- Load m.unit in get_domain() so MetricBound carries units from DB - Add Unit column to domains list template - Make load_transport_seed() idempotent with IntegrityError handling and metric unit backfill for existing DBs - Remove unused imports (json, sqlite3, Entity) - Simplify combinator loop to list comprehension - Merge duplicate conditional/valid branches in pipeline - Consolidate duplicated SQL in get_all_results() - Expand CLAUDE.md with fuller architecture docs and conventions Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
80 lines
5.2 KiB
Markdown
80 lines
5.2 KiB
Markdown
# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## What this project is
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PhysCom (Physical Combinatorics) — innovation discovery engine that generates entity combinations across dimensions (e.g. platform × power_source), filters by physical constraints, scores against domain-specific metrics, and ranks results. Includes a CLI, a Flask/HTMX web UI, and a 5-pass pipeline (constraints → estimation → scoring → LLM review → human review).
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## Commands
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- **Install**: `pip install -e ".[dev,web]"` (editable install with test and web deps)
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- **Tests (all)**: `python -m pytest tests/ -q` (48 tests, ~5s). Run after every change.
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- **Single test file**: `python -m pytest tests/test_scorer.py -q`
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- **Single test**: `python -m pytest tests/test_scorer.py::test_score_combination -q`
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- **Web dev server**: `python -m physcom_web`
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- **CLI**: `python -m physcom` (or `physcom` if installed)
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- **Docker**: `docker compose up web` / `docker compose run cli physcom seed`
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- **Seed data**: loaded automatically on first DB init (SQLite, `physcom.db` or `$PHYSCOM_DB`)
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## Architecture
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```
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src/physcom/ # Core library (no web dependency)
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models/ # Dataclasses: Entity, Dependency, Combination, Domain, MetricBound
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db/schema.py # DDL (all CREATE TABLE statements)
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db/repository.py # All DB access — single Repository class, sqlite3 row_factory=Row
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engine/combinator.py # Cartesian product of entities across dimensions
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engine/constraint_resolver.py # Pass 1: requires/excludes/mutex/range/force checks
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engine/scorer.py # Pass 3: log-normalize raw→0-1, weighted geometric mean composite
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engine/pipeline.py # Orchestrator: combo-first loop, incremental saves, resume, cancel
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llm/base.py # LLMProvider ABC (estimate_physics, review_plausibility)
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llm/providers/mock.py # MockLLMProvider for tests
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seed/transport_example.py # 9 platforms + 9 power sources, 2 domains
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src/physcom_web/ # Flask web UI
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app.py # App factory, get_repo(), DB path resolution
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routes/pipeline.py # Background thread pipeline execution, HTMX status/cancel endpoints
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routes/results.py # Results browse, detail view, human review submission
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routes/entities.py # Entity CRUD
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routes/domains.py # Domain listing
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templates/ # Jinja2, extends base.html, uses HTMX for polling
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static/style.css # Single stylesheet
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tests/ # pytest, uses seeded_repo fixture from conftest.py
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```
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## Key patterns
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- **Repository is the only DB interface.** No raw SQL outside `repository.py`.
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- **Pipeline is combo-first**: each combo goes through all requested passes before the next combo starts. Progress is persisted per-combo (crash-safe, resumable).
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- **`pipeline_runs` table** tracks run lifecycle: pending → running → completed/failed/cancelled. The web route creates the record, then starts a background thread with its own `sqlite3.Connection`.
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- **`combination_results`** has rows for ALL combos including blocked ones (pass_reached=1, composite_score=0.0). Scored combos get pass_reached=3+.
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- **Status guard**: `update_combination_status` refuses to downgrade `reviewed` → `scored`.
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- **`save_combination`** loads existing status/block_reason on dedup (important for resume).
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- **`ensure_metric`** backfills unit if the row already exists with an empty unit.
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- **MetricBound** carries `unit` — flows through seed → ensure_metric → metrics table → get_combination_scores → template display.
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- **HTMX polling**: `_run_status.html` partial polls every 2s while run is pending/running; stops polling when terminal.
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## Data flow (pipeline passes)
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1. **Pass 1 — Constraints**: `ConstraintResolver.resolve()` → blocked/conditional/valid. Blocked combos get a result row and `continue`.
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2. **Pass 2 — Estimation**: LLM or `_stub_estimate()` → raw metric values. Saved immediately via `save_raw_estimates()` (normalized_score=NULL).
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3. **Pass 3 — Scoring**: `Scorer.score_combination()` → log-normalized scores + weighted geometric mean composite. Saves via `save_scores()` + `save_result()`.
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4. **Pass 4 — LLM Review**: Only for above-threshold combos with an LLM provider. No real provider yet (only `MockLLMProvider`).
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5. **Pass 5 — Human Review**: Manual via web UI results page.
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## Testing
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- Tests use `seeded_repo` fixture (in-memory SQLite with transport seed data: 9 platforms, 9 power sources, 2 domains). There's also a bare `repo` fixture for tests that seed their own data.
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- Individual entity fixtures (walking, bicycle, spaceship, solar_sail, etc.) are defined in `conftest.py`.
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## Conventions
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- Python 3.11+, `from __future__ import annotations` everywhere.
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- Dataclasses for models, no ORM.
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- Don't use `cd` in Bash commands — run from the working directory so pre-approved permission patterns match.
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- Don't add docstrings/comments/type annotations to code you didn't change.
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- `INSERT OR IGNORE` won't update existing rows — if adding a new column/field to seed data, also add an UPDATE for backfill.
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- Jinja2 `0.0` is falsy — use `is not none` not `if value` when displaying scores that can legitimately be zero.
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