filename_base, target_duration_seconds=4, input_image_path=None):
-        if not self.USE_RUNWAYML or not self.runway_api_key:
-            logger.warning("RunwayML not enabled or API key missing. Cannot generate video clip.")
-            return None
-        output_video_filename = scene_identifier_filename_base.replace(".png", "_runway.mp4") # More specific extension
-        output_video_filepath = os.path.join(self.output_dir, output_video_filename)
-        logger.info(f"Attempting RunwayML video generation for: {prompt_text[:100]}... (Target duration: {target_duration_seconds}s)")
-        # --- START ACTUAL RUNWAYML API INTERACTION (HYPOTHETICAL - NEEDS IMPLEMENTATION) ---
-        # Example:
-        # if self.runway_client:
-        #     try:
-        #         # result = self.runway_client.generate(text=prompt_text, duration=target_duration_seconds, seed_image=input_image_path)
-        #         # result.save(output_video_filepath)
-        #         # return output_video_filepath
-        #     except Exception as e_runway:
-        #         logger.error(f"Actual RunwayML generation error: {e_runway}", exc_info=True)
-        #         return None
-        # else: logger.warning("RunwayML client not initialized (placeholder).")
-        # --- END ACTUAL RUNWAYML API INTERACTION (HYPOTHETICAL) ---
-        logger.warning("Using PLACEHOLDER video generation for RunwayML as actual API calls are not implemented.")
-        return self._create_placeholder_video_content(f"[RunwayML Placeholder] {prompt_text}", output_video_filename, duration=target_duration_seconds)
-
-    def _create_placeholder_video_content(self, text_description, filename, duration=4, size=None):
-        if size is None: size = self.video_frame_size
-        filepath = os.path.join(self.output_dir, filename)
-        txt_clip = None # Initialize
+    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
         try:
-            txt_clip = TextClip(text_description, fontsize=50, color='white', font=self.video_overlay_font,
-                                bg_color='black', size=size, method='caption').set_duration(duration)
-            txt_clip.write_videofile(filepath, fps=24, codec='libx264', preset='ultrafast', logger=None, threads=2)
-            logger.info(f"Placeholder video saved: {filepath}")
-            return filepath
-        except Exception as e: logger.error(f"Failed to create placeholder video {filepath}: {e}", exc_info=True); return None
+            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
         finally:
-            if txt_clip and hasattr(txt_clip, 'close'): txt_clip.close()
+            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) ...
         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:
-            logger.info(f"Attempting RunwayML video clip generation for {base_name}")
-            video_path = self._generate_video_clip_with_runwayml(
-                image_prompt_text, base_name,
-                target_duration_seconds=runway_target_duration,
-                input_image_path=input_image_for_runway
-            )
-            if video_path and os.path.exists(video_path):
-                asset_info = {'path': video_path, 'type': 'video', 'error': False, 'prompt_used': image_prompt_text}
-                return asset_info
-            else: logger.warning(f"RunwayML video clip generation failed for {base_name}. Falling back to image."); asset_info['error_message'] = "RunwayML video generation failed."
-
-        image_filename_with_ext = base_name + ".png"
-        filepath = os.path.join(self.output_dir, image_filename_with_ext)
-        asset_info['type'] = 'image'
-
+            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."
+        
+        image_filename_with_ext = base_name + ".png"; filepath = os.path.join(self.output_dir, image_filename_with_ext); asset_info['type'] = 'image'
         if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
-            max_retries = 2; attempt_num = 0
-            for attempt_num in range(max_retries):
+            max_r, att_n = 2, 0
+            for att_n in range(max_r):
                 try:
-                    logger.info(f"Attempt {attempt_num+1}: DALL-E ({self.dalle_model}) for: {image_prompt_text[:100]}...")
-                    client = openai.OpenAI(api_key=self.openai_api_key, timeout=90.0)
-                    response = client.images.generate(model=self.dalle_model, prompt=image_prompt_text, n=1, size=self.image_size_dalle3, quality="hd", response_format="url", style="vivid")
-                    image_url = response.data[0].url; revised_prompt = getattr(response.data[0], 'revised_prompt', None)
-                    if revised_prompt: logger.info(f"DALL-E 3 revised_prompt: {revised_prompt[:100]}...")
-                    image_response = requests.get(image_url, timeout=120); image_response.raise_for_status()
-                    img_data = Image.open(io.BytesIO(image_response.content));
-                    if img_data.mode != 'RGB': img_data = img_data.convert('RGB')
-                    img_data.save(filepath); logger.info(f"AI Image (DALL-E) saved: {filepath}");
-                    asset_info = {'path': filepath, 'type': 'image', 'error': False, 'prompt_used': image_prompt_text, 'revised_prompt': revised_prompt}
-                    return asset_info # Success
-                except openai.RateLimitError as e_rate: logger.warning(f"OpenAI Rate Limit on attempt {attempt_num+1}: {e_rate}. Retrying..."); time.sleep(5 * (attempt_num + 1)); asset_info['error_message'] = str(e_rate)
-                except openai.APIError as e_api: logger.error(f"OpenAI API Error: {e_api}"); asset_info['error_message'] = str(e_api); break
-                except requests.exceptions.RequestException as e_req: logger.error(f"Requests Error (DALL-E download): {e_req}"); asset_info['error_message'] = str(e_req); break
-                except Exception as e_gen: logger.error(f"Generic error (DALL-E gen): {e_gen}", exc_info=True); asset_info['error_message'] = str(e_gen); break
-            if asset_info['error']: logger.warning(f"DALL-E generation failed after {attempt_num+1} attempts. Trying Pexels fallback...")
-        
-        if self.USE_PEXELS and (asset_info['error'] or not (self.USE_AI_IMAGE_GENERATION and self.openai_api_key)):
-            pexels_query_text = scene_data.get('pexels_search_query_감독', f"{scene_data.get('emotional_beat','')} {scene_data.get('setting_description','')}")
-            pexels_path = self._search_pexels_image(pexels_query_text, image_filename_with_ext)
-            if pexels_path:
-                asset_info = {'path': pexels_path, 'type': 'image', 'error': False, 'prompt_used': f"Pexels: {pexels_query_text}"}
-                return asset_info
-            current_error_msg = asset_info.get('error_message', "")
-            asset_info['error_message'] = (current_error_msg + " Pexels search also failed or disabled.").strip()
-            if not asset_info['error']: logger.warning("Pexels search failed or was disabled (DALL-E not attempted).")
+                    logger.info(f"Attempt {att_n+1} DALL-E: {image_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")
+                    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}
+                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).")
+        
         if asset_info['error']:
-            logger.warning("All primary generation methods failed. Using placeholder image.")
-            placeholder_prompt_text = asset_info.get('prompt_used', image_prompt_text)
-            placeholder_path = self._create_placeholder_image_content(f"[Fallback Placeholder] {placeholder_prompt_text[:100]}...", image_filename_with_ext)
-            if placeholder_path:
-                asset_info = {'path': placeholder_path, 'type': 'image', 'error': False, 'prompt_used': placeholder_prompt_text}
-            else:
-                current_error_msg = asset_info.get('error_message', "")
-                asset_info['error_message'] = (current_error_msg + " Placeholder creation also failed.").strip()
+            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()
         return asset_info
 
     def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"):
-        if not self.USE_ELEVENLABS or not self.elevenlabs_client or not text_to_narrate:
-            logger.info("ElevenLabs conditions not met. Skipping audio generation.")
-            return None
-        audio_filepath = os.path.join(self.output_dir, output_filename)
+        # ... (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"Generating ElevenLabs audio (Voice ID: {self.elevenlabs_voice_id}) for: {text_to_narrate[:70]}...")
-            audio_stream_method = None
-            if hasattr(self.elevenlabs_client, 'text_to_speech') and hasattr(self.elevenlabs_client.text_to_speech, 'stream'):
-                audio_stream_method = self.elevenlabs_client.text_to_speech.stream; logger.info("Using elevenlabs_client.text_to_speech.stream()")
-            elif hasattr(self.elevenlabs_client, 'generate_stream') : audio_stream_method = self.elevenlabs_client.generate_stream; logger.info("Using elevenlabs_client.generate_stream()")
-            elif hasattr(self.elevenlabs_client, 'generate'):
-                logger.info("Using elevenlabs_client.generate() (non-streaming).")
-                voice_param = 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)
-                audio_bytes = self.elevenlabs_client.generate(text=text_to_narrate, voice=voice_param, model="eleven_multilingual_v2")
-                with open(audio_filepath, "wb") as f: f.write(audio_bytes)
-                logger.info(f"ElevenLabs audio (non-streamed) saved: {audio_filepath}"); return audio_filepath
-            else: logger.error("No recognized audio generation method found on ElevenLabs client."); return None
-
-            if audio_stream_method: # Streaming logic
-                voice_param_for_stream = {"voice_id": str(self.elevenlabs_voice_id)}
+            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'): voice_param_for_stream["voice_settings"] = self.elevenlabs_voice_settings.model_dump() # Pydantic v2
-                    elif hasattr(self.elevenlabs_voice_settings, 'dict'): voice_param_for_stream["voice_settings"] = self.elevenlabs_voice_settings.dict() # Pydantic v1
-                    else: voice_param_for_stream["voice_settings"] = self.elevenlabs_voice_settings
-                
-                audio_data_iterator = audio_stream_method(text=text_to_narrate, model_id="eleven_multilingual_v2", **voice_param_for_stream)
-                with open(audio_filepath, "wb") as f:
-                    for chunk in audio_data_iterator:
+                    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"ElevenLabs audio (streamed) saved: {audio_filepath}"); return audio_filepath
-        except AttributeError as ae: logger.error(f"AttributeError with ElevenLabs client: {ae}. SDK method/params might be different.", exc_info=True)
-        except Exception as e: logger.error(f"Error generating ElevenLabs audio: {e}", exc_info=True)
+                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
+    # =========================================================================
     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.")
@@ -347,7 +257,7 @@ class VisualEngine:
         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) # Duration for this scene in the animatic
+            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', '')
 
@@ -358,169 +268,138 @@ class VisualEngine:
             if target_scene_duration <= 0:
                 logger.warning(f"S{scene_num}: Invalid duration ({target_scene_duration}s). Skipping."); continue
 
-            current_scene_clip = None # The final MoviePy clip for this scene
+            current_scene_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}")
 
-                    # 1. Ensure image is RGBA for consistent alpha handling during processing
+                    # --- 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 the RGBA image
-                    img_thumbnail = img_rgba_source.copy() # Work on a copy
-                    resample_filter = Image.Resampling.LANCZOS if hasattr(Image.Resampling, 'LANCZOS') else (Image.ANTIALIAS if hasattr(Image, 'ANTIALIAS') else Image.BILINEAR)
+                    # 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 a target-sized RGBA canvas (fully transparent)
-                    canvas_rgba = Image.new('RGBA', self.video_frame_size, (0, 0, 0, 0))
-                    
-                    # 4. Paste the thumbnailed image (with its alpha) onto the center of the RGBA canvas
+                    # 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 img_thumbnail's alpha as mask
-                    logger.debug(f"S{scene_num}: Image pasted onto transparent RGBA canvas.")
-
-                    # 5. Create a final RGB image by pasting the RGBA canvas onto an opaque background
-                    #    This flattens transparency and ensures an RGB image for MoviePy.
-                    final_rgb_image_for_moviepy = Image.new("RGB", self.video_frame_size, (0, 0, 0)) # Opaque black background
-                    final_rgb_image_for_moviepy.paste(canvas_rgba, mask=canvas_rgba.split()[3]) # Paste using alpha from canvas_rgba
+                    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
 
-                    # --- CRITICAL DEBUG STEP: Save the image that will be fed to MoviePy ---
-                    debug_canvas_path = os.path.join(self.output_dir, f"debug_final_rgb_FOR_MOVIEPY_scene_{scene_num}.png")
-                    try:
-                        final_rgb_image_for_moviepy.save(debug_canvas_path)
-                        logger.info(f"DEBUG: Saved final RGB image for MoviePy (S{scene_num}) to {debug_canvas_path}")
-                    except Exception as e_save_canvas:
-                        logger.error(f"DEBUG: Failed to save final_rgb_image_for_moviepy (S{scene_num}): {e_save_canvas}")
+                    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.")
                     
-                    frame_np = np.array(final_rgb_image_for_moviepy) # Should be (H, W, 3) dtype uint8
-                    logger.debug(f"S{scene_num}: Converted to NumPy. Shape: {frame_np.shape}, Dtype: {frame_np.dtype}, Size: {frame_np.size}")
+                    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: logger.error(f"S{scene_num}: NumPy array is EMPTY. Skipping."); continue
-                    if frame_np.ndim != 3 or frame_np.shape[2] != 3: logger.error(f"S{scene_num}: NumPy array has unexpected shape {frame_np.shape}. Skipping."); continue
-                    if frame_np.dtype != np.uint8: frame_np = frame_np.astype(np.uint8); logger.warning(f"S{scene_num}: Converted NumPy array dtype to uint8.")
+                    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 from NumPy array.")
+                    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 # Start with base
+                    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')
-                        logger.debug(f"S{scene_num}: Ken Burns effect applied.")
                     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
 
                 elif asset_type == 'video':
-                    logger.debug(f"S{scene_num}: Loading video asset from {asset_path}")
-                    source_video_clip = None # Initialize
+                    # ... (Video processing logic - keep as in previous good version) ...
+                    source_video_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_for_video_asset = source_video_clip
+                        temp_clip = source_video_clip
                         if source_video_clip.duration != target_scene_duration:
-                            if source_video_clip.duration > target_scene_duration:
-                                temp_clip_for_video_asset = source_video_clip.subclip(0, 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_for_video_asset = source_video_clip.loop(duration=target_scene_duration)
-                                else: # Let it play its native length, will be set to target_scene_duration for concat
-                                    temp_clip_for_video_asset = 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 scene target ({target_scene_duration:.2f}s).")
-                        
-                        current_scene_clip = temp_clip_for_video_asset.set_duration(target_scene_duration)
-
-                        if current_scene_clip.size != list(self.video_frame_size):
-                            logger.debug(f"S{scene_num}: Resizing video clip from {current_scene_clip.size} to {self.video_frame_size}")
-                            current_scene_clip = current_scene_clip.resize(self.video_frame_size)
-                        
-                        logger.debug(f"S{scene_num}: Video asset processed. Final duration for scene: {current_scene_clip.duration:.2f}s")
-                    except Exception as e_vid_load:
-                        logger.error(f"S{scene_num}: Error loading/processing video file '{asset_path}': {e_vid_load}", exc_info=True)
-                        if source_video_clip and hasattr(source_video_clip, 'close'): source_video_clip.close()
-                        continue # Skip this asset
-                    finally: # Close original source if it was opened and different from the final clip
-                         if source_video_clip and source_video_clip is not current_scene_clip and hasattr(source_video_clip, 'close'):
-                             source_video_clip.close()
-
+                                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
+                    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
                 
-                # Add text overlay (common to both image and video assets)
-                if current_scene_clip and key_action:
-                    logger.debug(f"S{scene_num}: Adding text overlay: '{key_action}'")
-                    text_overlay_duration = min(target_scene_duration - 0.5, target_scene_duration * 0.8) if target_scene_duration > 0.5 else target_scene_duration
-                    text_overlay_start = (target_scene_duration - text_overlay_duration) / 2.0
-                    if text_overlay_duration > 0:
-                        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(text_overlay_duration).set_start(text_overlay_start).set_position(('center', 0.92), relative=True)
-                            current_scene_clip = CompositeVideoClip([current_scene_clip, txt_clip], size=self.video_frame_size, use_bgclip=True)
-                            logger.debug(f"S{scene_num}: Text overlay composited.")
-                        except Exception as e_txt: logger.error(f"S{scene_num}: Error creating TextClip or CompositeVideoClip for text: {e_txt}. Using clip without text.", exc_info=True)
+                if current_scene_clip and key_action: # Add text overlay
+                    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 successfully processed. Clip duration: {current_scene_clip.duration:.2f}s, Added to final list.")
-
-            except Exception as e_asset_proc:
-                logger.error(f"MAJOR Error processing asset for Scene {scene_num} ({asset_path}): {e_asset_proc}", exc_info=True)
-                # Ensure clip is closed if it was partially created
+                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()
+                elif current_scene_clip and hasattr(current_scene_clip, 'close'): current_scene_clip.close()
 
-        if not processed_moviepy_clips: logger.warning("No MoviePy clips were successfully processed. Aborting animatic assembly."); return None
+        if not processed_moviepy_clips: logger.warning("No clips processed. Aborting."); return None
         
         transition_duration = 0.75
         try:
-            if not processed_moviepy_clips: logger.error("No clips to concatenate after processing loop."); return None
-            logger.info(f"Concatenating {len(processed_moviepy_clips)} processed 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")
+            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 resulted in a None clip."); return None
+            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:
-                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)
-                elif final_composite_clip_obj.duration > 0:
-                    final_composite_clip_obj = final_composite_clip_obj.fx(vfx.fadein, min(transition_duration, final_composite_clip_obj.duration/2.0))
-                logger.debug("Applied fade in/out effects.")
+            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)
-                    logger.info(f"Adding narration. Video dur: {final_composite_clip_obj.duration:.2f}s, Audio dur: {narration_audio_clip.duration:.2f}s")
-                    final_composite_clip_obj = final_composite_clip_obj.set_audio(narration_audio_clip) # Audio will be cut/padded to video duration
-                    logger.info("Overall narration added to video.")
-                except Exception as e_audio: logger.error(f"Error adding overall narration: {e_audio}", exc_info=True)
+                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"Attempting to write final animatic: {output_path} (Duration: {final_composite_clip_obj.duration:.2f}s)")
-                moviepy_logger_setting = 'bar' # Default to progress bar
-
+                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', audio_codec='aac',
+                    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=moviepy_logger_setting, bitrate="5000k"
+                    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"Animatic video successfully created: {output_path}")
-                return output_path
-            else: logger.error("Final animatic clip is invalid or has zero duration. Cannot write file."); return None
-        except Exception as e_write: logger.error(f"Error during video file writing or final composition: {e_write}", exc_info=True); return None
+                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
         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 [])