Add Cloudflare Workers AI image generation (#973)

2026-09-22 13:38:31 +00:00 · 2026-05-09 09:53:39 +07:00
parent dd15d162fc
commit 787d248030
7 changed files with 433 additions and 18 deletions
@@ -393,6 +393,17 @@ export const PROVIDER_MODELS = {
    { id: "@cf/zai-org/glm-4.7-flash", name: "GLM 4.7 Flash" },
    { id: "@cf/qwen/qwq-32b", name: "QwQ 32B" },
    { id: "@cf/qwen/qwen2.5-coder-32b-instruct", name: "Qwen 2.5 Coder 32B Instruct" },
+    { id: "@cf/black-forest-labs/flux-2-klein-9b", name: "FLUX.2 Klein 9B", type: "image", params: ["size"] },
+    { id: "@cf/black-forest-labs/flux-2-klein-4b", name: "FLUX.2 Klein 4B", type: "image", params: ["size"] },
+    { id: "@cf/black-forest-labs/flux-2-dev", name: "FLUX.2 Dev", type: "image", params: ["size"] },
+    { id: "@cf/leonardo/lucid-origin", name: "Lucid Origin", type: "image", params: ["size"] },
+    { id: "@cf/leonardo/phoenix-1.0", name: "Phoenix 1.0", type: "image", params: ["size"] },
+    { id: "@cf/black-forest-labs/flux-1-schnell", name: "FLUX.1 Schnell", type: "image", params: ["size"] },
+    { id: "@cf/bytedance/stable-diffusion-xl-lightning", name: "SDXL Lightning", type: "image", params: ["size"] },
+    { id: "@cf/lykon/dreamshaper-8-lcm", name: "DreamShaper 8 LCM", type: "image", params: ["size"] },
+    { id: "@cf/runwayml/stable-diffusion-v1-5-img2img", name: "Stable Diffusion v1.5 Img2Img", type: "image", params: ["size"], capabilities: ["edit"] },
+    { id: "@cf/runwayml/stable-diffusion-v1-5-inpainting", name: "Stable Diffusion v1.5 Inpainting", type: "image", params: ["size"], capabilities: ["edit", "mask"] },
+    { id: "@cf/stabilityai/stable-diffusion-xl-base-1.0", name: "SDXL Base 1.0", type: "image", params: ["size"] },
  ],
  byteplus: [
    { id: "seed-2-0-pro-260328", name: "Seed 2.0 Pro" },
@@ -5,6 +5,12 @@ import { getExecutor } from "../executors/index.js";
 import { getImageAdapter } from "./imageProviders/index.js";
 import { urlToBase64 } from "./imageProviders/_base.js";

+function serializeRequestBody(requestBody) {
+  if (typeof FormData !== "undefined" && requestBody instanceof FormData) return requestBody;
+  if (typeof requestBody === "string") return requestBody;
+  return JSON.stringify(requestBody);
+}
+
 /**
 * Core image generation handler — orchestrator only.
 * Provider-specific URL/headers/body/parse/normalize live in `./imageProviders/{id}.js`.
@@ -44,9 +50,17 @@ export async function handleImageGenerationCore({
    );
  }

-  const url = adapter.buildUrl(model, credentials);
-  const headers = adapter.buildHeaders(credentials);
-  const requestBody = adapter.buildBody(model, body);
+  let url;
+  let headers;
+  let requestBody;
+
+  try {
+    url = adapter.buildUrl(model, credentials);
+    requestBody = await adapter.buildBody(model, body);
+    headers = adapter.buildHeaders(credentials, requestBody, model, body);
+  } catch (error) {
+    return createErrorResult(HTTP_STATUS.BAD_REQUEST, error.message || `Invalid ${provider} image request`);
+  }

  log?.debug?.("IMAGE", `${provider.toUpperCase()} | ${model} | prompt="${body.prompt.slice(0, 50)}..."`);

@@ -55,7 +69,7 @@ export async function handleImageGenerationCore({
    providerResponse = await fetch(url, {
      method: "POST",
      headers,
-      body: JSON.stringify(requestBody),
+      body: serializeRequestBody(requestBody),
    });
  } catch (error) {
    const errMsg = formatProviderError(error, provider, model, HTTP_STATUS.BAD_GATEWAY);
@@ -83,12 +97,13 @@ export async function handleImageGenerationCore({
      if (onCredentialsRefreshed) await onCredentialsRefreshed(newCredentials);

      try {
-        const retryHeaders = adapter.buildHeaders(credentials);
+        const retryBody = await adapter.buildBody(model, body);
+        const retryHeaders = adapter.buildHeaders(credentials, retryBody, model, body);
        const retryUrl = adapter.buildUrl(model, credentials);
        providerResponse = await fetch(retryUrl, {
          method: "POST",
          headers: retryHeaders,
-          body: JSON.stringify(requestBody),
+          body: serializeRequestBody(retryBody),
        });
      } catch {
        log?.warn?.("TOKEN", `${provider.toUpperCase()} | retry after refresh failed`);
@@ -114,6 +129,10 @@ export async function handleImageGenerationCore({
        log,
        streamToClient,
        onRequestSuccess,
+        url,
+        requestBody,
+        model,
+        body,
      });
      // Codex streaming case: returns an SSE Response directly
      if (parsed?.sseResponse) {
@@ -0,0 +1,178 @@
+import { nowSec, urlToBase64 } from "./_base.js";
+
+const BASE_URL = "https://api.cloudflare.com/client/v4/accounts";
+
+const MULTIPART_MODELS = new Set([
+  "@cf/black-forest-labs/flux-2-dev",
+  "@cf/black-forest-labs/flux-2-klein-4b",
+  "@cf/black-forest-labs/flux-2-klein-9b",
+]);
+
+const OPTIONAL_FIELDS = [
+  "negative_prompt",
+  "guidance",
+  "seed",
+  "num_steps",
+  "steps",
+  "strength",
+];
+
+function sizeToDimensions(size) {
+  const match = /^(\d+)x(\d+)$/.exec(String(size || ""));
+  if (!match) return {};
+  return {
+    width: Number(match[1]),
+    height: Number(match[2]),
+  };
+}
+
+function getDimensions(body) {
+  return {
+    ...sizeToDimensions(body.size),
+    ...(Number.isFinite(Number(body.width)) ? { width: Number(body.width) } : {}),
+    ...(Number.isFinite(Number(body.height)) ? { height: Number(body.height) } : {}),
+  };
+}
+
+async function resolveImageInput(value) {
+  if (Array.isArray(value)) {
+    return { bytes: value, b64: Buffer.from(value).toString("base64") };
+  }
+  if (typeof value !== "string") return null;
+  const trimmed = value.trim();
+  if (!trimmed) return null;
+  if (/^https?:\/\//i.test(trimmed)) {
+    const b64 = await urlToBase64(trimmed);
+    return { bytes: base64ToBytes(b64), b64 };
+  }
+  const match = /^data:image\/[^;]+;base64,(.+)$/i.exec(trimmed);
+  const b64 = match ? match[1] : trimmed;
+  return { bytes: base64ToBytes(b64), b64 };
+}
+
+function base64ToBytes(value) {
+  try {
+    return Array.from(Buffer.from(value, "base64"));
+  } catch {
+    return value;
+  }
+}
+
+function addOptionalFields(target, body, append) {
+  for (const key of OPTIONAL_FIELDS) {
+    const value = body[key];
+    if (value === undefined || value === null || value === "") continue;
+    append(target, key, value);
+  }
+}
+
+async function buildJsonBody(body) {
+  const req = { prompt: body.prompt, ...getDimensions(body) };
+
+  addOptionalFields(req, body, (target, key, value) => {
+    target[key] = value;
+  });
+
+  const imageData = await resolveImageInput(body.image);
+  if (imageData) {
+    req.image_b64 = imageData.b64;
+    req.image = imageData.bytes;
+  }
+
+  const maskData = await resolveImageInput(body.mask_image || body.maskImage || body.mask);
+  if (maskData) {
+    req.mask_b64 = maskData.b64;
+    req.mask = maskData.bytes;
+    req.mask_image = maskData.bytes;
+  }
+
+  return req;
+}
+
+function buildMultipartBody(body) {
+  const form = new FormData();
+  form.append("prompt", body.prompt);
+
+  const dimensions = getDimensions(body);
+  for (const [key, value] of Object.entries(dimensions)) {
+    form.append(key, String(value));
+  }
+
+  addOptionalFields(form, body, (target, key, value) => {
+    target.append(key, String(value));
+  });
+
+  return form;
+}
+
+function imageItemFromString(value) {
+  if (typeof value !== "string" || !value) return null;
+  if (/^data:image\/[^;]+;base64,/i.test(value)) {
+    return { b64_json: value.replace(/^data:image\/[^;]+;base64,/i, "") };
+  }
+  if (/^https?:\/\//i.test(value)) return { url: value };
+  return { b64_json: value };
+}
+
+function normalizeCloudflareResponse(responseBody) {
+  if (responseBody?.created && Array.isArray(responseBody?.data)) return responseBody;
+
+  const result = responseBody?.result ?? responseBody;
+  const queuedResponse = Array.isArray(result?.responses)
+    ? result.responses.find((item) => item?.success !== false)?.result
+    : null;
+  if (queuedResponse) return normalizeCloudflareResponse(queuedResponse);
+
+  const image =
+    (typeof result === "string" ? result : null) ||
+    result?.image ||
+    result?.data?.[0]?.b64_json ||
+    result?.data?.[0]?.url;
+
+  const item = imageItemFromString(image);
+  return {
+    created: nowSec(),
+    data: item ? [item] : [],
+  };
+}
+
+export default {
+  buildUrl: (model, creds) => {
+    const accountId = creds?.providerSpecificData?.accountId;
+    if (!accountId) throw new Error("cloudflare-ai requires accountId in providerSpecificData");
+    return `${BASE_URL}/${accountId}/ai/run/${model}`;
+  },
+
+  buildHeaders: (creds, requestBody) => {
+    const headers = {};
+    const isMultipart = typeof FormData !== "undefined" && requestBody instanceof FormData;
+    if (!isMultipart) {
+      headers["Content-Type"] = "application/json";
+    }
+    const key = creds?.apiKey || creds?.accessToken;
+    if (key) headers.Authorization = `Bearer ${key}`;
+    return headers;
+  },
+
+  buildBody: async (model, body) => (
+    MULTIPART_MODELS.has(model)
+      ? buildMultipartBody(body)
+      : await buildJsonBody(body)
+  ),
+
+  async parseResponse(response) {
+    const contentType = (response.headers.get("Content-Type") || "").toLowerCase();
+    if (contentType.startsWith("image/")) {
+      const buf = await response.arrayBuffer();
+      return {
+        created: nowSec(),
+        data: [{ b64_json: Buffer.from(buf).toString("base64") }],
+      };
+    }
+
+    const json = await response.json();
+    return normalizeCloudflareResponse(json);
+  },
+
+  normalize: normalizeCloudflareResponse,
+};
@@ -10,6 +10,7 @@ import falAi from "./falAi.js";
 import stabilityAi from "./stabilityAi.js";
 import blackForestLabs from "./blackForestLabs.js";
 import runwayml from "./runwayml.js";
+import cloudflareAi from "./cloudflareAi.js";

 const ADAPTERS = {
  openai: createOpenAIAdapter("openai"),
@@ -26,6 +27,7 @@ const ADAPTERS = {
  "stability-ai": stabilityAi,
  "black-forest-labs": blackForestLabs,
  runwayml,
+  "cloudflare-ai": cloudflareAi,
 };

 export function getImageAdapter(provider) {
@@ -42,6 +42,27 @@ const DEFAULT_RESPONSE_EXAMPLE = `{
  "usage": { "prompt_tokens": 9, "total_tokens": 9 }
 }`;

+const CLOUDFLARE_TEST_IMAGE_URL = "https://pub-1fb693cb11cc46b2b2f656f51e015a2c.r2.dev/dog.png";
+const CLOUDFLARE_TEST_MASK_URL = "https://pub-1fb693cb11cc46b2b2f656f51e015a2c.r2.dev/dog-mask.png";
+
+function getImageEditDefaults(providerId, modelId) {
+  if (providerId !== "cloudflare-ai") return {};
+  if (modelId === "@cf/runwayml/stable-diffusion-v1-5-img2img") {
+    return { image: CLOUDFLARE_TEST_IMAGE_URL };
+  }
+  if (modelId === "@cf/runwayml/stable-diffusion-v1-5-inpainting") {
+    return { image: CLOUDFLARE_TEST_IMAGE_URL, mask_image: CLOUDFLARE_TEST_MASK_URL };
+  }
+  return {};
+}
+
+function toImagePreviewSrc(value) {
+  const trimmed = typeof value === "string" ? value.trim() : "";
+  if (!trimmed) return "";
+  if (/^(data:image\/|https?:\/\/)/i.test(trimmed)) return trimmed;
+  return `data:image/png;base64,${trimmed}`;
+}
+
 // Config-driven example defaults per kind
 const KIND_EXAMPLE_CONFIG = {
  webSearch: {
@@ -909,9 +930,11 @@ function GenericExampleCard({ providerId, kind }) {
  const [selectedModel, setSelectedModel] = useState(kindModels[0]?.id ?? "");
  const selectedModelObj = kindModels.find((m) => m.id === selectedModel);
  const supportsEdit = !!selectedModelObj?.capabilities?.includes("edit");
+  const supportsMask = !!selectedModelObj?.capabilities?.includes("mask");

  const [input, setInput] = useState(safeExConfig.defaultInput || "");
  const [refImage, setRefImage] = useState("");
+  const [maskImage, setMaskImage] = useState("");
  const [extraValues, setExtraValues] = useState(() =>
    (safeExConfig.extraFields || []).reduce((acc, f) => { acc[f.key] = f.default ?? ""; return acc; }, {})
  );
@@ -960,6 +983,11 @@ function GenericExampleCard({ providerId, kind }) {
  const modelFull = !needsModel
    ? providerAlias
    : (selectedModel ? `${providerAlias}/${selectedModel}` : (allowManualModel ? "" : providerAlias));
+  const imageEditDefaults = getImageEditDefaults(providerId, selectedModel);
+  const effectiveRefImage = refImage.trim() || imageEditDefaults.image || "";
+  const effectiveMaskImage = maskImage.trim() || imageEditDefaults.mask_image || "";
+  const refImagePreviewSrc = toImagePreviewSrc(effectiveRefImage);
+  const maskImagePreviewSrc = toImagePreviewSrc(effectiveMaskImage);

  // Build request body with optional extra fields (only non-empty values)
  const extraBodyFromFields = Object.entries(extraValues).reduce((acc, [k, v]) => {
@@ -973,7 +1001,8 @@ function GenericExampleCard({ providerId, kind }) {
    [exConfig.bodyKey]: input,
    ...exConfig.extraBody,
    ...extraBodyFromFields,
-    ...(supportsEdit && refImage.trim() ? { image: refImage.trim() } : {}),
+    ...(supportsEdit && effectiveRefImage ? { image: effectiveRefImage } : {}),
+    ...(supportsMask && effectiveMaskImage ? { mask_image: effectiveMaskImage } : {}),
  };

  // Streaming supported for codex image (Plus/Pro accounts) — disabled when binary output requested
@@ -1186,7 +1215,7 @@ function GenericExampleCard({ providerId, kind }) {
                <input
                  value={refImage}
                  onChange={(e) => setRefImage(e.target.value)}
-                  placeholder="https://example.com/source.png"
+                  placeholder={imageEditDefaults.image || "https://example.com/source.png"}
                  className="w-full px-3 py-1.5 pr-7 text-sm border border-border rounded-lg bg-background focus:outline-none focus:border-primary"
                />
                {refImage && (
@@ -1199,9 +1228,9 @@ function GenericExampleCard({ providerId, kind }) {
                  </button>
                )}
              </div>
-              {refImage.trim() && (
+              {refImagePreviewSrc && (
                <img
-                  src={refImage.trim()}
+                  src={refImagePreviewSrc}
                  alt="Reference"
                  className="max-h-40 rounded-lg border border-border object-contain bg-sidebar"
                  onError={(e) => { e.currentTarget.style.display = "none"; }}
@@ -1212,6 +1241,39 @@ function GenericExampleCard({ providerId, kind }) {
          </Row>
        )}

+        {supportsMask && (
+          <Row label="Mask (URL)">
+            <div className="flex flex-col gap-2">
+              <div className="relative">
+                <input
+                  value={maskImage}
+                  onChange={(e) => setMaskImage(e.target.value)}
+                  placeholder={imageEditDefaults.mask_image || "https://example.com/mask.png"}
+                  className="w-full px-3 py-1.5 pr-7 text-sm border border-border rounded-lg bg-background focus:outline-none focus:border-primary"
+                />
+                {maskImage && (
+                  <button
+                    type="button"
+                    onClick={() => setMaskImage("")}
+                    className="absolute right-2 top-1/2 -translate-y-1/2 text-text-muted hover:text-primary transition-colors"
+                  >
+                    <span className="material-symbols-outlined text-[14px]">close</span>
+                  </button>
+                )}
+              </div>
+              {maskImagePreviewSrc && (
+                <img
+                  src={maskImagePreviewSrc}
+                  alt="Mask"
+                  className="max-h-40 rounded-lg border border-border object-contain bg-sidebar"
+                  onError={(e) => { e.currentTarget.style.display = "none"; }}
+                  onLoad={(e) => { e.currentTarget.style.display = "block"; }}
+                />
+              )}
+            </div>
+          </Row>
+        )}
+
        {/* Extra fields — for kinds without model concept (webSearch/webFetch), show all; otherwise filter by model.params */}
        {(exConfig.extraFields || [])
          .filter((f) => kindModels.length === 0 || (Array.isArray(selectedModelObj?.params) && selectedModelObj.params.includes(f.key)))
@@ -19,7 +19,7 @@ export const FREE_TIER_PROVIDERS = {
  ollama: { id: "ollama", alias: "ollama", name: "Ollama Cloud", icon: "cloud", color: "#ffffffff", textIcon: "OL", website: "https://ollama.com", notice: { text: "Free tier: light usage, 1 cloud model at a time (limits reset every 5h & 7d). Pro $20/mo · Max $100/mo.", apiKeyUrl: "https://ollama.com/settings/keys" } },
  vertex: { id: "vertex", alias: "vx", name: "Vertex AI", icon: "cloud", color: "#4285F4", textIcon: "VX", website: "https://cloud.google.com/vertex-ai", notice: { text: "New Google Cloud accounts get $300 free credits. Requires GCP project + Service Account with Vertex AI API enabled.", apiKeyUrl: "https://console.cloud.google.com/iam-admin/serviceaccounts" } },
  gemini: { id: "gemini", alias: "gemini", name: "Gemini", icon: "diamond", color: "#4285F4", textIcon: "GE", mediaPriority: 1, website: "https://ai.google.dev", notice: { apiKeyUrl: "https://aistudio.google.com/app/apikey" }, serviceKinds: ["llm", "embedding", "image", "imageToText", "webSearch", "tts", "stt"], sttConfig: { baseUrl: "https://generativelanguage.googleapis.com/v1beta/models", authType: "apikey", authHeader: "key", format: "gemini-stt", models: [{ id: "gemini-2.5-pro", name: "Gemini 2.5 Pro (Best)" }, { id: "gemini-2.5-flash", name: "Gemini 2.5 Flash" }, { id: "gemini-2.5-flash-lite", name: "Gemini 2.5 Flash Lite (Cheapest)" }, { id: "gemini-2.0-flash", name: "Gemini 2.0 Flash" }] }, searchViaChat: { defaultModel: "gemini-2.5-flash", pricingUrl: "https://ai.google.dev/pricing", freeTier: "Free tier: 15 RPM, 1M tokens/day on gemini-2.5-flash via AI Studio." }, embeddingConfig: { baseUrl: "https://generativelanguage.googleapis.com/v1beta/models", authType: "apikey", authHeader: "key", models: [{ id: "text-embedding-004", name: "Text Embedding 004", dimensions: 768 }, { id: "embedding-001", name: "Embedding 001", dimensions: 768 }] }, ttsConfig: { baseUrl: "https://generativelanguage.googleapis.com/v1beta/models", authType: "apikey", authHeader: "key", format: "gemini-tts", models: [{ id: "gemini-2.5-flash-preview-tts", name: "Gemini 2.5 Flash TTS" }, { id: "gemini-2.5-pro-preview-tts", name: "Gemini 2.5 Pro TTS" }] } },
-  "cloudflare-ai": { id: "cloudflare-ai", alias: "cf", name: "Cloudflare", icon: "cloud", color: "#F38020", textIcon: "CF", website: "https://developers.cloudflare.com/workers-ai/", notice: { text: "Workers AI free tier. Requires a Cloudflare API token and Account ID.", apiKeyUrl: "https://dash.cloudflare.com/profile/api-tokens" }, serviceKinds: ["llm"], hasProviderSpecificData: true },
+  "cloudflare-ai": { id: "cloudflare-ai", alias: "cf", name: "Cloudflare", icon: "cloud", color: "#F38020", textIcon: "CF", website: "https://developers.cloudflare.com/workers-ai/", notice: { text: "Workers AI free tier. Requires a Cloudflare API token and Account ID.", apiKeyUrl: "https://dash.cloudflare.com/profile/api-tokens" }, serviceKinds: ["llm", "image"], hasProviderSpecificData: true },
  byteplus: { id: "byteplus", alias: "bpm", name: "BytePlus ModelArk", icon: "cloud", color: "#2563EB", textIcon: "BP", website: "https://console.byteplus.com/ark", notice: { text: "Free credits for new accounts. Access to Seed 2.0, Kimi K2 Thinking, GLM 4.7, GPT-OSS-120B models.", apiKeyUrl: "https://console.byteplus.com/ark/region:ark+ap-southeast-1/apiKey" }, serviceKinds: ["llm"] },
 };

@@ -21,6 +21,7 @@ describe("handleImageGenerationCore", () => {

  afterEach(() => {
    global.fetch = originalFetch;
+    vi.useRealTimers();
  });

  it("validates required prompt field", async () => {
@@ -156,29 +157,54 @@ describe("handleImageGenerationCore", () => {
  });

  it("generates image with NanoBanana format", async () => {
-    global.fetch.mockResolvedValueOnce(
-      new Response(
-        JSON.stringify({ image: "base64nanobanana" }),
-        { status: 200, headers: { "Content-Type": "application/json" } }
+    vi.useFakeTimers();
+    global.fetch
+      .mockResolvedValueOnce(
+        new Response(
+          JSON.stringify({ code: 200, data: { taskId: "task-123" } }),
+          { status: 200, headers: { "Content-Type": "application/json" } }
+        )
      )
-    );
+      .mockResolvedValueOnce(
+        new Response(
+          JSON.stringify({
+            data: {
+              successFlag: 1,
+              response: { resultImageUrl: "https://example.com/nanobanana.png" },
+            },
+          }),
+          { status: 200, headers: { "Content-Type": "application/json" } }
+        )
+      );

-    const result = await handleImageGenerationCore({
+    const pending = handleImageGenerationCore({
      body: { prompt: "A robot", n: 2, size: "1024x1792" },
      modelInfo: { provider: "nanobanana", model: "nanobanana-flash" },
      credentials: { apiKey: "test-key" },
      log: null,
    });

+    await vi.advanceTimersByTimeAsync(1500);
+    const result = await pending;
+
    expect(result.success).toBe(true);
    const fetchCall = global.fetch.mock.calls[0];
    const requestBody = JSON.parse(fetchCall[1].body);
    expect(requestBody.type).toBe("TEXTTOIAMGE");
    expect(requestBody.numImages).toBe(2);
    expect(requestBody.image_size).toBe("9:16");
+    expect(global.fetch).toHaveBeenNthCalledWith(
+      2,
+      "https://api.nanobananaapi.ai/api/v1/nanobanana/record-info?taskId=task-123",
+      expect.objectContaining({
+        headers: expect.objectContaining({
+          Authorization: "Bearer test-key",
+        }),
+      })
+    );

    const responseBody = await result.response.json();
-    expect(responseBody.data[0].b64_json).toBe("base64nanobanana");
+    expect(responseBody.data[0].url).toBe("https://example.com/nanobanana.png");
  });

  it("generates image with SD WebUI format", async () => {
@@ -258,6 +284,123 @@ describe("handleImageGenerationCore", () => {
    expect(responseBody.data[0].b64_json).toBeTruthy();
  });

+  it("generates image with Cloudflare Workers AI JSON response", async () => {
+    global.fetch.mockResolvedValueOnce(
+      new Response(
+        JSON.stringify({
+          result: { image: "base64cloudflare" },
+          success: true,
+          errors: [],
+          messages: [],
+        }),
+        { status: 200, headers: { "Content-Type": "application/json" } }
+      )
+    );
+
+    const result = await handleImageGenerationCore({
+      body: { prompt: "A lighthouse", size: "1024x1536" },
+      modelInfo: { provider: "cloudflare-ai", model: "@cf/leonardo/lucid-origin" },
+      credentials: {
+        apiKey: "cf-token",
+        providerSpecificData: { accountId: "cf-account" },
+      },
+      log: null,
+    });
+
+    expect(result.success).toBe(true);
+    expect(global.fetch).toHaveBeenCalledWith(
+      "https://api.cloudflare.com/client/v4/accounts/cf-account/ai/run/@cf/leonardo/lucid-origin",
+      expect.objectContaining({
+        method: "POST",
+        headers: expect.objectContaining({
+          "Content-Type": "application/json",
+          Authorization: "Bearer cf-token",
+        }),
+      })
+    );
+
+    const fetchCall = global.fetch.mock.calls[0];
+    const requestBody = JSON.parse(fetchCall[1].body);
+    expect(requestBody.prompt).toBe("A lighthouse");
+    expect(requestBody.width).toBe(1024);
+    expect(requestBody.height).toBe(1536);
+
+    const responseBody = await result.response.json();
+    expect(responseBody.data[0].b64_json).toBe("base64cloudflare");
+  });
+
+  it("uses multipart form data for Cloudflare FLUX.2 models", async () => {
+    global.fetch.mockResolvedValueOnce(
+      new Response(
+        JSON.stringify({
+          result: { image: "base64flux2" },
+          success: true,
+        }),
+        { status: 200, headers: { "Content-Type": "application/json" } }
+      )
+    );
+
+    const result = await handleImageGenerationCore({
+      body: { prompt: "A mountain lake", size: "1792x1024", steps: 4 },
+      modelInfo: { provider: "cloudflare-ai", model: "@cf/black-forest-labs/flux-2-klein-9b" },
+      credentials: {
+        apiKey: "cf-token",
+        providerSpecificData: { accountId: "cf-account" },
+      },
+      log: null,
+    });
+
+    expect(result.success).toBe(true);
+
+    const fetchCall = global.fetch.mock.calls[0];
+    expect(fetchCall[1].headers).not.toHaveProperty("Content-Type");
+    expect(fetchCall[1].body).toBeInstanceOf(FormData);
+    expect(fetchCall[1].body.get("prompt")).toBe("A mountain lake");
+    expect(fetchCall[1].body.get("width")).toBe("1792");
+    expect(fetchCall[1].body.get("height")).toBe("1024");
+    expect(fetchCall[1].body.get("steps")).toBe("4");
+  });
+
+  it("resolves Cloudflare img2img and inpainting URL inputs before sending", async () => {
+    global.fetch
+      .mockResolvedValueOnce(new Response(new Uint8Array([1, 2, 3]), { status: 200, headers: { "Content-Type": "image/png" } }))
+      .mockResolvedValueOnce(new Response(new Uint8Array([4, 5, 6]), { status: 200, headers: { "Content-Type": "image/png" } }))
+      .mockResolvedValueOnce(
+        new Response(
+          JSON.stringify({ result: { image: "base64inpaint" }, success: true }),
+          { status: 200, headers: { "Content-Type": "application/json" } }
+        )
+      );
+
+    const result = await handleImageGenerationCore({
+      body: {
+        prompt: "Change to a lion",
+        image: "https://example.com/source.png",
+        mask_image: "https://example.com/mask.png",
+        size: "512x512",
+      },
+      modelInfo: { provider: "cloudflare-ai", model: "@cf/runwayml/stable-diffusion-v1-5-inpainting" },
+      credentials: {
+        apiKey: "cf-token",
+        providerSpecificData: { accountId: "cf-account" },
+      },
+      log: null,
+    });
+
+    expect(result.success).toBe(true);
+    expect(global.fetch).toHaveBeenNthCalledWith(1, "https://example.com/source.png");
+    expect(global.fetch).toHaveBeenNthCalledWith(2, "https://example.com/mask.png");
+
+    const providerCall = global.fetch.mock.calls[2];
+    expect(providerCall[0]).toBe("https://api.cloudflare.com/client/v4/accounts/cf-account/ai/run/@cf/runwayml/stable-diffusion-v1-5-inpainting");
+    const requestBody = JSON.parse(providerCall[1].body);
+    expect(requestBody.image).toEqual([1, 2, 3]);
+    expect(requestBody.image_b64).toBe(Buffer.from([1, 2, 3]).toString("base64"));
+    expect(requestBody.mask).toEqual([4, 5, 6]);
+    expect(requestBody.mask_image).toEqual([4, 5, 6]);
+    expect(requestBody.mask_b64).toBe(Buffer.from([4, 5, 6]).toString("base64"));
+  });
+
  it("handles provider error responses", async () => {
    global.fetch.mockResolvedValueOnce(
      new Response(