Bump version: 0.3.1 → 0.4.0

Catches format drift that accumulated across 13 authored files in
app/src and docs/. Auto-generated artifacts (tauri/src-tauri/gen,
docs/openapi.json, docs/cli.json, app/src/lib/api) were left alone
since the build regenerates them on each run — baking their formatted
state into git just causes churn next build.

No behavioral changes. Trailing commas, line wrapping, and indentation
only.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

.agents/skills/triage-prs/SKILL.md

@@ -0,0 +1,299 @@
+---
+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 Classifies every open PR into must-merge, candidate, superseded, or deferred; writes a working triage doc; and runs the merge loop end-to-end.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
+
+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then work it — rebasing where needed, merging in isolation-safe batches, applying post-merge follow-ups, and closing superseded or partially-applicable PRs with credit to their authors.
+
+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
+
+- Before a minor or major release when 10+ open PRs have accumulated
+- 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)
+- Clarity on the target version — the triage doc is named after it (e.g. `0.4.0_PR_TRIAGE.md`)
+
+## Workflow
+
+### 1. Set up an isolated PR-review worktree
+
+```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
+gh pr list --state open --limit 50 --json \
+  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]}'
+```
+
+You want, for each PR:
+- Size (`+additions/-deletions`)
+- 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.
+
+### 3. Classify into tiers
+
+Sort each PR into exactly one bucket:
+
+**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.

.bumpversion.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.3.1
+current_version = 0.4.0
 commit = True
 tag = True
 tag_name = v{new_version}

.dockerignore

@@ -38,7 +38,6 @@ biome.json
 .bumpversion.cfg
 .npmrc
 Makefile
-CHANGELOG.md
 CONTRIBUTING.md
 SECURITY.md
 LICENSE

.github/workflows/release.yml

@@ -203,6 +203,12 @@ 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

CHANGELOG.md

@@ -7,6 +7,117 @@
 
 ## [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.
@@ -444,7 +555,9 @@ 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/v0.2.3...HEAD
+[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
 [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

Dockerfile

@@ -9,7 +9,7 @@ FROM oven/bun:1 AS frontend
 WORKDIR /build
 
 # Copy workspace config and frontend source
-COPY package.json bun.lock ./
+COPY package.json bun.lock CHANGELOG.md ./
 COPY app/ ./app/
 COPY web/ ./web/
 

app/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@voicebox/app",
-  "version": "0.3.1",
+  "version": "0.4.0",
   "private": true,
   "type": "module",
   "scripts": {

app/src/components/AppFrame/AppFrame.tsx

@@ -14,15 +14,17 @@ 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 ? (

app/src/components/EffectsTab/EffectsTab.tsx

@@ -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>
+  );
 }

app/src/components/Generation/FloatingGenerateBox.tsx

@@ -1,7 +1,7 @@
 import { useQuery } from '@tanstack/react-query';
 import { useMatchRoute } from '@tanstack/react-router';
 import { AnimatePresence, motion } from 'framer-motion';
-import { Loader2, Sparkles } from 'lucide-react';
+import { Loader2, SlidersHorizontal, 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';
@@ -40,6 +40,7 @@ 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);
@@ -125,22 +126,29 @@ 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';
   useEffect(() => {
     if (selectedProfile?.language) {
       form.setValue('language', selectedProfile.language as LanguageCode);
     }
-    // Auto-switch engine if profile has a default
-    if (selectedProfile?.default_engine) {
-      form.setValue(
-        'engine',
-        selectedProfile.default_engine as
-          | 'qwen'
-          | 'luxtts'
-          | 'chatterbox'
-          | 'chatterbox_turbo'
-          | 'tada'
-          | 'kokoro',
-      );
+    // Auto-switch engine to match the profile
+    const engine = selectedProfile?.default_engine ?? selectedProfile?.preset_engine;
+    if (engine) {
+      form.setValue('engine', engine as EngineValue);
+    } else if (selectedProfile && selectedProfile.voice_type !== 'preset') {
+      // Cloned/designed profile with no default — ensure a compatible (non-preset) engine
+      const currentEngine = form.getValues('engine');
+      const presetEngines = new Set(['kokoro', 'qwen_custom_voice']);
+      if (presetEngines.has(currentEngine)) {
+        form.setValue('engine', 'qwen');
+      }
     }
     // Pre-fill effects from profile defaults
     if (
@@ -346,9 +354,80 @@ 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 }}

app/src/components/Generation/GenerationForm.tsx

@@ -1,5 +1,5 @@
-import { useEffect } from 'react';
 import { Loader2, Mic } from 'lucide-react';
+import { useEffect } from 'react';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import {
@@ -24,7 +24,11 @@ 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 { EngineModelSelector, applyEngineSelection, getEngineDescription } from './EngineModelSelector';
+import {
+  applyEngineSelection,
+  EngineModelSelector,
+  getEngineDescription,
+} from './EngineModelSelector';
 import { ParalinguisticInput } from './ParalinguisticInput';
 
 function getEngineSelectValue(engine: string): string {
@@ -114,7 +118,7 @@ export function GenerationForm() {
               )}
             />
 
-            {(form.watch('engine') === 'qwen' || form.watch('engine') === 'qwen_custom_voice') && (
+            {form.watch('engine') === 'qwen_custom_voice' && (
               <FormField
                 control={form.control}
                 name="instruct"

app/src/components/History/HistoryTable.tsx

@@ -45,6 +45,7 @@ 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,
@@ -124,6 +125,8 @@ export function HistoryTable() {
   });
 
   const deleteGeneration = useDeleteGeneration();
+  const clearFailed = useClearFailedGenerations();
+  const [clearFailedDialogOpen, setClearFailedDialogOpen] = useState(false);
   const exportGeneration = useExportGeneration();
   const exportGenerationAudio = useExportGenerationAudio();
   const importGeneration = useImportGeneration();
@@ -157,11 +160,11 @@ export function HistoryTable() {
   const pendingCount = useGenerationStore((state) => state.pendingGenerationIds.size);
   const prevPendingCountRef = useRef(pendingCount);
   useEffect(() => {
-    if (deleteGeneration.isSuccess || importGeneration.isSuccess) {
+    if (deleteGeneration.isSuccess || importGeneration.isSuccess || clearFailed.isSuccess) {
       setPage(0);
       setAllHistory([]);
     }
-  }, [deleteGeneration.isSuccess, importGeneration.isSuccess]);
+  }, [deleteGeneration.isSuccess, importGeneration.isSuccess, clearFailed.isSuccess]);
 
   useEffect(() => {
     // A generation finished (pending count decreased) — scroll back to show it
@@ -415,6 +418,27 @@ 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">
@@ -424,6 +448,23 @@ 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" />
           )}
@@ -759,6 +800,31 @@ 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>

app/src/components/ServerSettings/ModelProgress.tsx

@@ -12,7 +12,11 @@ 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);
 

app/src/components/ServerTab/ChangelogPage.tsx

@@ -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-1">
-        <h3 className="text-sm font-medium">{entry.version}</h3>
+      <div className="flex items-baseline gap-3 mb-3">
+        <h3 className="text-xl font-semibold tracking-tight">{entry.version}</h3>
         {entry.date && <span className="text-xs text-muted-foreground">{entry.date}</span>}
         {entry.version === 'Unreleased' && <Badge variant="outline">dev</Badge>}
       </div>

app/src/components/StoriesTab/StoryChatItem.tsx

@@ -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)}
             />
@@ -127,7 +127,10 @@ 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>
@@ -139,15 +142,12 @@ 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),
@@ -156,11 +156,7 @@ export function SortableStoryChatItem(props: Omit<StoryChatItemProps, 'dragHandl
 
   return (
     <div ref={setNodeRef} style={style} {...attributes}>
-      <StoryChatItem
-        {...props}
-        dragHandleProps={listeners}
-        isDragging={isDragging}
-      />
+      <StoryChatItem {...props} dragHandleProps={listeners} isDragging={isDragging} />
     </div>
   );
 }

app/src/components/StoriesTab/StoryTrackEditor.tsx

@@ -500,7 +500,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
   }, [trimmingItem, trimSide, tempTrimValues, storyId, trimItem, toast]);
 
   const handleSplit = useCallback(() => {
-    if (!selectedClipId) return;
+    if (!selectedClipId || splitItem.isPending) return;
 
     const item = items.find((i) => i.id === selectedClipId);
     if (!item) return;

app/src/components/VoiceProfiles/AudioSampleRecording.tsx

@@ -14,12 +14,7 @@ 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>
@@ -87,9 +82,7 @@ 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}
@@ -107,9 +100,7 @@ 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" />

app/src/components/VoiceProfiles/ProfileCard.tsx

@@ -25,9 +25,10 @@ const ENGINE_DISPLAY_NAMES: Record<string, string> = {
 
 interface ProfileCardProps {
   profile: VoiceProfileResponse;
+  disabled?: boolean;
 }
 
-export function ProfileCard({ profile }: ProfileCardProps) {
+export function ProfileCard({ profile, disabled }: ProfileCardProps) {
   const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
 
   const deleteProfile = useDeleteProfile();
@@ -40,6 +41,12 @@ export function ProfileCard({ profile }: ProfileCardProps) {
   const isSelected = selectedProfileId === profile.id;
 
   const handleSelect = () => {
+    // If disabled but already selected, bounce the selection to re-trigger engine auto-switch
+    if (disabled && isSelected) {
+      setSelectedProfileId(null);
+      setTimeout(() => setSelectedProfileId(profile.id), 0);
+      return;
+    }
     setSelectedProfileId(isSelected ? null : profile.id);
   };
 
@@ -80,8 +87,9 @@ export function ProfileCard({ profile }: ProfileCardProps) {
     <>
       <Card
         className={cn(
-          'cursor-pointer hover:shadow-md transition-all flex flex-col h-[162px]',
-          isSelected && 'ring-2 ring-accent shadow-md',
+          'cursor-pointer transition-all flex flex-col h-[162px]',
+          disabled ? 'opacity-40 hover:opacity-60' : 'hover:shadow-md',
+          isSelected && !disabled && 'ring-2 ring-accent shadow-md',
         )}
         onClick={handleSelect}
         tabIndex={0}

app/src/components/VoiceProfiles/ProfileList.tsx

@@ -1,4 +1,5 @@
-import { Mic, Music, Sparkles } from 'lucide-react';
+import { Info, Mic, Sparkles } from 'lucide-react';
+import { useEffect, useRef } from 'react';
 import { Button } from '@/components/ui/button';
 import { Card, CardContent } from '@/components/ui/card';
 import { useProfiles } from '@/lib/hooks/useProfiles';
@@ -9,16 +10,33 @@ import { ProfileForm } from './ProfileForm';
 /** Engines that use preset (built-in) voices instead of cloned profiles. */
 const PRESET_ENGINES = new Set(['kokoro', 'qwen_custom_voice']);
 
-/** Human-readable engine names for empty state messages. */
-const ENGINE_NAMES: Record<string, string> = {
-  kokoro: 'Kokoro',
-  qwen_custom_voice: 'Qwen CustomVoice',
-};
-
 export function ProfileList() {
   const { data: profiles, isLoading, error } = useProfiles();
   const setDialogOpen = useUIStore((state) => state.setProfileDialogOpen);
   const selectedEngine = useUIStore((state) => state.selectedEngine);
+  const selectedProfileId = useUIStore((state) => state.selectedProfileId);
+  const cardRefs = useRef<Map<string, HTMLDivElement>>(new Map());
+
+  // Scroll to the selected profile after engine/sort changes
+  useEffect(() => {
+    if (!selectedProfileId) return;
+    let timeoutId: ReturnType<typeof setTimeout> | null = null;
+    const rafId = requestAnimationFrame(() => {
+      const el = cardRefs.current.get(selectedProfileId);
+      if (!el) return;
+
+      // 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);
+    });
+    return () => {
+      cancelAnimationFrame(rafId);
+      if (timeoutId) clearTimeout(timeoutId);
+    };
+  }, [selectedProfileId, selectedEngine]);
 
   if (isLoading) {
     return null;
@@ -35,10 +53,18 @@ export function ProfileList() {
   const allProfiles = profiles || [];
   const isPresetEngine = PRESET_ENGINES.has(selectedEngine);
 
-  // Filter profiles based on selected engine
-  const filteredProfiles = isPresetEngine
-    ? allProfiles.filter((p) => p.voice_type === 'preset' && p.preset_engine === selectedEngine)
-    : allProfiles.filter((p) => p.voice_type !== 'preset');
+  /** Whether a profile is supported by the currently selected engine. */
+  const isSupported = (p: (typeof allProfiles)[number]) =>
+    isPresetEngine
+      ? p.voice_type === 'preset' && p.preset_engine === selectedEngine
+      : p.voice_type !== 'preset';
+
+  // Sort so supported profiles come first
+  const sortedProfiles = [...allProfiles].sort(
+    (a, b) => (isSupported(a) ? 0 : 1) - (isSupported(b) ? 0 : 1),
+  );
+
+  const hasUnsupported = sortedProfiles.some((p) => !isSupported(p));
 
   return (
     <div className="flex flex-col">
@@ -56,29 +82,26 @@ export function ProfileList() {
               </Button>
             </CardContent>
           </Card>
-        ) : filteredProfiles.length === 0 && isPresetEngine ? (
-          <Card>
-            <CardContent className="flex flex-col items-center justify-center py-12">
-              <Music className="h-12 w-12 text-muted-foreground mb-4" />
-              <p className="text-muted-foreground mb-2">
-                No {ENGINE_NAMES[selectedEngine] ?? selectedEngine} voices created yet.
-              </p>
-              <p className="text-sm text-muted-foreground mb-4">
-                Create a profile to choose a specific voice before generating.
-              </p>
-              <Button onClick={() => setDialogOpen(true)}>
-                <Sparkles className="mr-2 h-4 w-4" />
-                Create {ENGINE_NAMES[selectedEngine] ?? selectedEngine} Voice
-              </Button>
-            </CardContent>
-          </Card>
         ) : (
           <div className="flex gap-4 overflow-x-auto p-1 pb-1 lg:grid lg:grid-cols-3 lg:auto-rows-auto lg:overflow-x-visible lg:pb-[150px]">
-            {filteredProfiles.map((profile) => (
-              <div key={profile.id} className="shrink-0 w-[200px] lg:w-auto lg:shrink">
-                <ProfileCard profile={profile} />
+            {sortedProfiles.map((profile) => (
+              <div
+                key={profile.id}
+                className="shrink-0 w-[200px] lg:w-auto lg:shrink"
+                ref={(el) => {
+                  if (el) cardRefs.current.set(profile.id, el);
+                  else cardRefs.current.delete(profile.id);
+                }}
+              >
+                <ProfileCard profile={profile} disabled={!isSupported(profile)} />
               </div>
             ))}
+            {hasUnsupported && (
+              <div className="col-span-full flex items-center gap-2 text-xs text-muted-foreground py-2">
+                <Info className="h-3.5 w-3.5 shrink-0" />
+                <span>Only supported voice profiles can be selected for the current model.</span>
+              </div>
+            )}
           </div>
         )}
       </div>

app/src/components/ui/alert-dialog.tsx

@@ -111,4 +111,4 @@ export {
   AlertDialogDescription,
   AlertDialogAction,
   AlertDialogCancel,
-};
+};

app/src/lib/api/client.ts

@@ -270,6 +270,12 @@ 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);

app/src/lib/hooks/useGenerationForm.ts

@@ -10,6 +10,7 @@ import { useGeneration } from '@/lib/hooks/useGeneration';
 import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
 import { useGenerationStore } from '@/stores/generationStore';
 import { useServerStore } from '@/stores/serverStore';
+import { useUIStore } from '@/stores/uiStore';
 
 const generationSchema = z.object({
   text: z.string().min(1, '').max(50000),
@@ -45,6 +46,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
   const maxChunkChars = useServerStore((state) => state.maxChunkChars);
   const crossfadeMs = useServerStore((state) => state.crossfadeMs);
   const normalizeAudio = useServerStore((state) => state.normalizeAudio);
+  const selectedEngine = useUIStore((state) => state.selectedEngine);
   const [downloadingModelName, setDownloadingModelName] = useState<string | null>(null);
   const [downloadingDisplayName, setDownloadingDisplayName] = useState<string | null>(null);
 
@@ -62,7 +64,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
       seed: undefined,
       modelSize: '1.7B',
       instruct: '',
-      engine: 'qwen',
+      engine: (selectedEngine as GenerationFormValues['engine']) || 'qwen',
       ...options.defaultValues,
     },
   });
@@ -134,7 +136,9 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
 
       const hasModelSizes =
         engine === 'qwen' || engine === 'qwen_custom_voice' || engine === 'tada';
-      const supportsInstruct = engine === 'qwen' || engine === 'qwen_custom_voice';
+      // 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 effectsChain = options.getEffectsChain?.();
       // This now returns immediately with status="generating"
       const result = await generation.mutateAsync({

app/src/lib/hooks/useHistory.ts

@@ -29,6 +29,17 @@ 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();
 

app/src/lib/hooks/useModelDownloadToast.tsx

@@ -131,7 +131,8 @@ 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

app/src/lib/hooks/useSystemAudioCapture.ts

@@ -26,8 +26,24 @@ export function useSystemAudioCapture({
 
   // Check if system audio capture is supported
   useEffect(() => {
-    const supported = platform.audio.isSystemAudioSupported();
-    setIsSupported(supported);
+    let isActive = true;
+
+    void platform.audio
+      .isSystemAudioSupported()
+      .then((supported) => {
+        if (isActive) {
+          setIsSupported(supported);
+        }
+      })
+      .catch(() => {
+        if (isActive) {
+          setIsSupported(false);
+        }
+      });
+
+    return () => {
+      isActive = false;
+    };
   }, [platform]);
 
   const startRecording = useCallback(async () => {

app/src/platform/PlatformContext.tsx

@@ -9,11 +9,7 @@ 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 {

app/src/platform/types.ts

@@ -42,7 +42,7 @@ export interface AudioDevice {
 }
 
 export interface PlatformAudio {
-  isSystemAudioSupported(): boolean;
+  isSystemAudioSupported(): Promise<boolean>;
   startSystemAudioCapture(maxDurationSecs: number): Promise<void>;
   stopSystemAudioCapture(): Promise<Blob>;
   listOutputDevices(): Promise<AudioDevice[]>;

backend/__init__.py

@@ -1,3 +1,3 @@
 # Backend package
 
-__version__ = "0.3.1"
+__version__ = "0.4.0"

backend/app.py

@@ -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 str(file_path).startswith(str(frontend_dir)):
+        if full_path and file_path.is_file() and file_path.is_relative_to(frontend_dir):
             return FileResponse(file_path)
         return FileResponse(frontend_dir / "index.html", media_type="text/html")
 
@@ -146,15 +146,36 @@ 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:
-            return f"ROCm ({device_name})"
-        return f"CUDA ({device_name})"
+            label = f"ROCm ({device_name})"
+        else:
+            label = f"CUDA ({device_name})"
+        if not compatible:
+            label += " [UNSUPPORTED - see logs]"
+        return label
     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)"
 
 
@@ -216,6 +237,13 @@ 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())

backend/backends/base.py

@@ -126,6 +126,75 @@ 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],

backend/backends/chatterbox_backend.py

@@ -18,6 +18,8 @@ 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,
@@ -48,7 +50,7 @@ class ChatterboxTTSBackend:
         self._model_load_lock = asyncio.Lock()
 
     def _get_device(self) -> str:
-        return get_torch_device(force_cpu_on_mac=True)
+        return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
 
     def is_loaded(self) -> bool:
         return self.model is not None
@@ -117,10 +119,7 @@ class ChatterboxTTSBackend:
             del self.model
             self.model = None
             self._device = None
-            if device == "cuda":
-                import torch
-
-                torch.cuda.empty_cache()
+            empty_device_cache(device)
             logger.info("Chatterbox unloaded")
 
     async def create_voice_prompt(
@@ -200,7 +199,7 @@ class ChatterboxTTSBackend:
             import torch
 
             if seed is not None:
-                torch.manual_seed(seed)
+                manual_seed(seed, self._device)
 
             logger.info(f"[Chatterbox] Generating: lang={language}")
 
@@ -220,10 +219,7 @@ 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
 

backend/backends/chatterbox_turbo_backend.py

@@ -18,6 +18,8 @@ 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,
@@ -48,7 +50,7 @@ class ChatterboxTurboTTSBackend:
         self._model_load_lock = asyncio.Lock()
 
     def _get_device(self) -> str:
-        return get_torch_device(force_cpu_on_mac=True)
+        return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
 
     def is_loaded(self) -> bool:
         return self.model is not None
@@ -116,10 +118,7 @@ class ChatterboxTurboTTSBackend:
             del self.model
             self.model = None
             self._device = None
-            if device == "cuda":
-                import torch
-
-                torch.cuda.empty_cache()
+            empty_device_cache(device)
             logger.info("Chatterbox Turbo unloaded")
 
     async def create_voice_prompt(
@@ -181,7 +180,7 @@ class ChatterboxTurboTTSBackend:
             import torch
 
             if seed is not None:
-                torch.manual_seed(seed)
+                manual_seed(seed, self._device)
 
             logger.info("[Chatterbox Turbo] Generating (English)")
 
@@ -200,10 +199,7 @@ 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
 

backend/backends/hume_backend.py

@@ -24,6 +24,8 @@ 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,
 )
@@ -66,7 +68,7 @@ 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)
+        return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
 
     def is_loaded(self) -> bool:
         return self.model is not None
@@ -105,6 +107,7 @@ 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
@@ -142,9 +145,12 @@ class HumeTadaBackend:
                 allow_patterns=["tokenizer*", "special_tokens*"],
             )
 
-            # Determine dtype — use bf16 on CUDA for ~50% memory savings
+            # Determine dtype — use bf16 on CUDA/XPU 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
 
@@ -153,14 +159,14 @@ 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).
@@ -169,12 +175,11 @@ 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}")
@@ -188,11 +193,11 @@ class HumeTadaBackend:
             del self.encoder
             self.encoder = None
 
+        device = self._device
         self._device = None
 
-        import torch
-        if torch.cuda.is_available():
-            torch.cuda.empty_cache()
+        if device:
+            empty_device_cache(device)
 
         logger.info("HumeAI TADA unloaded")
 
@@ -213,9 +218,7 @@ 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)
@@ -239,9 +242,7 @@ 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 = {}
@@ -299,9 +300,7 @@ class HumeTadaBackend:
             from tada.modules.encoder import EncoderOutput
 
             if seed is not None:
-                torch.manual_seed(seed)
-                if torch.cuda.is_available():
-                    torch.cuda.manual_seed(seed)
+                manual_seed(seed, self._device)
 
             device = self._device
 

backend/backends/luxtts_backend.py

@@ -12,7 +12,14 @@ from typing import Optional, Tuple
 import numpy as np
 
 from . import TTSBackend
-from .base import is_model_cached, get_torch_device, combine_voice_prompts as _combine_voice_prompts, model_load_progress
+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
 
 logger = logging.getLogger(__name__)
@@ -30,7 +37,7 @@ class LuxTTSBackend:
         self._device = None
 
     def _get_device(self) -> str:
-        return get_torch_device(allow_mps=True)
+        return get_torch_device(allow_mps=True, allow_xpu=True)
 
     def is_loaded(self) -> bool:
         return self.model is not None
@@ -69,9 +76,12 @@ 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)
@@ -81,12 +91,12 @@ 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
 
-            import torch
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
+            empty_device_cache(device)
 
             logger.info("LuxTTS unloaded")
 
@@ -154,12 +164,8 @@ class LuxTTSBackend:
         await self.load_model()
 
         def _generate_sync():
-            import torch
-
             if seed is not None:
-                torch.manual_seed(seed)
-                if torch.cuda.is_available():
-                    torch.cuda.manual_seed(seed)
+                manual_seed(seed, self.device)
 
             wav = self.model.generate_speech(
                 text=text,

backend/backends/mlx_backend.py

@@ -6,7 +6,6 @@ from typing import Optional, List, Tuple
 import asyncio
 import logging
 import numpy as np
-import os
 from pathlib import Path
 
 logger = logging.getLogger(__name__)
@@ -21,6 +20,7 @@ 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:
@@ -96,32 +96,13 @@ class MLXTTSBackend:
         model_name = f"qwen-tts-{model_size}"
         is_cached = self._is_model_cached(model_size)
 
-        # 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)
+        with model_load_progress(model_name, is_cached):
+            from mlx_audio.tts import load
 
-        try:
-            with model_load_progress(model_name, is_cached):
-                from mlx_audio.tts import load
+            logger.info("Loading MLX TTS model %s...", model_size)
 
-                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)
+            with force_offline_if_cached(is_cached, model_name):
+                self.model = load(model_path)
 
         self._current_model_size = model_size
         self.model_size = model_size
@@ -329,7 +310,9 @@ class MLXSTTBackend:
 
             model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
             logger.info("Loading MLX Whisper model %s...", model_size)
-            self.model = load(model_name)
+
+            with force_offline_if_cached(is_cached, progress_model_name):
+                self.model = load(model_name)
 
         self.model_size = model_size
         logger.info("MLX Whisper model %s loaded successfully", model_size)

backend/backends/pytorch_backend.py

@@ -14,11 +14,14 @@ 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:
@@ -96,18 +99,28 @@ class PyTorchTTSBackend:
             model_path = self._get_model_path(model_size)
             logger.info("Loading TTS model %s on %s...", model_size, self.device)
 
-            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,
-                )
+            # 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,
+                    )
 
         self._current_model_size = model_size
         self.model_size = model_size
@@ -120,8 +133,7 @@ class PyTorchTTSBackend:
             self.model = None
             self._current_model_size = None
 
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
+            empty_device_cache(self.device)
 
             logger.info("TTS model unloaded")
 
@@ -213,9 +225,7 @@ class PyTorchTTSBackend:
             """Run synchronous generation in thread pool."""
             # Set seed if provided
             if seed is not None:
-                torch.manual_seed(seed)
-                if torch.cuda.is_available():
-                    torch.cuda.manual_seed(seed)
+                manual_seed(seed, self.device)
 
             # Generate audio - this is the blocking operation
             wavs, sample_rate = self.model.generate_voice_clone(
@@ -282,8 +292,9 @@ 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)
 
-            self.processor = WhisperProcessor.from_pretrained(model_name)
-            self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
+            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.model.to(self.device)
         self.model_size = model_size
@@ -297,8 +308,7 @@ class PyTorchSTTBackend:
             self.model = None
             self.processor = None
 
-            if torch.cuda.is_available():
-                torch.cuda.empty_cache()
+            empty_device_cache(self.device)
 
             logger.info("Whisper model unloaded")
 

backend/build_binary.py

@@ -52,6 +52,16 @@ 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():

backend/models.py

@@ -182,6 +182,7 @@ 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):

backend/pyi_rth_numpy_compat.py

@@ -0,0 +1,95 @@
+"""
+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()

backend/requirements.txt

@@ -8,7 +8,7 @@ sqlalchemy>=2.0.0
 alembic>=1.13.0
 
 # ML models
-torch>=2.7.0
+torch>=2.2.0
 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
+numpy>=1.24.0,<2.0
 numba>=0.60.0,<0.61.0
 pedalboard>=0.9.0
 

backend/routes/health.py

@@ -93,6 +93,12 @@ 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
@@ -110,6 +116,11 @@ 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
@@ -162,7 +173,11 @@ 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 "cpu"),
+        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/routes/history.py

@@ -62,6 +62,13 @@ 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,
@@ -89,6 +96,11 @@ 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,
     )
 

backend/routes/profiles.py

@@ -4,6 +4,7 @@ import io
 import json as _json
 import logging
 import tempfile
+from datetime import datetime
 from pathlib import Path
 
 from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile

backend/server.py

@@ -105,6 +105,11 @@ 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
@@ -164,6 +169,19 @@ 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")
@@ -178,6 +196,18 @@ 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

backend/services/cuda.py

@@ -11,6 +11,7 @@ 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
@@ -34,6 +35,12 @@ 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."""
@@ -241,6 +248,15 @@ 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:

backend/services/effects.py

@@ -11,6 +11,8 @@ 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
 
@@ -52,7 +54,6 @@ 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)
@@ -94,7 +95,6 @@ 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)

backend/services/history.py

@@ -264,6 +264,43 @@ 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,

backend/services/stories.py

@@ -484,13 +484,15 @@ async def split_story_item(
     Returns:
         List of two updated item details (original and new) or None if not found/invalid
     """
-    # Get the item
+    # Get the item with a row lock to prevent concurrent splits on the
+    # same clip (e.g. from rapid double-clicks racing each other).
     item = (
         db.query(DBStoryItem)
         .filter_by(
             id=item_id,
             story_id=story_id,
         )
+        .with_for_update()
         .first()
     )
     if not item:

backend/utils/cache.py

@@ -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)
+            prompt = torch.load(cache_file, weights_only=True)
             _memory_cache[cache_key] = prompt
             return prompt
         except Exception:

backend/utils/hf_offline_patch.py

@@ -1,17 +1,64 @@
 """Monkey-patch huggingface_hub to force offline mode with cached models.
 
-Prevents mlx_audio from making network requests when models are already
-downloaded. Must be imported BEFORE mlx_audio.
+Prevents mlx_audio / transformers 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:

docker-compose.yml

@@ -22,6 +22,7 @@ services:
 
     environment:
       - LOG_LEVEL=info
+      - NUMBA_CACHE_DIR=/tmp/numba_cache
 
     networks:
       - voicebox-net

docs/app/global.css

@@ -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%);

docs/app/og/docs/[...slug]/route.tsx

@@ -5,22 +5,13 @@ 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,

docs/content/docs/index.mdx

@@ -31,6 +31,6 @@ Voicebox is a **local-first voice cloning studio** -- a free and open-source alt
 
 ## Get Started
 
-- [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
+- [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

docs/source.config.ts

@@ -1,9 +1,4 @@
-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

docs/tsconfig.json

@@ -2,11 +2,7 @@
   "compilerOptions": {
     "baseUrl": ".",
     "target": "ESNext",
-    "lib": [
-      "dom",
-      "dom.iterable",
-      "esnext"
-    ],
+    "lib": ["dom", "dom.iterable", "esnext"],
     "allowJs": true,
     "skipLibCheck": true,
     "strict": true,
@@ -20,12 +16,8 @@
     "jsx": "react-jsx",
     "incremental": true,
     "paths": {
-      "@/*": [
-        "./*"
-      ],
-      "@/.source": [
-        ".source"
-      ]
+      "@/*": ["./*"],
+      "@/.source": [".source"]
     },
     "plugins": [
       {
@@ -40,7 +32,5 @@
     ".next/types/**/*.ts",
     ".next/dev/types/**/*.ts"
   ],
-  "exclude": [
-    "node_modules"
-  ]
+  "exclude": ["node_modules"]
 }

justfile

@@ -69,10 +69,22 @@ setup-python:
     }
     Write-Host "Installing Python dependencies..."
     & "{{ python }}" -m pip install --upgrade pip -q
-    $hasNvidia = $null -ne (Get-WmiObject Win32_VideoController | Where-Object { $_.Name -match 'NVIDIA' })
+    $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 { $_ -match 'Arc' }).Count -gt 0
     if ($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

landing/package.json

@@ -1,6 +1,6 @@
 {
   "name": "@voicebox/landing",
-  "version": "0.3.1",
+  "version": "0.4.0",
   "description": "Landing page for voicebox.sh",
   "scripts": {
     "dev": "bun --bun next dev --turbo",

package.json

@@ -1,6 +1,6 @@
 {
   "name": "voicebox",
-  "version": "0.3.1",
+  "version": "0.4.0",
   "private": true,
   "workspaces": [
     "app",

tauri/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@voicebox/tauri",
   "private": true,
-  "version": "0.3.1",
+  "version": "0.4.0",
   "type": "module",
   "scripts": {
     "dev": "vite",

tauri/src-tauri/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "voicebox"
-version = "0.3.1"
+version = "0.4.0"
 description = "A production-quality desktop app for Qwen3-TTS voice cloning and generation"
 authors = ["you"]
 license = ""

tauri/src-tauri/build.rs

@@ -5,6 +5,10 @@ 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");

tauri/src-tauri/src/audio_capture/macos.rs

@@ -13,6 +13,7 @@ use screencapturekit::{
     },
 };
 use std::io::Cursor;
+use std::process::Command;
 use std::sync::{Arc, Mutex};
 use tokio::sync::mpsc;
 
@@ -20,6 +21,10 @@ 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();
 
@@ -144,17 +149,22 @@ pub async fn stop_capture(state: &AudioCaptureState) -> Result<String, String> {
 }
 
 pub fn is_supported() -> bool {
-    // 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
-    }
+    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)
 }
 
 fn extract_audio_samples(sample_buffer: CMSampleBuffer) -> Result<Vec<f32>, String> {

tauri/src-tauri/src/audio_output.rs

@@ -401,9 +401,25 @@ 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(())
     }

tauri/src-tauri/src/main.rs

@@ -860,6 +860,22 @@ 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()

tauri/src-tauri/tauri.conf.json

@@ -1,7 +1,7 @@
 {
   "$schema": "https://schema.tauri.app/config/2",
   "productName": "Voicebox",
-  "version": "0.3.1",
+  "version": "0.4.0",
   "identifier": "sh.voicebox.app",
   "build": {
     "beforeDevCommand": "bun run dev",

tauri/src/platform/audio.ts

@@ -2,9 +2,8 @@ import { invoke } from '@tauri-apps/api/core';
 import type { PlatformAudio, AudioDevice } from '@/platform/types';
 
 export const tauriAudio: PlatformAudio = {
-  isSystemAudioSupported(): boolean {
-    // This will be checked dynamically via invoke
-    return true; // Tauri supports it, but actual support depends on platform
+  async isSystemAudioSupported(): Promise<boolean> {
+    return await invoke<boolean>('is_system_audio_supported');
   },
 
   async startSystemAudioCapture(maxDurationSecs: number): Promise<void> {

web/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@voicebox/web",
   "private": true,
-  "version": "0.3.1",
+  "version": "0.4.0",
   "type": "module",
   "scripts": {
     "dev": "vite",

web/src/platform/audio.ts

@@ -1,7 +1,7 @@
 import type { PlatformAudio, AudioDevice } from '@/platform/types';
 
 export const webAudio: PlatformAudio = {
-  isSystemAudioSupported(): boolean {
+  async isSystemAudioSupported(): Promise<boolean> {
     return false; // System audio capture not supported in web
   },