does kindness plus sadness equal to zero?

I'm pleased to announce the release of xsAI v0.2.

This version codename still corresponds to a song by Kizuna AI and you can listen to it:

btw, v0.1 is "Hello World"

OK, so here's the new features:

• Generate image
• Reasoning utils
• More schema library supported
• More providers
• More integrations

Generate Image

GPT 4o Image Generation is very popular these days, isn't it?

Now you can also use it via API and @xsai/generate-image:

import { generateImage } from '@xsai/generate-image'
import { env } from 'node:process'

const prompt = 'A children\'s book drawing of a veterinarian using a stethoscope to listen to the heartbeat of a baby otter.'

const { image } = await generateImage({
  apiKey: env.OPENAI_API_KEY!,
  baseURL: 'http://api.openai.com/v1/',
  model: 'gpt-image-1',
  prompt,
})

const { images } = await generateImage({
  apiKey: env.OPENAI_API_KEY!,
  baseURL: 'http://api.openai.com/v1/',
  n: 4,
  model: 'gpt-image-1',
  prompt,
})

If this feature is popular, we may introduce editImage later.

Reasoning Utils

We made @xsai/utils-reasoning for models like qwq and deepseek-r1:

import { generateText } from '@xsai/generate-text'
import { streamText } from '@xsai/stream-text'
import { extractReasoning, extractReasoningStream } from '@xsai/utils-reasoning'

const messages = [
  {
    content: 'You\'re a helpful assistant.',
    role: 'system'
  },
  {
    content: 'Why is the sky blue?',
    role: 'user'
  },
]

const { text: rawText } = await generateText({
  baseURL: 'http://localhost:11434/v1/',
  messages,
  model: 'deepseek-r1',
})

const { textStream: rawTextStream } = await streamText({
  baseURL: 'http://localhost:11434/v1/',
  messages,
  model: 'deepseek-r1',
})

// { reasoning: string | undefined, text: string }
const { reasoning, text } = extractReasoning(rawText!)
// { reasoningStream: ReadableStream<string>, textStream: ReadableStream<string> }
const { reasoningStream, textStream } = extractReasoningStream(rawTextStream)

More schema library supported

We have supported Zod 4 Beta before it was officially released. (also includes @zod/mini!)

Effect Schema is supported as well.

More providers

We now support Featherless.

Did you know we've added a lot of providers? view here.

Special providers

New 🤗 Transformer.js provider

Have you dreamed about a possible future where you can use xsAI completely offline without Ollama and other inference server setup? We mentioned a bit in the previous blog post about our roadmap, here we come.

We now get a new dedicated project called xsai-transformers on GitHub, where we wrapped the famous library to work with models and inference, Transformer.js to help you get started on running embedding, speech, transcription, chat completions models with seamlessly designed API that compatible to xsAI, in both browser, WASM supported or WebGPU supported environments.

If you are interested, try it on our live demo.

npm i xsai-transformers

It feels like this when using it:

import { createEmbedProvider } from 'xsai-transformers'
import embedWorkerURL from 'xsai-transformers/embed/worker?worker&url'
import { embed } from 'xsai'

const transformers = createEmbedProvider({ baseURL: `xsai-transformers:///?worker-url=${embedWorkerURL}` })

// [
//   -0.038177140057086945,
//   0.032910916954278946,
//   -0.005459371022880077,
//   // ...
// ]
const { embedding } = await embed({
  ...transformers.embed('Xenova/all-MiniLM-L6-v2'),
  input: 'sunny day at the beach'
})

unSpeech

While you may notice we removed unSpeech from @xsai-ext/providers-local (our written provider to connect speech synthesis services with the style of OpenAI API), this doesn't mean we completely gave up of unSpeech, instead, for the past month, we added support of Alibaba Cloud Model Studio and Volcano Engine to unSpeech.

Therefore, it's time for unSpeech to get its own package, you can still use all the previous provided features by installing unspeech:

npm i unspeech

More Integrations

Did you know? We now have official Agentic and VoltAgent integrations.

Join our Community

If you have questions about anything related to xsAI,

you're always welcome to ask our community on GitHub Discussions.

Why another AI SDK?

Vercel AI SDK is way too big, it includes unnecessary dependencies.

For example, Vercel AI SDK shipped with non-optional OpenTelemetry dependencies, and bind the user to use zod (you don't get to choose), and so much more...

This makes it hard to build small and decent AI applications & CLI tools with less bundle size and more controllable and atomic capabilities that user truly needed.

But, it doesn't need to be like this, isn't it?

So how small is xsAI?

Without further ado, let's look:

It's roughly a hundred times smaller than the Vercel AI SDK (*install size) and has most of its features.

Also it is 5.7KB gzipped, so the title is not wrong.

Getting started

You can install the xsai package, which contains all the core utils.

npm i xsai

Or install the corresponding packages separately according to the required features:

npm i @xsai/generate-text @xsai/embed @xsai/model

Generating Text

So let's start with some simple examples.

import { generateText } from '@xsai/generate-text'
import { env } from 'node:process'

const { text } = await generateText({
  apiKey: env.OPENAI_API_KEY!,
  baseURL: 'https://api.openai.com/v1/',
  model: 'gpt-4o'
  messages: [{
    role: 'user',
    content: 'Why is the sky blue?',
  }],
})

xsAI does not use the provider function like Vercel does by default, we simplified them into three shared fields: apiKey, baseURL and model.

• apiKey: Provider API Key
• baseURL: Provider Base URL (will be merged with the path of the corresponding util, e.g. new URL('chat/completions', 'https://api.openai.com/v1/'))
• model: Name of the model to use

Don't worry if you need to support non-OpenAI-compatible API provider, such as Claude, we left the possibilities to override fetch(...) where you can customize how the request is made, and how the response was handled.

This allows xsAI to support any OpenAI-compatible API without having to create provider packages.

Generating Text w/ Tool Calling

Continuing with the example above, we now add the tools.

import { generateText } from '@xsai/generate-text'
import { tool } from '@xsai/tool'
import { env } from 'node:process'
import * as z from 'zod'

const weather = await tool({
  name: 'weather',
  description: 'Get the weather in a location',
  parameters: z.object({
    location: z.string().describe('The location to get the weather for'),
  }),
  execute: async ({ location }) => ({
    location,
    temperature: 72 + Math.floor(Math.random() * 21) - 10,
  }),
})

const { text } = await generateText({
  apiKey: env.OPENAI_API_KEY!,
  baseURL: 'https://api.openai.com/v1/',
  model: 'gpt-4o'
  messages: [{
    role: 'user',
    content: 'What is the weather in San Francisco?',
  }],
  tools: [weather],
})

Wait, zod is not good for tree shaking and annoying. Can we use valibot? Of course!

import { tool } from '@xsai/tool'
import { description, object, pipe, string } from 'valibot'

const weather = await tool({
  name: 'weather',
  description: 'Get the weather in a location',
  parameters: object({
    location: pipe(
      string(),
      description('The location to get the weather for'),
    ),
  }),
  execute: async ({ location }) => ({
    location,
    temperature: 72 + Math.floor(Math.random() * 21) - 10,
  }),
})

We can even use arktype, and the list of compatibility will grow in the future:

import { tool } from '@xsai/tool'
import { type } from 'arktype'

const weather = await tool({
  name: 'weather',
  description: 'Get the weather in a location',
  parameters: type({
    location: 'string',
  }),
  execute: async ({ location }) => ({
    location,
    temperature: 72 + Math.floor(Math.random() * 21) - 10,
  }),
})

xsAI doesn't limit your choices into either zod, valibot, or arktype, with the power of Standard Schema, you can use any schema library it supported you like.

Easy migration

Are you already using the Vercel AI SDK? Let's see how to migrate to xsAI:

- import { openai } from '@ai-sdk/openai'
- import { generateText, tool } from 'ai'
+ import { generateText, tool } from 'xsai'
+ import { env } from 'node:process'
import * as z from 'zod'

const { text } = await generateText({
+ apiKey: env.OPENAI_API_KEY!,
+ baseURL: 'https://api.openai.com/v1/',
- model: openai('gpt-4o')
+ model: 'gpt-4o'
  messages: [{
    role: 'user',
    content: 'What is the weather in San Francisco?',
  }],
- tools: {
+ tools: [
-   weather: tool({
+   await tool({
+     name: 'weather',
      description: 'Get the weather in a location',
      parameters: z.object({
        location: z.string().describe('The location to get the weather for'),
      }),
      execute: async ({ location }) => ({
        location,
        temperature: 72 + Math.floor(Math.random() * 21) - 10,
      }),
    })
- },
+ ],
})

That's it!

Next steps

Big fan of Anthropic's MCP?

We are working on Model Context Protocol support: #84

Don't like any of the cloud provider?

We are working on a 🤗 Transformers.js provider that enables you to directly run LLMs and any 🤗 Transformers.js supported models directly in browser, with the power of WebGPU!

You can track the progress here: #41. It is really cool and playful to run embedding, speech, and transcribing models directly in the browser, so, stay tuned!

Need framework bindings?

We will do this in v0.2. See you next time!

Documentation

Since this is just an introduction article, it only covers generate-text and tool.

xsai has more utils:

export * from '@xsai/embed'
export * from '@xsai/generate-object'
export * from '@xsai/generate-speech'
export * from '@xsai/generate-text'
export * from '@xsai/generate-transcription'
export * from '@xsai/model'
export * from '@xsai/shared-chat'
export * from '@xsai/stream-object'
export * from '@xsai/stream-text'
export * from '@xsai/tool'
export * from '@xsai/utils-chat'
export * from '@xsai/utils-stream'

If you are interested, go to the documentation at https://xsai.js.org/docs to get started!

Besides xsAI, we made loads of other cool stuff too! Check out our moeru-ai GitHub organization!

Join our Community

If you have questions about anything related to xsAI,

you're always welcome to ask our community on GitHub Discussions.

Welcome to the Moeru AI Blog.