Add Image Redraw example combining multiple Cloudflare bindings

README.md

@@ -34,7 +34,7 @@ Need to deploy your Worker to Cloudflare? Python Workers are in open beta and ha
 - [**`dynamic-py-py/`**](dynamic-py-py) — shows how to load and run a Python Worker dynamically at runtime using a [Worker Loader](https://developers.cloudflare.com/workers/runtime-apis/bindings/worker-loader/) binding.
 - [**`django/`**](django) — runs a naive Django WSGI application directly on Python Workers.
 - [**`django-todo-d1/`**](django-todo-d1) — uses Django with D1 for a basic TODO application.
-
+- [**`image-redraw/`**](image-redraw) — an example that combines [FastAPI](https://fastapi.tiangolo.com/), [R2](https://developers.cloudflare.com/r2/), [Queues](https://developers.cloudflare.com/queues/), [Workflows](https://developers.cloudflare.com/workflows/) and [Workers AI](https://developers.cloudflare.com/workers-ai/) to redraw uploaded images.
 
 
 ## Open Beta and Limits

image-redraw/README.md

@@ -0,0 +1,74 @@
+# Image Redraw — FastAPI + R2 + Queues + Workflows + Workers AI
+
+[![Deploy to Cloudflare](https://deploy.workers.cloudflare.com/button)](https://deploy.workers.cloudflare.com/?url=https://github.com/cloudflare/python-workers-examples/tree/main/20-image-redraw)
+
+Upload a picture and get it back redrawn as a wobbly MS Paint doodle.
+
+This example demonstrates how to leverage multiple Cloudflare services to
+create a full-featured image processing pipeline using Python Workers.
+
+## What it uses
+
+- [Python Workers](https://developers.cloudflare.com/workers/languages/python/) — the runtime
+- [FastAPI](https://fastapi.tiangolo.com/) — the HTTP API, served over ASGI
+- [R2](https://developers.cloudflare.com/r2/) — stores uploaded originals and redrawn outputs
+- [Queues](https://developers.cloudflare.com/queues/) — hands work off the request path
+- [Workflows](https://developers.cloudflare.com/workflows/) — durable, retrying background execution
+- [Workers AI](https://developers.cloudflare.com/workers-ai/) — image generation guided by the uploaded reference
+- [Pillow](https://pillow.readthedocs.io/en/stable/) — image normalization inside the Workflow
+- [Static Assets](https://developers.cloudflare.com/workers/static-assets/) — the plain HTML/CSS/JS frontend
+
+```mermaid
+flowchart LR
+    Browser["Browser"]
+    Worker["Python Worker<br/>FastAPI"]
+    Queue[["Queue"]]
+    Workflow["Workflow"]
+    R2[("R2")]
+    AI["Workers AI"]
+
+    Browser --> Worker
+    Worker --> R2
+    Worker --> Queue
+    Queue --> Workflow
+    Workflow --> R2
+    Workflow --> AI
+```
+
+## The flow
+
+1. The browser POSTs the image bytes to the Worker.
+2. FastAPI validates the image and stores the original in R2, and
+   enqueues the job.
+3. The queue consumer turns each batch of IDs into Workflow instances.
+4. The Workflow reads the original from R2, normalizes it with Pillow, calls
+   Workers AI, and stores the result back in R2.
+
+
+## Setup
+
+First ensure that `uv` is installed:
+https://docs.astral.sh/uv/getting-started/installation/#standalone-installer
+
+**Workers AI is a remote binding, even during local development.** `wrangler.jsonc`
+declares `"ai": { "binding": "AI", "remote": true }`, so inference always runs on
+Cloudflare's network and bills against your account. Log in before starting the
+dev server:
+
+```sh
+uv run pwrangler login
+```
+
+## How to Run
+
+```sh
+uv run pywrangler dev
+```
+
+Then open http://localhost:8787/ in your browser.
+
+## How to deploy
+
+```sh
+uv run pywrangler deploy
+```

image-redraw/package.json

@@ -0,0 +1,13 @@
+{
+	"name": "image-redraw-worker",
+	"version": "0.0.0",
+	"private": true,
+	"scripts": {
+		"deploy": "uv run pywrangler deploy",
+		"dev": "uv run pywrangler dev",
+		"start": "uv run pywrangler dev"
+	},
+	"devDependencies": {
+		"wrangler": "^4.114.0"
+	}
+}

image-redraw/public/app.js

@@ -0,0 +1,279 @@
+const REFERENCE_SIZE = 511;
+const MAX_UPLOAD_BYTES = 5_000_000;
+const POLL_INTERVAL_MS = 2000;
+const MAX_POLLS = 150;
+const MAX_POLL_FAILURES = 3;
+const TYPE_LABELS = {
+  "image/png": "PNG",
+  "image/jpeg": "JPEG",
+  "image/webp": "WebP",
+};
+const ACCEPTED_TYPES = Object.keys(TYPE_LABELS);
+
+const byId = (id) => document.getElementById(id);
+const uploadForm = byId("upload-form");
+const fileInput = byId("file-input");
+const submitButton = byId("submit-button");
+const uploadStatus = byId("upload-status");
+const preview = byId("preview");
+const previewImage = byId("preview-image");
+const previewCaption = byId("preview-caption");
+const compare = byId("compare");
+const compareEmpty = byId("compare-empty");
+const compareMeta = byId("compare-meta");
+const originalImage = byId("original-image");
+const outputImage = byId("output-image");
+const gallery = byId("gallery");
+const galleryStatus = byId("gallery-status");
+const refreshButton = byId("refresh-button");
+
+let rawUpload = null;
+let previewUrl = null;
+let selectedJobId = null;
+
+const sleep = (ms) => new Promise((resolve) => setTimeout(resolve, ms));
+const shortId = (jobId) => jobId.slice(0, 8);
+
+function setStatus(element, message, tone = "info") {
+  element.textContent = message;
+  element.dataset.tone = tone;
+}
+
+function formatTime(isoString) {
+  const date = new Date(isoString);
+  if (Number.isNaN(date.getTime())) return "unknown time";
+  return date.toLocaleString([], {
+    month: "short",
+    day: "numeric",
+    hour: "2-digit",
+    minute: "2-digit",
+  });
+}
+
+function formatBytes(bytes) {
+  const kilobytes = bytes / 1024;
+  if (kilobytes < 1000) return `${kilobytes.toFixed(1)} KB`;
+  return `${(kilobytes / 1024).toFixed(2)} MB`;
+}
+
+async function requestJson(path, options) {
+  let response;
+  try {
+    response = await fetch(path, options);
+  } catch {
+    throw new Error("Network error. Is the Worker still running?");
+  }
+
+  const data = await response.json().catch(() => null);
+  if (!response.ok) {
+    const detail = typeof data?.detail === "string" ? data.detail : null;
+    throw new Error(detail ?? `Request failed with status ${response.status}`);
+  }
+  return data;
+}
+
+// Decodes only to prove the bytes are an image and to read the source size.
+// The bitmap is discarded; the original File is what gets uploaded.
+async function readSourceSize(file) {
+  let bitmap;
+  try {
+    bitmap = await createImageBitmap(file);
+  } catch {
+    throw new Error("That file could not be decoded as an image.");
+  }
+  const size = { width: bitmap.width, height: bitmap.height };
+  bitmap.close?.();
+  return size;
+}
+
+async function inspectFile(file) {
+  if (!ACCEPTED_TYPES.includes(file.type)) {
+    throw new Error("Only PNG, JPEG and WebP are supported.");
+  }
+  if (file.size > MAX_UPLOAD_BYTES) {
+    throw new Error(
+      `That file is ${file.size.toLocaleString()} bytes, over the ${MAX_UPLOAD_BYTES.toLocaleString()} byte limit. Try a smaller picture.`,
+    );
+  }
+
+  const { width, height } = await readSourceSize(file);
+  const label = TYPE_LABELS[file.type];
+  return {
+    file,
+    caption:
+      `${width}x${height} ${label} (${file.type}), ${formatBytes(file.size)}`,
+  };
+}
+
+async function showPreview() {
+  rawUpload = null;
+  preview.hidden = true;
+  if (previewUrl) URL.revokeObjectURL(previewUrl);
+  previewUrl = null;
+
+  const file = fileInput.files?.[0];
+  if (!file) {
+    setStatus(uploadStatus, "");
+    return;
+  }
+
+  setStatus(uploadStatus, "Checking your picture...");
+  try {
+    rawUpload = await inspectFile(file);
+    previewUrl = URL.createObjectURL(rawUpload.file);
+    previewImage.src = previewUrl;
+    previewImage.alt =
+      "The original picture you chose, shown at full size before it is uploaded.";
+    previewCaption.textContent = rawUpload.caption;
+    preview.hidden = false;
+    setStatus(uploadStatus, 'Ready. Press "Redraw it!".');
+  } catch (error) {
+    setStatus(uploadStatus, error.message, "error");
+  }
+}
+
+// Resolves with the terminal job object so the caller can read job.reason.
+async function pollJob(jobId) {
+  let failures = 0;
+
+  for (let attempt = 1; attempt <= MAX_POLLS; attempt += 1) {
+    await sleep(POLL_INTERVAL_MS);
+
+    let job;
+    try {
+      job = await requestJson(`/api/jobs/${jobId}`);
+      failures = 0;
+    } catch (error) {
+      failures += 1;
+      if (failures >= MAX_POLL_FAILURES) {
+        throw new Error(`Lost contact with the Worker. ${error.message}`);
+      }
+      continue;
+    }
+
+    if (job.status === "complete" || job.status === "failed") return job;
+    setStatus(
+      uploadStatus,
+      `Job ${shortId(jobId)} is ${job.status}... (checked ${attempt} times)`,
+    );
+  }
+
+  throw new Error("This redraw is taking too long. Try Refresh later.");
+}
+
+function selectJob(job) {
+  selectedJobId = job.jobId;
+  originalImage.src = job.originalUrl;
+  originalImage.alt = `The picture you uploaded for job ${shortId(job.jobId)}.`;
+  outputImage.src = job.outputUrl;
+  outputImage.alt = `Workers AI redraw of job ${shortId(job.jobId)}, in a clumsy MS Paint style.`;
+  compareMeta.textContent = `Job ${job.jobId} - finished ${formatTime(job.completedAt)}`;
+  compare.hidden = false;
+  compareEmpty.hidden = true;
+
+  for (const card of gallery.querySelectorAll(".card")) {
+    card.setAttribute("aria-pressed", String(card.dataset.jobId === job.jobId));
+  }
+}
+
+function createCard(job) {
+  const thumb = document.createElement("img");
+  thumb.src = job.outputUrl;
+  thumb.loading = "lazy";
+  thumb.alt = `Redrawn picture from job ${shortId(job.jobId)}`;
+
+  const time = document.createElement("span");
+  time.textContent = formatTime(job.completedAt);
+
+  const card = document.createElement("button");
+  card.type = "button";
+  card.className = "card";
+  card.dataset.jobId = job.jobId;
+  card.setAttribute("aria-pressed", String(job.jobId === selectedJobId));
+  card.append(thumb, time);
+  card.addEventListener("click", () => selectJob(job));
+
+  const item = document.createElement("li");
+  item.append(card);
+  return item;
+}
+
+function renderGallery(jobs) {
+  if (jobs.length === 0) {
+    const empty = document.createElement("li");
+    empty.className = "empty";
+    empty.textContent = "No pictures yet. Upload one to start the gallery.";
+    gallery.replaceChildren(empty);
+    return;
+  }
+  gallery.replaceChildren(...jobs.map(createCard));
+}
+
+async function loadGallery(jobIdToSelect) {
+  refreshButton.disabled = true;
+  setStatus(galleryStatus, "Loading gallery...");
+
+  try {
+    const jobs = (await requestJson("/api/jobs"))?.jobs ?? [];
+    renderGallery(jobs);
+    setStatus(
+      galleryStatus,
+      jobs.length === 1 ? "1 picture saved." : `${jobs.length} pictures saved.`,
+    );
+
+    const target = jobs.find((job) => job.jobId === jobIdToSelect);
+    if (target) selectJob(target);
+  } catch (error) {
+    setStatus(galleryStatus, error.message, "error");
+  } finally {
+    refreshButton.disabled = false;
+  }
+}
+
+uploadForm.addEventListener("submit", async (event) => {
+  event.preventDefault();
+  if (!rawUpload) await showPreview();
+  if (!rawUpload) {
+    if (!fileInput.files?.length) {
+      setStatus(uploadStatus, "Choose a picture first.", "error");
+    }
+    fileInput.focus();
+    return;
+  }
+
+  const upload = rawUpload.file;
+  fileInput.disabled = true;
+  submitButton.disabled = true;
+  try {
+    setStatus(uploadStatus, "Uploading to the Worker...");
+    const created = await requestJson("/api/jobs", {
+      method: "POST",
+      headers: { "Content-Type": upload.type },
+      body: upload,
+    });
+
+    setStatus(uploadStatus, `Job ${shortId(created.jobId)} is queued...`);
+    const job = await pollJob(created.jobId);
+    if (job.status === "complete") {
+      setStatus(uploadStatus, "Finished! Behold the artwork.", "done");
+      await loadGallery(job.jobId);
+    } else {
+      // The backend only ever sends a reason it is happy to show a visitor.
+      const reason =
+        typeof job.reason === "string" && job.reason
+          ? job.reason
+          : "The Workflow gave up on that one.";
+      setStatus(uploadStatus, reason, "error");
+    }
+  } catch (error) {
+    setStatus(uploadStatus, error.message, "error");
+  } finally {
+    fileInput.disabled = false;
+    submitButton.disabled = false;
+  }
+});
+
+fileInput.addEventListener("change", () => void showPreview());
+refreshButton.addEventListener("click", () => void loadGallery());
+
+void loadGallery();