Kokoro TTS API

FastAPI wrapper for Kokoro-82M text-to-speech model.

Dockerized with NVIDIA GPU support, simple queue handling via sqllite, and automatic chunking/stitching on lengthy input/outputs

Quick Start

# Start the API (will automatically clone source HF repo via git-lfs)
docker compose up --build

Test it out:

# From host terminal
python examples/test_tts.py "Hello world" --voice af_bella

Performance Benchmarks

Benchmarking was performed solely on generation via the local API (ignoring file transfers) using various text lengths up to ~10 minutes output, measuring processing time, token count, and output audio length. Tests were run on:

• Windows 11 Home w/ WSL2
• NVIDIA 4060Ti 16gb GPU @ CUDA 12.1
• 11th Gen i7-11700 @ 2.5GHz
• 64gb RAM
• Randomized chunks from H.G. Wells - The Time Machine

• Average processing speed: ~3.4 seconds per minute of audio output
• Efficient token processing: ~0.01 seconds per token
• Scales well with longer texts, maintains consistent performance

API Endpoints

GET /tts/voices           # List available voices
POST /tts                 # Generate speech
GET /tts/{request_id}     # Check generation status
GET /tts/file/{request_id} # Download audio file

Example Usage

List available voices:

python examples/test_tts.py

Generate speech:

# Default voice
python examples/test_tts.py "Your text here"

# Specific voice
python examples/test_tts.py --voice af_bella "Your text here"

# Get file path without downloading
python examples/test_tts.py --no-download "Your text here"

Generated files are saved in:

• With download: examples/output/
• Without download: src/output/ (in API container)

Requirements

• Docker
• NVIDIA GPU + CUDA
• nvidia-container-toolkit installed on host

Model

This API uses the Kokoro-82M model from HuggingFace.

Visit the model page for more details about training, architecture, and capabilities. I have no affiliation with any of their work, and produced this wrapper for ease of use and personal projects.

License

This project is licensed under the Apache License 2.0 - see below for details:

• The Kokoro model weights are licensed under Apache 2.0 (see model page)
• The FastAPI wrapper code in this repository is licensed under Apache 2.0 to match
• The inference code adapted from StyleTTS2 is MIT licensed

The full Apache 2.0 license text can be found at: https://www.apache.org/licenses/LICENSE-2.0