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ed54347e81 |
Fix runaway MLX Qwen audio chunks (#964)
* fix runaway MLX Qwen audio chunks * test: tighten runaway retry coverage --------- Co-authored-by: huanghua01 <[email protected]> |
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624f6a2140 |
fix(tada): run voice-prompt encode under torch.inference_mode (#955)
Encoder.eval() alone still builds an autograd graph because parameters require grad by default. On 8GB GPUs that ballooned TADA encode VRAM far past the model footprint (issue 890). Wrap the encode forward in inference_mode and add a unit test that asserts the flag is set. Co-authored-by: fooSynaptic <[email protected]> |
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30db291b01 |
fix(kokoro): add missing male Mandarin voices (#788)
Co-authored-by: Siddharth Chintawar <[email protected]> Co-authored-by: Cursor <[email protected]> |
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258b92c9c0 |
fix(offline): remove process-global offline guard from Qwen3 LLM loads (#924)
force_offline_if_cached flips HF_HUB_OFFLINE (env + huggingface_hub constant + transformers._is_offline_mode) process-wide for the duration of a cached LLM load, silently switching every concurrent model download/load on other threads to offline mode. With default capture settings (whisper-turbo STT + Qwen3 refinement + auto_refine) a first run downloads several models concurrently, and a poisoned fetch surfaces as "Can't load feature extractor..." (whisper) or "Unrecognized model ... model_type" (Qwen3) rather than anything mentioning offline mode. These are the last two call sites of the guard — the same pattern was deliberately removed app-wide in #524/#530 after identical failures, and the 0.5.0 LLM backend reintroduced it. LLM loads now run with the process's default HF_HUB_OFFLINE state, matching every other backend (issue #462 precedent). Fixes #841 Claude-Session: https://claude.ai/code/session_011iwL9AyeAWgz2jpgcHxJpC Co-authored-by: Claude Fable 5 <[email protected]> |
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e766c7cbfb |
feat(windows): Native AMD ROCm GPU Acceleration (Resolves #531) (#538)
* feat(windows): add native ROCm support for AMD GPUs Implements native ROCm architecture for Windows. - Adds backend build pipeline for voicebox-server-rocm.exe - Detects AMD GPUs dynamically and routes PyTorch allocations - Adds automatic download and update logic for ROCm dependencies - Refactors UI in GpuPage.tsx and GpuAcceleration.tsx to add AMD flows - Fixes 'Switch to CPU' lock on Windows via Tauri backend_override state - Resolves PyInstaller/rocm_sdk UnboundLocalError silent crashes - Resolves Numba/NumPy 2.x incompatibilities during Qwen3-TTS load - Resolves HF_HUB_OFFLINE Catch-22 for CustomVoice processor caching * fix(rocm): host libs archive under the app release tag, drop offline-load regression Align the ROCm libs download with the CUDA pattern: both the server core and the libs archive are published under the app-version release tag, with the libs content version encoded in the filename only. The previous code fetched libs from a separate rocm7.2-v1 tag, which disagreed with the download test. Also revert the unrelated Qwen CustomVoice changes that wrapped model loading in force_offline_if_cached (not imported — a NameError on load for every platform) and re-added a Base-model cache gate. The inference-path offline guard was deliberately removed previously. * feat(rocm): gate download on AMD detection and persist the backend variant The ROCm download section now only shows when the backend reports an AMD GPU on Windows (new supports_rocm health field, backed by the memoized is_amd_gpu_windows detection that was previously unused), or when ROCm is already downloaded/active. Make the backend override honor a pinned variant: set_backend_override persists the choice to disk so it survives an app restart, start_server reads it back, and a cuda/rocm pin now actually selects that variant instead of always preferring ROCm. A stale pin to a deleted backend self-heals to the default order rather than forcing CPU. Add the web no-op stub for the new method. * chore(rocm): drop incomplete vitest harness for the unused GpuAcceleration component GpuAcceleration.tsx is not routed anywhere (GpuPage is the live settings view), and the added vitest setup referenced testing-library/vitest deps that were not in the lockfile, breaking the web typecheck. Remove the dead component's test and its scaffolding to keep this PR scoped to the ROCm feature. * ci(rocm): add ROCm release-artifact pipeline Mirror the CUDA packaging path for ROCm so the runtime download has artifacts to fetch. scripts/package_rocm.py splits the PyInstaller --rocm onedir into voicebox-server-rocm.tar.gz (core) + rocm-libs-rocm7.2-v1.tar.gz (AMD runtime: HIP DLLs, rocBLAS Tensile data, MIOpen kernel DBs) + rocm-libs.json, matching the names services/rocm.py expects, both under the app-version release tag. The new build-rocm-windows job in release.yml builds on windows-latest/cp312 and lets build_binary.py --rocm pull the official AMD Radeon wheels. The file classifier can't be validated against a real AMD build on CI, so it has unit coverage (test_package_rocm.py) against a synthetic onedir layout. The prefixes/dir markers may need a tweak after the first real build on AMD hardware — the packager hard-fails loudly if it classifies zero ROCm files. --------- Co-authored-by: Jamie Pine <[email protected]> |
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7df366d0c8 |
feat: 0.5.0 Capture release — dictation, MCP, personalities (#544)
* feat(capture): dictation, personalities, 0.5.0 Ships the Capture release end to end. Global-hotkey dictation with synthetic paste into the focused app on macOS and Windows, an on-screen pill across recording / transcribing / refining, customizable push-to- talk and toggle chords, and an accessibility-permission prompt scoped to Settings → Captures with inline re-check feedback. Voice profiles gain optional personalities that power compose / rewrite / respond actions via a local Qwen3 LLM — shared with refinement, so there is one local LLM in the app, not two. Refinement hardened with deterministic Whisper-loop collapse before the LLM sees the transcript, per-capture flag snapshots for re-runs, and a ten-transcript evaluation harness across every bundled refinement size. Version bump 0.4.5 → 0.5.0. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * feat(mcp): local MCP server exposes voicebox.* tools to AI agents Mounts FastMCP at /mcp (Streamable HTTP) so Claude Code, Cursor, Windsurf, and the VS Code MCP extensions can call voicebox.speak, voicebox.transcribe, voicebox.list_captures, and voicebox.list_profiles against the running Voicebox server. Backend - new backend/mcp_server package (tools, middleware, profile resolve, pub/sub events); named mcp_server to avoid shadowing the installed mcp PyPI package FastMCP imports internally - app.py migrated from @app.on_event to lifespan= so FastMCP's session manager cohabits with Voicebox's startup/shutdown - new MCPClientBinding table + /mcp/bindings CRUD; ClientIdMiddleware reads X-Voicebox-Client-Id into a ContextVar and stamps last_seen_at - profile resolution precedence: explicit -> per-client binding -> capture_settings.default_playback_voice_id - POST /speak REST wrapper for non-MCP callers (shell, ACP, A2A) - GET /events/speak SSE broadcasts speak-start / speak-end so the pill surfaces agent-initiated speech - backend/mcp_shim proxy (plain httpx) for stdio-only MCP clients - PyInstaller spec updates + new --shim build target (~18 MB) Frontend - Settings -> MCP page with HTTP / stdio / claude-mcp-add copy snippets, default voice picker, per-client bindings table, connection status - useMCPBindings, useSpeakEvents hooks - CapturePill gains 'speaking' state; DictateWindow subscribes to SSE and emits dictate:show so the Rust side surfaces the pill window Native - tauri.conf.json externalBin now includes voicebox-mcp - show_dictate_window helper + dictate:show listener in main.rs - (also in this commit: InputMonitoringGate UX, hotkey_monitor tweaks, landing footer/navbar updates, new overview docs for captures / dictation / mcp-server / voice-personalities) Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * feat(mcp): Rust-owned speaking pill with self-contained audio playback The pill window now surfaces for agent-initiated speech without main-window involvement. Rust subscribes to /events/speak via a tokio task + reqwest streaming body (speak_monitor.rs), shows the pill, and forwards events to the dictate webview over Tauri's event bus. The pill plays audio via a plain HTMLAudioElement and emits dictate:hide when playback ends. The pill stays hidden through the ~1 s generation wait and only surfaces when audio actually starts, with the counter armed at that moment. Fixes a shared-dict mutation in mcp_server/events.publish() that caused the second subscriber (Rust speak_monitor) to receive `event: message` instead of named speak-start/speak-end frames. Also teaches the speak_monitor parser to handle CRLF framing (sse-starlette default). Main-window AudioPlayer now skips autoplay for source in {mcp, rest} to avoid double-play when both windows are alive. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * readme and dev script * feat(capture): gate global hotkey on dictation readiness checklist Stops the "stuck pill" failure where pressing the chord with missing STT/LLM models triggers a recording that has nowhere to land. The hotkey now stays disarmed until every gate (models downloaded, Input Monitoring + Accessibility granted) is green; the empty-state checklist in CapturesTab surfaces each unmet gate with a one-click action and auto-arms the chord once everything turns green. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * color * model download status * progress * personality: bool API, i18n across the app - Collapse intent tri-state (respond/rewrite/compose) to `personality: bool` on /generate, /speak, and voicebox.speak. Drop respond entirely; keep compose as a standalone button via /profiles/{id}/compose. Remove /rewrite, /respond, and /speak profile endpoints. - FloatingGenerateBox: Wand2 persona toggle + Dices compose button appear when the selected profile has a personality. ProfileCard badges Wand2 alongside the effects Sparkles. - MCP bindings: default_intent column → default_personality: bool. Migration drops the legacy column. - i18n: en / ja / zh-CN / zh-TW translation files filled out and wired through the capture, server, and profile UI. ```ts voicebox.speak({ text: "Deploy complete.", profile: "Morgan", personality: true, // rewrite through the profile's personality LLM }); ``` * i18n: GenerationPage sidebar copy * fix: BOOL import for windows crate 0.62 BOOL moved from Win32::Foundation to windows::core in 0.62. Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]> * fix(capture): layout-aware V keycode for synthetic paste on macOS macOS apps match Cmd+V against the layout-translated character via NSMenu key equivalents, so posting kVK_ANSI_V (= 9, the QWERTY V position) on Dvorak produces Cmd+. and never triggers Paste. New keyboard_layout module resolves the active layout's V keycode via TISCopyCurrentKeyboardLayoutInputSource + UCKeyTranslate, caches it in an AtomicU16, and refreshes on kTISNotifySelectedKeyboardInputSourceChanged. All TIS calls run on the main thread (init from Tauri setup; observer callback delivered to the main runloop); synthetic_keys::send_paste reads the cached value once per paste. Falls back to kVK_ANSI_V when resolution fails or the active input source carries no Unicode key layout data. Windows is intentionally left on hardcoded VK_V — SendInput delivers WM_KEYDOWN with wParam = VK_V to the target regardless of the active layout, which is why `Send "^v"` works for AutoHotkey on Dvorak Windows. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(capture): cooperative app activation for synthetic paste on macOS 14+ macOS 14 deprecated NSRunningApplication.activateWithOptions: in favour of a cooperative-activation pattern: the caller first yields activation rights to the target, then the target activate()s against the tightened Sonoma foreground rules. Without the yield, activate() on 14+ sometimes silently fails or only bounces the dock icon — the exact "paste lands in the wrong app" symptom we were previously one API break away from. activate_pid now discovers the 14+ selector via respondsToSelector: and branches: on 14+ it yieldActivationToApplication:'s from NSRunningApplication.current then calls -activate on the target; on 11–13 it stays on -activateWithOptions: (still the only option). Both branches propagate the BOOL return — if activation is refused we error out before clobbering the clipboard instead of silently proceeding. The respondsToSelector: result is cached in a OnceLock so the probe isn't repeated on every paste. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(capture): conditional clipboard restore + always-attempt on paste failure Two bugs in paste_final_text' clipboard handling: 1. Restore was unconditional. If the user ⌘C'd in the target app during the 400 ms paste-consume window — or a clipboard history tool (Paste, Pastebot, Maccy) or Universal Clipboard sync snapshotted our staged text — the blind restore overwrote their newer content with the pre-paste snapshot, silently losing user data. 2. send_paste' errors were propagated with ? before the restore, so a CGEventPost / SendInput failure left the user's clipboard stuck on the transcript. Fix folds both into one pattern: capture the post-write change count, re-read it after paste-consume, restore only when they match (plus treat a change-count read failure as "unknown, don't overwrite"). Isolate send_paste's error so the restore runs regardless of paste success, then propagate the paste error after. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * chore(deps): pin rdev to jamiepine/rdev fork Upstream Narsil/rdev has shipped no release since 2023-06 (crates.io still serves 0.5.3), so the Sonoma main-thread fix we depend on — PR #147, applied at hotkey_monitor.rs:184 — is only reachable via a git pin. A pin to a third-party repo breaks the build whenever the remote force-pushes, renames, or is taken down, and Cargo does not durably cache git-dep archives the way it does crates.io tarballs. Forking to jamiepine/rdev at the same SHA removes that failure mode without changing crate behavior and gives us a place to cherry-pick future OS-compatibility fixes on our own timeline. The SHA was verified to exist on the fork before re-pinning. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(mcp): idle timeout + escalating backoff for speak-SSE monitor Two reliability gaps in the /events/speak subscriber: 1. resp.chunk().await had no idle timeout. A backend that accepts the TCP connection but stops producing frames (deadlocked SSE endpoint, zombie process) would block the task forever without reconnecting. The pill window would never surface for agent-initiated speech and there would be nothing to log. Backend emits a `:ping` heartbeat every 15 s, so 45 s without any data is now treated as a dead stream — the task errors out and the reconnect loop takes over. 2. Flat 2 s backoff escalates nowhere. Logs fill with reconnect lines when the backend is down for minutes, and a backend that accepts + immediately closes connections (no data) spins the loop tightly. Backoff now escalates 500 ms → 30 s on unproductive rounds and resets only when at least one frame arrives (the connection was genuinely productive, not just accepted). Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(refinement): character-level loop collapse + pytest coverage The word-level pass catches single-word Whisper loops ("URL URL URL…") but misses two common hallucination patterns the PR had to claim as "edge cases": 1. Multi-word English loops — "thanks for watching thanks for watching…" × 6 sails through because no two consecutive tokens are identical after text.split(). 2. CJK loops — "謝謝觀看" × 7 sails through because text.split() returns a single unsplit token for the whole loop (no whitespace between characters). Add a character-level second pass: a non-greedy regex finds any 2–60 char substring that repeats min_run+ times immediately after itself and strips the run. The 2-char floor keeps emphasised single-letter runs ("wooooooow") intact. The 60-char ceiling covers every observed Whisper tail hallucination ("Please like and subscribe to my channel.", "Subtitles by the Amara.org community") while staying short enough that coincidental long-phrase repetition in legitimate speech doesn't hit the threshold. Whitespace normalisation only runs when the pass actually stripped something, so untouched transcripts keep their original spacing. New test_refinement_collapse.py gives the pre-processor its first deterministic unit-test coverage: 17 tests pinning the word-level legacy behaviour plus the new multi-word English / CJK / Japanese / emphasis-preservation cases. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(db): graceful fallback when SQLite < 3.35 on MCP bindings migration SQLite gained ALTER TABLE … DROP COLUMN in 3.35 (Mar 2021). Production PyInstaller builds bundle Python 3.12 which links to SQLite 3.40+ so that path is always safe, but a dev running the backend directly on Ubuntu 20.04 (3.31) or Debian 11 (3.34) would crash on first startup trying to drop the legacy default_intent column. Add _supports_drop_column(engine) — returns True on non-SQLite dialects (Postgres / MySQL have supported DROP COLUMN for decades) and gates on the runtime sqlite_version for SQLite. When unsupported, log a warning and leave the unused column in place: SQLAlchemy only maps declared columns, so a stray default_intent column does no reads or writes and can't interfere with runtime behaviour. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(mcp): correct lifespan shutdown order — drain MCP before unloading models The inline lifespan ran _run_shutdown inside the MCP context, so the TTS / Whisper / LLM models were unloaded *before* FastMCP's __aexit__ got a chance to cancel its in-flight session tasks. Any MCP request mid-generate at shutdown time would crash on "model unloaded" instead of receiving a clean session-cancelled error. Rewire via compose_lifespan (which was already defined in mcp_server.server for exactly this purpose but never used): AsyncExitStack enters factories in order and exits in LIFO, so MCP teardown fires first — cancelling sessions — and _run_shutdown runs after nothing is holding the models. Smoke test shows the log order flipped as expected: Ready StreamableHTTP session manager started ... running ... StreamableHTTP session manager shutting down ← was last, now first Voicebox server shutting down... ← was first, now last As a side benefit, _run_shutdown is now paired with _run_startup via try/finally inside voicebox_lifespan, so a partial startup (models half-loaded, MCP __aenter__ fails) still unloads whatever was loaded instead of leaking it to process exit. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(mcp): stamp last_seen_at on /speak too + tighten path predicate POST /speak is a REST wrapper around voicebox.speak for agents that don't talk MCP (shell scripts, ACP, A2A). It reads X-Voicebox-Client-Id and uses it for the same per-client profile resolution + default personality lookup the MCP tool does (speak.py:39-64), so its callers are first-class clients — but the ClientIdMiddleware only stamped last_seen_at on /mcp* paths. REST speak callers showed up as "never seen" in Settings → MCP despite actively acting on their bindings. Widen the stamp predicate to an explicit ("/mcp", "/speak") prefix list, and require a path boundary on match so future routes named /mcpfoo or /speakers don't silently inherit the stamp via the prefix. New test_client_id_middleware.py pins the scope with 17 parametrised cases (both the allowed set and the overlap cases that must not match). Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * feat(captures): scrubbable WaveSurfer player for capture detail view Replace the placeholder fake-waveform + play button in CapturesTab's audio card with a real CaptureInlinePlayer (wavesurfer.js). The player renders the actual waveform, lets users scrub through the clip, and shows a proper current/total timestamp pair in place of the duration-only label. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * feat(ui): persist selectedProfileId across sessions Wrap useUIStore in zustand/middleware's persist under the key voicebox-ui. partialize only selectedProfileId so volatile UI state (dialog open flags, form drafts, engine/voice pickers, sidebar) stays in-memory as before — but reopening the app no longer loses whichever profile the user was last working with. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * feat(captures): mirror readiness checklist into the settings sidebar The six-gate checklist only rendered in the CapturesTab empty state, so a user already on the settings page had no single surface showing which gate was red — the inline InputMonitoringNotice covered one, the model pickers covered another, and Accessibility was only hinted at by the auto-paste toggle. Mirror the same component into the right sidebar of the settings page so every gate (STT model, LLM model, Input Monitoring, Accessibility, plus the hotkey toggle in the main column) is always visible while the user configures dictation. New compact prop on DictationReadinessChecklist drops the centered header and empty-state max-width so it fits the 280 px sidebar next to the existing About / Differences blocks. Callers in compact mode own the heading — CapturesPage reuses the existing captures.readiness.title key (present in en / ja / zh-CN / zh-TW already) as an h3 matching the sibling sidebar sections. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * feat(captures): move sidebar checklist below differences + hide when all green Two small follow-ups to the sidebar checklist placement. Move it below the What's different section so the sticky top of the sidebar stays the page's narrative context (About → differences) and the checklist reads as a status panel rather than preamble. Gate the whole block on !readiness.allReady so once every gate is green the sidebar drops back to just About + What's different — no value in real estate full of checkmarks. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(captures): refetch readiness immediately after STT/LLM model swap useCaptureSettings updated its own cache optimistically but never invalidated ['capture-readiness'], so for up to 5 s (the poll interval) after switching stt_model or llm_model the checklist kept showing the previous model's ready/missing state. The backend endpoint resolves the model live on each call — it was just the frontend cache that lagged. Invalidate in onSettled only when the patch touched a model field, so unrelated updates (chord keys, toggles) don't pay for a refetch. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(captures): hide macOS-only copy when running on Windows / Linux Two surfaces leaked macOS-specific copy onto other platforms: 1. The Input Monitoring + Accessibility rows in the readiness checklist rendered everywhere. On Windows/Linux the Rust permission stubs return true, so the rows showed as permanent green checkmarks with copy like "macOS allows Voicebox to detect your global shortcut." — nonsense when you're on Windows. Gate both rows on a userAgent-based isMacOS check so they only render where the underlying TCC permission actually exists. 2. The global-shortcut setting description ended with "macOS will ask for Input Monitoring permission the first time you turn this on." That sentence rendered on every platform. The readiness checklist already surfaces the TCC requirement at the right moment on macOS, so the description doesn't need the platform note — drop it from en / ja / zh-CN / zh-TW. Other macOS strings (AccessibilityNotice, InputMonitoringNotice, their "stillMissing" hints) are already gated behind the Rust permission booleans returning false, which never happens on Windows/Linux, so they stay inert without further changes. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * feat(capture): swap the rdev fork for keytap 0.2, delete local chord state machine Dep swap: - Drop the git-pinned jamiepine/rdev fork we were carrying since the upstream crate is abandoned. - Depend on keytap 0.2 from crates.io — our own cross-platform global keyboard tap crate. Clean shutdown via Drop, Sonoma-safe by design (no TSMGetInputSourceProperty calls off the main thread, so `set_is_main_thread(false)` is gone), and properly versioned. Chord engine rewrite: - Delete hotkey_monitor.rs's internal Chord state machine (Match enum, KeyEvent enum, step()/classify() methods, associated unit tests). keytap's ChordMatcher subsumes it: Momentary chord for PTT, add_toggle() for Toggle-to-talk, longest-match resolution, sticky-end for Toggle. Net: -80 LOC in hotkey_monitor.rs; the remaining module is the dispatcher loop + Effect→Tauri translation. - Preserve the PTT→Toggle "RestartRecording" upgrade signal. keytap emits End(PTT)+Start(Toggle) atomically (same Instant) when the held set upgrades from a shorter chord to a longer superset. The dispatcher peeks at the matcher with a 5 ms recv_timeout after any End and coalesces the pair into Effect::RestartRecording so the frontend still gets the "discard the transition-moment audio" signal instead of an unrelated Stop+Start pair. - HotkeyMonitor::update_bindings now actually tears down the tap on empty bindings instead of leaving an idle CGEventTap around. New bindings rebuild the matcher and the dispatcher thread from scratch. key_codes.rs: - Rewrite the browser-code → Key table against keytap's cleaner Key variant names (`A`..`Z` not `KeyA`..`KeyZ`, `Digit0`..`Digit9` not `Num0`..`Num9`, `ArrowUp` not `UpArrow`, `AltLeft`/`AltRight` instead of `Alt`/`AltGr`, `Period` not `Dot`, …). On-disk chord string format (W3C `KeyboardEvent.code` identifiers) is unchanged, so capture_settings rows written before the swap round-trip identically. Legacy aliases (`Alt`, `AltGr`, `Num0`, `UpArrow`, `Dot`, …) kept for forward-compat on old rows. main.rs / input_monitoring.rs: - Update the few doc comments that referenced `rdev::listen` to describe keytap's Tap; no behavioural change. - build_chord_bindings now imports from keytap::Key. - enable_hotkey / disable_hotkey / update_chord_bindings reach into HotkeyMonitor via &mut since apply()/update_bindings() now mutate. Tests live in keytap now (22 chord-related tests in keytap 0.2, including the PTT→Toggle upgrade scenario that used to be tested in hotkey_monitor.rs). Voicebox's hotkey_monitor.rs is thin enough that local testing would be trivia. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * chore(deps): bump keytap 0.2 → 0.4 for macOS modifier-events fix 0.2 read CGEventFlags via CGEventGetIntegerValueField(event, 0x81), which is not a valid CGEventField id — macOS silently returned 0, so FlagsChanged events produced no KeyDown / KeyUp for any modifier key and the PTT / toggle chords never armed on macOS. 0.4 uses the documented CGEventGetFlags(event) API. 0.3 (tracing / serde / Fn / IntlBackslash) is picked up as a free consequence; no API surface we depend on changed. * perf(captures): stop polling readiness once both models are green useQuery was firing GET /capture/readiness every 5s forever, and also on every window focus. Once stt.ready and llm.ready are both true the answer can only change when the user swaps a model in settings, and useSettings already invalidates the query on that path — the polling was pure noise. Gate both refetchInterval and refetchOnWindowFocus on "not fully ready" so we fall silent once the checklist is green. * feat(ui): theme settings, stories polish, track editor restructure - add dark/light/system theme with persisted choice + OS change listener - restyle stories sidebar (search, item layout, border) to match captures - move floating generate box to right column of stories, add top fade mask - story track editor: sticky track labels aligned via flex rows, custom scrollbar with left/right zoom handles - capture pill light mode pass, fix inline waveform progress color - pull mcp_server hidden imports into the pyinstaller spec - notarization doc draft * fix mlx llm bundling * feat(ui): shared ListPane primitive + misc polish ListPane is a compound component (Header / TitleRow / Title / Actions / Search / Scroll) that owns the relative wrapper, faded right divider (50px top fade), top scroll mask, and absolute-positioned header used by every list-detail tab. Wires up CapturesTab, StoryList, and EffectsList. EffectsTab gets -mx-8 / pr-8 to match the edge-to-edge layout used elsewhere. Other changes: - MCPPage: native <select> → shadcn <Select> for default voice and per-binding voice pickers - Button outline variant: add hover:border-accent - Drop hover:text-destructive from trailing delete buttons (HistoryTable, GpuAcceleration, GpuPage, EffectsChainEditor, EffectsDetail) - HistoryTable empty state moved behind t('history.empty') - StoryContent scroll padding pt-14 → pt-16 - backend health reports the captures dir - landing CapturesMockup: "Send to" → "Export" with Download icon - CHANGELOG: drop [Unreleased] personality section * fix(captures): Play As autoplay + default voice + orphan recovery - Hand /generate ids to the global SSE watcher so playback fires on completion. The mutation onSuccess was checking audio_path on a queued row, which is always empty — autoplay never ran. - Bind the Play As voice selection to capture_settings.default_playback_voice_id, kept in sync with the Settings → Captures and Settings → MCP pickers. Picking from the split-button dropdown writes back to settings. - Extract AudioBars from HistoryTable into a shared component; use it for the Play As generating state in place of Loader2. - Stop the active-state hover from flashing white text when the button is in its lighter accent/10 fill. - Drop the gradient avatar swatches from the Settings → Captures voice dropdown. - Backend: when the gen worker exits without writing a terminal status (e.g. SQLite lock racing the failed-status write inside its own exception handler), the cancel endpoint now flips the row to failed instead of 409-ing. Worker also force-fails on its way out as a belt-and-suspenders. * fix(captures+chord): Stop button stops, ChordPicker accepts shorter chords Two unrelated correctness bugs caught in PR review: - The Play As "Stop" button was wired to handlePlayAs() unconditionally, so clicking it during playback kicked a fresh generation instead of halting. Now pauses the player when the click came from the main button while playbackState is 'playing'. Picking a different voice from the dropdown still kicks a new generation as before. - ChordPicker tracked the peak set of held keys but seeded the peak from initialKeys, so a user who opened the picker with a 3-key chord saved couldn't replace it with a 2-key chord — the candidate length never beat the seed. The peak now resets on the first press of a fresh sequence (when no keys were held immediately prior), then grows monotonically within that hold. * fix(settings): honor explicit null on nullable fields, ignore on the rest Routes were calling model_dump(exclude_none=True), which drops every client-sent null before it reaches the service. The service then layered on its own `if value is not None` guard. Net effect: setting a nullable column back to null was a no-op — the MCPPage default-voice picker sends null when the user picks "no default" and the row was silently keeping whatever was there before. Switched the routes to exclude_unset=True so absent fields stay absent but explicit nulls survive the dump, and centralised the per-field nullability check in the service. The check inspects the SQLAlchemy column metadata so non-nullable columns (stt_model, llm_model, the chord key lists) still drop nulls instead of crashing the request, while default_playback_voice_id can finally be cleared. * fix(captures): clean up audio files when create_capture fails The create flow wrote raw audio (and a transcoded .wav for non-wav sources) to data/captures before the DB row was committed, so any failure between the write and the commit — a webm that decoded to a 0-length array, a whisper model that errored mid-transcribe, a SQLite contention on the commit — left the audio on disk with nothing pointing at it. Over enough flaky uploads the directory grows without bound. Now every path written before the commit is tracked in a list, and the whole stretch from the first write to db.commit() runs inside a try/except that unlinks each tracked file on raise and re-raises. The transcode branch removes the raw file from the cleanup list only when the unlink actually succeeds, so an OSError on the raw-path delete still hands cleanup the original blob to retry. * fix(mcp): restrict voicebox.transcribe(audio_path=...) to loopback audio_path mode took any absolute filesystem path and returned its decoded contents as transcribed text with no caller verification beyond the existence/size checks. The X-Voicebox-Client-Id middleware records the header but never rejects an absent or fake one, so a Voicebox bound to 0.0.0.0 (the documented "remote access" mode) was effectively an unauthenticated arbitrary-local-file read primitive. The middleware now stashes the request's remote address in a ContextVar alongside the existing client_id, and audio_path mode refuses anything that doesn't parse as a loopback address (IPv4 127.0.0.0/8, IPv6 ::1). audio_base64 mode is unchanged — that path was always bounded to bytes the caller already has. Loopback callers (the Tauri webview, local CLI scripts, MCP clients on the same machine) keep working. Remote callers now have to send the audio over the wire if they want it transcribed. * fix: PR review nits — response shape, landing copy, form reset - /llm/generate's "model is downloading" branch was raising HTTPException(202, detail={...}), which wraps the payload in {"detail": ...} and forces clients to parse a success status as if it were an error. Switched to JSONResponse so the payload sits at the top level. - The landing page's "Language Models" card advertised "Qwen 3.5" with sizes 4B/2B/0.8B; we ship Qwen3 at 0.6B/1.7B/4B. Aligned to what's actually in the binary. - ProfileForm's discard-draft button reset the form without touching `personality` or `avatarFile`, so stale persona text and an attached avatar would survive the discard. The other three resets in the file already include both fields — this brings the discard path in line. * perf(mcp): move last_seen_at stamp off the request path ClientIdMiddleware was running the SQLAlchemy SELECT/INSERT/UPDATE/COMMIT inline on the event loop after every /mcp/* and /speak request. SQLite serialises writes, so concurrent MCP traffic queued behind the stamp write — the response sat waiting on a side-effect that the client never needs in band, and SSE streams would stall briefly per request. The middleware now hands the stamp to asyncio.to_thread via a fire-and- forget create_task so the response returns immediately and the write runs on the default executor. A module-level set keeps strong refs to in-flight tasks (per asyncio docs) so the GC can't collect them mid- write. The fallback path runs the stamp inline if no loop is available (tests/oddball callers) rather than silently dropping it. * fix(dictate): force-dismiss the speaking pill when SSE never comes back The pill subscribed to /generation/{id}/status to know when to start playback, but EventSource.onerror was a no-op — auto-reconnect was the intended recovery for transient drops. The gap: if the backend deletes the gen row mid-flight or the connection silently dies in a way the browser keeps retrying without ever getting a status event, the pill sits in 'speaking' forever and the user has no way to clear it. Added a 60-second hard cap that arms when the SSE opens and clears the moment any real status event lands. If it fires while the pill is still on the same id and audio never started, it force-dismisses. Same idea as the existing post-speak-end 15s grace, but covers the case where the backend never says anything at all. * fix: i18n cleanup + readiness checklist effect cadence + ChordPicker shadow - DictationReadinessChecklist was constructing downloadByModel as a fresh Map every render and listing it in the cleanup effect's deps. With the 1 s polling cadence and arbitrary parent rerenders the effect ran more often than it needed to. Memoised the Map on activeTasks; the effect now keys off the memo's identity. - zh-CN persona tooltipActive/ariaLabelActive matched their inactive twins byte-for-byte ("以人物设定朗读"). The other locales differentiate the active state with a -ing / -中 suffix; zh-CN now reads "正以人物设定朗读" when active. - personalityPlaceholder was a ~290-character paragraph that doubled as both the example text and the explanation, repeating most of what personalityHint already said. Trimmed to the example only and folded the explanation + leave-blank consequence into the hint, across all four locales. - Refinement model size keys were size06 / size17 / size4. Renamed the 4B variant to size40 so the decimal padding is consistent. - ChordPicker's open-effect bound a window.setTimeout id to a local `t`, shadowing the i18n `t` from useTranslation. Renamed to timeoutId. * perf(settings): persist generation sliders on release, not per pointer-move Both sliders on the generation settings page were calling update() — which is a React Query mutation that PATCHes /settings/generation — inside onValueChange. Dragging the chunk-limit slider from 800 to 3000 fired a request per pointer-move pixel, and a mid-drag failure plus optimistic rollback would leave persisted state visibly out of sync with the thumb position. Local state now mirrors each slider during a drag and the persist happens once on Radix's onValueCommit (pointer-up / keyboard-release). useEffects keep the local state in sync if the persisted value changes out-of-band — another window editing the same setting still updates the slider position cleanly. * chore(backend): Ruff lint pass — deprecated APIs, exception leaks, dead patterns Mechanical sweep of items called out in the PR review: - qwen_llm_backend: AutoModelForCausalLM.from_pretrained(torch_dtype=…) is deprecated in transformers ≥4.41 in favor of dtype=. Renamed. - routes/llm: try/except around backend.generate() raised HTTPException(500, detail=str(e)) which leaks stack traces / paths to clients and trips Ruff B904. Now logs the original exception server-side and hands the client a generic message; chained via `from e` to preserve traceback context. - mcp_bindings + mcp_server/context: datetime.utcnow() is deprecated since 3.12. Switched the two assignment sites to datetime.now(timezone.utc). The schema-level `default=datetime.utcnow` defaults in database/models.py are left for a later schema-aware pass. - routes/generations: `logger = …` sat between two import blocks (Ruff E402). Moved below imports. - mcp_server/server + tests/test_refinement_samples: typing.Callable / typing.Iterable have been preferred-via collections.abc since 3.9 (Ruff UP035). - routes/events: `except asyncio.TimeoutError` aliases plain `TimeoutError` since 3.11 (UP041). - services/captures: hoisted WHISPER_NATIVE_FORMATS to module scope (was a function-local UPPER_SNAKE that tripped N806) and replaced the raw_path.unlink try/except OSError-pass with contextlib.suppress (SIM105). Semantic equivalence preserved — written_files.remove(raw_path) still only runs when unlink succeeds because it sits inside the suppressed block after the unlink call. - database/migrations: hoisted the duplicate `import sqlite3` from inside two helper bodies to a single module-level import. * feat(stories): regenerate action on clips and the chat list dropdown The track editor's clip toolbar now has a regenerate icon next to Delete; clicking it kicks a fresh take of the selected clip's underlying generation through the same /generate/{id}/regenerate path the History table uses, and pushes the id into the global pending set so the SSE watcher picks it up. The chat list's per-item dropdown gets the same action between Play-from-here and Remove. Translation keys added under storyContent.itemActions / storyContent.toast across all four locales. * feat(stories): import external audio into the timeline (drag-drop + picker) You can now drop a music file onto the story content area or pick one through the new "Import audio" button in the add-clip popover. Both call POST /generate/import which writes the file to data/generations/<id>.<ext>, probes duration via librosa, and inserts a Generation row pointing at a singleton "Imported Audio" profile (created lazily on first import). The existing addStoryItem flow takes over from there — the timeline doesn't care that the row didn't come out of TTS. Engine field on the row is "import"; it's surfaced on StoryItemDetail so the chat list shows a music icon instead of the (missing) profile avatar and both the dropdown and the track-editor toolbar hide the Regenerate action — there's nothing to regenerate. Accepted formats: wav/mp3/flac/ogg/m4a/aac/webm, capped at 200 MB. Translation keys added across en/ja/zh-CN/zh-TW. * fix(audio): serve real Content-Type so imports decode in WaveSurfer /audio/{id} and /audio/version/{id} hardcoded media_type="audio/wav" on the FileResponse. That was a no-op when every generation came out of TTS (everything on disk was a .wav anyway), but imported audio keeps its source format — .mp3 / .m4a / .ogg — and the WaveSurfer MediaElement backend uses an <audio> tag that checks Content-Type before letting the clip play, so an MP3 announced as audio/wav silently failed to load. Both endpoints now derive the type via mimetypes.guess_type and fall back to audio/wav for unknown suffixes. Download filenames also keep the real extension instead of always saying ".wav". * feat(stories): zoom bar bounds tracked to project length, default 60s scope The track editor's zoom was clamped to a hardcoded [10, 200] pixels-per-second range, which had no relationship to the project — on a 4-minute story a "max zoom out" of 200 px/s still required scrolling, and on a 5-second story you could zoom all the way in to where every clip was a tiny sliver. Reframed the bounds in the unit the user actually thinks in: how many seconds of timeline are visible at once. Min scope is 10 s (most zoomed in), max scope is the entire project, and the default lands on a 60 s scope (or the full project, whichever is shorter) once the editor measures its visible track width on first mount. The pixels-per-second value still lives in component state (because every downstream calculation already uses it) but minPps/maxPps are computed from `containerWidth − LABEL_COL_WIDTH` and the project's effective duration, so the +/- buttons and the edge-drag handles on the scrollbar all clamp to bounds that move with the project. Re-clamping fires whenever those bounds shift — adding a long clip or resizing the window pulls the current zoom inside the new range instead of leaving the user parked outside it. * fix(stories): show the source filename on imported clips Imports were rendering as "Imported Audio" everywhere because every import points at the singleton voice profile. The filename was already being stored on the generation row (in the `text` field), so the chat item title and the timeline clip label now read from `text` when `engine === 'import'` and fall back to the profile name otherwise. The chat item also drops the language pill (always "en" on imports — not informative) and skips the transcript textarea since imports have no spoken text to show. * fix(stories): round split_time_ms before posting handleSplit was sending currentTimeMs - item.start_time_ms straight to the backend, which rejects it because StoryItemSplit.split_time_ms is typed as int and the playhead's currentTimeMs is a float (it's driven from HTMLAudioElement.currentTime, which carries sub-millisecond precision). Pydantic surfaced the mismatch as "Input should be a valid integer, got a number with a fractional part" and the toast read "Failed to split clip". Math.round at the call site, matching what the trim and move handlers already do. * feat(stories): per-clip volume control on the timeline Each story item now carries a volume column (linear gain, default 1.0, clamped 0.0–2.0 server-side). New PUT /stories/{}/items/{}/volume route + useUpdateStoryItemVolume hook + a Volume2 icon in the clip-edit toolbar that opens a popover with a 0–200% slider. Local slider state drives the visual during a drag; the persist fires once on onValueCommit, mirroring the generation-page slider pattern. Web Audio playback inserts a per-clip GainNode between source and master so volume changes apply live without re-decoding the buffer (source -> clipGain -> masterGain -> destination). Server-side mixdown in export multiplies the trimmed clip by its volume before summing into the timeline. Split + duplicate carry the volume forward to the new clips so trimming a faded section keeps the level you set. Migration adds the volume column with default 1.0 so existing rows read as full volume. * fix(stories): mute the clip waveform's media element so it can't bleed audio The clip waveforms drawn inside each timeline track use WaveSurfer with the default MediaElement backend, which creates an internal <audio> element to drive playback timing. Web Audio in useStoryPlayback is what actually produces sound, but WaveSurfer's element was happily preloading and — after the first user gesture unlocked browser autoplay — playing the source URL through the page output too. For TTS clips it was masked: they're short, both sources start at the same time, and stopping the BufferSourceNode at pause coincides with the natural end of the audio element. For long imports (a four-minute MP3) the BufferSourceNode stops on pause but WaveSurfer's element keeps going on its own track — which is exactly the "music keeps playing when I pause" symptom. Hand WaveSurfer a muted <audio> element via the `media` option so the visual still loads peaks but the element itself can never produce sound. preload="metadata" keeps the load lightweight. * fix(stories): hard-cut the audio graph on stop so long imports actually halt source.stop() was the only thing happening when a clip was halted, and on long imported buffers (multi-minute MP3s scheduled via source.start with a duration argument) it was silently failing to halt the buffer in some browsers — pause left the music playing and seek stacked another source on top of the original. The mute-the-WaveSurfer-element fix was a different bug along the same path; this is the one that actually addresses the duplicated audio. ActiveSource now carries the per-clip GainNode alongside the source, and stopSource detaches the onended handler before calling stop() (so the natural-end callback can't race with explicit teardown and re-delete a freshly rescheduled entry at the same id), then disconnects both nodes inside their own try/catch blocks. Even when stop() doesn't actually halt the buffer the graph is severed — no path from source to destination, no audio. * feat(stories): add empty tracks above/below the timeline Tiny + strips sit at the top of the topmost label cell and the bottom of the bottommost one, sticky-positioned in the label column so they follow horizontal scroll. Clicking either extends the visible track stack in that direction by one — above adds max(existing)+1, below adds min(existing)-1. Both compute against the full set (defaults + item-derived + previously-added) so successive clicks keep extending instead of fighting over the same number. Empty extras live in component state because a track only earns its keep once a clip lands on it. Once one does, item.track carries the number forward and the row keeps deriving from items naturally; if nothing lands there before reload, the empty row simply isn't there next time, which matches what the user expects of an unused affordance. * fix(mcp): bundle stdio shim sidecar * fix(captures): allow dictation without paste permission * fix(mcp): preserve speak engine defaults * fix(captures): use platform hotkey defaults * fix(mcp): preload speak pill window * fix(captures): hide unwired storage settings * feat(sponsors): add /sponsors page, homepage promo, and in-app strip * style(landing): drop pill chrome from /download maintainer kicker * changelog * better naming for sponsors * windows keybind note --------- Co-authored-by: Claude Opus 4.7 (1M context) <[email protected]> |
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Jamie PineandGitHub
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d61e884104 |
fix(offline): patch transformers mistral-regex check to survive HF failures (#530)
* fix(offline): patch transformers mistral-regex check to survive HF failures transformers 4.57.x's `PreTrainedTokenizerBase._patch_mistral_regex` calls `huggingface_hub.model_info(repo_id)` unconditionally during any non-local tokenizer load to probe for Mistral-family models. The call raises on `HF_HUB_OFFLINE=1`, on network outages, and on slow/blocked HF endpoints, and transformers doesn't catch any of it — the exception bubbles out of `from_pretrained` and kills the load for unrelated engines (Qwen TTS, Qwen CustomVoice, TADA, etc.). 0.4.2's load-time `force_offline_if_cached` guard walked straight into this trap: on cached online users it flipped `HF_HUB_OFFLINE=1` and converted a healthy load into a hard crash. 0.4.3's inference-path guard masked it; #524 removed the inference guard in 0.4.4, and users updating to 0.4.4 started hitting the same error on the load path instead (#526). Fix: - Wrap `_patch_mistral_regex` so any exception from the inner HF metadata check is swallowed and the tokenizer is returned unchanged. Voicebox never loads Mistral models, so the regex rewrite this check gates is a no-op for us; matches the success-path behavior for non-Mistral repos (tokenization_utils_base.py:2503). - Drop the `force_offline_if_cached` wraps from every load path (pytorch_backend Qwen + Whisper, qwen_custom_voice_backend, mlx_backend Qwen + Whisper). With the mistral patch in place they provide zero value and only risk re-introducing the same class of bug. Helper and its unit tests stay — still correct for targeted future use. - Add `backend/tests/test_offline_patch.py` covering OfflineModeIsEnabled / ConnectionError suppression, success pass-through, idempotence, and the missing-method no-op path. Fixes #526. * fix(offline): install mistral-regex patch for non-MLX backends The previous commit left the patch wired only through ``mlx_backend.py``'s existing import of ``hf_offline_patch``. On Windows/Linux/CUDA users who never load the MLX backend (everyone who hit #526), the patch module was never imported, so ``patch_transformers_mistral_regex`` never ran and the crash persisted. Hoist the import into ``backends/__init__.py``. Every backend imports from this package, so the module-level patch install runs before any ``from_pretrained`` call regardless of which engine the user picks. Caught by CodeRabbit and Cursor Bugbot on #530. |
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Jamie PineandGitHub
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0047352df1 |
fix(offline): remove inference-path HF_HUB_OFFLINE guards (#524)
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. |
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5aa1677a25 |
fix(offline): guard inference paths with HF_HUB_OFFLINE (#503)
* fix(offline): guard inference paths with HF_HUB_OFFLINE (#462) PR #443 wrapped the model *load* path with `force_offline_if_cached` so cached models don't phone home at startup. The context manager restores `HF_HUB_OFFLINE` on exit, which left inference paths (generate, transcribe, voice-prompt creation) unguarded — and `qwen_tts`, `mlx_audio`, and `transformers` perform lazy tokenizer/processor/config lookups during inference. With internet on, those lookups are near-instant and invisible; with internet off, `requests` hangs on DNS or connect until the network returns. This is exactly what users in #462 describe: model shows "Loaded", internet drops, generation "thinks" forever, internet comes back, generation completes. Chatterbox and LuxTTS don't exhibit this because their engine libs resolve everything through already-cached paths at load time. Fix: wrap each inference-sync body with `force_offline_if_cached(True, ...)`. Since inference only runs after a successful load, weights are known to be on disk, so `is_cached=True` is unconditional. Also adds the load-time guard that was missing from `qwen_custom_voice_backend.py` — CustomVoice previously had no offline protection at all. Paths patched: - PyTorchTTSBackend.create_voice_prompt (create_voice_clone_prompt) - PyTorchTTSBackend.generate (generate_voice_clone) - PyTorchSTTBackend.transcribe (Whisper generate + decoder-prompt-ids) - MLXTTSBackend.generate (mlx_audio generate, all branches) - MLXSTTBackend.transcribe (mlx_audio whisper generate) - QwenCustomVoiceBackend._load_model_sync + generate Does not address the secondary `check_model_inputs() missing 'func'` error reported in the same issue — that's a `transformers` 5.x version-skew bug on the install path, separate concern. Fixes #462. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(offline): mutate cached HF constants + threadsafe refcount Review feedback on the initial fix surfaced two real issues: 1. ``os.environ`` toggles alone don't flip offline mode. ``huggingface_hub.constants.HF_HUB_OFFLINE`` is read once at import time into a module-level bool; ``transformers.utils.hub._is_offline_mode`` mirrors that bool at its own import time. The hot paths (``_http._default_backend_factory`` in huggingface_hub, ``is_offline_mode`` in transformers) read the cached bools — not the env — so mutating only ``os.environ`` was a no-op. 2. Race condition on concurrent inference. Two threads running inside ``force_offline_if_cached`` via ``asyncio.to_thread`` could have thread A's ``finally`` strip thread B's offline protection mid-run. Rewrite the helper to: - mutate ``huggingface_hub.constants.HF_HUB_OFFLINE`` and ``transformers.utils.hub._is_offline_mode`` directly - refcount concurrent users under a single ``threading.RLock`` so a shared offline window is restored only when the last caller exits - still write ``os.environ`` for anything that reads it dynamically Also addresses the unused-variable ruff flag on the Whisper transcribe path (``audio, sr`` → ``audio, _sr``). New unit tests cover the cached-constant mutation, env propagation, no-op on ``is_cached=False``, nested contexts, and a threaded race where a slow thread must retain offline mode after a peer exits. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * fix(offline): atomic entry rollback + tidy test assertions Review follow-up: - Wrap the `_offline_refcount == 0` setup in a try/except so any failure during the cached-constant mutation (including unexpected non-ImportError like RuntimeError or AttributeError from a half-initialized module) rolls back *all* partial state before re-raising. Without this, a mid-setup crash could leave `huggingface_hub.constants.HF_HUB_OFFLINE` mutated but the refcount at 0 — a persistent offline flag outliving the process. - Swap ruff-flagged Yoda comparisons in the new test file (SIM300) and add a module-level note warning that these tests mutate global state and are not safe under cross-process parallelism. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> * test(offline): make concurrency test deterministic and bounded Replace the `sleep(0.15)` ordering hack with an explicit `threading.Event` the fast thread sets in `finally`. The slow thread waits on that event (bounded), then observes the flag — so we deterministically verify the slow thread still sees offline mode after the fast thread has exited. Also add timeouts to `barrier.wait()` and assert `not thread.is_alive()` after the joins so the test can't hang on an unexpected failure path. Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]> --------- Co-authored-by: Claude Opus 4.7 (1M context) <[email protected]> |
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8929947c7a |
fix(mlx): point Qwen 0.6B at the published mlx-community repo (#501)
The 0.6B slot was aliased to the 1.7B repo as a temporary fallback because `mlx-community/Qwen3-TTS-12Hz-0.6B-Base-bf16` wasn't published when MLX support shipped. That conversion is live now, so use it — Apple Silicon users picking 0.6B get the actual 0.6B model (1.2 GB instead of 3.5 GB). Also drops the now-obsolete troubleshooting entry and updates the triage notes in PROJECT_STATUS.md. Fixes #485. Co-authored-by: Claude Opus 4.7 (1M context) <[email protected]> |
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73170d0e92 |
feat(health): warn when GPU arch isn't supported by PyTorch build
Applies the compatibility-checker portion of #367. Adds a check_cuda_compatibility() helper that compares the current device's compute capability against torch.cuda._get_arch_list() and returns a human-readable warning if the PyTorch build doesn't support it. Wired into three places: • HealthResponse gains a gpu_compatibility_warning field so clients can surface the issue in the UI • Startup logs the warning as WARN level • _get_gpu_status() appends "[UNSUPPORTED - see logs]" to the GPU label shown in settings Skipped #367's other half — the switch from stable to nightly cu128 wheels across release.yml, build_binary.py, and justfile. That's redundant with #401's TORCH_CUDA_ARCH_LIST=...12.0+PTX approach and would introduce non-deterministic builds from shifting nightly releases. Co-Authored-By: nyzxor <[email protected]> Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]> |
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James PineandClaude Opus 4.6
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0317626677 |
fix(qwen): unify HF cache dir to avoid split cache on Windows
Applies the cache_dir portion of #218. On Windows local setups, model assets can split between .hf-cache/hub and .hf-cache/transformers when Qwen3TTSModel.from_pretrained doesn't explicitly pin the cache root — speech_tokenizer and preprocessor_config.json then fail to resolve during load, causing 500s at generation time. Routes both HF Hub and Transformers through hf_constants.HF_HUB_CACHE. Skipped the torch_dtype= → dtype= rename from #218: transformers 4.36 (our minimum) doesn't accept the dtype alias, only 4.46+. Once we bump the minimum we can make that change. Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]> |
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Jamie PineandGitHub
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b49f14a814 |
Merge pull request #319 from jamiepine/fix/startup-and-server-switch
fix: GUI startup with external server + data refresh on server switch |
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Jamie PineandGitHub
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9a955a77d2 |
Merge pull request #320 from jamiepine/feat/intel-xpu-support
feat: Intel Arc (XPU) GPU support |
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Jamie PineandGitHub
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c18591c0c3 |
Merge pull request #318 from jamiepine/fix/offline-model-loading
fix: force offline mode when loading cached models (Qwen TTS & Whisper) |
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James Pine
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4e0c731db8 | feat: add Qwen CustomVoice preset engine | ||
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James Pine
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3584283d84 |
feat: Kokoro 82M TTS engine + voice profile type system
Add Kokoro-82M as a new TTS engine — 82M params, CPU realtime, 8 languages, Apache 2.0. Unlike cloning engines, Kokoro uses pre-built voice styles, which required a new profile type system to support non-cloning engines cleanly. Kokoro engine: - New kokoro_backend.py implementing TTSBackend protocol - 50 built-in voices across en/es/fr/hi/it/pt/ja/zh - KPipeline API with language-aware G2P routing via misaki - PyInstaller bundling for misaki, language_tags, espeakng_loader, en_core_web_sm Voice profile type system: - New voice_type column: 'cloned' | 'preset' | 'designed' (future) - Preset profiles store engine + voice ID instead of audio samples - default_engine field on profiles — auto-selects engine on profile pick - Create Voice dialog: toggle between 'Clone from audio' and 'Built-in voice' - Edit dialog shows preset voice info instead of sample list for preset profiles - Engine selector locks to preset engine when preset profile is selected - Profile grid filters by engine — shows Kokoro voices when Kokoro selected - Custom empty state when no preset profiles exist for selected engine Bug fixes: - Fix relative audio paths in DB causing 404s in production builds - config.set_data_dir() now resolves to absolute paths - Startup migration converts existing relative paths to absolute Also updates PROJECT_STATUS.md and tts-engines.mdx developer guide. |
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James Pine
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707046237c |
fix: complete Intel XPU support — device-aware seeding, GPU status reporting, and setup detection
Address CodeRabbit review feedback and user-reported GPU acceleration failure: - Use shared manual_seed() in chatterbox, chatterbox_turbo, and luxtts backends so XPU (and future accelerators) get proper device seeding - Add XPU branch to _get_gpu_status() so startup log reports Intel Arc GPUs instead of 'None (CPU only)' - Add XPU VRAM reporting and correct backend_variant fallback in the /health endpoint - Switch justfile GPU detection from Get-WmiObject to Get-CimInstance, simplify the Arc regex to match 'Arc' (not 'Intel.*Arc'), log detected GPUs, and print manual install instructions on miss Resolves the root cause where IPEX was silently not installed due to WMI detection failure, causing CPU-only fallback on Intel Arc systems. |
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James Pine
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83ebababe7 |
feat: add Intel Arc (XPU) GPU support across all backends
Auto-detect Intel Arc GPUs during Windows setup and install PyTorch with XPU support + intel-extension-for-pytorch. Enable allow_xpu=True on all TTS backends (Chatterbox, Chatterbox Turbo, Hume TADA, LuxTTS) that previously only supported CUDA. Add shared empty_device_cache() and manual_seed() helpers in base.py to handle XPU memory management and reproducible seeding alongside CUDA. |
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James Pine
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2e95b7c5d8 |
fix: force offline mode when loading cached models (Qwen TTS & Whisper)
Qwen TTS and Whisper Base make network calls to HuggingFace even when model weights are fully cached locally, because from_pretrained() defaults to local_files_only=False. This causes failures for offline users. Add a reusable force_offline_if_cached() context manager that sets HF_HUB_OFFLINE=1 during model loading when is_model_cached() is True. Applied to all four affected load paths: - PyTorchTTSBackend (Qwen TTS) - PyTorchSTTBackend (Whisper) - MLXTTSBackend (refactored from inline implementation) - MLXSTTBackend (previously unprotected) Closes #82 |
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James Pine
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6bf40bd2d0 |
fix tokenizer patch corrupting AutoTokenizer for other engines
Replace the monkey-patch on AutoTokenizer.from_pretrained (which broke the classmethod descriptor and caused 'Tokenizer not loaded' errors when loading Qwen after TADA) with two targeted config patches: - Set AlignerConfig.tokenizer_name to the local ungated tokenizer path - Pre-load TadaConfig, inject tokenizer_name, pass config= to from_pretrained No global state is modified; other engines are unaffected. |
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James Pine
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12cda2e090 |
fix torchcodec error by using soundfile instead of torchaudio.load
torchaudio 2.10+ switched its default audio loading backend to torchcodec, which isn't installed. Replace torchaudio.load() with soundfile.read() in create_voice_prompt(). TADA's internal use of torchaudio.functional.resample() is unaffected (pure PyTorch math, no torchcodec dependency). |
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James Pine
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7a90290a76 |
fix gated Llama tokenizer error by redirecting to ungated mirror
TADA hardcodes 'meta-llama/Llama-3.2-1B' as its tokenizer source in both the Aligner and TadaForCausalLM.from_pretrained(). That repo is gated and requires accepting Meta's license on HuggingFace. Monkey-patch AutoTokenizer.from_pretrained during model loading to redirect Llama tokenizer requests to 'unsloth/Llama-3.2-1B', an ungated mirror with identical tokenizer files. The patch is scoped to model loading only and restored immediately after. |
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James Pine
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b02ce8e2f3 |
replace descript-audio-codec with lightweight DAC shim
The real descript-audio-codec package pulls in descript-audiotools, which transitively requires onnx, tensorboard, protobuf, matplotlib, pystoi, and other heavy dependencies. onnx fails to build from source on macOS due to CMake version incompatibility. TADA only uses Snake1d (a 7-line PyTorch module) from DAC. This commit adds a shim in backend/utils/dac_shim.py that registers fake dac.* modules in sys.modules with just the Snake1d class, completely eliminating the DAC/audiotools dependency chain. |
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James Pine
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4e7772a21d |
add HumeAI TADA TTS engine (1B English + 3B Multilingual)
Integrates HumeAI's TADA (Text-Acoustic Dual Alignment) speech-language model as a new TTS engine. TADA uses a novel 1:1 token-audio alignment that produces coherent speech over long sequences (700s+). Two model variants: - tada-1b: English-only, ~4GB, built on Llama 3.2 1B - tada-3b-ml: 10 languages, ~8GB, built on Llama 3.2 3B Backend uses the Encoder for voice prompt encoding with caching, and TadaForCausalLM with flow-matching diffusion for generation. Supports bf16 inference on CUDA, forces CPU on macOS (MPS compatibility). Installed with --no-deps due to torch>=2.7 pin conflict; descript-audio-codec and torchaudio added as explicit sub-dependencies. |
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Jamie Pine
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f1541701fb |
add model selection and expanded language support to /transcribe endpoint
Closes #233 |
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James Pine
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473bb3e9fb |
fix take-label race in regeneration, add accessible focus to select
- Use DB COUNT query instead of list length for take-N label to avoid TOCTOU race between list_versions and create_version - Add focus:bg-muted to SelectTrigger for keyboard focus visibility |
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James Pine
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b3012ed10c |
move CRUD and service modules into services/, platform_detect into utils/
Move 9 business-logic modules from the backend root into services/: channels, effects, history, profiles, stories, versions, export_import, transcribe, tts. Move platform_detect.py into utils/. Backend root now contains only infrastructure (app, main, config, server, models, build_binary) and docs. All 94 routes verified. |
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James Pine
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b7781951df | comment cleanup | ||
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Jamie Pine
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0813a3d9d6 |
refactor: remove dead code, deduplicate backends
Phase 1 - delete dead code: - studio.py, migrate_add_instruct.py, utils/validation.py - duplicate _profile_to_response in main.py, duplicate asyncio import - pointless _get_profiles_dir/_get_generations_dir wrappers - duplicate LANGUAGE_CODE_TO_NAME and WHISPER_HF_REPOS constants Phase 2 - extract backends/base.py with shared utilities: - is_model_cached() replaces 7 copy-pasted HF cache checks - get_torch_device() replaces 5 device detection methods - combine_voice_prompts() replaces 5 identical implementations - model_load_progress() ctx manager replaces progress boilerplate in all backends - patch_chatterbox_f32() replaces identical monkey-patches in both chatterbox backends net -1078 lines across the backend |
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Jamie Pine
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4e84415da7 | refactor start | ||
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James Pine
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de8558d197 |
Fix prod build: download progress, robust stderr, full tracebacks
- Force tqdm disable=False in TrackedTqdm so byte progress works in prod (huggingface_hub disables tqdm based on logger level, which prevents self.n from updating — our progress tracking needs the counter even though we don't render to terminal) - Harden devnull redirect to test writability, not just None check - Add full traceback logging to all backend error handlers - Add chatterbox/luxtts/zipvoice hidden imports and metadata to spec |
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James Pine
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2f535a772f |
fix: load model into local var before patching to avoid half-initialised state
Apply local-var-then-assign pattern to chatterbox_backend.py (multilingual) to match the turbo backend. Also use _current_model_size fallback in unload, delete, and status endpoints for consistent Qwen model size checks. |
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James Pine
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bfd7b815a5 |
fix: patch S3Tokenizer.log_mel_spectrogram for float64→float32 cast
The actual dtype mismatch was in S3Tokenizer.log_mel_spectrogram, not VoiceEncoder.forward. librosa.load returns float64 numpy, which torch.from_numpy preserves as double. The STFT output (double) then hits _mel_filters (float32) in a matmul at s3tokenizer.py:163. Now patching both entry points after model load: 1. S3Tokenizer.log_mel_spectrogram — cast audio to float32 before STFT 2. VoiceEncoder.forward — cast mels to float32 before LSTM Remove debug traceback logging (no longer needed). |
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James Pine
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47ce4cafdf |
fix: patch VoiceEncoder.forward to cast float64 mels to float32
The previous approach of patching librosa.load didn't work because melspectrogram itself performs float64 math (numpy dot, signal.lfilter) regardless of input dtype. The actual mismatch happens when pack() creates a float64 tensor from the mel arrays and passes it into the float32 LSTM weights in VoiceEncoder.forward(). Fix by monkey-patching VoiceEncoder.forward() to call mels.float() before the LSTM, ensuring the input always matches the model dtype. |
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James Pine
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5ccf79a8f7 |
Revert "fix: cast librosa float64 audio to float32 for Chatterbox voice encoder"
This reverts commit
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James Pine
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1d32170c2e |
fix: cast librosa float64 audio to float32 for Chatterbox voice encoder
The upstream VoiceEncoder's melspectrogram only casts to float32 when hp.normalized_mels is True (it defaults to False), so librosa's float64 output flows through as double tensors into float32 model weights, causing 'expected m1 and m2 to have the same dtype, but got: float != double'. Fix by monkey-patching prepare_conditionals in both Chatterbox and Chatterbox Turbo backends to ensure librosa.load returns float32. |
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James Pine
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ca74c155e2 |
fix: pass language parameter to Qwen TTS models and sync form with profile language
Both PyTorch and MLX backends silently dropped the language parameter — it was accepted by generate() but never forwarded to the underlying Qwen3-TTS model, causing it to default to auto-detection which frequently confuses similar languages (e.g. Portuguese for Spanish). - Add LANGUAGE_CODE_TO_NAME mapping (ISO 639-1 to full name) to both backends - PyTorch: pass language= to generate_voice_clone() - MLX: pass lang_code= to all 4 model.generate() call sites - Frontend: auto-sync generation form language with selected voice profile Closes #97 |
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Jamie PineandGitHub
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f58c7c1cf3 |
Merge pull request #262 from jamiepine/feat/linux-rocm-whisper-turbo
feat: Linux support, AMD ROCm, Whisper Turbo, and spawn fix |
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James Pine
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b5801891b8 |
feat: Linux support, AMD ROCm, Whisper Turbo, and spawn fix
Cherry-picked and adapted from PR #89 and #214: - Linux audio capture via PulseAudio/PipeWire monitor sources (cpal) - AMD ROCm GPU support: HSA_OVERRIDE_GFX_VERSION env var, ROCm detection - Whisper Turbo model (openai/whisper-large-v3-turbo) in all endpoints - Cleaner Whisper language handling via generate_kwargs - tauri::async_runtime::spawn fix to prevent panic on app shutdown - Enable Linux (ubuntu-22.04) in release CI matrix |
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Jamie PineandGitHub
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8f77c041f5 |
Merge pull request #152 from mpecanha/fix-offline-mode-crash
Fix: Prevent crashes when HuggingFace is unreachable |
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James Pine
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bf728a780c |
feat: add Chatterbox Turbo engine and per-engine language lists
- New ChatterboxTurboTTSBackend wrapping ChatterboxTurboTTS (ResembleAI/chatterbox-turbo) - English-only 350M model with paralinguistic tag support ([laugh], [cough], [chuckle]) - Bypasses upstream token=True bug by calling snapshot_download(token=None) + from_local() - Same CPU-on-macOS forcing and torch.load monkey-patching as multilingual backend - Full engine integration: generate, stream, model status/download/delete endpoints - Language dropdown now shows only languages supported by the selected engine - Per-engine language maps: Qwen (10), LuxTTS (en), Chatterbox (23), Turbo (en) - Auto-switches to English when selecting English-only engines - Backend language regex expanded to accept all 23 Chatterbox languages |
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James Pine
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cc07d4d3c9 |
fix: download progress tracking for all engines and inline progress UI
- Add HFProgressTracker to LuxTTS and Chatterbox backends so tqdm-based file-level download progress reaches the frontend (previously only Qwen had this, LuxTTS/Chatterbox showed a static spinner) - Add progress/current/total/filename fields to ActiveDownloadTask so the /tasks/active polling endpoint carries progress data - Show inline progress bar + bytes in the model list and detail modal, poll at 1s during active downloads (5s otherwise) - Fix GpuAcceleration crash: cudaStatusLoading was referenced before initialization in its own useQuery declaration |
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James Pine
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9beb9d7fec |
fix: install chatterbox-tts with --no-deps to avoid numpy pin conflict
chatterbox-tts 0.1.6 pins numpy<1.26 and torch==2.6 which are incompatible with Python 3.12+. Install with --no-deps and list its sub-dependencies explicitly in requirements.txt. Also removes HFProgressTracker from chatterbox backend to avoid 'generator didn't stop after throw()' errors from tqdm patching. |
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James Pine
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76bb207b2b |
feat: add Chatterbox TTS engine for multilingual voice cloning
- New ChatterboxTTSBackend wrapping ChatterboxMultilingualTTS (ResembleAI/chatterbox) - Supports 23 languages including Hebrew, forces CPU on macOS (MPS issue) - Monkey-patches torch.load for CPU loading, forces eager attention for compatibility - trim_tts_output utility cuts trailing silence/hallucination from Chatterbox output - Full engine integration: /generate, /generate/stream, model status/download/delete - Hebrew (he) added to supported languages in frontend and backend validation - Single flat model dropdown extended with Chatterbox option in both generation UIs - ModelManagement UI groups LuxTTS and Chatterbox under 'Other Voice Models' section |
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James Pine
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753158c1c9 |
fix: address review feedback — race condition, GPU safety, task GC
- Add threading lock to get_tts_backend_for_engine() to prevent race condition where concurrent requests could create duplicate backend instances (double-checked locking pattern) - Fix LuxTTS generate: call .detach().cpu() before .numpy() so it works on GPU/MPS devices, not just CPU - Store background download tasks in a module-level set to prevent garbage collection before completion (asyncio.create_task fire-and- forget pattern) - Deduplicate cache_key computation in LuxTTS create_voice_prompt - Prefix unused sr variable with underscore |
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James Pine
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d46eb5bcc6 |
feat: add LuxTTS as second TTS engine with multi-engine support
Introduce LuxTTS (ZipVoice) alongside Qwen TTS, enabling users to choose between engines at generation time. LuxTTS offers fast, English-focused voice cloning at 48kHz with ~1GB VRAM. Backend: - Add LuxTTSBackend with encode_prompt/generate_speech integration - Multi-engine registry (get_tts_backend_for_engine) replacing singleton - Engine-prefixed voice prompt cache keys to avoid collisions - Engine field on GenerationRequest (default 'qwen' for backward compat) - Engine dispatch in /generate and /generate/stream endpoints - LuxTTS in model status, download, and delete maps Frontend: - TTS Engine selector dropdown in GenerationForm (Qwen TTS / LuxTTS) - Conditionally hide Model Size and Delivery Instructions for LuxTTS - Engine field added to TypeScript types and Zod schema - LuxTTS section in Model Management page |
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Daddy Raegen
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a362d7de2a |
feat: add download cancel/clear UI, fix whisper-large and error reporting
- Add cancel (X) button on downloading and errored model items - Add collapsible Problems panel (VS Code-style) showing error details - Add "Clear All" button to reset all stale download/error state - Add POST /models/download/cancel endpoint to dismiss individual downloads - Add POST /tasks/clear endpoint to reset all task and progress state - Include error messages in /tasks/active response for visibility - Capture SSE error messages client-side for immediate display - Fix whisper-large using wrong HF repo (openai/whisper-large → openai/whisper-large-v3) - Fix Whisper HF repo mapping in both PyTorch and MLX backends - Shorten error toast to point users to Problems panel instead of wall of text |
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Makinde
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d00e28ffda |
Fix: Prevent crashes when HuggingFace is unreachable
Implements offline mode patch for API stability issues: - Add hf_offline_patch.py to monkey-patch huggingface_hub - Force cache-only lookups before mlx_audio imports - Create symlink from original Qwen repo to MLX community version when only MLX version is cached This fixes: - Issue #150: Internet required even with cached models - Issue #151: API crashes when HF network fails The patch ensures that if models are locally cached, no network requests are made to HuggingFace during speech generation. |
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Mriganka
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54d72ddfd0 | fix: resolve multiple issues (#96, #119, #111, #108, #121, #125, #127) |