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VoiceStudio/pyproject.toml
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Palash DebnathandClaude Fable 5 99357e8c5b feat(mcp): MCP server v1 — mount on /mcp, per-agent voice binding, stdio shim (Wave 2.2) (#368)
* feat(mcp): MCP server v1 — mount on /mcp, per-agent voice binding, stdio shim (Wave 2.2)

The FastMCP server (previously dead code, never mounted) is now mounted on
the main FastAPI app at /mcp via Streamable HTTP, with its session manager
composed into the app lifespan through an AsyncExitStack (best-effort: a
missing mcp package or OMNIVOICE_MCP_DISABLE=1 never breaks startup).
streamable_http_path set to '/' so the sub-mount lands at /mcp, not
/mcp/mcp. Adds the 'mcp' dependency (1.27.x).

Per-agent voice binding (Spec 2 headline): each MCP client sends an
X-OmniVoice-Client-Id header; generate_speech resolves the voice as
explicit arg > the client's binding > global default > app default. New
mcp_client_bindings table (alembic 0004 + _BASE_SCHEMA, additive/idempotent),
services/mcp_bindings.py (CRUD + resolve_voice + best-effort last_seen),
and a loopback-gated REST router (/api/mcp/bindings) the Settings panel
drives.

New transcribe tool (base64 audio in, 200 MB cap). Stdio shim
(backend/mcp_shim, httpx-only, ported from voicebox MIT) proxies stdio
clients to the mounted endpoint and forwards OMNIVOICE_CLIENT_ID as the
binding header. Settings → Sharing gains an MCP bindings panel. Docs:
docs/mcp.md (both connection modes + binding REST) and docs/mcp.json
updated to the shim form.

Tests: bindings service + resolution precedence + migration up/down (pure,
run locally); REST CRUD + mount-not-404 + disable-flag (main-importing,
validated in CI). MCP build + mount + initialize handshake verified
out-of-band (no torch).

Spec: docs/competitive-analysis.md Spec 2 / parity program Wave 2.2.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* test(mcp): assert /mcp mount via app.routes, not a lifespan client

The two main-importing mount tests ran the app lifespan, which now starts
the FastMCP session manager and binds asyncio queues to the test loop —
contaminating later lifespan-running tests ('bound to a different event
loop'). The mount happens at import time, so inspecting app.routes for the
/mcp Mount is the correct loop-free assertion. Same fix shape as the
Wave 0.2 consent tests.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* test(mcp): stop reload-main poisoning across the MCP test files

Root cause of the CI failure: the bindings REST fixture set
OMNIVOICE_MCP_DISABLE=1 and reloaded main but never restored it, so a
later 'from main import app' in test_mcp_mount saw /mcp un-mounted
({'/audio','/voice_audio'}). Reloading main mutates the shared module for
every subsequent test.

- REST fixture: drop the disable flag (the mount is harmless without a
  lifespan), yield the client, and restore main (+ core.config/db) to the
  default data dir in teardown so the global module is clean again.
- test_main_mounts_mcp_route: reload main with the disable flag cleared so
  the assertion is independent of any earlier reload.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

---------

Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
2026-06-12 11:56:19 +05:30

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[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"
[project]
name = "omnivoice"
version = "0.3.6"
description = "OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models"
readme = "README.md"
# Free and open-source under the GNU Affero General Public License v3 (see
# LICENSE). A commercial license is available for proprietary/closed-source use
# without AGPL obligations — contact OmniVoice@palash.dev. The bundled omnivoice/
# TTS model by Han Zhu remains Apache-2.0 upstream (Apache-2.0 is AGPL-compatible).
license = "AGPL-3.0-only"
requires-python = ">=3.11"
authors = [{name = "Han Zhu"}]
keywords = [
"tts",
"text-to-speech",
"speech-synthesis",
"zero-shot",
"multilingual",
"diffusion",
"voice-cloning",
]
classifiers = [
"Intended Audience :: Science/Research",
"Intended Audience :: Developers",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Multimedia :: Sound/Audio :: Speech",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
]
dependencies = [
"torch>=2.4",
"torchaudio>=2.4",
"transformers>=5.3.0",
"accelerate",
"pydub",
"gradio",
"tensorboardX",
"webdataset",
"numpy",
"soundfile",
# whisperx / faster-whisper import `pkg_resources` at runtime. setuptools
# 80+ DROPPED the bundled pkg_resources, so an unpinned ">=75" now resolves
# to a version WITHOUT it → "No module named 'pkg_resources'", which both
# breaks WhisperX transcription and makes its is_available() report false
# ("No ASR backend is ready"). Cap below 80 so pkg_resources stays present
# (issue #224; also #58). Revisit when whisperx/faster-whisper drop the
# pkg_resources dependency.
"setuptools>=75,<80",
"psutil>=7.2.2",
# Pinned to 3.x — pyannote 4.x removed `use_auth_token` from `Inference`
# which whisperx 3.4.2 still passes, blowing up `whisperx.load_model()`
# with TypeError. whisperx tests against pyannote 3.3.2+, so we track
# that range and revisit when whisperx releases a 4-compatible build.
"pyannote-audio>=3.3.2,<4.0",
"pyinstaller>=6.19.0",
"imageio-ffmpeg>=0.6.0",
"pedalboard>=0.9.14",
# Primary ASR — cross-platform, CTranslate2-based under the hood. WhisperX
# adds wav2vec2 forced alignment (±10-30 ms word timing vs Whisper's own
# ±100-300 ms) which directly improves lip-sync on the dub pipeline.
# Pulls `faster-whisper` transitively, so a WhisperX install also provides
# the plain faster-whisper backend as a fallback for rare-language audio
# where no wav2vec2 alignment model exists.
"whisperx>=3.1.0",
"faster-whisper>=1.0.0",
# Apple Silicon-only speedup; skipped everywhere else so `uv sync` can
# succeed on Linux/Windows/mac-Intel (no mlx wheels exist for those).
"mlx-whisper>=0.2.1 ; sys_platform == 'darwin' and platform_machine == 'arm64'",
# Apple Silicon-only rich TTS library — 14+ engines (Kokoro, CSM, Dia,
# Qwen3-TTS, Chatterbox, MeloTTS, OuteTTS, Spark, Higgs-Audio, Voxtral,
# …). Gives mac-ARM users a broad engine picker in Settings. Also gated
# by platform markers because it depends on mlx (Apple Silicon only).
"mlx-audio>=0.3.0 ; sys_platform == 'darwin' and platform_machine == 'arm64'",
"demucs>=4.0.1",
"yt-dlp>=2024.12.13",
"alembic>=1.13",
# Lightweight English TTS "Turbo" tier — 25-80 MB ONNX model, 8 preset
# voices (Bella, Jasper, Luna, Bruno, Rosie, Hugo, Kiki, Leo), CPU
# realtime on any platform. Complements OmniVoice's 2.4 GB multilingual
# zero-shot clone: when the caller just needs fast English narration with
# no reference sample, this is ~100× smaller + ~10× faster. Pinned to
# the exact wheel because the project is in developer preview and the
# 0.x API is explicitly unstable.
"kittentts @ https://github.com/KittenML/KittenTTS/releases/download/0.8.1/kittentts-0.8.1-py3-none-any.whl",
# Invisible audio watermarking — embeds imperceptible neural watermarks
# in AI-generated speech for provenance detection (SynthID-like).
# MIT license, ~5ms per segment on CPU, 16-bit message payload.
"audioseal>=0.1.3",
# API server — always needed for the Studio UI.
"fastapi",
"scalar-fastapi",
"uvicorn",
"python-multipart",
# Required by uvicorn for WebSocket support (real-time sidebar events).
"websockets",
# Offline translation — listed as builtin in the engine registry so the
# "Argos (Local, Fast)" option in the Dub tab works out-of-the-box.
"argostranslate>=1.9.0",
# Phase 1 AUTH-02: Fernet symmetric encryption + scrypt KDF for the
# at-rest HF token in the SQLite settings store. Pulled in directly so
# we don't depend on a transitive arrival via pyannote/huggingface_hub
# (Assumption A1 in RESEARCH.md was checked at execute-time and proved
# false — `cryptography` is not on the install path today).
"cryptography>=41",
"mcp>=1.2",
]
[project.optional-dependencies]
eval = [
"jiwer==3.1.0", # WER
"librosa", # Audio processing
"s3prl", # Speech representation (HuBERT etc.)
"funasr", # ASR models
"zhconv", # Chinese character normalization
"zhon", # Chinese punctuation
"unidecode", # Unicode normalization
]
ui = [
"gradio",
"gradio_client",
"requests",
]
# Phase 3 Plan 03-01 — Supertonic-3 opt-in engine. CPU-only ONNX TTS,
# 31 languages, ~99M params, ~400 MB model on first use. Default
# `uv sync --no-dev` does NOT install this; users opt in with
# `uv sync --extra supertonic` after accepting the OpenRAIL-M model
# license in Settings → Engines.
#
# Publisher verified per Plan 03-01 Task 1 (Package Legitimacy Audit):
# • PyPI maintainers = Yu Yechan / Juheon Lee / Hyeongju Kim (Supertone Inc.)
# • Repository = github.com/supertone-inc/supertonic-py
# • Same publisher ships supertonic-js on npm (same maintainer email)
# • Wheel inspected: pure-Python, no postinstall scripts, no subprocess/exec
# at module top level. ``supertonic.config.MODEL_CONFIGS["supertonic-3"]``
# itself pins the HF model revision by SHA — we re-pin to the same
# SHA in backend/engines/supertonic3/constants.py for TTS-03.
supertonic = [
"supertonic==1.3.1",
]
[project.scripts]
omnivoice-infer = "omnivoice.cli.infer:main"
omnivoice-infer-batch = "omnivoice.cli.infer_batch:main"
omnivoice-demo = "omnivoice.cli.demo:main"
omnivoice-dub = "omnivoice.cli.dub:main"
[project.urls]
Homepage = "https://github.com/k2-fsa/OmniVoice"
Repository = "https://github.com/k2-fsa/OmniVoice"
"Bug Tracker" = "https://github.com/k2-fsa/OmniVoice/issues"
[tool.uv.sources]
# Install PyTorch with CUDA support on Linux/Windows (CUDA doesn't exist for Mac).
# NOTE: We must explicitly request them as `dependencies` above. These improved
# versions will not be selected if they're only third-party dependencies.
torch = [
{ index = "pytorch-cuda", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
]
torchaudio = [
{ index = "pytorch-cuda", marker = "sys_platform == 'linux' or sys_platform == 'win32'" },
]
[[tool.uv.index]]
name = "pytorch-cuda"
# Use PyTorch built for NVIDIA Toolkit version 12.8.
# Available versions: https://pytorch.org/get-started/locally/
url = "https://download.pytorch.org/whl/cu128"
# Only use this index when explicitly requested by `tool.uv.sources`.
explicit = true
[tool.uv]
constraint-dependencies = [
"torch==2.8.0",
"torchaudio==2.8.0",
]
[tool.hatch.metadata]
# Needed so the KittenTTS wheel-URL dep in `project.dependencies` is accepted
# by hatchling's metadata validator. KittenTTS isn't on PyPI (dev preview),
# so pulling it via GH Releases URL is the only option today.
allow-direct-references = true
[tool.hatch.build.targets.sdist]
include = ["omnivoice"]
[tool.hatch.build.targets.wheel]
packages = ["omnivoice"]
[dependency-groups]
dev = [
"httpx>=0.28.1",
"pytest>=9.0.3",
"pytest-asyncio>=1.3.0",
"pytest-cov>=6.0",
]
[tool.pytest.ini_options]
# Bare `pytest` would otherwise walk into `research/` (1.2 GB of vendored
# upstream projects, each with its own test_*.py that calls sys.exit at
# module level) and INTERNALERROR. `backend/tests/` runs separately because
# it stubs `core.config` in sys.modules, which pollutes import state for
# other modules in the same session.
testpaths = ["tests"]
norecursedirs = [
"research",
"omnivoice/training",
"omnivoice/eval",
"frontend",
"deploy",
".venv",
"node_modules",
"omnivoice_data",
"backend/omnivoice_data",
]