docs(uiux): UIUX 设计方案大改 + 5 份作业指导书对齐 + 开发任务文档

- UIUX 文档：填充 19 个缺口（多主体画像/健康度/AI+看板/增长域/洞察域/创始人端/OODA/助推/商密）
- UIUX 文档：插入 6 个新章节（十四~十九），旧章节重编号为二十~三十一，更新目录和交叉引用
- 作业指导书 x5：导航改为 6 域分组，新增 Context Bar/工作模式/Insight Rail/决策线程/多工作区等 UI 概念
- 新建 docs/2-task-uiux.md：50 个代码落地开发任务，按 P0-P6 分优先级 + 8 Sprint 规划
- 后端/前端：大量新增模型、路由、组件（来自之前 Phase 开发）

backend/tests/test_predictor.py

@@ -0,0 +1,93 @@
+"""T4.10 智能预警 + 预测分析测试。"""
+
+import pytest
+from fastapi.testclient import TestClient
+
+from app.services.predictor import predict_trend, detect_anomalies
+
+
+class TestPredictTrend:
+    """趋势预测函数测试。"""
+
+    def test_predict_with_sufficient_data(self):
+        """有足够历史数据时应返回预测。"""
+        result = predict_trend([60, 62, 65, 68, 70], months_ahead=3)
+        assert "predicted" in result
+        assert len(result["predicted"]) == 3
+        assert all(0 <= p <= 100 for p in result["predicted"])
+        assert result["confidence"] > 0
+
+    def test_predict_with_insufficient_data(self):
+        """数据不足时应返回空预测。"""
+        result = predict_trend([50], months_ahead=3)
+        assert result["predicted"] == []
+        assert result["confidence"] == 0.0
+
+    def test_predict_stable_trend(self):
+        """稳定趋势斜率应接近 0。"""
+        result = predict_trend([70, 70, 70, 70], months_ahead=2)
+        assert abs(result["slope"]) < 0.1
+
+    def test_predict_upward_trend(self):
+        """上升趋势斜率应为正。"""
+        result = predict_trend([50, 55, 60, 65, 70], months_ahead=2)
+        assert result["slope"] > 0
+
+    def test_predict_downward_trend(self):
+        """下降趋势斜率应为负。"""
+        result = predict_trend([80, 75, 70, 65, 60], months_ahead=2)
+        assert result["slope"] < 0
+
+
+class TestDetectAnomalies:
+    """异常检测函数测试。"""
+
+    def test_detect_with_normal_data(self):
+        """正常数据不应检测到异常。"""
+        result = detect_anomalies([70, 71, 69, 70, 71])
+        assert result == []
+
+    def test_detect_with_anomaly(self):
+        """包含异常值时应检测到。"""
+        result = detect_anomalies([70, 71, 69, 70, 500], threshold=1.5)
+        assert len(result) > 0
+        assert 4 in result
+
+    def test_detect_with_insufficient_data(self):
+        """数据不足时应返回空。"""
+        assert detect_anomalies([50, 60]) == []
+
+    def test_detect_with_constant_data(self):
+        """恒定数据不应检测到异常。"""
+        assert detect_anomalies([70, 70, 70, 70]) == []
+
+
+class TestForecastEndpoint:
+    """预测接口测试。"""
+
+    def test_forecast_empty(self, client: TestClient, auth_headers: dict):
+        """无历史数据时应正常返回。"""
+        resp = client.get("/api/v1/dashboard/forecasts", headers=auth_headers)
+        assert resp.status_code == 200
+        data = resp.json()["data"]
+        assert "predictions" in data
+        assert "trend_direction" in data
+        assert "anomalies" in data
+
+    def test_forecast_with_company_id(self, client: TestClient, auth_headers: dict, company_id: str):
+        """指定企业 ID 应正常返回。"""
+        resp = client.get(
+            f"/api/v1/dashboard/forecasts?company_id={company_id}&months_ahead=3",
+            headers=auth_headers,
+        )
+        assert resp.status_code == 200
+
+    def test_forecast_invalid_months(self, client: TestClient, auth_headers: dict):
+        """无效 months_ahead 应返回 422。"""
+        resp = client.get("/api/v1/dashboard/forecasts?months_ahead=0", headers=auth_headers)
+        assert resp.status_code == 422
+
+    def test_forecast_no_auth(self, client: TestClient):
+        """未认证应返回 401。"""
+        resp = client.get("/api/v1/dashboard/forecasts")
+        assert resp.status_code == 401