Text to Speech (TTS)

Turn text into natural-sounding speech and save it as an audio file.

Basic usage

import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["QEVRON_API_KEY"], base_url="https://app.qevron.ai/v1")

resp = client.audio.speech.create(
    model="blab-tts",
    voice="naz",
    input="Hello! This audio was generated through Qevron.",
)
resp.stream_to_file("output.mp3")
print("output.mp3 saved")

With curl

curl https://app.qevron.ai/v1/audio/speech \
  -H "Authorization: Bearer $QEVRON_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "blab-tts",
    "voice": "naz",
    "input": "Hello! This audio was generated through Qevron.",
    "response_format": "mp3"
  }' --output output.mp3

Voice and format options

Parameter	Values	Description
voice	model-dependent	Speaker voice
response_format	mp3, opus, aac, flac	Output audio format
speed	0.25–4.0	Speech speed

Some TTS models in this deployment: blab-tts, blab-fast-tr-naz (Turkish), blab-fast-en-emma (English).

Tips

• Pick a language-appropriate model: a model optimized for the target language sounds more natural.
• Split long text: break very long text by sentence/paragraph and concatenate.
• Streaming: for real-time playback you can get audio chunk by chunk via stream_format (see Audio API).

Related: Audio API — TTS.