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https://github.com/jamiepine/voicebox.git
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Compare commits
2
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 James PineandClaude Opus 4.6
|
a10024fbd8 | ||
|
James PineandClaude Opus 4.6
|
7ebf57d8f4 |
@@ -1,299 +0,0 @@
|
||||
---
|
||||
name: triage-prs
|
||||
description: Use this skill to triage the open PR queue before a release. Classifies every open PR into must-merge, candidate, superseded, or deferred; writes a working triage doc; and runs the merge loop end-to-end. Designed for the pre-release "PR speedrun" pass where a solo maintainer wants to clear the inbound backlog in a single session.
|
||||
---
|
||||
|
||||
# Triage PRs
|
||||
|
||||
## Goal
|
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|
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Turn a backlog of open PRs into a shipped set of merges in a single focused session. Produce a tracked, resumable plan (`<VERSION>_PR_TRIAGE.md`), then work it — rebasing where needed, merging in isolation-safe batches, applying post-merge follow-ups, and closing superseded or partially-applicable PRs with credit to their authors.
|
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|
||||
This skill pairs with `draft-release-notes` and `release-bump`: triage first, then draft notes against the new main, then cut the release.
|
||||
|
||||
## When to use
|
||||
|
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- Before a minor or major release when 10+ open PRs have accumulated
|
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- When you want to unblock merging without losing the narrative of what's landing
|
||||
- When you know you can't personally review every PR deeply, but need to land the critical subset fast
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- `gh` CLI authenticated against the repo
|
||||
- A dedicated worktree for PR review (avoid contaminating `main` with checkouts of contributor branches)
|
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- Clarity on the target version — the triage doc is named after it (e.g. `0.4.0_PR_TRIAGE.md`)
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|
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## Workflow
|
||||
|
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### 1. Set up an isolated PR-review worktree
|
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|
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```bash
|
||||
git worktree list # check for stale ones first
|
||||
git worktree prune
|
||||
git worktree add ../voicebox-pr-review -b pr-review-<VERSION> main
|
||||
```
|
||||
|
||||
Keep the main worktree for release-prep work (changelog drafts, direct-to-main follow-ups). Keep the review worktree for `gh pr checkout` — each checkout moves HEAD to a contributor branch, which you don't want to do in the main worktree.
|
||||
|
||||
### 2. Gather metadata for every open PR
|
||||
|
||||
```bash
|
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gh pr list --state open --limit 50 --json \
|
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number,title,author,isDraft,mergeable,mergeStateStatus,files,additions,deletions,reviewDecision,statusCheckRollup,maintainerCanModify \
|
||||
--jq '.[] | {num: .number, title, author: .author.login, mergeable, state: .mergeStateStatus, canModify: .maintainerCanModify, changes: "+\(.additions)/-\(.deletions)", files: [.files[].path]}'
|
||||
```
|
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|
||||
You want, for each PR:
|
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- Size (`+additions/-deletions`)
|
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- Mergeable state (`CLEAN`, `UNSTABLE`, `DIRTY` = conflicts, `UNKNOWN` = GitHub still computing)
|
||||
- Whether maintainer edits are allowed on the branch (needed later if you rebase for the author)
|
||||
- File paths touched (helps spot overlaps between PRs)
|
||||
|
||||
`UNKNOWN` is common right after a push to main — just try the merge and see.
|
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|
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### 3. Classify into tiers
|
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|
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Sort each PR into exactly one bucket:
|
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|
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**Tier 1 — Merge:** small, mergeable, fixes a real bug, clean CI, low review cost. One-liners, dependency relaxations, targeted safety hardening. These are the easy wins.
|
||||
|
||||
**Tier 2 — Candidate, review:** medium size (50-200 lines), touches more surface area, looks sound but needs a closer read. New user-facing features that fit the product direction.
|
||||
|
||||
**Supersede:** the fix or feature is already covered by something merged. Close with a comment pointing to the superseding PR. Check carefully — "similar title" isn't proof; compare the actual diffs.
|
||||
|
||||
**Defer to next release:** big features, dirty conflicts, draft PRs, anything touching the release pipeline in ways that would introduce risk. Don't merge these in a speedrun — they need dedicated focus.
|
||||
|
||||
### 4. Write the triage doc
|
||||
|
||||
Create `<VERSION>_PR_TRIAGE.md` in the PR-review worktree root. Structure:
|
||||
|
||||
```markdown
|
||||
# <Repo> <VERSION> — PR Triage
|
||||
|
||||
Working doc for tracking which open PRs land in <VERSION>. Delete after release cut.
|
||||
|
||||
Last updated: <DATE>
|
||||
|
||||
## Progress
|
||||
|
||||
**Tier 1: 0 / N merged**
|
||||
**Tier 2: 0 / M handled**
|
||||
**Supersede triage: pending**
|
||||
|
||||
---
|
||||
|
||||
## Merge for <VERSION> — critical bug fixes
|
||||
|
||||
| PR | Status | Size | What it fixes | Why must-have |
|
||||
|---|---|---|---|---|
|
||||
| [#123](url) | [ ] | +5/-0 | ... | ... |
|
||||
|
||||
## Strong candidate — needs a quick review
|
||||
|
||||
| PR | Status | Size | Summary |
|
||||
|---|---|---|---|
|
||||
|
||||
## Close as superseded
|
||||
|
||||
| PR | Status | Reason |
|
||||
|---|---|---|
|
||||
|
||||
## Defer to <NEXT_VERSION>
|
||||
|
||||
- [#xxx](url) ... — reason
|
||||
|
||||
---
|
||||
|
||||
## Order of attack
|
||||
|
||||
1. Close superseded PRs (one-liner comments)
|
||||
2. Merge tier-1 in dependency-free batches — check file paths don't overlap
|
||||
3. Review tier-2 individually
|
||||
4. Rerun `draft-release-notes` to pick up everything
|
||||
5. Run `release-bump`
|
||||
```
|
||||
|
||||
The **Progress** header is the most important part — it's your scoreboard and lets you resume cleanly if the session gets interrupted.
|
||||
|
||||
### 5. Work the loop — per PR
|
||||
|
||||
For each PR in the tier-1 / tier-2 list:
|
||||
|
||||
**a. Checkout in the review worktree:**
|
||||
```bash
|
||||
cd ../voicebox-pr-review
|
||||
git checkout pr-review-<VERSION> # reset to neutral base
|
||||
gh pr checkout <N>
|
||||
```
|
||||
|
||||
**b. Read the *actual* commit, not `main..HEAD`:**
|
||||
|
||||
```bash
|
||||
git show HEAD # the PR's actual changes
|
||||
git show --stat HEAD # files touched + line counts
|
||||
```
|
||||
|
||||
**Do NOT review via `git diff main..HEAD`** if the PR branch is older than main. That diff includes *every commit that landed on main after the PR was forked* as `-` (deletion) lines. A 3-line PR can look like a 700-line revert. This is the single easiest way to misjudge a PR.
|
||||
|
||||
**c. Evaluate concerns:** correctness, scope, interaction with already-merged work, version compatibility (e.g. can't use an API that requires a dependency version we don't yet pin).
|
||||
|
||||
**d. Rebase if the branch is behind main:**
|
||||
```bash
|
||||
git fetch origin main
|
||||
git rebase origin/main
|
||||
```
|
||||
|
||||
This is **essential** before squash-merging. GitHub's squash computes `diff(PR-head, merge-base)` — on a stale branch, that diff includes reverting every in-between commit. Rebasing moves the merge-base forward so the squash is clean.
|
||||
|
||||
**e. If maintainer edits are allowed, push the rebase back to the contributor's fork:**
|
||||
```bash
|
||||
git remote add <author> https://github.com/<author>/<repo>.git
|
||||
git fetch <author> <branch> # get their ref first
|
||||
git push <author> HEAD:<branch> --force-with-lease
|
||||
```
|
||||
|
||||
This keeps GitHub's PR UI in sync with the rebased state and makes the merge clean from the GitHub side.
|
||||
|
||||
**f. Merge:**
|
||||
```bash
|
||||
gh pr merge <N> --squash
|
||||
```
|
||||
|
||||
**g. Update the triage doc** — flip the checkbox to `✅ merged <sha>` (use the short SHA from `gh pr view <N> --json mergeCommit --jq '.mergeCommit.oid[0:7]'`). Update the Progress header.
|
||||
|
||||
### 6. Batch tiny fixes
|
||||
|
||||
PRs with ≤5 line changes, clean CI, non-overlapping file paths, and obviously-correct intent (e.g. one-line dependency relax, env var add, import path fix) can be merged in a single loop without the review-per-PR ceremony:
|
||||
|
||||
```bash
|
||||
for pr in 425 384 416 429; do
|
||||
echo "=== Merging PR $pr ==="
|
||||
gh pr merge $pr --squash
|
||||
done
|
||||
```
|
||||
|
||||
Verify afterward that each landed cleanly:
|
||||
```bash
|
||||
for pr in 425 384 416 429; do
|
||||
gh pr view $pr --json state,mergeCommit --jq "{pr: $pr, state, sha: .mergeCommit.oid[0:7]}"
|
||||
done
|
||||
```
|
||||
|
||||
### 7. Post-merge follow-ups
|
||||
|
||||
Sometimes a PR is worth merging despite a known minor issue (e.g. incomplete dtype map, stale sentinel cleanup). Don't block the merge; apply the follow-up as a normal branch + PR right after:
|
||||
|
||||
```bash
|
||||
cd <main-worktree>
|
||||
git pull --ff-only origin main
|
||||
git checkout -b fix/<short-name>
|
||||
# edit...
|
||||
git commit -m "fix(<area>): <one-liner>"
|
||||
git push -u origin fix/<short-name>
|
||||
gh pr create --title "..." --body "Follow-up to #<N>. ..."
|
||||
```
|
||||
|
||||
Record both SHAs in the triage doc (`✅ merged <pr-sha> + follow-up <pr>`).
|
||||
|
||||
**Direct-to-main exception:** only under an explicit, scoped policy (e.g. "release speedrun"). Don't default to it.
|
||||
|
||||
### 8. Supersede: close with a credit-pointing comment
|
||||
|
||||
```bash
|
||||
gh pr close <N> --comment "Closing — superseded by merged #<M> which landed <brief description>. Thanks!"
|
||||
```
|
||||
|
||||
Check the diffs first — "similar title" is not enough. If the PR is *partially* superseded (the diagnosis is right but only half the changes are still needed), do a partial-apply instead.
|
||||
|
||||
### 9. Partial-apply pattern
|
||||
|
||||
When a PR has both valuable and questionable changes bundled:
|
||||
|
||||
```bash
|
||||
cd <main-worktree>
|
||||
git pull --ff-only origin main
|
||||
|
||||
# Cherry-pick specific files from the PR branch
|
||||
git checkout <pr-commit-sha> -- <file1> <file2>
|
||||
|
||||
# Review the staged changes, adjust as needed
|
||||
git diff --cached
|
||||
|
||||
# Apply any surgical edits to files you don't want to bulk-replace
|
||||
# (e.g. the PR's file predates a recent main commit you need to preserve)
|
||||
|
||||
# Commit with a trailer crediting the original author
|
||||
git commit -m "$(cat <<'EOF'
|
||||
<subject>
|
||||
|
||||
<body explaining what was kept vs dropped>
|
||||
|
||||
Co-Authored-By: <author> <[email protected]>
|
||||
EOF
|
||||
)"
|
||||
git push ... # branch + PR, unless under the direct-to-main exception
|
||||
```
|
||||
|
||||
Then close the PR with a comment explaining what was applied and what was dropped, referencing the commit SHA.
|
||||
|
||||
### 10. Keep the doc current
|
||||
|
||||
Every merge, every close, every follow-up → update `<VERSION>_PR_TRIAGE.md`. The doc is your session log. If you're interrupted and resume tomorrow, the doc is the only source of truth for "where am I."
|
||||
|
||||
### 11. When triage is done
|
||||
|
||||
- Every PR in the doc has a terminal status (✅ merged / ✅ closed / deferred)
|
||||
- Progress header shows N/N for each tier
|
||||
- Next skill to run is `draft-release-notes` (to regenerate `[Unreleased]` against the new main), then `release-bump`
|
||||
|
||||
You can delete the triage doc after the release ships, or keep it in version history as a record.
|
||||
|
||||
## Gotchas
|
||||
|
||||
- **`main..HEAD` on a stale branch lies.** It shows everything main gained since the branch split as deletions. Always review via `git show HEAD` for the PR's actual commit.
|
||||
- **Squash-merging an unrebased branch reverts in-between work.** The squash computes `diff(PR-head, merge-base)`. Rebase moves the merge-base forward.
|
||||
- **`mergeable=UNKNOWN`** is transient — GitHub is recomputing after a push. Just try the merge.
|
||||
- **Route ordering matters (FastAPI and similar):** `DELETE /history/failed` must be registered *before* `DELETE /history/{id}`, or the parameterized path will consume `"failed"` as an ID.
|
||||
- **Apple's `-weak_framework` overrides `-framework`** for the same framework, regardless of order — use it via `cargo:rustc-link-arg=-Wl,-weak_framework,Name` when a dependency hard-links something optional.
|
||||
- **Dependency version floors constrain what you can apply.** Before accepting a kwarg rename like `torch_dtype=` → `dtype=`, check the min-version pin supports it. Sometimes the right move is to cherry-pick half the PR.
|
||||
- **`cpal::Stream` and similar `!Send` audio types** can't cross `await` points or `spawn_blocking`. Sometimes a "not-ideal but correct" sync wait is the best available fix; flag but don't block.
|
||||
- **PyTorch nightly builds are not shippable for releases** — non-deterministic, can regress between runs. If a PR suggests switching to nightly to fix a GPU issue, prefer `TORCH_CUDA_ARCH_LIST=...+PTX` or wait for stable support instead.
|
||||
|
||||
## Canonical commands reference
|
||||
|
||||
```bash
|
||||
# Bulk PR metadata
|
||||
gh pr list --state open --limit 50 --json number,title,author,mergeable,mergeStateStatus,additions,deletions,maintainerCanModify,files
|
||||
|
||||
# Detailed single-PR view
|
||||
gh pr view <N> --json body,author,headRefName,baseRefName,mergeable,maintainerCanModify,files,statusCheckRollup
|
||||
|
||||
# The actual commit, not the branch-vs-main diff
|
||||
git show HEAD
|
||||
git show --stat HEAD
|
||||
gh pr diff <N>
|
||||
|
||||
# Rebase contributor branch onto current main
|
||||
git fetch origin main && git rebase origin/main
|
||||
|
||||
# Push rebase back to contributor fork (maintainerCanModify=true required)
|
||||
git remote add <author> https://github.com/<author>/<repo>.git
|
||||
git fetch <author> <branch>
|
||||
git push <author> HEAD:<branch> --force-with-lease
|
||||
|
||||
# Merge
|
||||
gh pr merge <N> --squash
|
||||
|
||||
# Confirm merge SHA for triage doc
|
||||
gh pr view <N> --json state,mergeCommit --jq '{state, sha: .mergeCommit.oid[0:7]}'
|
||||
|
||||
# Close superseded
|
||||
gh pr close <N> --comment "Closing — superseded by merged #<M>. Thanks!"
|
||||
```
|
||||
|
||||
## Notes
|
||||
|
||||
- **Never review a stale branch via `main..HEAD`.** This is the single most important line in this skill.
|
||||
- **The triage doc is the session state.** Lose the doc, lose the session. Update it after every action.
|
||||
- **Credit contributors even on partial-applies.** Use `Co-Authored-By:` trailers and close comments that link to the applied commit.
|
||||
- **Don't let perfect be the enemy of shipped.** A fix that goes from "broken" to "works with a minor known issue" is a strict improvement. Flag the issue, file a follow-up, merge the fix.
|
||||
+1
-1
@@ -1,5 +1,5 @@
|
||||
[bumpversion]
|
||||
current_version = 0.4.0
|
||||
current_version = 0.3.1
|
||||
commit = True
|
||||
tag = True
|
||||
tag_name = v{new_version}
|
||||
|
||||
@@ -38,6 +38,7 @@ biome.json
|
||||
.bumpversion.cfg
|
||||
.npmrc
|
||||
Makefile
|
||||
CHANGELOG.md
|
||||
CONTRIBUTING.md
|
||||
SECURITY.md
|
||||
LICENSE
|
||||
|
||||
@@ -203,12 +203,6 @@ jobs:
|
||||
- name: Build CUDA server binary (onedir)
|
||||
shell: bash
|
||||
working-directory: backend
|
||||
env:
|
||||
# Include Blackwell (sm_120) via PTX forward compatibility.
|
||||
# Pre-built PyTorch cu128 wheels ship native kernels for sm_80/86/89/90
|
||||
# but not sm_120. Setting this env var causes torch.utils.cpp_extension
|
||||
# (and any JIT-compiled kernels) to target Blackwell GPUs as well.
|
||||
TORCH_CUDA_ARCH_LIST: "8.0;8.6;8.9;9.0;12.0+PTX"
|
||||
run: python build_binary.py --cuda
|
||||
|
||||
- name: Package into server core + CUDA libs archives
|
||||
|
||||
+1
-114
@@ -7,117 +7,6 @@
|
||||
|
||||
## [Unreleased]
|
||||
|
||||
## [0.4.0] - 2026-04-16
|
||||
|
||||
The biggest Voicebox release yet. Three new TTS engines bring the lineup to **seven** — HumeAI TADA, Kokoro 82M, and Qwen CustomVoice join Qwen3-TTS, LuxTTS, Chatterbox Multilingual, and Chatterbox Turbo. GPU support broadens to Intel Arc (XPU) and NVIDIA Blackwell (RTX 50-series), with runtime diagnostics that warn when your PyTorch build doesn't match your GPU. The CUDA backend is now split into independently versioned server and library archives, so upgrading no longer redownloads 4 GB of PyTorch/CUDA DLLs.
|
||||
|
||||
This release also marks a big community moment: **13 new contributors** shipped fixes and features in 0.4.0. Thirty-plus bug fixes target the most-reported issues in the tracker — numpy 2.x TTS crashes, Windows background-server reliability, macOS 11 launch failures, audio playback silence, Stories clip-splitting races, history status staleness, and more.
|
||||
|
||||
### New TTS Engines
|
||||
|
||||
#### HumeAI TADA — Expressive English & Multilingual ([#296](https://github.com/jamiepine/voicebox/pull/296))
|
||||
- Added `tada-1b` (English) and `tada-3b-ml` (multilingual) backends
|
||||
- Replaced `descript-audio-codec` with a lightweight DAC shim to cut dependencies
|
||||
- Switched audio decoding to `soundfile` to sidestep `torchcodec` bundling issues
|
||||
- Redirected gated Llama tokenizer lookups to an ungated mirror so model loading works out of the box
|
||||
- Fixed tokenizer patch that was corrupting `AutoTokenizer` for other engines
|
||||
- Fixed TorchScript error in frozen builds
|
||||
|
||||
#### Kokoro 82M — Fast Lightweight TTS ([#325](https://github.com/jamiepine/voicebox/pull/325))
|
||||
- Added Kokoro 82M engine with a new voice profile type system that distinguishes preset voices from cloned profiles
|
||||
- Profile grid now handles engine compatibility directly — removed redundant dropdown filtering
|
||||
- Tightened Kokoro profile handling so preset voices can't be edited like cloned profiles
|
||||
|
||||
#### Qwen CustomVoice ([#328](https://github.com/jamiepine/voicebox/pull/328))
|
||||
- Added `qwen-custom-voice` preset engine backed by Qwen3-TTS
|
||||
- Enforced preset/profile engine compatibility across the generation flow
|
||||
- Floating generator now shows all engines instead of silently filtering
|
||||
|
||||
### Voice Profile UX
|
||||
|
||||
Until 0.4, every engine in Voicebox was a cloning model, so every voice profile was usable with every engine and the profile grid just showed them all. Introducing Kokoro and Qwen CustomVoice — which work from preset voices rather than cloned samples — broke that assumption for the first time. An early cut on `main` filtered the grid by the selected engine, which left users running pre-release builds thinking their cloned voices had vanished whenever they switched to a preset-only engine.
|
||||
|
||||
This release ships the resolution before it ever reaches a tagged version:
|
||||
|
||||
- **Grey-out instead of filter** — all profiles are always visible; unsupported ones render dimmed with a compatibility hint at the bottom of the grid
|
||||
- **Auto-switch on selection** — clicking a greyed-out profile selects it AND switches the engine to a compatible one, instead of silently doing nothing
|
||||
- **Instruct toggle restored for Qwen CustomVoice** — the floating generate box now reveals a delivery-instructions input (tone, emotion, pace) when CustomVoice is selected. Hidden across the board while the new multi-engine lineup was stabilizing because most engines don't honor the kwarg; now conditionally exposed only for the one engine that was actually trained for instruction-based style control
|
||||
- Supported profiles sort first; the grid scrolls the selected profile into view after engine/sort changes
|
||||
- Fixed engine desync on tab navigation — the form now initializes its engine from the store
|
||||
- Fixed the disabled-and-selected card click edge case by bouncing selection to re-trigger the auto-switch
|
||||
- Cleaned up scroll effect timers (requestAnimationFrame + setTimeout) to prevent stale DOM writes on unmount or rapid selection changes
|
||||
|
||||
### GPU & Platform
|
||||
|
||||
#### Intel Arc (XPU) Support ([#320](https://github.com/jamiepine/voicebox/pull/320))
|
||||
- First-class Intel Arc support across all PyTorch-based backends
|
||||
- Device-aware seeding, XPU detection in the GPU status panel, and setup flow detection
|
||||
- Reports correct device name and VRAM in settings
|
||||
|
||||
#### Blackwell / RTX 50-series Support ([#316](https://github.com/jamiepine/voicebox/pull/316), [#401](https://github.com/jamiepine/voicebox/pull/401))
|
||||
- Upgraded the CUDA backend from cu126 → cu128 for RTX 50-series support
|
||||
- Added `sm_120+PTX` to the CUDA build via `TORCH_CUDA_ARCH_LIST` for forward-compatibility with Blackwell architectures (closes 5 open reports: #386, #395, #396, #399, #400)
|
||||
- GPU settings UI fixes around install/uninstall state
|
||||
|
||||
#### GPU Compatibility Diagnostics ([#367](https://github.com/jamiepine/voicebox/pull/367), adapted)
|
||||
- New `check_cuda_compatibility()` compares the current device's compute capability against the bundled PyTorch's architecture list
|
||||
- Health endpoint exposes a `gpu_compatibility_warning` field so the UI can surface mismatches
|
||||
- Startup logs a `WARN` when the installed PyTorch build doesn't support the detected GPU
|
||||
- GPU status label shows `[UNSUPPORTED - see logs]` — no more silent "no kernel image" failures
|
||||
|
||||
#### Split CUDA Backend ([#298](https://github.com/jamiepine/voicebox/pull/298))
|
||||
- CUDA backend now ships as two independently versioned archives: a small server binary and a large libs archive (the ~4 GB of PyTorch/CUDA DLLs)
|
||||
- Upgrading Voicebox no longer redownloads the libs archive when only the server binary changed
|
||||
- Added `asyncio.Lock` around `download_cuda_binary()` so auto-update and manual download can't race on the same temp file ([#428](https://github.com/jamiepine/voicebox/pull/428))
|
||||
- Updated `package_cuda.py` for PyInstaller 6.18 onedir layout
|
||||
- Temp archives are always cleaned up on failure, even when the install aborts mid-extract
|
||||
|
||||
### Bug Fixes
|
||||
|
||||
#### Critical: TTS Generation
|
||||
- **numpy 2.x `torch.from_numpy` crash** ([#361](https://github.com/jamiepine/voicebox/pull/361)) — torch compiled against numpy 1.x ABI fails silently when paired with numpy 2.x, causing `RuntimeError: Numpy is not available` / `Unable to create tensor` on every TTS request in bundled macOS Intel / Rosetta builds. Pinned `numpy<2.0` in requirements and added a PyInstaller runtime hook with a `ctypes.memmove` fallback as belt-and-suspenders. Hardened afterward to raise on unknown dtypes instead of silently reinterpreting bytes as float32.
|
||||
|
||||
#### Platform Reliability
|
||||
- **Windows background server** ([#402](https://github.com/jamiepine/voicebox/pull/402)) — "keep server running after close" now actually keeps the server running. The HTTP `/watchdog/disable` request could lose the race against process exit on Windows; added a `.keep-running` sentinel file as a synchronous fallback, with stale-sentinel cleanup on startup to avoid orphan server processes
|
||||
- **macOS 11 launch crash** ([#424](https://github.com/jamiepine/voicebox/pull/424)) — weak-linked ScreenCaptureKit so the app can launch on macOS < 12.3 instead of crashing at dyld resolution. Gated system audio capture behind a real `sw_vers` version check so unsupported systems cleanly advertise "not available" rather than crashing at runtime
|
||||
- **macOS Intel (x86_64) setup** ([#416](https://github.com/jamiepine/voicebox/pull/416)) — relaxed `torch>=2.7.0` → `torch>=2.2.0`. PyTorch dropped pre-built x86_64 wheels after 2.2.2, so Intel Mac devs could no longer `pip install`. Now resolves to the latest compatible torch per platform
|
||||
- **Offline model loading** ([#318](https://github.com/jamiepine/voicebox/pull/318)) — Qwen TTS and Whisper force offline mode when loading cached models, so startup works without network access
|
||||
- **GUI startup with external server** ([#319](https://github.com/jamiepine/voicebox/pull/319)) — fixed GUI launch when pointed at a remote/external server, and added data refresh on server switch; hardened health validation and error handling
|
||||
- **Qwen3-TTS cache split on Windows** (adapted from [#218](https://github.com/jamiepine/voicebox/pull/218)) — route `Qwen3TTSModel.from_pretrained` through `hf_constants.HF_HUB_CACHE` so the speech tokenizer and `preprocessor_config.json` resolve from a single cache root
|
||||
- **Qwen3-TTS bundling** ([#305](https://github.com/jamiepine/voicebox/pull/305)) — bundle `qwen_tts` source files in the PyInstaller build to fix `inspect.getsource` errors in frozen builds
|
||||
- **Backend import paths** ([#345](https://github.com/jamiepine/voicebox/pull/345)) — moved lazy imports to top-level with absolute paths to resolve the "Failed to Save" preset error caused by `ModuleNotFoundError` in production builds
|
||||
- **Effects service import** ([#384](https://github.com/jamiepine/voicebox/pull/384)) — fixed `ModuleNotFoundError` on preset create/update by switching to relative imports (#349)
|
||||
|
||||
#### Audio & Playback
|
||||
- **cpal stream silent playback** ([#405](https://github.com/jamiepine/voicebox/pull/405)) — `cpal::Stream` was dropped on function return immediately after `play()`, causing every playback to fall silent. Now holds the stream until either the buffer drains or the stop flag fires (#404)
|
||||
|
||||
#### Stories & History
|
||||
- **Clip-splitting race** ([#403](https://github.com/jamiepine/voicebox/pull/403)) — rapid double-clicks on split could race through `split_story_item` with inconsistent state. Added `with_for_update()` row locking on the backend and an `isPending` guard on the frontend (#366)
|
||||
- **History `status` staleness** ([#394](https://github.com/jamiepine/voicebox/pull/394)) — `GET /history/{id}` was hardcoding `status="completed"` regardless of the DB row, breaking any client polling for job completion. Now returns `status`, `error`, `engine`, `model_size`, and `is_favorited` from the actual row
|
||||
- **"Clear failed" bulk button** ([#412](https://github.com/jamiepine/voicebox/pull/412)) — new `DELETE /history/failed` endpoint and a header strip showing `"N failed generations"` with a Clear button, complementing the per-row trash icon added in #321 (#410)
|
||||
- **Delete failed generations** ([#321](https://github.com/jamiepine/voicebox/pull/321)) — added a trash icon next to the retry button so failed entries can be cleaned up without having to retry first
|
||||
|
||||
#### Security & Safety
|
||||
- **Voice prompt cache hardening** ([#429](https://github.com/jamiepine/voicebox/pull/429)) — `torch.load(weights_only=True)` on cached voice prompts per PyTorch 2.6 recommendation; replaced string-based SPA path guard with `Path.is_relative_to()` for more robust path-traversal protection
|
||||
|
||||
#### Infrastructure & Docker
|
||||
- **Docker web build** ([#344](https://github.com/jamiepine/voicebox/pull/344)) — include `CHANGELOG.md` in the Docker web build so the in-app changelog page works in Docker deployments
|
||||
- **Docker numba cache** ([#425](https://github.com/jamiepine/voicebox/pull/425)) — set `NUMBA_CACHE_DIR` in docker-compose so numba can write its JIT cache in container runtime (#308)
|
||||
- **Relative media paths** ([#332](https://github.com/jamiepine/voicebox/pull/332)) — media paths now stored relative to the configured data dir rather than resolved against CWD, so the data directory is portable between installs
|
||||
|
||||
### Developer Tooling
|
||||
|
||||
- New `triage-prs` agent skill — encodes the end-to-end PR-speedrun workflow (classification → triage doc → rebase → squash-merge → follow-ups) so future release cycles can reproduce it
|
||||
- Rewrote the TTS engine guide with the patterns learned from adding TADA and Kokoro
|
||||
- Added the API refactor plan and CUDA libs addon design doc
|
||||
- Fixed broken links in the Get Started section ([#332](https://github.com/jamiepine/voicebox/pull/332))
|
||||
|
||||
### New Contributors
|
||||
|
||||
Huge thank you to everyone who contributed their first PR to Voicebox in this release:
|
||||
|
||||
[@liorshahverdi](https://github.com/liorshahverdi), [@nicoschtein](https://github.com/nicoschtein), [@ArfianID](https://github.com/ArfianID), [@aimaaaimaa](https://github.com/aimaaaimaa), [@maxmcoding](https://github.com/maxmcoding), [@Khalodddd](https://github.com/Khalodddd), [@LuisSambrano](https://github.com/LuisSambrano), [@shaun0927](https://github.com/shaun0927), [@malletfils](https://github.com/malletfils), [@mvanhorn](https://github.com/mvanhorn), [@kuishou68](https://github.com/kuishou68), [@txhno](https://github.com/txhno), [@MukundaKatta](https://github.com/MukundaKatta)
|
||||
|
||||
## [0.3.0] - 2026-03-17
|
||||
|
||||
This release rewrites the backend into a modular architecture, overhauls the settings UI into routed sub-pages, fixes audio player freezing, migrates documentation to Fumadocs, and ships a batch of bug fixes targeting the most-reported issues from the tracker.
|
||||
@@ -555,9 +444,7 @@ The first public release of Voicebox — an open-source voice synthesis studio p
|
||||
|
||||
Tauri v2, React, TypeScript, Tailwind CSS, FastAPI, Qwen3-TTS, Whisper, SQLite
|
||||
|
||||
[Unreleased]: https://github.com/jamiepine/voicebox/compare/v0.4.0...HEAD
|
||||
[0.4.0]: https://github.com/jamiepine/voicebox/compare/v0.3.0...v0.4.0
|
||||
[0.3.0]: https://github.com/jamiepine/voicebox/compare/v0.2.3...v0.3.0
|
||||
[Unreleased]: https://github.com/jamiepine/voicebox/compare/v0.2.3...HEAD
|
||||
[0.2.3]: https://github.com/jamiepine/voicebox/compare/v0.2.2...v0.2.3
|
||||
[0.2.2]: https://github.com/jamiepine/voicebox/compare/v0.2.1...v0.2.2
|
||||
[0.2.1]: https://github.com/jamiepine/voicebox/compare/v0.1.13...v0.2.1
|
||||
|
||||
+1
-1
@@ -9,7 +9,7 @@ FROM oven/bun:1 AS frontend
|
||||
WORKDIR /build
|
||||
|
||||
# Copy workspace config and frontend source
|
||||
COPY package.json bun.lock CHANGELOG.md ./
|
||||
COPY package.json bun.lock ./
|
||||
COPY app/ ./app/
|
||||
COPY web/ ./web/
|
||||
|
||||
|
||||
+1
-1
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@voicebox/app",
|
||||
"version": "0.4.0",
|
||||
"version": "0.3.1",
|
||||
"private": true,
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
|
||||
+9
-98
@@ -4,8 +4,6 @@ import voiceboxLogo from '@/assets/voicebox-logo.png';
|
||||
import ShinyText from '@/components/ShinyText';
|
||||
import { TitleBarDragRegion } from '@/components/TitleBarDragRegion';
|
||||
import { useAutoUpdater } from '@/hooks/useAutoUpdater';
|
||||
import { apiClient } from '@/lib/api/client';
|
||||
import type { HealthResponse } from '@/lib/api/types';
|
||||
import { TOP_SAFE_AREA_PADDING } from '@/lib/constants/ui';
|
||||
import { cn } from '@/lib/utils/cn';
|
||||
import { usePlatform } from '@/platform/PlatformContext';
|
||||
@@ -13,33 +11,6 @@ import { router } from '@/router';
|
||||
import { useLogStore } from '@/stores/logStore';
|
||||
import { useServerStore } from '@/stores/serverStore';
|
||||
|
||||
/**
|
||||
* Validate that a health response has the expected Voicebox-specific shape.
|
||||
* Prevents misidentifying an unrelated service on the same port.
|
||||
*/
|
||||
function isVoiceboxHealthResponse(health: HealthResponse): boolean {
|
||||
return (
|
||||
health?.status === 'healthy' &&
|
||||
typeof health.model_loaded === 'boolean' &&
|
||||
typeof health.gpu_available === 'boolean'
|
||||
);
|
||||
}
|
||||
|
||||
/**
|
||||
* Check whether a startup error indicates the port is occupied by an external
|
||||
* server (which we should try to reuse via health-check polling) vs. a real
|
||||
* failure (missing sidecar, signing issue, etc.) that should surface immediately.
|
||||
*/
|
||||
function isPortInUseError(error: unknown): boolean {
|
||||
const msg = error instanceof Error ? error.message : String(error);
|
||||
return (
|
||||
msg.includes('already in use') ||
|
||||
msg.includes('port') ||
|
||||
msg.includes('EADDRINUSE') ||
|
||||
msg.includes('address already in use')
|
||||
);
|
||||
}
|
||||
|
||||
const LOADING_MESSAGES = [
|
||||
'Warming up tensors...',
|
||||
'Calibrating synthesizer engine...',
|
||||
@@ -66,7 +37,6 @@ const LOADING_MESSAGES = [
|
||||
function App() {
|
||||
const platform = usePlatform();
|
||||
const [serverReady, setServerReady] = useState(false);
|
||||
const [startupError, setStartupError] = useState<string | null>(null);
|
||||
const [loadingMessageIndex, setLoadingMessageIndex] = useState(0);
|
||||
const serverStartingRef = useRef(false);
|
||||
|
||||
@@ -152,46 +122,6 @@ function App() {
|
||||
serverStartingRef.current = false;
|
||||
// @ts-expect-error - adding property to window
|
||||
window.__voiceboxServerStartedByApp = false;
|
||||
|
||||
// Only fall back to health-check polling when the error indicates the
|
||||
// port is occupied (likely an external server). For real failures
|
||||
// (missing sidecar, signing issues, etc.) surface the error immediately.
|
||||
if (!isPortInUseError(error)) {
|
||||
const msg = error instanceof Error ? error.message : String(error);
|
||||
console.error('Real startup failure — not polling:', msg);
|
||||
setStartupError(msg);
|
||||
return;
|
||||
}
|
||||
|
||||
// Fall back to polling: the server may already be running externally
|
||||
// (e.g. started via python/uvicorn/Docker). Poll the health endpoint
|
||||
// until it responds with a valid Voicebox payload, then transition to
|
||||
// the main UI.
|
||||
console.log('Falling back to health-check polling...');
|
||||
const pollInterval = setInterval(async () => {
|
||||
try {
|
||||
const health = await apiClient.getHealth();
|
||||
if (!isVoiceboxHealthResponse(health)) {
|
||||
console.log('Health response is not from a Voicebox server, keep polling...');
|
||||
return;
|
||||
}
|
||||
console.log('External Voicebox server detected via health check');
|
||||
clearInterval(pollInterval);
|
||||
setServerReady(true);
|
||||
} catch {
|
||||
// Server not ready yet, keep polling
|
||||
}
|
||||
}, 2000);
|
||||
|
||||
// Stop polling after 2 minutes and surface the failure
|
||||
setTimeout(() => {
|
||||
clearInterval(pollInterval);
|
||||
serverStartingRef.current = false;
|
||||
setStartupError(
|
||||
'Could not connect to a Voicebox server within 2 minutes. ' +
|
||||
'Please check that the server is running and try again.',
|
||||
);
|
||||
}, 120_000);
|
||||
});
|
||||
|
||||
// Cleanup: stop server on actual unmount (not StrictMode remount)
|
||||
@@ -238,34 +168,15 @@ function App() {
|
||||
className="w-48 h-48 object-contain animate-fade-in-scale relative z-10"
|
||||
/>
|
||||
</div>
|
||||
{startupError ? (
|
||||
<div className="animate-fade-in-delayed max-w-md mx-auto space-y-3">
|
||||
<p className="text-lg font-medium text-destructive">Server startup failed</p>
|
||||
<p className="text-sm text-muted-foreground">{startupError}</p>
|
||||
<button
|
||||
type="button"
|
||||
className="mt-2 px-4 py-2 text-sm rounded-md bg-primary text-primary-foreground hover:bg-primary/90 transition-colors"
|
||||
onClick={() => {
|
||||
setStartupError(null);
|
||||
serverStartingRef.current = false;
|
||||
// Trigger a re-mount of the effect by toggling state
|
||||
window.location.reload();
|
||||
}}
|
||||
>
|
||||
Retry
|
||||
</button>
|
||||
</div>
|
||||
) : (
|
||||
<div className="animate-fade-in-delayed">
|
||||
<ShinyText
|
||||
text={LOADING_MESSAGES[loadingMessageIndex]}
|
||||
className="text-lg font-medium text-muted-foreground"
|
||||
speed={2}
|
||||
color="hsl(var(--muted-foreground))"
|
||||
shineColor="hsl(var(--foreground))"
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
<div className="animate-fade-in-delayed">
|
||||
<ShinyText
|
||||
text={LOADING_MESSAGES[loadingMessageIndex]}
|
||||
className="text-lg font-medium text-muted-foreground"
|
||||
speed={2}
|
||||
color="hsl(var(--muted-foreground))"
|
||||
shineColor="hsl(var(--foreground))"
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
|
||||
@@ -14,17 +14,15 @@ interface AppFrameProps {
|
||||
export function AppFrame({ children }: AppFrameProps) {
|
||||
const routerState = useRouterState();
|
||||
const isStoriesRoute = routerState.location.pathname === '/stories';
|
||||
|
||||
|
||||
const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
|
||||
const { data: story } = useStory(selectedStoryId);
|
||||
|
||||
|
||||
// Show track editor when on stories route with a selected story that has items
|
||||
const showTrackEditor = isStoriesRoute && selectedStoryId && story && story.items.length > 0;
|
||||
|
||||
return (
|
||||
<div
|
||||
className={cn('h-screen bg-background flex flex-col overflow-hidden', TOP_SAFE_AREA_PADDING)}
|
||||
>
|
||||
<div className={cn('h-screen bg-background flex flex-col overflow-hidden', TOP_SAFE_AREA_PADDING)}>
|
||||
<TitleBarDragRegion />
|
||||
{children}
|
||||
{showTrackEditor ? (
|
||||
|
||||
@@ -1,20 +1,20 @@
|
||||
import { EffectsDetail } from './EffectsDetail';
|
||||
import { EffectsList } from './EffectsList';
|
||||
import {EffectsDetail} from "./EffectsDetail";
|
||||
import {EffectsList} from "./EffectsList";
|
||||
|
||||
export function EffectsTab() {
|
||||
return (
|
||||
<div className="flex flex-col h-full min-h-0 overflow-hidden">
|
||||
<div className="flex-1 min-h-0 flex gap-6 overflow-hidden">
|
||||
{/* Left - Presets list */}
|
||||
<div className="w-full max-w-[360px] shrink-0 flex flex-col min-h-0">
|
||||
<EffectsList />
|
||||
</div>
|
||||
return (
|
||||
<div className="flex flex-col h-full min-h-0 overflow-hidden">
|
||||
<div className="flex-1 min-h-0 flex gap-6 overflow-hidden">
|
||||
{/* Left - Presets list */}
|
||||
<div className="w-full max-w-[360px] shrink-0 flex flex-col min-h-0">
|
||||
<EffectsList />
|
||||
</div>
|
||||
|
||||
{/* Right - Detail / editor */}
|
||||
<div className="flex-1 min-h-0 flex flex-col">
|
||||
<EffectsDetail />
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
{/* Right - Detail / editor */}
|
||||
<div className="flex-1 min-h-0 flex flex-col">
|
||||
<EffectsDetail />
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import { useQuery } from '@tanstack/react-query';
|
||||
import { useMatchRoute } from '@tanstack/react-router';
|
||||
import { AnimatePresence, motion } from 'framer-motion';
|
||||
import { Loader2, SlidersHorizontal, Sparkles } from 'lucide-react';
|
||||
import { Loader2, Sparkles } from 'lucide-react';
|
||||
import { useEffect, useRef, useState } from 'react';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import { Form, FormControl, FormField, FormItem, FormMessage } from '@/components/ui/form';
|
||||
@@ -40,7 +40,6 @@ export function FloatingGenerateBox({
|
||||
const { data: selectedProfile } = useProfile(selectedProfileId || '');
|
||||
const { data: profiles } = useProfiles();
|
||||
const [isExpanded, setIsExpanded] = useState(false);
|
||||
const [isInstructExpanded, setIsInstructExpanded] = useState(false);
|
||||
const [selectedPresetId, setSelectedPresetId] = useState<string | null>(null);
|
||||
const containerRef = useRef<HTMLDivElement>(null);
|
||||
const textareaRef = useRef<HTMLTextAreaElement | null>(null);
|
||||
@@ -126,14 +125,7 @@ export function FloatingGenerateBox({
|
||||
}, [watchedEngine, setSelectedEngine]);
|
||||
|
||||
// Sync generation form language, engine, and effects with selected profile
|
||||
type EngineValue =
|
||||
| 'qwen'
|
||||
| 'luxtts'
|
||||
| 'chatterbox'
|
||||
| 'chatterbox_turbo'
|
||||
| 'tada'
|
||||
| 'kokoro'
|
||||
| 'qwen_custom_voice';
|
||||
type EngineValue = 'qwen' | 'luxtts' | 'chatterbox' | 'chatterbox_turbo' | 'tada' | 'kokoro' | 'qwen_custom_voice';
|
||||
useEffect(() => {
|
||||
if (selectedProfile?.language) {
|
||||
form.setValue('language', selectedProfile.language as LanguageCode);
|
||||
@@ -354,80 +346,9 @@ export function FloatingGenerateBox({
|
||||
: 'Generate speech'}
|
||||
</span>
|
||||
</div>
|
||||
|
||||
{/* Instruct toggle — only for Qwen CustomVoice, which actually honors the kwarg */}
|
||||
<AnimatePresence>
|
||||
{isExpanded && form.watch('engine') === 'qwen_custom_voice' && (
|
||||
<motion.div
|
||||
initial={{ opacity: 0, scale: 0.8 }}
|
||||
animate={{ opacity: 1, scale: 1 }}
|
||||
exit={{ opacity: 0, scale: 0.8 }}
|
||||
transition={{ duration: 0.2 }}
|
||||
className="absolute top-0 right-[calc(100%+0.5rem)]"
|
||||
>
|
||||
<div className="group relative">
|
||||
<Button
|
||||
type="button"
|
||||
variant="ghost"
|
||||
size="icon"
|
||||
onClick={() => setIsInstructExpanded((prev) => !prev)}
|
||||
className={cn(
|
||||
'h-10 w-10 rounded-full transition-all duration-200',
|
||||
isInstructExpanded
|
||||
? 'bg-accent text-accent-foreground border border-accent hover:bg-accent/90'
|
||||
: 'bg-card border border-border hover:bg-background/50',
|
||||
)}
|
||||
aria-label={
|
||||
isInstructExpanded
|
||||
? 'Hide delivery instructions'
|
||||
: 'Show delivery instructions'
|
||||
}
|
||||
aria-pressed={isInstructExpanded}
|
||||
>
|
||||
<SlidersHorizontal className="h-4 w-4" />
|
||||
</Button>
|
||||
<span className="pointer-events-none absolute bottom-full left-1/2 -translate-x-1/2 mb-2 whitespace-nowrap rounded-md bg-popover px-3 py-1.5 text-xs text-popover-foreground border border-border opacity-0 transition-opacity group-hover:opacity-100 z-[9999]">
|
||||
Delivery instructions (tone, emotion, pace)
|
||||
</span>
|
||||
</div>
|
||||
</motion.div>
|
||||
)}
|
||||
</AnimatePresence>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Additive instruct textarea — shown below main text when toggle is on and engine supports it */}
|
||||
<AnimatePresence>
|
||||
{isInstructExpanded && form.watch('engine') === 'qwen_custom_voice' && (
|
||||
<motion.div
|
||||
initial={{ opacity: 0, height: 0 }}
|
||||
animate={{ opacity: 1, height: 'auto' }}
|
||||
exit={{ opacity: 0, height: 0 }}
|
||||
transition={{ duration: 0.2, ease: 'easeOut' }}
|
||||
className="overflow-hidden"
|
||||
>
|
||||
<FormField
|
||||
control={form.control}
|
||||
name="instruct"
|
||||
render={({ field }) => (
|
||||
<FormItem className="mt-2">
|
||||
<FormControl>
|
||||
<Textarea
|
||||
{...field}
|
||||
placeholder="Delivery instructions — e.g. Speak slowly with warmth, Authoritative and clear..."
|
||||
className="resize-none bg-transparent border border-accent/20 focus-visible:ring-1 focus-visible:ring-accent/40 rounded-2xl text-sm placeholder:text-muted-foreground/60 w-full px-3 py-2"
|
||||
style={{ minHeight: '60px', maxHeight: '160px' }}
|
||||
maxLength={500}
|
||||
/>
|
||||
</FormControl>
|
||||
<FormMessage className="text-xs" />
|
||||
</FormItem>
|
||||
)}
|
||||
/>
|
||||
</motion.div>
|
||||
)}
|
||||
</AnimatePresence>
|
||||
|
||||
<AnimatePresence>
|
||||
<motion.div
|
||||
initial={{ height: 0, opacity: 0 }}
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
import { Loader2, Mic } from 'lucide-react';
|
||||
import { useEffect } from 'react';
|
||||
import { Loader2, Mic } from 'lucide-react';
|
||||
import { Button } from '@/components/ui/button';
|
||||
import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
|
||||
import {
|
||||
@@ -24,11 +24,7 @@ import { getLanguageOptionsForEngine, type LanguageCode } from '@/lib/constants/
|
||||
import { useGenerationForm } from '@/lib/hooks/useGenerationForm';
|
||||
import { useProfile } from '@/lib/hooks/useProfiles';
|
||||
import { useUIStore } from '@/stores/uiStore';
|
||||
import {
|
||||
applyEngineSelection,
|
||||
EngineModelSelector,
|
||||
getEngineDescription,
|
||||
} from './EngineModelSelector';
|
||||
import { EngineModelSelector, applyEngineSelection, getEngineDescription } from './EngineModelSelector';
|
||||
import { ParalinguisticInput } from './ParalinguisticInput';
|
||||
|
||||
function getEngineSelectValue(engine: string): string {
|
||||
@@ -118,7 +114,7 @@ export function GenerationForm() {
|
||||
)}
|
||||
/>
|
||||
|
||||
{form.watch('engine') === 'qwen_custom_voice' && (
|
||||
{(form.watch('engine') === 'qwen' || form.watch('engine') === 'qwen_custom_voice') && (
|
||||
<FormField
|
||||
control={form.control}
|
||||
name="instruct"
|
||||
|
||||
@@ -45,7 +45,6 @@ import { apiClient } from '@/lib/api/client';
|
||||
import type { EffectConfig, GenerationVersionResponse, HistoryResponse } from '@/lib/api/types';
|
||||
import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
|
||||
import {
|
||||
useClearFailedGenerations,
|
||||
useDeleteGeneration,
|
||||
useExportGeneration,
|
||||
useExportGenerationAudio,
|
||||
@@ -125,8 +124,6 @@ export function HistoryTable() {
|
||||
});
|
||||
|
||||
const deleteGeneration = useDeleteGeneration();
|
||||
const clearFailed = useClearFailedGenerations();
|
||||
const [clearFailedDialogOpen, setClearFailedDialogOpen] = useState(false);
|
||||
const exportGeneration = useExportGeneration();
|
||||
const exportGenerationAudio = useExportGenerationAudio();
|
||||
const importGeneration = useImportGeneration();
|
||||
@@ -160,11 +157,11 @@ export function HistoryTable() {
|
||||
const pendingCount = useGenerationStore((state) => state.pendingGenerationIds.size);
|
||||
const prevPendingCountRef = useRef(pendingCount);
|
||||
useEffect(() => {
|
||||
if (deleteGeneration.isSuccess || importGeneration.isSuccess || clearFailed.isSuccess) {
|
||||
if (deleteGeneration.isSuccess || importGeneration.isSuccess) {
|
||||
setPage(0);
|
||||
setAllHistory([]);
|
||||
}
|
||||
}, [deleteGeneration.isSuccess, importGeneration.isSuccess, clearFailed.isSuccess]);
|
||||
}, [deleteGeneration.isSuccess, importGeneration.isSuccess]);
|
||||
|
||||
useEffect(() => {
|
||||
// A generation finished (pending count decreased) — scroll back to show it
|
||||
@@ -418,27 +415,6 @@ export function HistoryTable() {
|
||||
|
||||
const history = allHistory;
|
||||
const hasMore = allHistory.length < total;
|
||||
const failedCount = history.filter((g) => g.status === 'failed').length;
|
||||
|
||||
const handleClearFailedConfirm = () => {
|
||||
clearFailed.mutate(undefined, {
|
||||
onSuccess: (data) => {
|
||||
setClearFailedDialogOpen(false);
|
||||
toast({
|
||||
title: 'Cleared failed generations',
|
||||
description: `${data.deleted} failed ${data.deleted === 1 ? 'generation' : 'generations'} removed.`,
|
||||
});
|
||||
},
|
||||
onError: (error) => {
|
||||
setClearFailedDialogOpen(false);
|
||||
toast({
|
||||
title: 'Failed to clear',
|
||||
description: error instanceof Error ? error.message : 'Unknown error',
|
||||
variant: 'destructive',
|
||||
});
|
||||
},
|
||||
});
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="flex flex-col h-full min-h-0 relative">
|
||||
@@ -448,23 +424,6 @@ export function HistoryTable() {
|
||||
</div>
|
||||
) : (
|
||||
<>
|
||||
{failedCount > 0 && (
|
||||
<div className="flex items-center justify-between px-1 pb-2">
|
||||
<span className="text-xs text-muted-foreground">
|
||||
{failedCount} failed {failedCount === 1 ? 'generation' : 'generations'}
|
||||
</span>
|
||||
<Button
|
||||
variant="ghost"
|
||||
size="sm"
|
||||
className="h-7 text-xs text-muted-foreground hover:text-destructive"
|
||||
onClick={() => setClearFailedDialogOpen(true)}
|
||||
disabled={clearFailed.isPending}
|
||||
>
|
||||
<Trash2 className="h-3 w-3 mr-1.5" />
|
||||
{clearFailed.isPending ? 'Clearing...' : 'Clear failed'}
|
||||
</Button>
|
||||
</div>
|
||||
)}
|
||||
{isScrolled && (
|
||||
<div className="absolute top-0 left-0 right-0 h-16 bg-gradient-to-b from-background to-transparent z-10 pointer-events-none" />
|
||||
)}
|
||||
@@ -800,31 +759,6 @@ export function HistoryTable() {
|
||||
</DialogContent>
|
||||
</Dialog>
|
||||
|
||||
<Dialog open={clearFailedDialogOpen} onOpenChange={setClearFailedDialogOpen}>
|
||||
<DialogContent>
|
||||
<DialogHeader>
|
||||
<DialogTitle>Clear failed generations</DialogTitle>
|
||||
<DialogDescription>
|
||||
This will permanently delete {failedCount} failed{' '}
|
||||
{failedCount === 1 ? 'generation' : 'generations'} from your history. This cannot be
|
||||
undone.
|
||||
</DialogDescription>
|
||||
</DialogHeader>
|
||||
<DialogFooter>
|
||||
<Button variant="outline" onClick={() => setClearFailedDialogOpen(false)}>
|
||||
Cancel
|
||||
</Button>
|
||||
<Button
|
||||
variant="destructive"
|
||||
onClick={handleClearFailedConfirm}
|
||||
disabled={clearFailed.isPending}
|
||||
>
|
||||
{clearFailed.isPending ? 'Clearing...' : 'Clear all'}
|
||||
</Button>
|
||||
</DialogFooter>
|
||||
</DialogContent>
|
||||
</Dialog>
|
||||
|
||||
<Dialog open={importDialogOpen} onOpenChange={setImportDialogOpen}>
|
||||
<DialogContent>
|
||||
<DialogHeader>
|
||||
|
||||
@@ -12,11 +12,7 @@ interface ModelProgressProps {
|
||||
isDownloading?: boolean;
|
||||
}
|
||||
|
||||
export function ModelProgress({
|
||||
modelName,
|
||||
displayName,
|
||||
isDownloading = false,
|
||||
}: ModelProgressProps) {
|
||||
export function ModelProgress({ modelName, displayName, isDownloading = false }: ModelProgressProps) {
|
||||
const [progress, setProgress] = useState<ModelProgressType | null>(null);
|
||||
const serverUrl = useServerStore((state) => state.serverUrl);
|
||||
|
||||
|
||||
@@ -182,8 +182,8 @@ function ChangelogEntryCard({ entry }: { entry: ChangelogEntry }) {
|
||||
|
||||
return (
|
||||
<div className="border-b border-border/50 pb-6">
|
||||
<div className="flex items-baseline gap-3 mb-3">
|
||||
<h3 className="text-xl font-semibold tracking-tight">{entry.version}</h3>
|
||||
<div className="flex items-baseline gap-3 mb-1">
|
||||
<h3 className="text-sm font-medium">{entry.version}</h3>
|
||||
{entry.date && <span className="text-xs text-muted-foreground">{entry.date}</span>}
|
||||
{entry.version === 'Unreleased' && <Badge variant="outline">dev</Badge>}
|
||||
</div>
|
||||
|
||||
@@ -87,7 +87,7 @@ export function StoryChatItem({
|
||||
alt={`${item.profile_name} avatar`}
|
||||
className={cn(
|
||||
'h-full w-full object-cover transition-all duration-200',
|
||||
!isCurrentlyPlaying && 'grayscale',
|
||||
!isCurrentlyPlaying && 'grayscale'
|
||||
)}
|
||||
onError={() => setAvatarError(true)}
|
||||
/>
|
||||
@@ -127,10 +127,7 @@ export function StoryChatItem({
|
||||
<Play className="mr-2 h-4 w-4" />
|
||||
Play from here
|
||||
</DropdownMenuItem>
|
||||
<DropdownMenuItem
|
||||
onClick={onRemove}
|
||||
className="text-destructive focus:text-destructive"
|
||||
>
|
||||
<DropdownMenuItem onClick={onRemove} className="text-destructive focus:text-destructive">
|
||||
<Trash2 className="mr-2 h-4 w-4" />
|
||||
Remove from Story
|
||||
</DropdownMenuItem>
|
||||
@@ -142,12 +139,15 @@ export function StoryChatItem({
|
||||
}
|
||||
|
||||
// Sortable wrapper component
|
||||
export function SortableStoryChatItem(
|
||||
props: Omit<StoryChatItemProps, 'dragHandleProps' | 'isDragging'>,
|
||||
) {
|
||||
const { attributes, listeners, setNodeRef, transform, transition, isDragging } = useSortable({
|
||||
id: props.item.generation_id,
|
||||
});
|
||||
export function SortableStoryChatItem(props: Omit<StoryChatItemProps, 'dragHandleProps' | 'isDragging'>) {
|
||||
const {
|
||||
attributes,
|
||||
listeners,
|
||||
setNodeRef,
|
||||
transform,
|
||||
transition,
|
||||
isDragging,
|
||||
} = useSortable({ id: props.item.generation_id });
|
||||
|
||||
const style = {
|
||||
transform: CSS.Transform.toString(transform),
|
||||
@@ -156,7 +156,11 @@ export function SortableStoryChatItem(
|
||||
|
||||
return (
|
||||
<div ref={setNodeRef} style={style} {...attributes}>
|
||||
<StoryChatItem {...props} dragHandleProps={listeners} isDragging={isDragging} />
|
||||
<StoryChatItem
|
||||
{...props}
|
||||
dragHandleProps={listeners}
|
||||
isDragging={isDragging}
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
@@ -500,7 +500,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
|
||||
}, [trimmingItem, trimSide, tempTrimValues, storyId, trimItem, toast]);
|
||||
|
||||
const handleSplit = useCallback(() => {
|
||||
if (!selectedClipId || splitItem.isPending) return;
|
||||
if (!selectedClipId) return;
|
||||
|
||||
const item = items.find((i) => i.id === selectedClipId);
|
||||
if (!item) return;
|
||||
|
||||
@@ -14,7 +14,12 @@ const MemoizedWaveform = memo(function MemoizedWaveform({
|
||||
<div className="absolute inset-0 pointer-events-none flex items-center justify-center opacity-30">
|
||||
<Visualizer audio={audioStream} autoStart strokeColor="#b39a3d">
|
||||
{({ canvasRef }) => (
|
||||
<canvas ref={canvasRef} width={500} height={150} className="w-full h-full" />
|
||||
<canvas
|
||||
ref={canvasRef}
|
||||
width={500}
|
||||
height={150}
|
||||
className="w-full h-full"
|
||||
/>
|
||||
)}
|
||||
</Visualizer>
|
||||
</div>
|
||||
@@ -82,7 +87,9 @@ export function AudioSampleRecording({
|
||||
<div className="space-y-4">
|
||||
{!isRecording && !file && (
|
||||
<div className="relative flex flex-col items-center justify-center gap-4 p-4 border-2 border-dashed rounded-lg min-h-[180px] overflow-hidden">
|
||||
{showWaveform && audioStream && <MemoizedWaveform audioStream={audioStream} />}
|
||||
{showWaveform && audioStream && (
|
||||
<MemoizedWaveform audioStream={audioStream} />
|
||||
)}
|
||||
<Button
|
||||
type="button"
|
||||
onClick={onStart}
|
||||
@@ -100,7 +107,9 @@ export function AudioSampleRecording({
|
||||
|
||||
{isRecording && (
|
||||
<div className="relative flex flex-col items-center justify-center gap-4 p-4 border-2 border-accent rounded-lg bg-accent/5 min-h-[180px] overflow-hidden">
|
||||
{showWaveform && audioStream && <MemoizedWaveform audioStream={audioStream} />}
|
||||
{showWaveform && audioStream && (
|
||||
<MemoizedWaveform audioStream={audioStream} />
|
||||
)}
|
||||
<div className="relative z-10 flex items-center gap-4">
|
||||
<div className="flex items-center gap-2">
|
||||
<div className="h-3 w-3 rounded-full bg-accent animate-pulse" />
|
||||
|
||||
@@ -28,9 +28,7 @@ export function ProfileList() {
|
||||
// Temporarily apply scroll-margin so it doesn't land flush at the top
|
||||
el.style.scrollMarginTop = '180px';
|
||||
el.scrollIntoView({ behavior: 'smooth', block: 'nearest', inline: 'nearest' });
|
||||
timeoutId = setTimeout(() => {
|
||||
el.style.scrollMarginTop = '';
|
||||
}, 500);
|
||||
timeoutId = setTimeout(() => { el.style.scrollMarginTop = ''; }, 500);
|
||||
});
|
||||
return () => {
|
||||
cancelAnimationFrame(rafId);
|
||||
|
||||
@@ -111,4 +111,4 @@ export {
|
||||
AlertDialogDescription,
|
||||
AlertDialogAction,
|
||||
AlertDialogCancel,
|
||||
};
|
||||
};
|
||||
@@ -270,12 +270,6 @@ class ApiClient {
|
||||
});
|
||||
}
|
||||
|
||||
async clearFailedGenerations(): Promise<{ deleted: number }> {
|
||||
return this.request<{ deleted: number }>(`/history/failed`, {
|
||||
method: 'DELETE',
|
||||
});
|
||||
}
|
||||
|
||||
async exportGeneration(generationId: string): Promise<Blob> {
|
||||
const url = `${this.getBaseUrl()}/history/${generationId}/export`;
|
||||
const response = await fetch(url);
|
||||
|
||||
@@ -136,9 +136,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
|
||||
|
||||
const hasModelSizes =
|
||||
engine === 'qwen' || engine === 'qwen_custom_voice' || engine === 'tada';
|
||||
// Only Qwen CustomVoice actually honors the instruct kwarg at model level.
|
||||
// Base Qwen3-TTS accepts the kwarg but ignores it.
|
||||
const supportsInstruct = engine === 'qwen_custom_voice';
|
||||
const supportsInstruct = engine === 'qwen' || engine === 'qwen_custom_voice';
|
||||
const effectsChain = options.getEffectsChain?.();
|
||||
// This now returns immediately with status="generating"
|
||||
const result = await generation.mutateAsync({
|
||||
|
||||
@@ -29,17 +29,6 @@ export function useDeleteGeneration() {
|
||||
});
|
||||
}
|
||||
|
||||
export function useClearFailedGenerations() {
|
||||
const queryClient = useQueryClient();
|
||||
|
||||
return useMutation({
|
||||
mutationFn: () => apiClient.clearFailedGenerations(),
|
||||
onSuccess: () => {
|
||||
queryClient.invalidateQueries({ queryKey: ['history'] });
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
export function useExportGeneration() {
|
||||
const platform = usePlatform();
|
||||
|
||||
|
||||
@@ -131,8 +131,7 @@ export function useModelDownloadToast({
|
||||
)}
|
||||
</div>
|
||||
),
|
||||
duration:
|
||||
progress.status === 'complete' || progress.status === 'error' ? 5000 : Infinity,
|
||||
duration: progress.status === 'complete' || progress.status === 'error' ? 5000 : Infinity,
|
||||
});
|
||||
|
||||
// Close connection and dismiss toast on completion or error
|
||||
|
||||
@@ -26,24 +26,8 @@ export function useSystemAudioCapture({
|
||||
|
||||
// Check if system audio capture is supported
|
||||
useEffect(() => {
|
||||
let isActive = true;
|
||||
|
||||
void platform.audio
|
||||
.isSystemAudioSupported()
|
||||
.then((supported) => {
|
||||
if (isActive) {
|
||||
setIsSupported(supported);
|
||||
}
|
||||
})
|
||||
.catch(() => {
|
||||
if (isActive) {
|
||||
setIsSupported(false);
|
||||
}
|
||||
});
|
||||
|
||||
return () => {
|
||||
isActive = false;
|
||||
};
|
||||
const supported = platform.audio.isSystemAudioSupported();
|
||||
setIsSupported(supported);
|
||||
}, [platform]);
|
||||
|
||||
const startRecording = useCallback(async () => {
|
||||
|
||||
@@ -1,19 +0,0 @@
|
||||
import { QueryClient } from '@tanstack/react-query';
|
||||
|
||||
/**
|
||||
* Shared QueryClient instance used across the app.
|
||||
*
|
||||
* Extracted into its own side-effect-free module so it can be imported from
|
||||
* both the React bootstrap (main.tsx) and non-React code (stores, utilities)
|
||||
* without pulling in ReactDOM or other bootstrap side effects.
|
||||
*/
|
||||
export const queryClient = new QueryClient({
|
||||
defaultOptions: {
|
||||
queries: {
|
||||
staleTime: 1000 * 60 * 5, // 5 minutes
|
||||
gcTime: 1000 * 60 * 10, // 10 minutes (formerly cacheTime)
|
||||
retry: 1,
|
||||
refetchOnWindowFocus: false,
|
||||
},
|
||||
},
|
||||
});
|
||||
+12
-2
@@ -1,10 +1,20 @@
|
||||
import { QueryClientProvider } from '@tanstack/react-query';
|
||||
import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
|
||||
// import { ReactQueryDevtools } from '@tanstack/react-query-devtools';
|
||||
import React from 'react';
|
||||
import ReactDOM from 'react-dom/client';
|
||||
import App from './App';
|
||||
import './index.css';
|
||||
import { queryClient } from './lib/queryClient';
|
||||
|
||||
const queryClient = new QueryClient({
|
||||
defaultOptions: {
|
||||
queries: {
|
||||
staleTime: 1000 * 60 * 5, // 5 minutes
|
||||
gcTime: 1000 * 60 * 10, // 10 minutes (formerly cacheTime)
|
||||
retry: 1,
|
||||
refetchOnWindowFocus: false,
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
ReactDOM.createRoot(document.getElementById('root')!).render(
|
||||
<React.StrictMode>
|
||||
|
||||
@@ -9,7 +9,11 @@ export interface PlatformProviderProps {
|
||||
}
|
||||
|
||||
export function PlatformProvider({ platform, children }: PlatformProviderProps) {
|
||||
return <PlatformContext.Provider value={platform}>{children}</PlatformContext.Provider>;
|
||||
return (
|
||||
<PlatformContext.Provider value={platform}>
|
||||
{children}
|
||||
</PlatformContext.Provider>
|
||||
);
|
||||
}
|
||||
|
||||
export function usePlatform(): Platform {
|
||||
|
||||
@@ -42,7 +42,7 @@ export interface AudioDevice {
|
||||
}
|
||||
|
||||
export interface PlatformAudio {
|
||||
isSystemAudioSupported(): Promise<boolean>;
|
||||
isSystemAudioSupported(): boolean;
|
||||
startSystemAudioCapture(maxDurationSecs: number): Promise<void>;
|
||||
stopSystemAudioCapture(): Promise<Blob>;
|
||||
listOutputDevices(): Promise<AudioDevice[]>;
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
import { create } from 'zustand';
|
||||
import { persist } from 'zustand/middleware';
|
||||
import { queryClient } from '@/lib/queryClient';
|
||||
|
||||
interface ServerStore {
|
||||
serverUrl: string;
|
||||
@@ -31,25 +30,11 @@ interface ServerStore {
|
||||
setCustomModelsDir: (dir: string | null) => void;
|
||||
}
|
||||
|
||||
/**
|
||||
* Invalidate all React Query caches so stale data from the previous
|
||||
* server is not shown. Called when the server URL changes.
|
||||
*/
|
||||
function invalidateAllServerData() {
|
||||
queryClient.invalidateQueries();
|
||||
}
|
||||
|
||||
export const useServerStore = create<ServerStore>()(
|
||||
persist(
|
||||
(set, get) => ({
|
||||
(set) => ({
|
||||
serverUrl: 'http://127.0.0.1:17493',
|
||||
setServerUrl: (url) => {
|
||||
const prev = get().serverUrl;
|
||||
set({ serverUrl: url });
|
||||
if (url !== prev) {
|
||||
invalidateAllServerData();
|
||||
}
|
||||
},
|
||||
setServerUrl: (url) => set({ serverUrl: url }),
|
||||
|
||||
isConnected: false,
|
||||
setIsConnected: (connected) => set({ isConnected: connected }),
|
||||
|
||||
+1
-1
@@ -1,3 +1,3 @@
|
||||
# Backend package
|
||||
|
||||
__version__ = "0.4.0"
|
||||
__version__ = "0.3.1"
|
||||
|
||||
+3
-31
@@ -135,7 +135,7 @@ def _mount_frontend(application: FastAPI) -> None:
|
||||
async def serve_spa(full_path: str):
|
||||
file_path = (frontend_dir / full_path).resolve()
|
||||
# Guard against path traversal — only serve files inside frontend_dir
|
||||
if full_path and file_path.is_file() and file_path.is_relative_to(frontend_dir):
|
||||
if full_path and file_path.is_file() and str(file_path).startswith(str(frontend_dir)):
|
||||
return FileResponse(file_path)
|
||||
return FileResponse(frontend_dir / "index.html", media_type="text/html")
|
||||
|
||||
@@ -146,36 +146,15 @@ def _get_gpu_status() -> str:
|
||||
"""Return a human-readable string describing GPU availability."""
|
||||
backend_type = get_backend_type()
|
||||
if torch.cuda.is_available():
|
||||
from .backends.base import check_cuda_compatibility
|
||||
|
||||
device_name = torch.cuda.get_device_name(0)
|
||||
compatible, _warning = check_cuda_compatibility()
|
||||
is_rocm = hasattr(torch.version, "hip") and torch.version.hip is not None
|
||||
if is_rocm:
|
||||
label = f"ROCm ({device_name})"
|
||||
else:
|
||||
label = f"CUDA ({device_name})"
|
||||
if not compatible:
|
||||
label += " [UNSUPPORTED - see logs]"
|
||||
return label
|
||||
return f"ROCm ({device_name})"
|
||||
return f"CUDA ({device_name})"
|
||||
elif hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
|
||||
return "MPS (Apple Silicon)"
|
||||
elif backend_type == "mlx":
|
||||
return "Metal (Apple Silicon via MLX)"
|
||||
|
||||
# Intel XPU (Arc / Data Center) via IPEX
|
||||
try:
|
||||
import intel_extension_for_pytorch # noqa: F401
|
||||
|
||||
if hasattr(torch, "xpu") and torch.xpu.is_available():
|
||||
try:
|
||||
xpu_name = torch.xpu.get_device_name(0)
|
||||
except Exception:
|
||||
xpu_name = "Intel GPU"
|
||||
return f"XPU ({xpu_name})"
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
return "None (CPU only)"
|
||||
|
||||
|
||||
@@ -237,13 +216,6 @@ def _register_lifecycle(application: FastAPI) -> None:
|
||||
logger.info("Backend: %s", backend_type.upper())
|
||||
logger.info("GPU: %s", _get_gpu_status())
|
||||
|
||||
# Warn if GPU architecture is not supported by this PyTorch build
|
||||
from .backends.base import check_cuda_compatibility
|
||||
|
||||
_compatible, _cuda_warning = check_cuda_compatibility()
|
||||
if not _compatible:
|
||||
logger.warning("GPU COMPATIBILITY: %s", _cuda_warning)
|
||||
|
||||
from .services.cuda import check_and_update_cuda_binary
|
||||
|
||||
create_background_task(check_and_update_cuda_binary())
|
||||
|
||||
@@ -126,75 +126,6 @@ def get_torch_device(
|
||||
return "cpu"
|
||||
|
||||
|
||||
def check_cuda_compatibility() -> tuple[bool, str | None]:
|
||||
"""Check if the installed PyTorch supports the current GPU's compute capability.
|
||||
|
||||
Returns:
|
||||
(compatible, warning_message) — compatible is True if OK or no CUDA GPU,
|
||||
warning_message is a human-readable string if there's a problem.
|
||||
"""
|
||||
import torch
|
||||
|
||||
if not torch.cuda.is_available():
|
||||
return True, None
|
||||
|
||||
major, minor = torch.cuda.get_device_capability(0)
|
||||
capability = f"{major}.{minor}"
|
||||
device_name = torch.cuda.get_device_name(0)
|
||||
sm_tag = f"sm_{major}{minor}"
|
||||
|
||||
# torch.cuda._get_arch_list() returns the SM architectures this build
|
||||
# was compiled for (e.g. ["sm_50", "sm_60", ..., "sm_90"]).
|
||||
try:
|
||||
arch_list = torch.cuda._get_arch_list()
|
||||
if arch_list:
|
||||
# Check for both sm_XX and compute_XX (JIT-compiled) entries
|
||||
compute_tag = f"compute_{major}{minor}"
|
||||
if sm_tag not in arch_list and compute_tag not in arch_list:
|
||||
return False, (
|
||||
f"{device_name} (compute capability {capability} / {sm_tag}) "
|
||||
f"is not supported by this PyTorch build. "
|
||||
f"Supported architectures: {', '.join(arch_list)}. "
|
||||
f"Install PyTorch nightly (cu128) for newer GPU support: "
|
||||
f"pip install torch --index-url https://download.pytorch.org/whl/nightly/cu128"
|
||||
)
|
||||
except AttributeError:
|
||||
pass
|
||||
|
||||
return True, None
|
||||
|
||||
|
||||
def empty_device_cache(device: str) -> None:
|
||||
"""
|
||||
Free cached memory on the given device (CUDA or XPU).
|
||||
|
||||
Backends should call this after unloading models so VRAM is returned
|
||||
to the OS.
|
||||
"""
|
||||
import torch
|
||||
|
||||
if device == "cuda" and torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
elif device == "xpu" and hasattr(torch, "xpu"):
|
||||
torch.xpu.empty_cache()
|
||||
|
||||
|
||||
def manual_seed(seed: int, device: str) -> None:
|
||||
"""
|
||||
Set the random seed on both CPU and the active accelerator.
|
||||
|
||||
Covers CUDA and Intel XPU so that generation is reproducible
|
||||
regardless of which GPU backend is in use.
|
||||
"""
|
||||
import torch
|
||||
|
||||
torch.manual_seed(seed)
|
||||
if device == "cuda" and torch.cuda.is_available():
|
||||
torch.cuda.manual_seed(seed)
|
||||
elif device == "xpu" and hasattr(torch, "xpu"):
|
||||
torch.xpu.manual_seed(seed)
|
||||
|
||||
|
||||
async def combine_voice_prompts(
|
||||
audio_paths: List[str],
|
||||
reference_texts: List[str],
|
||||
|
||||
@@ -18,8 +18,6 @@ from . import TTSBackend
|
||||
from .base import (
|
||||
is_model_cached,
|
||||
get_torch_device,
|
||||
empty_device_cache,
|
||||
manual_seed,
|
||||
combine_voice_prompts as _combine_voice_prompts,
|
||||
model_load_progress,
|
||||
patch_chatterbox_f32,
|
||||
@@ -50,7 +48,7 @@ class ChatterboxTTSBackend:
|
||||
self._model_load_lock = asyncio.Lock()
|
||||
|
||||
def _get_device(self) -> str:
|
||||
return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
|
||||
return get_torch_device(force_cpu_on_mac=True)
|
||||
|
||||
def is_loaded(self) -> bool:
|
||||
return self.model is not None
|
||||
@@ -119,7 +117,10 @@ class ChatterboxTTSBackend:
|
||||
del self.model
|
||||
self.model = None
|
||||
self._device = None
|
||||
empty_device_cache(device)
|
||||
if device == "cuda":
|
||||
import torch
|
||||
|
||||
torch.cuda.empty_cache()
|
||||
logger.info("Chatterbox unloaded")
|
||||
|
||||
async def create_voice_prompt(
|
||||
@@ -199,7 +200,7 @@ class ChatterboxTTSBackend:
|
||||
import torch
|
||||
|
||||
if seed is not None:
|
||||
manual_seed(seed, self._device)
|
||||
torch.manual_seed(seed)
|
||||
|
||||
logger.info(f"[Chatterbox] Generating: lang={language}")
|
||||
|
||||
@@ -219,7 +220,10 @@ class ChatterboxTTSBackend:
|
||||
else:
|
||||
audio = np.asarray(wav, dtype=np.float32)
|
||||
|
||||
sample_rate = getattr(self.model, "sr", None) or getattr(self.model, "sample_rate", 24000)
|
||||
sample_rate = (
|
||||
getattr(self.model, "sr", None)
|
||||
or getattr(self.model, "sample_rate", 24000)
|
||||
)
|
||||
|
||||
return audio, sample_rate
|
||||
|
||||
|
||||
@@ -18,8 +18,6 @@ from . import TTSBackend
|
||||
from .base import (
|
||||
is_model_cached,
|
||||
get_torch_device,
|
||||
empty_device_cache,
|
||||
manual_seed,
|
||||
combine_voice_prompts as _combine_voice_prompts,
|
||||
model_load_progress,
|
||||
patch_chatterbox_f32,
|
||||
@@ -50,7 +48,7 @@ class ChatterboxTurboTTSBackend:
|
||||
self._model_load_lock = asyncio.Lock()
|
||||
|
||||
def _get_device(self) -> str:
|
||||
return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
|
||||
return get_torch_device(force_cpu_on_mac=True)
|
||||
|
||||
def is_loaded(self) -> bool:
|
||||
return self.model is not None
|
||||
@@ -118,7 +116,10 @@ class ChatterboxTurboTTSBackend:
|
||||
del self.model
|
||||
self.model = None
|
||||
self._device = None
|
||||
empty_device_cache(device)
|
||||
if device == "cuda":
|
||||
import torch
|
||||
|
||||
torch.cuda.empty_cache()
|
||||
logger.info("Chatterbox Turbo unloaded")
|
||||
|
||||
async def create_voice_prompt(
|
||||
@@ -180,7 +181,7 @@ class ChatterboxTurboTTSBackend:
|
||||
import torch
|
||||
|
||||
if seed is not None:
|
||||
manual_seed(seed, self._device)
|
||||
torch.manual_seed(seed)
|
||||
|
||||
logger.info("[Chatterbox Turbo] Generating (English)")
|
||||
|
||||
@@ -199,7 +200,10 @@ class ChatterboxTurboTTSBackend:
|
||||
else:
|
||||
audio = np.asarray(wav, dtype=np.float32)
|
||||
|
||||
sample_rate = getattr(self.model, "sr", None) or getattr(self.model, "sample_rate", 24000)
|
||||
sample_rate = (
|
||||
getattr(self.model, "sr", None)
|
||||
or getattr(self.model, "sample_rate", 24000)
|
||||
)
|
||||
|
||||
return audio, sample_rate
|
||||
|
||||
|
||||
@@ -24,8 +24,6 @@ from . import TTSBackend
|
||||
from .base import (
|
||||
is_model_cached,
|
||||
get_torch_device,
|
||||
empty_device_cache,
|
||||
manual_seed,
|
||||
combine_voice_prompts as _combine_voice_prompts,
|
||||
model_load_progress,
|
||||
)
|
||||
@@ -68,7 +66,7 @@ class HumeTadaBackend:
|
||||
def _get_device(self) -> str:
|
||||
# Force CPU on macOS — MPS has issues with flow matching
|
||||
# and large vocab lm_head (>65536 output channels)
|
||||
return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
|
||||
return get_torch_device(force_cpu_on_mac=True)
|
||||
|
||||
def is_loaded(self) -> bool:
|
||||
return self.model is not None
|
||||
@@ -107,7 +105,6 @@ class HumeTadaBackend:
|
||||
# package. The real package pulls in onnx/tensorboard/matplotlib via
|
||||
# descript-audiotools, so we use a lightweight shim instead.
|
||||
from ..utils.dac_shim import install_dac_shim
|
||||
|
||||
install_dac_shim()
|
||||
|
||||
import torch
|
||||
@@ -145,12 +142,9 @@ class HumeTadaBackend:
|
||||
allow_patterns=["tokenizer*", "special_tokens*"],
|
||||
)
|
||||
|
||||
# Determine dtype — use bf16 on CUDA/XPU for ~50% memory savings
|
||||
# Determine dtype — use bf16 on CUDA for ~50% memory savings
|
||||
if device == "cuda" and torch.cuda.is_bf16_supported():
|
||||
model_dtype = torch.bfloat16
|
||||
elif device == "xpu":
|
||||
# Intel Arc (Alchemist+) supports bf16 natively
|
||||
model_dtype = torch.bfloat16
|
||||
else:
|
||||
model_dtype = torch.float32
|
||||
|
||||
@@ -159,14 +153,14 @@ class HumeTadaBackend:
|
||||
# This avoids monkey-patching AutoTokenizer.from_pretrained
|
||||
# which corrupts the classmethod descriptor for other engines.
|
||||
from tada.modules.aligner import AlignerConfig
|
||||
|
||||
AlignerConfig.tokenizer_name = tokenizer_path
|
||||
|
||||
# Load encoder (only needed for voice prompt encoding)
|
||||
from tada.modules.encoder import Encoder
|
||||
|
||||
logger.info("Loading TADA encoder...")
|
||||
self.encoder = Encoder.from_pretrained(TADA_CODEC_REPO, subfolder="encoder").to(device)
|
||||
self.encoder = Encoder.from_pretrained(
|
||||
TADA_CODEC_REPO, subfolder="encoder"
|
||||
).to(device)
|
||||
self.encoder.eval()
|
||||
|
||||
# Load the causal LM (includes decoder for wav generation).
|
||||
@@ -175,11 +169,12 @@ class HumeTadaBackend:
|
||||
# which hits the gated repo. Pre-load the config from HF,
|
||||
# inject the local tokenizer path, then pass it in.
|
||||
from tada.modules.tada import TadaForCausalLM, TadaConfig
|
||||
|
||||
logger.info(f"Loading TADA {model_size} model...")
|
||||
config = TadaConfig.from_pretrained(repo)
|
||||
config.tokenizer_name = tokenizer_path
|
||||
self.model = TadaForCausalLM.from_pretrained(repo, config=config, torch_dtype=model_dtype).to(device)
|
||||
self.model = TadaForCausalLM.from_pretrained(
|
||||
repo, config=config, torch_dtype=model_dtype
|
||||
).to(device)
|
||||
self.model.eval()
|
||||
|
||||
logger.info(f"HumeAI TADA {model_size} loaded successfully on {device}")
|
||||
@@ -193,11 +188,11 @@ class HumeTadaBackend:
|
||||
del self.encoder
|
||||
self.encoder = None
|
||||
|
||||
device = self._device
|
||||
self._device = None
|
||||
|
||||
if device:
|
||||
empty_device_cache(device)
|
||||
import torch
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
logger.info("HumeAI TADA unloaded")
|
||||
|
||||
@@ -218,7 +213,9 @@ class HumeTadaBackend:
|
||||
"""
|
||||
await self.load_model(self.model_size)
|
||||
|
||||
cache_key = ("tada_" + get_cache_key(audio_path, reference_text)) if use_cache else None
|
||||
cache_key = (
|
||||
"tada_" + get_cache_key(audio_path, reference_text)
|
||||
) if use_cache else None
|
||||
|
||||
if cache_key:
|
||||
cached = get_cached_voice_prompt(cache_key)
|
||||
@@ -242,7 +239,9 @@ class HumeTadaBackend:
|
||||
|
||||
# Encode with forced alignment
|
||||
text_arg = [reference_text] if reference_text else None
|
||||
prompt = self.encoder(audio, text=text_arg, sample_rate=sr)
|
||||
prompt = self.encoder(
|
||||
audio, text=text_arg, sample_rate=sr
|
||||
)
|
||||
|
||||
# Serialize EncoderOutput to a dict of CPU tensors for caching
|
||||
prompt_dict = {}
|
||||
@@ -300,7 +299,9 @@ class HumeTadaBackend:
|
||||
from tada.modules.encoder import EncoderOutput
|
||||
|
||||
if seed is not None:
|
||||
manual_seed(seed, self._device)
|
||||
torch.manual_seed(seed)
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.manual_seed(seed)
|
||||
|
||||
device = self._device
|
||||
|
||||
|
||||
@@ -12,14 +12,7 @@ from typing import Optional, Tuple
|
||||
import numpy as np
|
||||
|
||||
from . import TTSBackend
|
||||
from .base import (
|
||||
is_model_cached,
|
||||
get_torch_device,
|
||||
empty_device_cache,
|
||||
manual_seed,
|
||||
combine_voice_prompts as _combine_voice_prompts,
|
||||
model_load_progress,
|
||||
)
|
||||
from .base import is_model_cached, get_torch_device, combine_voice_prompts as _combine_voice_prompts, model_load_progress
|
||||
from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -37,7 +30,7 @@ class LuxTTSBackend:
|
||||
self._device = None
|
||||
|
||||
def _get_device(self) -> str:
|
||||
return get_torch_device(allow_mps=True, allow_xpu=True)
|
||||
return get_torch_device(allow_mps=True)
|
||||
|
||||
def is_loaded(self) -> bool:
|
||||
return self.model is not None
|
||||
@@ -76,12 +69,9 @@ class LuxTTSBackend:
|
||||
|
||||
if device == "cpu":
|
||||
import os
|
||||
|
||||
threads = os.cpu_count() or 4
|
||||
self.model = LuxTTS(
|
||||
model_path=LUXTTS_HF_REPO,
|
||||
device="cpu",
|
||||
threads=min(threads, 8),
|
||||
model_path=LUXTTS_HF_REPO, device="cpu", threads=min(threads, 8),
|
||||
)
|
||||
else:
|
||||
self.model = LuxTTS(model_path=LUXTTS_HF_REPO, device=device)
|
||||
@@ -91,12 +81,12 @@ class LuxTTSBackend:
|
||||
def unload_model(self) -> None:
|
||||
"""Unload model to free memory."""
|
||||
if self.model is not None:
|
||||
device = self.device
|
||||
del self.model
|
||||
self.model = None
|
||||
self._device = None
|
||||
|
||||
empty_device_cache(device)
|
||||
import torch
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
logger.info("LuxTTS unloaded")
|
||||
|
||||
@@ -164,8 +154,12 @@ class LuxTTSBackend:
|
||||
await self.load_model()
|
||||
|
||||
def _generate_sync():
|
||||
import torch
|
||||
|
||||
if seed is not None:
|
||||
manual_seed(seed, self.device)
|
||||
torch.manual_seed(seed)
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.manual_seed(seed)
|
||||
|
||||
wav = self.model.generate_speech(
|
||||
text=text,
|
||||
|
||||
@@ -6,6 +6,7 @@ from typing import Optional, List, Tuple
|
||||
import asyncio
|
||||
import logging
|
||||
import numpy as np
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -20,7 +21,6 @@ ensure_original_qwen_config_cached()
|
||||
from . import TTSBackend, STTBackend, LANGUAGE_CODE_TO_NAME, WHISPER_HF_REPOS
|
||||
from .base import is_model_cached, combine_voice_prompts as _combine_voice_prompts, model_load_progress
|
||||
from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
|
||||
from ..utils.hf_offline_patch import force_offline_if_cached
|
||||
|
||||
|
||||
class MLXTTSBackend:
|
||||
@@ -96,13 +96,32 @@ class MLXTTSBackend:
|
||||
model_name = f"qwen-tts-{model_size}"
|
||||
is_cached = self._is_model_cached(model_size)
|
||||
|
||||
with model_load_progress(model_name, is_cached):
|
||||
from mlx_audio.tts import load
|
||||
# Force offline mode when cached to avoid network requests
|
||||
original_hf_hub_offline = os.environ.get("HF_HUB_OFFLINE")
|
||||
if is_cached:
|
||||
os.environ["HF_HUB_OFFLINE"] = "1"
|
||||
logger.info("[PATCH] Model %s is cached, forcing HF_HUB_OFFLINE=1 to avoid network requests", model_size)
|
||||
|
||||
logger.info("Loading MLX TTS model %s...", model_size)
|
||||
try:
|
||||
with model_load_progress(model_name, is_cached):
|
||||
from mlx_audio.tts import load
|
||||
|
||||
with force_offline_if_cached(is_cached, model_name):
|
||||
self.model = load(model_path)
|
||||
logger.info("Loading MLX TTS model %s...", model_size)
|
||||
|
||||
try:
|
||||
self.model = load(model_path)
|
||||
except Exception as load_error:
|
||||
if is_cached and "offline" in str(load_error).lower():
|
||||
logger.warning("[PATCH] Offline load failed, trying with network: %s", load_error)
|
||||
os.environ.pop("HF_HUB_OFFLINE", None)
|
||||
self.model = load(model_path)
|
||||
else:
|
||||
raise
|
||||
finally:
|
||||
if original_hf_hub_offline is not None:
|
||||
os.environ["HF_HUB_OFFLINE"] = original_hf_hub_offline
|
||||
else:
|
||||
os.environ.pop("HF_HUB_OFFLINE", None)
|
||||
|
||||
self._current_model_size = model_size
|
||||
self.model_size = model_size
|
||||
@@ -310,9 +329,7 @@ class MLXSTTBackend:
|
||||
|
||||
model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
|
||||
logger.info("Loading MLX Whisper model %s...", model_size)
|
||||
|
||||
with force_offline_if_cached(is_cached, progress_model_name):
|
||||
self.model = load(model_name)
|
||||
self.model = load(model_name)
|
||||
|
||||
self.model_size = model_size
|
||||
logger.info("MLX Whisper model %s loaded successfully", model_size)
|
||||
|
||||
@@ -14,14 +14,11 @@ from . import TTSBackend, STTBackend, LANGUAGE_CODE_TO_NAME, WHISPER_HF_REPOS
|
||||
from .base import (
|
||||
is_model_cached,
|
||||
get_torch_device,
|
||||
empty_device_cache,
|
||||
manual_seed,
|
||||
combine_voice_prompts as _combine_voice_prompts,
|
||||
model_load_progress,
|
||||
)
|
||||
from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
|
||||
from ..utils.audio import load_audio
|
||||
from ..utils.hf_offline_patch import force_offline_if_cached
|
||||
|
||||
|
||||
class PyTorchTTSBackend:
|
||||
@@ -99,28 +96,18 @@ class PyTorchTTSBackend:
|
||||
model_path = self._get_model_path(model_size)
|
||||
logger.info("Loading TTS model %s on %s...", model_size, self.device)
|
||||
|
||||
# Route both HF Hub and Transformers through a single cache root.
|
||||
# On Windows local setups, model assets can otherwise split between
|
||||
# .hf-cache/hub and .hf-cache/transformers, causing speech_tokenizer
|
||||
# and preprocessor_config.json to fail to resolve during load.
|
||||
from huggingface_hub import constants as hf_constants
|
||||
tts_cache_dir = hf_constants.HF_HUB_CACHE
|
||||
|
||||
with force_offline_if_cached(is_cached, model_name):
|
||||
if self.device == "cpu":
|
||||
self.model = Qwen3TTSModel.from_pretrained(
|
||||
model_path,
|
||||
cache_dir=tts_cache_dir,
|
||||
torch_dtype=torch.float32,
|
||||
low_cpu_mem_usage=False,
|
||||
)
|
||||
else:
|
||||
self.model = Qwen3TTSModel.from_pretrained(
|
||||
model_path,
|
||||
cache_dir=tts_cache_dir,
|
||||
device_map=self.device,
|
||||
torch_dtype=torch.bfloat16,
|
||||
)
|
||||
if self.device == "cpu":
|
||||
self.model = Qwen3TTSModel.from_pretrained(
|
||||
model_path,
|
||||
torch_dtype=torch.float32,
|
||||
low_cpu_mem_usage=False,
|
||||
)
|
||||
else:
|
||||
self.model = Qwen3TTSModel.from_pretrained(
|
||||
model_path,
|
||||
device_map=self.device,
|
||||
torch_dtype=torch.bfloat16,
|
||||
)
|
||||
|
||||
self._current_model_size = model_size
|
||||
self.model_size = model_size
|
||||
@@ -133,7 +120,8 @@ class PyTorchTTSBackend:
|
||||
self.model = None
|
||||
self._current_model_size = None
|
||||
|
||||
empty_device_cache(self.device)
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
logger.info("TTS model unloaded")
|
||||
|
||||
@@ -225,7 +213,9 @@ class PyTorchTTSBackend:
|
||||
"""Run synchronous generation in thread pool."""
|
||||
# Set seed if provided
|
||||
if seed is not None:
|
||||
manual_seed(seed, self.device)
|
||||
torch.manual_seed(seed)
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.manual_seed(seed)
|
||||
|
||||
# Generate audio - this is the blocking operation
|
||||
wavs, sample_rate = self.model.generate_voice_clone(
|
||||
@@ -292,9 +282,8 @@ class PyTorchSTTBackend:
|
||||
model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
|
||||
logger.info("Loading Whisper model %s on %s...", model_size, self.device)
|
||||
|
||||
with force_offline_if_cached(is_cached, progress_model_name):
|
||||
self.processor = WhisperProcessor.from_pretrained(model_name)
|
||||
self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
|
||||
self.processor = WhisperProcessor.from_pretrained(model_name)
|
||||
self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
|
||||
|
||||
self.model.to(self.device)
|
||||
self.model_size = model_size
|
||||
@@ -308,7 +297,8 @@ class PyTorchSTTBackend:
|
||||
self.model = None
|
||||
self.processor = None
|
||||
|
||||
empty_device_cache(self.device)
|
||||
if torch.cuda.is_available():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
logger.info("Whisper model unloaded")
|
||||
|
||||
|
||||
@@ -52,16 +52,6 @@ def build_server(cuda=False):
|
||||
if platform.system() == "Windows":
|
||||
args.append("--noconsole")
|
||||
|
||||
# numpy 2.x / torch ABI mismatch fix: install memmove fallback for
|
||||
# torch.from_numpy() before the app starts. Runtime hooks run after
|
||||
# FrozenImporter is registered so frozen torch/numpy are importable.
|
||||
args.extend(
|
||||
[
|
||||
"--runtime-hook",
|
||||
str(backend_dir / "pyi_rth_numpy_compat.py"),
|
||||
]
|
||||
)
|
||||
|
||||
# Add local qwen_tts path if specified (for editable installs)
|
||||
qwen_tts_path = os.getenv("QWEN_TTS_PATH")
|
||||
if qwen_tts_path and Path(qwen_tts_path).exists():
|
||||
|
||||
@@ -89,14 +89,6 @@ def resolve_storage_path(path: str | Path | None) -> Path | None:
|
||||
|
||||
return stored_path
|
||||
|
||||
# 0.3.0 records sometimes stored relative paths with the data-dir name
|
||||
# baked in (e.g. "data/profiles/..."). Joining those directly with
|
||||
# _data_dir produces a spurious "<data_dir>/data/profiles/..." nest.
|
||||
if stored_path.parts and stored_path.parts[0] == "data":
|
||||
stored_path = (
|
||||
Path(*stored_path.parts[1:]) if len(stored_path.parts) > 1 else Path()
|
||||
)
|
||||
|
||||
return (_data_dir / stored_path).resolve()
|
||||
|
||||
|
||||
|
||||
@@ -182,7 +182,6 @@ class HealthResponse(BaseModel):
|
||||
vram_used_mb: Optional[float] = None
|
||||
backend_type: Optional[str] = None # Backend type (mlx or pytorch)
|
||||
backend_variant: Optional[str] = None # Binary variant (cpu or cuda)
|
||||
gpu_compatibility_warning: Optional[str] = None # Warning if GPU arch unsupported
|
||||
|
||||
|
||||
class DirectoryCheck(BaseModel):
|
||||
|
||||
@@ -1,95 +0,0 @@
|
||||
"""
|
||||
PyInstaller runtime hook: numpy 2.x / torch ABI mismatch fix.
|
||||
|
||||
Problem
|
||||
-------
|
||||
torch is compiled against numpy 1.x headers. numpy 2.x changed the version
|
||||
number returned by PyArray_GetNDArrayCVersion() (0x01000009 → 0x02000000),
|
||||
so torch's is_numpy_available() returns False and every torch.from_numpy()
|
||||
call raises:
|
||||
|
||||
RuntimeError: Numpy is not available
|
||||
|
||||
This surfaces as:
|
||||
|
||||
ValueError: Unable to create tensor, you should probably activate
|
||||
padding with 'padding=True'
|
||||
|
||||
during TTS generation (EncodecFeatureExtractor → BatchFeature.convert_to_tensors).
|
||||
|
||||
Fix
|
||||
---
|
||||
Runtime hooks execute after PyInstaller's FrozenImporter is registered, so
|
||||
frozen torch/numpy are importable here. We start a background thread that
|
||||
waits for torch to finish loading then wraps torch.from_numpy with a ctypes
|
||||
memmove fallback that bypasses the C-level numpy ABI check entirely.
|
||||
|
||||
This approach works with any numpy version and is safer than binary-patching
|
||||
libtorch_python.dylib (which risks PyArray_Descr struct layout mismatches).
|
||||
"""
|
||||
|
||||
import sys
|
||||
import threading
|
||||
|
||||
|
||||
def _patch_torch_from_numpy():
|
||||
import time
|
||||
|
||||
for _ in range(7200): # poll up to 360 s at 50 ms intervals
|
||||
time.sleep(0.05)
|
||||
torch = sys.modules.get("torch")
|
||||
if torch is None or not hasattr(torch, "from_numpy"):
|
||||
continue
|
||||
if getattr(torch, "_vb_from_numpy_patched", False):
|
||||
return
|
||||
try:
|
||||
import ctypes
|
||||
import numpy as np
|
||||
|
||||
_orig = torch.from_numpy
|
||||
|
||||
# Explicit numpy → torch dtype map. Silent fallback to float32 on
|
||||
# unknown dtypes would reinterpret the memcpy'd bytes as fp32 and
|
||||
# silently corrupt data (e.g. fp16 tensors from some TTS engines),
|
||||
# so we raise instead.
|
||||
dtype_map = {
|
||||
"float16": _t.float16,
|
||||
"float32": _t.float32,
|
||||
"float64": _t.float64,
|
||||
"int8": _t.int8,
|
||||
"int16": _t.int16,
|
||||
"int32": _t.int32,
|
||||
"int64": _t.int64,
|
||||
"uint8": _t.uint8,
|
||||
"bool": _t.bool,
|
||||
"complex64": _t.complex64,
|
||||
"complex128": _t.complex128,
|
||||
}
|
||||
|
||||
def _safe_from_numpy(
|
||||
arr, _orig=_orig, _c=ctypes, _np=np, _t=torch, _map=dtype_map
|
||||
):
|
||||
try:
|
||||
return _orig(arr)
|
||||
except RuntimeError:
|
||||
a = _np.ascontiguousarray(arr)
|
||||
key = str(a.dtype)
|
||||
if key not in _map:
|
||||
raise TypeError(
|
||||
f"pyi_rth_numpy_compat: unsupported numpy dtype "
|
||||
f"{key!r} in torch.from_numpy fallback; add an "
|
||||
f"explicit mapping rather than silently copying "
|
||||
f"bytes into the wrong dtype."
|
||||
)
|
||||
out = _t.empty(list(a.shape), dtype=_map[key])
|
||||
_c.memmove(out.data_ptr(), a.ctypes.data, a.nbytes)
|
||||
return out
|
||||
|
||||
torch.from_numpy = _safe_from_numpy
|
||||
torch._vb_from_numpy_patched = True
|
||||
except Exception:
|
||||
pass
|
||||
return
|
||||
|
||||
|
||||
threading.Thread(target=_patch_torch_from_numpy, daemon=True).start()
|
||||
@@ -8,7 +8,7 @@ sqlalchemy>=2.0.0
|
||||
alembic>=1.13.0
|
||||
|
||||
# ML models
|
||||
torch>=2.2.0
|
||||
torch>=2.7.0
|
||||
transformers>=4.36.0,<=4.57.6
|
||||
accelerate>=0.26.0
|
||||
huggingface_hub>=0.20.0
|
||||
@@ -50,7 +50,7 @@ en_core_web_sm @ https://github.com/explosion/spacy-models/releases/download/en_
|
||||
# Audio processing
|
||||
librosa>=0.10.0
|
||||
soundfile>=0.12.0
|
||||
numpy>=1.24.0,<2.0
|
||||
numpy>=1.24.0
|
||||
numba>=0.60.0,<0.61.0
|
||||
pedalboard>=0.9.0
|
||||
|
||||
|
||||
@@ -93,12 +93,6 @@ async def health():
|
||||
except ImportError:
|
||||
pass
|
||||
|
||||
gpu_compat_warning = None
|
||||
if has_cuda:
|
||||
from ..backends.base import check_cuda_compatibility
|
||||
|
||||
_compatible, gpu_compat_warning = check_cuda_compatibility()
|
||||
|
||||
gpu_available = has_cuda or has_mps or has_xpu or has_directml or backend_type == "mlx"
|
||||
|
||||
gpu_type = None
|
||||
@@ -116,11 +110,6 @@ async def health():
|
||||
vram_used = None
|
||||
if has_cuda:
|
||||
vram_used = torch.cuda.memory_allocated() / 1024 / 1024
|
||||
elif has_xpu:
|
||||
try:
|
||||
vram_used = torch.xpu.memory_allocated() / 1024 / 1024
|
||||
except Exception:
|
||||
pass # memory_allocated() may not be available on all IPEX versions
|
||||
|
||||
model_loaded = False
|
||||
model_size = None
|
||||
@@ -173,11 +162,7 @@ async def health():
|
||||
gpu_type=gpu_type,
|
||||
vram_used_mb=vram_used,
|
||||
backend_type=backend_type,
|
||||
backend_variant=os.environ.get(
|
||||
"VOICEBOX_BACKEND_VARIANT",
|
||||
"cuda" if torch.cuda.is_available() else ("xpu" if has_xpu else "cpu"),
|
||||
),
|
||||
gpu_compatibility_warning=gpu_compat_warning,
|
||||
backend_variant=os.environ.get("VOICEBOX_BACKEND_VARIANT", "cuda" if torch.cuda.is_available() else "cpu"),
|
||||
)
|
||||
|
||||
|
||||
|
||||
@@ -62,13 +62,6 @@ async def import_generation(
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.delete("/history/failed")
|
||||
async def clear_failed_generations(db: Session = Depends(get_db)):
|
||||
"""Delete every generation with status='failed'. Used by the UI's 'Clear failed' button (#410)."""
|
||||
count = await history.delete_failed_generations(db)
|
||||
return {"deleted": count}
|
||||
|
||||
|
||||
@router.get("/history/{generation_id}", response_model=models.HistoryResponse)
|
||||
async def get_generation(
|
||||
generation_id: str,
|
||||
@@ -96,11 +89,6 @@ async def get_generation(
|
||||
duration=gen.duration,
|
||||
seed=gen.seed,
|
||||
instruct=gen.instruct,
|
||||
engine=gen.engine or "qwen",
|
||||
model_size=gen.model_size,
|
||||
status=gen.status or "completed",
|
||||
error=gen.error,
|
||||
is_favorited=bool(gen.is_favorited),
|
||||
created_at=gen.created_at,
|
||||
)
|
||||
|
||||
|
||||
@@ -105,11 +105,6 @@ def _start_parent_watchdog(parent_pid, data_dir=None):
|
||||
This is the clean shutdown mechanism: instead of the Tauri app trying to
|
||||
forcefully kill the server (which spawns console windows on Windows),
|
||||
the server monitors its parent and shuts itself down gracefully.
|
||||
|
||||
The Tauri app writes a .keep-running sentinel file to data_dir before
|
||||
exiting when "remain running after close" is enabled. This is a reliable
|
||||
fallback for the HTTP /watchdog/disable request, which can race with
|
||||
process exit on Windows.
|
||||
"""
|
||||
import os
|
||||
import signal
|
||||
@@ -169,19 +164,6 @@ def _start_parent_watchdog(parent_pid, data_dir=None):
|
||||
if not alive:
|
||||
watchdog_logger.warning(f"Parent PID {parent_pid} not found on first check — disabling watchdog")
|
||||
return
|
||||
# Clear any stale .keep-running sentinel from a previous session. The
|
||||
# sentinel is only removed by the watchdog when it's consumed during a
|
||||
# grace period; if the HTTP /watchdog/disable path wins the race on a
|
||||
# "keep running" exit, the sentinel is left on disk. Wipe it here so a
|
||||
# future session can't inherit that stale signal.
|
||||
if data_dir:
|
||||
stale = os.path.join(data_dir, ".keep-running")
|
||||
if os.path.exists(stale):
|
||||
try:
|
||||
os.remove(stale)
|
||||
watchdog_logger.info("Removed stale .keep-running sentinel from previous session")
|
||||
except OSError as e:
|
||||
watchdog_logger.warning(f"Failed to remove stale sentinel: {e}")
|
||||
while True:
|
||||
if _watchdog_disabled:
|
||||
watchdog_logger.info("Watchdog disabled (keep server running), stopping monitor")
|
||||
@@ -196,18 +178,6 @@ def _start_parent_watchdog(parent_pid, data_dir=None):
|
||||
if _watchdog_disabled:
|
||||
watchdog_logger.info("Watchdog was disabled during grace period, keeping server alive")
|
||||
return
|
||||
# Check for sentinel file written by Tauri before exit.
|
||||
# This catches the case where the HTTP disable request
|
||||
# didn't arrive before the parent process died (common
|
||||
# on Windows where process teardown is fast).
|
||||
sentinel = os.path.join(data_dir, ".keep-running") if data_dir else None
|
||||
if sentinel and os.path.exists(sentinel):
|
||||
watchdog_logger.info("Found .keep-running sentinel file, keeping server alive")
|
||||
try:
|
||||
os.remove(sentinel)
|
||||
except OSError:
|
||||
pass
|
||||
return
|
||||
watchdog_logger.info("Watchdog still enabled after grace period, shutting down server...")
|
||||
if sys.platform == "win32":
|
||||
# sys.exit triggers SystemExit, allowing uvicorn to run
|
||||
|
||||
@@ -11,7 +11,6 @@ Both archives are extracted into {data_dir}/backends/cuda/ which forms the
|
||||
complete PyInstaller --onedir directory structure that torch expects.
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import hashlib
|
||||
import json
|
||||
import logging
|
||||
@@ -35,12 +34,6 @@ PROGRESS_KEY = "cuda-backend"
|
||||
# CUDA toolkit version or torch's CUDA dependency changes (e.g. cu126 -> cu128).
|
||||
CUDA_LIBS_VERSION = "cu128-v1"
|
||||
|
||||
# Prevents concurrent download_cuda_binary() calls from racing on the same
|
||||
# temp file. The auto-update background task and the manual HTTP endpoint
|
||||
# can both invoke download_cuda_binary(); without this lock the progress-
|
||||
# manager status check is a TOCTOU race.
|
||||
_download_lock = asyncio.Lock()
|
||||
|
||||
|
||||
def get_backends_dir() -> Path:
|
||||
"""Directory where downloaded backend binaries are stored."""
|
||||
@@ -248,15 +241,6 @@ async def download_cuda_binary(version: Optional[str] = None):
|
||||
Args:
|
||||
version: Version tag (e.g. "v0.3.0"). Defaults to current app version.
|
||||
"""
|
||||
if _download_lock.locked():
|
||||
logger.info("CUDA download already in progress, skipping duplicate request")
|
||||
return
|
||||
async with _download_lock:
|
||||
await _download_cuda_binary_locked(version)
|
||||
|
||||
|
||||
async def _download_cuda_binary_locked(version: Optional[str] = None):
|
||||
"""Inner implementation of download_cuda_binary, called under _download_lock."""
|
||||
import httpx
|
||||
|
||||
if version is None:
|
||||
|
||||
@@ -11,8 +11,6 @@ from typing import List, Optional
|
||||
from sqlalchemy.orm import Session
|
||||
from sqlalchemy.exc import IntegrityError
|
||||
|
||||
from ..utils.effects import validate_effects_chain
|
||||
|
||||
from ..database import EffectPreset as DBEffectPreset
|
||||
from ..models import EffectPresetResponse, EffectPresetCreate, EffectPresetUpdate, EffectConfig
|
||||
|
||||
@@ -54,6 +52,7 @@ def get_preset_by_name(name: str, db: Session) -> Optional[EffectPresetResponse]
|
||||
|
||||
def create_preset(data: EffectPresetCreate, db: Session) -> EffectPresetResponse:
|
||||
"""Create a new user effect preset."""
|
||||
from .utils.effects import validate_effects_chain
|
||||
|
||||
chain_dicts = [e.model_dump() for e in data.effects_chain]
|
||||
error = validate_effects_chain(chain_dicts)
|
||||
@@ -95,6 +94,7 @@ def update_preset(preset_id: str, data: EffectPresetUpdate, db: Session) -> Opti
|
||||
if data.description is not None:
|
||||
preset.description = data.description
|
||||
if data.effects_chain is not None:
|
||||
from .utils.effects import validate_effects_chain
|
||||
|
||||
chain_dicts = [e.model_dump() for e in data.effects_chain]
|
||||
error = validate_effects_chain(chain_dicts)
|
||||
|
||||
@@ -264,43 +264,6 @@ async def delete_generation(
|
||||
return True
|
||||
|
||||
|
||||
async def delete_failed_generations(db: Session) -> int:
|
||||
"""
|
||||
Delete every generation whose status is 'failed'.
|
||||
|
||||
Used by the "Clear failed" action in the UI so users can tidy up
|
||||
history after the model wasn't loaded, the app was closed mid-run,
|
||||
or a generation otherwise errored out (see issue #410).
|
||||
|
||||
Returns:
|
||||
Number of generations deleted.
|
||||
"""
|
||||
from . import versions as versions_mod
|
||||
|
||||
failed = db.query(DBGeneration).filter(DBGeneration.status == "failed").all()
|
||||
count = 0
|
||||
for generation in failed:
|
||||
# Clean up version files/rows first.
|
||||
versions_mod.delete_versions_for_generation(generation.id, db)
|
||||
|
||||
# Remove the main audio file if it somehow made it to disk.
|
||||
if generation.audio_path:
|
||||
audio_path = config.resolve_storage_path(generation.audio_path)
|
||||
if audio_path is not None and audio_path.exists():
|
||||
try:
|
||||
audio_path.unlink()
|
||||
except OSError:
|
||||
# Best-effort cleanup — don't abort the whole sweep
|
||||
# if a single file can't be removed.
|
||||
pass
|
||||
|
||||
db.delete(generation)
|
||||
count += 1
|
||||
|
||||
db.commit()
|
||||
return count
|
||||
|
||||
|
||||
async def delete_generations_by_profile(
|
||||
profile_id: str,
|
||||
db: Session,
|
||||
|
||||
@@ -484,15 +484,13 @@ async def split_story_item(
|
||||
Returns:
|
||||
List of two updated item details (original and new) or None if not found/invalid
|
||||
"""
|
||||
# Get the item with a row lock to prevent concurrent splits on the
|
||||
# same clip (e.g. from rapid double-clicks racing each other).
|
||||
# Get the item
|
||||
item = (
|
||||
db.query(DBStoryItem)
|
||||
.filter_by(
|
||||
id=item_id,
|
||||
story_id=story_id,
|
||||
)
|
||||
.with_for_update()
|
||||
.first()
|
||||
)
|
||||
if not item:
|
||||
|
||||
@@ -64,7 +64,7 @@ def get_cached_voice_prompt(
|
||||
cache_file = _get_cache_dir() / f"{cache_key}.prompt"
|
||||
if cache_file.exists():
|
||||
try:
|
||||
prompt = torch.load(cache_file, weights_only=True)
|
||||
prompt = torch.load(cache_file)
|
||||
_memory_cache[cache_key] = prompt
|
||||
return prompt
|
||||
except Exception:
|
||||
|
||||
@@ -1,64 +1,17 @@
|
||||
"""Monkey-patch huggingface_hub to force offline mode with cached models.
|
||||
|
||||
Prevents mlx_audio / transformers from making network requests when models
|
||||
are already downloaded. Must be imported BEFORE mlx_audio.
|
||||
Prevents mlx_audio from making network requests when models are already
|
||||
downloaded. Must be imported BEFORE mlx_audio.
|
||||
"""
|
||||
|
||||
import logging
|
||||
import os
|
||||
from contextlib import contextmanager
|
||||
from pathlib import Path
|
||||
from typing import Optional, Union
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@contextmanager
|
||||
def force_offline_if_cached(is_cached: bool, model_label: str = ""):
|
||||
"""Context manager that sets ``HF_HUB_OFFLINE=1`` while loading a cached model.
|
||||
|
||||
If *is_cached* is ``False`` the block runs normally (network allowed).
|
||||
If the offline load raises an error containing "offline" we automatically
|
||||
retry with network access so a partially-cached model still works.
|
||||
|
||||
Args:
|
||||
is_cached: Whether the model weights are already on disk.
|
||||
model_label: Human-readable name used in log messages.
|
||||
"""
|
||||
if not is_cached:
|
||||
yield
|
||||
return
|
||||
|
||||
original_value = os.environ.get("HF_HUB_OFFLINE")
|
||||
os.environ["HF_HUB_OFFLINE"] = "1"
|
||||
logger.info(
|
||||
"[offline-guard] %s is cached — forcing HF_HUB_OFFLINE=1",
|
||||
model_label or "model",
|
||||
)
|
||||
|
||||
try:
|
||||
yield
|
||||
except Exception as exc:
|
||||
if "offline" in str(exc).lower():
|
||||
logger.warning(
|
||||
"[offline-guard] Offline load failed for %s, retrying with network: %s",
|
||||
model_label or "model",
|
||||
exc,
|
||||
)
|
||||
# Restore original env and retry — caller must wrap the load
|
||||
# inside force_offline_if_cached so retrying here isn't possible.
|
||||
# Instead, propagate a flag via the exception so the caller can
|
||||
# decide. For simplicity we just let it fall through to the
|
||||
# finally block and re-raise.
|
||||
raise
|
||||
raise
|
||||
finally:
|
||||
if original_value is not None:
|
||||
os.environ["HF_HUB_OFFLINE"] = original_value
|
||||
else:
|
||||
os.environ.pop("HF_HUB_OFFLINE", None)
|
||||
|
||||
|
||||
def patch_huggingface_hub_offline():
|
||||
"""Monkey-patch huggingface_hub to force offline mode."""
|
||||
try:
|
||||
|
||||
@@ -22,7 +22,6 @@ services:
|
||||
|
||||
environment:
|
||||
- LOG_LEVEL=info
|
||||
- NUMBA_CACHE_DIR=/tmp/numba_cache
|
||||
|
||||
networks:
|
||||
- voicebox-net
|
||||
|
||||
+4
-4
@@ -1,7 +1,7 @@
|
||||
@import "tailwindcss";
|
||||
@import "fumadocs-ui/css/neutral.css";
|
||||
@import "fumadocs-ui/css/preset.css";
|
||||
@import "fumadocs-openapi/css/preset.css";
|
||||
@import 'tailwindcss';
|
||||
@import 'fumadocs-ui/css/neutral.css';
|
||||
@import 'fumadocs-ui/css/preset.css';
|
||||
@import 'fumadocs-openapi/css/preset.css';
|
||||
|
||||
:root {
|
||||
--color-fd-primary: hsl(43, 50%, 50%);
|
||||
|
||||
@@ -5,13 +5,22 @@ import { generate as DefaultImage } from 'fumadocs-ui/og';
|
||||
|
||||
export const revalidate = false;
|
||||
|
||||
export async function GET(_req: Request, { params }: RouteContext<'/og/docs/[...slug]'>) {
|
||||
export async function GET(
|
||||
_req: Request,
|
||||
{ params }: RouteContext<'/og/docs/[...slug]'>,
|
||||
) {
|
||||
const { slug } = await params;
|
||||
const page = source.getPage(slug.slice(0, -1));
|
||||
if (!page) notFound();
|
||||
|
||||
return new ImageResponse(
|
||||
<DefaultImage title={page.data.title} description={page.data.description} site="My App" />,
|
||||
(
|
||||
<DefaultImage
|
||||
title={page.data.title}
|
||||
description={page.data.description}
|
||||
site="My App"
|
||||
/>
|
||||
),
|
||||
{
|
||||
width: 1200,
|
||||
height: 630,
|
||||
|
||||
@@ -5,22 +5,17 @@ description: "How voice profile management works in Voicebox"
|
||||
|
||||
## Overview
|
||||
|
||||
Voice profiles are the unit of "a saved voice" in Voicebox. As of 0.4 they support two flavors backed by the same `profiles` table:
|
||||
|
||||
- **Cloned profiles** — store one or more reference audio samples; the cloning engine generates a voice embedding at use time
|
||||
- **Preset profiles** — store no audio; just a pointer to an engine-specific pre-built voice (e.g. Kokoro's `am_adam`, Qwen CustomVoice's `Ryan`)
|
||||
|
||||
The schema also reserves a third type, `designed`, for future text-described voices. Not currently used by any shipped engine.
|
||||
Voice profiles are the foundation of Voicebox's voice cloning capability. Each profile stores reference audio samples and metadata that the TTS model uses to clone a voice.
|
||||
|
||||
## Architecture
|
||||
|
||||
The voice profile system consists of three main components:
|
||||
|
||||
**Database Layer:** SQLite tables store profile metadata, sample references (cloned), and engine + voice ID (preset).
|
||||
**Database Layer:** SQLite tables store profile metadata and sample references.
|
||||
|
||||
**File Storage:** Audio samples are stored on disk in a structured directory format. Preset profiles have no on-disk audio.
|
||||
**File Storage:** Audio samples are stored on disk in a structured directory format.
|
||||
|
||||
**Profile Module:** `backend/services/profiles.py` provides the business logic for CRUD operations and dispatches to the appropriate engine based on `voice_type`.
|
||||
**Profile Module:** The `profiles.py` module provides the business logic for CRUD operations.
|
||||
|
||||
## Data Model
|
||||
|
||||
@@ -29,49 +24,27 @@ The voice profile system consists of three main components:
|
||||
```python
|
||||
class VoiceProfile(Base):
|
||||
__tablename__ = "profiles"
|
||||
|
||||
id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
|
||||
|
||||
id = Column(String, primary_key=True)
|
||||
name = Column(String, unique=True, nullable=False)
|
||||
description = Column(Text)
|
||||
language = Column(String, default="en")
|
||||
avatar_path = Column(String, nullable=True)
|
||||
effects_chain = Column(Text, nullable=True)
|
||||
|
||||
# Voice type system — added v0.3.x
|
||||
voice_type = Column(String, default="cloned") # "cloned" | "preset" | "designed"
|
||||
preset_engine = Column(String, nullable=True) # e.g. "kokoro" — only for preset
|
||||
preset_voice_id = Column(String, nullable=True) # e.g. "am_adam" — only for preset
|
||||
design_prompt = Column(Text, nullable=True) # text description — only for designed (reserved)
|
||||
default_engine = Column(String, nullable=True) # auto-selected engine, locked for preset
|
||||
|
||||
created_at = Column(DateTime, default=datetime.utcnow)
|
||||
updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
|
||||
created_at = Column(DateTime)
|
||||
updated_at = Column(DateTime)
|
||||
```
|
||||
|
||||
The `voice_type` column discriminates the three flavors:
|
||||
|
||||
| `voice_type` | `preset_engine` | `preset_voice_id` | Samples in `profile_samples` |
|
||||
| ------------ | --------------- | ----------------- | ---------------------------- |
|
||||
| `cloned` | NULL | NULL | Required (≥1 row) |
|
||||
| `preset` | engine name | voice ID string | None |
|
||||
| `designed` | NULL | NULL | None (uses `design_prompt`) |
|
||||
|
||||
The `default_engine` column is set automatically when the profile is created. For preset profiles it's locked to the source engine — switching engines at generation time will skip the profile (and the UI auto-switches back when the user clicks a greyed-out card; see the floating generate box and profile grid).
|
||||
|
||||
### ProfileSample Table
|
||||
|
||||
```python
|
||||
class ProfileSample(Base):
|
||||
__tablename__ = "profile_samples"
|
||||
|
||||
id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
|
||||
|
||||
id = Column(String, primary_key=True)
|
||||
profile_id = Column(String, ForeignKey("profiles.id"))
|
||||
audio_path = Column(String, nullable=False)
|
||||
reference_text = Column(Text, nullable=False)
|
||||
```
|
||||
|
||||
Only populated for cloned profiles. Preset and designed profiles have zero rows in this table.
|
||||
|
||||
## File Structure
|
||||
|
||||
Profiles are stored in the data directory:
|
||||
|
||||
@@ -31,6 +31,6 @@ Voicebox is a **local-first voice cloning studio** -- a free and open-source alt
|
||||
|
||||
## Get Started
|
||||
|
||||
- [Installation](/overview/installation) -- download and install Voicebox
|
||||
- [Quick Start](/overview/quick-start) -- get up and running in 5 minutes
|
||||
- [API Reference](/api-reference) -- integrate voice synthesis into your apps
|
||||
- [Installation](/docs/overview/installation) -- download and install Voicebox
|
||||
- [Quick Start](/docs/overview/quick-start) -- get up and running in 5 minutes
|
||||
- [API Reference](/docs/api-reference) -- integrate voice synthesis into your apps
|
||||
|
||||
@@ -1,43 +1,32 @@
|
||||
---
|
||||
title: "Creating Voice Profiles"
|
||||
description: "How to create voice profiles, both cloning-based and preset-based"
|
||||
description: "Advanced guide to creating high-quality voice profiles"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
A **voice profile** is a saved voice you can reuse across generations, stories, and the API. As of 0.4, Voicebox profiles come in two flavors that map to two different ways of getting a voice:
|
||||
Voice profiles are the foundation of voice cloning in Voicebox. This guide covers best practices for creating professional-quality voice profiles.
|
||||
|
||||
| Profile type | What it stores | Use when… |
|
||||
| -------------- | ---------------------------------------------------- | -------------------------------------------------------- |
|
||||
| **Cloned** | One or more reference audio samples + a voice embedding | You want to replicate a specific person's voice |
|
||||
| **Preset** | A reference to a pre-built voice in a specific engine | You want a curated, production-ready voice with no audio prep |
|
||||
|
||||
Both types live in the same Profiles tab and behave the same way at generation time — pick the type that matches your goal and follow the workflow below.
|
||||
|
||||
<Callout type="info">
|
||||
Not sure which to use? Cloning gives you a *specific* voice but needs clean audio. Preset gives you *good* voices instantly but you don't get to choose who they sound like.
|
||||
</Callout>
|
||||
|
||||
## Workflow A — Cloned Profiles
|
||||
|
||||
Use this when you want to replicate a specific person's voice from a recording.
|
||||
## Quick Start
|
||||
|
||||
<Steps>
|
||||
<Step title="Prepare Audio">
|
||||
10-30 seconds of clear speech, minimal background noise. See [Voice Cloning](/overview/voice-cloning) for the engine catalog.
|
||||
10-30 seconds of clear speech
|
||||
</Step>
|
||||
<Step title="Create Profile">
|
||||
**Profiles** → **+ New Profile** → choose a cloning engine (Qwen3-TTS, Chatterbox, LuxTTS, or TADA)
|
||||
**Profiles** → **+ New Profile**
|
||||
</Step>
|
||||
<Step title="Upload or Record Sample">
|
||||
Drag in an audio file, or record directly with the in-app recorder
|
||||
<Step title="Upload Sample">
|
||||
Add your audio file
|
||||
</Step>
|
||||
<Step title="Generate to Test">
|
||||
Use the profile to generate a test phrase. If quality is poor, add more samples
|
||||
<Step title="Generate">
|
||||
Use the profile to generate speech
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
### Audio Requirements (Cloning Only)
|
||||
## Audio Requirements
|
||||
|
||||
### Ideal Sample Characteristics
|
||||
|
||||
<Cards>
|
||||
<Card title="Duration">
|
||||
@@ -55,7 +44,7 @@ Use this when you want to replicate a specific person's voice from a recording.
|
||||
<Card title="Quality">
|
||||
**High fidelity**
|
||||
|
||||
44.1 kHz or 48 kHz sample rate
|
||||
44.1kHz or 48kHz sample rate
|
||||
Minimal compression
|
||||
</Card>
|
||||
<Card title="Content">
|
||||
@@ -69,16 +58,18 @@ Use this when you want to replicate a specific person's voice from a recording.
|
||||
### File Formats
|
||||
|
||||
Supported formats:
|
||||
- **WAV** (recommended) — Lossless quality
|
||||
- **MP3** — Acceptable, minimal compression
|
||||
- **M4A** — Acceptable
|
||||
- **FLAC** — Lossless alternative
|
||||
- **WAV** (recommended) - Lossless quality
|
||||
- **MP3** - Acceptable, minimal compression
|
||||
- **M4A** - Acceptable
|
||||
- **FLAC** - Lossless alternative
|
||||
|
||||
<Callout type="info">
|
||||
Use WAV for best results. Avoid heavily compressed formats.
|
||||
</Callout>
|
||||
|
||||
### Recording Tips
|
||||
## Recording Tips
|
||||
|
||||
### Environment
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="Quiet Space">
|
||||
@@ -96,25 +87,27 @@ Supported formats:
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Recording Settings">
|
||||
- 44.1 kHz or 48 kHz sample rate
|
||||
- 44.1kHz or 48kHz sample rate
|
||||
- 16-bit or 24-bit depth
|
||||
- Mono is fine (stereo will be converted)
|
||||
- Avoid automatic gain control
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
### Speaking Style
|
||||
### Speaking
|
||||
|
||||
- **Natural pace** — Don't rush or speak too slowly
|
||||
- **Clear articulation** — Pronounce words clearly
|
||||
- **Consistent volume** — Maintain steady loudness
|
||||
- **Normal tone** — Speak as you normally would
|
||||
- **Complete sentences** — Avoid fragments or "ums"
|
||||
- **Natural pace** - Don't rush or speak too slowly
|
||||
- **Clear articulation** - Pronounce words clearly
|
||||
- **Consistent volume** - Maintain steady loudness
|
||||
- **Normal tone** - Speak as you normally would
|
||||
- **Complete sentences** - Avoid fragments or "ums"
|
||||
|
||||
### Multiple Samples
|
||||
## Multiple Samples
|
||||
|
||||
Adding multiple samples can significantly improve quality:
|
||||
|
||||
### Why Multiple Samples?
|
||||
|
||||
<Cards>
|
||||
<Card title="Robustness">
|
||||
Model learns a more complete representation
|
||||
@@ -130,57 +123,110 @@ Adding multiple samples can significantly improve quality:
|
||||
</Card>
|
||||
</Cards>
|
||||
|
||||
### Sample Variety
|
||||
|
||||
Consider adding samples with:
|
||||
|
||||
1. **Different tones** — casual, formal, excited, calm
|
||||
2. **Different content** — narratives, questions, statements
|
||||
3. **Different recording conditions** — studio quality, room acoustics
|
||||
1. **Different tones**
|
||||
- Casual conversation
|
||||
- Professional/formal
|
||||
- Excited/enthusiastic
|
||||
- Calm/serious
|
||||
|
||||
2. **Different content**
|
||||
- Narratives
|
||||
- Questions
|
||||
- Statements
|
||||
- Emotions (happy, sad, neutral)
|
||||
|
||||
3. **Different recording conditions**
|
||||
- Studio quality
|
||||
- Phone call quality (if needed)
|
||||
- Room acoustics
|
||||
|
||||
<Callout type="warn">
|
||||
All samples should be from the **same speaker**. Mixing voices will produce poor results.
|
||||
</Callout>
|
||||
|
||||
### Processing Existing Audio
|
||||
## Processing Existing Audio
|
||||
|
||||
If you have existing audio (podcasts, videos, etc.):
|
||||
|
||||
### Extracting Clean Segments
|
||||
|
||||
<Steps>
|
||||
<Step title="Find Clean Speech">
|
||||
Look for segments with just the target speaker, no background music, minimal noise
|
||||
Look for segments with:
|
||||
- Just the target speaker
|
||||
- No background music
|
||||
- Minimal noise
|
||||
</Step>
|
||||
|
||||
<Step title="Use Audio Editor">
|
||||
Tools like Audacity or Adobe Audition: cut clean 10-30s segments, remove silence at start/end, normalize volume
|
||||
Tools like Audacity or Adobe Audition:
|
||||
- Cut out clean 10-30s segments
|
||||
- Remove silence at start/end
|
||||
- Normalize volume if needed
|
||||
</Step>
|
||||
|
||||
<Step title="Export as WAV">
|
||||
Save as high-quality WAV file
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
For light background noise, use Audacity's noise reduction (gentle settings — over-processing introduces artifacts).
|
||||
### Noise Reduction
|
||||
|
||||
### Testing & Iteration
|
||||
If you have light background noise:
|
||||
|
||||
After creating a cloned profile:
|
||||
```
|
||||
1. Use noise reduction in Audacity:
|
||||
- Select noise-only section
|
||||
- Get Noise Profile
|
||||
- Select full audio
|
||||
- Apply noise reduction (gentle settings)
|
||||
|
||||
2. Avoid over-processing:
|
||||
- Can introduce artifacts
|
||||
- May reduce voice quality
|
||||
```
|
||||
|
||||
## Testing & Iteration
|
||||
|
||||
### Test Your Profile
|
||||
|
||||
After creating a profile:
|
||||
|
||||
<Steps>
|
||||
<Step title="Generate Test">
|
||||
Try a simple phrase: `"Hello, this is a test of my voice profile."`
|
||||
Generate a simple phrase:
|
||||
```
|
||||
"Hello, this is a test of my voice profile."
|
||||
```
|
||||
</Step>
|
||||
|
||||
<Step title="Evaluate Quality">
|
||||
Listen for natural tone, clear pronunciation, proper prosody, lack of artifacts
|
||||
Listen for:
|
||||
- Natural tone
|
||||
- Clear pronunciation
|
||||
- Proper prosody
|
||||
- Lack of artifacts
|
||||
</Step>
|
||||
|
||||
<Step title="Iterate">
|
||||
If quality is poor: add more samples, try different source audio, check sample quality
|
||||
If quality is poor:
|
||||
- Add more samples
|
||||
- Try different source audio
|
||||
- Check sample quality
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
#### Common Issues
|
||||
### Common Issues
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="Robotic Voice">
|
||||
**Cause**: Poor quality samples or too short
|
||||
|
||||
**Fix**: Use longer, higher-quality samples
|
||||
**Fix**: Use longer, higher quality samples
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Wrong Tone">
|
||||
@@ -196,89 +242,51 @@ After creating a cloned profile:
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
## Workflow B — Preset Profiles
|
||||
|
||||
Use this when you want a ready-made voice without recording anything. Available engines: **Kokoro 82M** (50 voices) and **Qwen CustomVoice** (9 voices). See [Preset Voices](/overview/preset-voices) for the full catalog.
|
||||
|
||||
<Steps>
|
||||
<Step title="Create Profile">
|
||||
**Profiles** → **+ New Profile** → choose **Kokoro** or **Qwen CustomVoice** as the engine
|
||||
</Step>
|
||||
<Step title="Pick a Voice">
|
||||
The engine's voice catalog appears. Click any voice to preview it
|
||||
</Step>
|
||||
<Step title="Name and Save">
|
||||
Give the profile a name. No audio sample required
|
||||
</Step>
|
||||
<Step title="Generate">
|
||||
The profile is ready immediately — use it in the floating generate box or Generate page
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
<Callout type="info">
|
||||
Preset profiles are **locked to their source engine**. Switching to a different engine in the floating generate box greys out the profile, since the voice only exists in that engine. Clicking a greyed profile auto-switches the engine back.
|
||||
</Callout>
|
||||
|
||||
### Qwen CustomVoice + Instruct
|
||||
|
||||
Preset voices in Qwen CustomVoice support **delivery instructions** — natural-language style control over tone, pace, and emotion. The floating generate box shows a slider icon next to the generate button when a Qwen CustomVoice profile is selected; click it to reveal the instruct textarea.
|
||||
|
||||
See [Preset Voices → Using Instruct Mode](/overview/preset-voices#using-instruct-mode) for examples.
|
||||
|
||||
## Advanced Tips
|
||||
|
||||
### Celebrity / Character Voices (Cloning)
|
||||
### Celebrity/Character Voices
|
||||
|
||||
For cloning public figures or characters:
|
||||
|
||||
1. **Legal considerations** — Ensure you have rights or it's clearly fair use
|
||||
2. **Source quality** — Find high-quality interview audio or clean clips
|
||||
3. **Consistency** — Use clips where they speak similarly
|
||||
4. **Multiple samples** — Very important for recognizable voices
|
||||
1. **Legal considerations** - Ensure you have rights or it's fair use
|
||||
2. **Source quality** - Find high-quality interview audio or clean clips
|
||||
3. **Consistency** - Use clips where they speak similarly
|
||||
4. **Multiple samples** - Very important for recognizable voices
|
||||
|
||||
### Accent & Dialect (Cloning)
|
||||
### Accent & Dialect
|
||||
|
||||
Cloning models preserve accent and dialect:
|
||||
The model will preserve accent and dialect:
|
||||
|
||||
- British English samples generate British English output
|
||||
- Southern accent samples produce Southern accent output
|
||||
- Regional pronunciations are maintained
|
||||
- British English will generate British English
|
||||
- Southern accent will produce Southern accent
|
||||
- Regional pronunciations will be maintained
|
||||
|
||||
### Emotion Transfer (Cloning)
|
||||
### Emotion Transfer
|
||||
|
||||
The emotional tone of samples affects generation:
|
||||
|
||||
- Energetic samples → energetic output
|
||||
- Calm samples → calm output
|
||||
- Mix samples for a more versatile profile
|
||||
|
||||
For Qwen CustomVoice presets, use the **instruct** field instead of relying on sample emotion — that's exactly what it controls.
|
||||
- Energetic samples → Energetic output
|
||||
- Calm samples → Calm output
|
||||
- Mix samples for versatile profile
|
||||
|
||||
## Managing Profiles
|
||||
|
||||
### Organization
|
||||
|
||||
- **Descriptive names** — "John Smith - Professional Narrator"
|
||||
- **Add descriptions** — Note recording conditions, use cases, or which preset voice
|
||||
- **Language tags** — Mark the primary language
|
||||
- **Archive unused** — Keep profile list manageable
|
||||
- **Descriptive names** - "John Smith - Professional Narrator"
|
||||
- **Add descriptions** - Note recording conditions, use cases
|
||||
- **Language tags** - Mark the primary language
|
||||
- **Archive unused** - Keep profile list manageable
|
||||
|
||||
### Export / Import
|
||||
### Export/Import
|
||||
|
||||
- **Export** profiles to share or backup
|
||||
- **Import** from colleagues or teammates
|
||||
- **Cloned profiles** export with their voice embeddings (not the original audio)
|
||||
- **Preset profiles** export as engine + voice ID metadata only — the importer must have that engine's model installed
|
||||
- Profiles include voice embeddings, not original audio
|
||||
|
||||
## Next Steps
|
||||
|
||||
<Cards>
|
||||
<Card title="Voice Cloning" href="/overview/voice-cloning">
|
||||
Engine catalog and best practices for cloning
|
||||
</Card>
|
||||
<Card title="Preset Voices" href="/overview/preset-voices">
|
||||
Full catalog of Kokoro and Qwen CustomVoice voices
|
||||
</Card>
|
||||
<Card title="Generate Speech" href="/overview/generating-speech">
|
||||
Use your profile to generate speech
|
||||
</Card>
|
||||
|
||||
@@ -1,236 +0,0 @@
|
||||
---
|
||||
title: "GPU Acceleration"
|
||||
description: "How Voicebox uses your GPU — auto-detection, manual setup, troubleshooting"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
Voicebox auto-detects available accelerators on first launch and picks the fastest backend it can use. For most people this just works — open the app and you're already on the right backend.
|
||||
|
||||
This page is for the cases where it doesn't:
|
||||
|
||||
- You have a GPU but Voicebox is running on CPU
|
||||
- You upgraded GPUs (especially to RTX 50-series / Blackwell) and generation broke
|
||||
- You want to switch backends manually (e.g. force MLX over PyTorch on Apple Silicon)
|
||||
- You see `[UNSUPPORTED - see logs]` next to your GPU in Settings
|
||||
|
||||
## Backend Matrix
|
||||
|
||||
| Platform | Auto-selected backend | Notes |
|
||||
| --------------------------- | ------------------------- | ---------------------------------------------------- |
|
||||
| **macOS Apple Silicon** | MLX (Metal) | 4-5x faster than PyTorch via Apple Neural Engine |
|
||||
| **macOS Intel** | PyTorch CPU | No GPU acceleration available; PyTorch ≥ 2.2 only |
|
||||
| **Windows + NVIDIA** | PyTorch CUDA (cu128) | Auto-downloads the CUDA backend binary on first use |
|
||||
| **Windows + Intel Arc** | PyTorch XPU (IPEX) | New in 0.4 — works with Arc A-series and B-series |
|
||||
| **Windows generic GPU** | DirectML | Universal Windows GPU support; slower than CUDA |
|
||||
| **Linux + NVIDIA** | PyTorch CUDA (cu128) | Same auto-download flow as Windows |
|
||||
| **Linux + AMD** | PyTorch ROCm | Auto-configures `HSA_OVERRIDE_GFX_VERSION` |
|
||||
| **Linux + Intel Arc** | PyTorch XPU (IPEX) | |
|
||||
| **Any (no GPU)** | PyTorch CPU | Works everywhere; expect 5-50x slower than GPU |
|
||||
|
||||
The detected backend is shown in Settings → GPU. Logs at startup also print the chosen backend and the device name.
|
||||
|
||||
## Apple Silicon — MLX vs PyTorch
|
||||
|
||||
On M-series Macs, Voicebox ships an MLX-optimized backend that uses the Apple Neural Engine. It's **4-5x faster** than the PyTorch (CPU/Metal) path for supported engines.
|
||||
|
||||
| Engine | MLX support | Notes |
|
||||
| -------------------- | ----------- | ------------------------------------------- |
|
||||
| Qwen3-TTS | ✅ Native | Uses MLX exclusively when available |
|
||||
| Chatterbox / Turbo | PyTorch MPS | Falls back to Metal via PyTorch |
|
||||
| LuxTTS | PyTorch MPS | |
|
||||
| TADA | PyTorch MPS | |
|
||||
| Kokoro | PyTorch MPS | Requires `PYTORCH_ENABLE_MPS_FALLBACK=1` |
|
||||
| Qwen CustomVoice | PyTorch MPS | |
|
||||
| Whisper (transcribe) | ✅ Native | MLX-Whisper is the default on Apple Silicon |
|
||||
|
||||
The Whisper Turbo + MLX combo dropped transcription latency from ~20s to ~2-3s on M-series chips (see CHANGELOG entry for v0.1.10).
|
||||
|
||||
## Windows / Linux + NVIDIA — The CUDA Backend Swap
|
||||
|
||||
Voicebox doesn't bundle CUDA into the main installer (it would balloon downloads to multi-gigabyte territory for users who don't have an NVIDIA GPU). Instead, when you first need it, the app downloads a separate **CUDA backend binary** that contains the PyTorch + CUDA runtime.
|
||||
|
||||
<Steps>
|
||||
<Step title="Open Settings → GPU">
|
||||
If an NVIDIA GPU is detected, you'll see "Install CUDA backend" in the GPU panel
|
||||
</Step>
|
||||
<Step title="Click Install">
|
||||
The app downloads two archives separately:
|
||||
- **Server core** (~200-400 MB) — versioned with each Voicebox release
|
||||
- **CUDA libs** (~4 GB) — the heavy PyTorch + CUDA DLLs, versioned independently
|
||||
</Step>
|
||||
<Step title="Restart">
|
||||
Voicebox restarts to swap in the CUDA backend
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
<Callout type="info">
|
||||
The split-archive design (added in v0.4) means most Voicebox upgrades only redownload the small server-core archive. The 4 GB libs archive is only refreshed when the underlying CUDA toolkit or torch major version changes.
|
||||
</Callout>
|
||||
|
||||
### Auto-update
|
||||
|
||||
When a new Voicebox release ships, the GPU panel checks if the bundled server-core matches the installed CUDA version. If only the core changed (typical), it pulls the new core in the background. If the libs version changed (rare — only happens on cu126 → cu128 type bumps), you'll be prompted to confirm the larger download.
|
||||
|
||||
## RTX 50-series / Blackwell
|
||||
|
||||
Voicebox 0.4 added explicit RTX 50-series support:
|
||||
|
||||
- CUDA toolkit upgraded to **cu128** (previous releases used cu126 which lacks Blackwell kernels)
|
||||
- Build pinned with `TORCH_CUDA_ARCH_LIST=...12.0+PTX` for forward-compatibility
|
||||
|
||||
If you're on an RTX 5070 / 5080 / 5090 and you see "no kernel image is available" errors:
|
||||
|
||||
1. Make sure you're on Voicebox **≥ 0.4.0** (Settings → About)
|
||||
2. Reinstall the CUDA backend (Settings → GPU → Reinstall CUDA backend) — older installs may have stale cu126 libs
|
||||
3. If errors persist, see the GPU compatibility warnings section below
|
||||
|
||||
## Intel Arc (XPU)
|
||||
|
||||
New in 0.4. Works with both Arc A-series (Alchemist: A380, A580, A750, A770) and B-series (Battlemage).
|
||||
|
||||
### Setup
|
||||
|
||||
Voicebox auto-detects Arc GPUs and routes through Intel's PyTorch XPU backend (powered by IPEX — Intel Extension for PyTorch). No extra installation step beyond the standard Voicebox install.
|
||||
|
||||
Verify it's working:
|
||||
- Settings → GPU should show **XPU** followed by your Arc model name (e.g. `XPU (Intel Arc A770)`)
|
||||
- Startup logs print `Backend: PYTORCH` and `GPU: XPU (Intel Arc ...)`
|
||||
|
||||
### Engines on XPU
|
||||
|
||||
All PyTorch-based engines work on XPU. Performance is generally between CPU and CUDA — expect ~2-3x speedup over CPU for the larger models.
|
||||
|
||||
## DirectML
|
||||
|
||||
The fallback for Windows users with non-NVIDIA, non-Intel-Arc GPUs (older AMD discrete, integrated GPUs, etc.). Slower than CUDA and XPU but provides some acceleration over CPU.
|
||||
|
||||
Auto-selected when no other GPU backend is available.
|
||||
|
||||
## AMD ROCm (Linux)
|
||||
|
||||
ROCm provides PyTorch GPU acceleration on AMD discrete GPUs. Voicebox auto-configures `HSA_OVERRIDE_GFX_VERSION` for common cards that need the override.
|
||||
|
||||
### Verifying
|
||||
|
||||
```bash
|
||||
# In a terminal
|
||||
echo $HSA_OVERRIDE_GFX_VERSION
|
||||
# Should show e.g. 10.3.0 for RX 6000 series
|
||||
```
|
||||
|
||||
If detection fails, set the variable manually before launching Voicebox:
|
||||
|
||||
```bash
|
||||
export HSA_OVERRIDE_GFX_VERSION=10.3.0
|
||||
voicebox
|
||||
```
|
||||
|
||||
Common values:
|
||||
- `10.3.0` — RX 6000 series (RDNA 2)
|
||||
- `11.0.0` — RX 7000 series (RDNA 3)
|
||||
- `9.0.0` — Older Vega cards
|
||||
|
||||
## GPU Compatibility Warnings
|
||||
|
||||
Voicebox 0.4 added a runtime check that compares your GPU's compute capability against the architectures the bundled PyTorch was compiled for. If they don't match, you'll see:
|
||||
|
||||
- A startup log line: `WARNING: GPU COMPATIBILITY: <your GPU> is not supported by this PyTorch build...`
|
||||
- The GPU label in Settings shows `[UNSUPPORTED - see logs]`
|
||||
- The `/health` API returns a populated `gpu_compatibility_warning` field
|
||||
|
||||
### What to do
|
||||
|
||||
The most common trigger is a brand-new GPU architecture that pre-built PyTorch wheels don't yet cover natively. In order of preference:
|
||||
|
||||
1. **Update Voicebox** — newer releases ship newer PyTorch with broader arch support
|
||||
2. **Reinstall the CUDA backend** — Settings → GPU → Reinstall CUDA backend
|
||||
3. **For bleeding-edge GPUs (newer than current Blackwell):** install PyTorch nightly manually:
|
||||
```bash
|
||||
pip install torch --index-url https://download.pytorch.org/whl/nightly/cu128 --force-reinstall
|
||||
```
|
||||
Then point Voicebox at that environment via [Remote Mode](/overview/remote-mode) until stable PyTorch catches up.
|
||||
4. **Fall back to CPU** temporarily — set `VOICEBOX_FORCE_CPU=1` before launching
|
||||
|
||||
## CPU-Only Fallback
|
||||
|
||||
When no GPU is available (or you've forced it off), Voicebox runs the PyTorch CPU backend. Expect:
|
||||
|
||||
- 5-50x slower generation depending on engine and text length
|
||||
- Heavy CPU usage during generation
|
||||
- Some engines work better than others on CPU:
|
||||
- **Kokoro 82M** — runs at realtime on modern CPUs
|
||||
- **LuxTTS** — exceeds 150x realtime on CPU
|
||||
- **Chatterbox Turbo (350M)** — usable but slow
|
||||
- Larger models (Qwen 1.7B, Chatterbox Multilingual, TADA 3B) — painful
|
||||
|
||||
For CPU-bound use cases, prefer the smaller, lighter engines.
|
||||
|
||||
## Verifying Your Setup
|
||||
|
||||
Three places to check that the right backend is being used:
|
||||
|
||||
<Steps>
|
||||
<Step title="Settings → GPU">
|
||||
Shows the detected backend, GPU model, and VRAM (when applicable). Look for the `[UNSUPPORTED - see logs]` suffix
|
||||
</Step>
|
||||
<Step title="Settings → Logs">
|
||||
The "Server logs" tab shows the startup banner with `Backend: <type>` and `GPU: <name>`
|
||||
</Step>
|
||||
<Step title="Health endpoint">
|
||||
`curl http://localhost:17493/health` returns a JSON payload with `backend_type`, `backend_variant`, and `gpu_compatibility_warning` (when applicable)
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
<AccordionGroup>
|
||||
<Accordion title="Settings shows CPU instead of my GPU">
|
||||
- On NVIDIA: install the CUDA backend (Settings → GPU)
|
||||
- On Intel Arc: confirm IPEX detection in startup logs; restart the app after a driver update
|
||||
- On AMD Linux: check `HSA_OVERRIDE_GFX_VERSION` is set
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="'no kernel image is available' / 'CUDA error'">
|
||||
Almost always means the bundled PyTorch doesn't have kernels for your GPU's compute capability.
|
||||
|
||||
1. Update to Voicebox ≥ 0.4.0 (Blackwell support added there)
|
||||
2. Reinstall the CUDA backend
|
||||
3. If still broken, install PyTorch nightly via Remote Mode
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Out of memory (CUDA)">
|
||||
- Switch to a smaller model size (e.g. Qwen3 0.6B instead of 1.7B)
|
||||
- Use Settings → Models to unload other engines you're not using
|
||||
- Enable `low_cpu_mem_usage` is already on for CPU; for CUDA, the engine's `device_map` handles offload automatically
|
||||
- Close other GPU applications
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="MPS fallback errors on macOS">
|
||||
Some operations don't have a Metal implementation. Voicebox sets `PYTORCH_ENABLE_MPS_FALLBACK=1` for engines that need it (notably Kokoro), but if you launch from a custom env, set it manually:
|
||||
```bash
|
||||
export PYTORCH_ENABLE_MPS_FALLBACK=1
|
||||
```
|
||||
</Accordion>
|
||||
|
||||
<Accordion title="Generation works but is slow on my GPU">
|
||||
- Check Settings → GPU shows your GPU (not CPU)
|
||||
- Check VRAM usage — you may be paging to system memory
|
||||
- Try a smaller model
|
||||
- For NVIDIA: confirm cu128 is installed (Settings → GPU → version)
|
||||
</Accordion>
|
||||
</AccordionGroup>
|
||||
|
||||
## Next Steps
|
||||
|
||||
<Cards>
|
||||
<Card title="Remote Mode" href="/overview/remote-mode">
|
||||
Run the backend on a different machine with a stronger GPU
|
||||
</Card>
|
||||
<Card title="Model Management" href="/developer/model-management">
|
||||
Unload models to free GPU memory
|
||||
</Card>
|
||||
<Card title="Troubleshooting" href="/overview/troubleshooting">
|
||||
General troubleshooting beyond GPU
|
||||
</Card>
|
||||
</Cards>
|
||||
@@ -6,9 +6,7 @@
|
||||
"installation",
|
||||
"docker",
|
||||
"quick-start",
|
||||
"gpu-acceleration",
|
||||
"voice-cloning",
|
||||
"preset-voices",
|
||||
"stories-editor",
|
||||
"recording-transcription",
|
||||
"generation-history",
|
||||
|
||||
@@ -1,202 +0,0 @@
|
||||
---
|
||||
title: "Preset Voices"
|
||||
description: "Use built-in, ready-made voices without recording audio samples"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
Some Voicebox engines ship with a curated set of pre-built voices. Instead of cloning from your own audio sample, you pick a voice from a fixed catalog and the model speaks in that voice. No recording, no upload, no per-voice training required.
|
||||
|
||||
Two engines in 0.4 ship preset voices:
|
||||
|
||||
| Engine | Voices | Languages | Strengths |
|
||||
| --------------------- | ----------------------- | --------- | ------------------------------------------------------- |
|
||||
| **Kokoro 82M** | 50 | 9 | Tiny model, CPU-friendly, lowest VRAM of any engine |
|
||||
| **Qwen CustomVoice** | 9 (premium curated) | 4 | Natural-language style control over tone, emotion, pace |
|
||||
|
||||
<Callout type="info">
|
||||
Looking for cloning a specific person's voice instead? See [Voice Cloning](/overview/voice-cloning).
|
||||
</Callout>
|
||||
|
||||
## When to Use Preset Voices
|
||||
|
||||
<Cards>
|
||||
<Card title="No reference audio">
|
||||
You don't have (or don't want to provide) a recording of the target voice
|
||||
</Card>
|
||||
<Card title="Production reliability">
|
||||
Curated voices have predictable quality across any text input
|
||||
</Card>
|
||||
<Card title="Speed">
|
||||
Skip the audio cleanup, sample preparation, and quality iteration loop
|
||||
</Card>
|
||||
<Card title="Lightweight setup">
|
||||
Kokoro runs at CPU realtime with ~150 MB on disk — no GPU needed
|
||||
</Card>
|
||||
</Cards>
|
||||
|
||||
## Creating a Preset-Voice Profile
|
||||
|
||||
<Steps>
|
||||
<Step title="Open Profiles → New Profile">
|
||||
Same entry point as cloning profiles
|
||||
</Step>
|
||||
<Step title="Choose the engine">
|
||||
Select **Kokoro** or **Qwen CustomVoice** from the engine dropdown
|
||||
</Step>
|
||||
<Step title="Pick a preset voice">
|
||||
The voice catalog for the chosen engine appears — preview each by clicking it
|
||||
</Step>
|
||||
<Step title="Name and save">
|
||||
Give the profile a name. No audio sample needed — just save
|
||||
</Step>
|
||||
<Step title="Generate">
|
||||
Use the profile like any other in the floating generate box or the Generate page
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
<Callout type="info">
|
||||
Preset profiles are locked to their source engine — switching engines won't work since the voice exists only for that model. The profile grid greys out preset profiles when you switch to a different engine, and clicking one auto-switches the engine back to the right one.
|
||||
</Callout>
|
||||
|
||||
## Kokoro 82M — 50 Voices Across 9 Languages
|
||||
|
||||
Kokoro is the smallest engine in Voicebox at 82M parameters. It runs at CPU realtime with negligible VRAM, making it the best option for lightweight local inference. Voices are pre-built style vectors trained into the model — there's no concept of cloning here.
|
||||
|
||||
**Repository:** [`hexgrad/Kokoro-82M`](https://huggingface.co/hexgrad/Kokoro-82M) · Apache 2.0 licensed
|
||||
|
||||
### American English
|
||||
|
||||
| Female | Male |
|
||||
| ------- | ------- |
|
||||
| Alloy | Adam |
|
||||
| Aoede | Echo |
|
||||
| Bella | Eric |
|
||||
| Heart | Fenrir |
|
||||
| Jessica | Liam |
|
||||
| Kore | Michael |
|
||||
| Nicole | Onyx |
|
||||
| Nova | Puck |
|
||||
| River | Santa |
|
||||
| Sarah | |
|
||||
| Sky | |
|
||||
|
||||
### British English
|
||||
|
||||
| Female | Male |
|
||||
| -------- | ------ |
|
||||
| Alice | Daniel |
|
||||
| Emma | Fable |
|
||||
| Isabella | George |
|
||||
| Lily | Lewis |
|
||||
|
||||
### Other Languages
|
||||
|
||||
| Language | Voices |
|
||||
| ----------------- | ------------------------------------------- |
|
||||
| Spanish (`es`) | Dora (f), Alex (m), Santa (m) |
|
||||
| French (`fr`) | Siwis (f) |
|
||||
| Hindi (`hi`) | Alpha (f), Beta (f), Omega (m), Psi (m) |
|
||||
| Italian (`it`) | Sara (f), Nicola (m) |
|
||||
| Japanese (`ja`) | Alpha (f), Gongitsune (f), Nezumi (f), Tebukuro (f), Kumo (m) |
|
||||
| Portuguese (`pt`) | Dora (f), Alex (m), Santa (m) |
|
||||
| Chinese (`zh`) | Xiaobei (f), Xiaoni (f), Xiaoxiao (f), Xiaoyi (f) |
|
||||
|
||||
### Kokoro at a Glance
|
||||
|
||||
| Property | Value |
|
||||
| --------------- | -------------------------------------------- |
|
||||
| Parameters | 82M |
|
||||
| Sample rate | 24 kHz |
|
||||
| VRAM | ~150 MB (negligible on CPU) |
|
||||
| Speed | Realtime on CPU, faster on GPU |
|
||||
| Instruct | Not supported (preset voice carries the style) |
|
||||
| License | Apache 2.0 |
|
||||
|
||||
## Qwen CustomVoice — 9 Premium Voices with Instruct Control
|
||||
|
||||
Qwen CustomVoice ships with 9 curated speakers and supports **natural-language style control** — you tell the model how to deliver the line ("speak slowly with warmth", "authoritative and clear") and it adapts tone, emotion, and pace.
|
||||
|
||||
Two model sizes:
|
||||
- **1.7B** — full quality, recommended default
|
||||
- **0.6B** — lighter, faster, lower-end hardware
|
||||
|
||||
**Repository:** [`Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice`](https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice) (and 0.6B variant) · by Alibaba
|
||||
|
||||
### Voice Catalog
|
||||
|
||||
| Speaker | Gender | Language | Description |
|
||||
| --------- | ------ | -------- | ------------------------------------------------------------ |
|
||||
| Vivian | female | Chinese | Bright, slightly edgy young female voice |
|
||||
| Serena | female | Chinese | Warm, gentle young female voice |
|
||||
| Uncle Fu | male | Chinese | Seasoned male voice with a low, mellow timbre |
|
||||
| Dylan | male | Chinese | Youthful Beijing male voice with a clear, natural timbre |
|
||||
| Eric | male | Chinese | Lively Chengdu male voice with a slightly husky brightness |
|
||||
| Ryan | male | English | Dynamic male voice with strong rhythmic drive (default) |
|
||||
| Aiden | male | English | Sunny American male voice with a clear midrange |
|
||||
| Ono Anna | female | Japanese | Playful Japanese female voice with a light, nimble timbre |
|
||||
| Sohee | female | Korean | Warm Korean female voice with rich emotion |
|
||||
|
||||
### Using Instruct Mode
|
||||
|
||||
In the floating generate box, switch to a Qwen CustomVoice profile and click the **delivery instructions** toggle (slider icon, left of the generate button). A second textarea appears below the main text:
|
||||
|
||||
- Main text → what you want the voice to say
|
||||
- Instruct text → how you want it delivered
|
||||
|
||||
Examples of effective instruct prompts:
|
||||
|
||||
```
|
||||
Speak slowly with emphasis, like reading bedtime stories
|
||||
Warm and friendly, conversational tone
|
||||
Professional and authoritative, broadcast quality
|
||||
Whisper, intimate and close
|
||||
Excited and energetic, like sports commentary
|
||||
```
|
||||
|
||||
The full Generate page also surfaces the instruct field as a separate input.
|
||||
|
||||
### Qwen CustomVoice at a Glance
|
||||
|
||||
| Property | Value |
|
||||
| --------------- | -------------------------------------------------- |
|
||||
| Parameters | 1.7B / 0.6B |
|
||||
| Languages | Chinese, English, Japanese, Korean (10 supported) |
|
||||
| Voices | 9 curated preset speakers |
|
||||
| VRAM | ~3.5 GB (1.7B), ~1.2 GB (0.6B) |
|
||||
| Instruct | Yes — natural-language style control |
|
||||
| Cloning | No — paired Base Qwen3-TTS engine handles cloning |
|
||||
|
||||
## Cloning vs Preset — Quick Decision
|
||||
|
||||
| You want… | Use |
|
||||
| -------------------------------------------------- | ----------------------------------------- |
|
||||
| To replicate a specific person's voice | [Voice Cloning](/overview/voice-cloning) |
|
||||
| Production-ready voices with no audio prep | Kokoro or Qwen CustomVoice |
|
||||
| The smallest possible footprint (CPU-only) | Kokoro |
|
||||
| Fine control over delivery (tone, pace, emotion) | Qwen CustomVoice |
|
||||
| The broadest language coverage | [Voice Cloning](/overview/voice-cloning) via Chatterbox Multilingual (23 langs) |
|
||||
|
||||
## Limitations
|
||||
|
||||
<Callout type="warn">
|
||||
Preset voices are fixed — you can't fine-tune or modify the underlying voice. If you want a specific voice that isn't in the catalog, use a cloning engine and provide a reference sample.
|
||||
</Callout>
|
||||
|
||||
- Preset voices can't be exported to use in other Voicebox installations as audio (only as profile metadata pointing to the same engine + voice ID)
|
||||
- The Kokoro voice catalog is set by the upstream model — new voices appear only when hexgrad publishes new model releases
|
||||
- Qwen CustomVoice's 9 speakers are part of the model checkpoint — same constraint
|
||||
|
||||
## Next Steps
|
||||
|
||||
<Cards>
|
||||
<Card title="Voice Cloning" href="/overview/voice-cloning">
|
||||
Clone a specific voice from your own audio
|
||||
</Card>
|
||||
<Card title="Generate Speech" href="/overview/generating-speech">
|
||||
Use a profile to generate audio
|
||||
</Card>
|
||||
<Card title="Build Stories" href="/overview/building-stories">
|
||||
Compose multi-voice narratives
|
||||
</Card>
|
||||
</Cards>
|
||||
@@ -1,25 +1,11 @@
|
||||
---
|
||||
title: "Voice Cloning"
|
||||
description: "Clone any voice from a few seconds of reference audio"
|
||||
description: "Clone any voice from just a few seconds of audio"
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
Voicebox can replicate a specific person's voice from a short audio sample — known as **zero-shot voice cloning**. You provide 10-30 seconds of clear speech, the model extracts a voice embedding, and from then on you can generate any text in that voice.
|
||||
|
||||
Five engines in 0.4 support cloning:
|
||||
|
||||
| Engine | Languages | Strengths |
|
||||
| --------------------------- | --------- | -------------------------------------------------------------------------- |
|
||||
| **Qwen3-TTS** (0.6B / 1.7B) | 10 | High-quality multilingual, supports delivery instructions on the same kwarg |
|
||||
| **Chatterbox Multilingual** | 23 | Broadest language coverage — Arabic, Hindi, Swahili, Hebrew, more |
|
||||
| **Chatterbox Turbo** | English | Fast 350M model with paralinguistic emotion tags (`[laugh]`, `[sigh]`) |
|
||||
| **LuxTTS** | English | Lightweight (~1 GB VRAM), 48 kHz output, 150x realtime on CPU |
|
||||
| **TADA** (1B / 3B) | 10 | Speech-language model with 700s+ coherent long-form generation |
|
||||
|
||||
<Callout type="info">
|
||||
Don't want to record audio? Use a curated voice from Kokoro or Qwen CustomVoice instead — see [Preset Voices](/overview/preset-voices).
|
||||
</Callout>
|
||||
Voicebox uses **Qwen3-TTS** from Alibaba to achieve near-perfect voice cloning from just a few seconds of audio. The model captures prosody, emotion, and natural cadence.
|
||||
|
||||
## How It Works
|
||||
|
||||
@@ -27,30 +13,17 @@ Five engines in 0.4 support cloning:
|
||||
<Step title="Upload or Record Sample">
|
||||
Provide 10-30 seconds of clear speech from the target voice
|
||||
</Step>
|
||||
<Step title="Engine Analysis">
|
||||
The selected engine analyzes vocal characteristics, tone, and speaking patterns
|
||||
<Step title="Model Analysis">
|
||||
Qwen3-TTS analyzes vocal characteristics, tone, and speaking patterns
|
||||
</Step>
|
||||
<Step title="Voice Profile Created">
|
||||
A voice embedding is generated and stored with your profile
|
||||
The model generates a voice embedding for synthesis
|
||||
</Step>
|
||||
<Step title="Generate Speech">
|
||||
Use the profile to generate any text in the cloned voice
|
||||
</Step>
|
||||
</Steps>
|
||||
|
||||
## Choosing an Engine for Cloning
|
||||
|
||||
Different engines suit different use cases. The profile grid greys out unsupported engines so you can switch easily.
|
||||
|
||||
| If you want… | Pick |
|
||||
| -------------------------------------------------- | --------------------- |
|
||||
| Best overall quality on a few common languages | **Qwen3-TTS 1.7B** |
|
||||
| Faster generation, slightly lower quality | **Qwen3-TTS 0.6B** |
|
||||
| Languages outside Qwen's 10 (Arabic, Hindi, etc.) | **Chatterbox Multilingual** |
|
||||
| Expressive English with `[laugh]` `[sigh]` tags | **Chatterbox Turbo** |
|
||||
| CPU-only or GPU-light setup, English | **LuxTTS** |
|
||||
| Long-form generation (audiobooks, full chapters) | **TADA 3B** |
|
||||
|
||||
## Best Practices
|
||||
|
||||
### Sample Quality
|
||||
@@ -79,40 +52,24 @@ Adding multiple samples from the same speaker can improve quality:
|
||||
- Different recording conditions
|
||||
|
||||
<Callout type="info">
|
||||
The model will learn a more robust representation from diverse samples. Especially helpful for distinctive voices the model might otherwise smooth over.
|
||||
The model will learn a more robust representation from diverse samples.
|
||||
</Callout>
|
||||
|
||||
## Supported Languages by Engine
|
||||
## Supported Languages
|
||||
|
||||
- **Qwen3-TTS** — English, Chinese, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian (10)
|
||||
- **Chatterbox Multilingual** — Arabic, Chinese, Danish, Dutch, English, Finnish, French, German, Greek, Hebrew, Hindi, Italian, Japanese, Korean, Malay, Norwegian, Polish, Portuguese, Russian, Spanish, Swahili, Swedish, Turkish (23)
|
||||
- **Chatterbox Turbo** — English
|
||||
- **LuxTTS** — English
|
||||
- **TADA 3B** — 10 multilingual; **TADA 1B** — English
|
||||
Currently supported:
|
||||
- English
|
||||
- Chinese (Mandarin)
|
||||
|
||||
For complete language tables and engine-specific notes, see the [TTS Engines developer guide](/developer/tts-engines).
|
||||
More languages coming soon.
|
||||
|
||||
## Limitations
|
||||
|
||||
<Callout type="warn">
|
||||
Voice cloning should only be used with consent. Ensure you have permission to clone someone's voice. See the project's [SECURITY.md](https://github.com/jamiepine/voicebox/blob/main/SECURITY.md) and your local laws on synthetic voice content.
|
||||
Voice cloning should only be used with consent. Ensure you have permission to clone someone's voice.
|
||||
</Callout>
|
||||
|
||||
- Quality depends on sample clarity — noisy samples produce noisy clones
|
||||
- Works best with consistent speaking tone within a sample
|
||||
- Quality depends on sample clarity
|
||||
- Works best with consistent speaking tone
|
||||
- May struggle with extreme accents or speech impediments
|
||||
- Background noise reduces quality and can introduce artifacts
|
||||
|
||||
## Next Steps
|
||||
|
||||
<Cards>
|
||||
<Card title="Creating Voice Profiles" href="/overview/creating-voice-profiles">
|
||||
Step-by-step guide to creating profiles
|
||||
</Card>
|
||||
<Card title="Preset Voices" href="/overview/preset-voices">
|
||||
Use built-in voices instead of cloning
|
||||
</Card>
|
||||
<Card title="Generating Speech" href="/overview/generating-speech">
|
||||
Use a profile to generate audio
|
||||
</Card>
|
||||
</Cards>
|
||||
- Background noise reduces quality
|
||||
|
||||
@@ -1,4 +1,9 @@
|
||||
import { defineConfig, defineDocs, frontmatterSchema, metaSchema } from 'fumadocs-mdx/config';
|
||||
import {
|
||||
defineConfig,
|
||||
defineDocs,
|
||||
frontmatterSchema,
|
||||
metaSchema,
|
||||
} from 'fumadocs-mdx/config';
|
||||
|
||||
// You can customise Zod schemas for frontmatter and `meta.json` here
|
||||
// see https://fumadocs.dev/docs/mdx/collections
|
||||
|
||||
+14
-4
@@ -2,7 +2,11 @@
|
||||
"compilerOptions": {
|
||||
"baseUrl": ".",
|
||||
"target": "ESNext",
|
||||
"lib": ["dom", "dom.iterable", "esnext"],
|
||||
"lib": [
|
||||
"dom",
|
||||
"dom.iterable",
|
||||
"esnext"
|
||||
],
|
||||
"allowJs": true,
|
||||
"skipLibCheck": true,
|
||||
"strict": true,
|
||||
@@ -16,8 +20,12 @@
|
||||
"jsx": "react-jsx",
|
||||
"incremental": true,
|
||||
"paths": {
|
||||
"@/*": ["./*"],
|
||||
"@/.source": [".source"]
|
||||
"@/*": [
|
||||
"./*"
|
||||
],
|
||||
"@/.source": [
|
||||
".source"
|
||||
]
|
||||
},
|
||||
"plugins": [
|
||||
{
|
||||
@@ -32,5 +40,7 @@
|
||||
".next/types/**/*.ts",
|
||||
".next/dev/types/**/*.ts"
|
||||
],
|
||||
"exclude": ["node_modules"]
|
||||
"exclude": [
|
||||
"node_modules"
|
||||
]
|
||||
}
|
||||
|
||||
@@ -69,22 +69,10 @@ setup-python:
|
||||
}
|
||||
Write-Host "Installing Python dependencies..."
|
||||
& "{{ python }}" -m pip install --upgrade pip -q
|
||||
$gpus = Get-CimInstance Win32_VideoController | Select-Object -ExpandProperty Name
|
||||
Write-Host "Detected GPUs: $($gpus -join ', ')"
|
||||
$hasNvidia = ($gpus | Where-Object { $_ -match 'NVIDIA' }).Count -gt 0
|
||||
$hasIntelArc = ($gpus | Where-Object { $_ -match 'Arc' }).Count -gt 0
|
||||
$hasNvidia = $null -ne (Get-WmiObject Win32_VideoController | Where-Object { $_.Name -match 'NVIDIA' })
|
||||
if ($hasNvidia) { \
|
||||
Write-Host "NVIDIA GPU detected — installing PyTorch with CUDA support..."; \
|
||||
& "{{ pip }}" install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128; \
|
||||
} elseif ($hasIntelArc) { \
|
||||
Write-Host "Intel Arc GPU detected — installing PyTorch with XPU support..."; \
|
||||
& "{{ pip }}" install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/xpu; \
|
||||
& "{{ pip }}" install intel-extension-for-pytorch --index-url https://download.pytorch.org/whl/xpu; \
|
||||
} else { \
|
||||
Write-Host "No NVIDIA or Intel Arc GPU detected — using CPU-only PyTorch."; \
|
||||
Write-Host "If you have an Intel Arc GPU, install XPU support manually:"; \
|
||||
Write-Host " pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/xpu"; \
|
||||
Write-Host " pip install intel-extension-for-pytorch --index-url https://download.pytorch.org/whl/xpu"; \
|
||||
}
|
||||
& "{{ pip }}" install -r {{ backend_dir }}/requirements.txt
|
||||
& "{{ pip }}" install --no-deps chatterbox-tts
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@voicebox/landing",
|
||||
"version": "0.4.0",
|
||||
"version": "0.3.1",
|
||||
"description": "Landing page for voicebox.sh",
|
||||
"scripts": {
|
||||
"dev": "bun --bun next dev --turbo",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
'use client';
|
||||
|
||||
import { Github, Globe, Languages, MessageSquare, SlidersHorizontal, Zap } from 'lucide-react';
|
||||
import { Github, Globe, Languages, MessageSquare, Zap } from 'lucide-react';
|
||||
import { useEffect, useState } from 'react';
|
||||
import { ControlUI } from '@/components/ControlUI';
|
||||
import { Features } from '@/components/Features';
|
||||
@@ -236,101 +236,6 @@ export default function Home() {
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Qwen CustomVoice */}
|
||||
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
|
||||
<div className="flex items-start justify-between mb-3">
|
||||
<div>
|
||||
<h3 className="text-base font-semibold text-foreground">Qwen CustomVoice</h3>
|
||||
<span className="text-xs text-muted-foreground/60">by Alibaba</span>
|
||||
</div>
|
||||
<div className="flex gap-1.5">
|
||||
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
|
||||
1.7B
|
||||
</span>
|
||||
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
|
||||
0.6B
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
|
||||
Nine premium preset speakers with natural-language style control. Tell the model how
|
||||
to deliver — "speak slowly with warmth", "authoritative and clear" — and it adapts
|
||||
tone, emotion, and pace.
|
||||
</p>
|
||||
<div className="flex flex-wrap gap-2">
|
||||
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
|
||||
<SlidersHorizontal className="h-3 w-3" />
|
||||
Instruct control
|
||||
</span>
|
||||
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
|
||||
<Globe className="h-3 w-3" />
|
||||
10 languages
|
||||
</span>
|
||||
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
|
||||
9 preset voices
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* HumeAI TADA */}
|
||||
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
|
||||
<div className="flex items-start justify-between mb-3">
|
||||
<div>
|
||||
<h3 className="text-base font-semibold text-foreground">TADA</h3>
|
||||
<span className="text-xs text-muted-foreground/60">by Hume AI</span>
|
||||
</div>
|
||||
<div className="flex gap-1.5">
|
||||
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
|
||||
3B
|
||||
</span>
|
||||
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
|
||||
1B
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
|
||||
Speech-language model with text-acoustic dual alignment. Built for long-form
|
||||
generation — produces 700s+ of coherent audio without drift. Multilingual at 3B,
|
||||
English-focused at 1B.
|
||||
</p>
|
||||
<div className="flex flex-wrap gap-2">
|
||||
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
|
||||
<Globe className="h-3 w-3" />
|
||||
10 languages
|
||||
</span>
|
||||
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
|
||||
Long-form coherent
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Kokoro 82M */}
|
||||
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
|
||||
<div className="flex items-start justify-between mb-3">
|
||||
<div>
|
||||
<h3 className="text-base font-semibold text-foreground">Kokoro</h3>
|
||||
<span className="text-xs text-muted-foreground/60">by hexgrad · Apache 2.0</span>
|
||||
</div>
|
||||
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
|
||||
82M
|
||||
</span>
|
||||
</div>
|
||||
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
|
||||
Tiny 82M-parameter TTS that runs at CPU realtime with negligible VRAM. Pre-built
|
||||
voice styles instead of cloning — pick a voice, type, generate. Smallest footprint
|
||||
of any engine.
|
||||
</p>
|
||||
<div className="flex flex-wrap gap-2">
|
||||
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
|
||||
<Zap className="h-3 w-3" />
|
||||
CPU realtime
|
||||
</span>
|
||||
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
|
||||
Preset voices
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</section>
|
||||
|
||||
@@ -1,7 +1,6 @@
|
||||
import { Coffee } from 'lucide-react';
|
||||
import Image from 'next/image';
|
||||
import Link from 'next/link';
|
||||
import { DONATE_URL, GITHUB_REPO } from '@/lib/constants';
|
||||
import { GITHUB_REPO } from '@/lib/constants';
|
||||
|
||||
export function Footer() {
|
||||
return (
|
||||
@@ -20,19 +19,9 @@ export function Footer() {
|
||||
/>
|
||||
<span className="text-sm font-semibold">Voicebox</span>
|
||||
</div>
|
||||
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
|
||||
<p className="text-sm text-muted-foreground leading-relaxed">
|
||||
Open source voice cloning studio. Local-first, free forever.
|
||||
</p>
|
||||
<a
|
||||
href={DONATE_URL}
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
className="inline-flex items-center gap-2 rounded-lg border border-border/60 bg-card/60 px-3 py-2 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-[#FFDD00]/40"
|
||||
aria-label="Donate via Buy Me a Coffee"
|
||||
>
|
||||
<Coffee className="h-4 w-4 text-[#FFDD00]" />
|
||||
<span className="text-[13px] font-medium">Donate</span>
|
||||
</a>
|
||||
</div>
|
||||
|
||||
{/* Product */}
|
||||
|
||||
@@ -1,9 +1,9 @@
|
||||
'use client';
|
||||
|
||||
import { Coffee, Github } from 'lucide-react';
|
||||
import { Github } from 'lucide-react';
|
||||
import Image from 'next/image';
|
||||
import { useEffect, useState } from 'react';
|
||||
import { DONATE_URL, GITHUB_REPO } from '@/lib/constants';
|
||||
import { GITHUB_REPO } from '@/lib/constants';
|
||||
|
||||
function formatStarCount(count: number): string {
|
||||
if (count >= 1000) {
|
||||
@@ -75,33 +75,21 @@ export function Navbar() {
|
||||
</a>
|
||||
</div>
|
||||
|
||||
{/* Donate + GitHub star buttons */}
|
||||
<div className="flex items-center gap-2 justify-self-end">
|
||||
<a
|
||||
href={DONATE_URL}
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
className="hidden sm:flex items-center gap-2 rounded-lg border border-border/60 bg-card/60 px-3 py-1.5 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-[#FFDD00]/40"
|
||||
aria-label="Donate via Buy Me a Coffee"
|
||||
>
|
||||
<Coffee className="h-4 w-4 text-[#FFDD00]" />
|
||||
<span className="text-[13px] font-medium">Donate</span>
|
||||
</a>
|
||||
<a
|
||||
href={GITHUB_REPO}
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
className="flex items-center gap-2 rounded-lg border border-border/60 bg-card/60 px-3 py-1.5 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-border"
|
||||
>
|
||||
<Github className="h-4 w-4" />
|
||||
<span className="text-[13px] font-medium">Star</span>
|
||||
{starCount !== null && (
|
||||
<span className="border-l border-border/60 pl-2 text-[13px] font-semibold text-foreground">
|
||||
{formatStarCount(starCount)}
|
||||
</span>
|
||||
)}
|
||||
</a>
|
||||
</div>
|
||||
{/* GitHub star button */}
|
||||
<a
|
||||
href={GITHUB_REPO}
|
||||
target="_blank"
|
||||
rel="noopener noreferrer"
|
||||
className="flex items-center gap-2 justify-self-end rounded-lg border border-border/60 bg-card/60 px-3 py-1.5 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-border"
|
||||
>
|
||||
<Github className="h-4 w-4" />
|
||||
<span className="text-[13px] font-medium">Star</span>
|
||||
{starCount !== null && (
|
||||
<span className="border-l border-border/60 pl-2 text-[13px] font-semibold text-foreground">
|
||||
{formatStarCount(starCount)}
|
||||
</span>
|
||||
)}
|
||||
</a>
|
||||
</div>
|
||||
</nav>
|
||||
);
|
||||
|
||||
@@ -4,7 +4,6 @@ export const LATEST_VERSION = 'v0.1.0';
|
||||
|
||||
export const GITHUB_REPO = 'https://github.com/jamiepine/voicebox';
|
||||
export const GITHUB_RELEASES_PAGE = `${GITHUB_REPO}/releases`;
|
||||
export const DONATE_URL = 'https://buymeacoffee.com/jamiepine';
|
||||
|
||||
export const DOWNLOAD_LINKS = {
|
||||
macArm: GITHUB_RELEASES_PAGE,
|
||||
|
||||
+1
-1
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "voicebox",
|
||||
"version": "0.4.0",
|
||||
"version": "0.3.1",
|
||||
"private": true,
|
||||
"workspaces": [
|
||||
"app",
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@voicebox/tauri",
|
||||
"private": true,
|
||||
"version": "0.4.0",
|
||||
"version": "0.3.1",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
|
||||
Generated
+1
-1
@@ -5041,7 +5041,7 @@ checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
|
||||
|
||||
[[package]]
|
||||
name = "voicebox"
|
||||
version = "0.4.0"
|
||||
version = "0.3.1"
|
||||
dependencies = [
|
||||
"base64 0.22.1",
|
||||
"core-foundation-sys",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "voicebox"
|
||||
version = "0.4.0"
|
||||
version = "0.3.1"
|
||||
description = "A production-quality desktop app for Qwen3-TTS voice cloning and generation"
|
||||
authors = ["you"]
|
||||
license = ""
|
||||
|
||||
@@ -5,10 +5,6 @@ fn main() {
|
||||
// Link Swift runtime libraries for screencapturekit crate
|
||||
#[cfg(target_os = "macos")]
|
||||
{
|
||||
// ScreenCaptureKit does not exist on macOS 11, so weak-link it to
|
||||
// allow the app to launch and gate usage at runtime instead.
|
||||
println!("cargo:rustc-link-arg=-Wl,-weak_framework,ScreenCaptureKit");
|
||||
|
||||
// Add Swift runtime library paths to RPATH
|
||||
println!("cargo:rustc-link-arg=-Wl,-rpath,/usr/lib/swift");
|
||||
println!("cargo:rustc-link-arg=-L/usr/lib/swift");
|
||||
|
||||
@@ -13,7 +13,6 @@ use screencapturekit::{
|
||||
},
|
||||
};
|
||||
use std::io::Cursor;
|
||||
use std::process::Command;
|
||||
use std::sync::{Arc, Mutex};
|
||||
use tokio::sync::mpsc;
|
||||
|
||||
@@ -21,10 +20,6 @@ pub async fn start_capture(
|
||||
state: &AudioCaptureState,
|
||||
max_duration_secs: u32,
|
||||
) -> Result<(), String> {
|
||||
if !is_supported() {
|
||||
return Err("System audio capture requires macOS 12.3 or newer.".to_string());
|
||||
}
|
||||
|
||||
// Reset previous samples
|
||||
state.reset();
|
||||
|
||||
@@ -149,22 +144,17 @@ pub async fn stop_capture(state: &AudioCaptureState) -> Result<String, String> {
|
||||
}
|
||||
|
||||
pub fn is_supported() -> bool {
|
||||
macos_version_at_least(12, 3)
|
||||
}
|
||||
|
||||
fn macos_version_at_least(required_major: u64, required_minor: u64) -> bool {
|
||||
let output = match Command::new("sw_vers").arg("-productVersion").output() {
|
||||
Ok(output) if output.status.success() => output,
|
||||
_ => return false,
|
||||
};
|
||||
|
||||
let version = String::from_utf8_lossy(&output.stdout);
|
||||
let mut parts = version.trim().split('.');
|
||||
|
||||
let major = parts.next().and_then(|part| part.parse::<u64>().ok()).unwrap_or(0);
|
||||
let minor = parts.next().and_then(|part| part.parse::<u64>().ok()).unwrap_or(0);
|
||||
|
||||
major > required_major || (major == required_major && minor >= required_minor)
|
||||
// ScreenCaptureKit requires macOS 12.3+
|
||||
// Check if we're on a supported version
|
||||
#[cfg(target_os = "macos")]
|
||||
{
|
||||
// Basic check - ScreenCaptureKit should be available on macOS 12.3+
|
||||
true
|
||||
}
|
||||
#[cfg(not(target_os = "macos"))]
|
||||
{
|
||||
false
|
||||
}
|
||||
}
|
||||
|
||||
fn extract_audio_samples(sample_buffer: CMSampleBuffer) -> Result<Vec<f32>, String> {
|
||||
|
||||
@@ -401,25 +401,9 @@ impl AudioOutputState {
|
||||
eprintln!("play_to_device: Failed to play stream: {}", e);
|
||||
format!("Failed to play stream: {}", e)
|
||||
})?;
|
||||
|
||||
|
||||
eprintln!("play_to_device: Stream started successfully");
|
||||
|
||||
// Keep the stream alive until playback finishes.
|
||||
// Previously the stream was dropped immediately on function return,
|
||||
// causing silent playback (cpal stops output when its Stream is dropped).
|
||||
let total_samples = {
|
||||
buffer.lock().unwrap().len()
|
||||
};
|
||||
loop {
|
||||
let pos = position.load(std::sync::atomic::Ordering::Relaxed);
|
||||
if pos >= total_samples || stop_flag.load(std::sync::atomic::Ordering::Relaxed) {
|
||||
break;
|
||||
}
|
||||
std::thread::sleep(std::time::Duration::from_millis(10));
|
||||
}
|
||||
|
||||
// stream is dropped here, after audio has finished playing
|
||||
drop(stream);
|
||||
eprintln!("play_to_device: Function completed successfully");
|
||||
Ok(())
|
||||
}
|
||||
|
||||
@@ -53,41 +53,6 @@ fn find_voicebox_pid_on_port(port: u16) -> Option<u32> {
|
||||
None
|
||||
}
|
||||
|
||||
/// Check if a Voicebox server is responding on the given port.
|
||||
///
|
||||
/// Sends an HTTP GET to `/health` and returns `true` only if the response
|
||||
/// is valid JSON matching the Voicebox `HealthResponse` schema — specifically
|
||||
/// `status` must be `"healthy"`, and both `model_loaded` and `gpu_available`
|
||||
/// must be present as booleans. This prevents misidentifying an unrelated
|
||||
/// service that happens to expose a `/health` endpoint.
|
||||
#[allow(dead_code)] // Used in platform-specific cfg blocks
|
||||
fn check_health(port: u16) -> bool {
|
||||
let url = format!("http://127.0.0.1:{}/health", port);
|
||||
match reqwest::blocking::Client::builder()
|
||||
.timeout(std::time::Duration::from_secs(3))
|
||||
.build()
|
||||
{
|
||||
Ok(client) => match client.get(&url).send() {
|
||||
Ok(resp) => {
|
||||
if !resp.status().is_success() {
|
||||
return false;
|
||||
}
|
||||
// Parse as JSON and validate Voicebox-specific fields
|
||||
match resp.json::<serde_json::Value>() {
|
||||
Ok(body) => {
|
||||
body.get("status").and_then(|v| v.as_str()) == Some("healthy")
|
||||
&& body.get("model_loaded").map(|v| v.is_boolean()).unwrap_or(false)
|
||||
&& body.get("gpu_available").map(|v| v.is_boolean()).unwrap_or(false)
|
||||
}
|
||||
Err(_) => false,
|
||||
}
|
||||
}
|
||||
Err(_) => false,
|
||||
},
|
||||
Err(_) => false,
|
||||
}
|
||||
}
|
||||
|
||||
struct ServerState {
|
||||
child: Mutex<Option<tauri_plugin_shell::process::CommandChild>>,
|
||||
server_pid: Mutex<Option<u32>>,
|
||||
@@ -115,8 +80,7 @@ async fn start_server(
|
||||
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
|
||||
}
|
||||
|
||||
// Check if a voicebox server is already running on our port (from previous session with keep_running=true,
|
||||
// or an externally started server e.g. via `python`, `uvicorn`, Docker, etc.)
|
||||
// Check if a voicebox server is already running on our port (from previous session with keep_running=true)
|
||||
#[cfg(unix)]
|
||||
{
|
||||
use std::process::Command;
|
||||
@@ -137,20 +101,6 @@ async fn start_server(
|
||||
*state.server_pid.lock().unwrap() = Some(pid);
|
||||
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
|
||||
}
|
||||
} else {
|
||||
// Process name doesn't contain "voicebox" — could be an external
|
||||
// Python/uvicorn/Docker server. Verify via HTTP health check.
|
||||
println!("Port {} in use by '{}' (PID: {}), checking if it's a Voicebox server...", SERVER_PORT, command, pid_str);
|
||||
if check_health(SERVER_PORT) {
|
||||
println!("Health check passed — reusing external server on port {}", SERVER_PORT);
|
||||
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
|
||||
}
|
||||
println!("Health check failed — port is occupied by a non-Voicebox process");
|
||||
return Err(format!(
|
||||
"Port {} is already in use by another application ({}). \
|
||||
Close it or change the Voicebox server port.",
|
||||
SERVER_PORT, command
|
||||
));
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -164,24 +114,18 @@ async fn start_server(
|
||||
&format!("127.0.0.1:{}", SERVER_PORT).parse().unwrap(),
|
||||
std::time::Duration::from_secs(1),
|
||||
).is_ok() {
|
||||
// Port is in use — check if it's a voicebox process by name first
|
||||
// Port is in use — check if it's a voicebox process
|
||||
if let Some(pid) = find_voicebox_pid_on_port(SERVER_PORT) {
|
||||
println!("Found existing voicebox-server on port {} (PID: {}), reusing it", SERVER_PORT, pid);
|
||||
*state.server_pid.lock().unwrap() = Some(pid);
|
||||
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
|
||||
} else {
|
||||
return Err(format!(
|
||||
"Port {} is already in use by another application. \
|
||||
Close the other application or change the Voicebox port.",
|
||||
SERVER_PORT
|
||||
));
|
||||
}
|
||||
// Process name doesn't match — could be an external Python/Docker server.
|
||||
// Verify via HTTP health check before giving up.
|
||||
println!("Port {} in use by unknown process, checking if it's a Voicebox server...", SERVER_PORT);
|
||||
if check_health(SERVER_PORT) {
|
||||
println!("Health check passed — reusing external server on port {}", SERVER_PORT);
|
||||
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
|
||||
}
|
||||
return Err(format!(
|
||||
"Port {} is already in use by another application. \
|
||||
Close the other application or change the Voicebox port.",
|
||||
SERVER_PORT
|
||||
));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -860,22 +804,6 @@ pub fn run() {
|
||||
// Tell the server to disable its watchdog so it survives
|
||||
// after this process exits.
|
||||
println!("Keep server running: disabling watchdog...");
|
||||
|
||||
// Write a sentinel file as a reliable fallback. On Windows
|
||||
// the HTTP request below can race with process exit, leaving
|
||||
// the watchdog unaware it should stay alive. The sentinel
|
||||
// file is checked during the watchdog grace period.
|
||||
let data_dir = app
|
||||
.path()
|
||||
.app_data_dir()
|
||||
.unwrap_or_default();
|
||||
let sentinel = data_dir.join(".keep-running");
|
||||
if let Err(e) = std::fs::write(&sentinel, b"1") {
|
||||
eprintln!("Failed to write keep-running sentinel: {}", e);
|
||||
} else {
|
||||
println!("Wrote keep-running sentinel to {:?}", sentinel);
|
||||
}
|
||||
|
||||
let client = reqwest::blocking::Client::builder()
|
||||
.timeout(std::time::Duration::from_secs(2))
|
||||
.build()
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"$schema": "https://schema.tauri.app/config/2",
|
||||
"productName": "Voicebox",
|
||||
"version": "0.4.0",
|
||||
"version": "0.3.1",
|
||||
"identifier": "sh.voicebox.app",
|
||||
"build": {
|
||||
"beforeDevCommand": "bun run dev",
|
||||
|
||||
@@ -2,8 +2,9 @@ import { invoke } from '@tauri-apps/api/core';
|
||||
import type { PlatformAudio, AudioDevice } from '@/platform/types';
|
||||
|
||||
export const tauriAudio: PlatformAudio = {
|
||||
async isSystemAudioSupported(): Promise<boolean> {
|
||||
return await invoke<boolean>('is_system_audio_supported');
|
||||
isSystemAudioSupported(): boolean {
|
||||
// This will be checked dynamically via invoke
|
||||
return true; // Tauri supports it, but actual support depends on platform
|
||||
},
|
||||
|
||||
async startSystemAudioCapture(maxDurationSecs: number): Promise<void> {
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@voicebox/web",
|
||||
"private": true,
|
||||
"version": "0.4.0",
|
||||
"version": "0.3.1",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import type { PlatformAudio, AudioDevice } from '@/platform/types';
|
||||
|
||||
export const webAudio: PlatformAudio = {
|
||||
async isSystemAudioSupported(): Promise<boolean> {
|
||||
isSystemAudioSupported(): boolean {
|
||||
return false; // System audio capture not supported in web
|
||||
},
|
||||
|
||||
|
||||
Reference in New Issue
Block a user