76 lines
5.0 KiB
Markdown
76 lines
5.0 KiB
Markdown
# Tests
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Run everything from the repo root:
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```
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uv run --with pytest --with playwright pytest tests
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```
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- `test_*.py`: assert-based self-checks for template logic (lint of unfilled Python
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templates, the custom palette, presets in step with the template).
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- `page_check/`: **Seam 1.** Loads a dashboard page in headless Chromium with no
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backend, pushes contract envelopes through `window.__pyMsg`, and asserts on what
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is visible. Every case runs in light, dark and narrow (800px) mode.
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- By default it checks the no-AI template, filled with test values. To check a
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generated page instead, set `PAGE_CHECK_HTML=path/to/dashboard.html`.
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- The page sees a fake Qt bridge. Every action the page sends is recorded in
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`window.__calls` as `[slot, ...args]`.
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- `PAGE_CHECK_WIRED=1`: the page is wired to a bot (sample data off). Sample-data
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cases skip, and a case checks that the page's actions go to the bot. With no
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`PAGE_CHECK_HTML`, the template is checked with `SAMPLE_DATA` switched off.
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- `PAGE_CHECK_REPLAY=run.jsonl`: replay a real bot run (the JSON lines that
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`python dashboard/bot_runner.py` prints) instead of the built-in run.
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- To add a case, write a `test_*.py` file in `page_check/` that uses the `page`
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and `push(event, data)` fixtures from `conftest.py`.
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- Optional-section cases (`test_optional_sections.py`) skip on a generated page
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built without that section. The template must carry all of them. A page with
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the login section is signed in (`login_result ok`) before each case.
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- `test_sections.py`: the optional-section strip tool keeps only the chosen
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sections, and a page with none of them still passes the page check.
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- `page_check_ai/`: **Seam 1, AI web page.** Builds the React starter with npm
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(filled with test values, in a temp folder that keeps `node_modules`), serves it with
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its own `server_stub.py`, and checks bands, band filters, drafts, the approve gate
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"page X of Y" and the cost page (spend tiles, coverage pill, month breakdown,
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by-hand assumptions), plus every no-AI case. Tests set run and review state on the stub
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directly (the `stub` fixture). To check a generated dashboard folder instead, set
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`PAGE_CHECK_AI_DIR=path/to/dashboard`. Needs npm on PATH, else it skips.
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- `page_check_ai_desktop/`: **Seam 1, AI desktop page.** The no-AI `dashboard.html` with
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`ai_sections.html` pasted in, loaded from `file://` with a fake Qt bridge whose
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`ai_request` slot goes to `server_stub.dispatch()` in this process (what `ai_bridge.py`
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does). Runs the AI web page's review and cost cases and the no-AI cases unchanged, plus
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a tampered page calling the slot directly (still refused). To check a generated folder,
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set `PAGE_CHECK_AI_DESKTOP_DIR=path/to/dashboard`; `PAGE_CHECK_WIRED=1` as above.
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`test_ai_fetch.py` runs the review cases on the same page with no Qt bridge (a plain-HTML
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web project): the AI sections fetch `/api/...`, routed to `server_stub.dispatch()`.
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- `page_check_common.py`: what the three page checks share (modes, test fill, fake Qt
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bridge, stub loader, page opener, the list of no-AI cases the AI pages rerun).
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- `test_pricing.py`: the AI cost function (normal, long-context, thinking tokens,
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unknown model).
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- `test_reference_scan.py`: no patient data, internal IPs, credentials or keys in any
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bundled file, and every Superbill extract carries an `EXAMPLE ONLY` banner.
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- `evals/`: **Seam 2.** Runs the skills on a fixture project with `claude -p`,
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then grades the reply and runs the page check on the page it built:
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```
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uv run --with pytest --with playwright python tests/evals/run_eval.py a-empty
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```
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Results go to `evals/results/<fixture>.json`. To add a fixture, add an entry to
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`FIXTURES` in `run_eval.py`. An entry with a `"fixture"` key reuses another
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fixture folder with different answers: `c-keep` and `c-restyle` both run on
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`c-web-existing-frontend`, and also check what changed in the files it already had.
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An `"ai": True` entry (`d-ai-extraction`) expects the AI skill's React starter and
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runs `page_check_ai/` on the folder it built. An `"ai_desktop": True` entry
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(`e-pyqt-ai`) expects the desktop AI page and runs `page_check/` (with the bot replay)
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and `page_check_ai_desktop/` on it.
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For a bot fixture (`b-pyqt-bot`), the eval also dry-runs the generated
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`bot_runner.py`, saves its events to `evals/results/<fixture>.run.jsonl`, and
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replays them in the page check.
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- `fixtures/<letter>-<name>/`: small test projects for the evals.
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- `page_check_run_tab/` + `test_run_tab.py`: **Run tab skill.** The page filled with a test
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config and driven through `window.__pyMsg`: Trigger states, sheet preview with masked
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passwords, checkpoints driving steps/boxes/progress, green/amber/red endings, the no-input
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mode, the dark toggle and no horizontal scroll, each in light, dark and narrow mode. The
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Python side covers line parsing, endings, the sample workbook and `palette.py --write`.
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The end-to-end fake-bot check lives in the skill itself: `python skills/rpa-run-tab/templates/run_tab.py --selfcheck`.
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