Bump version: 0.4.3 → 0.4.4

0.4.3 wrapped every inference body (`generate`, `transcribe`,
`create_voice_clone_prompt`) with `force_offline_if_cached(True, …)` to
prevent lazy HF lookups from hanging when the network drops
mid-inference (#462). That trade broke online users: the guard flips
`huggingface_hub.constants.HF_HUB_OFFLINE` globally, so any legitimate
metadata call the library makes during generation (e.g. revision
resolution via `HfApi().model_info`) now raises:

    Cannot reach https://huggingface.co/api/models/Qwen/Qwen3-TTS-…:
    offline mode is enabled.

Hit by multiple users on 0.4.3 within hours of release. The offline
blast radius is much larger than the original hang it fixed.

This reverts the inference-path guards. Load-path guards stay — those
worked fine in 0.4.2 and aren't the source of the regression. The
`force_offline_if_cached` helper itself is unchanged; tests still pass.

The #462 hang (network dropping mid-inference) remains unaddressed by
this commit and will need a targeted fix that doesn't flip a global
flag — most likely per-call timeouts or library-specific
`local_files_only` arguments, not a process-wide env mutation.

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.4.3
+current_version = 0.4.4
 commit = True
 tag = True
 tag_name = v{new_version}

CHANGELOG.md

@@ -7,6 +7,16 @@
 
 ## [Unreleased]
 
+## [0.4.4] - 2026-04-21
+
+Hotfix for a regression in 0.4.3 where generation and transcription could fail outright with "offline mode is enabled" even when the user was online.
+
+### Reliability
+
+- **Inference no longer fails with "offline mode is enabled" while online** ([#524](https://github.com/jamiepine/voicebox/pull/524), reverts the inference-path guards from [#503](https://github.com/jamiepine/voicebox/pull/503)). 0.4.3 wrapped every inference body (`generate`, `transcribe`, `create_voice_clone_prompt`) with a process-wide `HF_HUB_OFFLINE` flip to stop lazy HuggingFace lookups from hanging when the network drops mid-inference ([#462](https://github.com/jamiepine/voicebox/issues/462)). That flag also blocks legitimate metadata calls (e.g. `HfApi().model_info` for revision resolution) so online users started seeing generation fail outright. Inference now runs with the process's default HF state. Load-time offline guards — which weren't the source of the regression — stay in place.
+
+**Known caveat**: users generating without an internet connection may see brief pauses during inference while HuggingFace metadata lookups time out (typically ~30s, after which the library recovers). A proper offline-mode toggle is planned for 0.4.5.
+
 ## [0.4.3] - 2026-04-20
 
 A patch focused on two user-impacting reliability fixes: macOS DMG notarization (unblocks `brew install voicebox` on macOS 15 Sequoia and fixes spurious "app isn't signed" Gatekeeper dialogs on older Intel Macs) and Kokoro Japanese voice initialization on fresh installs.
@@ -638,7 +648,8 @@ The first public release of Voicebox — an open-source voice synthesis studio p
 
 Tauri v2, React, TypeScript, Tailwind CSS, FastAPI, Qwen3-TTS, Whisper, SQLite
 
-[Unreleased]: https://github.com/jamiepine/voicebox/compare/v0.4.3...HEAD
+[Unreleased]: https://github.com/jamiepine/voicebox/compare/v0.4.4...HEAD
+[0.4.4]: https://github.com/jamiepine/voicebox/compare/v0.4.3...v0.4.4
 [0.4.3]: https://github.com/jamiepine/voicebox/compare/v0.4.2...v0.4.3
 [0.4.2]: https://github.com/jamiepine/voicebox/compare/v0.4.1...v0.4.2
 [0.4.1]: https://github.com/jamiepine/voicebox/compare/v0.4.0...v0.4.1

app/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@voicebox/app",
-  "version": "0.4.3",
+  "version": "0.4.4",
   "private": true,
   "type": "module",
   "scripts": {

backend/__init__.py

@@ -1,3 +1,3 @@
 # Backend package
 
-__version__ = "0.4.3"
+__version__ = "0.4.4"

backend/backends/mlx_backend.py

@@ -193,8 +193,6 @@ class MLXTTSBackend:
 
         logger.info("Generating audio for text: %s", text)
 
-        model_name = f"qwen-tts-{self._current_model_size}"
-
         def _generate_sync():
             """Run synchronous generation in thread pool."""
             # MLX generate() returns a generator yielding GenerationResult objects
@@ -220,40 +218,38 @@ class MLXTTSBackend:
                 logger.warning("Regenerating without voice prompt.")
                 ref_audio = None
 
-            # Model is loaded → weights are on disk. Force offline so
-            # lazy tokenizer/config lookups inside mlx_audio don't hang
-            # when the user is disconnected (issue #462).
-            with force_offline_if_cached(True, model_name):
-                # Check if model supports voice cloning via generate method
-                # MLX API may support ref_audio parameter directly
-                try:
-                    # Try with voice cloning parameters if supported
-                    if ref_audio:
-                        # Check if generate accepts ref_audio parameter
-                        import inspect
+            # Inference runs with the process's default HF_HUB_OFFLINE
+            # state. Forcing offline here (previously used to avoid lazy
+            # mlx_audio lookups hanging when the network drops mid-inference,
+            # issue #462) regressed online users because libraries make
+            # legitimate metadata calls during generation.
+            try:
+                if ref_audio:
+                    # Check if generate accepts ref_audio parameter
+                    import inspect
 
-                        sig = inspect.signature(self.model.generate)
-                        if "ref_audio" in sig.parameters:
-                            # Generate with voice cloning
-                            for result in self.model.generate(text, ref_audio=ref_audio, ref_text=ref_text, lang_code=lang):
-                                audio_chunks.append(np.array(result.audio))
-                                sample_rate = result.sample_rate
-                        else:
-                            # Fallback: generate without voice cloning
-                            for result in self.model.generate(text, lang_code=lang):
-                                audio_chunks.append(np.array(result.audio))
-                                sample_rate = result.sample_rate
+                    sig = inspect.signature(self.model.generate)
+                    if "ref_audio" in sig.parameters:
+                        # Generate with voice cloning
+                        for result in self.model.generate(text, ref_audio=ref_audio, ref_text=ref_text, lang_code=lang):
+                            audio_chunks.append(np.array(result.audio))
+                            sample_rate = result.sample_rate
                     else:
-                        # No voice prompt, generate normally
+                        # Fallback: generate without voice cloning
                         for result in self.model.generate(text, lang_code=lang):
                             audio_chunks.append(np.array(result.audio))
                             sample_rate = result.sample_rate
-                except Exception as e:
-                    # If voice cloning fails, try without it
-                    logger.warning("Voice cloning failed, generating without voice prompt: %s", e)
+                else:
+                    # No voice prompt, generate normally
                     for result in self.model.generate(text, lang_code=lang):
                         audio_chunks.append(np.array(result.audio))
                         sample_rate = result.sample_rate
+            except Exception as e:
+                # If voice cloning fails, try without it
+                logger.warning("Voice cloning failed, generating without voice prompt: %s", e)
+                for result in self.model.generate(text, lang_code=lang):
+                    audio_chunks.append(np.array(result.audio))
+                    sample_rate = result.sample_rate
 
             # Concatenate all chunks
             if audio_chunks:
@@ -347,8 +343,6 @@ class MLXSTTBackend:
         """
         await self.load_model_async(model_size)
 
-        progress_model_name = f"whisper-{self.model_size}"
-
         def _transcribe_sync():
             """Run synchronous transcription in thread pool."""
             # MLX Whisper transcription using generate method
@@ -357,11 +351,10 @@ class MLXSTTBackend:
             if language:
                 decode_options["language"] = language
 
-            # Model is loaded → weights are on disk. Force offline so
-            # lazy tokenizer/config lookups don't hang when the user is
-            # disconnected (issue #462).
-            with force_offline_if_cached(True, progress_model_name):
-                result = self.model.generate(str(audio_path), **decode_options)
+            # Inference runs with the process's default HF_HUB_OFFLINE
+            # state — see the comment in MLXTTSBackend.generate for the
+            # regression this revert fixes (issue #462).
+            result = self.model.generate(str(audio_path), **decode_options)
 
             # Extract text from result
             if isinstance(result, str):

backend/backends/pytorch_backend.py

@@ -172,19 +172,17 @@ class PyTorchTTSBackend:
                     # This shouldn't happen in practice, but handle it
                     return {"prompt": cached_prompt}, True
 
-        model_name = f"qwen-tts-{self._current_model_size}"
-
         def _create_prompt_sync():
             """Run synchronous voice prompt creation in thread pool."""
-            # Model is loaded → weights are on disk. Force offline so
-            # lazy tokenizer/config lookups inside qwen_tts don't hang
-            # when the user is disconnected (issue #462).
-            with force_offline_if_cached(True, model_name):
-                return self.model.create_voice_clone_prompt(
-                    ref_audio=str(audio_path),
-                    ref_text=reference_text,
-                    x_vector_only_mode=False,
-                )
+            # Inference runs with the process's default HF_HUB_OFFLINE
+            # state. Forcing offline here (issue #462) regressed online
+            # users whose libraries issue legitimate metadata lookups
+            # during voice-prompt creation.
+            return self.model.create_voice_clone_prompt(
+                ref_audio=str(audio_path),
+                ref_text=reference_text,
+                x_vector_only_mode=False,
+            )
 
         # Run blocking operation in thread pool
         voice_prompt_items = await asyncio.to_thread(_create_prompt_sync)
@@ -227,24 +225,20 @@ class PyTorchTTSBackend:
         # Load model
         await self.load_model_async(None)
 
-        model_name = f"qwen-tts-{self._current_model_size}"
-
         def _generate_sync():
             """Run synchronous generation in thread pool."""
             # Set seed if provided
             if seed is not None:
                 manual_seed(seed, self.device)
 
-            # Model is loaded → weights are on disk. Force offline so
-            # lazy tokenizer/config lookups inside qwen_tts don't hang
-            # when the user is disconnected (issue #462).
-            with force_offline_if_cached(True, model_name):
-                wavs, sample_rate = self.model.generate_voice_clone(
-                    text=text,
-                    voice_clone_prompt=voice_prompt,
-                    language=LANGUAGE_CODE_TO_NAME.get(language, "auto"),
-                    instruct=instruct,
-                )
+            # See _create_prompt_sync comment — inference runs with the
+            # process's default HF_HUB_OFFLINE state (issue #462).
+            wavs, sample_rate = self.model.generate_voice_clone(
+                text=text,
+                voice_clone_prompt=voice_prompt,
+                language=LANGUAGE_CODE_TO_NAME.get(language, "auto"),
+                instruct=instruct,
+            )
             return wavs[0], sample_rate
 
         # Run blocking inference in thread pool to avoid blocking event loop
@@ -342,46 +336,44 @@ class PyTorchSTTBackend:
         """
         await self.load_model_async(model_size)
 
-        progress_model_name = f"whisper-{self.model_size}"
-
         def _transcribe_sync():
             """Run synchronous transcription in thread pool."""
             # Load audio
             audio, _sr = load_audio(audio_path, sample_rate=16000)
 
-            # Model is loaded → weights are on disk. Force offline so
-            # `get_decoder_prompt_ids` and any lazy tokenizer lookups
-            # don't hang when the user is disconnected (issue #462).
-            with force_offline_if_cached(True, progress_model_name):
-                # Process audio
-                inputs = self.processor(
-                    audio,
-                    sampling_rate=16000,
-                    return_tensors="pt",
+            # Inference runs with the process's default HF_HUB_OFFLINE
+            # state — forcing offline here (issue #462) broke online users
+            # whose `get_decoder_prompt_ids` / tokenizer calls issue
+            # legitimate metadata lookups.
+            # Process audio
+            inputs = self.processor(
+                audio,
+                sampling_rate=16000,
+                return_tensors="pt",
+            )
+            inputs = inputs.to(self.device)
+
+            # Generate transcription
+            # If language is provided, force it; otherwise let Whisper auto-detect
+            generate_kwargs = {}
+            if language:
+                forced_decoder_ids = self.processor.get_decoder_prompt_ids(
+                    language=language,
+                    task="transcribe",
                 )
-                inputs = inputs.to(self.device)
+                generate_kwargs["forced_decoder_ids"] = forced_decoder_ids
 
-                # Generate transcription
-                # If language is provided, force it; otherwise let Whisper auto-detect
-                generate_kwargs = {}
-                if language:
-                    forced_decoder_ids = self.processor.get_decoder_prompt_ids(
-                        language=language,
-                        task="transcribe",
-                    )
-                    generate_kwargs["forced_decoder_ids"] = forced_decoder_ids
+            with torch.no_grad():
+                predicted_ids = self.model.generate(
+                    inputs["input_features"],
+                    **generate_kwargs,
+                )
 
-                with torch.no_grad():
-                    predicted_ids = self.model.generate(
-                        inputs["input_features"],
-                        **generate_kwargs,
-                    )
-
-                # Decode
-                transcription = self.processor.batch_decode(
-                    predicted_ids,
-                    skip_special_tokens=True,
-                )[0]
+            # Decode
+            transcription = self.processor.batch_decode(
+                predicted_ids,
+                skip_special_tokens=True,
+            )[0]
 
             return transcription.strip()
 

backend/backends/qwen_custom_voice_backend.py

@@ -186,7 +186,6 @@ class QwenCustomVoiceBackend:
         await self.load_model_async(None)
 
         speaker = voice_prompt.get("preset_voice_id") or QWEN_CV_DEFAULT_SPEAKER
-        model_name = f"qwen-custom-voice-{self._current_model_size}"
 
         def _generate_sync():
             if seed is not None:
@@ -206,11 +205,11 @@ class QwenCustomVoiceBackend:
             if instruct:
                 kwargs["instruct"] = instruct
 
-            # Model is loaded → weights are on disk. Force offline so
-            # lazy tokenizer/config lookups inside qwen_tts don't hang
-            # when the user is disconnected (issue #462).
-            with force_offline_if_cached(True, model_name):
-                wavs, sample_rate = self.model.generate_custom_voice(**kwargs)
+            # Inference runs with the process's default HF_HUB_OFFLINE
+            # state. Forcing offline here (issue #462) regressed online
+            # users whose libraries issue legitimate metadata lookups
+            # during generation.
+            wavs, sample_rate = self.model.generate_custom_voice(**kwargs)
             return wavs[0], sample_rate
 
         audio, sample_rate = await asyncio.to_thread(_generate_sync)

landing/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@voicebox/landing",
-  "version": "0.4.3",
+  "version": "0.4.4",
   "description": "Landing page for voicebox.sh",
   "scripts": {
     "dev": "next dev --turbo",

landing/src/components/TutorialsSection.tsx

@@ -29,10 +29,10 @@ const TUTORIALS: (Tutorial | null)[] = [
 		thumbnail: "/tutorials/kqxqjRsdD5E.jpg",
 	},
 	{
-		id: "yu9QHqOEqqA",
-		title: "This FREE AI Tool Just Destroyed ElevenLabs Voice Cloning (VoiceBox)",
-		author: "Danish Sofi",
-		thumbnail: "/tutorials/yu9QHqOEqqA.jpg",
+		id: "05YBqrWTLQ0",
+		title: "2026年最好的声音克隆工具？Voicebox完整测评：从下载到API调用，附速度对比",
+		author: "Tech指南",
+		thumbnail: "/tutorials/05YBqrWTLQ0.jpg",
 	},
 	{
 		id: "RRRBxNXgeKQ",

package.json

@@ -1,6 +1,6 @@
 {
   "name": "voicebox",
-  "version": "0.4.3",
+  "version": "0.4.4",
   "private": true,
   "workspaces": [
     "app",

tauri/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@voicebox/tauri",
   "private": true,
-  "version": "0.4.3",
+  "version": "0.4.4",
   "type": "module",
   "scripts": {
     "dev": "vite",

tauri/src-tauri/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "voicebox"
-version = "0.4.3"
+version = "0.4.4"
 description = "A production-quality desktop app for Qwen3-TTS voice cloning and generation"
 authors = ["you"]
 license = ""

tauri/src-tauri/tauri.conf.json

@@ -1,7 +1,7 @@
 {
   "$schema": "https://schema.tauri.app/config/2",
   "productName": "Voicebox",
-  "version": "0.4.3",
+  "version": "0.4.4",
   "identifier": "sh.voicebox.app",
   "build": {
     "beforeDevCommand": "bun run dev",

web/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@voicebox/web",
   "private": true,
-  "version": "0.4.3",
+  "version": "0.4.4",
   "type": "module",
   "scripts": {
     "dev": "vite",