Files
kebab/tasks/p8/p8-1-whisper-adapter.md
altair823 f9714aa5cb docs(rename): kb → kebab — README, tasks/, docs/, design doc, report
마지막 commit. 모든 .md 안의 `kb` 단어 일괄 갱신.

- 19 개 crate 이름 (`kb-core`, `kb-app`, …) → `kebab-*` (Rust 모듈
  path 표기 `kb_*` → `kebab_*` 포함).
- 미래 component (`kb-tui`, `kb-desktop`, `kb-asr-whisper`, `kb-ocr`,
  `kb-mcp`, `kb-vlm`, `kb-rerank`, `kb-vision-ocr`, `kb-index`,
  `kb-smoke`, `kb-architecture`) → `kebab-*` (P6+ 가 시작될 때
  같은 prefix 사용).
- CLI 명령 예제: `kb ingest` / `kb search` / `kb ask` / `kb init` /
  `kb doctor` / `kb inspect` / `kb list` / `kb eval` →
  `kebab <verb>`. fenced code block + 인라인 backtick 모두.
- XDG paths + env vars + binary 경로 (`target/release/kb` →
  `target/release/kebab`) 동기화.
- design doc / 최초 보고서 / SMOKE / HOTFIXES / phase epic / task
  spec 모든 reference 통일.
- task-decomposition.md 의 `git -c user.name=kb` 는 과거 git history
  기록용 author 정보라 그대로 유지 (실제 git history 의 author 는
  변경 불가).
- `tasks/phase-5-evaluation.md` 의 `status: planned` →
  `completed` 도 같이 (P5-1 + P5-2 PR 머지 후 미반영분).

## 검증

- `grep -rEn "\bkb-[a-z]|\bkb_[a-z]|\.config/kb\b|kb\.sqlite|\bKB_[A-Z]"
   --include="*.md"` 0 hits (task-decomposition.md 의 git author
  제외).
- 모든 file path reference 살아있음 (renamed file 들 모두 새 path
  로 update).

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-02 04:01:55 +00:00

7.9 KiB

phase, component, task_id, title, status, depends_on, unblocks, contract_source, contract_sections
phase component task_id title status depends_on unblocks contract_source contract_sections
P8 kebab-parse-audio (whisper adapter) p8-1 Audio Extractor + Transcriber trait + whisper.cpp adapter planned
p0-1
p1-6
p8-2
../../docs/superpowers/specs/2026-04-27-kebab-final-form-design.md
§3.4 Block::AudioRef + AudioRefBlock
§3.7a Transcript + TranscriptSegment
§9.3 audio policy
§9 versioning

p8-1 — Whisper adapter

Goal

Implement Extractor for MediaType::Audio(_) plus a Transcriber trait + whisper.cpp Rust binding adapter (whisper-rs). Produces a CanonicalDocument whose body is one AudioRefBlock populated with Transcript { segments, language, engine, engine_version }.

Why now / why this size

Audio stays a single, replaceable engine boundary (Transcriber trait). Extractor + adapter together because the extractor is essentially a thin shell over the transcriber.

Allowed dependencies

  • kebab-core
  • kebab-config
  • whisper-rs = "0.13" (or current stable)
  • symphonia = { version = "0.5", features = ["all"] } — decode .m4a/.mp3/.wav/.flac/.ogg to interleaved f32 PCM at the source's native sample rate / channel layout. Symphonia does NOT resample; that is rubato's job.
  • rubato = "0.15" — sample-rate conversion to 16 kHz mono f32 (the input shape whisper.cpp expects). Use rubato::FftFixedIn::new(input_sample_rate, 16_000, frames_per_chunk, sub_chunks, 1 /* channels after downmix */) for fixed-input streaming; pre-mix multi-channel to mono via simple averaging before the resampler.
  • serde, serde_json
  • time
  • tracing
  • thiserror

Forbidden dependencies

  • kebab-source-fs, kebab-parse-md, kebab-parse-pdf, kebab-parse-image, kebab-normalize, kebab-chunk, kebab-store-*, kebab-embed*, kebab-search, kebab-llm*, kebab-rag, kebab-tui, kebab-desktop

Inputs

input type source
RawAsset kebab_core::RawAsset kebab-source-fs
audio bytes &[u8] filesystem
kebab-config.audio { model_path, language, chunk_seconds, n_threads, gpu } runtime

Outputs

output type downstream
CanonicalDocument kebab_core::CanonicalDocument kebab-chunk (audio-segment-v1 chunker in p8-2)

Public surface (signatures only — no new types)

pub trait Transcriber: Send + Sync {
    fn engine(&self) -> &'static str;
    fn engine_version(&self) -> String;
    fn transcribe(&self, pcm_f32_16khz: &[f32], language_hint: Option<&kebab_core::Lang>) -> anyhow::Result<kebab_core::Transcript>;
}

pub struct WhisperCppTranscriber { /* internal: whisper_rs::WhisperContext */ }
impl WhisperCppTranscriber { pub fn new(config: &kebab_config::Config) -> anyhow::Result<Self>; }
impl Transcriber for WhisperCppTranscriber { /* per trait */ }

pub struct AudioExtractor { transcriber: std::sync::Arc<dyn Transcriber> }
impl AudioExtractor { pub fn new(transcriber: std::sync::Arc<dyn Transcriber>) -> Self; }
impl kebab_core::Extractor for AudioExtractor {
    fn supports(&self, m: &kebab_core::MediaType) -> bool { matches!(m, kebab_core::MediaType::Audio(_)) }
    fn parser_version(&self) -> kebab_core::ParserVersion { kebab_core::ParserVersion("audio-whisper-v1".into()) }
    fn extract(&self, ctx: &kebab_core::ExtractContext, bytes: &[u8]) -> anyhow::Result<kebab_core::CanonicalDocument>;
}

Behavior contract

  • Decode pipeline (in extract):
    1. symphonia opens the audio bytes, picks the best track, decodes to f32 PCM mono.
    2. Down-mixes to mono (mean of channels) and resamples to 16 kHz f32 via rubato::FftFixedIn (input rate from SymphoniaTrack::codec_params.sample_rate).
    3. Produces a single Vec<f32> for the entire audio.
  • Transcribe via transcriber.transcribe(&pcm, lang_hint). The trait returns Transcript { segments, language: detected_lang, engine, engine_version }.
  • Build AudioRefBlock { common, asset_id: asset.asset_id, duration_ms: ((pcm.len() as u64 * 1000) / 16_000), transcript: Some(transcript) }.
  • common.source_span = SourceSpan::Time { start_ms: 0, end_ms: duration_ms }.
  • title = filename without extension; lang = detected language from transcript (fallback Lang("und")).
  • metadata.user["audio"] = { "duration_ms": ..., "sample_rate": 16000, "channels": 1, "engine": "whisper.cpp", "engine_version": "..." }.
  • metadata.source_type = SourceType::Reference; trust_level = TrustLevel::Primary (transcripts are observed text, not generated narration).
  • provenance events: Discovered, Parsed, Transcribed.
  • block_id per design §4.2 with block_kind = "audio_ref", heading_path = [], ordinal = 0, source_span = SourceSpan::Time { start_ms: 0, end_ms: duration_ms }.
  • WhisperCppTranscriber:
    • Loads model from config.audio.model_path (e.g., ~/.local/share/kebab/models/whisper/ggml-large-v3.bin).
    • Runs with WhisperFullParams::new(SamplingStrategy::Greedy { best_of: 1 }) — deterministic.
    • Streams in chunks of config.audio.chunk_seconds (default 30) to bound memory; aggregates segments.
    • Transcript.segments populated with start_ms, end_ms, text, confidence: Some(p) from whisper's per-token probabilities (averaged), speaker: None (diarization is P+).
    • engine = "whisper.cpp", engine_version = whisper_rs::version().
  • Determinism: greedy sampling + fixed model + identical PCM → identical transcript text and segment timestamps. Tests use base.en (small fast model) for speed.
  • Failure modes:
    • Decode failure (unsupported codec) → anyhow::Error.
    • Model file missing → anyhow::Error with hint download whisper.cpp model and set audio.model_path.

Storage / wire effects

  • Reads: config.audio.model_path (model file).
  • Otherwise none directly.

Test plan

kind description fixture / data
unit 3-second WAV containing "hello world" → segments[0].text contains "hello world" (using base.en model, downloaded once for CI) fixtures/audio/hello.wav
unit duration_ms matches actual audio length within ±50 ms inline
unit corrupt audio → error fixtures/audio/corrupt.wav
unit model file missing → error with helpful hint inline
unit language hint passed to whisper changes detected language inline
determinism identical input → identical Transcript twice inline
#[ignore] integration 30-second Korean audio → segments_count > 1, language = "ko" requires large-v3 model
snapshot CanonicalDocument JSON stable for short fixture fixtures/audio/hello.wav

All tests under cargo test -p kebab-parse-audio. Mark slow/large-model tests #[ignore].

Definition of Done

  • cargo check -p kebab-parse-audio passes
  • cargo test -p kebab-parse-audio passes (excluding #[ignore])
  • No imports outside Allowed dependencies (resampler crate may be added — record in PR)
  • First-run model download path documented (NOT performed by code; user responsibility)
  • PR links design §3.4, §3.7a, §9.3

Out of scope

  • Diarization (P+).
  • Real-time / streaming transcription (P+).
  • Voice activity detection beyond what whisper.cpp offers internally.
  • Lossless re-encoding of source audio.

Risks / notes

  • whisper.cpp model files are large (1+ GB for large-v3). Tests must default to base.en (~150 MB) and ship a 3-second fixture.
  • macOS Metal acceleration: ensure whisper-rs feature flags align with M-series builds; document any required env vars.
  • Decoding errors for variable-bitrate .m4a are common; symphonia is the most reliable Rust option but expect occasional unsupported codec; fail clean rather than panic.
  • Resampling: rubato::FftFixedIn is the v1 default — high enough quality that whisper.cpp recognition is not the bottleneck, fast enough that decode + resample stays under real-time on M-series. If a regression appears, switch to SincFixedIn with PR; record the change in engine_version since transcript stability depends on the resampler.