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Text to Speech

Quick Start​

from pathlib import Path
from litellm import speech
import os 

os.environ["OPENAI_API_KEY"] = "sk-.."

speech_file_path = Path(__file__).parent / "speech.mp3"
response = speech(
        model="openai/tts-1",
        voice="alloy",
        input="the quick brown fox jumped over the lazy dogs",
    )
response.stream_to_file(speech_file_path)

Async Usage​

from litellm import aspeech
from pathlib import Path
import os, asyncio

os.environ["OPENAI_API_KEY"] = "sk-.."

async def test_async_speech(): 
    speech_file_path = Path(__file__).parent / "speech.mp3"
    response = await litellm.aspeech(
            model="openai/tts-1",
            voice="alloy",
            input="the quick brown fox jumped over the lazy dogs",
            api_base=None,
            api_key=None,
            organization=None,
            project=None,
            max_retries=1,
            timeout=600,
            client=None,
            optional_params={},
        )
    response.stream_to_file(speech_file_path)

asyncio.run(test_async_speech())

Proxy Usage​

LiteLLM provides an openai-compatible /audio/speech endpoint for Text-to-speech calls.

curl http://0.0.0.0:4000/v1/audio/speech \
  -H "Authorization: Bearer sk-1234" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "tts-1",
    "input": "The quick brown fox jumped over the lazy dog.",
    "voice": "alloy"
  }' \
  --output speech.mp3

Setup

- model_name: tts
  litellm_params:
    model: openai/tts-1
    api_key: os.environ/OPENAI_API_KEY
litellm --config /path/to/config.yaml

# RUNNING on http://0.0.0.0:4000

Azure Usage​

PROXY

 - model_name: azure/tts-1
    litellm_params:
      model: azure/tts-1
      api_base: "os.environ/AZURE_API_BASE_TTS"
      api_key: "os.environ/AZURE_API_KEY_TTS"
      api_version: "os.environ/AZURE_API_VERSION"

SDK

from litellm import completion

## set ENV variables
os.environ["AZURE_API_KEY"] = ""
os.environ["AZURE_API_BASE"] = ""
os.environ["AZURE_API_VERSION"] = ""

# azure call
speech_file_path = Path(__file__).parent / "speech.mp3"
response = speech(
        model="azure/<your-deployment-name",
        voice="alloy",
        input="the quick brown fox jumped over the lazy dogs",
    )
response.stream_to_file(speech_file_path)

✨ Enterprise LiteLLM Proxy - Set Max Request File Size​

Use this when you want to limit the file size for requests sent to audio/transcriptions

- model_name: whisper
  litellm_params:
    model: whisper-1
    api_key: sk-*******
    max_file_size_mb: 0.00001 # 👈 max file size in MB  (Set this intentionally very small for testing)
  model_info:
    mode: audio_transcription

Make a test Request with a valid file

curl --location 'http://localhost:4000/v1/audio/transcriptions' \
--header 'Authorization: Bearer sk-1234' \
--form 'file=@"/Users/ishaanjaffer/Github/litellm/tests/gettysburg.wav"' \
--form 'model="whisper"'

Expect to see the follow response 

{"error":{"message":"File size is too large. Please check your file size. Passed file size: 0.7392807006835938 MB. Max file size: 0.0001 MB","type":"bad_request","param":"file","code":500}}%