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Community Adapters

Mynth

The Mynth community adapter calls Flux, Recraft, Gemini, Qwen, Seedream, Wan, and Grok Imagine from generateImage(). Mynth maintains it.

Note

Mynth is in public beta. The model list and some request options can still change. The adapter follows the Mynth SDK closely, and Mynth welcomes feedback on the API.

1. Install

shell
npm i @mynthio/tanstack-ai-adapter @tanstack/ai

The adapter needs @tanstack/ai 0.34 or later.

2. Set the API key

Make a key in the Mynth API keys dashboard. Then put it in the environment of your server:

shell
MYNTH_API_KEY=mak_...

Warning

Keep MYNTH_API_KEY on the server. Do not put it in browser code or in public client environment variables. It can then end up in a client bundle.

3. Generate an image

ts
import { generateImage } from "@tanstack/ai";
import { mynthImage } from "@mynthio/tanstack-ai-adapter";

const result = await generateImage({
  adapter: mynthImage("black-forest-labs/flux.2-dev"),
  prompt: "Editorial product photo of a ceramic mug on a linen tablecloth",
  threadId: "thread-1",
  numberOfImages: 1,
  size: "square",
});

console.log(result.id);
console.log(result.model);
console.log(result.images[0]?.url);

You get a URL to the image in result.images[0]?.url. You pick the Mynth model when you create the adapter.

4. Stream it to your UI

Return the generation from a route with stream: true:

ts
import {
  generateImage,
  generationParamsFromRequest,
  toServerSentEventsResponse,
} from "@tanstack/ai";
import { mynthImage } from "@mynthio/tanstack-ai-adapter";

export async function POST(request: Request) {
  const { input, threadId, runId } = await generationParamsFromRequest(
    "image",
    request,
  );

  const stream = generateImage({
    adapter: mynthImage("auto"),
    prompt: input.prompt,
    threadId,
    runId,
    numberOfImages: 1,
    stream: true,
  });

  return toServerSentEventsResponse(stream);
}

On the client, use useGenerateImage(). For a full app, see the TanStack Start + Mynth adapter demo.

Image to image

Models that take image input work with content-part prompts. Mix the instruction text with reference images, for restyles, edits, reference-guided images, and try-on:

ts
import { generateImage } from "@tanstack/ai";
import { mynthImage } from "@mynthio/tanstack-ai-adapter";

const result = await generateImage({
  adapter: mynthImage("black-forest-labs/flux.2-dev"),
  prompt: [
    { type: "text", content: "Restyle this scene as a watercolor painting" },
    {
      type: "image",
      source: { type: "url", value: "https://example.com/photo.jpg" },
    },
  ],
  threadId: "thread-1",
});

The adapter maps the image parts to Mynth inputs:

  • Only models in MYNTH_IMAGE_INPUT_MODELS take image parts. An image part for another model is a compile-time error.
  • URL sources ({ type: "url", value }) and inline data sources ({ type: "data", value, mimeType }, sent as a data URI) both work.
  • The metadata.role of a part maps to the Mynth input intent. TanStack's "character" maps directly. The other roles use the automatic detection of Mynth.
  • For the finer Mynth intents (person, garment, pose, style, background, product, object), pass modelOptions.inputs with an explicit as.
  • The adapter combines the image parts of the prompt and the entries in modelOptions.inputs. Prompt parts come first.

Share settings across adapters

Use createMynthImage() to share settings across adapters:

ts
import { generateImage } from "@tanstack/ai";
import { createMynthImage } from "@mynthio/tanstack-ai-adapter";

const mynth = createMynthImage({
  apiKey: process.env.MYNTH_API_KEY!,
  baseUrl: "https://api.mynth.io",
});

const result = await generateImage({
  adapter: mynth("google/gemini-3.1-flash-image"),
  prompt: "A playful paper-cut illustration of a city park in spring",
  threadId: "thread-1",
});

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

You can still change the settings for one adapter:

ts
import { createMynthImage } from "@mynthio/tanstack-ai-adapter";

const mynth = createMynthImage();

const adapter = mynth("auto", {
  baseUrl: "https://proxy.example.com",
});
  • apiKey overrides MYNTH_API_KEY.
  • baseUrl is optional. Use it for proxies, tests, or custom deployments.

Models and options

Models

The adapter exports a runtime list and a type of the image models:

ts
import { MYNTH_IMAGE_MODELS, type MynthImageModel } from "@mynthio/tanstack-ai-adapter";

const defaultModel: MynthImageModel = "auto";

for (const model of MYNTH_IMAGE_MODELS) {
  console.log(model);
}
  • Use the list for model pickers, validation, and to keep the client and the server in sync.
  • MYNTH_IMAGE_INPUT_MODELS (and the MynthImageInputModel type) lists the models that take image input.
  • The models include auto, Flux, Recraft, Gemini, Qwen, Seedream, Imagine, Wan, Grok Imagine, and try-on models.

The exported list is a fixed snapshot, for type safety. For the live catalog with prices, use the models endpoint.

Model options

Top-level fields hold the common options: prompt, numberOfImages, and the short size. Put the Mynth options in modelOptions:

ts
import { generateImage } from "@tanstack/ai";
import { mynthImage } from "@mynthio/tanstack-ai-adapter";

const result = await generateImage({
  adapter: mynthImage("recraft/recraft-v4"),
  prompt: "Modern poster design for a jazz festival",
  threadId: "thread-1",
  numberOfImages: 2,
  size: "portrait",
  modelOptions: {
    negativePrompt: "watermark, blurry text",
    magicPrompt: true,
    size: {
      type: "aspect_ratio",
      aspectRatio: "4:5",
      scale: "4k",
    },
    output: {
      format: "png",
      quality: 90,
    },
    rating: true,
    metadata: {
      requestId: "req_123",
    },
  },
});
  • negativePrompt maps to negative_prompt. magicPrompt maps to magic_prompt.
  • rating sets content rating on the result. contentRating is an alias.
  • size overrides the top-level size. Use it for Mynth size objects, with aspect ratios and an optional scale: "4k". The top-level size takes short values such as "auto", "square", or "landscape".
  • destination sends the generation to a Mynth destination. It overrides the adapter default and the env default.
  • promptStructured expands into prompt, negative_prompt, and magic_prompt. When you set it, its positive overrides the plain prompt.

The result

The adapter returns the normalized image result of TanStack AI:

  • id: the Mynth task id.
  • model: the model that Mynth used, or the requested model if Mynth returned none.
  • images: only the images that succeeded.
  • images[*].revisedPrompt: set when Mynth improves the prompt.

API

ExportWhat it is
mynthImage(model, config?)Creates an image adapter. config.apiKey overrides MYNTH_API_KEY. config.baseUrl overrides the base URL. config.destination sets a default destination.
createMynthImage(config?)Creates a factory that returns adapters for a model.
MYNTH_IMAGE_MODELSA readonly array of the image model ids.
MynthImageModelThe type of the image model ids.
MYNTH_IMAGE_INPUT_MODELSA readonly array of the model ids that take image input (image to image, try-on).
MynthImageInputModelThe type of the model ids that take image input.

This package has only an image adapter for generateImage(). It has no chat or text adapter.

Advanced

Models endpoint

Mynth has a public catalog at https://api.mynth.io/models. It needs no API key, and it has the prices. Use it for a model picker with live prices:

ts
const response = await fetch("https://api.mynth.io/models");
const { data } = await response.json();

for (const model of data) {
  console.log(model.id, model.displayName, model.pricing);
}

Each entry looks about like this:

json
{
  "id": "black-forest-labs/flux.2-dev",
  "displayName": "FLUX.2 Dev",
  "pricing": {
    "perImage": { "base": "0.01", "4k": "0.04" },
    "perInput": "0.002",
  },
}

With the Mynth SDK, new Mynth().models.list() gives the same data. See the Mynth SDK README and Mynth.

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