"""回归测试: predictions 表 agent_weights 独立持久化。

验证:
  1. ORM 模型有 agent_weights 列(JSONB, 可空)
  2. 迁移文件存在且可逆
  3. orchestrator 写入 agent_weights
"""
from __future__ import annotations

from pathlib import Path
from unittest.mock import MagicMock, patch

import pytest

from src.db.models import Prediction

# 仓库根目录下的 alembic 迁移目录 —— 相对本测试文件解析,
# 避免硬编码某台机器/CI 上的绝对路径(见 tests/test_regressions.py 的 _read 约定)。
REPO_ROOT = Path(__file__).resolve().parent.parent
MIGRATION_PATH = REPO_ROOT / "alembic" / "versions" / "0014_predictions_agent_weights.py"


class TestAgentWeightsColumn:
    """验证 predictions 表有 agent_weights 列。"""

    def test_orm_has_agent_weights_column(self):
        """ORM 模型应包含 agent_weights 列。"""
        cols = {c.name: c for c in Prediction.__table__.columns}
        assert "agent_weights" in cols, "predictions 表应有 agent_weights 列"

    def test_agent_weights_is_jsonb(self):
        """agent_weights 应为 JSONB 类型。"""
        col = Prediction.__table__.columns["agent_weights"]
        # JSONB 类型检查
        assert "JSON" in str(col.type).upper() or "JSONB" in str(col.type).upper()

    def test_agent_weights_nullable(self):
        """agent_weights 应可空(旧行保持 NULL)。"""
        col = Prediction.__table__.columns["agent_weights"]
        assert col.nullable is True, "agent_weights 应可空"


class TestMigration:
    """验证迁移文件存在且内容正确。"""

    def test_migration_exists(self):
        assert MIGRATION_PATH.is_file(), f"迁移文件不存在: {MIGRATION_PATH}"

    def test_migration_content(self):
        content = MIGRATION_PATH.read_text(encoding="utf-8")

        assert "agent_weights" in content
        assert "upgrade" in content
        assert "downgrade" in content
        assert "downgrade" in content and "drop_column" in content
        assert "nullable=True" in content


class TestOrchestratorWritesAgentWeights:
    """验证 orchestrator 写入 agent_weights。"""

    @pytest.mark.asyncio
    async def test_orchestrator_writes_agent_weights_to_upsert(self):
        """orchestrator 应将 agent_weights 传入 _insert_or_find_by_fingerprint。"""
        from src.llm.agents import orchestrator as orch_mod
        from src.llm.agents.base import AgentReport
        from src.llm.context_builder import MatchHeader

        header = MatchHeader(
            match_id=999, home_name="A", away_name="B",
            league_name="X", season=None, match_date="?",
            match_dt=None, stage=None,
            home_team_id=1, away_team_id=2, league_id=1,
        )

        # 构造有效专家报告(至少 1 个 ok)
        reports = [
            AgentReport(agent="form", status="ok", analysis="good"),
            AgentReport(agent="stats", status="error", analysis="failed"),
            AgentReport(agent="home_away", status="ok", analysis="good"),
            AgentReport(agent="standings", status="no_data", analysis="无数据"),
            AgentReport(agent="h2h", status="error", analysis="failed"),
        ]

        captured_values = {}

        async def mock_specialists(h, *, version, before, model_override=None):
            return reports

        async def mock_provider(aid, **kw):
            return MagicMock(model="test-model")

        async def mock_header(mid, db=None):
            return header

        async def mock_aggregator(header, reports, *, provider, version):
            return {
                "pred_home_goals": 2,
                "pred_away_goals": 1,
                "pred_1x2": "1",
                "subjective_confidence": 0.7,
                "reasoning": "test",
                "agent_weights": {"form": 0.3, "home_away": 0.5, "stats": 0.2},
            }, 100, 50

        async def mock_upsert(session, *, values):
            captured_values.update(values)
            p = MagicMock()
            p.id = 1
            p.provider = "test"
            p.model = "test"
            p.prompt_version = "v1"
            p.pred_home_goals = 2
            p.pred_away_goals = 1
            p.pred_1x2 = "1"
            p.subjective_confidence = 0.7
            p.reasoning = "test"
            p.agent_outputs = []
            p.agent_weights = values.get("agent_weights")
            return p

        class FakeUow:
            async def __aenter__(self):
                return self
            async def __aexit__(self, *a):
                pass
            async def get(self, cls, id):
                return MagicMock()

        with patch.object(orch_mod, "run_specialists", mock_specialists), \
             patch.object(orch_mod, "_agent_provider", mock_provider), \
             patch.object(orch_mod, "load_match_header", mock_header), \
             patch.object(orch_mod, "_insert_or_find_by_fingerprint", mock_upsert), \
             patch.object(orch_mod, "run_aggregator", mock_aggregator), \
             patch.object(orch_mod, "get_uow", FakeUow):

            result = await orch_mod.predict_match_multi(999)

        # 断言 agent_weights 被写入
        assert "agent_weights" in captured_values, "agent_weights 应传入 _insert_or_find_by_fingerprint"
        assert captured_values["agent_weights"] is not None, "agent_weights 不应为 None"
        assert "form" in captured_values["agent_weights"], "agent_weights 应包含专家权重"
        print(f"PASS: agent_weights = {captured_values['agent_weights']}")