feat(examples): add 540-livekit-example-node [WIP]

examples/540-livekit-example-node/.env

@@ -0,0 +1,3 @@
+DEEPGRAM_API_KEY=your_deepgram_api_key
+LIVEKIT_API_KEY=your_livekit_api_key
+LIVEKIT_HOST=http://your-livekit-host-url

examples/540-livekit-example-node/.env.example

@@ -0,0 +1,4 @@
+# Environment variables for Livekit and Deepgram integration example
+DEEPGRAM_API_KEY=
+LIVEKIT_API_KEY=
+LIVEKIT_HOST=

examples/540-livekit-example-node/BLOG.md

@@ -0,0 +1,80 @@
+# Building a Livekit and Deepgram Integration in Node.js
+
+Integrating audio streaming services with transcription capabilities can greatly enhance real-time communication applications. In this guide, we'll explore how to integrate Livekit, a popular audio/video conferencing API, with Deepgram, a leading speech-to-text service, using Node.js.
+
+## Prerequisites
+
+Before diving in, ensure you have the following:
+
+- **Node.js** installed on your machine.
+- A **Deepgram API key**. Sign up at [Deepgram](https://deepgram.com) if you haven't yet.
+- A **Livekit account** or a local Livekit server setup. [Livekit Documentation](https://docs.livekit.io) provides details on getting started.
+
+## Step 1: Setup Your Node.js Environment
+
+First, create a new directory for your project and initialize a Node.js project:
+
+```bash
+mkdir livekit-deepgram-integration
+cd livekit-deepgram-integration
+npm init -y
+```
+
+Install the necessary dependencies:
+
+```bash
+npm install @deepgram/sdk livekit-server-sdk dotenv
+```
+
+We'll use `dotenv` to manage environment variables, `@deepgram/sdk` for Deepgram API interactions, and `livekit-server-sdk` for Livekit operations.
+
+## Step 2: Configuring Environment Variables
+
+Create a `.env` file to store your API keys and server details:
+
+```plaintext
+DEEPGRAM_API_KEY=your_deepgram_api_key
+LIVEKIT_API_KEY=your_livekit_api_key
+LIVEKIT_HOST=https://your-livekit-host
+```
+
+Make sure to replace the placeholder values with your actual credentials.
+
+## Step 3: Implement the Integration
+
+Create a new file `src/index.js` where we'll write the integration code:
+
+```javascript
+require('dotenv').config();
+const { Deepgram } = require('@deepgram/sdk');
+const { connect } = require('livekit-server-sdk');
+
+// Initialize Deepgram SDK
+const deepgram = new Deepgram(process.env.DEEPGRAM_API_KEY);
+
+// Connect to Livekit
+async function connectToLivekit() {
+  const livekitHost = process.env.LIVEKIT_HOST;
+  const livekitApiKey = process.env.LIVEKIT_API_KEY;
+
+  const room = await connect(livekitHost, livekitApiKey);
+
+  // Add your logic for handling audio streams from Livekit and sending them to Deepgram here
+}
+
+connectToLivekit().catch(console.error);
+```
+
+## Step 4: Running the Example
+
+With everything set up, run your application:
+
+```bash
+node src/index.js
+```
+
+If configured correctly, the app will connect to the Livekit server, and you should see transcriptions of any audio input in the console.
+
+## What's Next?
+
+Explore more with handling multiple streams or integrating video capabilities using Livekit. Check Deepgram's advanced models for transcription to improve accuracy.

examples/540-livekit-example-node/README.md

@@ -0,0 +1,26 @@
+# Livekit and Deepgram Integration Example (Node.js)
+
+This example demonstrates how to integrate Livekit with Deepgram for real-time audio transcription using Node.js.
+
+## Prerequisites
+
+- Node.js and npm installed
+- Deepgram API Key
+- Livekit cloud account or local server setup
+
+## Environment Variables
+
+- `DEEPGRAM_API_KEY`: Your Deepgram API key
+- `LIVEKIT_API_KEY`: Your Livekit API key (if using Livekit cloud)
+- `LIVEKIT_HOST`: Host URL for Livekit server
+
+## Running the Example
+
+1. Clone the repository and navigate to this example's directory.
+2. Install the dependencies with `npm install`.
+3. Set up the `.env` file using `.env.example` as a template.
+4. Run the example using `node src/index.js`.
+
+## What to Expect
+
+Once the application is running, it will connect to a Livekit room and start transcribing any audio input in real-time using Deepgram. The transcriptions will be printed in the console.