feat: 足球 LLM 预测服务初始提交

Profeto — 给 LLM 提供数据,让 LLM 预测足球比分。

核心模块:
- FastAPI 后端 + PostgreSQL (SQLAlchemy async)
- 多 Agent LLM 预测 (5 专家 + 终裁)
- 数据采集 (bzzoiro / understat / injuries)
- React 前端 (Vite + Tailwind)

包含:
- 数据源抽象 (DataSource 协议 + 注册表)
- Alembic 数据库迁移
- Prompt 模板 (单/多 Agent)
- 核心路径单元测试

tests/test_core.py

@@ -0,0 +1,112 @@
+"""测试核心路径。"""
+import pytest
+from datetime import datetime, timezone
+from src.data.normalize import NormalizedMatch, normalize_bzzoiro, _parse_date, _to_int, _to_float, derive_season_label
+
+
+class TestNormalize:
+    def test_parse_date_iso(self):
+        assert _parse_date("2026-09-15T15:00:00Z") is not None
+
+    def test_parse_date_bare(self):
+        assert _parse_date("2026-09-15") is not None
+
+    def test_parse_date_none(self):
+        assert _parse_date(None) is None
+        assert _parse_date("") is None
+
+    def test_to_int_strict(self):
+        assert _to_int("2") == 2
+        assert _to_int("2.0") == 2
+        assert _to_int("2.8") is None  # 拒绝非整数值
+        assert _to_int(None) is None
+        assert _to_int("-") is None
+
+    def test_to_float(self):
+        assert _to_float("1.5") == 1.5
+        assert _to_float(None) is None
+
+    def test_normalize_bzzoiro_finished(self):
+        raw = {
+            "event_date": "2026-09-15T15:00:00Z",
+            "status": "finished",
+            "home_team": "Man City",
+            "away_team": "Man United",
+            "home_score": 2,
+            "away_score": 1,
+            "round_number": 5,
+        }
+        m = normalize_bzzoiro(raw, "E0")
+        assert m is not None
+        assert m.home_team == "Manchester City"
+        assert m.away_team == "Manchester United"
+        assert m.home_goals == 2
+        assert m.away_goals == 1
+        assert m.match_status == "finished"
+        assert m.match_stage == "第 5 轮"
+
+    def test_normalize_bzzoiro_unknown_status(self):
+        raw = {"event_date": "2026-09-15", "status": "weird", "home_team": "A", "away_team": "B"}
+        assert normalize_bzzoiro(raw, "E0") is None
+
+    def test_normalized_match_validate_finished_no_score(self):
+        m = NormalizedMatch(
+            league_type="E0", date=_parse_date("2026-09-15"),
+            home_team="A", away_team="B", match_status="finished",
+        )
+        with pytest.raises(ValueError, match="must have score"):
+            m.validate()
+
+    def test_normalized_match_validate_goals_range(self):
+        m = NormalizedMatch(
+            league_type="E0", date=_parse_date("2026-09-15"),
+            home_team="A", away_team="B", match_status="finished",
+            home_goals=50, away_goals=0,
+        )
+        with pytest.raises(ValueError, match="out of range"):
+            m.validate()
+
+
+class TestSeasonLabel:
+    def test_august_is_new_season(self):
+        # 8 月属于新赛季
+        d = datetime(2026, 8, 15, tzinfo=timezone.utc)
+        assert derive_season_label(d) == "2026-2027"
+
+    def test_july_is_old_season(self):
+        # 7 月属于上一赛季
+        d = datetime(2026, 7, 15, tzinfo=timezone.utc)
+        assert derive_season_label(d) == "2025-2026"
+
+    def test_january_is_old_season(self):
+        d = datetime(2026, 1, 15, tzinfo=timezone.utc)
+        assert derive_season_label(d) == "2025-2026"
+
+
+class TestProviderMock:
+    """用 mock 测试 LLM provider 的解析逻辑。"""
+
+    @pytest.mark.asyncio
+    async def test_provider_parses_json(self, monkeypatch):
+        from src.llm.provider import LLMProvider
+
+        async def fake_post(*args, **kwargs):
+            class FakeResp:
+                status_code = 200
+                def raise_for_status(self): pass
+                def json(self):
+                    return {
+                        "choices": [{"message": {"content": '{"pred_home_goals": 1.5, "pred_away_goals": 1.0, "1x2": "1", "confidence": 0.7, "reasoning": "test"}'}}],
+                        "usage": {"prompt_tokens": 100, "completion_tokens": 50},
+                    }
+            return FakeResp()
+
+        import httpx
+        monkeypatch.setattr(httpx.AsyncClient, "post", fake_post)
+
+        p = LLMProvider(api_key="test", model="gpt-4o")
+        resp = await p.chat("sys", "user", json_mode=True)
+        assert resp.error is None
+        assert resp.parsed is not None
+        assert resp.parsed["pred_home_goals"] == 1.5
+        assert resp.parsed["1x2"] == "1"