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James RussoandClaude Opus 4.6 7389c0c89b feat(cli): add tts command for local text-to-speech via Kokoro-82M (#201 )

* feat(cli): add `tts` command for local text-to-speech via Kokoro-82M

Adds `hyperframes tts` — generate speech audio locally using Kokoro-82M
(ONNX), no API key needed. Mirrors the transcribe command architecture.

- New command: `hyperframes tts "text" --voice af_heart --output speech.wav`
- 54 voices across 8 languages, ~5x realtime on CPU
- Auto-downloads model (~311 MB) + voices (~27 MB) to ~/.cache/hyperframes/tts/
- Requires Python 3.8+ with kokoro-onnx installed
- Extracted shared `downloadFile` utility from whisper/manager.ts with
  atomic .tmp→rename to prevent partial download corruption
- Added hyperframes-tts skill with voice selection guide
- Updated CLAUDE.md with TTS docs, voice table, and skill reference

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* docs(tts): improve skill per skill-creator guidelines

- Move trigger info from body to frontmatter description
- Remove `trigger` field (not a valid frontmatter field)
- Remove CLI flag docs Claude can derive from --help
- Remove redundant voice tables (keep content-to-voice mapping)
- Fix composition audio example to use actual <audio> element pattern
- Keep non-obvious workflows: TTS+transcribe for captions, long scripts

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* docs(tts): add guidance for using external TTS sources

Help users understand when to use cloud TTS (voice cloning, broader
languages, higher quality) vs the built-in Kokoro model, and how
external audio integrates into the same composition workflow.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* docs(tts): prioritize HeyGen API as recommended cloud TTS

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* docs(tts): remove external TTS section for now

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* fix(tts): set required: false on input arg so --list works standalone

Citty treats positional args as required by default unless explicitly
set to required: false. Without this, `hyperframes tts --list` fails
with "Missing required positional argument".

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* feat(tts): add --help examples and fix required:false for --list

Add examples section to `tts --help` matching the pattern from other
commands (transcribe, render, etc.). Fix citty positional arg requiring
explicit `required: false` for --list to work standalone.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

* docs: add CLI command checklist to CLAUDE.md

Ensure new commands always get --help examples in help.ts.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

2026-04-02 14:09:25 -07:00

2.6 KiB

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name, description

name	description
hyperframes-tts	Generate speech audio locally using Kokoro-82M (no API key). Use when asked to create narration, voiceover, or text-to-speech audio for compositions, or when a user needs spoken audio from text. Covers voice selection, speed tuning, and integrating TTS output with compositions and captions.

Text-to-Speech

Voice Selection

Match voice to content. Default is af_heart.

Content type	Voice	Why
Product demo	`af_heart`/`af_nova`	Warm, professional
Tutorial / how-to	`am_adam`/`bf_emma`	Neutral, easy to follow
Marketing / promo	`af_sky`/`am_michael`	Energetic or authoritative
Documentation	`bf_emma`/`bm_george`	Clear British English, formal
Casual / social	`af_heart`/`af_sky`	Approachable, natural

Run npx hyperframes tts --list for all 54 voices (8 languages: EN, JP, ZH, KO, FR, DE, IT, PT).

Speed Tuning

0.7-0.8 — Tutorial, complex content, accessibility
1.0 — Natural pace (default)
1.1-1.2 — Intros, transitions, upbeat content
1.5+ — Rarely appropriate; test carefully

Composing with TTS Audio

Generate a voiceover and use it as the audio track:

npx hyperframes tts "Your script here" --voice af_nova --output narration.wav

Then reference it in the composition as a standard <audio> element:

<audio
  id="narration"
  data-start="0"
  data-duration="auto"
  data-track-index="2"
  src="narration.wav"
  data-volume="1"
></audio>

TTS + Captions Workflow

Generate speech, then transcribe it back for word-level caption timestamps:

# 1. Generate speech
npx hyperframes tts script.txt --voice af_heart --output narration.wav

# 2. Transcribe for word-level timestamps
npx hyperframes transcribe narration.wav

# 3. Result: narration.wav + transcript.json ready for captions

This avoids manually timing captions — whisper extracts precise word boundaries from the generated audio.

Long Scripts

For scripts longer than a few paragraphs, write the text to a .txt file and pass the path:

npx hyperframes tts script.txt --voice bf_emma --output narration.wav

The model handles long text well but very long inputs (>5 minutes of speech) may benefit from splitting into segments.

Requirements

Python 3.8+ with kokoro-onnx and soundfile installed (pip install kokoro-onnx soundfile)
Model downloads automatically on first use (~311 MB + ~27 MB voices, cached in ~/.cache/hyperframes/tts/)

2.6 KiB Raw Blame History