Phase 3.5a(classifier+refusal gate+grounding) 위에 4개 Item 추가: Item 0: ask_events telemetry 배선 - AskEvent ORM 모델 + record_ask_event() — ask_events INSERT 완성 - defense_layers에 input_snapshot(query, chunks, answer) 저장 - refused/normal 두 경로 모두 telemetry 호출 Item 3: evidence 간 numeric conflict detection - 동일 단위 다른 숫자 → weak flag - "이상/이하/초과/미만" threshold 표현 → skip (FP 방지) Item 4: fabricated_number normalization 개선 - 단위 접미사 건/원 추가, 범위 표현(10~20%) 양쪽 추출 - bare number 2자리 이상만 (1자리 FP 제거) Item 1: exaone semantic verifier (판단권 잠금 배선) - verifier_service.py — 3s timeout, circuit breaker, severity 3단계 - direct_negation만 strong, numeric/intent→medium, 나머지→weak - verifier strong 단독 refuse 금지 — grounding과 교차 필수 - 6-tier re-gate (4라운드 리뷰 확정) - grounding strong 2+ OR max_score<0.2 → verifier skip Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
184 lines
6.1 KiB
Python
184 lines
6.1 KiB
Python
"""Exaone semantic verifier (Phase 3.5b).
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답변-근거 간 의미적 모순(contradiction) 감지. rule-based grounding_check 가 못 잡는
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미묘한 모순 포착. classifier 와 동일 패턴: circuit breaker + timeout + fail open.
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## Severity 3단계
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- strong: direct_negation (완전 모순) → re-gate 교차 자격
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- medium: numeric_conflict, intent_core_mismatch → confidence 하향 (누적 시 강제 low)
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- weak: nuance, unsupported_claim → 로깅 + mild confidence 하향
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## 핵심 원칙
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- **Verifier strong 단독 refuse 금지** — grounding strong 과 교차해야 refuse
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- **Timeout 3s** — 느리면 없는 게 낫다 (fail open)
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- MLX gate 미사용 (GPU Ollama concurrent OK)
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"""
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from __future__ import annotations
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import asyncio
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import time
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from dataclasses import dataclass, field
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from typing import TYPE_CHECKING, Literal
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from ai.client import AIClient, _load_prompt, parse_json_response
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from core.config import settings
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from core.utils import setup_logger
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if TYPE_CHECKING:
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from .evidence_service import EvidenceItem
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logger = setup_logger("verifier")
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LLM_TIMEOUT_MS = 3000
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CIRCUIT_THRESHOLD = 5
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CIRCUIT_RECOVERY_SEC = 60
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_failure_count = 0
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_circuit_open_until: float | None = None
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# severity 매핑 (프롬프트 "critical"/"minor" → 코드 strong/medium/weak)
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_SEVERITY_MAP: dict[str, dict[str, Literal["strong", "medium", "weak"]]] = {
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"direct_negation": {"critical": "strong", "minor": "strong"},
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"numeric_conflict": {"critical": "medium", "minor": "medium"},
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"intent_core_mismatch": {"critical": "medium", "minor": "medium"},
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"nuance": {"critical": "weak", "minor": "weak"},
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"unsupported_claim": {"critical": "weak", "minor": "weak"},
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}
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@dataclass(slots=True)
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class Contradiction:
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"""개별 모순 발견."""
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type: str # direct_negation / numeric_conflict / intent_core_mismatch / nuance / unsupported_claim
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severity: Literal["strong", "medium", "weak"]
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claim: str
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evidence_ref: str
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explanation: str
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@dataclass(slots=True)
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class VerifierResult:
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status: Literal["ok", "timeout", "error", "circuit_open", "skipped"]
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contradictions: list[Contradiction]
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elapsed_ms: float
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try:
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VERIFIER_PROMPT = _load_prompt("verifier.txt")
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except FileNotFoundError:
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VERIFIER_PROMPT = ""
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logger.warning("verifier.txt not found — verifier will always skip")
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def _build_input(
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answer: str,
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evidence: list[EvidenceItem],
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) -> str:
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"""답변 + evidence spans → 프롬프트."""
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spans = "\n\n".join(
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f"[{e.n}] {(e.title or '').strip()}\n{e.span_text}"
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for e in evidence
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)
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return (
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VERIFIER_PROMPT
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.replace("{answer}", answer)
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.replace("{numbered_evidence}", spans)
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)
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def _map_severity(ctype: str, raw_severity: str) -> Literal["strong", "medium", "weak"]:
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"""type + raw severity → 코드 severity 3단계."""
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type_map = _SEVERITY_MAP.get(ctype, {"critical": "weak", "minor": "weak"})
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return type_map.get(raw_severity, "weak")
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async def verify(
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query: str,
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answer: str,
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evidence: list[EvidenceItem],
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) -> VerifierResult:
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"""답변-근거 semantic 검증. Parallel with grounding_check.
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Returns:
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VerifierResult. status "ok" 이 아니면 contradictions 빈 리스트 (fail open).
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"""
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global _failure_count, _circuit_open_until
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t_start = time.perf_counter()
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if _circuit_open_until and time.time() < _circuit_open_until:
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return VerifierResult("circuit_open", [], 0.0)
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if not VERIFIER_PROMPT:
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return VerifierResult("skipped", [], 0.0)
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if not hasattr(settings.ai, "verifier") or settings.ai.verifier is None:
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return VerifierResult("skipped", [], 0.0)
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if not answer or not evidence:
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return VerifierResult("skipped", [], 0.0)
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prompt = _build_input(answer, evidence)
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client = AIClient()
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try:
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async with asyncio.timeout(LLM_TIMEOUT_MS / 1000):
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raw = await client._request(settings.ai.verifier, prompt)
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_failure_count = 0
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except asyncio.TimeoutError:
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_failure_count += 1
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if _failure_count >= CIRCUIT_THRESHOLD:
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_circuit_open_until = time.time() + CIRCUIT_RECOVERY_SEC
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logger.error(f"verifier circuit OPEN for {CIRCUIT_RECOVERY_SEC}s")
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logger.warning("verifier timeout")
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return VerifierResult(
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"timeout", [],
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(time.perf_counter() - t_start) * 1000,
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)
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except Exception as e:
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_failure_count += 1
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if _failure_count >= CIRCUIT_THRESHOLD:
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_circuit_open_until = time.time() + CIRCUIT_RECOVERY_SEC
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logger.error(f"verifier circuit OPEN for {CIRCUIT_RECOVERY_SEC}s")
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logger.warning(f"verifier error: {e}")
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return VerifierResult(
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"error", [],
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(time.perf_counter() - t_start) * 1000,
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)
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finally:
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await client.close()
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elapsed_ms = (time.perf_counter() - t_start) * 1000
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parsed = parse_json_response(raw)
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if not isinstance(parsed, dict):
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logger.warning("verifier parse failed raw=%r", (raw or "")[:200])
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return VerifierResult("error", [], elapsed_ms)
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# contradiction 파싱
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raw_items = parsed.get("contradictions") or []
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if not isinstance(raw_items, list):
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raw_items = []
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results: list[Contradiction] = []
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for item in raw_items[:5]:
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if not isinstance(item, dict):
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continue
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ctype = item.get("type", "")
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if ctype not in _SEVERITY_MAP:
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ctype = "unsupported_claim"
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raw_sev = item.get("severity", "minor")
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severity = _map_severity(ctype, raw_sev)
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claim = str(item.get("claim", ""))[:50]
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ev_ref = str(item.get("evidence_ref", ""))[:50]
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explanation = str(item.get("explanation", ""))[:30]
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results.append(Contradiction(ctype, severity, claim, ev_ref, explanation))
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logger.info(
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"verifier ok query=%r contradictions=%d strong=%d medium=%d elapsed_ms=%.0f",
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query[:60],
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len(results),
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sum(1 for c in results if c.severity == "strong"),
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sum(1 for c in results if c.severity == "medium"),
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elapsed_ms,
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)
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return VerifierResult("ok", results, elapsed_ms)
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