A proposed browser standard for provider-agnostic AI inference.
Status: Experimental Draft
Spec: SPEC.md
- Inference Bridge — official Chrome extension that injects
window.inferenceand routes to OpenAI, Anthropic, OpenRouter, Ollama, or experimental OpenAI-compatible servers (source)
Install from the Chrome Web Store, or for development clone the repository and load it unpacked from chrome://extensions (Developer mode → Load unpacked → select the repo root).
- Examples index — gallery of demo apps (source)
- Chat demo — minimal chat UI that uses the API (source)
- Social demo — post + replies with a Grok-like Ask AI panel (source)
- Translate demo — short haiku translated with
ipa-toolscomplete(source)
The specification defines the standard. Inference Bridge implements that standard and may also include experimental features that are not part of the API contract yet. Applications should target the Inference Provider API (request and getFeatures), not extension-specific namespaces.
Today, every AI-powered web application has to reinvent the same infrastructure:
- Ask users for API keys
- Integrate every inference provider separately
- Proxy requests through their own backend
- Build custom permission systems
The Inference Provider API (IPA) proposes a standard browser interface that allows web applications to request inference from a user-approved browser extension without ever accessing API keys.
Inspired by NIP-07, IPA separates applications from providers, giving users complete control over where inference is performed.
- Users own their API keys.
- Applications request inference, not providers.
- Users choose providers.
- Users choose models.
- Applications should be provider agnostic.
- Local and remote inference are first-class citizens.
- Permission is explicit.
- API keys never leave the browser extension.
for await (const chunk of window.inference.request({
method: "chat",
messages: [
{
role: "user",
content: `Is this true?:\n\nNostr is dead.`
}
]
})) {
if (chunk.type === "accepted") {
// permission resolved; provider call may begin
} else if (chunk.type === "reasoning_delta") {
// optional: model reasoning / chain-of-thought
} else if (chunk.type === "delta") {
// append chunk.content to the reply UI
} else if (chunk.type === "done") {
// final message / usage; message.reasoning when reasoning was streamed
}
}request is required. getFeatures reports optional capabilities such as tool calling and request options (for example reasoningEffort, temperature); implementations that omit it advertise none. If the app only needs the final message, drain to done (inline sketch — or use ipa-tools’s complete):
async function complete(request) {
let done;
for await (const chunk of window.inference.request(request)) {
if (chunk.type === "done") done = chunk;
}
return done;
}
const { model, message, usage } = await complete({
method: "chat",
messages: [{ role: "user", content: "Is this true?:\n\nNostr is dead." }],
});The helper is application code, not part of window.inference. It throws InferenceError the same way iterating request does.
Feature-detect optional capabilities before sending tools. Missing getFeatures means none:
const features = window.inference.getFeatures?.() ?? {};
if (features.toolCalling) {
const tools = [
{
type: "function",
function: {
name: "get_weather",
description: "Get the current weather for a city",
parameters: {
type: "object",
properties: { city: { type: "string" } },
required: ["city"],
},
},
},
];
for await (const chunk of window.inference.request({
method: "chat",
messages: [{ role: "user", content: "What's the weather in Austin?" }],
tools,
})) {
if (chunk.type === "done" && chunk.message.toolCalls?.length) {
// page executes the function, appends role: "tool" results, calls request again
}
}
}Request options can be sent without feature detection — unsupported keys are ignored:
// Prefer less thinking / lower temperature for translation
for await (const chunk of window.inference.request({
method: "chat",
messages: [{ role: "user", content: "Translate to Spanish: Hello" }],
options: {
reasoningEffort: "none",
temperature: 0.2,
},
})) {
// ...
}Any multi-round tool loop is application code. Implementations that do not
advertise toolCalling reject tools with invalid_request. Unsupported
options keys are ignored (not rejected) so apps may send them for forward
compatibility. For a ready-made loop (plus types and complete), see the
non-normative ipa-tools package
(npm install ipa-tools).
Sending tools on IPA request without a toolCalling advertisement is
invalid_request. Prefer getFeatures().toolCalling before enabling tools;
see ipa-tools.
The extension prompts the user for permission:
Allow inference?
primal.net
Provider
[ Ollama ▼ ]
Model
[ Gemma 4 ▼ ]
Request preview
user: Is this true?:
Nostr is dead.
[ ] Remember for this site
Allow once, or deny only this request.
[Allow] [Deny]
Request preview is optional extension UX for this draft, not part of the API
contract. When the request includes tools, the permission UI must list the
function names; a persistent chat grant does not silently cover a later tools
request.
The user chooses the provider and model. With “Remember for this site” checked, Allow persists access for that origin together with the chosen provider and model; Deny permanently blocks it. Changing the extension’s global default does not alter existing origin grants.
Text chat is required. Tool calling is optional: implementations that support it
return { toolCalling: true } from getFeatures and accept tools on
request. The page defines and executes function tools; the extension only
relays schemas, toolCalls, and results. Optional options (for example
options.reasoningEffort: "auto" | "none" | "low" | "medium" | "high",
options.temperature: number in [0, 2]) lets apps prefer generation settings
when the matching getFeatures().options key is true — not a permission change;
user override or clamp controls are optional extension UX. See
SPEC.md.
- Standard browser API
- Provider agnostic
- Bring Your Own Key (BYOK)
- Local-first compatible
- Per-origin permissions
- Streaming support
- Zero backend required
- Optional capability discovery (
getFeatures) - Optional function tools, executed by the page
- Optional request
options(for examplereasoningEffort,temperature)
- Replacing provider SDKs
- Billing
- Authentication
- Defining inference protocols
- Choosing the "best" model
An IPA-compatible browser extension could route requests to any provider, including:
- OpenAI
- Anthropic
- Google Gemini
- xAI
- OpenRouter
- ppq.ai
- Routstr
- Ollama
- LM Studio
- Local inference servers
Applications should not need to know which provider the user has selected.
Local servers often reject requests that carry a chrome-extension:// Origin
header (commonly HTTP 403). IPA extensions that support local inference should
strip or rewrite that header on their own requests to loopback endpoints so
users are not asked to set OLLAMA_ORIGINS=chrome-extension://* or similar
allowlists. Widening the local server's origin allowlist remains a fallback, not
the preferred path.
Chrome MV3 reference: Inference Bridge
does this with declarativeNetRequestWithHostAccess and dynamic rules in
src/ollama-origin-bypass.js
and
src/loopback-origin-bypass.js
that remove Origin / Referer for local Ollama and other loopback
OpenAI-compatible servers. See SPEC.md Security for the normative
guidance.
That permission lets the extension modify request headers only for hosts already
listed in host_permissions—it is not a browser-wide rewrite capability. Still
treat it as privileged: a compromised or overly broad extension could alter
headers on those hosts. Prefer port-scoped loopback permissions (for example
http://localhost:11434/*) over http://localhost/*, keep DNR rules limited to
local inference endpoints, and do not use DNR to touch remote provider traffic.
This is still preferable to asking every user to set
OLLAMA_ORIGINS=chrome-extension://*, which trusts every installed extension
talking to Ollama.
- A "Grok" button on every social post.
- AI-powered documentation.
- Browser-based coding tools and other page-executed function tools.
- Translation.
- Writing assistance.
- Local-first AI applications.
Some topics that still need community discussion:
- Is
window.inferencethe right namespace? - Which further capability constraints, if any, do applications need beyond tools and
options? - Are
"auto" | "none" | "low" | "medium" | "high"the rightoptions.reasoningEffortlevels, or should the field become a provider-mapped budget/token object? - Which further keys belong under
options(for examplemaxTokens), and should clamp/override UX stay optional? - Should model selection always remain under user control?
- Should images, embeddings, and speech use this API or separate APIs?
- How should extensions surface token usage? Should estimated cost remain optional UX until pricing metadata is defined?
- Should
getFeaturesgrow beyond booleans (for example nested tool kinds), or stay one key per capability? - Should hosted / provider-executed tools (web search, MCP) be specified, or remain implementation-specific?
- Should tool calls stream as their own chunk type, or stay on
done.message.toolCallsonly? - Should structured outputs (e.g. JSON Schema /
responseFormat) be part of IPA, or left to prompt engineering until providers converge? - How should permission UIs present multi-message requests — e.g. emphasize the last user message and collapse system/context by default?
- Should applications be encouraged or required to round-trip
message.reasoningon later turns for providers that benefit from it?
This proposal is intentionally in an early draft stage.
The goal is to collaboratively design an open browser standard for provider-agnostic inference—not a specific implementation.
Contributions of all kinds are welcome, including:
- Design feedback
- API suggestions
- Security considerations
- Alternative approaches
- Reference implementations
- Browser extension prototypes
- Related standards or prior art
If you have an idea or concern, please open an issue.
This project is licensed under the MIT License. See LICENSE for details.