Audio responses

Use this guide for spoken output from a Response. To synthesize supplied text directly, see Text to speech. The OpenAI examples use its custom-request method for MKA1 extensions that are not part of the OpenAI Responses types.

Generate audio (text-to-speech)

Request audio output by setting modalities to ["text", "audio"] and specifying a voice and format in the audio parameter. The response includes both the text transcript and base64-encoded audio data.

Audio configuration

Parameter	Options	Default
`voice`	`alloy` and other voice profiles	`alloy`
`format`	`wav`, `mp3`, `flac`, `opus`, `pcm16`	`wav`

Audio is synthesized at 24 kHz, 16-bit mono.

import { SDK } from '@meetkai/mka1';
import { writeFileSync } from 'fs';
import type { ResponseObject } from '@meetkai/mka1/models/components';

const sdk = new SDK({ bearerAuth: 'Bearer <mka1-api-key>' });

const result = await sdk.llm.responses.create({
  xOnBehalfOf: '<end-user-id>', // optional — attribute the request to one of your end users
  responsesCreateRequest: {
    model: 'auto',
    input: 'Say hello in a friendly way. Keep it very short.',
    modalities: ['text', 'audio'],
    audio: { voice: 'alloy', format: 'wav' },
  },
});

// The output includes an output_audio item with base64 data and a transcript

import OpenAI from 'openai';
import { writeFileSync } from 'fs';

const openai = new OpenAI({
  apiKey: '<mka1-api-key>',
  baseURL: 'https://apigw.mka1.com/api/v1/llm/',
  defaultHeaders: { 'X-On-Behalf-Of': '<end-user-id>' },
});

const response = await openai.post<{ output: Array<{ type: string; data?: string; transcript?: string }> }>('/responses', { body: {
  model: 'auto',
  input: 'Say hello in a friendly way. Keep it very short.',
  modalities: ['text', 'audio'],
  audio: { voice: 'alloy', format: 'wav' },
  stream: false,
} });

// Find the audio output
const audioItem = response.output.find((item) => item.type === 'output_audio');
// audioItem.data contains base64-encoded WAV
// audioItem.transcript contains the spoken text

from meetkai_mka1 import SDK
import base64

sdk = SDK(bearer_auth="Bearer <mka1-api-key>")

result = sdk.llm.responses.create(
    model="auto",
    input="Say hello in a friendly way. Keep it very short.",
    modalities=["text", "audio"],
    audio={"voice": "alloy", "format": "wav"},
)

# The output includes an output_audio item with base64 data and a transcript

using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;
using MeetKai.MKA1.Types.Requests;

var sdk = new SDK(bearerAuth: "Bearer <mka1-api-key>");

var result = await sdk.Llm.Responses.CreateAsync(new ResponsesCreateRequest()
{
    Model = "auto",
    Input = ResponsesCreateRequestInput.CreateStr("Say hello in a friendly way. Keep it very short."),
    Modalities = new List<ResponsesCreateRequestModality>
    {
        ResponsesCreateRequestModality.Text,
        ResponsesCreateRequestModality.Audio,
    },
    Audio = new Audio()
    {
        Voice = "alloy",
        Format = ResponsesCreateRequestFormat.Wav,
    },
});

// The output includes an output_audio item with base64 data and a transcript

mka1 llm responses create \
  -H 'X-On-Behalf-Of: <end-user-id>' \
  --body '{
    "model": "auto",
    "input": "Say hello in a friendly way. Keep it very short.",
    "modalities": ["text", "audio"],
    "audio": { "voice": "alloy", "format": "wav" }
  }'

curl https://apigw.mka1.com/api/v1/llm/responses \
  --request POST \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer <mka1-api-key>' \
  --header 'X-On-Behalf-Of: <end-user-id>' \
  --data '{
    "model": "auto",
    "input": "Say hello in a friendly way. Keep it very short.",
    "modalities": ["text", "audio"],
    "audio": { "voice": "alloy", "format": "wav" }
  }'

The response contains an output_audio item with the base64-encoded audio and a transcript of what was spoken:

{
  "status": "completed",
  "output": [
    {
      "type": "message",
      "role": "assistant",
      "content": [
        { "type": "output_text", "text": "Hello!" }
      ]
    },
    {
      "type": "output_audio",
      "id": "audio_460caf1079b34fa0b4aa74448dff4ea7",
      "data": "<Base64-encoded WAV audio data>",
      "transcript": "Hi there!",
      "status": "completed"
    }
  ]
}

The data field contains the full audio file (268 KB in this example). The transcript field contains the text the model chose to speak — which may differ slightly from the text output.

Save audio to a file

const result = await sdk.llm.responses.create({
  responsesCreateRequest: {
    model: 'auto',
    input: 'Read this sentence aloud: The quick brown fox jumps over the lazy dog.',
    modalities: ['text', 'audio'],
    audio: { voice: 'alloy', format: 'mp3' },
  },
}) as ResponseObject;

// Find the audio output in the response
const audioItem = result.output.find((item) => item.type === 'output_audio');
if (audioItem) {
  const audioBuffer = Buffer.from(audioItem.data, 'base64');
  writeFileSync('output.mp3', audioBuffer);
}

const response = await openai.post<{ output: Array<{ type: string; data?: string; transcript?: string }> }>('/responses', { body: {
  model: 'auto',
  input: 'Read this sentence aloud: The quick brown fox jumps over the lazy dog.',
  modalities: ['text', 'audio'],
  audio: { voice: 'alloy', format: 'mp3' },
  stream: false,
} });

const audioItem = response.output.find((item) => item.type === 'output_audio');
if (audioItem?.data) {
  const audioBuffer = Buffer.from(audioItem.data, 'base64');
  writeFileSync('output.mp3', audioBuffer);
}

result = sdk.llm.responses.create(
    model="auto",
    input="Read this sentence aloud: The quick brown fox jumps over the lazy dog.",
    modalities=["text", "audio"],
    audio={"voice": "alloy", "format": "mp3"},
)

# Find the audio output in the response
for item in result.output:
    if item.type == "output_audio":
        audio_bytes = base64.b64decode(item.data)
        with open("output.mp3", "wb") as f:
            f.write(audio_bytes)

var result = await sdk.Llm.Responses.CreateAsync(new ResponsesCreateRequest()
{
    Model = "auto",
    Input = ResponsesCreateRequestInput.CreateStr(
        "Read this sentence aloud: The quick brown fox jumps over the lazy dog."),
    Modalities = new List<ResponsesCreateRequestModality>
    {
        ResponsesCreateRequestModality.Text,
        ResponsesCreateRequestModality.Audio,
    },
    Audio = new Audio()
    {
        Voice = "alloy",
        Format = ResponsesCreateRequestFormat.Mp3,
    },
});

// Save the audio output to a file
// (iterate result.Output to find the output_audio item and decode its base64 data)

# Generate audio and extract the base64 data, then decode to a file
mka1 llm responses create \
  --body '{
    "model": "auto",
    "input": "Read this sentence aloud: The quick brown fox jumps over the lazy dog.",
    "modalities": ["text", "audio"],
    "audio": { "voice": "alloy", "format": "mp3" }
  }' \
  --output-format json \
  --jq '.output[] | select(.type == "output_audio") | .data' | base64 -d > output.mp3

# Generate audio and extract the base64 data, then decode to a file
curl -s https://apigw.mka1.com/api/v1/llm/responses \
  --request POST \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer <mka1-api-key>' \
  --data '{
    "model": "auto",
    "input": "Read this sentence aloud: The quick brown fox jumps over the lazy dog.",
    "modalities": ["text", "audio"],
    "audio": { "voice": "alloy", "format": "mp3" }
  }' | jq -r '.output[] | select(.type == "output_audio") | .data' | base64 -d > output.mp3

Supported languages

Audio output supports automatic language detection and 20+ languages including English, Chinese, Hindi, Spanish, Arabic, Bengali, Portuguese, Russian, Japanese, Punjabi, German, Korean, French, Turkish, Italian, Thai, Polish, Dutch, Indonesian, Vietnamese, and Urdu. For dedicated speech synthesis, see Text to speech.

Get started

SDKs and CLI

Responses

Standalone APIs

Agents

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Compute

Authentication

Production

Audio responses

Generate audio (text-to-speech)

Audio configuration

Save audio to a file

Supported languages

​Generate audio (text-to-speech)

​Audio configuration

​Save audio to a file

​Supported languages

Generate audio (text-to-speech)

Audio configuration

Save audio to a file

Supported languages