quiverai-ai-provider

QuiverAI provider for the Vercel AI SDK.

QuiverAI generates scalable vector graphics (SVG) from text prompts and images. SVG is an interesting edge case in AI generation: it is plain text (XML markup) that renders as a vector image. That duality means you can use it through two different AI SDK interfaces — streamText / generateText if you want a progressive streaming UX where the SVG builds up character by character, or generateImage if you prefer the more natural "give me an image" API. Both are supported.

Installation

npm install quiverai-ai-provider ai

pnpm add quiverai-ai-provider ai

Provider Instance

import { quiverai } from 'quiverai-ai-provider';

For a customized setup:

import { createQuiverAI } from 'quiverai-ai-provider';

const quiverai = createQuiverAI({
  apiKey: 'your-api-key', // defaults to QUIVERAI_API_KEY env var
  baseURL: 'custom-url', // optional, defaults to https://api.quiver.ai/v1
  headers: { /* custom headers */ }, // optional
});

Settings

| Option | Type | Description | |---|---|---| | apiKey | string | API key sent as Authorization: Bearer. Defaults to QUIVERAI_API_KEY. | | baseURL | string | Override the API base URL. | | headers | Record<string, string> | Extra headers included in every request. | | fetch | FetchFunction | Custom fetch implementation (useful for testing/proxying). |

Language Models

Use streamText or generateText to receive SVG markup as text output. Streaming is especially useful for progressive rendering — each token is a small SVG fragment you can render live in the browser as it arrives.

Streaming

import { quiverai } from 'quiverai-ai-provider';
import { streamText } from 'ai';

const result = streamText({
  model: quiverai('arrow-preview'),
  prompt: 'A red circle with a blue border',
});

for await (const chunk of result.textStream) {
  process.stdout.write(chunk); // progressive SVG markup
}

console.log('Usage:', await result.usage);

Non-streaming

import { quiverai } from 'quiverai-ai-provider';
import { generateText } from 'ai';

const { text, usage } = await generateText({
  model: quiverai('arrow-preview'),
  prompt: 'A red circle with a blue border',
});

console.log(text); // complete SVG markup

Vectorization (image → SVG)

Include an image file part in the prompt to convert a raster image to SVG:

import { quiverai } from 'quiverai-ai-provider';
import { generateText } from 'ai';
import { readFileSync } from 'node:fs';

const { text } = await generateText({
  model: quiverai('arrow-preview'),
  messages: [
    {
      role: 'user',
      content: [
        {
          type: 'file',
          data: readFileSync('logo.png'),
          mediaType: 'image/png',
        },
      ],
    },
  ],
});

console.log(text); // SVG markup of the vectorized image

Model Capabilities

| Model | Text-to-SVG | Image-to-SVG | Streaming | |---|:---:|:---:|:---:| | arrow-preview | ✓ | ✓ | ✓ |

Unsupported Features

The following AI SDK parameters are not supported and will produce a warning if provided: tools, responseFormat, stopSequences, topK, seed, frequencyPenalty.

Image Models

Use generateImage for a conventional image generation workflow. The SVG is returned as a Uint8Array containing UTF-8 encoded markup — write it directly to a .svg file or decode it to a string.

Basic Usage

import { quiverai } from 'quiverai-ai-provider';
import { generateImage } from 'ai';
import { writeFileSync } from 'node:fs';

const { images } = await generateImage({
  model: quiverai.image('arrow-preview'),
  prompt: 'A red circle with a blue border',
});

const decoder = new TextDecoder();
for (const image of images) {
  console.log(decoder.decode(image.uint8Array)); // SVG markup
  writeFileSync(`output-${Date.now()}.svg`, image.uint8Array);
}

Vectorization (image → SVG)

import { quiverai } from 'quiverai-ai-provider';
import { generateImage } from 'ai';
import { readFileSync } from 'node:fs';

const { images } = await generateImage({
  model: quiverai.image('arrow-preview'),
  prompt: '',
  files: [
    {
      type: 'file',
      data: readFileSync('logo.png'),
      mediaType: 'image/png',
    },
  ],
  providerOptions: {
    quiverai: {
      autoCrop: true,
      targetSize: 512,
    },
  },
});

Provider Options

Pass QuiverAI-specific options via providerOptions.quiverai on any call:

import { quiverai, type QuiverAILanguageProviderOptions } from 'quiverai-ai-provider';
import { generateText } from 'ai';

const { text } = await generateText({
  model: quiverai('arrow-preview'),
  prompt: 'A minimalist logo for a coffee shop',
  providerOptions: {
    quiverai: {
      instructions: 'flat design, monochrome, geometric shapes only',
      temperature: 0.7,
      maxOutputTokens: 4096,
    } satisfies QuiverAILanguageProviderOptions,
  },
});

| Option | Type | Description | |---|---|---| | instructions | string | Additional style/quality instructions appended to the prompt (text-to-SVG only). | | temperature | number | Controls randomness. | | topP | number | Nucleus sampling threshold. | | maxOutputTokens | number | Maximum tokens to generate. | | autoCrop | boolean | Auto-crop source image before vectorization. | | targetSize | number | Target output size in pixels (vectorization only). |

Provider Metadata

const { images, providerMetadata } = await generateImage({
  model: quiverai.image('arrow-preview'),
  prompt: 'A red circle with a blue border',
});

console.log(providerMetadata?.quiverai);
// {
//   images: [{ mimeType: 'image/svg+xml' }],
//   usage: { inputTokens: 0, outputTokens: 0, totalTokens: 0 }
// }

Note: QuiverAI currently returns 0 for all token counts (inputTokens, outputTokens, totalTokens). Pricing is a fixed cost per generation, not token-based.

Contributing

Setup

git clone https://github.com/pmontp19/quiverai-ai-sdk-provider.git
cd quiverai-ai-sdk-provider
npm install

A pre-commit hook runs biome check --write on staged files automatically.

Scripts

| Command | Description | |---|---| | npm run check | Lint and format check (biome) | | npm run check:fix | Auto-fix lint and format issues | | npm run type-check | TypeScript type checking | | npm test | Run tests | | npm run build | Build the package |

Making changes

Every PR that affects the published package must include a changeset — a small file that describes what changed and the semver bump type.

npx changeset

This prompts you to select the bump type (patch, minor, or major) and write a short summary. It creates a markdown file in .changeset/ that you commit alongside your code.

If you forget, the CI changeset-check job will fail on your PR as a reminder.

Release flow

1. PRs with changesets are merged into main.
2. The Release workflow automatically opens a "chore: version packages" PR that bumps version in package.json and updates CHANGELOG.md.
3. When that PR is merged, the package is published to npm automatically.

Adding a changeset retroactively

If a PR was already merged without a changeset, create one on a new branch:

git checkout -b chore/add-changeset
npx changeset
# select the bump type and describe the change that was already merged
git add .changeset/
git commit -m "chore: add missing changeset for <feature>"

Then open a PR. Once merged, the release PR will pick it up.

License

MIT