docs: fix grok video snippets failing kiira; publish @tanstack/ai-angular (#826)

docs: fix grok video snippets so kiira passes; publish ai-angular

The grok video-generation snippets in docs/adapters/grok.md and
docs/media/video-generation.md referenced generateVideo/grokVideo
without importing them, failing the test:kiira gate on main and
aborting every release run before changeset publish.

Make each standalone fence self-contained with its own imports, and
add a changeset to cut a clean @tanstack/ai-angular release (npm 0.0.1
shipped unresolved workspace: specifiers from a manual publish).

Author: AlemTuzlak

.changeset/publish-ai-angular.md

@@ -0,0 +1,5 @@
+---
+'@tanstack/ai-angular': patch
+---
+
+Publish a working `@tanstack/ai-angular` build. The only version previously on npm (`0.0.1`) was seeded with a manual `npm publish` and shipped unresolved `workspace:` specifiers in its `dependencies`/`peerDependencies`, making it uninstallable (`EUNSUPPORTEDPROTOCOL`). Releasing through the changesets pipeline rewrites those specifiers to concrete versions.

docs/adapters/grok.md

@@ -270,6 +270,9 @@ console.log(status.url); // hosted .mp4 URL
 For image-to-video (required for `grok-imagine-video-1.5`, optional for `grok-imagine-video`), include an `image` prompt part as the starting frame and describe the desired motion in the text part. URL sources are fetched by xAI's servers (so they must be publicly reachable); use a `data` source for a base64 starting frame:
 
 ```typescript
+import { generateVideo } from "@tanstack/ai";
+import { grokVideo } from "@tanstack/ai-grok";
+
 const { jobId } = await generateVideo({
   adapter: grokVideo("grok-imagine-video-1.5"),
   prompt: [

docs/media/video-generation.md

@@ -598,6 +598,9 @@ const { jobId } = await generateVideo({
 Image-to-video (required for `grok-imagine-video-1.5`) — include an `image` prompt part as the starting frame. URL sources are fetched by xAI's servers (so they must be publicly reachable); use a `data` source for a base64 starting frame:
 
 ```typescript
+import { generateVideo } from '@tanstack/ai'
+import { grokVideo } from '@tanstack/ai-grok'
+
 const { jobId } = await generateVideo({
   adapter: grokVideo('grok-imagine-video-1.5'),
   prompt: [
@@ -615,6 +618,8 @@ const { jobId } = await generateVideo({
 Both models accept any whole second in the **1–15** range. A raw `duration` is coerced into that range rather than rejected — values are clamped to `[1, 15]` and rounded to the nearest second. Inspect or pre-snap the range the same way as Veo:
 
 ```typescript
+import { grokVideo } from '@tanstack/ai-grok'
+
 const adapter = grokVideo('grok-imagine-video')
 
 adapter.availableDurations() // { kind: 'range', min: 1, max: 15, step: 1, unit: 'seconds' }