"""作业 4 验收测试：LLM 接入采集节点。

分组：
- 接口与工具（提示词加载、FakeLLM 记录、前缀解析、固定时钟）：
  现在就应该通过；
- 关键代码（run_collect / validate_candidate / validate_accident_time）：
  实现前会失败，属预期状态。
"""

from datetime import datetime

import pytest

from src.agent.clock import FixedClock, validate_accident_time
from src.agent.collect import (
    CollectReplyError,
    parse_state_reply,
    run_collect,
)
from src.agent.fields import FieldCandidate, FieldStatus, validate_candidate
from src.agent.graph import build_graph
from src.agent.llm import FakeLLMService
from src.agent.prompts import COLLECTION, load_prompt


def collect_state(**overrides) -> dict:
    state = {
        "session_id": "s1",
        # 使用完整句而非短促词，避免触发分流守卫（“你好”<=2 字）
        "input_text": "发生了交通事故，两辆车追尾",
        "stage_code": "1002",
        "turn_count": 1,
        "no_reply_count": 0,
        "clarify_count": 0,
        "accident_fields": {},
        "turn_patch": {},
        "client_event": "",
    }
    state.update(overrides)
    return state


# ---------- 接口与工具（现在即应通过） ----------


def test_prompt_file_has_source_header():
    text = load_prompt(COLLECTION)
    assert "事故信息采集2025118.json" in text
    assert "nodeId" in text
    assert "原文开始" in text


@pytest.mark.asyncio
async def test_fake_llm_records_calls():
    llm = FakeLLMService(lambda s, u: f"<state>1002</state>{u}")
    out = await llm.complete("sys", "你好")
    assert out == "<state>1002</state>你好"
    assert len(llm.calls) == 1
    assert llm.calls[0]["user_message"] == "你好"


def test_parse_state_reply_valid():
    code, body = parse_state_reply("<state>1002</state>请问有几辆车？")
    assert code == "1002"
    assert body == "请问有几辆车？"


def test_parse_state_reply_missing_prefix_raises():
    with pytest.raises(ValueError):
        parse_state_reply("没有前缀的回复")


def test_fixed_clock():
    fixed = datetime(2026, 10, 19, 12, 0, 0)
    assert FixedClock(fixed).now() == fixed


# ---------- 关键代码（实现前失败，属预期） ----------


@pytest.mark.asyncio
async def test_collect_single_llm_call():
    # 计划作业 4-3：一次轮次一次模型调用，同时产出前缀与正文
    llm = FakeLLMService(
        lambda s, u: "<state>1002</state>请问有几辆汽车卷入了这次事故呢？"
    )
    result = await run_collect(collect_state(), llm)
    # 对话调用 + 独立的字段提取调用（计划作业 4-4）
    assert len(llm.calls) == 2
    assert result["response_text"].startswith("<state>1002</state>")
    assert result["turn_count"] == 2


@pytest.mark.asyncio
async def test_collect_routes_to_photo_when_llm_says_so():
    # LLM 提议 2000（白名单合法）：写状态，下一轮路由到 single_photo
    llm = FakeLLMService(
        lambda s, u: "<state>2000</state>好的，信息已记录。接下来请对准车辆前方拍摄。"
    )
    result = await run_collect(collect_state(), llm)
    assert result["stage_code"] == "2000"
    assert len(llm.calls) == 2  # 对话 + 提取


@pytest.mark.asyncio
async def test_collect_missing_prefix_repaired_once():
    # 第一次回复缺前缀 → 受控修复重试一次（带修复指令），第二次合法
    replies = iter(["没有前缀的回复", "<state>1002</state>请问您现在还在事故现场吗？"])

    def responder(s, u):
        # 修复调用应携带修复指令（对前缀的要求）
        if len(llm.calls) == 1:
            assert "<state>" in u or "state" in s
        return next(replies)

    llm = FakeLLMService(responder)
    result = await run_collect(collect_state(), llm)
    assert len(llm.calls) == 3  # 对话 + 修复 + 提取
    assert result["response_text"].startswith("<state>1002</state>")


@pytest.mark.asyncio
async def test_collect_missing_prefix_unrepaired_is_recognizable_error():
    # 修复后仍缺前缀：抛 CollectReplyError，不提交业务状态，
    # 且调用次数 = 原调用 + 1 次修复（不得无限重试）
    llm = FakeLLMService(lambda s, u: "还是没有前缀")
    with pytest.raises(CollectReplyError):
        await run_collect(collect_state(), llm)
    assert len(llm.calls) == 2


@pytest.mark.asyncio
async def test_collect_illegal_stage_proposal_not_committed():
    # LLM 提议非法阶段码（9999 未登记 / 非法）：不得写状态，
    # 修复一次后仍非法 → 保持当前阶段并给出可识别错误
    llm = FakeLLMService(lambda s, u: "<state>9999</state>正文")
    with pytest.raises(CollectReplyError):
        await run_collect(collect_state(), llm)
    assert len(llm.calls) == 2


@pytest.mark.asyncio
async def test_graph_collect_node_with_llm():
    # 图级：首轮走 welcome（确定性，不调模型）；第二轮起 collect
    # 节点经 Runtime 注入的 llm 走 run_collect
    from src.agent.graph import GraphDeps

    llm = FakeLLMService(lambda s, u: "<state>1002</state>收到。")
    graph = build_graph()
    first = await graph.ainvoke(
        {"session_id": "s1", "input_text": "追尾了"},
        config={"configurable": {"thread_id": "s1"}},
        context=GraphDeps(llm=llm),
    )
    assert len(llm.calls) == 0  # welcome 是确定性节点
    assert first["stage_code"] == "1001"

    result = await graph.ainvoke(
        {"session_id": "s1", "input_text": "继续办理"},
        config={"configurable": {"thread_id": "s1"}},
        context=GraphDeps(llm=llm),
    )
    assert len(llm.calls) == 2  # collect 对话 + 提取
    assert result["response_text"].startswith("<state>1002</state>")
    assert result["stage_code"] == "1002"


# ---------- 字段候选与时间校验（实现前失败，属预期） ----------


def test_validate_candidate_unknown_key_rejected():
    # 计划作业 4-4/6-7：未知 key 不得写入正式字段
    with pytest.raises(ValueError):
        validate_candidate(FieldCandidate(key="not_a_field", value=1))


def test_validate_candidate_future_time_rejected():
    clock = FixedClock(datetime(2026, 10, 19, 12, 0, 0))
    result = validate_candidate(
        FieldCandidate(key="sgfssj", value="明天早上八点"), clock=clock
    )
    assert result.status != FieldStatus.CONFIRMED


def test_validate_candidate_count_not_inferred_from_description():
    # 计划作业 4-8：数量未知不得从“追尾”等词推断
    result = validate_candidate(FieldCandidate(key="jdcsl", value="追尾"))
    assert result.status != FieldStatus.CONFIRMED


def test_validate_accident_time_parses_absolute_and_relative():
    now = datetime(2026, 10, 19, 12, 0, 0)
    assert validate_accident_time("11点45分", now) is True
    assert validate_accident_time("刚才", now) is True
    assert validate_accident_time("明天早上八点", now) is False
    assert validate_accident_time("乱七八糟", now) is False