app.py

# core/visual_engine.py
from PIL import Image, ImageDraw, ImageFont, ImageOps
# --- MONKEY PATCH FOR Image.ANTIALIAS ---
try:
    if hasattr(Image, 'Resampling') and hasattr(Image.Resampling, 'LANCZOS'): # Pillow 9+
        if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.Resampling.LANCZOS
    elif hasattr(Image, 'LANCZOS'): # Pillow 8
         if not hasattr(Image, 'ANTIALIAS'): Image.ANTIALIAS = Image.LANCZOS
    elif not hasattr(Image, 'ANTIALIAS'):
             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 ---

from moviepy.editor import (ImageClip, VideoFileClip, concatenate_videoclips, TextClip,
                            CompositeVideoClip, AudioFileClip)
import moviepy.video.fx.all as vfx
import numpy as np
import os
import openai
import requests
import io
import time
import random
import logging

logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)

# --- ElevenLabs Client Import ---
ELEVENLABS_CLIENT_IMPORTED = False; ElevenLabsAPIClient = None; Voice = None; VoiceSettings = None
try:
    from elevenlabs.client import ElevenLabs as ImportedElevenLabsClient
    from elevenlabs import Voice as ImportedVoice, VoiceSettings as ImportedVoiceSettings
    ElevenLabsAPIClient = ImportedElevenLabsClient; Voice = ImportedVoice; VoiceSettings = ImportedVoiceSettings
    ELEVENLABS_CLIENT_IMPORTED = True; logger.info("ElevenLabs client components imported.")
except Exception as e_eleven: logger.warning(f"ElevenLabs client import failed: {e_eleven}. Audio disabled.")

# --- RunwayML Client Import (Placeholder) ---
RUNWAYML_SDK_IMPORTED = False; RunwayMLClient = None
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.")


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"
        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"
        ]
        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'

        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 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
        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:
            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_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 _get_text_dimensions(self, text_content, font_obj):
        default_line_height = getattr(font_obj, 'size', self.font_size_pil)
        if not text_content: return 0, default_line_height
        try:
            if hasattr(font_obj, 'getbbox'):
                bbox = font_obj.getbbox(text_content); width = bbox[2] - bbox[0]; height = bbox[3] - bbox[1]
                return width, height if height > 0 else default_line_height
            elif hasattr(font_obj, 'getsize'):
                width, height = font_obj.getsize(text_content)
                return width, height if height > 0 else default_line_height
            else: return int(len(text_content) * default_line_height * 0.6), int(default_line_height * 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)); draw = ImageDraw.Draw(img)
        padding = 25; max_text_width = size[0] - (2 * padding); lines = []
        if not text_description: text_description = "(Placeholder: No text description provided)"
        words = text_description.split(); current_line = ""
        for word in words:
            test_line = current_line + word + " "; line_width_test, _ = self._get_text_dimensions(test_line.strip(), self.font)
            if line_width_test <= max_text_width: current_line = test_line
            else:
                if current_line.strip(): lines.append(current_line.strip())
                word_width, _ = self._get_text_dimensions(word, self.font)
                if word_width > max_text_width:
                    avg_char_w = self._get_text_dimensions("A", self.font)[0] or 10
                    chars_that_fit = int(max_text_width / avg_char_w)
                    lines.append(word[:chars_that_fit-3] + "..." if len(word) > chars_that_fit else word) # Corrected line
                    current_line = ""
                else: current_line = word + " "
        if current_line.strip(): lines.append(current_line.strip())
        if not lines and text_description:
            avg_char_w = self._get_text_dimensions("A", self.font)[0] or 10; chars_that_fit = int(max_text_width / avg_char_w)
            lines.append(text_description[:chars_that_fit-3] + "..." if len(text_description) > chars_that_fit else text_description)
        elif not lines: lines.append("(Placeholder Text Error)")
        _, single_line_height = self._get_text_dimensions("Ay", self.font); single_line_height = single_line_height if single_line_height > 0 else (self.font_size_pil + 2)
        line_spacing = 2; max_lines_to_display = min(len(lines), (size[1]-(2*padding))//(single_line_height+line_spacing)) if single_line_height > 0 else 1
        if max_lines_to_display <= 0: max_lines_to_display = 1
        total_text_block_height = max_lines_to_display * single_line_height + (max_lines_to_display-1)*line_spacing
        y_text_start = padding + (size[1]-(2*padding)-total_text_block_height)/2.0; current_y = y_text_start
        for i in range(max_lines_to_display):
            line_content = lines[i]; line_width_actual, _ = self._get_text_dimensions(line_content, self.font)
            x_text = max(padding, (size[0]-line_width_actual)/2.0)
            draw.text((x_text, current_y), line_content, font=self.font, fill=(200,200,180)); current_y += single_line_height + line_spacing
            if i==6 and max_lines_to_display > 7 and len(lines) > max_lines_to_display:
                ellipsis_width, _ = self._get_text_dimensions("...",self.font); x_ellipsis = max(padding, (size[0]-ellipsis_width)/2.0)
                draw.text((x_ellipsis, current_y), "...", 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"Error saving placeholder image {filepath}: {e}", exc_info=True); return None

    def _search_pexels_image(self, query, output_filename_base):
        if not self.USE_PEXELS or not self.pexels_api_key: return None
        headers = {"Authorization": self.pexels_api_key}
        params = {"query": query, "per_page": 1, "orientation": "landscape", "size": "large2x"}
        base_name, _ = os.path.splitext(output_filename_base)
        pexels_filename = base_name + f"_pexels_{random.randint(1000,9999)}.jpg" # Use base_name
        filepath = os.path.join(self.output_dir, pexels_filename)
        try:
            logger.info(f"Pexels search: '{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() # This line and subsequent ones are now correctly in the try block
            if data.get("photos") and len(data["photos"]) > 0:
                photo_details = data["photos"][0]
                photo_url = photo_details["src"]["large2x"]
                logger.info(f"Downloading Pexels image from: {photo_url}")
                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':
                    logger.debug(f"Pexels image mode is {img_data.mode}, converting to RGB.")
                    img_data = img_data.convert('RGB')
                img_data.save(filepath)
                logger.info(f"Pexels image saved successfully: {filepath}")
                return filepath
            else:
                logger.info(f"No photos found on Pexels for query: '{effective_query}'")
                return None
        except requests.exceptions.RequestException as e_req: logger.error(f"Pexels request error for query '{query}': {e_req}", exc_info=True)
        except json.JSONDecodeError as e_json: logger.error(f"Pexels JSON decode error for query '{query}': {e_json}", exc_info=True)
        except Exception as e: logger.error(f"General Pexels error for query '{query}': {e}", exc_info=True)
        return None

    def _generate_video_clip_with_runwayml(self, pt, iip, sifnb, tds=5): # Renamed for clarity
        if not self.USE_RUNWAYML or not self.runway_api_key: logger.warning("RunwayML disabled."); return None
        if not iip or not os.path.exists(iip): logger.error(f"Runway Gen-4 needs input image. Path invalid: {iip}"); return None
        runway_dur = 10 if tds > 7 else 5
        ovfn = sifnb.replace(".png", f"_runway_gen4_d{runway_dur}s.mp4") # sifnb should be base name
        ovfp = os.path.join(self.output_dir, ovfn)
        logger.info(f"Runway Gen-4 (Placeholder) img: {os.path.basename(iip)}, motion: '{pt[:100]}...', dur: {runway_dur}s")
        logger.warning("Using PLACEHOLDER video for Runway Gen-4.")
        img_clip=None; txt_c=None; final_ph_clip=None
        try:
            img_clip = ImageClip(iip).set_duration(runway_dur)
            txt = f"Runway Gen-4 Placeholder\nInput: {os.path.basename(iip)}\nMotion: {pt[:50]}..."
            txt_c = TextClip(txt, fontsize=24,color='white',font=self.video_overlay_font,bg_color='rgba(0,0,0,0.5)',size=(self.video_frame_size[0]*0.8,None),method='caption').set_duration(runway_dur).set_position('center')
            final_ph_clip = CompositeVideoClip([img_clip, txt_c], size=img_clip.size)
            final_ph_clip.write_videofile(ovfp,fps=24,codec='libx264',preset='ultrafast',logger=None,threads=2)
            logger.info(f"Runway Gen-4 placeholder video: {ovfp}"); return ovfp
        except Exception as e: logger.error(f"Runway Gen-4 placeholder error: {e}",exc_info=True); return None
        finally:
            if img_clip and hasattr(img_clip,'close'): img_clip.close()
            if txt_c and hasattr(txt_c,'close'): txt_c.close()
            if final_ph_clip and hasattr(final_ph_clip,'close'): final_ph_clip.close()

    def _create_placeholder_video_content(self, td, fn, dur=4, sz=None):
        if sz is None: sz = self.video_frame_size; fp = os.path.join(self.output_dir, fn); tc = None
        try: tc = TextClip(td, fontsize=50,color='white',font=self.video_overlay_font,bg_color='black',size=sz,method='caption').set_duration(dur)
        tc.write_videofile(fp,fps=24,codec='libx264',preset='ultrafast',logger=None,threads=2); logger.info(f"Generic placeholder video: {fp}"); return fp
        except Exception as e: logger.error(f"Generic placeholder error {fp}: {e}",exc_info=True); return None
        finally:
            if tc and hasattr(tc,'close'): tc.close()

    def generate_scene_asset(self, image_generation_prompt_text, motion_prompt_text_for_video,
                             scene_data, scene_identifier_filename_base, # This is base_name, no ext
                             generate_as_video_clip=False, runway_target_duration=5):
        base_name = scene_identifier_filename_base # Already a base name
        asset_info = {'path': None, 'type': 'none', 'error': True, 'prompt_used': image_generation_prompt_text, 'error_message': 'Generation not attempted'}
        input_image_for_runway_path = None
        image_filename_for_base = base_name + "_base_image.png" # Specific name for base image file
        temp_image_asset_info = {'error': True, 'prompt_used': image_generation_prompt_text, 'error_message': 'Base image generation not attempted'}

        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:
                    img_fp_dalle = os.path.join(self.output_dir, image_filename_for_base)
                    logger.info(f"Attempt {att_n+1} DALL-E (base img): {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_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_img = Image.open(io.BytesIO(ir.content));
                    if id_img.mode != 'RGB': id_img = id_img.convert('RGB')
                    id_img.save(img_fp_dalle); logger.info(f"DALL-E base image: {img_fp_dalle}");
                    input_image_for_runway_path = img_fp_dalle
                    temp_image_asset_info = {'path': img_fp_dalle, 'type': 'image', 'error': False, 'prompt_used': image_generation_prompt_text, 'revised_prompt': rp}
                    break
                except openai.RateLimitError as e: logger.warning(f"OpenAI Rate Limit {att_n+1}: {e}. Retry..."); time.sleep(5*(att_n+1)); temp_image_asset_info['error_message']=str(e)
                except Exception as e: logger.error(f"DALL-E error: {e}", exc_info=True); temp_image_asset_info['error_message']=str(e); break
            if temp_image_asset_info['error']: logger.warning(f"DALL-E failed after {att_n+1} attempts for base image.")
        
        if temp_image_asset_info['error'] and self.USE_PEXELS:
            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_for_base) # Use base name for pexels
            if pp: input_image_for_runway_path = pp; temp_image_asset_info = {'path': pp, 'type': 'image', 'error': False, 'prompt_used': f"Pexels: {pqt}"}
            else: current_em = temp_image_asset_info.get('error_message',""); temp_image_asset_info['error_message']=(current_em + " Pexels failed.").strip()

        if temp_image_asset_info['error']:
            logger.warning("Base image (DALL-E/Pexels) failed. Placeholder base image.")
            ppt = temp_image_asset_info.get('prompt_used', image_generation_prompt_text)
            php = self._create_placeholder_image_content(f"[Base Img Placeholder] {ppt[:100]}...", image_filename_for_base)
            if php: input_image_for_runway_path = php; temp_image_asset_info = {'path': php, 'type': 'image', 'error': False, 'prompt_used': ppt}
            else: current_em=temp_image_asset_info.get('error_message',"");temp_image_asset_info['error_message']=(current_em + " Base placeholder failed.").strip()
        
        if generate_as_video_clip:
            if self.USE_RUNWAYML and input_image_for_runway_path:
                video_path = self._generate_video_clip_with_runwayml(motion_prompt_text_for_video, input_image_for_runway_path, base_name, runway_target_duration) # Pass base_name
                if video_path and os.path.exists(video_path):
                    return {'path': video_path, 'type': 'video', 'error': False, 'prompt_used': motion_prompt_text_for_video, 'base_image_path': input_image_for_runway_path}
                else: asset_info = temp_image_asset_info; asset_info['error'] = True; asset_info['error_message'] = "RunwayML video gen failed; using base image."; asset_info['type'] = 'image'; return asset_info
            elif not self.USE_RUNWAYML: asset_info = temp_image_asset_info; asset_info['error_message'] = "RunwayML disabled; using base image."; asset_info['type'] = 'image'; return asset_info
            else: asset_info = temp_image_asset_info; asset_info['error_message'] = (asset_info.get('error_message',"") + " Base image failed, Runway video not attempted.").strip(); asset_info['type'] = 'image'; return asset_info
        else: return temp_image_asset_info

    def generate_narration_audio(self, ttn, ofn="narration_overall.mp3"):
        if not self.USE_ELEVENLABS or not self.elevenlabs_client or not ttn: logger.info("11L skip."); return None; afp=os.path.join(self.output_dir,ofn)
        try: logger.info(f"11L audio (Voice:{self.elevenlabs_voice_id}): {ttn[: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=ttn,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=ttn,model_id="eleven_multilingual_v2",**vps)
        with open(afp,"wb")as f:
            for c in adi:
                if c:f.write(c)
        logger.info(f"11L audio (stream): {afp}");return afp
        except Exception as e:logger.error(f"11L audio error: {e}",exc_info=True);return None

    def assemble_animatic_from_assets(self, asset_data_list, overall_narration_path=None, output_filename="final_video.mp4", fps=24):
        if not asset_data_list: logger.warning("No assets for animatic."); return None
        processed_clips = []; narration_clip = None; final_clip = None
        logger.info(f"Assembling from {len(asset_data_list)} assets. Frame: {self.video_frame_size}.")

        for i, asset_info in enumerate(asset_data_list):
            asset_path, asset_type, scene_dur = asset_info.get('path'), asset_info.get('type'), asset_info.get('duration', 4.5)
            scene_num, key_action = asset_info.get('scene_num', i + 1), asset_info.get('key_action', '')
            logger.info(f"S{scene_num}: Path='{asset_path}', Type='{asset_type}', Dur='{scene_dur}'s")

            if not (asset_path and os.path.exists(asset_path)): logger.warning(f"S{scene_num}: Not found '{asset_path}'. Skip."); continue
            if scene_dur <= 0: logger.warning(f"S{scene_num}: Invalid duration ({scene_dur}s). Skip."); continue

            current_scene_mvpy_clip = None
            try:
                if asset_type == 'image':
                    pil_img = Image.open(asset_path); logger.debug(f"S{scene_num}: Loaded img. Mode:{pil_img.mode}, Size:{pil_img.size}")
                    img_rgba = pil_img.convert('RGBA') if pil_img.mode != 'RGBA' else pil_img.copy()
                    thumb = img_rgba.copy(); rf = Image.Resampling.LANCZOS if hasattr(Image.Resampling,'LANCZOS') else Image.BILINEAR; thumb.thumbnail(self.video_frame_size,rf)
                    cv_rgba = Image.new('RGBA',self.video_frame_size,(0,0,0,0)); xo,yo=(self.video_frame_size[0]-thumb.width)//2,(self.video_frame_size[1]-thumb.height)//2
                    cv_rgba.paste(thumb,(xo,yo),thumb)
                    final_rgb_pil = Image.new("RGB",self.video_frame_size,(0,0,0)); final_rgb_pil.paste(cv_rgba,mask=cv_rgba.split()[3])
                    dbg_path = os.path.join(self.output_dir,f"debug_PRE_NUMPY_S{scene_num}.png"); final_rgb_pil.save(dbg_path); logger.info(f"DEBUG: Saved PRE_NUMPY_S{scene_num} to {dbg_path}")
                    frame_np = np.array(final_rgb_pil,dtype=np.uint8);
                    if not frame_np.flags['C_CONTIGUOUS']: frame_np=np.ascontiguousarray(frame_np,dtype=np.uint8)
                    logger.debug(f"S{scene_num}: NumPy for MoviePy. Shape:{frame_np.shape}, DType:{frame_np.dtype}, C-Contig:{frame_np.flags['C_CONTIGUOUS']}")
                    if frame_np.size==0 or frame_np.ndim!=3 or frame_np.shape[2]!=3: logger.error(f"S{scene_num}: Invalid NumPy. Skip."); continue
                    clip_base = ImageClip(frame_np,transparent=False).set_duration(scene_dur)
                    mvpy_dbg_path=os.path.join(self.output_dir,f"debug_MOVIEPY_FRAME_S{scene_num}.png"); clip_base.save_frame(mvpy_dbg_path,t=0.1); logger.info(f"DEBUG: Saved MOVIEPY_FRAME_S{scene_num} to {mvpy_dbg_path}")
                    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':
                    src_clip=None
                    try:
                        src_clip=VideoFileClip(asset_path,target_resolution=(self.video_frame_size[1],self.video_frame_size[0])if self.video_frame_size else None, audio=False)
                        tmp_clip=src_clip
                        if src_clip.duration!=scene_dur:
                            if src_clip.duration>scene_dur:tmp_clip=src_clip.subclip(0,scene_dur)
                            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 src_clip and src_clip is not current_scene_mvpy_clip and hasattr(src_clip,'close'):src_clip.close()
                else: logger.warning(f"S{scene_num} Unknown asset type '{asset_type}'. Skip."); continue
                if current_scene_mvpy_clip and key_action:
                    try:
                        to_dur=min(current_scene_mvpy_clip.duration-0.5,current_scene_mvpy_clip.duration*0.8)if current_scene_mvpy_clip.duration>0.5 else current_scene_mvpy_clip.duration
                        to_start=0.25
                        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)
                    except Exception as e:logger.error(f"S{scene_num} TextClip error:{e}. No text.",exc_info=True)
                if current_scene_mvpy_clip:processed_clips.append(current_scene_mvpy_clip);logger.info(f"S{scene_num} Processed. Dur:{current_scene_mvpy_clip.duration:.2f}s.")
            except Exception as e:logger.error(f"MAJOR Error S{scene_num} ({asset_path}):{e}",exc_info=True)
            finally:
                if current_scene_mvpy_clip and hasattr(current_scene_mvpy_clip,'close'):
                    try: current_scene_mvpy_clip.close()
                    except: pass

        if not processed_clips:logger.warning("No clips processed. Abort.");return None
        td=0.75
        try:
            logger.info(f"Concatenating {len(processed_clips)} clips.");
            if len(processed_clips)>1:final_clip=concatenate_videoclips(processed_clips,padding=-td if td>0 else 0,method="compose")
            elif processed_clips:final_clip=processed_clips[0]
            if not final_clip:logger.error("Concatenation failed.");return None
            logger.info(f"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_clips + ([narration_clip] if narration_clip else []) + ([final_clip] if final_clip else [])
            for clip_obj in clips_to_close:
                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}")