
chrome-ai
Vercel AI provider for Chrome built-in model (Gemini Nano)
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Chrome AI is a Vercel AI provider for Chrome's built-in model (Gemini Nano). It allows users to create language models using Chrome's AI capabilities. The tool is under development and may contain errors and frequent changes. Users can install the ChromeAI provider module and use it to generate text, stream text, and generate objects. To enable AI in Chrome, users need to have Chrome version 127 or greater and turn on specific flags. The tool is designed for developers and researchers interested in experimenting with Chrome's built-in AI features.
README:
⚠️ 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.
The ChromeAI provider is available in the chrome-ai
module. You can install it with:
npm install chrome-ai
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('text', {
// additional settings
temperature: 0.5,
topK: 5,
});
You can use the following optional settings to customize:
-
modelId
'text' (default:
'text'`) -
temperature
number
(default:0.8
) -
topK
number
(default:3
)
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
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.
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.
Or you can try using the experimental feature: chrome-ai/polyfill
, to use chrome-ai
in any browser that supports WebGPU and WebAssembly.
import 'chrome-ai/polyfill';
// or
require('chrome-ai/polyfill');
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