- docs/overview.md: rewrite for current architecture (src/ layout, split JS/CSS modules, credentials/models/functions/ui config categories, correct test fixture targets) - docs/contributing.md: new — documentation philosophy and style guide - AGENTS.md: add rule to follow docs/contributing.md
159 lines
8.6 KiB
Markdown
159 lines
8.6 KiB
Markdown
# Bookshelf — Technical Overview
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## Purpose
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Photo-based book cataloger. Hierarchy: Room → Cabinet → Shelf → Book.
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AI plugins identify spine text; archive plugins supply bibliographic metadata.
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## Stack
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- **Server**: FastAPI + SQLite (no ORM), Python 3.11+, Poetry (`poetry run serve`)
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- **Frontend**: Vanilla JS SPA — `static/index.html` + `static/css/` + `static/js/`; no build step
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- **AI**: OpenAI-compatible API (OpenRouter, OpenAI, etc.) via `openai` library
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- **Images**: Stored uncompressed in `data/images/`; Pillow used server-side for crops and AI prep
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## Directory Layout
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```
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src/
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app.py # FastAPI app, exception handlers
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api.py # All routes (APIRouter)
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db.py # All SQL; connection() / transaction() context managers
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files.py # Image file I/O; DATA_DIR, IMAGES_DIR
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config.py # Config loading and typed AppConfig
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models.py # Typed dataclasses / mashumaro decoders
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errors.py # Domain exceptions (NotFoundError, BadRequestError subtypes)
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logic/
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__init__.py # dispatch_plugin() orchestrator + re-exports
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boundaries.py # Boundary math, shelf/spine crop sources, boundary detector runner
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identification.py # Status computation, text recognizer, book identifier runners
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archive.py # Archive searcher runner (sync + background)
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batch.py # Batch pipeline, process_book_sync
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images.py # crop_save, prep_img_b64, serve_crop
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plugins/
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__init__.py # Registry: load_plugins(), get_plugin(), get_manifest()
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rate_limiter.py # Thread-safe per-domain rate limiter
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ai_compat/ # AI plugin implementations
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archives/ # Archive plugin implementations
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scripts/
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presubmit.py # Poetry console entry points: fmt, presubmit
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static/
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index.html # HTML shell + CSS/JS imports (load order matters)
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css/ # base, layout, tree, forms, overlays
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js/ # state → helpers → api → canvas-boundary → tree-render →
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# detail-render → canvas-crop → editing → photo → events → init
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config/
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credentials.default.yaml # API endpoints and keys (override in credentials.user.yaml)
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models.default.yaml # Model selection and prompts per AI function
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functions.default.yaml # Plugin definitions and per-plugin settings
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ui.default.yaml # UI display settings
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*.user.yaml # Gitignored overrides — create these with real values
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data/ # Runtime: books.db + images/ (gitignored)
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tests/
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*.py # Python tests (pytest)
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js/pure-functions.test.js # JS tests (node:test)
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docs/
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overview.md # This file
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contributing.md # Documentation and contribution standards
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```
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## Layer Architecture
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Unidirectional: `api` → `logic` → `db` / `files`. No layer may import from a layer above it.
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- **api**: HTTP parsing, entity existence checks via `db.connection()`, calls logic, returns HTTP responses. Owns HTTPException and status codes.
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- **logic**: Business operations, no HTTP/FastAPI imports. Raises domain exceptions from `errors.py` for expected failures.
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- **db / files**: SQL and file I/O only. Returns typed dataclasses or None. Never raises domain exceptions.
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## Configuration System
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Config loaded from `config/*.default.yaml` merged with `config/*.user.yaml`. Deep merge: dicts recursive, lists replaced. Typed via `mashumaro BasicDecoder[AppConfig]`.
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Categories:
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| File | Purpose |
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|------|---------|
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| `credentials` | `base_url` + `api_key` per endpoint; no model or prompt |
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| `models` | `credentials` ref + `model` string + optional `extra_body` + `prompt` |
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| `functions` | Plugin definitions; dict key = plugin_id (unique across all categories) |
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| `ui` | Frontend display settings |
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Minimal setup — create `config/credentials.user.yaml`:
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```yaml
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credentials:
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openrouter:
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api_key: "sk-or-your-actual-key"
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```
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## Plugin System
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### Categories
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| Category | Input | Output | DB field |
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|----------|-------|--------|----------|
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| `boundary_detectors` (`target=shelves`) | cabinet image | `{boundaries:[…], confidence:N}` | `cabinets.ai_shelf_boundaries` |
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| `boundary_detectors` (`target=books`) | shelf image | `{boundaries:[…]}` | `shelves.ai_book_boundaries` |
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| `text_recognizers` | spine image | `{raw_text, title, author, …}` | `books.raw_text` + `candidates` |
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| `book_identifiers` | raw_text | `{title, author, …, confidence}` | `books.ai_*` + `candidates` |
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| `archive_searchers` | query string | `[{source, title, author, …}, …]` | `books.candidates` |
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### Universal plugin endpoint
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```
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POST /api/{entity_type}/{entity_id}/plugin/{plugin_id}
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```
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Routes to the correct runner via `dispatch_plugin()` in `logic/__init__.py`.
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### AI Plugin Configuration
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- `credentials` file: connection only — `base_url`, `api_key`.
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- `models` file: `credentials` ref, `model` string, `prompt` text, optional `extra_body`.
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- `functions` file: per-plugin settings — `model`, `max_image_px` (default 1600), `confidence_threshold` (default 0.8), `auto_queue`, `rate_limit_seconds`, `timeout`.
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- `OUTPUT_FORMAT` is a hardcoded class constant in each plugin — not user-configurable; injected into the prompt as `${OUTPUT_FORMAT}` by `AIClient`.
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### Archive plugins
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All implement `search(query: str) -> list[CandidateRecord]`. Use shared `RATE_LIMITER` singleton for per-domain throttling.
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### Auto-queue
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- After `text_recognizer` completes → fires all `archive_searchers` with `auto_queue: true` in background thread pool.
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- `POST /api/batch` → runs `text_recognizers` then `archive_searchers` for all unidentified books.
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## Database Schema (key fields)
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| Table | Notable columns |
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|-------|-----------------|
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| `cabinets` | `shelf_boundaries` (JSON `[…]`), `ai_shelf_boundaries` (JSON `{pluginId:[…]}`) |
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| `shelves` | `book_boundaries`, `ai_book_boundaries` (same format), `photo_filename` (optional override) |
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| `books` | `raw_text`, `ai_title/author/year/isbn/publisher`, `candidates` (JSON `[{source,…}]`), `identification_status` |
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`identification_status`: `unidentified` → `ai_identified` → `user_approved`.
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## Boundary System
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N interior boundaries → N+1 segments. `full = [0] + boundaries + [1]`. Segment K spans `full[K]..full[K+1]`.
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- User boundaries: `shelf_boundaries` / `book_boundaries` (editable via canvas drag)
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- AI suggestions: `ai_shelf_boundaries` / `ai_book_boundaries` (JSON object `{pluginId: [fractions]}`)
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- Shelf K image = cabinet photo cropped to `(0, y_start, 1, y_end)` unless shelf has override photo
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- Book K spine = shelf image cropped to `(x_start, *, x_end, *)` with composed crop if cabinet-based
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## Frontend JS
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No ES modules, no bundler. All files use global scope; load order in `index.html` is the dependency order. State lives in `state.js` (`S`, `_plugins`, `_bnd`, `_photoQueue`, etc.). Events delegated via `#app` in `events.js`.
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## Tooling
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```
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poetry run serve # start uvicorn on :8000
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poetry run fmt # black (in-place)
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poetry run presubmit # black --check + flake8 + pyright + pytest + JS tests
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npm install # install ESLint + Prettier (requires network; enables JS lint/fmt in presubmit)
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npm run lint # ESLint on static/js/
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npm run fmt # Prettier on static/js/
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```
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Line length: 120. Pyright strict mode. Pytest fixtures with `yield` return `Iterator[T]`.
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Test fixtures: monkeypatch `db.DB_PATH` / `files.DATA_DIR` / `files.IMAGES_DIR`.
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## Key API Endpoints
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```
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GET /api/config # UI config + plugin manifest
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GET /api/tree # full nested tree
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POST /api/{entity_type}/{entity_id}/plugin/{plugin_id} # universal plugin runner
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PATCH /api/cabinets/{id}/boundaries # update shelf boundary list
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PATCH /api/shelves/{id}/boundaries # update book boundary list
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GET /api/shelves/{id}/image # shelf image (override or cabinet crop)
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GET /api/books/{id}/spine # book spine crop
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POST /api/books/{id}/process # full auto-queue pipeline (single book)
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POST /api/batch / GET /api/batch/status # batch processing
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POST /api/books/{id}/dismiss-field # dismiss a candidate suggestion
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PATCH /api/{kind}/reorder # drag-to-reorder
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POST /api/cabinets/{id}/crop / POST /api/shelves/{id}/crop # permanent crop
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```
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