chore(release): v0.3.4 (#269)

Patch release. Version bumped across all sources + lock files; [0.3.4] CHANGELOG.

Ships:
- #255 — PyTorch-Whisper backend works as a standalone fallback (no cuDNN 8,
  no OMNIVOICE_PRELOAD_TTS_ASR=1), unblocking Windows+NVIDIA users hitting the
  cudnn_ops_infer64_8.dll error.

Tagging v0.3.4 triggers release.yml (desktop) + docker.yml.

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

.github/workflows/release.yml

@@ -540,7 +540,13 @@ jobs:
 
           # Gather artifact paths per matrix leg's `bundles` (msi/app/dmg/deb/appimage/updater).
           # `find` is portable across all three runners (Git Bash on Windows).
-          mapfile -t ARTIFACTS < <(find "$BUNDLE_DIR" -type f \
+          # NB: macOS runners use /bin/bash 3.2, which has no `mapfile` (a bash 4+
+          # builtin) — using it 127'd this step and dropped the macOS SHA256SUMS
+          # for v0.3.1 and v0.3.2. A `while read` loop is portable to bash 3.2.
+          ARTIFACTS=()
+          while IFS= read -r artifact; do
+            ARTIFACTS+=("$artifact")
+          done < <(find "$BUNDLE_DIR" -type f \
             \( -name "*.dmg" -o -name "*.app.tar.gz" -o -name "*.app.tar.gz.sig" \
                -o -name "*.msi" -o -name "*.msi.sig" \
                -o -name "*.AppImage" -o -name "*.AppImage.sig" \

CHANGELOG.md

@@ -6,6 +6,32 @@ The format is loosely based on [Keep a Changelog](https://keepachangelog.com/).
 Versions track the desktop app (`tauri.conf.json` + `frontend/src-tauri/Cargo.toml`).
 The bundled TTS model package (`pyproject.toml`) is versioned independently.
 
+## [0.3.4] — 2026-06-03
+
+### Fixed
+- **Transcription on Windows + NVIDIA failed with `Could not locate
+  cudnn_ops_infer64_8.dll`.** WhisperX/faster-whisper need cuDNN 8 (via
+  CTranslate2); when the side-loaded `cudnn8_compat` libs are missing, the
+  **PyTorch Whisper** backend (Settings → Models) now works as a drop-in
+  fallback — it builds its own transformers pipeline on PyTorch's cuDNN-9
+  stack, with no CTranslate2/cuDNN-8 dependency and no
+  `OMNIVOICE_PRELOAD_TTS_ASR=1` required. (#255)
+
+## [0.3.3] — 2026-06-03
+
+### Fixed
+- **Settings → About showed the wrong architecture in the Docker/web build.**
+  The "Architecture" row rendered the *client browser's* platform
+  (`navigator.platform` → e.g. "Win32"); it now reports the **server's** CPU
+  architecture from the backend (`platform.machine()`), correct for both the
+  desktop app and Docker. The blank version/GPU/RAM/VRAM in the same report
+  were the loopback-gate 403s already fixed in v0.3.2. (#262)
+
+### CI
+- The release SHA-256 checksum step no longer uses `mapfile` (a bash 4+
+  builtin) — it broke on the macOS runner's bash 3.2 and dropped the macOS
+  `SHA256SUMS` for v0.3.1/v0.3.2. Now portable to bash 3.2.
+
 ## [0.3.2] — 2026-06-03
 
 ### Fixed

backend/api/routers/dub_core.py

@@ -404,12 +404,11 @@ async def dub_transcribe_stream(job_id: str):
             else:
                 from services.asr_backend import get_active_asr_backend
                 try:
+                    # The PyTorch-Whisper backend lazily builds its own pipeline
+                    # when no preloaded `_asr_pipe` is present (issue #255), so it
+                    # no longer needs OMNIVOICE_PRELOAD_TTS_ASR=1 — don't reject it
+                    # here; any load failure surfaces per-chunk with a real cause.
                     _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
                     f = build_failure(e, stage="transcribe-preflight", include_diagnostic=False)

backend/api/routers/system.py

@@ -1,5 +1,6 @@
 import os
 import sys
+import platform
 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,

backend/api/schemas.py

@@ -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 = ""

backend/core/version.py

@@ -12,4 +12,4 @@ from importlib.metadata import PackageNotFoundError, version
 try:
     APP_VERSION = version("omnivoice")
 except PackageNotFoundError:  # non-installed source checkout
-    APP_VERSION = "0.3.2"
+    APP_VERSION = "0.3.4"

backend/services/asr_backend.py

@@ -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

docs/install/troubleshooting.md

@@ -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.

frontend/package.json

@@ -1,7 +1,7 @@
 {
   "name": "omnivoice-studio",
   "private": true,
-  "version": "0.3.2",
+  "version": "0.3.4",
   "type": "module",
   "scripts": {
     "dev": "vite",

frontend/src-tauri/Cargo.lock

@@ -2878,7 +2878,7 @@ dependencies = [
 
 [[package]]
 name = "omnivoice-studio"
-version = "0.3.2"
+version = "0.3.4"
 dependencies = [
  "dirs-next",
  "enigo",

frontend/src-tauri/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "omnivoice-studio"
-version = "0.3.2"
+version = "0.3.4"
 description = "OmniVoice Studio – AI voice cloning & dubbing desktop app"
 authors = ["Debpalash"]
 license = "AGPL-3.0"

frontend/src-tauri/tauri.conf.json

@@ -1,7 +1,7 @@
 {
   "$schema": "../node_modules/@tauri-apps/cli/config.schema.json",
   "productName": "OmniVoice Studio",
-  "version": "0.3.2",
+  "version": "0.3.4",
   "identifier": "com.debpalash.omnivoice-studio",
   "build": {
     "frontendDist": "../dist",

frontend/src/api/types.ts

@@ -60,6 +60,7 @@ export interface SystemInfo {
   app_version?: string;
   python?: string;
   platform?: string;
+  arch?: string;
   device?: string;
   data_dir?: string;
   outputs_dir?: string;

frontend/src/pages/Settings.jsx

@@ -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

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "omnivoice"
-version = "0.3.2"
+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

tests/test_pytorch_whisper_fallback.py

@@ -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"

tests/test_router_smoke.py

@@ -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):

uv.lock

@@ -3058,7 +3058,7 @@ wheels = [
 
 [[package]]
 name = "omnivoice"
-version = "0.3.2"
+version = "0.3.4"
 source = { editable = "." }
 dependencies = [
     { name = "accelerate" },