#!/usr/bin/env python3
import argparse
import base64
import datetime as dt
import json
import os
import random
import re
import sys
import urllib.error
import urllib.request
from pathlib import Path
def slugify(text: str) -> str:
text = text.lower().strip()
text = re.sub(r"[^a-z0-9]+", "-", text)
text = re.sub(r"-{2,}", "-", text).strip("-")
return text or "image"
def default_out_dir() -> Path:
now = dt.datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
preferred = Path.home() / "Projects" / "tmp"
base = preferred if preferred.is_dir() else Path("./tmp")
base.mkdir(parents=True, exist_ok=True)
return base / f"openai-image-gen-{now}"
def pick_prompts(count: int) -> list[str]:
subjects = [
"a lobster astronaut",
"a brutalist lighthouse",
"a cozy reading nook",
"a cyberpunk noodle shop",
"a Vienna street at dusk",
"a minimalist product photo",
"a surreal underwater library",
]
styles = [
"ultra-detailed studio photo",
"35mm film still",
"isometric illustration",
"editorial photography",
"soft watercolor",
"architectural render",
"high-contrast monochrome",
]
lighting = [
"golden hour",
"overcast soft light",
"neon lighting",
"dramatic rim light",
"candlelight",
"foggy atmosphere",
]
prompts: list[str] = []
for _ in range(count):
prompts.append(
f"{random.choice(styles)} of {random.choice(subjects)}, {random.choice(lighting)}"
)
return prompts
def request_images(
api_key: str,
prompt: str,
model: str,
size: str,
quality: str,
) -> dict:
url = "https://api.openai.com/v1/images/generations"
body = json.dumps(
{
"model": model,
"prompt": prompt,
"size": size,
"quality": quality,
"n": 1,
"response_format": "b64_json",
}
).encode("utf-8")
req = urllib.request.Request(
url,
method="POST",
headers={
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
},
data=body,
)
try:
with urllib.request.urlopen(req, timeout=300) as resp:
return json.loads(resp.read().decode("utf-8"))
except urllib.error.HTTPError as e:
payload = e.read().decode("utf-8", errors="replace")
raise RuntimeError(f"OpenAI Images API failed ({e.code}): {payload}") from e
def write_gallery(out_dir: Path, items: list[dict]) -> None:
thumbs = "\n".join(
[
f"""
{it["prompt"]}
""".strip()
for it in items
]
)
html = f"""
openai-image-gen
openai-image-gen
Output: {out_dir.as_posix()}
{thumbs}
"""
(out_dir / "index.html").write_text(html, encoding="utf-8")
def main() -> int:
ap = argparse.ArgumentParser(description="Generate images via OpenAI Images API.")
ap.add_argument("--prompt", help="Single prompt. If omitted, random prompts are generated.")
ap.add_argument("--count", type=int, default=8, help="How many images to generate.")
ap.add_argument("--model", default="gpt-image-1", help="Image model id.")
ap.add_argument("--size", default="1024x1024", help="Image size (e.g. 1024x1024, 1536x1024).")
ap.add_argument("--quality", default="high", help="Image quality (varies by model).")
ap.add_argument("--out-dir", default="", help="Output directory (default: ./tmp/openai-image-gen-).")
args = ap.parse_args()
api_key = (os.environ.get("OPENAI_API_KEY") or "").strip()
if not api_key:
print("Missing OPENAI_API_KEY", file=sys.stderr)
return 2
out_dir = Path(args.out_dir).expanduser() if args.out_dir else default_out_dir()
out_dir.mkdir(parents=True, exist_ok=True)
prompts = [args.prompt] * args.count if args.prompt else pick_prompts(args.count)
items: list[dict] = []
for idx, prompt in enumerate(prompts, start=1):
print(f"[{idx}/{len(prompts)}] {prompt}")
res = request_images(api_key, prompt, args.model, args.size, args.quality)
b64 = res.get("data", [{}])[0].get("b64_json")
if not b64:
raise RuntimeError(f"Unexpected response: {json.dumps(res)[:400]}")
png = base64.b64decode(b64)
filename = f"{idx:03d}-{slugify(prompt)[:40]}.png"
(out_dir / filename).write_bytes(png)
items.append({"prompt": prompt, "file": filename})
(out_dir / "prompts.json").write_text(json.dumps(items, indent=2), encoding="utf-8")
write_gallery(out_dir, items)
print(f"\nWrote: {(out_dir / 'index.html').as_posix()}")
return 0
if __name__ == "__main__":
raise SystemExit(main())