d91beef0fd314250d8d9b94de86dfea019a8bd96
17
Commits
| Author | SHA1 | Message | Date | |
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 Palash Debnath
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08569397d3 |
fix(asr): secure configured endpoints and refresh guidance (#1751)
Refreshes README and linked docs with accurate installation, platform, privacy, API, and model-license guidance; documents local gigastt; and pins OpenAI-compatible ASR traffic to the configured secure origin. Closes #1736. |
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Palash Debnath
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7718a7a10b |
fix: cross-platform dictation delivery (#1610)
Makes dictation delivery, capture, recovery, model fallback, AEC, and localized status behavior reliable across macOS, Windows, and Linux. |
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velixio
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2b6f49c596 |
feat(workers): make inbound mode reachable — settings, endpoints, docs
Wires the two transport halves into something a user can actually turn on. Two independent switches, deliberately not one. "Accept connections" makes this machine a node others dial; "saved connections" are the nodes this panel dials out to. A workstation with a GPU that also drives jobs on a second box does both, so neither implies the other. Binding stays on 127.0.0.1 until someone explicitly widens it, and widening is its own field rather than a flag riding along with the enable toggle. With no encryption that boundary is the difference between a credential on one machine and a credential on a network, so it is never crossed as a side effect. The API reports `exposed` so the UI can say which side of it the user is on. Saved nodes are redialled only after the control plane is up, since the connector hands frames to its servicer. Failing to listen records the reason rather than leaving the feature looking enabled while it quietly accepts nothing. Docs say plainly that this mode is unencrypted, that the connection string is a password crossing the network in the clear, and that dial-out remains the better choice when one machine is enough. The Security section no longer implies its TLS guarantees cover both modes. |
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velixio
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673e544812 |
Merge origin/main into feat/worker-protocol-v1
Three conflicts, all additive on both sides — resolved by keeping both
rather than choosing, since either side's entries were real shipped work:
* CHANGELOG.md — remote-GPU entries against branding, IndexTTS 2.5 and
the recording-input work
* setup/download.py — the per-target progress reset against main's
active-install tracking; both belong in the same finally block
* docs/features.yaml — the remote-worker and model docs against
docs/branding.md
Backend 5349 passed, frontend 1871 passed. `bun install --frozen-lockfile`
reports no changes, so the Docker build sees the same tree CI does.
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velixio
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b7caa494eb |
feat(workers): remote downloads, audiobook chapters, and one port that stays honest
Five workstreams that finish the remote-GPU line, plus the test hole that let a broken signature reach a commit. **Downloads go through the normal path** (Phase 5). Rather than a second remote-only route, the existing Models install flow became target-aware, so a model landing on a worker uses the same code, the same progress events and the same UI as a local one. Progress rows key on (target, repo_id) — the aggregator keyed on bare repo_id, so the same model downloading here and on a worker at once collapsed into one row that told the user nothing true about either. **Audiobooks render chapter by chapter on the worker** (Phase 8), with per-chapter local fallback and ONE aggregated notice. The failure that shape exists to prevent: a remote GPU that sleeps at chapter 40 of 200 must not turn a working book into 160 rows of PROGRESS_LEASE_EXPIRED. Dictation is deliberately NOT ported — it runs ASR per utterance inside a live WebSocket loop, and paying queue admission plus a round trip there would spend the one thing that route is for. **Dubbing stays local, and says so** (Phase 7). The coarse worker operation is not finished, so the picker still reports dubbing as local rather than showing a green remote chip over work this machine is doing. What could not wait is the in-loop OOM retry: it sniffed the error string and flushed the *local* CUDA cache, which under remote execution is the wrong machine's GPU entirely. That is fixed now, before the path that would have exercised it exists. **Two instances can no longer share the control plane.** A second VoiceStudio silently bound the same worker port and coexisted, so remote workers landed on whichever process won the race — a session that registers with one instance and appears dead to the other. This produced hours of misdiagnosis during hardware testing and would hit any user with the app open twice. The second instance now keeps running locally and explains the conflict instead of quietly competing. **And the hole that allowed all this to be missable.** gpu_gateway called Scheduler.submit(pinned_worker_id=...) one commit before that parameter existed. Every remote generation raised TypeError; 5236 tests passed anyway, because nothing exercised the gateway against the real scheduler. tests/test_gpu_gateway_scheduler_contract.py now runs that path for real and binds every gateway→dependency call signature. Verified by renaming the parameter away and watching both tests fail with the original error. Gallery previews also fall back to a local render when a downloaded clip cannot be decoded, rather than yielding silence. Backend 5274 passed, frontend 1812 passed. Not yet verified on hardware: Phases 4, 5, 6, 7, 8. Only the TTS path and its artifact transport have been proven on a real GPU. |
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velixio
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bda169c900 |
feat(workers): pin work to the chosen GPU, and say when its model is missing
Three phases that only make sense together: a job that names a worker, a worker that reports honestly what it can actually run, and the small defects that made both lie. **Pinning** (Phase 1). `pinned_worker_id` is now honoured in both places that choose a worker — `eligible_workers` and `select_worker` build independent lists, so applying it to one silently leaked work onto whichever machine was least busy. The pin persists across a restart via an additive column, deliberately not alembic (justified in the code, per the precedent already in db.py): quitting mid-render used to drop it without a word. `max_attempts=1` was rejected as the mechanism — it makes the FIRST failure terminal, including the penalty-free ones a stale advisory view produces routinely. Cancel now actually reaches the worker. `WorkerServicer.cancel` had zero callers, so cancelling released the slot while the GPU thread kept running, and a late result could resurrect the task as COMPLETED — `commit_result` assigned that state directly, bypassing the transition table where CANCELLED is terminal by construction. **Honest capabilities** (Phase 4). A worker now probes whether weights are actually present, and a job stops BEFORE dispatch with a typed 409 naming the model and the machine, instead of failing mid-task. The probe fails OPEN: `is_cached`/`cache_is_complete` cannot see a user-managed clone outside the HF layout, so only a positive "absent" refuses. Refusing an engine that works today would break the compatibility promise. `pool.supports` deliberately still ignores `downloaded` — had it not, the scheduler would drop the worker and answer with a terminal NO_CAPABLE_WORKER, which tells the user to check their install when the truth is one download away. The frontend no longer offers "Report this bug" for that state; it offers the download. Catalog tags resolve against the TARGET's OS/arch/backend, not this machine's. From a Mac control plane, a CUDA worker's model list was showing the mlx-community repos it cannot run and hiding the ones it needs. **And the quiet ones** (Phase 0 leftovers): a model's human label rides its own proto field so renaming it cannot orphan breaker history; an empty model_id no longer forks the capacity slot key into two slots for one model; the idle sweep cannot evict an engine out from under a live LOCAL render. Verified on real hardware, which is the only verification that has ever caught anything here: 2025 characters, default settings, routed to an RTX 4090 over the wire — 100% GPU utilisation on the remote box, 119.6 s of 24 kHz audio returned in 16.6 s, 5.7 MB delivered out of band through the artifact path rather than the control stream. Backend 5259 passed, frontend 1808 passed. |
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Palash Debnath
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04410a458d |
Release VoiceStudio 5.0.0 (#1487)
Complete the VoiceStudio identity, release documentation, assets, version mirrors, and safe cross-platform development startup. |
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Palash Debnath
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95a35b8e07 |
feat(indextts): add native IndexTTS 2.5 support (#1485)
* feat(indextts): add native 2.5 sidecar support * fix(indextts): preserve legacy language metadata * docs(indextts): state model license terms accurately * fix: preserve IndexTTS upgrades and duration controls * fix: complete IndexTTS upgrade safeguards |
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acd36badee |
feat(engines): PocketTTS CPU-only sidecar shape (#1306) (#1328)
* feat(engines): PocketTTS CPU-only sidecar shape (#1306) Sidecar SHAPE for review, mirroring omnivoice-subprocess: PocketTTSBackend(SubprocessBackend) (CPU-only, parent interpreter, optional-dep gate) plus a stdio sidecar (ready/ping/synthesize/shutdown, lazy TTSModel.load_model, per-ref voice cache, generate_audio to int16 PCM). Registered in services/tts_backend.py. Batch protocol; streaming raised as a follow-up. CI smoke, gated-weights preflight, 4-platform install, licence-accept gate deferred to on-top after shape review. * feat(engines): PocketTTS sidecar handles 6 languages (en/fr/de/pt/it/es) load_model(language=...) per language (cached), maps OmniVoice's language value to a pocket-tts model language, and picks the default preset voice per language when no ref clip is given. Represents PocketTTS accurately: it is multilingual, not english-only. The HF model card's 'English only' line is stale, confirmed by the GitHub README and pocket-tts 2.1.0. * fix(engines): list pockettts in docs inventory; drop unused logger docs/features.yaml tts_engines now includes pockettts, clearing the docs-drift test that failed CI (every registered engine must be in the inventory). Removed the unused logger line CodeQL flagged. No readme/doc entry yet, matching opt-in engines like supertonic3 and omnivoice-gguf; a doc page can land with the rest of the integration. * fix(engines): address PocketTTS sidecar review findings - Cold-load watchdog: heartbeat progress frames during the gated weights download so the parent does not kill a healthy sidecar mid-load, plus a 600s recv timeout on the backend. - Unsupported language: raise a clear error instead of silently falling back to English and mispronouncing. - Voice-state cache: LRU-bounded to 8 entries so a long session cannot leak memory. - ref_audio SSRF: reject URLs (local file paths only) to preserve local-first. Addresses the 3 Greptile P1 + 1 CodeRabbit Major on #1328. * fix(engines): invalidate voice cache on ref-file change; reject non-finite recv timeout - Voice-state cache key now folds the ref_audio file mtime+size, so a file replaced at the same path no longer returns a stale voice from the previous contents (Greptile P1). - recv_timeout_s rejects inf/nan env values via math.isfinite and falls back to 600s, so the deadline can't be silently disabled (CodeRabbit Major). * fix(engines): nanosecond mtime in voice cache fingerprint int(st.st_mtime) lost sub-second precision, so a file replaced at the same path within one second with the same size kept the old key and returned a stale voice. Use st.st_mtime_ns for full resolution (Greptile P1 on the follow-up fix commit). * fix(engines): raise on multi-channel audio instead of unsafe downmix The defensive mean(axis=0) assumed channels-first; on channels-last (N,2) it averaged across time, producing garbage. The engine returns mono, so the branch is unreachable in practice. Raise on ndim>1 so an upstream shape change surfaces as a loud error frame instead of silent noise. (debpalash review on #1328) * fix(engines): include import error in pockettts is_available message CodeRabbit Minor on #1328: the exception was caught as 'e' but never shown. * fix(engines): lock _send to prevent concurrent-write framing corruption Greptile P1 on #1328: the cold-load heartbeat thread and the main loop both call _send (stdout write). The stop+join serializes the normal case, but a join timeout leaves a window where both threads write length+body segments concurrently, interleaving the wire framing. Add a threading.Lock around the write so concurrent _send calls are serialized regardless. * test(engines): cover the PocketTTS sidecar's silent failure modes The four review findings fixed on this PR are all silent by construction: an unsupported language rendered fluent, confident, wrong audio; the channels-last downmix produced noise; interleaved frames desynchronized the pipe permanently; a re-recorded clip kept serving the old voice. None of them raise, and none would be caught by an end-to-end smoke test that only asserts audio came back. 49 tests over the sidecar's pure logic — language selection, PCM conversion, wire framing, the LRU voice cache — plus the backend surface (recv-timeout guards, CPU-only declaration, sample-rate lockstep with the sidecar, lazy registration). The model is mocked and the sidecar is stdlib-only at import time, so none of it needs the optional pocket-tts wheel or a child process. Verified fail-before/pass-after by reverting the lock and the multi-channel guard: the framing test fails with a length header decoded from inside another frame's body, which is the corruption itself rather than a proxy for it. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> --------- Co-authored-by: debpalash <nizam4103@gmail.com> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com> |
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Paolo Antinori
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47c51698c9 |
feat(engines): add omnivoice-subprocess, a crash-isolated (killable) TTS engine (#1292)
* feat(engines): add omnivoice-subprocess, a crash-isolated TTS engine The default in-process OmniVoice engine runs on the GPU ThreadPoolExecutor. When a generate or load exceeds its execution budget the pool is "reset", but the abandoned worker thread cannot be killed (Python cannot interrupt a native torch/MPS call), so it keeps holding the device until it finishes on its own and later synths queue behind it and hang. The reset restores pool capacity but not the device. This is the residual root cause behind the closed #730 and #1190: the messaging/reset mitigations address the symptom, not the device-holding zombie. Add an opt-in `omnivoice-subprocess` engine that runs the same model in a child process via SubprocessBackend. A child process can be hard-killed: on a recv-timeout the watchdog calls proc.kill(), reclaiming VRAM/device, and the next request transparently respawns a fresh sidecar. The in-process engine remains the default, so existing users see no change; this is an opt-in for unattended / scheduled / reaction-triggered synthesis where a stuck job must self-recover instead of hanging until a manual restart. Base-class and mitigation changes that ship with it: - SubprocessBackend.generate() now consumes non-terminal {"op":"progress"} frames a sidecar emits during a cold load (previously the first cold generate after spawn failed, then worked on retry). Additive: engines that reply with audio directly are unaffected. - recv_timeout_s is overridable per engine (default 60s unchanged); the new engine sets it to the generate budget so a long-but-valid synth is not falsely killed while a wedged one still is. - make_room_before_generate(): free idle GPU memory before a warm, heavy generate. The cold-load path already evicted; the warm path skipped it, so a long synth on a VRAM-tight MPS box could contend its way into the budget. Verified end-to-end against the live model (cold / warm / recovery-after-kill) and under a sustained + concurrent-pressure soak: killed-worker recovery 5/5, chunked long text 9/9, no memory leak. * Address review: install_hint + move make_room into get_model - Add `omnivoice-subprocess` to `_INSTALL_HINTS`; the test_install_hints_cover_all_registered_backends gate requires every registered backend to carry one (this was the CI failure). - Move the warm-generate VRAM eviction out of the /generate and /v1/audio/speech routes and into get_model()'s warm-return path, so EVERY native TTS generate is covered (REST, WS TTS, dub, batch, audiobook), not just the two REST routes. Drops the now-redundant per-route wiring. (Greptile P1: the per-route placement missed the other generation surfaces.) * Address review: drop dead long-text eviction path; log probe failure - _should_make_room_for_generate: the long-text headroom boost became dead code once the eviction moved into get_model() (which has no text), so the long-text branch never fired. Removed the text param, the long-text threshold/multiplier branch, and the now-unused _env_float helper. The core RAM-tight gate (the part that matters on a starved box) is unchanged. - Log the available_memory probe failure at debug instead of silently swallowing it (CodeRabbit: silent swallow breaks the debug trail). - Tests updated for the text-agnostic policy. * fix(engines): stop subprocess generate() self-deadlock on 1-worker pools SubprocessBackend.generate() acquires a GPU-pool slot for accounting, but /v1/audio/speech and /generate dispatch backend.generate() via run_on_gpu_pool_guarded, i.e. already ON a pool worker. On a 1-worker pool (MPS) the inner pool.submit queued behind the very job running it and slot_future.result(timeout=10) raised before the sidecar ever spawned, so omnivoice-subprocess (and every other subprocess engine on MPS) surfaced the in-process 300s-abandon instead of synthesizing. Skip the slot acquisition when current_thread() is already a gpu-pool worker; the outer guard already accounts for the slot. Direct callers (off the pool) still acquire one. Regression test added (generate on a pool worker). * Address review: reword slot-skip comment (fixes watermark-coverage CI) + simplify - The slot-skip comment said "dispatch backend.generate() via", and test_watermark_route_coverage's _SYNTH_CALL regex matches the literal backend.generate( anywhere in a module, so it counted subprocess_backend.py as a synthesis producer that must reference mark_synthetic (it doesn't — the routes apply mark_synthetic; the engine sits below the chokepoint, like tts_backend.py). Reworded to "dispatch generate() via". - Fold in the simplify refinement: single negated predicate, import+pool moved into the acquire branch. |
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debpalashandClaude Fable 5
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63fd497caf |
feat: TTS-only first run, platform-curated ASR, guided OS permissions, parakeet-mlx
Only the TTS model (~2.4 GB) is required on first run; ASR models are per-platform curated picks (curated_on in models.yaml) installed on demand. Every transcription surface returns a typed asr_model_missing error with a one-click download CTA instead of silently pulling multi-GB Whisper weights. Settings -> Models is a grouped, platform-aware catalog. New guided permissions UX (wizard System Check + Settings -> Permissions + mic pre-flight) with native mic-state checks and OS settings deep-links. New parakeet-mlx engine brings Parakeet TDT v3 to Apple Silicon (language-gated capture preference so multilingual dictation never regresses). Docs: expressive-speech page, Flush/Unload + CPU-fallback triage, clone-length FAQ. Hardening: preflight fails open for custom model pins, ROCm curation no longer inherits NVIDIA picks, Windows mic probe reads the NonPackaged consent key, CaptureWidget setup race fixed, offline-cache CI simulation fixes so empty-cache runners stay green. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> |
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5ca9f54e47 |
docs: migration guide for stranded Real-Time-Voice-Cloning users + sharper local-first promise (#1085)
RTVC (CorentinJ's 50k-star SV2TTS repo) is archived; its users need a maintained home. New docs/migration/real-time-voice-cloning.md maps every RTVC concept to its OmniVoice equivalent (encoder+utterance → reference clip, toolbox → app, vocoder choice → Settings → Engines, demo_cli.py → REST API/CLI/MCP), is honest about what RTVC did that we don't (research toolbox, three-stage training, MIT license, smaller footprint), and walks the first clone with verified UI labels only. Wired into docs/features.yaml's existence-checked docs list and linked from the README Quickstart. README tagline now states the local-first promise verbatim at the very top: "No accounts. No API keys. No cloud." — everything else on the front page is unchanged. Co-authored-by: mergetest <test@local> Co-authored-by: Claude Fable 5 <noreply@anthropic.com> |
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5a7d9cc05c |
feat(asr): generic OpenAI-compatible transcription backend (#877) (#1003)
First slice of the community's two-track proposal for #877: a generic OpenAI-compatible ASR backend that works TODAY, without waiting on transformers to ship a direct Qwen3-ASR integration (tracked separately, still blocked upstream). Points OmniVoice's transcription at any server exposing POST /v1/audio/transcriptions — a self-hosted Qwen3-ASR/ FunASR/SenseVoice server, or OpenAI's own API. - New OpenAICompatASRBackend (backend/services/asr_backend.py): a pure network client, no local model, no install. Prefers response_format=verbose_json for real per-segment timestamps, degrades to plain text (matching MoonshineASRBackend's shape) when a minimal server rejects that format. Never leaks a raw SDK/httpx exception to the caller (#977 convention) — wraps network/auth failures in a clean, actionable RuntimeError naming the server. - Settings persist via the same encrypted-secret convention as services/llm_providers.py (settings_store.set_secret for the API key — Fernet-encrypted, never a .env row, never echoed back; get_text/ set_text for base_url/model). New GET/PUT /api/settings/ asr-openai-compat, loopback-gated like every other settings route. - Frontend: a small settings panel (Settings → Models) mirroring HFMirrorPanel's exact structure. No ASR engine picker exists yet for ANY ASR backend (only TTS has one) — activating this engine still needs OMNIVOICE_ASR_BACKEND=openai-compat-asr; documented plainly rather than pretending otherwise. - README's ASR Engines table (9 → 10 engines) and docs/features.yaml's drift-checker inventory updated; the '9 engines, all fully local' claim corrected since this one genuinely isn't. - docs/engines/openai-compatible-asr.md: setup steps + an explicit privacy note (unlike every other ASR engine, audio leaves the machine to whatever server is configured). Regression tests: tests/test_asr_openai_compat_877.py (12 tests) — is_available() gating, verbose_json + plain-text response adaptation, network-failure error hygiene, SDK retry disabling, and the settings endpoints' persist/mask/clear-vs-unchanged semantics. Fixed two real full-suite-only failures found during verification (not brushed aside): the API route inventory snapshot needed regenerating for the two new routes, and this file's own tests had a module- staleness bug — a collection-time settings_store import went stale relative to a test-time-fresh fixture when another test elsewhere in the ~2400-test suite reimports the module — fixed by making settings_store itself a fixture resolved at test-run time, same lesson already applied to tests/test_mm2_lifecycle.py earlier this session. Co-authored-by: mergetest <test@local> Co-authored-by: Claude Fable 5 <noreply@anthropic.com> |
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3d0705fdb7 |
feat(engines): Confucius4-TTS — finalized (API-validated + unit-tested; opt-in, GPU run pending) (#590) (#637)
* feat(engines): Confucius4-TTS scaffold (opt-in, needs hardware validation) (#590) Plumbing for netease-youdao's Confucius4-TTS — LLM-based 14-language cross-lingual zero-shot voice cloning, Apache-2.0 — mirroring the opt-in subprocess-venv pattern of dots.tts / MOSS-TTS-v1.5: - engines/confucius4/__init__.py: Confucius4Backend(SubprocessBackend), CUDA-only (gpu_compat=("cuda",)), language passthrough, ref_audio→prompt_wav. is_available reports a clear reason and stays unavailable without a clone. - bootstrap.py: dedicated Python 3.10 venv resolution (user clone-level venv → package venv → uv bootstrap), import-probed on `confuciustts`. - main.py: sidecar speaking the same length-prefixed JSON-over-stdio protocol as the other engines, calling ConfuciusTTS(config_path, device).generate(text, lang, prompt_wav). - Registered lazily in _LAZY_REGISTRY; docs/engines/confucius4-tts.md. Gated behind OMNIVOICE_CONFUCIUS4_TTS_DIR — inert on every default install, never imports the upstream package unless opted in. The sidecar's synthesis API is derived from the upstream README and is NOT yet validated on a CUDA box; the module, docs, and CHANGELOG all flag this. 4 tests pin registration + inert-by-default. No version bump. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(#590): register Confucius4 in install-hints + docs inventory (CI gates) Registering the engine tripped two completeness gates: every backend needs an install_hint (test_issue_fixes) and every registry engine must appear in the tts_engines docs inventory + README (check-docs-drift). Add the install_hint, the docs/features.yaml entry, and the README engine-table row (with the scaffold caveat). Docs-drift clean; gates pass. No version bump. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(confucius4): finalize — validate API vs upstream, add 22 sidecar unit tests, document external deps (Amphion/w2v-bert/weights) The synthesis API (ConfuciusTTS(config_path, device) → generate(text, lang, prompt_wav) → tensor, model.sample_rate) is confirmed against the netease-youdao/Confucius4-TTS repo. Added runnable unit tests for the sidecar's pure logic (language norm, tensor→PCM mono/stereo/clip, config resolution, wire framing, synthesize dispatch with the model mocked) — 22 cases, all green. Docs now list the external deps (Amphion/MaskGCT codec, facebook/w2v-bert-2.0, ~2-4GB HF checkpoint) and CUDA 12.6. Softened the scaffold warnings to reflect API-validated + unit-tested status; a one-time CUDA GPU run is still needed to confirm live inference + true sample rate. --------- Co-authored-by: mergetest <test@local> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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022a3bd6b9 |
feat(dictation): live local dictation via sherpa-onnx + Voice settings panel (#683)
* feat(dictation): live local dictation via sherpa-onnx + Voice settings panel Add a sherpa-onnx ASR engine alongside the existing Whisper/NeMo dictation path, powering a genuinely live experience: as you speak, words type straight into the focused field (streaming partials via a new simulate_type command, self-correcting with backspaces) and commit per pause. Backend: - SherpaDictationBackend + sherpa_dictation registry of the 7 models (Parakeet TDT v3/v2, streaming Zipformer EN/ZH/bilingual, Paraformer bilingual, Whisper Tiny) from csukuangfj/* int8 HF repos; CPU provider for cross-platform parity. - /dictation/models + /dictation/prefs router; get_capture_asr_backend() honors the selected dictation model. get_active_asr_backend() (dub transcription) and the legacy WebM/Opus capture path are untouched. - True streaming over /ws/transcribe (OnlineRecognizer: live partials + per-endpoint finals); offline models surface partials via short re-decode. Frontend: - New "Voice" settings panel (enable, Toggle/Hold mode, model picker with offline/streaming/recommended badges + per-model download/delete). - Live word-by-word typing via simulate_type (enigo) with prefix-diff delta and backspace correction; paste fallback retained, no double-insertion. Deps: sherpa-onnx>=1.13.3 (+ sherpa-onnx-core); uv.lock regenerated, Docker frozen-install verified. API route-inventory snapshot updated. 40+ new tests. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(dictation): register sherpa-onnx-asr engine in README + features inventory Fixes the docs-drift CI guard: the new sherpa-onnx-asr ASR engine existed in the registry but not in docs/features.yaml or README. Adds the live-dictation engine row to the ASR Engines table, bumps the engine counts (8→9), and adds the inventory entry. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(changelog): fold live-dictation into the [0.3.8] section main is 0.3.8 (untagged), so the dictation feature belongs in that release, not a separate [Unreleased] block. Merge the two Added lists under one [0.3.8], refresh the headline to lead with live dictation, and correct the capture description to reflect live word-by-word typing (not paste-on-pause). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: mergetest <test@local> Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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mergetestandClaude Opus 4.8
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3777d3a62c |
feat(tts): add MOSS-TTS-v1.5 (8B) and dots.tts (2B) as opt-in engines (#498)
Adds two zero-shot voice-cloning TTS engines requested in #498, both opt-in and subprocess-isolated with their own dedicated venv — the same pattern as IndexTTS-2. The dedicated venv is forced, not just chosen: each upstream pins a transformers version that conflicts with the parent's >=5.3 (MOSS-TTS-v1.5 ==5.0.0, dots.tts ==4.57.0), so they cannot share the parent interpreter. Because they use the clone+venv bootstrap (env var -> clone -> uv venv), this touches no pyproject.toml / uv.lock / bun.lock — `uv sync --all-extras` and Docker's `bun install --frozen-lockfile` are unchanged, so main's CI/Docker matrix stays green. Engines: - moss-tts-v15: 8B, 31 langs, ~16 GB weights, 24 kHz. AutoModel/ AutoProcessor via trust_remote_code. gpu_compat=(cuda,cpu) — MPS is undocumented/untested upstream so it is never claimed; on a Mac it runs on CPU. Apache-2.0, no license gate. - dots-tts: 2B, 24 langs, ~9 GB weights, 48 kHz. DotsTtsRuntime; continuation cloning (prompt_audio_path+prompt_text). Upstream is Linux/macOS-only, so is_available() gates it off cleanly on Windows (cross-platform parity rule — it is opt-in, never a broken default). Wiring: registered in _LAZY_REGISTRY + _INSTALL_HINTS. list_backends() surfaces both as subprocess/[cuda,cpu]/available-until-installed; the data-driven Settings engine picker needs no frontend change. Tests (19, fail-before/pass-after): registry resolution, subprocess marker, no-MPS gpu_compat, the Windows gate, not-installed honesty, and the parent-side generate() kwarg arbitration. Existing engine suite still 55 passed / 5 skipped. Sidecar inference follows the upstream-documented APIs but, like IndexTTS/Supertonic, can't be executed in CI without the multi-GB model clones. Docs (same-PR per docs-sync rule): README + README_CN engine tables, new docs/engines/moss-tts-v15.md + dots-tts.md, disk-usage.md (torch-dedup note), CHANGELOG. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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Palash DebnathandClaude Fable 5
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11c498eeb5 |
ci(docs): daily docs-drift job — canonical inventory vs README/docs/registries (Wave 0.1) (#353)
docs/features.yaml is the curated single source of truth (12 features, 11 TTS + 7 ASR engine ids, required install docs). scripts/check-docs-drift.py diffs it against README.md, docs/, and the engine registries — parsing registry keys from source so the CI runner never imports torch. The daily workflow updates ONE rolling 'docs-drift' issue in place and auto-closes it when clean (pattern adapted from Patter, MIT). Self-test includes a real-repo-is-clean gate, so any PR that changes engines/features without updating the inventory fails CI too. Spec: docs/competitive-analysis.md Spec 9a / parity program Wave 0.1. Co-authored-by: Claude Fable 5 <noreply@anthropic.com> |