#!/usr/bin/env python3 """ Venus A-4 (Social Proof) — Meta Carousel Slide Bright cream/white background, testimonial quote cards with gold accents Hybrid: Gemini background + Playwright HTML overlay Output: 1080x1080 PNG → /home/jay/workspace/output/meta-ads/a-group-venus/venus-A4-proof.png """ import base64 import sys import time from pathlib import Path import requests from playwright.sync_api import sync_playwright from gen_config import WORKSPACE_ROOT, FONT_DIR, CTA_MIN_PX # ── paths ────────────────────────────────────────────────────────────────────── OUTPUT_DIR = WORKSPACE_ROOT / "output/meta-ads/a-group-venus" BG_PATH = OUTPUT_DIR / "_bg_venus_a4_proof.jpg" HTML_PATH = OUTPUT_DIR / "_venus_a4_proof_template.html" OUT_PATH = OUTPUT_DIR / "venus-A4-proof.png" OUTPUT_DIR.mkdir(parents=True, exist_ok=True) # ── Gemini config ────────────────────────────────────────────────────────────── sys.path.insert(0, str(WORKSPACE_ROOT / "tools/ai-image-gen")) import gcloud_auth # noqa: E402 GEMINI_API_BASE = "https://generativelanguage.googleapis.com/v1beta" MODEL_PRIMARY = "gemini-3-pro-image-preview" MODEL_FALLBACK = "gemini-3.1-flash-image-preview" SCOPE = "https://www.googleapis.com/auth/generative-language" BG_PROMPT = """ Create a warm, serene, light-toned abstract background for a premium Korean insurance team advertisement. COMPOSITION: 1:1 square, 1080x1080px. Full bleed. No text, no people, no faces. VISUAL CONCEPT: A bright, airy cream and off-white background suffused with soft golden light rays gently streaming downward from the upper area of the canvas. Minimal, clean, and sophisticated. Like warm morning sunlight filtering through sheer curtains in an elegant space. BACKGROUND ELEMENTS: - Warm cream / off-white base (#F5F0E8 to #FAFAF5) — light, airy, and calming - Soft golden light rays (#C9A84C tones at very low opacity, ~10-15%) streaming diagonally from upper-left to center, creating a gentle glow without harshness _SIZE_26PX = 26 _SIZE_34PX = 34 _CTA_PX = CTA_MIN_PX _SIZE_44PX = 44 _SIZE_66PX = 66 _SIZE_80PX = 80 _LH_1 = 1 _LH_1_20 = 1.20 _LH_0_65 = 0.65 _LH_1_52 = 1.52 _LH_1_50 = 1.50 - Very subtle warm beige texture — like fine linen or smooth matte paper surface - Gentle gradient: slightly warmer (more golden-ivory) at center, fading to pure cream at edges - Top zone (top 20%): slightly lighter/cleaner area for text readability on light background - Bottom zone: barely perceptible warm ivory shadow, soft and non-distracting - Overall feel: low-saturation, minimal, photographic quality — background recedes behind content MOOD / ATMOSPHERE: - Trust. Transparency. Credibility. Warmth. - Clean premium consulting feel — trustworthy and human - "Real results, real people" — intimate and credible, not hype-filled - Like a bright, beautifully lit minimalist studio where genuine testimonials were shared COLOR PALETTE: - Primary base: Warm cream (#F5F0E8), off-white (#FAFAF5), ivory (#F0EBE0) - Accent glow: Very subtle golden-amber (#C9A84C at 8-12% opacity) as soft light wash - No dark tones, no navy, no deep shadows - No cool gray, no blue — pure warm cream/ivory family only - Maximum luminosity; bright but never harsh or clinical white STYLE REQUIREMENTS: - NO stock photography aesthetic - NO people, faces, hands, or human figures - NO text, numbers, or labels - NO dark backgrounds or high contrast zones - Minimalist, ultra-premium advertising quality — background is supportive, not dominant - Photographic texture quality — fine, subtle, warm - The testimonial cards will overlay this background, so keep it clean and uncluttered """ # ── Step 1: Generate Gemini background ──────────────────────────────────────── def generate_background() -> Path: if BG_PATH.exists(): print(f"[BG] 기존 배경 이미지 재사용: {BG_PATH}") return BG_PATH print("[BG] Gemini API로 배경 이미지 생성 중...") token = gcloud_auth.get_service_account_token(SCOPE) def _call(model_id: str) -> requests.Response: url = f"{GEMINI_API_BASE}/models/{model_id}:generateContent" headers = { "Authorization": f"Bearer {token}", "Content-Type": "application/json", } payload = { "contents": [{"parts": [{"text": BG_PROMPT}]}], "generationConfig": {"responseModalities": ["IMAGE", "TEXT"]}, } return requests.post(url, headers=headers, json=payload, timeout=300) t0 = time.time() resp = _call(MODEL_PRIMARY) if resp.status_code in (403, 404): print(f"[BG] Pro 모델 실패 (HTTP {resp.status_code}), fallback 시도...") resp = _call(MODEL_FALLBACK) resp.raise_for_status() data = resp.json() candidates = data.get("candidates", []) if not candidates: raise RuntimeError(f"candidates 없음: {str(data)[:300]}") parts = candidates[0].get("content", {}).get("parts", []) img_part = next((p for p in parts if "inlineData" in p), None) if img_part is None: texts = [p.get("text", "") for p in parts if "text" in p] raise RuntimeError(f"이미지 없음. 텍스트 응답: {texts[:2]}") mime = img_part["inlineData"].get("mimeType", "image/jpeg") b64 = img_part["inlineData"]["data"] ext = ".jpg" if "jpeg" in mime else ".png" fpath = BG_PATH.with_suffix(ext) fpath.write_bytes(base64.b64decode(b64)) print(f"[BG] 완료: {fpath.name} ({fpath.stat().st_size:,} bytes, {time.time()-t0:.1f}초)") return fpath # ── Step 2: Build HTML overlay ────────────────────────────────────────────────── def build_html(bg_path: Path) -> str: bg_url = f"file://{bg_path.resolve()}" font_dir = str(FONT_DIR) return f"""
서울대보험쌤

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이제는 고객을 선택합니다.
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4/5
""" def write_html(bg_path: Path) -> Path: html_content = build_html(bg_path) HTML_PATH.write_text(html_content, encoding="utf-8") print(f"[HTML] 오버레이 저장: {HTML_PATH}") return HTML_PATH # ── Step 3: Playwright screenshot ───────────────────────────────────────────── def capture(html_path: Path, out_path: Path) -> None: print("[RENDER] Playwright 캡처 시작...") with sync_playwright() as p: browser = p.chromium.launch() try: page = browser.new_page(viewport={"width": 1080, "height": 1080}) page.goto(f"file://{html_path.resolve()}", wait_until="networkidle") # Wait for fonts and rendering page.evaluate("async () => { await document.fonts.ready; }") page.wait_for_timeout(2500) out_path.parent.mkdir(parents=True, exist_ok=True) page.screenshot( path=str(out_path), type="png", clip={"x": 0, "y": 0, "width": 1080, "height": 1080}, ) finally: browser.close() size_kb = out_path.stat().st_size / 1024 print(f"[RENDER] 완료: {out_path} ({size_kb:.0f} KB)") # ── Main ─────────────────────────────────────────────────────────────────────── if __name__ == "__main__": t_start = time.time() print("=" * 60) print("Venus A-4 (Social Proof) — 하이브리드 이미지 생성") print(f"출력: {OUT_PATH}") print("=" * 60) bg = generate_background() html = write_html(bg) capture(html, OUT_PATH) elapsed = time.time() - t_start print(f"\n[완료] {OUT_PATH.name} ({elapsed:.1f}초 총 소요)")