#!/usr/bin/env python3 """ yt-thumbnail — Gera thumbnails para clips do YouTube Usa LLM para criar prompt estruturado + IA para gerar imagem Uso: yt-thumbnail --title "Titulo do clip" --output thumb.jpg yt-thumbnail --title "Titulo" --description "Sobre o que eh o clip" """ import sys import os import json import urllib.request from PIL import Image, ImageDraw, ImageFont, ImageFilter import io # Config SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__)) CONFIG_DIR = os.environ.get('GWS_CONFIG_DIR', os.path.join(SCRIPT_DIR, '..', 'config')) ENV_FILE = os.path.join(CONFIG_DIR, '.env') # Load env if os.path.exists(ENV_FILE): with open(ENV_FILE) as f: for line in f: line = line.strip() if line and not line.startswith('#') and '=' in line: key, val = line.split('=', 1) os.environ[key] = val PIRAMYD_API_KEY = os.environ.get('PIRAMYD_API_KEY', '') PIRAMYD_URL = 'https://api.piramyd.cloud/v1' OPENROUTER_API_KEY = os.environ.get('OPENROUTER_API_KEY', '') OPENROUTER_URL = 'https://openrouter.ai/api/v1' IMAGE_MODEL = os.environ.get('THUMB_MODEL', 'flux2-klein-4b') CHAT_MODEL = 'claude-sonnet-4.5' # LLM provider configs (loaded from env, set by scheduler) ANTHROPIC_API_KEY = os.environ.get('ANTHROPIC_API_KEY', '') ANTHROPIC_URL = 'https://api.anthropic.com/v1' PROVIDER_MAP = { 'piramyd': {'url': PIRAMYD_URL, 'key_env': 'PIRAMYD_API_KEY'}, 'openrouter': {'url': OPENROUTER_URL, 'key_env': 'OPENROUTER_API_KEY'}, 'anthropic': {'url': ANTHROPIC_URL, 'key_env': 'ANTHROPIC_API_KEY'}, 'claude-oauth': {'url': None, 'key_env': None}, } def _get_llm_chain(): """Build ordered list of LLM providers to try, from env vars.""" chain = [] for i in range(1, 4): provider = os.environ.get(f'THUMB_LLM_{i}_PROVIDER', '').strip() model = os.environ.get(f'THUMB_LLM_{i}_MODEL', '').strip() if not provider: continue if provider not in PROVIDER_MAP: continue if provider == 'claude-oauth': # Claude CLI nao precisa de key nem model chain.append({'provider': 'claude-oauth', 'model': model or 'default', 'url': None, 'api_key': None}) continue if not model: continue info = PROVIDER_MAP[provider] api_key = os.environ.get(info['key_env'], '') if not api_key: continue chain.append({'provider': provider, 'model': model, 'url': info['url'], 'api_key': api_key}) # Fallback: se nenhum configurado, usa o comportamento original if not chain and PIRAMYD_API_KEY: chain.append({'provider': 'piramyd', 'model': CHAT_MODEL, 'url': PIRAMYD_URL, 'api_key': PIRAMYD_API_KEY}) return chain BRAND = os.environ.get('THUMB_BRAND', 'INEMA TDS') WIDTH = 1280 HEIGHT = 720 FONT_PATH = '/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf' # Visual config from environment (overridable via dashboard) THUMB_FONT_SIZE = int(os.environ.get('THUMB_FONT_SIZE', '78')) THUMB_TEXT_COLOR = os.environ.get('THUMB_TEXT_COLOR', '#FFFFFF') THUMB_ACCENT_COLOR = os.environ.get('THUMB_ACCENT_COLOR', '#00D4FF') THUMB_BRAND_COLOR = os.environ.get('THUMB_BRAND_COLOR', '#6366F1') THUMB_TEXT_POSITION = os.environ.get('THUMB_TEXT_POSITION', 'top-left') def hex_to_rgb(hex_color): """Convert hex color (#RRGGBB) to RGB tuple.""" hex_color = hex_color.lstrip('#') return tuple(int(hex_color[i:i+2], 16) for i in (0, 2, 4)) DEFAULT_SYSTEM_PROMPT = """Voce e especialista na criacao de prompts para geracao de thumbnails de YouTube para o canal INEMA TDS (canal de tecnologia, programacao, IA e automacao). Sua missao e transformar qualquer titulo de video em um prompt detalhado, otimizado para alta taxa de cliques (CTR) e pronto para uso em geradores de imagem. Checklist: 1) Analise o titulo e identifique tema e emocao central. 2) Escolha uma metafora visual FORTE e INESPERADA ligada ao tema. 3) Defina cores vibrantes e contrastantes. 4) Crie uma frase curta e impactante (max 5 palavras em portugues). 5) Pense na composicao: espaco para texto, foco visual, alto contraste. Diretrizes: - Estilo: fotorealista com iluminacao cinematica, alto contraste - Cores: vibrantes, contrastantes (neon azul, roxo, laranja, vermelho) - Proporcao: 16:9 (1792x1024) - A frase curta NAO e o titulo completo, e uma versao impactante de 2-5 palavras - Metafora visual deve ser algo CONCRETO e VISUAL (objeto, cena, acao) - NAO incluir: marcas d'agua, bordas, logotipos, emojis, textos longos, conteudo sensivel, maos deformadas Retorne SOMENTE este JSON: { "frase_curta": "(string; 2-5 palavras impactantes em portugues)", "cena_principal": "(string; descricao detalhada da cena/metafora visual principal)", "fundo_tematico": "(string; cenario coerente com o tema)", "cores_dominantes": "(string; cores vibrantes separadas por virgula)", "composicao": "(string; como os elementos estao dispostos, onde fica o espaco para texto)", "negative_prompt": "watermark, border, long text, deformed hands, extra fingers, cluttered, low quality, blurry text" }""" # Load custom prompt from config file if exists _prompt_file = os.path.join(CONFIG_DIR, 'prompt_thumb.txt') if os.path.exists(_prompt_file): with open(_prompt_file) as _f: _custom = _f.read().strip() if _custom: SYSTEM_PROMPT = _custom else: SYSTEM_PROMPT = DEFAULT_SYSTEM_PROMPT else: SYSTEM_PROMPT = DEFAULT_SYSTEM_PROMPT def _call_llm_claude_oauth(system_prompt, user_msg): """Call Claude CLI (OAuth) via subprocess. Returns content string.""" import subprocess full_prompt = f'{system_prompt}\n\n---\n\n{user_msg}' result = subprocess.run( ['claude', '-p', '--output-format', 'json', full_prompt], capture_output=True, text=True, timeout=120 ) if result.returncode != 0: raise RuntimeError(f'Claude CLI erro (code {result.returncode}): {result.stderr[:200]}') data = json.loads(result.stdout) if data.get('is_error'): raise RuntimeError(f'Claude CLI retornou erro: {data.get("result", "")[:200]}') return data.get('result', '') def _call_llm_anthropic(provider_cfg, system_prompt, user_msg): """Call Anthropic Messages API directly. Returns content string.""" payload = { 'model': provider_cfg['model'], 'system': system_prompt, 'messages': [{'role': 'user', 'content': user_msg}], 'temperature': 0.7, 'max_tokens': 500 } body = json.dumps(payload).encode() req = urllib.request.Request(f'{provider_cfg["url"]}/messages', data=body) req.add_header('Content-Type', 'application/json') req.add_header('x-api-key', provider_cfg['api_key']) req.add_header('anthropic-version', '2023-06-01') resp = urllib.request.urlopen(req, timeout=60) result = json.loads(resp.read()) return result['content'][0]['text'] def _call_llm(provider_cfg, messages): """Call a single LLM provider (OpenAI-compatible API). Returns parsed content or raises.""" payload = { 'model': provider_cfg['model'], 'messages': messages, 'temperature': 0.7, 'max_tokens': 500 } body = json.dumps(payload).encode() req = urllib.request.Request(f'{provider_cfg["url"]}/chat/completions', data=body) req.add_header('Content-Type', 'application/json') req.add_header('Authorization', f'Bearer {provider_cfg["api_key"]}') resp = urllib.request.urlopen(req, timeout=60) result = json.loads(resp.read()) return result['choices'][0]['message']['content'] def generate_prompt_json(title, description=''): """Usa LLM para gerar o JSON estruturado do prompt. Tenta multiplos providers.""" user_msg = f'Titulo do video: "{title}"' if description: user_msg += f'\nDescricao: {description}' messages = [ {'role': 'system', 'content': SYSTEM_PROMPT}, {'role': 'user', 'content': user_msg} ] chain = _get_llm_chain() if not chain: raise ValueError('Nenhum provider LLM configurado') import re last_err = None for i, cfg in enumerate(chain, 1): try: print(f' [1/3] Gerando prompt com LLM ({cfg["provider"]}/{cfg["model"]}) tentativa {i}/{len(chain)}...', flush=True) if cfg['provider'] == 'claude-oauth': content = _call_llm_claude_oauth(SYSTEM_PROMPT, user_msg) elif cfg['provider'] == 'anthropic': content = _call_llm_anthropic(cfg, SYSTEM_PROMPT, user_msg) else: content = _call_llm(cfg, messages) json_match = re.search(r'\{[\s\S]*\}', content) if json_match: return json.loads(json_match.group()) raise ValueError(f'LLM nao retornou JSON valido: {content[:200]}') except Exception as e: last_err = e print(f' LLM {i} falhou ({cfg["provider"]}/{cfg["model"]}): {e}', file=sys.stderr, flush=True) continue raise last_err def build_image_prompt(prompt_data): """Monta o prompt final para o gerador de imagem.""" return ( f'IMPORTANT: DO NOT include any text, letters, words or writing in the image. ' f'Professional YouTube thumbnail, photorealistic, cinematic lighting. ' f'Scene: {prompt_data["cena_principal"]}. ' f'Background: {prompt_data["fundo_tematico"]}. ' f'Color scheme: {prompt_data["cores_dominantes"]}. ' f'Composition: {prompt_data["composicao"]}. ' f'Style: Realistic photo with cinematic lighting, high contrast, dramatic shadows, ' f'optimized for YouTube thumbnail. Aspect ratio 16:9. ' f'NO TEXT IN IMAGE. ' f'Do not include: text, letters, words, writing, {prompt_data["negative_prompt"]}' ) KIE_API_KEY = os.environ.get('KIE_API_KEY', '') KIE_URL = 'https://api.kie.ai/api/v1' MINIMAX_API_KEY = os.environ.get('MINIMAX_API_KEY', '') MINIMAX_URL = 'https://api.minimax.io/v1' GOOGLE_API_KEY = os.environ.get('GOOGLE_IMAGE_API_KEY', '') or os.environ.get('GEMINI_API_KEY', '') GOOGLE_IMAGE_MODEL = os.environ.get('GOOGLE_IMAGE_MODEL', 'imagen-4.0-fast-generate-001') INEMAIMG_URL = os.environ.get('INEMAIMG_URL', 'http://localhost:8000') INEMAIMG_MODEL_DEFAULT = 'flux2-klein' INEMAIMG_TIMEOUT = int(os.environ.get('INEMAIMG_TIMEOUT_S', '1800')) # Image provider config from env IMAGE_PROVIDER = os.environ.get('THUMB_IMAGE_PROVIDER', 'piramyd') # Kie model -> endpoint mapping KIE_ENDPOINTS = { 'gpt4o-image': '/gpt4o-image/generate', 'flux-kontext-pro': '/flux/kontext/generate', 'flux-kontext-max': '/flux/kontext/generate', } def _generate_image_piramyd(image_prompt): """Gera imagem via Piramyd API (sincrono, OpenAI-compatible).""" payload = { 'model': IMAGE_MODEL, 'prompt': image_prompt, 'n': 1, 'size': '1792x1024' } body = json.dumps(payload).encode() req = urllib.request.Request(f'{PIRAMYD_URL}/images/generations', data=body) req.add_header('Content-Type', 'application/json') req.add_header('Authorization', f'Bearer {PIRAMYD_API_KEY}') resp = urllib.request.urlopen(req, timeout=120) result = json.loads(resp.read()) data = result.get('data', []) if not data or not data[0].get('url'): raise ValueError('Piramyd nao retornou imagem') return data[0]['url'] def _generate_image_kie(image_prompt): """Gera imagem via Kie.ai API (assincrono, polling).""" import time model = IMAGE_MODEL # Modelos que usam /jobs/createTask (novo endpoint unificado) if model in ('z-image',): # z-image tem limite de 1000 chars e funciona melhor com prompts curtos short_prompt = image_prompt if len(image_prompt) > 400: # Extrair essencia: pegar ate o primeiro ponto da cena + cores parts = image_prompt.split('. ') short_prompt = '. '.join(parts[:3])[:400] if not short_prompt.endswith('.'): short_prompt += '.' short_prompt += ' Photorealistic, cinematic, 16:9. DO NOT include any text, letters or words in the image.' payload = { 'model': model, 'input': { 'prompt': short_prompt, 'aspect_ratio': '16:9' } } endpoint = '/jobs/createTask' elif 'flux-kontext' in model: payload = { 'prompt': image_prompt, 'model': model, 'aspectRatio': '16:9', 'outputFormat': 'jpeg', } endpoint = KIE_ENDPOINTS.get(model, '/flux/kontext/generate') else: payload = { 'prompt': image_prompt, 'size': '3:2', } if model not in KIE_ENDPOINTS: payload['model'] = model endpoint = KIE_ENDPOINTS.get(model, '/gpt4o-image/generate') body = json.dumps(payload).encode() req = urllib.request.Request(f'{KIE_URL}{endpoint}', data=body) req.add_header('Content-Type', 'application/json') req.add_header('Authorization', f'Bearer {KIE_API_KEY}') resp = urllib.request.urlopen(req, timeout=60) result = json.loads(resp.read()) if result.get('code') != 200: raise ValueError(f'Kie erro: {result.get("msg", "unknown")}') task_id = result['data']['taskId'] print(f' Kie task: {task_id}, aguardando...', flush=True) # Poll for result (max 180s) for attempt in range(60): time.sleep(3) poll_url = f'{KIE_URL}/jobs/recordInfo?taskId={task_id}' poll_req = urllib.request.Request(poll_url) poll_req.add_header('Authorization', f'Bearer {KIE_API_KEY}') poll_resp = urllib.request.urlopen(poll_req, timeout=30) poll_data = json.loads(poll_resp.read()) data = poll_data.get('data') or {} state = data.get('state', '') if state == 'success': result_json = json.loads(data.get('resultJson', '{}')) urls = result_json.get('resultUrls', []) if urls: return urls[0] raise ValueError('Kie retornou sucesso mas sem URL') elif state == 'fail': raise ValueError(f'Kie task falhou: {poll_data}') # waiting/queuing/generating/null -> continue if attempt % 10 == 9: print(f' Kie ainda processando... ({(attempt+1)*3}s)', flush=True) raise ValueError('Kie timeout (180s)') def _generate_image_minimax(image_prompt): """Gera imagem via MiniMax API (image-01).""" import base64 as b64 payload = { 'model': 'image-01', 'prompt': image_prompt, 'aspect_ratio': '16:9', 'response_format': 'base64' } body = json.dumps(payload).encode() req = urllib.request.Request(f'{MINIMAX_URL}/image_generation', data=body) req.add_header('Content-Type', 'application/json') req.add_header('Authorization', f'Bearer {MINIMAX_API_KEY}') resp = urllib.request.urlopen(req, timeout=120) result = json.loads(resp.read()) base_resp = result.get('base_resp', {}) if base_resp.get('status_code', 0) != 0: raise ValueError(f'MiniMax erro: {base_resp.get("status_msg", "unknown")}') data = result.get('data', []) if not data: raise ValueError('MiniMax nao retornou imagem') img_b64 = data[0].get('b64_image', '') if not img_b64: raise ValueError('MiniMax sem base64 na resposta') img_bytes = b64.b64decode(img_b64) return img_bytes def _generate_image_local(image_prompt): """Gera imagem via inemaimg local (FastAPI em INEMAIMG_URL, padrao do imkt4/timesmkt3).""" import base64 as b64 model = IMAGE_MODEL or INEMAIMG_MODEL_DEFAULT # 1024x576 = 16:9 exato e multiplos de 64 (requisito do servidor) payload = { 'model': model, 'prompt': image_prompt, 'width': 1024, 'height': 576, } body = json.dumps(payload).encode() req = urllib.request.Request(f'{INEMAIMG_URL}/generate', data=body) req.add_header('Content-Type', 'application/json') resp = urllib.request.urlopen(req, timeout=INEMAIMG_TIMEOUT) result = json.loads(resp.read()) img_b64 = result.get('image') if not img_b64: raise ValueError(f'inemaimg nao retornou image. keys={list(result.keys())}') return b64.b64decode(img_b64) def _generate_image_google(image_prompt): """Gera imagem via Google Imagen API.""" import base64 as b64 model = GOOGLE_IMAGE_MODEL payload = { 'instances': [{'prompt': image_prompt}], 'parameters': {'sampleCount': 1, 'aspectRatio': '16:9'} } body = json.dumps(payload).encode() url = f'https://generativelanguage.googleapis.com/v1beta/models/{model}:predict?key={GOOGLE_API_KEY}' req = urllib.request.Request(url, data=body) req.add_header('Content-Type', 'application/json') resp = urllib.request.urlopen(req, timeout=120) result = json.loads(resp.read()) predictions = result.get('predictions', []) if not predictions: raise ValueError('Google Imagen nao retornou imagem') img_bytes = b64.b64decode(predictions[0]['bytesBase64Encoded']) return img_bytes def generate_ai_image(image_prompt): """Gera imagem usando o provider configurado.""" provider = IMAGE_PROVIDER print(f' [2/3] Gerando imagem com {provider}/{IMAGE_MODEL}...', flush=True) if provider in ('minimax', 'google', 'local'): if provider == 'minimax': img_bytes = _generate_image_minimax(image_prompt) elif provider == 'local': img_bytes = _generate_image_local(image_prompt) else: img_bytes = _generate_image_google(image_prompt) img = Image.open(io.BytesIO(img_bytes)) img = img.resize((WIDTH, HEIGHT), Image.LANCZOS).convert('RGB') return img elif provider == 'kie': img_url = _generate_image_kie(image_prompt) else: img_url = _generate_image_piramyd(image_prompt) # Download dl_req = urllib.request.Request(img_url) dl_req.add_header('User-Agent', 'Mozilla/5.0') with urllib.request.urlopen(dl_req, timeout=60) as resp: img_data = resp.read() img = Image.open(io.BytesIO(img_data)) img = img.resize((WIDTH, HEIGHT), Image.LANCZOS).convert('RGB') return img def create_gradient_bg(): """Fallback local.""" img = Image.new('RGB', (WIDTH, HEIGHT)) for y in range(HEIGHT): r = int(10 + 10 * y / HEIGHT) g = int(10 + 5 * y / HEIGHT) b = int(30 + 20 * y / HEIGHT) for x in range(WIDTH): img.putpixel((x, y), (r, g, b)) return img def wrap_text(text, font, max_width, draw): """Quebra texto em linhas.""" words = text.split() lines = [] current = '' for word in words: test = (current + ' ' + word).strip() bbox = draw.textbbox((0, 0), test, font=font) if bbox[2] - bbox[0] > max_width and current: lines.append(current) current = word else: current = test if current: lines.append(current) return lines[:3] # Font path mapping FONT_MAP = { 'montserrat-extrabold': os.path.expanduser('~/.local/share/fonts/Montserrat-ExtraBold.ttf'), 'montserrat-black': os.path.expanduser('~/.local/share/fonts/Montserrat-Black.ttf'), 'bebas-neue': os.path.expanduser('~/.local/share/fonts/BebasNeue-Regular.ttf'), 'anton': os.path.expanduser('~/.local/share/fonts/Anton-Regular.ttf'), 'dejavu': '/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf', } PRESETS = { 'premium': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'82','DESIGN_LAST_LINE_SCALE':'15','DESIGN_LINE_HEIGHT':'90','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#F5F3EE','DESIGN_HIGHLIGHT_COLOR':'#D9B65B','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#D9B65B','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'8','DESIGN_SHADOW_OPACITY':'180','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'160','DESIGN_GRADIENT_COVERAGE':'40','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'26','DESIGN_BRAND_COLOR':'#D9B65B','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'youtube': {'DESIGN_FONT':'anton','DESIGN_FONT_SIZE':'90','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'96','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FFFF00','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#FF0000','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'4','DESIGN_SHADOW_OPACITY':'255','DESIGN_GRADIENT':'none','DESIGN_GRADIENT_OPACITY':'0','DESIGN_GRADIENT_COVERAGE':'0','DESIGN_BRAND_FONT':'anton','DESIGN_BRAND_SIZE':'28','DESIGN_BRAND_COLOR':'#FF0000','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, 'clean': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'76','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'88','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_ENABLED':'false','DESIGN_ACCENT_COLOR':'#6366F1','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'6','DESIGN_SHADOW_OPACITY':'150','DESIGN_GRADIENT':'left','DESIGN_GRADIENT_OPACITY':'120','DESIGN_GRADIENT_COVERAGE':'35','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#6366F1','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'neon': {'DESIGN_FONT':'bebas-neue','DESIGN_FONT_SIZE':'88','DESIGN_LAST_LINE_SCALE':'10','DESIGN_LINE_HEIGHT':'92','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#00F5FF','DESIGN_HIGHLIGHT_COLOR':'#FF00FF','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#00F5FF','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#00F5FF','DESIGN_SHADOW_SIZE':'10','DESIGN_SHADOW_OPACITY':'100','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'180','DESIGN_GRADIENT_COVERAGE':'45','DESIGN_BRAND_FONT':'bebas-neue','DESIGN_BRAND_SIZE':'28','DESIGN_BRAND_COLOR':'#00F5FF','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'fallback': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'72','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'84','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_ENABLED':'false','DESIGN_ACCENT_COLOR':'#6366F1','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'3','DESIGN_SHADOW_OPACITY':'255','DESIGN_GRADIENT':'none','DESIGN_GRADIENT_OPACITY':'0','DESIGN_GRADIENT_COVERAGE':'0','DESIGN_BRAND_FONT':'dejavu','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#6366F1','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'mrbeast': {'DESIGN_FONT':'anton','DESIGN_FONT_SIZE':'100','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'105','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FFD700','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#FFD700','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'false','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'5','DESIGN_SHADOW_OPACITY':'255','DESIGN_GRADIENT':'none','DESIGN_GRADIENT_OPACITY':'0','DESIGN_GRADIENT_COVERAGE':'0','DESIGN_BRAND_FONT':'anton','DESIGN_BRAND_SIZE':'30','DESIGN_BRAND_COLOR':'#FFD700','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, 'techreview': {'DESIGN_FONT':'montserrat-black','DESIGN_FONT_SIZE':'78','DESIGN_LAST_LINE_SCALE':'10','DESIGN_LINE_HEIGHT':'88','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#E3F2FD','DESIGN_HIGHLIGHT_COLOR':'#4FC3F7','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#4FC3F7','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#0D47A1','DESIGN_SHADOW_SIZE':'8','DESIGN_SHADOW_OPACITY':'160','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'150','DESIGN_GRADIENT_COVERAGE':'45','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#4FC3F7','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'tutorial': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'80','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'90','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#4CAF50','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#4CAF50','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#1B5E20','DESIGN_SHADOW_SIZE':'3','DESIGN_SHADOW_OPACITY':'220','DESIGN_GRADIENT':'top','DESIGN_GRADIENT_OPACITY':'140','DESIGN_GRADIENT_COVERAGE':'35','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'26','DESIGN_BRAND_COLOR':'#4CAF50','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'breaking': {'DESIGN_FONT':'anton','DESIGN_FONT_SIZE':'94','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'100','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFEB3B','DESIGN_HIGHLIGHT_COLOR':'#FF5722','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#FF5722','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'4','DESIGN_SHADOW_OPACITY':'255','DESIGN_GRADIENT':'full-bottom','DESIGN_GRADIENT_OPACITY':'200','DESIGN_GRADIENT_COVERAGE':'50','DESIGN_BRAND_FONT':'anton','DESIGN_BRAND_SIZE':'28','DESIGN_BRAND_COLOR':'#FFEB3B','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'bottom-left'}, 'minimal': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'68','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'80','DESIGN_TRACKING':'very-tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#1A1A1A','DESIGN_HIGHLIGHT_COLOR':'#1A1A1A','DESIGN_HIGHLIGHT_ENABLED':'false','DESIGN_ACCENT_COLOR':'#E0E0E0','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'false','DESIGN_SHADOW_TYPE':'none','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'0','DESIGN_SHADOW_OPACITY':'0','DESIGN_GRADIENT':'left','DESIGN_GRADIENT_OPACITY':'200','DESIGN_GRADIENT_COVERAGE':'50','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'22','DESIGN_BRAND_COLOR':'#9E9E9E','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, 'cinematic': {'DESIGN_FONT':'montserrat-black','DESIGN_FONT_SIZE':'80','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'88','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#F5A623','DESIGN_HIGHLIGHT_COLOR':'#00C2C7','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#F5A623','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'10','DESIGN_SHADOW_OPACITY':'200','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'180','DESIGN_GRADIENT_COVERAGE':'50','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#F5A623','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'bottom-left'}, 'gradient': {'DESIGN_FONT':'montserrat-black','DESIGN_FONT_SIZE':'84','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'92','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#BF00FF','DESIGN_HIGHLIGHT_COLOR':'#FF007F','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#8B00FF','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#4A0080','DESIGN_SHADOW_SIZE':'8','DESIGN_SHADOW_OPACITY':'150','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'160','DESIGN_GRADIENT_COVERAGE':'40','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#BF00FF','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'splitscreen': {'DESIGN_FONT':'anton','DESIGN_FONT_SIZE':'88','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'94','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FFE135','DESIGN_HIGHLIGHT_ENABLED':'false','DESIGN_ACCENT_COLOR':'#FFFFFF','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'false','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'4','DESIGN_SHADOW_OPACITY':'255','DESIGN_GRADIENT':'none','DESIGN_GRADIENT_OPACITY':'0','DESIGN_GRADIENT_COVERAGE':'0','DESIGN_BRAND_FONT':'anton','DESIGN_BRAND_SIZE':'26','DESIGN_BRAND_COLOR':'#FFFFFF','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center'}, 'colorpop': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'78','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'88','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FF1C1C','DESIGN_HIGHLIGHT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#FF1C1C','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'3','DESIGN_SHADOW_OPACITY':'200','DESIGN_GRADIENT':'left','DESIGN_GRADIENT_OPACITY':'140','DESIGN_GRADIENT_COVERAGE':'40','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#FF1C1C','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'retro': {'DESIGN_FONT':'dejavu','DESIGN_FONT_SIZE':'74','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'86','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#F2E8D5','DESIGN_HIGHLIGHT_COLOR':'#C45E26','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#C45E26','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#3D2B1F','DESIGN_SHADOW_SIZE':'3','DESIGN_SHADOW_OPACITY':'200','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'120','DESIGN_GRADIENT_COVERAGE':'35','DESIGN_BRAND_FONT':'dejavu','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#C45E26','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, '3dextrude': {'DESIGN_FONT':'anton','DESIGN_FONT_SIZE':'96','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'102','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFD700','DESIGN_HIGHLIGHT_COLOR':'#FFD700','DESIGN_HIGHLIGHT_ENABLED':'false','DESIGN_ACCENT_COLOR':'#FFD700','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'false','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#4A2C00','DESIGN_SHADOW_SIZE':'5','DESIGN_SHADOW_OPACITY':'255','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'180','DESIGN_GRADIENT_COVERAGE':'45','DESIGN_BRAND_FONT':'anton','DESIGN_BRAND_SIZE':'28','DESIGN_BRAND_COLOR':'#FFD700','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, 'glassmorphism': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'74','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'86','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#E0E0FF','DESIGN_HIGHLIGHT_ENABLED':'false','DESIGN_ACCENT_COLOR':'#A855F7','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#3B82F6','DESIGN_SHADOW_SIZE':'6','DESIGN_SHADOW_OPACITY':'80','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'100','DESIGN_GRADIENT_COVERAGE':'50','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'22','DESIGN_BRAND_COLOR':'#A855F7','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, 'darkacademia': {'DESIGN_FONT':'dejavu','DESIGN_FONT_SIZE':'72','DESIGN_LAST_LINE_SCALE':'10','DESIGN_LINE_HEIGHT':'84','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#D4A574','DESIGN_HIGHLIGHT_COLOR':'#F2E8D5','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#8B6F47','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#1A0E08','DESIGN_SHADOW_SIZE':'8','DESIGN_SHADOW_OPACITY':'180','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'170','DESIGN_GRADIENT_COVERAGE':'50','DESIGN_BRAND_FONT':'dejavu','DESIGN_BRAND_SIZE':'22','DESIGN_BRAND_COLOR':'#8B6F47','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'boldoutline': {'DESIGN_FONT':'anton','DESIGN_FONT_SIZE':'92','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'98','DESIGN_TRACKING':'normal','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_ENABLED':'false','DESIGN_ACCENT_COLOR':'#FFFFFF','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'false','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'6','DESIGN_SHADOW_OPACITY':'255','DESIGN_GRADIENT':'none','DESIGN_GRADIENT_OPACITY':'0','DESIGN_GRADIENT_COVERAGE':'0','DESIGN_BRAND_FONT':'anton','DESIGN_BRAND_SIZE':'28','DESIGN_BRAND_COLOR':'#FFFFFF','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, 'elegantdark': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'76','DESIGN_LAST_LINE_SCALE':'15','DESIGN_LINE_HEIGHT':'86','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#C9B37E','DESIGN_HIGHLIGHT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#C9B37E','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'8','DESIGN_SHADOW_OPACITY':'190','DESIGN_GRADIENT':'top-left','DESIGN_GRADIENT_OPACITY':'170','DESIGN_GRADIENT_COVERAGE':'45','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'24','DESIGN_BRAND_COLOR':'#C9B37E','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'top-left'}, 'tiktok': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'64','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'76','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FE2C55','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#25F4EE','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'outline','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'4','DESIGN_SHADOW_OPACITY':'220','DESIGN_GRADIENT':'top','DESIGN_GRADIENT_OPACITY':'180','DESIGN_GRADIENT_COVERAGE':'50','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'22','DESIGN_BRAND_COLOR':'#FE2C55','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, 'stories': {'DESIGN_FONT':'montserrat-extrabold','DESIGN_FONT_SIZE':'56','DESIGN_LAST_LINE_SCALE':'0','DESIGN_LINE_HEIGHT':'68','DESIGN_TRACKING':'tight','DESIGN_CASE':'upper','DESIGN_TEXT_COLOR':'#FFFFFF','DESIGN_HIGHLIGHT_COLOR':'#FF6B6B','DESIGN_HIGHLIGHT_ENABLED':'true','DESIGN_ACCENT_COLOR':'#FF6B6B','DESIGN_ACCENT_WIDTH':'250','DESIGN_ACCENT_HEIGHT':'5','DESIGN_ACCENT_GAP':'30','DESIGN_ACCENT_ENABLED':'true','DESIGN_SHADOW_TYPE':'blur','DESIGN_SHADOW_COLOR':'#000000','DESIGN_SHADOW_SIZE':'8','DESIGN_SHADOW_OPACITY':'200','DESIGN_GRADIENT':'top','DESIGN_GRADIENT_OPACITY':'200','DESIGN_GRADIENT_COVERAGE':'60','DESIGN_BRAND_FONT':'montserrat-extrabold','DESIGN_BRAND_SIZE':'20','DESIGN_BRAND_COLOR':'#FF6B6B','DESIGN_BRAND_POSITION':'bottom-left','DESIGN_POSITION':'center-left'}, } def compose_thumbnail(bg, frase_curta, cores_str, output_path): """Compoe thumbnail final: imagem + texto overlay com design configuravel.""" # Se tem random preset selecionado, aplicar env vars (salvo ou hardcoded) random_preset = os.environ.get('DESIGN_RANDOM_PRESET', '') if random_preset: # Tentar carregar preset salvo (customizado) do env saved_json = os.environ.get('DESIGN_SAVED_PRESET', '') if saved_json: try: import json as _json saved = _json.loads(saved_json) field_map = { 'font': 'DESIGN_FONT', 'fontSize': 'DESIGN_FONT_SIZE', 'lastLineScale': 'DESIGN_LAST_LINE_SCALE', 'lineHeight': 'DESIGN_LINE_HEIGHT', 'tracking': 'DESIGN_TRACKING', 'case': 'DESIGN_CASE', 'textColor': 'DESIGN_TEXT_COLOR', 'highlightColor': 'DESIGN_HIGHLIGHT_COLOR', 'highlightEnabled': 'DESIGN_HIGHLIGHT_ENABLED', 'accentColor': 'DESIGN_ACCENT_COLOR', 'shadowType': 'DESIGN_SHADOW_TYPE', 'shadowColor': 'DESIGN_SHADOW_COLOR', 'shadowSize': 'DESIGN_SHADOW_SIZE', 'shadowOpacity': 'DESIGN_SHADOW_OPACITY', 'gradient': 'DESIGN_GRADIENT', 'gradientOpacity': 'DESIGN_GRADIENT_OPACITY', 'gradientCoverage': 'DESIGN_GRADIENT_COVERAGE', 'brand': 'DESIGN_BRAND', 'brandFont': 'DESIGN_BRAND_FONT', 'brandSize': 'DESIGN_BRAND_SIZE', 'brandColor': 'DESIGN_BRAND_COLOR', 'brandPosition': 'DESIGN_BRAND_POSITION', 'position': 'DESIGN_POSITION' } for js_key, env_key in field_map.items(): if js_key in saved: os.environ[env_key] = str(saved[js_key]) except Exception: pass elif random_preset in PRESETS: for k, v in PRESETS[random_preset].items(): os.environ[k] = v print(f' [thumb] Preset ativo: {random_preset}') # Read design config from env (set by scheduler from CONFIG sheet) design_font = os.environ.get('DESIGN_FONT', 'dejavu') design_font_size = int(os.environ.get('DESIGN_FONT_SIZE', THUMB_FONT_SIZE)) design_last_line_scale = int(os.environ.get('DESIGN_LAST_LINE_SCALE', '0')) design_line_height = int(os.environ.get('DESIGN_LINE_HEIGHT', str(design_font_size + 16))) design_tracking = os.environ.get('DESIGN_TRACKING', 'normal') design_case = os.environ.get('DESIGN_CASE', 'upper') design_text_color = hex_to_rgb(os.environ.get('DESIGN_TEXT_COLOR', THUMB_TEXT_COLOR)) design_highlight_color = hex_to_rgb(os.environ.get('DESIGN_HIGHLIGHT_COLOR', THUMB_ACCENT_COLOR)) design_highlight_enabled = os.environ.get('DESIGN_HIGHLIGHT_ENABLED', 'false') == 'true' design_shadow_type = os.environ.get('DESIGN_SHADOW_TYPE', 'outline') design_shadow_color = hex_to_rgb(os.environ.get('DESIGN_SHADOW_COLOR', '#000000')) design_shadow_size = int(os.environ.get('DESIGN_SHADOW_SIZE', '3')) design_shadow_opacity = int(os.environ.get('DESIGN_SHADOW_OPACITY', '255')) design_gradient = os.environ.get('DESIGN_GRADIENT', 'none') design_gradient_opacity = int(os.environ.get('DESIGN_GRADIENT_OPACITY', '140')) design_gradient_coverage = int(os.environ.get('DESIGN_GRADIENT_COVERAGE', '40')) design_accent_color = hex_to_rgb(os.environ.get('DESIGN_ACCENT_COLOR', THUMB_ACCENT_COLOR)) design_accent_width = int(os.environ.get('DESIGN_ACCENT_WIDTH', '250')) design_accent_height = int(os.environ.get('DESIGN_ACCENT_HEIGHT', '5')) design_accent_gap = int(os.environ.get('DESIGN_ACCENT_GAP', '30')) design_accent_enabled = os.environ.get('DESIGN_ACCENT_ENABLED', 'true') == 'true' design_stroke_enabled = os.environ.get('DESIGN_STROKE_ENABLED', 'false') == 'true' design_stroke_color = hex_to_rgb(os.environ.get('DESIGN_STROKE_COLOR', '#000000')) design_stroke_size = int(os.environ.get('DESIGN_STROKE_SIZE', '2')) design_brand = os.environ.get('DESIGN_BRAND', BRAND) design_brand_font = os.environ.get('DESIGN_BRAND_FONT', 'dejavu') design_brand_size = int(os.environ.get('DESIGN_BRAND_SIZE', '26')) design_brand_color = hex_to_rgb(os.environ.get('DESIGN_BRAND_COLOR', THUMB_BRAND_COLOR)) design_brand_position = os.environ.get('DESIGN_BRAND_POSITION', 'bottom-left') design_position = os.environ.get('DESIGN_POSITION', THUMB_TEXT_POSITION) font_path = FONT_MAP.get(design_font, FONT_MAP['dejavu']) if not os.path.exists(font_path): font_path = FONT_MAP['dejavu'] # Apply text case text = frase_curta.upper() if design_case == 'upper' else frase_curta # Convert to RGBA for compositing bg = bg.convert('RGBA') # --- Gradient overlay --- if design_gradient != 'none': gradient = Image.new('RGBA', (WIDTH, HEIGHT), (0, 0, 0, 0)) coverage_px = int(WIDTH * design_gradient_coverage / 100) coverage_py = int(HEIGHT * design_gradient_coverage / 100) for i in range(max(coverage_px, coverage_py)): alpha = int(design_gradient_opacity * (1 - i / max(coverage_px, coverage_py))) if alpha < 0: alpha = 0 if design_gradient == 'left': if i < coverage_px: line = Image.new('RGBA', (1, HEIGHT), (0, 0, 0, alpha)) gradient.paste(line, (i, 0)) elif design_gradient == 'top': if i < coverage_py: line = Image.new('RGBA', (WIDTH, 1), (0, 0, 0, alpha)) gradient.paste(line, (0, i)) elif design_gradient == 'top-left': if i < coverage_px: line = Image.new('RGBA', (1, HEIGHT), (0, 0, 0, alpha)) gradient.paste(line, (i, 0)) if i < coverage_py: line = Image.new('RGBA', (WIDTH, 1), (0, 0, 0, max(0, alpha // 2))) gradient.paste(line, (0, i)) elif design_gradient == 'full-bottom': if i < coverage_py: y = HEIGHT - 1 - i line = Image.new('RGBA', (WIDTH, 1), (0, 0, 0, alpha)) gradient.paste(line, (0, y)) bg = Image.alpha_composite(bg, gradient) # --- Text rendering --- font = ImageFont.truetype(font_path, design_font_size) max_text_width = int(WIDTH * 0.8) draw_temp = ImageDraw.Draw(bg) lines = wrap_text(text, font, max_text_width, draw_temp) total_height = len(lines) * design_line_height # Position bottom_y = int(HEIGHT - total_height - HEIGHT * 0.12) positions = { 'top-left': (int(WIDTH * 0.05), int(HEIGHT * 0.08)), 'top-center': (int(WIDTH * 0.05), int(HEIGHT * 0.08)), 'top-right': (int(WIDTH * 0.05), int(HEIGHT * 0.08)), 'center': (int(WIDTH * 0.05), int((HEIGHT - total_height) / 2)), 'center-left': (int(WIDTH * 0.05), int((HEIGHT - total_height) / 2)), 'center-right': (int(WIDTH * 0.05), int((HEIGHT - total_height) / 2)), 'bottom-left': (int(WIDTH * 0.05), bottom_y), 'bottom-center': (int(WIDTH * 0.05), bottom_y), 'bottom-right': (int(WIDTH * 0.05), bottom_y), } x_start, y_start = positions.get(design_position, positions['top-left']) # Horizontal alignment if 'right' in design_position: max_line_w = max(draw_temp.textbbox((0, 0), l, font=font)[2] for l in lines) if lines else 0 x_start = WIDTH - max_line_w - int(WIDTH * 0.05) elif 'center' in design_position and 'left' not in design_position and 'right' not in design_position: max_line_w = max(draw_temp.textbbox((0, 0), l, font=font)[2] for l in lines) if lines else 0 x_start = int((WIDTH - max_line_w) / 2) # --- Shadow / Outline --- if design_shadow_type == 'blur': # Create shadow layer shadow_layer = Image.new('RGBA', (WIDTH, HEIGHT), (0, 0, 0, 0)) shadow_draw = ImageDraw.Draw(shadow_layer) shadow_fill = (*design_shadow_color, design_shadow_opacity) for i, line in enumerate(lines): y = y_start + i * design_line_height lx = x_start if 'center' in design_position and 'left' not in design_position and 'right' not in design_position: lw = shadow_draw.textbbox((0, 0), line, font=font)[2] lx = int((WIDTH - lw) / 2) cur_font = font if i == len(lines) - 1 and design_last_line_scale > 0: bigger = int(design_font_size * (1 + design_last_line_scale / 100)) cur_font = ImageFont.truetype(font_path, bigger) shadow_draw.text((lx + 2, y + 2), line, font=cur_font, fill=shadow_fill) shadow_layer = shadow_layer.filter(ImageFilter.GaussianBlur(radius=design_shadow_size)) bg = Image.alpha_composite(bg, shadow_layer) draw = ImageDraw.Draw(bg) if design_shadow_type == 'outline': for i, line in enumerate(lines): y = y_start + i * design_line_height lx = x_start if 'center' in design_position and 'left' not in design_position and 'right' not in design_position: lw = draw.textbbox((0, 0), line, font=font)[2] lx = int((WIDTH - lw) / 2) cur_font = font if i == len(lines) - 1 and design_last_line_scale > 0: bigger = int(design_font_size * (1 + design_last_line_scale / 100)) cur_font = ImageFont.truetype(font_path, bigger) sz = design_shadow_size for dx in range(-sz, sz + 1): for dy in range(-sz, sz + 1): if dx != 0 or dy != 0: draw.text((lx + dx, y + dy), line, font=cur_font, fill=design_shadow_color) # --- Stroke (borda) --- if design_stroke_enabled: for i, line in enumerate(lines): y = y_start + i * design_line_height lx = x_start if 'center' in design_position and 'left' not in design_position and 'right' not in design_position: lw = draw.textbbox((0, 0), line, font=font)[2] lx = int((WIDTH - lw) / 2) cur_font = font if i == len(lines) - 1 and design_last_line_scale > 0: bigger = int(design_font_size * (1 + design_last_line_scale / 100)) cur_font = ImageFont.truetype(font_path, bigger) sz = design_stroke_size for dx in range(-sz, sz + 1): for dy in range(-sz, sz + 1): if abs(dx) + abs(dy) >= sz: # só bordas externas draw.text((lx + dx, y + dy), line, font=cur_font, fill=design_stroke_color) # --- Main text --- for i, line in enumerate(lines): y = y_start + i * design_line_height lx = x_start if 'center' in design_position and 'left' not in design_position and 'right' not in design_position: lw = draw.textbbox((0, 0), line, font=font)[2] lx = int((WIDTH - lw) / 2) is_last = (i == len(lines) - 1) cur_font = font if is_last and design_last_line_scale > 0: bigger = int(design_font_size * (1 + design_last_line_scale / 100)) cur_font = ImageFont.truetype(font_path, bigger) color = design_highlight_color if (is_last and design_highlight_enabled) else design_text_color draw.text((lx, y), line, font=cur_font, fill=color) # --- Accent line --- if design_accent_enabled: accent_y = y_start + total_height + design_accent_gap draw.rectangle([x_start, accent_y, x_start + design_accent_width, accent_y + design_accent_height], fill=design_accent_color) # --- Brand pill --- brand_font_path = FONT_MAP.get(design_brand_font, FONT_MAP['dejavu']) if not os.path.exists(brand_font_path): brand_font_path = FONT_MAP['dejavu'] brand_font = ImageFont.truetype(brand_font_path, design_brand_size) bbox = draw.textbbox((0, 0), design_brand, font=brand_font) brand_w = bbox[2] - bbox[0] brand_h = bbox[3] - bbox[1] # Brand position margin = 30 if 'right' in design_brand_position: bx = WIDTH - brand_w - margin - 14 elif 'center' in design_brand_position: bx = int((WIDTH - brand_w) / 2) else: # left (default) bx = margin + 14 if 'top' in design_brand_position: by = margin else: # bottom (default) by = HEIGHT - brand_h - margin - 8 bg_pill = Image.new('RGBA', (WIDTH, HEIGHT), (0, 0, 0, 0)) pill_draw = ImageDraw.Draw(bg_pill) pill_draw.rounded_rectangle( [bx - 14, by - 8, bx + brand_w + 14, by + brand_h + 16], radius=8, fill=(0, 0, 0, 180) ) bg = Image.alpha_composite(bg, bg_pill) draw = ImageDraw.Draw(bg) draw.text((bx, by), design_brand, font=brand_font, fill=design_brand_color) # Save as RGB JPEG bg.convert('RGB').save(output_path, 'JPEG', quality=92) return output_path def generate_thumbnail(title, description='', output_path='thumbnail.jpg'): """Pipeline completo: LLM prompt -> IA image -> Pillow compose.""" try: # 1. LLM gera prompt estruturado prompt_data = generate_prompt_json(title, description) print(f' Frase: "{prompt_data["frase_curta"]}"', flush=True) print(f' Cena: {prompt_data["cena_principal"][:80]}...', flush=True) # 2. Gera imagem image_prompt = build_image_prompt(prompt_data) bg = generate_ai_image(image_prompt) # 3. Compoe thumbnail print(' [3/3] Compondo thumbnail...', flush=True) result = compose_thumbnail(bg, prompt_data['frase_curta'], prompt_data.get('cores_dominantes', ''), output_path) # Salva JSON do prompt para referencia json_path = output_path.rsplit('.', 1)[0] + '_prompt.json' with open(json_path, 'w') as f: json.dump(prompt_data, f, ensure_ascii=False, indent=2) print(f' Thumbnail salva: {result}', flush=True) return result except Exception as e: print(f' Erro no pipeline: {e}', file=sys.stderr) print(f' Usando fallback local...', flush=True) bg = create_gradient_bg() result = compose_thumbnail(bg, title[:70], '', output_path) print(f' Thumbnail (fallback): {result}', flush=True) return result if __name__ == '__main__': import argparse parser = argparse.ArgumentParser(description='Gera thumbnail para clip YouTube com IA') parser.add_argument('--title', '-t', required=True, help='Titulo do clip') parser.add_argument('--description', '-d', default='', help='Descricao do conteudo') parser.add_argument('--output', '-o', default='thumbnail.jpg', help='Arquivo de saida') parser.add_argument('--model', '-m', default=None, help='Modelo de imagem') args = parser.parse_args() if args.model: IMAGE_MODEL = args.model generate_thumbnail(args.title, args.description, args.output)