Files
US2KR/us2kr/summarize.py
T
jsahnandClaude Fable 5 ed48f4c96b Add an LLM fact-check pass over the generated briefing
After summarisation the report is verified against the collected
payload (numbers, directions, unsupported claims) by a second LLM call
with a Verification JSON schema. Major issues trigger one revision and
a re-check; minor-only verdicts are normalized to ok. Failures never
block delivery. The verdict is stored in the result JSON and shown on
the dashboard (badge + 검증 메모). Disable with US2KR_VERIFY_ENABLED.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-09-01 10:37:39 +09:00

73 lines
2.9 KiB
Python

"""Glue between the pipeline and the LLM layer."""
from __future__ import annotations
import logging
from us2kr.config import Settings
from us2kr.llm.base import LLMError, LLMProvider
from us2kr.llm.minimax import MiniMaxProvider
from us2kr.models import MarketPayload, Report, Verification
log = logging.getLogger(__name__)
def build_provider(settings: Settings) -> LLMProvider:
"""Construct the configured LLM provider (MiniMax only for now)."""
return MiniMaxProvider(settings)
def summarize_payload(payload: MarketPayload, provider: LLMProvider) -> tuple[Report, str]:
"""Summarise via the provider and guarantee `report.data_gaps` includes every payload gap."""
report, model_used = provider.summarize(payload)
merged: list[str] = []
for gap in [*payload.data_gaps, *report.data_gaps]:
if gap and gap not in merged:
merged.append(gap)
if merged != list(report.data_gaps):
report = report.model_copy(update={"data_gaps": merged})
log.info("summary produced by %s (%d data gaps)", model_used, len(merged))
return report, model_used
def _consistent(verification: Verification) -> Verification:
"""Force `ok` to mean "no major issues" - verifier models are inconsistent about minor-only cases."""
ok = not verification.has_major
return verification if verification.ok == ok else verification.model_copy(update={"ok": ok})
def verify_and_revise(
payload: MarketPayload, report: Report, provider: LLMProvider
) -> tuple[Report, Verification]:
"""Fact-check the report; on major issues ask for one revision and re-check it.
Returns (possibly revised report, verification of the returned report). Raises LLMError only when
the *initial* verification cannot be produced; a failed revision keeps the original report.
"""
raw_verification, model = provider.verify(payload, report)
verification = _consistent(raw_verification)
log.info(
"verification by %s: ok=%s issues=%d (major=%s)",
model,
verification.ok,
len(verification.issues),
verification.has_major,
)
if not verification.has_major:
return report, verification
for issue in verification.issues:
log.warning("verification issue [%s] %s -> %s", issue.severity, issue.claim, issue.problem)
try:
revised, model = provider.revise(payload, report, verification.issues)
log.info("report revised by %s after verification issues", model)
re_verification, model = provider.verify(payload, revised)
re_verification = _consistent(re_verification)
log.info(
"re-verification by %s: ok=%s issues=%d", model, re_verification.ok, len(re_verification.issues)
)
return revised, re_verification
except LLMError as exc:
log.warning("revision failed; keeping the original report and verdict: %s", exc)
return report, verification