"""Unit tests for the pure renderers: dict in, HTML/Markdown/JSON out (no DB)."""

import json

from agenteval.evaluation.report_render import (
    render_campaign_markdown,
    render_html,
    render_json,
    render_markdown,
)


def _run_report(**overrides) -> dict:
    """A hand-built report dict matching generate_report's shape."""
    report = {
        "run_id": "run-1",
        "target_id": "t-1",
        "target_name": "客服机器人",
        "scenario_id": "s-1",
        "scenario_name": "售后场景",
        "scenario_version": 2,
        "triggered_by": "manual",
        "status": "completed",
        "started_at": "2026-07-30T10:00:00+00:00",
        "completed_at": "2026-07-30T10:05:00+00:00",
        "summary": {
            "total_cases": 2,
            "passed_cases": 1,
            "failed_cases": 1,
            "total_rules": 3,
            "passed_rules": 2,
            "pass_rate": 0.5,
            "connectivity_cases": 1,
            "judged_pass_rate": 0.0,
        },
        "cases": [
            {
                "case_id": "case-a",
                "passed": True,
                "connectivity": True,
                "turns": [
                    {
                        "round": 0,
                        "sent_text": "你好",
                        "reply_text": "您好，请问有什么可以帮您？",
                        "latency_ms": 120,
                        "question_msg_id": "m-1",
                    }
                ],
                "results": [],
            },
            {
                "case_id": "case-b",
                "passed": False,
                "connectivity": False,
                "turns": [
                    {
                        "round": 0,
                        "sent_text": "退货流程",
                        "reply_text": None,
                        "latency_ms": None,
                        "question_msg_id": "m-2",
                    }
                ],
                "results": [
                    {"rule_type": "keyword_match", "passed": False, "score": 0.0, "reason": "缺少关键词"},
                ],
            },
        ],
    }
    report.update(overrides)
    return report


def _campaign_report() -> dict:
    """A hand-built dict matching generate_campaign_report's shape."""
    return {
        "campaign_id": "c-1",
        "name": "夜间巡检",
        "target_id": "t-1",
        "status": "completed",
        "window_seconds": 7200,
        "time_scale": 1.0,
        "started_at": "2026-07-30T00:00:00+00:00",
        "completed_at": "2026-07-30T02:00:00+00:00",
        "summary": {
            "total_runs": 2,
            "completed_runs": 2,
            "overall_pass_rate": 0.75,
            "overall_availability": 1.0,
            "avg_latency_ms": 150.0,
        },
        "time_trend": [
            {
                "bucket_index": 0,
                "start_seconds": 0.0,
                "end_seconds": 3600.0,
                "run_count": 2,
                "pass_rate": 0.75,
                "availability": 1.0,
                "avg_latency_ms": 150.0,
            },
            {
                "bucket_index": 1,
                "start_seconds": 3600.0,
                "end_seconds": 7200.0,
                "run_count": 0,
                "pass_rate": None,
                "availability": None,
                "avg_latency_ms": None,
            },
        ],
        "capability_summary": [
            {
                "scenario_id": "s-1",
                "scenario_name": "售后场景",
                "run_count": 2,
                "pass_rate": 0.75,
                "availability": 1.0,
                "avg_latency_ms": 150.0,
            },
        ],
    }


# ── render_html ─────────────────────────────────────────────────────────────

def test_render_html_contains_names_and_summary():
    html = render_html(_run_report())
    assert "客服机器人" in html
    assert "售后场景" in html
    assert "50.00%" in html  # pass_rate 0.5


def test_render_html_contains_turns_and_rule_badges():
    html = render_html(_run_report())
    assert "退货流程" in html
    assert "keyword_match" in html
    assert "失败" in html


# ── render_markdown ─────────────────────────────────────────────────────────

def test_render_markdown_summary_table():
    md = render_markdown(_run_report())
    assert "| 总用例数 | 2 |" in md
    assert "| 通过率 | 50.0% |" in md
    assert "| 连通用例 | 1 |" in md


def test_render_markdown_connectivity_badge_and_no_reply():
    md = render_markdown(_run_report())
    assert "🔗" in md  # connectivity case badge
    assert "（连通用例，未配置判定标准）" in md
    assert "（无回复）" in md


def test_render_markdown_judged_pass_rate_dash_when_none():
    report = _run_report()
    report["summary"]["judged_pass_rate"] = None
    md = render_markdown(report)
    assert "| 判定型通过率 | — |" in md


# ── render_json ─────────────────────────────────────────────────────────────

def test_render_json_roundtrips():
    report = _run_report()
    parsed = json.loads(render_json(report))
    assert parsed == report


# ── render_campaign_markdown ────────────────────────────────────────────────

def test_render_campaign_markdown_summary_and_axes():
    md = render_campaign_markdown(_campaign_report())
    assert "# 活动周期报告 — 夜间巡检" in md
    assert "| 整窗通过率 | 75.0% |" in md
    assert "## 时间趋势" in md
    assert "## 能力汇总" in md
    assert "| 售后场景 | 2 | 75.0% | 100.0% | 150ms |" in md


def test_render_campaign_markdown_empty_bucket_dashes():
    md = render_campaign_markdown(_campaign_report())
    # bucket 1 has no runs: pass_rate/availability/latency all render as —
    assert "| 1h–2h | 0 | — | — | — |" in md


def _analysis() -> dict:
    """A hand-built dict matching the stored campaign analysis result shape."""
    return {
        "overall": "整窗通过率偏低，售后场景拖后腿",
        "problems": [
            {
                "severity": "high",
                "title": "售后答非所问",
                "description": "多轮对话中反复偏离用户问题",
                "scenario_ids": ["s-1"],
                "evidence_run_ids": ["run-abc", "run-def"],
            },
            {
                "severity": "low",
                "title": "响应偏慢",
                "description": "高峰时段时延偏高",
                "scenario_ids": ["s-2"],
                "evidence_run_ids": [],
            },
        ],
        "scenario_narratives": [
            {"scenario_id": "s-1", "narrative": "售后场景表现不稳定"},
            {"scenario_id": "s-2", "narrative": "售前场景表现稳定"},
        ],
        "suggestions": [
            {"priority": 2, "text": "次要建议：扩容"},
            {"priority": 1, "text": "首要建议：补充售后知识库"},
        ],
    }


def test_render_campaign_markdown_appends_analysis_sections():
    md = render_campaign_markdown(
        _campaign_report(),
        analysis=_analysis(),
        scenario_names={"s-1": "售后场景", "s-2": "售前场景"},
    )
    assert "## 智能分析" in md
    assert "### 总体结论" in md
    assert "整窗通过率偏低，售后场景拖后腿" in md
    assert "### 问题诊断" in md
    assert "**[高] 售后答非所问**（场景：售后场景）" in md
    assert "`run-abc`" in md and "`run-def`" in md
    assert "**[低] 响应偏慢**（场景：售前场景）" in md
    assert "### 分场景叙述" in md
    assert "**售后场景**：售后场景表现不稳定" in md
    assert "### 改善建议" in md
    # 建议按 priority 升序
    assert md.index("首要建议") < md.index("次要建议")


def test_render_campaign_markdown_analysis_falls_back_to_id_prefix():
    md = render_campaign_markdown(_campaign_report(), analysis=_analysis(), scenario_names={})
    assert "**[高] 售后答非所问**（场景：s-1）" in md


def test_render_campaign_markdown_without_analysis_unchanged():
    md = render_campaign_markdown(_campaign_report())
    assert "智能分析" not in md


def test_render_campaign_markdown_header_readability():
    md = render_campaign_markdown(_campaign_report(), target_name="客服机器人")
    assert "**评测对象**: 客服机器人" in md
    assert "**状态**: 已完成" in md
    assert "**窗口**: 2h（正式线）" in md
    assert "**开始时间**: 2026-07-30 00:00" in md
    assert "**完成时间**: 2026-07-30 02:00" in md
    assert "| 0h–1h | 2 | 75.0% | 100.0% | 150ms |" in md


def test_render_campaign_markdown_header_falls_back_to_target_id():
    md = render_campaign_markdown(_campaign_report())
    assert "**评测对象**: t-1" in md


def test_render_campaign_markdown_accelerated_line():
    report = _campaign_report()
    report["window_seconds"] = 86400
    report["time_scale"] = 4.0
    md = render_campaign_markdown(report)
    assert "**窗口**: 24h（加速调试线 ×4，压缩后实际耗时约 6h）" in md


def _comparison() -> dict:
    """A hand-built dict matching the comparison context the export endpoint resolves."""
    return {
        "result": {
            "trend": "regressing",
            "summary": "整体质量下滑，售后场景恶化",
            "problem_evolution": [
                {
                    "status": "persisting",
                    "title": "售后答非所问",
                    "scenario_ids": ["s-1"],
                    "detail": "问题仍未收敛",
                },
                {"status": "resolved", "title": "响应偏慢", "scenario_ids": [], "detail": ""},
            ],
            "suggestion_tracking": [
                {"status": "partial", "text": "补充售后知识库", "note": "仅覆盖部分问题"},
                {"status": "new", "text": "新增建议：监控时延", "note": ""},
            ],
        },
        "baseline_name": "上一期巡检",
        "baseline_completed_at": "2026-07-29T02:00:00+00:00",
        "model_name": "qwen-max",
        "updated_at": "2026-07-30T03:00:00+00:00",
        "metric_diff": {
            "overall": {
                "pass_rate": {"baseline": 0.8, "current": 0.75, "delta": -0.05},
                "availability": {"baseline": 1.0, "current": 0.5, "delta": -0.5},
                "avg_latency_ms": {"baseline": 120.0, "current": 150.0, "delta": 30.0},
            },
            "scenarios": [
                {
                    "scenario_id": "s-1",
                    "scenario_name": "售后场景",
                    "pass_rate": {"baseline": 0.7, "current": 0.6, "delta": -0.1},
                    "availability": {"baseline": None, "current": None, "delta": None},
                    "avg_latency_ms": {"baseline": 100.0, "current": 140.0, "delta": 40.0},
                },
            ],
        },
    }


def test_render_campaign_markdown_appends_comparison_section():
    md = render_campaign_markdown(
        _campaign_report(),
        comparison=_comparison(),
        scenario_names={"s-1": "售后场景"},
    )
    assert "## 周期对比" in md
    assert "基线：「上一期巡检」（完成于 2026-07-29 02:00）" in md
    assert "分析模型：qwen-max" in md
    assert "生成于：2026-07-30 03:00" in md
    assert "**趋势**：退化 — 整体质量下滑，售后场景恶化" in md
    assert "### 指标变化" in md
    assert "| 整窗（总体） | 80.0% → 75.0%（-5.0pp） | 100.0% → 50.0%（-50.0pp） | 120ms → 150ms（+30.0ms） |" in md
    assert "| 售后场景 | 70.0% → 60.0%（-10.0pp） | — → —（—） | 100ms → 140ms（+40.0ms） |" in md
    assert "### 问题演变" in md
    assert "**[持续] 售后答非所问**（场景：售后场景）" in md
    assert "  问题仍未收敛" in md
    assert "**[消解] 响应偏慢**" in md
    assert "### 建议落实情况" in md
    assert "**[部分落实] 补充售后知识库**" in md
    assert "  仅覆盖部分问题" in md
    assert "**[新增] 新增建议：监控时延**" in md


def test_render_campaign_markdown_comparison_comes_after_analysis():
    md = render_campaign_markdown(_campaign_report(), analysis=_analysis(), comparison=_comparison())
    assert md.index("## 智能分析") < md.index("## 周期对比")


def test_render_campaign_markdown_without_comparison_unchanged():
    md = render_campaign_markdown(_campaign_report())
    assert "周期对比" not in md


# ── render_campaign_markdown: 探索发现附录（v0.9 票据 05）────────────────────


def _exploration() -> dict:
    return {
        "session_count": 3,
        "sessions_with_experience": 3,
        "goal_achieved_count": 1,
        "goal_achievement_rate": 0.3333,
        "issues": [
            {"issue": "缴费入口难找", "count": 2},
            {"issue": "验证码收不到", "count": 1},
        ],
        "misled": [{"issue": "被误导选了错误套餐", "count": 1}],
        "judge_review": {
            "reviewed_sessions": 1,
            "findings": [{"dimension": "hallucination", "rating": "poor", "comment": "编造了不存在的政策"}],
            "summaries": ["服务态度好但存在幻觉"],
        },
    }


def test_render_campaign_markdown_appends_exploration_appendix():
    md = render_campaign_markdown(_campaign_report(), exploration=_exploration())
    assert "## 探索发现" in md
    assert "| 探索会话数 | 3 |" in md
    assert "| 目标达成率 | 33.3% |" in md
    assert "缴费入口难找 ×2" in md
    assert "验证码收不到 ×1" in md
    assert "被误导选了错误套餐 ×1" in md
    assert "编造了不存在的政策" in md
    assert "复核结论：服务态度好但存在幻觉" in md


def test_render_campaign_markdown_exploration_without_judge_or_issues():
    md = render_campaign_markdown(
        _campaign_report(),
        exploration={
            "session_count": 1,
            "sessions_with_experience": 1,
            "goal_achieved_count": 1,
            "goal_achievement_rate": 1.0,
            "issues": [],
            "misled": [],
            "judge_review": None,
        },
    )
    assert "## 探索发现" in md
    assert "无" in md  # 空问题清单回落文案


def test_render_campaign_markdown_exploration_comes_after_comparison():
    md = render_campaign_markdown(
        _campaign_report(), analysis=_analysis(), comparison=_comparison(), exploration=_exploration()
    )
    assert md.index("## 智能分析") < md.index("## 周期对比") < md.index("## 探索发现")


def test_render_campaign_markdown_without_exploration_byte_identical():
    base = render_campaign_markdown(_campaign_report(), analysis=_analysis(), comparison=_comparison())
    with_none = render_campaign_markdown(
        _campaign_report(), analysis=_analysis(), comparison=_comparison(), exploration=None
    )
    assert base == with_none
    assert "探索发现" not in base