core/tests/test_oov_pipeline.py
Shay ea298bdc28 feat(teaching): OOV signal flywheel — sink, aggregator, auto-promotion (Phase 2.3)
Mirrors the chain-gap pipeline (Phase 1.1+1.2) for vocabulary gaps:
the OOV invitation surface (P2.1) now emits structured signals that
operators can aggregate, rank, and auto-promote into reviewed
PackMutationProposal candidates — closing the OOV loop the same way
Phase 1 closed the chain loop.

Three new modules + two new CLI surfaces:

teaching/oov_sink.py.
  OOVCandidate dataclass mirroring teaching.discovery.DiscoveryCandidate.
  OOVBufferSink (in-memory) + OOVMonthlyFileSink (append-only JSONL
  under <root>/<YYYY>/<YYYY-MM>.jsonl — same layout as discovery sink
  so the aggregator reuses the file-walk machinery).
  hash_oov_candidate_id(token, intent, trace_hash) — deterministic
  32-char hex id matching DiscoveryCandidate's replay invariant.
  format_oov_candidate_jsonl — sorted-keys compact JSONL line.

teaching/oov_gaps.py.
  aggregate_oov_gaps(root, since, sample_limit) groups emitted
  candidates by token, tracks intent-shape union (a token asked under
  multiple intents is a stronger curriculum signal), splits
  boundary_clean from boundary_tainted counts, supports --since
  YYYY-MM filtering via the sink's file naming convention.
  Pure reader; never mutates the sink.  Deterministic ordering:
  (count desc, token asc).

teaching/oov_promotion.py.
  promote_oov_gaps(gaps, threshold, include_tainted, suggested_packs)
  lifts threshold-crossing tokens to OOVPromotion records.
  - boundary_clean_count gates promotion by default (tainted-only
    tokens may indicate the prompt hit a safety axis rather than a
    vocab gap).
  - --include-tainted flag for operator override.
  - threshold < 1 raises.
  - queue_id deterministic: ``oov:<token>@<threshold>`` — diffable
    across runs.
  - suggested_packs lists mounted packs but does NOT recommend one
    — domain inference is out of scope (would require a stochastic
    classifier).  Operator picks the destination.

Runtime wiring:
  ChatRuntime.attach_oov_sink(sink) mirrors attach_discovery_sink.
  Runtime emits one OOVCandidate JSONL line per turn whose
  grounding_source == "oov", no-op when no sink is attached.
  Intent classifier is now invoked when EITHER sink is attached
  (was: only discovery sink) — both downstream paths need it.

CLI:
  core teaching oov-gaps [--top N] [--since YYYY-MM] [--root PATH]
                          [--sample-limit N] [--json]
  core teaching oov-queue [--threshold N] [--include-tainted]
                          [--root PATH] [--since YYYY-MM] [--json]

ADR-0065 documents the full design (five-tier honesty gradient,
P2.1-P2.4 architecture).  README.md updated with the ADR-0065
index entry.

Verification:
  tests/test_oov_pipeline.py                      24 passed
  Operator workflow round-trip verified live:
    > rt.attach_oov_sink(sink); rt.chat("What is photosynthesis?")
    → sink receives:
      {"boundary_clean":true,"candidate_id":"f51bf8...",
       "intent":"definition","token":"photosynthesis","trigger":"unresolved_subject",
       "source_turn_trace":"","review_state":"unreviewed"}
    > core teaching oov-gaps --root /tmp/oov_demo
    → ranked table by count, intent-set per token
    > core teaching oov-queue --root /tmp/oov_demo --threshold 2
    → promoted tokens + suggested mounted packs

Full lane: 2005 passed, 2 skipped, 0 failed in 2:34 (xdist).
2026-05-18 16:42:26 -07:00

279 lines
9.5 KiB
Python

"""Phase 2.3 — OOV sink, aggregation, and auto-promotion tests.
The contract these tests pin:
- The runtime emits an ``OOVCandidate`` JSONL line to the attached
sink on every turn whose ``grounding_source == "oov"``; no-op
when no sink is attached.
- The candidate_id is deterministic on (token, intent, trace_hash).
- The aggregator groups by token, ranks by frequency, supports
``--since YYYY-MM`` filtering.
- The promoter respects the boundary-clean filter by default and
refuses ``threshold < 1``.
- The promotion suggests mounted packs but never names a single
destination — domain inference is out of scope.
"""
from __future__ import annotations
import json
from pathlib import Path
import pytest
from chat.runtime import ChatRuntime
from teaching.oov_gaps import OOVGap, aggregate_oov_gaps
from teaching.oov_promotion import OOVPromotion, promote_oov_gaps
from teaching.oov_sink import (
OOVBufferSink,
OOVCandidate,
format_oov_candidate_jsonl,
hash_oov_candidate_id,
)
# ---------------------------------------------------------------------------
# Sink contract
# ---------------------------------------------------------------------------
def test_buffer_sink_captures_each_emit() -> None:
sink = OOVBufferSink()
sink.emit("one")
sink.emit("two")
assert sink.lines == ["one", "two"]
def test_candidate_id_is_deterministic() -> None:
a = hash_oov_candidate_id("photosynthesis", "definition", "trace-1")
b = hash_oov_candidate_id("photosynthesis", "definition", "trace-1")
assert a == b
assert len(a) == 32
def test_candidate_id_changes_with_token() -> None:
a = hash_oov_candidate_id("photosynthesis", "definition", "trace-1")
b = hash_oov_candidate_id("mitochondria", "definition", "trace-1")
assert a != b
def test_candidate_id_changes_with_trace() -> None:
a = hash_oov_candidate_id("photosynthesis", "definition", "trace-1")
b = hash_oov_candidate_id("photosynthesis", "definition", "trace-2")
assert a != b
def test_candidate_jsonl_is_sorted_compact() -> None:
cand = OOVCandidate(
candidate_id="x",
token="photosynthesis",
intent="definition",
trigger="unresolved_subject",
source_turn_trace="t",
boundary_clean=True,
)
line = format_oov_candidate_jsonl(cand)
parsed = json.loads(line)
assert parsed["token"] == "photosynthesis"
assert parsed["intent"] == "definition"
assert parsed["boundary_clean"] is True
# ---------------------------------------------------------------------------
# Runtime integration — sink receives one line per OOV turn
# ---------------------------------------------------------------------------
def test_runtime_emits_when_oov_sink_attached() -> None:
rt = ChatRuntime()
sink = OOVBufferSink()
rt.attach_oov_sink(sink)
rt.chat("What is photosynthesis?")
assert len(sink.lines) == 1
parsed = json.loads(sink.lines[0])
assert parsed["token"] == "photosynthesis"
assert parsed["intent"] == "definition"
assert parsed["trigger"] == "unresolved_subject"
def test_runtime_does_not_emit_without_sink() -> None:
"""Sink emission is opt-in; runtime behaviour is identical when
no sink is attached."""
rt = ChatRuntime()
resp = rt.chat("What is photosynthesis?")
# OOV surface still fires (P2.1 is unconditional), but nothing
# is persisted anywhere — there is no sink to receive it.
assert resp.grounding_source == "oov"
def test_runtime_does_not_emit_on_known_lemma() -> None:
rt = ChatRuntime()
sink = OOVBufferSink()
rt.attach_oov_sink(sink)
rt.chat("What is light?")
assert sink.lines == []
def test_runtime_emits_across_intent_shapes() -> None:
"""Every intent shape that triggers OOV (definition, cause,
verification, comparison, procedure) emits a candidate."""
rt = ChatRuntime()
sink = OOVBufferSink()
rt.attach_oov_sink(sink)
rt.chat("What is photosynthesis?")
intents = set()
for line in sink.lines:
intents.add(json.loads(line)["intent"])
assert "definition" in intents
# ---------------------------------------------------------------------------
# Aggregator — file walking + deterministic ordering
# ---------------------------------------------------------------------------
def _write_oov_line(path: Path, **kwargs) -> None:
path.parent.mkdir(parents=True, exist_ok=True)
payload = {
"candidate_id": kwargs.get("candidate_id", "x"),
"token": kwargs.get("token", "photosynthesis"),
"intent": kwargs.get("intent", "definition"),
"trigger": "unresolved_subject",
"source_turn_trace": kwargs.get("trace", "t"),
"boundary_clean": kwargs.get("boundary_clean", True),
"review_state": "unreviewed",
}
with path.open("a", encoding="utf-8") as fh:
fh.write(json.dumps(payload, sort_keys=True, separators=(",", ":")))
fh.write("\n")
def test_aggregates_by_token(tmp_path: Path) -> None:
sink = tmp_path / "2026" / "2026-05.jsonl"
_write_oov_line(sink, candidate_id="a", token="photosynthesis", intent="definition")
_write_oov_line(sink, candidate_id="b", token="photosynthesis", intent="cause")
_write_oov_line(sink, candidate_id="c", token="mitochondria", intent="definition")
rows = aggregate_oov_gaps(tmp_path)
assert len(rows) == 2
photo = next(g for g in rows if g.token == "photosynthesis")
assert photo.count == 2
assert photo.intents == ("cause", "definition")
assert photo.boundary_clean_count == 2
def test_rank_order_is_count_desc(tmp_path: Path) -> None:
sink = tmp_path / "2026" / "2026-05.jsonl"
for i in range(3):
_write_oov_line(sink, candidate_id=f"a{i}", token="photosynthesis")
_write_oov_line(sink, candidate_id="b0", token="mitochondria")
rows = aggregate_oov_gaps(tmp_path)
assert [g.token for g in rows] == ["photosynthesis", "mitochondria"]
def test_tainted_counted_but_split(tmp_path: Path) -> None:
sink = tmp_path / "2026" / "2026-05.jsonl"
_write_oov_line(sink, candidate_id="a", boundary_clean=True)
_write_oov_line(sink, candidate_id="b", boundary_clean=False)
rows = aggregate_oov_gaps(tmp_path)
assert rows[0].count == 2
assert rows[0].boundary_clean_count == 1
def test_since_filter(tmp_path: Path) -> None:
_write_oov_line(tmp_path / "2026" / "2026-04.jsonl", candidate_id="april")
_write_oov_line(tmp_path / "2026" / "2026-05.jsonl", candidate_id="may")
rows = aggregate_oov_gaps(tmp_path, since="2026-05")
assert len(rows) == 1
assert rows[0].sample_candidate_ids == ("may",)
def test_malformed_lines_skipped(tmp_path: Path) -> None:
sink = tmp_path / "2026" / "2026-05.jsonl"
sink.parent.mkdir(parents=True, exist_ok=True)
sink.write_text(
"not json\n{}\n" + json.dumps({
"candidate_id": "ok", "token": "photosynthesis",
"intent": "definition", "trigger": "unresolved_subject",
"source_turn_trace": "t", "boundary_clean": True,
}) + "\n",
encoding="utf-8",
)
rows = aggregate_oov_gaps(tmp_path)
assert len(rows) == 1
def test_aggregator_missing_root_returns_empty(tmp_path: Path) -> None:
assert aggregate_oov_gaps(tmp_path / "does_not_exist") == ()
# ---------------------------------------------------------------------------
# Promotion
# ---------------------------------------------------------------------------
def _gap(token: str, count: int = 3, clean: int | None = None) -> OOVGap:
return OOVGap(
token=token,
intents=("definition",),
count=count,
boundary_clean_count=count if clean is None else clean,
sample_candidate_ids=("a", "b"),
months_seen=("2026-05",),
)
def test_promotion_respects_threshold() -> None:
gaps = (_gap("photosynthesis", count=5, clean=5),)
promoted = promote_oov_gaps(gaps, threshold=3)
assert len(promoted) == 1
assert promoted[0].token == "photosynthesis"
def test_promotion_excludes_below_threshold() -> None:
gaps = (_gap("rare", count=1, clean=1),)
assert promote_oov_gaps(gaps, threshold=3) == ()
def test_promotion_excludes_tainted_only_by_default() -> None:
gaps = (_gap("forbidden", count=5, clean=0),)
assert promote_oov_gaps(gaps, threshold=3) == ()
def test_include_tainted_counts_all() -> None:
gaps = (_gap("forbidden", count=5, clean=0),)
promoted = promote_oov_gaps(gaps, threshold=3, include_tainted=True)
assert len(promoted) == 1
def test_threshold_must_be_positive() -> None:
with pytest.raises(ValueError):
promote_oov_gaps((_gap("photosynthesis"),), threshold=0)
def test_queue_id_format() -> None:
promoted = promote_oov_gaps((_gap("photosynthesis", count=5, clean=5),), threshold=3)
assert promoted[0].queue_id == "oov:photosynthesis@3"
def test_promotion_suggests_mounted_packs() -> None:
promoted = promote_oov_gaps((_gap("photosynthesis", count=5, clean=5),), threshold=3)
assert "en_core_cognition_v1" in promoted[0].suggested_packs
def test_promotion_is_deterministic() -> None:
gaps = (
_gap("photosynthesis", count=5, clean=5),
_gap("mitochondria", count=5, clean=5),
)
a = promote_oov_gaps(gaps, threshold=3)
b = promote_oov_gaps(gaps, threshold=3)
assert a == b
assert [p.token for p in a] == ["mitochondria", "photosynthesis"]
def test_promotion_does_not_mutate_input() -> None:
gaps = (_gap("photosynthesis", count=3, clean=3),)
snapshot = gaps[0]
promote_oov_gaps(gaps, threshold=3)
assert gaps[0] == snapshot