TheRouter.aiTheRouter.ai

Audio API Guide

Use audio inputs and outputs with OpenAI's audio-capable models through TheRouter's unified API.

Supported Models

Audio-capable models at TheRouter:

Audio Formats

Supported input formats:

Note: Maximum audio file size: 25MB for Chat Completions API, 25MB for Whisper transcription.

Examples

Python - Audio Input (Base64)

from openai import OpenAI
import base64

client = OpenAI(
    api_key="your_therouter_api_key",
    base_url="https://api.therouter.ai/v1"
)

# Encode audio file to base64
def encode_audio(audio_path):
    with open(audio_path, "rb") as audio_file:
        return base64.b64encode(audio_file.read()).decode("utf-8")

base64_audio = encode_audio("path/to/audio.mp3")

response = client.chat.completions.create(
    model="openai/gpt-audio-1.5",
    modalities=["text", "audio"],
    audio={"voice": "alloy", "format": "wav"},
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "input_audio",
                    "input_audio": {
                        "data": base64_audio,
                        "format": "mp3"
                    }
                }
            ]
        }
    ]
)

# Access audio output if available
if response.choices[0].message.audio:
    audio_data = response.choices[0].message.audio.data
    # Decode base64 audio
    audio_bytes = base64.b64decode(audio_data)
    with open("response.wav", "wb") as f:
        f.write(audio_bytes)

# Access text transcript
print(response.choices[0].message.content)

TypeScript - Audio Input + Text

import OpenAI from "openai";
import * as fs from "fs";

const client = new OpenAI({
  apiKey: process.env.THEROUTER_API_KEY,
  baseURL: "https://api.therouter.ai/v1",
});

// Encode audio file
function encodeAudio(audioPath: string): string {
  const audioBuffer = fs.readFileSync(audioPath);
  return audioBuffer.toString("base64");
}

const base64Audio = encodeAudio("path/to/audio.mp3");

const response = await client.chat.completions.create({
  model: "openai/gpt-audio-1.5",
  modalities: ["text", "audio"],
  audio: { voice: "alloy", format: "pcm16" },
  messages: [
    {
      role: "user",
      content: [
        {
          type: "text",
          text: "Please respond to my audio message",
        },
        {
          type: "input_audio",
          input_audio: {
            data: base64Audio,
            format: "mp3",
          },
        },
      ],
    },
  ],
});

// Handle audio output
if (response.choices[0].message.audio) {
  const audioData = response.choices[0].message.audio.data;
  const audioBuffer = Buffer.from(audioData, "base64");
  fs.writeFileSync("response.pcm16", audioBuffer);
}

console.log(response.choices[0].message.content);

cURL - Whisper Transcription

curl https://api.therouter.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer ${THEROUTER_API_KEY}" \
  -F file="@audio.mp3" \
  -F model="openai/whisper-1" \
  -F language="en" \
  -F response_format="json"

Python - Text-to-Speech

from openai import OpenAI
from pathlib import Path

client = OpenAI(
    api_key="your_therouter_api_key",
    base_url="https://api.therouter.ai/v1"
)

speech_file_path = Path(__file__).parent / "speech.mp3"

response = client.audio.speech.create(
    model="openai/tts-1-hd",
    voice="nova",
    input="Hello! This is a test of TheRouter's text-to-speech API."
)

response.stream_to_file(speech_file_path)

cURL - Realtime API

# Note: Realtime API uses WebSocket connection
# Example connection (requires WebSocket client)
wscat -c "wss://api.therouter.ai/v1/realtime?model=openai/gpt-realtime-1.5" \
  -H "Authorization: Bearer ${THEROUTER_API_KEY}" \
  -H "OpenAI-Beta: realtime=v1"

# Send session update
{
  "type": "session.update",
  "session": {
    "modalities": ["text", "audio"],
    "voice": "alloy"
  }
}

Audio Output Formats

Supported output formats for audio generation:

Voice Options

Available voices for audio output:

Error Handling

400 Bad Request - Unsupported Model

{
  "error": {
    "message": "Model anthropic/claude-sonnet-4.6 does not support audio content. Use models like openai/gpt-audio-1.5 for audio.",
    "type": "invalid_request_error",
    "code": "multimodal_not_supported"
  }
}

Solution: Use an audio-capable model from the list above.

400 Bad Request - Invalid Audio Format

{
  "error": {
    "message": "Invalid audio format. Supported formats: wav, mp3, flac, m4a, mpeg, mpga, ogg, webm",
    "type": "invalid_request_error",
    "code": "invalid_audio_format"
  }
}

Solution: Convert audio to a supported format.

413 Payload Too Large

Solution: Compress audio or split into smaller chunks. Maximum: 25MB.

Best Practices

Pricing Notes

Audio pricing differs from text:

Related