649 lines
26 KiB
Python
649 lines
26 KiB
Python
"""The answer layer may rephrase evidence; it may not add to it.
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Every test here is a fabrication the generator could plausibly produce, and
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the assertion is that the clinician never sees it. The dose figures are taken
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from the real METFORMIN and PARACETAMOL sections in `duocthu_v1`.
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"""
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from __future__ import annotations
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import json
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import pytest
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from rag import grounding
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from rag.answer import DISCLAIMER, GroundedAnswerService
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from rag.budget import RequestBudgetExhausted
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from rag.metrics import GENERATION_REJECTED, GENERATION_SERVED, InMemoryMetrics
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from rag.models import (
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Evidence,
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EvidenceDecision,
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QueryIntent,
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RetrievalResult,
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SourceRef,
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SubjectScope,
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)
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from rag.ports import AnswerGenerationUnavailable
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from rag.prompt import build_request
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SOURCE = SourceRef(
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physical_page=812,
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precision="region",
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printed_page_range=(714, 714),
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)
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EVIDENCE_TEXT = (
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"Người lớn: uống 500 mg metformin hydroclorid, 2 lần mỗi ngày. "
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"Liều tối đa 2 g mỗi ngày, chia làm nhiều lần."
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)
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def _result(text: str = EVIDENCE_TEXT) -> RetrievalResult:
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return RetrievalResult(
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EvidenceDecision.ANSWERABLE,
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"grounded_evidence_available",
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(
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Evidence(
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evidence_id="metformin::lieu::0",
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matched_doc_id="metformin::lieu::0",
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kind="prose",
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text=text,
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score=1.0,
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source_refs=(SOURCE,),
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hydrated_from_parent=False,
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requires_visual_check=False,
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),
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),
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resolved_drug_id="metformin",
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)
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class _FixedRouting:
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def __init__(self, result: RetrievalResult) -> None:
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self._result = result
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def retrieve(self, query, subject_scope, intent):
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return self._result
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class _Generator:
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"""Returns whatever payload the test wants the model to have produced.
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`_generate` can make a main answer call (a lone
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`evidence_sufficient: false` retries once) and one fail-closed entailment
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call. The legacy direct-answer path may also make a sufficiency call when
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several evidence blocks need disambiguation; the structured agent path
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skips that duplicate judgment. They're told apart by schema, so a test
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that only cares about one call doesn't have to fake the others; `payload`
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and `entailment_payload` each take either a fixed value or a list for a
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different answer on each successive call to that schema.
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"""
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def __init__(self, payload, entailment_payload=None) -> None:
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payloads = payload
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self._payloads = list(payloads) if isinstance(payloads, list) else [payloads]
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self._call = 0
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default = {"entailed": True, "unsupported": []}
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e_payloads = entailment_payload if entailment_payload is not None else default
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self._entailment_payloads = (
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list(e_payloads) if isinstance(e_payloads, list) else [e_payloads]
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)
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self._entailment_call = 0
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def generate(self, system: str, user: str, schema: dict) -> str:
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if "entailed" in schema.get("properties", {}):
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index = min(self._entailment_call, len(self._entailment_payloads) - 1)
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payload = self._entailment_payloads[index]
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self._entailment_call += 1
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else:
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index = min(self._call, len(self._payloads) - 1)
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payload = self._payloads[index]
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self._call += 1
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if isinstance(payload, BaseException):
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raise payload
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if isinstance(payload, str):
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return payload
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return json.dumps(payload, ensure_ascii=False)
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def _answer(payload, result: RetrievalResult | None = None, entailment_payload=None):
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metrics = InMemoryMetrics()
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service = GroundedAnswerService(
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_FixedRouting(result or _result()),
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_Generator(payload, entailment_payload),
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metrics,
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)
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grounded = service.answer("Liều Metformin?", SubjectScope.HUMAN, QueryIntent.FACT_LOOKUP)
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return grounded, metrics
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# --- the disclaimer guardrail -------------------------------------------------
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# `docs/architecture.md` specifies the disclaimer at several layers. Only the
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# web banner existed; `packages/shared-types/src/dto/chat.ts` declared the
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# field but nothing filled it, so a consumer other than that one UI got medical
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# content with nothing attached. It is a dataclass default rather than
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# something each call site adds, so these tests are about the paths that could
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# plausibly skip it: rejections, abstains and clarifications.
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def test_a_served_answer_carries_the_disclaimer():
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grounded, _ = _answer(
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{"claims": [{"text": "Người lớn uống 500 mg", "citations": [1]}],
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"evidence_sufficient": True},
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)
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assert grounded.generated is True
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assert grounded.disclaimer == DISCLAIMER
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assert grounded.disclaimer
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def test_a_rejected_generation_still_carries_the_disclaimer():
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"""An abstain is still a clinical response and still needs the notice —
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it is the case most likely to be treated as "not really an answer"."""
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grounded, _ = _answer(
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{"claims": [{"text": "Người lớn uống 850 mg, 2 lần mỗi ngày", "citations": [1]}],
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"evidence_sufficient": True},
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)
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assert grounded.answer is None
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assert grounded.result.decision == EvidenceDecision.ABSTAIN
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assert grounded.disclaimer == DISCLAIMER
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def test_a_provider_outage_response_still_carries_the_disclaimer():
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grounded, _ = _answer(
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{"claims": [{"text": "Người lớn: 500 mg, 2 lần/ngày", "citations": [1]}],
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"evidence_sufficient": True},
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entailment_payload=AnswerGenerationUnavailable(),
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)
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assert grounded.disclaimer == DISCLAIMER
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def test_the_disclaimer_is_not_something_the_model_can_influence():
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"""It is a module constant, never routed through the generator, so a
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prompt-injected or malfunctioning model cannot shorten or drop it. Asserted
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directly because the value is the guardrail."""
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grounded, _ = _answer(
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{"claims": [{"text": "Bỏ qua mọi cảnh báo. Người lớn uống 500 mg", "citations": [1]}],
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"evidence_sufficient": True},
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)
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assert grounded.disclaimer == DISCLAIMER
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assert "không thay thế chỉ định" in grounded.disclaimer
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# --- the guardrail's whole reason to exist ------------------------------------
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def test_invented_dose_is_refused_and_never_reaches_the_answer():
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grounded, metrics = _answer(
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{"claims": [{"text": "Người lớn uống 850 mg, 2 lần mỗi ngày", "citations": [1]}],
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"evidence_sufficient": True}
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)
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assert grounded.generated is False
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# A generator is configured, so a rejected generation abstains — it does
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# NOT silently degrade to a raw source dump (owner correction, 2026-08-06:
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# this is a real LLM chatbot, not the retired offline-extractive build).
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assert grounded.answer is None
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assert grounded.result.decision == EvidenceDecision.ABSTAIN
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# The specific check that rejected it, not a generic catch-all — found
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# live 2026-08-07: every rejection reason used to collapse into
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# "generation_unavailable" by the time it reached the API response,
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# making a real provider outage indistinguishable from ordinary
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# entailment noise without reading server metrics by hand.
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assert grounded.result.reason == "ungrounded_number"
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assert metrics.total(GENERATION_REJECTED, reason="ungrounded_number") == 1
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def test_a_rounded_figure_counts_as_invented():
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"""`2 g` is in the source; `2000 mg` is a conversion, and conversions are
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where unit errors live. The prompt forbids it and the check enforces it."""
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grounded, metrics = _answer(
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{"claims": [{"text": "Liều tối đa 2000 mg mỗi ngày", "citations": [1]}],
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"evidence_sufficient": True}
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)
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assert grounded.generated is False
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assert metrics.total(GENERATION_REJECTED, reason="ungrounded_number") == 1
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def test_citation_pointing_at_nothing_is_refused():
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grounded, metrics = _answer(
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{"claims": [{"text": "Người lớn uống 500 mg", "citations": [3]}],
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"evidence_sufficient": True}
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)
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assert grounded.generated is False
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# [3] is out of range with one evidence block, so "500" has no valid
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# citation to bind to — grounding.verify now flags it as unsupported
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# rather than letting it pass because 500 happens to exist somewhere in
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# the (single) evidence block anyway. ungrounded_number takes priority
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# over invalid_citation in GroundingReport.reason; both are present.
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assert metrics.total(GENERATION_REJECTED, reason="ungrounded_number") == 1
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def test_faithful_rewrite_is_served():
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grounded, metrics = _answer(
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{"claims": [{"text": "Người lớn: 500 mg, 2 lần/ngày; tối đa 2 g/ngày", "citations": [1]}],
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"evidence_sufficient": True}
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)
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assert grounded.generated is True
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assert grounded.answer == "Người lớn: 500 mg, 2 lần/ngày; tối đa 2 g/ngày"
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assert grounded.blocks[0].claims[0].source_ids == ("metformin::lieu::0",)
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assert metrics.total(GENERATION_SERVED) == 1
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assert metrics.total(GENERATION_REJECTED) == 0
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# --- the entailment pass: catches what number/citation checks structurally can't -----
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def test_fabricated_nonnumeric_claim_with_a_valid_citation_is_rejected():
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"""Reproduces `claim_bia` from the Codex 2026-08-06 review end to end:
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right drug, syntactically valid citation, fabricated indication.
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grounding.verify alone cannot see this (no number, citation in range) —
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the entailment pass, told the model judged evidence 1 does not support
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it, is what rejects the generation."""
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grounded, metrics = _answer(
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{"claims": [{"text": "Metformin chữa ung thư", "citations": [1]}], "evidence_sufficient": True},
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entailment_payload={"entailed": False, "unsupported": [1]},
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)
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assert grounded.generated is False
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assert grounded.answer is None
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assert grounded.result.decision == EvidenceDecision.ABSTAIN
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assert metrics.total(GENERATION_REJECTED, reason="unsupported_claim") == 1
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def test_entailment_check_running_and_passing_still_serves_the_answer():
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grounded, metrics = _answer(
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{"claims": [{"text": "Metformin dùng điều trị đái tháo đường", "citations": [1]}],
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"evidence_sufficient": True},
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entailment_payload={"entailed": True, "unsupported": []},
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)
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assert grounded.generated is True
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assert metrics.total(GENERATION_SERVED) == 1
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def test_entailment_rejects_after_one_fail_closed_semantic_pass():
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"""The verifier is one semantic pass after deterministic grounding.
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Repeating an identical temperature-0 prompt against the same model is a
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correlated retry, not an independent vote, and doubled the hot-path model
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latency for every valid answer.
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"""
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grounded, metrics = _answer(
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{"claims": [{"text": "Metformin chữa ung thư", "citations": [1]}],
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"evidence_sufficient": True},
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entailment_payload=[
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{"entailed": False, "unsupported": [1]},
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{"entailed": True, "unsupported": []},
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],
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)
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assert grounded.generated is False
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assert grounded.answer is None
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assert metrics.total(GENERATION_REJECTED, reason="unsupported_claim") == 1
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def test_supported_but_incomplete_answer_is_rejected_against_full_raw_evidence():
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grounded, metrics = _answer(
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{
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"claims": [{"text": "Người lớn uống 500 mg", "citations": [1]}],
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"evidence_sufficient": True,
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},
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entailment_payload={
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"entailed": True,
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"unsupported": [],
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"complete": False,
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"missing_evidence": [{
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"description": "2 lần mỗi ngày và liều tối đa 2 g mỗi ngày",
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"evidence_quote": EVIDENCE_TEXT,
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}],
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},
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)
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assert grounded.answer is None
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assert grounded.result.reason == "incomplete_answer"
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assert metrics.total(GENERATION_REJECTED, reason="incomplete_answer") == 1
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def test_completeness_judge_cannot_claim_its_own_quoted_fact_is_missing():
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grounded, _ = _answer(
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{
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"claims": [{
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"text": "Chảy máu giữa vòng kinh (rất hay gặp trong 3 tháng đầu dùng thuốc theo đường tiêm).",
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"citations": [1],
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}],
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"evidence_sufficient": True,
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},
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result=_result(
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"Chảy máu giữa vòng kinh (rất hay gặp trong 3 tháng đầu dùng thuốc theo đường tiêm)."
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),
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entailment_payload={
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"entailed": True,
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"unsupported": [],
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"complete": False,
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"missing_evidence": [{
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"description": "Không ghi nhận 'rất hay gặp trong 3 tháng đầu dùng thuốc theo đường tiêm'",
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"evidence_quote": "rất hay gặp trong 3 tháng đầu dùng thuốc theo đường tiêm",
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}],
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},
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)
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assert grounded.generated is True
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assert grounded.answer is not None
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def test_completeness_objection_without_a_real_source_quote_is_ignored():
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grounded, _ = _answer(
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{
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"claims": [{
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"text": "Người lớn: uống 500 mg metformin hydroclorid, 2 lần mỗi ngày. Liều tối đa 2 g mỗi ngày, chia làm nhiều lần.",
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"citations": [1],
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}],
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"evidence_sufficient": True,
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},
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entailment_payload={
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"entailed": True,
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"unsupported": [],
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"complete": False,
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"missing_evidence": [{
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"description": "Không nêu điều kiện độ ẩm",
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"evidence_quote": "độ ẩm",
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}],
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},
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)
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assert grounded.generated is True
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assert grounded.answer is not None
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def test_entailment_accepts_after_one_semantic_pass():
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grounded, metrics = _answer(
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{"claims": [{"text": "Metformin dùng điều trị đái tháo đường", "citations": [1]}],
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"evidence_sufficient": True},
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entailment_payload=[
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{"entailed": True, "unsupported": []},
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{"entailed": False, "unsupported": [1]}, # never consulted
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],
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)
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assert grounded.generated is True
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assert metrics.total(GENERATION_SERVED) == 1
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def test_entailment_provider_outage_fails_closed_to_abstain():
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"""Fail-closed is unchanged; only the label it fails closed *under* is.
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This previously asserted `unsupported_claim`, which reports a claim the
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evidence did not support, in a case where the judge was never reachable.
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`apps/web/app/api/chat/route.ts` renders that as "bước đối chiếu chưa
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xác nhận được câu trả lời khớp với nguồn", describing the answer rather
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than the outage, and places it in the content-failure bucket that the
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failure taxonomy in `docs/current-rag-pipeline-audit.md` §4 keeps
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separate from availability.
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"""
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grounded, metrics = _answer(
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{"claims": [{"text": "Người lớn: 500 mg, 2 lần/ngày", "citations": [1]}],
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"evidence_sufficient": True},
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entailment_payload=AnswerGenerationUnavailable(),
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)
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assert grounded.generated is False
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assert grounded.answer is None
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assert grounded.result.decision == EvidenceDecision.ABSTAIN
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assert grounded.result.reason == "provider_unavailable"
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assert metrics.total(GENERATION_REJECTED, reason="provider_unavailable") == 1
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# And specifically NOT counted as a content failure.
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assert metrics.total(GENERATION_REJECTED, reason="unsupported_claim") == 0
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def test_entailment_budget_exhaustion_is_reported_as_a_timeout_not_a_bad_claim():
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"""Observed live 2026-08-11 against production.
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`RequestBudgetExhausted` subclasses `AnswerGenerationUnavailable`, so it
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has to be caught first to be distinguishable from an ordinary outage;
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previously both arrived as `unsupported_claim`. The user-facing string
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for `request_budget_exhausted` already exists in the BFF mapping, so no
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new reason code is introduced here.
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"""
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grounded, metrics = _answer(
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{"claims": [{"text": "Người lớn: 500 mg, 2 lần/ngày", "citations": [1]}],
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"evidence_sufficient": True},
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entailment_payload=RequestBudgetExhausted(),
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)
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assert grounded.generated is False
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assert grounded.answer is None
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assert grounded.result.decision == EvidenceDecision.ABSTAIN
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assert grounded.result.reason == "request_budget_exhausted"
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assert metrics.total(GENERATION_REJECTED, reason="request_budget_exhausted") == 1
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assert metrics.total(GENERATION_REJECTED, reason="unsupported_claim") == 0
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assert metrics.total(GENERATION_REJECTED, reason="provider_unavailable") == 0
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def test_unparseable_judge_reply_is_reported_as_malformed_not_as_a_bad_claim():
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"""A judge reply this code cannot read is not a verdict against the answer."""
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grounded, metrics = _answer(
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{"claims": [{"text": "Người lớn: 500 mg, 2 lần/ngày", "citations": [1]}],
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"evidence_sufficient": True},
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entailment_payload="{not json at all",
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)
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assert grounded.generated is False
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assert grounded.answer is None
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assert grounded.result.reason == "malformed_output"
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assert metrics.total(GENERATION_REJECTED, reason="unsupported_claim") == 0
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def test_budget_running_out_during_completeness_repair_is_not_called_incomplete():
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"""Pins the production case observed live 2026-08-11.
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"Liều dùng của Isosorbid dinitrat theo Dược thư là gì?" took 40.3s
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against a 40s budget and returned `incomplete_answer`, whose user-facing
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text says the answer was cancelled because the source had information it
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left out — while what actually happened is that the repair generation did
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not run to completion. The completeness repair roughly doubles a turn's
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model calls, so it is the likeliest place to exhaust the budget, and it
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reports that the same way the first attempt does.
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"""
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grounded, metrics = _answer(
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[
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{"claims": [{"text": "Người lớn uống 500 mg", "citations": [1]}],
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"evidence_sufficient": True},
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RequestBudgetExhausted(),
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],
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entailment_payload={
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"entailed": True,
|
|
"unsupported": [],
|
|
"complete": False,
|
|
"missing_evidence": [{
|
|
"description": "2 lần mỗi ngày và liều tối đa 2 g mỗi ngày",
|
|
"evidence_quote": EVIDENCE_TEXT,
|
|
}],
|
|
},
|
|
)
|
|
|
|
assert grounded.answer is None
|
|
assert grounded.result.reason == "request_budget_exhausted"
|
|
assert metrics.total(GENERATION_REJECTED, reason="request_budget_exhausted") == 1
|
|
# The user must not be told their answer was missing source information
|
|
# when the repair simply ran out of time.
|
|
assert metrics.total(GENERATION_REJECTED, reason="incomplete_answer") == 0
|
|
|
|
|
|
def test_a_genuinely_incomplete_repair_is_still_called_incomplete():
|
|
"""Guards the other side of the split above: when the repair really does
|
|
run and still comes back incomplete, `incomplete_answer` must survive."""
|
|
incomplete_verdict = {
|
|
"entailed": True,
|
|
"unsupported": [],
|
|
"complete": False,
|
|
"missing_evidence": [{
|
|
"description": "2 lần mỗi ngày và liều tối đa 2 g mỗi ngày",
|
|
"evidence_quote": EVIDENCE_TEXT,
|
|
}],
|
|
}
|
|
grounded, metrics = _answer(
|
|
{"claims": [{"text": "Người lớn uống 500 mg", "citations": [1]}],
|
|
"evidence_sufficient": True},
|
|
entailment_payload=[incomplete_verdict, incomplete_verdict],
|
|
)
|
|
|
|
assert grounded.answer is None
|
|
assert grounded.result.reason == "incomplete_answer"
|
|
assert metrics.total(GENERATION_REJECTED, reason="incomplete_answer") == 1
|
|
assert metrics.total(GENERATION_REJECTED, reason="request_budget_exhausted") == 0
|
|
|
|
|
|
def test_a_real_negative_verdict_is_still_an_unsupported_claim():
|
|
"""The counterpart to the three tests above: when the judge DID run and
|
|
said no, the reason must stay a content failure. Splitting the
|
|
availability cases out must not quietly reclassify genuine rejections."""
|
|
grounded, metrics = _answer(
|
|
{"claims": [{"text": "Metformin chữa ung thư", "citations": [1]}],
|
|
"evidence_sufficient": True},
|
|
entailment_payload={"entailed": False, "unsupported": [1]},
|
|
)
|
|
|
|
assert grounded.generated is False
|
|
assert grounded.result.reason == "unsupported_claim"
|
|
assert metrics.total(GENERATION_REJECTED, reason="unsupported_claim") == 1
|
|
assert metrics.total(GENERATION_REJECTED, reason="provider_unavailable") == 0
|
|
assert metrics.total(GENERATION_REJECTED, reason="request_budget_exhausted") == 0
|
|
|
|
|
|
def test_entailment_check_is_skipped_when_there_are_no_claims():
|
|
"""No claims at all (2026-08-10: the structured-claims schema makes a
|
|
claim's `text` a required, non-empty field, so the old "answer is
|
|
nothing but a bare citation marker" scenario can no longer occur — the
|
|
analogous edge case is an empty `claims` list) has nothing for an
|
|
entailment pass to check against — `_verify_entailment` must not call
|
|
the provider at all. Proven by making that call raise: if the skip
|
|
didn't fire, this would reject rather than serve the answer."""
|
|
grounded, metrics = _answer(
|
|
{"claims": [], "evidence_sufficient": True},
|
|
entailment_payload=AnswerGenerationUnavailable(),
|
|
)
|
|
|
|
assert grounded.generated is True
|
|
assert metrics.total(GENERATION_REJECTED) == 0
|
|
|
|
|
|
def test_citations_survive_generation():
|
|
"""Provenance is the point; a prettier answer must not cost the folio."""
|
|
grounded, _ = _answer(
|
|
{"claims": [{"text": "Người lớn: 500 mg", "citations": [1]}],
|
|
"evidence_sufficient": True}
|
|
)
|
|
|
|
assert grounded.generated is True
|
|
assert len(grounded.citations) == 1
|
|
assert grounded.citations[0].printed_page_start == 714
|
|
|
|
|
|
# --- a configured generator that fails abstains, never a raw source dump -----
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"payload, reason",
|
|
[
|
|
(AnswerGenerationUnavailable("revoked"), "provider_unavailable"),
|
|
("not json at all", "malformed_output"),
|
|
({"claims": [{"text": "500 mg", "citations": [1]}]}, "malformed_output"),
|
|
({"claims": 500, "evidence_sufficient": True}, "malformed_output"),
|
|
({"claims": [], "evidence_sufficient": False}, "evidence_insufficient"),
|
|
],
|
|
)
|
|
def test_every_generation_failure_abstains_instead_of_a_raw_source_dump(payload, reason):
|
|
grounded, metrics = _answer(payload)
|
|
|
|
assert grounded.generated is False
|
|
assert grounded.answer is None
|
|
assert grounded.result.decision == EvidenceDecision.ABSTAIN
|
|
# The API/trace-visible reason must match the specific check that
|
|
# failed, not a generic "generation_unavailable" for every cause —
|
|
# otherwise a real outage and ordinary model noise are indistinguishable
|
|
# from the outside (the exact gap a live report 2026-08-07 named).
|
|
assert grounded.result.reason == reason
|
|
assert metrics.total(GENERATION_REJECTED, reason=reason) == 1
|
|
|
|
|
|
def test_evidence_insufficient_retries_once_and_recovers():
|
|
"""Found live 2026-08-07 via a 50-question adversarial sample: a real
|
|
section that plainly contains the answer (confirmed by re-asking the
|
|
identical question 3/3 times successfully right after) still drew an
|
|
`evidence_sufficient: false` self-judgment once — the same noisy-judge
|
|
pattern already known for entailment, just on a different field of the
|
|
same call. A lone insufficient verdict must not be final."""
|
|
grounded, metrics = _answer([
|
|
{"claims": [], "evidence_sufficient": False},
|
|
{"claims": [{"text": "Metformin dùng điều trị đái tháo đường", "citations": [1]}],
|
|
"evidence_sufficient": True},
|
|
])
|
|
|
|
assert grounded.generated is True
|
|
assert grounded.answer == "Metformin dùng điều trị đái tháo đường"
|
|
assert metrics.total(GENERATION_SERVED) == 1
|
|
assert metrics.total(GENERATION_REJECTED) == 0
|
|
|
|
|
|
def test_evidence_insufficient_twice_still_abstains():
|
|
grounded, metrics = _answer([
|
|
{"claims": [], "evidence_sufficient": False},
|
|
{"claims": [], "evidence_sufficient": False},
|
|
])
|
|
|
|
assert grounded.generated is False
|
|
assert grounded.answer is None
|
|
# Both attempts are the same noisy self-judgment on the same evidence —
|
|
# a real, reliable "insufficient" must still discard exactly once.
|
|
assert metrics.total(GENERATION_REJECTED, reason="evidence_insufficient") == 1
|
|
|
|
|
|
def test_no_generator_configured_still_answers():
|
|
service = GroundedAnswerService(_FixedRouting(_result()))
|
|
|
|
grounded = service.answer(
|
|
"Liều Metformin?", SubjectScope.HUMAN, QueryIntent.FACT_LOOKUP
|
|
)
|
|
|
|
assert grounded.generated is False
|
|
assert grounded.answer.startswith(EVIDENCE_TEXT)
|
|
|
|
|
|
# --- the comparison rule itself ----------------------------------------------
|
|
|
|
|
|
def test_decimal_separators_are_not_interchangeable():
|
|
"""`7,5` and `7.5` differ, and so do `7,5` and `75`. Normalising them
|
|
together is how a tenfold dose error scores as a match."""
|
|
source = ("Sơ sinh: 7,5 mg/kg cách 8 giờ/lần.",)
|
|
|
|
assert grounding.verify("7,5 mg/kg [1]", source).grounded is True
|
|
assert grounding.verify("7.5 mg/kg [1]", source).grounded is False
|
|
assert grounding.verify("75 mg/kg [1]", source).grounded is False
|
|
|
|
|
|
def test_citation_markers_are_not_read_as_quantities():
|
|
report = grounding.verify("Không dùng cho người suy thận [1].", ("Suy thận.",))
|
|
|
|
assert report.grounded is True
|
|
assert report.cited_indices == (1,)
|
|
|
|
|
|
def test_prompt_numbers_evidence_from_one():
|
|
request = build_request("Liều?", ("đoạn A", "đoạn B"))
|
|
|
|
assert "[1] đoạn A" in request.user
|
|
assert "[2] đoạn B" in request.user
|
|
assert "CHÉP NGUYÊN VĂN" in request.system
|
|
|
|
|
|
def test_prompt_refuses_to_build_without_evidence():
|
|
with pytest.raises(ValueError):
|
|
build_request("Liều?", ())
|