Phase 47 (owner permission 2026-08-27, TODO.md L10–11, roadmap R1): the
full Podman quadlet family (.container, .network, .volume, .image,
.pod, .kube, .swap, .os, .endpoint) and .j2 Jinja templates join the
allowed + default A9 import formats, chunked as plain text (owner
decision — no TOML/Jinja-aware splitter). No env configuration needed:
a default import now indexes them.
- app/config.py: _ALLOWED_IMPORT_EXTENSIONS + the default
import_extensions CSV gain the ten names (the original seven first);
the never-widen BOR_IMPORT_EXTENSIONS validator is untouched and
still rejects truly unknown extensions.
- app/rag/chunker.py: ten _FORMAT_CHUNKERS entries -> chunk_text
(HARD_MAX_CHARS 1200 honored, unknown-suffix fallback unchanged);
docstring/comments cite the A9 revision 2026-08-27.
- tests/fixtures/docs/homelab/: quadlet/compose.container (realistic
quadlet TOML, >1500 chars, [Unit]/[Service]/[Container] sections,
RESE-QUADLET-SENTINEL-77aa), quadlet/lan.network,
quadlet/cache.volume, templates/deploy.j2 (for/set/if Jinja
constructs + RESE-JINJA-SENTINEL-33dd). Every suite that seeds the
fixture tree updates its 9 -> 13 document-count constants.
- tests/unit/test_config.py: allowed set carries all seventeen formats,
default CSV + dotted import_extension_set include the ten, the
validator accepts the new names and still rejects unknowns.
- tests/unit/test_chunker.py: dispatch parity with chunk_text for every
new suffix (parametrized), the .container fixture chunks >=2 under
the cap with the sentinel surviving, the .j2 fixture keeps {{ }}
verbatim, the unknown-suffix fallback is unchanged.
- tests/unit/test_importer.py: a default-extensions walk over a temp
tree indexes exactly the ten new files (unknown/hidden/excluded
filtered), the original seven still walk, stem-title fallback holds.
- tests/integration/test_import_quadlet_jinja.py (new): import_sources
over a temp tree with .container/.volume/.j2 -> documents + chunks
rows with stem titles; delta re-import updates only the changed .j2
doc; prune drops the deleted .volume doc with cascade.
- tests/e2e/test_quadlet_jinja_import.py (new, story suite, mock-only,
isolation): GET /api/docs (admin session) lists the four new-format
docs with non-zero chunk counts and stem titles; the Sources table
renders a row + .doc-link per file; the phase-26 modal shows the
.container TOML ([Container] section + sentinel) with stem title and
the container format badge; a RESE-JINJA-SENTINEL-33dd question
FTS-matches the .j2 chunk -> honest-positive (A8: LOW requires zero
FTS hits) — the bubble is not .is-deflected and a source chip names
templates/deploy.j2.
- README.md + .env.example: the extended default format set (A9
revised 2026-08-27, plain-text chunking, narrow-only rule intact).
- .agent/PLAN.md: the A9 revision (owner-locked R1) — A9 row status,
the revision note under the anchors table, and the §5 chunking-policy
+ §11 workflow lines. The only PLAN edit this phase.
Gates: uv run pytest 795 passed; app/ coverage TOTAL 99% (>90%);
ruff check + pyright clean; story E2E 4/4 in isolation (DB up);
regression E2E suites test_import_documents (3) / test_sync_button
(3) / test_git_sources_admin (6) green in isolation.
Also records the 47_quadlet_jinja_import task-file moves (01–03)
todo/ -> complete/.
282 lines
11 KiB
Python
282 lines
11 KiB
Python
"""Phase 31 E2E (Playwright): the stored KB overview reaches every turn.
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Story: ``.agent/user_stories/kb-overview-prompt.md``
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Run in isolation (DB must be up: ``podman compose up -d db``):
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uv run pytest tests/e2e/test_kb_overview.py -v --no-cov
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The story: a single-row ``kb_overview`` table holds a lite-generated
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plain-text outline of the KB's basic categories; every chat turn — HIGH
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(grounded) and LOW (deflected) alike — injects it into the system prompt
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as the ``<knowledge_base>`` section, so the agent knows roughly what the
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KB contains before retrieval returns. The mock LLM echoes the section's
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first bullet into its answer (`` (kb: <first bullet>)`` — the
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``(tuning: …)`` steering-echo precedent), which makes the prompt change
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observable in the rendered UI deterministically.
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The row is seeded **directly in the DB** so the INJECTION path is what
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is under test (the import-time trigger is integration-tested in
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``tests/integration/test_import_docs_overview.py``). The outline is
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multi-line so the echo must pick the FIRST bullet — not the intro line,
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not a later line. The last test additionally runs the real
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``regenerate_overview`` against the mock to cover the mock's
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``KB_OVERVIEW_MODE`` generation branch end-to-end (stored outline is the
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byte-stable 8-token digest of the generator's document list).
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Test → story mapping (Playwright Mapping Rule):
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1. ``test_on_topic_answer_echoes_kb_overview``
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2. ``test_deflected_answer_still_echoes_kb_overview``
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3. ``test_absent_row_yields_no_kb_echo``
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4. ``test_mock_generated_outline_is_stored_and_echoed``
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"""
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from __future__ import annotations
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import asyncio
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import re
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from pathlib import Path
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from threading import Thread
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from typing import Any
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from playwright.sync_api import Page, expect
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from sqlalchemy import select, text
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from app.config import Settings
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from app.db import SessionLocal
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from app.models import Document, KbOverview, QueryLog
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from app.rag.importer import ImportSummary, import_sources
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from app.rag.llm import LLMClient
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from app.rag.overview import build_overview_prompt, regenerate_overview
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from tests.e2e.mock_llm import TOKEN_RE
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REPO = Path(__file__).resolve().parents[2]
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FIXTURES = REPO / "tests" / "fixtures" / "docs"
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QUESTION = "How is my Kubernetes cluster set up?"
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OFF_TOPIC = "How do I bake sourdough bread?"
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MOCK_ANSWER_MARKER = "Deterministic mock answer for E2E"
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#: The stored outline: multi-line ``-`` bullets (the generator's locked
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#: format). The echo must pick the FIRST bullet — the parsing (skip the
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#: intro line, strip the dash) is part of the story.
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OVERVIEW = (
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"- Kubernetes cluster and node maintenance notes\n"
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"- Backup schedules and restore runbooks\n"
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"- Networking: static DNS and kafkabridge"
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)
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FIRST_BULLET = "Kubernetes cluster and node maintenance notes"
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KB_ECHO = f"(kb: {FIRST_BULLET})"
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# --- Importer + thread helpers (test_document_summaries.py pattern) ---
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async def _import_fixtures(mock_port: int) -> ImportSummary:
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kwargs: dict[str, Any] = {
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"_env_file": None,
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"llm_base_url": f"http://127.0.0.1:{mock_port}/v1",
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}
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settings = Settings(**kwargs) # pyright: ignore[reportCallIssue]
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return await import_sources([FIXTURES], LLMClient(settings))
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def _run_in_thread(coro: Any) -> Any:
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"""Run a coroutine on a worker thread.
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Playwright's sync API keeps an asyncio loop running on the test thread,
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so ``asyncio.run`` cannot be called directly from a test body.
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"""
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box: dict[str, Any] = {}
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def runner() -> None:
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try:
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box["value"] = asyncio.run(coro)
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except BaseException as e: # noqa: BLE001 — re-raised on the test thread
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box["error"] = e
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t = Thread(target=runner)
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t.start()
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t.join()
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if "error" in box:
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raise box["error"]
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return box["value"]
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def _reset_db(
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mock_port: int, seed: bool, overview: str | None = None
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) -> ImportSummary | None:
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"""Truncate the KB (+ query log, steering, kb_overview), re-import the
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fixtures, and optionally seed the single ``kb_overview`` row."""
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with SessionLocal() as db:
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db.execute(
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text("TRUNCATE chunks, documents, query_log, steering_notes, kb_overview")
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)
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db.commit()
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if overview is not None:
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db.add(KbOverview(id=1, content=overview))
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db.commit()
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if not seed:
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return None
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return _run_in_thread(_import_fixtures(mock_port))
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def _ask(page: Page, app_url: str, question: str, done_text: str) -> Any:
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"""Submit *question* and wait until the streamed answer has fully
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landed.
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``done_text`` is the deterministic last thing the answer contains for
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its path: the ``(kb: …)`` echo (grounded AND deflected turns with a
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stored row — it is appended after everything else) or the mock
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marker (the no-row control, where the echo is absent by design).
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"""
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page.set_default_timeout(30_000)
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page.goto(app_url)
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page.fill("#message-input", question)
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page.click("#send-btn")
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bubble = page.locator(".msg.brain .bubble")
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bubble.first.wait_for(state="visible", timeout=30_000)
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expect(bubble.first).to_contain_text(done_text, timeout=30_000)
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expect(page.locator("#send-btn")).to_be_enabled()
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expect(page.locator("#send-label")).to_have_text("Send")
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return bubble.first
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def _last_query_log() -> QueryLog:
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with SessionLocal() as db:
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rows = db.scalars(select(QueryLog)).all()
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assert len(rows) == 1, f"expected exactly one query_log row, got {len(rows)}"
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return rows[0]
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def _overview_row() -> KbOverview | None:
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with SessionLocal() as db:
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return db.get(KbOverview, 1)
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def _doc_rows() -> list[tuple[str, str, str, str | None]]:
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with SessionLocal() as db:
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rows = db.execute(
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select(Document.source, Document.path, Document.title, Document.summary)
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.order_by(Document.source, Document.path)
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).all()
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return [(source, path, title, summary) for source, path, title, summary in rows]
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# --- 1. Injection: grounded turn ------------------------------------------
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def test_on_topic_answer_echoes_kb_overview(
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page: Page, app_url: str, mock_llm: int, db_ready: None
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) -> None:
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"""On-topic question with a stored row: the rendered answer ENDS with
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the mock's echo of the ``<knowledge_base>`` section's first bullet —
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only possible if the section reached the LLM prompt."""
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summary = _reset_db(mock_llm, seed=True, overview=OVERVIEW)
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assert summary is not None and summary.added == 13 # phase 47 added quadlet+j2
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assert _overview_row() is not None # the row the turn must inject
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bubble = _ask(page, app_url, QUESTION, KB_ECHO)
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# The echo is the LAST thing in the bubble (the section was in the
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# HIGH prompt) and names the FIRST outline bullet (not the intro,
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# not a later line).
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expect(bubble).to_have_text(
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re.compile(rf"{re.escape(KB_ECHO)}\s*$"), timeout=30_000
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)
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# Grounded, not deflected — the overview does not change the gate.
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expect(page.locator(".msg.brain.is-deflected")).to_have_count(0)
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row = _last_query_log()
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assert row.question == QUESTION
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assert row.deflected is False
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# --- 2. Injection: deflected turn ------------------------------------------
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def test_deflected_answer_still_echoes_kb_overview(
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page: Page, app_url: str, mock_llm: int, db_ready: None
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) -> None:
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"""Off-topic question (LOW path): the deflected answer STILL carries
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the echo — the ``<knowledge_base>`` section is in the LOW prompt too
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(that is what lets the model offer real alternatives)."""
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_reset_db(mock_llm, seed=True, overview=OVERVIEW)
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# The deflection answer carries no mock marker — the kb echo is its
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# deterministic end, so it doubles as the completion signal.
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bubble = _ask(page, app_url, OFF_TOPIC, KB_ECHO)
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expect(page.locator(".msg.brain.is-deflected")).to_have_count(1)
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expect(bubble).to_have_text(re.compile(r"haven't done anything like that"))
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expect(bubble).to_have_text(
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re.compile(rf"{re.escape(KB_ECHO)}\s*$"), timeout=30_000
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)
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row = _last_query_log()
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assert row.question == OFF_TOPIC
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assert row.deflected is True
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# --- 3. Absence: no row → no echo ------------------------------------------
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def test_absent_row_yields_no_kb_echo(
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page: Page, app_url: str, mock_llm: int, db_ready: None
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) -> None:
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"""Delete the row: a fresh question's answer carries NO ``(kb: …)``
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suffix — the section is absent and the prompt behaves exactly like
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the pre-phase text (byte-identity is unit-asserted; this proves it
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end-to-end through the rendered answer)."""
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summary = _reset_db(mock_llm, seed=True, overview=OVERVIEW)
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assert summary is not None
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# Now delete the row (the absence control).
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with SessionLocal() as db:
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db.execute(text("TRUNCATE kb_overview"))
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db.commit()
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assert _overview_row() is None
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bubble = _ask(page, app_url, QUESTION, MOCK_ANSWER_MARKER)
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expect(bubble).to_contain_text(MOCK_ANSWER_MARKER)
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expect(bubble).not_to_contain_text("(kb:")
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row = _last_query_log()
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assert row.deflected is False # grounded either way — only the echo is gone
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# --- 4. Generation: KB_OVERVIEW_MODE branch through the real regenerator ----
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def test_mock_generated_outline_is_stored_and_echoed(
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page: Page, app_url: str, mock_llm: int, db_ready: None
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) -> None:
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"""The mock's ``KB_OVERVIEW_MODE`` branch is exercised end-to-end:
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the real ``regenerate_overview`` (``LLMClient`` pointed at the mock)
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stores the byte-stable 8-token digest of the generator's document
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list, and a chat turn echoes its first bullet."""
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summary = _reset_db(mock_llm, seed=True, overview=None)
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assert summary is not None and summary.added == 13 # phase 47 added quadlet+j2
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assert _overview_row() is None # direct import never regenerates
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kwargs: dict[str, Any] = {
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"_env_file": None,
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"llm_base_url": f"http://127.0.0.1:{mock_llm}/v1",
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}
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settings = Settings(**kwargs) # pyright: ignore[reportCallIssue]
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ok = _run_in_thread(regenerate_overview(LLMClient(settings)))
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assert ok is True
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row = _overview_row()
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assert row is not None and row.id == 1
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# Byte-stable expectation: the mock digests the generator's user
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# message (the same document list, the same cap) to its first 8 tokens.
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_, user = build_overview_prompt(_doc_rows())
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expected = "Knowledge base outline:\n- " + " ".join(
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TOKEN_RE.findall(user.lower())[:8]
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)
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assert row.content == expected
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first_bullet = row.content.splitlines()[1].removeprefix("- ").strip()
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assert first_bullet # the digest line is non-empty
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# A grounded chat turn echoes the STORED outline's first bullet.
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bubble = _ask(page, app_url, QUESTION, f"(kb: {first_bullet})")
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expect(bubble).to_have_text(
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re.compile(rf"\(kb: {re.escape(first_bullet)}\)\s*$"), timeout=30_000
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)
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expect(page.locator(".msg.brain.is-deflected")).to_have_count(0)
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