docs(coding-agent): document async extension factories closes #3469
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@@ -7,6 +7,10 @@
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- Added extension support for customizing the interactive streaming working indicator via `ctx.ui.setWorkingIndicator()`, including custom animated frames, static indicators, hidden indicators, a new `working-indicator.ts` example extension, and updated extension/TUI/RPC docs ([#3413](https://github.com/badlogic/pi-mono/issues/3413))
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- Added `/clone` to duplicate the current active branch into a new session, while keeping `/fork` focused on forking from a previous user message ([#2962](https://github.com/badlogic/pi-mono/issues/2962))
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### Changed
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- Documented async extension factory functions in the extensions and custom-provider docs, including startup ordering and dynamic model/provider discovery via async initialization ([#3469](https://github.com/badlogic/pi-mono/issues/3469))
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### Fixed
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- Fixed `pi update` reinstalling npm packages that are already at the latest published version by checking the installed package version before running `npm install <pkg>@latest` ([#3000](https://github.com/badlogic/pi-mono/issues/3000))
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@@ -335,6 +335,8 @@ export default function (pi: ExtensionAPI) {
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}
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```
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The default export can also be `async`. pi waits for async extension factories before startup continues, which is useful for one-time initialization such as fetching remote model lists before calling `pi.registerProvider()`.
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**What's possible:**
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- Custom tools (or replace built-in tools entirely)
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- Sub-agents and plan mode
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@@ -59,6 +59,8 @@ export default function (pi: ExtensionAPI) {
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}
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```
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The extension factory can also be `async`. For dynamic model discovery, fetch and register models in the factory instead of `session_start`. pi waits for the factory before startup continues, so the provider is available during interactive startup and to `pi --list-models`.
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## Override Existing Provider
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The simplest use case: redirect an existing provider through a proxy.
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@@ -91,6 +93,41 @@ When only `baseUrl` and/or `headers` are provided (no `models`), all existing mo
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To add a completely new provider, specify `models` along with the required configuration.
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If the model list comes from a remote endpoint, use an async extension factory:
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```typescript
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import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
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export default async function (pi: ExtensionAPI) {
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const response = await fetch("http://localhost:1234/v1/models");
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const payload = (await response.json()) as {
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data: Array<{
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id: string;
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name?: string;
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context_window?: number;
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max_tokens?: number;
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}>;
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};
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pi.registerProvider("local-openai", {
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baseUrl: "http://localhost:1234/v1",
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apiKey: "LOCAL_OPENAI_API_KEY",
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api: "openai-completions",
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models: payload.data.map((model) => ({
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id: model.id,
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name: model.name ?? model.id,
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reasoning: false,
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input: ["text"],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: model.context_window ?? 128000,
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maxTokens: model.max_tokens ?? 4096,
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})),
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});
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}
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```
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This registers the fetched models before startup finishes.
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```typescript
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pi.registerProvider("my-llm", {
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baseUrl: "https://api.my-llm.com/v1",
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@@ -151,7 +151,7 @@ Node.js built-ins (`node:fs`, `node:path`, etc.) are also available.
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## Writing an Extension
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An extension exports a default function that receives `ExtensionAPI`:
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An extension exports a default factory function that receives `ExtensionAPI`. The factory can be synchronous or asynchronous:
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```typescript
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import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
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@@ -176,6 +176,45 @@ export default function (pi: ExtensionAPI) {
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Extensions are loaded via [jiti](https://github.com/unjs/jiti), so TypeScript works without compilation.
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If the factory returns a `Promise`, pi awaits it before continuing startup. That means async initialization completes before `session_start`, before `resources_discover`, and before provider registrations queued via `pi.registerProvider()` are flushed.
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### Async factory functions
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Use an async factory for one-time startup work such as fetching remote configuration or dynamically discovering available models.
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```typescript
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import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
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export default async function (pi: ExtensionAPI) {
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const response = await fetch("http://localhost:1234/v1/models");
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const payload = (await response.json()) as {
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data: Array<{
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id: string;
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name?: string;
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context_window?: number;
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max_tokens?: number;
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}>;
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};
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pi.registerProvider("local-openai", {
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baseUrl: "http://localhost:1234/v1",
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apiKey: "LOCAL_OPENAI_API_KEY",
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api: "openai-completions",
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models: payload.data.map((model) => ({
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id: model.id,
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name: model.name ?? model.id,
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reasoning: false,
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input: ["text"],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: model.context_window ?? 128000,
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maxTokens: model.max_tokens ?? 4096,
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})),
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});
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}
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```
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This pattern makes the fetched models available during normal startup and to `pi --list-models`.
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### Extension Styles
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**Single file** - simplest, for small extensions:
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@@ -1371,6 +1410,8 @@ Register or override a model provider dynamically. Useful for proxies, custom en
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Calls made during the extension factory function are queued and applied once the runner initialises. Calls made after that — for example from a command handler following a user setup flow — take effect immediately without requiring a `/reload`.
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If you need to discover models from a remote endpoint, prefer an async extension factory over deferring the fetch to `session_start`. pi waits for the factory before startup continues, so the registered models are available immediately, including to `pi --list-models`.
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```typescript
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// Register a new provider with custom models
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pi.registerProvider("my-proxy", {
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