Browser.AI

Browser Prototype for On-Device AI

Browser.AI brings powerful AI models directly to your browser--supporting chat, tool calls, and embeddings--keeping your data private and enabling faster, more responsive AI interactions without cloud dependency.

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About Browser.AI Prototype

Browser.AI is an open-source project aimed at highlighting the power of on-device AI in the browser. The prototype provides a simple API on the window object that allows developers to interact with AI models directly in the browser. This project exists to demonstrate the potential of on-device AI, which I outlined in a proposal to the W3C.

API

The API is exposed through the window.ai object.

Permissions

The permissions object provides methods to interact with the permissions system.

models

The models method returns a list of available models.

await window.ai.permissions.models();

Output

[
  {
    "model": "llama3.2",
    "available": true
  },
  {
    "model": "llama3.1",
    "available": true
  },
  {
    "model": "gemma2",
    "available": true
  }
]

request

The request method requests access to a specific model.

await window.ai.permissions.request({ model: 'llama3.1' });

Model

The model object provides methods to interact with a specific model.

connect

The connect method connects to a specific model.

const session = await window.ai.model.connect({ model: 'llama3.1' });

Session

The session object provides methods to interact with the model session.

chat

The chat method starts a chat session.

await session.chat({ messages: [ { role: 'user', content: 'hello!' } ]});

Output

{
  "id": "fn6cq1zciy",
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": "Hello! How are you today? Is there something I can help you with or would you like to chat?"
      },
      "finish_reason": "stop"
    }
  ],
  "created": "2024-10-11T01:14:37.204701Z",
  "model": "llama3.1",
  "usage": {
    "total_duration": 6854656244,
    "load_duration": 41462875,
    "prompt_eval_count": 12,
    "prompt_eval_duration": 955155000,
    "eval_count": 23,
    "eval_duration": 5856371000
  }
}

Tools

The chat method supports tool calls

Output

const addFunc = (a, b) => a + b;

const addTool = {
  type: "function",
  function: {
    name: "addFunc",
    description: "Add two numbers together.",
    parameters: {
      type: "object",
      required: ["a", "b"],
      properties: {
        a: {
          type: "number",
          description: "The first number to add.",
        },
        b: {
          type: "number",
          description: "The second number to add.",
        },
      },
    },
  },
}

if(await window.ai.permissions.request({ model: 'llama3.2', silent: true })) {
  const session = await window.ai.model.connect({ model: 'llama3.2' });
  const response = await session.chat({ messages: [{ role: 'user', content: 'add 1 and 2' }], tools: [addTool] })
  
  if (response.choices[0].message.tool_calls) {
    const { name, arguments } = response.choices[0].message.tool_calls[0].function;
    const result = addFunc(arguments.a, arguments.b);
    console.log("Function " + name + " called with result: " + result);
  }
  
  console.log(response)
}

embed

The embed method starts an embed session.

await session.embed({ input: "Hello world" });

Output

{
  "model": "llama3.1",
  "embeddings": [
    [
      -0.0070958203,
      -0.019203912,
      ...
    ]
  ]
}

info

The info method provides details about the model.

const info = await window.ai.model.info({ model: 'llama3.1' });

Output

{
  "model": "llama3.1",
  "license": "[Model License]",
  "details": {
    "parent_model": "",
    "format": "gguf",
    "family": "llama",
    "families": [
      "llama"
    ],
    "parameter_size": "8.0B",
    "quantization_level": "Q4_0"
  }
}

Contribute

Check out the project on GitHub: Browser.AI GitHub Repository

Learn more about the proposal we submitted to the W3C: Browser.AI W3C Proposal