Server

This page covers server-side inference for Fish Audio S2, plus quick links for WebUI inference and Docker deployment.

API Server Inference

Fish Speech provides an HTTP API server entrypoint at tools/api_server.py.

Start the server locally

python tools/api_server.py \
  --llama-checkpoint-path checkpoints/s2-pro \
  --decoder-checkpoint-path checkpoints/s2-pro/codec.pth \
  --listen 0.0.0.0:8080

Common options:

--compile: enable torch.compile optimization
--half: use fp16 mode
--api-key: require bearer token authentication
--workers: set worker process count

Health check

curl -X GET http://127.0.0.1:8080/v1/health

Expected response:

{"status":"ok"}

Main API endpoint

POST /v1/tts for text-to-speech generation
POST /v1/vqgan/encode for VQ encode
POST /v1/vqgan/decode for VQ decode

Python client example

The base TTS model is selected when the server starts. In the example above, the server is started with the checkpoints/s2-pro weights, so every request sent to http://127.0.0.1:8080/v1/tts will use S2-Pro automatically. There is no separate per-request model field in tools/api_client.py for local server calls.

python tools/api_client.py \
  --url http://127.0.0.1:8080/v1/tts \
  --text "Hello from Fish Speech" \
  --output s2-pro-demo

If you want to select a saved reference voice, use --reference_id. This chooses the voice reference, not the base TTS model:

python tools/api_client.py \
  --url http://127.0.0.1:8080/v1/tts \
  --text "Hello from Fish Speech" \
  --reference_id my-speaker \
  --output s2-pro-demo

WebUI Inference

For WebUI usage, see:

WebUI Inference

Docker

For Docker-based server or WebUI deployment, see:

Docker Setup

You can also start the server profile directly with Docker Compose:

docker compose --profile server up

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