"""Detail-path guards: skip intents never pollute drafts; LLM gate routes before fact-merge."""

from __future__ import annotations

from types import SimpleNamespace
from typing import Any

from app.builder_conversation.candidate import _candidate_rewrite
from app.builder_conversation.predicates import _is_no_information_reply
from app.builder_conversation.rescue import llm_detail_route
from app.chat_intents import ChatTurnClassification
from builder_flow_helpers import create_builder_session, send_message, start_education
from test_api import active_component


class _StubClassifier:
    def __init__(self, result: ChatTurnClassification) -> None:
        self.result = result

    def classify(self, message: str, *, state_summary: dict[str, Any]) -> ChatTurnClassification:
        return self.result


def _agent(classifier: Any) -> Any:
    return SimpleNamespace(
        expander=SimpleNamespace(expand=lambda entry, *, context: {}),
        _chat_intent_classifier=classifier,
    )


def _profile_with_draft() -> dict[str, Any]:
    return {
        "job_type": "campus",
        "builder": {
            "active_section": "education",
            "identity_draft": {"school": "X 大学", "description": "完成数据库课程项目。"},
            "gap_state": {"asked": ["academic_result"], "skipped": [], "rounds": 1},
        },
    }


def test_skip_words_count_as_no_information() -> None:
    for word in ("跳过", "先跳过", "跳过吧", "不用了", "不需要", "以后再说", "没有了"):
        assert _is_no_information_reply(word), word


def test_skip_reply_does_not_pollute_description(client: Any) -> None:
    session_id, body = create_builder_session(client)
    start_education(client, session_id, body)
    send_message(client, session_id, "完成数据库课程项目。")  # triggers the gap prompt
    reply = send_message(client, session_id, "跳过")
    card = active_component(reply)["data"]
    assert card["component"] == "experience_confirm_card"
    assert "跳过" not in str(card["value"].get("description") or "")


def test_detail_gate_no_info_skips_gap_without_merging() -> None:
    agent = _agent(_StubClassifier(ChatTurnClassification(intent="no_info", confidence=0.9)))
    transition = llm_detail_route(agent, _profile_with_draft(), "先跳过这个")

    assert transition is not None
    state = transition.profile["builder"]
    assert "先跳过这个" not in state["identity_draft"]["description"]
    assert "academic_result" in state["gap_state"]["skipped"]


def test_detail_gate_revise_regenerates_candidate() -> None:
    agent = _agent(_StubClassifier(ChatTurnClassification(
        intent="revise_proposal", confidence=0.9, revision_instruction="再简洁一点",
    )))
    transition = llm_detail_route(agent, _profile_with_draft(), "帮我再精简下")

    assert transition is not None
    assert transition.profile["builder"]["pending_entry"]["_proposal"] is not None
    assert "帮我再精简下" not in transition.profile["builder"]["identity_draft"]["description"]


def test_detail_gate_chitchat_does_not_merge() -> None:
    agent = _agent(_StubClassifier(ChatTurnClassification(intent="chitchat", confidence=0.9)))
    transition = llm_detail_route(agent, _profile_with_draft(), "好的谢谢")

    assert transition is not None
    assert transition.profile["builder"]["identity_draft"]["description"] == "完成数据库课程项目。"


def test_detail_gate_passes_facts_and_low_confidence_through() -> None:
    facts = _agent(_StubClassifier(ChatTurnClassification(intent="provide_facts", confidence=0.9)))
    assert llm_detail_route(facts, _profile_with_draft(), "GPA 4.3") is None
    shaky = _agent(_StubClassifier(ChatTurnClassification(intent="no_info", confidence=0.4)))
    assert llm_detail_route(shaky, _profile_with_draft(), "跳过") is None


def test_candidate_rewrite_ensure_facts_appends_missing() -> None:
    class _Expander:
        def expand(self, entry: dict[str, Any], *, context: dict[str, Any]) -> dict[str, Any]:
            return {"optimized_description": "主修课程：数据结构、计算机视觉。", "source": "test"}

    agent = SimpleNamespace(expander=_Expander())
    proposal = _candidate_rewrite(
        agent,
        {"job_type": "campus"},
        {"description": "学习数据结构、计算机视觉课程。GPA: 4.3/5.0，排名前百分之10。"},
        "education",
        ensure_facts=True,
    )
    assert "GPA: 4.3/5.0" in proposal["optimized_description"]
    assert "排名前百分之10" in proposal["optimized_description"]
    assert proposal["uncovered_facts"] == []