photopea-embedded-editor
Embed Photopea in web apps using photopea.js. Covers embedding, file I/O, scripting, exporting, layers, text, filters, and the full Photoshop-compatible API.
What this skill does
# Photopea Embedded Editor Skill ## Using photopea.js (yikuansun/PhotopeaAPI) in Websites & Apps --- ## When to Use This Skill Use this skill for **every task** that involves: - Embedding Photopea as an image editor inside a webpage or web app - Controlling an embedded Photopea instance from your JavaScript code - Automating image editing workflows from a host page (open files, run scripts, export results) - Building an image editing feature into your product using Photopea as the engine - Writing scripts to manipulate documents, layers, text, selections, filters, colors, and paths **Do NOT** use raw `postMessage` wiring — always use `photopea.js` as the wrapper. --- ## Library: photopea.js `photopea.js` is a Promises-based JavaScript wrapper around the Photopea Live Messaging API. Repository: https://github.com/yikuansun/PhotopeaAPI npm package: https://www.npmjs.com/package/photopea ### Installation **CDN (no build step)** ```html <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/photopea.min.js"></script> ``` **Self-hosted** ```html <script src="./photopea.min.js"></script> ``` **npm (Webpack / Vite / Rollup)** ```bash npm install photopea ``` ```js import Photopea from "photopea"; ``` --- ## Core API: The `Photopea` Class | Method | Description | |--------|-------------| | `Photopea.createEmbed(container)` | Creates + injects the iframe, resolves when ready | | `new Photopea(window.parent)` | Plugin mode: wrap the parent window | | `pea.runScript(script)` | Run JS string inside Photopea; returns output array | | `pea.loadAsset(arrayBuffer)` | Load binary file (image, font, brush, etc.) | | `pea.openFromURL(url, asSmart)` | Open remote URL as new doc or smart object layer | | `pea.exportImage(type)` | Export current doc; returns `Blob` (`"png"` or `"jpg"`) | All methods return Promises — always `await` or `.then()`. --- ## Step 1 — Embed The container `<div>` **must** have a fixed width and height before calling `createEmbed`. ```html <div id="editor" style="width:1000px; height:650px;"></div> <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/photopea.min.js"></script> <script> Photopea.createEmbed(document.getElementById("editor")).then(async (pea) => { // pea is ready }); </script> ``` **React:** ```jsx import { useEffect, useRef } from "react"; import Photopea from "photopea"; export default function Editor() { const containerRef = useRef(null); const peaRef = useRef(null); useEffect(() => { if (!containerRef.current || peaRef.current) return; Photopea.createEmbed(containerRef.current).then((pea) => { peaRef.current = pea; }); }, []); return <div ref={containerRef} style={{ width: "100%", height: "650px" }} />; } ``` --- ## Step 2 — Opening Files ```js // Remote URL → new document await pea.openFromURL("https://example.com/design.psd", false); // Remote URL → smart object layer inside current document await pea.openFromURL("https://example.com/overlay.png", true); // Local file (user input → ArrayBuffer → loadAsset) document.getElementById("fileInput").addEventListener("change", async (e) => { const buf = await e.target.files[0].arrayBuffer(); await pea.loadAsset(buf); }); // Base64 data URI via runScript await pea.runScript(`app.open("data:image/png;base64,iVBORw0...");`); ``` --- ## Step 3 — Running Scripts `runScript` sends a JS string, returns an array of `app.echoToOE(...)` values + `"done"` last. ```js const result = await pea.runScript(`app.echoToOE("hello");`); // result → ["hello", "done"] // Return structured data const out = await pea.runScript(` app.echoToOE(JSON.stringify({ width: app.activeDocument.width, height: app.activeDocument.height, layers: app.activeDocument.layers.length })); `); const info = JSON.parse(out[0]); ``` --- ## Step 4 — Exporting ```js // PNG Blob (via exportImage) const blob = await pea.exportImage("png"); document.getElementById("preview").src = URL.createObjectURL(blob); // JPEG Blob const blob = await pea.exportImage("jpg"); // WebP / PSD / quality-controlled JPEG via saveToOE const result = await pea.runScript(`app.activeDocument.saveToOE("webp:0.85");`); const webpBlob = new Blob([result[0]], { type: "image/webp" }); const result = await pea.runScript(`app.activeDocument.saveToOE("psd:true");`); const psdBlob = new Blob([result[0]], { type: "application/octet-stream" }); // Trigger download async function download(pea, filename = "export.png") { const blob = await pea.exportImage("png"); const a = Object.assign(document.createElement("a"), { href: URL.createObjectURL(blob), download: filename }); a.click(); } ``` **Export format strings for `saveToOE`:** | String | Format | |--------|--------| | `"png"` | PNG lossless | | `"jpg"` | JPEG default | | `"jpg:0.8"` | JPEG quality 0.0–1.0 | | `"webp:0.7"` | WebP quality 0.0–1.0 | | `"psd"` | Full PSD | | `"psd:true"` | Minified PSD | | `"svg:true"` | SVG | --- ## Step 5 — Loading Assets ```js // Font const buf = await (await fetch("https://example.com/MyFont.otf")).arrayBuffer(); await pea.loadAsset(buf); // Now usable in textItem.font // Brush await pea.loadAsset(await (await fetch("Nature.ABR")).arrayBuffer()); // Gradient await pea.loadAsset(await (await fetch("Gradients.GRD")).arrayBuffer()); ``` --- ## Step 6 — Plugin Mode ```js // Your page is inside Photopea's sidebar iframe const pea = new Photopea(window.parent); const out = await pea.runScript(`app.echoToOE(app.activeDocument.width);`); console.log("Width:", out[0]); // Load an asset from your plugin const buf = await (await fetch("https://my-assets.com/sticker.png")).arrayBuffer(); await pea.loadAsset(buf); ``` Plugin config: ```json { "environment": { "plugins": [{ "name": "My Plugin", "url": "https://my-plugin.example.com", "icon": "===https://my-plugin.example.com/icon.png" }] } } ``` --- ## Utility Patterns ### addImageAndWait — robust async layer insertion ```js async function addImageAndWait(pea, imgURI) { let count = "done"; while (count === "done") count = (await pea.runScript(`app.echoToOE(app.activeDocument.layers.length)`))[0]; count = parseInt(count); const imageUrlLiteral = JSON.stringify(imgURI); await pea.runScript(`app.open(${imageUrlLiteral}, null, true);`); return new Promise((resolve) => { const check = async () => { const n = parseInt((await pea.runScript( `app.echoToOE(app.activeDocument.layers.length)` ))[0]); n === count + 1 ? resolve() : setTimeout(check, 50); }; check(); }); } ``` ### getDocumentAsImage — returns `<img>` element ```js async function getDocumentAsImage(pea) { const result = await pea.runScript(`app.activeDocument.saveToOE('png')`); return new Promise((resolve) => { const fr = new FileReader(); fr.addEventListener("load", (e) => { const img = new Image(); img.src = e.target.result; resolve(img); }); fr.readAsDataURL(new Blob([result[0]], { type: "image/png" })); }); } ``` --- ## Real-World Patterns ### Pattern A — Open + Export UI ```html <input type="file" id="fileInput" accept="image/*,.psd"> <button id="exportBtn">Export PNG</button> <div id="editor" style="width:100%;height:600px;"></div> <script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/photopea.min.js"></script> <script> let pea; Photopea.createEmbed(document.getElementById("editor")).then(p => pea = p); document.getElementById("fileInput").addEventListener("change", async e => { await pea.loadAsset(await e.target.files[0].arrayBuffer()); }); document.getElementById("exportBtn").addEventListener("click", async () => { const blob = await pea.exportImage("png"); const a = Object.assign(document.createElement("a"), { href: URL.createObjectURL(blob), download: "export.png" }); a.click(); }); </script> ``` ### Pattern B — Template + Text Edit + Export ```js async function generateCard(pea, name,
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.