---
title: "How It Integrates"
source: Panaversity Learn Agentic AI
source_url: https://github.com/panaversity/learn-agentic-ai
licence: Apache-2.0
domain: agentic-ai
subdomain: panaversity-agentic
date_added: 2026-04-25
---

The integration between LiveKit and OpenAI's Realtime API is a powerful combination for building real-time, multimodal AI applications, particularly voice-driven experiences like those seen in ChatGPT’s Advanced Voice feature. LiveKit, an open-source WebRTC platform, and OpenAI, with its Realtime API, have collaborated to streamline this process, enabling developers to create low-latency, speech-to-speech interactions with GPT-4o. Here’s how it works and what you need to know:

### How It Integrates
1. **Architecture Overview**:
   - **Client-Side**: A LiveKit client SDK (e.g., for JavaScript, iOS, or Android) captures user audio or video from a device and streams it via WebRTC to LiveKit’s edge network.
   - **LiveKit Cloud**: Acts as a bridge, routing the media to a backend agent (your server-side code) with sub-100ms latency.
   - **Backend Agent**: Uses the LiveKit Agents Framework (in Python or Node.js) to relay the audio to OpenAI’s Realtime API over a WebSocket connection.
   - **OpenAI Realtime API**: Processes the audio input with GPT-4o, generating a response (text or audio), which is streamed back via WebSocket to the agent.
   - **Return Path**: The agent sends the response through LiveKit Cloud back to the user’s device via WebRTC.

2. **Key Component - MultimodalAgent**:
   - LiveKit provides a `MultimodalAgent` class that wraps OpenAI’s Realtime API, abstracting the raw WebSocket protocol. This class handles both text and audio modalities dynamically, allowing inputs and outputs in either form.
   - It supports all Realtime API parameters (e.g., voice selection like "alloy," temperature, turn detection) and adds features like buffered playback, function calling, and load balancing.

3. **WebRTC vs. WebSocket**:
   - LiveKit uses WebRTC for client-to-agent communication, leveraging its resilience to packet loss and low-latency capabilities over the public internet.
   - WebSocket is used between the agent and OpenAI’s API, suitable for server-to-server communication where network conditions are more stable.

### Steps to Integrate
1. **Set Up LiveKit**:
   - Create a LiveKit Cloud account or self-host the server (open-source under Apache 2.0).
   - Install the LiveKit CLI (`lk`) and authenticate: `lk cloud auth`.
   - Generate access tokens for your app via the LiveKit dashboard.

2. **Bootstrap an Agent**:
   - Use the LiveKit Agents Framework (Python or Node.js). Install it with `pip install livekit-agents` or `npm install @livekit/agents`.
   - Create an agent using a template:
     ```bash
     lk agent create my-agent
     ```
   - Configure it to use the `MultimodalAgent` class with your OpenAI API key:
     ```python
     from livekit.agents import MultimodalAgent
     agent = MultimodalAgent(openai_api_key="your-api-key")
     ```

3. **Frontend Integration**:
   - Use LiveKit’s client SDKs to connect users to a room:
     ```javascript
     import { Room, connect } from '@livekit/client';
     const room = new Room();
     await connect(room, 'your-token', 'wss://your-livekit-server');
     ```
   - Add the `useVoiceAssistant` hook for real-time audio and state management:
     ```javascript
     import { useVoiceAssistant } from '@livekit/agents-react';
     const { state, audioTrack } = useVoiceAssistant();
     ```

4. **Connect to OpenAI Realtime API**:
   - The `MultimodalAgent` handles the WebSocket connection to OpenAI automatically. Ensure your OpenAI API key is set (via environment variable or directly in code).
   - Test the connection using LiveKit’s Realtime Playground: `realtime-playground.livekit.io`.

5. **Run and Test**:
   - Launch your agent: `lk agent run my-agent`.
   - Connect via the frontend and start a conversation. The Playground or a custom UI (e.g., with `BarVisualizer`) provides visual feedback.

### Benefits of Integration
- **Low Latency**: Combines WebRTC’s real-time media transport with OpenAI’s ~300ms response time.
- **Scalability**: LiveKit’s load balancing and failover ensure reliability as user demand grows.
- **Flexibility**: Open-source nature allows customization, and `MultimodalAgent` supports switching between modalities or even other LLMs in the future.
- **Ease of Use**: Prebuilt abstractions, SDKs, and playgrounds reduce development time.

### Practical Example
Imagine a voice assistant app:
- User says, "What’s the weather like?"
- LiveKit streams the audio to your agent.
- The agent relays it to OpenAI’s Realtime API, which responds with audio: "It’s sunny and 72°F."
- LiveKit delivers the response back to the user, all in under a second.

### Resources
- **LiveKit Docs**: Guides on OpenAI integration and quickstarts (docs.livekit.io).
- **GitHub**: `livekit/agents` for the framework, `livekit-examples/realtime-playground` for a demo.
- **Blog**: LiveKit’s announcement on the partnership (blog.livekit.io, October 3, 2024).

## Twilio

The integration between Twilio and OpenAI's Realtime API is a well-established approach for building conversational AI applications, particularly voice-based ones like phone agents or virtual assistants. Twilio, a leading cloud communications platform, pairs effectively with OpenAI’s Realtime API to enable low-latency, speech-to-speech interactions using GPT-4o. Here’s a breakdown of how this integration works, its benefits, and practical steps to set it up:

### How It Integrates
1. **Architecture Overview**:
   - **Twilio Voice**: Handles inbound/outbound calls via the Public Switched Telephone Network (PSTN) and converts them into WebSocket-based media streams using Twilio Media Streams.
   - **Backend Server**: A custom server (e.g., in Node.js or Python) proxies audio between Twilio’s WebSocket and OpenAI’s Realtime API WebSocket.
   - **OpenAI Realtime API**: Processes the audio input directly with GPT-4o, bypassing traditional speech-to-text and text-to-speech steps, and streams back an audio response.
   - **Return Path**: The server sends the AI’s audio response back to Twilio, which delivers it to the caller.

2. **Key Mechanism**:
   - Twilio uses TwiML (Twilio Markup Language) to initiate a bidirectional WebSocket stream when a call is made or received.
   - The server forwards raw audio (typically in G.711 μ-law format, supported by Twilio) to OpenAI’s API, which returns audio in the same format for seamless playback.

3. **Collaboration**:
   - Announced on October 1, 2024, Twilio and OpenAI collaborated to integrate the Realtime API into Twilio’s ecosystem, simplifying the process for Twilio’s 300,000+ customers and 10 million developers.

### Steps to Integrate
1. **Prerequisites**:
   - A Twilio account with a phone number (sign up at twilio.com).
   - An OpenAI account with Realtime API access and an API key (available via openai.com).
   - A tunneling tool like ngrok (ngrok.com) for local development to expose your server to Twilio.

2. **Set Up Twilio**:
   - Purchase a Twilio phone number in the Twilio Console.
   - Configure it to point to a TwiML endpoint or a WebSocket URL (e.g., `wss://your-server.com/media-stream`).

3. **Build the Server**:
   - Use Node.js or Python with frameworks like Fastify or FastAPI.
   - Example in Node.js (simplified):
     ```javascript
     import Fastify from 'fastify';
     import WebSocket from 'ws';
     const fastify = Fastify();
     fastify.register(import('@fastify/websocket'));
     fastify.get('/media-stream', { websocket: true }, (connection, req) => {
       const openaiWS = new WebSocket('wss://api.openai.com/v1/realtime', {
         headers: { Authorization: `Bearer ${process.env.OPENAI_API_KEY}` }
       });
       connection.on('message', (data) => openaiWS.send(data));
       openaiWS.on('message', (data) => connection.send(data));
     });
     fastify.listen({ port: 8080 });
     ```
   - This proxies audio between Twilio and OpenAI.

4. **Configure TwiML**:
   - Create a TwiML bin in Twilio or host it on your server:
     ```xml
     <?xml version="1.0" encoding="UTF-8"?>
     <Response>
       <Connect>
         <Stream url="wss://your-server.com/media-stream"/>
       </Connect>
     </Response>
     ```
   - Link this to your Twilio phone number under “A call comes in.”

5. **Run and Test**:
   - Start your server and ngrok (`ngrok http 8080`).
   - Call your Twilio number or trigger an outbound call via Twilio’s API. The audio will flow through the server to OpenAI and back.

### Benefits
- **Low Latency**: Direct speech-to-speech reduces delays (OpenAI’s API achieves ~300ms response time), enhanced by Twilio’s real-time streaming.
- **Scalability**: Twilio’s infrastructure supports high call volumes, and OpenAI’s API scales with usage.
- **Ease of Use**: Twilio’s prebuilt integrations (e.g., CodeExchange apps like live translation demos) and OpenAI’s WebSocket simplicity lower the barrier to entry.
- **Flexibility**: Supports use cases like customer support agents, real-time translation, or outbound calling (e.g., tutorials from Twilio’s blog, November 13, 2024).

### Challenges
- **Cost**: Twilio charges per minute (e.g., $0.0085/min for calls), and OpenAI’s Realtime API costs $0.06/min input and $0.24/min output, which can add up for long sessions.
- **Setup Complexity**: Requires managing WebSockets and audio formats, though Twilio’s docs and OpenAI’s Realtime Console help.
- **Beta Limitations**: As of March 20, 2025, the Realtime API is still in beta, with occasional quirks like voice cutoffs or limited voice options (e.g., alloy, echo, shimmer).

### Practical Examples
- **Inbound AI Agent**: A caller dials a Twilio number, and the AI answers questions (e.g., Twilio’s Node.js tutorial, September 30, 2024).
- **Outbound Calls**: The AI initiates a call to a user (e.g., Twilio’s Python outbound guide, November 13, 2024).
- **Live Translation**: A Flex contact center uses the API to translate between a caller and agent in real time (Twilio CodeExchange demo).

### Resources
- **Twilio Docs**: Tutorials for Node.js, Python, and Flex integrations (twilio.com/docs).
- **OpenAI Docs**: Realtime API reference (platform.openai.com/docs).
- **GitHub Repos**: `twilio-samples/live-translation-openai-realtime-api` or `openai/openai-realtime-twilio-demo`.

## Hybrid

Integrating Twilio, OpenAI's Realtime API, and LiveKit together creates a hybrid system that combines Twilio’s telephony capabilities, OpenAI’s real-time AI processing, and LiveKit’s WebRTC-based audio/video streaming. This setup is ideal for applications requiring both traditional phone interactions and modern web-based real-time communication, enhanced by AI-driven voice responses. Here’s how they can work together, including architecture, benefits, and practical implementation steps as of March 20, 2025.

### Conceptual Architecture
1. **Twilio (Telephony Layer)**:
   - Handles inbound/outbound PSTN calls (traditional phone network).
   - Converts phone audio into a WebSocket stream using Twilio Media Streams.

2. **LiveKit (WebRTC Layer)**:
   - Manages WebRTC-based audio/video streams from web or mobile clients.
   - Acts as a bridge to unify Twilio’s telephony streams and web-based participants in a single “room.”

3. **OpenAI Realtime API (AI Layer)**:
   - Processes audio inputs from both Twilio and LiveKit, delivering GPT-4o-powered speech-to-speech responses.
   - Streams AI-generated audio back to the system via WebSocket.

4. **Backend Server (Integration Hub)**:
   - Orchestrates the flow of audio between Twilio, LiveKit, and OpenAI.
   - Handles WebSocket connections, audio format conversions, and room management.

### How It Works Together
- **Scenario**: A customer calls a Twilio phone number, a web user joins via a LiveKit room, and both interact with an AI assistant powered by OpenAI.
  1. **Twilio Call**: The customer dials in, Twilio streams audio to the backend via WebSocket.
  2. **LiveKit Room**: The web user connects to a LiveKit room using a client SDK (e.g., JavaScript), streaming audio via WebRTC.
  3. **Backend Processing**: The server joins the Twilio stream and LiveKit room as participants, forwarding all audio to OpenAI’s Realtime API.
  4. **AI Response**: OpenAI processes the combined inputs and streams back an audio response (e.g., in G.711 μ-law for compatibility).
  5. **Delivery**: The backend relays the AI’s audio to Twilio (for the phone caller) and LiveKit (for the web user), ensuring a seamless conversation.

### Benefits
- **Unified Communication**: Bridges telephony (Twilio) and web-based real-time comms (LiveKit) with AI enhancement (OpenAI).
- **Scalability**: Twilio and LiveKit handle large-scale telephony and WebRTC traffic, while OpenAI scales AI processing.
- **Low Latency**: WebRTC (LiveKit) and WebSocket (Twilio/OpenAI) ensure sub-second delays, critical for natural conversations.
- **Flexibility**: Supports diverse use cases—e.g., customer support with phone and web agents, hybrid meetings, or multilingual call centers with real-time translation.

### Implementation Steps
1. **Set Up Twilio**:
   - Purchase a Twilio phone number and configure it with a TwiML endpoint:
     ```xml
     <Response>
       <Connect>
         <Stream url="wss://your-server.com/twilio-stream"/>
       </Connect>
     </Response>
     ```

2. **Set Up LiveKit**:
   - Create a LiveKit Cloud account or self-host (docs.livekit.io).
   - Generate an access token for a room (e.g., `lk token create --room my-room`).

3. **Backend Server Setup**:
   - Use Python with `livekit-agents` and `twilio` libraries, or Node.js with `@livekit/agents` and `ws`.
   - Example in Python:
     ```python
     import asyncio
     from livekit import rtc, agents
     from websockets import connect as ws_connect
     from twilio.twiml.voice_response import VoiceResponse, Connect

     # Twilio WebSocket handler
     async def handle_twilio_stream(twilio_ws):
         async with ws_connect("wss://api.openai.com/v1/realtime", extra_headers={"Authorization": f"Bearer {OPENAI_API_KEY}"}) as openai_ws:
             async for msg in twilio_ws:
                 await openai_ws.send(msg)
                 response = await openai_ws.recv()
                 await twilio_ws.send(response)

     # LiveKit Agent
     async def run_agent():
         room = rtc.Room()
         await room.connect("wss://your-livekit-server", "your-token")
         agent = agents.MultimodalAgent(openai_api_key=OPENAI_API_KEY)
         await agent.start(room)

     # FastAPI server for Twilio TwiML
     from fastapi import FastAPI
     app = FastAPI()
     @app.get("/twilio")
     async def twilio_endpoint():
         response = VoiceResponse()
         response.connect().stream(url="wss://your-server.com/twilio-stream")
         return str(response)

     if __name__ == "__main__":
         asyncio.run(run_agent())
     ```
   - Run with a tunneling tool like ngrok: `ngrok http 8000`.

4. **Frontend for LiveKit**:
   - Use LiveKit’s client SDK to join the room:
     ```javascript
     import { Room, connect } from '@livekit/client';
     const room = new Room();
     await connect(room, 'your-token', 'wss://your-livekit-server');
     ```

5. **Audio Flow**:
   - Twilio audio → Backend → OpenAI → Backend → Twilio.
   - LiveKit audio → Room → Agent → OpenAI → Room → LiveKit clients.

6. **Test the System**:
   - Dial the Twilio number and join the LiveKit room from a browser. Speak, and the AI should respond to both participants.

### Challenges
- **Audio Format Sync**: Twilio uses G.711 μ-law, while LiveKit defaults to Opus. The backend must convert or ensure OpenAI’s output matches Twilio’s requirements.
- **Cost**: Twilio ($0.0085/min), OpenAI ($0.06/min input, $0.24/min output), and LiveKit hosting (e.g., $60/month AWS) can accumulate.
- **Complexity**: Managing two streaming protocols (WebRTC and WebSocket) requires careful synchronization.

### Practical Use Case
- **Hybrid Customer Support**: A customer calls via Twilio, a web-based agent joins via LiveKit, and OpenAI’s AI assists both in real time (e.g., answering FAQs or translating).
- **Demo**: Twilio’s blog (October 2024) and LiveKit’s OpenAI integration docs (October 3, 2024) suggest this hybrid model for contact centers.

### Resources
- **Twilio Docs**: Media Streams (twilio.com/docs/voice/twiml/stream).
- **LiveKit Docs**: Agents Framework (docs.livekit.io/agents).
- **OpenAI Docs**: Realtime API (platform.openai.com/docs/guides/realtime).

This trio, leveraging Twilio’s telephony, LiveKit’s WebRTC, and OpenAI’s AI, offers a robust, multi-channel conversational platform as of March 20, 2025. 

## Pakistan Phone Numbers

Yes, Twilio does provide phone numbers in Pakistan, but their availability and capabilities are limited compared to some other regions due to local regulations and telecom infrastructure. As of March 20, 2025, Twilio offers virtual phone numbers in Pakistan, primarily mobile numbers, that can be used for specific purposes like SMS and voice communications. Here’s a detailed breakdown based on available information:

### Availability of Twilio Phone Numbers in Pakistan
- **Mobile Numbers**: Twilio provides mobile phone numbers in Pakistan that are SMS-enabled and voice-capable. These numbers are generally available through the Twilio Console or Phone Numbers API, allowing you to search and purchase them programmatically or manually.
- **Local Numbers**: While Twilio supports local numbers in over 100 countries, Pakistan is not explicitly listed as having widely available local (geographic) numbers in their documentation. The focus in Pakistan appears to be on mobile numbers rather than landline or local prefixes tied to specific cities.
- **Toll-Free Numbers**: Toll-free numbers are not currently offered in Pakistan by Twilio, as their toll-free coverage is limited to countries like the U.S., Canada, the U.K., and a few others.

### Capabilities
- **SMS**: Pakistani mobile numbers from Twilio can send and receive SMS messages. However, there are some nuances:
  - Two-way messaging (sending and receiving replies) is supported when using a Pakistani number to contact Pakistani recipients.
  - For international SMS, Twilio numbers can send messages to Pakistan, but Sender IDs (e.g., alphanumeric IDs) may be replaced by a numeric ID to ensure delivery due to local carrier restrictions.
- **Voice**: These mobile numbers support making and receiving voice calls. International dialing permissions can be enabled via Twilio’s global settings, though call quality and costs depend on carrier routing.
- **MMS**: Multimedia Messaging Service (MMS) is not supported in Pakistan with Twilio numbers, as MMS is limited to specific regions like the U.S.

### How to Get a Phone Number in Pakistan
1. **Twilio Console**:
   - Sign up for a Twilio account (free trial includes $15 credit, no credit card required initially).
   - Navigate to the "Phone Numbers" section, select "Buy a Number," and filter by country (Pakistan, ISO code: PK).
   - Choose a mobile number based on available capabilities (e.g., SMS, Voice).
2. **API Access**:
   - Use the Twilio Phone Numbers API to programmatically search for available numbers:
     ```bash
     curl -X GET "https://api.twilio.com/2010-04-01/Accounts/{AccountSid}/AvailablePhoneNumbers/PK/Mobile.json" \
     -u {AccountSid}:{AuthToken}
     ```
   - Purchase the number using the Incoming Phone Numbers API once identified.
3. **Verification**: Regulatory requirements may necessitate verification (e.g., for SMS campaigns), but for basic use, numbers are available instantly after purchase.

### Pricing
- **Number Cost**: Mobile numbers in Pakistan typically start at $1.00/month (standard Twilio pricing for many regions), though exact costs can vary and are visible in the Console during selection.
- **Usage Costs**:
  - SMS: Around $0.045 to send, $0.0075 to receive (indicative, varies by volume).
  - Voice: Approximately $0.014/min to make calls, $0.0085/min to receive (pay-as-you-go rates).
  - Volume discounts apply automatically at scale; enterprise pricing is available for high usage.

### Limitations and Considerations
- **Regulatory Compliance**: Pakistan’s telecom authority (PTA) imposes strict rules. Twilio advises reviewing use cases with legal counsel to ensure compliance, especially for marketing SMS, which may require opt-in consent.
- **Beta Status**: Some Pakistani numbers might be in "Beta" (not fully guaranteed), meaning capabilities could be subject to change or testing.
- **Sender ID**: Alphanumeric Sender IDs are not reliably supported in Pakistan; they’re often replaced with numeric IDs by local carriers for delivery.
- **Availability**: While Twilio has numbers in Pakistan, inventory might not be as deep as in major markets like the U.S. or Europe, so specific prefixes may be limited.

### Conclusion
Twilio does offer phone numbers in Pakistan, primarily mobile ones with SMS and voice capabilities, accessible via their Console or API. They’re suitable for applications like customer support, notifications, or two-way communication within Pakistan. However, toll-free or local geographic numbers aren’t widely available, and SMS features come with carrier-specific caveats. To confirm current availability, you can check the Twilio Console directly or contact their support, as inventory and regulations evolve.
