Audio & embeddings

Text-to-speech (TTS), speech recognition (ASR) and text embeddings.

Text-to-speech (TTS)

POST https://api.onefast.ai/v1/audio/speech

Returns the audio as a binary stream.

cURL

curl https://api.onefast.ai/v1/audio/speech \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "speech-2.8-turbo",
    "input": "Hello, and welcome to our service.",
    "voice": "male-qn-qingse",
    "response_format": "mp3"
  }' --output speech.mp3

Python

from openai import OpenAI

client = OpenAI(api_key="sk-xxx", base_url="https://api.onefast.ai/v1")
with client.audio.speech.with_streaming_response.create(
    model="speech-2.8-turbo",
    input="Hello, and welcome to our service.",
    voice="male-qn-qingse",
    response_format="mp3",
) as resp:
    resp.stream_to_file("speech.mp3")

• Billed by character count; each Chinese, Japanese or Korean character counts as 2 characters.
• If you pass an OpenAI voice name (such as alloy), the default English voice is used.
• OpenAI model names work as-is: tts-1 and gpt-4o-mini-tts map to speech-2.8-turbo, and tts-1-hd maps to speech-2.8-hd. Existing OpenAI SDK code only needs a new base_url and key.
• Unsupported formats such as opus / aac are returned as mp3.

Speech recognition (ASR)

POST https://api.onefast.ai/v1/audio/transcriptions

Compatible with the OpenAI transcription API. Upload an audio file (multipart/form-data) and get the recognized text back.

cURL

curl https://api.onefast.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $API_KEY" \
  -F model="asr-1.0" \
  -F file="@meeting.mp3" \
  -F response_format="json"

Python

from openai import OpenAI

client = OpenAI(api_key="sk-xxx", base_url="https://api.onefast.ai/v1")
result = client.audio.transcriptions.create(
    model="asr-1.0",
    file=open("meeting.mp3", "rb"),
)
print(result.text)

What each response_format returns:

Streaming events use the same format as OpenAI:

data: {"type":"transcript.text.delta","delta":"Hello"}

data: {"type":"transcript.text.done","text":"Hello everyone","usage":{"type":"duration","seconds":7,"input_tokens":117}}

• Billed by audio duration (seconds, rounded up), based on the duration in the result.
• Split audio longer than 500 seconds before uploading. Speech recognition does not need high sample rates: 16 kHz mono or a compressed format gives the same accuracy.
• /v1/audio/translations (speech translation) is not supported.

MiniMax-compatible endpoints

Code already written against the official MiniMax documentation works by changing only the domain and key. Request and response formats are unchanged.

Text-to-speech (sync)

POST https://api.onefast.ai/v1/t2a_v2

cURL

curl https://api.onefast.ai/v1/t2a_v2 \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "speech-2.8-hd",
    "text": "Hello, welcome to our service.",
    "stream": false,
    "voice_setting": {"voice_id": "English_expressive_narrator", "speed": 1, "emotion": "happy"},
    "audio_setting": {"format": "mp3", "sample_rate": 32000}
  }'

• Returns JSON. The audio is in data.audio, hex-encoded; usage is in extra_info.usage_characters.
• stream: true is supported (SSE chunks of hex audio; the last frame has data.status = 2 and the full usage).
• Fields such as voice_setting, audio_setting, pronunciation_dict, language_boost and voice_modify work as documented.
• output_format is always hex (no audio download URLs) and subtitle_enable is not available. wav / flac / pcm accept at most 2,000 characters per request.

Speech recognition

POST https://api.onefast.ai/v1/speech_to_text

cURL

curl https://api.onefast.ai/v1/speech_to_text \
  -H "Authorization: Bearer $API_KEY" \
  -H "language: en" \
  -F model="asr-1.0" \
  -F file="@meeting.mp3" \
  -F response_format="verbose_json" \
  -F timestamp_level="word"

• The language hint goes in the language request header (optional; detected automatically if omitted).
• response_format supports json / verbose_json / srt / vtt; timestamp_level supports sentence (default) / word. With stream: true, results come back as SSE events {"index","delta","finish","duration"}.
• File limits and billing are the same as in Speech recognition (ASR) above.

Text embeddings

POST https://api.onefast.ai/v1/embeddings

cURL

curl https://api.onefast.ai/v1/embeddings \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "text-embedding-3-small", "input": "The food was delicious."}'

Python

emb = client.embeddings.create(model="text-embedding-3-small", input=["First passage", "Second passage"])
print(len(emb.data), len(emb.data[0].embedding))

Billed by input tokens.