Update core/visual_engine.py

core/visual_engine.py

@@ -1,11 +1,32 @@
 # core/visual_engine.py
-# ... (imports remain the same as the last full version) ...
-from PIL import Image, ImageDraw, ImageFont, ImageOps 
+from PIL import Image, ImageDraw, ImageFont, ImageOps # Pillow should be >= 10.1.0
+# --- MONKEY PATCH FOR Image.ANTIALIAS ---
+# This is applied at module load time.
+try:
+    if hasattr(Image, 'Resampling') and hasattr(Image.Resampling, 'LANCZOS'): # Pillow 9+
+        if not hasattr(Image, 'ANTIALIAS'):
+            Image.ANTIALIAS = Image.Resampling.LANCZOS
+            print("INFO: Monkey-patched PIL.Image.ANTIALIAS with Image.Resampling.LANCZOS.")
+    elif hasattr(Image, 'LANCZOS'): # Pillow 8 used Image.LANCZOS directly
+         if not hasattr(Image, 'ANTIALIAS'):
+            Image.ANTIALIAS = Image.LANCZOS
+            print("INFO: Monkey-patched PIL.Image.ANTIALIAS with Image.LANCZOS.")
+except AttributeError:
+    print("WARNING: Could not determine Pillow version or attributes for ANTIALIAS monkey-patch. Video effects might fail.")
+# --- END MONKEY PATCH ---
+
 from moviepy.editor import (ImageClip, concatenate_videoclips, TextClip, 
                             CompositeVideoClip, AudioFileClip)
 import moviepy.video.fx.all as vfx 
 import numpy as np
-import os, openai, requests, io, time, random, subprocess, logging
+import os
+import openai
+import requests
+import io
+import time
+import random 
+import subprocess 
+import logging
 
 logger = logging.getLogger(__name__)
 logger.setLevel(logging.INFO)
@@ -22,208 +43,229 @@ except Exception as e: logger.warning(f"General ElevenLabs import error: {e}. Au
 
 
 class VisualEngine:
-    def __init__(self, output_dir="temp_cinegen_media", default_elevenlabs_voice_id="Rachel"): # Added default
+    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)
-        # ... (font setup, OpenAI, Pexels init - same as previous) ...
-        self.font_filename="arial.ttf"; self.font_path_in_container=f"/usr/local/share/fonts/truetype/mycustomfonts/{self.font_filename}"
-        self.font_size_pil=20; self.video_overlay_font_size=30; self.video_overlay_font_color='white'; self.video_overlay_font='Liberation-Sans-Bold'
-        try: self.font = ImageFont.truetype(self.font_path_in_container, self.font_size_pil); # logger.info(f"Placeholder font: {self.font_path_in_container}.")
+        self.font_filename = "arial.ttf"; self.font_path_in_container = f"/usr/local/share/fonts/truetype/mycustomfonts/{self.font_filename}"
+        self.font_size_pil = 20; self.video_overlay_font_size = 30; self.video_overlay_font_color = 'white'; self.video_overlay_font = 'Liberation-Sans-Bold' # Or 'Arial-Bold'
+        try: self.font = ImageFont.truetype(self.font_path_in_container, self.font_size_pil); logger.info(f"Placeholder font loaded: {self.font_path_in_container}.")
         except IOError: logger.warning(f"Placeholder font '{self.font_path_in_container}' fail. 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 # Use passed default or "Rachel"
+        self.dalle_model = "dall-e-3"; self.image_size_dalle3 = "1792x1024"; self.video_frame_size = (1280, 720) 
+        self.elevenlabs_api_key = None; self.USE_ELEVENLABS = False; self.elevenlabs_client = None 
+        self.elevenlabs_voice_id = default_elevenlabs_voice_id
         if VoiceSettings and ELEVENLABS_CLIENT_IMPORTED: 
             self.elevenlabs_voice_settings = VoiceSettings(stability=0.60, similarity_boost=0.80, style=0.15, use_speaker_boost=True)
         else: self.elevenlabs_voice_settings = None
         self.pexels_api_key = None; self.USE_PEXELS = False
         logger.info("VisualEngine initialized.")
 
-    def set_openai_api_key(self,k): # Same
-        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): # Modified to accept voice_id
+    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: # Prioritize voice ID from secret if provided
-            self.elevenlabs_voice_id = voice_id_from_secret
-            logger.info(f"ElevenLabs Voice ID set from secret/config: {self.elevenlabs_voice_id}")
-        
+        if voice_id_from_secret: self.elevenlabs_voice_id = voice_id_from_secret; logger.info(f"ElevenLabs Voice ID set from config: {self.elevenlabs_voice_id}")
         if api_key and ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient: 
             try: 
                 self.elevenlabs_client = ElevenLabsAPIClient(api_key=api_key) 
                 if self.elevenlabs_client: self.USE_ELEVENLABS=True; logger.info(f"ElevenLabs Client Ready (Voice: {self.elevenlabs_voice_id}).")
                 else: self.USE_ELEVENLABS=False; logger.warning("ElevenLabs client is None post-init.")
-            except Exception as e: 
-                logger.error(f"Error initializing ElevenLabs client: {e}. Disabled.", exc_info=True); 
-                self.USE_ELEVENLABS=False; self.elevenlabs_client = None
-        else: 
-            self.USE_ELEVENLABS=False; self.elevenlabs_client = None
-            if not (ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient):pass 
-            else: logger.info("ElevenLabs API Key not provided. Disabled.")
-            
-    def set_pexels_api_key(self,k): # Same
-        self.pexels_api_key=k; self.USE_PEXELS=bool(k)
-        logger.info(f"Pexels Search {'Ready.' if k else 'Disabled.'}")
+            except Exception as e: logger.error(f"Error initializing ElevenLabs client: {e}. Disabled.", exc_info=True); self.USE_ELEVENLABS=False; self.elevenlabs_client = None
+        else: self.USE_ELEVENLABS=False; self.elevenlabs_client = None; 
+              
+    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.'}")
     
-    # _get_text_dimensions, _create_placeholder_image_content, _search_pexels_image, generate_image_visual
-    # remain the same as the last full version.
-    def _get_text_dimensions(self,t,f): # Same
-        if not t: return 0,self.font_size_pil 
+    def _get_text_dimensions(self,text_content,font_obj): # Same
+        if not text_content: return 0,self.font_size_pil 
         try:
-            if hasattr(f,'getbbox'): bb=f.getbbox(t);w=bb[2]-bb[0];h=bb[3]-bb[1];return w, h if h > 0 else self.font_size_pil
-            elif hasattr(f,'getsize'): w,h=f.getsize(t);return w, h if h > 0 else self.font_size_pil
-            else: return int(len(t)*self.font_size_pil*0.6),int(self.font_size_pil*1.2 if self.font_size_pil*1.2>0 else self.font_size_pil)
-        except: return int(len(t)*self.font_size_pil*0.6),int(self.font_size_pil*1.2)
+            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 self.font_size_pil
+            elif hasattr(font_obj,'getsize'): w,h=font_obj.getsize(text_content);return w, h if h > 0 else self.font_size_pil
+            else: return int(len(text_content)*self.font_size_pil*0.6),int(self.font_size_pil*1.2 if self.font_size_pil*1.2>0 else self.font_size_pil)
+        except: return int(len(text_content)*self.font_size_pil*0.6),int(self.font_size_pil*1.2)
     
-    def _create_placeholder_image_content(self,td,fn,s=None): # Same
-        if s is None: s = self.video_frame_size
-        img=Image.new('RGB',s,color=(20,20,40));d=ImageDraw.Draw(img);p=25;max_w=s[0]-(2*p);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] <= max_w: cl=tl
+    def _create_placeholder_image_content(self,text_description,filename,size=None): # Same
+        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
             else:
-                if cl: ls.append(cl.strip()); cl=w+" "
-        if cl: ls.append(cl.strip())
-        if not ls: ls.append("(Text error or too long for placeholder)")
+                if current_line: lines.append(current_line.strip()); current_line=word+" "
+        if current_line: lines.append(current_line.strip())
+        if not lines: lines.append("(Text error or too long for placeholder)")
         _,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_ls=min(len(ls),(s[1]-(2*p))//(single_line_h+2))
-        yt=p + (s[1]-(2*p) - max_ls*(single_line_h+2))/2.0
-        for i in range(max_ls):
-            line=ls[i];line_w,_=self._get_text_dimensions(line,self.font);xt=(s[0]-line_w)/2.0
-            d.text((xt,yt),line,font=self.font,fill=(200,200,180));yt+=single_line_h+2
-            if i==6 and max_ls > 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
+        max_lines_to_display=min(len(lines),(size[1]-(2*padding))//(single_line_h+2))
+        y_text=padding + (size[1]-(2*padding) - max_lines_to_display*(single_line_h+2))/2.0
+        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): # Same
         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": "large"}
         pexels_filename = output_filename_base.replace(".png", f"_pexels_{random.randint(1000,9999)}.jpg")
-        fp = os.path.join(self.output_dir, pexels_filename)
+        filepath = os.path.join(self.output_dir, pexels_filename)
         try:
-            logger.info(f"Searching Pexels for: '{query}'"); eff_q = " ".join(query.split()[:5]); params["query"] = eff_q
-            r = requests.get("https://api.pexels.com/v1/search", headers=headers, params=params, timeout=20)
-            r.raise_for_status(); data = r.json()
+            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:
-                url = data["photos"][0]["src"]["large2x"] 
-                img_r = requests.get(url, timeout=60); img_r.raise_for_status()
-                img_d = Image.open(io.BytesIO(img_r.content))
-                if img_d.mode != 'RGB': img_d = img_d.convert('RGB')
-                img_d.save(fp); logger.info(f"Pexels image saved: {fp}"); return fp
-            else: logger.info(f"No photos on Pexels for: '{eff_q}'")
-        except Exception as e: logger.error(f"Pexels error for '{query}': {e}", exc_info=True)
+                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 on Pexels for query: '{effective_query}'")
+        except Exception as e: logger.error(f"Pexels search/download for query '{query}': {e}", exc_info=True)
         return None
 
     def generate_image_visual(self, image_prompt_text, scene_data, scene_identifier_filename): # Same
-        fp = os.path.join(self.output_dir, scene_identifier_filename)
+        filepath = os.path.join(self.output_dir, scene_identifier_filename)
         if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
-            retries = 2
-            for attempt in range(retries):
+            max_retries = 2
+            for attempt in range(max_retries):
                 try:
                     logger.info(f"Attempt {attempt+1}: DALL-E ({self.dalle_model}) for: {image_prompt_text[:100]}...")
                     client = openai.OpenAI(api_key=self.openai_api_key, timeout=90.0) 
-                    resp = 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")
-                    img_url = resp.data[0].url; rev_prompt = getattr(resp.data[0], 'revised_prompt', None)
-                    if rev_prompt: logger.info(f"DALL-E 3 revised_prompt: {rev_prompt[:100]}...")
-                    img_resp = requests.get(img_url, timeout=120); img_resp.raise_for_status()
-                    img_d = Image.open(io.BytesIO(img_resp.content)); 
-                    if img_d.mode != 'RGB': img_d = img_d.convert('RGB')
-                    img_d.save(fp); logger.info(f"AI Image (DALL-E) saved: {fp}"); return fp 
+                    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}"); return filepath 
                 except openai.RateLimitError as e: 
                     logger.warning(f"OpenAI Rate Limit: {e}. Retrying after {5*(attempt+1)}s..."); time.sleep(5 * (attempt + 1))
-                    if attempt == retries - 1: logger.error("Max retries for RateLimitError."); break
+                    if attempt == max_retries - 1: logger.error("Max retries for RateLimitError."); break
                     else: continue
                 except openai.APIError as e: logger.error(f"OpenAI API Error: {e}"); break 
                 except requests.exceptions.RequestException as e: logger.error(f"Requests Error (DALL-E download): {e}"); break
                 except Exception as e: logger.error(f"Generic error (DALL-E gen): {e}", exc_info=True); break
-            logger.warning("DALL-E failed. Trying Pexels fallback...")
-            pexels_q_text = scene_data.get('pexels_search_query_감독', f"{scene_data.get('emotional_beat','')} {scene_data.get('setting_description','')}")
-            pexels_p = self._search_pexels_image(pexels_q_text, scene_identifier_filename)
-            if pexels_p: return pexels_p
+            logger.warning("DALL-E generation failed. Trying Pexels fallback...")
+            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, scene_identifier_filename)
+            if pexels_path: return pexels_path
             logger.warning("Pexels also failed/disabled. Using placeholder.")
             return self._create_placeholder_image_content(f"[AI/Pexels Failed] {image_prompt_text[:100]}...", scene_identifier_filename)
         else: 
             return self._create_placeholder_image_content(image_prompt_text, scene_identifier_filename)
 
-    def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"): # Uses self.elevenlabs_voice_id
+    def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"): # Corrected client call
         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)
         try:
-            # self.elevenlabs_voice_id is now set during set_elevenlabs_api_key or by UI
             logger.info(f"Generating ElevenLabs audio (Voice ID: {self.elevenlabs_voice_id}) for: {text_to_narrate[:70]}...")
             
+            # Use the client's text_to_speech.stream() method
             if hasattr(self.elevenlabs_client, 'text_to_speech') and hasattr(self.elevenlabs_client.text_to_speech, 'stream'):
                 logger.info("Using elevenlabs_client.text_to_speech.stream()")
                 audio_data_iterator = self.elevenlabs_client.text_to_speech.stream(
                     text=text_to_narrate,
-                    voice_id=str(self.elevenlabs_voice_id), # Ensure voice_id is a string
+                    voice_id=str(self.elevenlabs_voice_id), # Must be string ID for this method
                     model_id="eleven_multilingual_v2", 
+                    # voice_settings=self.elevenlabs_voice_settings # Pass VoiceSettings if API supports it here
                 )
-            elif hasattr(self.elevenlabs_client, 'generate') and Voice: # Fallback, ensure Voice is imported
-                 logger.info("Using elevenlabs_client.generate() with Voice object.")
-                 voice_param = Voice(voice_id=str(self.elevenlabs_voice_id), settings=self.elevenlabs_voice_settings if self.elevenlabs_voice_settings else None)
+            # Fallback if .generate() with Voice object is preferred by a slightly different client version
+            elif hasattr(self.elevenlabs_client, 'generate') and Voice and self.elevenlabs_voice_settings:
+                 logger.info("Using elevenlabs_client.generate() with Voice object as fallback.")
+                 voice_param = Voice(voice_id=str(self.elevenlabs_voice_id), settings=self.elevenlabs_voice_settings)
                  audio_data_iterator = self.elevenlabs_client.generate(
                     text=text_to_narrate, voice=voice_param, model="eleven_multilingual_v2")
             else:
-                logger.error("No recognized audio generation method on ElevenLabs client."); return None
+                logger.error("No recognized audio generation method found on ElevenLabs client (tried text_to_speech.stream and generate).")
+                return None
             
             with open(audio_filepath, "wb") as f:
                 for chunk in audio_data_iterator: 
                     if chunk: f.write(chunk)
             logger.info(f"ElevenLabs audio saved: {audio_filepath}")
             return audio_filepath
-        except AttributeError as ae: logger.error(f"AttributeError with ElevenLabs client: {ae}.", exc_info=True)
-        except Exception as e: logger.error(f"Error generating ElevenLabs audio: {e}", exc_info=True)
+        except AttributeError as ae:
+             logger.error(f"AttributeError with ElevenLabs client: {ae}. SDK method/structure might be different.", exc_info=True)
+        except Exception as e:
+            logger.error(f"Error generating ElevenLabs audio: {e}", exc_info=True)
         return None
 
-    def create_video_from_images(self, image_data_list, overall_narration_path=None, output_filename="final_video.mp4", fps=24, duration_per_image=4.5): # Same as previous
+    def create_video_from_images(self, image_data_list, overall_narration_path=None, output_filename="final_video.mp4", fps=24, duration_per_image=4.5):
         if not image_data_list: logger.warning("No image data for video."); return None
         processed_clips=[]; narration_audio_clip=None; final_video_clip_obj=None
         logger.info(f"Preparing {len(image_data_list)} clips. Target frame: {self.video_frame_size}. Duration/img: {duration_per_image}s.")
+
         for i, data in enumerate(image_data_list):
             img_path, scene_num, key_action = data.get('path'), data.get('scene_num', i+1), data.get('key_action', '')
             if not (img_path and os.path.exists(img_path)): logger.warning(f"Img not found: {img_path}"); continue
             try:
-                pil_img = Image.open(img_path); 
+                pil_img = Image.open(img_path)
                 if pil_img.mode != 'RGB': pil_img = pil_img.convert('RGB')
-                img_copy = pil_img.copy(); img_copy.thumbnail(self.video_frame_size, Image.Resampling.LANCZOS) 
+                
+                img_copy = pil_img.copy()
+                # Using modern Resampling.LANCZOS
+                img_copy.thumbnail(self.video_frame_size, Image.Resampling.LANCZOS) 
+                
                 canvas = Image.new('RGB', self.video_frame_size, (random.randint(0,5), random.randint(0,5), random.randint(0,5))) 
-                xo,yo=(self.video_frame_size[0]-img_copy.width)//2, (self.video_frame_size[1]-img_copy.height)//2
-                canvas.paste(img_copy, (xo,yo)); frame_np = np.array(canvas)
+                xo, yo = (self.video_frame_size[0]-img_copy.width)//2, (self.video_frame_size[1]-img_copy.height)//2
+                canvas.paste(img_copy, (xo,yo))
+                frame_np = np.array(canvas)
+                
                 img_clip_base = ImageClip(frame_np).set_duration(duration_per_image)
-                # img_clip = img_clip_base # Test: No Ken Burns if ANTIALIAS error persists
-                end_scale = random.uniform(1.03, 1.08); img_clip = img_clip_base.fx(vfx.resize, lambda t: 1+(end_scale-1)*(t/duration_per_image)); img_clip = img_clip.set_position('center')
+
+                # Ken Burns Effect (vfx.resize) - THIS IS THE LINE THAT CAUSED ANTIALIAS ERROR
+                # If ANTIALIAS error persists even with monkey patch and correct Pillow/MoviePy versions,
+                # this specific effect might need to be disabled or re-implemented differently.
+                # For now, we assume the monkey patch or correct versions will fix it.
+                try:
+                    end_scale = random.uniform(1.03, 1.08)
+                    img_clip = img_clip_base.fx(vfx.resize, lambda t: 1 + (end_scale - 1) * (t / duration_per_image))
+                    img_clip = img_clip.set_position('center')
+                except AttributeError as e_alias: # Specifically catch ANTIALIAS here if it happens
+                    if 'ANTIALIAS' in str(e_alias):
+                        logger.error(f"ANTIALIAS error during vfx.resize for {img_path}. Disabling Ken Burns for this clip. Error: {e_alias}")
+                        img_clip = img_clip_base # Use the clip without the resize effect
+                    else:
+                        raise # Re-raise other AttributeErrors
+                except Exception as e_fx: # Catch other errors from fx
+                    logger.error(f"Error applying vfx.resize for {img_path}. Using base clip. Error: {e_fx}")
+                    img_clip = img_clip_base
+
+
                 if key_action:
-                    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(10,10,20,0.8)', method='caption', align='West', size=(self.video_frame_size[0]*0.9, None), kerning=-1, stroke_color='black', stroke_width=1.5
+                    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(10,10,20,0.8)', method='caption', align='West',
+                                        size=(self.video_frame_size[0]*0.9, None), kerning=-1, stroke_color='black', stroke_width=1.5
                                        ).set_duration(duration_per_image-1.0).set_start(0.5).set_position(('center',0.92),relative=True)
                     final_scene_clip = CompositeVideoClip([img_clip, txt_clip], size=self.video_frame_size, use_bgclip=True, bg_color=(0,0,0))
                 else: final_scene_clip = img_clip
                 processed_clips.append(final_scene_clip)
             except Exception as e: logger.error(f"Creating video clip for {img_path}: {e}", exc_info=True)
+        
         if not processed_clips: logger.warning("No clips processed for video."); return None
+        
         transition = 0.75 
         try:
             final_video_clip_obj = concatenate_videoclips(processed_clips, padding=-transition, method="compose")
-            if final_video_clip_obj.duration > transition*2: final_video_clip_obj = final_video_clip_obj.fx(vfx.fadein, transition).fx(vfx.fadeout, transition)
+            if final_video_clip_obj.duration > transition*2: 
+                final_video_clip_obj = final_video_clip_obj.fx(vfx.fadein, transition).fx(vfx.fadeout, transition)
+            
             if overall_narration_path and os.path.exists(overall_narration_path):
                 try:
                     narration_audio_clip = AudioFileClip(overall_narration_path)
-                    if narration_audio_clip.duration < final_video_clip_obj.duration: final_video_clip_obj = final_video_clip_obj.subclip(0, narration_audio_clip.duration)
+                    if narration_audio_clip.duration < final_video_clip_obj.duration:
+                        final_video_clip_obj = final_video_clip_obj.subclip(0, narration_audio_clip.duration)
                     final_video_clip_obj = final_video_clip_obj.set_audio(narration_audio_clip); logger.info("Overall narration added.")
                 except Exception as e: logger.error(f"Adding overall narration: {e}", exc_info=True)
+            
             output_path = os.path.join(self.output_dir, output_filename); logger.info(f"Writing final video to: {output_path}")
-            final_video_clip_obj.write_videofile(output_path, fps=fps, codec='libx264', preset='medium', audio_codec='aac',
+            final_video_clip_obj.write_videofile(output_path, 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")
             logger.info(f"Video successfully created: {output_path}"); return output_path