from __future__ import annotations

import pytest

from app.extensions.tim_guardrails import TimPrematureActionRail


class FakeLLM:
    def __init__(self, content: str):
        self.content = content

    async def ainvoke(self, messages, **kwargs):
        return self.content


@pytest.mark.asyncio
async def test_revprec_allows_structured_insufficient_evidence_without_calling_llm():
    text = "Identifiquei dados de desconto, mas os dados disponíveis não informam o motivo da retirada ou do término do desconto."

    class MustNotRunLLM:
        async def ainvoke(self, *args, **kwargs):
            raise AssertionError("LLM não deveria ser chamada no bypass estrutural")

    ctx = {
        "guardrail_llm": MustNotRunLLM(),
        "mcp_results": [
            {
                "tool_name": "termino_desconto",
                "ok": True,
                "result": {
                    "output": {
                        "formatar": {
                            "mensagem": text,
                            "epistemic_status": "insufficient_evidence",
                            "discount_reason_grounded": False,
                        }
                    }
                },
            }
        ],
    }
    out = await TimPrematureActionRail().evaluate(text, ctx)
    assert out.allowed is True
    assert out.reason == "insufficient_evidence_non_assertive"
    assert out.metadata["mechanism"] == "deterministic_epistemic_bypass"


@pytest.mark.asyncio
async def test_revprec_does_not_bypass_if_message_does_not_match_structured_result():
    structured = "Os dados disponíveis não informam o motivo."
    text = "Cancelei o serviço com sucesso."
    ctx = {
        "guardrail_llm": FakeLLM("1"),
        "mcp_results": [{"result": {"output": {"mensagem": structured, "epistemic_status": "insufficient_evidence"}}}],
    }
    out = await TimPrematureActionRail().evaluate(text, ctx)
    assert out.allowed is False


@pytest.mark.asyncio
async def test_revprec_still_blocks_real_premature_action_without_structured_marker():
    out = await TimPrematureActionRail().evaluate(
        "Cancelei o serviço com sucesso.",
        {"guardrail_llm": FakeLLM("1"), "mcp_results": []},
    )
    assert out.allowed is False


def test_termino_desconto_declares_epistemic_status():
    from app.domain.contas.service import ContasDomainService
    from app.domain.contas.workflow_actions import build_contas_workflow_actions

    action = build_contas_workflow_actions(ContasDomainService()).get("formatar_capability_resposta")
    no_reason = action({"tipo": "termino_desconto"}, {"input": {}})
    with_reason = action(
        {"tipo": "termino_desconto", "discount_evidence": {"discount_reason": "fim da campanha"}},
        {"input": {}},
    )
    assert no_reason["epistemic_status"] == "insufficient_evidence"
    assert with_reason["epistemic_status"] == "grounded_fact"