core/visual_engine.py

# core/visual_engine.py
from PIL import Image, ImageDraw, ImageFont
from moviepy.editor import (ImageClip, 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 
from elevenlabs import generate as elevenlabs_generate_audio, set_api_key as elevenlabs_set_api_key_func

class VisualEngine:
    def __init__(self, output_dir="temp_cinegen_media"):
        self.output_dir = output_dir; os.makedirs(self.output_dir, exist_ok=True)
        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='Arial-Bold'
        try: self.font = ImageFont.truetype(self.font_path_in_container, self.font_size_pil); print(f"Placeholder font: {self.font_path_in_container}.")
        except IOError: print(f"Warn: 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_voice_id = "Rachel"
        self.pexels_api_key = None; self.USE_PEXELS = False

    def set_openai_api_key(self,k): 
        self.openai_api_key=k; self.USE_AI_IMAGE_GENERATION=bool(k)
        print(f"DALL-E ({self.dalle_model}) {'Ready' if k else 'Disabled'}.")
    def set_elevenlabs_api_key(self,k):
        self.elevenlabs_api_key=k
        if k: 
            try: elevenlabs_set_api_key_func(k); self.USE_ELEVENLABS=True; print("ElevenLabs Ready.")
            except Exception as e: print(f"ElevenLabs key set error: {e}. Disabled."); self.USE_ELEVENLABS=False
        else: self.USE_ELEVENLABS=False
    def set_pexels_api_key(self,k):
        self.pexels_api_key=k; self.USE_PEXELS=bool(k)
        print(f"Pexels {'Ready' if k else 'Disabled'}.")

    def _get_text_dimensions(self,t,f): 
        if not t: 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*.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*.6),int(self.font_size_pil*1.2)
    
    def _create_placeholder_image_content(self,td,fn,s=(1280,720)): 
        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)"
        ws=td.split();cl=""
        for w in ws:
            tl=cl+w+" ";
            if self._get_text_dimensions(tl,self.font)[0]<=max_w: cl=tl
            else:
                if cl:ls.append(cl.strip())
                cl=w+" "
        if cl:ls.append(cl.strip())
        if not ls:ls.append("(Text err)")
        _,sh=self._get_text_dimensions("Ay",self.font);sh=sh if sh>0 else self.font_size_pil+2
        max_ls=min(len(ls),(s[1]-2*p)//(sh+2));
        yt=p+(s[1]-2*p-max_ls*(sh+2))/2.0
        for i in range(max_ls):
            line=ls[i];lw,_=self._get_text_dimensions(line,self.font);xt=(s[0]-lw)/2.0
            d.text((xt,yt),line,font=self.font,fill=(200,200,180));yt+=sh+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:print(f"Err placeholder save: {e}");return None

    def _search_pexels_image(self, query, output_filename):
        if not self.USE_PEXELS or not self.pexels_api_key: return None
        headers = {"Authorization": self.pexels_api_key}
        params = {"query": query, "per_page": 3, "orientation": "landscape", "size": "large"}
        pexels_filename = output_filename.replace(".png", f"_pexels_{random.randint(100,999)}.jpg")
        filepath = os.path.join(self.output_dir, pexels_filename)
        try:
            print(f"Searching Pexels for: '{query}'")
            query_parts = query.split(); effective_query = " ".join(query_parts[:5])
            params["query"] = effective_query
            response = requests.get("https://api.pexels.com/v1/search", headers=headers, params=params, timeout=15)
            response.raise_for_status(); data = response.json()
            if data.get("photos"):
                photo_url = data["photos"][0]["src"]["large2x"] 
                image_response = requests.get(photo_url, timeout=45); 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); print(f"Pexels image saved: {filepath}"); return filepath
            else: print(f"No photos on Pexels for: '{effective_query}'")
        except Exception as e: print(f"Pexels error for '{query}': {e}")
        return None

    def generate_image_visual(self, image_prompt_text, scene_data, scene_identifier_filename):
        filepath = os.path.join(self.output_dir, scene_identifier_filename)
        if self.USE_AI_IMAGE_GENERATION and self.openai_api_key:
            max_retries = 2
            for attempt in range(max_retries):
                try:
                    print(f"Attempt {attempt+1}: DALL-E ({self.dalle_model}) for: {image_prompt_text[:120]}...")
                    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: 
                        print(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)
                    print(f"AI Image (DALL-E) saved: {filepath}")
                    return filepath 
                
                except openai.RateLimitError as e: 
                    print(f"OpenAI Rate Limit: {e}. Retrying after {5*(attempt+1)}s...")
                    time.sleep(5 * (attempt + 1))
                    # CORRECTED INDENTATION FOR THIS BLOCK
                    if attempt == max_retries - 1: 
                        print("Max retries reached for RateLimitError.")
                        break # Break from the for loop if max retries hit for RateLimitError
                    else:
                        continue # Go to the next attempt in the for loop
                
                except openai.APIError as e: 
                    print(f"OpenAI API Error: {e}")
                    break # Break from loop, will try Pexels/placeholder
                except requests.exceptions.RequestException as e: 
                    print(f"Requests Error (DALL-E image download): {e}")
                    break # Break from loop
                except Exception as e: 
                    print(f"Generic error (DALL-E gen): {e}")
                    break # Break from loop
            
            # This code block is reached if the 'for' loop completes (max retries) 
            # or if it 'break's due to an error other than RateLimitError (where it 'continue's)
            print("DALL-E generation failed or max retries reached. 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
            
            print("Pexels also failed/disabled. Using placeholder.")
            return self._create_placeholder_image_content(
                f"[AI/Pexels Failed] Original Prompt: {image_prompt_text[:100]}...", 
                scene_identifier_filename, size=self.video_frame_size
            )
        else: # AI image generation not enabled
            return self._create_placeholder_image_content(
                image_prompt_text, scene_identifier_filename, size=self.video_frame_size
            )

    def generate_narration_audio(self, text_to_narrate, output_filename="narration_overall.mp3"):
        if not self.USE_ELEVENLABS or not self.elevenlabs_api_key or not text_to_narrate:
            print("ElevenLabs disabled/no text. Skipping audio."); return None
        audio_filepath = os.path.join(self.output_dir, output_filename)
        try:
            print(f"Generating ElevenLabs audio (Voice: {self.elevenlabs_voice_id}) for: {text_to_narrate[:70]}...")
            # elevenlabs_set_api_key_func(self.elevenlabs_api_key) # Set key if library requires it per call
            audio_data = elevenlabs_generate_audio(text=text_to_narrate, voice=self.elevenlabs_voice_id, model="eleven_multilingual_v2")
            with open(audio_filepath, "wb") as f: f.write(audio_data)
            print(f"ElevenLabs audio saved: {audio_filepath}"); return audio_filepath
        except ImportError: print("ElevenLabs library not found. Install it.")
        except Exception as e: print(f"Error ElevenLabs audio: {e}")
        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):
        if not image_data_list: return None
        print(f"Creating video from {len(image_data_list)} image sets.")
        processed_clips = []
        narration_audio_clip = None 
        final_video_clip_obj = None 

        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)): print(f"Img not found: {img_path}"); continue
            try:
                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)
                canvas = Image.new('RGB', self.video_frame_size, (random.randint(0,15), random.randint(0,15), random.randint(0,15))) 
                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 = ImageClip(frame_np).set_duration(duration_per_image)
                end_scale = random.uniform(1.05, 1.12) # Ken Burns zoom
                img_clip = img_clip.fx(vfx.resize, lambda t: 1 + (end_scale - 1) * (t / duration_per_image))
                img_clip = img_clip.set_position('center')
                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(10,10,20,0.75)', method='caption', align='West',
                                        size=(self.video_frame_size[0]*0.9, None), kerning=-1, stroke_color='black', stroke_width=1
                                       ).set_duration(duration_per_image - 1.0).set_start(0.5).set_position(('center', 0.9), relative=True)
                    final_scene_clip = CompositeVideoClip([img_clip, txt_clip], size=self.video_frame_size)
                else: final_scene_clip = img_clip
                processed_clips.append(final_scene_clip)
            except Exception as e: print(f"Error clip for {img_path}: {e}.")
        
        if not processed_clips: print("No clips for video."); return None
        transition = 0.8 
        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 overall_narration_path and os.path.exists(overall_narration_path):
            try:
                narration_audio_clip = AudioFileClip(overall_narration_path)
                final_video_clip_obj = final_video_clip_obj.set_audio(narration_audio_clip)
                if narration_audio_clip.duration < final_video_clip_obj.duration:
                    final_video_clip_obj = final_video_clip_obj.subclip(0, narration_audio_clip.duration)
                print("Overall narration added.")
            except Exception as e: print(f"Error adding narration: {e}.")
        
        output_path = os.path.join(self.output_dir, output_filename)
        try:
            final_video_clip_obj.write_videofile(output_path, fps=fps, codec='libx264', preset='medium', # 'medium' or 'slow'
                                        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")
            print(f"Video created: {output_path}"); return output_path
        except Exception as e: print(f"Error writing video: {e}"); return None
        finally:
            for c in processed_clips: 
                if hasattr(c, 'close'): c.close()
            if narration_audio_clip and hasattr(narration_audio_clip, 'close'): narration_audio_clip.close()
            if final_video_clip_obj and hasattr(final_video_clip_obj, 'close'): final_video_clip_obj.close()