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

Project description

open-image

open-image

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

PyPI version Python versions MIT license GitHub stars

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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.


Features

Four ways to feed a prompt

four input methods

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.


Model-agnostic by design

model-agnostic 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.


--extra escape hatch

extra param forwarding

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.


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 .

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 "..."

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)
--list-models List known OpenAI image models with notes, then exit
--install-skill Re-install Claude Code skill at ~/.claude/skills/open-image/ (overwrites)

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

Gallery

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

sample gallery

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

Error handling

Every error path exits with a clear, actionable message:

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

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.


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.


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.


License

MIT © 2026 tvtdev94

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