feat(mockup): add OpenAI Codex (gpt-5.6-sol + built-in image_gen) raster mockup generator
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@@ -1,21 +1,28 @@
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import * as fs from "node:fs";
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import * as path from "node:path";
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import * as os from "node:os";
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import { spawn } from "node:child_process";
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import { GoogleGenAI } from "@google/genai";
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export const NANO_BANANA_MODELS = [
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{
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id: "codex-image-gen",
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label: "OpenAI Codex (gpt-5.6-sol + Built-in image_gen) — Recommended",
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description: "codex-image-gen — High-resolution photorealistic raster PNG product & apparel mockups via OpenAI Codex built-in image_gen"
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},
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{
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id: "gemini-nano-banana-2.1",
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label: "Nano Banana 2.1 (Default High-Efficiency + Free-Tier Auto Fallback)",
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label: "Nano Banana 2.1 (Google Gemini + Free-Tier Auto Fallback)",
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description: "gemini-nano-banana-2.1 — Uses native Nano Banana 2.1 on Tier 1 keys, with automatic Gemini 3.1 Flash-Lite Vector Mockup fallback on Free Tier keys"
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},
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{
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id: "gemini-3-pro-image",
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label: "Nano Banana Pro (Studio Quality)",
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label: "Nano Banana Pro (Gemini Studio Quality)",
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description: "gemini-3-pro-image — High-detail studio mockup generation and multi-turn editing"
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},
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{
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id: "gemini-3.1-flash-lite-image",
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label: "Nano Banana 2 Lite (Ultra-Fast)",
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label: "Nano Banana 2 Lite (Gemini Ultra-Fast)",
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description: "gemini-3.1-flash-lite-image — Rapid concept sketching and quick iterations"
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}
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];
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@@ -88,6 +95,149 @@ export function buildNanoBananaPrompt({
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return finalPrompt;
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}
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export function isCodexConfigured() {
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const codexHome = process.env.CODEX_HOME || path.join(os.homedir(), ".codex");
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return fs.existsSync(path.join(codexHome, "auth.json"));
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}
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function findNewestGeneratedImage(generatedImagesRoot, startedAtMs) {
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if (!fs.existsSync(generatedImagesRoot)) return null;
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let newestFile = null;
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let newestMtime = 0;
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for (const entry of fs.readdirSync(generatedImagesRoot, { withFileTypes: true })) {
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const fullEntry = path.join(generatedImagesRoot, entry.name);
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if (entry.isDirectory()) {
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for (const sub of fs.readdirSync(fullEntry, { withFileTypes: true })) {
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if (sub.isFile() && /\.(png|jpg|jpeg|webp)$/i.test(sub.name)) {
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const candidate = path.join(fullEntry, sub.name);
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const stat = fs.statSync(candidate);
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if (stat.mtimeMs >= startedAtMs - 2000 && stat.mtimeMs > newestMtime) {
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newestMtime = stat.mtimeMs;
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newestFile = candidate;
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}
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}
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}
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} else if (entry.isFile() && /\.(png|jpg|jpeg|webp)$/i.test(entry.name)) {
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const stat = fs.statSync(fullEntry);
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if (stat.mtimeMs >= startedAtMs - 2000 && stat.mtimeMs > newestMtime) {
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newestMtime = stat.mtimeMs;
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newestFile = fullEntry;
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}
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}
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}
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return newestFile;
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}
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/**
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* Generates or edits a high-resolution raster PNG mockup using OpenAI Codex CLI
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* (`codex exec -m gpt-5.6-sol`) and its built-in `image_gen` tool.
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*/
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export async function generateWithCodex({
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prompt,
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referenceImagePath = null,
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outputDir
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}) {
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const codexHome = process.env.CODEX_HOME || path.join(os.homedir(), ".codex");
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const generatedImagesRoot = path.join(codexHome, "generated_images");
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const startedAtMs = Date.now();
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const instruction = referenceImagePath && fs.existsSync(referenceImagePath)
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? `Use the built-in image_gen tool right now to edit the attached reference image according to this instruction: ${prompt}. Do not run any shell commands, just call image_gen and reply DONE.`
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: `Use the built-in image_gen tool right now to generate this image: ${prompt}. Do not run any shell commands, just call image_gen and reply DONE.`;
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const args = [
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"exec",
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"-m",
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process.env.CODEX_MODEL || "gpt-5.6-sol",
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"--skip-git-repo-check",
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"--json"
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];
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if (referenceImagePath && fs.existsSync(referenceImagePath) && !referenceImagePath.endsWith(".svg")) {
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args.push("-i", referenceImagePath);
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}
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args.push(instruction);
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const { stdout, stderr, exitCode } = await new Promise((resolve, reject) => {
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const child = spawn("codex", args, {
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stdio: ["ignore", "pipe", "pipe"],
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env: { ...process.env }
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});
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let out = "";
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let err = "";
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child.stdout.on("data", (d) => {
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out += d.toString();
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});
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child.stderr.on("data", (d) => {
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err += d.toString();
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});
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child.on("error", reject);
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child.on("close", (code) => {
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resolve({ stdout: out, stderr: err, exitCode: code });
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});
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});
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// Extract thread_id from JSONL stdout
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let threadId = null;
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let lastAgentText = null;
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for (const line of stdout.split("\n")) {
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const trimmed = line.trim();
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if (!trimmed.startsWith("{")) continue;
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try {
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const evt = JSON.parse(trimmed);
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if (evt.type === "thread.started" && evt.thread_id) {
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threadId = evt.thread_id;
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} else if (evt.type === "item.completed" && evt.item?.type === "agent_message") {
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lastAgentText = evt.item.text;
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}
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} catch {
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// ignore non-json lines
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}
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}
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let sourceImagePath = null;
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if (threadId) {
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const threadDir = path.join(generatedImagesRoot, threadId);
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if (fs.existsSync(threadDir)) {
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const files = fs
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.readdirSync(threadDir)
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.filter((f) => /\.(png|jpg|jpeg|webp)$/i.test(f))
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.map((f) => path.join(threadDir, f));
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if (files.length > 0) {
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sourceImagePath = files[files.length - 1];
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}
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}
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}
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if (!sourceImagePath) {
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sourceImagePath = findNewestGeneratedImage(generatedImagesRoot, startedAtMs);
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}
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if (!sourceImagePath || !fs.existsSync(sourceImagePath)) {
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throw new Error(
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`Codex completed (exit ${exitCode}) without saving an image. ${stderr || lastAgentText || ""}`.trim()
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);
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}
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const ext = path.extname(sourceImagePath).replace(/^\./, "") || "png";
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const filename = `codex-${Date.now()}-${Math.random().toString(36).slice(2, 7)}.${ext}`;
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const fullPath = path.join(outputDir, filename);
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fs.mkdirSync(outputDir, { recursive: true });
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fs.copyFileSync(sourceImagePath, fullPath);
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return {
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filename,
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imageUrl: `/mockups/${filename}`,
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mimeType: `image/${ext === "jpg" ? "jpeg" : ext}`,
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modelUsed: "OpenAI Codex (gpt-5.6-sol / image_gen)",
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interactionId: threadId,
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textNotes: "Generated high-resolution raster PNG via OpenAI Codex built-in image_gen."
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};
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}
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function extractSvgBlock(text) {
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if (!text) return null;
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const match = String(text).match(/<svg[\s\S]*?<\/svg>/i);
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@@ -124,7 +274,7 @@ async function generateFreeTierSvgMockup({
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: "",
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"DESIGN RULES:",
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"1. Include a sleek studio backdrop (`#121621` radial gradient).",
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"2. If the brief mentions a t-shirt, draw a realistic, well-proportioned crewneck t-shirt silhouette with collar ribbing, sleeve seams, subtle fabric shading, and the requested garment hex color. Place the custom screenprint illustration and vintage typography either full-front (`cx=400, cy=360`) or in the 5-inch left-chest pocket zone (`cx=490, cy=285`, scaled compactly) according to the brief.",
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"2. If the brief mentions a t-shirt, draw a realistic, well-proponed crewneck t-shirt silhouette with collar ribbing, sleeve seams, subtle fabric shading, and the requested garment hex color. Place the custom screenprint illustration and vintage typography either full-front (`cx=400, cy=360`) or in the 5-inch left-chest pocket zone (`cx=490, cy=285`, scaled compactly) according to the brief.",
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"3. If the brief is a sticker, poster, or app UI, draw the realistic die-cut border, gallery frame, or device frame accordingly.",
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"4. Draw rich, multi-layered custom vector illustration paths, badges, emblems, stars/mountains/icons, and bold screenprint typography with high contrast against the garment/surface color.",
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"5. Return ONLY the raw `<svg xmlns=\"http://www.w3.org/2000/svg\" viewBox=\"0 0 800 800\">...</svg>` code block with no markdown explanation."
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@@ -153,29 +303,44 @@ async function generateFreeTierSvgMockup({
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mimeType: "image/svg+xml",
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modelUsed: "gemini-3.1-flash-lite (Free-Tier Vector Mockup)",
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interactionId: interaction.id || null,
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textNotes: "Generated via Gemini 3.1 Flash-Lite Vector Studio (Free Tier key detected; enable Tier 1 billing in Google AI Studio for raster Nano Banana 2.1)."
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textNotes: "Generated via Gemini 3.1 Flash-Lite Vector Studio."
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};
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}
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/**
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* Generates or edits an image using Google Gemini Nano Banana (`gemini-nano-banana-2.1`)
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* via the official `@google/genai` Interactions API (`ai.interactions.create`),
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* with automatic fallback to `gemini-3.1-flash-lite` vector mockup generation when
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* a Free Tier key hits `limit: 0`.
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* Generates or edits an image using:
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* 1. OpenAI Codex (`codex-image-gen`) built-in `image_gen` tool (default when selected or when Codex auth is available), OR
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* 2. Google Gemini Nano Banana (`gemini-nano-banana-2.1`) with automatic fallback to `Codex` or `gemini-3.1-flash-lite` SVG when Free Tier quota is 0.
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*/
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export async function generateWithNanoBanana({
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apiKey,
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model = "gemini-nano-banana-2.1",
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model = "codex-image-gen",
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prompt,
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referenceImagePath = null,
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referenceImageBase64 = null,
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referenceMimeType = "image/png",
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outputDir
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}) {
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// 1. Primary path: OpenAI Codex built-in image_gen
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if (model === "codex-image-gen" || (!apiKey && isCodexConfigured())) {
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return await generateWithCodex({
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prompt,
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referenceImagePath,
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outputDir
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});
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}
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const resolvedKey = apiKey || process.env.GEMINI_API_KEY || process.env.GOOGLE_API_KEY;
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if (!resolvedKey) {
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if (isCodexConfigured()) {
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return await generateWithCodex({
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prompt,
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referenceImagePath,
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outputDir
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});
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}
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const err = new Error(
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"No Gemini API key configured. Click '🍌 Nano Banana' in the top bar (or set GEMINI_API_KEY) to generate live mockups, or use the Interactive T-Shirt Canvas Compositor."
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"No AI image provider configured. Select 'OpenAI Codex (image_gen)' or configure a Gemini API key in Settings."
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);
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err.code = "MISSING_API_KEY";
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throw err;
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@@ -242,8 +407,15 @@ export async function generateWithNanoBanana({
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};
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} catch (err) {
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const msg = String(err?.message || "");
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// If Free Tier quota is 0 for native raster image models, seamlessly fall back to Gemini 3.1 Flash-Lite SVG Vector Mockup!
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if (msg.includes("429") || msg.includes("Free Tier") || msg.includes("limit: 0") || msg.includes("quota")) {
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// If OpenAI Codex is authenticated on this host, prefer high-res raster generation via Codex!
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if (isCodexConfigured()) {
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return await generateWithCodex({
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prompt,
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referenceImagePath,
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outputDir
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});
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}
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return await generateFreeTierSvgMockup({
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ai,
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prompt,
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