> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mka1.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Audio responses
> Generate spoken output alongside a Responses API reply.
Use this guide for spoken output from a [Response](/docs/responses). To synthesize supplied text directly, see [Text to speech](/docs/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"]`. The response includes the text reply and a base64-encoded recording of it.
### Audio configuration
Audio output is always a WAV file: 24 kHz, 16-bit mono. The voice follows the language of the reply, which the API detects from the text (see [Supported languages](#supported-languages)). The request's `audio` object (`voice` and `format`) is accepted but has no effect, so the examples omit it.
```ts TypeScript SDK theme={null}
import { SDK } from '@meetkai/mka1';
import { writeFileSync } from 'fs';
import type { ResponseObject } from '@meetkai/mka1/models/components';
const sdk = new SDK({ bearerAuth: 'Bearer ' });
const result = await sdk.llm.responses.create({
xOnBehalfOf: '', // 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'],
},
});
// The output includes an output_audio item with base64 data and a transcript
```
```ts OpenAI SDK theme={null}
import OpenAI from 'openai';
import { writeFileSync } from 'fs';
const openai = new OpenAI({
apiKey: '',
baseURL: 'https://apigw.mka1.com/api/v1/llm/',
defaultHeaders: { 'X-On-Behalf-Of': '' },
});
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'],
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
```
```python Python SDK theme={null}
from meetkai_mka1 import SDK
import base64
sdk = SDK(bearer_auth="Bearer ")
result = sdk.llm.responses.create(
model="auto",
input="Say hello in a friendly way. Keep it very short.",
modalities=["text", "audio"],
)
# The output includes an output_audio item with base64 data and a transcript
```
```csharp C# SDK theme={null}
using MeetKai.MKA1;
using MeetKai.MKA1.Types.Components;
using MeetKai.MKA1.Types.Requests;
var sdk = new SDK(bearerAuth: "Bearer ");
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.Text,
ResponsesCreateRequestModality.Audio,
},
});
// The output includes an output_audio item with base64 data and a transcript
```
```bash CLI theme={null}
mka1 llm responses create \
-H 'X-On-Behalf-Of: ' \
--body '{
"model": "auto",
"input": "Say hello in a friendly way. Keep it very short.",
"modalities": ["text", "audio"]
}'
```
```bash Bash theme={null}
curl https://apigw.mka1.com/api/v1/llm/responses \
--request POST \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer ' \
--header 'X-On-Behalf-Of: ' \
--data '{
"model": "auto",
"input": "Say hello in a friendly way. Keep it very short.",
"modalities": ["text", "audio"]
}'
```
The response contains an `output_audio` item with the base64-encoded audio and a transcript of what was spoken:
```json theme={null}
{
"status": "completed",
"output": [
{
"type": "message",
"role": "assistant",
"content": [
{ "type": "output_text", "text": "Hello!" }
]
},
{
"type": "output_audio",
"id": "audio_460caf1079b34fa0b4aa74448dff4ea7",
"data": "",
"transcript": "Hello!",
"status": "completed"
}
]
}
```
The `data` field contains the complete WAV file. The `transcript` field contains the text that was spoken, which is the reply's output text. If speech synthesis fails, the response still completes, without an `output_audio` item.
### Save audio to a file
```ts TypeScript SDK theme={null}
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'],
},
}) 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.wav', audioBuffer);
}
```
```ts OpenAI SDK theme={null}
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'],
stream: false,
} });
const audioItem = response.output.find((item) => item.type === 'output_audio');
if (audioItem?.data) {
const audioBuffer = Buffer.from(audioItem.data, 'base64');
writeFileSync('output.wav', audioBuffer);
}
```
```python Python SDK theme={null}
result = sdk.llm.responses.create(
model="auto",
input="Read this sentence aloud: The quick brown fox jumps over the lazy dog.",
modalities=["text", "audio"],
)
# 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.wav", "wb") as f:
f.write(audio_bytes)
```
```csharp C# SDK theme={null}
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.Text,
ResponsesCreateRequestModality.Audio,
},
});
// Save the audio output to a file
// (iterate result.Output to find the output_audio item and decode its base64 data)
```
```bash CLI theme={null}
# 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"]
}' \
--output-format json \
--jq '.output[] | select(.type == "output_audio") | .data' | base64 -d > output.wav
```
```bash Bash theme={null}
# 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 ' \
--data '{
"model": "auto",
"input": "Read this sentence aloud: The quick brown fox jumps over the lazy dog.",
"modalities": ["text", "audio"]
}' | jq -r '.output[] | select(.type == "output_audio") | .data' | base64 -d > output.wav
```
### Supported languages
Audio responses speak the languages listed in [Text to speech](/docs/text-to-speech#supported-languages). A reply in any other language is spoken with the English voice.
To choose the language yourself, or to get MP3 instead of WAV, send the reply text to [Text to speech](/docs/text-to-speech).
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