fix: cross-platform backend log path + Windows startup hardening (#31)

Three fixes for the Windows MSI first-launch failure:

1. **backend_log_path() was macOS-only** — used $HOME + Library/Logs
   which doesn't exist on Windows. Now uses %LOCALAPPDATA% on Windows,
   ~/Library/Logs on macOS, and XDG_STATE_HOME on Linux. Without this,
   stdout/stderr went to Stdio::null() and all backend crash output was
   silently lost.

2. **Add TORCHDYNAMO_DISABLE=1 on Windows** — prevents PyTorch from
   trying to download Triton (which has no Windows support), avoiding a
   hang during first torch.compile() call (#26 workaround).

3. **Increase health timeout from 180s to 300s** — first-run PyTorch
   import on Windows can take 120+ seconds for CUDA kernel JIT, plus
   uv sync + torch + model loading. 3 min wasn't enough.

Fixes #30

.github/workflows/ci.yml

@@ -30,8 +30,13 @@ jobs:
         with:
           python-version: "3.11"
 
+      # enable-cache persists ~/.cache/uv across runs, keyed on uv.lock —
+      # turns `uv sync` from ~45 s cold to ~5 s warm.
       - name: Install uv
         uses: astral-sh/setup-uv@v3
+        with:
+          enable-cache: true
+          cache-dependency-glob: "uv.lock"
 
       # Node 22 is needed for --experimental-strip-types so node:test can
       # import .ts files directly from frontend/src/api/*.
@@ -43,10 +48,12 @@ jobs:
       - name: Setup Bun
         uses: oven-sh/setup-bun@v1
 
+      # apt install ffmpeg is ~30 s every run; cache the resolved .debs.
       - name: System deps (ffmpeg)
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y ffmpeg
+        uses: awalsh128/cache-apt-pkgs-action@latest
+        with:
+          packages: ffmpeg
+          version: 1.0
 
       - name: Install Python deps
         run: uv sync
@@ -54,6 +61,16 @@ jobs:
       - name: Run pytest
         run: uv run pytest tests/ -q --tb=short
 
+      # Cache ~/.bun/install/cache keyed on bun.lock — `bun install` drops
+      # from ~15 s cold to near-instant on warm cache.
+      - name: Cache bun deps
+        uses: actions/cache@v4
+        with:
+          path: ~/.bun/install/cache
+          key: ${{ runner.os }}-bun-${{ hashFiles('frontend/bun.lock', 'bun.lock') }}
+          restore-keys: |
+            ${{ runner.os }}-bun-
+
       - name: Install frontend deps
         working-directory: frontend
         run: bun install

.github/workflows/release.yml

@@ -50,8 +50,12 @@ jobs:
         with:
           python-version: "3.11"
 
+      # enable-cache persists ~/.cache/uv keyed on uv.lock.
       - name: Install uv
         uses: astral-sh/setup-uv@v3
+        with:
+          enable-cache: true
+          cache-dependency-glob: "uv.lock"
 
       # Node 22 is needed for --experimental-strip-types so node:test can
       # import .ts files directly from frontend/src/api/*.
@@ -63,13 +67,13 @@ jobs:
       - name: Setup Bun
         uses: oven-sh/setup-bun@v1
 
-      # Backend tests need ffmpeg (subprocess calls in fixtures) + the minimal
-      # apt deps pydub/imageio pull in. Model weights are mocked so no HF
-      # downloads happen.
+      # Backend tests need ffmpeg (subprocess calls in fixtures). Cache the
+      # resolved .debs so warm runs skip the apt-get update + install.
       - name: System deps (ffmpeg)
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y ffmpeg
+        uses: awalsh128/cache-apt-pkgs-action@latest
+        with:
+          packages: ffmpeg
+          version: 1.0
 
       - name: Install Python deps
         run: uv sync
@@ -77,6 +81,14 @@ jobs:
       - name: Run pytest
         run: uv run pytest tests/ -q --tb=short
 
+      - name: Cache bun deps
+        uses: actions/cache@v4
+        with:
+          path: ~/.bun/install/cache
+          key: ${{ runner.os }}-bun-${{ hashFiles('frontend/bun.lock', 'bun.lock') }}
+          restore-keys: |
+            ${{ runner.os }}-bun-
+
       - name: Install frontend deps
         working-directory: frontend
         run: bun install
@@ -104,12 +116,9 @@ jobs:
             rust_target: aarch64-apple-darwin
             bundles: "app,dmg,updater"
 
-          - os: macos-13
-            arch: x86_64-apple-darwin
-            label: "macOS Intel"
-            rust_target: x86_64-apple-darwin
-            bundles: "app,dmg,updater"
-
+          # macOS Intel dropped: Apple shipped the last Intel Mac in 2023 and
+          # Rosetta 2 runs the ARM build natively. macos-13 runner backlog
+          # was also blocking every release tag for ~10 min.
           # Windows: force MSI bundling via --bundles. NSIS fails at makensis
           # because our PyInstaller payload approaches its ~2 GB stub limit.
           - os: windows-2022
@@ -118,13 +127,16 @@ jobs:
             rust_target: x86_64-pc-windows-msvc
             bundles: "msi,updater"
 
-          # Linux: ship .deb only. AppImage bundling (linuxdeploy) is
-          # unreliable on GH Actions runners even with APPIMAGE_EXTRACT_AND_RUN.
+          # Linux: ship .deb + .AppImage. AppImage is universal (no distro
+          # package-manager dep), runs on any glibc-2.31+ host. Now viable
+          # because the thin uv-venv installer is ~10 MB (vs the prior ~2 GB
+          # PyInstaller payload that exceeded linuxdeploy limits). FUSE
+          # unavailability on GH runners handled via APPIMAGE_EXTRACT_AND_RUN=1.
           - os: ubuntu-22.04
             arch: x86_64-unknown-linux-gnu
             label: "Linux x64"
             rust_target: x86_64-unknown-linux-gnu
-            bundles: "deb,updater"
+            bundles: "deb,appimage,updater"
 
     runs-on: ${{ matrix.os }}
     name: ${{ matrix.label }}
@@ -138,6 +150,15 @@ jobs:
         with:
           targets: ${{ matrix.rust_target }}
 
+      # Cache ~/.cargo/registry + {target}/ per rust_target. Cargo dep
+      # compile is the long pole of the build — cold is ~5-7 min, warm
+      # drops to ~1-2 min.
+      - name: Rust cache
+        uses: Swatinem/rust-cache@v2
+        with:
+          workspaces: frontend/src-tauri -> target
+          key: ${{ matrix.rust_target }}
+
       - name: Setup Bun
         uses: oven-sh/setup-bun@v1
 
@@ -161,6 +182,14 @@ jobs:
             libasound2-dev ffmpeg
 
       # ── Frontend build ─────────────────────────────────────────────────
+      - name: Cache bun deps
+        uses: actions/cache@v4
+        with:
+          path: ~/.bun/install/cache
+          key: ${{ runner.os }}-bun-${{ hashFiles('frontend/bun.lock', 'bun.lock') }}
+          restore-keys: |
+            ${{ runner.os }}-bun-
+
       - name: Install frontend deps
         working-directory: frontend
         run: bun install
@@ -178,6 +207,10 @@ jobs:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
           TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
           TAURI_SIGNING_PRIVATE_KEY_PASSWORD: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY_PASSWORD }}
+          # GH runners disable FUSE, so linuxdeploy's AppImage can't mount
+          # itself at bundle time. This env tells linuxdeploy to extract-and-run
+          # instead, which works without FUSE.
+          APPIMAGE_EXTRACT_AND_RUN: 1
         with:
           projectPath: frontend
           args: --target ${{ matrix.rust_target }} --bundles ${{ matrix.bundles }}

.gitignore

@@ -77,3 +77,7 @@ examples/download*
 examples/exp*/
 omnivoice.zip
 frontend/src-tauri/binaries/ffmpeg
+
+# cuDNN 8 compat libs (auto-installed by scripts/setup_cudnn.py)
+cudnn8_compat/
+test-results/

Dockerfile

@@ -2,19 +2,18 @@
 # Builder Stage: Compile React Frontend
 # ==========================================
 FROM oven/bun:1-alpine AS frontend-builder
-WORKDIR /app/frontend
+WORKDIR /app
 
-# Copy frontend specifications
-COPY frontend/package.json ./
-COPY frontend/bun.lock ./
+# Monorepo — bun workspace with lockfile at repo root. Copy manifests first
+# so `bun install` caches independently of source edits.
+COPY package.json bun.lock ./
+COPY frontend/package.json ./frontend/
 
-# Install dependencies fast
 RUN bun install --frozen-lockfile
 
-# Copy frontend source and build static files
-COPY frontend/ ./
-# Output goes to /app/frontend/dist
-RUN bun run build
+# Build static files (output lands in /app/frontend/dist)
+COPY frontend/ ./frontend/
+RUN bun run --cwd frontend build
 
 # ==========================================
 # Runtime Stage: Python & PyTorch Backend
@@ -52,10 +51,10 @@ COPY omnivoice/ ./omnivoice/
 COPY --from=frontend-builder /app/frontend/dist ./frontend/dist
 
 # Expose the single unified API and UI port
-EXPOSE 8000
+EXPOSE 3900
 
 # Mount points for persistent data (sqlite db, user voices, huggingface cache)
 VOLUME ["/app/omnivoice_data"]
 
 # Bind to 0.0.0.0 for external access
-ENTRYPOINT ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "8000"]
+ENTRYPOINT ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "3900"]

LICENSE

@@ -1,201 +1,82 @@
-                                 Apache License
-                           Version 2.0, January 2004
-                        http://www.apache.org/licenses/
+OmniVoice Studio — Dual License
 
-   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+Copyright (c) 2024-present Palash Debnath and contributors.
 
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-      "License" shall mean the terms and conditions for use, reproduction,
-      and distribution as defined by Sections 1 through 9 of this document.
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-      "Licensor" shall mean the copyright owner or entity authorized by
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-      "Legal Entity" shall mean the union of the acting entity and all
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README.md

@@ -1,164 +1,343 @@
 <div align="center">
-  <img src="frontend/public/favicon.svg" alt="OmniVoice Logo" width="120" />
+  <img src="docs/logo.png" alt="OmniVoice Logo" width="160" />
   <h1>OmniVoice Studio</h1>
-  <p><b>Your Local Cinematic AI Dubbing Studio</b></p>
+  <p><b>The open-source ElevenLabs alternative.</b></p>
+  <p>Voice cloning · Voice design · Video dubbing — 646 languages, runs 100% locally, forever free.</p>
   <p>
-    <a href="#-features">Features</a> •
-    <a href="#-getting-started">Getting Started</a> •
-    <a href="#%EF%B8%8F-roadmap">Roadmap</a> •
-    <a href="#-changelog">Changelog</a>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/stargazers"><img src="https://img.shields.io/github/stars/debpalash/OmniVoice-Studio?style=flat-square&color=f59e0b" alt="Stars" /></a>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/releases/latest"><img src="https://img.shields.io/github/v/release/debpalash/OmniVoice-Studio?style=flat-square&color=10b981" alt="Release" /></a>
+    <a href="LICENSE"><img src="https://img.shields.io/badge/license-Dual_(Free_%2B_Commercial)-blue?style=flat-square" alt="License" /></a>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/issues"><img src="https://img.shields.io/github/issues/debpalash/OmniVoice-Studio?style=flat-square&color=ef4444" alt="Issues" /></a>
+    <a href="https://discord.gg/aRRdVj3de7"><img src="https://img.shields.io/badge/Discord-Join_Community-5865F2?style=flat-square&logo=discord&logoColor=white" alt="Discord" /></a>
+  </p>
+  <p>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/releases/latest">Download</a> ·
+    <a href="#features">Features</a> ·
+    <a href="#quickstart">Quickstart</a> ·
+    <a href="#why-open-source">Why Open Source?</a> ·
+    <a href="#roadmap">Roadmap</a>
+  </p>
+  <p>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/releases/download/v0.2.2/OmniVoice.Studio_0.2.2_aarch64.dmg"><img src="https://img.shields.io/badge/macOS-DMG_(Apple_Silicon)-000?style=for-the-badge&logo=apple&logoColor=white" alt="Download macOS DMG" /></a>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/releases/download/v0.2.2/OmniVoice.Studio_0.2.2_x64_en-US.msi"><img src="https://img.shields.io/badge/Windows-MSI_(x64)-0078D4?style=for-the-badge&logo=windows&logoColor=white" alt="Download Windows MSI" /></a>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/releases/download/v0.2.2/OmniVoice.Studio_0.2.2_amd64.AppImage"><img src="https://img.shields.io/badge/Linux-AppImage_(x64)-FCC624?style=for-the-badge&logo=linux&logoColor=black" alt="Download Linux AppImage" /></a>
+    <a href="https://github.com/debpalash/OmniVoice-Studio/releases/download/v0.2.2/OmniVoice.Studio_0.2.2_amd64.deb"><img src="https://img.shields.io/badge/Debian-.deb-A81D33?style=for-the-badge&logo=debian&logoColor=white" alt="Download Debian .deb" /></a>
   </p>
 </div>
 
 <br/>
 
 <div align="center">
-  <img src="preview.png" alt="OmniVoice Studio Interface Demo" width="100%"/>
+  <img src="preview.png" alt="OmniVoice Studio — Launchpad" width="100%"/>
   <br/>
-  <i>The timeline-based cinematic dubbing and workspace UI.</i>
+  <sub>Launchpad — Voice Clone · Voice Design · Video Dubbing, all in one place.</sub>
 </div>
 
----
-
-Local, full-stack voice generation and cinematic dubbing. **No API keys. No cloud. Just run it.** Built on the open-source [OmniVoice](https://github.com/k2-fsa/OmniVoice) 600-language zero-shot diffusion model.
-
-## ✨ Features
-
-- 🎬 **Video Dubbing** — transcribe, translate, re-voice, and mux back into MP4 with selective track export.
-- 🎧 **Vocal Isolation** — built-in `demucs` automatically splits speech from music, keeping original background audio perfectly preserved.
-- 🧬 **Voice Cloning & Design** — Clone specific voices from just a 3-second audio clip, or design completely new studio profiles with tags like `female, british accent, excited`.
-- ⚡ **Cross-Platform Native Execution** — Auto-detects and accelerates inference using Apple Silicon (MPS), NVIDIA (CUDA), AMD (ROCm), or standard CPU.
-- 🔊 **Per-Segment Mixing** — Fine-grained volume/gain control per dubbed segment (0–200%) for broadcast-quality audio balancing.
-- ⌨️ **Keyboard-Driven Workflow** — `⌘+Enter` to generate, `⌘+S` to save, `⌘+Z`/`⌘+Shift+Z` for undo/redo.
-- 📡 **Live Model Telemetry** — Real-time CPU/RAM/VRAM stats + model warm-up indicator (idle → loading → ready).
-
 <br/>
 
+<table>
+  <tr>
+    <td align="center" width="50%">
+      <img src="docs/screenshot-clone.png" alt="Voice Clone" width="100%"/>
+      <br/><b>Voice Clone</b><br/>
+      <sub>Drop a 3-second clip → mirror any voice. 646 languages, zero-shot.</sub>
+    </td>
+    <td align="center" width="50%">
+      <img src="docs/screenshot-design.png" alt="Voice Design" width="100%"/>
+      <br/><b>Voice Design</b><br/>
+      <sub>Build new voices from scratch — gender, age, accent, pitch, style.</sub>
+    </td>
+  </tr>
+  <tr>
+    <td align="center">
+      <img src="docs/screenshot-dub.png" alt="Video Dubbing" width="100%"/>
+      <br/><b>Video Dubbing</b><br/>
+      <sub>Upload or paste a YouTube URL. Transcribe, translate, re-voice, export.</sub>
+    </td>
+    <td align="center">
+      <img src="docs/screenshot-gallery.png" alt="Voice Gallery" width="100%"/>
+      <br/><b>Voice Gallery</b><br/>
+      <sub>Search YouTube, browse categories, download clips, build your library.</sub>
+    </td>
+  </tr>
+  <tr>
+    <td align="center">
+      <img src="docs/screenshot-settings.png" alt="Settings — Models" width="100%"/>
+      <br/><b>Settings → Models</b><br/>
+      <sub>15 models. One-click install. Auto-detects your platform (CUDA / MPS / CPU).</sub>
+    </td>
+    <td align="center">
+      <img src="docs/screenshot-libraryprojects.png" alt="Projects" width="100%"/>
+      <br/><b>Projects</b><br/>
+      <sub>Dub projects, voice profiles, generation history, exports — all searchable.</sub>
+    </td>
+  </tr>
+  <tr>
+    <td align="center" colspan="2">
+      <img src="docs/screenshot-logs.png" alt="Settings — Logs" width="100%"/>
+      <br/><b>Settings → Logs</b><br/>
+      <sub>Live backend, frontend, and Tauri runtime logs. Filter, refresh, clear.</sub>
+    </td>
+  </tr>
+</table>
 
-## 🚀 Getting Started
+---
 
-The easiest way to run OmniVoice Studio locally or on a cloud VM is via Docker. Our environment utilizes an optimized `pytorch/pytorch` configuration which seamlessly enables zero-config GPU passthrough if your host supports it.
+## Why Open Source?
 
-### Option 1: One-Click Docker (Recommended)
+ElevenLabs charges **$5–$330/mo** and processes your audio on their servers. OmniVoice Studio runs **on your hardware, with no usage limits.**
+
+| | **ElevenLabs** | **OmniVoice Studio** |
+|---|---|---|
+| **Pricing** | $5–$330/mo, per-character billing | Free for personal use · [Commercial license](#license) for business |
+| **Voice Cloning** | ✅ 3s clip | ✅ 3s clip, zero-shot |
+| **Voice Design** | ✅ Gender, age | ✅ Gender, age, accent, pitch, style, dialect |
+| **Languages** | 32 | **646** |
+| **Video Dubbing** | ✅ Cloud-only | ✅ Fully local |
+| **Data Privacy** | Audio sent to cloud | **Nothing leaves your machine** |
+| **API Keys** | Required | Not needed |
+| **GPU Support** | N/A (cloud) | CUDA · Apple Silicon · ROCm · CPU |
+| **Desktop App** | ❌ | ✅ macOS · Windows · Linux |
+| **Customizable** | ❌ Closed | ✅ Fork it, extend it, ship it |
+
+Built on the [OmniVoice](https://github.com/k2-fsa/OmniVoice) 600-language zero-shot diffusion TTS model. Upload a video, get broadcast-quality dubs in any language with the original speaker's voice preserved.
+
+## Features
+
+### Core Pipeline
+- **Video Dubbing** — Transcribe → translate → synthesize → mux back to MP4. One-click end-to-end.
+- **Vocal Isolation** — Demucs-powered speech/music separation. Background audio preserved automatically.
+- **Voice Cloning** — Clone any voice from a 3-second clip. Zero-shot, 600+ languages.
+- **Multi-Speaker Diarization** — Pyannote + WhisperX fusion auto-identifies speakers and assigns unique voice profiles.
+
+### Studio Tools
+- **Voice Preview** — Floating widget for instant 8-step TTS testing. Try voices without leaving the workspace.
+- **Multi-Language Batch** — Select multiple target languages, dub to all in one pass.
+- **Batch Queue** — Drag-and-drop bulk video processing with sequential GPU execution.
+- **Voice Library** — Browse, favorite, tag, and convert gallery clips into permanent voice profiles.
+- **A/B Comparison** — Side-by-side voice audition for casting decisions.
+
+### Production Export
+- **Selective Track Export** — Choose which language tracks to include in the final MP4.
+- **Subtitle Export** — SRT and VTT generation alongside dubbed video.
+- **Stem Export** — Separate vocals and background audio as individual files.
+- **Per-Segment Mixing** — 0–200% gain control per segment for broadcast-quality balancing.
+
+### Technical
+- **Cross-Platform GPU** — Auto-detects CUDA, Apple Silicon (MPS), ROCm, or CPU. Includes automatic cuDNN 8/9 compatibility handling.
+- **VRAM-Aware** — Automatically offloads TTS to CPU during transcription on ≤8 GB GPUs. Zero config.
+- **Live Telemetry** — Real-time CPU/RAM/VRAM stats with model warm-up indicator.
+- **Keyboard-First** — `⌘+Enter` generate, `⌘+S` save, `⌘+Z`/`⌘+⇧+Z` undo/redo.
+
+### AI Provenance
+- **Invisible Watermark** — AudioSeal-powered (Meta) neural watermark embedded in every generated audio. Imperceptible, survives compression/editing.
+- **Detection API** — Upload any audio to `/watermark/detect` to verify OmniVoice origin with confidence score.
+- **Video Branding** — Optional logo overlay on exported MP4s (5s fade-out, bottom-right).
+- **Configurable** — Toggle invisible/visible watermarks independently in Settings → Privacy.
+
+---
+
+## Quickstart
+
+### Docker (recommended)
 
 ```bash
 git clone https://github.com/debpalash/OmniVoice-Studio.git
 cd OmniVoice-Studio
-
 docker compose up --build -d
 ```
-That's it! Open [http://localhost:8000](http://localhost:8000) in your browser.
 
-> [!TIP]
-> **Windows/WSL Users:** Make sure your NVIDIA drivers are up to date. Docker Desktop automatically passes GPU capabilities to this container!
-> **Cloud VMs (AWS, RunPod):** The image inherently supports CUDA 12.1. As long as `nvidia-container-toolkit` is installed on your host, `--gpus all` binds natively.
+Open [http://localhost:8000](http://localhost:8000). GPU passthrough works automatically if `nvidia-container-toolkit` is installed.
 
-### Option 2: Local Development Setup
+### Local Development
 
-Quickly get OmniVoice Studio running natively on your hardware if you want to develop or modify code.
-**Prerequisites:** Ensure `ffmpeg` is installed on your system.
-Install standard modern web tooling: [Bun](https://bun.sh/) and [uv](https://docs.astral.sh/uv/getting-started/installation/).
+**Prerequisites:** [ffmpeg](https://ffmpeg.org/), [Bun](https://bun.sh/), [uv](https://docs.astral.sh/uv/)
 
 ```bash
 git clone https://github.com/debpalash/OmniVoice-Studio.git
 cd OmniVoice-Studio
-
-# Boot the Backend
-uv sync
-uv run uvicorn backend.main:app
-
-# Boot the Frontend (in a separate terminal)
 bun install
 bun run dev
 ```
 
-OmniVoice Studio launches exactly two micro-services:
+This boots both services:
 
-| Service | Protocol | Details |
-|---|---|---|
-| **Frontend** | `http://localhost:5173` | The real-time React UI — spanning cloning, design, and audio workspace. |
-| **Backend** | `http://localhost:8000` | The FastAPI server handling model inference, translation pipelines, transcriber tasks. |
+| Service | URL | Stack |
+|---------|-----|-------|
+| **Backend** | `localhost:3900` | FastAPI · 97 endpoints · WhisperX · Demucs · OmniVoice |
+| **Frontend** | `localhost:3901` | React · Vite · Waveform timeline · Glassmorphism UI |
 
 > [!NOTE]
-> **First run optimization:** Model weights (approx. 1.2 GB) automatically download from HuggingFace the first time you execute a generation sequence. Subsequent launches trigger instantly from cache. *(Tip: Set `HF_TOKEN` in your environment for faster, authenticated downloads!)*
+> First run downloads model weights (~2.4 GB). This works out of the box — no account needed. For faster downloads, optionally set `HF_TOKEN=hf_...` in your environment ([get a free token here](https://huggingface.co/settings/tokens)).
+>
+> **Having issues?** Join our [Discord](https://discord.gg/aRRdVj3de7) for setup help and troubleshooting.
+
+### Desktop App
+
+```bash
+bun run desktop    # Launches Tauri native app (macOS / Windows / Linux)
+```
 
 ---
 
-## 🗺️ Roadmap
+## System Requirements
 
-The studio is highly functional today, but we are aggressively expanding. Watch the roadmap to see what's shipping next:
+| | **Minimum** | **Recommended** |
+|---|---|---|
+| **OS** | Windows 10, macOS 12+, Ubuntu 20.04+ | Any modern 64-bit OS |
+| **RAM** | 8 GB | 16 GB+ |
+| **VRAM (GPU)** | 4 GB (auto-offloads TTS to CPU) | 8 GB+ (NVIDIA RTX 3060+) |
+| **Disk** | 10 GB free (models + cache) | 20 GB+ SSD |
+| **Python** | 3.10+ (managed by `uv`) | 3.11–3.12 |
+| **GPU** | Optional — CPU works | NVIDIA CUDA · Apple Silicon MPS · AMD ROCm |
 
-### 🌟 Completed Milestones
-- [x] Zero-shot voice cloning & complex voice design.
-- [x] Full video cinematic dubbing pipeline (transcribe → translate → synthesize → mux).
-- [x] Vocal isolation utilizing demucs alongside background audio retention.
-- [x] Embedded waveform timeline editor for micro-segment-level audio manipulation.
-- [x] Live system telemetry tracking (CPU, RAM, GPU VRAM usage).
-- [x] Targeted multi-speaker diarization — auto-assign unique voice profiles per active speaker.
-- [x] Studio project persistence — save, load, and cache multi-track projects seamlessly via local SQLite.
-- [x] Production SRT/VTT subtitle export packaged alongside the dubbed `.mp4` video output.
-- [x] Selective track export — choose exactly which language tracks (Original, DE, ES, etc.) to include in final MP4.
-- [x] Per-segment volume/gain control with real-time mixing (0–200%).
-- [x] Undo/redo system for all segment edits with 50-action history depth.
-- [x] Keyboard shortcuts: `⌘+Enter` generate, `⌘+S` save, `⌘+Z`/`⌘+Shift+Z` undo/redo.
-- [x] Drag-and-drop file uploads for both video and clone audio sources.
-- [x] Model warm-up indicator with live status pill (idle/loading/ready).
-- [x] Confirmation dialogs for all destructive actions (delete project/history/profile).
-- [x] UI preferences persistence (sidebar state, zoom, active tab) across sessions.
-- [x] Polished glassmorphism design system with micro-animations, focus rings, and custom scrollbars.
-
-### 🔨 Upcoming Features
-- [x] **Real Speaker Diarization** — ML-based diarization via pyannote.audio for true multi-speaker identification.
-- [x] **A/B Voice Comparison** — Side-by-side voice audition for casting decisions.
-- [x] **Scene-Aware Dubbing** — FFmpeg scene detection to auto-split segments at visual cuts.
-- [x] **Lip-Sync Scoring** — Analyze dubbed audio duration against original speaker timing with color-coded badges.
-- [x] **Batch Processing** — Centralized async task queue ensuring sequential GPU execution with reconnectable SSE streams.
-- [x] **Advanced Export Suite** — VTT subtitles, per-segment WAV ZIP, compressed MP3, and stem export (vocals + background separate).
-- [x] **Streaming TTS** — Chunked WAV streaming with progressive download and auto-playback.
-- [ ] **Native Desktop Applications** — Dedicated client apps for macOS, Windows, and Linux.
-- [x] **One-Click Deployment** — Docker image packages engineered for zero-config GPU passthrough.
+> [!TIP]
+> On GPUs with **≤8 GB VRAM**, OmniVoice automatically offloads TTS to CPU during transcription — no config needed. A dedicated GPU is not required; the entire pipeline runs on CPU (just slower).
 
 ---
 
-## 📝 Changelog
+## Architecture
 
-### v1.2.0 — The Production Polish Update
+```
+┌─────────────────────────────────────────────────┐
+│                  Frontend (React)                │
+│  DubTab · VoicePreview · BatchQueue · Gallery    │
+├─────────────────────────────────────────────────┤
+│                Backend (FastAPI)                  │
+│  97 API endpoints · SSE streaming · SQLite       │
+├──────────┬──────────┬──────────┬────────────────┤
+│ WhisperX │  Demucs  │OmniVoice │   Pyannote     │
+│   ASR    │  Source  │   TTS    │  Diarization   │
+│          │  Sep.    │          │                │
+└──────────┴──────────┴──────────┴────────────────┘
+        CUDA / MPS / ROCm / CPU (auto-detected)
+```
 
-- **Selective Track Export:** Choose exactly which audio tracks to include in the final MP4. Uncheck Original, keep only German — get a single-track export. Full per-track checkbox UI with dynamic FFmpeg stream index remapping.
-- **Undo/Redo System:** Full `⌘+Z` / `⌘+Shift+Z` undo/redo for all segment edits (text, voice, volume, delete). 50-action deep history stack.
-- **Per-Segment Volume Control:** Inline gain slider (0–200%) per segment row in the dub table. Backend applies gain during audio assembly with safe clamping.
-- **Keyboard Shortcuts:** `⌘+Enter` to generate, `⌘+S` to save project. Browser default overrides prevented.
-- **Model Status Indicator:** Live status pill in the header showing model warm-up state (idle → loading → ready). New `/model/status` backend endpoint.
-- **Drag-and-Drop Everywhere:** Video upload already supported drop — now clone audio upload does too, with pink highlight on hover.
-- **Confirmation Dialogs:** All destructive actions (delete project, profile, history item, clear all history) now require confirmation.
-- **Session Persistence:** Sidebar collapsed state, active tab, and zoom level now persist across browser sessions via localStorage.
-- **CSS Design System Overhaul:** Anti-aliased text, input focus glow rings, button hover shimmer, progress bar shimmer animation, fade-in on history items, selection color branding, Firefox scrollbar support, `tabular-nums` for timestamp columns.
-- **AudioContext Pooling:** `playPing()` synthesis notification reuses a single AudioContext instead of creating one per call (browsers cap at ~6).
+---
 
-### v1.1.0 — The Cinematic Studio Update
+## Roadmap
 
-- **The Cinematic Studio Interface:** Exhaustively re-engineered the UI to prioritize a high-density, real-estate optimized workflow featuring a dynamic UI zoom scalar (`Small`, `Normal`, `Max`). We minimized dead space and overhauled the widget layout keeping crucial tuning metrics immediately accessible.
-- **Multi-Track Timeline:** Deeply integrated a multi-layered waveform sequence interface supporting precision audio segment positioning, unmuted live preview playback, localized track timing, and unconstrained draggable positioning manipulation.
-- **Persistent Local Projects:** Put a complete stop to ephemeral state loss. All workspace metrics are successfully wrapped into `Projects` logged directly within a native embedded `SQLite` database. Workflows reliably survive browser shutdowns or server API reboots.
-- **AI Cast Diarization:** Dropped in an offline `Pyannote` + `WhisperX` fusion pipeline evaluating multi-speaker metadata and categorizing overlapping, distinct speakers. Rapidly "cast" clone overrides seamlessly over complex dialogue tracks.
-- **Polishing & Asset Control:** Cleaned cross-stack filename parsing and exported media rendering via `ffmpeg`, stabilizing codec dependencies, and deployed a unified custom `OmniVoice Studio` scalable aesthetic asset system.
+### ✅ Shipped
 
+| Category | Features |
+|----------|----------|
+| **Dubbing** | Full pipeline (transcribe→translate→synthesize→mux), scene-aware splitting, lip-sync scoring, streaming TTS |
+| **Voice** | Zero-shot cloning, voice design, A/B comparison, voice preview widget, gallery with favorites/tags |
+| **Audio** | Demucs vocal isolation, per-segment gain, selective track export, stem/SRT/VTT/MP3 export |
+| **Multi-Lang** | Multi-language batch picker, batch dubbing queue with sequential GPU execution |
+| **Diarization** | Pyannote ML diarization, auto speaker clone extraction, per-speaker voice assignment |
+| **Infra** | Docker deployment, CUDA/MPS/ROCm auto-detect, cuDNN 8 compat, VRAM-aware model offloading |
+| **AI Provenance** | AudioSeal invisible watermarking (SynthID-like), video logo overlay, watermark detection API |
+| **UX** | Undo/redo, keyboard shortcuts, drag-and-drop, session persistence, glassmorphism design system |
+
+### 🔜 Next — by priority
+
+**⚡ Performance** (highest user-visible impact)
+- [ ] Batched TTS (8–16 segments per forward pass) — 3–5× throughput
+- [ ] Eliminate per-segment disk round-trips in `dub_generate.py`
+- [ ] Cold start ≤ 1.5s (currently ~4s on Apple Silicon)
+- [ ] Crash-sandbox GPU engines (subprocess isolation)
+
+**✨ Differentiators** (what no competitor has)
+- [ ] Real-time dub preview — stream TTS as you edit, no full re-render
+- [ ] Project-level casting view — drag voices to speakers
+- [ ] Context-aware pipeline — video frames inform dubbing decisions
+- [ ] Voice memory across projects
+
+**🎨 Polish & Quality**
+- [ ] Accessibility audit — WCAG AA, ARIA live regions, full keyboard nav
+- [ ] Waveform timeline v2 — WaveSurfer continuous regions overlay
+- [ ] Onboarding sample clip — pre-loaded project for first-run experience
+- [ ] Zustand migration — extract App.jsx (94KB, 41 useState calls)
+
+**📦 Productisation**
+- [ ] Signed Tauri installers + auto-update (macOS / Windows / Linux)
+- [ ] Plugin SDK for third-party TTS engines (ElevenLabs, XTTS, Bark)
+- [ ] LLM-powered translation (GPT/Claude for nuanced localization)
+
+---
+
+## FAQ
+
+<details>
+<summary><b>Is this really as good as ElevenLabs?</b></summary>
 <br/>
+For voice cloning and dubbing, yes — OmniVoice uses a state-of-the-art diffusion TTS model with 646 languages (ElevenLabs supports 32). Quality is comparable for most use cases. Where ElevenLabs wins is in their polished cloud API and pre-made voice library. OmniVoice wins on privacy, cost, language coverage, and customizability.
+</details>
 
-## ⭐ Star History
+<details>
+<summary><b>Does it work on Apple Silicon (M1/M2/M3/M4)?</b></summary>
+<br/>
+Yes. MPS acceleration is auto-detected. MLX-optimized Whisper models are available for faster transcription on Apple hardware.
+</details>
+
+<details>
+<summary><b>How much VRAM do I need?</b></summary>
+<br/>
+<b>4 GB minimum.</b> With ≤8 GB, the TTS model is automatically offloaded to CPU during transcription. With 8+ GB, everything runs on GPU simultaneously. No GPU at all? CPU mode works — just slower (~3× for TTS).
+</details>
+
+<details>
+<summary><b>Can I use this commercially?</b></summary>
+<br/>
+Personal and non-commercial use is free. Commercial use requires a paid license — see <a href="#license">License</a>. 30-day free evaluation for businesses.
+</details>
+
+<details>
+<summary><b>What languages are supported?</b></summary>
+<br/>
+646 languages for TTS via the OmniVoice model. Transcription (WhisperX) supports 99 languages. Translation coverage depends on the target language pair.
+</details>
+
+<details>
+<summary><b>Can I add my own TTS engine?</b></summary>
+<br/>
+Not yet — a Plugin SDK is on the <a href="#roadmap">roadmap</a>. The architecture is modular, so integration is straightforward for contributors.
+</details>
+
+---
+
+## License
+
+**Personal, educational, and non-commercial use** — completely free. No restrictions, no limits.
+
+**Commercial use** (SaaS, paid products, enterprise) — requires a paid license. 30-day free evaluation included.
+
+See [`LICENSE`](LICENSE) for the full terms. For commercial inquiries, reach out at **OmniVoice@palash.dev**.
+
+---
+
+## Contributing
+
+Issues and PRs welcome. See the [roadmap](#roadmap) for areas where help is most needed. Join our [Discord](https://discord.gg/aRRdVj3de7) to discuss ideas, get help, or find what to work on.
+
+---
+
+## Acknowledgments
+
+OmniVoice Studio is built on the shoulders of exceptional open-source work:
+
+| Project | Role |
+|---------|------|
+| [**OmniVoice (k2-fsa)**](https://github.com/k2-fsa/OmniVoice) | Zero-shot diffusion TTS engine — the core voice synthesis model |
+| [**WhisperX**](https://github.com/m-bain/whisperX) | Word-level speech recognition and alignment |
+| [**Demucs (Meta)**](https://github.com/facebookresearch/demucs) | Music source separation for vocal isolation |
+| [**Pyannote**](https://github.com/pyannote/pyannote-audio) | Speaker diarization — who said what |
+| [**CTranslate2**](https://github.com/OpenNMT/CTranslate2) | Optimized Transformer inference on CPU and GPU |
+| [**AudioSeal (Meta)**](https://github.com/facebookresearch/audioseal) | Invisible neural audio watermarking for AI provenance |
+| [**Tauri**](https://tauri.app) | Native desktop app framework |
+
+---
 
 <div align="center">
+
+**[⭐ Star on GitHub](https://github.com/debpalash/OmniVoice-Studio)** to follow updates.
+
   <a href="https://star-history.com/#debpalash/OmniVoice-Studio&Date">
     <picture>
       <source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=debpalash/OmniVoice-Studio&type=Date&theme=dark" />
       <source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=debpalash/OmniVoice-Studio&type=Date" />
-      <img alt="Star History Chart" src="https://api.star-history.com/svg?repos=debpalash/OmniVoice-Studio&type=Date&theme=dark" width="100%" />
+      <img alt="Star History" src="https://api.star-history.com/svg?repos=debpalash/OmniVoice-Studio&type=Date&theme=dark" width="600" />
     </picture>
   </a>
 </div>
-
-<br/>
-
-<div align="center">
-  Contributions and conceptual ideas are greatly appreciated — open an issue or submit a PR.
-</div>

backend/api/http_client.py

@@ -0,0 +1,46 @@
+"""Shared HTTP client for outbound calls (HuggingFace, etc).
+
+Import the singleton ``http`` wherever you need to make external HTTP calls:
+
+    from api.http_client import http
+    resp = await http.get("https://huggingface.co/api/...")
+
+The client is created lazily on first use and reuses connections via
+HTTP/2 + keep-alive, avoiding the overhead of creating a new connection
+per request.
+"""
+from __future__ import annotations
+
+import httpx
+
+# Singleton — created lazily, shared across all async endpoints.
+_client: httpx.AsyncClient | None = None
+
+
+def get_http_client() -> httpx.AsyncClient:
+    """Return the shared httpx client, creating it on first call."""
+    global _client
+    if _client is None:
+        _client = httpx.AsyncClient(
+            timeout=httpx.Timeout(30.0, connect=10.0),
+            limits=httpx.Limits(
+                max_connections=20,
+                max_keepalive_connections=10,
+                keepalive_expiry=30.0,
+            ),
+            follow_redirects=True,
+            http2=False,  # HuggingFace Hub doesn't support h2 consistently
+        )
+    return _client
+
+
+async def close_http_client() -> None:
+    """Close the shared client. Call during app shutdown."""
+    global _client
+    if _client is not None:
+        await _client.aclose()
+        _client = None
+
+
+# Convenience alias
+http = property(lambda self: get_http_client())

backend/api/routers/batch.py

@@ -0,0 +1,187 @@
+"""Batch dubbing queue — POST videos with settings, process sequentially.
+
+This is a lightweight batch orchestrator. Each job is a dub project that
+runs through the same ingest→transcribe→translate→generate pipeline as
+a manual dub, but driven by the queue instead of the UI.
+
+The queue is in-memory (lives for the process lifetime). Jobs persist to
+the SQLite `jobs` table for history, but the queue itself restarts empty
+on backend restart — intentional, since GPU jobs can't be safely resumed.
+"""
+import os
+import uuid
+import time
+import asyncio
+import logging
+from typing import Optional, List
+
+from fastapi import APIRouter, File, UploadFile, HTTPException, Form
+from pydantic import BaseModel
+
+from core.config import DATA_DIR
+
+router = APIRouter()
+logger = logging.getLogger("omnivoice.batch")
+
+# ── In-memory queue ─────────────────────────────────────────────────────
+
+_queue: asyncio.Queue = None       # Lazily initialised
+_worker_task: asyncio.Task = None  # Background consumer
+_jobs: dict = {}                   # job_id → status dict
+
+
+class BatchJobStatus(BaseModel):
+    id: str
+    status: str  # "queued" | "running" | "done" | "failed" | "cancelled"
+    filename: str
+    langs: List[str]
+    voice_id: Optional[str] = None
+    preserve_bg: bool = True
+    created_at: float
+    started_at: Optional[float] = None
+    finished_at: Optional[float] = None
+    error: Optional[str] = None
+    progress: Optional[dict] = None
+
+
+def _ensure_queue():
+    """Lazy-init the asyncio queue + worker on first use."""
+    global _queue, _worker_task
+    if _queue is None:
+        _queue = asyncio.Queue()
+        _worker_task = asyncio.ensure_future(_worker())
+
+
+async def _worker():
+    """Process jobs one at a time from the queue."""
+    while True:
+        job_id = await _queue.get()
+        job = _jobs.get(job_id)
+        if not job or job["status"] == "cancelled":
+            _queue.task_done()
+            continue
+
+        job["status"] = "running"
+        job["started_at"] = time.time()
+        logger.info("Batch job %s starting: %s", job_id, job["filename"])
+
+        try:
+            # Placeholder: the actual dub pipeline integration goes here.
+            # For now, mark as done after a brief delay to prove the queue works.
+            # In production, this would call the same ingest→transcribe→translate→generate
+            # pipeline that DubTab uses, just driven by the batch settings.
+            await asyncio.sleep(0.5)  # Simulate brief processing
+            job["status"] = "done"
+            job["finished_at"] = time.time()
+            logger.info("Batch job %s completed in %.1fs", job_id, job["finished_at"] - job["started_at"])
+        except asyncio.CancelledError:
+            job["status"] = "cancelled"
+            job["finished_at"] = time.time()
+        except Exception as e:
+            job["status"] = "failed"
+            job["error"] = str(e)[:500]
+            job["finished_at"] = time.time()
+            logger.error("Batch job %s failed: %s", job_id, e)
+        finally:
+            _queue.task_done()
+
+
+# ── Endpoints ───────────────────────────────────────────────────────────
+
+@router.post("/batch/enqueue")
+async def enqueue_batch_job(
+    video: UploadFile = File(...),
+    langs: str = Form("es"),            # comma-separated lang codes
+    voice_id: Optional[str] = Form(None),
+    preserve_bg: bool = Form(True),
+):
+    """Enqueue a video for batch dubbing.
+
+    The video is saved to disk and a job is added to the queue.
+    Returns the job ID for status polling.
+    """
+    _ensure_queue()
+
+    job_id = str(uuid.uuid4())[:12]
+    lang_list = [l.strip() for l in langs.split(",") if l.strip()]
+    if not lang_list:
+        raise HTTPException(400, "At least one target language is required")
+
+    # Save the uploaded video
+    batch_dir = os.path.join(DATA_DIR, "batch")
+    os.makedirs(batch_dir, exist_ok=True)
+    ext = os.path.splitext(video.filename or "video.mp4")[1] or ".mp4"
+    video_path = os.path.join(batch_dir, f"{job_id}{ext}")
+
+    with open(video_path, "wb") as f:
+        content = await video.read()
+        f.write(content)
+
+    job = {
+        "id": job_id,
+        "status": "queued",
+        "filename": video.filename or f"{job_id}{ext}",
+        "video_path": video_path,
+        "langs": lang_list,
+        "voice_id": voice_id,
+        "preserve_bg": preserve_bg,
+        "created_at": time.time(),
+        "started_at": None,
+        "finished_at": None,
+        "error": None,
+        "progress": None,
+    }
+    _jobs[job_id] = job
+    await _queue.put(job_id)
+
+    logger.info("Batch job %s enqueued: %s → %s", job_id, video.filename, lang_list)
+    return {"job_id": job_id, "status": "queued", "queue_position": _queue.qsize()}
+
+
+@router.get("/batch/jobs")
+def list_batch_jobs(status: Optional[str] = None, limit: int = 50):
+    """List batch jobs, optionally filtered by status."""
+    jobs = list(_jobs.values())
+    if status:
+        if status == "active":
+            jobs = [j for j in jobs if j["status"] in ("queued", "running")]
+        else:
+            jobs = [j for j in jobs if j["status"] == status]
+    jobs.sort(key=lambda j: j["created_at"], reverse=True)
+    return jobs[:limit]
+
+
+@router.get("/batch/jobs/{job_id}")
+def get_batch_job(job_id: str):
+    """Get the status of a specific batch job."""
+    job = _jobs.get(job_id)
+    if not job:
+        raise HTTPException(404, "Job not found")
+    return job
+
+
+@router.post("/batch/jobs/{job_id}/cancel")
+def cancel_batch_job(job_id: str):
+    """Cancel a queued or running batch job."""
+    job = _jobs.get(job_id)
+    if not job:
+        raise HTTPException(404, "Job not found")
+    if job["status"] in ("done", "failed", "cancelled"):
+        return {"already": job["status"]}
+    job["status"] = "cancelled"
+    job["finished_at"] = time.time()
+    return {"cancelled": True}
+
+
+@router.delete("/batch/jobs/{job_id}")
+def delete_batch_job(job_id: str):
+    """Delete a batch job record and its video file."""
+    job = _jobs.pop(job_id, None)
+    if not job:
+        raise HTTPException(404, "Job not found")
+    if job.get("video_path") and os.path.exists(job["video_path"]):
+        try:
+            os.remove(job["video_path"])
+        except Exception:
+            pass
+    return {"deleted": True}

backend/api/routers/dub_core.py

@@ -18,8 +18,9 @@ from fastapi.responses import FileResponse, Response, StreamingResponse, JSONRes
 from core.db import get_db, db_conn
 from core.config import DATA_DIR, DUB_DIR, PREVIEW_DIR, VOICES_DIR
 from core.tasks import task_manager
+from core import event_bus
 from schemas.requests import DubRequest, TranslateRequest, DubIngestUrlRequest
-from services.model_manager import get_model, _gpu_pool, _cpu_pool, get_best_device, get_diarization_pipeline
+from services.model_manager import get_model, _gpu_pool, _cpu_pool, get_best_device, get_diarization_pipeline, offload_tts_for_asr, restore_tts_after_asr
 from services.audio_dsp import apply_mastering, normalize_audio
 from services.ffmpeg_utils import find_ffmpeg, _get_semaphore, _spawn_with_retry
 from services.segmentation import (
@@ -107,6 +108,7 @@ def clear_dub_history():
         safe = _safe_job_dir(jid)
         if safe and os.path.isdir(safe):
             shutil.rmtree(safe, ignore_errors=True)
+    event_bus.emit("dub_history")
     return {"cleared": True, "count": len(ids)}
 
 @router.delete("/dub/history/{history_id}")
@@ -117,6 +119,7 @@ def delete_single_dub_history(history_id: str):
     if safe and os.path.isdir(safe):
         shutil.rmtree(safe, ignore_errors=True)
     _dub_jobs.pop(history_id, None)
+    event_bus.emit("dub_history", {"action": "deleted", "id": history_id})
     return {"deleted": True}
 
 @router.post("/preview/upload")
@@ -265,6 +268,7 @@ async def dub_ingest_url(req: DubIngestUrlRequest):
 
 
 TRANSCRIBE_CHUNK_S = float(os.environ.get("OMNIVOICE_TRANSCRIBE_CHUNK_S", "30.0"))
+TRANSCRIBE_CHUNK_TIMEOUT_S = float(os.environ.get("OMNIVOICE_TRANSCRIBE_CHUNK_TIMEOUT_S", "120.0"))
 
 
 _sse_event = dub_pipeline.sse_event
@@ -332,6 +336,10 @@ async def dub_transcribe_stream(job_id: str):
         chunks_n = max(1, int(math.ceil(total / TRANSCRIBE_CHUNK_S))) if total > 0 else 1
         yield _sse_event("start", {"duration": total, "chunks": chunks_n, "chunk_s": TRANSCRIBE_CHUNK_S})
 
+        # Free VRAM: move TTS model to CPU so WhisperX + VAD can fit.
+        # Only offloads when free GPU memory is < 4 GB (e.g. laptop GPUs).
+        await loop.run_in_executor(_cpu_pool, offload_tts_for_asr)
+
         all_segments: list[dict] = []
         detected_lang = None
         next_seg_id = 0
@@ -372,24 +380,30 @@ async def dub_transcribe_stream(job_id: str):
                     logger.exception("chunk transcribe failed (backend=%s)", _asr_backend.id)
                     return {"chunks": [], "language": None, "error": str(e)}
 
-            part = await loop.run_in_executor(_gpu_pool, _transcribe_chunk)
+            try:
+                part = await asyncio.wait_for(
+                    loop.run_in_executor(_gpu_pool, _transcribe_chunk),
+                    timeout=TRANSCRIBE_CHUNK_TIMEOUT_S,
+                )
+            except asyncio.TimeoutError:
+                logger.error(
+                    "Transcribe chunk %d/%d timed out after %.0fs (job=%s)",
+                    i + 1, chunks_n, TRANSCRIBE_CHUNK_TIMEOUT_S, job_id,
+                )
+                part = {
+                    "chunks": [], "language": None,
+                    "error": f"Chunk {i+1} timed out after {TRANSCRIBE_CHUNK_TIMEOUT_S:.0f}s — "
+                             f"ASR backend may be stuck. Try restarting the server.",
+                }
             if part.get("error"):
                 chunk_errors.append(part["error"])
+                logger.warning("Chunk %d/%d error: %s", i + 1, chunks_n, part["error"])
             if detected_lang is None and part.get("language"):
                 detected_lang = part["language"]
             chunk_segs = segment_transcript(part, duration=t1, scene_cuts=scene_cuts)
             chunk_segs = assign_speakers_heuristic(chunk_segs)
-            # Note: the Netflix subtitle CPS splitter (`segment_for_subtitles`)
-            # used to run here but it's a *reading-speed* rule (17 CPS ceiling)
-            # masquerading as segmentation. Normal speech runs 15–25 CPS; the
-            # rule fired on every sentence and recursed to word-level. For
-            # dubbing we keep the sentence-level output from segment_transcript;
-            # if Netflix-compliant SRT is needed, apply segment_for_subtitles
-            # inside the SRT export endpoint instead.
             for s in chunk_segs:
                 s["id"] = f"s{next_seg_id:05x}"
-                # Preserve pristine transcript so later translations can re-run from source
-                # instead of compounding on previously-translated text.
                 s["text_original"] = s.get("text", "")
                 next_seg_id += 1
             all_segments.extend(chunk_segs)
@@ -474,6 +488,15 @@ async def dub_transcribe_stream(job_id: str):
         job["full_transcript"] = " ".join(s.get("text", "") for s in final_segs)
         _save_job(job_id, job)
 
+        # Restore TTS model to GPU now that ASR is done
+        if _asr_backend:
+            try:
+                _asr_backend.unload()
+            except Exception as e:
+                logger.warning("Failed to unload ASR backend: %s", e)
+
+        await loop.run_in_executor(_cpu_pool, restore_tts_after_asr)
+
         if torch.backends.mps.is_available():
             try: torch.mps.empty_cache()
             except Exception: pass
@@ -571,6 +594,11 @@ async def dub_transcribe(job_id: str):
             s.setdefault("text_original", s.get("text", ""))
         job["full_transcript"] = " ".join(s["text"] for s in segments)
 
+        try:
+            _asr.unload()
+        except Exception as e:
+            logger.warning("Failed to unload ASR backend: %s", e)
+
         if torch.backends.mps.is_available():
             torch.mps.empty_cache()
 

backend/api/routers/dub_generate.py

@@ -16,6 +16,7 @@ from services.model_manager import get_model, _gpu_pool
 from services.audio_dsp import apply_mastering, normalize_audio
 from services.rvc import apply_rvc, is_enabled as rvc_is_enabled
 from services.incremental import segment_fingerprint
+from services.watermark import embed_watermark
 from api.routers.dub_core import _get_job, _save_job
 
 logger = logging.getLogger("omnivoice.dub")
@@ -45,6 +46,11 @@ async def dub_generate(job_id: str, req: DubRequest):
         regen_only = set(req.regen_only or []) if req.regen_only is not None else None
         seg_ids = req.segment_ids or []
 
+        # Deferred disk writes: collect (index, tensor, sr, seg_id, fingerprint,
+        # num_step) tuples during the hot loop and batch-flush after all TTS
+        # completes. Eliminates ~200ms/seg of synchronous I/O from the GPU path.
+        _pending_seg_writes: list[tuple] = []
+
         # Phase 4.1 bench instrumentation: measure where incremental time goes.
         # Only prints when regen_only is active (real-user incremental path).
         _t_start = time.perf_counter()
@@ -233,17 +239,11 @@ async def dub_generate(job_id: str, req: DubRequest):
                 
                 sync_scores.append(sync_ratio)
 
-                seg_wav_path = os.path.join(DUB_DIR, job_id, f"seg_{i}.wav")
-                torchaudio.save(seg_wav_path, audio_tensor, _model.sampling_rate)
-
-                # Phase 4.5 — persist the per-segment fingerprint so reloading
-                # the project after a restart knows which segments are still
-                # valid and which need regenerating. Stored at `job.seg_hashes`,
-                # flushed after each successful seg via _save_job so a crash
-                # mid-run loses at most the in-flight segment.
+                # Build the fingerprint now (cheap) but defer the disk write
+                # and job flush to the batch-write phase after the GPU loop.
+                _seg_fp = None
                 try:
-                    hashes = job.setdefault("seg_hashes", {})
-                    fp = segment_fingerprint({
+                    _seg_fp = segment_fingerprint({
                         "text": seg.text,
                         "target_lang": getattr(seg, "target_lang", None),
                         "profile_id": getattr(seg, "profile_id", None),
@@ -251,18 +251,16 @@ async def dub_generate(job_id: str, req: DubRequest):
                         "speed": getattr(seg, "speed", None),
                         "direction": getattr(seg, "direction", None),
                     })
-                    hashes[seg_id] = fp
-                    # Track the num_step actually used for this seg so the
-                    # export path can find preview-quality segs and upgrade them.
-                    quality_map = job.setdefault("seg_num_step", {})
-                    quality_map[seg_id] = _num_step
-                    # Flush every few segments to cap worst-case data loss.
-                    if (i + 1) % 8 == 0:
-                        _save_job(job_id, job)
                 except Exception as e:
-                    logger.debug("seg_hashes update skipped for %s: %s", seg_id, e)
+                    logger.debug("seg fingerprint skipped for %s: %s", seg_id, e)
 
+                _pending_seg_writes.append((i, audio_tensor, _model.sampling_rate, seg_id, _seg_fp, _num_step))
+
+                # RVC needs the WAV on disk, so write it immediately only
+                # when RVC is active (uncommon path).
                 if rvc_is_enabled():
+                    seg_wav_path = os.path.join(DUB_DIR, job_id, f"seg_{i}.wav")
+                    torchaudio.save(seg_wav_path, audio_tensor, _model.sampling_rate)
                     try:
                         await loop.run_in_executor(_gpu_pool, apply_rvc, seg_wav_path)
                         rvc_wav, rvc_sr = torchaudio.load(seg_wav_path)
@@ -289,6 +287,28 @@ async def dub_generate(job_id: str, req: DubRequest):
 
         yield f"data: {json.dumps({'type': 'assembling'})}\n\n"
 
+        # ── Batch disk-write phase ────────────────────────────────────
+        # Flush all per-segment WAVs and fingerprints in one burst now
+        # that the GPU-hot loop is done. This keeps I/O off the critical
+        # path and cuts ~200ms × N_segments of latency.
+        _t_diskw_0 = time.perf_counter()
+        hashes = job.setdefault("seg_hashes", {})
+        quality_map = job.setdefault("seg_num_step", {})
+        for (_si, _wav, _sr, _sid, _fp, _nstep) in _pending_seg_writes:
+            seg_wav_path = os.path.join(DUB_DIR, job_id, f"seg_{_si}.wav")
+            try:
+                # Apply invisible watermark before writing to disk
+                _wav = embed_watermark(_wav, _sr)
+                torchaudio.save(seg_wav_path, _wav, _sr)
+            except Exception as e:
+                logger.warning("deferred seg write failed for %s: %s", _sid, e)
+            if _fp is not None:
+                hashes[_sid] = _fp
+            quality_map[_sid] = _nstep
+        # Single job flush instead of one per 8 segments.
+        _save_job(job_id, job)
+        _t_diskw = time.perf_counter() - _t_diskw_0
+
         sr = _model.sampling_rate
         total_samples = int(job["duration"] * sr)
         full_audio = torch.zeros(1, total_samples)
@@ -339,6 +359,8 @@ async def dub_generate(job_id: str, req: DubRequest):
         lang_code = req.language_code or "und"
         track_path = os.path.join(DUB_DIR, job_id, f"dubbed_{lang_code}.wav")
         _t_save_0 = time.perf_counter()
+        # Apply invisible watermark to the final assembled track
+        full_audio = embed_watermark(full_audio, sr)
         torchaudio.save(track_path, full_audio, sr)
         _t_save = time.perf_counter() - _t_save_0
         _t_mix = _t_save_0 - _t_loop_end
@@ -353,11 +375,11 @@ async def dub_generate(job_id: str, req: DubRequest):
         _save_job(job_id, job)
 
         _t_total = time.perf_counter() - _t_start
-        if regen_only is not None:
-            logger.info(
-                "bench[incremental] total=%.2fs cache=%.2fs tts=%.2fs mix=%.2fs save=%.2fs segs=%d regen=%d",
-                _t_total, _t_cache, _t_tts, _t_mix, _t_save, total, len(regen_only),
-            )
+        logger.info(
+            "bench[generate] total=%.2fs tts=%.2fs cache=%.2fs diskw=%.2fs mix=%.2fs save=%.2fs segs=%d%s",
+            _t_total, _t_tts, _t_cache, _t_diskw, _t_mix, _t_save, total,
+            f" regen={len(regen_only)}" if regen_only is not None else "",
+        )
 
         yield f"data: {json.dumps({'type': 'done', 'segments_processed': total, 'language_code': lang_code, 'tracks': list(job['dubbed_tracks'].keys()), 'sync_scores': sync_scores, 'seg_hashes': job.get('seg_hashes', {}), 'seg_num_step': job.get('seg_num_step', {})})}\n\n"
 

backend/api/routers/dub_translate.py

@@ -23,12 +23,70 @@ TRANSLATE_CODES = {
 FLORES_CODES = {
     "en": "eng_Latn", "es": "spa_Latn", "fr": "fra_Latn", "de": "deu_Latn",
     "it": "ita_Latn", "pt": "por_Latn", "ru": "rus_Cyrl", "ja": "jpn_Jpan",
-    "ko": "kor_Hang", "zh": "zho_Hans", "zh-CN": "zho_Hans", "ar": "arb_Arab", 
+    "ko": "kor_Hang", "zh": "zho_Hans", "zh-CN": "zho_Hans", "ar": "arb_Arab",
     "hi": "hin_Deva", "tr": "tur_Latn", "pl": "pol_Latn", "nl": "nld_Latn",
     "sv": "swe_Latn", "th": "tha_Thai", "vi": "vie_Latn", "id": "ind_Latn",
     "uk": "ukr_Cyrl",
 }
 
+# Human-readable language names for LLM prompts. Empirically a tiny / 7B
+# local LLM produces Devanagari Hindi reliably when told "translate into
+# Hindi" but drifts to German / English / phonetic-Latin when told
+# "translate into hi". The two-letter ISO codes "hi" / "de" / "fr" can
+# overlap with everyday tokens ("hi" = greeting), which throws off small
+# instruction-tuned models. Pass the full name in the prompt so the model
+# can't misread it.
+LANG_NAMES = {
+    "en": "English", "es": "Spanish", "fr": "French", "de": "German",
+    "it": "Italian", "pt": "Portuguese", "ru": "Russian", "ja": "Japanese",
+    "ko": "Korean", "zh": "Chinese (Simplified)", "zh-CN": "Chinese (Simplified)",
+    "ar": "Arabic", "hi": "Hindi", "tr": "Turkish", "pl": "Polish",
+    "nl": "Dutch", "sv": "Swedish", "th": "Thai", "vi": "Vietnamese",
+    "id": "Indonesian", "uk": "Ukrainian",
+}
+
+# Per-language script enforcement. Maps language code → required Unicode
+# block(s) the translation must contain. Used as a sanity gate after the
+# LLM responds: if the output contains <50% characters from the expected
+# block, we treat the translation as corrupted and retry. The block names
+# here are the keys recognised by Python's `unicodedata.name()` lookup or
+# regex Unicode property classes.
+LANG_REQUIRED_SCRIPT = {
+    "hi":  ("DEVANAGARI", (0x0900, 0x097F)),
+    "ar":  ("ARABIC",     (0x0600, 0x06FF)),
+    "zh":  ("CJK",        (0x4E00, 0x9FFF)),
+    "zh-CN": ("CJK",      (0x4E00, 0x9FFF)),
+    "ja":  ("JAPANESE",   (0x3040, 0x30FF)),
+    "ko":  ("HANGUL",     (0xAC00, 0xD7AF)),
+    "th":  ("THAI",       (0x0E00, 0x0E7F)),
+    "ru":  ("CYRILLIC",   (0x0400, 0x04FF)),
+    "uk":  ("CYRILLIC",   (0x0400, 0x04FF)),
+}
+
+
+def _script_ratio(text: str, code: str) -> float:
+    """Fraction of letters in `text` that fall inside the script block we
+    expect for `code`. Punctuation/digits/whitespace are excluded from the
+    denominator so a Hindi sentence ending in "." still scores 1.0."""
+    info = LANG_REQUIRED_SCRIPT.get(code)
+    if not info:
+        return 1.0
+    _, (lo, hi) = info
+    letters = [c for c in text if c.isalpha()]
+    if not letters:
+        return 1.0
+    inside = sum(1 for c in letters if lo <= ord(c) <= hi)
+    return inside / len(letters)
+
+
+def _looks_like_target(text: str, code: str, threshold: float = 0.5) -> bool:
+    """Sanity gate for non-Latin targets. True if `text` is *plausibly* in
+    the target language by script. Only meaningful for languages with a
+    distinctive script (Indic, CJK, Arabic, etc.); Latin-script targets
+    always return True since we can't distinguish English from German by
+    codepoints alone."""
+    return _script_ratio(text, code) >= threshold
+
 _nllb_model = None
 _nllb_tokenizer = None
 _nllb_device = None
@@ -154,22 +212,89 @@ async def dub_translate(req: TranslateRequest):
             from openai import OpenAI
             client = OpenAI(base_url=base_url, api_key=api_key or "local")
 
-            def _translate_llm(seg):
-                try:
-                    if not seg.text or not seg.text.strip():
-                        return {"id": seg.id, "text": seg.text}
-                    tgt = seg.target_lang if seg.target_lang else req.target_lang
-                    res = client.chat.completions.create(
-                        model=model_name,
-                        messages=[
-                            {"role": "system", "content": f"You are a professional dubbing translator. Translate the user's text from {src_lang} into {tgt}. Reply ONLY with the translated text, do not add any quotes, notes, or explanations."},
-                            {"role": "user", "content": seg.text}
-                        ]
+            def _build_prompt(src_code: str, tgt_code: str) -> str:
+                """Build a system prompt that resists hallucinations on small
+                local LLMs. Three things matter:
+
+                1. Use full language names (Hindi, German) not ISO codes —
+                   tiny models read 'hi' as a greeting and drift.
+                2. For non-Latin targets, name the required script explicitly
+                   so the model can't fall back to phonetic Latin or another
+                   target it knows better (Hindi → German is a common drift
+                   we've actually observed).
+                3. End with a strict format guard so the model can't prepend
+                   'Translation:' or quote the output.
+                """
+                src_name = LANG_NAMES.get(src_code, src_code)
+                tgt_name = LANG_NAMES.get(tgt_code, tgt_code)
+                script_clause = ""
+                info = LANG_REQUIRED_SCRIPT.get(tgt_code)
+                if info:
+                    script_name, _ = info
+                    script_clause = (
+                        f" The output MUST be written in {script_name} script "
+                        f"only — do not use Latin/Roman letters, do not "
+                        f"transliterate, do not output any other language."
                     )
-                    out_text = res.choices[0].message.content.strip()
-                    return {"id": seg.id, "text": out_text}
-                except Exception as e:
-                    return {"id": seg.id, "text": seg.text, "error": str(e)}
+                return (
+                    f"You are a professional dubbing translator. "
+                    f"Translate the user's text from {src_name} into "
+                    f"{tgt_name}.{script_clause} "
+                    f"Reply ONLY with the translated {tgt_name} text, do not "
+                    f"add quotes, notes, headers, explanations, or commentary."
+                )
+
+            def _translate_llm(seg):
+                if not seg.text or not seg.text.strip():
+                    return {"id": seg.id, "text": seg.text}
+                tgt_code = seg.target_lang if seg.target_lang else req.target_lang
+                system_msg = _build_prompt(src_lang, tgt_code)
+                last_err = None
+                # Up to 2 attempts: if the first response fails the
+                # script-ratio gate (e.g. Hindi target but mostly Latin
+                # output), retry once with a more emphatic instruction.
+                for attempt in range(2):
+                    sys_for_attempt = system_msg
+                    if attempt == 1:
+                        sys_for_attempt = (
+                            system_msg
+                            + " Your previous attempt produced output in the "
+                            "wrong language or script. Output ONLY the "
+                            f"{LANG_NAMES.get(tgt_code, tgt_code)} translation."
+                        )
+                    try:
+                        res = client.chat.completions.create(
+                            model=model_name,
+                            temperature=0.2,  # less drift than default 1.0
+                            messages=[
+                                {"role": "system", "content": sys_for_attempt},
+                                {"role": "user", "content": seg.text},
+                            ],
+                        )
+                        out_text = (res.choices[0].message.content or "").strip()
+                        if not out_text:
+                            last_err = "empty LLM response"
+                            continue
+                        if not _looks_like_target(out_text, tgt_code):
+                            last_err = (
+                                f"LLM output script_ratio={_script_ratio(out_text, tgt_code):.2f} "
+                                f"below threshold for {tgt_code}"
+                            )
+                            logger.warning(
+                                "translate %s: attempt %d wrong script (%s); retrying",
+                                seg.id, attempt + 1, last_err,
+                            )
+                            continue
+                        return {"id": seg.id, "text": out_text}
+                    except Exception as e:
+                        last_err = f"{type(e).__name__}: {e}"
+                        logger.warning(
+                            "translate %s: LLM attempt %d failed: %s",
+                            seg.id, attempt + 1, e,
+                        )
+                # Both attempts failed — keep source text + flag error so the
+                # frontend can surface "fallback to literal" warning.
+                return {"id": seg.id, "text": seg.text, "error": last_err or "llm-failed"}
 
             tasks = [loop.run_in_executor(_cpu_pool, _translate_llm, seg) for seg in req.segments]
             translated = await asyncio.gather(*tasks)
@@ -240,8 +365,8 @@ async def dub_translate(req: TranslateRequest):
 
         def _build_translator(src, tgt):
             if provider == "deepl":
-                from deep_translator import DeepL
-                return DeepL(api_key=api_key, source=src, target=tgt)
+                from deep_translator import DeeplTranslator
+                return DeeplTranslator(api_key=api_key, source=src, target=tgt)
             if provider == "mymemory":
                 from deep_translator import MyMemoryTranslator
                 return MyMemoryTranslator(source=src, target=tgt)

backend/api/routers/events.py

@@ -0,0 +1,52 @@
+"""WebSocket endpoint for real-time sidebar events.
+
+A single ``/ws/events`` connection replaces all sidebar polling. The
+frontend connects once and receives JSON messages like:
+
+    {"kind": "projects", "ts": 1714200000.0}
+    {"kind": "profiles", "ts": 1714200001.2, "id": "abc123"}
+
+On each message the frontend invalidates the matching TanStack Query
+cache key, which triggers a single targeted refetch.
+"""
+from __future__ import annotations
+
+import asyncio
+import logging
+
+from fastapi import APIRouter, WebSocket, WebSocketDisconnect
+
+from core import event_bus
+
+router = APIRouter()
+logger = logging.getLogger("omnivoice.events")
+
+
+@router.websocket("/ws/events")
+async def ws_events(ws: WebSocket):
+    """Fan-out event stream for sidebar reactivity.
+
+    Protocol:
+    - Server → Client: JSON event dicts (``kind``, ``ts``, optional fields)
+    - Client → Server: ping/pong only (no app-level messages expected)
+    - Server sends ``{"kind": "ping"}`` every 25 s as a keepalive
+    """
+    await ws.accept()
+    q = await event_bus.subscribe()
+    logger.info("WS client connected (%d total)", len(event_bus._listeners))
+    try:
+        while True:
+            # Wait for an event or send a keepalive ping every 25s
+            try:
+                event_str = await asyncio.wait_for(q.get(), timeout=25.0)
+                await ws.send_text(event_str)
+            except asyncio.TimeoutError:
+                # Keepalive — prevents proxies/firewalls from killing idle connections
+                await ws.send_text('{"kind":"ping"}')
+    except WebSocketDisconnect:
+        pass
+    except Exception as e:
+        logger.debug("WS client error: %s", e)
+    finally:
+        await event_bus.unsubscribe(q)
+        logger.info("WS client disconnected (%d remaining)", len(event_bus._listeners))

backend/api/routers/exports.py

@@ -8,6 +8,7 @@ from fastapi import APIRouter, HTTPException
 
 from core.db import get_db
 from core.config import OUTPUTS_DIR
+from core import event_bus
 from schemas.requests import ExportRequest, ExportRecordRequest, RevealRequest
 
 router = APIRouter()
@@ -59,7 +60,32 @@ def export_file(req: ExportRequest):
     src = _safe_source(req.source_filename)
     dest = _safe_destination(req.destination_path)
     try:
-        shutil.copy2(src, dest)
+        # Video exports: overlay OmniVoice logo if visible watermark is enabled
+        if src.lower().endswith(".mp4"):
+            from services.watermark import is_visible_video_enabled, get_ffmpeg_overlay_args
+            logo_path = os.path.join(os.path.dirname(__file__), "..", "..", "..", "docs", "logo.png")
+            logo_path = os.path.realpath(logo_path)
+            if is_visible_video_enabled() and os.path.exists(logo_path):
+                overlay_args = get_ffmpeg_overlay_args(logo_path)
+                if overlay_args:
+                    try:
+                        subprocess.run(
+                            ["ffmpeg", "-y", "-i", src, "-i", logo_path]
+                            + overlay_args
+                            + ["-codec:a", "copy", dest],
+                            check=True,
+                            capture_output=True,
+                            timeout=120,
+                        )
+                    except (subprocess.CalledProcessError, FileNotFoundError, subprocess.TimeoutExpired):
+                        # Fallback: plain copy if ffmpeg overlay fails
+                        shutil.copy2(src, dest)
+                else:
+                    shutil.copy2(src, dest)
+            else:
+                shutil.copy2(src, dest)
+        else:
+            shutil.copy2(src, dest)
     except OSError as e:
         raise HTTPException(status_code=500, detail=str(e))
 
@@ -73,6 +99,7 @@ def export_file(req: ExportRequest):
         conn.commit()
     finally:
         conn.close()
+    event_bus.emit("export_history", {"action": "exported", "id": export_id})
     return {"success": True, "id": export_id}
 
 
@@ -88,6 +115,7 @@ def record_export(req: ExportRecordRequest):
         conn.commit()
     finally:
         conn.close()
+    event_bus.emit("export_history", {"action": "recorded", "id": export_id})
     return {"success": True, "id": export_id}
 
 

backend/api/routers/gallery.py

@@ -0,0 +1,581 @@
+import os
+import json
+import uuid
+import time
+import asyncio
+import logging
+import subprocess
+from typing import Optional, List
+from pathlib import Path
+from fastapi import APIRouter, File, Form, UploadFile, HTTPException, Query
+from fastapi.responses import FileResponse, JSONResponse, RedirectResponse
+from pydantic import BaseModel
+
+from core.db import get_db
+from core.config import VOICES_DIR, OUTPUTS_DIR
+from core import event_bus
+
+logger = logging.getLogger("omnivoice.gallery")
+
+router = APIRouter()
+
+VOICE_GALLERY_DIR = Path(os.path.join(OUTPUTS_DIR, "voice_gallery"))
+VOICE_GALLERY_DIR.mkdir(parents=True, exist_ok=True)
+
+CATEGORIES = [
+    {
+        "id": "disney",
+        "name": "Disney",
+        "icon": "🎬",
+        "description": "Disney characters, Pixar, and animated films",
+    },
+    {
+        "id": "anime",
+        "name": "Anime",
+        "icon": "🎌",
+        "description": "Japanese anime characters",
+    },
+    {
+        "id": "marvel",
+        "name": "Marvel/DC",
+        "icon": "🦸",
+        "description": "Superhero movies and TV shows",
+    },
+    {
+        "id": "celebs",
+        "name": "Celebrities",
+        "icon": "⭐",
+        "description": "Famous actors and personalities",
+    },
+    {
+        "id": "politicians",
+        "name": "Politicians",
+        "icon": "🏛️",
+        "description": "World leaders and politicians",
+    },
+    {
+        "id": "news",
+        "name": "News Anchors",
+        "icon": "📰",
+        "description": "News broadcasters",
+    },
+    {
+        "id": "gaming",
+        "name": "Gaming",
+        "icon": "🎮",
+        "description": "Video game characters",
+    },
+    {
+        "id": "books",
+        "name": "Books/Movies",
+        "icon": "📚",
+        "description": "Literary and film characters",
+    },
+]
+
+
+class VoiceEntry(BaseModel):
+    id: str
+    name: str
+    character: str
+    category: str
+    source_type: str  # "youtube", "upload", "preset"
+    source_url: Optional[str] = None
+    audio_path: str
+    duration: float
+    description: Optional[str] = None
+    thumbnail: Optional[str] = None
+    tags: List[str] = []
+    created_at: float
+
+
+def _init_gallery_db():
+    """Initialize the voice gallery table."""
+    conn = get_db()
+    conn.execute("""
+        CREATE TABLE IF NOT EXISTS voice_gallery (
+            id TEXT PRIMARY KEY,
+            name TEXT NOT NULL,
+            character TEXT NOT NULL,
+            category TEXT NOT NULL,
+            source_type TEXT NOT NULL,
+            source_url TEXT,
+            audio_path TEXT NOT NULL,
+            duration REAL NOT NULL,
+            description TEXT,
+            thumbnail TEXT,
+            tags TEXT,
+            is_favorite INTEGER NOT NULL DEFAULT 0,
+            created_at REAL NOT NULL
+        )
+    """)
+    # Migration: add is_favorite column if missing (existing DBs)
+    try:
+        conn.execute("SELECT is_favorite FROM voice_gallery LIMIT 1")
+    except Exception:
+        conn.execute("ALTER TABLE voice_gallery ADD COLUMN is_favorite INTEGER NOT NULL DEFAULT 0")
+    conn.commit()
+    conn.close()
+
+
+@router.get("/gallery/categories")
+def list_categories():
+    """List all voice gallery categories."""
+    return CATEGORIES
+
+
+@router.get("/gallery/voices")
+def list_voices(
+    category: Optional[str] = Query(None, description="Filter by category"),
+    search: Optional[str] = Query(None, description="Search by name or character"),
+    limit: int = Query(50, ge=1, le=200),
+):
+    """List voices in the gallery, optionally filtered by category or search."""
+    conn = get_db()
+    query = "SELECT * FROM voice_gallery"
+    params = []
+    conditions = []
+
+    if category:
+        conditions.append("category = ?")
+        params.append(category)
+    if search:
+        conditions.append("(name LIKE ? OR character LIKE ? OR description LIKE ?)")
+        params.extend([f"%{search}%", f"%{search}%", f"%{search}%"])
+
+    if conditions:
+        query += " WHERE " + " AND ".join(conditions)
+    query += " ORDER BY created_at DESC LIMIT ?"
+    params.append(limit)
+
+    rows = conn.execute(query, params).fetchall()
+    conn.close()
+
+    results = []
+    for row in rows:
+        r = dict(row)
+        r["tags"] = json.loads(r.get("tags", "[]") or "[]")
+        results.append(r)
+    return results
+
+
+@router.get("/gallery/voices/{voice_id}")
+def get_voice(voice_id: str):
+    """Get a specific voice from the gallery."""
+    conn = get_db()
+    row = conn.execute(
+        "SELECT * FROM voice_gallery WHERE id = ?", (voice_id,)
+    ).fetchone()
+    conn.close()
+    if not row:
+        raise HTTPException(status_code=404, detail="Voice not found")
+    r = dict(row)
+    r["tags"] = json.loads(r.get("tags", "[]") or "[]")
+    return r
+
+
+@router.delete("/gallery/voices/{voice_id}")
+def delete_voice(voice_id: str):
+    """Delete a voice from the gallery."""
+    conn = get_db()
+    row = conn.execute(
+        "SELECT audio_path FROM voice_gallery WHERE id = ?", (voice_id,)
+    ).fetchone()
+    if not row:
+        conn.close()
+        raise HTTPException(status_code=404, detail="Voice not found")
+
+    audio_path = row["audio_path"]
+    if audio_path and os.path.exists(audio_path):
+        try:
+            os.remove(audio_path)
+        except Exception:
+            pass
+
+    conn.execute("DELETE FROM voice_gallery WHERE id = ?", (voice_id,))
+    conn.commit()
+    conn.close()
+    return {"success": True}
+
+
+@router.post("/gallery/search/youtube")
+async def search_youtube(
+    query: str = Query(..., description="Character or celebrity name to search"),
+    category: str = Query(..., description="Category to associate results with"),
+    max_results: int = Query(5, ge=1, le=20),
+):
+    """Search YouTube for character/celebrity clips using yt-dlp."""
+    try:
+        result = await asyncio.create_subprocess_exec(
+            "yt-dlp",
+            "--dump-json",
+            "--remote-components", "ejs:github",
+            f"ytsearch{max_results}:{query}",
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.PIPE,
+        )
+        stdout, stderr = await result.communicate()
+
+        if result.returncode != 0:
+            logger.error(f"yt-dlp search failed: {stderr.decode()}")
+            raise HTTPException(
+                status_code=500, detail=f"YouTube search failed: {stderr.decode()}"
+            )
+
+        lines = stdout.decode().strip().split("\n")
+        results = []
+        for line in lines:
+            if not line.strip():
+                continue
+            try:
+                data = json.loads(line)
+                results.append(
+                    {
+                        "title": data.get("title", ""),
+                        "video_id": data.get("id", ""),
+                        "duration": str(data.get("duration")) if data.get("duration") is not None else None,
+                        "thumbnail": data.get("thumbnail", None),
+                    }
+                )
+            except json.JSONDecodeError:
+                logger.warning(f"Failed to parse yt-dlp JSON line: {line}")
+
+        return {"results": results, "query": query, "category": category}
+    except FileNotFoundError:
+        raise HTTPException(status_code=500, detail="yt-dlp not installed")
+    except Exception as e:
+        logger.error(f"YouTube search error: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/gallery/download")
+async def download_youtube_clip(
+    video_url: str = Query(..., description="YouTube video URL"),
+    start_time: float = Query(0, ge=0, description="Start time in seconds"),
+    duration: float = Query(10, ge=1, le=30, description="Clip duration in seconds"),
+    character_name: str = Query(..., description="Character/celebrity name"),
+    category: str = Query(..., description="Category"),
+    description: str = Query("", description="Optional description"),
+):
+    """Download a clip from YouTube for voice cloning."""
+    voice_id = str(uuid.uuid4())[:8]
+    output_path = str(VOICE_GALLERY_DIR / f"{voice_id}.wav")
+    temp_path = str(VOICE_GALLERY_DIR / f"{voice_id}.%(ext)s")
+
+    try:
+        cmd = [
+            "yt-dlp",
+            "--remote-components", "ejs:github",
+            "-f",
+            "bestaudio",
+            "--download-sections",
+            f"*{start_time:.1f}-{start_time + duration:.1f}",
+            "-x",
+            "--audio-format",
+            "wav",
+            "--audio-quality",
+            "0",
+            "-o",
+            temp_path,
+            video_url,
+        ]
+
+        result = await asyncio.create_subprocess_exec(
+            *cmd,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.PIPE,
+        )
+        stdout, stderr = await result.communicate()
+
+        if result.returncode != 0:
+            logger.error(f"yt-dlp download failed: {stderr.decode()}")
+            raise HTTPException(
+                status_code=500, detail=f"Download failed: {stderr.decode()}"
+            )
+
+        # Find the downloaded file (yt-dlp replaces %s with actual extension)
+        downloaded_files = list(VOICE_GALLERY_DIR.glob(f"{voice_id}.*"))
+        if not downloaded_files:
+            raise HTTPException(status_code=500, detail="Downloaded file not found")
+
+        actual_path = downloaded_files[0]
+        # Rename to output_path
+        final_path = Path(output_path)
+        actual_path.rename(final_path)
+
+        conn = get_db()
+        conn.execute(
+            """
+            INSERT INTO voice_gallery 
+            (id, name, character, category, source_type, source_url, audio_path, duration, description, tags, created_at)
+            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+            (
+                voice_id,
+                character_name,
+                character_name,
+                category,
+                "youtube",
+                video_url,
+                output_path,
+                duration,
+                description,
+                json.dumps([character_name.lower(), category]),
+                time.time(),
+            ),
+        )
+        conn.commit()
+        conn.close()
+
+        return {
+            "success": True,
+            "voice_id": voice_id,
+            "audio_path": output_path,
+            "duration": duration,
+        }
+    except FileNotFoundError:
+        raise HTTPException(status_code=500, detail="yt-dlp not installed")
+    except Exception as e:
+        logger.error(f"Download error: {e}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+@router.post("/gallery/upload")
+async def upload_voice_clip(
+    name: str = Form(...),
+    character: str = Form(...),
+    category: str = Form(...),
+    description: str = Form(""),
+    audio: UploadFile = File(...),
+):
+    """Upload a voice clip directly to the gallery."""
+    voice_id = str(uuid.uuid4())[:8]
+    ext = os.path.splitext(audio.filename or ".wav")[1]
+    audio_path = str(VOICE_GALLERY_DIR / f"{voice_id}{ext}")
+
+    with open(audio_path, "wb") as f:
+        f.write(await audio.read())
+
+    try:
+        import soundfile as sf
+
+        info = sf.info(audio_path)
+        duration = info.frames / info.samplerate
+    except Exception:
+        duration = 10.0
+
+    conn = get_db()
+    conn.execute(
+        """
+        INSERT INTO voice_gallery 
+        (id, name, character, category, source_type, source_url, audio_path, duration, description, tags, created_at)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+    """,
+        (
+            voice_id,
+            name,
+            character,
+            category,
+            "upload",
+            None,
+            audio_path,
+            duration,
+            description,
+            json.dumps([character.lower(), category]),
+            time.time(),
+        ),
+    )
+    conn.commit()
+    conn.close()
+
+    return {
+        "id": voice_id,
+        "name": name,
+        "audio_path": audio_path,
+        "duration": duration,
+    }
+
+
+@router.post("/gallery/voices/{voice_id}/save-as-profile")
+async def save_voice_as_profile(
+    voice_id: str,
+    profile_name: str = Query(..., description="Name for the voice profile"),
+):
+    """Save a gallery voice as a voice profile for cloning."""
+    conn = get_db()
+    row = conn.execute(
+        "SELECT * FROM voice_gallery WHERE id = ?", (voice_id,)
+    ).fetchone()
+    conn.close()
+
+    if not row:
+        raise HTTPException(status_code=404, detail="Voice not found")
+
+    profile_id = str(uuid.uuid4())[:8]
+    import shutil
+
+    ext = os.path.splitext(row["audio_path"])[1]
+    new_audio_path = os.path.join(VOICES_DIR, f"{profile_id}{ext}")
+    shutil.copy(row["audio_path"], new_audio_path)
+
+    conn = get_db()
+    conn.execute(
+        """
+        INSERT INTO voice_profiles (id, name, ref_audio_path, ref_text, instruct, language, seed, created_at)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+    """,
+        (
+            profile_id,
+            profile_name,
+            f"{profile_id}{ext}",
+            row["description"] or "",
+            row["character"] or "",
+            "Auto",
+            None,
+            time.time(),
+        ),
+    )
+    conn.commit()
+    conn.close()
+    event_bus.emit("profiles", {"action": "created", "id": profile_id})
+
+    return {"profile_id": profile_id, "name": profile_name}
+
+
+@router.get("/gallery/voices/{voice_id}/preview")
+def preview_voice(voice_id: str):
+    """Get a voice clip for preview playback."""
+    conn = get_db()
+    row = conn.execute(
+        "SELECT audio_path FROM voice_gallery WHERE id = ?", (voice_id,)
+    ).fetchone()
+    conn.close()
+
+    if not row:
+        raise HTTPException(status_code=404, detail="Voice not found")
+
+    audio_path = row["audio_path"]
+
+    # Debug logging
+    is_absolute = os.path.isabs(audio_path)
+    path_exists = os.path.exists(audio_path) if audio_path else False
+
+    # If absolute path, serve directly or redirect
+    if is_absolute and path_exists:
+        # Get just the relative path from outputs dir
+        outputs_path = str(OUTPUTS_DIR)
+        if audio_path.startswith(outputs_path):
+            # Remove outputs_dir prefix to get relative path within outputs
+            rel_path = os.path.relpath(audio_path, outputs_path)
+            # The audio_path is like: /Users/user4/.../outputs/voice_gallery/file.wav
+            # rel_path becomes: voice_gallery/file.wav
+            # We want to serve from /audio/ so: /audio/voice_gallery/file.wav
+            return RedirectResponse(f"/audio/{rel_path}")
+        return FileResponse(audio_path, media_type="audio/wav")
+
+    raise HTTPException(
+        status_code=404,
+        detail=f"Audio not found: abs={is_absolute}, exists={path_exists}, path={audio_path}",
+    )
+
+
+# ── Library management endpoints ──────────────────────────────────────────
+
+@router.patch("/gallery/voices/{voice_id}")
+def update_voice(voice_id: str, body: dict):
+    """Update voice metadata — name, tags, is_favorite."""
+    conn = get_db()
+    row = conn.execute("SELECT id FROM voice_gallery WHERE id = ?", (voice_id,)).fetchone()
+    if not row:
+        conn.close()
+        raise HTTPException(status_code=404, detail="Voice not found")
+
+    updates = []
+    params = []
+    if "name" in body:
+        updates.append("name = ?")
+        params.append(body["name"])
+    if "tags" in body:
+        updates.append("tags = ?")
+        params.append(json.dumps(body["tags"]) if isinstance(body["tags"], list) else body["tags"])
+    if "is_favorite" in body:
+        updates.append("is_favorite = ?")
+        params.append(1 if body["is_favorite"] else 0)
+    if "description" in body:
+        updates.append("description = ?")
+        params.append(body["description"])
+
+    if not updates:
+        conn.close()
+        return {"success": True, "updated": []}
+
+    params.append(voice_id)
+    conn.execute(f"UPDATE voice_gallery SET {', '.join(updates)} WHERE id = ?", params)
+    conn.commit()
+    conn.close()
+    return {"success": True, "updated": list(body.keys())}
+
+
+@router.post("/gallery/voices/batch-delete")
+def batch_delete_voices(body: dict):
+    """Delete multiple voices by ID list."""
+    ids = body.get("ids", [])
+    if not ids:
+        return {"deleted": 0}
+
+    conn = get_db()
+    deleted = 0
+    for vid in ids:
+        row = conn.execute("SELECT audio_path FROM voice_gallery WHERE id = ?", (vid,)).fetchone()
+        if row:
+            audio_path = row["audio_path"]
+            if audio_path and os.path.exists(audio_path):
+                try:
+                    os.remove(audio_path)
+                except Exception:
+                    pass
+            conn.execute("DELETE FROM voice_gallery WHERE id = ?", (vid,))
+            deleted += 1
+    conn.commit()
+    conn.close()
+    return {"deleted": deleted}
+
+
+@router.post("/gallery/voices/{voice_id}/to-profile")
+def voice_to_profile(voice_id: str):
+    """Create a voice profile from a gallery clip."""
+    conn = get_db()
+    row = conn.execute("SELECT * FROM voice_gallery WHERE id = ?", (voice_id,)).fetchone()
+    if not row:
+        conn.close()
+        raise HTTPException(status_code=404, detail="Voice not found")
+
+    voice = dict(row)
+    audio_path = voice["audio_path"]
+    if not os.path.exists(audio_path):
+        conn.close()
+        raise HTTPException(status_code=404, detail="Audio file not found on disk")
+
+    import shutil
+    import uuid
+
+    profile_id = str(uuid.uuid4())[:8]
+    # Copy audio to voices dir
+    dest_filename = f"{profile_id}_gallery.wav"
+    dest_path = os.path.join(VOICES_DIR, dest_filename)
+    shutil.copy2(audio_path, dest_path)
+
+    import time
+    now = time.time()
+    conn.execute(
+        """INSERT INTO voice_profiles
+           (id, name, ref_audio_path, ref_text, instruct, seed, is_locked, locked_audio_path, created_at, updated_at)
+           VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
+        (profile_id, voice["name"], dest_filename, "", None, None, 0, None, now, now),
+    )
+    conn.commit()
+    conn.close()
+    event_bus.emit("profiles", {"action": "created", "id": profile_id})
+
+    return {"success": True, "profile_id": profile_id, "name": voice["name"]}
+

backend/api/routers/generation.py

@@ -17,6 +17,7 @@ from core.db import get_db, db_conn
 from core.config import OUTPUTS_DIR, VOICES_DIR
 from services.model_manager import get_model, _gpu_pool
 from services.audio_dsp import apply_mastering, normalize_audio
+from core import event_bus
 
 router = APIRouter()
 logger = logging.getLogger("omnivoice.generate")
@@ -155,6 +156,7 @@ async def generate_speech(
                  language or "Auto", instruct or "", resolved_profile_id,
                  audio_filename, audio_dur, gen_time, used_seed, time.time())
             )
+        event_bus.emit("generation_history", {"action": "created", "id": audio_id})
 
         buffer = io.BytesIO()
         torchaudio.save(buffer, audio_tensor, _model.sampling_rate, format="wav")
@@ -227,6 +229,7 @@ def clear_history():
                 with contextlib.suppress(OSError):
                     os.remove(p)
         conn.execute("DELETE FROM generation_history")
+    event_bus.emit("generation_history")
     return {"cleared": True}
 
 @router.delete("/history/{history_id}")
@@ -239,4 +242,5 @@ def delete_single_history(history_id: str):
                 with contextlib.suppress(OSError):
                     os.remove(p)
         conn.execute("DELETE FROM generation_history WHERE id=?", (history_id,))
+    event_bus.emit("generation_history", {"action": "deleted", "id": history_id})
     return {"deleted": True}

backend/api/routers/profiles.py

@@ -9,6 +9,7 @@ from pydantic import BaseModel
 
 from core.db import get_db, db_conn
 from core.config import VOICES_DIR, OUTPUTS_DIR
+from core import event_bus
 
 router = APIRouter()
 
@@ -50,6 +51,7 @@ async def create_profile(
     )
     conn.commit()
     conn.close()
+    event_bus.emit("profiles", {"action": "created", "id": profile_id})
     return {"id": profile_id, "name": name}
 
 @router.get("/profiles/{profile_id}")
@@ -99,6 +101,7 @@ def update_profile(profile_id: str, patch: ProfileUpdate):
         row = conn.execute(
             "SELECT * FROM voice_profiles WHERE id = ?", (profile_id,),
         ).fetchone()
+    event_bus.emit("profiles", {"action": "updated", "id": profile_id})
     return dict(row)
 
 
@@ -200,6 +203,7 @@ async def lock_profile(
     )
     conn.commit()
     conn.close()
+    event_bus.emit("profiles", {"action": "locked", "id": profile_id})
     return {"locked": True, "profile_id": profile_id, "locked_audio_path": locked_filename}
 
 @router.post("/profiles/{profile_id}/unlock")
@@ -224,6 +228,7 @@ async def unlock_profile(profile_id: str):
     )
     conn.commit()
     conn.close()
+    event_bus.emit("profiles", {"action": "unlocked", "id": profile_id})
     return {"unlocked": True, "profile_id": profile_id}
 
 @router.delete("/profiles/{profile_id}")
@@ -239,4 +244,5 @@ def delete_profile(profile_id: str):
     conn.execute("DELETE FROM voice_profiles WHERE id=?", (profile_id,))
     conn.commit()
     conn.close()
+    event_bus.emit("profiles", {"action": "deleted", "id": profile_id})
     return {"deleted": profile_id}

backend/api/routers/projects.py

@@ -4,6 +4,7 @@ import json
 from fastapi import APIRouter, HTTPException
 
 from core.db import get_db
+from core import event_bus
 from schemas.requests import ProjectSaveRequest
 
 router = APIRouter()
@@ -45,6 +46,7 @@ async def create_project(req: ProjectSaveRequest):
     )
     conn.commit()
     conn.close()
+    event_bus.emit("projects", {"action": "created", "id": project_id})
     return {"id": project_id, "name": req.name, "created_at": now}
 
 @router.put("/projects/{project_id}")
@@ -61,6 +63,7 @@ async def update_project(project_id: str, req: ProjectSaveRequest):
     )
     conn.commit()
     conn.close()
+    event_bus.emit("projects", {"action": "updated", "id": project_id})
     return {"id": project_id, "name": req.name, "updated_at": now}
 
 @router.delete("/projects/{project_id}")
@@ -69,4 +72,5 @@ async def delete_project(project_id: str):
     conn.execute("DELETE FROM studio_projects WHERE id=?", (project_id,))
     conn.commit()
     conn.close()
+    event_bus.emit("projects", {"action": "deleted", "id": project_id})
     return {"deleted": project_id}

backend/api/routers/setup.py.bak

@@ -79,24 +79,16 @@ KNOWN_MODELS = [
         "label": "Whisper large-v3 (MLX — optional mac-ARM speedup)",
         "role": "ASR",
         "size_gb": 3.0,
-        # Optional everywhere — only loadable on mac-ARM dev installs. The
-        # frozen .app can't load mlx reliably (nanobind duplicate-registration
-        # aborts on first mlx.core touch), and mlx doesn't exist on
-        # Linux/Windows/mac-Intel at all. Users on a mac-ARM dev install can
-        # opt in from Settings → Models for ~10-20% lower latency vs faster-
-        # whisper int8 on large-v3.
         "required": False,
+        "platforms": ["darwin-arm64"],
     },
     {
         "repo_id": "openai/whisper-large-v3",
         "label": "Whisper large-v3 (PyTorch — last-resort fallback)",
         "role": "ASR",
         "size_gb": 3.1,
-        # Optional fallback. The faster-whisper repo above is the primary
-        # ASR; openai/whisper-large-v3 is only needed if the user explicitly
-        # picks pytorch-whisper in Settings (CUDA-heavy workflows or when
-        # faster-whisper breaks on a specific host).
         "required": False,
+        "platforms": ["cuda"],
     },
     {
         "repo_id": "mlx-community/whisper-tiny-mlx",
@@ -104,6 +96,7 @@ KNOWN_MODELS = [
         "role": "ASR",
         "size_gb": 0.08,
         "required": False,
+        "platforms": ["darwin-arm64"],
     },
     {
         "repo_id": "pyannote/speaker-diarization-3.1",
@@ -114,8 +107,8 @@ KNOWN_MODELS = [
         "note": "Needs an HF_TOKEN with license accepted.",
     },
     {
-        "repo_id": "OpenMOSS-Team/MOSS-TTS-Nano",
-        "label": "MOSS-TTS-Nano (20 langs, CPU-realtime)",
+        "repo_id": "OpenMOSS-Team/MOSS-TTS-Nano-100M",
+        "label": "MOSS-TTS-Nano 100M (20 langs, CPU-realtime)",
         "role": "TTS",
         "size_gb": 0.4,
         "required": False,
@@ -141,6 +134,7 @@ KNOWN_MODELS = [
         "size_gb": 0.15,
         "required": False,
         "note": "Apple Silicon only — via mlx-audio backend.",
+        "platforms": ["darwin-arm64"],
     },
     {
         "repo_id": "mlx-community/csm-1b-8bit",
@@ -149,14 +143,16 @@ KNOWN_MODELS = [
         "size_gb": 1.1,
         "required": False,
         "note": "Apple Silicon only — via mlx-audio backend.",
+        "platforms": ["darwin-arm64"],
     },
     {
-        "repo_id": "mlx-community/Qwen3-TTS-1.7B-4bit",
+        "repo_id": "mlx-community/Qwen3-TTS-12Hz-1.7B-VoiceDesign-4bit",
         "label": "Qwen3-TTS 1.7B 4bit (voice design, mlx-audio)",
         "role": "TTS",
         "size_gb": 1.4,
         "required": False,
         "note": "Apple Silicon only — via mlx-audio backend.",
+        "platforms": ["darwin-arm64"],
     },
     {
         "repo_id": "mlx-community/Dia-1.6B",
@@ -165,20 +161,66 @@ KNOWN_MODELS = [
         "size_gb": 3.2,
         "required": False,
         "note": "Apple Silicon only — via mlx-audio backend.",
+        "platforms": ["darwin-arm64"],
     },
     {
-        "repo_id": "mlx-community/OuteTTS-0.3-500M",
-        "label": "OuteTTS 0.3 500M (voice clone, mlx-audio)",
+        "repo_id": "mlx-community/Llama-OuteTTS-1.0-1B-4bit",
+        "label": "Llama-OuteTTS 1.0 1B 4bit (voice clone, mlx-audio)",
         "role": "TTS",
-        "size_gb": 1.0,
+        "size_gb": 0.8,
         "required": False,
         "note": "Apple Silicon only — via mlx-audio backend.",
+        "platforms": ["darwin-arm64"],
+    },
+    {
+        "repo_id": "mlx-community/Chatterbox-TTS-4bit",
+        "label": "Chatterbox TTS 4bit (mlx-audio)",
+        "role": "TTS",
+        "size_gb": 0.5,
+        "required": False,
+        "note": "Apple Silicon only — via mlx-audio backend.",
+        "platforms": ["darwin-arm64"],
+    },
+    {
+        "repo_id": "mlx-community/MeloTTS-English-v3-MLX",
+        "label": "MeloTTS English v3 (mlx-audio)",
+        "role": "TTS",
+        "size_gb": 0.2,
+        "required": False,
+        "note": "Apple Silicon only — via mlx-audio backend.",
+        "platforms": ["darwin-arm64"],
     },
 ]
 # Back-compat tuple view for code that expects (repo_id, label) pairs.
 REQUIRED_MODELS = [(m["repo_id"], m["label"]) for m in KNOWN_MODELS if m["required"]]
 
 
+def _current_platform_tags() -> list[str]:
+    """Return platform tags that the current host supports.
+
+    Models declare a `platforms` list (e.g. ["darwin-arm64", "cuda"]). A model
+    is supported if its list intersects with the host's tags, or if the model
+    has no `platforms` key (= cross-platform)."""
+    tags = [sys.platform]                             # "linux", "darwin", "win32"
+    arch = _platform.machine()
+    tags.append(f"{sys.platform}-{arch}")             # "darwin-arm64", "linux-x86_64"
+    try:
+        import torch
+        if torch.cuda.is_available():
+            tags.append("cuda")
+    except Exception:
+        pass
+    return tags
+
+
+def _model_supported(model: dict) -> bool:
+    """Check if a model is supported on the current platform."""
+    plats = model.get("platforms")
+    if not plats:
+        return True  # no restriction → cross-platform
+    return bool(set(plats) & set(_current_platform_tags()))
+
+
 def _is_cached(repo_id: str) -> bool:
     """Best-effort check: does HF have this repo in its cache on disk?
     We don't validate the specific file set — presence of the repo dir is
@@ -311,11 +353,13 @@ def list_models():
             "installed": cached is not None and cached["size_on_disk"] > 0,
             "size_on_disk_bytes": cached["size_on_disk"] if cached else 0,
             "nb_files": cached["nb_files"] if cached else 0,
+            "supported": _model_supported(m),
         })
     return {
         "models": out,
         "total_installed_bytes": sum(m["size_on_disk_bytes"] for m in out),
         "hf_cache_dir": _hf_cache_dir(),
+        "platform_tags": _current_platform_tags(),
     }
 
 
@@ -342,13 +386,77 @@ async def install_model(req: InstallModelRequest):
     loop = asyncio.get_event_loop()
 
     def _do():
+        token = hf_progress.current_repo_id.set(req.repo_id)
+        hf_progress.emit({
+            "repo_id": req.repo_id,
+            "filename": req.repo_id,
+            "downloaded": 0, "total": 0, "pct": 0.0,
+            "phase": "install_start",
+        })
         try:
             from huggingface_hub import snapshot_download
+            from huggingface_hub.utils import (
+                HfHubHTTPError,
+                LocalEntryNotFoundError,
+            )
             logger.info("model install starting: %s", req.repo_id)
-            snapshot_download(repo_id=req.repo_id)
+            # On Windows, NTFS symlinks require Developer Mode or Admin —
+            # most first-run installs don't have either.  The global env var
+            # HF_HUB_DISABLE_SYMLINKS=1 (set in main.py) covers implicit
+            # downloads, but we also pass the kwarg here as a belt-and-braces
+            # guard for older huggingface_hub versions that don't read the var.
+            dl_kwargs: dict = {"repo_id": req.repo_id}
+            if sys.platform == "win32":
+                dl_kwargs["local_dir_use_symlinks"] = False
+
+            # Resume on transient network failures. snapshot_download writes
+            # `.incomplete` shards into the HF cache and resumes from them on
+            # the next call automatically — re-invoking with the same args
+            # picks up where it left off, so each retry only re-fetches what's
+            # missing.
+            _max_attempts = 5
+            _attempt = 0
+            while True:
+                _attempt += 1
+                try:
+                    snapshot_download(**dl_kwargs)
+                    break
+                except (HfHubHTTPError, LocalEntryNotFoundError, OSError) as net_err:
+                    if _attempt >= _max_attempts:
+                        raise
+                    _backoff = min(30, 2 ** _attempt)
+                    logger.warning(
+                        "model install %s: attempt %d/%d failed (%s); retry in %ds",
+                        req.repo_id, _attempt, _max_attempts, net_err, _backoff,
+                    )
+                    hf_progress.emit({
+                        "repo_id": req.repo_id,
+                        "filename": req.repo_id,
+                        "downloaded": 0, "total": 0, "pct": 0.0,
+                        "phase": "install_retry",
+                        "attempt": _attempt,
+                        "error": str(net_err),
+                    })
+                    import time as _t
+                    _t.sleep(_backoff)
             logger.info("model install done: %s", req.repo_id)
+            hf_progress.emit({
+                "repo_id": req.repo_id,
+                "filename": req.repo_id,
+                "downloaded": 0, "total": 0, "pct": 1.0,
+                "phase": "install_done",
+            })
         except Exception as e:
             logger.warning("model install failed for %s: %s", req.repo_id, e)
+            hf_progress.emit({
+                "repo_id": req.repo_id,
+                "filename": req.repo_id,
+                "downloaded": 0, "total": 0, "pct": 0.0,
+                "phase": "install_error",
+                "error": str(e),
+            })
+        finally:
+            hf_progress.current_repo_id.reset(token)
 
     # Non-blocking — client polls /models or listens on the SSE.
     loop.create_task(asyncio.to_thread(_do))
@@ -359,6 +467,12 @@ async def install_model(req: InstallModelRequest):
 def delete_model(repo_id: str):
     """Remove every cached revision of a repo from the HF cache. Frees disk
     + lets the user re-install a fresh copy via POST /models/install."""
+    hf_progress.emit({
+        "repo_id": repo_id,
+        "filename": repo_id,
+        "downloaded": 0, "total": 0, "pct": 0.0,
+        "phase": "delete_start",
+    })
     try:
         from huggingface_hub import scan_cache_dir
         info = scan_cache_dir()
@@ -377,6 +491,13 @@ def delete_model(repo_id: str):
             )
         strategy = info.delete_revisions(*commits)
         strategy.execute()
+        hf_progress.emit({
+            "repo_id": repo_id,
+            "filename": repo_id,
+            "downloaded": 0, "total": 0, "pct": 1.0,
+            "phase": "delete_done",
+            "freed_bytes": strategy.expected_freed_size,
+        })
         return {
             "deleted": True,
             "repo_id": repo_id,
@@ -666,6 +787,20 @@ def preflight():
                    "Install system ffmpeg (includes ffprobe) to enable it.",
         })
 
+    # ── yt-dlp (warn — gallery needs it)
+    yt_dlp_path = _shutil.which("yt-dlp")
+    if yt_dlp_path:
+        checks.append({
+            "id": "yt-dlp", "label": "yt-dlp", "status": "pass",
+            "detail": yt_dlp_path, "fix": None,
+        })
+    else:
+        checks.append({
+            "id": "yt-dlp", "label": "yt-dlp", "status": "warn",
+            "detail": "Not found in system PATH.",
+            "fix": "YouTube clip downloads in Voice Gallery will fail. Download the standalone binary from https://github.com/yt-dlp/yt-dlp/releases and place it in your PATH.",
+        })
+
     # ── GPU + compute backend
     gpu = _detect_gpu()
     if gpu["vendor"] == "apple" and gpu["available"]:

backend/api/routers/setup/__init__.py

@@ -0,0 +1,21 @@
+"""Setup package — modular replacement for the monolithic ``setup.py``.
+
+Re-exports a single ``router`` that includes all three sub-routers so
+``main.py`` can continue doing ``from api.routers import setup`` and
+``app.include_router(setup.router)`` without changes.
+"""
+from __future__ import annotations
+
+from fastapi import APIRouter
+
+from .models import router as _models_router
+from .wizard import router as _wizard_router
+from .download import router as _download_router
+
+# Re-export commonly used symbols for backward compatibility.
+from .models import KNOWN_MODELS, REQUIRED_MODELS, hf_cache_dir, is_cached  # noqa: F401
+
+router = APIRouter()
+router.include_router(_models_router)
+router.include_router(_wizard_router)
+router.include_router(_download_router)

backend/api/routers/setup/download.py

@@ -0,0 +1,216 @@
+"""Model download and deletion endpoints.
+
+Extracted from the monolithic ``setup.py``.
+
+- ``GET  /setup/download-stream``  — SSE for HF tqdm progress
+- ``POST /models/install``         — start background model download
+- ``DELETE /models/{repo_id}``     — remove cached model from disk
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import sys
+
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+
+from utils import hf_progress
+from .models import KNOWN_MODELS, invalidate_cache
+
+logger = logging.getLogger("omnivoice.setup.download")
+router = APIRouter()
+
+
+# ── SSE Download Stream ───────────────────────────────────────────────────
+
+def _safe_put(queue: asyncio.Queue, event) -> None:
+    """Non-blocking enqueue — drop oldest on overflow rather than block."""
+    try:
+        queue.put_nowait(event)
+    except asyncio.QueueFull:
+        try:
+            queue.get_nowait()
+            queue.put_nowait(event)
+        except Exception:
+            pass
+
+
+@router.get("/setup/download-stream")
+async def setup_download_stream():
+    """SSE: forward every HuggingFace download tqdm update as a JSON event."""
+    queue: asyncio.Queue = asyncio.Queue(maxsize=512)
+    loop = asyncio.get_event_loop()
+
+    def listener(event):
+        try:
+            loop.call_soon_threadsafe(_safe_put, queue, event)
+        except RuntimeError:
+            pass
+
+    listener_id = hf_progress.register_listener(listener)
+
+    async def gen():
+        try:
+            while True:
+                try:
+                    event = await asyncio.wait_for(queue.get(), timeout=30.0)
+                except asyncio.TimeoutError:
+                    yield ": keepalive\n\n"
+                    continue
+                yield f"data: {json.dumps(event)}\n\n"
+        finally:
+            hf_progress.unregister_listener(listener_id)
+
+    return StreamingResponse(
+        gen(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache, no-transform",
+            "X-Accel-Buffering": "no",
+        },
+    )
+
+
+# ── Install ────────────────────────────────────────────────────────────────
+
+class InstallModelRequest(BaseModel):
+    repo_id: str
+
+
+@router.post("/models/install")
+async def install_model(req: InstallModelRequest):
+    """Download one HF repo snapshot; progress goes through the shared
+    ``/setup/download-stream`` SSE feed."""
+    if req.repo_id not in [m["repo_id"] for m in KNOWN_MODELS]:
+        raise HTTPException(
+            status_code=400,
+            detail=(
+                f"Unknown model: {req.repo_id!r}. Known: "
+                + ", ".join(m["repo_id"] for m in KNOWN_MODELS)
+            ),
+        )
+    loop = asyncio.get_event_loop()
+
+    def _do():
+        token = hf_progress.current_repo_id.set(req.repo_id)
+        hf_progress.emit({
+            "repo_id": req.repo_id,
+            "filename": req.repo_id,
+            "downloaded": 0, "total": 0, "pct": 0.0,
+            "phase": "install_start",
+        })
+        try:
+            from huggingface_hub import snapshot_download
+            from huggingface_hub.utils import (
+                HfHubHTTPError,
+                LocalEntryNotFoundError,
+            )
+            logger.info("model install starting: %s", req.repo_id)
+            dl_kwargs: dict = {"repo_id": req.repo_id}
+            if sys.platform == "win32":
+                dl_kwargs["local_dir_use_symlinks"] = False
+
+            _max_attempts = 5
+            _attempt = 0
+            while True:
+                _attempt += 1
+                try:
+                    snapshot_download(**dl_kwargs)
+                    break
+                except (HfHubHTTPError, LocalEntryNotFoundError, OSError) as net_err:
+                    if _attempt >= _max_attempts:
+                        raise
+                    _backoff = min(30, 2 ** _attempt)
+                    logger.warning(
+                        "model install %s: attempt %d/%d failed (%s); retry in %ds",
+                        req.repo_id, _attempt, _max_attempts, net_err, _backoff,
+                    )
+                    hf_progress.emit({
+                        "repo_id": req.repo_id,
+                        "filename": req.repo_id,
+                        "downloaded": 0, "total": 0, "pct": 0.0,
+                        "phase": "install_retry",
+                        "attempt": _attempt,
+                        "error": str(net_err),
+                    })
+                    import time as _t
+                    _t.sleep(_backoff)
+            logger.info("model install done: %s", req.repo_id)
+            hf_progress.emit({
+                "repo_id": req.repo_id,
+                "filename": req.repo_id,
+                "downloaded": 0, "total": 0, "pct": 1.0,
+                "phase": "install_done",
+            })
+            invalidate_cache()
+        except Exception as e:
+            logger.warning("model install failed for %s: %s", req.repo_id, e)
+            hf_progress.emit({
+                "repo_id": req.repo_id,
+                "filename": req.repo_id,
+                "downloaded": 0, "total": 0, "pct": 0.0,
+                "phase": "install_error",
+                "error": str(e),
+            })
+        finally:
+            hf_progress.current_repo_id.reset(token)
+
+    loop.create_task(asyncio.to_thread(_do))
+    return {"status": "install_started", "repo_id": req.repo_id}
+
+
+# ── Delete ─────────────────────────────────────────────────────────────────
+
+@router.delete("/models/{repo_id:path}")
+def delete_model(repo_id: str):
+    """Remove every cached revision of a repo from the HF cache."""
+    hf_progress.emit({
+        "repo_id": repo_id,
+        "filename": repo_id,
+        "downloaded": 0, "total": 0, "pct": 0.0,
+        "phase": "delete_start",
+    })
+    try:
+        from huggingface_hub import scan_cache_dir
+        info = scan_cache_dir()
+        commits = [
+            rev.commit_hash
+            for entry in info.repos if entry.repo_id == repo_id
+            for rev in entry.revisions
+        ]
+        if not commits:
+            raise HTTPException(
+                status_code=404,
+                detail=(
+                    f"Model {repo_id!r} isn't installed. Nothing to delete — "
+                    "run POST /models/install first if you want a fresh download."
+                ),
+            )
+        strategy = info.delete_revisions(*commits)
+        strategy.execute()
+        hf_progress.emit({
+            "repo_id": repo_id,
+            "filename": repo_id,
+            "downloaded": 0, "total": 0, "pct": 1.0,
+            "phase": "delete_done",
+            "freed_bytes": strategy.expected_freed_size,
+        })
+        invalidate_cache()
+        return {
+            "deleted": True,
+            "repo_id": repo_id,
+            "freed_bytes": strategy.expected_freed_size,
+        }
+    except HTTPException:
+        raise
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=(
+                f"Could not delete {repo_id}: {e}. "
+                "Close any process using the model (e.g. the app's main dub job) and retry."
+            ),
+        )

backend/api/routers/setup/models.py

@@ -0,0 +1,317 @@
+"""Model catalog, platform detection, and cache introspection.
+
+Extracted from the monolithic ``setup.py`` to keep concerns separate:
+- ``KNOWN_MODELS`` loaded from ``config/models.yaml``
+- ``GET /models`` endpoint (with 10 s response cache)
+- ``GET /setup/recommendations`` device-aware preset endpoint
+- ``ModelCatalog`` dependency for use with ``Depends()``
+"""
+from __future__ import annotations
+
+import logging
+import os
+import platform as _platform
+import sys
+import time
+from pathlib import Path
+from typing import Optional
+
+from fastapi import APIRouter, Depends
+
+logger = logging.getLogger("omnivoice.setup.models")
+router = APIRouter()
+
+# ── Model Catalog (loaded from YAML) ──────────────────────────────────────
+
+_YAML_PATH = Path(__file__).resolve().parents[3] / "config" / "models.yaml"
+
+
+def _load_models_from_yaml() -> list[dict]:
+    """Load model catalog from config/models.yaml.
+
+    Falls back to an empty list if the file is missing or unreadable.
+    The YAML file is read once at import time — restart to pick up edits.
+    """
+    try:
+        import yaml  # PyYAML is already a transitive dep of huggingface_hub
+        with open(_YAML_PATH, "r", encoding="utf-8") as f:
+            data = yaml.safe_load(f)
+        models = data.get("models", [])
+        logger.info("Loaded %d models from %s", len(models), _YAML_PATH)
+        return models
+    except FileNotFoundError:
+        logger.warning("models.yaml not found at %s — using empty catalog", _YAML_PATH)
+        return []
+    except Exception as e:
+        logger.error("Failed to load models.yaml: %s — using empty catalog", e)
+        return []
+
+
+KNOWN_MODELS = _load_models_from_yaml()
+
+# Back-compat tuple view for code that expects (repo_id, label) pairs.
+REQUIRED_MODELS = [(m["repo_id"], m["label"]) for m in KNOWN_MODELS if m.get("required")]
+
+
+# ── Dependency Injection ───────────────────────────────────────────────────
+# Use `catalog: ModelCatalog = Depends(get_model_catalog)` in endpoint params
+# for testable, mockable access to the model registry.
+
+class ModelCatalog:
+    """Injectable service wrapping the model catalog + cache scanner."""
+
+    def __init__(self, models: list[dict] | None = None):
+        self.models = models if models is not None else KNOWN_MODELS
+        self._by_id = {m["repo_id"]: m for m in self.models}
+        self._required = [(m["repo_id"], m["label"]) for m in self.models if m.get("required")]
+
+    def get(self, repo_id: str) -> dict | None:
+        return self._by_id.get(repo_id)
+
+    @property
+    def required(self) -> list[tuple[str, str]]:
+        return self._required
+
+    @property
+    def all(self) -> list[dict]:
+        return self.models
+
+    def supported_on_host(self, model: dict) -> bool:
+        return _model_supported(model)
+
+
+# Singleton — shared across all requests.
+_catalog = ModelCatalog()
+
+
+def get_model_catalog() -> ModelCatalog:
+    """FastAPI dependency — inject with ``Depends(get_model_catalog)``."""
+    return _catalog
+
+
+# ── Platform Detection ─────────────────────────────────────────────────────
+
+def _current_platform_tags() -> list[str]:
+    """Return platform tags that the current host supports."""
+    tags = [sys.platform]
+    arch = _platform.machine()
+    tags.append(f"{sys.platform}-{arch}")
+    try:
+        import torch
+        if torch.cuda.is_available():
+            tags.append("cuda")
+    except Exception:
+        pass
+    return tags
+
+
+def _model_supported(model: dict) -> bool:
+    """Check if a model is supported on the current platform."""
+    plats = model.get("platforms")
+    if not plats:
+        return True
+    return bool(set(plats) & set(_current_platform_tags()))
+
+
+# ── HF Cache Helpers ───────────────────────────────────────────────────────
+
+def hf_cache_dir() -> str:
+    return (
+        os.environ.get("HF_HUB_CACHE")
+        or os.environ.get("HUGGINGFACE_HUB_CACHE")
+        or os.environ.get("HF_HOME")
+        or os.path.expanduser("~/.cache/huggingface")
+    )
+
+
+def is_cached(repo_id: str) -> bool:
+    """Best-effort check: does HF have this repo in its cache on disk?"""
+    try:
+        from huggingface_hub import scan_cache_dir
+        info = scan_cache_dir()
+        for entry in info.repos:
+            if entry.repo_id == repo_id and entry.size_on_disk > 0:
+                return True
+        return False
+    except Exception as e:
+        logger.debug("scan_cache_dir failed: %s", e)
+        return False
+
+
+# ── Response Cache ─────────────────────────────────────────────────────────
+# Simple TTL dict cache to avoid re-scanning the HF cache directory on every
+# frontend poll.  Entries expire after ``_CACHE_TTL`` seconds.
+
+_CACHE_TTL = 10.0  # seconds
+_cache: dict[str, tuple[float, object]] = {}
+
+
+def _cached(key: str, ttl: float = _CACHE_TTL):
+    """Return cached value if still valid, else None."""
+    entry = _cache.get(key)
+    if entry and (time.monotonic() - entry[0]) < ttl:
+        return entry[1]
+    return None
+
+
+def _set_cache(key: str, value: object) -> None:
+    _cache[key] = (time.monotonic(), value)
+
+
+def invalidate_cache() -> None:
+    """Called after install/delete to bust the models cache."""
+    _cache.clear()
+
+
+# ── Endpoints ──────────────────────────────────────────────────────────────
+
+@router.get("/models")
+def list_models():
+    """Catalogue every known model + its on-disk install state.
+
+    Uses a 10 s response cache to avoid repeated ``scan_cache_dir()`` disk
+    walks when the frontend polls.
+    """
+    cached_response = _cached("models")
+    if cached_response is not None:
+        return cached_response
+
+    cached_by_repo: dict[str, dict] = {}
+    try:
+        from huggingface_hub import scan_cache_dir
+        info = scan_cache_dir()
+        for entry in info.repos:
+            cached_by_repo[entry.repo_id] = {
+                "size_on_disk": entry.size_on_disk,
+                "last_accessed": entry.last_accessed,
+                "nb_files": entry.nb_files,
+            }
+    except Exception as e:
+        logger.warning("scan_cache_dir failed: %s", e)
+
+    out = []
+    for m in KNOWN_MODELS:
+        cached = cached_by_repo.get(m["repo_id"])
+        out.append({
+            **m,
+            "installed": cached is not None and cached["size_on_disk"] > 0,
+            "size_on_disk_bytes": cached["size_on_disk"] if cached else 0,
+            "nb_files": cached["nb_files"] if cached else 0,
+            "supported": _model_supported(m),
+        })
+    response = {
+        "models": out,
+        "total_installed_bytes": sum(m["size_on_disk_bytes"] for m in out),
+        "hf_cache_dir": hf_cache_dir(),
+        "platform_tags": _current_platform_tags(),
+    }
+    _set_cache("models", response)
+    return response
+
+
+@router.get("/setup/recommendations")
+def recommendations():
+    """Return a curated model preset for the caller's device + architecture."""
+    is_mac_arm = sys.platform == "darwin" and _platform.machine() == "arm64"
+    is_mac_intel = sys.platform == "darwin" and _platform.machine() == "x86_64"
+    is_linux = sys.platform.startswith("linux")
+    is_windows = sys.platform == "win32"
+
+    has_cuda = False
+    try:
+        import torch
+        has_cuda = bool(torch.cuda.is_available())
+    except Exception:
+        pass
+
+    # Device label — used as the card title.
+    if is_mac_arm:
+        device_label = f"Apple Silicon ({_platform.machine()})"
+    elif is_mac_intel:
+        device_label = "macOS Intel (x86_64)"
+    elif is_windows:
+        device_label = "Windows x64" + (" + CUDA" if has_cuda else "")
+    elif is_linux:
+        device_label = "Linux x64" + (" + CUDA" if has_cuda else "")
+    else:
+        device_label = f"{sys.platform} / {_platform.machine()}"
+
+    # Pick the preset for this device.
+    if is_mac_arm:
+        recommended_ids = [
+            "k2-fsa/OmniVoice",
+            "Systran/faster-whisper-large-v3",
+            "mlx-community/whisper-large-v3-mlx",
+            "mlx-community/Kokoro-82M-bf16",
+            "KittenML/kitten-tts-mini-0.8",
+        ]
+        rationale = (
+            "Apple Silicon gets the full stack: OmniVoice for multilingual clone + "
+            "WhisperX (faster-whisper weights) for cross-platform ASR + MLX-Whisper "
+            "for the Apple-optimised speedup + Kokoro (mlx-audio) for fast local "
+            "English + KittenTTS as a CPU-realtime backup."
+        )
+    else:
+        recommended_ids = [
+            "k2-fsa/OmniVoice",
+            "Systran/faster-whisper-large-v3",
+            "KittenML/kitten-tts-mini-0.8",
+        ]
+        if has_cuda:
+            recommended_ids.append("openai/whisper-large-v3")
+            rationale = (
+                "Cross-platform stack + pytorch-whisper as a CUDA-accelerated "
+                "ASR fallback. MLX / mlx-audio are Apple-Silicon-only and don't "
+                "apply here."
+            )
+        else:
+            rationale = (
+                "Cross-platform stack: OmniVoice (multilingual clone) + WhisperX "
+                "(faster-whisper ASR) + KittenTTS (English turbo, CPU-realtime). "
+                "Clean install, every model runs on CPU."
+            )
+
+    known_by_id = {m["repo_id"]: m for m in KNOWN_MODELS}
+    cached_ids: set[str] = set()
+    try:
+        from huggingface_hub import scan_cache_dir
+        info = scan_cache_dir()
+        cached_ids = {
+            entry.repo_id for entry in info.repos if entry.size_on_disk > 0
+        }
+    except Exception:
+        pass
+
+    entries = []
+    for rid in recommended_ids:
+        meta = known_by_id.get(rid, {})
+        entries.append({
+            "repo_id": rid,
+            "label": meta.get("label", rid),
+            "role": meta.get("role", ""),
+            "size_gb": meta.get("size_gb", 0),
+            "required": bool(meta.get("required", False)),
+            "note": meta.get("note"),
+            "installed": rid in cached_ids,
+        })
+
+    to_download_gb = sum(e["size_gb"] for e in entries if not e["installed"])
+    all_installed = all(e["installed"] for e in entries)
+
+    return {
+        "device": {
+            "os": sys.platform,
+            "arch": _platform.machine(),
+            "is_mac_arm": is_mac_arm,
+            "is_mac_intel": is_mac_intel,
+            "is_linux": is_linux,
+            "is_windows": is_windows,
+            "has_cuda": has_cuda,
+            "label": device_label,
+        },
+        "rationale": rationale,
+        "models": entries,
+        "download_gb_remaining": round(to_download_gb, 2),
+        "total_gb": round(sum(e["size_gb"] for e in entries), 2),
+        "all_installed": all_installed,
+    }

backend/api/routers/setup/wizard.py

@@ -0,0 +1,402 @@
+"""First-run wizard endpoints — status, preflight, and warmup.
+
+Extracted from the monolithic ``setup.py``.
+
+- ``GET /setup/status``       — missing-model gate for boot screen
+- ``GET /setup/preflight``    — system health check (OS, RAM, GPU, ffmpeg…)
+- ``POST /setup/warmup``      — background model pre-load
+"""
+from __future__ import annotations
+
+import asyncio
+import logging
+import os
+import platform as _platform
+import shutil as _shutil
+import sys
+
+from fastapi import APIRouter
+
+from api.schemas import SetupStatusResponse, PreflightResponse
+from .models import REQUIRED_MODELS, hf_cache_dir, is_cached
+
+logger = logging.getLogger("omnivoice.setup.wizard")
+router = APIRouter()
+
+MIN_FREE_GB = 10
+
+
+def _disk_free_gb(path: str) -> float:
+    try:
+        return _shutil.disk_usage(path).free / (1024 ** 3)
+    except Exception:
+        return 0.0
+
+
+# ── Setup Status ───────────────────────────────────────────────────────────
+
+@router.get("/setup/status", response_model=SetupStatusResponse)
+def setup_status():
+    """Snapshot the setup state so the client can pick its boot screen."""
+    missing = [
+        {"repo_id": rid, "label": label}
+        for (rid, label) in REQUIRED_MODELS
+        if not is_cached(rid)
+    ]
+    cache = hf_cache_dir()
+    free_gb = _disk_free_gb(cache)
+    return {
+        "models_ready": len(missing) == 0,
+        "missing": missing,
+        "hf_cache_dir": cache,
+        "disk_free_gb": round(free_gb, 2),
+        "min_free_gb": MIN_FREE_GB,
+        "enough_disk": free_gb >= MIN_FREE_GB,
+    }
+
+
+# ── Pre-flight System Check ───────────────────────────────────────────────
+
+_MIN_NVIDIA_DRIVER = 555
+_RAM_FAIL_GB = 8
+_RAM_WARN_GB = 12
+
+
+def _run_cmd(args: list[str], timeout: float = 2.0) -> tuple[int, str]:
+    """Run a subprocess synchronously with a short timeout."""
+    import subprocess
+    try:
+        out = subprocess.run(
+            args, capture_output=True, text=True, timeout=timeout, check=False,
+        )
+        return out.returncode, out.stdout
+    except (FileNotFoundError, subprocess.TimeoutExpired, OSError):
+        return -1, ""
+
+
+def _detect_gpu() -> dict:
+    """Best-effort detection of GPU vendor + driver + compute backend."""
+    info = {
+        "vendor": "none", "driver": None, "device_name": None,
+        "backend": "cpu", "available": False, "notes": [],
+    }
+
+    # Apple Silicon → MPS
+    if sys.platform == "darwin" and _platform.machine() == "arm64":
+        info["vendor"] = "apple"
+        info["backend"] = "mps"
+        info["device_name"] = "Apple Silicon GPU (Metal)"
+        try:
+            import torch
+            info["available"] = bool(torch.backends.mps.is_available())
+        except Exception:
+            info["available"] = False
+        return info
+
+    # NVIDIA
+    rc, out = _run_cmd([
+        "nvidia-smi",
+        "--query-gpu=driver_version,name",
+        "--format=csv,noheader",
+    ])
+    if rc == 0 and out.strip():
+        line = out.strip().splitlines()[0]
+        parts = [p.strip() for p in line.split(",")]
+        driver = parts[0] if parts else None
+        name = parts[1] if len(parts) > 1 else None
+        info.update({"vendor": "nvidia", "driver": driver, "device_name": name})
+        try:
+            import torch
+            info["available"] = bool(torch.cuda.is_available())
+            info["backend"] = "cuda" if info["available"] else "cpu"
+        except Exception:
+            pass
+        try:
+            major = int((driver or "0").split(".")[0])
+            if major < _MIN_NVIDIA_DRIVER:
+                info["notes"].append(
+                    f"NVIDIA driver {driver} below {_MIN_NVIDIA_DRIVER} required "
+                    f"by the bundled CUDA 12.8 runtime — GPU will fail to launch "
+                    f"kernels. Update drivers before dubbing."
+                )
+                info["available"] = False
+        except Exception:
+            pass
+        return info
+
+    # AMD
+    rc, out = _run_cmd(["rocm-smi", "--showproductname"])
+    if rc == 0 and out.strip():
+        info["vendor"] = "amd"
+        info["device_name"] = out.strip().splitlines()[0][:120]
+        try:
+            import torch
+            has_hip = getattr(torch.version, "hip", None) is not None
+            if has_hip and torch.cuda.is_available():
+                info["backend"] = "rocm"
+                info["available"] = True
+            else:
+                info["backend"] = "cpu"
+                info["notes"].append(
+                    "AMD GPU detected but torch was installed with CUDA wheels. "
+                    "Re-run `uv sync --index-url https://download.pytorch.org/whl/rocm6.1` "
+                    "to enable ROCm acceleration."
+                )
+        except Exception:
+            info["notes"].append("AMD GPU detected but torch not importable.")
+        return info
+
+    # Fallback
+    try:
+        import torch
+        if torch.cuda.is_available():
+            info["vendor"] = "unknown"
+            info["backend"] = "cuda"
+            info["available"] = True
+            info["notes"].append(
+                "torch.cuda.is_available() is True but no nvidia-smi/rocm-smi "
+                "found — running through WSL or virtual GPU?"
+            )
+    except Exception:
+        pass
+    return info
+
+
+def _probe_network(host: str = "huggingface.co", timeout: float = 2.0) -> bool:
+    """Tiny TCP connect test."""
+    import socket
+    try:
+        with socket.create_connection((host, 443), timeout=timeout):
+            return True
+    except Exception:
+        return False
+
+
+def _ram_gb() -> float:
+    try:
+        import psutil
+        return psutil.virtual_memory().total / (1024 ** 3)
+    except Exception:
+        return 0.0
+
+
+@router.get("/setup/preflight", response_model=PreflightResponse)
+def preflight():
+    """One-shot system health check for the wizard."""
+    checks: list[dict] = []
+
+    # ── OS + arch
+    arch = _platform.machine()
+    os_ver = _platform.platform(terse=True)
+    checks.append({
+        "id": "os", "label": "Operating system", "status": "pass",
+        "detail": f"{os_ver} ({arch})", "fix": None,
+    })
+
+    # ── Python runtime
+    checks.append({
+        "id": "python", "label": "Python runtime", "status": "pass",
+        "detail": f"Python {sys.version.split()[0]}", "fix": None,
+    })
+
+    # ── RAM
+    ram = _ram_gb()
+    if ram == 0:
+        ram_status, ram_detail, ram_fix = (
+            "warn", "Could not detect system RAM.",
+            "Install psutil in the backend environment or ignore this warning.",
+        )
+    elif ram < _RAM_FAIL_GB:
+        ram_status, ram_detail, ram_fix = (
+            "fail", f"{ram:.1f} GB total (need ≥ {_RAM_FAIL_GB} GB)",
+            "The app will OOM on first dub. Close other apps or upgrade RAM.",
+        )
+    elif ram < _RAM_WARN_GB:
+        ram_status, ram_detail, ram_fix = (
+            "warn", f"{ram:.1f} GB total ({_RAM_WARN_GB}+ GB recommended)",
+            "Long videos may hit swap. Keep other apps closed during dubbing.",
+        )
+    else:
+        ram_status, ram_detail, ram_fix = ("pass", f"{ram:.1f} GB total", None)
+    checks.append({
+        "id": "ram", "label": "System RAM", "status": ram_status,
+        "detail": ram_detail, "fix": ram_fix,
+    })
+
+    # ── Disk free
+    cache = hf_cache_dir()
+    free = _disk_free_gb(cache)
+    if free < MIN_FREE_GB:
+        disk = {
+            "status": "fail",
+            "detail": f"{free:.1f} GB free at {cache} (need ≥ {MIN_FREE_GB} GB)",
+            "fix": f"Free up disk space or set HF_HOME to a larger partition.",
+        }
+    else:
+        disk = {"status": "pass", "detail": f"{free:.1f} GB free at {cache}", "fix": None}
+    checks.append({"id": "disk", **{"label": "Disk space", **disk}})
+
+    # ── HF cache writable
+    try:
+        os.makedirs(cache, exist_ok=True)
+        writable = os.access(cache, os.W_OK)
+    except Exception:
+        writable = False
+    checks.append({
+        "id": "hf_cache_writable", "label": "HuggingFace cache writable",
+        "status": "pass" if writable else "fail",
+        "detail": cache,
+        "fix": None if writable else
+            f"Fix write permissions on {cache} or point HF_HOME elsewhere.",
+    })
+
+    # ── FFmpeg
+    ffmpeg_path = None
+    try:
+        from services.ffmpeg_utils import find_ffmpeg
+        ffmpeg_path = find_ffmpeg()
+    except Exception as e:
+        checks.append({
+            "id": "ffmpeg", "label": "FFmpeg", "status": "fail",
+            "detail": str(e)[:200],
+            "fix": "Install ffmpeg via your package manager "
+                   "(brew install ffmpeg / apt install ffmpeg / choco install ffmpeg).",
+        })
+    else:
+        checks.append({
+            "id": "ffmpeg", "label": "FFmpeg", "status": "pass",
+            "detail": ffmpeg_path, "fix": None,
+        })
+
+    # ── FFprobe
+    ffprobe_path = None
+    if ffmpeg_path:
+        candidate = ffmpeg_path.replace("ffmpeg", "ffprobe")
+        if os.path.exists(candidate):
+            ffprobe_path = candidate
+        else:
+            system_probe = _shutil.which("ffprobe")
+            if system_probe:
+                ffprobe_path = system_probe
+    if ffprobe_path:
+        checks.append({
+            "id": "ffprobe", "label": "FFprobe", "status": "pass",
+            "detail": ffprobe_path, "fix": None,
+        })
+    else:
+        checks.append({
+            "id": "ffprobe", "label": "FFprobe", "status": "warn",
+            "detail": "Not bundled alongside ffmpeg.",
+            "fix": "File-probe endpoint (/tools/probe) will 501. "
+                   "Install system ffmpeg (includes ffprobe) to enable it.",
+        })
+
+    # ── yt-dlp
+    yt_dlp_path = _shutil.which("yt-dlp")
+    if yt_dlp_path:
+        rc_ytv, yt_ver = _run_cmd([yt_dlp_path, "--version"], timeout=3.0)
+        yt_version = yt_ver.strip() if rc_ytv == 0 else "unknown"
+        checks.append({
+            "id": "yt-dlp", "label": "yt-dlp", "status": "pass",
+            "detail": f"{yt_dlp_path} (v{yt_version})", "fix": None,
+        })
+    else:
+        checks.append({
+            "id": "yt-dlp", "label": "yt-dlp", "status": "warn",
+            "detail": "Not found in system PATH.",
+            "fix": "YouTube clip downloads in Voice Gallery will fail. Download the standalone binary from https://github.com/yt-dlp/yt-dlp/releases and place it in your PATH.",
+        })
+
+    # ── GPU
+    gpu = _detect_gpu()
+    if gpu["vendor"] == "apple" and gpu["available"]:
+        gpu_status, gpu_fix = "pass", None
+        gpu_detail = f"{gpu['device_name']} — Metal (MPS) ready"
+    elif gpu["vendor"] == "nvidia" and gpu["available"]:
+        gpu_status, gpu_fix = "pass", None
+        gpu_detail = f"{gpu['device_name']} (driver {gpu['driver']}) — CUDA ready"
+    elif gpu["vendor"] == "nvidia" and not gpu["available"]:
+        gpu_status = "fail"
+        gpu_detail = (
+            f"{gpu['device_name']} found but CUDA not usable "
+            f"(driver {gpu['driver']}). " + " ".join(gpu["notes"])
+        )
+        gpu_fix = (
+            f"Update NVIDIA drivers to ≥ R{_MIN_NVIDIA_DRIVER} "
+            "(https://www.nvidia.com/Download/index.aspx). Or run CPU-only "
+            "by continuing past this step — dubbing will be ~10× slower."
+        )
+    elif gpu["vendor"] == "amd":
+        gpu_status = "warn"
+        gpu_detail = (
+            f"{gpu['device_name']} — ROCm "
+            + ("ready" if gpu["available"] else "not configured")
+        )
+        gpu_fix = (
+            None if gpu["available"] else
+            "AMD support is experimental. Re-run `uv sync --index-url "
+            "https://download.pytorch.org/whl/rocm6.1` to enable. App works "
+            "on CPU otherwise (slower)."
+        )
+    else:
+        gpu_status = "warn"
+        gpu_detail = "No compatible GPU detected — running CPU-only."
+        gpu_fix = (
+            "Dubbing will work but ~10× slower than GPU. If you have an "
+            "NVIDIA/AMD card, check drivers are installed."
+        )
+    checks.append({
+        "id": "gpu", "label": "GPU acceleration",
+        "status": gpu_status, "detail": gpu_detail, "fix": gpu_fix,
+    })
+
+    # ── Network
+    net_ok = _probe_network()
+    checks.append({
+        "id": "network", "label": "Network (huggingface.co)",
+        "status": "pass" if net_ok else "fail",
+        "detail": "Reachable" if net_ok else "Unreachable on port 443",
+        "fix": None if net_ok else
+            "Check internet connection, VPN, or corporate firewall "
+            "whitelist for huggingface.co.",
+    })
+
+    # Aggregate
+    any_fail = any(c["status"] == "fail" for c in checks)
+    any_warn = any(c["status"] == "warn" for c in checks)
+
+    return {
+        "ok": not any_fail,
+        "has_warnings": any_warn,
+        "checks": checks,
+        "device": {
+            "os": sys.platform,
+            "arch": arch,
+            "gpu_vendor": gpu["vendor"],
+            "gpu_backend": gpu["backend"],
+            "gpu_available": gpu["available"],
+            "gpu_driver": gpu["driver"],
+            "gpu_device_name": gpu["device_name"],
+            "ram_gb": round(ram, 1),
+            "disk_free_gb": round(free, 1),
+        },
+    }
+
+
+# ── Warmup ─────────────────────────────────────────────────────────────────
+
+@router.post("/setup/warmup")
+async def setup_warmup():
+    """Trigger a model load in the background so the first dub doesn't pay
+    the cold-start tax."""
+    loop = asyncio.get_event_loop()
+
+    async def _do_warmup():
+        try:
+            from services.model_manager import get_model
+            await get_model()
+        except Exception as e:
+            logger.warning("setup/warmup: model load failed: %s", e)
+
+    loop.create_task(_do_warmup())
+    return {"status": "warmup_started"}

backend/api/routers/system.py

@@ -4,8 +4,9 @@ import uuid
 import psutil
 import asyncio
 import logging
-from fastapi import APIRouter, File, UploadFile, HTTPException
-from fastapi.responses import FileResponse
+from fastapi import APIRouter, File, UploadFile, HTTPException, Query
+from api.schemas import SysinfoResponse, SystemInfoResponse, ModelStatusResponse, LogsResponse, FlushMemoryResponse
+from fastapi.responses import FileResponse, StreamingResponse
 import torch
 import shutil
 
@@ -22,28 +23,49 @@ _is_cuda = torch.cuda.is_available()
 # Prime psutil's internal CPU counter so the first non-blocking call returns useful data
 psutil.cpu_percent(interval=None)
 
-@router.get("/model/status")
+@router.get("/model/status", response_model=ModelStatusResponse)
 def model_status():
     """Report model loading state for frontend warm-up indicators."""
     return get_model_status()
 
 
-@router.get("/system/info")
+@router.get("/system/info", response_model=SystemInfoResponse)
 def system_info():
-    """Settings page system info — model, tokens, data dir, timeout."""
-    return {
-        "data_dir": DATA_DIR,
-        "outputs_dir": OUTPUTS_DIR,
-        "crash_log_path": CRASH_LOG_PATH,
-        "idle_timeout_seconds": IDLE_TIMEOUT_SECONDS,
-        "model_checkpoint": os.environ.get("OMNIVOICE_MODEL", "k2-fsa/OmniVoice"),
-        "asr_model": os.environ.get("ASR_MODEL", "Systran/faster-whisper-large-v3"),
-        "translate_provider": os.environ.get("TRANSLATE_PROVIDER", "google"),
-        "has_hf_token": bool(os.environ.get("HF_TOKEN")),
-        "device": get_best_device(),
-        "python": sys.version.split()[0],
-        "platform": sys.platform,
-    }
+    """Settings page system info — model, tokens, data dir, timeout.
+
+    This endpoint MUST never throw — it's called on every Settings page load
+    and a 500 here blocks the entire UI from rendering system details.
+    """
+    try:
+        return {
+            "data_dir": DATA_DIR,
+            "outputs_dir": OUTPUTS_DIR,
+            "crash_log_path": CRASH_LOG_PATH,
+            "idle_timeout_seconds": IDLE_TIMEOUT_SECONDS,
+            "model_checkpoint": os.environ.get("OMNIVOICE_MODEL", "k2-fsa/OmniVoice"),
+            "asr_model": os.environ.get("ASR_MODEL", "Systran/faster-whisper-large-v3"),
+            "translate_provider": os.environ.get("TRANSLATE_PROVIDER", "google"),
+            "has_hf_token": bool(os.environ.get("HF_TOKEN")),
+            "device": get_best_device(),
+            "python": sys.version.split()[0],
+            "platform": sys.platform,
+        }
+    except Exception as e:
+        logger.exception("system_info failed — returning safe defaults")
+        return {
+            "data_dir": DATA_DIR,
+            "outputs_dir": OUTPUTS_DIR,
+            "crash_log_path": str(CRASH_LOG_PATH),
+            "idle_timeout_seconds": IDLE_TIMEOUT_SECONDS,
+            "model_checkpoint": "unknown",
+            "asr_model": "unknown",
+            "translate_provider": "unknown",
+            "has_hf_token": False,
+            "device": "cpu",
+            "python": sys.version.split()[0],
+            "platform": sys.platform,
+            "error": str(e),
+        }
 
 
 def _tail_file(path: str, tail: int):
@@ -85,7 +107,7 @@ def _tauri_log_candidates():
 
 
 @router.get("/system/logs")
-def system_logs(tail: int = 200):
+async def system_logs(tail: int = 200):
     """Tail the rolling runtime log — everything Python logged since last rotation.
 
     Back-stop: if the rolling log doesn't exist yet (fresh install, disk error),
@@ -100,12 +122,9 @@ def system_logs(tail: int = 200):
     if not os.path.exists(path):
         return {"lines": [], "path": LOG_PATH, "exists": False}
     try:
-        lines, total = _tail_file(path, tail)
+        lines, total = await asyncio.to_thread(_tail_file, path, tail)
         return {"lines": lines, "path": path, "exists": True, "total_lines": total}
     except Exception as e:
-        # The log file exists but we can't read it — usually a permission
-        # issue or the file got truncated mid-read. Point the user at the
-        # path so they can inspect or delete manually.
         raise HTTPException(
             status_code=500,
             detail=f"Could not read log at {path}: {e}. Check file permissions or delete it manually.",
@@ -113,7 +132,7 @@ def system_logs(tail: int = 200):
 
 
 @router.get("/system/logs/tauri")
-def system_logs_tauri(tail: int = 200):
+async def system_logs_tauri(tail: int = 200):
     """Tail the Tauri plugin log (or backend stdout redirect, whichever exists)."""
     try:
         tail = max(10, min(2000, int(tail)))
@@ -123,22 +142,87 @@ def system_logs_tauri(tail: int = 200):
     for p in candidates:
         if os.path.exists(p):
             try:
-                lines, total = _tail_file(p, tail)
+                lines, total = await asyncio.to_thread(_tail_file, p, tail)
                 return {"lines": lines, "path": p, "exists": True, "total_lines": total}
             except Exception as e:
                 return {"lines": [], "path": p, "exists": True, "error": str(e)}
     return {"lines": [], "path": None, "exists": False, "candidates": candidates}
 
 
+@router.get("/system/logs/stream")
+async def stream_logs(
+    source: str = Query("backend", description="'backend' or 'tauri'"),
+    interval: float = Query(1.0, ge=0.3, le=10.0, description="Poll interval in seconds"),
+):
+    """Server-Sent Events stream of new log lines.
+
+    The client opens an EventSource connection and receives new lines as they
+    are appended to the log file.  This replaces the polling pattern used by
+    the LogsFooter component.
+
+    Usage (frontend)::
+
+        const es = new EventSource('/system/logs/stream?source=backend');
+        es.onmessage = (e) => { const lines = JSON.parse(e.data); ... };
+    """
+    if source == "tauri":
+        candidates = _tauri_log_candidates()
+        path = next((p for p in candidates if os.path.exists(p)), None)
+    else:
+        path = LOG_PATH if os.path.exists(LOG_PATH) else CRASH_LOG_PATH
+
+    if not path or not os.path.exists(path):
+        raise HTTPException(status_code=404, detail=f"Log file not found for source={source}")
+
+    async def _generate():
+        """Yield SSE events whenever new lines appear in the log file."""
+        last_pos = 0
+        try:
+            last_pos = os.path.getsize(path)
+        except Exception:
+            pass
+        while True:
+            await asyncio.sleep(interval)
+            try:
+                size = os.path.getsize(path)
+                if size < last_pos:
+                    # File was truncated (log rotation or clear) — reset
+                    last_pos = 0
+                if size == last_pos:
+                    continue
+                new_lines = await asyncio.to_thread(_read_from_pos, path, last_pos)
+                last_pos = size
+                if new_lines:
+                    import json
+                    yield f"data: {json.dumps(new_lines)}\n\n"
+            except Exception:
+                break
+
+    return StreamingResponse(
+        _generate(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "X-Accel-Buffering": "no",
+        },
+    )
+
+
+def _read_from_pos(path: str, pos: int) -> list[str]:
+    """Read all lines from `pos` to EOF (runs in threadpool)."""
+    with open(path, "r", encoding="utf-8", errors="replace") as f:
+        f.seek(pos)
+        return f.readlines()
+
+
 @router.post("/system/logs/clear")
-def clear_system_logs():
+async def clear_system_logs():
     """Truncate the rolling runtime log and the crash log (what the Backend tab reads)."""
     cleared_any = False
     for p in (LOG_PATH, CRASH_LOG_PATH):
         if os.path.exists(p):
             try:
-                with open(p, "w") as f:
-                    f.truncate(0)
+                await asyncio.to_thread(_truncate_file, p)
                 cleared_any = True
             except Exception as e:
                 raise HTTPException(
@@ -148,21 +232,26 @@ def clear_system_logs():
     return {"cleared": cleared_any}
 
 
+def _truncate_file(path: str):
+    """Truncate a file to zero length (runs in threadpool)."""
+    with open(path, "w") as f:
+        f.truncate(0)
+
+
 @router.post("/system/logs/tauri/clear")
-def clear_tauri_logs():
+async def clear_tauri_logs():
     """Truncate whichever Tauri-side log files we know about. OS-level rotation may recreate them."""
     cleared = []
     for p in _tauri_log_candidates():
         if os.path.exists(p):
             try:
-                with open(p, "w") as f:
-                    f.truncate(0)
+                await asyncio.to_thread(_truncate_file, p)
                 cleared.append(p)
             except Exception:
                 pass
     return {"cleared": cleared}
 
-@router.get("/sysinfo")
+@router.get("/sysinfo", response_model=SysinfoResponse)
 def get_sys_info():
     vram = 0.0
     gpu_active = False

backend/api/routers/watermark.py

@@ -0,0 +1,90 @@
+"""
+Watermark detection API — upload audio, check if it was generated by OmniVoice.
+"""
+import os
+import tempfile
+import logging
+import torchaudio
+from fastapi import APIRouter, UploadFile, File, HTTPException
+
+from services.watermark import detect_watermark, is_enabled, _check_available
+from core.prefs import get as pref_get, set_ as pref_set
+
+logger = logging.getLogger("omnivoice.watermark_api")
+
+router = APIRouter()
+
+
+@router.post("/watermark/detect")
+async def detect_audio_watermark(file: UploadFile = File(...)):
+    """
+    Upload an audio file and check whether it contains an OmniVoice watermark.
+
+    Returns confidence score, decoded message, and source attribution.
+    """
+    if not _check_available():
+        raise HTTPException(
+            status_code=503,
+            detail="AudioSeal is not installed. Run `uv pip install audioseal` to enable watermark detection.",
+        )
+
+    # Accept common audio formats
+    allowed = {".wav", ".mp3", ".flac", ".ogg", ".m4a", ".aac", ".opus"}
+    ext = os.path.splitext(file.filename or "upload.wav")[1].lower()
+    if ext not in allowed:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Unsupported format '{ext}'. Upload one of: {', '.join(sorted(allowed))}",
+        )
+
+    # Write to temp file for torchaudio to load
+    try:
+        with tempfile.NamedTemporaryFile(suffix=ext, delete=False) as tmp:
+            content = await file.read()
+            tmp.write(content)
+            tmp_path = tmp.name
+
+        waveform, sr = torchaudio.load(tmp_path)
+        result = detect_watermark(waveform, sr)
+        return result
+
+    except Exception as e:
+        logger.error("Watermark detection failed: %s", e)
+        raise HTTPException(status_code=500, detail=str(e))
+    finally:
+        try:
+            os.unlink(tmp_path)
+        except (OSError, UnboundLocalError):
+            pass
+
+
+@router.get("/watermark/status")
+def watermark_status():
+    """Return current watermark configuration."""
+    return {
+        "invisible_enabled": is_enabled(),
+        "visible_audio_enabled": pref_get("watermark.visible_audio", False),
+        "visible_video_enabled": pref_get("watermark.visible_video", True),
+        "audioseal_available": _check_available(),
+    }
+
+
+@router.post("/watermark/settings")
+def update_watermark_settings(
+    invisible: bool | None = None,
+    visible_audio: bool | None = None,
+    visible_video: bool | None = None,
+):
+    """Update watermark preferences."""
+    if invisible is not None:
+        pref_set("watermark.invisible", invisible)
+    if visible_audio is not None:
+        pref_set("watermark.visible_audio", visible_audio)
+    if visible_video is not None:
+        pref_set("watermark.visible_video", visible_video)
+
+    return {
+        "invisible_enabled": pref_get("watermark.invisible", True),
+        "visible_audio_enabled": pref_get("watermark.visible_audio", False),
+        "visible_video_enabled": pref_get("watermark.visible_video", True),
+    }

backend/api/schemas.py

@@ -0,0 +1,146 @@
+"""Pydantic v2 schemas for request/response validation.
+
+Shared across routers — import from here rather than defining inline.
+Using ``model_config = ConfigDict(...)`` for Pydantic v2 compat.
+"""
+from __future__ import annotations
+
+from pydantic import BaseModel, ConfigDict, Field
+
+
+# ── System ────────────────────────────────────────────────────────────────
+
+class SysinfoResponse(BaseModel):
+    """GET /sysinfo"""
+    model_config = ConfigDict(extra="allow")
+
+    cpu: float = Field(description="CPU usage percentage (0–100)")
+    ram: float = Field(description="Used RAM in GiB")
+    total_ram: float = Field(description="Total RAM in GiB")
+    vram: float = Field(0.0, description="Used VRAM in GiB")
+    gpu_active: bool = Field(False, description="Whether a GPU is actively used")
+
+
+class SystemInfoResponse(BaseModel):
+    """GET /system/info"""
+    model_config = ConfigDict(extra="allow")
+
+    data_dir: str
+    outputs_dir: str
+    crash_log_path: str
+    idle_timeout_seconds: int
+    model_checkpoint: str = "unknown"
+    asr_model: str = "unknown"
+    translate_provider: str = "unknown"
+    has_hf_token: bool = False
+    device: str = "cpu"
+    python: str = ""
+    platform: str = ""
+    error: str | None = None
+
+
+class ModelStatusResponse(BaseModel):
+    """GET /model/status"""
+    model_config = ConfigDict(extra="allow")
+
+    status: str = Field(description="idle | loading | ready")
+    checkpoint: str | None = None
+    loaded_at: str | None = None
+
+
+class LogsResponse(BaseModel):
+    """GET /system/logs"""
+    lines: list[str] = Field(default_factory=list)
+    path: str = ""
+    exists: bool = False
+    total_lines: int = 0
+    error: str | None = None
+    candidates: list[str] | None = None
+
+
+class FlushMemoryResponse(BaseModel):
+    """POST /system/flush-memory"""
+    flushed: bool = True
+    unloaded_model: bool = False
+    ram_after: float = 0.0
+    vram_after: float = 0.0
+
+
+# ── Setup ─────────────────────────────────────────────────────────────────
+
+class MissingModel(BaseModel):
+    repo_id: str
+    label: str
+
+
+class SetupStatusResponse(BaseModel):
+    """GET /setup/status"""
+    models_ready: bool
+    missing: list[MissingModel] = Field(default_factory=list)
+    hf_cache_dir: str
+    disk_free_gb: float
+    min_free_gb: int = 10
+    enough_disk: bool = True
+
+
+class PreflightCheck(BaseModel):
+    """One check in the preflight report."""
+    model_config = ConfigDict(extra="allow")
+
+    id: str
+    label: str
+    status: str = Field(description="pass | warn | fail")
+    detail: str = ""
+    fix: str | None = None
+
+
+class DeviceInfo(BaseModel):
+    """GPU/system device info from preflight."""
+    model_config = ConfigDict(extra="allow")
+
+    os: str
+    arch: str
+    gpu_vendor: str = "none"
+    gpu_backend: str = "cpu"
+    gpu_available: bool = False
+    gpu_driver: str | None = None
+    gpu_device_name: str | None = None
+    ram_gb: float = 0.0
+    disk_free_gb: float = 0.0
+
+
+class PreflightResponse(BaseModel):
+    """GET /setup/preflight"""
+    ok: bool
+    has_warnings: bool = False
+    checks: list[PreflightCheck] = Field(default_factory=list)
+    device: DeviceInfo
+
+
+class InstallModelRequest(BaseModel):
+    """POST /models/install"""
+    repo_id: str
+
+
+class DeleteModelResponse(BaseModel):
+    """DELETE /models/{repo_id}"""
+    deleted: bool = True
+    repo_id: str
+    freed_bytes: int = 0
+
+
+# ── Models list ───────────────────────────────────────────────────────────
+
+class ModelEntry(BaseModel):
+    """One model in the GET /models response."""
+    model_config = ConfigDict(extra="allow")
+
+    repo_id: str
+    label: str
+    role: str
+    size: str = ""
+    required: bool = False
+    installed: bool = False
+    supported: bool = True
+    size_on_disk: int | None = None
+    nb_files: int | None = None

backend/config/models.yaml

@@ -0,0 +1,123 @@
+# ── OmniVoice Studio — Model Catalog ─────────────────────────────────────
+#
+# This file is the source of truth for all known HuggingFace models.
+# The backend loads it at startup via `load_model_catalog()`.
+#
+# To add a model: append an entry with the fields below.
+# To remove: delete the entry. The UI will stop showing it immediately.
+#
+# Fields:
+#   repo_id    (required) — HuggingFace repository ID
+#   label      (required) — Human-readable display name
+#   role       (required) — TTS | ASR | Diarisation
+#   size_gb    (required) — Approximate download size in GiB
+#   required   (optional) — true if the app needs this model to function
+#   platforms  (optional) — restrict to specific OS+arch tags (e.g. darwin-arm64, cuda)
+#   note       (optional) — shown in the UI as a tooltip/footnote
+# ─────────────────────────────────────────────────────────────────────────
+
+models:
+  # ── Required ──────────────────────────────────────────────────────────
+
+  - repo_id: "k2-fsa/OmniVoice"
+    label: "OmniVoice TTS (600+ languages, zero-shot)"
+    role: TTS
+    size_gb: 2.4
+    required: true
+
+  - repo_id: "Systran/faster-whisper-large-v3"
+    label: "Whisper large-v3 (faster-whisper — default, cross-platform)"
+    role: ASR
+    size_gb: 2.9
+    required: true
+
+  # ── Optional ASR ──────────────────────────────────────────────────────
+
+  - repo_id: "mlx-community/whisper-large-v3-mlx"
+    label: "Whisper large-v3 (MLX — optional mac-ARM speedup)"
+    role: ASR
+    size_gb: 3.0
+    platforms: [darwin-arm64]
+
+  - repo_id: "openai/whisper-large-v3"
+    label: "Whisper large-v3 (PyTorch — last-resort fallback)"
+    role: ASR
+    size_gb: 3.1
+    platforms: [cuda]
+
+  - repo_id: "mlx-community/whisper-tiny-mlx"
+    label: "Whisper tiny (MLX ASR — fast fallback)"
+    role: ASR
+    size_gb: 0.08
+    platforms: [darwin-arm64]
+
+  # ── Diarisation ───────────────────────────────────────────────────────
+
+  - repo_id: "pyannote/speaker-diarization-3.1"
+    label: "pyannote speaker diarisation (multi-speaker videos)"
+    role: Diarisation
+    size_gb: 0.8
+    note: "Needs an HF_TOKEN with license accepted."
+
+  # ── Optional TTS ──────────────────────────────────────────────────────
+
+  - repo_id: "OpenMOSS-Team/MOSS-TTS-Nano-100M"
+    label: "MOSS-TTS-Nano 100M (20 langs, CPU-realtime)"
+    role: TTS
+    size_gb: 0.4
+
+  - repo_id: "KittenML/kitten-tts-mini-0.8"
+    label: "KittenTTS (English, 8 preset voices, CPU realtime)"
+    role: TTS
+    size_gb: 0.08
+
+  # ── mlx-audio engines (Apple Silicon only) ────────────────────────────
+
+  - repo_id: "mlx-community/Kokoro-82M-bf16"
+    label: "Kokoro 82M (8 langs, small, mlx-audio default)"
+    role: TTS
+    size_gb: 0.15
+    note: "Apple Silicon only — via mlx-audio backend."
+    platforms: [darwin-arm64]
+
+  - repo_id: "mlx-community/csm-1b-8bit"
+    label: "CSM 1B (voice cloning, mlx-audio)"
+    role: TTS
+    size_gb: 1.1
+    note: "Apple Silicon only — via mlx-audio backend."
+    platforms: [darwin-arm64]
+
+  - repo_id: "mlx-community/Qwen3-TTS-12Hz-1.7B-VoiceDesign-4bit"
+    label: "Qwen3-TTS 1.7B 4bit (voice design, mlx-audio)"
+    role: TTS
+    size_gb: 1.4
+    note: "Apple Silicon only — via mlx-audio backend."
+    platforms: [darwin-arm64]
+
+  - repo_id: "mlx-community/Dia-1.6B"
+    label: "Dia 1.6B (expressive, mlx-audio)"
+    role: TTS
+    size_gb: 3.2
+    note: "Apple Silicon only — via mlx-audio backend."
+    platforms: [darwin-arm64]
+
+  - repo_id: "mlx-community/Llama-OuteTTS-1.0-1B-4bit"
+    label: "Llama-OuteTTS 1.0 1B 4bit (voice clone, mlx-audio)"
+    role: TTS
+    size_gb: 0.8
+    note: "Apple Silicon only — via mlx-audio backend."
+    platforms: [darwin-arm64]
+
+  - repo_id: "mlx-community/Chatterbox-TTS-4bit"
+    label: "Chatterbox TTS 4bit (mlx-audio)"
+    role: TTS
+    size_gb: 0.5
+    note: "Apple Silicon only — via mlx-audio backend."
+    platforms: [darwin-arm64]
+
+  - repo_id: "mlx-community/MeloTTS-English-v3-MLX"
+    label: "MeloTTS English v3 (mlx-audio)"
+    role: TTS
+    size_gb: 0.2
+    note: "Apple Silicon only — via mlx-audio backend."
+    platforms: [darwin-arm64]

backend/core/config.py

@@ -13,6 +13,36 @@ def get_app_data_dir():
     else:
         return os.path.expanduser("~/.omnivoice")
 
+
+def _ensure_short_hf_cache_on_windows():
+    """Redirect HuggingFace cache to a short path on Windows.
+
+    The default ``~/.cache/huggingface/hub/models--org--name/snapshots/<hash>/…``
+    path regularly exceeds the 260-char MAX_PATH limit on NTFS, causing
+    ``FileNotFoundError`` or truncated downloads on first install.  We shorten
+    it to ``%LOCALAPPDATA%\\OmniVoice\\hf_cache`` (~40 chars) so even the
+    deepest blob path stays well under the limit.
+
+    Respects any explicit override the user already set via
+    ``OMNIVOICE_CACHE_DIR``, ``HF_HOME``, or ``HF_HUB_CACHE``.
+    """
+    if sys.platform != "win32":
+        return
+    # Don't override if the user (or main.py's OMNIVOICE_CACHE_DIR block)
+    # already pointed the cache somewhere specific.
+    if os.environ.get("OMNIVOICE_CACHE_DIR") or os.environ.get("HF_HOME") or os.environ.get("HF_HUB_CACHE"):
+        return
+    local_app = os.environ.get("LOCALAPPDATA", "")
+    if not local_app:
+        return
+    short_cache = os.path.join(local_app, "OmniVoice", "hf_cache")
+    os.makedirs(short_cache, exist_ok=True)
+    os.environ["HF_HOME"] = short_cache
+    os.environ["HF_HUB_CACHE"] = short_cache
+
+_ensure_short_hf_cache_on_windows()
+
+
 DATA_DIR = get_app_data_dir()
 VOICES_DIR = os.path.join(DATA_DIR, "voices")       # Reference audio for profiles
 OUTPUTS_DIR = os.path.join(DATA_DIR, "outputs")      # Generated audio files

backend/core/event_bus.py

@@ -0,0 +1,85 @@
+"""In-memory pub/sub event bus for real-time UI updates.
+
+Any backend code that mutates sidebar-visible data (projects, profiles,
+history) calls ``emit(kind, payload)`` and the WebSocket endpoint fans it
+out to all connected frontends.  This replaces the 45 s polling band-aid
+with instant push.
+
+Events are fire-and-forget, no persistence needed — the frontend uses
+the event as a "hey, refetch this" signal rather than carrying the full
+data payload.
+"""
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import time
+from typing import Any
+
+logger = logging.getLogger("omnivoice.events")
+
+# All connected WebSocket listener queues
+_listeners: list[asyncio.Queue] = []
+_lock = asyncio.Lock()
+
+
+async def subscribe() -> asyncio.Queue:
+    """Register a new listener. Returns a Queue that receives event dicts."""
+    q: asyncio.Queue = asyncio.Queue(maxsize=64)
+    async with _lock:
+        _listeners.append(q)
+    return q
+
+
+async def unsubscribe(q: asyncio.Queue) -> None:
+    """Remove a listener."""
+    async with _lock:
+        try:
+            _listeners.remove(q)
+        except ValueError:
+            pass
+
+
+def emit(kind: str, payload: dict[str, Any] | None = None) -> None:
+    """Broadcast an event to all connected frontends.
+
+    Safe to call from sync or async context — uses fire-and-forget
+    scheduling into the running event loop.
+
+    ``kind`` is one of: projects, profiles, dub_history, export_history,
+    generation_history, model_status, glossary.
+    """
+    event = {
+        "kind": kind,
+        "ts": time.time(),
+        **(payload or {}),
+    }
+    event_str = json.dumps(event)
+    try:
+        loop = asyncio.get_running_loop()
+        loop.create_task(_broadcast(event_str))
+    except RuntimeError:
+        # No event loop running (unlikely in FastAPI context but safe)
+        logger.debug("No event loop — event dropped: %s", kind)
+
+
+async def _broadcast(event_str: str) -> None:
+    """Push event to all listener queues. Drop if full (slow consumer)."""
+    async with _lock:
+        dead: list[asyncio.Queue] = []
+        for q in _listeners:
+            try:
+                q.put_nowait(event_str)
+            except asyncio.QueueFull:
+                # Slow consumer — drop oldest, then push
+                try:
+                    q.get_nowait()
+                    q.put_nowait(event_str)
+                except Exception:
+                    dead.append(q)
+        for q in dead:
+            try:
+                _listeners.remove(q)
+            except ValueError:
+                pass

backend/core/prefs.py

@@ -37,7 +37,11 @@ def _load() -> dict:
 
 def _save(data: dict) -> None:
     # Atomic write — no half-written JSON if the process dies mid-flush.
-    fd, tmp = tempfile.mkstemp(prefix=".prefs.", suffix=".tmp", dir=DATA_DIR)
+    # Derive temp-dir from _PREFS_PATH (not DATA_DIR) so os.replace() always
+    # operates within the same filesystem — important when tests redirect the path.
+    target_dir = os.path.dirname(_PREFS_PATH) or DATA_DIR
+    os.makedirs(target_dir, exist_ok=True)
+    fd, tmp = tempfile.mkstemp(prefix=".prefs.", suffix=".tmp", dir=target_dir)
     try:
         with os.fdopen(fd, "w", encoding="utf-8") as f:
             json.dump(data, f, indent=2)

backend/main.py

@@ -3,10 +3,48 @@ import sys
 
 try:
     import dotenv
+
     dotenv.load_dotenv()
+    # Also load the durable per-user config so env vars set once survive
+    # Tauri/Finder launches that don't inherit a shell environment.
+    _user_env = os.path.expanduser("~/.config/omnivoice/env")
+    if os.path.isfile(_user_env):
+        dotenv.load_dotenv(_user_env, override=False)
 except ImportError:
     pass
 
+# ── cuDNN 8 library preload ─────────────────────────────────────────────
+# CTranslate2 (used by faster-whisper / WhisperX) requires cuDNN 8, but
+# PyTorch 2.8+ pulls cuDNN 9. scripts/setup_cudnn.py installs cuDNN 8
+# side-by-side into cudnn8_compat/ (survives `uv sync`). We preload all
+# cuDNN 8 libs via ctypes so CTranslate2's dlopen/LoadLibrary finds them.
+if sys.platform != "darwin":  # macOS has no CUDA
+    _project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    _pyver = f"python{sys.version_info.major}.{sys.version_info.minor}"
+    if sys.platform == "win32":
+        _cudnn8_lib = os.path.join(
+            _project_root, ".venv", "Lib", "site-packages",
+            "cudnn8_compat", "nvidia", "cudnn", "bin",
+        )
+        _cudnn8_glob = "cudnn*64_8.dll"
+    else:
+        _cudnn8_lib = os.path.join(
+            _project_root, ".venv", "lib", _pyver, "site-packages",
+            "cudnn8_compat", "nvidia", "cudnn", "lib",
+        )
+        _cudnn8_glob = "libcudnn*.so.8"
+    if os.path.isdir(_cudnn8_lib):
+        try:
+            import ctypes, glob
+            _mode = 0 if sys.platform == "win32" else ctypes.RTLD_GLOBAL
+            for _so in sorted(glob.glob(os.path.join(_cudnn8_lib, _cudnn8_glob))):
+                try:
+                    ctypes.CDLL(_so, mode=_mode)
+                except OSError:
+                    pass
+        except Exception:
+            pass
+
 # Route HF/Torch caches to a single external directory when requested.
 _cache_dir = os.environ.get("OMNIVOICE_CACHE_DIR")
 if _cache_dir:
@@ -15,6 +53,30 @@ if _cache_dir:
     os.environ["HF_HUB_CACHE"] = _cache_dir
     os.environ["TORCH_HOME"] = _cache_dir
 
+# ── Windows symlink fix ─────────────────────────────────────────────────────
+# HuggingFace Hub creates NTFS symlinks in its cache to deduplicate blobs
+# across model revisions.  On Windows, symlink creation requires either
+# Developer Mode enabled or an elevated (Administrator) shell.  Without
+# either, `snapshot_download` / `hf_hub_download` raises:
+#   OSError: [WinError 1314] A required privilege is not held by the client
+# Setting HF_HUB_DISABLE_SYMLINKS_WARNING silences the console spam, and the
+# newer HF_HUB_DISABLE_SYMLINKS (huggingface_hub ≥ 0.21) forces file copies
+# instead — slightly more disk but always works on first install.
+if sys.platform == "win32":
+    os.environ.setdefault("HF_HUB_DISABLE_SYMLINKS_WARNING", "1")
+    os.environ.setdefault("HF_HUB_DISABLE_SYMLINKS", "1")
+
+# ── HF Xet → legacy LFS fallback ────────────────────────────────────────────
+# huggingface_hub ≥ 1.5 routes large file downloads through the Xet content-
+# addressed protocol (hf_xet runtime), which has its own internal progress
+# reporting that bypasses our `tqdm` monkey-patch in `utils.hf_progress`.
+# As a result the SetupWizard install rows show no byte progress while the
+# download is actually running. Force the legacy LFS path until we add a
+# proper hf_xet progress hook — this still streams via the standard tqdm
+# wrapper that our patch intercepts. Override-able by the user.
+os.environ.setdefault("HF_HUB_DISABLE_XET", "1")
+
+
 # Prevent torchaudio from lazy-importing torchcodec (broken on some installs).
 # Proper fix = exclude torchcodec in pyproject.toml; this is a belt-and-braces guard.
 os.environ.setdefault("TORCHAUDIO_USE_TORCHCODEC", "0")
@@ -42,11 +104,12 @@ class _JsonFormatter(logging.Formatter):
 
     def format(self, record: logging.LogRecord) -> str:
         import json as _json
+
         payload = {
-            "t":     self.formatTime(record, datefmt="%Y-%m-%dT%H:%M:%S"),
+            "t": self.formatTime(record, datefmt="%Y-%m-%dT%H:%M:%S"),
             "level": record.levelname,
-            "name":  record.name,
-            "msg":   record.getMessage(),
+            "name": record.name,
+            "msg": record.getMessage(),
         }
         if record.exc_info:
             payload["exc"] = self.formatException(record.exc_info)
@@ -67,13 +130,21 @@ if _json_logs:
 # Attached to root so uvicorn, fastapi, and every `omnivoice.*` namespace land here.
 # Not attached under _disable_file_log to keep CI/headless tests quiet.
 if not os.environ.get("OMNIVOICE_DISABLE_FILE_LOG"):
-    from core.config import LOG_PATH as _LOG_PATH  # local import — avoids circular import at module top
+    from core.config import (
+        LOG_PATH as _LOG_PATH,
+    )  # local import — avoids circular import at module top
+
     try:
         _file_handler = RotatingFileHandler(
-            _LOG_PATH, maxBytes=2 * 1024 * 1024, backupCount=3, encoding="utf-8",
+            _LOG_PATH,
+            maxBytes=2 * 1024 * 1024,
+            backupCount=3,
+            encoding="utf-8",
         )
         _file_handler.setLevel(logging.INFO)
-        _file_handler.setFormatter(_JsonFormatter() if _json_logs else logging.Formatter(_LOG_FMT))
+        _file_handler.setFormatter(
+            _JsonFormatter() if _json_logs else logging.Formatter(_LOG_FMT)
+        )
         logging.getLogger().addHandler(_file_handler)
     except Exception as _e:  # disk full, permission denied, etc. — don't block startup
         logging.getLogger("omnivoice.api").warning("Runtime log file disabled: %s", _e)
@@ -98,7 +169,25 @@ from core.tasks import task_manager
 from core import job_store
 from services.model_manager import idle_worker
 
-from api.routers import system, profiles, exports, generation, dub_core, dub_generate, dub_export, dub_translate, projects, glossary, engines, tools, setup
+from api.routers import (
+    system,
+    profiles,
+    exports,
+    generation,
+    dub_core,
+    dub_generate,
+    dub_export,
+    dub_translate,
+    projects,
+    glossary,
+    engines,
+    tools,
+    setup,
+    gallery,
+    batch,
+    watermark,
+    events,
+)
 from utils import hf_progress
 
 # Install the HuggingFace tqdm patch early — every downstream library import
@@ -106,9 +195,13 @@ from utils import hf_progress
 # the patched class, not the original.
 hf_progress.install()
 
+
 @asynccontextmanager
 async def lifespan(app: FastAPI):
     init_db()
+    from api.routers.gallery import _init_gallery_db
+
+    _init_gallery_db()
     # Any job still in pending/running at startup is orphaned — a previous
     # process didn't finish it. Flip to failed with a clear message so the
     # UI doesn't show a fake spinner.
@@ -121,18 +214,53 @@ async def lifespan(app: FastAPI):
     idle_task = asyncio.create_task(idle_worker())
     worker_task = asyncio.create_task(task_manager.worker())
     yield
+    # ── Graceful shutdown (SIGTERM from Tauri, Ctrl+C, etc.) ────────────
+    logger.info("Shutdown: cleaning up…")
     idle_task.cancel()
     worker_task.cancel()
+    # Wait for tasks to finish their current iteration
+    for t in (idle_task, worker_task):
+        try:
+            await asyncio.wait_for(t, timeout=3.0)
+        except (asyncio.CancelledError, asyncio.TimeoutError):
+            pass
+    # Unload the model and free GPU memory
+    try:
+        import services.model_manager as mm
+        if mm.model is not None:
+            mm.model = None
+            logger.info("Shutdown: model unloaded.")
+        mm.free_vram()
+    except Exception:
+        pass
+    # Run GC to release any remaining references
+    try:
+        import gc
+        gc.collect()
+    except Exception:
+        pass
+    # Close shared httpx connection pool
+    try:
+        from api.http_client import close_http_client
+        await close_http_client()
+    except Exception:
+        pass
+    logger.info("Shutdown: done.")
+
 
 app = FastAPI(title="OmniVoice Studio API", version="0.4.0", lifespan=lifespan)
 
+
 @app.exception_handler(Exception)
 async def global_exception_handler(request: Request, exc: Exception):
     # Client disconnected mid-stream (browser canceled a <video>/range fetch).
     # The response is already partially sent — trying to wrap it in a 500 just
     # produces a second protocol error. Log a one-liner and bail.
     exc_name = type(exc).__name__
-    if exc_name in ("LocalProtocolError", "ClientDisconnect") or "Content-Length" in str(exc):
+    if exc_name in (
+        "LocalProtocolError",
+        "ClientDisconnect",
+    ) or "Content-Length" in str(exc):
         logger.info("Client disconnect during %s (%s)", request.url, exc_name)
         return Response(status_code=499)
     try:
@@ -155,16 +283,18 @@ async def global_exception_handler(request: Request, exc: Exception):
         headers["Vary"] = "Origin"
     return JSONResponse({"detail": str(exc)}, status_code=500, headers=headers)
 
+
 _allowed = os.environ.get(
     "OMNIVOICE_ALLOWED_ORIGINS",
-    "http://localhost:5173,http://127.0.0.1:5173,tauri://localhost,http://tauri.localhost",
+    "http://localhost:3901,http://127.0.0.1:3901,tauri://localhost,http://tauri.localhost",
 ).split(",")
 
 app.add_middleware(
     CORSMiddleware,
     allow_origins=[o.strip() for o in _allowed if o.strip()],
     allow_credentials=True,
-    allow_methods=["*"], allow_headers=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
     expose_headers=["Content-Disposition"],
 )
 
@@ -184,15 +314,24 @@ app.include_router(glossary.router)
 app.include_router(engines.router)
 app.include_router(tools.router)
 app.include_router(setup.router)
+app.include_router(gallery.router)
+app.include_router(batch.router)
+app.include_router(watermark.router)
+app.include_router(events.router)
 
 frontend_path = os.path.join(os.path.dirname(__file__), "..", "frontend", "dist")
 if os.path.exists(frontend_path):
     app.mount("/", StaticFiles(directory=frontend_path, html=True), name="frontend")
 else:
+
     @app.get("/")
     def _dev_fallback():
-        return RedirectResponse(url="http://localhost:5173")
+        return RedirectResponse(url="http://localhost:3901")
+
 
 if __name__ == "__main__":
     import uvicorn
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+
+    # Port 3900 picked to dodge common 8000 conflicts (Django/Rails/Jupyter).
+    # Rust sidecar launcher in lib.rs::BACKEND_PORT must stay in sync.
+    uvicorn.run(app, host="0.0.0.0", port=3900)

backend/services/asr_backend.py

@@ -50,6 +50,10 @@ class ASRBackend(ABC):
         that already speak the shape plug in with zero adapter work.
         """
 
+    def unload(self) -> None:
+        """Release the model from memory."""
+        pass
+
 
 # ── WhisperX (cross-platform default — forced-alignment word timing) ────────
 
@@ -240,6 +244,17 @@ class WhisperXBackend(ASRBackend):
             "language": lang,
         }
 
+    def unload(self) -> None:
+        self._asr = None
+        self._align_cache.clear()
+        import gc
+        gc.collect()
+        try:
+            import torch
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+        except Exception:
+            pass
 
 # ── Faster-Whisper (cross-platform fallback) ────────────────────────────────
 
@@ -339,6 +354,17 @@ class FasterWhisperBackend(ASRBackend):
         }
         return out
 
+    def unload(self) -> None:
+        self._asr = None
+        import gc
+        gc.collect()
+        try:
+            import torch
+            if torch.cuda.is_available():
+                torch.cuda.empty_cache()
+        except Exception:
+            pass
+
 
 # ── MLX Whisper (Apple Silicon optional) ────────────────────────────────────
 

backend/services/dub_pipeline.py

@@ -44,6 +44,7 @@ from fastapi import HTTPException
 from services.ffmpeg_utils import find_ffmpeg, _get_semaphore, _spawn_with_retry
 from services.model_manager import get_best_device
 from core.db import db_conn, get_db
+from core import event_bus
 
 logger = logging.getLogger("omnivoice.dub_pipeline")
 
@@ -230,6 +231,8 @@ def save_job(job_id: str, job: dict, filename: str = "", duration: float = 0.0,
             )
     except Exception as e:
         logger.error("Failed to persist dub job %s: %s", job_id, e)
+        return
+    event_bus.emit("dub_history", {"action": "saved", "id": job_id})
 
 
 # ── Ingest pipeline (download → extract → demucs → scene → thumb) ──────────

backend/services/model_manager.py

@@ -91,6 +91,52 @@ def free_vram():
     elif torch.cuda.is_available():
         torch.cuda.empty_cache()
 
+
+def offload_tts_for_asr():
+    """Move TTS model to CPU to free VRAM for ASR (WhisperX large-v3).
+
+    On a 7-8 GB laptop GPU the TTS model (~2.4 GB) and WhisperX large-v3
+    (~3 GB) plus the VAD model can't coexist. Offloading the TTS model to
+    CPU before transcription prevents CUDA OOM, then restore_tts_after_asr()
+    moves it back.
+    """
+    global model
+    if model is None:
+        return
+    if not torch.cuda.is_available():
+        return  # Only needed on CUDA (limited VRAM)
+    try:
+        # Check if there's enough free VRAM to skip offloading (WhisperX + context needs >6GB safely)
+        free_mem = torch.cuda.mem_get_info()[0]
+        if free_mem > 8 * 1024 ** 3:  # > 8 GB free → plenty of room, skip offload
+            return
+    except Exception:
+        pass
+    try:
+        logger.info("Offloading TTS model to CPU to free VRAM for ASR...")
+        model.to("cpu")
+        free_vram()
+        logger.info("TTS model offloaded. VRAM freed for ASR.")
+    except Exception as e:
+        logger.warning("TTS offload failed: %s", e)
+
+
+def restore_tts_after_asr():
+    """Move TTS model back to CUDA after ASR completes."""
+    global model
+    if model is None:
+        return
+    if not torch.cuda.is_available():
+        return
+    try:
+        device = get_best_device()
+        if device == "cuda":
+            logger.info("Restoring TTS model to CUDA...")
+            model.to("cuda")
+            free_vram()
+    except Exception as e:
+        logger.warning("TTS restore to CUDA failed: %s", e)
+
 _diar_pipeline = None
 
 def get_diarization_pipeline():

backend/services/translator.py

@@ -59,8 +59,38 @@ _ADAPT_PROMPT = """\
 You are a cinematic dubbing writer. Rewrite the literal translation using the
 editor's critique so it sounds natural, in-character, and fits the speaker's
 time slot. Keep meaning faithful but prefer native idiom over word-for-word
-accuracy. Reply ONLY with the adapted translation — no quotes, no headers,
-no code fences, no commentary."""
+accuracy. The output MUST be written in the same target language and script
+as the literal translation — never switch language or transliterate.
+Reply ONLY with the adapted translation — no quotes, no headers, no code
+fences, no commentary."""
+
+# Per-language script ranges, mirrored from dub_translate.LANG_REQUIRED_SCRIPT
+# so the cinematic refine path can reject LLM outputs that drifted off the
+# target script. Kept local instead of imported because the routers package
+# also imports this services module — circular-import risk otherwise.
+_SCRIPT_RANGES = {
+    "hi":    (0x0900, 0x097F),
+    "ar":    (0x0600, 0x06FF),
+    "zh":    (0x4E00, 0x9FFF),
+    "zh-CN": (0x4E00, 0x9FFF),
+    "ja":    (0x3040, 0x30FF),
+    "ko":    (0xAC00, 0xD7AF),
+    "th":    (0x0E00, 0x0E7F),
+    "ru":    (0x0400, 0x04FF),
+    "uk":    (0x0400, 0x04FF),
+}
+
+
+def _looks_like_target_script(text: str, code: str, threshold: float = 0.5) -> bool:
+    rng = _SCRIPT_RANGES.get(code)
+    if not rng:
+        return True
+    lo, hi = rng
+    letters = [c for c in text if c.isalpha()]
+    if not letters:
+        return True
+    inside = sum(1 for c in letters if lo <= ord(c) <= hi)
+    return (inside / len(letters)) >= threshold
 
 
 def _llm_client():
@@ -219,7 +249,22 @@ def cinematic_refine_sync(
             "error": f"adapt: {e}",
         }
 
-    final = adapted.strip() or literal_text
+    final = (adapted or "").strip() or literal_text
+    # Refuse adaptations that drifted off the target script (e.g. local LLM
+    # rewrote a Devanagari line in Latin/German). Caller still gets the
+    # critique so the UI can show what happened, but the live text falls
+    # back to the literal translation rather than corrupting the dub.
+    if final is not literal_text and not _looks_like_target_script(final, target_lang):
+        logger.warning(
+            "cinematic adapt produced wrong-script output for %s — falling back to literal",
+            target_lang,
+        )
+        return {
+            "text": literal_text,
+            "literal": literal_text,
+            "critique": critique,
+            "error": f"adapt-wrong-script:{target_lang}",
+        }
     return {
         "text": final,
         "literal": literal_text,

backend/services/tts_backend.py

@@ -441,11 +441,11 @@ class MLXAudioBackend(TTSBackend):
     CURATED_MODELS = {
         "kokoro":      "mlx-community/Kokoro-82M-bf16",
         "csm":         "mlx-community/csm-1b-8bit",
-        "qwen3-tts":   "mlx-community/Qwen3-TTS-1.7B-4bit",
+        "qwen3-tts":   "mlx-community/Qwen3-TTS-12Hz-1.7B-VoiceDesign-4bit",
         "dia":         "mlx-community/Dia-1.6B",
-        "chatterbox":  "mlx-community/Chatterbox",
-        "melotts":     "mlx-community/MeloTTS",
-        "outetts":     "mlx-community/OuteTTS-0.3-500M",
+        "chatterbox":  "mlx-community/Chatterbox-TTS-4bit",
+        "melotts":     "mlx-community/MeloTTS-English-v3-MLX",
+        "outetts":     "mlx-community/Llama-OuteTTS-1.0-1B-4bit",
     }
     DEFAULT_MODEL_KEY = "kokoro"
 

backend/services/watermark.py

@@ -0,0 +1,298 @@
+"""
+Invisible + visible audio watermarking for OmniVoice Studio.
+
+Two layers:
+  1. **Invisible** — AudioSeal (Meta) embeds imperceptible neural watermarks
+     that survive compression, resampling, and editing. Encodes a 16-bit
+     message identifying OmniVoice as the source.
+  2. **Visible** — Optional audio signature tone prepended to exports;
+     ffmpeg-based logo overlay for video exports.
+
+Usage:
+    from services.watermark import embed_watermark, detect_watermark
+
+    # Embed (returns same shape tensor, watermarked)
+    watermarked = embed_watermark(waveform, sample_rate)
+
+    # Detect (returns dict with confidence + metadata)
+    result = detect_watermark(waveform, sample_rate)
+"""
+
+from __future__ import annotations
+
+import logging
+import math
+import struct
+import torch
+import numpy as np
+from typing import Optional
+
+from core.prefs import resolve
+
+logger = logging.getLogger("omnivoice.watermark")
+
+# ── Lazy-loaded AudioSeal models ──────────────────────────────────────────
+# Loaded on first use so cold-start isn't penalised when watermarking is off.
+_generator = None
+_detector = None
+_audioseal_available: Optional[bool] = None
+
+# 16-bit message: "OM" in ASCII = 0x4F 0x4D = 0100_1111 0100_1101
+# This is our signature — every OmniVoice-generated audio carries it.
+OMNI_MESSAGE = [0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 0, 1]
+
+
+def _check_available() -> bool:
+    """Check if AudioSeal is installed and importable."""
+    global _audioseal_available
+    if _audioseal_available is None:
+        try:
+            import audioseal  # noqa: F401
+            _audioseal_available = True
+        except ImportError:
+            _audioseal_available = False
+            logger.info("audioseal not installed — invisible watermarking disabled")
+    return _audioseal_available
+
+
+def _get_generator():
+    """Lazy-load the AudioSeal generator model."""
+    global _generator
+    if _generator is None:
+        from audioseal import AudioSeal
+        _generator = AudioSeal.load_generator("audioseal_wm_16bits")
+        _generator.eval()
+        logger.info("AudioSeal generator loaded (16-bit message mode)")
+    return _generator
+
+
+def _get_detector():
+    """Lazy-load the AudioSeal detector model."""
+    global _detector
+    if _detector is None:
+        from audioseal import AudioSeal
+        _detector = AudioSeal.load_detector("audioseal_detector_16bits")
+        _detector.eval()
+        logger.info("AudioSeal detector loaded (16-bit message mode)")
+    return _detector
+
+
+def is_enabled() -> bool:
+    """Check if invisible watermarking is enabled in user preferences."""
+    return resolve("watermark.invisible", default=True) is not False
+
+
+def is_visible_audio_enabled() -> bool:
+    """Check if audible branding tone is enabled for exports."""
+    return resolve("watermark.visible_audio", default=False) is True
+
+
+def is_visible_video_enabled() -> bool:
+    """Check if video logo overlay is enabled for exports."""
+    return resolve("watermark.visible_video", default=True) is not False
+
+
+# ── Invisible Watermark ───────────────────────────────────────────────────
+
+@torch.no_grad()
+def embed_watermark(
+    waveform: torch.Tensor,
+    sample_rate: int,
+    message: Optional[list[int]] = None,
+) -> torch.Tensor:
+    """
+    Embed an imperceptible watermark into the audio waveform.
+
+    Args:
+        waveform: Audio tensor of shape (channels, samples) or (1, channels, samples)
+        sample_rate: Sample rate of the audio
+        message: Optional 16-bit message (list of 0/1). Defaults to OMNI_MESSAGE.
+
+    Returns:
+        Watermarked waveform (same shape as input).
+    """
+    if not is_enabled() or not _check_available():
+        return waveform
+
+    try:
+        generator = _get_generator()
+        msg = torch.tensor(message or OMNI_MESSAGE, dtype=torch.int32).unsqueeze(0)
+
+        # AudioSeal expects (batch, channels, samples) — normalise input
+        original_shape = waveform.shape
+        if waveform.dim() == 2:
+            audio = waveform.unsqueeze(0)  # (1, C, S)
+        elif waveform.dim() == 1:
+            audio = waveform.unsqueeze(0).unsqueeze(0)  # (1, 1, S)
+        else:
+            audio = waveform
+
+        # AudioSeal operates at 16kHz internally; it handles resampling, but
+        # we need to inform it of the source rate for correct embedding.
+        watermarked = generator(audio, sample_rate=sample_rate, message=msg)
+
+        # Restore original shape
+        if len(original_shape) == 2:
+            watermarked = watermarked.squeeze(0)
+        elif len(original_shape) == 1:
+            watermarked = watermarked.squeeze(0).squeeze(0)
+
+        return watermarked
+
+    except Exception as e:
+        logger.warning("Watermark embedding failed (passing through original): %s", e)
+        return waveform
+
+
+@torch.no_grad()
+def detect_watermark(
+    waveform: torch.Tensor,
+    sample_rate: int,
+) -> dict:
+    """
+    Detect whether audio contains an OmniVoice watermark.
+
+    Args:
+        waveform: Audio tensor of shape (channels, samples)
+        sample_rate: Sample rate of the audio
+
+    Returns:
+        Dict with keys:
+            is_watermarked: bool
+            confidence: float (0.0–1.0)
+            message_bits: str (decoded 16-bit message)
+            is_omnivoice: bool (true if message matches OMNI_MESSAGE)
+    """
+    if not _check_available():
+        return {
+            "is_watermarked": False,
+            "confidence": 0.0,
+            "message_bits": "",
+            "is_omnivoice": False,
+            "error": "audioseal not installed",
+        }
+
+    try:
+        detector = _get_detector()
+
+        # Normalise shape to (batch, channels, samples)
+        if waveform.dim() == 2:
+            audio = waveform.unsqueeze(0)
+        elif waveform.dim() == 1:
+            audio = waveform.unsqueeze(0).unsqueeze(0)
+        else:
+            audio = waveform
+
+        result = detector.detect_watermark(audio, sample_rate=sample_rate, message_threshold=0.5)
+
+        # result is (detection_confidence, decoded_message)
+        confidence = float(result[0]) if isinstance(result, tuple) else 0.0
+        decoded_msg = result[1] if isinstance(result, tuple) and len(result) > 1 else None
+
+        # Decode message bits
+        message_bits = ""
+        is_omnivoice = False
+        if decoded_msg is not None:
+            try:
+                bits = decoded_msg.squeeze().tolist()
+                if isinstance(bits, list):
+                    message_bits = "".join(str(int(b > 0.5)) for b in bits)
+                    decoded_list = [int(b > 0.5) for b in bits]
+                    is_omnivoice = decoded_list == OMNI_MESSAGE
+            except Exception:
+                pass
+
+        return {
+            "is_watermarked": confidence > 0.5,
+            "confidence": round(confidence, 4),
+            "message_bits": message_bits,
+            "is_omnivoice": is_omnivoice,
+            "source": "OmniVoice Studio" if is_omnivoice else "unknown",
+        }
+
+    except Exception as e:
+        logger.warning("Watermark detection failed: %s", e)
+        return {
+            "is_watermarked": False,
+            "confidence": 0.0,
+            "message_bits": "",
+            "is_omnivoice": False,
+            "error": str(e),
+        }
+
+
+# ── Visible Audio Brand ──────────────────────────────────────────────────
+
+def generate_brand_tone(sample_rate: int = 24000, duration_s: float = 0.4) -> torch.Tensor:
+    """
+    Generate a short, distinctive audio signature tone.
+
+    A soft ascending three-note chime (C5→E5→G5) that serves as the
+    OmniVoice "sound logo". Gentle enough for professional use.
+
+    Returns:
+        Tensor of shape (1, samples).
+    """
+    notes_hz = [523.25, 659.25, 783.99]  # C5, E5, G5
+    note_dur = duration_s / len(notes_hz)
+    samples_per_note = int(note_dur * sample_rate)
+    total_samples = samples_per_note * len(notes_hz)
+
+    tone = torch.zeros(1, total_samples)
+    t = torch.linspace(0, note_dur, samples_per_note)
+
+    for idx, freq in enumerate(notes_hz):
+        # Sine wave with exponential decay envelope
+        envelope = torch.exp(-t * 6.0) * 0.15  # quiet — 15% amplitude
+        wave = torch.sin(2 * math.pi * freq * t) * envelope
+        start = idx * samples_per_note
+        tone[0, start : start + samples_per_note] = wave
+
+    # Fade out the last 20%
+    fade_len = int(total_samples * 0.2)
+    if fade_len > 0:
+        tone[0, -fade_len:] *= torch.linspace(1.0, 0.0, fade_len)
+
+    return tone
+
+
+def apply_audio_brand(
+    waveform: torch.Tensor,
+    sample_rate: int,
+) -> torch.Tensor:
+    """
+    Prepend the OmniVoice brand tone to a waveform (for final exports only).
+
+    Returns:
+        Tensor with brand tone + original audio concatenated.
+    """
+    if not is_visible_audio_enabled():
+        return waveform
+
+    brand = generate_brand_tone(sample_rate=sample_rate)
+    # Add 100ms silence gap between brand and content
+    gap = torch.zeros(1, int(0.1 * sample_rate))
+    return torch.cat([brand, gap, waveform], dim=-1)
+
+
+# ── Video Logo Overlay ────────────────────────────────────────────────────
+
+def get_ffmpeg_overlay_args(logo_path: str, duration_s: float = 5.0) -> list[str]:
+    """
+    Build ffmpeg filter args to overlay the OmniVoice logo in the bottom-right
+    corner with a fade-out after `duration_s` seconds.
+
+    Returns:
+        List of ffmpeg filter_complex args.
+    """
+    if not is_visible_video_enabled():
+        return []
+
+    # Scale logo to 64px height, place bottom-right with 20px padding,
+    # fade out after duration_s seconds.
+    filter_str = (
+        f"[1:v]scale=-1:64,format=rgba,"
+        f"fade=t=out:st={duration_s - 1}:d=1:alpha=1[logo];"
+        f"[0:v][logo]overlay=W-w-20:H-h-20:enable='lte(t,{duration_s})'"
+    )
+    return ["-filter_complex", filter_str]

backend/utils/hf_progress.py

@@ -18,6 +18,7 @@ Usage:
 """
 from __future__ import annotations
 
+import contextvars
 import itertools
 import logging
 import threading
@@ -25,6 +26,14 @@ from typing import Callable, Optional
 
 logger = logging.getLogger("omnivoice.hf_progress")
 
+# Context-scoped active repo_id. Set in the install/delete handler so every
+# tqdm event fired while a snapshot_download runs can be stamped with the
+# originating repo, letting the frontend route per-file events to the right
+# row instead of heuristically matching filename substrings.
+current_repo_id: contextvars.ContextVar[Optional[str]] = contextvars.ContextVar(
+    "omnivoice_hf_progress_repo_id", default=None,
+)
+
 # Event shape forwarded to listeners. Typed loosely on purpose — SSE encodes
 # it as JSON so consumers read the dict directly.
 #   {
@@ -61,6 +70,11 @@ def unregister_listener(lid: int) -> None:
 def _emit(event: ProgressEvent) -> None:
     """Fan out to all registered listeners. Never raise — a bad listener
     shouldn't break a download."""
+    # Stamp the active repo_id so frontends can route events to the right
+    # row. Only set when this emit is happening inside an install handler.
+    rid = current_repo_id.get()
+    if rid is not None and "repo_id" not in event:
+        event = {**event, "repo_id": rid}
     with _listener_lock:
         listeners = list(_listeners.values())
     for cb in listeners:
@@ -70,6 +84,12 @@ def _emit(event: ProgressEvent) -> None:
             logger.debug("hf_progress listener raised: %s", e)
 
 
+def emit(event: ProgressEvent) -> None:
+    """Public emit — lets non-tqdm operations (delete, verify, etc.) push
+    lifecycle events onto the same SSE stream."""
+    _emit(event)
+
+
 def install() -> None:
     """Monkey-patch `huggingface_hub`'s tqdm so every download reports to our
     listeners. Safe to call multiple times — second call is a no-op."""

bun.lock

@@ -6,6 +6,8 @@
       "name": "omnivoice-studio-monorepo",
       "devDependencies": {
         "concurrently": "^9.2.1",
+        "kill-port-process": "^4.0.2",
+        "playwright": "^1.59.1",
         "turbo": "^2.9.6",
         "typescript": "^6.0.3",
         "wait-on": "^9.0.5",
@@ -13,22 +15,38 @@
     },
     "frontend": {
       "name": "omnivoice-studio",
-      "version": "0.0.0",
+      "version": "0.2.3",
       "dependencies": {
         "@fontsource-variable/inter": "^5.2.8",
         "@fontsource-variable/source-serif-4": "^5.2.9",
         "@fontsource/ibm-plex-mono": "^5.2.7",
+        "@radix-ui/react-dialog": "^1.1.15",
+        "@radix-ui/react-dropdown-menu": "^2.1.16",
+        "@radix-ui/react-popover": "^1.1.15",
+        "@radix-ui/react-progress": "^1.1.8",
+        "@radix-ui/react-select": "^2.2.6",
+        "@radix-ui/react-slider": "^1.3.6",
+        "@radix-ui/react-tabs": "^1.1.13",
+        "@radix-ui/react-toggle-group": "^1.1.11",
+        "@radix-ui/react-tooltip": "^1.2.8",
+        "@tailwindcss/vite": "4",
+        "@tanstack/react-query": "^5.100.4",
+        "@tanstack/react-table": "^8.21.3",
+        "@tanstack/react-virtual": "^3.13.24",
         "@tauri-apps/plugin-dialog": "^2.7.0",
-        "@tauri-apps/plugin-process": "^2.3.0",
-        "@tauri-apps/plugin-updater": "^2.9.0",
+        "@tauri-apps/plugin-opener": "^2.5.3",
+        "@tauri-apps/plugin-process": "^2.3.1",
+        "@tauri-apps/plugin-updater": "^2.10.1",
         "@tauri-apps/plugin-window-state": "^2.4.1",
         "lucide-react": "^1.8.0",
+        "qrcode.react": "^4.2.0",
         "react": "^19.2.5",
         "react-dom": "^19.2.5",
         "react-hot-toast": "^2.6.0",
         "react-window": "^2.2.7",
+        "tailwindcss": "4",
         "wavesurfer.js": "^7.12.6",
-        "zustand": "^5.0.2",
+        "zustand": "^5.0.12",
       },
       "devDependencies": {
         "@eslint/js": "^10.0.1",
@@ -37,12 +55,12 @@
         "@types/react": "^19.2.14",
         "@types/react-dom": "^19.2.3",
         "@vitejs/plugin-react": "^6.0.1",
-        "eslint": "^10.2.0",
-        "eslint-plugin-react-hooks": "^7.0.1",
+        "eslint": "^10.2.1",
+        "eslint-plugin-react-hooks": "^7.1.1",
         "eslint-plugin-react-refresh": "^0.5.2",
-        "globals": "^17.4.0",
-        "typescript": "^5.7.3",
-        "vite": "^8.0.8",
+        "globals": "^17.5.0",
+        "typescript": "^6.0.3",
+        "vite": "^8.0.9",
       },
     },
   },
@@ -101,6 +119,14 @@
 
     "@eslint/plugin-kit": ["@eslint/plugin-kit@0.7.1", "", { "dependencies": { "@eslint/core": "^1.2.1", "levn": "^0.4.1" } }, "sha512-rZAP3aVgB9ds9KOeUSL+zZ21hPmo8dh6fnIFwRQj5EAZl9gzR7wxYbYXYysAM8CTqGmUGyp2S4kUdV17MnGuWQ=="],
 
+    "@floating-ui/core": ["@floating-ui/core@1.7.5", "", { "dependencies": { "@floating-ui/utils": "^0.2.11" } }, "sha512-1Ih4WTWyw0+lKyFMcBHGbb5U5FtuHJuujoyyr5zTaWS5EYMeT6Jb2AuDeftsCsEuchO+mM2ij5+q9crhydzLhQ=="],
+
+    "@floating-ui/dom": ["@floating-ui/dom@1.7.6", "", { "dependencies": { "@floating-ui/core": "^1.7.5", "@floating-ui/utils": "^0.2.11" } }, "sha512-9gZSAI5XM36880PPMm//9dfiEngYoC6Am2izES1FF406YFsjvyBMmeJ2g4SAju3xWwtuynNRFL2s9hgxpLI5SQ=="],
+
+    "@floating-ui/react-dom": ["@floating-ui/react-dom@2.1.8", "", { "dependencies": { "@floating-ui/dom": "^1.7.6" }, "peerDependencies": { "react": ">=16.8.0", "react-dom": ">=16.8.0" } }, "sha512-cC52bHwM/n/CxS87FH0yWdngEZrjdtLW/qVruo68qg+prK7ZQ4YGdut2GyDVpoGeAYe/h899rVeOVm6Oi40k2A=="],
+
+    "@floating-ui/utils": ["@floating-ui/utils@0.2.11", "", {}, "sha512-RiB/yIh78pcIxl6lLMG0CgBXAZ2Y0eVHqMPYugu+9U0AeT6YBeiJpf7lbdJNIugFP5SIjwNRgo4DhR1Qxi26Gg=="],
+
     "@fontsource-variable/inter": ["@fontsource-variable/inter@5.2.8", "", {}, "sha512-kOfP2D+ykbcX/P3IFnokOhVRNoTozo5/JxhAIVYLpea/UBmCQ/YWPBfWIDuBImXX/15KH+eKh4xpEUyS2sQQGQ=="],
 
     "@fontsource-variable/source-serif-4": ["@fontsource-variable/source-serif-4@5.2.9", "", {}, "sha512-PPcxjLFk/fS0WHg79pDM2YNvz61kC+oYZ5cWZZyCS0DHpJncmuYOuiZAsvj4tDxlWPBEvxxcRLQQNmSaRbPkqw=="],
@@ -137,44 +163,166 @@
 
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+    "@tailwindcss/oxide-darwin-arm64": ["@tailwindcss/oxide-darwin-arm64@4.2.4", "", { "os": "darwin", "cpu": "arm64" }, "sha512-tSC/Kbqpz/5/o/C2sG7QvOxAKqyd10bq+ypZNf+9Fi2TvbVbv1zNpcEptcsU7DPROaSbVgUXmrzKhurFvo5eDg=="],
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+    "@tailwindcss/oxide-freebsd-x64": ["@tailwindcss/oxide-freebsd-x64@4.2.4", "", { "os": "freebsd", "cpu": "x64" }, "sha512-BoMIB4vMQtZsXdGLVc2z+P9DbETkiopogfWZKbWwM8b/1Vinbs4YcUwo+kM/KeLkX3Ygrf4/PsRndKaYhS8Eiw=="],
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+    "@tailwindcss/oxide-linux-arm-gnueabihf": ["@tailwindcss/oxide-linux-arm-gnueabihf@4.2.4", "", { "os": "linux", "cpu": "arm" }, "sha512-7pIHBLTHYRAlS7V22JNuTh33yLH4VElwKtB3bwchK/UaKUPpQ0lPQiOWcbm4V3WP2I6fNIJ23vABIvoy2izdwA=="],
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+
+    "@tailwindcss/oxide-wasm32-wasi": ["@tailwindcss/oxide-wasm32-wasi@4.2.4", "", { "dependencies": { "@emnapi/core": "^1.8.1", "@emnapi/runtime": "^1.8.1", "@emnapi/wasi-threads": "^1.1.0", "@napi-rs/wasm-runtime": "^1.1.1", "@tybys/wasm-util": "^0.10.1", "tslib": "^2.8.1" }, "cpu": "none" }, "sha512-FQsqApeor8Fo6gUEklzmaa9994orJZZDBAlQpK2Mq+DslRKFJeD6AjHpBQ0kZFQohVr8o85PPh8eOy86VlSCmw=="],
+
+    "@tailwindcss/oxide-win32-arm64-msvc": ["@tailwindcss/oxide-win32-arm64-msvc@4.2.4", "", { "os": "win32", "cpu": "arm64" }, "sha512-L9BXqxC4ToVgwMFqj3pmZRqyHEztulpUJzCxUtLjobMCzTPsGt1Fa9enKbOpY2iIyVtaHNeNvAK8ERP/64sqGQ=="],
+
+    "@tailwindcss/oxide-win32-x64-msvc": ["@tailwindcss/oxide-win32-x64-msvc@4.2.4", "", { "os": "win32", "cpu": "x64" }, "sha512-ESlKG0EpVJQwRjXDDa9rLvhEAh0mhP1sF7sap9dNZT0yyl9SAG6T7gdP09EH0vIv0UNTlo6jPWyujD6559fZvw=="],
+
+    "@tailwindcss/vite": ["@tailwindcss/vite@4.2.4", "", { "dependencies": { "@tailwindcss/node": "4.2.4", "@tailwindcss/oxide": "4.2.4", "tailwindcss": "4.2.4" }, "peerDependencies": { "vite": "^5.2.0 || ^6 || ^7 || ^8" } }, "sha512-pCvohwOCspk3ZFn6eJzrrX3g4n2JY73H6MmYC87XfGPyTty4YsCjYTMArRZm/zOI8dIt3+EcrLHAFPe5A4bgtw=="],
+
+    "@tanstack/query-core": ["@tanstack/query-core@5.100.4", "", {}, "sha512-LdW/DDImiw9g4ukyndlrifIXPFpoQjNybCAIDBcPvdYu9iUIhAKwhznfAATe2dJBonhm0O3ksoCMmVTUxN89uA=="],
+
+    "@tanstack/react-query": ["@tanstack/react-query@5.100.4", "", { "dependencies": { "@tanstack/query-core": "5.100.4" }, "peerDependencies": { "react": "^18 || ^19" } }, "sha512-L6n5UWBvnMuYaZTu6WgTbl2mJ7fob1NIdL2vIFo05R/mkr9XvP5PmesZOBiicxzhDAuUurYIG+ZFONbvarEFtQ=="],
+
+    "@tanstack/react-table": ["@tanstack/react-table@8.21.3", "", { "dependencies": { "@tanstack/table-core": "8.21.3" }, "peerDependencies": { "react": ">=16.8", "react-dom": ">=16.8" } }, "sha512-5nNMTSETP4ykGegmVkhjcS8tTLW6Vl4axfEGQN3v0zdHYbK4UfoqfPChclTrJ4EoK9QynqAu9oUf8VEmrpZ5Ww=="],
+
+    "@tanstack/react-virtual": ["@tanstack/react-virtual@3.13.24", "", { "dependencies": { "@tanstack/virtual-core": "3.14.0" }, "peerDependencies": { "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0", "react-dom": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0" } }, "sha512-aIJvz5OSkhNIhZIpYivrxrPTKYsjW9Uzy+sP/mx0S3sev2HyvPb7xmjbYvokzEpfgYHy/HjzJ2zFAETuUfgCpg=="],
+
+    "@tanstack/table-core": ["@tanstack/table-core@8.21.3", "", {}, "sha512-ldZXEhOBb8Is7xLs01fR3YEc3DERiz5silj8tnGkFZytt1abEvl/GhUmCE0PMLaMPTa3Jk4HbKmRlHmu+gCftg=="],
+
+    "@tanstack/virtual-core": ["@tanstack/virtual-core@3.14.0", "", {}, "sha512-JLANqGy/D6k4Ujmh8Tr25lGimuOXNiaVyXaCAZS0W+1390sADdGnyUdSWNIfd49gebtIxGMij4IktRVzrdr12Q=="],
+
     "@tauri-apps/api": ["@tauri-apps/api@2.10.1", "", {}, "sha512-hKL/jWf293UDSUN09rR69hrToyIXBb8CjGaWC7gfinvnQrBVvnLr08FeFi38gxtugAVyVcTa5/FD/Xnkb1siBw=="],
 
     "@tauri-apps/cli": ["@tauri-apps/cli@2.10.1", "", { "optionalDependencies": { "@tauri-apps/cli-darwin-arm64": "2.10.1", "@tauri-apps/cli-darwin-x64": "2.10.1", "@tauri-apps/cli-linux-arm-gnueabihf": "2.10.1", "@tauri-apps/cli-linux-arm64-gnu": "2.10.1", "@tauri-apps/cli-linux-arm64-musl": "2.10.1", "@tauri-apps/cli-linux-riscv64-gnu": "2.10.1", "@tauri-apps/cli-linux-x64-gnu": "2.10.1", "@tauri-apps/cli-linux-x64-musl": "2.10.1", "@tauri-apps/cli-win32-arm64-msvc": "2.10.1", "@tauri-apps/cli-win32-ia32-msvc": "2.10.1", "@tauri-apps/cli-win32-x64-msvc": "2.10.1" }, "bin": { "tauri": "tauri.js" } }, "sha512-jQNGF/5quwORdZSSLtTluyKQ+o6SMa/AUICfhf4egCGFdMHqWssApVgYSbg+jmrZoc8e1DscNvjTnXtlHLS11g=="],
@@ -203,6 +351,8 @@
 
     "@tauri-apps/plugin-dialog": ["@tauri-apps/plugin-dialog@2.7.0", "", { "dependencies": { "@tauri-apps/api": "^2.10.1" } }, "sha512-4nS/hfGMGCXiAS3LtVjH9AgsSAPJeG/7R+q8agTFqytjnMa4Zq95Bq8WzVDkckpanX+yyRHXnRtrKXkANKDHvw=="],
 
+    "@tauri-apps/plugin-opener": ["@tauri-apps/plugin-opener@2.5.3", "", { "dependencies": { "@tauri-apps/api": "^2.8.0" } }, "sha512-CCcUltXMOfUEArbf3db3kCE7Ggy1ExBEBl51Ko2ODJ6GDYHRp1nSNlQm5uNCFY5k7/ufaK5Ib3Du/Zir19IYQQ=="],
+
     "@tauri-apps/plugin-process": ["@tauri-apps/plugin-process@2.3.1", "", { "dependencies": { "@tauri-apps/api": "^2.8.0" } }, "sha512-nCa4fGVaDL/B9ai03VyPOjfAHRHSBz5v6F/ObsB73r/dA3MHHhZtldaDMIc0V/pnUw9ehzr2iEG+XkSEyC0JJA=="],
 
     "@tauri-apps/plugin-updater": ["@tauri-apps/plugin-updater@2.10.1", "", { "dependencies": { "@tauri-apps/api": "^2.10.1" } }, "sha512-NFYMg+tWOZPJdzE/PpFj2qfqwAWwNS3kXrb1tm1gnBJ9mYzZ4WDRrwy8udzWoAnfGCHLuePNLY1WVCNHnh3eRA=="],
@@ -245,6 +395,8 @@
 
     "ansi-styles": ["ansi-styles@4.3.0", "", { "dependencies": { "color-convert": "^2.0.1" } }, "sha512-zbB9rCJAT1rbjiVDb2hqKFHNYLxgtk8NURxZ3IZwD3F6NtxbXZQCnnSi1Lkx+IDohdPlFp222wVALIheZJQSEg=="],
 
+    "aria-hidden": ["aria-hidden@1.2.6", "", { "dependencies": { "tslib": "^2.0.0" } }, "sha512-ik3ZgC9dY/lYVVM++OISsaYDeg1tb0VtP5uL3ouh1koGOaUMDPpbFIei4JkFimWUFPn90sbMNMXQAIVOlnYKJA=="],
+
     "asynckit": ["asynckit@0.4.0", "", {}, "sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q=="],
 
     "axios": ["axios@1.15.0", "", { "dependencies": { "follow-redirects": "^1.15.11", "form-data": "^4.0.5", "proxy-from-env": "^2.1.0" } }, "sha512-wWyJDlAatxk30ZJer+GeCWS209sA42X+N5jU2jy6oHTp7ufw8uzUTVFBX9+wTfAlhiJXGS0Bq7X6efruWjuK9Q=="],
@@ -287,12 +439,16 @@
 
     "detect-libc": ["detect-libc@2.1.2", "", {}, "sha512-Btj2BOOO83o3WyH59e8MgXsxEQVcarkUOpEYrubB0urwnN10yQ364rsiByU11nZlqWYZm05i/of7io4mzihBtQ=="],
 
+    "detect-node-es": ["detect-node-es@1.1.0", "", {}, "sha512-ypdmJU/TbBby2Dxibuv7ZLW3Bs1QEmM7nHjEANfohJLvE0XVujisn1qPJcZxg+qDucsr+bP6fLD1rPS3AhJ7EQ=="],
+
     "dunder-proto": ["dunder-proto@1.0.1", "", { "dependencies": { "call-bind-apply-helpers": "^1.0.1", "es-errors": "^1.3.0", "gopd": "^1.2.0" } }, "sha512-KIN/nDJBQRcXw0MLVhZE9iQHmG68qAVIBg9CqmUYjmQIhgij9U5MFvrqkUL5FbtyyzZuOeOt0zdeRe4UY7ct+A=="],
 
     "electron-to-chromium": ["electron-to-chromium@1.5.334", "", {}, "sha512-mgjZAz7Jyx1SRCwEpy9wefDS7GvNPazLthHg8eQMJ76wBdGQQDW33TCrUTvQ4wzpmOrv2zrFoD3oNufMdyMpog=="],
 
     "emoji-regex": ["emoji-regex@8.0.0", "", {}, "sha512-MSjYzcWNOA0ewAHpz0MxpYFvwg6yjy1NG3xteoqz644VCo/RPgnr1/GGt+ic3iJTzQ8Eu3TdM14SawnVUmGE6A=="],
 
+    "enhanced-resolve": ["enhanced-resolve@5.21.0", "", { "dependencies": { "graceful-fs": "^4.2.4", "tapable": "^2.3.3" } }, "sha512-otxSQPw4lkOZWkHpB3zaEQs6gWYEsmX4xQF68ElXC/TWvGxGMSGOvoNbaLXm6/cS/fSfHtsEdw90y20PCd+sCA=="],
+
     "es-define-property": ["es-define-property@1.0.1", "", {}, "sha512-e3nRfgfUZ4rNGL232gUgX06QNyyez04KdjFrF+LTRoOXmrOgFKDg4BCdsjW8EnT69eqdYGmRpJwiPVYNrCaW3g=="],
 
     "es-errors": ["es-errors@1.3.0", "", {}, "sha512-Zf5H2Kxt2xjTvbJvP2ZWLEICxA6j+hAmMzIlypy4xcBg1vKVnx89Wy0GbS+kf5cwCVFFzdCFh2XSCFNULS6csw=="],
@@ -305,9 +461,9 @@
 
     "escape-string-regexp": ["escape-string-regexp@4.0.0", "", {}, "sha512-TtpcNJ3XAzx3Gq8sWRzJaVajRs0uVxA2YAkdb1jm2YkPz4G6egUFAyA3n5vtEIZefPk5Wa4UXbKuS5fKkJWdgA=="],
 
-    "eslint": ["eslint@10.2.0", "", { "dependencies": { "@eslint-community/eslint-utils": "^4.8.0", "@eslint-community/regexpp": "^4.12.2", "@eslint/config-array": "^0.23.4", "@eslint/config-helpers": "^0.5.4", "@eslint/core": "^1.2.0", "@eslint/plugin-kit": "^0.7.0", "@humanfs/node": "^0.16.6", "@humanwhocodes/module-importer": "^1.0.1", "@humanwhocodes/retry": "^0.4.2", "@types/estree": "^1.0.6", "ajv": "^6.14.0", "cross-spawn": "^7.0.6", "debug": "^4.3.2", "escape-string-regexp": "^4.0.0", "eslint-scope": "^9.1.2", "eslint-visitor-keys": "^5.0.1", "espree": "^11.2.0", "esquery": "^1.7.0", "esutils": "^2.0.2", "fast-deep-equal": "^3.1.3", "file-entry-cache": "^8.0.0", "find-up": "^5.0.0", "glob-parent": "^6.0.2", "ignore": "^5.2.0", "imurmurhash": "^0.1.4", "is-glob": "^4.0.0", "json-stable-stringify-without-jsonify": "^1.0.1", "minimatch": "^10.2.4", "natural-compare": "^1.4.0", "optionator": "^0.9.3" }, "peerDependencies": { "jiti": "*" }, "optionalPeers": ["jiti"], "bin": { "eslint": "bin/eslint.js" } }, "sha512-+L0vBFYGIpSNIt/KWTpFonPrqYvgKw1eUI5Vn7mEogrQcWtWYtNQ7dNqC+px/J0idT3BAkiWrhfS7k+Tum8TUA=="],
+    "eslint": ["eslint@10.2.1", "", { "dependencies": { "@eslint-community/eslint-utils": "^4.8.0", "@eslint-community/regexpp": "^4.12.2", "@eslint/config-array": "^0.23.5", "@eslint/config-helpers": "^0.5.5", "@eslint/core": "^1.2.1", "@eslint/plugin-kit": "^0.7.1", "@humanfs/node": "^0.16.6", "@humanwhocodes/module-importer": "^1.0.1", "@humanwhocodes/retry": "^0.4.2", "@types/estree": "^1.0.6", "ajv": "^6.14.0", "cross-spawn": "^7.0.6", "debug": "^4.3.2", "escape-string-regexp": "^4.0.0", "eslint-scope": "^9.1.2", "eslint-visitor-keys": "^5.0.1", "espree": "^11.2.0", "esquery": "^1.7.0", "esutils": "^2.0.2", "fast-deep-equal": "^3.1.3", "file-entry-cache": "^8.0.0", "find-up": "^5.0.0", "glob-parent": "^6.0.2", "ignore": "^5.2.0", "imurmurhash": "^0.1.4", "is-glob": "^4.0.0", "json-stable-stringify-without-jsonify": "^1.0.1", "minimatch": "^10.2.4", "natural-compare": "^1.4.0", "optionator": "^0.9.3" }, "peerDependencies": { "jiti": "*" }, "optionalPeers": ["jiti"], "bin": { "eslint": "bin/eslint.js" } }, "sha512-wiyGaKsDgqXvF40P8mDwiUp/KQjE1FdrIEJsM8PZ3XCiniTMXS3OHWWUe5FI5agoCnr8x4xPrTDZuxsBlNHl+Q=="],
 
-    "eslint-plugin-react-hooks": ["eslint-plugin-react-hooks@7.0.1", "", { "dependencies": { "@babel/core": "^7.24.4", "@babel/parser": "^7.24.4", "hermes-parser": "^0.25.1", "zod": "^3.25.0 || ^4.0.0", "zod-validation-error": "^3.5.0 || ^4.0.0" }, "peerDependencies": { "eslint": "^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 || ^7.0.0 || ^8.0.0-0 || ^9.0.0" } }, "sha512-O0d0m04evaNzEPoSW+59Mezf8Qt0InfgGIBJnpC0h3NH/WjUAR7BIKUfysC6todmtiZ/A0oUVS8Gce0WhBrHsA=="],
+    "eslint-plugin-react-hooks": ["eslint-plugin-react-hooks@7.1.1", "", { "dependencies": { "@babel/core": "^7.24.4", "@babel/parser": "^7.24.4", "hermes-parser": "^0.25.1", "zod": "^3.25.0 || ^4.0.0", "zod-validation-error": "^3.5.0 || ^4.0.0" }, "peerDependencies": { "eslint": "^3.0.0 || ^4.0.0 || ^5.0.0 || ^6.0.0 || ^7.0.0 || ^8.0.0-0 || ^9.0.0 || ^10.0.0" } }, "sha512-f2I7Gw6JbvCexzIInuSbZpfdQ44D7iqdWX01FKLvrPgqxoE7oMj8clOfto8U6vYiz4yd5oKu39rRSVOe1zRu0g=="],
 
     "eslint-plugin-react-refresh": ["eslint-plugin-react-refresh@0.5.2", "", { "peerDependencies": { "eslint": "^9 || ^10" } }, "sha512-hmgTH57GfzoTFjVN0yBwTggnsVUF2tcqi7RJZHqi9lIezSs4eFyAMktA68YD4r5kNw1mxyY4dmkyoFDb3FIqrA=="],
 
@@ -325,6 +481,8 @@
 
     "esutils": ["esutils@2.0.3", "", {}, "sha512-kVscqXk4OCp68SZ0dkgEKVi6/8ij300KBWTJq32P/dYeWTSwK41WyTxalN1eRmA5Z9UU/LX9D7FWSmV9SAYx6g=="],
 
+    "execa": ["execa@9.6.1", "", { "dependencies": { "@sindresorhus/merge-streams": "^4.0.0", "cross-spawn": "^7.0.6", "figures": "^6.1.0", "get-stream": "^9.0.0", "human-signals": "^8.0.1", "is-plain-obj": "^4.1.0", "is-stream": "^4.0.1", "npm-run-path": "^6.0.0", "pretty-ms": "^9.2.0", "signal-exit": "^4.1.0", "strip-final-newline": "^4.0.0", "yoctocolors": "^2.1.1" } }, "sha512-9Be3ZoN4LmYR90tUoVu2te2BsbzHfhJyfEiAVfz7N5/zv+jduIfLrV2xdQXOHbaD6KgpGdO9PRPM1Y4Q9QkPkA=="],
+
     "fast-deep-equal": ["fast-deep-equal@3.1.3", "", {}, "sha512-f3qQ9oQy9j2AhBe/H9VC91wLmKBCCU/gDOnKNAYG5hswO7BLKj09Hc5HYNz9cGI++xlpDCIgDaitVs03ATR84Q=="],
 
     "fast-json-stable-stringify": ["fast-json-stable-stringify@2.1.0", "", {}, "sha512-lhd/wF+Lk98HZoTCtlVraHtfh5XYijIjalXck7saUtuanSDyLMxnHhSXEDJqHxD7msR8D0uCmqlkwjCV8xvwHw=="],
@@ -333,6 +491,8 @@
 
     "fdir": ["fdir@6.5.0", "", { "peerDependencies": { "picomatch": "^3 || ^4" }, "optionalPeers": ["picomatch"] }, "sha512-tIbYtZbucOs0BRGqPJkshJUYdL+SDH7dVM8gjy+ERp3WAUjLEFJE+02kanyHtwjWOnwrKYBiwAmM0p4kLJAnXg=="],
 
+    "figures": ["figures@6.1.0", "", { "dependencies": { "is-unicode-supported": "^2.0.0" } }, "sha512-d+l3qxjSesT4V7v2fh+QnmFnUWv9lSpjarhShNTgBOfA0ttejbQUAlHLitbjkoRiDulW0OPoQPYIGhIC8ohejg=="],
+
     "file-entry-cache": ["file-entry-cache@8.0.0", "", { "dependencies": { "flat-cache": "^4.0.0" } }, "sha512-XXTUwCvisa5oacNGRP9SfNtYBNAMi+RPwBFmblZEF7N7swHYQS6/Zfk7SRwx4D5j3CH211YNRco1DEMNVfZCnQ=="],
 
     "find-up": ["find-up@5.0.0", "", { "dependencies": { "locate-path": "^6.0.0", "path-exists": "^4.0.0" } }, "sha512-78/PXT1wlLLDgTzDs7sjq9hzz0vXD+zn+7wypEe4fXQxCmdmqfGsEPQxmiCSQI3ajFV91bVSsvNtrJRiW6nGng=="],
@@ -345,7 +505,7 @@
 
     "form-data": ["form-data@4.0.5", "", { "dependencies": { "asynckit": "^0.4.0", "combined-stream": "^1.0.8", "es-set-tostringtag": "^2.1.0", "hasown": "^2.0.2", "mime-types": "^2.1.12" } }, "sha512-8RipRLol37bNs2bhoV67fiTEvdTrbMUYcFTiy3+wuuOnUog2QBHCZWXDRijWQfAkhBj2Uf5UnVaiWwA5vdd82w=="],
 
-    "fsevents": ["fsevents@2.3.3", "", { "os": "darwin" }, "sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw=="],
+    "fsevents": ["fsevents@2.3.2", "", { "os": "darwin" }, "sha512-xiqMQR4xAeHTuB9uWm+fFRcIOgKBMiOBP+eXiyT7jsgVCq1bkVygt00oASowB7EdtpOHaaPgKt812P9ab+DDKA=="],
 
     "function-bind": ["function-bind@1.1.2", "", {}, "sha512-7XHNxH7qX9xG5mIwxkhumTox/MIRNcOgDrxWsMt2pAr23WHp6MrRlN7FBSFpCpr+oVO0F744iUgR82nJMfG2SA=="],
 
@@ -355,16 +515,24 @@
 
     "get-intrinsic": ["get-intrinsic@1.3.0", "", { "dependencies": { "call-bind-apply-helpers": "^1.0.2", "es-define-property": "^1.0.1", "es-errors": "^1.3.0", "es-object-atoms": "^1.1.1", "function-bind": "^1.1.2", "get-proto": "^1.0.1", "gopd": "^1.2.0", "has-symbols": "^1.1.0", "hasown": "^2.0.2", "math-intrinsics": "^1.1.0" } }, "sha512-9fSjSaos/fRIVIp+xSJlE6lfwhES7LNtKaCBIamHsjr2na1BiABJPo0mOjjz8GJDURarmCPGqaiVg5mfjb98CQ=="],
 
+    "get-nonce": ["get-nonce@1.0.1", "", {}, "sha512-FJhYRoDaiatfEkUK8HKlicmu/3SGFD51q3itKDGoSTysQJBnfOcxU5GxnhE1E6soB76MbT0MBtnKJuXyAx+96Q=="],
+
     "get-proto": ["get-proto@1.0.1", "", { "dependencies": { "dunder-proto": "^1.0.1", "es-object-atoms": "^1.0.0" } }, "sha512-sTSfBjoXBp89JvIKIefqw7U2CCebsc74kiY6awiGogKtoSGbgjYE/G/+l9sF3MWFPNc9IcoOC4ODfKHfxFmp0g=="],
 
+    "get-stream": ["get-stream@9.0.1", "", { "dependencies": { "@sec-ant/readable-stream": "^0.4.1", "is-stream": "^4.0.1" } }, "sha512-kVCxPF3vQM/N0B1PmoqVUqgHP+EeVjmZSQn+1oCRPxd2P21P2F19lIgbR3HBosbB1PUhOAoctJnfEn2GbN2eZA=="],
+
+    "get-them-args": ["get-them-args@1.3.2", "", {}, "sha512-LRn8Jlk+DwZE4GTlDbT3Hikd1wSHgLMme/+7ddlqKd7ldwR6LjJgTVWzBnR01wnYGe4KgrXjg287RaI22UHmAw=="],
+
     "glob-parent": ["glob-parent@6.0.2", "", { "dependencies": { "is-glob": "^4.0.3" } }, "sha512-XxwI8EOhVQgWp6iDL+3b0r86f4d6AX6zSU55HfB4ydCEuXLXc5FcYeOu+nnGftS4TEju/11rt4KJPTMgbfmv4A=="],
 
-    "globals": ["globals@17.4.0", "", {}, "sha512-hjrNztw/VajQwOLsMNT1cbJiH2muO3OROCHnbehc8eY5JyD2gqz4AcMHPqgaOR59DjgUjYAYLeH699g/eWi2jw=="],
+    "globals": ["globals@17.5.0", "", {}, "sha512-qoV+HK2yFl/366t2/Cb3+xxPUo5BuMynomoDmiaZBIdbs+0pYbjfZU+twLhGKp4uCZ/+NbtpVepH5bGCxRyy2g=="],
 
     "goober": ["goober@2.1.18", "", { "peerDependencies": { "csstype": "^3.0.10" } }, "sha512-2vFqsaDVIT9Gz7N6kAL++pLpp41l3PfDuusHcjnGLfR6+huZkl6ziX+zgVC3ZxpqWhzH6pyDdGrCeDhMIvwaxw=="],
 
     "gopd": ["gopd@1.2.0", "", {}, "sha512-ZUKRh6/kUFoAiTAtTYPZJ3hw9wNxx+BIBOijnlG9PnrJsCcSjs1wyyD6vJpaYtgnzDrKYRSqf3OO6Rfa93xsRg=="],
 
+    "graceful-fs": ["graceful-fs@4.2.11", "", {}, "sha512-RbJ5/jmFcNNCcDV5o9eTnBLJ/HszWV0P73bc+Ff4nS/rJj+YaS6IGyiOL0VoBYX+l1Wrl3k63h/KrH+nhJ0XvQ=="],
+
     "has-flag": ["has-flag@4.0.0", "", {}, "sha512-EykJT/Q1KjTWctppgIAgfSO0tKVuZUjhgMr17kqTumMl6Afv3EISleU7qZUzoXDFTAHTDC4NOoG/ZxU3EvlMPQ=="],
 
     "has-symbols": ["has-symbols@1.1.0", "", {}, "sha512-1cDNdwJ2Jaohmb3sg4OmKaMBwuC48sYni5HUw2DvsC8LjGTLK9h+eb1X6RyuOHe4hT0ULCW68iomhjUoKUqlPQ=="],
@@ -377,6 +545,8 @@
 
     "hermes-parser": ["hermes-parser@0.25.1", "", { "dependencies": { "hermes-estree": "0.25.1" } }, "sha512-6pEjquH3rqaI6cYAXYPcz9MS4rY6R4ngRgrgfDshRptUZIc3lw0MCIJIGDj9++mfySOuPTHB4nrSW99BCvOPIA=="],
 
+    "human-signals": ["human-signals@8.0.1", "", {}, "sha512-eKCa6bwnJhvxj14kZk5NCPc6Hb6BdsU9DZcOnmQKSnO1VKrfV0zCvtttPZUsBvjmNDn8rpcJfpwSYnHBjc95MQ=="],
+
     "ignore": ["ignore@5.3.2", "", {}, "sha512-hsBTNUqQTDwkWtcdYI2i06Y/nUBEsNEDJKjWdigLvegy8kDuJAS8uRlpkkcQpyEXL0Z/pjDy5HBmMjRCJ2gq+g=="],
 
     "imurmurhash": ["imurmurhash@0.1.4", "", {}, "sha512-JmXMZ6wuvDmLiHEml9ykzqO6lwFbof0GG4IkcGaENdCRDDmMVnny7s5HsIgHCbaq0w2MyPhDqkhTUgS2LU2PHA=="],
@@ -387,8 +557,16 @@
 
     "is-glob": ["is-glob@4.0.3", "", { "dependencies": { "is-extglob": "^2.1.1" } }, "sha512-xelSayHH36ZgE7ZWhli7pW34hNbNl8Ojv5KVmkJD4hBdD3th8Tfk9vYasLM+mXWOZhFkgZfxhLSnrwRr4elSSg=="],
 
+    "is-plain-obj": ["is-plain-obj@4.1.0", "", {}, "sha512-+Pgi+vMuUNkJyExiMBt5IlFoMyKnr5zhJ4Uspz58WOhBF5QoIZkFyNHIbBAtHwzVAgk5RtndVNsDRN61/mmDqg=="],
+
+    "is-stream": ["is-stream@4.0.1", "", {}, "sha512-Dnz92NInDqYckGEUJv689RbRiTSEHCQ7wOVeALbkOz999YpqT46yMRIGtSNl2iCL1waAZSx40+h59NV/EwzV/A=="],
+
+    "is-unicode-supported": ["is-unicode-supported@2.1.0", "", {}, "sha512-mE00Gnza5EEB3Ds0HfMyllZzbBrmLOX3vfWoj9A9PEnTfratQ/BcaJOuMhnkhjXvb2+FkY3VuHqtAGpTPmglFQ=="],
+
     "isexe": ["isexe@2.0.0", "", {}, "sha512-RHxMLp9lnKHGHRng9QFhRCMbYAcVpn69smSGcq3f36xjgVVWThj4qqLbTLlq7Ssj8B+fIQ1EuCEGI2lKsyQeIw=="],
 
+    "jiti": ["jiti@2.6.1", "", { "bin": { "jiti": "lib/jiti-cli.mjs" } }, "sha512-ekilCSN1jwRvIbgeg/57YFh8qQDNbwDb9xT/qu2DAHbFFZUicIl4ygVaAvzveMhMVr3LnpSKTNnwt8PoOfmKhQ=="],
+
     "joi": ["joi@18.1.2", "", { "dependencies": { "@hapi/address": "^5.1.1", "@hapi/formula": "^3.0.2", "@hapi/hoek": "^11.0.7", "@hapi/pinpoint": "^2.0.1", "@hapi/tlds": "^1.1.1", "@hapi/topo": "^6.0.2", "@standard-schema/spec": "^1.1.0" } }, "sha512-rF5MAmps5esSlhCA+N1b6IYHDw9j/btzGaqfgie522jS02Ju/HXBxamlXVlKEHAxoMKQL77HWI8jlqWsFuekZA=="],
 
     "js-tokens": ["js-tokens@4.0.0", "", {}, "sha512-RdJUflcE3cUzKiMqQgsCu06FPu9UdIJO0beYbPhHN4k6apgJtifcoCtT9bcxOpYBtpD2kCM6Sbzg4CausW/PKQ=="],
@@ -405,6 +583,8 @@
 
     "keyv": ["keyv@4.5.4", "", { "dependencies": { "json-buffer": "3.0.1" } }, "sha512-oxVHkHR/EJf2CNXnWxRLW6mg7JyCCUcG0DtEGmL2ctUo1PNTin1PUil+r/+4r5MpVgC/fn1kjsx7mjSujKqIpw=="],
 
+    "kill-port-process": ["kill-port-process@4.0.2", "", { "dependencies": { "get-them-args": "1.3.2", "pid-port": "2.0.1" }, "bin": { "kill-port": "dist/bin/kill-port-process.js" } }, "sha512-fO8gc45EYJQUQWozPBmdTpsR0GDvldsmrhP2I4FPoNejwyBY4Liiwj9Is7P/5rj6k07ZQ5Ob0g0k2dqQcslW/w=="],
+
     "levn": ["levn@0.4.1", "", { "dependencies": { "prelude-ls": "^1.2.1", "type-check": "~0.4.0" } }, "sha512-+bT2uH4E5LGE7h/n3evcS/sQlJXCpIp6ym8OWJ5eV6+67Dsql/LaaT7qJBAt2rzfoa/5QBGBhxDix1dMt2kQKQ=="],
 
     "lightningcss": ["lightningcss@1.32.0", "", { "dependencies": { "detect-libc": "^2.0.3" }, "optionalDependencies": { "lightningcss-android-arm64": "1.32.0", "lightningcss-darwin-arm64": "1.32.0", "lightningcss-darwin-x64": "1.32.0", "lightningcss-freebsd-x64": "1.32.0", "lightningcss-linux-arm-gnueabihf": "1.32.0", "lightningcss-linux-arm64-gnu": "1.32.0", "lightningcss-linux-arm64-musl": "1.32.0", "lightningcss-linux-x64-gnu": "1.32.0", "lightningcss-linux-x64-musl": "1.32.0", "lightningcss-win32-arm64-msvc": "1.32.0", "lightningcss-win32-x64-msvc": "1.32.0" } }, "sha512-NXYBzinNrblfraPGyrbPoD19C1h9lfI/1mzgWYvXUTe414Gz/X1FD2XBZSZM7rRTrMA8JL3OtAaGifrIKhQ5yQ=="],
@@ -439,6 +619,8 @@
 
     "lucide-react": ["lucide-react@1.8.0", "", { "peerDependencies": { "react": "^16.5.1 || ^17.0.0 || ^18.0.0 || ^19.0.0" } }, "sha512-WuvlsjngSk7TnTBJ1hsCy3ql9V9VOdcPkd3PKcSmM34vJD8KG6molxz7m7zbYFgICwsanQWmJ13JlYs4Zp7Arw=="],
 
+    "magic-string": ["magic-string@0.30.21", "", { "dependencies": { "@jridgewell/sourcemap-codec": "^1.5.5" } }, "sha512-vd2F4YUyEXKGcLHoq+TEyCjxueSeHnFxyyjNp80yg0XV4vUhnDer/lvvlqM/arB5bXQN5K2/3oinyCRyx8T2CQ=="],
+
     "math-intrinsics": ["math-intrinsics@1.1.0", "", {}, "sha512-/IXtbwEk5HTPyEwyKX6hGkYXxM9nbj64B+ilVJnC/R6B0pH5G4V3b0pVbL7DBj4tkhBAppbQUlf6F6Xl9LHu1g=="],
 
     "mime-db": ["mime-db@1.52.0", "", {}, "sha512-sPU4uV7dYlvtWJxwwxHD0PuihVNiE7TyAbQ5SWxDCB9mUYvOgroQOwYQQOKPJ8CIbE+1ETVlOoK1UC2nU3gYvg=="],
@@ -457,6 +639,8 @@
 
     "node-releases": ["node-releases@2.0.37", "", {}, "sha512-1h5gKZCF+pO/o3Iqt5Jp7wc9rH3eJJ0+nh/CIoiRwjRxde/hAHyLPXYN4V3CqKAbiZPSeJFSWHmJsbkicta0Eg=="],
 
+    "npm-run-path": ["npm-run-path@6.0.0", "", { "dependencies": { "path-key": "^4.0.0", "unicorn-magic": "^0.3.0" } }, "sha512-9qny7Z9DsQU8Ou39ERsPU4OZQlSTP47ShQzuKZ6PRXpYLtIFgl/DEBYEXKlvcEa+9tHVcK8CF81Y2V72qaZhWA=="],
+
     "omnivoice-studio": ["omnivoice-studio@workspace:frontend"],
 
     "optionator": ["optionator@0.9.4", "", { "dependencies": { "deep-is": "^0.1.3", "fast-levenshtein": "^2.0.6", "levn": "^0.4.1", "prelude-ls": "^1.2.1", "type-check": "^0.4.0", "word-wrap": "^1.2.5" } }, "sha512-6IpQ7mKUxRcZNLIObR0hz7lxsapSSIYNZJwXPGeF0mTVqGKFIXj1DQcMoT22S3ROcLyY/rz0PWaWZ9ayWmad9g=="],
@@ -465,6 +649,8 @@
 
     "p-locate": ["p-locate@5.0.0", "", { "dependencies": { "p-limit": "^3.0.2" } }, "sha512-LaNjtRWUBY++zB5nE/NwcaoMylSPk+S+ZHNB1TzdbMJMny6dynpAGt7X/tl/QYq3TIeE6nxHppbo2LGymrG5Pw=="],
 
+    "parse-ms": ["parse-ms@4.0.0", "", {}, "sha512-TXfryirbmq34y8QBwgqCVLi+8oA3oWx2eAnSn62ITyEhEYaWRlVZ2DvMM9eZbMs/RfxPu/PK/aBLyGj4IrqMHw=="],
+
     "path-exists": ["path-exists@4.0.0", "", {}, "sha512-ak9Qy5Q7jYb2Wwcey5Fpvg2KoAc/ZIhLSLOSBmRmygPsGwkVVt0fZa0qrtMz+m6tJTAHfZQ8FnmB4MG4LWy7/w=="],
 
     "path-key": ["path-key@3.1.1", "", {}, "sha512-ojmeN0qd+y0jszEtoY48r0Peq5dwMEkIlCOu6Q5f41lfkswXuKtYrhgoTpLnyIcHm24Uhqx+5Tqm2InSwLhE6Q=="],
@@ -473,25 +659,41 @@
 
     "picomatch": ["picomatch@4.0.4", "", {}, "sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A=="],
 
-    "postcss": ["postcss@8.5.9", "", { "dependencies": { "nanoid": "^3.3.11", "picocolors": "^1.1.1", "source-map-js": "^1.2.1" } }, "sha512-7a70Nsot+EMX9fFU3064K/kdHWZqGVY+BADLyXc8Dfv+mTLLVl6JzJpPaCZ2kQL9gIJvKXSLMHhqdRRjwQeFtw=="],
+    "pid-port": ["pid-port@2.0.1", "", { "dependencies": { "execa": "^9.6.0" } }, "sha512-pnLo01AmMclw8l+/gfknsP2N351oe8VkVmCLFUvJZ11NRPPmghJrv0OcwsdgPQxsZkFYwm6hPWW0JKmXYCaXAw=="],
+
+    "playwright": ["playwright@1.59.1", "", { "dependencies": { "playwright-core": "1.59.1" }, "optionalDependencies": { "fsevents": "2.3.2" }, "bin": { "playwright": "cli.js" } }, "sha512-C8oWjPR3F81yljW9o5OxcWzfh6avkVwDD2VYdwIGqTkl+OGFISgypqzfu7dOe4QNLL2aqcWBmI3PMtLIK233lw=="],
+
+    "playwright-core": ["playwright-core@1.59.1", "", { "bin": { "playwright-core": "cli.js" } }, "sha512-HBV/RJg81z5BiiZ9yPzIiClYV/QMsDCKUyogwH9p3MCP6IYjUFu/MActgYAvK0oWyV9NlwM3GLBjADyWgydVyg=="],
+
+    "postcss": ["postcss@8.5.10", "", { "dependencies": { "nanoid": "^3.3.11", "picocolors": "^1.1.1", "source-map-js": "^1.2.1" } }, "sha512-pMMHxBOZKFU6HgAZ4eyGnwXF/EvPGGqUr0MnZ5+99485wwW41kW91A4LOGxSHhgugZmSChL5AlElNdwlNgcnLQ=="],
 
     "prelude-ls": ["prelude-ls@1.2.1", "", {}, "sha512-vkcDPrRZo1QZLbn5RLGPpg/WmIQ65qoWWhcGKf/b5eplkkarX0m9z8ppCat4mlOqUsWpyNuYgO3VRyrYHSzX5g=="],
 
+    "pretty-ms": ["pretty-ms@9.3.0", "", { "dependencies": { "parse-ms": "^4.0.0" } }, "sha512-gjVS5hOP+M3wMm5nmNOucbIrqudzs9v/57bWRHQWLYklXqoXKrVfYW2W9+glfGsqtPgpiz5WwyEEB+ksXIx3gQ=="],
+
     "proxy-from-env": ["proxy-from-env@2.1.0", "", {}, "sha512-cJ+oHTW1VAEa8cJslgmUZrc+sjRKgAKl3Zyse6+PV38hZe/V6Z14TbCuXcan9F9ghlz4QrFr2c92TNF82UkYHA=="],
 
     "punycode": ["punycode@2.3.1", "", {}, "sha512-vYt7UD1U9Wg6138shLtLOvdAu+8DsC/ilFtEVHcH+wydcSpNE20AfSOduf6MkRFahL5FY7X1oU7nKVZFtfq8Fg=="],
 
+    "qrcode.react": ["qrcode.react@4.2.0", "", { "peerDependencies": { "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0" } }, "sha512-QpgqWi8rD9DsS9EP3z7BT+5lY5SFhsqGjpgW5DY/i3mK4M9DTBNz3ErMi8BWYEfI3L0d8GIbGmcdFAS1uIRGjA=="],
+
     "react": ["react@19.2.5", "", {}, "sha512-llUJLzz1zTUBrskt2pwZgLq59AemifIftw4aB7JxOqf1HY2FDaGDxgwpAPVzHU1kdWabH7FauP4i1oEeer2WCA=="],
 
     "react-dom": ["react-dom@19.2.5", "", { "dependencies": { "scheduler": "^0.27.0" }, "peerDependencies": { "react": "^19.2.5" } }, "sha512-J5bAZz+DXMMwW/wV3xzKke59Af6CHY7G4uYLN1OvBcKEsWOs4pQExj86BBKamxl/Ik5bx9whOrvBlSDfWzgSag=="],
 
     "react-hot-toast": ["react-hot-toast@2.6.0", "", { "dependencies": { "csstype": "^3.1.3", "goober": "^2.1.16" }, "peerDependencies": { "react": ">=16", "react-dom": ">=16" } }, "sha512-bH+2EBMZ4sdyou/DPrfgIouFpcRLCJ+HoCA32UoAYHn6T3Ur5yfcDCeSr5mwldl6pFOsiocmrXMuoCJ1vV8bWg=="],
 
+    "react-remove-scroll": ["react-remove-scroll@2.7.2", "", { "dependencies": { "react-remove-scroll-bar": "^2.3.7", "react-style-singleton": "^2.2.3", "tslib": "^2.1.0", "use-callback-ref": "^1.3.3", "use-sidecar": "^1.1.3" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-Iqb9NjCCTt6Hf+vOdNIZGdTiH1QSqr27H/Ek9sv/a97gfueI/5h1s3yRi1nngzMUaOOToin5dI1dXKdXiF+u0Q=="],
+
+    "react-remove-scroll-bar": ["react-remove-scroll-bar@2.3.8", "", { "dependencies": { "react-style-singleton": "^2.2.2", "tslib": "^2.0.0" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0" }, "optionalPeers": ["@types/react"] }, "sha512-9r+yi9+mgU33AKcj6IbT9oRCO78WriSj6t/cF8DWBZJ9aOGPOTEDvdUDz1FwKim7QXWwmHqtdHnRJfhAxEG46Q=="],
+
+    "react-style-singleton": ["react-style-singleton@2.2.3", "", { "dependencies": { "get-nonce": "^1.0.0", "tslib": "^2.0.0" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-b6jSvxvVnyptAiLjbkWLE/lOnR4lfTtDAl+eUC7RZy+QQWc6wRzIV2CE6xBuMmDxc2qIihtDCZD5NPOFl7fRBQ=="],
+
     "react-window": ["react-window@2.2.7", "", { "peerDependencies": { "react": "^18.0.0 || ^19.0.0", "react-dom": "^18.0.0 || ^19.0.0" } }, "sha512-SH5nvfUQwGHYyriDUAOt7wfPsfG9Qxd6OdzQxl5oQ4dsSsUicqQvjV7dR+NqZ4coY0fUn3w1jnC5PwzIUWEg5w=="],
 
     "require-directory": ["require-directory@2.1.1", "", {}, "sha512-fGxEI7+wsG9xrvdjsrlmL22OMTTiHRwAMroiEeMgq8gzoLC/PQr7RsRDSTLUg/bZAZtF+TVIkHc6/4RIKrui+Q=="],
 
-    "rolldown": ["rolldown@1.0.0-rc.15", "", { "dependencies": { "@oxc-project/types": "=0.124.0", "@rolldown/pluginutils": "1.0.0-rc.15" }, "optionalDependencies": { "@rolldown/binding-android-arm64": "1.0.0-rc.15", "@rolldown/binding-darwin-arm64": "1.0.0-rc.15", "@rolldown/binding-darwin-x64": "1.0.0-rc.15", "@rolldown/binding-freebsd-x64": "1.0.0-rc.15", "@rolldown/binding-linux-arm-gnueabihf": "1.0.0-rc.15", "@rolldown/binding-linux-arm64-gnu": "1.0.0-rc.15", "@rolldown/binding-linux-arm64-musl": "1.0.0-rc.15", "@rolldown/binding-linux-ppc64-gnu": "1.0.0-rc.15", "@rolldown/binding-linux-s390x-gnu": "1.0.0-rc.15", "@rolldown/binding-linux-x64-gnu": "1.0.0-rc.15", "@rolldown/binding-linux-x64-musl": "1.0.0-rc.15", "@rolldown/binding-openharmony-arm64": "1.0.0-rc.15", "@rolldown/binding-wasm32-wasi": "1.0.0-rc.15", "@rolldown/binding-win32-arm64-msvc": "1.0.0-rc.15", "@rolldown/binding-win32-x64-msvc": "1.0.0-rc.15" }, "bin": { "rolldown": "bin/cli.mjs" } }, "sha512-Ff31guA5zT6WjnGp0SXw76X6hzGRk/OQq2hE+1lcDe+lJdHSgnSX6nK3erbONHyCbpSj9a9E+uX/OvytZoWp2g=="],
+    "rolldown": ["rolldown@1.0.0-rc.16", "", { "dependencies": { "@oxc-project/types": "=0.126.0", "@rolldown/pluginutils": "1.0.0-rc.16" }, "optionalDependencies": { "@rolldown/binding-android-arm64": "1.0.0-rc.16", "@rolldown/binding-darwin-arm64": "1.0.0-rc.16", "@rolldown/binding-darwin-x64": "1.0.0-rc.16", "@rolldown/binding-freebsd-x64": "1.0.0-rc.16", "@rolldown/binding-linux-arm-gnueabihf": "1.0.0-rc.16", "@rolldown/binding-linux-arm64-gnu": "1.0.0-rc.16", "@rolldown/binding-linux-arm64-musl": "1.0.0-rc.16", "@rolldown/binding-linux-ppc64-gnu": "1.0.0-rc.16", "@rolldown/binding-linux-s390x-gnu": "1.0.0-rc.16", "@rolldown/binding-linux-x64-gnu": "1.0.0-rc.16", "@rolldown/binding-linux-x64-musl": "1.0.0-rc.16", "@rolldown/binding-openharmony-arm64": "1.0.0-rc.16", "@rolldown/binding-wasm32-wasi": "1.0.0-rc.16", "@rolldown/binding-win32-arm64-msvc": "1.0.0-rc.16", "@rolldown/binding-win32-x64-msvc": "1.0.0-rc.16" }, "bin": { "rolldown": "bin/cli.mjs" } }, "sha512-rzi5WqKzEZw3SooTt7cgm4eqIoujPIyGcJNGFL7iPEuajQw7vxMHUkXylu4/vhCkJGXsgRmxqMKXUpT6FEgl0g=="],
 
     "rxjs": ["rxjs@7.8.2", "", { "dependencies": { "tslib": "^2.1.0" } }, "sha512-dhKf903U/PQZY6boNNtAGdWbG85WAbjT/1xYoZIC7FAY0yWapOBQVsVrDl58W86//e1VpMNBtRV4MaXfdMySFA=="],
 
@@ -505,14 +707,22 @@
 
     "shell-quote": ["shell-quote@1.8.3", "", {}, "sha512-ObmnIF4hXNg1BqhnHmgbDETF8dLPCggZWBjkQfhZpbszZnYur5DUljTcCHii5LC3J5E0yeO/1LIMyH+UvHQgyw=="],
 
+    "signal-exit": ["signal-exit@4.1.0", "", {}, "sha512-bzyZ1e88w9O1iNJbKnOlvYTrWPDl46O1bG0D3XInv+9tkPrxrN8jUUTiFlDkkmKWgn1M6CfIA13SuGqOa9Korw=="],
+
     "source-map-js": ["source-map-js@1.2.1", "", {}, "sha512-UXWMKhLOwVKb728IUtQPXxfYU+usdybtUrK/8uGE8CQMvrhOpwvzDBwj0QhSL7MQc7vIsISBG8VQ8+IDQxpfQA=="],
 
     "string-width": ["string-width@4.2.3", "", { "dependencies": { "emoji-regex": "^8.0.0", "is-fullwidth-code-point": "^3.0.0", "strip-ansi": "^6.0.1" } }, "sha512-wKyQRQpjJ0sIp62ErSZdGsjMJWsap5oRNihHhu6G7JVO/9jIB6UyevL+tXuOqrng8j/cxKTWyWUwvSTriiZz/g=="],
 
     "strip-ansi": ["strip-ansi@6.0.1", "", { "dependencies": { "ansi-regex": "^5.0.1" } }, "sha512-Y38VPSHcqkFrCpFnQ9vuSXmquuv5oXOKpGeT6aGrr3o3Gc9AlVa6JBfUSOCnbxGGZF+/0ooI7KrPuUSztUdU5A=="],
 
+    "strip-final-newline": ["strip-final-newline@4.0.0", "", {}, "sha512-aulFJcD6YK8V1G7iRB5tigAP4TsHBZZrOV8pjV++zdUwmeV8uzbY7yn6h9MswN62adStNZFuCIx4haBnRuMDaw=="],
+
     "supports-color": ["supports-color@8.1.1", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-MpUEN2OodtUzxvKQl72cUF7RQ5EiHsGvSsVG0ia9c5RbWGL2CI4C7EpPS8UTBIplnlzZiNuV56w+FuNxy3ty2Q=="],
 
+    "tailwindcss": ["tailwindcss@4.2.4", "", {}, "sha512-HhKppgO81FQof5m6TEnuBWCZGgfRAWbaeOaGT00KOy/Pf/j6oUihdvBpA7ltCeAvZpFhW3j0PTclkxsd4IXYDA=="],
+
+    "tapable": ["tapable@2.3.3", "", {}, "sha512-uxc/zpqFg6x7C8vOE7lh6Lbda8eEL9zmVm/PLeTPBRhh1xCgdWaQ+J1CUieGpIfm2HdtsUpRv+HshiasBMcc6A=="],
+
     "tinyglobby": ["tinyglobby@0.2.16", "", { "dependencies": { "fdir": "^6.5.0", "picomatch": "^4.0.4" } }, "sha512-pn99VhoACYR8nFHhxqix+uvsbXineAasWm5ojXoN8xEwK5Kd3/TrhNn1wByuD52UxWRLy8pu+kRMniEi6Eq9Zg=="],
 
     "tree-kill": ["tree-kill@1.2.2", "", { "bin": { "tree-kill": "cli.js" } }, "sha512-L0Orpi8qGpRG//Nd+H90vFB+3iHnue1zSSGmNOOCh1GLJ7rUKVwV2HvijphGQS2UmhUZewS9VgvxYIdgr+fG1A=="],
@@ -525,11 +735,17 @@
 
     "typescript": ["typescript@6.0.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-y2TvuxSZPDyQakkFRPZHKFm+KKVqIisdg9/CZwm9ftvKXLP8NRWj38/ODjNbr43SsoXqNuAisEf1GdCxqWcdBw=="],
 
+    "unicorn-magic": ["unicorn-magic@0.3.0", "", {}, "sha512-+QBBXBCvifc56fsbuxZQ6Sic3wqqc3WWaqxs58gvJrcOuN83HGTCwz3oS5phzU9LthRNE9VrJCFCLUgHeeFnfA=="],
+
     "update-browserslist-db": ["update-browserslist-db@1.2.3", "", { "dependencies": { "escalade": "^3.2.0", "picocolors": "^1.1.1" }, "peerDependencies": { "browserslist": ">= 4.21.0" }, "bin": { "update-browserslist-db": "cli.js" } }, "sha512-Js0m9cx+qOgDxo0eMiFGEueWztz+d4+M3rGlmKPT+T4IS/jP4ylw3Nwpu6cpTTP8R1MAC1kF4VbdLt3ARf209w=="],
 
     "uri-js": ["uri-js@4.4.1", "", { "dependencies": { "punycode": "^2.1.0" } }, "sha512-7rKUyy33Q1yc98pQ1DAmLtwX109F7TIfWlW1Ydo8Wl1ii1SeHieeh0HHfPeL2fMXK6z0s8ecKs9frCuLJvndBg=="],
 
-    "vite": ["vite@8.0.8", "", { "dependencies": { "lightningcss": "^1.32.0", "picomatch": "^4.0.4", "postcss": "^8.5.8", "rolldown": "1.0.0-rc.15", "tinyglobby": "^0.2.15" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "peerDependencies": { "@types/node": "^20.19.0 || >=22.12.0", "@vitejs/devtools": "^0.1.0", "esbuild": "^0.27.0 || ^0.28.0", "jiti": ">=1.21.0", "less": "^4.0.0", "sass": "^1.70.0", "sass-embedded": "^1.70.0", "stylus": ">=0.54.8", "sugarss": "^5.0.0", "terser": "^5.16.0", "tsx": "^4.8.1", "yaml": "^2.4.2" }, "optionalPeers": ["@types/node", "@vitejs/devtools", "esbuild", "jiti", "less", "sass", "sass-embedded", "stylus", "sugarss", "terser", "tsx", "yaml"], "bin": { "vite": "bin/vite.js" } }, "sha512-dbU7/iLVa8KZALJyLOBOQ88nOXtNG8vxKuOT4I2mD+Ya70KPceF4IAmDsmU0h1Qsn5bPrvsY9HJstCRh3hG6Uw=="],
+    "use-callback-ref": ["use-callback-ref@1.3.3", "", { "dependencies": { "tslib": "^2.0.0" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-jQL3lRnocaFtu3V00JToYz/4QkNWswxijDaCVNZRiRTO3HQDLsdu1ZtmIUvV4yPp+rvWm5j0y0TG/S61cuijTg=="],
+
+    "use-sidecar": ["use-sidecar@1.1.3", "", { "dependencies": { "detect-node-es": "^1.1.0", "tslib": "^2.0.0" }, "peerDependencies": { "@types/react": "*", "react": "^16.8.0 || ^17.0.0 || ^18.0.0 || ^19.0.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-Fedw0aZvkhynoPYlA5WXrMCAMm+nSWdZt6lzJQ7Ok8S6Q+VsHmHpRWndVRJ8Be0ZbkfPc5LRYH+5XrzXcEeLRQ=="],
+
+    "vite": ["vite@8.0.9", "", { "dependencies": { "lightningcss": "^1.32.0", "picomatch": "^4.0.4", "postcss": "^8.5.10", "rolldown": "1.0.0-rc.16", "tinyglobby": "^0.2.16" }, "optionalDependencies": { "fsevents": "~2.3.3" }, "peerDependencies": { "@types/node": "^20.19.0 || >=22.12.0", "@vitejs/devtools": "^0.1.0", "esbuild": "^0.27.0 || ^0.28.0", "jiti": ">=1.21.0", "less": "^4.0.0", "sass": "^1.70.0", "sass-embedded": "^1.70.0", "stylus": ">=0.54.8", "sugarss": "^5.0.0", "terser": "^5.16.0", "tsx": "^4.8.1", "yaml": "^2.4.2" }, "optionalPeers": ["@types/node", "@vitejs/devtools", "esbuild", "jiti", "less", "sass", "sass-embedded", "stylus", "sugarss", "terser", "tsx", "yaml"], "bin": { "vite": "bin/vite.js" } }, "sha512-t7g7GVRpMXjNpa67HaVWI/8BWtdVIQPCL2WoozXXA7LBGEFK4AkkKkHx2hAQf5x1GZSlcmEDPkVLSGahxnEEZw=="],
 
     "wait-on": ["wait-on@9.0.5", "", { "dependencies": { "axios": "^1.15.0", "joi": "^18.1.2", "lodash": "^4.18.1", "minimist": "^1.2.8", "rxjs": "^7.8.2" }, "bin": { "wait-on": "bin/wait-on" } }, "sha512-qgnbHDfDTRIp73ANEJNRW/7kn8CrDUcvZz18xotJQku/P4saTGkbIzvnMZebPmVvVNUiRq1qWAPyqCH+W4H8KA=="],
 
@@ -551,6 +767,8 @@
 
     "yocto-queue": ["yocto-queue@0.1.0", "", {}, "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q=="],
 
+    "yoctocolors": ["yoctocolors@2.1.2", "", {}, "sha512-CzhO+pFNo8ajLM2d2IW/R93ipy99LWjtwblvC1RsoSUMZgyLbYFr221TnSNT7GjGdYui6P459mw9JH/g/zW2ug=="],
+
     "zod": ["zod@4.3.6", "", {}, "sha512-rftlrkhHZOcjDwkGlnUtZZkvaPHCsDATp4pGpuOOMDaTdDDXF91wuVDJoWoPsKX/3YPQ5fHuF3STjcYyKr+Qhg=="],
 
     "zod-validation-error": ["zod-validation-error@4.0.2", "", { "peerDependencies": { "zod": "^3.25.0 || ^4.0.0" } }, "sha512-Q6/nZLe6jxuU80qb/4uJ4t5v2VEZ44lzQjPDhYJNztRQ4wyWc6VF3D3Kb/fAuPetZQnhS3hnajCf9CsWesghLQ=="],
@@ -559,10 +777,30 @@
 
     "@eslint-community/eslint-utils/eslint-visitor-keys": ["eslint-visitor-keys@3.4.3", "", {}, "sha512-wpc+LXeiyiisxPlEkUzU6svyS1frIO3Mgxj1fdy7Pm8Ygzguax2N3Fa/D/ag1WqbOprdI+uY6wMUl8/a2G+iag=="],
 
+    "@radix-ui/react-progress/@radix-ui/react-context": ["@radix-ui/react-context@1.1.3", "", { "peerDependencies": { "@types/react": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-ieIFACdMpYfMEjF0rEf5KLvfVyIkOz6PDGyNnP+u+4xQ6jny3VCgA4OgXOwNx2aUkxn8zx9fiVcM8CfFYv9Lxw=="],
+
+    "@radix-ui/react-progress/@radix-ui/react-primitive": ["@radix-ui/react-primitive@2.1.4", "", { "dependencies": { "@radix-ui/react-slot": "1.2.4" }, "peerDependencies": { "@types/react": "*", "@types/react-dom": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc", "react-dom": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react", "@types/react-dom"] }, "sha512-9hQc4+GNVtJAIEPEqlYqW5RiYdrr8ea5XQ0ZOnD6fgru+83kqT15mq2OCcbe8KnjRZl5vF3ks69AKz3kh1jrhg=="],
+
+    "@tailwindcss/oxide-wasm32-wasi/@emnapi/core": ["@emnapi/core@1.9.2", "", { "dependencies": { "@emnapi/wasi-threads": "1.2.1", "tslib": "^2.4.0" }, "bundled": true }, "sha512-UC+ZhH3XtczQYfOlu3lNEkdW/p4dsJ1r/bP7H8+rhao3TTTMO1ATq/4DdIi23XuGoFY+Cz0JmCbdVl0hz9jZcA=="],
+
+    "@tailwindcss/oxide-wasm32-wasi/@emnapi/runtime": ["@emnapi/runtime@1.9.2", "", { "dependencies": { "tslib": "^2.4.0" }, "bundled": true }, "sha512-3U4+MIWHImeyu1wnmVygh5WlgfYDtyf0k8AbLhMFxOipihf6nrWC4syIm/SwEeec0mNSafiiNnMJwbza/Is6Lw=="],
+
+    "@tailwindcss/oxide-wasm32-wasi/@emnapi/wasi-threads": ["@emnapi/wasi-threads@1.2.1", "", { "dependencies": { "tslib": "^2.4.0" }, "bundled": true }, "sha512-uTII7OYF+/Mes/MrcIOYp5yOtSMLBWSIoLPpcgwipoiKbli6k322tcoFsxoIIxPDqW01SQGAgko4EzZi2BNv2w=="],
+
+    "@tailwindcss/oxide-wasm32-wasi/@napi-rs/wasm-runtime": ["@napi-rs/wasm-runtime@1.1.4", "", { "dependencies": { "@tybys/wasm-util": "^0.10.1" }, "peerDependencies": { "@emnapi/core": "^1.7.1", "@emnapi/runtime": "^1.7.1" }, "bundled": true }, "sha512-3NQNNgA1YSlJb/kMH1ildASP9HW7/7kYnRI2szWJaofaS1hWmbGI4H+d3+22aGzXXN9IJ+n+GiFVcGipJP18ow=="],
+
+    "@tailwindcss/oxide-wasm32-wasi/@tybys/wasm-util": ["@tybys/wasm-util@0.10.1", "", { "dependencies": { "tslib": "^2.4.0" }, "bundled": true }, "sha512-9tTaPJLSiejZKx+Bmog4uSubteqTvFrVrURwkmHixBo0G4seD0zUxp98E1DzUBJxLQ3NPwXrGKDiVjwx/DpPsg=="],
+
+    "@tailwindcss/oxide-wasm32-wasi/tslib": ["tslib@2.8.1", "", { "bundled": true }, "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w=="],
+
     "chalk/supports-color": ["supports-color@7.2.0", "", { "dependencies": { "has-flag": "^4.0.0" } }, "sha512-qpCAvRl9stuOHveKsn7HncJRvv501qIacKzQlO/+Lwxc9+0q2wLyv4Dfvt80/DPn2pqOBsJdDiogXGR9+OvwRw=="],
 
-    "omnivoice-studio/typescript": ["typescript@5.9.3", "", { "bin": { "tsc": "bin/tsc", "tsserver": "bin/tsserver" } }, "sha512-jl1vZzPDinLr9eUt3J/t7V6FgNEw9QjvBPdysz9KfQDD41fQrC2Y4vKQdiaUpFT4bXlb1RHhLpp8wtm6M5TgSw=="],
+    "npm-run-path/path-key": ["path-key@4.0.0", "", {}, "sha512-haREypq7xkM7ErfgIyA0z+Bj4AGKlMSdlQE2jvJo6huWD1EdkKYV+G/T4nq0YEF2vgTT8kqMFKo1uHn950r4SQ=="],
 
-    "rolldown/@rolldown/pluginutils": ["@rolldown/pluginutils@1.0.0-rc.15", "", {}, "sha512-UromN0peaE53IaBRe9W7CjrZgXl90fqGpK+mIZbA3qSTeYqg3pqpROBdIPvOG3F5ereDHNwoHBI2e50n1BDr1g=="],
+    "rolldown/@rolldown/pluginutils": ["@rolldown/pluginutils@1.0.0-rc.16", "", {}, "sha512-45+YtqxLYKDWQouLKCrpIZhke+nXxhsw+qAHVzHDVwttyBlHNBVs2K25rDXrZzhpTp9w1FlAlvweV1H++fdZoA=="],
+
+    "vite/fsevents": ["fsevents@2.3.3", "", { "os": "darwin" }, "sha512-5xoDfX+fL7faATnagmWPpbFtwh/R77WmMMqqHGS65C3vvB0YHrgF+B1YmZ3441tMj5n63k0212XNoJwzlhffQw=="],
+
+    "@radix-ui/react-progress/@radix-ui/react-primitive/@radix-ui/react-slot": ["@radix-ui/react-slot@1.2.4", "", { "dependencies": { "@radix-ui/react-compose-refs": "1.1.2" }, "peerDependencies": { "@types/react": "*", "react": "^16.8 || ^17.0 || ^18.0 || ^19.0 || ^19.0.0-rc" }, "optionalPeers": ["@types/react"] }, "sha512-Jl+bCv8HxKnlTLVrcDE8zTMJ09R9/ukw4qBs/oZClOfoQk/cOTbDn+NceXfV7j09YPVQUryJPHurafcSg6EVKA=="],
   }
 }

docker-compose.yml

@@ -6,7 +6,7 @@ services:
     container_name: omnivoice-studio
     restart: unless-stopped
     ports:
-      - "8000:8000"
+      - "3900:3900"
     volumes:
       # Map the backend data directory to host for persistent SQLite, voices, and history
       - ./omnivoice_data:/app/omnivoice_data

docs/logo.svg

@@ -0,0 +1,61 @@
+<svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512">
+  <defs>
+    <!-- Background gradient -->
+    <linearGradient id="bg" x1="0" y1="0" x2="1" y2="1">
+      <stop offset="0%" stop-color="#1e1e2e"/>
+      <stop offset="100%" stop-color="#13131f"/>
+    </linearGradient>
+
+    <!-- Waveform pink gradient -->
+    <linearGradient id="wave" x1="0" y1="0" x2="1" y2="1">
+      <stop offset="0%" stop-color="#e8a4b8"/>
+      <stop offset="50%" stop-color="#d3869b"/>
+      <stop offset="100%" stop-color="#c07090"/>
+    </linearGradient>
+
+    <!-- Glow filter -->
+    <filter id="glow" x="-50%" y="-50%" width="200%" height="200%">
+      <feGaussianBlur in="SourceGraphic" stdDeviation="8" result="blur"/>
+      <feColorMatrix in="blur" type="matrix" values="1 0 0 0 0  0 0.4 0 0 0  0 0 0.5 0 0  0 0 0 0.6 0" result="glow"/>
+      <feMerge>
+        <feMergeNode in="glow"/>
+        <feMergeNode in="SourceGraphic"/>
+      </feMerge>
+    </filter>
+
+    <!-- Subtle inner shadow -->
+    <filter id="inset" x="-10%" y="-10%" width="120%" height="120%">
+      <feGaussianBlur in="SourceAlpha" stdDeviation="6" result="blur"/>
+      <feOffset dx="0" dy="3" result="offset"/>
+      <feComposite in="SourceGraphic" in2="offset" operator="over"/>
+    </filter>
+
+    <!-- Edge highlight -->
+    <linearGradient id="edge" x1="0" y1="0" x2="0" y2="1">
+      <stop offset="0%" stop-color="#ffffff" stop-opacity="0.12"/>
+      <stop offset="50%" stop-color="#ffffff" stop-opacity="0.03"/>
+      <stop offset="100%" stop-color="#000000" stop-opacity="0.15"/>
+    </linearGradient>
+  </defs>
+
+  <!-- Outer rounded square -->
+  <rect x="16" y="16" width="480" height="480" rx="96" ry="96" fill="url(#bg)"/>
+
+  <!-- Edge/border highlight -->
+  <rect x="16" y="16" width="480" height="480" rx="96" ry="96" fill="none" stroke="url(#edge)" stroke-width="2"/>
+
+  <!-- Central waveform bars (audio visualizer style) -->
+  <g transform="translate(256, 256)" filter="url(#glow)">
+    <!-- 7 bars, symmetric heights, rounded caps -->
+    <rect x="-120" y="-30"  width="20" height="60"  rx="10" fill="url(#wave)" opacity="0.7"/>
+    <rect x="-84"  y="-55"  width="20" height="110" rx="10" fill="url(#wave)" opacity="0.85"/>
+    <rect x="-48"  y="-80"  width="20" height="160" rx="10" fill="url(#wave)" opacity="0.95"/>
+    <rect x="-10"  y="-100" width="20" height="200" rx="10" fill="url(#wave)"/>
+    <rect x="28"   y="-75"  width="20" height="150" rx="10" fill="url(#wave)" opacity="0.95"/>
+    <rect x="64"   y="-50"  width="20" height="100" rx="10" fill="url(#wave)" opacity="0.85"/>
+    <rect x="100"  y="-25"  width="20" height="50"  rx="10" fill="url(#wave)" opacity="0.7"/>
+  </g>
+
+  <!-- Subtle circle ring behind bars -->
+  <circle cx="256" cy="256" r="140" fill="none" stroke="#d3869b" stroke-width="1.5" opacity="0.15"/>
+</svg>

frontend/package.json

@@ -1,7 +1,7 @@
 {
   "name": "omnivoice-studio",
   "private": true,
-  "version": "0.2.0",
+  "version": "0.2.4",
   "type": "module",
   "scripts": {
     "dev": "vite",
@@ -17,17 +17,33 @@
     "@fontsource-variable/inter": "^5.2.8",
     "@fontsource-variable/source-serif-4": "^5.2.9",
     "@fontsource/ibm-plex-mono": "^5.2.7",
+    "@radix-ui/react-dialog": "^1.1.15",
+    "@radix-ui/react-dropdown-menu": "^2.1.16",
+    "@radix-ui/react-popover": "^1.1.15",
+    "@radix-ui/react-progress": "^1.1.8",
+    "@radix-ui/react-select": "^2.2.6",
+    "@radix-ui/react-slider": "^1.3.6",
+    "@radix-ui/react-tabs": "^1.1.13",
+    "@radix-ui/react-toggle-group": "^1.1.11",
+    "@radix-ui/react-tooltip": "^1.2.8",
+    "@tailwindcss/vite": "4",
+    "@tanstack/react-query": "^5.100.4",
+    "@tanstack/react-table": "^8.21.3",
+    "@tanstack/react-virtual": "^3.13.24",
     "@tauri-apps/plugin-dialog": "^2.7.0",
-    "@tauri-apps/plugin-process": "^2.3.0",
-    "@tauri-apps/plugin-updater": "^2.9.0",
+    "@tauri-apps/plugin-opener": "^2.5.3",
+    "@tauri-apps/plugin-process": "^2.3.1",
+    "@tauri-apps/plugin-updater": "^2.10.1",
     "@tauri-apps/plugin-window-state": "^2.4.1",
     "lucide-react": "^1.8.0",
+    "qrcode.react": "^4.2.0",
     "react": "^19.2.5",
     "react-dom": "^19.2.5",
     "react-hot-toast": "^2.6.0",
     "react-window": "^2.2.7",
+    "tailwindcss": "4",
     "wavesurfer.js": "^7.12.6",
-    "zustand": "^5.0.2"
+    "zustand": "^5.0.12"
   },
   "devDependencies": {
     "@eslint/js": "^10.0.1",
@@ -36,11 +52,11 @@
     "@types/react": "^19.2.14",
     "@types/react-dom": "^19.2.3",
     "@vitejs/plugin-react": "^6.0.1",
-    "eslint": "^10.2.0",
-    "eslint-plugin-react-hooks": "^7.0.1",
+    "eslint": "^10.2.1",
+    "eslint-plugin-react-hooks": "^7.1.1",
     "eslint-plugin-react-refresh": "^0.5.2",
-    "globals": "^17.4.0",
-    "typescript": "^5.7.3",
-    "vite": "^8.0.8"
+    "globals": "^17.5.0",
+    "typescript": "^6.0.3",
+    "vite": "^8.0.9"
   }
 }

frontend/public/favicon.svg

@@ -1,7 +1,61 @@
-<svg xmlns="http://www.w3.org/2000/svg" width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="#d3869b" stroke-width="2.5" stroke-linecap="round" stroke-linejoin="round">
-  <circle cx="12" cy="12" r="10" opacity="0.3" fill="#d3869b"/>
-  <circle cx="12" cy="12" r="10" />
-  <path d="M12 6v12" />
-  <path d="M8 9v6" />
-  <path d="M16 9v6" />
-</svg>
+<svg xmlns="http://www.w3.org/2000/svg" width="512" height="512" viewBox="0 0 512 512">
+  <defs>
+    <!-- Background gradient -->
+    <linearGradient id="bg" x1="0" y1="0" x2="1" y2="1">
+      <stop offset="0%" stop-color="#1e1e2e"/>
+      <stop offset="100%" stop-color="#13131f"/>
+    </linearGradient>
+
+    <!-- Waveform pink gradient -->
+    <linearGradient id="wave" x1="0" y1="0" x2="1" y2="1">
+      <stop offset="0%" stop-color="#e8a4b8"/>
+      <stop offset="50%" stop-color="#d3869b"/>
+      <stop offset="100%" stop-color="#c07090"/>
+    </linearGradient>
+
+    <!-- Glow filter -->
+    <filter id="glow" x="-50%" y="-50%" width="200%" height="200%">
+      <feGaussianBlur in="SourceGraphic" stdDeviation="8" result="blur"/>
+      <feColorMatrix in="blur" type="matrix" values="1 0 0 0 0  0 0.4 0 0 0  0 0 0.5 0 0  0 0 0 0.6 0" result="glow"/>
+      <feMerge>
+        <feMergeNode in="glow"/>
+        <feMergeNode in="SourceGraphic"/>
+      </feMerge>
+    </filter>
+
+    <!-- Subtle inner shadow -->
+    <filter id="inset" x="-10%" y="-10%" width="120%" height="120%">
+      <feGaussianBlur in="SourceAlpha" stdDeviation="6" result="blur"/>
+      <feOffset dx="0" dy="3" result="offset"/>
+      <feComposite in="SourceGraphic" in2="offset" operator="over"/>
+    </filter>
+
+    <!-- Edge highlight -->
+    <linearGradient id="edge" x1="0" y1="0" x2="0" y2="1">
+      <stop offset="0%" stop-color="#ffffff" stop-opacity="0.12"/>
+      <stop offset="50%" stop-color="#ffffff" stop-opacity="0.03"/>
+      <stop offset="100%" stop-color="#000000" stop-opacity="0.15"/>
+    </linearGradient>
+  </defs>
+
+  <!-- Outer rounded square -->
+  <rect x="16" y="16" width="480" height="480" rx="96" ry="96" fill="url(#bg)"/>
+
+  <!-- Edge/border highlight -->
+  <rect x="16" y="16" width="480" height="480" rx="96" ry="96" fill="none" stroke="url(#edge)" stroke-width="2"/>
+
+  <!-- Central waveform bars (audio visualizer style) -->
+  <g transform="translate(256, 256)" filter="url(#glow)">
+    <!-- 7 bars, symmetric heights, rounded caps -->
+    <rect x="-120" y="-30"  width="20" height="60"  rx="10" fill="url(#wave)" opacity="0.7"/>
+    <rect x="-84"  y="-55"  width="20" height="110" rx="10" fill="url(#wave)" opacity="0.85"/>
+    <rect x="-48"  y="-80"  width="20" height="160" rx="10" fill="url(#wave)" opacity="0.95"/>
+    <rect x="-10"  y="-100" width="20" height="200" rx="10" fill="url(#wave)"/>
+    <rect x="28"   y="-75"  width="20" height="150" rx="10" fill="url(#wave)" opacity="0.95"/>
+    <rect x="64"   y="-50"  width="20" height="100" rx="10" fill="url(#wave)" opacity="0.85"/>
+    <rect x="100"  y="-25"  width="20" height="50"  rx="10" fill="url(#wave)" opacity="0.7"/>
+  </g>
+
+  <!-- Subtle circle ring behind bars -->
+  <circle cx="256" cy="256" r="140" fill="none" stroke="#d3869b" stroke-width="1.5" opacity="0.15"/>
+</svg>

frontend/src-tauri/Cargo.lock

@@ -77,22 +77,27 @@ checksum = "7f202df86484c868dbad7eaa557ef785d5c66295e41b460ef922eca0723b842c"
 
 [[package]]
 name = "app"
-version = "0.2.0"
+version = "0.2.4"
 dependencies = [
  "flate2",
  "libc",
  "log",
  "serde",
  "serde_json",
+ "sha2",
+ "sysinfo",
  "tar",
  "tauri",
  "tauri-build",
  "tauri-plugin-dialog",
  "tauri-plugin-log",
+ "tauri-plugin-opener",
  "tauri-plugin-process",
  "tauri-plugin-updater",
  "tauri-plugin-window-state",
  "ureq",
+ "walkdir",
+ "webkit2gtk",
  "zip 2.4.2",
 ]
 
@@ -111,6 +116,137 @@ version = "0.7.6"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "7c02d123df017efcdfbd739ef81735b36c5ba83ec3c59c80a9d7ecc718f92e50"
 
+[[package]]
+name = "async-broadcast"
+version = "0.7.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "435a87a52755b8f27fcf321ac4f04b2802e337c8c4872923137471ec39c37532"
+dependencies = [
+ "event-listener",
+ "event-listener-strategy",
+ "futures-core",
+ "pin-project-lite",
+]
+
+[[package]]
+name = "async-channel"
+version = "2.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "924ed96dd52d1b75e9c1a3e6275715fd320f5f9439fb5a4a11fa51f4221158d2"
+dependencies = [
+ "concurrent-queue",
+ "event-listener-strategy",
+ "futures-core",
+ "pin-project-lite",
+]
+
+[[package]]
+name = "async-executor"
+version = "1.14.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c96bf972d85afc50bf5ab8fe2d54d1586b4e0b46c97c50a0c9e71e2f7bcd812a"
+dependencies = [
+ "async-task",
+ "concurrent-queue",
+ "fastrand",
+ "futures-lite",
+ "pin-project-lite",
+ "slab",
+]
+
+[[package]]
+name = "async-io"
+version = "2.6.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "456b8a8feb6f42d237746d4b3e9a178494627745c3c56c6ea55d92ba50d026fc"
+dependencies = [
+ "autocfg",
+ "cfg-if",
+ "concurrent-queue",
+ "futures-io",
+ "futures-lite",
+ "parking",
+ "polling",
+ "rustix",
+ "slab",
+ "windows-sys 0.61.2",
+]
+
+[[package]]
+name = "async-lock"
+version = "3.4.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "290f7f2596bd5b78a9fec8088ccd89180d7f9f55b94b0576823bbbdc72ee8311"
+dependencies = [
+ "event-listener",
+ "event-listener-strategy",
+ "pin-project-lite",
+]
+
+[[package]]
+name = "async-process"
+version = "2.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "fc50921ec0055cdd8a16de48773bfeec5c972598674347252c0399676be7da75"
+dependencies = [
+ "async-channel",
+ "async-io",
+ "async-lock",
+ "async-signal",
+ "async-task",
+ "blocking",
+ "cfg-if",
+ "event-listener",
+ "futures-lite",
+ "rustix",
+]
+
+[[package]]
+name = "async-recursion"
+version = "1.1.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "3b43422f69d8ff38f95f1b2bb76517c91589a924d1559a0e935d7c8ce0274c11"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+]
+
+[[package]]
+name = "async-signal"
+version = "0.2.14"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "52b5aaafa020cf5053a01f2a60e8ff5dccf550f0f77ec54a4e47285ac2bab485"
+dependencies = [
+ "async-io",
+ "async-lock",
+ "atomic-waker",
+ "cfg-if",
+ "futures-core",
+ "futures-io",
+ "rustix",
+ "signal-hook-registry",
+ "slab",
+ "windows-sys 0.61.2",
+]
+
+[[package]]
+name = "async-task"
+version = "4.7.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "8b75356056920673b02621b35afd0f7dda9306d03c79a30f5c56c44cf256e3de"
+
+[[package]]
+name = "async-trait"
+version = "0.1.89"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9035ad2d096bed7955a320ee7e2230574d28fd3c3a0f186cbea1ff3c7eed5dbb"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+]
+
 [[package]]
 name = "atk"
 version = "0.18.2"
@@ -218,6 +354,19 @@ dependencies = [
  "objc2",
 ]
 
+[[package]]
+name = "blocking"
+version = "1.6.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e83f8d02be6967315521be875afa792a316e28d57b5a2d401897e2a7921b7f21"
+dependencies = [
+ "async-channel",
+ "async-task",
+ "futures-io",
+ "futures-lite",
+ "piper",
+]
+
 [[package]]
 name = "borsh"
 version = "1.6.1"
@@ -462,6 +611,15 @@ dependencies = [
  "memchr",
 ]
 
+[[package]]
+name = "concurrent-queue"
+version = "2.5.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "4ca0197aee26d1ae37445ee532fefce43251d24cc7c166799f4d46817f1d3973"
+dependencies = [
+ "crossbeam-utils",
+]
+
 [[package]]
 name = "convert_case"
 version = "0.4.0"
@@ -848,6 +1006,33 @@ version = "1.2.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "4ef6b89e5b37196644d8796de5268852ff179b44e96276cf4290264843743bb7"
 
+[[package]]
+name = "endi"
+version = "1.1.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "66b7e2430c6dff6a955451e2cfc438f09cea1965a9d6f87f7e3b90decc014099"
+
+[[package]]
+name = "enumflags2"
+version = "0.7.12"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "1027f7680c853e056ebcec683615fb6fbbc07dbaa13b4d5d9442b146ded4ecef"
+dependencies = [
+ "enumflags2_derive",
+ "serde",
+]
+
+[[package]]
+name = "enumflags2_derive"
+version = "0.7.12"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "67c78a4d8fdf9953a5c9d458f9efe940fd97a0cab0941c075a813ac594733827"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+]
+
 [[package]]
 name = "env_filter"
 version = "0.1.4"
@@ -885,6 +1070,27 @@ dependencies = [
  "windows-sys 0.61.2",
 ]
 
+[[package]]
+name = "event-listener"
+version = "5.4.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "e13b66accf52311f30a0db42147dadea9850cb48cd070028831ae5f5d4b856ab"
+dependencies = [
+ "concurrent-queue",
+ "parking",
+ "pin-project-lite",
+]
+
+[[package]]
+name = "event-listener-strategy"
+version = "0.5.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "8be9f3dfaaffdae2972880079a491a1a8bb7cbed0b8dd7a347f668b4150a3b93"
+dependencies = [
+ "event-listener",
+ "pin-project-lite",
+]
+
 [[package]]
 name = "fastrand"
 version = "2.4.1"
@@ -1048,6 +1254,19 @@ version = "0.3.32"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "cecba35d7ad927e23624b22ad55235f2239cfa44fd10428eecbeba6d6a717718"
 
+[[package]]
+name = "futures-lite"
+version = "2.6.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f78e10609fe0e0b3f4157ffab1876319b5b0db102a2c60dc4626306dc46b44ad"
+dependencies = [
+ "fastrand",
+ "futures-core",
+ "futures-io",
+ "parking",
+ "pin-project-lite",
+]
+
 [[package]]
 name = "futures-macro"
 version = "0.3.32"
@@ -1436,6 +1655,12 @@ version = "0.5.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "2304e00983f87ffb38b55b444b5e3b60a884b5d30c0fca7d82fe33449bbe55ea"
 
+[[package]]
+name = "hermit-abi"
+version = "0.5.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "fc0fef456e4baa96da950455cd02c081ca953b141298e41db3fc7e36b1da849c"
+
 [[package]]
 name = "hex"
 version = "0.4.3"
@@ -1764,6 +1989,25 @@ dependencies = [
  "serde",
 ]
 
+[[package]]
+name = "is-docker"
+version = "0.2.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "928bae27f42bc99b60d9ac7334e3a21d10ad8f1835a4e12ec3ec0464765ed1b3"
+dependencies = [
+ "once_cell",
+]
+
+[[package]]
+name = "is-wsl"
+version = "0.4.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "173609498df190136aa7dea1a91db051746d339e18476eed5ca40521f02d7aa5"
+dependencies = [
+ "is-docker",
+ "once_cell",
+]
+
 [[package]]
 name = "itoa"
 version = "1.0.18"
@@ -2141,6 +2385,15 @@ version = "0.1.14"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "72ef4a56884ca558e5ddb05a1d1e7e1bfd9a68d9ed024c21704cc98872dae1bb"
 
+[[package]]
+name = "ntapi"
+version = "0.4.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c3b335231dfd352ffb0f8017f3b6027a4917f7df785ea2143d8af2adc66980ae"
+dependencies = [
+ "winapi",
+]
+
 [[package]]
 name = "num-conv"
 version = "0.2.1"
@@ -2329,6 +2582,18 @@ version = "1.21.4"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "9f7c3e4beb33f85d45ae3e3a1792185706c8e16d043238c593331cc7cd313b50"
 
+[[package]]
+name = "open"
+version = "5.3.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9f3bab717c29a857abf75fcef718d441ec7cb2725f937343c734740a985d37fd"
+dependencies = [
+ "dunce",
+ "is-wsl",
+ "libc",
+ "pathdiff",
+]
+
 [[package]]
 name = "openssl-probe"
 version = "0.2.1"
@@ -2341,6 +2606,16 @@ version = "0.2.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "04744f49eae99ab78e0d5c0b603ab218f515ea8cfe5a456d7629ad883a3b6e7d"
 
+[[package]]
+name = "ordered-stream"
+version = "0.2.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9aa2b01e1d916879f73a53d01d1d6cee68adbb31d6d9177a8cfce093cced1d50"
+dependencies = [
+ "futures-core",
+ "pin-project-lite",
+]
+
 [[package]]
 name = "osakit"
 version = "0.3.1"
@@ -2380,6 +2655,12 @@ dependencies = [
  "system-deps",
 ]
 
+[[package]]
+name = "parking"
+version = "2.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f38d5652c16fde515bb1ecef450ab0f6a219d619a7274976324d5e377f7dceba"
+
 [[package]]
 name = "parking_lot"
 version = "0.12.5"
@@ -2403,6 +2684,12 @@ dependencies = [
  "windows-link 0.2.1",
 ]
 
+[[package]]
+name = "pathdiff"
+version = "0.2.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "df94ce210e5bc13cb6651479fa48d14f601d9858cfe0467f43ae157023b938d3"
+
 [[package]]
 name = "percent-encoding"
 version = "2.3.2"
@@ -2602,6 +2889,17 @@ version = "0.2.17"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "a89322df9ebe1c1578d689c92318e070967d1042b512afbe49518723f4e6d5cd"
 
+[[package]]
+name = "piper"
+version = "0.2.5"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c835479a4443ded371d6c535cbfd8d31ad92c5d23ae9770a61bc155e4992a3c1"
+dependencies = [
+ "atomic-waker",
+ "fastrand",
+ "futures-io",
+]
+
 [[package]]
 name = "pkg-config"
 version = "0.3.33"
@@ -2640,6 +2938,20 @@ dependencies = [
  "miniz_oxide",
 ]
 
+[[package]]
+name = "polling"
+version = "3.11.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5d0e4f59085d47d8241c88ead0f274e8a0cb551f3625263c05eb8dd897c34218"
+dependencies = [
+ "cfg-if",
+ "concurrent-queue",
+ "hermit-abi",
+ "pin-project-lite",
+ "rustix",
+ "windows-sys 0.61.2",
+]
+
 [[package]]
 name = "potential_utf"
 version = "0.1.5"
@@ -3544,6 +3856,16 @@ version = "1.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"
 
+[[package]]
+name = "signal-hook-registry"
+version = "1.4.8"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c4db69cba1110affc0e9f7bcd48bbf87b3f4fc7c61fc9155afd4c469eb3d6c1b"
+dependencies = [
+ "errno",
+ "libc",
+]
+
 [[package]]
 name = "simd-adler32"
 version = "0.3.9"
@@ -3758,6 +4080,19 @@ dependencies = [
  "syn 2.0.117",
 ]
 
+[[package]]
+name = "sysinfo"
+version = "0.33.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "4fc858248ea01b66f19d8e8a6d55f41deaf91e9d495246fd01368d99935c6c01"
+dependencies = [
+ "core-foundation-sys",
+ "libc",
+ "memchr",
+ "ntapi",
+ "windows 0.57.0",
+]
+
 [[package]]
 name = "system-deps"
 version = "6.2.2"
@@ -3803,7 +4138,7 @@ dependencies = [
  "tao-macros",
  "unicode-segmentation",
  "url",
- "windows",
+ "windows 0.61.3",
  "windows-core 0.61.2",
  "windows-version",
  "x11-dl",
@@ -3892,7 +4227,7 @@ dependencies = [
  "webkit2gtk",
  "webview2-com",
  "window-vibrancy",
- "windows",
+ "windows 0.61.3",
 ]
 
 [[package]]
@@ -4039,6 +4374,28 @@ dependencies = [
  "time",
 ]
 
+[[package]]
+name = "tauri-plugin-opener"
+version = "2.5.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "fc624469b06f59f5a29f874bbc61a2ed737c0f9c23ef09855a292c389c42e83f"
+dependencies = [
+ "dunce",
+ "glob",
+ "objc2-app-kit",
+ "objc2-foundation",
+ "open",
+ "schemars 0.8.22",
+ "serde",
+ "serde_json",
+ "tauri",
+ "tauri-plugin",
+ "thiserror 2.0.18",
+ "url",
+ "windows 0.61.3",
+ "zbus",
+]
+
 [[package]]
 name = "tauri-plugin-process"
 version = "2.3.1"
@@ -4119,7 +4476,7 @@ dependencies = [
  "url",
  "webkit2gtk",
  "webview2-com",
- "windows",
+ "windows 0.61.3",
 ]
 
 [[package]]
@@ -4144,7 +4501,7 @@ dependencies = [
  "url",
  "webkit2gtk",
  "webview2-com",
- "windows",
+ "windows 0.61.3",
  "wry",
 ]
 
@@ -4523,9 +4880,21 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "63e71662fa4b2a2c3a26f570f037eb95bb1f85397f3cd8076caed2f026a6d100"
 dependencies = [
  "pin-project-lite",
+ "tracing-attributes",
  "tracing-core",
 ]
 
+[[package]]
+name = "tracing-attributes"
+version = "0.1.31"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "7490cfa5ec963746568740651ac6781f701c9c5ea257c58e057f3ba8cf69e8da"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+]
+
 [[package]]
 name = "tracing-core"
 version = "0.1.36"
@@ -4575,6 +4944,17 @@ version = "1.19.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "562d481066bde0658276a35467c4af00bdc6ee726305698a55b86e61d7ad82bb"
 
+[[package]]
+name = "uds_windows"
+version = "1.2.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f2f6fb2847f6742cd76af783a2a2c49e9375d0a111c7bef6f71cd9e738c72d6e"
+dependencies = [
+ "memoffset",
+ "tempfile",
+ "windows-sys 0.61.2",
+]
+
 [[package]]
 name = "unic-char-property"
 version = "0.9.0"
@@ -5001,10 +5381,10 @@ checksum = "7130243a7a5b33c54a444e54842e6a9e133de08b5ad7b5861cd8ed9a6a5bc96a"
 dependencies = [
  "webview2-com-macros",
  "webview2-com-sys",
- "windows",
+ "windows 0.61.3",
  "windows-core 0.61.2",
- "windows-implement",
- "windows-interface",
+ "windows-implement 0.60.2",
+ "windows-interface 0.59.3",
 ]
 
 [[package]]
@@ -5025,7 +5405,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "381336cfffd772377d291702245447a5251a2ffa5bad679c99e61bc48bacbf9c"
 dependencies = [
  "thiserror 2.0.18",
- "windows",
+ "windows 0.61.3",
  "windows-core 0.61.2",
 ]
 
@@ -5075,6 +5455,16 @@ dependencies = [
  "windows-version",
 ]
 
+[[package]]
+name = "windows"
+version = "0.57.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "12342cb4d8e3b046f3d80effd474a7a02447231330ef77d71daa6fbc40681143"
+dependencies = [
+ "windows-core 0.57.0",
+ "windows-targets 0.52.6",
+]
+
 [[package]]
 name = "windows"
 version = "0.61.3"
@@ -5097,14 +5487,26 @@ dependencies = [
  "windows-core 0.61.2",
 ]
 
+[[package]]
+name = "windows-core"
+version = "0.57.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d2ed2439a290666cd67ecce2b0ffaad89c2a56b976b736e6ece670297897832d"
+dependencies = [
+ "windows-implement 0.57.0",
+ "windows-interface 0.57.0",
+ "windows-result 0.1.2",
+ "windows-targets 0.52.6",
+]
+
 [[package]]
 name = "windows-core"
 version = "0.61.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "c0fdd3ddb90610c7638aa2b3a3ab2904fb9e5cdbecc643ddb3647212781c4ae3"
 dependencies = [
- "windows-implement",
- "windows-interface",
+ "windows-implement 0.60.2",
+ "windows-interface 0.59.3",
  "windows-link 0.1.3",
  "windows-result 0.3.4",
  "windows-strings 0.4.2",
@@ -5116,8 +5518,8 @@ version = "0.62.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "b8e83a14d34d0623b51dce9581199302a221863196a1dde71a7663a4c2be9deb"
 dependencies = [
- "windows-implement",
- "windows-interface",
+ "windows-implement 0.60.2",
+ "windows-interface 0.59.3",
  "windows-link 0.2.1",
  "windows-result 0.4.1",
  "windows-strings 0.5.1",
@@ -5134,6 +5536,17 @@ dependencies = [
  "windows-threading",
 ]
 
+[[package]]
+name = "windows-implement"
+version = "0.57.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "9107ddc059d5b6fbfbffdfa7a7fe3e22a226def0b2608f72e9d552763d3e1ad7"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+]
+
 [[package]]
 name = "windows-implement"
 version = "0.60.2"
@@ -5145,6 +5558,17 @@ dependencies = [
  "syn 2.0.117",
 ]
 
+[[package]]
+name = "windows-interface"
+version = "0.57.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "29bee4b38ea3cde66011baa44dba677c432a78593e202392d1e9070cf2a7fca7"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+]
+
 [[package]]
 name = "windows-interface"
 version = "0.59.3"
@@ -5178,6 +5602,15 @@ dependencies = [
  "windows-link 0.1.3",
 ]
 
+[[package]]
+name = "windows-result"
+version = "0.1.2"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5e383302e8ec8515204254685643de10811af0ed97ea37210dc26fb0032647f8"
+dependencies = [
+ "windows-targets 0.52.6",
+]
+
 [[package]]
 name = "windows-result"
 version = "0.3.4"
@@ -5477,6 +5910,9 @@ name = "winnow"
 version = "0.7.15"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "df79d97927682d2fd8adb29682d1140b343be4ac0f08fd68b7765d9c059d3945"
+dependencies = [
+ "memchr",
+]
 
 [[package]]
 name = "winnow"
@@ -5629,7 +6065,7 @@ dependencies = [
  "webkit2gtk",
  "webkit2gtk-sys",
  "webview2-com",
- "windows",
+ "windows 0.61.3",
  "windows-core 0.61.2",
  "windows-version",
  "x11-dl",
@@ -5698,6 +6134,67 @@ dependencies = [
  "synstructure",
 ]
 
+[[package]]
+name = "zbus"
+version = "5.14.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ca82f95dbd3943a40a53cfded6c2d0a2ca26192011846a1810c4256ef92c60bc"
+dependencies = [
+ "async-broadcast",
+ "async-executor",
+ "async-io",
+ "async-lock",
+ "async-process",
+ "async-recursion",
+ "async-task",
+ "async-trait",
+ "blocking",
+ "enumflags2",
+ "event-listener",
+ "futures-core",
+ "futures-lite",
+ "hex",
+ "libc",
+ "ordered-stream",
+ "rustix",
+ "serde",
+ "serde_repr",
+ "tracing",
+ "uds_windows",
+ "uuid",
+ "windows-sys 0.61.2",
+ "winnow 0.7.15",
+ "zbus_macros",
+ "zbus_names",
+ "zvariant",
+]
+
+[[package]]
+name = "zbus_macros"
+version = "5.14.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "897e79616e84aac4b2c46e9132a4f63b93105d54fe8c0e8f6bffc21fa8d49222"
+dependencies = [
+ "proc-macro-crate 3.5.0",
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+ "zbus_names",
+ "zvariant",
+ "zvariant_utils",
+]
+
+[[package]]
+name = "zbus_names"
+version = "4.3.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "ffd8af6d5b78619bab301ff3c560a5bd22426150253db278f164d6cf3b72c50f"
+dependencies = [
+ "serde",
+ "winnow 0.7.15",
+ "zvariant",
+]
+
 [[package]]
 name = "zerocopy"
 version = "0.8.48"
@@ -5824,3 +6321,43 @@ dependencies = [
  "log",
  "simd-adler32",
 ]
+
+[[package]]
+name = "zvariant"
+version = "5.10.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5708299b21903bbe348e94729f22c49c55d04720a004aa350f1f9c122fd2540b"
+dependencies = [
+ "endi",
+ "enumflags2",
+ "serde",
+ "winnow 0.7.15",
+ "zvariant_derive",
+ "zvariant_utils",
+]
+
+[[package]]
+name = "zvariant_derive"
+version = "5.10.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "5b59b012ebe9c46656f9cc08d8da8b4c726510aef12559da3e5f1bf72780752c"
+dependencies = [
+ "proc-macro-crate 3.5.0",
+ "proc-macro2",
+ "quote",
+ "syn 2.0.117",
+ "zvariant_utils",
+]
+
+[[package]]
+name = "zvariant_utils"
+version = "3.3.0"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "f75c23a64ef8f40f13a6989991e643554d9bef1d682a281160cf0c1bc389c5e9"
+dependencies = [
+ "proc-macro2",
+ "quote",
+ "serde",
+ "syn 2.0.117",
+ "winnow 0.7.15",
+]

frontend/src-tauri/Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "app"
-version = "0.2.0"
+version = "0.2.4"
 description = "A Tauri App"
 authors = ["you"]
 license = ""
@@ -27,6 +27,7 @@ tauri-plugin-dialog = "2"
 tauri-plugin-window-state = "2.0.0"
 tauri-plugin-updater = "2"
 tauri-plugin-process = "2"
+tauri-plugin-opener = "2"
 
 # First-run bootstrap: the installer ships ~10 MB with only the Tauri
 # shell + pyproject.toml + uv.lock + backend source. On first launch the
@@ -39,8 +40,19 @@ ureq = "2"
 tar = "0.4"
 flate2 = "1"
 
+# ── Rust IPC commands (cross-platform) ──
+# get_sysinfo: CPU + RAM metrics without HTTP round-trip
+sysinfo = { version = "0.33", default-features = false, features = ["system"] }
+# hf_cache_scan: walk HF cache directory 3-5× faster than Python
+walkdir = "2"
+# File hash verification (optional, for future integrity checks)
+sha2 = "0.10"
+
 [target.'cfg(windows)'.dependencies]
 zip = { version = "2", default-features = false, features = ["deflate"] }
 
 [target.'cfg(unix)'.dependencies]
 libc = "0.2"
+
+[target.'cfg(target_os = "linux")'.dependencies]
+webkit2gtk = "2.0"

frontend/src-tauri/capabilities/default.json

@@ -18,6 +18,7 @@
     "dialog:allow-ask",
     "updater:default",
     "process:default",
-    "process:allow-restart"
+    "process:allow-restart",
+    "opener:default"
   ]
 }

frontend/src-tauri/src/lib.rs

@@ -1,13 +1,23 @@
 use std::fs;
-use std::io::{self, Read};
+use std::io::{self, BufRead, BufReader, Read};
 use std::net::TcpStream;
 use std::path::{Path, PathBuf};
 use std::process::{Child, Command, Stdio};
-use std::sync::Mutex;
-use std::time::Duration;
-use tauri::Manager;
+use std::sync::{Arc, Mutex};
+use std::time::{Duration, Instant};
+use serde::Serialize;
+use tauri::{Emitter, Manager};
 
-const BACKEND_PORT: u16 = 8000;
+// Unique port range (3900-3902) chosen to avoid common conflicts:
+// 8000 collides with Django/Rails/Jupyter/Airflow on most dev machines.
+// 3900 is the backend (FastAPI + uvicorn), 3901 is the Vite dev server,
+// 3902 is reserved for future IPC / websocket listeners.
+fn backend_port() -> u16 {
+    std::env::var("OMNIVOICE_PORT")
+        .ok()
+        .and_then(|v| v.parse().ok())
+        .unwrap_or(3900)
+}
 
 // Version of the Astral `uv` binary we download at first run when no system
 // uv is on PATH. Pinned for reproducibility — bump alongside the uv.lock
@@ -18,6 +28,138 @@ pub struct BackendState {
     pub process: Mutex<Option<Child>>,
 }
 
+// ── Bootstrap progress (for the React splash screen) ─────────────────────
+
+#[derive(Clone, Serialize, Debug)]
+#[serde(tag = "stage", rename_all = "snake_case")]
+pub enum BootstrapStage {
+    /// Working out whether we need to bootstrap at all.
+    Checking,
+    /// Fetching the standalone `uv` binary from astral-sh/uv releases.
+    DownloadingUv { percent: Option<u8> },
+    /// Creating the Python 3.11 venv.
+    CreatingVenv,
+    /// Running `uv sync --frozen --no-dev`. Biggest time sink on first run
+    /// (~5-10 min to pull torch + whisperx + faster-whisper + demucs).
+    InstallingDeps,
+    /// Fetching the per-platform static ffmpeg binary from the
+    /// ffmpeg-static GitHub release. ~30-70 MB.
+    DownloadingFfmpeg { percent: Option<u8> },
+    /// Venv ready, spawning uvicorn. Should be <5 s.
+    StartingBackend,
+    /// Backend is listening and healthy. Frontend can leave the splash.
+    Ready,
+    /// Something blew up; message carries the reason.
+    Failed { message: String },
+}
+
+pub struct BootstrapState {
+    pub stage: Arc<Mutex<BootstrapStage>>,
+}
+
+fn set_stage(state: &Arc<Mutex<BootstrapStage>>, stage: BootstrapStage) {
+    if let Ok(mut guard) = state.lock() {
+        *guard = stage;
+    }
+}
+
+// ── Splash log + byte-progress event channel ─────────────────────────────
+//
+// Two Tauri events drive the splash UI's log panel + per-stage progress
+// bar. The splash polls `bootstrap_status` for the coarse stage label and
+// listens on these for live detail.
+
+#[derive(Clone, Serialize)]
+struct LogPayload {
+    stage: String,
+    line: String,
+}
+
+#[derive(Clone, Serialize)]
+struct ProgressPayload {
+    stage: String,
+    bytes_done: u64,
+    bytes_total: u64,
+    percent: Option<u8>,
+}
+
+fn emit_log<R: tauri::Runtime>(app: &tauri::AppHandle<R>, stage: &str, line: &str) {
+    let _ = app.emit(
+        "bootstrap-log",
+        LogPayload { stage: stage.to_string(), line: line.to_string() },
+    );
+}
+
+fn emit_progress<R: tauri::Runtime>(
+    app: &tauri::AppHandle<R>,
+    stage: &str,
+    done: u64,
+    total: u64,
+) {
+    let percent = if total > 0 {
+        Some(((done as f64 / total as f64) * 100.0).min(100.0) as u8)
+    } else {
+        None
+    };
+    let _ = app.emit(
+        "bootstrap-progress",
+        ProgressPayload {
+            stage: stage.to_string(),
+            bytes_done: done,
+            bytes_total: total,
+            percent,
+        },
+    );
+}
+
+/// Stream stdout+stderr of a long-running subprocess line-by-line into the
+/// splash log panel. Replaces blocking `.status()` calls so the user sees
+/// `uv sync` chatter during the 5–10 min pip resolve. Returns the exit
+/// status once the child exits.
+fn run_streaming<R: tauri::Runtime>(
+    app: &tauri::AppHandle<R>,
+    stage: &str,
+    cmd: &mut Command,
+) -> io::Result<std::process::ExitStatus> {
+    cmd.stdout(Stdio::piped()).stderr(Stdio::piped());
+    let mut child = cmd.spawn()?;
+    let stdout = child.stdout.take();
+    let stderr = child.stderr.take();
+    let app_out = app.clone();
+    let app_err = app.clone();
+    let stage_out = stage.to_string();
+    let stage_err = stage.to_string();
+    let h_out = std::thread::spawn(move || {
+        if let Some(s) = stdout {
+            for line in BufReader::new(s).lines().flatten() {
+                log::info!("[{}] {}", stage_out, line);
+                emit_log(&app_out, &stage_out, &line);
+            }
+        }
+    });
+    let h_err = std::thread::spawn(move || {
+        if let Some(s) = stderr {
+            for line in BufReader::new(s).lines().flatten() {
+                log::info!("[{}] {}", stage_err, line);
+                emit_log(&app_err, &stage_err, &line);
+            }
+        }
+    });
+    let status = child.wait()?;
+    let _ = h_out.join();
+    let _ = h_err.join();
+    Ok(status)
+}
+
+#[tauri::command]
+fn bootstrap_status(state: tauri::State<'_, BootstrapState>) -> BootstrapStage {
+    state
+        .stage
+        .lock()
+        .map(|g| g.clone())
+        .unwrap_or(BootstrapStage::Checking)
+}
+
 // ── Port probing ──────────────────────────────────────────────────────────
 
 /// Just "something is listening on :port"
@@ -241,8 +383,19 @@ fn copy_dir_recursive(src: &Path, dst: &Path) -> io::Result<()> {
 /// Dev mode wins: if `.venv` exists at the project root, reuse it (matches
 /// the behaviour of `bun run dev`). Otherwise copy the bundled pyproject.toml
 /// + uv.lock + backend/ from Tauri resources into `app_local_data_dir/project`
-/// and run `uv venv` + `uv sync --frozen --no-dev` there.
-fn ensure_venv_ready<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<(PathBuf, PathBuf)> {
+/// and run `uv venv` + `uv sync --frozen --no-dev` there. All subprocess
+/// stdout/stderr is streamed to the splash log panel via Tauri events.
+fn ensure_venv_ready<R: tauri::Runtime>(app: &tauri::AppHandle<R>, progress: Option<&Arc<Mutex<BootstrapStage>>>) -> Option<(PathBuf, PathBuf)> {
+    let fail = |progress: Option<&Arc<Mutex<BootstrapStage>>>, msg: &str| {
+        log::error!("{}", msg);
+        if let Some(p) = progress {
+            set_stage(p, BootstrapStage::Failed { message: msg.to_string() });
+        }
+    };
+    if let Some(p) = progress {
+        set_stage(p, BootstrapStage::Checking);
+    }
+
     if let Some(dev_root) = find_dev_project_root() {
         let dev_venv = dev_root.join(".venv");
         let dev_py = venv_python_path(&dev_venv);
@@ -265,32 +418,49 @@ fn ensure_venv_ready<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<(PathBuf,
     }
 
     let resource_dir = app.path().resource_dir().ok()?;
-    let resource_pyproject = resource_dir.join("pyproject.toml");
-    let resource_uvlock = resource_dir.join("uv.lock");
-    let resource_backend = resource_dir.join("backend");
+
+    // Tauri v2 replaces `../` with `_up_/` in bundled resource paths. So
+    // `../../pyproject.toml` from tauri.conf.json becomes
+    // `$RESOURCE/_up_/_up_/pyproject.toml` on Windows MSI and Linux deb.
+    // macOS .app bundles flatten resources into Contents/Resources/ directly.
+    // Try both layouts so the bootstrap works across all platforms.
+    let flat = resource_dir.clone();
+    let up2  = resource_dir.join("_up_").join("_up_");
+
+    let (resource_pyproject, resource_uvlock, resource_backend) = if flat.join("pyproject.toml").is_file() {
+        (flat.join("pyproject.toml"), flat.join("uv.lock"), flat.join("backend"))
+    } else if up2.join("pyproject.toml").is_file() {
+        (up2.join("pyproject.toml"), up2.join("uv.lock"), up2.join("backend"))
+    } else {
+        fail(progress, &format!(
+            "Missing bootstrap resources — checked flat={} and _up_={}\n  pyproject.toml: flat={}, up2={}",
+            flat.display(), up2.display(),
+            flat.join("pyproject.toml").display(),
+            up2.join("pyproject.toml").display()));
+        return None;
+    };
+
     if !resource_pyproject.is_file() || !resource_backend.is_dir() {
-        log::warn!(
+        fail(progress, &format!(
             "Missing bootstrap resources (pyproject={}, backend={})",
-            resource_pyproject.display(),
-            resource_backend.display()
-        );
+            resource_pyproject.display(), resource_backend.display()));
         return None;
     }
 
     log::info!("First-run venv bootstrap in {}", project_dir.display());
     if let Err(e) = fs::create_dir_all(&project_dir) {
-        log::error!("mkdir {} failed: {}", project_dir.display(), e);
+        fail(progress, &format!("mkdir {} failed: {}", project_dir.display(), e));
         return None;
     }
     if let Err(e) = fs::copy(&resource_pyproject, project_dir.join("pyproject.toml")) {
-        log::error!("copy pyproject.toml: {}", e);
+        fail(progress, &format!("copy pyproject.toml: {}", e));
         return None;
     }
     if resource_uvlock.is_file() {
         let _ = fs::copy(&resource_uvlock, project_dir.join("uv.lock"));
     }
     if let Err(e) = copy_dir_recursive(&resource_backend, &backend_dir) {
-        log::error!("copy backend/: {}", e);
+        fail(progress, &format!("copy backend/: {}", e));
         return None;
     }
 
@@ -298,31 +468,42 @@ fn ensure_venv_ready<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<(PathBuf,
     // standalone binary into `app_data/tools`.
     let uv_path = match Command::new("uv").arg("--version").output() {
         Ok(_) => PathBuf::from("uv"),
-        Err(_) => match install_uv_standalone(&app_data.join("tools")) {
-            Ok(p) => p,
-            Err(e) => {
-                log::error!("uv install failed: {}", e);
-                return None;
+        Err(_) => {
+            if let Some(p) = progress {
+                set_stage(p, BootstrapStage::DownloadingUv { percent: None });
             }
-        },
+            match install_uv_standalone(&app_data.join("tools")) {
+                Ok(p) => p,
+                Err(e) => {
+                    fail(progress, &format!("uv install failed: {}", e));
+                    return None;
+                }
+            }
+        }
     };
     log::info!("Bootstrap uv: {}", uv_path.display());
 
-    let status = Command::new(&uv_path)
-        .args(["venv", "--python", "3.11"])
-        .current_dir(&project_dir)
-        .status();
-    if !matches!(status, Ok(s) if s.success()) {
-        log::error!("uv venv failed: {:?}", status);
+    if let Some(p) = progress {
+        set_stage(p, BootstrapStage::CreatingVenv);
+    }
+    let mut venv_cmd = Command::new(&uv_path);
+    venv_cmd.args(["venv", "--python", "3.11"]).current_dir(&project_dir);
+    let status = run_streaming(app, "creating_venv", &mut venv_cmd);
+    if !matches!(status, Ok(ref s) if s.success()) {
+        fail(progress, &format!("uv venv failed: {:?}", status));
         return None;
     }
 
-    let sync_status = Command::new(&uv_path)
-        .args(["sync", "--frozen", "--no-dev"])
-        .current_dir(&project_dir)
-        .status();
-    if !matches!(sync_status, Ok(s) if s.success()) {
-        log::error!("uv sync failed: {:?}", sync_status);
+    if let Some(p) = progress {
+        set_stage(p, BootstrapStage::InstallingDeps);
+    }
+    let mut sync_cmd = Command::new(&uv_path);
+    sync_cmd
+        .args(["sync", "--frozen", "--no-dev", "--verbose"])
+        .current_dir(&project_dir);
+    let sync_status = run_streaming(app, "installing_deps", &mut sync_cmd);
+    if !matches!(sync_status, Ok(ref s) if s.success()) {
+        fail(progress, &format!("uv sync failed: {:?}", sync_status));
         return None;
     }
 
@@ -346,16 +527,170 @@ fn find_dev_project_root() -> Option<PathBuf> {
 }
 
 fn backend_log_path() -> PathBuf {
-    let home = std::env::var("HOME").unwrap_or_else(|_| "/tmp".to_string());
-    let log_dir = PathBuf::from(&home).join("Library/Logs/OmniVoice");
+    // Cross-platform log directory:
+    //   macOS:   ~/Library/Logs/OmniVoice
+    //   Linux:   $XDG_STATE_HOME/OmniVoice  or  ~/.local/state/OmniVoice
+    //   Windows: %LOCALAPPDATA%\OmniVoice\Logs
+    let log_dir = if cfg!(target_os = "macos") {
+        let home = std::env::var("HOME").unwrap_or_else(|_| "/tmp".to_string());
+        PathBuf::from(home).join("Library/Logs/OmniVoice")
+    } else if cfg!(target_os = "windows") {
+        let base = std::env::var("LOCALAPPDATA")
+            .or_else(|_| std::env::var("USERPROFILE").map(|u| format!("{}\\AppData\\Local", u)))
+            .unwrap_or_else(|_| "C:\\Temp".to_string());
+        PathBuf::from(base).join("OmniVoice").join("Logs")
+    } else {
+        // Linux / other Unix
+        let base = std::env::var("XDG_STATE_HOME")
+            .or_else(|_| std::env::var("HOME").map(|h| format!("{}/.local/state", h)))
+            .unwrap_or_else(|_| "/tmp".to_string());
+        PathBuf::from(base).join("OmniVoice")
+    };
     let _ = fs::create_dir_all(&log_dir);
     log_dir.join("backend.log")
 }
 
+// ── ffmpeg static binary fetch (cross-platform, no extraction) ───────────
+//
+// We pull a single statically-linked binary per host platform from the
+// long-lived `ffmpeg-static` GitHub release (MIT, ffmpeg-6.0). One binary,
+// no archive — just download, chmod +x, done. URLs intentionally pinned
+// to a specific tag for reproducibility; bump `FFMPEG_TAG` to upgrade.
+const FFMPEG_TAG: &str = "b6.0";
+
+fn ffmpeg_download_url() -> Option<&'static str> {
+    match (std::env::consts::OS, std::env::consts::ARCH) {
+        ("macos", "aarch64")  => Some("ffmpeg-darwin-arm64"),
+        ("macos", "x86_64")   => Some("ffmpeg-darwin-x64"),
+        ("linux", "x86_64")   => Some("ffmpeg-linux-x64"),
+        ("linux", "aarch64")  => Some("ffmpeg-linux-arm64"),
+        ("windows", "x86_64") => Some("ffmpeg-win32-x64.exe"),
+        _ => None,
+    }
+}
+
+/// Download the static ffmpeg binary into `app_data/bin/ffmpeg[.exe]`.
+/// Idempotent: if the file exists and is executable, no-ops. Streams byte
+/// progress to the splash via `bootstrap-progress`.
+fn install_ffmpeg<R: tauri::Runtime>(
+    app: &tauri::AppHandle<R>,
+    dest_dir: &Path,
+    progress: Option<&Arc<Mutex<BootstrapStage>>>,
+) -> io::Result<PathBuf> {
+    let bin_name = if cfg!(windows) { "ffmpeg.exe" } else { "ffmpeg" };
+    let final_path = dest_dir.join(bin_name);
+
+    if final_path.is_file() {
+        // Treat any non-zero file as good enough — the user can delete it
+        // to force a re-download. Avoids bullying users on flaky networks.
+        if let Ok(meta) = fs::metadata(&final_path) {
+            if meta.len() > 1_000_000 {
+                return Ok(final_path);
+            }
+        }
+    }
+
+    let asset = ffmpeg_download_url().ok_or_else(|| {
+        io::Error::new(io::ErrorKind::Unsupported, "no ffmpeg binary for this platform")
+    })?;
+    let url = format!(
+        "https://github.com/eugeneware/ffmpeg-static/releases/download/{}/{}",
+        FFMPEG_TAG, asset
+    );
+
+    fs::create_dir_all(dest_dir)?;
+    let tmp_path = dest_dir.join(format!("{}.part", bin_name));
+    let _ = fs::remove_file(&tmp_path);
+
+    if let Some(p) = progress {
+        set_stage(p, BootstrapStage::DownloadingFfmpeg { percent: Some(0) });
+    }
+    emit_log(app, "downloading_ffmpeg", &format!("GET {}", url));
+
+    let resp = ureq::get(&url)
+        .timeout(Duration::from_secs(300))
+        .call()
+        .map_err(|e| io::Error::new(io::ErrorKind::Other, format!("ffmpeg download: {}", e)))?;
+    if resp.status() != 200 {
+        return Err(io::Error::new(
+            io::ErrorKind::Other,
+            format!("ffmpeg HTTP {} from {}", resp.status(), url),
+        ));
+    }
+    let total: u64 = resp
+        .header("Content-Length")
+        .and_then(|v| v.parse().ok())
+        .unwrap_or(0);
+
+    let mut reader = resp.into_reader();
+    let mut out = fs::File::create(&tmp_path)?;
+    let mut buf = [0u8; 64 * 1024];
+    let mut done: u64 = 0;
+    let mut last_emit = Instant::now();
+    loop {
+        let n = reader.read(&mut buf)?;
+        if n == 0 { break; }
+        use std::io::Write;
+        out.write_all(&buf[..n])?;
+        done += n as u64;
+        if last_emit.elapsed() > Duration::from_millis(150) {
+            emit_progress(app, "downloading_ffmpeg", done, total);
+            if let Some(p) = progress {
+                let pct = if total > 0 {
+                    Some(((done as f64 / total as f64) * 100.0) as u8)
+                } else { None };
+                set_stage(p, BootstrapStage::DownloadingFfmpeg { percent: pct });
+            }
+            last_emit = Instant::now();
+        }
+    }
+    drop(out);
+    emit_progress(app, "downloading_ffmpeg", done, total.max(done));
+
+    fs::rename(&tmp_path, &final_path)?;
+    #[cfg(unix)]
+    {
+        use std::os::unix::fs::PermissionsExt;
+        let mut perms = fs::metadata(&final_path)?.permissions();
+        perms.set_mode(0o755);
+        fs::set_permissions(&final_path, perms)?;
+    }
+    emit_log(app, "downloading_ffmpeg",
+        &format!("ffmpeg ready at {} ({} bytes)", final_path.display(), done));
+    Ok(final_path)
+}
+
+/// Resolve the ffmpeg path to inject into the backend env. Order: app-data
+/// download (preferred — controlled), bundled resource (legacy), system
+/// PATH (None — let the backend find it). Triggers a fresh download into
+/// `app_data/bin/` if nothing usable is on disk.
+fn ensure_ffmpeg_ready<R: tauri::Runtime>(
+    app: &tauri::AppHandle<R>,
+    progress: Option<&Arc<Mutex<BootstrapStage>>>,
+) -> Option<PathBuf> {
+    let app_data = app.path().app_local_data_dir().ok()?;
+    let bin_dir = app_data.join("bin");
+    let installed = bin_dir.join(if cfg!(windows) { "ffmpeg.exe" } else { "ffmpeg" });
+    if installed.is_file() {
+        return Some(installed);
+    }
+    if let Some(bundled) = find_bundled_ffmpeg(app) {
+        return Some(bundled);
+    }
+    match install_ffmpeg(app, &bin_dir, progress) {
+        Ok(p) => Some(p),
+        Err(e) => {
+            emit_log(app, "downloading_ffmpeg", &format!("ffmpeg fetch failed: {}", e));
+            log::warn!("ffmpeg fetch failed: {} — backend will fall back to system PATH", e);
+            None
+        }
+    }
+}
+
 /// Stage the bundled ffmpeg binary and return its absolute path. The path is
 /// exported via `OMNIVOICE_FFMPEG` so the Python backend uses it over a
 /// system install. Returns None if the bundled binary isn't present.
-fn find_bundled_ffmpeg<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<PathBuf> {
+fn find_bundled_ffmpeg<R: tauri::Runtime>(app: &tauri::AppHandle<R>) -> Option<PathBuf> {
     let dir = app.path().resource_dir().ok()?;
     let candidates = [
         dir.join("bin/ffmpeg"),
@@ -375,7 +710,7 @@ fn find_bundled_ffmpeg<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<PathBuf
 
 // ── Spawn the backend via the bootstrapped venv Python ────────────────────
 
-fn spawn_backend<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<Child> {
+fn spawn_backend<R: tauri::Runtime>(app: &tauri::AppHandle<R>, progress: Option<&Arc<Mutex<BootstrapStage>>>) -> Option<Child> {
     let log_path = backend_log_path();
     let err_path = log_path.with_file_name("backend_err.log");
     log::info!(
@@ -384,7 +719,7 @@ fn spawn_backend<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<Child> {
         err_path.display(),
     );
 
-    let (python, backend_dir) = match ensure_venv_ready(app) {
+    let (python, backend_dir) = match ensure_venv_ready(app, progress) {
         Some(x) => x,
         None => {
             log::error!("Venv bootstrap failed — backend not started");
@@ -392,11 +727,28 @@ fn spawn_backend<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<Child> {
         }
     };
 
+    // Fetch ffmpeg before flipping to StartingBackend so the splash shows
+    // the real-time download. Failure isn't fatal — we'll fall back to the
+    // system PATH and let the backend log the missing-ffmpeg error itself.
+    let ffmpeg_path = ensure_ffmpeg_ready(app, progress);
+
+    if let Some(p) = progress {
+        set_stage(p, BootstrapStage::StartingBackend);
+    }
+
     let stdout_file = fs::File::create(&log_path).ok();
     let stderr_file = fs::File::create(&err_path).ok();
 
     let mut env: Vec<(String, String)> = vec![("PYTHONUNBUFFERED".into(), "1".into())];
-    if let Some(ff) = find_bundled_ffmpeg(app) {
+    // Windows: Triton doesn't exist, so torch.compile tries to download it
+    // and fails. TORCHDYNAMO_DISABLE skips torch.compile entirely. Also
+    // disable HF symlinks (NTFS symlinks need Developer Mode / admin).
+    if cfg!(target_os = "windows") {
+        env.push(("TORCHDYNAMO_DISABLE".into(), "1".into()));
+        env.push(("HF_HUB_DISABLE_SYMLINKS_WARNING".into(), "1".into()));
+        env.push(("HF_HUB_DISABLE_SYMLINKS".into(), "1".into()));
+    }
+    if let Some(ff) = ffmpeg_path {
         env.push(("OMNIVOICE_FFMPEG".into(), ff.to_string_lossy().into_owned()));
         let path_sep = if cfg!(windows) { ";" } else { ":" };
         env.push((
@@ -424,7 +776,7 @@ fn spawn_backend<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<Child> {
             "--host",
             "127.0.0.1",
             "--port",
-            &BACKEND_PORT.to_string(),
+            &backend_port().to_string(),
         ])
         .stdout(stdout_file.map(Stdio::from).unwrap_or_else(Stdio::null))
         .stderr(stderr_file.map(Stdio::from).unwrap_or_else(Stdio::null))
@@ -445,15 +797,288 @@ fn spawn_backend<R: tauri::Runtime>(app: &tauri::App<R>) -> Option<Child> {
     }
 }
 
+// ── Native IPC commands ──────────────────────────────────────────────────
+//
+// These replace HTTP round-trips for local-only data. The frontend tries
+// `invoke()` first and falls back to the Python HTTP endpoint when running
+// in browser dev mode (no Tauri shell).
+
+/// System metrics: CPU + RAM. Replaces `GET /sysinfo` (polled every 5 s).
+/// VRAM is not available from the `sysinfo` crate — the frontend merges
+/// this with the Python endpoint's `vram` / `gpu_active` fields.
+#[tauri::command]
+fn get_sysinfo() -> SysinfoPayload {
+    use sysinfo::System;
+
+    let mut sys = System::new();
+    sys.refresh_cpu_usage();
+    sys.refresh_memory();
+
+    // CPU usage needs two measurements with a gap to be meaningful. On the
+    // very first call the values will be 0 — the frontend's 5 s poll cycle
+    // naturally provides the second reading.
+    let cpu = sys.global_cpu_usage() as f64;
+    let ram = sys.used_memory() as f64 / (1024.0 * 1024.0 * 1024.0);
+    let total_ram = sys.total_memory() as f64 / (1024.0 * 1024.0 * 1024.0);
+
+    SysinfoPayload {
+        cpu: (cpu * 100.0).round() / 100.0,
+        ram: (ram * 100.0).round() / 100.0,
+        total_ram: (total_ram * 100.0).round() / 100.0,
+        // VRAM stays at 0 — Python endpoint provides the real value.
+        vram: 0.0,
+        gpu_active: false,
+    }
+}
+
+#[derive(Serialize, Clone)]
+struct SysinfoPayload {
+    cpu: f64,
+    ram: f64,
+    total_ram: f64,
+    vram: f64,
+    gpu_active: bool,
+}
+
+/// Tail the last N lines of a log file. Replaces `GET /system/logs` and
+/// `GET /system/logs/tauri`. Uses seek-from-end for large files.
+#[tauri::command]
+fn read_log_tail(source: String, tail: Option<usize>) -> LogTailPayload {
+    let tail = tail.unwrap_or(300).clamp(10, 2000);
+
+    let path = match source.as_str() {
+        "backend" => backend_runtime_log_path(),
+        "tauri" => tauri_log_path(),
+        _ => return LogTailPayload {
+            lines: vec![],
+            path: String::new(),
+            exists: false,
+            total_lines: 0,
+        },
+    };
+
+    let path_str = path.to_string_lossy().to_string();
+    if !path.exists() {
+        return LogTailPayload {
+            lines: vec![],
+            path: path_str,
+            exists: false,
+            total_lines: 0,
+        };
+    }
+
+    match fs::read_to_string(&path) {
+        Ok(content) => {
+            let all_lines: Vec<&str> = content.lines().collect();
+            let total = all_lines.len();
+            let start = total.saturating_sub(tail);
+            let lines: Vec<String> = all_lines[start..]
+                .iter()
+                .map(|l| format!("{}\n", l))
+                .collect();
+            LogTailPayload {
+                lines,
+                path: path_str,
+                exists: true,
+                total_lines: total,
+            }
+        }
+        Err(_) => LogTailPayload {
+            lines: vec![],
+            path: path_str,
+            exists: true,
+            total_lines: 0,
+        },
+    }
+}
+
+#[derive(Serialize, Clone)]
+struct LogTailPayload {
+    lines: Vec<String>,
+    path: String,
+    exists: bool,
+    total_lines: usize,
+}
+
+/// The backend's rolling runtime log — the file Python's RotatingFileHandler
+/// writes to. Mirrors the path in `backend/core/config.py`.
+fn backend_runtime_log_path() -> PathBuf {
+    // Same logic as Python's `get_app_data_dir()` in core/config.py
+    let data_dir = if cfg!(target_os = "macos") {
+        dirs_data_dir().join("OmniVoice")
+    } else if cfg!(target_os = "windows") {
+        PathBuf::from(
+            std::env::var("APPDATA").unwrap_or_else(|_| ".".to_string()),
+        )
+        .join("OmniVoice")
+    } else {
+        // Linux: ~/.omnivoice
+        PathBuf::from(
+            std::env::var("HOME").unwrap_or_else(|_| "/tmp".to_string()),
+        )
+        .join(".omnivoice")
+    };
+    data_dir.join("omnivoice.log")
+}
+
+/// macOS: ~/Library/Application Support
+/// Falls back to home dir on other platforms (not used directly there).
+fn dirs_data_dir() -> PathBuf {
+    #[cfg(target_os = "macos")]
+    {
+        PathBuf::from(
+            std::env::var("HOME").unwrap_or_else(|_| "/tmp".to_string()),
+        )
+        .join("Library/Application Support")
+    }
+    #[cfg(not(target_os = "macos"))]
+    {
+        PathBuf::from(
+            std::env::var("HOME").unwrap_or_else(|_| "/tmp".to_string()),
+        )
+    }
+}
+
+/// Tauri plugin log file — the file `tauri-plugin-log` writes to.
+fn tauri_log_path() -> PathBuf {
+    let bid = "com.debpalash.omnivoice-studio";
+    let home = std::env::var("HOME").unwrap_or_else(|_| "/tmp".to_string());
+
+    if cfg!(target_os = "macos") {
+        PathBuf::from(&home)
+            .join("Library/Logs")
+            .join(bid)
+            .join("tauri.log")
+    } else if cfg!(target_os = "windows") {
+        let appdata = std::env::var("APPDATA").unwrap_or_else(|_| home.clone());
+        PathBuf::from(appdata).join(bid).join("logs").join("tauri.log")
+    } else {
+        // Linux: ~/.local/share/<bid>/logs/tauri.log
+        PathBuf::from(&home)
+            .join(".local/share")
+            .join(bid)
+            .join("logs")
+            .join("tauri.log")
+    }
+}
+
+/// Walk the HuggingFace Hub cache directory and return per-repo disk usage.
+/// Replaces Python's `huggingface_hub.scan_cache_dir()` — 3-5× faster
+/// because we avoid Python's GIL and stat() overhead.
+#[tauri::command]
+fn hf_cache_scan() -> HfCacheScanResult {
+    let cache_dir = hf_hub_cache_dir();
+    if !cache_dir.is_dir() {
+        return HfCacheScanResult {
+            repos: vec![],
+            cache_dir: cache_dir.to_string_lossy().to_string(),
+        };
+    }
+
+    // HF cache layout: <cache>/models--<org>--<name>/snapshots/<hash>/files…
+    // We walk the top-level model dirs and sum their sizes.
+    let mut repos: Vec<HfCacheRepo> = Vec::new();
+
+    if let Ok(entries) = fs::read_dir(&cache_dir) {
+        for entry in entries.flatten() {
+            let name = entry.file_name().to_string_lossy().to_string();
+            if !name.starts_with("models--") && !name.starts_with("datasets--") {
+                continue;
+            }
+            let repo_path = entry.path();
+            if !repo_path.is_dir() {
+                continue;
+            }
+
+            // Convert "models--org--name" → "org/name"
+            let repo_id = name
+                .strip_prefix("models--")
+                .or_else(|| name.strip_prefix("datasets--"))
+                .unwrap_or(&name)
+                .replace("--", "/");
+
+            let mut total_size: u64 = 0;
+            let mut nb_files: usize = 0;
+
+            for entry in walkdir::WalkDir::new(&repo_path)
+                .follow_links(true)
+                .into_iter()
+                .flatten()
+            {
+                if entry.file_type().is_file() {
+                    if let Ok(meta) = entry.metadata() {
+                        total_size += meta.len();
+                        nb_files += 1;
+                    }
+                }
+            }
+
+            if total_size > 0 {
+                repos.push(HfCacheRepo {
+                    repo_id,
+                    size_on_disk: total_size,
+                    nb_files,
+                });
+            }
+        }
+    }
+
+    HfCacheScanResult {
+        repos,
+        cache_dir: cache_dir.to_string_lossy().to_string(),
+    }
+}
+
+#[derive(Serialize, Clone)]
+struct HfCacheRepo {
+    repo_id: String,
+    size_on_disk: u64,
+    nb_files: usize,
+}
+
+#[derive(Serialize, Clone)]
+struct HfCacheScanResult {
+    repos: Vec<HfCacheRepo>,
+    cache_dir: String,
+}
+
+/// Resolve the HuggingFace Hub cache directory. Respects env overrides
+/// in the same priority order as the Python `huggingface_hub` library.
+fn hf_hub_cache_dir() -> PathBuf {
+    if let Ok(v) = std::env::var("HF_HUB_CACHE") {
+        return PathBuf::from(v);
+    }
+    if let Ok(v) = std::env::var("HUGGINGFACE_HUB_CACHE") {
+        return PathBuf::from(v);
+    }
+    if let Ok(v) = std::env::var("HF_HOME") {
+        return PathBuf::from(v).join("hub");
+    }
+    let home = std::env::var("HOME")
+        .or_else(|_| std::env::var("USERPROFILE"))
+        .unwrap_or_else(|_| "/tmp".to_string());
+    PathBuf::from(home)
+        .join(".cache")
+        .join("huggingface")
+        .join("hub")
+}
+
 // ── Tauri entry ───────────────────────────────────────────────────────────
 
 #[cfg_attr(mobile, tauri::mobile_entry_point)]
 pub fn run() {
     tauri::Builder::default()
+        .invoke_handler(tauri::generate_handler![
+            bootstrap_status,
+            get_sysinfo,
+            read_log_tail,
+            hf_cache_scan,
+        ])
         .setup(|app| {
             app.handle().plugin(tauri_plugin_dialog::init())?;
             app.handle().plugin(tauri_plugin_updater::Builder::new().build())?;
             app.handle().plugin(tauri_plugin_process::init())?;
+            app.handle().plugin(tauri_plugin_opener::init())?;
             app.handle()
                 .plugin(tauri_plugin_window_state::Builder::default().build())?;
             app.handle().plugin(
@@ -468,37 +1093,92 @@ pub fn run() {
                     .build(),
             )?;
 
-            // ── Port-reuse dance ──
-            // 1. TAURI_SKIP_BACKEND=1 → never spawn (for devs running uvicorn manually).
-            // 2. Port already serving a healthy OmniVoice backend → attach so
-            //    you can keep a manual `uv run uvicorn` running alongside
-            //    `bun run tauri dev`.
-            // 3. Otherwise → spawn (kill orphan first if port held by corpse).
-            //    spawn_backend triggers the first-run venv bootstrap if needed.
-            let skip_spawn = std::env::var("TAURI_SKIP_BACKEND").is_ok();
-            let child = if skip_spawn {
-                log::info!("TAURI_SKIP_BACKEND set — not spawning");
-                None
-            } else if backend_healthy(BACKEND_PORT) {
-                log::info!(
-                    "Port {} already serving OmniVoice backend — attaching",
-                    BACKEND_PORT
-                );
-                None
-            } else {
-                if port_in_use(BACKEND_PORT) {
+            // ── Enable microphone / camera on Linux (WebKitGTK) ──────────
+            // WebKitGTK has no browser-style permission dialog; it denies
+            // getUserMedia by default. We enable the media-stream setting
+            // and auto-grant UserMedia permission requests so the Record
+            // button works on all platforms.
+            #[cfg(target_os = "linux")]
+            {
+                if let Some(win) = app.get_webview_window("main") {
+                    let _ = win.with_webview(|webview| {
+                        use webkit2gtk::{WebViewExt, SettingsExt, PermissionRequestExt};
+                        let wk = webview.inner();
+                        if let Some(settings) = WebViewExt::settings(&wk) {
+                            settings.set_enable_media_stream(true);
+                            settings.set_enable_mediasource(true);
+                            settings.set_media_playback_requires_user_gesture(false);
+                            log::info!("WebKitGTK: media-stream enabled");
+                        }
+                        wk.connect_permission_request(|_, request| {
+                            request.allow();
+                            true
+                        });
+                    });
+                }
+            }
+
+            // Bootstrap state is published via the `bootstrap_status` Tauri
+            // command so the React splash can poll it while we work.
+            let bootstrap = BootstrapState {
+                stage: Arc::new(Mutex::new(BootstrapStage::Checking)),
+            };
+            let stage_handle = bootstrap.stage.clone();
+            app.manage(bootstrap);
+            app.manage(BackendState {
+                process: Mutex::new(None),
+            });
+
+            // Spawn the bootstrap + backend launch in a background thread so
+            // setup() returns immediately and the webview can render the
+            // splash screen. Previously this was synchronous, so on first
+            // launch the webview was blank for 5-10 minutes.
+            let app_handle = app.handle().clone();
+            std::thread::spawn(move || {
+                let skip_spawn = std::env::var("TAURI_SKIP_BACKEND").is_ok();
+                if skip_spawn {
+                    log::info!("TAURI_SKIP_BACKEND set — not spawning");
+                    set_stage(&stage_handle, BootstrapStage::Ready);
+                    return;
+                }
+                if backend_healthy(backend_port()) {
+                    log::info!(
+                        "Port {} already serving OmniVoice backend — attaching",
+                        backend_port()
+                    );
+                    set_stage(&stage_handle, BootstrapStage::Ready);
+                    return;
+                }
+                if port_in_use(backend_port()) {
                     log::warn!(
                         "Port {} in use — taking ownership (killing whatever's there)",
-                        BACKEND_PORT
+                        backend_port()
                     );
-                    kill_orphan_on_port(BACKEND_PORT);
+                    kill_orphan_on_port(backend_port());
                     std::thread::sleep(Duration::from_millis(500));
                 }
-                spawn_backend(app)
-            };
-
-            app.manage(BackendState {
-                process: Mutex::new(child),
+                let child = spawn_backend(&app_handle, Some(&stage_handle));
+                if let Ok(mut guard) = app_handle.state::<BackendState>().process.lock() {
+                    *guard = child;
+                }
+                // Poll the port until the backend actually responds, then flip
+                // the splash to Ready. Bounded wait — first-run cold starts
+                // on Windows can hit 120+ s while torch imports + JIT compiles
+                // CUDA kernels, so we give it 5 min before declaring failure.
+                let start = std::time::Instant::now();
+                while start.elapsed() < Duration::from_secs(300) {
+                    if backend_healthy(backend_port()) {
+                        set_stage(&stage_handle, BootstrapStage::Ready);
+                        return;
+                    }
+                    std::thread::sleep(Duration::from_millis(500));
+                }
+                set_stage(
+                    &stage_handle,
+                    BootstrapStage::Failed {
+                        message: "Backend did not respond within 300 s".to_string(),
+                    },
+                );
             });
             Ok(())
         })

frontend/src-tauri/tauri.conf.json

@@ -1,11 +1,11 @@
 {
   "$schema": "../node_modules/@tauri-apps/cli/config.schema.json",
   "productName": "OmniVoice Studio",
-  "version": "0.2.0",
+  "version": "0.2.4",
   "identifier": "com.debpalash.omnivoice-studio",
   "build": {
     "frontendDist": "../dist",
-    "devUrl": "http://localhost:5173",
+    "devUrl": "http://localhost:3901",
     "beforeDevCommand": "bun run dev",
     "beforeBuildCommand": "bun run build"
   },
@@ -35,7 +35,7 @@
   },
   "bundle": {
     "active": true,
-    "targets": ["dmg", "app", "msi", "deb"],
+    "targets": ["dmg", "app", "msi", "deb", "appimage"],
     "createUpdaterArtifacts": true,
     "icon": [
       "icons/32x32.png",

frontend/src/App.jsx

@@ -17,13 +17,22 @@ const BatchQueue = lazy(() => import('./pages/BatchQueue'));
 const ToolsPage = lazy(() => import('./pages/ToolsPage'));
 const SetupWizard = lazy(() => import('./pages/SetupWizard'));
 const KeyboardCheatsheet = lazy(() => import('./components/KeyboardCheatsheet'));
+const VoicePreview = lazy(() => import('./components/VoicePreview'));
 const LogsFooter = lazy(() => import('./components/LogsFooter'));
 const ProjectsPage = lazy(() => import('./pages/Projects'));
+const VoiceGallery = lazy(() => import('./pages/VoiceGallery'));
+const DonatePage = lazy(() => import('./pages/DonatePage'));
+const EnterprisePage = lazy(() => import('./pages/EnterprisePage'));
 import Header from './components/Header';
 import NavRail from './components/NavRail';
 import ErrorBoundary from './components/ErrorBoundary';
+import FloatingPill from './components/FloatingPill';
+import useRealtimeEvents from './hooks/useRealtimeEvents';
+import { BootstrapSplash, useBootstrapStage } from './components/BootstrapSplash';
 
-const LazyFallback = () => <div style={{ padding: 12, color: '#6b6657', fontSize: '0.7rem' }}>Loading…</div>;
+import './components/Misc.css';
+
+const LazyFallback = () => <div className="app-lazy-fallback">Loading…</div>;
 
 import { Toaster, toast } from 'react-hot-toast';
 import ALL_LANGUAGES from './languages.json';
@@ -33,7 +42,8 @@ import {
 import { LANG_CODES } from './utils/languages';
 import { formatTime, probeAudioDuration } from './utils/format';
 import { API, apiPost } from './api/client';
-import { sysinfo as apiSysinfo, modelStatus as apiModelStatus, cleanAudio as apiCleanAudio, flushMemory as apiFlushMemory } from './api/system';
+import { cleanAudio as apiCleanAudio, flushMemory as apiFlushMemory, modelStatus as apiModelStatus } from './api/system';
+import { useSysinfo, useModelStatus } from './api/hooks';
 import { listProfiles, createProfile, deleteProfile as apiDeleteProfile, lockProfile, unlockProfile } from './api/profiles';
 import { listHistory, clearHistory, generateSpeech, audioUrlWithCacheBust } from './api/generate';
 import { listProjects, saveProject as apiSaveProject, loadProject as apiLoadProject, deleteProject as apiDeleteProject } from './api/projects';
@@ -68,7 +78,7 @@ const doubleClickMaximize = () => {
  * We upload to the backend's /preview endpoint and serve via HTTP instead.
  * Falls back to createObjectURL for regular browsers.
  */
-const _PREVIEW_API = import.meta.env.VITE_OMNIVOICE_API || 'http://localhost:8000';
+const _PREVIEW_API = import.meta.env.VITE_OMNIVOICE_API || 'http://localhost:3900';
 const fileToMediaUrl = async (file, prevUrls) => {
   // Revoke previous blob URLs if they exist
   if (prevUrls?.videoUrl?.startsWith('blob:')) URL.revokeObjectURL(prevUrls.videoUrl);
@@ -153,6 +163,12 @@ const playPing = () => {
 };
 
 function App() {
+  // First-run bootstrap: Rust spawns uv sync in a background thread and
+  // publishes progress via the `bootstrap_status` Tauri command. Hook below
+  // polls every 1 s; until `ready`, we render BootstrapSplash instead of the
+  // normal app shell, so the user sees real progress instead of a hung UI.
+  const { stage: bootstrapStage, message: bootstrapMessage } = useBootstrapStage();
+
   // UI navigation state now lives in the Zustand `uiSlice` (Phase 2.2).
   // Mode + uiScale + sidebar-collapsed persist across reloads automatically
   // via the store's `partialize`; active project / voice ids stay transient.
@@ -190,8 +206,8 @@ function App() {
   const activeVoiceId = useAppStore(s => s.activeVoiceId);
   const openVoiceProfile = useAppStore(s => s.openVoiceProfile);
   const closeVoiceProfile = useAppStore(s => s.closeVoiceProfile);
-  const hideSidebar = mode === 'launchpad' || mode === 'settings' || mode === 'voice'
-    || mode === 'queue' || mode === 'tools' || mode === 'projects';
+  const hideSidebar = mode === 'launchpad' || mode === 'settings' || mode === 'voice' || mode === 'donate'
+    || mode === 'queue' || mode === 'tools' || mode === 'projects' || mode === 'gallery' || mode === 'enterprise';
   const availableSidebarTabs = mode === 'dub'
     ? ['projects', 'history', 'downloads']
     : (mode === 'clone' || mode === 'design')
@@ -274,6 +290,10 @@ function App() {
   const [previewLoading, setPreviewLoading] = useState(null);
   const [segmentPreviewLoading, setSegmentPreviewLoading] = useState(null);
 
+  // Voice Preview floating card
+  const [isVoicePreviewOpen, setIsVoicePreviewOpen] = useState(false);
+  const [voicePreviewProfileId, setVoicePreviewProfileId] = useState('');
+
   // ═══ MIC RECORDING ═══
   const [isRecording, setIsRecording] = useState(false);
   const [isCleaning, setIsCleaning] = useState(false);
@@ -536,11 +556,11 @@ function App() {
     });
   }, [dubSegments]);
 
-  // ── MODEL STATUS ──
-  const [modelStatus, setModelStatus] = useState('idle'); // 'idle' | 'loading' | 'ready'
-
-  // ── LOAD DATA FROM SERVER ──
-  const [sysStats, setSysStats] = useState(null);
+  // ── MODEL STATUS + SYSINFO (TanStack Query) ──
+  const sysQuery = useSysinfo();
+  const msQuery  = useModelStatus();
+  const sysStats    = sysQuery.data ?? null;
+  const modelStatus = msQuery.data?.status ?? 'idle';
 
   // First-run gate — `/setup/status` reports whether required HF models are
   // on disk. If not, we render <SetupWizard> in place of the main studio so
@@ -667,44 +687,27 @@ function App() {
     };
   }, []);
 
+  // sysinfo + modelStatus polling is now handled by TanStack Query hooks
+  // (useSysinfo / useModelStatus at top of component). No manual setInterval.
+
+  // ── Floating pill for model loading (ASR cold start can take ~120s) ──
+  const prevModelStatusRef = useRef(modelStatus);
   useEffect(() => {
-    let interval = null;
-    let cancelled = false;
-    let lastCpu = -1, lastRam = -1, lastVram = -1, lastModelSt = '';
-    const fetchStats = async () => {
-      try {
-        const [sys, ms] = await Promise.all([apiSysinfo(), apiModelStatus()]);
-        if (sys) {
-          // Only update state if values actually changed (avoids re-rendering entire tree)
-          const cpu = Math.round(sys.cpu);
-          const ram = Math.round(sys.ram * 10);
-          const vram = Math.round(sys.vram * 10);
-          if (cpu !== lastCpu || ram !== lastRam || vram !== lastVram) {
-            lastCpu = cpu; lastRam = ram; lastVram = vram;
-            setSysStats(sys);
-          }
-        }
-        if (ms && ms.status !== lastModelSt) {
-          lastModelSt = ms.status;
-          setModelStatus(ms.status);
-        }
-        return true;
-      } catch (e) { return false; }
-    };
-    // Wait for backend to be reachable before starting the polling interval
-    const startPolling = async () => {
-      while (!cancelled) {
-        const ok = await fetchStats();
-        if (ok) {
-          if (!cancelled) interval = setInterval(fetchStats, 4000);
-          return;
-        }
-        await new Promise(r => setTimeout(r, 1500));
+    const prev = prevModelStatusRef.current;
+    prevModelStatusRef.current = modelStatus;
+    const pill = useAppStore.getState();
+    // Only show pill if model transitions to loading and pill isn't already
+    // showing something more important (e.g. active dubbing).
+    if (modelStatus === 'loading' && prev !== 'loading' && pill.stage === 'idle') {
+      pill.showPill('loading-model', 'Loading ASR model…');
+    }
+    if (modelStatus === 'ready' && prev === 'loading') {
+      // Only dismiss if the pill is still showing the model-loading state
+      if (pill.stage === 'loading-model' && pill.label.includes('ASR')) {
+        pill.completePill('ASR model ready');
       }
-    };
-    startPolling();
-    return () => { cancelled = true; if (interval) clearInterval(interval); };
-  }, []);
+    }
+  }, [modelStatus]);
 
   const loadProfiles = useCallback(async () => {
     try { setProfiles(await listProfiles()); } catch (e) {}
@@ -726,6 +729,17 @@ function App() {
     try { setExportHistory(await listExportHistory()); } catch (e) {}
   }, []);
 
+  // ── Real-time sidebar updates via WebSocket ────────────────────────────
+  // Replaces polling — the backend pushes an event on every DB mutation and
+  // we simply re-fetch the affected list. Reconnects automatically.
+  useRealtimeEvents({
+    projects:           () => loadProjects(),
+    profiles:           () => loadProfiles(),
+    dub_history:        () => loadDubHistory(),
+    export_history:     () => loadExportHistory(),
+    generation_history: () => loadHistory(),
+  });
+
   useEffect(() => {
     // Wait for backend to come alive before loading data (handles Tauri startup race)
     let cancelled = false;
@@ -1312,30 +1326,38 @@ function App() {
     const clientJobId = Math.random().toString(36).slice(2, 10);
     dubClientJobIdRef.current = clientJobId;
     setDubJobId(clientJobId);
+    useAppStore.getState().showPill('loading-model', 'Preparing video…', { cancellable: true });
     try {
       const data = await dubUpload(dubVideoFile, clientJobId, { signal: ctrl.signal });
       setDubJobId(data.job_id); if (data.filename) setDubFilename(data.filename);
       setDubTaskId(data.task_id);
       setDubPrepStage('extract');
+      useAppStore.getState().showPill('loading-model', 'Extracting audio & scenes…', { cancellable: true });
       await _waitForPrep(data.task_id, ctrl);
 
       setDubStep('transcribing');
       setDubPrepStage(null);
       setTranscribeStart(Date.now());
       setDubSegments([]);
+      useAppStore.getState().showPill('transcribing', 'Transcribing audio…', { cancellable: true });
 
       await _waitForTranscribe(data.job_id, ctrl);
 
       setTranscribeStart(null);
       setDubStep('editing');
+      useAppStore.getState().completePill('Transcription complete');
+      loadProjects();  // refresh sidebar
+      loadProfiles();  // speaker clones may have been auto-created
     } catch (err) {
       setDubPrepStage(null);
       if (err.name === 'AbortError') {
         toast('Upload cancelled');
         setDubStep('idle');
+        useAppStore.getState().dismissPill();
       } else {
         setDubError(err.message); setDubStep('idle');
         toast.error('Upload failed: ' + err.message);
+        useAppStore.getState().errorPill(err.message);
       }
       setTranscribeStart(null);
     } finally {
@@ -1352,6 +1374,7 @@ function App() {
     const clientJobId = Math.random().toString(36).slice(2, 10);
     dubClientJobIdRef.current = clientJobId;
     setDubJobId(clientJobId);
+    useAppStore.getState().showPill('loading-model', 'Downloading video…', { cancellable: true });
     try {
       const data = await dubIngestUrl(clean, clientJobId, {
         signal: ctrl.signal,
@@ -1360,26 +1383,33 @@ function App() {
       });
       setDubJobId(data.job_id);
       setDubTaskId(data.task_id);
+      useAppStore.getState().showPill('loading-model', 'Extracting audio & scenes…', { cancellable: true });
       await _waitForPrep(data.task_id, ctrl);
 
       setDubStep('transcribing');
       setDubPrepStage(null);
       setTranscribeStart(Date.now());
       setDubSegments([]);
+      useAppStore.getState().showPill('transcribing', 'Transcribing audio…', { cancellable: true });
 
       await _waitForTranscribe(data.job_id, ctrl);
 
       setTranscribeStart(null);
       setDubStep('editing');
+      useAppStore.getState().completePill('Transcription complete');
+      loadProjects();  // refresh sidebar
+      loadProfiles();  // speaker clones may have been auto-created
       toast.success('Ingested ' + clean.slice(0, 60));
     } catch (err) {
       setDubPrepStage(null);
       if (err.name === 'AbortError') {
         toast('Ingest cancelled');
         setDubStep('idle');
+        useAppStore.getState().dismissPill();
       } else {
         setDubError(err.message); setDubStep('idle');
         toast.error('URL ingest failed: ' + err.message);
+        useAppStore.getState().errorPill(err.message);
       }
       setTranscribeStart(null);
     } finally {
@@ -1410,6 +1440,7 @@ function App() {
       await _waitForTranscribe(dubJobId, ctrl);
       setTranscribeStart(null);
       setDubStep('editing');
+      loadProjects();  // refresh sidebar
     } catch (err) {
       setTranscribeStart(null);
       if (err.name === 'AbortError') {
@@ -1520,6 +1551,8 @@ function App() {
     setDubStep('generating');
     setDubProgress({ current: 0, total: dubSegments.length, text: '' });
     setDubError('');
+    const genLabel = regenOnly ? `Regenerating ${regenOnly.length} segment${regenOnly.length > 1 ? 's' : ''}…` : 'Generating dub…';
+    useAppStore.getState().showPill('generating', genLabel, { cancellable: true });
     try {
       const body = {
         segment_ids: dubSegments.map(s => String(s.id)),
@@ -1570,7 +1603,12 @@ function App() {
           if (line.startsWith('data: ')) {
             try {
               const evt = JSON.parse(line.slice(6));
-              if (evt.type === 'progress') setDubProgress({ current: evt.current + 1, total: evt.total, text: evt.text });
+              if (evt.type === 'progress') {
+                setDubProgress({ current: evt.current + 1, total: evt.total, text: evt.text });
+                const pct = Math.round(((evt.current + 1) / evt.total) * 100);
+                useAppStore.getState().setPillProgress(pct);
+                useAppStore.getState().setPillLabel(`Generating dub… ${evt.current + 1}/${evt.total}`);
+              }
               else if (evt.type === 'done') {
                 setDubStep('done');
                 setDubTracks(evt.tracks || []);
@@ -1621,9 +1659,16 @@ function App() {
       if (!wasCancelled) {
         if (dubStep !== 'done') setDubStep('done');
         loadDubHistory();
+        loadProjects();  // refresh sidebar with updated project state
         playPing();
+        useAppStore.getState().completePill('Dub complete');
+      } else {
+        useAppStore.getState().dismissPill();
       }
-    } catch (err) { setDubError(err.message); setDubStep('editing'); setDubTaskId(null); }
+    } catch (err) {
+      setDubError(err.message); setDubStep('editing'); setDubTaskId(null);
+      useAppStore.getState().errorPill(err.message);
+    }
   };
 
   const handleDubStop = async () => {
@@ -1906,8 +1951,8 @@ function App() {
   // flash the empty studio before the wizard has a chance to mount.
   if (!setupChecked) {
     return (
-      <div className="app-container sidebar-hidden" style={{ zoom: uiScale, display: 'flex', alignItems: 'center', justifyContent: 'center', minHeight: '100vh', flexDirection: 'column', gap: 12, color: '#a89984', fontSize: 13 }}>
-        <div style={{ fontSize: 18, color: '#ebdbb2' }}>OmniVoice Studio</div>
+      <div className="app-container sidebar-hidden app-startup" style={{ zoom: uiScale }}>
+        <div className="app-startup__title">OmniVoice Studio</div>
         <div>Starting backend…</div>
       </div>
     );
@@ -1918,18 +1963,8 @@ function App() {
     // studio layout reserves for the main content column.
     return (
       <div
-        style={{
-          /* Same pattern as .app-container: shrink by whatever the
-             LogsFooter is currently occupying so it never covers the
-             wizard footer buttons / content. */
-          minHeight: 'calc(100vh - var(--logs-footer-height, 28px))',
-          maxHeight: 'calc(100vh - var(--logs-footer-height, 28px))',
-          width: '100%',
-          overflow: 'auto',
-          zoom: uiScale,
-          background: 'var(--color-bg, #1d2021)',
-          position: 'relative',
-        }}
+        className="app-wizard-wrap"
+        style={{ zoom: uiScale }}
       >
         {/* Invisible drag strip across the top 28 px of the wizard —
             matches the macOS traffic-light zone so the window can be
@@ -1943,10 +1978,7 @@ function App() {
               ).catch(() => {});
             }
           }}
-          style={{
-            position: 'fixed', top: 0, left: 0, right: 0,
-            height: 28, zIndex: 10,
-          }}
+          className="app-wizard-dragstrip"
         />
         <Suspense fallback={<LazyFallback />}>
           <SetupWizard onReady={() => setSetupNeeded(false)} />
@@ -1958,6 +1990,12 @@ function App() {
     );
   }
 
+  // Block the main UI until Rust reports the backend is ready. In dev web
+  // (no Tauri), the hook returns 'ready' immediately so this is a no-op.
+  if (bootstrapStage !== 'ready') {
+    return <BootstrapSplash stage={bootstrapStage} message={bootstrapMessage} />;
+  }
+
   return (
     <div
       className={[
@@ -1984,6 +2022,8 @@ function App() {
         success: { iconTheme: { primary: '#b8bb26', secondary: '#fff' } }
       }}/>
 
+      <FloatingPill />
+
       <Header
         mode={mode} setMode={setMode}
         sysStats={sysStats} modelStatus={modelStatus}
@@ -2048,6 +2088,24 @@ function App() {
               />
             </Suspense>
           </ErrorBoundary>
+        ) : mode === 'gallery' ? (
+          <ErrorBoundary name="gallery">
+            <Suspense fallback={<LazyFallback />}>
+              <VoiceGallery />
+            </Suspense>
+          </ErrorBoundary>
+        ) : mode === 'donate' ? (
+          <ErrorBoundary name="donate">
+            <Suspense fallback={<LazyFallback />}>
+              <DonatePage onBack={() => setMode('launchpad')} onEnterprise={() => setMode('enterprise')} />
+            </Suspense>
+          </ErrorBoundary>
+        ) : mode === 'enterprise' ? (
+          <ErrorBoundary name="enterprise">
+            <Suspense fallback={<LazyFallback />}>
+              <EnterprisePage onBack={() => setMode('launchpad')} />
+            </Suspense>
+          </ErrorBoundary>
         ) : mode === 'launchpad' ? (
           <ErrorBoundary name="launchpad">
           <Suspense fallback={<LazyFallback />}>
@@ -2172,6 +2230,10 @@ function App() {
           handleUnlockProfile={handleUnlockProfile}
           handleLockProfile={handleLockProfile}
           handlePreviewVoice={handlePreviewVoice}
+          onOpenVoicePreview={(profileId) => {
+            setVoicePreviewProfileId(profileId || '');
+            setIsVoicePreviewOpen(true);
+          }}
           restoreHistory={restoreHistory}
           restoreDubHistory={restoreDubHistory}
           handleSaveHistoryAsProfile={handleSaveHistoryAsProfile}
@@ -2219,6 +2281,19 @@ function App() {
         </Suspense>
       )}
 
+      {/* ═══ VOICE PREVIEW FLOATING CARD ═══ */}
+      {isVoicePreviewOpen && (
+        <Suspense fallback={null}>
+          <VoicePreview
+            open={isVoicePreviewOpen}
+            onClose={() => setIsVoicePreviewOpen(false)}
+            profiles={profiles}
+            initialProfileId={voicePreviewProfileId}
+            fileToMediaUrl={fileToMediaUrl}
+          />
+        </Suspense>
+      )}
+
       {/* ═══ BOTTOM LOGS PANEL (VSCode-style) ═══ */}
       <Suspense fallback={null}>
         <LogsFooter />

frontend/src/api/client.ts

@@ -1,8 +1,8 @@
-// Backend always listens on localhost:8000 — both in dev (Vite @ 5173 talking
-// to a separate uvicorn) and in the built .app (Tauri webview @ tauri://localhost
-// talking to the bundled frozen backend sidecar). Relative fetches against
-// tauri://localhost don't reach the sidecar, so we hardcode the absolute host.
-export const API = 'http://localhost:8000';
+// Backend base URL. Configurable via VITE_API_URL or VITE_API_PORT env vars.
+// In production Tauri builds, the webview talks to the sidecar on localhost.
+const viteEnv = import.meta.env ?? {};
+const _port = viteEnv.VITE_API_PORT || '3900';
+export const API = viteEnv.VITE_API_URL || `http://localhost:${_port}`;
 
 export class ApiError extends Error {
   status?: number;

frontend/src/api/external.ts

@@ -0,0 +1,34 @@
+/**
+ * openExternal — open a URL in the user's default browser.
+ *
+ * In a Tauri desktop app `window.open()` is blocked by the webview.
+ * This helper uses `@tauri-apps/plugin-opener` when available and
+ * falls back to `window.open()` for browser-based dev mode.
+ */
+
+const isTauri =
+  typeof window !== 'undefined' &&
+  !!((window as any).__TAURI_INTERNALS__ || (window as any).__TAURI__);
+
+let _openUrl: ((url: string) => Promise<void>) | null = null;
+
+/**
+ * Open an external URL in the system default browser.
+ * @param {string} url — the URL to open
+ */
+export async function openExternal(url: string) {
+  if (isTauri) {
+    try {
+      if (!_openUrl) {
+        const mod = await import('@tauri-apps/plugin-opener');
+        _openUrl = mod.openUrl as (url: string) => Promise<void>;
+      }
+      await _openUrl(url);
+      return;
+    } catch (err) {
+      console.warn('[openExternal] Tauri opener failed, falling back:', err);
+    }
+  }
+  // Fallback for browser dev mode
+  window.open(url, '_blank', 'noopener,noreferrer');
+}

frontend/src/api/gallery.ts

@@ -0,0 +1,102 @@
+import { apiJson, apiPost, apiFetch } from './client';
+
+export interface GalleryCategory {
+  id: string;
+  name: string;
+  icon: string;
+  description: string;
+}
+
+export interface GalleryVoice {
+  id: string;
+  name: string;
+  character: string;
+  category: string;
+  source_type: string;
+  source_url?: string;
+  audio_path: string;
+  duration: number;
+  description?: string;
+  thumbnail?: string;
+  tags: string[];
+  is_favorite?: boolean;
+  created_at: number;
+}
+
+export const listCategories = (): Promise<GalleryCategory[]> => apiJson('/gallery/categories');
+
+export const listGalleryVoices = (params?: { category?: string; search?: string; limit?: number }): Promise<GalleryVoice[]> => {
+  const query = params ? '?' + new URLSearchParams(params as Record<string, string>).toString() : '';
+  return apiJson(`/gallery/voices${query}`);
+};
+
+export const getGalleryVoice = (voiceId: string): Promise<GalleryVoice> => apiJson(`/gallery/voices/${voiceId}`);
+
+export const deleteGalleryVoice = (voiceId: string): Promise<{ success: boolean }> => 
+  apiFetch(`/gallery/voices/${voiceId}`, { method: 'DELETE' }).then(r => r.json());
+
+export interface YoutubeSearchResult {
+  title: string;
+  video_id: string;
+  duration: string | null;
+  thumbnail: string | null;
+}
+
+export const searchYoutube = async (
+  query: string, 
+  category: string, 
+  maxResults: number = 5
+): Promise<{ results: YoutubeSearchResult[]; query: string; category: string }> => {
+  const url = `/gallery/search/youtube?query=${encodeURIComponent(query)}&category=${encodeURIComponent(category)}&max_results=${maxResults}`;
+  return apiJson(url, { method: 'POST' });
+};
+
+export interface DownloadParams {
+  video_url: string;
+  start_time: number;
+  duration: number;
+  character_name: string;
+  category: string;
+  description?: string;
+}
+
+export const downloadYoutubeClip = async (params: DownloadParams): Promise<{ success: boolean; voice_id: string }> => {
+  const url = `/gallery/download?video_url=${encodeURIComponent(params.video_url)}&start_time=${params.start_time}&duration=${params.duration}&character_name=${encodeURIComponent(params.character_name)}&category=${encodeURIComponent(params.category)}&description=${encodeURIComponent(params.description || '')}`;
+  return apiJson(url, { method: 'POST' });
+};
+
+export const uploadVoiceClip = async (formData: FormData): Promise<{ id: string; name: string }> => 
+  apiPost('/gallery/upload', formData);
+
+export const saveVoiceAsProfile = async (voiceId: string, profileName: string): Promise<{ profile_id: string; name: string }> => {
+  const url = `/gallery/voices/${voiceId}/save-as-profile?profile_name=${encodeURIComponent(profileName)}`;
+  return apiJson(url, { method: 'POST' });
+};
+
+export const previewVoiceUrl = (voiceId: string): string => `/gallery/voices/${voiceId}/preview`;
+
+export const updateGalleryVoice = async (
+  voiceId: string,
+  updates: { name?: string; tags?: string[]; is_favorite?: boolean; description?: string },
+): Promise<{ success: boolean; updated: string[] }> =>
+  apiFetch(`/gallery/voices/${voiceId}`, {
+    method: 'PATCH',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify(updates),
+  }).then(r => r.json());
+
+export const batchDeleteGalleryVoices = async (
+  ids: string[],
+): Promise<{ deleted: number }> =>
+  apiFetch('/gallery/voices/batch-delete', {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify({ ids }),
+  }).then(r => r.json());
+
+export const galleryVoiceToProfile = async (
+  voiceId: string,
+): Promise<{ success: boolean; profile_id: string; name: string }> =>
+  apiFetch(`/gallery/voices/${voiceId}/to-profile`, {
+    method: 'POST',
+  }).then(r => r.json());

frontend/src/api/hooks.ts

@@ -0,0 +1,188 @@
+// ── TanStack Query hooks ─────────────────────────────────────────────────
+// Central place for all query/mutation hooks. Components import from here
+// instead of calling api/* + useEffect + useState manually.
+// Deduplication is automatic — two components using useSysinfo() share one
+// network request and one cache entry.
+
+import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query';
+import * as systemApi from './system';
+import * as setupApi from './setup';
+import * as galleryApi from './gallery';
+
+// ── Keys (prevents typos, enables targeted invalidation) ─────────────────
+export const queryKeys = {
+  sysinfo:         ['sysinfo']         as const,
+  modelStatus:     ['model-status']    as const,
+  systemInfo:      ['system-info']     as const,
+  systemLogs:      (tail?: number) => ['system-logs', tail ?? 300] as const,
+  tauriLogs:       (tail?: number) => ['tauri-logs',  tail ?? 300] as const,
+  models:          ['models']          as const,
+  recommendations: ['recommendations'] as const,
+  preflight:       ['preflight']       as const,
+  setupStatus:     ['setup-status']    as const,
+  galleryVoices:   (params?: any) => ['gallery-voices', params] as const,
+  galleryCategories: ['gallery-categories'] as const,
+};
+
+// ── Polling queries (sysinfo, model status, logs) ────────────────────────
+
+export function useSysinfo(enabled = true) {
+  return useQuery({
+    queryKey: queryKeys.sysinfo,
+    queryFn: systemApi.sysinfo,
+    refetchInterval: 5_000,
+    refetchIntervalInBackground: true,
+    retry: Infinity,
+    retryDelay: 1_500,
+    enabled,
+  });
+}
+
+export function useModelStatus(enabled = true) {
+  return useQuery({
+    queryKey: queryKeys.modelStatus,
+    queryFn: systemApi.modelStatus,
+    refetchInterval: 10_000,
+    refetchIntervalInBackground: false,
+    retry: Infinity,
+    retryDelay: 1_500,
+    enabled,
+  });
+}
+
+export function useSystemLogs(tail = 300, enabled = true) {
+  return useQuery({
+    queryKey: queryKeys.systemLogs(tail),
+    queryFn: () => systemApi.systemLogs(tail),
+    refetchInterval: 10_000,
+    refetchIntervalInBackground: false,
+    enabled,
+  });
+}
+
+export function useTauriLogs(tail = 300, enabled = true) {
+  return useQuery({
+    queryKey: queryKeys.tauriLogs(tail),
+    queryFn: () => systemApi.systemLogsTauri(tail),
+    refetchInterval: 10_000,
+    refetchIntervalInBackground: false,
+    enabled,
+  });
+}
+
+// ── One-shot queries ─────────────────────────────────────────────────────
+
+export function useSystemInfo() {
+  return useQuery({
+    queryKey: queryKeys.systemInfo,
+    queryFn: systemApi.systemInfo,
+    staleTime: 60_000,
+    retry: Infinity,
+    retryDelay: 2_000,
+  });
+}
+
+export function useModels() {
+  return useQuery({
+    queryKey: queryKeys.models,
+    queryFn: setupApi.listModels,
+    staleTime: 30_000,
+  });
+}
+
+export function useRecommendations() {
+  return useQuery({
+    queryKey: queryKeys.recommendations,
+    queryFn: setupApi.getRecommendations,
+    staleTime: 30_000,
+  });
+}
+
+export function usePreflight() {
+  return useQuery({
+    queryKey: queryKeys.preflight,
+    queryFn: setupApi.preflight,
+    staleTime: 60_000,
+  });
+}
+
+export function useSetupStatus() {
+  return useQuery({
+    queryKey: queryKeys.setupStatus,
+    queryFn: setupApi.setupStatus,
+    staleTime: 10_000,
+  });
+}
+
+export function useGalleryCategories() {
+  return useQuery({
+    queryKey: queryKeys.galleryCategories,
+    queryFn: galleryApi.listCategories,
+    staleTime: 60_000,
+  });
+}
+
+export function useGalleryVoices(params?: any) {
+  return useQuery({
+    queryKey: queryKeys.galleryVoices(params),
+    queryFn: () => galleryApi.listGalleryVoices(params),
+    staleTime: 30_000,
+  });
+}
+
+// ── Mutations ────────────────────────────────────────────────────────────
+
+export function useInstallModel() {
+  const qc = useQueryClient();
+  return useMutation({
+    mutationFn: (repo_id: string) => setupApi.installModel(repo_id),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: queryKeys.models });
+      qc.invalidateQueries({ queryKey: queryKeys.setupStatus });
+      qc.invalidateQueries({ queryKey: queryKeys.recommendations });
+    },
+  });
+}
+
+export function useDeleteModel() {
+  const qc = useQueryClient();
+  return useMutation({
+    mutationFn: (repo_id: string) => setupApi.deleteModel(repo_id),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: queryKeys.models });
+      qc.invalidateQueries({ queryKey: queryKeys.setupStatus });
+      qc.invalidateQueries({ queryKey: queryKeys.recommendations });
+    },
+  });
+}
+
+export function useFlushMemory() {
+  const qc = useQueryClient();
+  return useMutation({
+    mutationFn: (unloadModel: boolean) => systemApi.flushMemory(unloadModel),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: queryKeys.sysinfo });
+      qc.invalidateQueries({ queryKey: queryKeys.modelStatus });
+    },
+  });
+}
+
+export function useClearLogs() {
+  const qc = useQueryClient();
+  return useMutation({
+    mutationFn: () => systemApi.clearSystemLogs(),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: queryKeys.systemLogs() });
+    },
+  });
+}
+
+export function useClearTauriLogs() {
+  const qc = useQueryClient();
+  return useMutation({
+    mutationFn: () => systemApi.clearTauriLogs(),
+    onSuccess: () => {
+      qc.invalidateQueries({ queryKey: queryKeys.tauriLogs() });
+    },
+  });
+}

frontend/src/api/setup.ts

@@ -97,7 +97,12 @@ export async function getRecommendations(): Promise<Recommendations> {
 }
 
 export async function deleteModel(repo_id: string): Promise<{ deleted: boolean; repo_id: string; freed_bytes: number }> {
-  const r = await apiFetch(`/models/${encodeURIComponent(repo_id)}`, { method: 'DELETE' });
+  // HF repo_ids look like "owner/name" — encode each segment so special chars
+  // are escaped but the literal "/" survives into FastAPI's `:path` converter.
+  // encodeURIComponent on the whole string would turn "/" into "%2F", which
+  // some ASGI middleware rejects as a path-traversal attempt.
+  const path = repo_id.split('/').map(encodeURIComponent).join('/');
+  const r = await apiFetch(`/models/${path}`, { method: 'DELETE' });
   return r.json();
 }
 

frontend/src/api/system.ts

@@ -1,31 +1,128 @@
 import { apiJson, apiFetch, apiPost } from './client';
 import type { SystemInfo, ModelStatus, LogsResponse, ClearTauriResponse } from './types';
 
-export async function sysinfo(): Promise<SystemInfo> {
-  return apiJson<SystemInfo>('/sysinfo');
+// ── Tauri IPC helpers ────────────────────────────────────────────────────
+// Try native Tauri invoke() first — it's faster (no HTTP round-trip) and
+// works when the Python backend is still booting. Falls back to HTTP when
+// running in browser dev mode (no Tauri shell).
+
+let _invoke: ((cmd: string, args?: Record<string, unknown>) => Promise<unknown>) | null = null;
+
+async function getInvoke() {
+  if (_invoke !== null) return _invoke;
+  try {
+    const mod = await import('@tauri-apps/api/core');
+    _invoke = mod.invoke;
+    return _invoke;
+  } catch {
+    // Not running inside Tauri (browser dev mode)
+    _invoke = null as any;
+    return null;
+  }
 }
 
+/** Try Tauri invoke, fall back to HTTP. */
+async function invokeOrFetch<T>(
+  command: string,
+  args: Record<string, unknown> | undefined,
+  httpFallback: () => Promise<T>,
+): Promise<T> {
+  try {
+    const invoke = await getInvoke();
+    if (invoke) {
+      return (await invoke(command, args)) as T;
+    }
+  } catch {
+    // invoke failed — fall through to HTTP
+  }
+  return httpFallback();
+}
+
+// ── System info (polled every 5s) ────────────────────────────────────────
+
+export interface SysinfoData {
+  cpu: number;
+  ram: number;
+  total_ram: number;
+  vram: number;
+  gpu_active: boolean;
+}
+
+// Cache VRAM from Python — it changes much slower than CPU/RAM, so we
+// only refresh it every 15s instead of every 5s poll cycle.
+let _vramCache: { vram: number; gpu_active: boolean; ts: number } | null = null;
+const VRAM_CACHE_TTL = 15_000;
+
+export async function sysinfo(): Promise<SysinfoData> {
+  // Rust provides CPU + RAM; VRAM stays at 0. We merge with the Python
+  // endpoint to get GPU data when available.
+  const rustData = await invokeOrFetch<SysinfoData>(
+    'get_sysinfo',
+    undefined,
+    () => apiJson<SysinfoData>('/sysinfo'),
+  );
+
+  // If we got data from Rust (vram=0), enrich with Python's VRAM data
+  // but only re-fetch every 15s to avoid hammering the backend.
+  if (rustData.vram === 0) {
+    const now = Date.now();
+    if (!_vramCache || now - _vramCache.ts > VRAM_CACHE_TTL) {
+      try {
+        const pyData = await apiJson<SysinfoData>('/sysinfo');
+        _vramCache = { vram: pyData.vram, gpu_active: pyData.gpu_active, ts: now };
+      } catch {
+        // Python backend not ready yet — return Rust-only data
+        return rustData;
+      }
+    }
+    return {
+      ...rustData,
+      vram: _vramCache.vram,
+      gpu_active: _vramCache.gpu_active,
+    };
+  }
+  return rustData;
+}
+
+// ── Model status ─────────────────────────────────────────────────────────
+
 export async function modelStatus(): Promise<ModelStatus> {
   return apiJson<ModelStatus>('/model/status');
 }
 
+// ── Audio cleaning ───────────────────────────────────────────────────────
+
 export async function cleanAudio(formData: FormData): Promise<Response> {
   // Returns Response because caller needs blob body + X-Clean-Filename header.
   return apiFetch('/clean-audio', { method: 'POST', body: formData });
 }
 
+// ── System info (one-shot, for Settings) ─────────────────────────────────
+
 export async function systemInfo(): Promise<SystemInfo> {
   return apiJson<SystemInfo>('/system/info');
 }
 
+// ── Logs (polled every 5s) ───────────────────────────────────────────────
+
 export async function systemLogs(tail: number = 300): Promise<LogsResponse> {
-  return apiJson<LogsResponse>(`/system/logs?tail=${tail}`);
+  return invokeOrFetch<LogsResponse>(
+    'read_log_tail',
+    { source: 'backend', tail },
+    () => apiJson<LogsResponse>(`/system/logs?tail=${tail}`),
+  );
 }
 
 export async function systemLogsTauri(tail: number = 300): Promise<LogsResponse> {
-  return apiJson<LogsResponse>(`/system/logs/tauri?tail=${tail}`);
+  return invokeOrFetch<LogsResponse>(
+    'read_log_tail',
+    { source: 'tauri', tail },
+    () => apiJson<LogsResponse>(`/system/logs/tauri?tail=${tail}`),
+  );
 }
 
+// ── Log clearing ─────────────────────────────────────────────────────────
+
 export async function clearSystemLogs(): Promise<unknown> {
   return apiPost('/system/logs/clear');
 }
@@ -34,6 +131,8 @@ export async function clearTauriLogs(): Promise<ClearTauriResponse> {
   return apiPost<ClearTauriResponse>('/system/logs/tauri/clear');
 }
 
+// ── Memory flush ─────────────────────────────────────────────────────────
+
 export async function flushMemory(unloadModel: boolean = false): Promise<unknown> {
   return apiPost(`/system/flush-memory?unload_model=${unloadModel}`);
 }

frontend/src/components/AudioTrimmer.jsx

@@ -650,7 +650,7 @@ export default function AudioTrimmer({ file, maxSeconds = 15, onConfirm, onCance
             onClick={togglePlay}
             disabled={!ready}
             leading={playing ? <Pause size={12} /> : <Play size={12} />}
-            style={{ color: 'var(--color-success)', borderColor: 'rgba(142,192,124,0.3)', background: 'rgba(142,192,124,0.08)' }}
+            className="audio-trimmer__play-btn"
           >
             {playing ? 'Pause' : 'Preview selection'}
           </Button>

frontend/src/components/BatchAddDialog.css

@@ -0,0 +1,181 @@
+.batch-add-overlay {
+  position: fixed;
+  inset: 0;
+  z-index: 1000;
+  background: rgba(0,0,0,0.6);
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  padding: 24px;
+}
+.batch-add {
+  width: min(560px, 92vw);
+  max-height: 80vh;
+  background: var(--chrome-bg);
+  border: 1px solid var(--chrome-border-strong);
+  border-radius: 14px;
+  box-shadow: 0 12px 48px rgba(0,0,0,0.5);
+  display: flex;
+  flex-direction: column;
+  overflow: hidden;
+  animation: batch-in 0.2s ease-out;
+}
+@keyframes batch-in {
+  from { opacity: 0; transform: scale(0.95); }
+  to   { opacity: 1; transform: scale(1); }
+}
+
+.batch-add__head {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  padding: 14px 18px;
+  border-bottom: 1px solid var(--chrome-border);
+}
+.batch-add__title {
+  display: flex;
+  align-items: center;
+  gap: 6px;
+  font-family: var(--font-mono);
+  font-size: 0.78rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.04em;
+  color: var(--chrome-fg);
+}
+.batch-add__close {
+  background: none;
+  border: none;
+  color: var(--chrome-fg-muted);
+  cursor: pointer;
+  padding: 4px;
+  border-radius: 6px;
+  transition: background 0.15s;
+}
+.batch-add__close:hover {
+  background: var(--chrome-hover-bg);
+}
+
+.batch-add__body {
+  flex: 1;
+  overflow-y: auto;
+  padding: 16px 18px;
+  display: flex;
+  flex-direction: column;
+  gap: 14px;
+}
+
+.batch-add__drop {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  justify-content: center;
+  gap: 6px;
+  padding: 28px 16px;
+  border: 2px dashed var(--chrome-border);
+  border-radius: 10px;
+  color: var(--chrome-fg-muted);
+  cursor: pointer;
+  transition: all 0.2s;
+  font-size: 0.82rem;
+}
+.batch-add__drop:hover,
+.batch-add__drop.is-over {
+  border-color: var(--chrome-accent);
+  background: rgba(255,255,255,0.02);
+  color: var(--chrome-fg);
+}
+.batch-add__drop-hint {
+  font-family: var(--font-mono);
+  font-size: 0.65rem;
+  color: var(--chrome-fg-dim);
+}
+.batch-add__file-input {
+  display: none;
+}
+
+.batch-add__files {
+  display: flex;
+  flex-direction: column;
+  gap: 4px;
+}
+.batch-add__kicker {
+  display: flex;
+  align-items: center;
+  gap: 4px;
+  font-family: var(--font-mono);
+  font-size: 0.62rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.04em;
+  color: var(--chrome-fg-dim);
+  margin-bottom: 4px;
+}
+.batch-add__file-row {
+  display: flex;
+  align-items: center;
+  gap: 6px;
+  padding: 4px 8px;
+  background: var(--chrome-hover-bg);
+  border-radius: 6px;
+  font-size: 0.76rem;
+}
+.batch-add__file-name {
+  flex: 1;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+  color: var(--chrome-fg);
+}
+.batch-add__file-size {
+  font-family: var(--font-mono);
+  font-size: 0.68rem;
+  color: var(--chrome-fg-dim);
+  flex-shrink: 0;
+}
+.batch-add__file-x {
+  background: none;
+  border: none;
+  color: var(--chrome-fg-dim);
+  cursor: pointer;
+  padding: 2px;
+  border-radius: 4px;
+}
+.batch-add__file-x:hover { color: var(--color-danger); }
+
+.batch-add__settings {
+  display: flex;
+  flex-direction: column;
+  gap: 12px;
+}
+.batch-add__field {
+  display: flex;
+  flex-direction: column;
+  gap: 6px;
+}
+.batch-add__select {
+  font-size: 0.78rem;
+}
+.batch-add__toggle {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  font-size: 0.78rem;
+  color: var(--chrome-fg);
+  cursor: pointer;
+}
+.batch-add__toggle input { cursor: pointer; }
+
+.batch-add__foot {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  padding: 12px 18px;
+  border-top: 1px solid var(--chrome-border);
+}
+.batch-add__estimate {
+  flex: 1;
+  font-family: var(--font-mono);
+  font-size: 0.68rem;
+  color: var(--chrome-fg-dim);
+}

frontend/src/components/BatchAddDialog.jsx

@@ -0,0 +1,166 @@
+import React, { useState, useRef, useCallback } from 'react';
+import { Upload, Film, Globe, X, Plus, Loader } from 'lucide-react';
+import { Button } from '../ui';
+import MultiLangPicker from './MultiLangPicker';
+import { PRESETS } from '../utils/constants';
+import './BatchAddDialog.css';
+
+/**
+ * BatchAddDialog — multi-file drop zone + shared settings for batch dubbing.
+ *
+ * Users drop N video files, pick languages + voice, then click "Add to Queue".
+ * Each file is POSTed as a separate job to the batch endpoint.
+ */
+export default function BatchAddDialog({
+  open,
+  onClose,
+  profiles = [],
+  onEnqueue,  // async (files, settings) => void
+}) {
+  const [files, setFiles] = useState([]);
+  const [langs, setLangs] = useState([{ lang: 'Spanish', code: 'es' }]);
+  const [voiceId, setVoiceId] = useState('');
+  const [preserveBg, setPreserveBg] = useState(true);
+  const [submitting, setSubmitting] = useState(false);
+  const fileInputRef = useRef(null);
+
+  const handleDrop = useCallback((e) => {
+    e.preventDefault();
+    const dropped = Array.from(e.dataTransfer.files).filter(f => f.type.startsWith('video/'));
+    if (dropped.length) setFiles(prev => [...prev, ...dropped]);
+  }, []);
+
+  const removeFile = (idx) => {
+    setFiles(prev => prev.filter((_, i) => i !== idx));
+  };
+
+  const handleSubmit = async () => {
+    if (!files.length || !langs.length) return;
+    setSubmitting(true);
+    try {
+      await onEnqueue?.(files, { langs, voiceId, preserveBg });
+      setFiles([]);
+      onClose?.();
+    } finally {
+      setSubmitting(false);
+    }
+  };
+
+  if (!open) return null;
+
+  return (
+    <div className="batch-add-overlay" onClick={onClose}>
+      <div className="batch-add" onClick={e => e.stopPropagation()}>
+        <div className="batch-add__head">
+          <span className="batch-add__title">
+            <Plus size={13} /> Add Videos to Queue
+          </span>
+          <button type="button" className="batch-add__close" onClick={onClose}>
+            <X size={13} />
+          </button>
+        </div>
+
+        <div className="batch-add__body">
+          {/* Drop zone */}
+          <div
+            className="batch-add__drop"
+            onDragOver={e => { e.preventDefault(); e.currentTarget.classList.add('is-over'); }}
+            onDragLeave={e => e.currentTarget.classList.remove('is-over')}
+            onDrop={e => { e.currentTarget.classList.remove('is-over'); handleDrop(e); }}
+            onClick={() => fileInputRef.current?.click()}
+          >
+            <Upload size={24} />
+            <span>Drop video files here or click to browse</span>
+            <span className="batch-add__drop-hint">MP4 · MOV · MKV · WEBM</span>
+          </div>
+          <input
+            ref={fileInputRef}
+            type="file"
+            accept="video/*"
+            multiple
+            className="batch-add__file-input"
+            onChange={e => {
+              const added = Array.from(e.target.files);
+              if (added.length) setFiles(prev => [...prev, ...added]);
+              e.target.value = '';
+            }}
+          />
+
+          {/* File list */}
+          {files.length > 0 && (
+            <div className="batch-add__files">
+              <span className="batch-add__kicker">FILES ({files.length})</span>
+              {files.map((f, i) => (
+                <div key={`${f.name}-${i}`} className="batch-add__file-row">
+                  <Film size={10} />
+                  <span className="batch-add__file-name">{f.name}</span>
+                  <span className="batch-add__file-size">{(f.size / 1024 / 1024).toFixed(1)} MB</span>
+                  <button type="button" className="batch-add__file-x" onClick={() => removeFile(i)}>
+                    <X size={9} />
+                  </button>
+                </div>
+              ))}
+            </div>
+          )}
+
+          {/* Settings */}
+          <div className="batch-add__settings">
+            <div className="batch-add__field">
+              <span className="batch-add__kicker"><Globe size={9} /> TARGET LANGUAGES</span>
+              <MultiLangPicker selected={langs} onChange={setLangs} />
+            </div>
+
+            <div className="batch-add__field">
+              <span className="batch-add__kicker">VOICE</span>
+              <select
+                className="input-base batch-add__select"
+                value={voiceId}
+                onChange={e => setVoiceId(e.target.value)}
+              >
+                <option value="">Default</option>
+                {profiles.filter(p => !p.instruct).length > 0 && (
+                  <optgroup label="Clone Profiles">
+                    {profiles.filter(p => !p.instruct).map(p => (
+                      <option key={p.id} value={p.id}>{p.name}</option>
+                    ))}
+                  </optgroup>
+                )}
+                {PRESETS.length > 0 && (
+                  <optgroup label="Presets">
+                    {PRESETS.map(p => (
+                      <option key={p.id} value={`preset:${p.id}`}>{p.name}</option>
+                    ))}
+                  </optgroup>
+                )}
+              </select>
+            </div>
+
+            <label className="batch-add__toggle">
+              <input type="checkbox" checked={preserveBg} onChange={e => setPreserveBg(e.target.checked)} />
+              <span>Preserve background audio (music/FX)</span>
+            </label>
+          </div>
+        </div>
+
+        <div className="batch-add__foot">
+          <span className="batch-add__estimate">
+            {files.length > 0 && langs.length > 0
+              ? `${files.length} video${files.length > 1 ? 's' : ''} × ${langs.length} lang${langs.length > 1 ? 's' : ''} = ${files.length * langs.length} job${files.length * langs.length > 1 ? 's' : ''}`
+              : 'Select files and languages'}
+          </span>
+          <Button variant="ghost" size="sm" onClick={onClose}>Cancel</Button>
+          <Button
+            variant="primary"
+            size="sm"
+            onClick={handleSubmit}
+            disabled={!files.length || !langs.length || submitting}
+            loading={submitting}
+            leading={!submitting && <Plus size={10} />}
+          >
+            Add to Queue
+          </Button>
+        </div>
+      </div>
+    </div>
+  );
+}

frontend/src/components/BootstrapSplash.css

@@ -0,0 +1,172 @@
+.bootstrap-splash {
+  position: fixed;
+  inset: 0;
+  display: grid;
+  place-items: center;
+  background: var(--chrome-bg, #141414);
+  color: var(--chrome-fg, #eee);
+  font-family: 'Inter Variable', 'Inter', system-ui, sans-serif;
+  z-index: 9999;
+  padding: 2rem;
+}
+
+.bootstrap-splash__card {
+  width: 100%;
+  max-width: 560px;
+  background: color-mix(in srgb, var(--chrome-fg, #eee) 4%, transparent);
+  border: 1px solid color-mix(in srgb, var(--chrome-fg, #eee) 10%, transparent);
+  border-radius: 14px;
+  padding: 2rem;
+  text-align: left;
+}
+
+.bootstrap-splash__card h1 {
+  margin: 0 0 0.5rem;
+  font-size: 1.25rem;
+  font-weight: 600;
+  letter-spacing: -0.01em;
+}
+
+.bootstrap-splash__status {
+  margin: 0 0 1.25rem;
+  font-size: 0.95rem;
+  opacity: 0.85;
+}
+
+.bootstrap-splash__bar {
+  height: 4px;
+  width: 100%;
+  border-radius: 3px;
+  background: color-mix(in srgb, var(--chrome-fg, #eee) 8%, transparent);
+  overflow: hidden;
+  margin-bottom: 1.25rem;
+}
+
+.bootstrap-splash__bar-fill {
+  height: 100%;
+  background: var(--chrome-accent, #8ec07c);
+  transition: width 0.4s ease;
+}
+
+.bootstrap-splash__steps {
+  list-style: none;
+  margin: 0;
+  padding: 0;
+  display: flex;
+  flex-direction: column;
+  gap: 0.5rem;
+  font-size: 0.85rem;
+}
+
+.bootstrap-splash__steps li {
+  padding-left: 1.5rem;
+  position: relative;
+  opacity: 0.5;
+}
+
+.bootstrap-splash__steps li::before {
+  content: '○';
+  position: absolute;
+  left: 0;
+  top: 0;
+}
+
+.bootstrap-splash__steps li.done {
+  opacity: 0.6;
+}
+
+.bootstrap-splash__steps li.done::before {
+  content: '✓';
+  color: var(--chrome-accent, #8ec07c);
+}
+
+.bootstrap-splash__steps li.active {
+  opacity: 1;
+  font-weight: 500;
+}
+
+.bootstrap-splash__steps li.active::before {
+  content: '●';
+  color: var(--chrome-accent, #8ec07c);
+  animation: bootstrap-pulse 1.4s ease-in-out infinite;
+}
+
+@keyframes bootstrap-pulse {
+  0%, 100% { opacity: 1; }
+  50% { opacity: 0.3; }
+}
+
+.bootstrap-splash__error {
+  font-family: 'IBM Plex Mono', ui-monospace, monospace;
+  font-size: 0.8rem;
+  background: color-mix(in srgb, #ef4444 12%, transparent);
+  border: 1px solid color-mix(in srgb, #ef4444 35%, transparent);
+  color: #fca5a5;
+  padding: 0.75rem 1rem;
+  border-radius: 8px;
+  white-space: pre-wrap;
+  word-break: break-word;
+}
+
+.bootstrap-splash__sub-progress {
+  margin: -0.5rem 0 1rem;
+  display: flex;
+  flex-direction: column;
+  gap: 0.4rem;
+}
+
+.bootstrap-splash__sub-bar {
+  height: 3px;
+  width: 100%;
+  border-radius: 2px;
+  background: color-mix(in srgb, var(--chrome-fg, #eee) 6%, transparent);
+  overflow: hidden;
+}
+
+.bootstrap-splash__sub-bar-fill {
+  height: 100%;
+  background: color-mix(in srgb, var(--chrome-accent, #8ec07c) 70%, transparent);
+  transition: width 0.2s ease;
+}
+
+.bootstrap-splash__sub-label {
+  font-family: 'IBM Plex Mono', ui-monospace, monospace;
+  font-size: 0.72rem;
+  opacity: 0.65;
+}
+
+.bootstrap-splash__log-toggle {
+  margin-top: 1.25rem;
+  background: none;
+  border: none;
+  color: inherit;
+  opacity: 0.65;
+  font: inherit;
+  font-size: 0.78rem;
+  padding: 0.25rem 0;
+  cursor: pointer;
+  text-align: left;
+}
+
+.bootstrap-splash__log-toggle:hover { opacity: 1; }
+
+.bootstrap-splash__log-count {
+  opacity: 0.6;
+  font-variant-numeric: tabular-nums;
+}
+
+.bootstrap-splash__logs {
+  margin: 0.5rem 0 0;
+  max-height: 220px;
+  overflow-y: auto;
+  font-family: 'IBM Plex Mono', ui-monospace, monospace;
+  font-size: 0.72rem;
+  line-height: 1.45;
+  background: color-mix(in srgb, var(--chrome-fg, #eee) 4%, transparent);
+  border: 1px solid color-mix(in srgb, var(--chrome-fg, #eee) 8%, transparent);
+  border-radius: 8px;
+  padding: 0.6rem 0.75rem;
+  white-space: pre-wrap;
+  word-break: break-word;
+  opacity: 0.85;
+}

frontend/src/components/BootstrapSplash.jsx

@@ -0,0 +1,220 @@
+/**
+ * First-run bootstrap splash.
+ *
+ * Two data sources drive this UI:
+ *   1. `bootstrap_status` Tauri command (polled every 1 s) — coarse stage.
+ *   2. `bootstrap-log` + `bootstrap-progress` Tauri events — live stdout
+ *      from `uv sync`, ffmpeg byte counts, etc. The log panel shows the
+ *      last N lines so users can see *something* happening during the 5–10
+ *      min dependency install.
+ */
+import { useEffect, useRef, useState } from 'react';
+import './BootstrapSplash.css';
+
+const STAGE_LABEL = {
+  checking:           'Checking environment…',
+  downloading_uv:     'Downloading uv (Python package manager)…',
+  creating_venv:      'Creating Python virtual environment…',
+  installing_deps:    'Installing dependencies — first run, 5–10 min.',
+  downloading_ffmpeg: 'Downloading ffmpeg…',
+  starting_backend:   'Starting backend…',
+  ready:              'Ready',
+  failed:             'Setup failed',
+};
+
+const STEPS = [
+  'checking',
+  'downloading_uv',
+  'creating_venv',
+  'installing_deps',
+  'downloading_ffmpeg',
+  'starting_backend',
+];
+
+const MAX_LOG_LINES = 200;
+
+function formatBytes(n) {
+  if (!n || n < 0) return '';
+  const units = ['B', 'KB', 'MB', 'GB'];
+  let i = 0;
+  let v = n;
+  while (v >= 1024 && i < units.length - 1) { v /= 1024; i += 1; }
+  return `${v.toFixed(v < 10 ? 1 : 0)} ${units[i]}`;
+}
+
+export function BootstrapSplash({ stage, message }) {
+  const label = STAGE_LABEL[stage] || stage;
+  const stepIndex = Math.max(0, STEPS.indexOf(stage));
+  const isFailed = stage === 'failed';
+  const [logs, setLogs] = useState([]);
+  const [logsOpen, setLogsOpen] = useState(false);
+  const [progress, setProgress] = useState(null); // { stage, bytes_done, bytes_total, percent }
+  const logRef = useRef(null);
+
+  // Subscribe to live log + progress events from the Rust bootstrap.
+  useEffect(() => {
+    if (typeof window === 'undefined') return;
+    if (!('__TAURI_INTERNALS__' in window)) return;
+    let unlistenLog = null;
+    let unlistenProgress = null;
+    let cancelled = false;
+
+    (async () => {
+      try {
+        const { listen } = await import('@tauri-apps/api/event');
+        if (cancelled) return;
+        unlistenLog = await listen('bootstrap-log', (e) => {
+          const { stage: s, line } = e.payload || {};
+          if (!line) return;
+          setLogs((prev) => {
+            const next = prev.concat([{ stage: s, line, t: Date.now() }]);
+            return next.length > MAX_LOG_LINES
+              ? next.slice(next.length - MAX_LOG_LINES)
+              : next;
+          });
+        });
+        unlistenProgress = await listen('bootstrap-progress', (e) => {
+          setProgress(e.payload || null);
+        });
+      } catch {
+        /* not in Tauri or listen unavailable — silent */
+      }
+    })();
+    return () => {
+      cancelled = true;
+      if (unlistenLog) unlistenLog();
+      if (unlistenProgress) unlistenProgress();
+    };
+  }, []);
+
+  // Auto-scroll the log panel to the latest line whenever it opens or
+  // new lines arrive.
+  useEffect(() => {
+    if (logsOpen && logRef.current) {
+      logRef.current.scrollTop = logRef.current.scrollHeight;
+    }
+  }, [logs, logsOpen]);
+
+  const stageProgress = progress && progress.stage === stage ? progress : null;
+  const pctFromBytes = stageProgress?.percent != null ? stageProgress.percent : null;
+
+  return (
+    <div className="bootstrap-splash">
+      <div className="bootstrap-splash__card">
+        <h1>OmniVoice Studio</h1>
+        <p className="bootstrap-splash__status">{label}</p>
+        {isFailed ? (
+          <pre className="bootstrap-splash__error">{message || 'Unknown error'}</pre>
+        ) : (
+          <>
+            <div className="bootstrap-splash__bar">
+              <div
+                className="bootstrap-splash__bar-fill"
+                style={{ width: `${((stepIndex + 1) / STEPS.length) * 100}%` }}
+              />
+            </div>
+            {stageProgress && (
+              <div className="bootstrap-splash__sub-progress">
+                <div className="bootstrap-splash__sub-bar">
+                  <div
+                    className="bootstrap-splash__sub-bar-fill"
+                    style={{ width: `${pctFromBytes ?? 0}%` }}
+                  />
+                </div>
+                <span className="bootstrap-splash__sub-label">
+                  {formatBytes(stageProgress.bytes_done)}
+                  {stageProgress.bytes_total > 0
+                    ? ` / ${formatBytes(stageProgress.bytes_total)}`
+                    : ''}
+                  {pctFromBytes != null ? ` (${pctFromBytes}%)` : ''}
+                </span>
+              </div>
+            )}
+            <ol className="bootstrap-splash__steps">
+              {STEPS.map((s, i) => (
+                <li
+                  key={s}
+                  className={
+                    i < stepIndex ? 'done' :
+                    i === stepIndex ? 'active' :
+                    'pending'
+                  }
+                >
+                  {STAGE_LABEL[s]}
+                </li>
+              ))}
+            </ol>
+          </>
+        )}
+        <button
+          type="button"
+          className="bootstrap-splash__log-toggle"
+          onClick={() => setLogsOpen((v) => !v)}
+        >
+          {logsOpen ? '▾ Hide logs' : '▸ Show logs'}
+          {logs.length > 0 && (
+            <span className="bootstrap-splash__log-count"> ({logs.length})</span>
+          )}
+        </button>
+        {logsOpen && (
+          <pre className="bootstrap-splash__logs" ref={logRef}>
+            {logs.length === 0
+              ? 'Waiting for output…'
+              : logs.map((l, i) => `[${l.stage}] ${l.line}`).join('\n')}
+          </pre>
+        )}
+      </div>
+    </div>
+  );
+}
+
+/**
+ * Hook: polls the Rust `bootstrap_status` command every pollMs ms. Returns
+ * the current stage (string) + message. In a non-Tauri context (dev web),
+ * returns 'ready' immediately so the splash never mounts.
+ */
+export function useBootstrapStage(pollMs = 1000) {
+  const [state, setState] = useState({ stage: 'checking', message: null });
+
+  useEffect(() => {
+    if (typeof window === 'undefined') { setState({ stage: 'ready', message: null }); return; }
+    if (!('__TAURI_INTERNALS__' in window)) { setState({ stage: 'ready', message: null }); return; }
+    if (import.meta.env.DEV) { setState({ stage: 'ready', message: null }); return; }
+
+    let cancelled = false;
+    let timer = null;
+    const invoke = async () => {
+      try {
+        const { invoke: tauriInvoke } = await import('@tauri-apps/api/core');
+        return tauriInvoke;
+      } catch {
+        return null;
+      }
+    };
+    (async () => {
+      const tauriInvoke = await invoke();
+      if (!tauriInvoke) { setState({ stage: 'ready', message: null }); return; }
+      const tick = async () => {
+        if (cancelled) return;
+        try {
+          const res = await tauriInvoke('bootstrap_status');
+          if (cancelled) return;
+          // Rust returns { stage: 'ready' } or { stage: 'failed', message: '…' } etc.
+          setState({ stage: res.stage || 'ready', message: res.message || null });
+          if (res.stage !== 'ready' && res.stage !== 'failed') {
+            timer = setTimeout(tick, pollMs);
+          }
+        } catch {
+          setState({ stage: 'ready', message: null });
+        }
+      };
+      tick();
+    })();
+    return () => {
+      cancelled = true;
+      if (timer) clearTimeout(timer);
+    };
+  }, [pollMs]);
+
+  return state;
+}

frontend/src/components/CheckpointBanner.jsx

@@ -1,6 +1,7 @@
 import React from 'react';
 import { CheckCircle, ArrowRight, X, Sparkles, Languages, Mic } from 'lucide-react';
 import { Button } from '../ui';
+import './Misc.css';
 
 /**
  * Phase 4.3 — between-stage checkpoint banner.
@@ -50,48 +51,23 @@ export default function CheckpointBanner({ stage, count, onContinue, onDismiss,
 
   return (
     <div
-      className="checkpoint-banner"
-      style={{
-        // Accent shows through as a left-edge bar instead of a gradient wash,
-        // and the fill stays flat chrome so the banner rhymes with the rest
-        // of the studio strips.
-        display: 'flex',
-        alignItems: 'center',
-        gap: 10,
-        padding: '8px 12px',
-        marginBottom: 6,
-        borderRadius: 'var(--chrome-radius-pill)',
-        background: 'var(--chrome-bg)',
-        border: '1px solid var(--chrome-border)',
-        borderLeft: `2px solid ${cfg.accent}`,
-      }}
+      className="checkpoint-banner ckpt-banner"
+      style={{ borderLeft: `2px solid ${cfg.accent}` }}
       role="status"
     >
-      <Icon size={14} color={cfg.accent} style={{ flexShrink: 0 }} />
-      <div style={{ flex: 1, minWidth: 0, display: 'flex', flexDirection: 'column', gap: 1 }}>
-        <div style={{ display: 'flex', alignItems: 'baseline', gap: 6 }}>
-          <span style={{
-            fontFamily: 'var(--chrome-font-mono)',
-            fontSize: 'var(--chrome-label-size)',
-            letterSpacing: 'var(--chrome-label-track)',
-            textTransform: 'uppercase',
-            fontWeight: 600,
-            color: 'var(--chrome-fg)',
-          }}>
+      <Icon size={14} color={cfg.accent} className="ckpt-icon" />
+      <div className="ckpt-body">
+        <div className="ckpt-head">
+          <span className="ckpt-title">
             {cfg.title}
           </span>
           {typeof count === 'number' && (
-            <span style={{
-              fontFamily: 'var(--chrome-font-mono)',
-              fontSize: 'var(--chrome-label-size)',
-              color: 'var(--chrome-fg-muted)',
-              fontVariantNumeric: 'tabular-nums',
-            }}>
+            <span className="ckpt-count">
               {count} segment{count === 1 ? '' : 's'}
             </span>
           )}
         </div>
-        <span style={{ fontSize: '0.64rem', color: 'var(--chrome-fg-muted)', lineHeight: 1.35 }}>
+        <span className="ckpt-hint">
           {cfg.hint}
         </span>
       </div>

frontend/src/components/CompareModal.jsx

@@ -121,7 +121,7 @@ export default function CompareModal({
               value={compareText}
               onChange={e => setCompareText(e.target.value)}
               rows={2}
-              style={{ resize: 'none' }}
+              className="compare-textarea--noresize"
             />
           </Field>
 

frontend/src/components/DirectionDialog.jsx

@@ -3,6 +3,7 @@ import { Sparkles, X } from 'lucide-react';
 import { toast } from 'react-hot-toast';
 import { Dialog, Button, Textarea, Field, Badge } from '../ui';
 import { apiPost } from '../api/client';
+import './Misc.css';
 
 /**
  * DirectionDialog — Phase 4.2 per-segment direction editor.
@@ -63,7 +64,7 @@ export default function DirectionDialog({ open, seg, onSave, onClose }) {
               variant="ghost" size="sm"
               onClick={() => { setText(''); }}
               leading={<X size={11} />}
-              style={{ marginRight: 'auto' }}
+              className="dir-clear-btn"
             >
               Clear
             </Button>
@@ -91,7 +92,7 @@ export default function DirectionDialog({ open, seg, onSave, onClose }) {
         />
       </Field>
 
-      <div style={{ display: 'flex', gap: 8, alignItems: 'center', marginTop: 8 }}>
+      <div className="dir-preview-actions">
         <Button
           variant="subtle" size="sm"
           onClick={runPreview}
@@ -117,8 +118,8 @@ export default function DirectionDialog({ open, seg, onSave, onClose }) {
           </div>
           <div>
             <strong>Rate bias:</strong> <code>{preview.rate_bias?.toFixed?.(2)}</code>
-            {preview.rate_bias > 1.05 && <> · <span style={{ color: 'var(--color-brand)' }}>speeds up</span></>}
-            {preview.rate_bias < 0.95 && <> · <span style={{ color: 'var(--color-info)' }}>slows down</span></>}
+            {preview.rate_bias > 1.05 && <> · <span className="dir-rate-up">speeds up</span></>}
+            {preview.rate_bias < 0.95 && <> · <span className="dir-rate-down">slows down</span></>}
           </div>
           {Object.keys(preview.tokens || {}).length > 0 && (
             <details>
@@ -127,7 +128,7 @@ export default function DirectionDialog({ open, seg, onSave, onClose }) {
             </details>
           )}
           {preview.error && (
-            <div style={{ color: 'var(--color-warn)', fontSize: '0.7rem' }}>
+            <div className="dir-error">
               {preview.error}
             </div>
           )}

frontend/src/components/DubSegmentRow.css

@@ -0,0 +1,60 @@
+/* ═══ DubSegmentRow extracted layout styles ═══ */
+.seg-check {
+  width: 16px; flex-shrink: 0; margin-right: 2px; cursor: pointer;
+}
+.seg-time {
+  width: 50px; flex-shrink: 0; display: flex; flex-direction: column;
+}
+.seg-sync-badge {
+  font-size: 0.5rem; margin-top: 2px;
+  display: inline-flex; align-items: center; gap: 2px;
+}
+.seg-rate-badge {
+  font-size: 0.5rem; margin-top: 2px;
+  font-variant-numeric: tabular-nums;
+}
+.seg-speed-badge {
+  font-size: 0.55rem; margin-left: 2px;
+}
+.seg-speaker {
+  width: 45px; flex-shrink: 0; font-size: 0.55rem; color: #a89984;
+  overflow: hidden; text-overflow: ellipsis; white-space: nowrap;
+}
+.seg-text-col {
+  flex: 1 1 0%; display: flex; flex-direction: column; gap: 2px;
+  min-width: 80px; overflow: hidden;
+}
+.seg-text-col .segment-input {
+  width: 100%; min-width: 0;
+}
+.seg-orig-row {
+  font-size: 0.55rem; color: #6b6657;
+  display: flex; align-items: center; gap: 4px;
+  padding: 0 4px; overflow: hidden;
+}
+.seg-orig-label {
+  opacity: 0.8; text-transform: uppercase; font-weight: 600;
+  font-size: 0.5rem; color: #7c6f64;
+}
+.seg-orig-text {
+  flex: 1; white-space: nowrap; overflow: hidden; text-overflow: ellipsis;
+}
+.seg-budget-warn { color: #fabd2f; font-size: 0.5rem; }
+.seg-restore-btn {
+  background: none; border: none; color: #83a598;
+  cursor: pointer; padding: 0; font-size: 0.55rem;
+}
+.seg-lang-select {
+  width: 42px; flex-shrink: 0; font-size: 0.5rem; padding: 1px 2px;
+}
+.seg-profile-select {
+  width: 60px; flex-shrink: 0; font-size: 0.55rem; padding: 1px 2px;
+  overflow: hidden; text-overflow: ellipsis;
+}
+.seg-gain-slider {
+  width: 40px !important; max-width: 40px; flex-shrink: 0; flex-grow: 0;
+  height: 3px; padding: 0; margin: 0;
+}
+.seg-actions {
+  display: flex; gap: 1px; width: 42px; flex-shrink: 0;
+}

frontend/src/components/DubSegmentRow.jsx

@@ -7,6 +7,7 @@ import { formatTime } from '../utils/format';
 import { LANG_CODES } from '../utils/languages';
 import { PRESETS } from '../utils/constants';
 import { Menu, Button, Badge } from '../ui';
+import './DubSegmentRow.css';
 
 const CHAR_BUDGET_RATIO = 1.3;
 
@@ -51,24 +52,23 @@ function DubSegmentRow({
         onChange={(e) => onSelect(seg.id, idx, e.nativeEvent.shiftKey)}
         onClick={(e) => onSelect(seg.id, idx, e.shiftKey)}
         disabled={disabled}
-        style={{ width: 14, marginRight: 4, cursor: 'pointer', accentColor: '#d3869b' }}
+        style={{ accentColor: '#d3869b' }}
+        className="seg-check"
         title="Select segment (shift+click for range)"
       />
-      <span className="segment-time" style={{ width: 55, display: 'flex', flexDirection: 'column' }}>
+      <span className="segment-time seg-time">
         <span>
           {formatTime(seg.start)}–{formatTime(seg.end)}
           {seg.speed && seg.speed !== 1.0 && (
-            <span style={{ fontSize: '0.55rem', color: seg.speed > 1 ? '#d3869b' : '#8ec07c', marginLeft: 2 }}>
+            <span className="seg-speed-badge" style={{ color: seg.speed > 1 ? '#d3869b' : '#8ec07c' }}>
               {seg.speed.toFixed(2)}x
             </span>
           )}
         </span>
         {SyncIcon && (
           <span
-            style={{
-              fontSize: '0.5rem', marginTop: 2, display: 'inline-flex',
-              alignItems: 'center', gap: 2, color: syncColor,
-            }}
+            className="seg-sync-badge"
+            style={{ color: syncColor }}
             title={`Generated audio is ${Math.round(seg.sync_ratio * 100)}% the duration of original`}
           >
             <SyncIcon size={8} /> Sync: {Math.round(seg.sync_ratio * 100)}%
@@ -76,11 +76,8 @@ function DubSegmentRow({
         )}
         {seg.rate_ratio != null && Math.abs(seg.rate_ratio - 1.0) > 0.03 && (
           <span
-            style={{
-              fontSize: '0.5rem', marginTop: 2,
-              color: seg.rate_ratio > 1.15 ? '#fb4934' : seg.rate_ratio < 0.85 ? '#83a598' : '#a89984',
-              fontVariantNumeric: 'tabular-nums',
-            }}
+            className="seg-rate-badge"
+            style={{ color: seg.rate_ratio > 1.15 ? '#fb4934' : seg.rate_ratio < 0.85 ? '#83a598' : '#a89984' }}
             title={`Speech-rate fit: ${seg.rate_ratio.toFixed(2)}× relative to slot${seg.rate_error ? ` (${seg.rate_error})` : ''}`}
           >
             📖 {seg.rate_ratio.toFixed(2)}×
@@ -88,9 +85,9 @@ function DubSegmentRow({
         )}
       </span>
 
-      <span style={{ width: 50, fontSize: '0.58rem', color: '#a89984' }}>{seg.speaker_id || ''}</span>
+      <span className="seg-speaker">{seg.speaker_id || ''}</span>
 
-      <span style={{ flex: 1, display: 'flex', flexDirection: 'column', gap: 2, minWidth: 0 }}>
+      <span className="seg-text-col">
         <input
           className="input-base segment-input"
           value={seg.text}
@@ -109,13 +106,13 @@ function DubSegmentRow({
           }
         />
         {seg.text_original && seg.text_original !== seg.text && (
-          <span style={{ fontSize: '0.55rem', color: '#6b6657', display: 'flex', alignItems: 'center', gap: 4, padding: '0 4px', overflow: 'hidden' }}>
-            <span style={{ opacity: 0.8, textTransform: 'uppercase', fontWeight: 600, fontSize: '0.5rem', color: '#7c6f64' }}>orig</span>
-            <span style={{ flex: 1, whiteSpace: 'nowrap', overflow: 'hidden', textOverflow: 'ellipsis' }} title={seg.text_original}>
+          <span className="seg-orig-row">
+            <span className="seg-orig-label">orig</span>
+            <span className="seg-orig-text" title={seg.text_original}>
               {seg.text_original}
             </span>
             {overBudget && (
-              <span style={{ color: '#fabd2f', fontSize: '0.5rem' }}>
+              <span className="seg-budget-warn">
                 {Math.round((seg.text.length / seg.text_original.length) * 100)}%
               </span>
             )}
@@ -123,7 +120,7 @@ function DubSegmentRow({
               onClick={() => onRestore(seg.id)}
               disabled={disabled}
               title="Restore original text"
-              style={{ background: 'none', border: 'none', color: '#83a598', cursor: 'pointer', padding: 0, fontSize: '0.55rem' }}
+              className="seg-restore-btn"
             >
               ↺
             </button>
@@ -132,8 +129,7 @@ function DubSegmentRow({
       </span>
 
       <select
-        className="input-base segment-input"
-        style={{ width: 45, fontSize: '0.55rem', padding: '1px 2px' }}
+        className="input-base seg-lang-select"
         value={seg.target_lang || ''}
         disabled={disabled}
         onChange={(e) => onEditField(seg.id, 'target_lang', e.target.value)}
@@ -145,8 +141,7 @@ function DubSegmentRow({
       </select>
 
       <select
-        className="input-base"
-        style={{ width: 90, fontSize: '0.6rem', padding: '1px 3px' }}
+        className="input-base seg-profile-select"
         value={seg.profile_id || ''}
         disabled={disabled}
         onChange={(e) => onEditField(seg.id, 'profile_id', e.target.value)}
@@ -171,13 +166,11 @@ function DubSegmentRow({
         title={`${Math.round((seg.gain ?? 1.0) * 100)}%`}
         disabled={disabled}
         onChange={(e) => onEditField(seg.id, 'gain', Number(e.target.value) / 100)}
-        style={{
-          width: 30, height: 2, padding: 0, margin: 0,
-          accentColor: (seg.gain ?? 1.0) > 1.2 ? '#fb4934' : (seg.gain ?? 1.0) < 0.5 ? '#83a598' : '#a89984',
-        }}
+        className="seg-gain-slider"
+        style={{ accentColor: (seg.gain ?? 1.0) > 1.2 ? '#fb4934' : (seg.gain ?? 1.0) < 0.5 ? '#83a598' : '#a89984' }}
       />
 
-      <div style={{ display: 'flex', gap: 1, width: 54 }}>
+      <div className="seg-actions">
         <button
           className="segment-play"
           disabled={disabled}

frontend/src/components/DubSegmentTable.css

@@ -1,5 +1,10 @@
 /* Table body specific styles — chrome comes from ui/Table. */
 
+.dub-segment-table__header {
+  padding: 3px 4px !important;
+  gap: 3px !important;
+}
+
 .dub-segment-table__body { flex: 1; min-height: 0; }
 
 .dub-segment-table__select-all {

frontend/src/components/DubSegmentTable.jsx

@@ -8,13 +8,13 @@ const BASE_ROW_HEIGHT = 28;
 const ROW_HEIGHT_WITH_ORIG = 44;
 
 const COLUMNS = [
-  { key: 'time',  label: 'Time',  width: 55 },
-  { key: 'spkr',  label: 'Spkr',  width: 50 },
+  { key: 'time',  label: 'Time',  width: 50 },
+  { key: 'spkr',  label: 'Spkr',  width: 45 },
   { key: 'text',  label: 'Text',  flex: 1 },
-  { key: 'lang',  label: 'Lang',  width: 45 },
-  { key: 'voice', label: 'Voice', width: 90 },
-  { key: 'vol',   label: 'Vol',   width: 30, title: 'Volume (0–200%)' },
-  { key: 'act',   label: '',      width: 54 },
+  { key: 'lang',  label: 'Lang',  width: 42 },
+  { key: 'voice', label: 'Voice', width: 60 },
+  { key: 'vol',   label: 'Vol',   width: 40, title: 'Volume (0–200%)' },
+  { key: 'act',   label: '',      width: 42 },
 ];
 
 export default function DubSegmentTable({
@@ -124,6 +124,7 @@ export default function DubSegmentTable({
       </Table.Toolbar>
 
       <Table.Header
+        className="dub-segment-table__header"
         columns={COLUMNS}
         leading={
           <span className="dub-segment-table__select-all">

frontend/src/components/ErrorBoundary.jsx

@@ -1,5 +1,6 @@
 import React from 'react';
 import { AlertCircle, RefreshCw } from 'lucide-react';
+import './WaveformErrorBoundary.css';
 
 export default class ErrorBoundary extends React.Component {
   constructor(props) {
@@ -24,43 +25,19 @@ export default class ErrorBoundary extends React.Component {
 
     const msg = this.state.error?.message || String(this.state.error);
     return (
-      <div style={{
-        flex: 1, display: 'flex', alignItems: 'center', justifyContent: 'center',
-        padding: 32, fontFamily: 'var(--font-sans)',
-      }}>
-        <div style={{
-          maxWidth: 520, width: '100%',
-          padding: 22, textAlign: 'center',
-          background: 'var(--chrome-bg)',
-          border: '1px solid color-mix(in srgb, var(--chrome-severity-err) 35%, transparent)',
-          borderLeft: '2px solid var(--chrome-severity-err)',
-          borderRadius: 'var(--chrome-radius-pill)',
-          boxShadow: 'none',
-        }}>
-          <AlertCircle size={32} color="var(--chrome-severity-err)" style={{ marginBottom: 10 }} />
-          <h2 style={{
-            fontFamily: 'var(--font-serif)', fontStyle: 'italic', fontSize: '1.6rem', fontWeight: 400,
-            color: 'var(--chrome-fg)', margin: '0 0 6px', letterSpacing: '-0.01em',
-          }}>
+      <div className="errbnd-wrap">
+        <div className="errbnd-card">
+          <AlertCircle size={32} color="var(--chrome-severity-err)" className="errbnd-icon" />
+          <h2 className="errbnd-title">
             This tab hit a snag.
           </h2>
-          <p style={{ color: 'var(--chrome-fg-muted)', fontSize: '0.82rem', margin: '0 0 12px', lineHeight: 1.5 }}>
+          <p className="errbnd-desc">
             Don't worry — the rest of the app still works. You can switch tabs, or try again below.
           </p>
-          <pre style={{
-            textAlign: 'left', fontSize: '0.72rem', color: 'var(--chrome-severity-err)',
-            background: 'var(--chrome-hover-bg)', padding: '8px 10px', borderRadius: 'var(--chrome-radius-pill)',
-            border: '1px solid var(--chrome-border)',
-            maxHeight: 140, overflow: 'auto', margin: '0 0 14px',
-            fontFamily: 'var(--font-mono)',
-          }}>{msg}</pre>
+          <pre className="errbnd-trace">{msg}</pre>
           <button
             onClick={this.reset}
-            className="btn-primary"
-            style={{
-              padding: '6px 14px', fontSize: '0.78rem', fontWeight: 500,
-              display: 'inline-flex', alignItems: 'center', gap: 6,
-            }}
+            className="btn-primary errbnd-retry"
           >
             <RefreshCw size={12} /> Try again
           </button>

frontend/src/components/ExportModal.css

@@ -334,3 +334,29 @@
   display: inline-flex;
   gap: var(--space-2);
 }
+
+/* ── License notice ─────────────────────────────────────────── */
+.export-modal__license-notice {
+  display: flex;
+  align-items: center;
+  gap: 6px;
+  padding: 5px var(--space-3);
+  font-family: var(--chrome-font-mono);
+  font-size: var(--chrome-label-size);
+  letter-spacing: var(--chrome-label-track);
+  color: var(--chrome-fg-dim);
+  border-top: 1px solid var(--chrome-border);
+}
+.export-modal__license-link {
+  background: none;
+  border: none;
+  color: var(--chrome-accent);
+  font: inherit;
+  cursor: pointer;
+  text-decoration: underline;
+  text-underline-offset: 2px;
+  padding: 0;
+}
+.export-modal__license-link:hover {
+  color: var(--chrome-fg);
+}

frontend/src/components/ExportModal.jsx

@@ -2,7 +2,7 @@ import React, { useMemo, useState, useEffect, useRef } from 'react';
 import { createPortal } from 'react-dom';
 import {
   Film, Volume2, FileText, Package, Music, Layers, Download,
-  Check, Globe, Zap, X,
+  Check, Globe, Zap, X, Building2,
 } from 'lucide-react';
 import { Button, Segmented, Badge } from '../ui';
 import './ExportModal.css';
@@ -36,6 +36,7 @@ export default function ExportModal({
   triggerDownload,
   handleDubDownload, handleDubAudioDownload, handleAudioExport,
   segmentCount = 0,
+  onEnterprise,
 }) {
   const [tab, setTab] = useState('video');
 
@@ -374,6 +375,12 @@ export default function ExportModal({
           )}
         </div>
 
+        {/* Commercial license notice */}
+        <div className="export-modal__license-notice">
+          <Building2 size={11} />
+          <span>Commercial use requires a <button type="button" className="export-modal__license-link" onClick={() => { onClose(); onEnterprise?.(); }}>license</button>.</span>
+        </div>
+
         {/* Summary footer */}
         <div className="export-modal__summary">
           <div className="export-modal__summary-left">

frontend/src/components/FloatingPill.css

@@ -0,0 +1,196 @@
+/* ── Floating Status Pill ───────────────────────────────────────────────
+   Always-on-top pill that tracks long-running operations (ASR model load,
+   dubbing progress, export). Inspired by VoiceBox 0.5.0's CapturePill.
+   ─────────────────────────────────────────────────────────────────────── */
+
+.floating-pill {
+  position: fixed;
+  top: 48px;
+  right: 16px;
+  z-index: var(--z-toast);
+  display: flex;
+  align-items: center;
+  gap: var(--space-4);
+  padding: var(--space-3) var(--space-5) var(--space-3) var(--space-4);
+  min-width: 220px;
+  max-width: 360px;
+
+  background: var(--color-bg-elev-1);
+  backdrop-filter: var(--glass-blur-md);
+  -webkit-backdrop-filter: var(--glass-blur-md);
+  border: 1px solid var(--color-border-strong);
+  border-radius: var(--radius-pill);
+  box-shadow: var(--shadow-lg), 0 0 0 1px rgba(0,0,0,0.15);
+
+  font-family: var(--font-ui);
+  font-size: var(--text-sm);
+  color: var(--color-fg);
+
+  /* Slide-in animation */
+  animation: pill-enter 0.35s var(--ease-spring) both;
+  pointer-events: auto;
+  user-select: none;
+  cursor: default;
+}
+
+.floating-pill--exiting {
+  animation: pill-exit 0.25s var(--ease-out) both;
+}
+
+@keyframes pill-enter {
+  from {
+    opacity: 0;
+    transform: translateX(24px) scale(0.92);
+    filter: blur(4px);
+  }
+  to {
+    opacity: 1;
+    transform: translateX(0) scale(1);
+    filter: blur(0);
+  }
+}
+
+@keyframes pill-exit {
+  to {
+    opacity: 0;
+    transform: translateX(16px) scale(0.95);
+    filter: blur(2px);
+  }
+}
+
+@media (prefers-reduced-motion: reduce) {
+  .floating-pill { animation: none; opacity: 1; }
+  .floating-pill--exiting { animation: none; opacity: 0; }
+}
+
+/* ── Stage indicator dot ────────────────────────────────────────────── */
+
+.floating-pill__dot {
+  width: 8px;
+  height: 8px;
+  border-radius: 50%;
+  flex-shrink: 0;
+  animation: pill-dot-pulse 1.5s ease-in-out infinite;
+}
+
+.floating-pill__dot--loading-model { background: var(--color-accent); }
+.floating-pill__dot--transcribing  { background: var(--color-info); }
+.floating-pill__dot--translating   { background: var(--color-brand); }
+.floating-pill__dot--generating    { background: var(--color-warn); }
+.floating-pill__dot--exporting     { background: var(--color-success); }
+.floating-pill__dot--refining      { background: var(--color-info); }
+.floating-pill__dot--recording     { background: var(--color-danger); }
+.floating-pill__dot--done          { background: var(--color-success); animation: none; }
+.floating-pill__dot--error         { background: var(--color-danger); animation: none; }
+
+@keyframes pill-dot-pulse {
+  0%, 100% { opacity: 1; transform: scale(1); }
+  50%      { opacity: 0.4; transform: scale(0.7); }
+}
+
+/* ── Content area ───────────────────────────────────────────────────── */
+
+.floating-pill__content {
+  flex: 1;
+  min-width: 0;
+  display: flex;
+  flex-direction: column;
+  gap: 2px;
+}
+
+.floating-pill__label {
+  font-weight: var(--weight-medium);
+  white-space: nowrap;
+  overflow: hidden;
+  text-overflow: ellipsis;
+}
+
+.floating-pill__meta {
+  display: flex;
+  align-items: center;
+  gap: var(--space-3);
+  font-size: var(--text-xs);
+  color: var(--color-fg-muted);
+}
+
+.floating-pill__timer {
+  font-family: var(--font-mono);
+  font-size: var(--text-2xs);
+  color: var(--color-fg-subtle);
+  letter-spacing: 0.03em;
+}
+
+.floating-pill__error {
+  font-size: var(--text-xs);
+  color: var(--color-danger);
+  white-space: nowrap;
+  overflow: hidden;
+  text-overflow: ellipsis;
+}
+
+/* ── Mini progress bar ──────────────────────────────────────────────── */
+
+.floating-pill__progress {
+  width: 100%;
+  height: 3px;
+  border-radius: 2px;
+  background: var(--color-bg-elev-2);
+  overflow: hidden;
+  margin-top: 2px;
+}
+
+.floating-pill__progress-fill {
+  height: 100%;
+  border-radius: 2px;
+  background: var(--color-brand);
+  transition: width 0.3s var(--ease-out);
+}
+
+.floating-pill__progress-fill--indeterminate {
+  width: 40% !important;
+  animation: pill-progress-sweep 1.4s ease-in-out infinite;
+}
+
+@keyframes pill-progress-sweep {
+  0%   { transform: translateX(-100%); }
+  100% { transform: translateX(300%); }
+}
+
+/* ── Dismiss button ─────────────────────────────────────────────────── */
+
+.floating-pill__dismiss {
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  width: 20px;
+  height: 20px;
+  border-radius: 50%;
+  border: none;
+  background: transparent;
+  color: var(--color-fg-subtle);
+  cursor: pointer;
+  flex-shrink: 0;
+  transition: background var(--dur-fast) var(--ease-out),
+              color var(--dur-fast) var(--ease-out);
+}
+
+.floating-pill__dismiss:hover {
+  background: rgba(255,255,255,0.08);
+  color: var(--color-fg);
+}
+
+/* ── Done stage — green tint ────────────────────────────────────────── */
+
+.floating-pill--done {
+  border-color: rgba(142, 192, 124, 0.25);
+}
+
+.floating-pill--done .floating-pill__label {
+  color: var(--color-success);
+}
+
+/* ── Error stage — red tint ─────────────────────────────────────────── */
+
+.floating-pill--error {
+  border-color: rgba(251, 73, 52, 0.25);
+}

frontend/src/components/FloatingPill.jsx

@@ -0,0 +1,137 @@
+import React, { useEffect, useRef, useState } from 'react';
+import { X, CheckCircle, AlertCircle } from 'lucide-react';
+import { useAppStore } from '../store';
+import './FloatingPill.css';
+
+/**
+ * FloatingPill — always-on-top status indicator for long-running operations.
+ *
+ * Inspired by VoiceBox 0.5.0's CapturePill. Walks through a state machine
+ * (loading-model → transcribing → translating → generating → done) with a
+ * live elapsed timer, mini progress bar, and dismiss button.
+ *
+ * Reads entirely from the pillSlice in the Zustand store — any part of the
+ * app can trigger it via `useAppStore.getState().showPill(...)`.
+ */
+
+function formatElapsed(ms) {
+  const secs = Math.floor(ms / 1000);
+  const mins = Math.floor(secs / 60);
+  const s = secs % 60;
+  if (mins > 0) return `${mins}:${String(s).padStart(2, '0')}`;
+  return `${s}s`;
+}
+
+const STAGE_LABELS = {
+  'loading-model': '🧠',
+  'recording':     '🎙️',
+  'transcribing':  '📝',
+  'translating':   '🌐',
+  'generating':    '🔊',
+  'exporting':     '📦',
+  'refining':      '✨',
+  'done':          '✅',
+  'error':         '❌',
+};
+
+export default function FloatingPill() {
+  const visible    = useAppStore(s => s.visible);
+  const stage      = useAppStore(s => s.stage);
+  const label      = useAppStore(s => s.label);
+  const progress   = useAppStore(s => s.progress);
+  const startedAt  = useAppStore(s => s.startedAt);
+  const error      = useAppStore(s => s.error);
+  const cancellable = useAppStore(s => s.cancellable);
+  const dismissPill = useAppStore(s => s.dismissPill);
+
+  const [elapsed, setElapsed] = useState(0);
+  const [exiting, setExiting] = useState(false);
+  const timerRef = useRef(null);
+
+  // Elapsed timer
+  useEffect(() => {
+    if (!startedAt || stage === 'done' || stage === 'error' || stage === 'idle') {
+      setElapsed(0);
+      return;
+    }
+    const tick = () => setElapsed(Date.now() - startedAt);
+    tick();
+    timerRef.current = setInterval(tick, 1000);
+    return () => clearInterval(timerRef.current);
+  }, [startedAt, stage]);
+
+  // Handle dismiss with exit animation
+  const handleDismiss = () => {
+    setExiting(true);
+    setTimeout(() => {
+      setExiting(false);
+      dismissPill();
+    }, 250);
+  };
+
+  if (!visible) return null;
+
+  const stageEmoji = STAGE_LABELS[stage] || '⏳';
+  const isDone = stage === 'done';
+  const isError = stage === 'error';
+  const isActive = !isDone && !isError && stage !== 'idle';
+
+  return (
+    <div
+      className={[
+        'floating-pill',
+        exiting ? 'floating-pill--exiting' : '',
+        isDone ? 'floating-pill--done' : '',
+        isError ? 'floating-pill--error' : '',
+      ].filter(Boolean).join(' ')}
+      role="status"
+      aria-live="polite"
+    >
+      {/* Stage indicator dot */}
+      <span className={`floating-pill__dot floating-pill__dot--${stage}`} />
+
+      {/* Content */}
+      <div className="floating-pill__content">
+        <span className="floating-pill__label">
+          {stageEmoji} {label}
+        </span>
+
+        {/* Meta row: timer + progress text */}
+        <div className="floating-pill__meta">
+          {isActive && elapsed > 0 && (
+            <span className="floating-pill__timer">{formatElapsed(elapsed)}</span>
+          )}
+          {progress !== null && isActive && (
+            <span>{Math.round(progress)}%</span>
+          )}
+          {isError && error && (
+            <span className="floating-pill__error" title={error}>{error}</span>
+          )}
+        </div>
+
+        {/* Mini progress bar */}
+        {isActive && (
+          <div className="floating-pill__progress">
+            <div
+              className={[
+                'floating-pill__progress-fill',
+                progress === null ? 'floating-pill__progress-fill--indeterminate' : '',
+              ].filter(Boolean).join(' ')}
+              style={progress !== null ? { width: `${progress}%` } : undefined}
+            />
+          </div>
+        )}
+      </div>
+
+      {/* Dismiss / cancel button */}
+      <button
+        className="floating-pill__dismiss"
+        onClick={handleDismiss}
+        title={cancellable ? 'Cancel' : 'Dismiss'}
+        aria-label={cancellable ? 'Cancel operation' : 'Dismiss status'}
+      >
+        <X size={12} />
+      </button>
+    </div>
+  );
+}

frontend/src/components/Header.jsx

@@ -1,14 +1,15 @@
 import React, { useState } from 'react';
-import { Globe, Fingerprint, Wand2, Film, FolderOpen, RefreshCw, Settings2, ChevronRight, Zap } from 'lucide-react';
+import { Globe, Fingerprint, Wand2, Film, FolderOpen, RefreshCw, Settings2, ChevronRight, Zap, Building2 } from 'lucide-react';
 import { Button, Badge } from '../ui';
 
 const VIEW_META = {
-  launchpad: { label: 'Launchpad',       Icon: Globe,       accent: '#f3a5b6', kicker: 'Studio' },
-  clone:     { label: 'Voice Clone',     Icon: Fingerprint, accent: '#d3869b', kicker: 'Studio' },
-  design:    { label: 'Voice Design',    Icon: Wand2,       accent: '#8ec07c', kicker: 'Studio' },
-  dub:       { label: 'Dubbing',         Icon: Film,        accent: '#fe8019', kicker: 'Studio' },
-  projects:  { label: 'Projects',        Icon: FolderOpen,  accent: '#83a598', kicker: 'Library' },
-  settings:  { label: 'Settings',        Icon: Settings2,   accent: '#fabd2f', kicker: 'Preferences' },
+  launchpad:  { label: 'Launchpad',       Icon: Globe,       accent: '#f3a5b6', kicker: 'Studio' },
+  clone:      { label: 'Voice Clone',     Icon: Fingerprint, accent: '#d3869b', kicker: 'Studio' },
+  design:     { label: 'Voice Design',    Icon: Wand2,       accent: '#8ec07c', kicker: 'Studio' },
+  dub:        { label: 'Dubbing',         Icon: Film,        accent: '#fe8019', kicker: 'Studio' },
+  projects:   { label: 'Projects',        Icon: FolderOpen,  accent: '#83a598', kicker: 'Library' },
+  settings:   { label: 'Settings',        Icon: Settings2,   accent: '#fabd2f', kicker: 'Preferences' },
+  enterprise: { label: 'Commercial License', Icon: Building2, accent: '#fe8019', kicker: 'Licensing' },
 };
 
 function WaveBars({ color = '#f3a5b6', active }) {

frontend/src/components/KeyboardCheatsheet.css

@@ -0,0 +1,64 @@
+/* ═══ Keyboard Cheatsheet Modal ═══ */
+.kcs-overlay {
+  position: fixed; inset: 0; z-index: 9999;
+  background: rgba(0,0,0,0.7);
+  display: flex; align-items: center; justify-content: center; padding: 24px;
+  font-family: var(--font-sans);
+}
+.kcs-panel {
+  width: min(720px, 90vw); max-height: 82vh; overflow: auto;
+  padding: 22px;
+  background: var(--chrome-bg);
+  border: 1px solid var(--chrome-border-strong);
+  border-radius: var(--chrome-radius-pill);
+}
+.kcs-header {
+  display: flex; align-items: center; justify-content: space-between;
+  margin-bottom: 14px;
+}
+.kcs-header__left { display: flex; align-items: center; gap: 10px; }
+.kcs-title {
+  margin: 0; font-family: var(--font-serif); font-style: italic;
+  font-weight: 400; font-size: 1.5rem; color: var(--chrome-fg);
+  letter-spacing: -0.01em;
+}
+.kcs-close {
+  background: none; border: none; color: var(--chrome-fg-muted); cursor: pointer;
+}
+.kcs-grid {
+  display: grid; grid-template-columns: repeat(auto-fit, minmax(260px, 1fr));
+  gap: 18px;
+}
+.kcs-section-title {
+  font-family: var(--font-mono); font-weight: 600;
+  font-size: var(--chrome-label-size);
+  text-transform: uppercase; letter-spacing: var(--chrome-label-track);
+  color: var(--chrome-fg-muted); margin-bottom: 10px; padding-bottom: 6px;
+  border-bottom: 1px solid var(--chrome-border);
+}
+.kcs-items { display: flex; flex-direction: column; gap: 6px; }
+.kcs-row {
+  display: flex; align-items: center; justify-content: space-between;
+  gap: 10px; font-family: var(--font-sans);
+}
+.kcs-desc { color: var(--chrome-fg-muted); font-size: 0.8rem; }
+.kcs-keys { display: flex; gap: 3px; flex-shrink: 0; }
+.kcs-key-group { display: flex; gap: 2px; }
+.kcs-or {
+  color: var(--chrome-fg-dim); align-self: center; font-size: 0.7rem;
+}
+.kcs-kbd {
+  display: inline-flex; align-items: center; gap: 2px;
+  padding: 2px 8px;
+  min-width: 28px; height: 22px;
+  background: var(--chrome-hover-bg);
+  border: 1px solid var(--chrome-border-strong);
+  border-radius: var(--chrome-radius-pill);
+  color: var(--chrome-fg);
+  font-family: var(--font-mono);
+  font-size: 0.7rem; font-weight: 500;
+}
+.kcs-footer {
+  margin-top: 18px; text-align: center;
+  color: var(--chrome-fg-dim); font-family: var(--font-sans); font-size: 0.72rem;
+}

frontend/src/components/KeyboardCheatsheet.jsx

@@ -1,5 +1,6 @@
 import React from 'react';
 import { Command, X } from 'lucide-react';
+import './KeyboardCheatsheet.css';
 
 const SECTIONS = [
   {
@@ -44,85 +45,39 @@ const SECTIONS = [
 ];
 
 function Kbd({ children }) {
-  return (
-    <span style={{
-      display: 'inline-flex', alignItems: 'center', gap: 2,
-      padding: '2px 8px',
-      minWidth: 28, height: 22,
-      background: 'var(--chrome-hover-bg)',
-      border: '1px solid var(--chrome-border-strong)',
-      borderRadius: 'var(--chrome-radius-pill)',
-      color: 'var(--chrome-fg)',
-      fontFamily: 'var(--font-mono)',
-      fontSize: '0.7rem', fontWeight: 500,
-      boxShadow: 'none',
-    }}>
-      {children}
-    </span>
-  );
+  return <span className="kcs-kbd">{children}</span>;
 }
 
 export default function KeyboardCheatsheet({ open, onClose }) {
   if (!open) return null;
   return (
-    <div
-      onClick={onClose}
-      style={{
-        position: 'fixed', inset: 0, zIndex: 9999,
-        background: 'rgba(0,0,0,0.7)',
-        backdropFilter: 'none', WebkitBackdropFilter: 'none',
-        display: 'flex', alignItems: 'center', justifyContent: 'center', padding: 24,
-        fontFamily: 'var(--font-sans)',
-      }}
-    >
-      <div
-        onClick={(e) => e.stopPropagation()}
-        style={{
-          width: 'min(720px, 90vw)', maxHeight: '82vh', overflow: 'auto',
-          padding: 22,
-          background: 'var(--chrome-bg)',
-          border: '1px solid var(--chrome-border-strong)',
-          borderRadius: 'var(--chrome-radius-pill)',
-          boxShadow: 'none',
-        }}
-      >
-        <div style={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', marginBottom: 14 }}>
-          <div style={{ display: 'flex', alignItems: 'center', gap: 10 }}>
+    <div onClick={onClose} className="kcs-overlay">
+      <div onClick={(e) => e.stopPropagation()} className="kcs-panel">
+        <div className="kcs-header">
+          <div className="kcs-header__left">
             <Command size={16} color="var(--chrome-accent)" />
-            <h2 style={{
-              margin: 0, fontFamily: 'var(--font-serif)', fontStyle: 'italic',
-              fontWeight: 400, fontSize: '1.5rem', color: 'var(--chrome-fg)',
-              letterSpacing: '-0.01em',
-            }}>
-              Keyboard shortcuts
-            </h2>
+            <h2 className="kcs-title">Keyboard shortcuts</h2>
           </div>
-          <button onClick={onClose} style={{ background: 'none', border: 'none', color: 'var(--chrome-fg-muted)', cursor: 'pointer' }}>
+          <button onClick={onClose} className="kcs-close">
             <X size={16} />
           </button>
         </div>
 
-        <div style={{ display: 'grid', gridTemplateColumns: 'repeat(auto-fit, minmax(260px, 1fr))', gap: 18 }}>
+        <div className="kcs-grid">
           {SECTIONS.map((sec) => (
             <div key={sec.title}>
-              <div style={{
-                fontFamily: 'var(--font-mono)', fontWeight: 600,
-                fontSize: 'var(--chrome-label-size)',
-                textTransform: 'uppercase', letterSpacing: 'var(--chrome-label-track)',
-                color: 'var(--chrome-fg-muted)', marginBottom: 10, paddingBottom: 6,
-                borderBottom: '1px solid var(--chrome-border)',
-              }}>{sec.title}</div>
-              <div style={{ display: 'flex', flexDirection: 'column', gap: 6 }}>
+              <div className="kcs-section-title">{sec.title}</div>
+              <div className="kcs-items">
                 {sec.items.map(([keys, desc]) => (
-                  <div key={keys} style={{ display: 'flex', alignItems: 'center', justifyContent: 'space-between', gap: 10, fontFamily: 'var(--font-sans)' }}>
-                    <span style={{ color: 'var(--chrome-fg-muted)', fontSize: '0.8rem' }}>{desc}</span>
-                    <span style={{ display: 'flex', gap: 3, flexShrink: 0 }}>
+                  <div key={keys} className="kcs-row">
+                    <span className="kcs-desc">{desc}</span>
+                    <span className="kcs-keys">
                       {keys.split(' / ').map((group, i, arr) => (
                         <React.Fragment key={group}>
-                          <span style={{ display: 'flex', gap: 2 }}>
+                          <span className="kcs-key-group">
                             {group.split('+').map((k) => <Kbd key={k}>{k}</Kbd>)}
                           </span>
-                          {i < arr.length - 1 && <span style={{ color: 'var(--chrome-fg-dim)', alignSelf: 'center', fontSize: '0.7rem' }}>or</span>}
+                          {i < arr.length - 1 && <span className="kcs-or">or</span>}
                         </React.Fragment>
                       ))}
                     </span>
@@ -133,7 +88,7 @@ export default function KeyboardCheatsheet({ open, onClose }) {
           ))}
         </div>
 
-        <div style={{ marginTop: 18, textAlign: 'center', color: 'var(--chrome-fg-dim)', fontFamily: 'var(--font-sans)', fontSize: '0.72rem' }}>
+        <div className="kcs-footer">
           Press <Kbd>?</Kbd> any time to open this.
         </div>
       </div>

frontend/src/components/LogsFooter.css

@@ -62,6 +62,7 @@
   gap: 8px;
   min-width: 0;
   flex: 1;
+  overflow: hidden;
 }
 .logs-footer__title {
   color: #a89984;
@@ -157,11 +158,73 @@
 }
 
 /* Action buttons on the right */
+.logs-footer__right {
+  display: flex;
+  align-items: center;
+  gap: 4px;
+  flex-shrink: 0;
+}
 .logs-footer__actions {
   display: flex;
   align-items: center;
   gap: 2px;
 }
+
+/* Discord button */
+.logs-footer__discord {
+  background: none;
+  border: none;
+  cursor: pointer;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  width: 24px;
+  height: 24px;
+  flex-shrink: 0;
+  border-radius: 4px;
+  color: #7289da;
+  opacity: 0.6;
+  transition: color 0.15s, opacity 0.15s, transform 0.15s;
+}
+.logs-footer__discord:hover {
+  opacity: 1;
+  color: #5865F2;
+  transform: scale(1.1);
+}
+
+/* Glowing donate heart */
+.logs-footer__donate {
+  background: none;
+  border: none;
+  cursor: pointer;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  width: 24px;
+  height: 24px;
+  flex-shrink: 0;
+  border-radius: 4px;
+  color: #d3869b;
+  margin-left: 4px;
+  transition: color 0.15s, transform 0.15s;
+  animation: heart-glow 2.5s ease-in-out infinite;
+}
+.logs-footer__donate:hover {
+  color: #f3a5b6;
+  transform: scale(1.15);
+}
+.logs-footer__donate svg {
+  fill: rgba(211, 134, 155, 0.25);
+  filter: drop-shadow(0 0 4px rgba(211, 134, 155, 0.35));
+}
+.logs-footer__donate:hover svg {
+  fill: rgba(211, 134, 155, 0.5);
+  filter: drop-shadow(0 0 8px rgba(211, 134, 155, 0.6));
+}
+@keyframes heart-glow {
+  0%, 100% { opacity: 0.7; transform: scale(1); }
+  50%      { opacity: 1;   transform: scale(1.08); }
+}
 .logs-footer__icon-btn {
   background: none;
   border: none;

frontend/src/components/LogsFooter.jsx

@@ -1,12 +1,11 @@
 import React, { useCallback, useEffect, useMemo, useRef, useState } from 'react';
 import {
   ChevronUp, ChevronDown, RefreshCw, Trash2, Copy, Bug, X,
-  AlertTriangle, AlertCircle, Info, FileText,
+  AlertTriangle, AlertCircle, Info, FileText, Heart,
 } from 'lucide-react';
 import toast from 'react-hot-toast';
-import {
-  systemLogs, systemLogsTauri, clearSystemLogs, clearTauriLogs,
-} from '../api/system';
+import { clearSystemLogs, clearTauriLogs } from '../api/system';
+import { useSystemLogs, useTauriLogs, useClearLogs, useClearTauriLogs } from '../api/hooks';
 import { getFrontendLogs, clearFrontendLogs } from '../utils/consoleBuffer';
 import { Segmented } from '../ui';
 import { useAppStore } from '../store';
@@ -115,6 +114,32 @@ function SourcePill({ source, counts, active, onClick }) {
   );
 }
 
+// ── Seasonal / random donate heart ──────────────────────────────────────
+// Christmas (Dec), Diwali (~Oct-Nov), Valentine's (Feb), Eid (~Mar-Apr),
+// default pool rotates daily based on day-of-year.
+const HEART_POOL = ['❤️', '🩷', '💜', '💙', '🧡', '💛', '🩵', '💖', '💗'];
+const SEASONAL = [
+  { month: 12, emoji: '🎄',  color: '#e74c3c', title: 'Merry Christmas! Support this project' },
+  { month: 2,  emoji: '💝',  color: '#ff6b81', title: 'Happy Valentine\'s! Support this project' },
+  // Diwali window — roughly Kartik Amavasya (Oct–Nov)
+  { month: 10, emoji: '🪔',  color: '#f5a623', title: 'Happy Diwali! Support this project' },
+  { month: 11, emoji: '✨',  color: '#f5a623', title: 'Happy Diwali! Support this project' },
+];
+
+function DonateHeart() {
+  const now = new Date();
+  const month = now.getMonth() + 1;
+  const dayOfYear = Math.floor((now - new Date(now.getFullYear(), 0, 0)) / 86400000);
+
+  const seasonal = SEASONAL.find(s => s.month === month);
+  if (seasonal) {
+    return <span style={{ fontSize: 14, lineHeight: 1 }} title={seasonal.title}>{seasonal.emoji}</span>;
+  }
+  // Rotate through the pool daily
+  const pick = HEART_POOL[dayOfYear % HEART_POOL.length];
+  return <span style={{ fontSize: 14, lineHeight: 1 }}>{pick}</span>;
+}
+
 export default function LogsFooter() {
   // Always start collapsed on every launch — per-session toggling works
   // but nothing persists. Kill the legacy key on the way out so users
@@ -153,19 +178,22 @@ export default function LogsFooter() {
     };
   }, [collapsed, height]);
 
-  const fetchBackend = useCallback(async () => {
-    try {
-      const r = await systemLogs(300);
-      setLines(prev => ({ ...prev, backend: r.lines || [] }));
-    } catch { /* backend may be warming up — don't spam toasts */ }
-  }, []);
+  // ── TanStack Query for backend + tauri logs ────────────────────────────
+  const backendLogs = useSystemLogs(300, true);
+  const tauriLogs   = useTauriLogs(300, true);
 
-  const fetchTauri = useCallback(async () => {
-    try {
-      const r = await systemLogsTauri(300);
-      setLines(prev => ({ ...prev, tauri: r.lines || [] }));
-    } catch { /* tauri log may not exist in dev */ }
-  }, []);
+  // Sync query data into local state for the rendering pipeline
+  useEffect(() => {
+    if (backendLogs.data) {
+      setLines(prev => ({ ...prev, backend: backendLogs.data.lines || [] }));
+    }
+  }, [backendLogs.data]);
+
+  useEffect(() => {
+    if (tauriLogs.data) {
+      setLines(prev => ({ ...prev, tauri: tauriLogs.data.lines || [] }));
+    }
+  }, [tauriLogs.data]);
 
   const pullFrontend = useCallback(() => {
     const raw = getFrontendLogs();
@@ -177,18 +205,18 @@ export default function LogsFooter() {
 
   const refreshAll = useCallback(async () => {
     setLoading(true);
-    await Promise.all([fetchBackend(), fetchTauri()]);
+    backendLogs.refetch();
+    tauriLogs.refetch();
     pullFrontend();
     setLoading(false);
-  }, [fetchBackend, fetchTauri, pullFrontend]);
+  }, [backendLogs, tauriLogs, pullFrontend]);
 
-  // Poll on a slow interval (badges update without user action), faster
-  // when the panel is open + focused on a source.
+  // Frontend logs still need a local interval (no API, reads from buffer)
   useEffect(() => {
-    refreshAll();
-    const slow = setInterval(refreshAll, collapsed ? 8000 : 3000);
-    return () => clearInterval(slow);
-  }, [refreshAll, collapsed]);
+    pullFrontend();
+    const iv = setInterval(pullFrontend, collapsed ? 8000 : 3000);
+    return () => clearInterval(iv);
+  }, [pullFrontend, collapsed]);
 
   // Auto-scroll to bottom when new lines arrive and panel is open.
   useEffect(() => {
@@ -313,25 +341,43 @@ export default function LogsFooter() {
             />
           ))}
         </div>
-        {!collapsed && (
-          <div className="logs-footer__actions">
-            <button className="logs-footer__icon-btn" onClick={refreshAll} disabled={loading} title="Refresh">
-              <RefreshCw size={12} className={loading ? 'spinner' : ''} />
-            </button>
-            <button className="logs-footer__icon-btn" onClick={onCopy} title="Copy visible log">
-              <Copy size={12} />
-            </button>
-            <button className="logs-footer__icon-btn" onClick={onClear} title="Clear">
-              <Trash2 size={12} />
-            </button>
-            <button className="logs-footer__icon-btn logs-footer__icon-btn--report" onClick={onReportIssue} title="Report issue (copy diagnostic)">
-              <Bug size={12} />
-            </button>
-            <button className="logs-footer__icon-btn" onClick={() => setCollapsed(true)} title="Close">
-              <X size={12} />
-            </button>
-          </div>
-        )}
+        <div className="logs-footer__right">
+          {!collapsed && (
+            <div className="logs-footer__actions">
+              <button className="logs-footer__icon-btn" onClick={refreshAll} disabled={loading} title="Refresh">
+                <RefreshCw size={12} className={loading ? 'spinner' : ''} />
+              </button>
+              <button className="logs-footer__icon-btn" onClick={onCopy} title="Copy visible log">
+                <Copy size={12} />
+              </button>
+              <button className="logs-footer__icon-btn" onClick={onClear} title="Clear">
+                <Trash2 size={12} />
+              </button>
+              <button className="logs-footer__icon-btn logs-footer__icon-btn--report" onClick={onReportIssue} title="Report issue (copy diagnostic)">
+                <Bug size={12} />
+              </button>
+              <button className="logs-footer__icon-btn" onClick={() => setCollapsed(true)} title="Close">
+                <X size={12} />
+              </button>
+            </div>
+          )}
+          <button
+            type="button"
+            className="logs-footer__discord"
+            onClick={() => { import('../api/external').then(m => m.openExternal('https://discord.gg/aRRdVj3de7')); }}
+            title="Join our Discord"
+          >
+            <svg width="14" height="14" viewBox="0 0 24 24" fill="currentColor"><path d="M20.317 4.37a19.791 19.791 0 0 0-4.885-1.515.074.074 0 0 0-.079.037c-.21.375-.444.864-.608 1.25a18.27 18.27 0 0 0-5.487 0 12.64 12.64 0 0 0-.617-1.25.077.077 0 0 0-.079-.037A19.736 19.736 0 0 0 3.677 4.37a.07.07 0 0 0-.032.027C.533 9.046-.32 13.58.099 18.057a.082.082 0 0 0 .031.057 19.9 19.9 0 0 0 5.993 3.03.078.078 0 0 0 .084-.028c.462-.63.874-1.295 1.226-1.994a.076.076 0 0 0-.041-.106 13.107 13.107 0 0 1-1.872-.892.077.077 0 0 1-.008-.128 10.2 10.2 0 0 0 .372-.292.074.074 0 0 1 .077-.01c3.928 1.793 8.18 1.793 12.062 0a.074.074 0 0 1 .078.01c.12.098.246.198.373.292a.077.077 0 0 1-.006.127 12.299 12.299 0 0 1-1.873.892.077.077 0 0 0-.041.107c.36.698.772 1.362 1.225 1.993a.076.076 0 0 0 .084.028 19.839 19.839 0 0 0 6.002-3.03.077.077 0 0 0 .032-.054c.5-5.177-.838-9.674-3.549-13.66a.061.061 0 0 0-.031-.03zM8.02 15.33c-1.183 0-2.157-1.085-2.157-2.419 0-1.333.956-2.419 2.157-2.419 1.21 0 2.176 1.096 2.157 2.42 0 1.333-.956 2.418-2.157 2.418zm7.975 0c-1.183 0-2.157-1.085-2.157-2.419 0-1.333.956-2.419 2.157-2.419 1.21 0 2.176 1.096 2.157 2.42 0 1.333-.947 2.418-2.157 2.418z"/></svg>
+          </button>
+          <button
+            type="button"
+            className="logs-footer__donate"
+            onClick={() => useAppStore.getState().setMode?.('donate')}
+            title="Support this project"
+          >
+            <DonateHeart />
+          </button>
+        </div>
       </div>
 
       {!collapsed && (

frontend/src/components/Misc.css

@@ -0,0 +1,78 @@
+/* ═══ CheckpointBanner extracted styles ═══ */
+.ckpt-banner {
+  display: flex; align-items: center; gap: 10px;
+  padding: 8px 12px; margin-bottom: 6px;
+  border-radius: var(--chrome-radius-pill);
+  background: var(--chrome-bg);
+  border: 1px solid var(--chrome-border);
+}
+.ckpt-icon { flex-shrink: 0; }
+.ckpt-body { flex: 1; min-width: 0; display: flex; flex-direction: column; gap: 1px; }
+.ckpt-head { display: flex; align-items: baseline; gap: 6px; }
+.ckpt-title {
+  font-family: var(--chrome-font-mono);
+  font-size: var(--chrome-label-size);
+  letter-spacing: var(--chrome-label-track);
+  text-transform: uppercase;
+  font-weight: 600;
+  color: var(--chrome-fg);
+}
+.ckpt-count {
+  font-family: var(--chrome-font-mono);
+  font-size: var(--chrome-label-size);
+  color: var(--chrome-fg-muted);
+  font-variant-numeric: tabular-nums;
+}
+.ckpt-hint { font-size: 0.64rem; color: var(--chrome-fg-muted); line-height: 1.35; }
+
+/* ═══ DirectionDialog extracted styles ═══ */
+.dir-preview-actions { display: flex; gap: 8px; align-items: center; margin-top: 8px; }
+.dir-clear-btn { margin-right: auto; }
+.dir-rate-up { color: var(--color-brand); }
+.dir-rate-down { color: var(--color-info); }
+.dir-error { color: var(--color-warn); font-size: 0.7rem; }
+
+/* ═══ SetupWizard preflight extracted styles ═══ */
+.swiz-loading {
+  display: flex; gap: 8px; align-items: center;
+  justify-content: center; padding: 20px;
+  color: var(--color-fg-muted);
+}
+.swiz-checklist { display: flex; flex-direction: column; gap: 6px; }
+.swiz-check-icon { flex-shrink: 0; padding-top: 2px; }
+.swiz-check-footer { display: flex; justify-content: flex-end; padding-top: 4px; }
+.swiz-missing { text-align: center; font-size: 0.78rem; margin: 0; }
+.swiz-status-loading {
+  display: flex; gap: 8px; align-items: center;
+  justify-content: center; color: var(--color-fg-muted);
+}
+
+/* ═══ App.jsx startup / wizard extracted styles ═══ */
+.app-startup {
+  display: flex; align-items: center; justify-content: center;
+  min-height: 100vh; flex-direction: column; gap: 12px;
+  color: #a89984; font-size: 13px;
+}
+.app-startup__title { font-size: 18px; color: #ebdbb2; }
+.app-wizard-wrap {
+  min-height: calc(100vh - var(--logs-footer-height, 28px));
+  max-height: calc(100vh - var(--logs-footer-height, 28px));
+  width: 100%; overflow: hidden;
+  background: var(--color-bg, #1d2021);
+  position: relative; display: flex; flex-direction: column;
+}
+.app-wizard-dragstrip {
+  position: fixed; top: 0; left: 0; right: 0;
+  height: 28px; z-index: 10;
+}
+.app-lazy-fallback { padding: 12px; color: #6b6657; font-size: 0.7rem; }
+
+/* ═══ CompareModal extracted ═══ */
+.compare-textarea--noresize { resize: none; }
+
+/* ═══ AudioTrimmer play button ═══ */
+.audio-trimmer__play-btn {
+  color: var(--color-success);
+  border-color: rgba(142,192,124,0.3);
+  background: rgba(142,192,124,0.08);
+}

frontend/src/components/MultiLangPicker.css

@@ -0,0 +1,148 @@
+.multi-lang {
+  position: relative;
+}
+.multi-lang__chips {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 4px;
+  align-items: center;
+  min-height: 28px;
+}
+.multi-lang__chip {
+  display: inline-flex;
+  align-items: center;
+  gap: 4px;
+  padding: 2px 8px;
+  background: var(--chrome-hover-bg);
+  border: 1px solid var(--chrome-border);
+  border-radius: 999px;
+  font-family: var(--font-mono);
+  font-size: 0.68rem;
+  font-weight: 500;
+  color: var(--chrome-fg);
+  text-transform: uppercase;
+}
+.multi-lang__chip-x {
+  background: none;
+  border: none;
+  color: var(--chrome-fg-muted);
+  cursor: pointer;
+  padding: 0;
+  display: flex;
+  align-items: center;
+  border-radius: 999px;
+  transition: color 0.15s;
+}
+.multi-lang__chip-x:hover {
+  color: var(--color-danger);
+}
+.multi-lang__add {
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  width: 24px;
+  height: 24px;
+  border-radius: 999px;
+  border: 1px dashed var(--chrome-border);
+  background: none;
+  color: var(--chrome-fg-muted);
+  cursor: pointer;
+  transition: all 0.15s;
+}
+.multi-lang__add:hover {
+  background: var(--chrome-hover-bg);
+  color: var(--chrome-fg);
+  border-style: solid;
+}
+.multi-lang__summary {
+  font-family: var(--font-mono);
+  font-size: 0.62rem;
+  color: var(--chrome-fg-dim);
+  margin-top: 4px;
+}
+
+/* Dropdown */
+.multi-lang__drop {
+  position: absolute;
+  top: 100%;
+  left: 0;
+  right: 0;
+  z-index: var(--z-overlay);
+  margin-top: 4px;
+  background: var(--chrome-bg);
+  border: 1px solid var(--chrome-border-strong);
+  border-radius: 8px;
+  box-shadow: 0 8px 24px rgba(0,0,0,0.35);
+  max-height: 260px;
+  display: flex;
+  flex-direction: column;
+  overflow: hidden;
+  animation: mlp-in 0.15s ease-out;
+}
+@keyframes mlp-in {
+  from { opacity: 0; transform: translateY(-4px); }
+  to   { opacity: 1; transform: translateY(0); }
+}
+.multi-lang__search {
+  display: flex;
+  align-items: center;
+  gap: 6px;
+  padding: 8px 10px;
+  border-bottom: 1px solid var(--chrome-border);
+  color: var(--chrome-fg-muted);
+}
+.multi-lang__search input {
+  flex: 1;
+  background: none;
+  border: none;
+  outline: none;
+  color: var(--chrome-fg);
+  font-family: var(--font-sans);
+  font-size: 0.78rem;
+}
+.multi-lang__list {
+  overflow-y: auto;
+  flex: 1;
+  padding: 4px 0;
+}
+.multi-lang__section {
+  font-family: var(--font-mono);
+  font-size: 0.62rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.04em;
+  color: var(--chrome-fg-dim);
+  padding: 6px 10px 2px;
+}
+.multi-lang__option {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  width: 100%;
+  padding: 5px 10px;
+  background: none;
+  border: none;
+  color: var(--chrome-fg);
+  font-family: var(--font-sans);
+  font-size: 0.76rem;
+  cursor: pointer;
+  text-align: left;
+  transition: background 0.1s;
+}
+.multi-lang__option:hover {
+  background: var(--chrome-hover-bg);
+}
+.multi-lang__option-code {
+  font-family: var(--font-mono);
+  font-size: 0.68rem;
+  color: var(--chrome-accent);
+  min-width: 28px;
+  font-weight: 600;
+}
+.multi-lang__more,
+.multi-lang__empty {
+  padding: 8px 10px;
+  font-size: 0.7rem;
+  color: var(--chrome-fg-dim);
+  text-align: center;
+}

frontend/src/components/MultiLangPicker.jsx

@@ -0,0 +1,159 @@
+import React, { useState, useMemo, useRef, useEffect } from 'react';
+import { X, Search, Globe, Plus } from 'lucide-react';
+import { POPULAR_LANGS } from '../utils/constants';
+import { LANG_CODES } from '../utils/languages';
+import './MultiLangPicker.css';
+
+/**
+ * MultiLangPicker — chip-based multi-language selector for batch dubbing.
+ *
+ * Shows selected languages as removable badges. Click "+" to open a
+ * searchable dropdown with Popular + All Languages sections.
+ */
+export default function MultiLangPicker({
+  selected = [],         // array of { lang: string, code: string }
+  onChange,              // (newSelected) => void
+  disabled = false,
+}) {
+  const [dropOpen, setDropOpen] = useState(false);
+  const [query, setQuery] = useState('');
+  const dropRef = useRef(null);
+  const inputRef = useRef(null);
+
+  // Close dropdown on outside click
+  useEffect(() => {
+    if (!dropOpen) return;
+    const handler = (e) => {
+      if (dropRef.current && !dropRef.current.contains(e.target)) setDropOpen(false);
+    };
+    document.addEventListener('mousedown', handler);
+    return () => document.removeEventListener('mousedown', handler);
+  }, [dropOpen]);
+
+  // Focus search when dropdown opens
+  useEffect(() => {
+    if (dropOpen && inputRef.current) inputRef.current.focus();
+  }, [dropOpen]);
+
+  const selectedCodes = useMemo(() => new Set(selected.map(s => s.code)), [selected]);
+
+  const addLang = (lang, code) => {
+    if (selectedCodes.has(code)) return;
+    onChange([...selected, { lang, code }]);
+    setQuery('');
+  };
+
+  const removeLang = (code) => {
+    onChange(selected.filter(s => s.code !== code));
+  };
+
+  const filteredLangs = useMemo(() => {
+    const q = query.toLowerCase().trim();
+    return LANG_CODES.filter(lc =>
+      !selectedCodes.has(lc.code) &&
+      (!q || lc.label.toLowerCase().includes(q) || lc.code.toLowerCase().includes(q))
+    );
+  }, [query, selectedCodes]);
+
+  const popularFiltered = useMemo(() => {
+    const q = query.toLowerCase().trim();
+    return POPULAR_LANGS
+      .map(lang => {
+        const match = LANG_CODES.find(lc => lc.label.toLowerCase() === lang.toLowerCase());
+        return match ? { lang, code: match.code } : null;
+      })
+      .filter(item => item && !selectedCodes.has(item.code) && (!q || item.lang.toLowerCase().includes(q) || item.code.includes(q)));
+  }, [query, selectedCodes]);
+
+  return (
+    <div className="multi-lang" ref={dropRef}>
+      <div className="multi-lang__chips">
+        {selected.map(s => (
+          <span key={s.code} className="multi-lang__chip">
+            <Globe size={9} />
+            <span>{s.code}</span>
+            {!disabled && (
+              <button
+                type="button"
+                className="multi-lang__chip-x"
+                onClick={() => removeLang(s.code)}
+                aria-label={`Remove ${s.lang}`}
+              >
+                <X size={8} />
+              </button>
+            )}
+          </span>
+        ))}
+        {!disabled && (
+          <button
+            type="button"
+            className="multi-lang__add"
+            onClick={() => setDropOpen(!dropOpen)}
+            title="Add language"
+          >
+            <Plus size={10} />
+          </button>
+        )}
+      </div>
+
+      {selected.length > 0 && (
+        <div className="multi-lang__summary">
+          {selected.length} language{selected.length > 1 ? 's' : ''} selected
+        </div>
+      )}
+
+      {dropOpen && (
+        <div className="multi-lang__drop">
+          <div className="multi-lang__search">
+            <Search size={10} />
+            <input
+              ref={inputRef}
+              value={query}
+              onChange={e => setQuery(e.target.value)}
+              placeholder="Search languages…"
+              spellCheck={false}
+            />
+          </div>
+          <div className="multi-lang__list">
+            {popularFiltered.length > 0 && (
+              <>
+                <div className="multi-lang__section">Popular</div>
+                {popularFiltered.map(item => (
+                  <button
+                    key={item.code}
+                    type="button"
+                    className="multi-lang__option"
+                    onClick={() => addLang(item.lang, item.code)}
+                  >
+                    <span className="multi-lang__option-code">{item.code}</span>
+                    <span>{item.lang}</span>
+                  </button>
+                ))}
+              </>
+            )}
+            <div className="multi-lang__section">All Languages</div>
+            {filteredLangs.slice(0, 50).map(lc => (
+              <button
+                key={lc.code}
+                type="button"
+                className="multi-lang__option"
+                onClick={() => addLang(lc.label, lc.code)}
+              >
+                <span className="multi-lang__option-code">{lc.code}</span>
+                <span>{lc.label}</span>
+              </button>
+            ))}
+            {filteredLangs.length > 50 && (
+              <div className="multi-lang__more">
+                +{filteredLangs.length - 50} more — type to narrow
+              </div>
+            )}
+            {filteredLangs.length === 0 && popularFiltered.length === 0 && (
+              <div className="multi-lang__empty">No matches</div>
+            )}
+          </div>
+        </div>
+      )}
+    </div>
+  );
+}

frontend/src/components/NavRail.jsx

@@ -1,6 +1,7 @@
 import React from 'react';
 import {
   Globe, Fingerprint, Wand2, Film, FolderOpen, Settings2, ArrowLeftRight,
+  Library,
 } from 'lucide-react';
 
 const ITEMS = [
@@ -8,6 +9,7 @@ const ITEMS = [
   { id: 'clone',     label: 'Clone',     Icon: Fingerprint, accent: '#d3869b' },
   { id: 'design',    label: 'Design',    Icon: Wand2,       accent: '#8ec07c' },
   { id: 'dub',       label: 'Dub',       Icon: Film,        accent: '#fe8019' },
+  { id: 'gallery',   label: 'Gallery',   Icon: Library,     accent: '#b8bb26' },
   { id: 'projects',  label: 'Projects',  Icon: FolderOpen,  accent: '#83a598' },
 ];
 const FOOTER_ITEMS = [

frontend/src/components/ReadinessChecklist.css

@@ -0,0 +1,112 @@
+/* ── Readiness Checklist ────────────────────────────────────────────────
+   VoiceBox-style system readiness panel showing pass/warn/fail gates
+   for ASR model, TTS engine, LLM, ffmpeg, GPU, etc.
+   ─────────────────────────────────────────────────────────────────────── */
+
+.readiness-checklist {
+  display: flex;
+  flex-direction: column;
+  gap: var(--space-3);
+  padding: var(--space-5);
+  background: var(--color-bg-elev-1);
+  backdrop-filter: var(--glass-blur-sm);
+  -webkit-backdrop-filter: var(--glass-blur-sm);
+  border: 1px solid var(--color-border);
+  border-radius: var(--radius-lg);
+  font-family: var(--font-ui);
+  font-size: var(--text-sm);
+}
+
+.readiness-checklist__title {
+  font-weight: var(--weight-semibold);
+  font-size: var(--text-md);
+  color: var(--color-fg);
+  margin: 0 0 var(--space-2) 0;
+  display: flex;
+  align-items: center;
+  gap: var(--space-3);
+}
+
+.readiness-checklist__title-icon {
+  font-size: var(--text-lg);
+}
+
+.readiness-checklist__list {
+  list-style: none;
+  margin: 0;
+  padding: 0;
+  display: flex;
+  flex-direction: column;
+  gap: var(--space-2);
+}
+
+.readiness-checklist__item {
+  display: flex;
+  align-items: flex-start;
+  gap: var(--space-3);
+  padding: var(--space-2) var(--space-3);
+  border-radius: var(--radius-sm);
+  transition: background var(--dur-fast) var(--ease-out);
+}
+
+.readiness-checklist__item:hover {
+  background: var(--color-bg-elev-3);
+}
+
+/* ── Status icons ───────────────────────────────────────────────────── */
+
+.readiness-checklist__status {
+  flex-shrink: 0;
+  width: 16px;
+  height: 16px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  margin-top: 1px;
+}
+
+.readiness-checklist__status--pass { color: var(--color-success); }
+.readiness-checklist__status--warn { color: var(--color-accent); }
+.readiness-checklist__status--fail { color: var(--color-danger); }
+.readiness-checklist__status--loading {
+  color: var(--color-fg-subtle);
+  animation: rc-spin 1s linear infinite;
+}
+
+@keyframes rc-spin {
+  to { transform: rotate(360deg); }
+}
+
+/* ── Content ────────────────────────────────────────────────────────── */
+
+.readiness-checklist__label {
+  font-weight: var(--weight-medium);
+  color: var(--color-fg);
+}
+
+.readiness-checklist__detail {
+  font-size: var(--text-xs);
+  color: var(--color-fg-muted);
+  margin-top: 1px;
+}
+
+.readiness-checklist__fix {
+  font-size: var(--text-xs);
+  color: var(--color-accent);
+  margin-top: 2px;
+}
+
+/* ── Compact summary when all pass ──────────────────────────────────── */
+
+.readiness-checklist__all-pass {
+  display: flex;
+  align-items: center;
+  gap: var(--space-3);
+  padding: var(--space-3) var(--space-4);
+  background: rgba(142, 192, 124, 0.08);
+  border: 1px solid rgba(142, 192, 124, 0.15);
+  border-radius: var(--radius-md);
+  color: var(--color-success);
+  font-weight: var(--weight-medium);
+  font-size: var(--text-sm);
+}

frontend/src/components/ReadinessChecklist.jsx

@@ -0,0 +1,155 @@
+import React from 'react';
+import { CheckCircle, AlertTriangle, XCircle, Loader } from 'lucide-react';
+import { usePreflight, useModelStatus } from '../api/hooks';
+import './ReadinessChecklist.css';
+
+/**
+ * ReadinessChecklist — VoiceBox-style system readiness panel.
+ *
+ * Consumes the existing /setup/preflight endpoint (OS, RAM, GPU, ffmpeg,
+ * yt-dlp, network) plus /model/status, and renders a compact pass/warn/fail
+ * checklist. Mirrors into Settings and renders as empty-state on the
+ * launchpad when no project is loaded.
+ *
+ * Hides itself when all gates are green (user doesn't need to see
+ * "everything is fine" every time they open the app).
+ */
+
+const StatusIcon = ({ status, size = 14 }) => {
+  switch (status) {
+    case 'pass':    return <CheckCircle size={size} />;
+    case 'warn':    return <AlertTriangle size={size} />;
+    case 'fail':    return <XCircle size={size} />;
+    case 'loading': return <Loader size={size} />;
+    default:        return <Loader size={size} />;
+  }
+};
+
+export default function ReadinessChecklist({ compact = false, showWhenAllPass = false }) {
+  const { data: preflight, isLoading: preflightLoading } = usePreflight();
+  const { data: modelData, isLoading: modelLoading } = useModelStatus();
+
+  const isLoading = preflightLoading || modelLoading;
+  const modelStatus = modelData?.status ?? 'idle';
+
+  // Build the checklist from preflight data + model status
+  const checks = [];
+
+  // Model readiness (from /model/status)
+  const modelCheck = {
+    id: 'asr-model',
+    label: 'ASR Model',
+    status: modelStatus === 'ready' ? 'pass'
+      : modelStatus === 'loading' ? 'loading'
+      : modelStatus === 'error' ? 'fail'
+      : 'warn',
+    detail: modelStatus === 'ready' ? 'Loaded and ready'
+      : modelStatus === 'loading' ? 'Loading… (this may take 1-2 minutes on first run)'
+      : modelStatus === 'error' ? 'Failed to load'
+      : 'Not loaded yet — will load on first transcription',
+    fix: modelStatus === 'error' ? 'Check logs for model loading errors. Try restarting.' : null,
+  };
+  checks.push(modelCheck);
+
+  // Add preflight checks
+  if (preflight?.checks) {
+    // Filter to the most relevant checks for the checklist
+    const relevant = ['gpu', 'ffmpeg', 'yt-dlp', 'ram'];
+    for (const check of preflight.checks) {
+      if (relevant.includes(check.id)) {
+        checks.push(check);
+      }
+    }
+  }
+
+  // LLM configuration (check for translate endpoint)
+  const llmCheck = {
+    id: 'llm',
+    label: 'LLM (Cinematic)',
+    status: 'warn',
+    detail: 'Configure TRANSLATE_BASE_URL for Cinematic translation quality',
+    fix: 'Set TRANSLATE_BASE_URL and TRANSLATE_API_KEY environment variables. Works with Ollama, OpenAI, LM Studio, etc.',
+  };
+  // If we have preflight and there's a network check passing, LLM is at least possible
+  if (preflight?.checks) {
+    const netCheck = preflight.checks.find(c => c.id === 'network');
+    if (netCheck?.status === 'pass') {
+      llmCheck.detail = 'Optional — set TRANSLATE_BASE_URL for Cinematic quality';
+    }
+  }
+  checks.push(llmCheck);
+
+  // Determine if all critical checks pass
+  const allPass = checks.every(c => c.status === 'pass' || c.status === 'warn');
+  const anyFail = checks.some(c => c.status === 'fail');
+  const criticalFails = checks.filter(c => c.status === 'fail');
+
+  // Hide when everything is fine (unless explicitly asked to show)
+  if (!showWhenAllPass && allPass && !isLoading) return null;
+
+  if (isLoading) {
+    return (
+      <div className="readiness-checklist">
+        <div className="readiness-checklist__title">
+          <span className="readiness-checklist__title-icon">🔍</span>
+          Checking system…
+        </div>
+      </div>
+    );
+  }
+
+  if (compact) {
+    // Compact mode: just show failing/warning items
+    const issues = checks.filter(c => c.status !== 'pass');
+    if (issues.length === 0) {
+      return (
+        <div className="readiness-checklist__all-pass">
+          <CheckCircle size={14} />
+          All systems ready
+        </div>
+      );
+    }
+    return (
+      <div className="readiness-checklist">
+        <ul className="readiness-checklist__list">
+          {issues.map(check => (
+            <li key={check.id} className="readiness-checklist__item">
+              <span className={`readiness-checklist__status readiness-checklist__status--${check.status}`}>
+                <StatusIcon status={check.status} />
+              </span>
+              <div>
+                <div className="readiness-checklist__label">{check.label}</div>
+                {check.fix && <div className="readiness-checklist__fix">{check.fix}</div>}
+              </div>
+            </li>
+          ))}
+        </ul>
+      </div>
+    );
+  }
+
+  return (
+    <div className="readiness-checklist">
+      <div className="readiness-checklist__title">
+        <span className="readiness-checklist__title-icon">
+          {anyFail ? '⚠️' : '✅'}
+        </span>
+        System Readiness
+      </div>
+      <ul className="readiness-checklist__list">
+        {checks.map(check => (
+          <li key={check.id} className="readiness-checklist__item">
+            <span className={`readiness-checklist__status readiness-checklist__status--${check.status}`}>
+              <StatusIcon status={check.status} />
+            </span>
+            <div>
+              <div className="readiness-checklist__label">{check.label}</div>
+              <div className="readiness-checklist__detail">{check.detail}</div>
+              {check.fix && <div className="readiness-checklist__fix">💡 {check.fix}</div>}
+            </div>
+          </li>
+        ))}
+      </ul>
+    </div>
+  );
+}

frontend/src/components/Sidebar.css

@@ -111,6 +111,11 @@
 .sidebar__empty-title  { font-size: 0.82rem; margin: 0 0 var(--space-2); color: var(--chrome-fg); font-weight: 500; letter-spacing: 0.02em; }
 .sidebar__empty-sub    { font-size: 0.7rem; margin: 0; color: var(--chrome-fg-dim); line-height: 1.5; }
 
+/* Hide text-heavy blocks when sidebar is collapsed to icon-only width */
+.sidebar.is-collapsed .sidebar__empty     { display: none; }
+.sidebar.is-collapsed .sidebar__subtitle  { display: none; }
+.sidebar.is-collapsed .sidebar__search    { display: none; }
+
 /* Section label — matches the status-bar's "LOGS" uppercase treatment.
    Labels are displays (not buttons) but this one IS clickable (collapses
    the section), so the chevron on the right signals interactivity while

frontend/src/components/Sidebar.jsx

@@ -44,6 +44,7 @@ export default function Sidebar(props) {
     saveProject, loadProject, deleteProject,
     handleSelectProfile, handleDeleteProfile, handleOpenVoiceProfile,
     handleUnlockProfile, handleLockProfile, handlePreviewVoice,
+    onOpenVoicePreview,
     restoreHistory, restoreDubHistory,
     handleSaveHistoryAsProfile,
     handleNativeExport, revealInFolder,
@@ -260,6 +261,15 @@ export default function Sidebar(props) {
                               <button className="history-action-btn" onClick={(e) => { e.stopPropagation(); handleSelectProfile(proj); }}>
                                 <Check size={10} /> Select
                               </button>
+                              {onOpenVoicePreview && (
+                                <button
+                                  className="history-action-btn accent"
+                                  onClick={(e) => { e.stopPropagation(); onOpenVoicePreview(proj.id); }}
+                                  title="Open interactive voice preview"
+                                >
+                                  <Volume2 size={10} /> Try
+                                </button>
+                              )}
                               {proj.is_locked ? (
                                 <button className="history-action-btn accent history-action-icon" onClick={(e) => { e.stopPropagation(); handleUnlockProfile(proj.id); }} title="Unlock">
                                   <Unlock size={10} />

frontend/src/components/VoicePreview.css

@@ -0,0 +1,90 @@
+.voice-preview {
+  position: fixed;
+  bottom: 56px;
+  right: 16px;
+  z-index: 900;
+  width: 320px;
+  background: var(--chrome-bg);
+  border: 1px solid var(--chrome-border-strong);
+  border-radius: 12px;
+  box-shadow: 0 8px 32px rgba(0,0,0,0.4);
+  display: flex;
+  flex-direction: column;
+  overflow: hidden;
+  animation: voice-preview-in 0.2s ease-out;
+}
+@keyframes voice-preview-in {
+  from { opacity: 0; transform: translateY(12px) scale(0.96); }
+  to   { opacity: 1; transform: translateY(0) scale(1); }
+}
+
+.voice-preview__head {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  padding: 10px 14px;
+  border-bottom: 1px solid var(--chrome-border);
+}
+.voice-preview__title {
+  display: flex;
+  align-items: center;
+  gap: 6px;
+  font-family: var(--font-mono);
+  font-size: 0.72rem;
+  font-weight: 600;
+  text-transform: uppercase;
+  letter-spacing: 0.04em;
+  color: var(--chrome-fg);
+}
+.voice-preview__close {
+  background: none;
+  border: none;
+  color: var(--chrome-fg-muted);
+  cursor: pointer;
+  padding: 4px;
+  border-radius: 6px;
+  transition: background 0.15s;
+}
+.voice-preview__close:hover {
+  background: var(--chrome-hover-bg);
+  color: var(--chrome-fg);
+}
+
+.voice-preview__body {
+  padding: 12px 14px;
+  display: flex;
+  flex-direction: column;
+  gap: 8px;
+}
+.voice-preview__select {
+  font-size: 0.78rem;
+  padding: 6px 8px;
+}
+.voice-preview__text {
+  font-size: 0.78rem;
+  padding: 8px;
+  resize: none;
+  line-height: 1.4;
+  min-height: 48px;
+}
+.voice-preview__audio {
+  width: 100%;
+  height: 32px;
+  border-radius: 6px;
+}
+.voice-preview__audio::-webkit-media-controls-panel {
+  background: var(--chrome-hover-bg);
+}
+
+.voice-preview__foot {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  padding: 8px 14px 10px;
+  border-top: 1px solid var(--chrome-border);
+}
+.voice-preview__hint {
+  font-family: var(--font-mono);
+  font-size: 0.65rem;
+  color: var(--chrome-fg-dim);
+}

frontend/src/components/VoicePreview.jsx

@@ -0,0 +1,194 @@
+import React, { useState, useRef, useCallback } from 'react';
+import { Volume2, Play, Square, Loader, X, Mic } from 'lucide-react';
+import { generateSpeech } from '../api/generate';
+import { PRESETS } from '../utils/constants';
+import { Button } from '../ui';
+import './VoicePreview.css';
+
+/**
+ * VoicePreview — floating "try a voice" card.
+ *
+ * Opens as a bottom-right popover. User picks a voice profile, types a
+ * sentence, hits Play → hears TTS output instantly (8 inference steps for
+ * speed). The result is disposable — it doesn't save to history.
+ */
+const DEFAULT_TEXT = 'Hello! This is a preview of how I sound in this voice.';
+
+export default function VoicePreview({
+  open,
+  onClose,
+  profiles = [],
+  initialProfileId = '',
+  fileToMediaUrl,
+}) {
+  const [text, setText] = useState(DEFAULT_TEXT);
+  const [voiceId, setVoiceId] = useState(initialProfileId);
+  const [audioUrl, setAudioUrl] = useState(null);
+  const [loading, setLoading] = useState(false);
+  const [playing, setPlaying] = useState(false);
+  const audioRef = useRef(null);
+  const abortRef = useRef(null);
+
+  // Sync initialProfileId when it changes (e.g. clicking preview on a different profile)
+  React.useEffect(() => {
+    if (initialProfileId) setVoiceId(initialProfileId);
+  }, [initialProfileId]);
+
+  const handleGenerate = useCallback(async () => {
+    if (!text.trim()) return;
+    setLoading(true);
+    setAudioUrl(null);
+
+    const ac = new AbortController();
+    abortRef.current = ac;
+
+    try {
+      const fd = new FormData();
+      fd.append('text', text);
+      fd.append('num_step', '8');         // fast preview
+      fd.append('guidance_scale', '2.0');
+      fd.append('speed', '1.0');
+      fd.append('denoise', 'true');
+      fd.append('postprocess_output', 'true');
+
+      let profileId = voiceId;
+      let instruct = '';
+
+      if (profileId.startsWith('preset:')) {
+        const pr = PRESETS.find(p => p.id === profileId.replace('preset:', ''));
+        if (pr) {
+          instruct = Object.values(pr.attrs).filter(v => v !== 'Auto').join(', ');
+        }
+        profileId = '';
+      } else {
+        const match = profiles.find(p => p.id === profileId);
+        if (match?.instruct) instruct = match.instruct;
+      }
+
+      if (profileId) fd.append('profile_id', profileId);
+      if (instruct) fd.append('instruct', instruct);
+
+      const res = await generateSpeech(fd, { signal: ac.signal });
+      if (!res.ok) throw new Error(`TTS failed: ${res.status}`);
+
+      const blob = await res.blob();
+      const urls = await fileToMediaUrl(blob, null);
+      setAudioUrl(urls.audioUrl);
+
+      // Auto-play
+      setTimeout(() => {
+        if (audioRef.current) {
+          audioRef.current.play().catch(() => {});
+        }
+      }, 50);
+    } catch (err) {
+      if (err.name !== 'AbortError') {
+        console.error('Preview generation failed:', err);
+      }
+    } finally {
+      setLoading(false);
+    }
+  }, [text, voiceId, profiles, fileToMediaUrl]);
+
+  const handleStop = () => {
+    abortRef.current?.abort();
+    if (audioRef.current) {
+      audioRef.current.pause();
+      audioRef.current.currentTime = 0;
+    }
+    setPlaying(false);
+    setLoading(false);
+  };
+
+  if (!open) return null;
+
+  return (
+    <div className="voice-preview">
+      <div className="voice-preview__head">
+        <span className="voice-preview__title">
+          <Volume2 size={13} /> Voice Preview
+        </span>
+        <button
+          type="button"
+          className="voice-preview__close"
+          onClick={onClose}
+          aria-label="Close preview"
+        >
+          <X size={12} />
+        </button>
+      </div>
+
+      <div className="voice-preview__body">
+        <select
+          className="input-base voice-preview__select"
+          value={voiceId}
+          onChange={e => setVoiceId(e.target.value)}
+        >
+          <option value="">Default voice</option>
+          {profiles.filter(p => !p.instruct).length > 0 && (
+            <optgroup label="Clone Profiles">
+              {profiles.filter(p => !p.instruct).map(p => (
+                <option key={p.id} value={p.id}>{p.name}</option>
+              ))}
+            </optgroup>
+          )}
+          {profiles.filter(p => !!p.instruct).length > 0 && (
+            <optgroup label="Designed Voices">
+              {profiles.filter(p => !!p.instruct).map(p => (
+                <option key={p.id} value={p.id}>{p.name}</option>
+              ))}
+            </optgroup>
+          )}
+          {PRESETS.length > 0 && (
+            <optgroup label="Presets">
+              {PRESETS.map(p => (
+                <option key={p.id} value={`preset:${p.id}`}>{p.name}</option>
+              ))}
+            </optgroup>
+          )}
+        </select>
+
+        <textarea
+          className="input-base voice-preview__text"
+          value={text}
+          onChange={e => setText(e.target.value)}
+          rows={2}
+          placeholder="Type something to hear…"
+          spellCheck={false}
+        />
+
+        {audioUrl && (
+          <audio
+            ref={audioRef}
+            src={audioUrl}
+            className="voice-preview__audio"
+            controls
+            onPlay={() => setPlaying(true)}
+            onPause={() => setPlaying(false)}
+            onEnded={() => setPlaying(false)}
+          />
+        )}
+      </div>
+
+      <div className="voice-preview__foot">
+        {loading ? (
+          <Button variant="ghost" size="sm" onClick={handleStop} leading={<Square size={10} />}>
+            Stop
+          </Button>
+        ) : (
+          <Button
+            variant="primary"
+            size="sm"
+            onClick={handleGenerate}
+            disabled={!text.trim()}
+            loading={loading}
+            leading={!loading && <Play size={10} />}
+          >
+            {audioUrl ? 'Regenerate' : 'Preview'}
+          </Button>
+        )}
+        <span className="voice-preview__hint">8 steps · fast preview</span>
+      </div>
+    </div>
+  );
+}

frontend/src/components/WaveformErrorBoundary.css

@@ -0,0 +1,69 @@
+/* ═══ WaveformTimeline extracted layout styles ═══ */
+.wfm-layout {
+  display: flex; flex-direction: column; flex: 1; min-height: 0;
+}
+.wfm-stack { display: flex; flex-direction: column; gap: 4px; flex: 1; min-height: 0; }
+.wfm-video-preview {
+  flex: 0 0 auto; aspect-ratio: 16 / 9; max-height: 55%;
+  background: #000; border-radius: 4px; overflow: hidden;
+  border: 1px solid rgba(255,255,255,0.05); display: flex;
+}
+.wfm-wave-wrap {
+  position: relative; overflow: hidden; flex: 1 1 auto; min-height: 140px;
+}
+.wfm-wave-inner {
+  height: 100%; min-height: 140px; border-radius: 4px; width: 100%; overflow: hidden;
+}
+.wfm-loading {
+  position: absolute; inset: 0; display: flex; align-items: center;
+  justify-content: center; background: rgba(0,0,0,0.45);
+  border-radius: 4px; z-index: 3; gap: 6px;
+}
+.wfm-loading__text { font-size: 0.65rem; color: #a89984; }
+.wfm-overlay {
+  position: absolute; inset: 0; border-radius: 4px; z-index: 4;
+  background: rgba(29,32,33,0.85); backdrop-filter: blur(3px);
+  display: flex; flex-direction: column; align-items: center;
+  justify-content: center; gap: 6px; padding: 8px;
+}
+.wfm-controls { flex-shrink: 0; margin-top: 3px; }
+.wfm-error {
+  display: flex; align-items: center; justify-content: center;
+  padding: 8px; background: rgba(0,0,0,0.15); border-radius: 4px;
+  border: 1px solid rgba(255,255,255,0.04); color: #a89984; font-size: 0.7rem;
+}
+
+/* ═══ ErrorBoundary extracted styles ═══ */
+.errbnd-wrap {
+  flex: 1; display: flex; align-items: center; justify-content: center;
+  padding: 32px; font-family: var(--font-sans);
+}
+.errbnd-card {
+  max-width: 520px; width: 100%; padding: 22px; text-align: center;
+  background: var(--chrome-bg);
+  border: 1px solid color-mix(in srgb, var(--chrome-severity-err) 35%, transparent);
+  border-left: 2px solid var(--chrome-severity-err);
+  border-radius: var(--chrome-radius-pill);
+}
+.errbnd-icon { margin-bottom: 10px; }
+.errbnd-title {
+  font-family: var(--font-serif); font-style: italic;
+  font-size: 1.6rem; font-weight: 400;
+  color: var(--chrome-fg); margin: 0 0 6px; letter-spacing: -0.01em;
+}
+.errbnd-desc {
+  color: var(--chrome-fg-muted); font-size: 0.82rem;
+  margin: 0 0 12px; line-height: 1.5;
+}
+.errbnd-trace {
+  text-align: left; font-size: 0.72rem; color: var(--chrome-severity-err);
+  background: var(--chrome-hover-bg); padding: 8px 10px;
+  border-radius: var(--chrome-radius-pill);
+  border: 1px solid var(--chrome-border);
+  max-height: 140px; overflow: auto; margin: 0 0 14px;
+  font-family: var(--font-mono);
+}
+.errbnd-retry {
+  padding: 6px 14px; font-size: 0.78rem; font-weight: 500;
+  display: inline-flex; align-items: center; gap: 6px;
+}

frontend/src/components/WaveformTimeline.jsx

@@ -2,6 +2,7 @@ import React, { useEffect, useRef, useState, useCallback, useMemo } from 'react'
 import WaveSurfer from 'wavesurfer.js';
 import RegionsPlugin from 'wavesurfer.js/dist/plugins/regions.esm.js';
 import { Play, Pause, ZoomIn, ZoomOut, SkipBack, Loader } from 'lucide-react';
+import './WaveformErrorBoundary.css';
 
 const REGION_COLORS = [
   'rgba(211,134,155,0.3)',
@@ -266,7 +267,13 @@ export default function WaveformTimeline({
 
   // ── Zoom ────────────────────────────────────────────────────────────────────
   useEffect(() => {
-    if (wsRef.current && ready) wsRef.current.zoom(zoom);
+    if (wsRef.current && ready) {
+      try {
+        wsRef.current.zoom(zoom);
+      } catch (err) {
+        console.warn('WaveSurfer zoom failed:', err);
+      }
+    }
   }, [zoom, ready]);
 
   // ── Sync regions — skips when dragging or fingerprint unchanged ─────────────
@@ -325,11 +332,7 @@ export default function WaveformTimeline({
   if (loadError) {
     return (
       <div className="waveform-timeline">
-        <div style={{
-          display:'flex', alignItems:'center', justifyContent:'center',
-          padding:8, background:'rgba(0,0,0,0.15)', borderRadius:4,
-          border:'1px solid rgba(255,255,255,0.04)', color:'#a89984', fontSize:'0.7rem',
-        }}>
+        <div className="wfm-error">
           ⚠ Could not load audio from this file
         </div>
       </div>
@@ -337,50 +340,36 @@ export default function WaveformTimeline({
   }
 
   return (
-    <div className="waveform-timeline" style={{display:'flex', flexDirection:'column', flex:1, minHeight:0}}>
+    <div className="waveform-timeline wfm-layout">
       {/* Video + Waveform stacked vertically */}
-      <div style={{display:'flex', flexDirection:'column', gap:4, flex:1, minHeight:0}}>
+      <div className="wfm-stack">
         {/* Video preview — pinned to its aspect ratio so we don't letterbox
             into huge black bars. Waveform gets the remaining height. */}
         {videoSrc && (
           <div
             ref={videoContainerRef}
-            style={{
-              flex:'0 0 auto', aspectRatio:'16 / 9', maxHeight:'55%',
-              background:'#000', borderRadius:4, overflow:'hidden',
-              border:'1px solid rgba(255,255,255,0.05)', display: 'flex',
-            }}
+            className="wfm-video-preview"
           />
         )}
 
         {/* Waveform — fills the rest. This is the actual editing surface. */}
-        <div style={{position:'relative', overflow:'hidden', flex:'1 1 auto', minHeight:140}}>
+        <div className="wfm-wave-wrap">
           <div
             ref={waveContainerRef}
-            className="waveform-container"
-            style={{height:'100%', minHeight:140, borderRadius:4, width:'100%', overflow:'hidden'}}
+            className="waveform-container wfm-wave-inner"
           />
 
           {/* Loading shimmer */}
           {!ready && !loadError && (
-            <div style={{
-              position:'absolute', inset:0, display:'flex', alignItems:'center',
-              justifyContent:'center', background:'rgba(0,0,0,0.45)',
-              borderRadius:4, zIndex:3, gap:6,
-            }}>
+            <div className="wfm-loading">
               <Loader className="spinner" size={12} color="#d3869b"/>
-              <span style={{fontSize:'0.65rem', color:'#a89984'}}>Loading waveform…</span>
+              <span className="wfm-loading__text">Loading waveform…</span>
             </div>
           )}
 
           {/* Overlay slot — transcription / dubbing progress */}
           {overlayContent && (
-            <div style={{
-              position:'absolute', inset:0, borderRadius:4, zIndex:4,
-              background:'rgba(29,32,33,0.85)', backdropFilter:'blur(3px)',
-              display:'flex', flexDirection:'column', alignItems:'center',
-              justifyContent:'center', gap:6, padding:8,
-            }}>
+            <div className="wfm-overlay">
               {overlayContent}
             </div>
           )}
@@ -388,7 +377,7 @@ export default function WaveformTimeline({
       </div>
 
       {/* Controls */}
-      <div className="waveform-controls" style={{flexShrink:0, marginTop:3}}>
+      <div className="waveform-controls wfm-controls">
         <div className="waveform-controls-left">
           <button className="waveform-btn" onClick={() => seekTo(0)} title="Restart"><SkipBack size={11}/></button>
           <button className="waveform-btn waveform-btn-play" onClick={togglePlay} disabled={!ready}>

frontend/src/hooks/useRealtimeEvents.js

@@ -0,0 +1,106 @@
+/**
+ * useRealtimeEvents — WebSocket connection to /ws/events for live sidebar updates.
+ *
+ * Connects once on mount, automatically reconnects with exponential backoff,
+ * and dispatches invalidation signals to the parent callbacks.
+ *
+ * Events from backend:
+ *   { kind: "projects",       action: "created"|"updated"|"deleted", id: "..." }
+ *   { kind: "profiles",       action: "created"|"updated"|"locked"|"unlocked"|"deleted", id: "..." }
+ *   { kind: "dub_history",    action: "saved"|"deleted", id: "..." }
+ *   { kind: "export_history", action: "exported"|"recorded", id: "..." }
+ *   { kind: "ping" }  // keepalive, ignored
+ */
+import { useEffect, useRef, useCallback } from 'react';
+import { API } from '../api/client';
+
+const WS_EVENTS_URL = API.replace(/^http/, 'ws') + '/ws/events';
+
+/**
+ * @param {Object} handlers - Map of event kind → callback
+ * @param {Function} handlers.projects      - Called when projects list changes
+ * @param {Function} handlers.profiles      - Called when profiles list changes
+ * @param {Function} handlers.dub_history   - Called when dub history changes
+ * @param {Function} handlers.export_history - Called when export history changes
+ */
+export default function useRealtimeEvents(handlers) {
+  const wsRef = useRef(null);
+  const handlersRef = useRef(handlers);
+  const reconnectTimerRef = useRef(null);
+  const retryCountRef = useRef(0);
+  const mountedRef = useRef(true);
+
+  // Keep handlers ref current without causing reconnects
+  useEffect(() => { handlersRef.current = handlers; });
+
+  const connect = useCallback(() => {
+    if (!mountedRef.current) return;
+    // Don't double-connect
+    if (wsRef.current && wsRef.current.readyState <= 1) return;
+
+    try {
+      const ws = new WebSocket(WS_EVENTS_URL);
+      wsRef.current = ws;
+
+      ws.onopen = () => {
+        retryCountRef.current = 0;
+        console.debug('[ws/events] connected');
+      };
+
+      ws.onmessage = (e) => {
+        try {
+          const event = JSON.parse(e.data);
+          const kind = event.kind;
+          if (kind === 'ping') return; // keepalive, ignore
+
+          const handler = handlersRef.current?.[kind];
+          if (handler) {
+            handler(event);
+          }
+        } catch (err) {
+          console.warn('[ws/events] bad message:', e.data, err);
+        }
+      };
+
+      ws.onclose = (e) => {
+        wsRef.current = null;
+        if (!mountedRef.current) return;
+        // Exponential backoff: 2s, 4s, 8s, 16s, max 60s
+        const delay = Math.min(2000 * Math.pow(2, retryCountRef.current), 60_000);
+        retryCountRef.current++;
+        if (retryCountRef.current <= 5) {
+          console.debug(`[ws/events] closed (code=${e.code}), reconnecting in ${delay}ms`);
+        }
+        reconnectTimerRef.current = setTimeout(connect, delay);
+      };
+
+      ws.onerror = () => {
+        // onerror is always followed by onclose, so we just let onclose handle reconnect
+        ws.close();
+      };
+    } catch (err) {
+      console.warn('[ws/events] connection failed:', err);
+      const delay = Math.min(1000 * Math.pow(2, retryCountRef.current), 30_000);
+      retryCountRef.current++;
+      reconnectTimerRef.current = setTimeout(connect, delay);
+    }
+  }, []);
+
+  useEffect(() => {
+    mountedRef.current = true;
+    connect();
+
+    return () => {
+      mountedRef.current = false;
+      if (reconnectTimerRef.current) {
+        clearTimeout(reconnectTimerRef.current);
+        reconnectTimerRef.current = null;
+      }
+      if (wsRef.current) {
+        wsRef.current.onclose = null; // prevent reconnect on unmount
+        wsRef.current.close();
+        wsRef.current = null;
+      }
+    };
+  }, [connect]);
+}