B.D. Murphy 7dde69ebb3 Name the book on the speakers page and add a project switcher
Reported: the speakers page showed 51 needing review in Chrome on Windows
and 20 in Safari on the Mac, and showed no names starting with D including
"Deal Hunter" - despite several reloads.

Neither browser was wrong. The active project is a per-browser cookie, so
each browser was on a different book and the two lists are unrelated:

  Last Dwarf                 91 speakers, 51 need checking, 0 D-names
  DealHunterShip_4.0e        61 speakers, 19 need checking, includes
                             Deal Hunter, Dealer, Distorted Voice,
                             Duchess Victoria, Duty Nurse

"Deal Hunter" is the ship AI in the Deal Hunter book and is not a Last
Dwarf character, so its absence there was correct. The page gave no hint
that the book was even part of what was being displayed.

- The speakers page now shows a "Reviewing <project>" banner next to the
  counts, so the number and the book it belongs to are read together.
- Added a project switcher directly on that page; previously changing
  project meant navigating via the dashboard.
- activate_project accepts ?next=, restricted to same-site relative paths
  so the switcher can stay put. Verified //evil.com and https://evil.com
  both fall back to "/".
- list_projects registered as a template global, following the existing
  active_project pattern; it degrades to [] on any error.

routes.py stays at its 76 pre-existing ruff errors. Suite: 684 passed, 8
pre-existing.
2026-10-10 19:45:47 -07:00

UmbraAudio

Quality-first multi-pass audiobook generation from English manuscripts.

Features

  • 5-pass pipeline: Analysis → Voice Design → Mapping → Test → Generate
  • Multi-engine TTS: Chatterbox (primary), Qwen3-TTS (secondary)
  • LLM-enhanced: BookNLP for NLP, LLM for profiling/emotion/pronunciation
  • Web review: FastAPI + HTMX at checkpoints for human approval

Quick Start

python -m umbraaudio.cli init <manuscript.epub> --name 'My Book'
python -m umbraaudio.cli analyze
python -m umbraaudio.cli voices
python -m umbraaudio.cli review

Requirements

  • Python 3.11+
  • NVIDIA GPU with CUDA support (RTX 3060 or better recommended)
  • ffmpeg

Development

pip install -e ".[dev]"
ruff check umbraaudio/
pytest tests/ -v

Commit cadence: commit at least once every Sunday. Never leave a week (let alone a month) of work uncommitted — a single accidental git checkout on 2026-09-20 wiped out a month of changes to umbraaudio/web/routes.py. See AGENTS.md → Commit Cadence.

scripts/commit_check.sh enforces the nudge: it exits non-zero once the tree has been dirty longer than a week. The LaunchAgent com.umbraaudio.commitcheck runs it every Sunday at 18:00 and posts a macOS notification when there is uncommitted work.

scripts/commit_check.sh            # warn if dirty > 7 days
scripts/commit_check.sh --days 3   # tighter threshold
scripts/commit_check.sh --any      # warn on any uncommitted change

Rebuilding from source

The repo tracks source only; large runtime data is reconstructed as needed.

  1. Models: weights are not committed (see .gitignore). Download them:

    bash scripts/download_models.sh   # ~9 GB, targets ./models
    
  2. Qwen3-TTS is a git submodule pinned to upstream commit 022e286:

    git submodule update --init --recursive
    

    The tts_server/web-demo backend includes a local UI customization to qwen_tts/cli/demo.py. It is preserved as a patch — reapply it after checking out the submodule:

    cd Qwen3-TTS && git apply ../scripts/qwen3_tts_demo_umbra_patch.patch
    
  3. Environment: copy/keep .env (contains secrets) and set UMBRA_TTS__* model paths under models/.

Book projects (e.g. DealHunterShip_...) are committed separately under their own project directories and are not part of this program repository.

Description
Quality-first multi-pass audiobook generation pipeline (5-pass: Analysis -> Voice Design -> Mapping -> Test -> Generate). FastAPI+HTMX review UI, Edge-TTS/Qwen3-TTS multi-engine voice, SQLite state.
Readme Apache-2.0 37 MiB
Languages
Python 84.8%
HTML 11.4%
Shell 3%
PLpgSQL 0.7%