Contact emails

a...@chromium.org, m...@chromium.org, btri...@chromium.org,
dome...@chromium.org, kenjibah...@chromium.org

Explainer

https://github.com/webmachinelearning/prompt-api/blob/main/README.md

Specification

None yet, although some of the shared infrastructure in
https://webmachinelearning.github.io/writing-assistance-apis/#supporting
will be used.

Summary

An API designed for interacting with an AI language model using text,
image, and audio inputs. It supports various use cases, from generating
image captions and performing visual searches to transcribing audio,
classifying sound events, generating text following specific instructions,
and extracting information or insights from text. It supports structured
outputs which ensure that responses adhere to a predefined format,
typically expressed as a JSON schema, to enhance response conformance and
facilitate seamless integration with downstream applications that require
standardized output formats.

This API is also exposed in Chrome Extensions, currently as an Origin
Trial. This Intent is for exposure as an Origin Trial on the web.

Blink component

Blink>AI>Prompt
<https://issues.chromium.org/issues?q=customfield1222907:%22Blink%3EAI%3EPrompt%22>

TAG review

https://github.com/w3ctag/design-reviews/issues/1093

TAG review status

Pending

Risks

Interoperability and Compatibility

This feature, like all built-in AI features, has inherent interoperability
risks due to the use of AI models whose behavior is not fully specified.
See some general discussion in
https://www.w3.org/reports/ai-web-impact/#interop.

In particular, because the output in response to a given prompt varies by
language model, it is possible for developers to write brittle code that
relies on specific output formats or quality, and does not work across
multiple browsers or multiple versions of the same browser.

There are some reasons to be optimistic that web developers won't write
such brittle code. Language models are inherently nondeterministic, so
creating dependencies on their exact output is difficult. And many users
will not have the hardware necessary to run a language model, so developers
will need to code in a way such that the prompt API is always used as an
enhancement, or has appropriate fallback to cloud services.

Several parts of the API design help steer developers in the right
direction, as well. The API has clear availability testing features for
developers to use, and requires developers to state their required
capabilities (e.g., modalities and languages) up front. Most importantly,
the structured outputs feature can help mitigate against writing brittle
code that relies on specific output formats.



Gecko: No signal (https://github.com/mozilla/standards-positions/issues/1213
)

WebKit: No signal (https://github.com/WebKit/standards-positions/issues/495)

Web developers: Strongly positive (
https://github.com/webmachinelearning/prompt-api/blob/main/README.md#stakeholder-feedback
)

Other signals: We are also working with Microsoft Edge developers on this
feature, with them contributing the structured output functionality.

Activation

This feature would definitely benefit from having polyfills, backed by any
of: cloud services, lazily-loaded client-side models using WebGPU, or the
web developer's own server. We anticipate seeing an ecosystem of such
polyfills grow as more developers experiment with this API.


WebView application risks

Does this intent deprecate or change behavior of existing APIs, such that
it has potentially high risk for Android WebView-based applications?

None


Goals for experimentation

Validate the technical implementation and developer experience of
multimodal inputs with a broader audience and actual usage.

Assess how structured output improves ergonomics and could address
interoperability concerns between implementations (e.g. different
underlying models).

Gather extensive feedback from a wide range of web developers rooted in
real world usage.

Identify diverse and innovative use cases to inform a roadmap of task APIs.

Ongoing technical constraints

None


Debuggability

It is possible that giving DevTools more insight into the nondeterministic
states of the model, e.g. random seeds, could help with debugging. See
discussion at https://github.com/webmachinelearning/prompt-api/issues/74.

We also have some internal debugging pages which give more detail on the
model's status, e.g. chrome://on-device-internals, and parts of these might
be suitable to port into DevTools.


Will this feature be supported on all six Blink platforms (Windows, Mac,
Linux, ChromeOS, Android, and Android WebView)?

No

Not all platforms will come with a language model. In particular, in the
initial stages we are focusing on Windows, Mac, and Linux.


Is this feature fully tested by web-platform-tests
<https://chromium.googlesource.com/chromium/src/+/main/docs/testing/web_platform_tests.md>
?

No

We plan to write web platform tests for the API surface as much as
possible. The core responses from the model will be difficult to test, but
some facets are testable, e.g. the adherence to structured output response
constraints.


Flag name on about://flags

prompt-api-for-gemini-nano-multimodal-input

Finch feature name

AIPromptAPIMultimodalInput

Requires code in //chrome?

True

Tracking bug

https://issues.chromium.org/issues/417530643

Measurement

We have various use counters for the API, e.g. LanguageModel_Create

Non-OSS dependencies

Does the feature depend on any code or APIs outside the Chromium open
source repository and its open-source dependencies to function?

Yes: this feature depends on a language model, which is bridged to the
open-source parts of the implementation via the interfaces in
//services/on_device_model.

Estimated milestones

Origin trial desktop first

139

Origin trial desktop last

144

DevTrial on desktop

137

DevTrial on Android

137


Anticipated spec changes

Open questions about a feature may be a source of future web compat or
interop issues. Please list open issues (e.g. links to known github issues
in the project for the feature specification) whose resolution may
introduce web compat/interop risk (e.g., changing to naming or structure of
the API in a non-backward-compatible way).

https://github.com/webmachinelearning/prompt-api/issues/42 is somewhat
worth keeping an eye on, but we believe a forward-compatible approach is
possible by just providing constant min = max values.

Link to entry on the Chrome Platform Status

https://chromestatus.com/feature/5134603979063296?gate=5106702730657792

Links to previous Intent discussions

Intent to Prototype:
https://groups.google.com/a/chromium.org/d/msgid/blink-dev/CAM0wra_LXU8KkcVJ0x%3DzYa4h_sC3FaHGdaoM59FNwwtRAsOALQ%40mail.gmail.com


This intent message was generated by Chrome Platform Status
<https://chromestatus.com/>.

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