arborist/tests/test_repair.py
russell@unturf.com 9930fc7f1d
qa: chain-segment failure localization + re-prompt repair tier
Two enhancements continuing the toy-Hermes design pass:

#1 Chain-segment failure localization

aborist/qa/dag.py: `localize_failure(audit_mode, n_sources, n_quotes,
n_verified)` maps a non-STRICT verdict to the pipeline stage that
introduced the failure:

    retrieval  no admitted sources (gate over-rejected, or corpus
               genuinely lacks the topic) → ingest more / relax breadth
    context    sources retrieved but no quotes extracted (per-source
               cap dropped relevant content, or model declined to cite)
               → raise cap / tighten prompt
    answer     quotes extracted but didn't all verify (model fabricated,
               paraphrased inside quotes, appended citations) → mechanical
               + re-prompt repair targets exactly this case

`failure_stage` lands on the run_dag's verify node payload AND on the
result dict so an operator can read the reason at a glance — `failure_stage='answer'`
means stop tuning the verifier & fix the model behavior. Debugging
becomes typed instead of vague.

#2 Re-prompt repair (second tier of the hybrid loop)

aborist/qa/repair.py: `reprompt_repair(...)` builds a feedback message
naming the failed quotes & asks the model to rewrite using only
verbatim citations. Hard rule: only fires when
`policy["repair_max_reprompts"] > 0` (default 0); caller enforces the
cap by looping at most that many times.

aborist/qa/query.py + aborist/qa/runner.py: after mechanical repair,
if the answer is still HYBRID/UNGROUNDED with unverified quotes,
loop up to `repair_max_reprompts` times. Each iteration: build
feedback (assistant turn with current answer + user turn with failed
spans), call LLM, verify. Accept the new answer if `n_verified`
strictly improved; otherwise break (the model's not converging,
don't waste cycles).

The mechanical + re-prompt combination handles the cases each tier
declines individually:
    mechanical alone:  synthetic_elision split, trailing_artifact trim,
                       no_overlap remove
    + re-prompt:       paraphrase, partial_paraphrase, interior_elision
                       needing semantic judgment, fabrications the
                       model can recognize when shown its own quote

`repair_max_reprompts` lives in DEFAULT_QUERY_POLICY +
DEFAULT_POLICY so it folds into governance_policy_hash. Default 0
preserves single-shot semantics for callers that don't opt in. Each
re-prompt iteration adds a `{action: reprompt_rewrite, diagnosis:
model_feedback_loop}` entry to repair_changes; audit chain captures
the full transition through the existing providence_repair event.

Tests:
- dag: localize_failure across all four cases (STRICT, retrieval,
  context, answer); failure_stage embedded in run_dag verify node.
- repair: stub client with sequenced answers (failing first, clean
  on re-prompt) — assert two LLM calls, STRICT verdict, reprompt_rewrite
  in the change log.

484 tests pass (dag +5, repair +1). The pre-existing test_burn flake
under full-suite ordering remains; passes in isolation.
2026-04-29 19:27:33 -04:00

283 lines
10 KiB
Python

"""Mechanical answer-repair loop.
`mechanical_repair` applies sidecar repair suggestions (synthetic_elision
split, trailing_artifact trim, no_overlap remove) to an answer text
deterministically. The query/ask runners gate this behind
`policy["repair_enabled"]` and re-verify the repaired text; if the
post-repair verdict isn't worse, the repaired answer is persisted with
a `providence_repair` audit event recording the pre→post transition.
These tests cover:
- Each repair action produces the right substitution.
- Idempotence: running repair on already-clean text is a no-op.
- query() integration: repair_enabled=True can promote HYBRID/quote →
STRICT/quote on synthetic_elision cases without an extra LLM call.
- query() default repair_enabled=False leaves answer text untouched.
"""
from __future__ import annotations
from typing import Iterator
from aborist.document import Document
from aborist.ingest import ingest_source
from aborist.qa import query
from aborist.qa.client import StubClient
from aborist.qa.repair import mechanical_repair
from aborist.source import Source
from aborist.store import connect
# ---------------------------------------------------------------- mechanical_repair
def test_mechanical_repair_splits_synthetic_elision():
"""`"prefix [...] suffix"` (both halves verbatim) becomes
`"prefix" ... "suffix"`."""
context = (
"The film centers on the fictional Isla Nublar, in Costa Rica. "
"Universal Studios acquired the rights to the novel."
)
answer = (
'The plot states "The film centers on the fictional Isla Nublar [...] '
'Universal Studios acquired the rights to the novel".'
)
bad_quote = (
"The film centers on the fictional Isla Nublar [...] "
"Universal Studios acquired the rights to the novel"
)
out = mechanical_repair(answer, [bad_quote], context)
assert len(out["changes"]) == 1
assert out["changes"][0]["action"] == "split_into_two_quotes"
# Two separate quoted spans now appear:
assert '"The film centers on the fictional Isla Nublar"' in out["repaired_text"]
assert '"Universal Studios acquired the rights to the novel"' in out["repaired_text"]
# `[...]` no longer appears inside any single quoted span.
assert "[...]" not in out["repaired_text"]
def test_mechanical_repair_trims_trailing_citation():
"""`"prose. (Source: ...)"` becomes `"prose."`."""
context = (
"Pikachu can store electricity in its cheeks and release it in "
"lightning-based attacks. Pikachu evolves from Pichu."
)
bad_quote = (
"Pikachu can store electricity in its cheeks and release it in "
"lightning-based attacks. (Source: https://en.wikipedia.org/wiki/Pikachu)"
)
answer = f'According to source: "{bad_quote}"'
out = mechanical_repair(answer, [bad_quote], context)
assert len(out["changes"]) == 1
assert out["changes"][0]["action"] == "trim_trailing_artifact"
assert "(Source:" not in out["repaired_text"]
def test_mechanical_repair_removes_no_overlap_line():
"""Full-invention spans get the line stripped from the answer."""
context = "Pikachu is a Pokémon species."
bad_quote = "The Roman Senate convened in 49 BC to debate Caesar's rebellion"
answer = (
"- Pikachu lives in the wild\n"
f'- "{bad_quote}"\n'
"- Pichu evolves into Pikachu\n"
)
out = mechanical_repair(answer, [bad_quote], context)
assert len(out["changes"]) == 1
assert out["changes"][0]["action"] == "remove_claim"
assert bad_quote not in out["repaired_text"]
# Other bullets preserved.
assert "Pikachu lives in the wild" in out["repaired_text"]
assert "Pichu evolves into Pikachu" in out["repaired_text"]
def test_mechanical_repair_idempotent_on_clean_text():
"""No unverified quotes → no change."""
context = "Cloud is the protagonist."
answer = 'The source: "Cloud is the protagonist".'
out = mechanical_repair(answer, [], context)
assert out["changes"] == []
assert out["repaired_text"] == answer
# ---------------------------------------------------------------- query() integration
class FakeSource(Source):
source_type = "test"
def __init__(self, docs):
self.docs = docs
def iter_documents(self) -> Iterator[Document]:
yield from self.docs
def _doc(uri, content):
return Document(uri=uri, content=content, source_type="test", title=uri.rsplit("/", 1)[-1])
def test_query_repair_disabled_default_leaves_answer_unchanged(tmp_path):
"""`policy["repair_enabled"]` defaults to False — answer text in the
persisted record matches what the LLM produced."""
main_db = tmp_path / "corpus.db"
qa_db = tmp_path / "qa.db"
long_text = (
"Capitalism is an economic system based on private ownership "
"of the means of production. " * 20
)
docs = [_doc("test://capitalism", long_text)]
conn = connect(main_db)
try:
ingest_source(conn, FakeSource(docs))
finally:
conn.close()
# Answer with a synthetic_elision-style bad quote.
bad_answer = (
'"Capitalism is an economic system based on private ownership '
'[...] of the means of production."'
)
result = query(
question="What is capitalism?",
qa_db=qa_db,
chat_client=StubClient(answer=bad_answer),
model_id="m",
single_db=main_db,
)
# Repair off → answer text unchanged from LLM output.
qa_conn = connect(qa_db)
try:
row = qa_conn.execute(
"SELECT answer_text FROM providence_cache WHERE cache_key=?",
(result["cache_key"],),
).fetchone()
finally:
qa_conn.close()
assert row["answer_text"] == bad_answer
assert result["repair_changes"] == []
def test_query_reprompt_rewrites_on_paraphrase_failure(tmp_path):
"""Re-prompt tier handles cases mechanical declines (paraphrase,
interior_elision needing semantic judgment). The stub returns a
failing answer on first call & a clean verbatim quote on the
second; with `repair_max_reprompts=1`, the system promotes the
verdict to STRICT and the persisted answer is the re-written one."""
main_db = tmp_path / "corpus.db"
qa_db = tmp_path / "qa.db"
src_text = (
"Capitalism is an economic system based on private ownership "
"of the means of production. " * 10
)
docs = [_doc("test://capitalism", src_text)]
conn = connect(main_db)
try:
ingest_source(conn, FakeSource(docs))
finally:
conn.close()
# First call: paraphrase inside a quote that won't substring-match
# AND won't trigger mechanical repair (no [...], no Source-tail, not
# full invention — clearly a paraphrase).
bad_answer = (
'"Capitalism is an economic philosophy based on personal control "'
'"over production"'
)
# Second call (re-prompt): clean verbatim quote.
good_answer = (
'"Capitalism is an economic system based on private ownership '
'of the means of production"'
)
class _SeqClient:
def __init__(self):
self.calls = []
self.answers = [bad_answer, good_answer]
def chat_completion(self, messages, **kw):
self.calls.append(messages)
return self.answers[len(self.calls) - 1] if self.calls else self.answers[0]
client = _SeqClient()
from aborist.qa.query import DEFAULT_QUERY_POLICY
policy = dict(DEFAULT_QUERY_POLICY)
policy["repair_enabled"] = True
policy["repair_max_reprompts"] = 1
result = query(
question="What is capitalism?",
qa_db=qa_db,
chat_client=client,
model_id="m",
single_db=main_db,
policy=policy,
)
assert len(client.calls) == 2 # one initial + one re-prompt
assert result["audit_mode"] == "STRICT"
assert any(
c["action"] == "reprompt_rewrite" for c in result["repair_changes"]
)
def test_query_repair_enabled_promotes_synthetic_elision_to_strict(tmp_path):
"""With `repair_enabled=True`, the mechanical loop splits a
`[...]`-elided quote into two verbatim spans, re-verifies, & lands
STRICT instead of HYBRID. Persisted answer is the repaired text."""
main_db = tmp_path / "corpus.db"
qa_db = tmp_path / "qa.db"
# Source phrase the model will fail to quote verbatim:
src_text = (
"Capitalism is an economic system based on private ownership "
"of the means of production. " * 20
)
docs = [_doc("test://capitalism", src_text)]
conn = connect(main_db)
try:
ingest_source(conn, FakeSource(docs))
finally:
conn.close()
bad_answer = (
'Per the source: "Capitalism is an economic system based on private ownership '
'[...] of the means of production".'
)
# Build a policy variant with repair_enabled=True.
from aborist.qa.query import DEFAULT_QUERY_POLICY
policy = dict(DEFAULT_QUERY_POLICY)
policy["repair_enabled"] = True
result = query(
question="What is capitalism?",
qa_db=qa_db,
chat_client=StubClient(answer=bad_answer),
model_id="m",
single_db=main_db,
policy=policy,
)
# Repair fired & promoted the verdict.
assert result["pre_repair_audit_mode"] in ("HYBRID", "UNGROUNDED")
assert result["audit_mode"] == "STRICT"
assert len(result["repair_changes"]) >= 1
assert result["repair_changes"][0]["action"] == "split_into_two_quotes"
# Persisted answer is the REPAIRED text (no `[...]` inside any quote).
qa_conn = connect(qa_db)
try:
row = qa_conn.execute(
"SELECT answer_text FROM providence_cache WHERE cache_key=?",
(result["cache_key"],),
).fetchone()
# Audit chain has the providence_repair event.
evt = qa_conn.execute(
"SELECT event_type, body FROM audit_events "
"WHERE event_type='providence_repair' ORDER BY seq DESC LIMIT 1"
).fetchone()
finally:
qa_conn.close()
assert "[...]" not in row["answer_text"]
assert evt is not None
assert evt["event_type"] == "providence_repair"