安全加固 + 数据管线修复 + 质量改进(第2批)

安全加固:
- /api/v1/predict 限流改用 get_client_ip 防 X-Forwarded-For 伪造
- 新增 TRUST_PROXY_HEADERS/REQUIRE_ADMIN_AUTH 配置,默认 fail-closed
- 生产环境管理接口未配置鉴权时拒绝(503),不再放行

数据管线修复:
- injuries IntegrityError 改用 begin_nested(SAVEPOINT)隔离批次
- injuries 空名单 vs 未配置语义区分(has_data 精确标记)
- bzzoiro 统计字段映射(shots/possession/cards) + 入库条件放宽
- available_at 语义收紧(回测防泄漏)
- team_names NFKD 去变音双重查找 + 补齐变体键

预测系统改进:
- multi-agent 全专家失败时 status=degraded 跳过终裁
- agent_weights 独立持久化到 predictions 表

新增迁移:
- 0014_predictions_agent_weights.py

新增测试(8个文件):
- test_ip_spoofing.py: 限流防伪造
- test_require_admin_fail_closed.py: 生产 fail-closed
- test_injuries_integrity_rollback.py: SAVEPOINT 隔离
- test_injuries_slice_semantic.py: 空名单 vs 未配置
- test_available_at.py: 回测防泄漏
- test_bzzoirot_stats.py: 统计字段映射
- test_team_names_normalize.py: NFKD 变体
- test_multi_agent_degraded.py: 全失败 degraded
- test_agent_weights_persist.py: 权重持久化

src/llm/agents/orchestrator.py

@@ -243,11 +243,35 @@ async def predict_match_multi(
     # 2. 并行专家(各自独立配置,使用统一 cutoff)
     reports = await run_specialists(header, version=version, before=cutoff)
 
-    # 3. 终裁
-    aggregator_provider = await _agent_provider("aggregator", tier="aggregator")
-    final, agg_prompt_tokens, agg_completion_tokens = await run_aggregator(
-        header, reports, provider=aggregator_provider, version=version
-    )
+    # 2.5 统计有效专家报告数量
+    ok_reports = [r for r in reports if r.status == "ok"]
+    has_valid_data = len(ok_reports) > 0
+
+    # 3. 终裁(仅当有有效专家报告时执行)
+    if has_valid_data:
+        aggregator_provider = await _agent_provider("aggregator", tier="aggregator")
+        final, agg_prompt_tokens, agg_completion_tokens = await run_aggregator(
+            header, reports, provider=aggregator_provider, version=version
+        )
+    else:
+        # 所有专家无数据/均失败:跳过终裁,标记 degraded
+        logger.warning(
+            "match %s: 所有 %d 位专家均无有效数据,跳过终裁,标记 degraded",
+            match_id, len(reports),
+        )
+        aggregator_provider = await _agent_provider("aggregator", tier="aggregator")
+        final = {
+            "pred_home_goals": None,
+            "pred_away_goals": None,
+            "alt_pred_home_goals": None,
+            "alt_pred_away_goals": None,
+            "pred_1x2": None,
+            "subjective_confidence": None,
+            "reasoning": f"所有 {len(reports)} 位专家均无有效数据或预测失败(状态: {','.join(r.status for r in reports)})",
+            "agent_weights": {},
+        }
+        agg_prompt_tokens = 0
+        agg_completion_tokens = 0
 
     latency_ms = int((time.perf_counter() - start) * 1000)
 
@@ -262,15 +286,23 @@ async def predict_match_multi(
         if m is None:
             raise ValueError(f"match {match_id} not found")
 
-        # 严格校验终裁输出
+        # 根据是否有有效数据决定校验策略
         from src.llm.validation import validate_agent_weights, validate_prediction_output
-        try:
-            validated = validate_prediction_output(final)
-        except Exception as e:
-            raise RuntimeError(f"终裁输出校验失败: {e}")
 
-        # agent_weights 同样必须过校验(旧实现直接取 raw 值落库,未做任何检查)
-        agent_weights = validate_agent_weights(final.get("agent_weights"))
+        if has_valid_data:
+            # 有有效报告:严格校验终裁输出
+            try:
+                validated = validate_prediction_output(final)
+            except Exception as e:
+                raise RuntimeError(f"终裁输出校验失败: {e}")
+            agent_weights = validate_agent_weights(final.get("agent_weights"))
+            pred_status = "success"
+        else:
+            # 无有效报告:跳过严格校验,直接构造降级结果
+            validated = None  # type: ignore
+            agent_weights = {}
+            pred_status = "degraded"
+
         pred = await _upsert_prediction(
             session,
             match_id=match_id,
@@ -283,16 +315,17 @@ async def predict_match_multi(
                 "prompt_tokens": sum(r.prompt_tokens or 0 for r in reports) + agg_prompt_tokens,
                 "completion_tokens": sum(r.completion_tokens or 0 for r in reports) + agg_completion_tokens,
                 "latency_ms": latency_ms,
-                "pred_home_goals": validated.pred_home_goals,
-                "pred_away_goals": validated.pred_away_goals,
-                "alt_pred_home_goals": validated.alt_pred_home_goals,
-                "alt_pred_away_goals": validated.alt_pred_away_goals,
-                "pred_1x2": validated.pred_1x2,
-                "subjective_confidence": validated.subjective_confidence,
-                "reasoning": validated.reasoning,
+                "pred_home_goals": validated.pred_home_goals if validated else None,
+                "pred_away_goals": validated.pred_away_goals if validated else None,
+                "alt_pred_home_goals": validated.alt_pred_home_goals if validated else None,
+                "alt_pred_away_goals": validated.alt_pred_away_goals if validated else None,
+                "pred_1x2": validated.pred_1x2 if validated else None,
+                "subjective_confidence": validated.subjective_confidence if validated else None,
+                "reasoning": validated.reasoning if validated else final.get("reasoning", ""),
                 "raw_response": final,
                 "agent_outputs": [r.to_dict() for r in reports],
-                "status": "success",
+                "agent_weights": agent_weights,
+                "status": pred_status,
                 "match_kickoff_at": match_kickoff_at,
                 "prediction_cutoff_at": prediction_cutoff_at,
                 "prediction_created_at": now,