# twilio-voice-conversation-relay

Build voice-powered AI agents on Twilio with real-time speech handling. Wraps speech recognition (ASR) and text-to-speech (TTS) over WebSocket, so you work with text, not raw audio streams.

- skill · `type=skill` · Codex, ChatGPT · 1 install · ★ 7604
- Author: Twilio · official OpenAI repository
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/openai/plugins/tree/HEAD/plugins/twilio-developer-kit/skills/twilio-voice-conversation-relay/SKILL.md
- Updated: 2026-10-08
- HTML: https://affpapa.org/en/nevibecode/skills/twilio-voice-conversation-relay

## What it does

ConversationRelay connects Twilio's telephony to your app via a persistent WebSocket. Twilio manages ASR and TTS; your code receives call transcripts as text, passes them to an LLM, and returns text responses that Twilio plays back as speech.

The skill covers TwiML setup (Python and Node.js examples), WebSocket message types (`connected`, `prompt`, `interrupt`, `dtmf`, `error`), sending text for playback with the `last` flag, streaming LLM tokens for lower latency, and voice and provider configuration (ASR: Deepgram, Google Cloud STT; TTS: Deepgram, Amazon Polly, Google Cloud TTS, ElevenLabs).

Limitations: no raw audio access (use Media Streams instead), no built-in conversation memory, no WebSocket auto-reconnect (call hangs up on disconnect), incompatible with Media Streams on the same call. Requires a Twilio account with ConversationRelay access (granted via Console onboarding), `TWILIO_ACCOUNT_SID` and `TWILIO_AUTH_TOKEN`, a TLS-secured WebSocket server, and your own LLM integration.

## Install

### Codex (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill twilio-voice-conversation-relay -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/twilio-voice-conversation-relay/SKILL.md` — For all projects use ~/.agents/skills/

### Claude Code

1. **Skills CLI (Vercel)**
```bash
npx skills add openai/plugins --skill twilio-voice-conversation-relay -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/twilio-voice-conversation-relay/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/twilio-voice-conversation-relay/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/twilio-voice-conversation-relay/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install openai/plugins twilio-voice-conversation-relay
```

2. **Manually: put the files in place**
- File: `.github/skills/twilio-voice-conversation-relay/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/openai/plugins --path plugins/twilio-developer-kit/skills/twilio-voice-conversation-relay
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/twilio-voice-conversation-relay/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/openai/plugins/tree/HEAD/plugins/twilio-developer-kit/skills/twilio-voice-conversation-relay/SKILL.md

## When to use it
- Build a voice bot that answers caller questions in real time
- Replace IVR menus with an AI agent using natural speech
- Handle keypad input (DTMF) and speech recognition on the same call
- Stream LLM responses to speech as they are generated, without waiting for completion
- Configure voice, language, and TTS provider per call

## Example prompts
- Set up a voice agent that listens to the caller and responds via OpenAI — use the skill to handle WebSocket connection and Twilio events
- Configure TwiML so incoming calls route to your WebSocket server by adding `conversation_relay()` with your chosen voice
- Stream LLM response tokens so Twilio begins speaking while the model is still generating

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 45712d674b66ec08.

BEGIN THIRD-PARTY FILE 45712d674b66ec08
````text
---
name: twilio-voice-conversation-relay
description: >
  Build AI-powered voice agents using Twilio ConversationRelay. Handles
  real-time speech recognition (ASR), text-to-speech (TTS), and bidirectional
  audio streaming via WebSocket. Covers TwiML setup, WebSocket message types,
  LLM integration, streaming responses, and voice provider configuration. Use
  this skill to build voice bots, IVR replacements, or real-time AI voice
  assistants on Twilio calls.
---

## Overview

ConversationRelay connects Twilio's telephony layer to your app via a persistent WebSocket. Twilio handles ASR (speech-to-text) and TTS (text-to-speech); your app receives transcripts, calls an LLM, and sends text back for playback.

```
Caller ←→ Twilio (ASR/TTS) ←→ WebSocket ←→ Your App ←→ LLM
```

---

## Prerequisites

- Upgraded Twilio account with ConversationRelay access (requires onboarding)
  — New to Twilio? See `twilio-account-setup`
  — Start onboarding at: [Console > Voice > ConversationRelay](https://console.twilio.com/us1/voice/conversation-relay) — access is **not** instant
- A voice-capable Twilio phone number
- `TWILIO_ACCOUNT_SID` and `TWILIO_AUTH_TOKEN` — see `twilio-iam-auth-setup`
- WebSocket server reachable via `wss://` (TLS required)
- An LLM integration (OpenAI, Anthropic, etc.)
- For placing calls: see `twilio-voice-outbound-calls`

**Onboarding:** Complete via Console > Voice > ConversationRelay > Onboarding. Select TTS/ASR providers:
- **TTS:** Deepgram, Amazon Polly, Google Cloud TTS, ElevenLabs
- **ASR:** Deepgram, Google Cloud STT

---

## Quickstart

**Step 1 — Return TwiML pointing to your WebSocket server**

**Python (Flask)**
```python
from flask import Flask
from twilio.twiml.voice_response import VoiceResponse, Connect, ConversationRelay

app = Flask(__name__)

@app.route("/voice", methods=["POST"])
def voice():
    response = VoiceResponse()
    connect = Connect()
    connect.conversation_relay(
        url="wss://yourapp.com/ws/voice",
        welcome_greeting="Hello! How can I help you today?"
    )
    response.append(connect)
    return str(response)
```

**Node.js (Express)**
```node
const { VoiceResponse } = require("twilio").twiml;

app.post("/voice", (req, res) => {
    const response = new VoiceResponse();
    const connect = response.connect();
    connect.conversationRelay({
        url: "wss://yourapp.com/ws/voice",
        welcomeGreeting: "Hello! How can I help you today?",
    });
    res.type("text/xml").send(response.toString());
});
```
````
END THIRD-PARTY FILE 45712d674b66ec08

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First 2540 of 7634 bytes. © Twilio · MIT · https://github.com/openai/plugins/tree/HEAD/plugins/twilio-developer-kit/skills/twilio-voice-conversation-relay/SKILL.md

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