Text To Audio - Localai

+++ disableToc = false title = "Text to Audio (TTS)" weight = 11 url = "/features/text-to-audio/" +++

API Compatibility

The LocalAI TTS API is compatible with the OpenAI TTS API and the Elevenlabs API.

LocalAI API

The /tts endpoint can also be used to generate speech from text.

Usage

Input: input, model

For example, to generate an audio file, you can send a POST request to the /tts endpoint with the instruction as the request body:

bash

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
  "input": "Hello world",
  "model": "tts"
}'

Returns an audio/wav file.

Streaming TTS

LocalAI supports streaming TTS generation, allowing audio to be played as it's generated. This is useful for real-time applications and reduces latency.

To enable streaming, add "stream": true to your request:

bash

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
  "input": "Hello world, this is a streaming test",
  "model": "voxcpm",
  "stream": true
}' | aplay

The audio will be streamed chunk-by-chunk as it's generated, allowing playback to start before generation completes. This is particularly useful for long texts or when you want to minimize perceived latency.

You can also pipe the streamed audio directly to audio players like aplay (Linux) or save it to a file:

bash

# Stream to aplay (Linux)
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
  "input": "This is a longer text that will be streamed as it is generated",
  "model": "voxcpm",
  "stream": true
}' | aplay

# Stream to a file
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
  "input": "Streaming audio to file",
  "model": "voxcpm",
  "stream": true
}' > output.wav

Note: Streaming TTS is currently supported by the voxcpm backend. Other backends will fall back to non-streaming mode if streaming is not supported.

Backends

🐸 Coqui

Required: Don't use LocalAI images ending with the -core tag,. Python dependencies are required in order to use this backend.

Coqui works without any configuration, to test it, you can run the following curl command:

    curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
        "backend": "coqui",
        "model": "tts_models/en/ljspeech/glow-tts",
        "input":"Hello, this is a test!"
        }'

You can use the env variable COQUI_LANGUAGE to set the language used by the coqui backend.

You can also use config files to configure tts models (see section below on how to use config files).

Piper

To install the piper audio models manually:

Download Voices from https://github.com/rhasspy/piper/releases/tag/v0.0.2
Extract the .tar.tgz files (.onnx,.json) inside models
Run the following command to test the model is working

To use the tts endpoint, run the following command. You can specify a backend with the backend parameter. For example, to use the piper backend:

bash

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
  "model":"it-riccardo_fasol-x-low.onnx",
  "backend": "piper",
  "input": "Ciao, sono Ettore"
}' | aplay

Note:

aplay is a Linux command. You can use other tools to play the audio file.
The model name is the filename with the extension.
The model name is case sensitive.
LocalAI must be compiled with the GO_TAGS=tts flag.

Transformers-musicgen

LocalAI also has experimental support for transformers-musicgen for the generation of short musical compositions. Currently, this is implemented via the same requests used for text to speech:

curl --request POST \
  --url http://localhost:8080/tts \
  --header 'Content-Type: application/json' \
  --data '{
    "backend": "transformers-musicgen",
    "model": "facebook/musicgen-medium",
    "input": "Cello Rave"
}' | aplay

Future versions of LocalAI will expose additional control over audio generation beyond the text prompt.

ACE-Step

ACE-Step 1.5 is a music generation model that can create music from text descriptions, lyrics, or audio samples. It supports both simple text-to-music and advanced music generation with metadata like BPM, key scale, and time signature.

Setup

Install the ace-step-turbo model from the Model gallery or run local-ai run models install ace-step-turbo.

Usage

ACE-Step supports two modes: Simple mode (text description + vocal language) and Advanced mode (caption, lyrics, BPM, key, and more).

Simple mode:

bash

curl http://localhost:8080/v1/audio/speech -H "Content-Type: application/json" -d '{
  "model": "ace-step-turbo",
  "input": "A soft Bengali love song for a quiet evening",
  "vocal_language": "bn"
}' --output music.flac

Advanced mode (using the /sound endpoint):

bash

curl http://localhost:8080/sound -H "Content-Type: application/json" -d '{
  "model": "ace-step-turbo",
  "caption": "A funky Japanese disco track",
  "lyrics": "[Verse 1]\n...",
  "bpm": 120,
  "keyscale": "Ab major",
  "language": "ja",
  "duration_seconds": 225
}' --output music.flac

Configuration

You can configure ACE-Step models with various options:

yaml

name: ace-step-turbo
backend: ace-step
parameters:
  model: acestep-v15-turbo
known_usecases:
  - sound_generation
  - tts
options:
  - "device:auto"
  - "use_flash_attention:true"
  - "init_lm:true"  # Enable LLM for enhanced generation
  - "lm_model_path:acestep-5Hz-lm-0.6B"  # or acestep-5Hz-lm-4B
  - "lm_backend:pt"  # or vllm
  - "temperature:0.85"
  - "top_p:0.9"
  - "inference_steps:8"
  - "guidance_scale:7.0"

VibeVoice

VibeVoice-Realtime is a real-time text-to-speech model that generates natural-sounding speech with voice cloning capabilities.

Setup

Install the vibevoice model in the Model gallery or run local-ai run models install vibevoice.

Usage

Use the tts endpoint by specifying the vibevoice backend:

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "vibevoice",
     "input":"Hello!"
   }' | aplay

Voice cloning

VibeVoice supports voice cloning through voice preset files. You can configure a model with a specific voice:

yaml

name: vibevoice
backend: vibevoice
parameters:
  model: microsoft/VibeVoice-Realtime-0.5B
tts:
  voice: "Frank"  # or use audio_path to specify a .pt file path
  # Available English voices: Carter, Davis, Emma, Frank, Grace, Mike

Then you can use the model:

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "vibevoice",
     "input":"Hello!"
   }' | aplay

Pocket TTS

Pocket TTS is a lightweight text-to-speech model designed to run efficiently on CPUs. It supports voice cloning through HuggingFace voice URLs or local audio files.

Setup

Install the pocket-tts model in the Model gallery or run local-ai run models install pocket-tts.

Usage

Use the tts endpoint by specifying the pocket-tts backend:

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "pocket-tts",
     "input":"Hello world, this is a test."
   }' | aplay

Voice cloning

Pocket TTS supports voice cloning through built-in voice names, HuggingFace URLs, or local audio files. You can configure a model with a specific voice:

yaml

name: pocket-tts
backend: pocket-tts
tts:
  voice: "azelma"  # Built-in voice name
  # Or use HuggingFace URL: "hf://kyutai/tts-voices/alba-mackenna/casual.wav"
  # Or use local file path: "path/to/voice.wav"
  # Available built-in voices: alba, marius, javert, jean, fantine, cosette, eponine, azelma

You can also pre-load a default voice for faster first generation:

yaml

name: pocket-tts
backend: pocket-tts
options:
  - "default_voice:azelma"  # Pre-load this voice when model loads

Then you can use the model:

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "pocket-tts",
     "input":"Hello world, this is a test."
   }' | aplay

Qwen3-TTS

Qwen3-TTS is a high-quality text-to-speech model that supports three modes: custom voice (predefined speakers), voice design (natural language instructions), and voice cloning (from reference audio).

Setup

Install the qwen-tts model in the Model gallery or run local-ai run models install qwen-tts.

Usage

Use the tts endpoint by specifying the qwen-tts backend:

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "qwen-tts",
     "input":"Hello world, this is a test."
   }' | aplay

Custom Voice Mode

Qwen3-TTS supports predefined speakers. You can specify a speaker using the voice parameter:

yaml

name: qwen-tts
backend: qwen-tts
parameters:
  model: Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice
tts:
  voice: "Vivian"  # Available speakers: Vivian, Serena, Uncle_Fu, Dylan, Eric, Ryan, Aiden, Ono_Anna, Sohee

Available speakers:

Chinese: Vivian, Serena, Uncle_Fu, Dylan, Eric
English: Ryan, Aiden
Japanese: Ono_Anna
Korean: Sohee

Voice Design Mode

Voice Design allows you to create custom voices using natural language instructions. Configure the model with an instruct option:

yaml

name: qwen-tts-design
backend: qwen-tts
parameters:
  model: Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign
options:
  - "instruct:体现撒娇稚嫩的萝莉女声，音调偏高且起伏明显，营造出黏人、做作又刻意卖萌的听觉效果。"

Then use the model:

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "qwen-tts-design",
     "input":"Hello world, this is a test."
   }' | aplay

Voice Clone Mode

Voice Clone allows you to clone a voice from reference audio. Configure the model with an AudioPath and optional ref_text:

yaml

name: qwen-tts-clone
backend: qwen-tts
parameters:
  model: Qwen/Qwen3-TTS-12Hz-1.7B-Base
tts:
  audio_path: "path/to/reference_audio.wav"  # Reference audio file
options:
  - "ref_text:This is the transcript of the reference audio."
  - "x_vector_only_mode:false"  # Set to true to use only speaker embedding (ref_text not required)

You can also use URLs or base64 strings for the reference audio. The backend automatically detects the mode based on available parameters (AudioPath → VoiceClone, instruct option → VoiceDesign, voice parameter → CustomVoice).

Then use the model:

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "qwen-tts-clone",
     "input":"Hello world, this is a test."
   }' | aplay

Multi-Voice Clone Mode

Qwen3-TTS also supports loading multiple voices for voice cloning, allowing you to select different voices at request time. Configure multiple voices using the voices option:

yaml

name: qwen-tts-multi-voice
backend: qwen-tts
parameters:
  model: Qwen/Qwen3-TTS-12Hz-1.7B-Base
options:
  - voices:[{"name":"jane","audio":"voices/jane.wav","ref_text":"voices/jane-ref.txt"},{"name":"john","audio":"voices/john.wav","ref_text":"voices/john-ref.txt"}]

The voices option accepts a JSON array where each voice entry must have:

name: The voice identifier (used in API requests)
audio: Path to the reference audio file (relative to model directory or absolute)
ref_text: Path to the reference text file for the audio it is paired with

Then use the model with voice selection:

bash

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "qwen-tts-multi-voice",
     "input":"Hello world, this is Jane speaking.",
     "voice": "jane"
   }' | aplay

# Switch to a different voice
curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{         
     "model": "qwen-tts-multi-voice",
     "input":"Hello world, this is John speaking.",
     "voice": "john"
   }' | aplay

Voice Selection Priority:

voice parameter in the API request (highest priority)
voice option in the model configuration
Error if voice is not found among configured voices

Error Handling: If you request a voice that doesn't exist in the voices list, the API will return an error with a list of available voices:

json

{"error": "Voice 'unknown' not found. Available voices: jane, john"}

Backward Compatibility: The multi-voice mode is backward compatible with existing single-voice configurations. Models using audio_path in the tts section will continue to work as before.

You can also use a config-file to specify TTS models and their parameters.

In the following example we define a custom config to load the xtts_v2 model, and specify a voice and language.

yaml


name: xtts_v2
backend: coqui
parameters:
  language: fr
  model: tts_models/multilingual/multi-dataset/xtts_v2

tts:
  voice: Ana Florence

With this config, you can now use the following curl command to generate a text-to-speech audio file:

bash

curl -L http://localhost:8080/tts \
    -H "Content-Type: application/json" \
    -d '{
"model": "xtts_v2",
"input": "Bonjour, je suis Ana Florence. Comment puis-je vous aider?"
}' | aplay

Response format

To provide some compatibility with OpenAI API regarding response_format, ffmpeg must be installed (or a docker image including ffmpeg used) to leverage converting the generated wav file before the api provide its response.

Warning regarding a change in behaviour. Before this addition, the parameter was ignored and a wav file was always returned, with potential codec errors later in the integration (like trying to decode a mp3 file from a wav, which is the default format used by OpenAI)

Supported format thanks to ffmpeg are wav, mp3, aac, flac, opus, defaulting to wav if an unknown or no format is provided.

bash

curl http://localhost:8080/tts -H "Content-Type: application/json" -d '{
  "input": "Hello world",
  "model": "tts",
  "response_format": "mp3"
}'

If a response_format is added in the query (other than wav) and ffmpeg is not available, the call will fail.