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 
import subprocess # For the dummy video fallback

# --- ElevenLabs Import ---
ELEVENLABS_CLIENT_IMPORTED = False
ElevenLabsAPIClient = None # Placeholder for the class
Voice = None               # Placeholder for the class
VoiceSettings = None       # Placeholder for the class

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
    print("Successfully imported ElevenLabs client components (SDK v1.x.x pattern).")
except ImportError as e_eleven:
    print(f"WARNING: Could not import ElevenLabs client components: {e_eleven}. ElevenLabs audio generation will be disabled.")
except Exception as e_gen_eleven: # Catch any other general import error for elevenlabs
    print(f"WARNING: General error importing ElevenLabs: {e_gen_eleven}. ElevenLabs audio generation will be disabled.")


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 loaded: {self.font_path_in_container}.") # Less verbose
        except IOError:
            print(f"Warning: Placeholder font '{self.font_path_in_container}' not loaded. 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)

        # ElevenLabs Client
        self.elevenlabs_api_key = None
        self.USE_ELEVENLABS = False
        self.elevenlabs_client = None 
        self.elevenlabs_voice_id = "Rachel" # Default, can be name or ID
        if VoiceSettings: # Check if VoiceSettings was successfully imported
            self.elevenlabs_voice_settings = VoiceSettings(
                stability=0.65, similarity_boost=0.75, 
                style=0.1, use_speaker_boost=True
            )
        else:
            self.elevenlabs_voice_settings = None

        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,api_key):
        self.elevenlabs_api_key=api_key
        if api_key and ELEVENLABS_CLIENT_IMPORTED and ElevenLabsAPIClient: 
            try: 
                self.elevenlabs_client = ElevenLabsAPIClient(api_key=api_key) 
                # Optional: Test client (e.g., fetch voices) can be added here for robust init
                # voices_test = self.elevenlabs_client.voices.get_all() # This makes an API call
                # if voices_test and voices_test.voices: print("ElevenLabs client connected.")
                self.USE_ELEVENLABS=True
                # print("ElevenLabs Client Ready.")
            except Exception as e: 
                print(f"Error initializing ElevenLabs client with API key: {e}. ElevenLabs Disabled."); 
                self.USE_ELEVENLABS=False; self.elevenlabs_client = None
        else: 
            self.USE_ELEVENLABS=False; self.elevenlabs_client = None
            # if not ELEVENLABS_CLIENT_IMPORTED or not ElevenLabsAPIClient:
                # print("ElevenLabs Client class was not imported. ElevenLabs Disabled.") # Already printed at import
            # else:
                # print("ElevenLabs API Key not provided. ElevenLabs Disabled.") # Less verbose
            
    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,text_content,font_obj):
        if not text_content: return 0,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 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: # Fallback
                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 Exception: # Generic fallback on error
            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=(1280,720)):
        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 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_lines_to_display=min(len(lines),(size[1]-(2*padding))//(single_line_h+2)) # Max lines based on height
        
        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: # Show ellipsis if more text
                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:print(f"Error saving placeholder image {filepath}: {e}");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": "large"} # Get only 1 relevant image
        pexels_filename = output_filename_base.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}'")
            effective_query = " ".join(query.split()[:5]) # Use first 5 words for Pexels query
            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"] # High quality
                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); print(f"Pexels image saved: {filepath}"); return filepath
            else: print(f"No photos found on Pexels for query: '{effective_query}'")
        except Exception as e: print(f"Pexels search/download error for query '{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))
                    if attempt == max_retries - 1: print("Max retries for RateLimitError."); break
                    else: continue
                except openai.APIError as e: print(f"OpenAI API Error: {e}"); break 
                except requests.exceptions.RequestException as e: print(f"Requests Error (DALL-E download): {e}"); break
                except Exception as e: print(f"Generic error (DALL-E gen): {e}"); break
            
            print("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
            
            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: 
            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_client or not text_to_narrate:
            # print("ElevenLabs not enabled, client not initialized, or no text. Skipping audio.") # Less verbose
            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]}...")
            
            voice_param = self.elevenlabs_voice_id # Default to string ID
            if Voice and self.elevenlabs_voice_settings: # Check if Voice & VoiceSettings were imported
                voice_param = Voice(
                    voice_id=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" # Or other models e.g. "eleven_turbo_v2"
            )
            
            with open(audio_filepath, "wb") as f:
                for chunk in audio_data_iterator: 
                    if chunk: f.write(chunk)
            
            print(f"ElevenLabs audio saved: {audio_filepath}")
            return audio_filepath
        except AttributeError as ae:
             print(f"AttributeError with ElevenLabs client (method name like 'generate' might differ): {ae}")
        except Exception as e:
            print(f"Error generating 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: print("No image data for video."); return None
        # print(f"Creating video from {len(image_data_list)} image sets.") # Less verbose
        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(0,10), random.randint(0,10), random.randint(0,10))) 
                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) 
                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 creating video clip for {img_path}: {e}.")
        
        if not processed_clips: print("No clips processed 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)
                current_video_duration = final_video_clip_obj.duration
                # If narration is shorter, trim video. If narration is longer, audio will be cut by video duration.
                if narration_audio_clip.duration < current_video_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)
                print("Overall narration added to video.")
            except Exception as e: print(f"Error adding overall narration: {e}.")
        
        output_path = os.path.join(self.output_dir, output_filename)
        try:
            print(f"Writing final video to: {output_path}")
            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") # Consider 'medium' preset
            print(f"Video successfully created: {output_path}"); return output_path
        except Exception as e: print(f"Error writing video file: {e}"); return None
        finally:
            for c_item in processed_clips: 
                if hasattr(c_item, 'close'): c_item.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()