Voice - Adding Voice Capabilities to Mastra Agents
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Published: 2026-05-11 · Source: crawler_authoritative
Tình huống
Mastra Agent SDK documentation for configuring voice capabilities including text-to-speech (TTS), speech-to-text (STT), and speech-to-speech interactions using various voice providers.
Insight
Mastra agents can be enhanced with voice capabilities using the voice property during agent initialization. The @mastra/voice-openai package provides TTS and STT through the OpenAIVoice class. Basic usage involves creating a voice provider instance and passing it to the Agent constructor alongside the model and instructions. The agent.voice.speak() method returns a Node.js stream that can be piped to files or speakers, accepting options like filetype: 'm4a' or ‘mp3’. The agent.voice.listen() method transcribes audio streams, requiring a filetype option for proper parsing. For real-time interactions, OpenAIRealtimeVoice from @mastra/voice-openai-realtime provides speech-to-speech capabilities via WebSocket connections with methods connect(), send(), and close(). The CompositeVoice class allows combining different providers for input (STT) and output (TTS) operations. Event system supports ‘speaking’ (audio data from provider), ‘writing’ (transcribed text from provider or user), and ‘error’ events. AI SDK models can be passed directly to CompositeVoice using models like openai.transcription('whisper-1') for STT and elevenlabs.speech('eleven_turbo_v2') for TTS.
Hành động
To add voice to an agent: 1) Import required packages (@mastra/core/agent, voice provider package). 2) Initialize a voice provider (e.g., new OpenAIVoice()). 3) Pass the voice instance to the Agent constructor via the voice property. 4) Use agent.voice.speak(text, options) to generate speech, which returns a readable stream. 5) Use agent.voice.listen(audioStream, options) to transcribe audio input. For speech-to-speech: 1) Initialize OpenAIRealtimeVoice with API key and model. 2) Create agent with voice provider. 3) Call agent.voice.connect() to establish WebSocket. 4) Use agent.voice.send(microphoneStream) to send audio. 5) Call agent.voice.close() when done. For multiple providers: use CompositeVoice({ input: providerForSTT, output: providerForTTS }). Listen to events with agent.voice.on('eventName', callback) where eventName is ‘speaking’, ‘writing’, or ‘error’.
Kết quả
The agent gains voice interaction capabilities - speak() generates audio streams playable through speakers or saveable to files, listen() returns transcribed text from audio input. Realtime voice providers establish WebSocket connections for real-time speech-to-speech communication with event-based responses.
Điều kiện áp dụng
Requires @mastra/core/agent and a voice provider package (e.g., @mastra/voice-openai, @mastra/voice-openai-realtime). Speech-to-speech requires WebSocket-capable providers and microphone access via @mastra/node-audio.
Nội dung gốc (Original)
Voice
Mastra agents can be enhanced with voice capabilities, allowing them to speak responses and listen to user input. You can configure an agent to use either a single voice provider or combine multiple providers for different operations.
Basic usage
The simplest way to add voice to an agent is to use a single provider for both speaking and listening:
import { createReadStream } from 'fs'
import path from 'path'
import { Agent } from '@mastra/core/agent'
import { OpenAIVoice } from '@mastra/voice-openai'
// Initialize the voice provider with default settings
const voice = new OpenAIVoice()
// Create an agent with voice capabilities
export const agent = new Agent({
id: 'voice-agent',
name: 'Voice Agent',
instructions: `You are a helpful assistant with both STT and TTS capabilities.`,
model: 'openai/gpt-5.4',
voice,
})
// The agent can now use voice for interaction
const audioStream = await agent.voice.speak("Hello, I'm your AI assistant!", {
filetype: 'm4a',
})
playAudio(audioStream!)
try {
const transcription = await agent.voice.listen(audioStream)
console.log(transcription)
} catch (error) {
console.error('Error transcribing audio:', error)
}Working with audio streams
The speak() and listen() methods work with Node.js streams. Here’s how to save and load audio files:
Saving Speech Output
The speak method returns a stream that you can pipe to a file or speaker.
import { createWriteStream } from 'fs'
import path from 'path'
// Generate speech and save to file
const audio = await agent.voice.speak('Hello, World!')
const filePath = path.join(process.cwd(), 'agent.mp3')
const writer = createWriteStream(filePath)
audio.pipe(writer)
await new Promise<void>((resolve, reject) => {
writer.on('finish', () => resolve())
writer.on('error', reject)
})Transcribing Audio Input
The listen method expects a stream of audio data from a microphone or file.
import { createReadStream } from 'fs'
import path from 'path'
// Read audio file and transcribe
const audioFilePath = path.join(process.cwd(), '/agent.m4a')
const audioStream = createReadStream(audioFilePath)
try {
console.log('Transcribing audio file...')
const transcription = await agent.voice.listen(audioStream, {
filetype: 'm4a',
})
console.log('Transcription:', transcription)
} catch (error) {
console.error('Error transcribing audio:', error)
}Speech-to-speech voice interactions
For more dynamic and interactive voice experiences, you can use real-time voice providers that support speech-to-speech capabilities:
import { Agent } from '@mastra/core/agent'
import { getMicrophoneStream } from '@mastra/node-audio'
import { OpenAIRealtimeVoice } from '@mastra/voice-openai-realtime'
import { search, calculate } from '../tools'
// Initialize the realtime voice provider
const voice = new OpenAIRealtimeVoice({
apiKey: process.env.OPENAI_API_KEY,
model: 'gpt-5.1-realtime',
speaker: 'alloy',
})
// Create an agent with speech-to-speech voice capabilities
export const agent = new Agent({
id: 'speech-to-speech-agent',
name: 'Speech-to-Speech Agent',
instructions: `You are a helpful assistant with speech-to-speech capabilities.`,
model: 'openai/gpt-5.4',
tools: {
// Tools configured on Agent are passed to voice provider
search,
calculate,
},
voice,
})
// Establish a WebSocket connection
await agent.voice.connect()
// Start a conversation
agent.voice.speak("Hello, I'm your AI assistant!")
// Stream audio from a microphone
const microphoneStream = getMicrophoneStream()
agent.voice.send(microphoneStream)
// When done with the conversation
agent.voice.close()Event System
The realtime voice provider emits several events you can listen for:
// Listen for speech audio data sent from voice provider
agent.voice.on('speaking', ({ audio }) => {
// audio contains ReadableStream or Int16Array audio data
})
// Listen for transcribed text sent from both voice provider and user
agent.voice.on('writing', ({ text, role }) => {
console.log(`${role} said: ${text}`)
})
// Listen for errors
agent.voice.on('error', error => {
console.error('Voice error:', error)
})Examples
End-to-end voice interaction
This example demonstrates a voice interaction between two agents. The hybrid voice agent, which uses multiple providers, speaks a question, which is saved as an audio file. The unified voice agent listens to that file, processes the question, generates a response, and speaks it back. Both audio outputs are saved to the audio directory.
The following files are created:
- hybrid-question.mp3 – Hybrid agent’s spoken question.
- unified-response.mp3 – Unified agent’s spoken response.
import 'dotenv/config'
import path from 'path'
import { createReadStream } from 'fs'
import { Agent } from '@mastra/core/agent'
import { CompositeVoice } from '@mastra/core/voice'
import { OpenAIVoice } from '@mastra/voice-openai'
import { Mastra } from '@mastra/core'
// Saves an audio stream to a file in the audio directory, creating the directory if it doesn't exist.
export const saveAudioToFile = async (
audio: NodeJS.ReadableStream,
filename: string,
): Promise<void> => {
const audioDir = path.join(process.cwd(), 'audio')
const filePath = path.join(audioDir, filename)
await fs.promises.mkdir(audioDir, { recursive: true })
const writer = createWriteStream(filePath)
audio.pipe(writer)
return new Promise((resolve, reject) => {
writer.on('finish', resolve)
writer.on('error', reject)
})
}
// Saves an audio stream to a file in the audio directory, creating the directory if it doesn't exist.
export const convertToText = async (input: string | NodeJS.ReadableStream): Promise<string> => {
if (typeof input === 'string') {
return input
}
const chunks: Buffer[] = []
return new Promise((resolve, reject) => {
inputData.on('data', chunk => chunks.push(Buffer.from(chunk)))
inputData.on('error', reject)
inputData.on('end', () => resolve(Buffer.concat(chunks).toString('utf-8')))
})
}
export const hybridVoiceAgent = new Agent({
id: 'hybrid-voice-agent',
name: 'Hybrid Voice Agent',
model: 'openai/gpt-5.4',
instructions: 'You can speak and listen using different providers.',
voice: new CompositeVoice({
input: new OpenAIVoice(),
output: new OpenAIVoice(),
}),
})
export const unifiedVoiceAgent = new Agent({
id: 'unified-voice-agent',
name: 'Unified Voice Agent',
instructions: 'You are an agent with both STT and TTS capabilities.',
model: 'openai/gpt-5.4',
voice: new OpenAIVoice(),
})
export const mastra = new Mastra({
agents: { hybridVoiceAgent, unifiedVoiceAgent },
})
const hybridVoiceAgent = mastra.getAgent('hybridVoiceAgent')
const unifiedVoiceAgent = mastra.getAgent('unifiedVoiceAgent')
const question = 'What is the meaning of life in one sentence?'
const hybridSpoken = await hybridVoiceAgent.voice.speak(question)
await saveAudioToFile(hybridSpoken!, 'hybrid-question.mp3')
const audioStream = createReadStream(path.join(process.cwd(), 'audio', 'hybrid-question.mp3'))
const unifiedHeard = await unifiedVoiceAgent.voice.listen(audioStream)
const inputText = await convertToText(unifiedHeard!)
const unifiedResponse = await unifiedVoiceAgent.generate(inputText)
const unifiedSpoken = await unifiedVoiceAgent.voice.speak(unifiedResponse.text)
await saveAudioToFile(unifiedSpoken!, 'unified-response.mp3')Using Multiple Providers
For more flexibility, you can use different providers for speaking and listening using the CompositeVoice class:
import { Agent } from '@mastra/core/agent'
import { CompositeVoice } from '@mastra/core/voice'
import { OpenAIVoice } from '@mastra/voice-openai'
import { PlayAIVoice } from '@mastra/voice-playai'
export const agent = new Agent({
id: 'voice-agent',
name: 'Voice Agent',
instructions: `You are a helpful assistant with both STT and TTS capabilities.`,
model: 'openai/gpt-5.4',
// Create a composite voice using OpenAI for listening and PlayAI for speaking
voice: new CompositeVoice({
input: new OpenAIVoice(),
output: new PlayAIVoice(),
}),
})Using AI SDK
Mastra supports using AI SDK’s transcription and speech models directly in CompositeVoice, giving you access to a wide range of providers through the AI SDK ecosystem:
import { Agent } from '@mastra/core/agent'
import { CompositeVoice } from '@mastra/core/voice'
import { openai } from '@ai-sdk/openai'
import { elevenlabs } from '@ai-sdk/elevenlabs'
import { groq } from '@ai-sdk/groq'
export const agent = new Agent({
id: 'aisdk-voice-agent',
name: 'AI SDK Voice Agent',
instructions: `You are a helpful assistant with voice capabilities.`,
model: 'openai/gpt-5.4',
// Pass AI SDK models directly to CompositeVoice
voice: new CompositeVoice({
input: openai.transcription('whisper-1'), // AI SDK transcription model
output: elevenlabs.speech('eleven_turbo_v2'), // AI SDK speech model
}),
})
// Use voice capabilities as usual
const audioStream = await agent.voice.speak('Hello!')
const transcribedText = await agent.voice.listen(audioStream)Mix and Match Providers
You can mix AI SDK models with Mastra voice providers:
import { CompositeVoice } from '@mastra/core/voice'
import { PlayAIVoice } from '@mastra/voice-playai'
import { openai } from '@ai-sdk/openai'
// Use AI SDK for transcription and Mastra provider for speech
const voice = new CompositeVoice({
input: openai.transcription('whisper-1'), // AI SDK
output: new PlayAIVoice(), // Mastra provider
})For the complete list of supported AI SDK providers and their capabilities:
Supported voice providers
Mastra supports multiple voice providers for text-to-speech (TTS) and speech-to-text (STT) capabilities:
| Provider | Package | Features | Reference |
|---|---|---|---|
| OpenAI | @mastra/voice-openai | TTS, STT | Documentation |
| OpenAI Realtime | @mastra/voice-openai-realtime | Realtime speech-to-speech | Documentation |
| AWS Nova Sonic | @mastra/voice-aws-nova-sonic | Realtime speech-to-speech via AWS Bedrock | Documentation |
| ElevenLabs | @mastra/voice-elevenlabs | High-quality TTS | Documentation |
| PlayAI | @mastra/voice-playai | TTS | Documentation |
@mastra/voice-google | TTS, STT | Documentation | |
| Deepgram | @mastra/voice-deepgram | STT | Documentation |
| Murf | @mastra/voice-murf | TTS | Documentation |
| Speechify | @mastra/voice-speechify | TTS | Documentation |
| Sarvam | @mastra/voice-sarvam | TTS, STT | Documentation |
| Azure | @mastra/voice-azure | TTS, STT | Documentation |
| Cloudflare | @mastra/voice-cloudflare | TTS | Documentation |
Next steps
- Voice API Reference: Detailed API documentation for voice capabilities
- Text to Speech Examples: Interactive story generator and other TTS implementations
- Speech to Text Examples: Voice memo app and other STT implementations
- Speech to Speech Examples: Real-time voice conversation with call analysis
Liên kết
- Nền tảng: Dev Framework · Mastra
- Nguồn: https://mastra.ai/docs/agents/adding-voice