@blackbelt-technology/pi-dashboard-nano-banana

skillmaintained

TypeScript port of the nano-banana-imagegen pi skill. Generate and edit images with Google Gemini image models via the @the-focus-ai/nano-banana CLI, with GEMINI_API_KEY resolution, output-path handling and batch generation. Exposed as a pi skill and the

by · v0.7.0 · published 2w ago

$ pi install npm:@blackbelt-technology/pi-dashboard-nano-banana
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README

@blackbelt-technology/pi-dashboard-nano-banana

TypeScript port of the standalone nano-banana-imagegen pi skill — no Python. Generate and edit images with Google's Gemini image models via the @the-focus-ai/nano-banana CLI, wrapped with automatic GEMINI_API_KEY resolution, output-path handling and bounded-concurrency batch generation.

Exposed two ways:

  • pi skill.pi/skills/nano-banana-imagegen (auto-loads on image-gen requests).
  • CLI binpi-nano-banana.

Usage

pi-nano-banana "a serene mountain landscape at sunset"
pi-nano-banana "add a hot air balloon to the sky" --file photo.jpg
pi-nano-banana "a minimalist logo" --output logo.png --model gemini-2.0-flash-exp

GEMINI_API_KEY (or GOOGLE_API_KEY) resolves from, in order: --api-key, the environment, a project-local .env (cwd + up to two parents), then a package-local .env. Nothing is committed — .env is gitignored.

Programmatic API

import { generateImage, batchGenerate } from "@blackbelt-technology/pi-dashboard-nano-banana/nano-banana.js";

await generateImage({ prompt: "a fox", output: "fox.png" });

await batchGenerate({
  jobs: [
    { name: "hero", prompt: "wide cinematic hero", output: "out/hero.png" },
    { name: "icon", prompt: "flat minimal icon", output: "out/icon.png" },
  ],
  concurrency: 3,
});

batchGenerate powers the storyboard step of @blackbelt-technology/pi-dashboard-video-production.

Prerequisites

  • Node (runs as TypeScript via pi's jiti loader — no build step).
  • Network access for npx to fetch the underlying nano-banana CLI.
  • A Gemini API key from https://aistudio.google.com/apikey.