MeloTTS-API

A simple, robust, and OpenAI-compatible FastAPI wrapper for the MyShell-AI/MeloTTS text-to-speech engine.

This project provides an easy-to-use HTTP interface for MeloTTS, allowing you to integrate high-quality, natural-sounding text-to-speech into your applications with simple API calls. The API structure is designed to mimic common TTS services for easy integration.

Features

• High-Quality TTS: Leverages the power of MeloTTS for fast and natural-sounding speech synthesis.
• OpenAI-Compatible Endpoint: Includes a /v1/audio/speech endpoint that mirrors the structure of OpenAI's TTS API for drop-in compatibility with tools like Open WebUI.
• RESTful Interface: Provides clear endpoints to list available models and voices.
• Reliable Installation: A comprehensive requirements.txt file ensures a clean and complete installation in an isolated environment.
• CPU Ready: Configured to run on CPU out-of-the-box, no GPU required.

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🚀 Installation

For a reliable setup, please follow these steps exactly. This guide has been tested on Debian-based systems like Linux Mint 20 and Ubuntu 24.04.

📋 Step 1: System Prerequisites

For a barebones system, you will need to install Git and Python's core tools first.

sudo apt update && sudo apt upgrade -y
sudo apt install git python3 python3-pip python3-venv -y

📦 Step 2: Clone This Repository

git clone https://github.com/highfillgoods/MeloTTS-API-Locally.git cd MeloTTS-API-Locally 🌿 Step 3: Create and Activate a Virtual Environment

Using a dedicated environment helps prevent conflicts. Choose one of the following options.

Option A: Using conda

conda create --name melo_api_env python=3.11 -y conda activate melo_api_env

Option B: Using venv (Standard Python)

python3 -m venv venv source venv/bin/activate

🐍 Step 4: Install Python Dependencies

This single command installs all necessary Python packages from the perfected requirements.txt file.

pip install -r requirements.txt

🧠 Step 5: Download NLTK Language Models

The text processor requires data packages from the NLTK library. This command downloads the necessary models.

python3 -m nltk.downloader averaged_perceptron_tagger punkt

▶️ Running the API Server

Once the installation is complete, start the API server with Uvicorn.

uvicorn melotts_api:app --host 0.0.0.0 --port 8000

The server will start, load the MeloTTS model, and become available at http://0.0.0.0:8000.

🔌 Connecting to Open WebUI

This API is designed to work directly with Open WebUI.

In Open WebUI, navigate to Settings > Audio. Configure the TTS Settings section with the following values: Text-to-Speech Engine: OpenAI OpenAI API Base URL: http://localhost:8000/v1 OpenAI API Key: Can be set to anything (e.g., 12345). Your settings should look like this:

🛠️ Direct API Usage (Advanced)

You can also interact with the API directly using tools like curl.

List Available Models

curl http://localhost:8000/v1/models

List Available Voices

curl http://localhost:8000/v1/audio/voices Synthesize Speech

Test audio Generation of voices

curl -X POST \
  http://localhost:8000/v1/audio/speech \
  -H "Content-Type: application/json" \
  --data '{
    "input": "Hello, this is a test from the land down under.",
    "voice": "EN-AU"
  }' \
  --output test_audio.mp3

Bonus: Running the Original MeloTTS WebUI

These instructions are for running the original Gradio WebUI developed by MyShell-AI, which is separate from the FastAPI server above. It's recommended to do this in a different folder and a new, clean environment.

Clone the Original MeloTTS Repository

Make sure you are in your home directory or outside your API project folder

git clone https://github.com/myshell-ai/MeloTTS.git cd MeloTTS Create a Separate, Clean Environment (e.g., conda create --name melo_ui_env python=3.11 -y) and activate it.

Install All WebUI Dependencies. Note: We do not use pip install melo.

pip install torch torchvision torchaudio gradio librosa tqdm transformers cn2an pypinyin jieba eng_to_ipa inflect unidecode num2words pykakasi fugashi g2p_en anyascii jamo gruut cached_path unidic

python3 -m nltk.downloader averaged_perceptron_tagger punkt python3 -m melo.app

Open in browser for Original MeloTTS WebUI

http://localhost:7860