Update getting-started.mdx

Author: git-bruh

src/content/docs/realtime/agents/getting-started.mdx

@@ -11,7 +11,7 @@ description: Deploy your first Realtime Agent using the CLI.
 
 import { Render, PackageManagers, WranglerConfig, TypeScriptExample } from "~/components";
 
-This guide will instruct you through setting up and deploying your first Realtime Agents project. You will use [Workers](/workers/), the [Realtime Agents SDK](TODO), a Workers AI binding, and a large language model (LLM) to deploy your first AI-powered application on the Cloudflare global network.
+This guide will instruct you through setting up and deploying your first Realtime Agents project. You will use [Workers](/workers/), the Realtime Agents SDK, a Workers AI binding, and a large language model (LLM) to deploy your first AI-powered application on the Cloudflare global network.
 
 <Render file="prereqs" product="workers" />
 
@@ -76,9 +76,9 @@ Update the `index.ts` file in your `hello-agent` application directory with the
 <TypeScriptExample filename="index.ts">
 
 ```ts
-import { DeepgramSTT, TextProcessor, Meeting, ElevenLabsTTS, ArtificialObject } from '@cloudflare/realtime-agents';
+import { DeepgramSTT, TextComponent, RealtimeKitTransport, ElevenLabsTTS, ArtificialObject } from '@cloudflare/realtime-agents';
 
-class MyTextProcessor extends TextProcessor {
+class MyTextProcessor extends TextComponent {
 	env: Env;
 
 	constructor(env: Env) {
@@ -90,7 +90,7 @@ class MyTextProcessor extends TextProcessor {
 		const { response } = await this.env.AI.run('@cf/meta/llama-3.1-8b-instruct', {
 			prompt: text,
 		});
-		reply(response);
+		reply(response!);
 	}
 }
 
@@ -99,11 +99,11 @@ export class RoomObject extends ArtificialObject<Env> {
 		super(ctx, env);
 	}
 
-	async init(meetingId: string, authToken: string, workerUrl: string) {
+	async init(meetingId: string, authToken: string, workerUrl: string, accountId: string, apiToken: string) {
 		// Construct your text processor for generating responses to text
 		const textProcessor = new MyTextProcessor(this.env);
 		// Construct a Meeting object to join the RTK meeting
-		const meeting = await Meeting.init(meetingId, authToken, [
+		const meeting = new RealtimeKitTransport(meetingId, authToken, [
 			{
 				media_kind: 'audio',
 				stream_kind: 'webcam',
@@ -118,6 +118,8 @@ export class RoomObject extends ArtificialObject<Env> {
 			[meeting, new DeepgramSTT(this.env.DEEPGRAM_API_KEY), textProcessor, new ElevenLabsTTS(this.env.ELEVENLABS_API_KEY), meeting],
 			meetingId,
 			workerUrl,
+			accountId,
+			apiToken,
 		);
 
 		// The RTK meeting object is accessible to us, so we can register handlers
@@ -165,7 +167,7 @@ export default {
 				}
 
 				// We just need the part after `Bearer `
-				await stub.init(meetingId, authHeader.split(' ')[1], url.host);
+				await stub.init(meetingId, authHeader.split(' ')[1], url.host, env.ACCOUNT_ID, env.API_TOKEN);
 
 				return new Response(null, { status: 200 });
 			case '/deinit':
@@ -189,9 +191,33 @@ The Realtime Agents SDK provides several elements that work together to create a
 
 - `ElevenLabsTTS`: Converts the generated responses to audio to be spoken in the meeting
 
-We use all of these elements together to create a simple chatbot-like pipeline. As a pre-requisite, we require the meeting ID to be joined along with an authorization token for joining the meeting, which is passed during the worker invocation
+We use all of these elements together to create a simple chatbot-like pipeline. As a pre-requisite, we require the meeting ID to be joined along with an authorization token for joining the meeting, which is passed during the worker invocation. Additionally, our class must extend `ArtificialObject` as it contains certain internal logic to handle interactions with our pipeline backend
 
-Additionally, our class must extend `ArtificialObject` as it contains certain internal logic to handle interactions with our pipeline backend
+In `wrangler.jsonc`, append the following fields to enable the [Node.js Compatibility](https://developers.cloudflare.com/workers/runtime-apis/nodejs/) flag and create our Durable Object:
+
+```json
+	"compatibility_flags": ["nodejs_compat"],
+	"migrations": [
+		{
+			"new_sqlite_classes": ["RoomObject"],
+			"tag": "v1",
+		},
+	],
+	"durable_objects": {
+		"bindings": [
+			{
+				"class_name": "RoomObject",
+				"name": "ROOM_OBJECT",
+			},
+		],
+	},
+```
+
+You must also setup a few [secrets](https://developers.cloudflare.com/workers/configuration/secrets/):
+
+- `ACCOUNT_ID`: Your Cloudflare account ID
+- `API_TOKEN`: Cloudflare API token scoped for `Admin` access to `Realtime`
+- `ELEVENLABS_API_KEY`, `DEEPGRAM_API_KEY`: ElevenLabs & Deepgram API keys
 
 ## 5. Deploy your AI Worker