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>
123 lines
5.6 KiB
Markdown
123 lines
5.6 KiB
Markdown
---
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phase: P6
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component: kebab-parse-image (caption adapter)
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task_id: p6-3
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title: "ModelCaption adapter (LanguageModel-driven, feature-gated)"
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status: planned
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depends_on: [p6-1, p4-2]
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unblocks: []
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contract_source: ../../docs/superpowers/specs/2026-04-27-kebab-final-form-design.md
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contract_sections: [§3.4 ImageRefBlock.caption, §3.7a ModelCaption, §9.1 caption (model-generated, low trust)]
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---
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# p6-3 — Caption adapter
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## Goal
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Optionally populate `ImageRefBlock.caption` with `ModelCaption { text, model, model_version }` produced by a vision-capable LM (e.g., `qwen2.5-vl:7b` via Ollama). Feature-gated; default OFF.
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## Why now / why this size
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Captioning closes the multimodal loop. Strict separation from OCR keeps trust levels distinct: captions are generated, OCR is observed. Adapter is small — single trait method + one prompt.
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## Allowed dependencies
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- `kebab-core`
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- `kebab-config`
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- `kebab-parse-image`
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- `kebab-llm` (LanguageModel trait)
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- `base64`
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- `serde`, `serde_json`
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- `image` (resize for prompt cost control)
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- `tracing`
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- `thiserror`
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## Forbidden dependencies
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- `kebab-source-fs`, `kebab-parse-md`, `kebab-normalize`, `kebab-chunk`, `kebab-store-*`, `kebab-embed*`, `kebab-search`, `kebab-rag`, `kebab-llm-local` (only via trait), `kebab-tui`, `kebab-desktop`
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## Inputs
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| input | type | source |
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|-------|------|--------|
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| image bytes | `&[u8]` | extractor |
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| `dyn LanguageModel` (vision-capable) | runtime | injected |
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| `kebab-config.image.caption` | `{ enabled, max_pixels, prompt_template_version }` | runtime |
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## Outputs
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| output | type | downstream |
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|--------|------|------------|
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| `ModelCaption` | `kebab_core::ModelCaption` | merged into `ImageRefBlock.caption` |
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## Public surface (signatures only — no new types)
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```rust
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pub fn caption_image(
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llm: &dyn kebab_core::LanguageModel,
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image_bytes: &[u8],
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cfg: &kebab_config::Config,
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) -> anyhow::Result<kebab_core::ModelCaption>;
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pub fn apply_caption(
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llm: &dyn kebab_core::LanguageModel,
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image_bytes: &[u8],
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block: &mut kebab_core::ImageRefBlock,
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cfg: &kebab_config::Config,
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) -> anyhow::Result<()>;
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```
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## Behavior contract
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- Feature gate: if `config.image.caption.enabled = false` (default), `apply_caption` is a no-op (returns `Ok(())` without invoking LM).
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- Pre-process: downscale image to `config.image.caption.max_pixels` (default 768×768 long edge) preserving aspect; encode as PNG.
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- Build prompt:
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- `system = "이미지를 한 문장으로 객관적으로 설명한다. 추측은 피하고, 보이는 것만 적는다."`
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- `user` = `[image_base64]\n\n위 이미지를 한국어로 한 문장으로 설명하라.` (if `lang` hint == "ko") or English variant otherwise.
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- The base64 wrapper assumes the LM adapter routes vision inputs via Ollama's `images: [base64]` field (this is provider-specific; the adapter is responsible for rendering the prompt to wire). For non-vision LMs, return an error and skip.
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- Call `llm.generate_stream(GenerateRequest { system, user, stop: vec!["\n\n"], max_tokens: 96, temperature: 0.0, seed: Some(0) })`. Collect tokens until `Done`.
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- `ModelCaption { text: collected, model: llm.model_ref().id, model_version: llm.model_ref().provider }` (use provider as a coarse "version" proxy; if a vision model exposes a stable revision, prefer that).
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- `apply_caption` sets `block.caption = Some(...)` and appends `Provenance::CaptionApplied` event.
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- Trust: caption is **model-generated** and labeled `trust_level = TrustLevel::Generated` if the caller propagates trust into chunk-level UI; this task only emits the `ModelCaption`.
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- Failure modes:
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- LM error → return `anyhow::Error`; caller may decide to skip (do not fail the entire ingest).
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- Empty LM output → still set `block.caption = Some(ModelCaption { text: "" })` so downstream code can distinguish "captioning attempted, no result" from "captioning never attempted".
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- Determinism: `temperature=0` + `seed=0`. Tests use `MockLanguageModel` to assert deterministic captions.
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## Storage / wire effects
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- None directly. Caller persists via `kebab-store-sqlite`.
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## Test plan
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| kind | description | fixture / data |
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|------|-------------|----------------|
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| unit | feature disabled → `apply_caption` no-op | inline (config.enabled = false) |
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| unit | mock LM emits "사진 한 장" → `block.caption.text = "사진 한 장"` | inline |
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| unit | mock LM emits empty token stream → `block.caption = Some(ModelCaption { text: "" })` | inline |
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| unit | Korean lang hint produces Korean prompt; English hint → English prompt | inline |
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| unit | downscale honors `max_pixels` (resulting bytes < some threshold) | fixture large image |
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| determinism | identical input + temperature=0 + seed=0 → identical caption (mock) | inline |
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All tests under `cargo test -p kebab-parse-image caption` with mock LM only.
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## Definition of Done
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- [ ] `cargo check -p kebab-parse-image --features caption` passes
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- [ ] `cargo test -p kebab-parse-image caption` passes
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- [ ] No imports outside Allowed dependencies
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- [ ] Feature default OFF; only on when user opts in via config
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- [ ] PR links design §3.4 ImageRefBlock.caption, §9.1
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## Out of scope
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- Multimodal RAG that uses caption text in answer (P+).
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- CLIP / image embedding for cross-modal search (P+).
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- Caption translation (P+).
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## Risks / notes
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- Vision LMs hallucinate. The system prompt explicitly forbids guessing, but expect false captions; UI and RAG must always label captions as model-generated.
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- Ollama `qwen2.5-vl` accepts base64 images via `images:[]` — this is provider-specific; documenting the wire shape in the spec keeps adapter swaps cheap.
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- Large images bloat prompt costs; cap aggressively (768×768 long edge default).
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