B.D. Murphy a4c88f8bde Make speaker approval actually clear the badge, without navigating
Reviewer report: pressing Approve left the "needs check" badge in place and
appeared to navigate to a new page.

Root cause was a split brain, not a single bug. Approve writes the
voice_status.json ledger, but speaker_confidence read the voice_status key
embedded in speakers.json. That inline copy is stale - the web layer
overwrites it from the ledger on read (_load_speakers), so the page showed
the right value while the assessment computed from the old one. In Last
Dwarf, "Advisor" was 'pending' in speakers.json and 'approved' in the
ledger, so the reviewer's click had saved and still left it flagged.

- assess_speakers() takes the ledger as an explicit argument, authoritative
  over the inline key; load_speaker_assessments() reads voice_status.json.
- New SpeakerAssessment.reviewed flag, surfaced in the serialized view.
- Approval clears the badge but keeps the reasons visible: the underlying
  facts (role-only name, one utterance) stay inspectable on hover rather
  than being silently discarded.
- Corrupt/ non-dict ledgers degrade to {} - this module never raises.
- Approve swapped #speakers-list with innerHTML, replacing the whole
  reviewer list with a single <tr>; now swaps only its own row via
  outerHTML on #speaker-row-N.
- The review panel explained only rename/merge and never mentioned Approve,
  so the process was unclear; it now lists the three outcomes.

16 new tests. Suite: 681 passed, 8 pre-existing failures unchanged.
2026-10-10 18:46:07 -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
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Shell 3%
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