Chrome AI

Vercel AI provider for Chrome built-in model (Gemini Nano).

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⚠️ Note:

• This module is under development and may contain errors and frequent incompatible changes.
• Chrome's implementation of built-in AI with Gemini Nano is an experiment and will change as they test and address feedback.
• If you've never heard of it before, follow these steps to turn on Chrome's built-in AI.

📦 Installation

The ChromeAI provider is available in the chrome-ai module. You can install it with:

npm install chrome-ai

🦄 Language Models

The chromeai provider instance is a function that you can invoke to create a language model:

import { chromeai } from 'chrome-ai';

const model = chromeai();

It automatically selects the correct model id. You can also pass additional settings in the second argument:

import { chromeai } from 'chrome-ai';

const model = chromeai('generic', {
  // additional settings
  temperature: 0.5,
  topK: 5,
});

You can use the following optional settings to customize:

• modelId 'text' | 'generic' (default: 'generic')
• temperature number (default: 0.8)
• topK number (default: 3)

Embedding models

import { chromeai } from 'chrome-ai';
import { embedMany, cosineSimilarity } from 'ai';

const { embeddings } = await embedMany({
  model: chromeai.embedding(),
  values: ['sunny day at the beach', 'rainy afternoon in the city'],
});
// [[1.9545, 0.0318...], [1.8015, 0.1504...]]

const similarity = cosineSimilarity(embeddings[0], embeddings[1]);
// similarity: 0.9474937159037822

🎯 Examples

You can use Chrome built-in language models to generate text with the generateText or streamText function:

import { generateText } from 'ai';
import { chromeai } from 'chrome-ai';

const { text } = await generateText({
  model: chromeai(),
  prompt: 'Who are you?',
});

console.log(text); //  I am a large language model, trained by Google.

import { streamText } from 'ai';
import { chromeai } from 'chrome-ai';

const { textStream } = await streamText({
  model: chromeai(),
  prompt: 'Who are you?',
});

let result = '';
for await (const textPart of textStream) {
  result = textPart;
}

console.log(result);
//  I am a large language model, trained by Google.

Chrome built-in language models can also be used in the generateObject/streamObject function:

import { generateObject } from 'ai';
import { chromeai } from 'chrome-ai';
import { z } from 'zod';

const { object } = await generateObject({
  model: chromeai(),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(
        z.object({
          name: z.string(),
          amount: z.string(),
        })
      ),
      steps: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a lasagna recipe.',
});

console.log(object);
// { recipe: {...} }

import { streamObject } from 'ai';
import { chromeai } from 'chrome-ai';
import { z } from 'zod';

const { partialObjectStream } = await streamObject({
  model: chromeai(),
  schema: z.object({
    recipe: z.object({
      name: z.string(),
      ingredients: z.array(
        z.object({
          name: z.string(),
          amount: z.string(),
        })
      ),
      steps: z.array(z.string()),
    }),
  }),
  prompt: 'Generate a lasagna recipe.',
});

for await (const partialObject of result.partialObjectStream) {
  console.log(JSON.stringify(partialObject, null, 2));
  // { recipe: {...} }
}

Due to model reasons, toolCall/functionCall are not supported. We are making an effort to implement these functions by prompt engineering.

Enable AI in Chrome

Chrome built-in AI is a preview feature, you need to use chrome version 127 or greater, now in dev or canary channel, may release on stable chanel at Jul 17, 2024.

After then, you should turn on these flags:

• chrome://flags/#prompt-api-for-gemini-nano: Enabled
• chrome://flags/#optimization-guide-on-device-model: Enabled BypassPrefRequirement
• chrome://components/: Click Optimization Guide On Device Model to download the model.

License

MIT License © 2024 Jeason