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b4f1fe18d7 |
@@ -540,7 +540,13 @@ jobs:
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# Gather artifact paths per matrix leg's `bundles` (msi/app/dmg/deb/appimage/updater).
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# `find` is portable across all three runners (Git Bash on Windows).
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mapfile -t ARTIFACTS < <(find "$BUNDLE_DIR" -type f \
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# NB: macOS runners use /bin/bash 3.2, which has no `mapfile` (a bash 4+
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# builtin) — using it 127'd this step and dropped the macOS SHA256SUMS
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# for v0.3.1 and v0.3.2. A `while read` loop is portable to bash 3.2.
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ARTIFACTS=()
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while IFS= read -r artifact; do
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ARTIFACTS+=("$artifact")
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done < <(find "$BUNDLE_DIR" -type f \
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\( -name "*.dmg" -o -name "*.app.tar.gz" -o -name "*.app.tar.gz.sig" \
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-o -name "*.msi" -o -name "*.msi.sig" \
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-o -name "*.AppImage" -o -name "*.AppImage.sig" \
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@@ -6,6 +6,45 @@ The format is loosely based on [Keep a Changelog](https://keepachangelog.com/).
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Versions track the desktop app (`tauri.conf.json` + `frontend/src-tauri/Cargo.toml`).
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The bundled TTS model package (`pyproject.toml`) is versioned independently.
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## [0.3.4] — 2026-06-03
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|
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### Fixed
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||||
- **Transcription on Windows + NVIDIA failed with `Could not locate
|
||||
cudnn_ops_infer64_8.dll`.** WhisperX/faster-whisper need cuDNN 8 (via
|
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CTranslate2); when the side-loaded `cudnn8_compat` libs are missing, the
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**PyTorch Whisper** backend (Settings → Models) now works as a drop-in
|
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fallback — it builds its own transformers pipeline on PyTorch's cuDNN-9
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stack, with no CTranslate2/cuDNN-8 dependency and no
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`OMNIVOICE_PRELOAD_TTS_ASR=1` required. (#255)
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## [0.3.3] — 2026-06-03
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### Fixed
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- **Settings → About showed the wrong architecture in the Docker/web build.**
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The "Architecture" row rendered the *client browser's* platform
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(`navigator.platform` → e.g. "Win32"); it now reports the **server's** CPU
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architecture from the backend (`platform.machine()`), correct for both the
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desktop app and Docker. The blank version/GPU/RAM/VRAM in the same report
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were the loopback-gate 403s already fixed in v0.3.2. (#262)
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### CI
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- The release SHA-256 checksum step no longer uses `mapfile` (a bash 4+
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builtin) — it broke on the macOS runner's bash 3.2 and dropped the macOS
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`SHA256SUMS` for v0.3.1/v0.3.2. Now portable to bash 3.2.
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## [0.3.2] — 2026-06-03
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|
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### Fixed
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- **"Loopback origin required" all over the Docker UI** (and a blank version).
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The `/system/*` and `/api/settings/*` routes are restricted to a loopback
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origin, but Docker's NAT makes every request look non-loopback, so the gate
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403'd the operator out of the admin UI — including `/system/info` (blanking
|
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the version) and HF-token entry. The Docker image now runs with
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`OMNIVOICE_SERVER_MODE=1`, which relaxes the gate for the headless
|
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deployment; exposure is governed by the `-p` port mapping plus the optional
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share PIN. Desktop builds are unaffected — their loopback boundary (and the
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denial of admin routes to LAN share guests) is unchanged. (#261)
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## [0.3.1] — 2026-06-03
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First tagged build of the 0.3 line off `main` — it ships the accumulated
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@@ -5,9 +5,12 @@ These are intentionally tiny — one concern per dependency — so they can be
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composed at the route or router level without surprises.
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Currently exposed:
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- `require_loopback`: 403 unless the request came from a loopback origin.
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- `require_loopback`: 403 unless the request came from a loopback origin
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(bypassed in explicit server mode — see `_server_mode`).
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"""
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import os
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from fastapi import HTTPException, Request
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@@ -19,6 +22,28 @@ from fastapi import HTTPException, Request
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# the guard: nothing here matches a non-loopback origin.
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_LOOPBACK_HOSTS = frozenset({"127.0.0.1", "::1", "localhost"})
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_TRUTHY = frozenset({"1", "true", "yes", "on"})
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def _server_mode() -> bool:
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"""Whether this process is a headless server deployment (Docker image).
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In Docker the loopback gate is *unenforceable*: Docker's network NAT
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rewrites ``request.client.host`` to the bridge gateway (e.g. 172.17.0.1)
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even for a localhost-only ``-p 127.0.0.1:3900:3900`` mapping, so every
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request looks non-loopback and the gate 403s the operator out of the
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system/settings routes they need (issue #261 — incl. ``/system/info``,
|
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which blanks the version display).
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The Docker image sets ``OMNIVOICE_SERVER_MODE=1`` to opt out of the gate.
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Network exposure then rests on the operator's port mapping plus the
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optional share PIN (``NetworkAccessMiddleware`` still 401s unauthenticated
|
||||
non-loopback clients whenever a PIN is set). The desktop build never sets
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this, so its loopback boundary — including denying LAN share guests access
|
||||
to admin routes — is unchanged. Read at call time so it stays testable.
|
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"""
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return os.environ.get("OMNIVOICE_SERVER_MODE", "").strip().lower() in _TRUTHY
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def require_loopback(request: Request) -> None:
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"""Reject any request whose `client.host` is not a loopback address.
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@@ -35,7 +60,14 @@ def require_loopback(request: Request) -> None:
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Returns None on success (FastAPI dependency convention). Raises 403
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on rejection — the response body is `{"detail": "loopback origin required"}`
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so existing tests for `/system/set-env` keep passing without modification.
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In server mode (Docker, see `_server_mode`) the gate is a no-op: the
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loopback origin is unenforceable there and exposure is governed by the
|
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deployment's port mapping + the optional share PIN instead.
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"""
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host = request.client.host if request.client else None
|
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if host not in _LOOPBACK_HOSTS:
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raise HTTPException(status_code=403, detail="loopback origin required")
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if host in _LOOPBACK_HOSTS:
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return
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if _server_mode():
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return
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raise HTTPException(status_code=403, detail="loopback origin required")
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@@ -404,12 +404,11 @@ async def dub_transcribe_stream(job_id: str):
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else:
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from services.asr_backend import get_active_asr_backend
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try:
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# The PyTorch-Whisper backend lazily builds its own pipeline
|
||||
# when no preloaded `_asr_pipe` is present (issue #255), so it
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# no longer needs OMNIVOICE_PRELOAD_TTS_ASR=1 — don't reject it
|
||||
# here; any load failure surfaces per-chunk with a real cause.
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_asr_backend = get_active_asr_backend(asr_pipe=getattr(_model, "_asr_pipe", None))
|
||||
if _asr_backend.id == "pytorch-whisper" and getattr(_model, "_asr_pipe", None) is None:
|
||||
preflight_error = (
|
||||
"No ASR backend is ready. Install WhisperX/faster-whisper/MLX Whisper "
|
||||
"or set OMNIVOICE_PRELOAD_TTS_ASR=1 before launch to use the PyTorch fallback."
|
||||
)
|
||||
except Exception as e:
|
||||
from core.failure import build_failure
|
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f = build_failure(e, stage="transcribe-preflight", include_diagnostic=False)
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||||
@@ -1,5 +1,6 @@
|
||||
import os
|
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import sys
|
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import platform
|
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import uuid
|
||||
import psutil
|
||||
import asyncio
|
||||
@@ -181,6 +182,7 @@ def system_info():
|
||||
"device": get_best_device(),
|
||||
"python": sys.version.split()[0],
|
||||
"platform": sys.platform,
|
||||
"arch": platform.machine(),
|
||||
"ffmpeg_ok": bool(_ffmpeg),
|
||||
"ffmpeg_path": _ffmpeg or "",
|
||||
"proxy_url": os.environ.get("HTTP_PROXY") or os.environ.get("http_proxy") or "",
|
||||
@@ -207,6 +209,7 @@ def system_info():
|
||||
"device": "cpu",
|
||||
"python": sys.version.split()[0],
|
||||
"platform": sys.platform,
|
||||
"arch": platform.machine(),
|
||||
"proxy_url": "",
|
||||
"share_enabled": network_share.get_state().enabled,
|
||||
"share_port": network_share.get_state().share_port,
|
||||
|
||||
@@ -37,6 +37,7 @@ class SystemInfoResponse(BaseModel):
|
||||
device: str = "cpu"
|
||||
python: str = ""
|
||||
platform: str = ""
|
||||
arch: str = ""
|
||||
error: str | None = None
|
||||
ffmpeg_ok: bool = False
|
||||
ffmpeg_path: str = ""
|
||||
|
||||
@@ -12,4 +12,4 @@ from importlib.metadata import PackageNotFoundError, version
|
||||
try:
|
||||
APP_VERSION = version("omnivoice")
|
||||
except PackageNotFoundError: # non-installed source checkout
|
||||
APP_VERSION = "0.3.1"
|
||||
APP_VERSION = "0.3.4"
|
||||
|
||||
@@ -577,22 +577,32 @@ class PyTorchWhisperBackend(ASRBackend):
|
||||
def _ensure_pipe(self):
|
||||
if self._pipe is not None:
|
||||
return
|
||||
# Fall back to grabbing the TTS model's ASR head.
|
||||
import asyncio
|
||||
from services.model_manager import get_model
|
||||
try:
|
||||
loop = asyncio.get_running_loop()
|
||||
if loop.is_running():
|
||||
raise RuntimeError(
|
||||
"PyTorchWhisperBackend needs the ASR pipe — pass it via constructor "
|
||||
"when calling from an async context."
|
||||
)
|
||||
model = loop.run_until_complete(get_model())
|
||||
except RuntimeError:
|
||||
model = asyncio.run(get_model())
|
||||
self._pipe = getattr(model, "_asr_pipe", None)
|
||||
if self._pipe is None:
|
||||
raise RuntimeError("Loaded TTS model has no `_asr_pipe` attribute.")
|
||||
# Build a standalone transformers Whisper pipeline on demand. This runs
|
||||
# on PyTorch's own stack (cuDNN 9 ships with torch), so it works as a
|
||||
# fallback on machines where WhisperX / faster-whisper can't load
|
||||
# cuDNN 8 (the `cudnn_ops_infer64_8.dll` failure, issue #255) — and it
|
||||
# needs neither OMNIVOICE_PRELOAD_TTS_ASR=1 nor a loaded TTS model.
|
||||
# When the TTS model already has an ASR head, dub_core passes it via the
|
||||
# constructor and this path is skipped.
|
||||
import torch
|
||||
from transformers import pipeline as hf_pipeline
|
||||
from services.model_manager import get_best_device
|
||||
|
||||
model_name = os.environ.get(
|
||||
"OMNIVOICE_PYTORCH_ASR_MODEL", "openai/whisper-large-v3-turbo"
|
||||
)
|
||||
device = get_best_device()
|
||||
asr_dtype = torch.float16 if str(device).startswith("cuda") else torch.float32
|
||||
logger.info(
|
||||
"PyTorchWhisperBackend: loading standalone ASR pipeline %s on %s",
|
||||
model_name, device,
|
||||
)
|
||||
self._pipe = hf_pipeline(
|
||||
"automatic-speech-recognition",
|
||||
model=model_name,
|
||||
dtype=asr_dtype,
|
||||
device_map=device,
|
||||
)
|
||||
|
||||
def transcribe(self, audio_path: str, *, word_timestamps: bool = True) -> dict:
|
||||
import soundfile as sf
|
||||
|
||||
@@ -29,6 +29,13 @@ ENV HF_HOME=/app/omnivoice_data/huggingface
|
||||
# Allow bare imports (from core.config, from services.*, etc.) when
|
||||
# uvicorn is started as `backend.main:app` from WORKDIR /app.
|
||||
ENV PYTHONPATH=/app/backend
|
||||
# Headless server deployment: relax the desktop-only loopback origin gate.
|
||||
# Docker's network NAT rewrites the client host to the bridge gateway, so the
|
||||
# gate would otherwise 403 the operator out of /system/* and /api/settings/*
|
||||
# ("Loopback origin required", issue #261). Exposure is governed by the
|
||||
# operator's `-p` port mapping plus the optional share PIN. Desktop builds
|
||||
# never set this, so their loopback boundary is unchanged.
|
||||
ENV OMNIVOICE_SERVER_MODE=1
|
||||
|
||||
# Install system dependencies (FFmpeg is critical for torchaudio/scene splitting)
|
||||
RUN apt-get update && apt-get install -y --no-install-recommends \
|
||||
|
||||
@@ -46,6 +46,12 @@ services:
|
||||
# OMNIVOICE_BIND_HOST=0.0.0.0 here only opens the container's own
|
||||
# interface. The backend default is 127.0.0.1 (see backend/main.py).
|
||||
- OMNIVOICE_BIND_HOST=0.0.0.0
|
||||
# Headless server: relax the desktop-only loopback origin gate so the
|
||||
# web UI's /system/* and /api/settings/* routes work through Docker's
|
||||
# NAT (issue #261). Already baked into the image; shown here so it's
|
||||
# discoverable. If you front the container with your own auth proxy on
|
||||
# loopback, set this to 0 to re-enable the strict gate.
|
||||
- OMNIVOICE_SERVER_MODE=1
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-sf", "http://localhost:3900/health"]
|
||||
interval: 30s
|
||||
@@ -76,6 +82,9 @@ services:
|
||||
# service above. The host-side `127.0.0.1:3900:3900` mapping keeps
|
||||
# LAN reachability off by default.
|
||||
- OMNIVOICE_BIND_HOST=0.0.0.0
|
||||
# See the CPU service above — relaxes the loopback origin gate for the
|
||||
# headless Docker deployment (issue #261). Set to 0 to re-enable it.
|
||||
- OMNIVOICE_SERVER_MODE=1
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-sf", "http://localhost:3900/health"]
|
||||
interval: 30s
|
||||
|
||||
@@ -118,6 +118,15 @@ Two paths are worth persisting across container restarts:
|
||||
The running version is now shown in **Settings → About → Version** (read live
|
||||
from the backend), so the web UI no longer displays a dash in Docker.
|
||||
- **Checking which version is running:** `docker exec omnivoice python -c "import importlib.metadata; print(importlib.metadata.version('omnivoice'))"`, or hit the `/health` endpoint — it returns `{"status": "ok", "device": ..., "version": "0.3.x"}`.
|
||||
- **"Loopback origin required" errors (and a blank version):** the desktop
|
||||
build restricts the `/system/*` and `/api/settings/*` routes to a loopback
|
||||
origin, but Docker's NAT makes every request look non-loopback, so the gate
|
||||
used to 403 the whole admin UI (issue #261). The image now ships with
|
||||
`OMNIVOICE_SERVER_MODE=1`, which relaxes that gate for the headless
|
||||
deployment — exposure is instead governed by your `-p` port mapping (keep the
|
||||
`127.0.0.1:` prefix to stay local) plus the optional share PIN. If you front
|
||||
the container with your own auth proxy on loopback, set `OMNIVOICE_SERVER_MODE=0`
|
||||
to re-enable the strict gate.
|
||||
- **Media-preview 404 in LAN mode:** see the [LAN access](#lan-access) section
|
||||
above — the `window.location.host` fix shipped in v0.3.
|
||||
- **GPU not detected:** verify `docker run --rm --gpus all nvidia/cuda:12.8.0-base-ubuntu22.04 nvidia-smi` succeeds first.
|
||||
|
||||
@@ -121,7 +121,24 @@ falling back to faster-whisper`.
|
||||
path and is still fast. If you want the latest CT2 wheels, run `uv sync`
|
||||
from a fresh source checkout.
|
||||
|
||||
## 10. IndexTTS / CosyVoice / ChatterboxTTS clash
|
||||
## 10. Windows: `Could not locate cudnn_ops_infer64_8.dll` during transcription
|
||||
|
||||
**Symptom:** on Windows + NVIDIA, transcription/dubbing fails and the backend
|
||||
log shows `Could not locate cudnn_ops_infer64_8.dll`. Settings → Models shows
|
||||
WhisperX or faster-whisper selected.
|
||||
|
||||
**Cause:** WhisperX and faster-whisper run on **CTranslate2**, which needs
|
||||
**cuDNN 8**, but PyTorch 2.8 ships cuDNN 9. OmniVoice side-loads a cuDNN-8 copy
|
||||
from `.venv\Lib\site-packages\cudnn8_compat\`; if that folder is missing
|
||||
(some upgrade paths don't install it), CTranslate2 can't find the DLL.
|
||||
|
||||
**Fix:** switch the ASR backend to **PyTorch Whisper** in **Settings → Models**.
|
||||
It runs on PyTorch's own stack (cuDNN 9, bundled with torch) and needs no
|
||||
cuDNN-8 DLL — it loads its Whisper pipeline on demand (no extra env var). To
|
||||
keep using faster-whisper/WhisperX instead, reinstall to restore the bundled
|
||||
`cudnn8_compat` libraries.
|
||||
|
||||
## 11. IndexTTS / CosyVoice / ChatterboxTTS clash
|
||||
|
||||
**Symptom:** installing one of these engines breaks the others — e.g. after
|
||||
installing CosyVoice, IndexTTS errors out with import conflicts.
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "omnivoice-studio",
|
||||
"private": true,
|
||||
"version": "0.3.1",
|
||||
"version": "0.3.4",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
|
||||
Generated
+1
-1
@@ -2878,7 +2878,7 @@ dependencies = [
|
||||
|
||||
[[package]]
|
||||
name = "omnivoice-studio"
|
||||
version = "0.3.1"
|
||||
version = "0.3.4"
|
||||
dependencies = [
|
||||
"dirs-next",
|
||||
"enigo",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "omnivoice-studio"
|
||||
version = "0.3.1"
|
||||
version = "0.3.4"
|
||||
description = "OmniVoice Studio – AI voice cloning & dubbing desktop app"
|
||||
authors = ["Debpalash"]
|
||||
license = "AGPL-3.0"
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"$schema": "../node_modules/@tauri-apps/cli/config.schema.json",
|
||||
"productName": "OmniVoice Studio",
|
||||
"version": "0.3.1",
|
||||
"version": "0.3.4",
|
||||
"identifier": "com.debpalash.omnivoice-studio",
|
||||
"build": {
|
||||
"frontendDist": "../dist",
|
||||
|
||||
@@ -60,6 +60,7 @@ export interface SystemInfo {
|
||||
app_version?: string;
|
||||
python?: string;
|
||||
platform?: string;
|
||||
arch?: string;
|
||||
device?: string;
|
||||
data_dir?: string;
|
||||
outputs_dir?: string;
|
||||
|
||||
@@ -1355,7 +1355,7 @@ export default function Settings() {
|
||||
<Row label={t('about.version')} value={appVersion || info?.app_version || '—'} mono />
|
||||
<Row label={t('about.tauri_runtime')} value={tauriVersion || (isTauri() ? '—' : t('about.web_preview'))} mono />
|
||||
<Row label={t('about.platform')} value={info?.platform || '—'} />
|
||||
<Row label={t('about.architecture')} value={typeof navigator !== 'undefined' ? (navigator.userAgentData?.platform || navigator.platform || '—') : '—'} mono />
|
||||
<Row label={t('about.architecture')} value={info?.arch || '—'} mono />
|
||||
<Row label={t('about.python')} value={info?.python || '—'} mono />
|
||||
<Row label={t('about.compute_device')} value={info?.device || '—'} mono />
|
||||
<Row label={t('about.gpu_active')} value={hw?.gpu_active
|
||||
|
||||
+1
-1
@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
|
||||
|
||||
[project]
|
||||
name = "omnivoice"
|
||||
version = "0.3.1"
|
||||
version = "0.3.4"
|
||||
description = "OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models"
|
||||
readme = "README.md"
|
||||
# Source-available under FSL-1.1-ALv2 (see LICENSE); each release converts to
|
||||
|
||||
@@ -0,0 +1,55 @@
|
||||
"""`require_loopback` gate contract (issue #261).
|
||||
|
||||
The gate must stay strict on the desktop build (non-loopback → 403, which is the
|
||||
PR #81 trust boundary), but become a no-op in the headless Docker server mode,
|
||||
where Docker's NAT makes the loopback origin unenforceable and exposure is
|
||||
governed by the port mapping + the share PIN instead.
|
||||
"""
|
||||
from types import SimpleNamespace
|
||||
|
||||
import pytest
|
||||
from fastapi import HTTPException
|
||||
|
||||
from api.dependencies import require_loopback
|
||||
|
||||
|
||||
def _req(host):
|
||||
"""Minimal stand-in for a Starlette Request — the gate only reads client.host."""
|
||||
return SimpleNamespace(client=SimpleNamespace(host=host) if host else None)
|
||||
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _clear_server_mode(monkeypatch):
|
||||
# Start each test from the desktop default regardless of the ambient env.
|
||||
monkeypatch.delenv("OMNIVOICE_SERVER_MODE", raising=False)
|
||||
|
||||
|
||||
@pytest.mark.parametrize("host", ["127.0.0.1", "::1", "localhost"])
|
||||
def test_loopback_always_allowed(host):
|
||||
require_loopback(_req(host)) # must not raise
|
||||
|
||||
|
||||
def test_non_loopback_rejected_by_default():
|
||||
with pytest.raises(HTTPException) as exc:
|
||||
require_loopback(_req("172.17.0.1")) # Docker bridge gateway
|
||||
assert exc.value.status_code == 403
|
||||
assert "loopback" in str(exc.value.detail).lower()
|
||||
|
||||
|
||||
def test_missing_client_rejected_by_default():
|
||||
with pytest.raises(HTTPException):
|
||||
require_loopback(_req(None))
|
||||
|
||||
|
||||
@pytest.mark.parametrize("val", ["1", "true", "TRUE", "yes", "on"])
|
||||
def test_server_mode_allows_non_loopback(monkeypatch, val):
|
||||
monkeypatch.setenv("OMNIVOICE_SERVER_MODE", val)
|
||||
require_loopback(_req("172.17.0.1")) # must not raise
|
||||
require_loopback(_req("127.0.0.1")) # loopback still fine
|
||||
|
||||
|
||||
@pytest.mark.parametrize("val", ["0", "false", "no", "", "off"])
|
||||
def test_falsey_server_mode_keeps_gate_strict(monkeypatch, val):
|
||||
monkeypatch.setenv("OMNIVOICE_SERVER_MODE", val)
|
||||
with pytest.raises(HTTPException):
|
||||
require_loopback(_req("10.0.0.5"))
|
||||
@@ -0,0 +1,83 @@
|
||||
"""PyTorch-Whisper backend must work as a standalone fallback (issue #255).
|
||||
|
||||
On machines where WhisperX / faster-whisper can't load cuDNN 8
|
||||
(`cudnn_ops_infer64_8.dll` missing), the PyTorch-Whisper backend should build
|
||||
its own transformers pipeline on demand — without OMNIVOICE_PRELOAD_TTS_ASR=1
|
||||
and without loading the full TTS model.
|
||||
"""
|
||||
import sys
|
||||
import types
|
||||
|
||||
import pytest
|
||||
|
||||
from services import asr_backend as ab
|
||||
|
||||
|
||||
def test_is_available_when_transformers_present():
|
||||
ok, msg = ab.PyTorchWhisperBackend.is_available()
|
||||
assert ok is True
|
||||
assert msg == "ready"
|
||||
|
||||
|
||||
def test_reuses_constructor_pipe_without_building(monkeypatch):
|
||||
sentinel = object()
|
||||
be = ab.PyTorchWhisperBackend(asr_pipe=sentinel)
|
||||
|
||||
def _boom(*a, **k):
|
||||
raise AssertionError("must not build a pipeline when one was passed in")
|
||||
|
||||
# transformers.pipeline is imported lazily inside _ensure_pipe.
|
||||
fake_tf = types.ModuleType("transformers")
|
||||
fake_tf.pipeline = _boom
|
||||
monkeypatch.setitem(sys.modules, "transformers", fake_tf)
|
||||
|
||||
be._ensure_pipe()
|
||||
assert be._pipe is sentinel
|
||||
|
||||
|
||||
def test_lazy_builds_standalone_pipeline(monkeypatch):
|
||||
"""No preloaded pipe → build a standalone transformers ASR pipeline, with no
|
||||
call into the TTS model loader (get_model)."""
|
||||
captured = {}
|
||||
|
||||
def fake_pipeline(task, **kw):
|
||||
captured["task"] = task
|
||||
captured["kw"] = kw
|
||||
return lambda *a, **k: {"chunks": []}
|
||||
|
||||
fake_tf = types.ModuleType("transformers")
|
||||
fake_tf.pipeline = fake_pipeline
|
||||
monkeypatch.setitem(sys.modules, "transformers", fake_tf)
|
||||
monkeypatch.setattr("services.model_manager.get_best_device", lambda: "cpu")
|
||||
|
||||
# Guard: building the standalone pipe must NOT pull in the full TTS model.
|
||||
import services.model_manager as mm
|
||||
|
||||
def _no_get_model(*a, **k):
|
||||
raise AssertionError("standalone ASR build must not call get_model()")
|
||||
|
||||
monkeypatch.setattr(mm, "get_model", _no_get_model, raising=False)
|
||||
|
||||
be = ab.PyTorchWhisperBackend(asr_pipe=None)
|
||||
be._ensure_pipe()
|
||||
|
||||
assert be._pipe is not None
|
||||
assert captured["task"] == "automatic-speech-recognition"
|
||||
assert captured["kw"]["model"] # a concrete model name was chosen
|
||||
|
||||
|
||||
def test_pytorch_asr_model_overridable_via_env(monkeypatch):
|
||||
captured = {}
|
||||
|
||||
def fake_pipeline(task, **kw):
|
||||
captured["kw"] = kw
|
||||
return object()
|
||||
|
||||
fake_tf = types.ModuleType("transformers")
|
||||
fake_tf.pipeline = fake_pipeline
|
||||
monkeypatch.setitem(sys.modules, "transformers", fake_tf)
|
||||
monkeypatch.setattr("services.model_manager.get_best_device", lambda: "cpu")
|
||||
monkeypatch.setenv("OMNIVOICE_PYTORCH_ASR_MODEL", "openai/whisper-small")
|
||||
|
||||
ab.PyTorchWhisperBackend(asr_pipe=None)._ensure_pipe()
|
||||
assert captured["kw"]["model"] == "openai/whisper-small"
|
||||
@@ -37,6 +37,10 @@ def test_system_info_smoke(client):
|
||||
# running version from here so it shows the real version, not a dash (#249).
|
||||
from core.version import APP_VERSION
|
||||
assert body["app_version"] == APP_VERSION
|
||||
# Settings → About → Architecture must reflect the SERVER's machine, not the
|
||||
# client browser's navigator.platform (which showed "Win32" in Docker, #262).
|
||||
import platform as _pf
|
||||
assert body["arch"] == _pf.machine()
|
||||
|
||||
|
||||
def test_health_exposes_version(client):
|
||||
|
||||
Reference in New Issue
Block a user