Files
teamai-test/.teamai/skills/common/gpt-image-2/scripts/generate.js
T

192 lines
5.5 KiB
JavaScript

import process from "node:process";
import {
DEFAULT_IMAGE_DIR,
DEFAULT_MODEL,
buildBaseUrl,
buildDefaultImagePath,
ensureFilesExist,
extractGeneratedBytes,
loadAmbientEnv,
printJson,
readPromptInput,
resolveOutput,
saveImage,
savePrompt,
postJson,
slugify,
} from "./shared.js";
function printHelp() {
console.log(`Usage:
node scripts/generate.js --prompt "A cute baby sea otter" --image out/otter.png
Options:
--prompt <text> Prompt text
--promptfile <path> Load prompt from a file
--prompt-output <path> Save the final prompt to a specific file
--image <path> Output image path (default: ${DEFAULT_IMAGE_DIR}/<slug>-<timestamp>.png)
--model <name> Model override (default: ${DEFAULT_MODEL})
--size <WxH> Output size
--n <count> Number of images
--quality <level> auto | high | medium | low
--background <mode> transparent | opaque | auto
--moderation <level> low | auto
--output-format <format> png | jpeg | webp
--output-compression <0-100> Compression for jpeg/webp
--json Print structured output
-h, --help Show help`);
}
function parseCli(argv) {
const cfg = {
prompt: null,
promptFile: null,
promptOutput: null,
imagePath: null,
model: null,
size: null,
n: null,
quality: null,
background: null,
moderation: null,
outputFormat: null,
outputCompression: null,
json: false,
help: false,
};
for (let i = 0; i < argv.length; i += 1) {
const arg = argv[i];
if (arg === "-h" || arg === "--help") {
cfg.help = true;
continue;
}
if (arg === "--json") {
cfg.json = true;
continue;
}
if (arg === "--prompt") {
cfg.prompt = argv[++i] || null;
if (!cfg.prompt) throw new Error("Missing value for --prompt");
continue;
}
if (arg === "--promptfile") {
cfg.promptFile = argv[++i] || null;
if (!cfg.promptFile) throw new Error("Missing value for --promptfile");
continue;
}
if (arg === "--prompt-output") {
cfg.promptOutput = argv[++i] || null;
if (!cfg.promptOutput) throw new Error("Missing value for --prompt-output");
continue;
}
if (arg === "--image") {
cfg.imagePath = argv[++i] || null;
if (!cfg.imagePath) throw new Error("Missing value for --image");
continue;
}
if (arg === "--model") {
cfg.model = argv[++i] || null;
if (!cfg.model) throw new Error("Missing value for --model");
continue;
}
if (arg === "--size") {
cfg.size = argv[++i] || null;
if (!cfg.size) throw new Error("Missing value for --size");
continue;
}
if (arg === "--n") {
cfg.n = argv[++i] || null;
if (!cfg.n) throw new Error("Missing value for --n");
continue;
}
if (arg === "--quality") {
cfg.quality = argv[++i] || null;
if (!cfg.quality) throw new Error("Missing value for --quality");
continue;
}
if (arg === "--background") {
cfg.background = argv[++i] || null;
if (!cfg.background) throw new Error("Missing value for --background");
continue;
}
if (arg === "--moderation") {
cfg.moderation = argv[++i] || null;
if (!cfg.moderation) throw new Error("Missing value for --moderation");
continue;
}
if (arg === "--output-format") {
cfg.outputFormat = argv[++i] || null;
if (!cfg.outputFormat) throw new Error("Missing value for --output-format");
continue;
}
if (arg === "--output-compression") {
cfg.outputCompression = argv[++i] || null;
if (!cfg.outputCompression) throw new Error("Missing value for --output-compression");
continue;
}
throw new Error(`Unknown option: ${arg}`);
}
return cfg;
}
function buildPayload(cfg, prompt) {
const payload = {
prompt,
model: cfg.model || process.env.OPENAI_IMAGE_MODEL || DEFAULT_MODEL,
};
if (cfg.size) payload.size = cfg.size;
if (cfg.n) payload.n = Number(cfg.n);
if (cfg.quality) payload.quality = cfg.quality;
if (cfg.background) payload.background = cfg.background;
if (cfg.moderation) payload.moderation = cfg.moderation;
if (cfg.outputFormat) payload.output_format = cfg.outputFormat;
if (cfg.outputCompression) payload.output_compression = Number(cfg.outputCompression);
return payload;
}
function buildRequestUrl() {
return `${buildBaseUrl()}/images/generations`;
}
async function run() {
const cfg = parseCli(process.argv.slice(2));
if (cfg.help) {
printHelp();
return;
}
await loadAmbientEnv();
const prompt = await readPromptInput(cfg.prompt, cfg.promptFile);
const nameHint = slugify(prompt.split(/\s+/).slice(0, 8).join(" "), "generated-image");
const promptPath = await savePrompt(prompt, cfg.promptOutput, nameHint);
const outputPath = resolveOutput(cfg.imagePath, buildDefaultImagePath("generate", nameHint));
await ensureFilesExist([], "input");
const payload = buildPayload(cfg, prompt);
const url = buildRequestUrl();
const json = await postJson(url, payload);
const bytes = await extractGeneratedBytes(json);
await saveImage(outputPath, bytes);
if (cfg.json) {
printJson({
savedImage: outputPath,
savedPrompt: promptPath,
model: payload.model,
requestUrl: url,
apiResponse: json,
});
return;
}
console.log(outputPath);
}
run().catch((error) => {
const message = error instanceof Error ? error.message : String(error);
console.error(message);
process.exit(1);
});