Mynth

The Mynth adapter gives you access to Mynth image generation models through TanStack AI. It is a community adapter for generateImage() with typed model IDs, normalized image results, image-to-image support, and Mynth-specific request options through modelOptions.

Mynth is image-only in this package. Reach for it when you want TanStack AI's image generation workflow with Mynth models such as Flux, Recraft, Gemini, Qwen, Seedream, Wan, and Grok Imagine.

Quick note: Mynth is in public beta, so the model lineup and a few request options are still settling. The adapter tracks the Mynth SDK closely, and we welcome feedback on the API and integration experience.

Installation

# bun
bun add @mynthio/tanstack-ai-adapter @tanstack/ai

# pnpm
pnpm add @mynthio/tanstack-ai-adapter @tanstack/ai

# npm
npm install @mynthio/tanstack-ai-adapter @tanstack/ai

# bun
bun add @mynthio/tanstack-ai-adapter @tanstack/ai

# pnpm
pnpm add @mynthio/tanstack-ai-adapter @tanstack/ai

# npm
npm install @mynthio/tanstack-ai-adapter @tanstack/ai

The adapter targets @tanstack/ai 0.34 and newer.

Authentication

Set your Mynth API key in the environment:

MYNTH_API_KEY=mak_...

MYNTH_API_KEY=mak_...

Keep MYNTH_API_KEY on the server only. Never expose it in browser code or public client environment variables, or it may end up in a client bundle.

You can also pass apiKey directly in the adapter config. baseUrl is optional and useful for proxies, tests, or custom deployments.

If you need a key, create one in the Mynth API keys dashboard.

Quick Start

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",
  numberOfImages: 1,
  size: "square",
});

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

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",
  numberOfImages: 1,
  size: "square",
});

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

TanStack AI adapters are model-bound, so you choose the Mynth model when you create the adapter.

Reusable Provider

Use createMynthImage() when you want to share config across multiple adapters:

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",
});

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

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",
});

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

You can still override shared config per adapter:

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

const mynth = createMynthImage();

const adapter = mynth("auto", {
  baseUrl: "https://proxy.example.com",
});

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

const mynth = createMynthImage();

const adapter = mynth("auto", {
  baseUrl: "https://proxy.example.com",
});

Model Options

Use TanStack's top-level fields for common options such as prompt, numberOfImages, and shorthand size. Use modelOptions for Mynth-specific options:

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",
  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",
    },
  },
});

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",
  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",
    },
  },
});

Notes:

modelOptions.negativePrompt maps to Mynth's negative_prompt, and modelOptions.magicPrompt maps to magic_prompt
modelOptions.rating configures content rating on the result. The older contentRating name still works as an alias
modelOptions.promptStructured is still supported for compatibility and expands into prompt, negative_prompt, and magic_prompt. When set, its positive overrides the plain prompt
modelOptions.size overrides the top-level size. Use it when you need structured Mynth size objects, including aspect ratios and an optional scale: "4k"
Top-level size is for shorthand values such as "auto" and preset strings like "square" or "landscape"
modelOptions.destination delivers the generation to a configured Mynth destination, overriding any adapter-level or env default

Image Inputs (image-to-image)

Models that accept image inputs work with TanStack AI's content-part prompts, so you can mix instruction text with reference images for image-to-image, reference-guided, edit, and try-on flows. The adapter maps the image parts onto Mynth's inputs:

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" },
    },
  ],
});

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" },
    },
  ],
});

A few things worth knowing:

Only models in MYNTH_IMAGE_INPUT_MODELS accept image parts. Passing image parts to a text-only model is a compile-time error
Both URL sources ({ type: "url", value }) and inline data sources ({ type: "data", value, mimeType }, encoded as a data URI) are supported
A part's metadata.role maps to Mynth's input intent. TanStack's "character" maps directly, and the other generic roles fall back to Mynth's automatic detection
For Mynth's finer-grained intents (person, garment, pose, style, background, product, object), pass modelOptions.inputs with an explicit as
Image parts from the prompt and entries in modelOptions.inputs are combined, with prompt parts first

Available Models

The adapter exports a runtime list and a type union for supported image models:

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);
}

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);
}

This is handy for model selectors, validation, and keeping client and server code in sync. There is a matching MYNTH_IMAGE_INPUT_MODELS list (and MynthImageInputModel type) for the subset that accepts image inputs.

Mynth supports model IDs across multiple providers, including 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 pricing, use the models endpoint below.

Models endpoint

Mynth exposes a public catalog at https://api.mynth.io/models. It does not require an API key, and it carries pricing today with room for more metadata over time. This is the source of truth if you want to render a picker with live pricing rather than the static exported list.

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);
}

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 roughly like this:

jsonc

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

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

If you already use the Mynth SDK, the same data is available through new Mynth().models.list().

Streaming Example

This adapter also works with TanStack AI's streaming image workflow:

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

export async function POST(request: Request) {
  const { prompt, model } = await request.json();

  const stream = generateImage({
    adapter: mynthImage(model ?? "auto"),
    prompt,
    numberOfImages: 1,
    stream: true,
  });

  return toServerSentEventsResponse(stream);
}

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

export async function POST(request: Request) {
  const { prompt, model } = await request.json();

  const stream = generateImage({
    adapter: mynthImage(model ?? "auto"),
    prompt,
    numberOfImages: 1,
    stream: true,
  });

  return toServerSentEventsResponse(stream);
}

For a full example using useGenerateImage(), see the TanStack Start + Mynth adapter demo.

Supported Capabilities

Image generation with generateImage()
Image-to-image with content-part prompts on input-capable models
Streaming image generation with stream: true
Typed model IDs through MYNTH_IMAGE_MODELS and MynthImageModel
Mynth-specific request options through modelOptions

The adapter returns TanStack AI's normalized image result shape:

id: the Mynth task id
model: the resolved model returned by Mynth, or the requested model as a fallback
images: only successful images are included
images[*].revisedPrompt: included when Mynth enhances the prompt

API Reference

mynthImage(model, config?)

Creates a Mynth image adapter directly.

model: a MynthImageModel
config.apiKey?: optional override for MYNTH_API_KEY
config.baseUrl?: optional base URL override
config.destination?: optional default destination for generated images

Returns a MynthImageAdapter for use with generateImage().

createMynthImage(config?)

Creates a reusable provider factory that returns model-bound adapters.

MYNTH_IMAGE_MODELS

Readonly array of supported Mynth image model IDs.

MynthImageModel

Type union of supported Mynth image model IDs.

MYNTH_IMAGE_INPUT_MODELS

Readonly array of model IDs that accept image inputs (image-to-image, try-on).

MynthImageInputModel

Type union of the model IDs that accept image inputs.

Limitations

This package only provides an image adapter for generateImage()
It does not provide chat or text-generation adapters

Mynth

Mynth#

Installation#

Authentication#

Quick Start#

Reusable Provider#

Model Options#

Image Inputs (image-to-image)#

Available Models#

Models endpoint#

Streaming Example#

Supported Capabilities#

API Reference#

mynthImage(model, config?)#

createMynthImage(config?)#

MYNTH_IMAGE_MODELS#

MynthImageModel#

MYNTH_IMAGE_INPUT_MODELS#

MynthImageInputModel#

Limitations#

Next Steps#

Mynth

Installation

Authentication

Quick Start

Reusable Provider

Model Options

Image Inputs (image-to-image)

Available Models

Models endpoint

Streaming Example

Supported Capabilities

API Reference

mynthImage(model, config?)

createMynthImage(config?)

MYNTH_IMAGE_MODELS

MynthImageModel

MYNTH_IMAGE_INPUT_MODELS

MynthImageInputModel

Limitations

Next Steps