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LocalAI/backend/go/magpie-tts-cpp
mudler's LocalAI [bot] 90355cd444 chore: ⬆️ Update mudler/magpie-tts.cpp to 3008ff73fc2d2da9e4d743b09350aa7023e8980c (#11126)
⬆️ Update mudler/magpie-tts.cpp

Signed-off-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: mudler <2420543+mudler@users.noreply.github.com>
2026-07-26 00:37:10 +02:00
..

Magpie TTS C++ backend

This backend runs NVIDIA's Magpie TTS Multilingual 357M GGUF through magpie-tts.cpp, a from-scratch C++/ggml port (model + NanoCodec + tokenizer + G2P dictionaries in one self-contained GGUF, no Python at inference time). It generates 22.05 kHz mono speech in 5 baked voices across 9+ languages.

The library is loaded via purego (cgo-less dlopen) exactly like qwen3-tts-cpp / moss-tts-cpp; the flat C-API (magpie_tts_capi_*) is exported directly by the upstream shared library, so there is no local C shim.

Model configuration

The model path points at the single GGUF:

name: magpie-tts-cpp
backend: magpie-tts-cpp
parameters:
  model: magpie-tts-multilingual-357m-q8_0.gguf
known_usecases:
  - tts
options:
  - "speaker:Aria"   # optional default voice (Aria, Jason, John, Leo, Sofia, or 0-4)
  - "language:en"    # optional default language

GGUFs live at mudler/magpie-tts.cpp-gguf (q8_0 recommended: near-lossless, ~624 MB, fastest decode).

Voices and languages

Magpie has 5 baked speakers - Aria, Jason, John, Leo, Sofia - and no voice cloning. The request voice accepts the names case-insensitively or the indices 0-4; empty selects Aria. Languages: en, es, de, fr, it, pt-BR, hi, vi, ko, ar-AE, ar-SA, ar-MSA (case-insensitive; default en).

API example

curl http://localhost:8080/v1/audio/speech \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "magpie-tts-cpp",
    "input": "Hello world, this is a test of the text to speech system.",
    "voice": "sofia",
    "language": "en"
  }' \
  --output speech.wav

Native end-to-end test

The labeled test loads a real GGUF, synthesizes WAVs (verifying rate, layout and non-silence), and exercises the streaming path:

make -C backend/go/magpie-tts-cpp magpie-tts-cpp

MAGPIETTS_MODEL=/path/to/magpie-tts-multilingual-357m-q8_0.gguf \
MAGPIETTS_LIBRARY=backend/go/magpie-tts-cpp/libgomagpiettscpp-fallback.so \
  go test ./backend/go/magpie-tts-cpp -ginkgo.label-filter=e2e

bash test.sh does the same and auto-downloads the q8_0 GGUF when MAGPIETTS_MODEL is unset.