Zhipu AI Provider - Vercel AI SDK Community Provider

This is a Zhipu (Z.ai) prodiver for the Vercel AI SDK. It enables seamless integration with Language (GLM), Embedding and Image Models provided on bigmodel.cn or z.ai by ZhipuAI.

Setup

# npm
npm i zhipu-ai-provider

# pnpm
pnpm add zhipu-ai-provider

# yarn
yarn add zhipu-ai-provider

# bun
bun add zhipu-ai-provider

Set up your .env file / environment with your API key.

ZHIPU_API_KEY=<your-api-key>

Provider Instance

You can import the default provider instance zhipu from zhipu-ai-provider (This automatically reads the API key from the environment variable ZHIPU_API_KEY):

import { zhipu } from 'zhipu-ai-provider' // for bigmodel.cn
// or
import { zai } from 'zhipu-ai-provider' // for z.ai

Alternatively, you can create a provider instance with custom configuration with createZhipu:

import { createZhipu } from 'zhipu-ai-provider';

const zhipu = createZhipu({
  baseURL: "https://open.bigmodel.cn/api/paas/v4",
  apiKey: "your-api-key"
});

You can use the following optional settings to customize the Zhipu provider instance:

• baseURL: string
  • Use a different URL prefix for API calls, e.g. to use proxy servers. The default prefix is https://open.bigmodel.cn/api/paas/v4.
• apiKey: string
  • Your API key for Zhipu BigModel Platform. If not provided, the provider will attempt to read the API key from the environment variable ZHIPU_API_KEY.
• headers: Record<string,string>
  • Custom headers to include in the requests.

Language Model Example

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

const { text } = await generateText({
  model: zhipu('glm-4-plus'),
  prompt: 'Why is the sky blue?',
});

console.log(result)

To disable thinking for hybrid models like glm-4.7, you can set the think option to disable either in the model options or in the providerOptions:

const { text } = await generateText({
  model: zhipu('glm-4.7', {
    think: {
      type: 'disable'
    }, // Disable thinking
  }),
  prompt: 'Explain quantum computing in simple terms.',
});

or

const { text } = await generateText({
  model: zhipu('glm-4.7'),
  prompt: 'Explain quantum computing in simple terms.',
  providerOptions: {
    zhipu: {
      think: {
        type: 'disable'
      }
    }
  }
});

Embedding Example

const { embedding } = await embed({
  model: zhipu.textEmbeddingModel("embedding-3", {
    dimensions: 256, // Optional, defaults to 2048
  }),
  value: "Hello, world!",
});

console.log(embedding);

Image Generation Example

Zhipu supports image generation with glm-image or cogview models, but the api does not return images in base64 or buffer format, so the image urls are returned in the providerMetadata field.

import { experimental_generateImage as generateImage } from 'ai';
import { zhipu } from 'zhipu-ai-provider';

const { image, providerMetadata } = await generateImage({
  model: zhipu.ImageModel('cogview-4-250304'),
  prompt: 'A beautiful landscape with mountains and a river',
  size: '1024x1024',  // optional
  providerOptions: {  // optional
      zhipu: {
          quality: 'hd'
      }
  }
});

console.log(providerMetadata.zhipu.images[0].url)

Features Support

• Text generation
• Text embedding
• Image generation
• Chat
• Tools
• Streaming
• Structured output
• Reasoning
• Vision
• Vision Reasoning
• Provider-defined tools
• Video Models
• Audio Models

Documentation

• Zhipu documentation
• Z.AI documentation
• Vercel AI SDK documentation
• Zhipu AI Provider Repo