open-image 0.5.0

Tiny CLI for OpenAI image generation. Prompt in, PNG out. Model-agnostic.

open-image

Tiny CLI for OpenAI image generation. Prompt in, PNG out. Model-agnostic.

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Why another CLI?

Every serious image-gen workflow needs a stable, forgettable command — one you can pipe into, script around, and re-run six months later without rewriting. The official SDKs are fine for apps; they're heavy for "just give me a PNG."

open-image is ~340 lines of Python, pure stdlib + openai — one file for the CLI (gen.py), two tiny stdlib-only helpers for the Claude Code skill. No framework, no config, no lock-in to a specific model.

pip install open-image
export OPENAI_API_KEY=sk-...
open-image --prompt "a red fox in a snowy forest, cinematic"
# → /abs/path/output/20260423-223012-a1b2c3d4.png

That's it.

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Features

Four ways to feed a prompt

Method	Example
Inline	open-image --prompt "a red fox in snow"
File	open-image --prompt-file prompts/scene.txt
Stdin	echo "a blue cat" | open-image
Editor	open-image (no args in a TTY → opens $EDITOR, or notepad on Windows, vi otherwise)

The resolver picks them in that order. Lines starting with # in the editor buffer are stripped — write notes to yourself without polluting the prompt.

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Model-agnostic by design

--model is a flag, not a constant. The day a new image model ships, swap the string — no code change, no version bump, no fork:

open-image --model gpt-image-2   --prompt "..."   # default; requires org verification
open-image --model gpt-image-1   --prompt "..."   # transparency, output_format support
open-image --model future-model  --prompt "..."   # whenever it arrives

Default is gpt-image-2. Change per call, or alias open-image='open-image --model gpt-image-1' in your shell if you prefer a different default.

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Curated styles + aspect shortcuts

Quick prompt modifiers — no need to memorize style fragments or --extra JSON for common sizes:

# Style preset: appends "3D render, octane render, hyperrealistic detail, 8k" to the prompt
open-image --style 3d-render --prompt "a cat astronaut"

# Aspect shortcut: equivalent to --extra '{"size":"1024x1792"}'
open-image --portrait --prompt "a tall waterfall"

# Combine freely — portrait 3D render
open-image --style 3d-render --portrait --prompt "a cat astronaut"

# Discover what's available
open-image --list-styles

8 styles: 3d-render, anime, watercolor, cyberpunk, photoreal, sketch, oil-painting, minimalist. Hard-capped at 10 forever — for more variety, use --extra or write style words directly in your prompt. This isn't a style library.

3 aspect flags: --portrait (1024×1792), --landscape (1792×1024), --square (1024×1024). Mutually exclusive. If you also pass --extra '{"size":...}', your --extra value wins (explicit beats implicit). Filename slug always derives from the original prompt, never the style-augmented one — so filenames stay short and readable.

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--extra escape hatch

Any keyword the API accepts, --extra forwards verbatim to openai.images.generate(**params). Zero client-side validation — the API is the source of truth:

open-image \
  --model gpt-image-2 \
  --extra '{"size":"1024x1024","quality":"high"}' \
  --prompt "a lone surfer at dawn, Hokusai woodblock style"

open-image \
  --model gpt-image-1 \
  --extra '{"size":"1024x1024","output_format":"png","transparency":true}' \
  --prompt "a minimalist cat icon on a transparent background"

If you pass a wrong key, the API error surfaces verbatim — exactly what you want for debugging. No wrapper in the way.

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Install

From PyPI (recommended)

pip install open-image

With pipx (isolated global command)

pipx install open-image

From source

git clone https://github.com/tvtdev94/open-image
cd open-image
pip install -e .

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Setup

Set your OpenAI API key (must have image-generation credit):

# Option A — environment variable (recommended)
export OPENAI_API_KEY=sk-...

# Option B — per-call flag
open-image --api-key sk-... --prompt "..."

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Flags

Flag	Default	Purpose
--prompt	—	Inline prompt text
--prompt-file	—	Path to a file containing the prompt
--model	gpt-image-2	Any OpenAI image model (gpt-image-2, gpt-image-1, dall-e-3, dall-e-2, …)
--extra	{}	JSON object forwarded to images.generate
--out-dir	./output	Where to save PNGs (auto-created)
--api-key	$OPENAI_API_KEY	Override via flag if not in env
--keep	50	Keep only N newest PNGs in --out-dir after save; 0 disables pruning
--name	auto-derived from prompt	Custom slug for output filename (kebab-case, ASCII)
--style	—	Append a curated prompt fragment (one of 8 — run --list-styles)
--list-styles	—	List known styles with full fragments, then exit
--portrait	—	Shortcut for --extra '{"size":"1024x1792"}' (mutually exclusive with --landscape/--square)
--landscape	—	Shortcut for --extra '{"size":"1792x1024"}'
--square	—	Shortcut for --extra '{"size":"1024x1024"}'
--list-models	—	List known OpenAI image models with notes, then exit
--install-skill	—	Re-install Claude Code skill at ~/.claude/skills/open-image/ (overwrites)

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Output

./output/{YYYYMMDD-HHMMSS}-{slug}-{uuid8}.png

{slug} is auto-derived from the prompt (kebab-case, ASCII-folded, max 40 chars — handles diacritics, Vietnamese horn/stroke letters, emoji-stripped, falls back to image). Override with --name "my-slug".

One PNG per response.data item (so n=4 → four files). Absolute path(s) printed to stdout, one per line — friendly to xargs, fzf, wl-copy, whatever you pipe into.

open-image --prompt "a red fox in snowy forest"
# → ./output/20260426-183246-a-red-fox-in-snowy-forest-a1b2c3d4.png

open-image --prompt "anything" --name "hero-shot"
# → ./output/20260426-183246-hero-shot-a1b2c3d4.png

open-image --prompt "a corgi" | tee -a log.txt
open-image --prompt "a corgi" | head -n1 | xargs -I{} open {}    # macOS preview

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Gallery

All generated by open-image with gpt-image-2:

A close-up cinematic macro of a bee hovering over a lotus at sunrise.	A bustling night market in a cyberpunk Hanoi alleyway.

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Error handling

Every error path exits with a clear, actionable message:

• No API key → ERROR: No API key. Set OPENAI_API_KEY env or pass --api-key.
• --extra not valid JSON → parser error with column offset
• Empty prompt → ERROR: Empty prompt.
• API failure (auth, model access, invalid params) → API error string forwarded verbatim
• Un-writable --out-dir → PermissionError surfaced with the path

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Models supported

The CLI is model-agnostic — --model accepts any string. These are the models known at write time; pass any future model ID without a code change.

Model	Notes
gpt-image-2	Default. Requires org verification on OpenAI dashboard. Returns b64_json.
gpt-image-1	Newer GPT image model. Supports input_fidelity, transparency, output_format.
dall-e-3	n=1 only. Sizes: 1024x1024 / 1792x1024 / 1024x1792. quality: standard / hd. style: vivid / natural. Pass response_format=b64_json via --extra for offline storage.
dall-e-2	n>1 supported. Sizes: 256x256 / 512x512 / 1024x1024.

Run open-image --list-models to print this table at any time.

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Claude Code integration

If you use Claude Code, open-image ships a Claude skill that teaches the agent how to use this CLI — no manual prompt setup.

• Zero-step install: pip install open-image is enough. On the next Python startup (any Python invocation on that machine — no CLI required), the skill is silently written to ~/.claude/skills/open-image/SKILL.md. Skipped entirely if ~/.claude/ doesn't exist.
• Auto-update on upgrade: pip install -U open-image → next Python startup → skill content auto-syncs to the new version. No manual step.
• Force re-install (rarely needed, e.g. after editing the skill): open-image --install-skill.

Once installed, Claude Code knows when to call open-image, which models exist, how --extra works, and how to capture the stdout paths.

How it works (transparency)

open-image ships a tiny .pth file to your Python site-packages/ so the skill is synced on every Python startup (idempotent — only writes when content changes). Cost: a couple of stat() calls per Python startup, sub-millisecond. Removing the package via pip uninstall open-image removes the .pth and stops the sync.

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Philosophy

Three principles:

• YAGNI — no MCP server, no HTTP wrapper, no runtime plugins. The optional Claude Code skill is just markdown — Claude reads it, no daemon, no IPC. If your agent has a shell, it can use this.
• KISS — argparse + stdlib + one SDK call. Zero abstractions between you and the API.
• DRY — --extra means the tool never needs a new flag per new API param.

The whole tool fits in your head. When a future model adds a parameter, you already know how to use it.

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License

MIT © 2026 tvtdev94