Audio

curl https://gateway.toolken.ai/v1/audio/speech \
  -H "X-Toolken-Key: tk_live_..." \
  -H "Authorization: Bearer sk-..." \
  -H "Content-Type: application/json" \
  -d '{"model": "tts-1", "input": "Hello from Toolken.", "voice": "alloy"}' \
  --output speech.mp3

curl https://gateway.toolken.ai/v1/audio/transcriptions \
  -H "X-Toolken-Key: tk_live_..." \
  -H "Authorization: Bearer sk-..." \
  -F model=whisper-1 \
  -F [email protected]

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.toolken.ai/v1",
    api_key="sk-...",
    default_headers={"X-Toolken-Key": "tk_live_..."},
)

# Text-to-speech
response = client.audio.speech.create(
    model="tts-1",
    voice="alloy",
    input="Hello from Toolken.",
)
response.stream_to_file("speech.mp3")

import OpenAI from "openai";
import fs from "fs";

const client = new OpenAI({
  baseURL: "https://gateway.toolken.ai/v1",
  apiKey: "sk-...",
  defaultHeaders: { "X-Toolken-Key": "tk_live_..." },
});

// Text-to-speech
const mp3 = await client.audio.speech.create({
  model: "tts-1",
  voice: "alloy",
  input: "Hello from Toolken.",
});
const buffer = Buffer.from(await mp3.arrayBuffer());
fs.writeFileSync("speech.mp3", buffer);

{
  "text": "Hello from Toolken."
}

POST

audio

curl https://gateway.toolken.ai/v1/audio/speech \
  -H "X-Toolken-Key: tk_live_..." \
  -H "Authorization: Bearer sk-..." \
  -H "Content-Type: application/json" \
  -d '{"model": "tts-1", "input": "Hello from Toolken.", "voice": "alloy"}' \
  --output speech.mp3

curl https://gateway.toolken.ai/v1/audio/transcriptions \
  -H "X-Toolken-Key: tk_live_..." \
  -H "Authorization: Bearer sk-..." \
  -F model=whisper-1 \
  -F [email protected]

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.toolken.ai/v1",
    api_key="sk-...",
    default_headers={"X-Toolken-Key": "tk_live_..."},
)

# Text-to-speech
response = client.audio.speech.create(
    model="tts-1",
    voice="alloy",
    input="Hello from Toolken.",
)
response.stream_to_file("speech.mp3")

import OpenAI from "openai";
import fs from "fs";

const client = new OpenAI({
  baseURL: "https://gateway.toolken.ai/v1",
  apiKey: "sk-...",
  defaultHeaders: { "X-Toolken-Key": "tk_live_..." },
});

// Text-to-speech
const mp3 = await client.audio.speech.create({
  model: "tts-1",
  voice: "alloy",
  input: "Hello from Toolken.",
});
const buffer = Buffer.from(await mp3.arrayBuffer());
fs.writeFileSync("speech.mp3", buffer);

{
  "text": "Hello from Toolken."
}

Pass-through to the provider’s audio endpoint (speech, transcription, translation). Request and response bodies follow the standard OpenAI Audio API schema. The provider is inferred from the model name (e.g. tts-1, whisper-1 route to OpenAI).

Audio requests pass through to your provider and work today. They are not yet counted toward your cost totals. Full cost tracking for audio is coming soon.

Audio supports both JSON (application/json) and multipart/form-data bodies. Use JSON for text-to-speech (TTS) requests and multipart/form-data for transcription and translation (Whisper) requests, following the standard OpenAI Audio API schema.

Headers

X-Toolken-Key

string

required

Your Toolken API key. Validated by the gateway and stripped before forwarding.

Authorization

string

required

Your provider key in Bearer format (BYOK), e.g. Bearer sk-.... Forwarded untouched, never stored.

X-Toolken-Metadata

string

Primary attribution channel. JSON object of key-value pairs (e.g. {"agent":"research-agent","customer_id":"cust_abc"}). Each key becomes a groupable dimension in the dashboard.

X-Toolken-Metadata-*

string

Flat-header shorthand. X-Toolken-Metadata-Agent: research-agent writes metadata key agent. Equivalent to sending the same key in X-Toolken-Metadata.

X-Toolken-Metadata-Feature

string

Sets the feature metadata key. Use to group costs by agent name, workflow, UI surface, or job type.

X-Toolken-Metadata-Customer-Id

string

Sets the customer_id metadata key. Use to attribute costs to an end-customer, org slug, or account ID.

Body

model

string

required

Audio model identifier (e.g. tts-1 for speech, whisper-1 for transcription/translation).

Additional fields follow the standard OpenAI Audio API schema. For speech, include input (text to synthesize) and voice. For transcription and translation, send multipart/form-data with a file field.

Response

Speech requests return audio bytes (audio/mpeg). Transcription and translation requests return a JSON object with a text field. The response is forwarded verbatim from the provider.

curl https://gateway.toolken.ai/v1/audio/speech \
  -H "X-Toolken-Key: tk_live_..." \
  -H "Authorization: Bearer sk-..." \
  -H "Content-Type: application/json" \
  -d '{"model": "tts-1", "input": "Hello from Toolken.", "voice": "alloy"}' \
  --output speech.mp3

curl https://gateway.toolken.ai/v1/audio/transcriptions \
  -H "X-Toolken-Key: tk_live_..." \
  -H "Authorization: Bearer sk-..." \
  -F model=whisper-1 \
  -F [email protected]

from openai import OpenAI

client = OpenAI(
    base_url="https://gateway.toolken.ai/v1",
    api_key="sk-...",
    default_headers={"X-Toolken-Key": "tk_live_..."},
)

# Text-to-speech
response = client.audio.speech.create(
    model="tts-1",
    voice="alloy",
    input="Hello from Toolken.",
)
response.stream_to_file("speech.mp3")

import OpenAI from "openai";
import fs from "fs";

const client = new OpenAI({
  baseURL: "https://gateway.toolken.ai/v1",
  apiKey: "sk-...",
  defaultHeaders: { "X-Toolken-Key": "tk_live_..." },
});

// Text-to-speech
const mp3 = await client.audio.speech.create({
  model: "tts-1",
  voice: "alloy",
  input: "Hello from Toolken.",
});
const buffer = Buffer.from(await mp3.arrayBuffer());
fs.writeFileSync("speech.mp3", buffer);

{
  "text": "Hello from Toolken."
}

Embeddings Images

Gateway API

AI Gateway

Models

Toolken API

Headers

Body

Response

​Headers

​Body

​Response

Headers

Body

Response