Chrome Prompt API Reference

Complete implementation guide for Chrome's built-in Prompt API using Gemini Nano.

Hardware & OS Requirements

OS: Windows 10/11, macOS 13+ (Ventura+), Linux, ChromeOS (Platform 16389.0.0+) on Chromebook Plus Storage: 22 GB free (model downloaded separately) GPU: >4 GB VRAM OR CPU: 16 GB RAM + 4 cores Network: Unmetered connection for download Chrome: 138+ (Extensions in stable, Web in origin trial)

Not supported: Mobile (Android, iOS), non-Chromebook Plus ChromeOS

Check model size:

chrome://on-device-internals

Model removed if storage <10 GB after download.

Language Support

From Chrome 140: English, Spanish, Japanese (input/output)

Availability Check

const availability = await LanguageModel.availability();
// Returns: "unavailable" | "downloadable" | "downloading" | "available"

CRITICAL: Always pass same options to

availability()

as you use in

create()

. Some models don't support certain modalities/languages.

Model Parameters

await LanguageModel.params();
// { defaultTopK: 3, maxTopK: 128, defaultTemperature: 1, maxTemperature: 2 }

Session Creation

Basic Session

const session = await LanguageModel.create();

With Custom Parameters

const params = await LanguageModel.params();
const session = await LanguageModel.create({
  temperature: Math.min(params.defaultTemperature * 1.2, 2.0),
  topK: params.defaultTopK
});

With Download Monitoring

const session = await LanguageModel.create({
  monitor(m) {
    m.addEventListener('downloadprogress', (e) => {
      console.log(`Downloaded ${e.loaded * 100}%`);
    });
  }
});

With AbortSignal

const controller = new AbortController();
stopButton.onclick = () => controller.abort();

const session = await LanguageModel.create({
  signal: controller.signal
});

Initial Prompts (Context Setting)

const session = await LanguageModel.create({
  initialPrompts: [
    { role: 'system', content: 'You are a helpful assistant.' },
    { role: 'user', content: 'What is the capital of Italy?' },
    { role: 'assistant', content: 'The capital of Italy is Rome.' },
    { role: 'user', content: 'What language is spoken there?' },
    { role: 'assistant', content: 'The official language is Italian.' }
  ]
});

Use cases:

• Resume stored sessions after browser restart
• N-shot prompting
• Set assistant personality/tone
• Provide conversation history

Multimodal Input (Origin Trial)

expectedInputs & expectedOutputs

const session = await LanguageModel.create({
  expectedInputs: [
    {
      type: "text",  // or "image", "audio"
      languages: ["en" /* system */, "ja" /* user prompt */]
    }
  ],
  expectedOutputs: [
    { type: "text", languages: ["ja"] }
  ]
});

Input types: text, image, audio Output types: text only

Throws

NotSupportedError

if unsupported modality.

Using with Images/Audio

const session = await LanguageModel.create({
  initialPrompts: [{
    role: 'system',
    content: 'Analyze images for patterns.'
  }],
  expectedInputs: [{ type: 'image' }]
});

// Append image
await session.append([{
  role: 'user',
  content: [
    { type: 'text', value: 'Analyze this image' },
    { type: 'image', value: fileInput.files[0] }
  ]
}]);

Prompting Methods

Non-Streaming (Short Responses)

const result = await session.prompt('Write me a haiku!');
console.log(result);

Streaming (Long Responses)

const stream = session.promptStreaming('Write me a long poem!');
for await (const chunk of stream) {
  console.log(chunk);  // Partial results as they arrive
}

With AbortSignal

const controller = new AbortController();
stopButton.onclick = () => controller.abort();

const result = await session.prompt('Write a poem', {
  signal: controller.signal
});

Response Constraints (Structured Output)

Pass JSON Schema to get predictable JSON responses:

const schema = {
  type: "object",
  properties: {
    hashtags: {
      type: "array",
      maxItems: 3,
      items: {
        type: "string",
        pattern: "^#[^\\s#]+$"
      }
    }
  },
  required: ["hashtags"],
  additionalProperties: false
};

const result = await session.prompt(
  `Generate hashtags for: ${post}`,
  { responseConstraint: schema }
);

const data = JSON.parse(result);  // Guaranteed valid JSON

Simple boolean example:

const schema = { "type": "boolean" };
const result = await session.prompt(
  `Is this about pottery?\n\n${text}`,
  { responseConstraint: schema }
);
console.log(JSON.parse(result));  // true or false

Measure input quota usage:

const usage = session.measureInputUsage({ responseConstraint: schema });

Omit schema from input quota:

const result = await session.prompt(
  `Summarize as JSON { rating } with 0-5 number:`,
  {
    responseConstraint: schema,
    omitResponseConstraintInput: true
  }
);

Response Prefixes

Guide model output format by prefilling assistant response:

const result = await session.prompt([
  { role: 'user', content: 'Create a TOML character sheet' },
  { role: 'assistant', content: '```toml\n', prefix: true }
]);
// Model continues from "```toml\n"

append() Method

Add messages to session without immediate response (useful for multimodal):

await session.append([
  {
    role: 'user',
    content: [
      { type: 'text', value: 'First context message' },
      { type: 'image', value: imageFile }
    ]
  }
]);

// Later, prompt with accumulated context
const result = await session.prompt('Analyze the images');

Promise fulfills when validated and appended.

Session Management

Check Quota

console.log(`${session.inputUsage}/${session.inputQuota}`);
const remaining = session.inputQuota - session.inputUsage;

When quota exceeded, oldest messages lost from context.

Clone Session

Clones inherit parameters, initial prompts, and history:

const mainSession = await LanguageModel.create({
  initialPrompts: [{ role: 'system', content: 'Speak like a pirate' }]
});

const clone1 = await mainSession.clone();
const clone2 = await mainSession.clone({ signal: controller.signal });

// Independent conversations with same setup
await clone1.prompt('Tell me a joke about parrots');
await clone2.prompt('Tell me a joke about treasure');

Use for: Parallel conversations, "what if" scenarios, resource efficiency

Restore Session from localStorage

let sessionData = getFromLocalStorage(uuid) || {
  initialPrompts: [],
  topK: (await LanguageModel.params()).defaultTopK,
  temperature: (await LanguageModel.params()).defaultTemperature
};

const session = await LanguageModel.create(sessionData);

// Track conversation
const stream = session.promptStreaming(prompt);
let result = '';
for await (const chunk of stream) {
  result = chunk;
}

sessionData.initialPrompts.push(
  { role: 'user', content: prompt },
  { role: 'assistant', content: result }
);

localStorage.setItem(uuid, JSON.stringify(sessionData));

Destroy Session

session.destroy();
// Frees resources, aborts ongoing execution
// Session unusable after destroy

Best practice: Keep one empty session alive to keep model loaded. Destroy only when truly done.

User Activation Requirement

Model download requires user interaction:

if (navigator.userActivation.isActive) {
  const session = await LanguageModel.create();
}

Sticky activation events: click, tap, keydown, mousedown

Permission Policy & iframes

Default: Top-level windows + same-origin iframes only

Grant cross-origin iframe access:

<iframe src="https://cross-origin.example.com/"
        allow="language-model">
</iframe>

Not available in Web Workers (permission policy complexity)

Local Development (localhost)

1. Go to

   chrome://flags/#prompt-api-for-gemini-nano-multimodal-input

2. Select Enabled
3. Relaunch Chrome
4. Open DevTools, type:

   await LanguageModel.availability();

5. Should return

   "available"

Troubleshoot:

• Restart Chrome
• Check

  chrome://on-device-internals

  → Model Status tab
• Wait for model download to complete

Chrome Extensions

Available in Chrome 138+ stable for extensions.

Remove expired origin trial permissions:

{
  "permissions": ["aiLanguageModelOriginTrial"]  // REMOVE THIS
}

Register for current origin trial if needed.

Best Practices

Session management:

• Clone sessions to preserve initial prompts
• Use AbortController to let users stop responses
• Track inputUsage to warn before quota exceeded
• Destroy unused sessions to free memory
• Keep one empty session alive to keep model ready

Performance:

• Use streaming for long responses
• append() messages in advance for multimodal
• Monitor download progress, inform users
• Check availability before creating sessions

Structured output:

• Use JSON Schema for predictable responses
• LLMs good at generating schemas from descriptions
• Validate with JSON Schema validators
• Use prefix for format guidance

Context preservation:

• Store conversation in localStorage for restoration
• Use initialPrompts for session context
• Clone for parallel conversations with same context

Error Handling

try {
  const session = await LanguageModel.create();
  const result = await session.prompt('Hello');
} catch (err) {
  if (err.name === 'AbortError') {
    // User stopped generation
  } else if (err.name === 'NotSupportedError') {
    // Unsupported modality/language
  } else {
    console.error(err.name, err.message);
  }
}

Key Limitations

• Desktop only (no mobile)
• 22 GB storage required
• Unmetered network for download
• No Web Workers support
• Output is text-only (input can be multimodal)
• Context window has token limits
• Model removed if storage <10 GB after download

Use Cases

• AI-powered search on page content
• Content classification/filtering
• Event extraction from pages
• Contact information extraction
• Chatbots with conversation memory
• Offline AI features
• Privacy-sensitive data processing
• Content summarization
• Translation assistance
• Image/audio analysis (multimodal)