TanStack
AI
Community Adapters

Cloudflare

@cloudflare/tanstack-ai is the community Cloudflare package. It provides:

  • Workers AI models, which run on the Cloudflare network.
  • AI Gateway routing to OpenAI, Anthropic, Gemini, Grok, and OpenRouter, with caching, rate limits, and one bill.

Cloudflare maintains this package. TanStack AI also has its own Cloudflare adapter, @tanstack/ai-cloudflare. See the Cloudflare adapter page.

1. Install

shell
npm i @cloudflare/tanstack-ai @tanstack/ai

2. Set up access

Inside a Cloudflare Worker, use the env.AI binding. You need no API key.

Outside a Worker, use the REST credentials. Put them in the environment of your server:

shell
CLOUDFLARE_ACCOUNT_ID=your-account-id
CLOUDFLARE_API_KEY=your-api-key

3. Stream a chat

ts
import { chat, toHttpResponse } from "@tanstack/ai";
import { createWorkersAiChat } from "@cloudflare/tanstack-ai";
import { env } from "./env";

const adapter = createWorkersAiChat(
  "@cf/meta/llama-4-scout-17b-16e-instruct",
  { binding: env.AI },
);

const response = chat({
  adapter,
  stream: true,
  messages: [{ role: "user", content: "Hello!" }],
  threadId: "thread-1",
});

const httpResponse = toHttpResponse(response);

Return httpResponse from your Worker. Outside a Worker, pass the account ID and the API key:

ts
import { createWorkersAiChat } from "@cloudflare/tanstack-ai";

const adapter = createWorkersAiChat(
  "@cf/meta/llama-4-scout-17b-16e-instruct",
  {
    accountId: "your-account-id",
    apiKey: "your-api-key",
  },
);

Images

ts
import { generateImage } from "@tanstack/ai";
import { createWorkersAiImage } from "@cloudflare/tanstack-ai";
import { env } from "./env";

const adapter = createWorkersAiImage(
  "@cf/stabilityai/stable-diffusion-xl-base-1.0",
  { binding: env.AI },
);

const result = await generateImage({
  adapter,
  prompt: "a cat in space",
  threadId: "thread-1",
});

console.log(result.images[0]?.b64Json);

Transcription

ts
import { generateTranscription } from "@tanstack/ai";
import { createWorkersAiTranscription } from "@cloudflare/tanstack-ai";
import { env, audioArrayBuffer } from "./env";

const adapter = createWorkersAiTranscription(
  "@cf/openai/whisper-large-v3-turbo",
  { binding: env.AI },
);

const result = await generateTranscription({
  adapter,
  audio: audioArrayBuffer,
  threadId: "thread-1",
});

console.log(result.text);
console.log(result.segments);

Transcription models: @cf/openai/whisper, @cf/openai/whisper-tiny-en, @cf/openai/whisper-large-v3-turbo, and @cf/deepgram/nova-3.

Speech

ts
import { generateSpeech } from "@tanstack/ai";
import { createWorkersAiTts } from "@cloudflare/tanstack-ai";
import { env } from "./env";

const adapter = createWorkersAiTts("@cf/deepgram/aura-2-en", {
  binding: env.AI,
});

const result = await generateSpeech({
  adapter,
  text: "Hello world",
  threadId: "thread-1",
});

console.log(result.audio);

Summarization

ts
import { summarize, type AnySummarizeAdapter } from "@tanstack/ai";
import { createWorkersAiSummarize } from "@cloudflare/tanstack-ai";
import { env } from "./env";

const adapter: AnySummarizeAdapter = createWorkersAiSummarize("@cf/facebook/bart-large-cnn", {
  binding: env.AI,
});

const result = await summarize({
  adapter,
  text: "Long article here...",
  threadId: "thread-1",
});

console.log(result.summary);

AI Gateway

Send requests through AI Gateway to get caching, rate limits, and one bill. It works for Workers AI and for other providers.

Workers AI through the gateway:

ts
import { createWorkersAiChat } from "@cloudflare/tanstack-ai";
import { env } from "./env";

const adapter = createWorkersAiChat(
  "@cf/meta/llama-4-scout-17b-16e-instruct",
  {
    binding: env.AI.gateway("my-gateway-id"),
    apiKey: env.WORKERS_AI_TOKEN,
  },
);

Other providers through the gateway. For other providers, also install their TanStack AI packages:

shell
npm i @tanstack/ai-openai @tanstack/ai-anthropic @tanstack/ai-gemini @tanstack/ai-grok @tanstack/ai-openrouter

Install only the providers that you use. In a Worker, use the binding:

ts
import {
  createOpenAiChat,
  createAnthropicChat,
  createGeminiChat,
  createGrokChat,
  createOpenRouterChat,
} from "@cloudflare/tanstack-ai";
import { env } from "./env";

const openai = createOpenAiChat("gpt-4o", {
  binding: env.AI.gateway("my-gateway-id"),
});

const anthropic = createAnthropicChat("claude-sonnet-4-5", {
  binding: env.AI.gateway("my-gateway-id"),
});

const grok = createGrokChat("grok-4.3", {
  binding: env.AI.gateway("my-gateway-id"),
});

const openrouter = createOpenRouterChat("openai/gpt-4o", {
  binding: env.AI.gateway("my-gateway-id"),
});

Outside a Worker, use the credentials:

ts
import { createOpenAiChat } from "@cloudflare/tanstack-ai";

const adapter = createOpenAiChat("gpt-4o", {
  accountId: "your-account-id",
  gatewayId: "your-gateway-id",
  cfApiKey: "your-cf-api-key",
  apiKey: "provider-api-key",
});

Cache options

The binding mode and the credentials mode both take cache options:

ts
import { createOpenAiChat } from "@cloudflare/tanstack-ai";
import { env } from "./env";

const adapter = createOpenAiChat("gpt-4o", {
  binding: env.AI.gateway("my-gateway-id"),
  skipCache: false,
  cacheTtl: 3600,
  customCacheKey: "my-key",
  metadata: { user: "test" },
});

Models and options

Configuration modes

Workers AI has four modes:

ModeConfigWhat it does
Plain binding{ binding: env.AI }Direct access, no gateway.
Plain REST{ accountId, apiKey }REST API, no gateway.
Gateway binding{ binding: env.AI.gateway(id) }Through AI Gateway, with the binding.
Gateway REST{ accountId, gatewayId, ... }Through AI Gateway, with REST.

Other providers (OpenAI, Anthropic, Gemini, Grok, OpenRouter) work only in the gateway modes.

Capabilities

ProviderChatSummarizeImagesTranscriptionSpeech
Workers AIYesYesYesYesYes
OpenAIYesYesYesYesYes
AnthropicYesYesNoNoNo
GeminiYesYesYesNoYes
GrokYesYesYesNoNo
OpenRouterYesYesYesNoNo

Workers AI factories

  • createWorkersAiChat(model, config): chat and structured output.
  • createWorkersAiImage(model, config): images.
  • createWorkersAiTranscription(model, config): speech to text (Whisper, Deepgram).
  • createWorkersAiTts(model, config): text to speech (Deepgram Aura).
  • createWorkersAiSummarize(model, config): summarization (BART-large-CNN).

Gateway provider factories

  • OpenAI: createOpenAiChat(model, config), createOpenAiSummarize, createOpenAiImage, createOpenAiTranscription, createOpenAiTts.
  • Anthropic: createAnthropicChat(model, config), createAnthropicSummarize.
  • Gemini: createGeminiChat(model, config), createGeminiSummarize, createGeminiImage, createGeminiTts.
  • Grok: createGrokChat(model, config), createGrokSummarize, createGrokImage.
  • OpenRouter: createOpenRouterChat(model, config), createOpenRouterSummarize, createOpenRouterImage.

The source and the issues are on GitHub.

Edit on GitHub
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