diff --git a/README.md b/README.md
index 1d3ad3b..a7c34e2 100644
--- a/README.md
+++ b/README.md
@@ -67,8 +67,8 @@
### 1.9 AI 拍照巡检闭环（计划 #5/#6/#8/#9）
-- `ai-service/`：FastAPI + ONNX Runtime（默认 mock 模式；`POST /detect` 返回框/类别/置信度，`POST /stream-detect` 拉流抽帧骨架，`GET /metrics` 监控指标）
-- 拍照上传 → AI 检测 → 风险评分（0-100 分，绿/黄/橙/红四级）→ 巡检记录（`inspection_records`，`Idempotency-Key` 幂等）
+- `ai-service/`：FastAPI + ONNX Runtime（默认 mock 模式；`POST /detect` 返回框/类别/置信度、`modelVersion`、`isMock`、`abnormalProbability`，`POST /internal/stream-tasks` 受限拉流任务，`GET /metrics` 监控指标）
+- 拍照上传 → AI 检测 → 风险评分（0-100 分，绿/黄/橙/红四级，只消费 AI 异常概率，缺失项不按 0 参与）→ 巡检记录（`inspection_records`，`Idempotency-Key` 幂等）
- 小程序「拍照巡检」页；Web「巡检记录」页（技术员复查）
### 1.10 知识库与阶段风险提示（计划 #10/#13）
@@ -595,8 +595,8 @@ python -m venv .venv
MODEL_MODE=mock .venv\Scripts\python -m uvicorn app.main:app --host 0.0.0.0 --port 8000
```
-- 接口：`GET /health`、`POST /detect`（multipart 图片）、`POST /stream-detect`（摄像头流拉帧骨架）、`GET /metrics`（含 GPU 信息）
-- 默认 mock 模式；训练恢复后放 `models/best.onnx` 并设 `MODEL_MODE=onnx`（`MODEL_LABELS` 可配类别）
+- 接口：`GET /health`、`POST /detect`（multipart 图片，返回 `abnormalProbability`）、`POST /internal/stream-tasks`（受限摄像头流拉帧任务）、`GET /metrics`（含 GPU 信息）
+- 默认 mock 模式且响应带 `isMock=true`；训练恢复后放 `models/best.onnx` 并设 `MODEL_MODE=onnx`（`MODEL_LABELS` 可配类别、`MODEL_VERSION` 必须显式配置）
- 开发服务器部署：`/home/pan/ai-service`（venv + `start.sh`，:8000），服务器 pip 源已配置清华镜像
### 12.7 开发服务器部署摘要
diff --git a/ai-service/README.md b/ai-service/README.md
index 89489e1..a3f02ed 100644
--- a/ai-service/README.md
+++ b/ai-service/README.md
@@ -5,7 +5,7 @@ FastAPI + ONNX Runtime 的蚕病检测推理服务。YOLO 训练挂起期间以
## 接口
- `GET /health` → `{"status":"ok","model":"mock|onnx"}`
-- `POST /detect`（multipart 字段 `file`）→ `{"model":"mock","detections":[{"bbox":{x,y,w,h},"class":"healthy|sick","confidence":0.95}]}`
+- `POST /detect`（multipart 字段 `file`）→ `{"model":"mock","modelVersion":"...","isMock":true,"status":"healthy|abnormal|unknown","abnormalProbability":0,"detections":[{"bbox":{x,y,w,h},"class":"healthy|sick","confidence":0.95}]}`
- `POST /internal/stream-tasks`（需 `X-Internal-Key`）→ 创建受限拉流任务，不再接受客户端任意 URL
## 本地运行
@@ -33,6 +33,7 @@ powershell -ExecutionPolicy Bypass -File scripts/verify.ps1
| `MODEL_MODE` | `mock` | `mock` / `onnx` |
| `MODEL_PATH` | `models/best.onnx` | ONNX 模型路径 |
| `MODEL_LABELS` | `healthy,sick` | 类别列表（逗号分隔） |
+| `MODEL_VERSION` | `mock-2026.08.14` / `best.onnx` | 模型版本；真实模型上线时必须显式配置 |
| `MOCK_CLASS` | `healthy` | mock 返回类别 |
| `MOCK_CONFIDENCE` | `0.95` | mock 返回置信度 |
| `INTERNAL_API_KEY` | `silk-internal-2026` | 内部接口认证密钥 |
@@ -42,5 +43,6 @@ powershell -ExecutionPolicy Bypass -File scripts/verify.ps1
## 说明
-- 只做检测，风险评分在 Go 后端计算（#9：0.5×AI 置信度 + 0.2×环境 + 0.15×阶段 + 0.15×整齐度）。
+- 只做检测并返回 `abnormalProbability`；风险评分在 Go 后端计算（#9：0.5×AI 异常概率 + 0.2×环境 + 0.15×阶段 + 0.15×整齐度，缺失项归一化）。
+- `healthy` 高置信度不贡献异常概率；空检测或 `unknown` 返回 `unknown`，不自动视为健康。
- ONNX 后处理按 YOLOv8 常见输出格式实现（含 letterbox 与 NMS），训练产物出来后需用真实模型校准验证。
diff --git a/ai-service/app/config.py b/ai-service/app/config.py
index 825b9e3..17c019a 100644
--- a/ai-service/app/config.py
+++ b/ai-service/app/config.py
@@ -5,6 +5,7 @@ MODEL_MODE = os.getenv("MODEL_MODE", "mock")
MODEL_PATH = os.getenv("MODEL_PATH", "models/best.onnx")
# YOLO 类别（二分类训练基线：healthy/sick；7 类病种扩展后再调整）
MODEL_LABELS = os.getenv("MODEL_LABELS", "healthy,sick").split(",")
+MODEL_VERSION = os.getenv("MODEL_VERSION", "mock-2026.08.14" if MODEL_MODE == "mock" else "best.onnx")
# mock 模式返回的固定结果
MOCK_CLASS = os.getenv("MOCK_CLASS", "healthy")
MOCK_CONFIDENCE = float(os.getenv("MOCK_CONFIDENCE", "0.95"))
diff --git a/ai-service/app/detector.py b/ai-service/app/detector.py
index 8095515..9512718 100644
--- a/ai-service/app/detector.py
+++ b/ai-service/app/detector.py
@@ -5,6 +5,52 @@ from abc import ABC, abstractmethod
from PIL import Image
+def _label_set(labels) -> set[str]:
+ return {label.strip().lower() for label in labels if label.strip()}
+
+
+def abnormal_probability(detections: list[dict], labels: tuple[str, ...] | list[str]) -> float:
+ """单帧异常概率：取异常类检测的最高置信度，避免多框求和造成虚高。"""
+ abnormal = _label_set(labels) - {"healthy"}
+ best = 0.0
+ for detection in detections:
+ class_name = str(detection.get("class_name", "")).strip().lower()
+ if class_name in ("", "healthy", "unknown"):
+ continue
+ if abnormal and class_name not in abnormal:
+ continue
+ try:
+ confidence = float(detection.get("confidence", 0))
+ except (TypeError, ValueError):
+ confidence = 0.0
+ best = max(best, min(1.0, max(0.0, confidence)))
+ return best
+
+
+def detection_status(detections: list[dict], labels: tuple[str, ...] | list[str]) -> str:
+ """空检测或 unknown 类不再被当作 healthy。"""
+ if not detections:
+ return "unknown"
+ abnormal = _label_set(labels) - {"healthy"}
+ healthy_seen = False
+ unknown_seen = False
+ for detection in detections:
+ class_name = str(detection.get("class_name", "")).strip().lower()
+ if abnormal and class_name in abnormal:
+ return "abnormal"
+ if not abnormal and class_name not in ("", "healthy", "unknown"):
+ return "abnormal"
+ if class_name == "healthy":
+ healthy_seen = True
+ elif class_name in ("", "unknown"):
+ unknown_seen = True
+ else:
+ unknown_seen = True
+ if healthy_seen and not unknown_seen:
+ return "healthy"
+ return "unknown"
+
+
class Detector(ABC):
@abstractmethod
def detect(self, image_bytes: bytes) -> list[dict]:
diff --git a/ai-service/app/main.py b/ai-service/app/main.py
index dc006a9..7625a9f 100644
--- a/ai-service/app/main.py
+++ b/ai-service/app/main.py
@@ -6,7 +6,7 @@ import time
from fastapi import FastAPI, File, HTTPException, Request, UploadFile
from . import config
-from .detector import MockDetector, ONNXDetector
+from .detector import MockDetector, ONNXDetector, abnormal_probability, detection_status
from .stream_tasks import StreamTaskWorker, is_allowed_stream_ref
app = FastAPI(title="Silk AI Service", version="0.1.0")
@@ -36,7 +36,12 @@ else:
@app.get("/health")
def health():
- return {"status": "ok", "model": config.MODEL_MODE}
+ return {
+ "status": "ok",
+ "model": config.MODEL_MODE,
+ "modelVersion": config.MODEL_VERSION,
+ "isMock": isinstance(detector, MockDetector),
+ }
@app.post("/detect")
@@ -50,6 +55,10 @@ async def detect(file: UploadFile = File(...)):
raise HTTPException(status_code=400, detail=str(exc)) from exc
return {
"model": config.MODEL_MODE,
+ "modelVersion": config.MODEL_VERSION,
+ "isMock": isinstance(detector, MockDetector),
+ "status": detection_status(detections, config.MODEL_LABELS),
+ "abnormalProbability": abnormal_probability(detections, config.MODEL_LABELS),
"detections": [
{
"bbox": d["bbox"],
@@ -112,6 +121,8 @@ def metrics():
gpu = None
return {
"model": config.MODEL_MODE,
+ "modelVersion": config.MODEL_VERSION,
+ "isMock": isinstance(detector, MockDetector),
"uptimeSeconds": int(time.time() - START_TIME),
"requests": reqs,
"avgLatencyMs": round(avg, 2),
diff --git a/ai-service/tests/test_api.py b/ai-service/tests/test_api.py
index 2173990..6be53d2 100644
--- a/ai-service/tests/test_api.py
+++ b/ai-service/tests/test_api.py
@@ -6,7 +6,9 @@ os.environ.setdefault("ALLOWED_STREAM_HOSTS", "localhost,127.0.0.1,100.83.103.1"
from fastapi.testclient import TestClient
+from app import main as main_module
from app.main import app
+from app.detector import MockDetector
# 1x1 透明 PNG
TINY_PNG = base64.b64decode(
@@ -22,6 +24,8 @@ def test_health():
body = r.json()
assert body["status"] == "ok"
assert body["model"] in ("mock", "onnx")
+ assert body["modelVersion"]
+ assert body["isMock"] is True
def test_detect_ok():
@@ -29,6 +33,10 @@ def test_detect_ok():
assert r.status_code == 200
body = r.json()
assert body["model"] == "mock"
+ assert body["modelVersion"]
+ assert body["isMock"] is True
+ assert body["status"] == "healthy"
+ assert body["abnormalProbability"] == 0
assert len(body["detections"]) >= 1
d = body["detections"][0]
assert d["class"] in ("healthy", "sick")
@@ -36,6 +44,28 @@ def test_detect_ok():
assert d["bbox"]["w"] > 0
+def test_detect_uses_abnormal_class_confidence(monkeypatch):
+ monkeypatch.setattr(main_module, "detector", MockDetector(class_name="sick", confidence=0.92))
+ r = client.post("/detect", files={"file": ("a.png", TINY_PNG, "image/png")})
+ assert r.status_code == 200
+ body = r.json()
+ assert body["status"] == "abnormal"
+ assert body["abnormalProbability"] == 0.92
+
+
+def test_detect_empty_result_is_unknown(monkeypatch):
+ class EmptyDetector:
+ def detect(self, image_bytes):
+ return []
+
+ monkeypatch.setattr(main_module, "detector", EmptyDetector())
+ r = client.post("/detect", files={"file": ("a.png", TINY_PNG, "image/png")})
+ assert r.status_code == 200
+ body = r.json()
+ assert body["status"] == "unknown"
+ assert body["abnormalProbability"] == 0
+
+
def test_detect_empty_file_rejected():
r = client.post("/detect", files={"file": ("a.png", b"", "image/png")})
assert r.status_code == 400
diff --git a/ai-service/tests/test_detector.py b/ai-service/tests/test_detector.py
index 756203a..b6c4ed3 100644
--- a/ai-service/tests/test_detector.py
+++ b/ai-service/tests/test_detector.py
@@ -2,7 +2,7 @@ import base64
import pytest
-from app.detector import MockDetector
+from app.detector import MockDetector, abnormal_probability, detection_status
# 1x1 透明 PNG
TINY_PNG = base64.b64decode(
@@ -23,3 +23,22 @@ def test_mock_detector_rejects_invalid_image():
det = MockDetector()
with pytest.raises(ValueError):
det.detect(b"not an image")
+
+
+def test_abnormal_probability_ignores_healthy_and_unknown():
+ detections = [
+ {"class_name": "healthy", "confidence": 0.95},
+ {"class_name": "unknown", "confidence": 0.8},
+ {"class_name": "sick", "confidence": 0.72},
+ ]
+ assert abnormal_probability(detections, ("healthy", "sick")) == 0.72
+
+
+def test_detection_status_returns_unknown_for_empty_or_unknown():
+ assert detection_status([], ("healthy", "sick")) == "unknown"
+ assert detection_status([{"class_name": "unknown", "confidence": 0.8}], ("healthy", "sick")) == "unknown"
+ assert detection_status([{"class_name": "healthy", "confidence": 0.95}], ("healthy", "sick")) == "healthy"
+ assert detection_status(
+ [{"class_name": "white_muscardine", "confidence": 0.7}],
+ ("healthy", "white_muscardine", "nuclear_polyhedrosis"),
+ ) == "abnormal"
diff --git a/miniapp/src/pages/inspection/index.tsx b/miniapp/src/pages/inspection/index.tsx
index 2ee0137..f35fc48 100644
--- a/miniapp/src/pages/inspection/index.tsx
+++ b/miniapp/src/pages/inspection/index.tsx
@@ -113,6 +113,7 @@ const InspectionPage: React.FC = () => {
? '检测到疑似异常'
: '未见明显异常'
: 'AI 检测失败'}
+ {result.isMock ? '（联调 Mock）' : ''}
{result.aiStatus === 'done' && result.detections && result.detections.length > 0 ? (
@@ -145,6 +146,7 @@ const InspectionPage: React.FC = () => {
? '疑似异常'
: '正常'
: '检测失败'}
+ {rec.isMock ? '（Mock）' : ''}
{formatRelativeTime(rec.createdAt)}
diff --git a/miniapp/src/types/index.ts b/miniapp/src/types/index.ts
index 82db964..d319e74 100644
--- a/miniapp/src/types/index.ts
+++ b/miniapp/src/types/index.ts
@@ -223,6 +223,17 @@ export interface InspectionRecord {
detections?: AIDetection[];
riskScore?: number;
riskLevel?: string;
+ riskAssessment?: {
+ score: number;
+ level: string;
+ confidence: string;
+ modelVersion: string;
+ ruleVersion: string;
+ components: Record;
+ missing: string[];
+ };
+ modelVersion?: string;
+ isMock?: boolean;
aiStatus: string;
idempotencyKey?: string;
createdAt?: string;
diff --git a/scripts/risk_historical_review.sql b/scripts/risk_historical_review.sql
new file mode 100644
index 0000000..aa0a8c1
--- /dev/null
+++ b/scripts/risk_historical_review.sql
@@ -0,0 +1,27 @@
+-- Task 6 Step 5: 只读历史数据评估报告
+-- 仅统计，不更新数据；未经人工确认不得批量重算或覆盖历史 risk_score/risk_level。
+
+WITH real_inspections AS (
+ SELECT
+ id,
+ risk_level,
+ risk_score,
+ detections
+ FROM inspection_records
+ WHERE ai_status = 'done'
+ AND (is_mock IS NULL OR is_mock = false)
+)
+SELECT
+ risk_level,
+ count(*) AS records,
+ count(*) FILTER (
+ WHERE EXISTS (
+ SELECT 1
+ FROM jsonb_array_elements(detections) AS d
+ WHERE d->>'class' = 'healthy'
+ AND COALESCE((d->>'confidence')::numeric, 0) >= 0.80
+ )
+ ) AS healthy_high_conf_records
+FROM real_inspections
+GROUP BY risk_level
+ORDER BY risk_level;
diff --git a/server-go/cmd/server/main.go b/server-go/cmd/server/main.go
index 8467ba7..04a13d6 100644
--- a/server-go/cmd/server/main.go
+++ b/server-go/cmd/server/main.go
@@ -111,7 +111,7 @@ func main() {
handler.RegisterVideoRecordRoutes(api, db, mediaSvc, cfg)
handler.RegisterStorageRoutes(api, db)
handler.RegisterKnowledgeRoutes(api, db, s3Svc, cfg.S3BucketImages)
- handler.RegisterInspectionRoutes(api, db, s3Svc, aiSvc, cfg.S3BucketImages, wechatSvc, cfg.WechatTemplateInspection)
+ handler.RegisterInspectionRoutes(api, db, s3Svc, aiSvc, cfg.S3BucketImages, wechatSvc, cfg.WechatTemplateInspection, cfg.AppEnv)
handler.RegisterTrayBatchRoutes(api, db)
handler.RegisterWechatRoutes(api, db, wechatSvc)
handler.RegisterWeatherRoutes(api, db, weatherSvc)
diff --git a/server-go/internal/database/migrate.go b/server-go/internal/database/migrate.go
index e01df10..529eff2 100644
--- a/server-go/internal/database/migrate.go
+++ b/server-go/internal/database/migrate.go
@@ -8,12 +8,12 @@ import (
"github.com/golang-migrate/migrate/v4"
"github.com/golang-migrate/migrate/v4/database/postgres"
"github.com/golang-migrate/migrate/v4/source/iofs"
- "silk-server-go/migrations"
"gorm.io/gorm"
+ "silk-server-go/migrations"
)
// CurrentSchemaVersion 是当前后端代码期望的迁移版本。
-const CurrentSchemaVersion = "1"
+const CurrentSchemaVersion = "2"
// RunMigrations 使用嵌入式 SQL 迁移文件将数据库升级到最新版本。
func RunMigrations(db *gorm.DB) error {
diff --git a/server-go/internal/database/migrate_test.go b/server-go/internal/database/migrate_test.go
index 00fc19b..b3b6720 100644
--- a/server-go/internal/database/migrate_test.go
+++ b/server-go/internal/database/migrate_test.go
@@ -100,4 +100,8 @@ func TestEmbeddedMigrationsIncludeBaseline(t *testing.T) {
if version != 1 {
t.Fatalf("expected baseline migration version 1, got %d", version)
}
+ next, err := driver.Next(version)
+ if err != nil || next != 2 {
+ t.Fatalf("expected risk assessment migration version 2, got %d (err %v)", next, err)
+ }
}
diff --git a/server-go/internal/handler/health.go b/server-go/internal/handler/health.go
index d5f3396..19c0a80 100644
--- a/server-go/internal/handler/health.go
+++ b/server-go/internal/handler/health.go
@@ -44,7 +44,7 @@ func roomHealthProfile(db *gorm.DB) gin.HandlerFunc {
}
db.Table("inspection_records").
Select("risk_level, count(*) AS cnt").
- Where("room_id = ? AND ai_status = 'done' AND risk_level IS NOT NULL AND created_at >= ?", id, since).
+ Where("room_id = ? AND ai_status = 'done' AND risk_level IS NOT NULL AND created_at >= ? AND COALESCE(is_mock, false) = false", id, since).
Group("risk_level").
Scan(&riskRows)
riskCounts := map[string]int64{}
diff --git a/server-go/internal/handler/inspection.go b/server-go/internal/handler/inspection.go
index f89e0c8..5c5c04f 100644
--- a/server-go/internal/handler/inspection.go
+++ b/server-go/internal/handler/inspection.go
@@ -5,6 +5,7 @@ import (
"context"
"encoding/json"
"io"
+ "log/slog"
"net/http"
"regexp"
"strconv"
@@ -26,8 +27,8 @@ func isUUID(s string) bool {
}
// RegisterInspectionRoutes 注册 AI 巡检路由
-func RegisterInspectionRoutes(rg *gin.RouterGroup, db *gorm.DB, s3 *service.S3Service, ai *service.AIClient, imageBucket string, wechat *service.WechatService, inspectionTemplateID string) {
- rg.POST("/inspections", middleware.RequirePermission(db, "inspection:create"), createInspection(db, s3, ai, imageBucket, wechat, inspectionTemplateID))
+func RegisterInspectionRoutes(rg *gin.RouterGroup, db *gorm.DB, s3 *service.S3Service, ai *service.AIClient, imageBucket string, wechat *service.WechatService, inspectionTemplateID string, appEnv string) {
+ rg.POST("/inspections", middleware.RequirePermission(db, "inspection:create"), createInspection(db, s3, ai, imageBucket, wechat, inspectionTemplateID, appEnv))
rg.GET("/inspections", middleware.RequirePermission(db, "inspection:read"), listInspections(db))
}
@@ -43,9 +44,29 @@ func currentUserID(c *gin.Context) *string {
return nil
}
+func buildRiskInput(detRes *service.AIDetectResponse) service.RiskInput {
+ status := detRes.Status
+ if status == "" {
+ status = service.AIDetectionStatus(detRes.Detections)
+ }
+ modelVersion := detRes.ModelVersion
+ if modelVersion == "" {
+ modelVersion = "unknown"
+ }
+ in := service.RiskInput{ModelVersion: modelVersion}
+ if status != "unknown" {
+ aiProb := detRes.AbnormalProbability
+ if len(detRes.Detections) > 0 && aiProb == 0 {
+ aiProb = service.AbnormalProbability(detRes.Detections)
+ }
+ in.AI = &aiProb
+ }
+ return in
+}
+
// createInspection 拍照巡检：图片存 S3 → 调 AI /detect → 写记录。
// 幂等：客户端传 Idempotency-Key 头时，重复请求返回已有记录。
-func createInspection(db *gorm.DB, s3 *service.S3Service, ai *service.AIClient, bucket string, wechat *service.WechatService, inspectionTemplateID string) gin.HandlerFunc {
+func createInspection(db *gorm.DB, s3 *service.S3Service, ai *service.AIClient, bucket string, wechat *service.WechatService, inspectionTemplateID string, appEnv string) gin.HandlerFunc {
return func(c *gin.Context) {
idemKey := strings.TrimSpace(c.GetHeader("Idempotency-Key"))
roomID := strings.TrimSpace(c.PostForm("roomId"))
@@ -113,49 +134,55 @@ func createInspection(db *gorm.DB, s3 *service.S3Service, ai *service.AIClient,
} else {
raw, _ := json.Marshal(detRes.Detections)
rec.Detections = raw
-
- // 风险评分（#9）：AI 置信度取检测结果最大值；环境/阶段系数在有 roomId 时按房间数据计算
- aiConf := 0.0
- for _, d := range detRes.Detections {
- if d.Confidence > aiConf {
- aiConf = d.Confidence
- }
+ isMock := detRes.IsMock
+ rec.IsMock = &isMock
+ modelVersion := detRes.ModelVersion
+ if modelVersion == "" {
+ modelVersion = "unknown"
}
- stageCoef, envCoef := loadRoomRisk(db, roomID)
- score := service.ComputeRiskScore(service.RiskInput{
- AI: aiConf,
- Env: envCoef,
- Stage: stageCoef,
- })
- rec.RiskScore = &score
- level := service.RiskLevel(score)
- rec.RiskLevel = &level
+ rec.ModelVersion = &modelVersion
- // 微信订阅消息（#11 骨架）：风险非绿且用户已授权时异步推送
- if key := service.WechatTemplateKey(level); key != "" {
- go func(uid *string, lv string, sc float64) {
- if uid == nil || !wechat.Configured() || inspectionTemplateID == "" {
- return
+ if appEnv == "production" && isMock {
+ slog.Error("生产环境收到 Mock AI 检测结果，按失败记录", "modelVersion", modelVersion, "roomId", roomID)
+ rec.AIStatus = "failed"
+ } else {
+ // 风险评分（#9 V2）：只消费 AI 异常概率；缺失环境/阶段不填 0
+ riskInput := buildRiskInput(detRes)
+ riskInput.Env, riskInput.Stage = loadRoomRisk(db, roomID)
+ assessment := service.ComputeRiskScore(riskInput)
+ rec.RiskScore = &assessment.Score
+ rec.RiskLevel = &assessment.Level
+ rawRisk, _ := json.Marshal(assessment)
+ rec.RiskAssessment = rawRisk
+
+ // 微信订阅消息（#11 骨架）：Mock 结果不进入告警，风险非绿且用户已授权时异步推送
+ if !isMock {
+ if key := service.WechatTemplateKey(assessment.Level); key != "" {
+ go func(uid *string, lv string, sc float64) {
+ if uid == nil || !wechat.Configured() || inspectionTemplateID == "" {
+ return
+ }
+ var binding model.WechatBinding
+ if db.Where("user_id = ?", *uid).First(&binding).Error != nil {
+ return
+ }
+ var authorized []string
+ if len(binding.AuthorizedTemplates) > 0 {
+ _ = json.Unmarshal(binding.AuthorizedTemplates, &authorized)
+ }
+ if !service.IsAuthorized(authorized, key) {
+ return
+ }
+ _ = wechat.SendSubscribe(
+ context.Background(),
+ binding.OpenID,
+ inspectionTemplateID,
+ service.BuildSubscribeData(lv, sc),
+ "pages/inspection/index",
+ )
+ }(rec.UserID, assessment.Level, assessment.Score)
}
- var binding model.WechatBinding
- if db.Where("user_id = ?", *uid).First(&binding).Error != nil {
- return
- }
- var authorized []string
- if len(binding.AuthorizedTemplates) > 0 {
- _ = json.Unmarshal(binding.AuthorizedTemplates, &authorized)
- }
- if !service.IsAuthorized(authorized, key) {
- return
- }
- _ = wechat.SendSubscribe(
- context.Background(),
- binding.OpenID,
- inspectionTemplateID,
- service.BuildSubscribeData(lv, sc),
- "pages/inspection/index",
- )
- }(rec.UserID, level, score)
+ }
}
}
@@ -175,17 +202,19 @@ func createInspection(db *gorm.DB, s3 *service.S3Service, ai *service.AIClient,
}
}
-// loadRoomRisk 加载房间阶段系数与环境系数（无房间/无数据时返回 0）
-func loadRoomRisk(db *gorm.DB, roomID string) (stageCoef, envCoef float64) {
+// loadRoomRisk 加载房间阶段系数与环境系数（无房间/无数据时返回 nil）
+func loadRoomRisk(db *gorm.DB, roomID string) (*float64, *float64) {
if roomID == "" {
- return 0, 0
+ return nil, nil
}
var room model.Room
if db.Where("id = ?", roomID).First(&room).Error != nil {
- return 0, 0
+ return nil, nil
}
+ var stageCoef *float64
if room.Stage != nil {
- stageCoef = service.StageCoefficient(*room.Stage)
+ value := service.StageCoefficient(*room.Stage)
+ stageCoef = &value
}
var humidity, temperature *float64
@@ -209,7 +238,11 @@ func loadRoomRisk(db *gorm.DB, roomID string) (stageCoef, envCoef float64) {
First(&t).Error; err == nil {
temperature = &t.Value
}
- envCoef = service.EnvCoefficient(temperature, humidity)
+ var envCoef *float64
+ if humidity != nil || temperature != nil {
+ value := service.EnvCoefficient(temperature, humidity)
+ envCoef = &value
+ }
return stageCoef, envCoef
}
diff --git a/server-go/internal/handler/inspection_test.go b/server-go/internal/handler/inspection_test.go
index fd6a3e7..92cff1e 100644
--- a/server-go/internal/handler/inspection_test.go
+++ b/server-go/internal/handler/inspection_test.go
@@ -1,6 +1,10 @@
package handler
-import "testing"
+import (
+ "testing"
+
+ "silk-server-go/internal/service"
+)
func TestIsUUID(t *testing.T) {
valid := []string{
@@ -19,3 +23,33 @@ func TestIsUUID(t *testing.T) {
}
}
}
+
+func TestBuildRiskInputUsesAbnormalProbability(t *testing.T) {
+ in := buildRiskInput(&service.AIDetectResponse{
+ ModelVersion: "silk-yolo-2026.08.1",
+ Status: "abnormal",
+ AbnormalProbability: 0.93,
+ })
+ if in.AI == nil || *in.AI != 0.93 {
+ t.Fatalf("AI 异常概率应进入风险输入，实际 %v", in.AI)
+ }
+ if in.ModelVersion != "silk-yolo-2026.08.1" {
+ t.Errorf("modelVersion = %s", in.ModelVersion)
+ }
+}
+
+func TestBuildRiskInputUnknownKeepsAIMissing(t *testing.T) {
+ in := buildRiskInput(&service.AIDetectResponse{Status: "unknown"})
+ if in.AI != nil {
+ t.Fatalf("unknown 状态不应把 0 当作 AI 组件，实际 %v", in.AI)
+ }
+}
+
+func TestBuildRiskInputFallsBackToDetections(t *testing.T) {
+ in := buildRiskInput(&service.AIDetectResponse{
+ Detections: []service.AIDetection{{ClassName: "sick", Confidence: 0.9}},
+ })
+ if in.AI == nil || *in.AI != 0.9 {
+ t.Fatalf("旧 AI 响应应从检测类别计算异常概率，实际 %v", in.AI)
+ }
+}
diff --git a/server-go/internal/model/inspection.go b/server-go/internal/model/inspection.go
index 936708d..0c943be 100644
--- a/server-go/internal/model/inspection.go
+++ b/server-go/internal/model/inspection.go
@@ -14,6 +14,9 @@ type InspectionRecord struct {
Detections json.RawMessage `gorm:"column:detections;type:jsonb" json:"detections,omitempty"`
RiskScore *float64 `gorm:"column:risk_score;type:float" json:"riskScore,omitempty"`
RiskLevel *string `gorm:"column:risk_level;size:16" json:"riskLevel,omitempty"`
+ RiskAssessment json.RawMessage `gorm:"column:risk_assessment;type:jsonb" json:"riskAssessment,omitempty"`
+ ModelVersion *string `gorm:"column:model_version;size:64" json:"modelVersion,omitempty"`
+ IsMock *bool `gorm:"column:is_mock;default:false" json:"isMock,omitempty"`
AIStatus string `gorm:"column:ai_status;size:16;default:done" json:"aiStatus"`
IdempotencyKey *string `gorm:"column:idempotency_key;size:128;uniqueIndex" json:"idempotencyKey,omitempty"`
CreatedAt time.Time `gorm:"type:timestamptz" json:"createdAt"`
diff --git a/server-go/internal/service/ai_client.go b/server-go/internal/service/ai_client.go
index 4c4a8b8..53628f2 100644
--- a/server-go/internal/service/ai_client.go
+++ b/server-go/internal/service/ai_client.go
@@ -29,8 +29,36 @@ type AIDetection struct {
// AIDetectResponse /detect 响应
type AIDetectResponse struct {
- Model string `json:"model"`
- Detections []AIDetection `json:"detections"`
+ Model string `json:"model"`
+ ModelVersion string `json:"modelVersion"`
+ IsMock bool `json:"isMock"`
+ Status string `json:"status"`
+ AbnormalProbability float64 `json:"abnormalProbability"`
+ Detections []AIDetection `json:"detections"`
+}
+
+// AIDetectionStatus 从检测结果归纳 AI 状态；空检测或 unknown 不当作 healthy。
+func AIDetectionStatus(detections []AIDetection) string {
+ if len(detections) == 0 {
+ return "unknown"
+ }
+ healthySeen := false
+ unknownSeen := false
+ for _, d := range detections {
+ class := strings.ToLower(strings.TrimSpace(d.ClassName))
+ switch class {
+ case "healthy":
+ healthySeen = true
+ case "", "unknown":
+ unknownSeen = true
+ default:
+ return "abnormal"
+ }
+ }
+ if healthySeen && !unknownSeen {
+ return "healthy"
+ }
+ return "unknown"
}
// AIClient ai-service HTTP 客户端
diff --git a/server-go/internal/service/ai_client_test.go b/server-go/internal/service/ai_client_test.go
index b80c949..745fcff 100644
--- a/server-go/internal/service/ai_client_test.go
+++ b/server-go/internal/service/ai_client_test.go
@@ -24,7 +24,11 @@ func TestAIClientDetectParsesResult(t *testing.T) {
}
w.Header().Set("Content-Type", "application/json")
_ = json.NewEncoder(w).Encode(map[string]any{
- "model": "mock",
+ "model": "mock",
+ "modelVersion": "silk-yolo-2026.08.1",
+ "isMock": true,
+ "status": "abnormal",
+ "abnormalProbability": 0.93,
"detections": []map[string]any{
{"bbox": map[string]float64{"x": 1, "y": 2, "w": 3, "h": 4}, "class": "sick", "confidence": 0.93},
},
@@ -40,6 +44,15 @@ func TestAIClientDetectParsesResult(t *testing.T) {
if res.Model != "mock" {
t.Errorf("model = %s, want mock", res.Model)
}
+ if res.ModelVersion != "silk-yolo-2026.08.1" {
+ t.Errorf("modelVersion = %s, want silk-yolo-2026.08.1", res.ModelVersion)
+ }
+ if !res.IsMock {
+ t.Error("isMock 应解析为 true")
+ }
+ if res.Status != "abnormal" || res.AbnormalProbability != 0.93 {
+ t.Errorf("AI 语义字段解析不正确: %+v", res)
+ }
if len(res.Detections) != 1 {
t.Fatalf("detections 数量 = %d, want 1", len(res.Detections))
}
@@ -49,6 +62,21 @@ func TestAIClientDetectParsesResult(t *testing.T) {
}
}
+func TestAIDetectionStatus(t *testing.T) {
+ if got := AIDetectionStatus(nil); got != "unknown" {
+ t.Errorf("空检测应为 unknown，实际 %s", got)
+ }
+ if got := AIDetectionStatus([]AIDetection{{ClassName: "healthy"}}); got != "healthy" {
+ t.Errorf("全健康应为 healthy，实际 %s", got)
+ }
+ if got := AIDetectionStatus([]AIDetection{{ClassName: "unknown"}}); got != "unknown" {
+ t.Errorf("unknown 应为 unknown，实际 %s", got)
+ }
+ if got := AIDetectionStatus([]AIDetection{{ClassName: "sick"}}); got != "abnormal" {
+ t.Errorf("异常类别应为 abnormal，实际 %s", got)
+ }
+}
+
func TestAIClientDetectServerError(t *testing.T) {
srv := httptest.NewServer(http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
http.Error(w, "boom", http.StatusInternalServerError)
diff --git a/server-go/internal/service/cross_validate.go b/server-go/internal/service/cross_validate.go
index 9180c00..c595a59 100644
--- a/server-go/internal/service/cross_validate.go
+++ b/server-go/internal/service/cross_validate.go
@@ -1,5 +1,7 @@
package service
+import "strings"
+
// CrossValidate 交叉验证：AI 检测结果 vs LAMP 检测结果（规格书：一致→确认诊断；不一致→升级专家会诊）
func CrossValidate(aiClass, lampResult string, lampDiseases []string) (bool, string) {
switch {
@@ -7,6 +9,8 @@ func CrossValidate(aiClass, lampResult string, lampDiseases []string) (bool, str
return false, "LAMP 判读无效，建议复检或专家会诊"
case aiClass == "":
return false, "未找到关联巡检记录，暂无法交叉验证"
+ case aiClass == "unknown":
+ return false, "AI 结果未知，建议复检或专家会诊"
case aiClass == "sick" && lampResult == "positive":
return true, "AI 检出异常与 LAMP 阳性一致，确认诊断"
case aiClass == "healthy" && lampResult == "negative":
@@ -20,15 +24,26 @@ func CrossValidate(aiClass, lampResult string, lampDiseases []string) (bool, str
}
}
-// AIClassFromDetections 从巡检检测结果归纳 AI 结论（任一非 healthy 视为 sick）
+// AIClassFromDetections 从巡检检测结果归纳 AI 结论；空检测或 unknown 不当作 healthy。
func AIClassFromDetections(detections []AIDetection) string {
if len(detections) == 0 {
- return ""
+ return "unknown"
}
+ healthySeen := false
+ unknownSeen := false
for _, d := range detections {
- if d.ClassName != "healthy" {
+ class := strings.ToLower(strings.TrimSpace(d.ClassName))
+ switch class {
+ case "healthy":
+ healthySeen = true
+ case "", "unknown":
+ unknownSeen = true
+ default:
return "sick"
}
}
- return "healthy"
+ if healthySeen && !unknownSeen {
+ return "healthy"
+ }
+ return "unknown"
}
diff --git a/server-go/internal/service/cross_validate_test.go b/server-go/internal/service/cross_validate_test.go
index adfaba1..0d62e53 100644
--- a/server-go/internal/service/cross_validate_test.go
+++ b/server-go/internal/service/cross_validate_test.go
@@ -13,6 +13,7 @@ func TestCrossValidate(t *testing.T) {
{"AI健康+LAMP阴性 一致", "healthy", "negative", true},
{"AI异常+LAMP阴性 不一致", "sick", "negative", false},
{"AI健康+LAMP阳性 不一致", "healthy", "positive", false},
+ {"AI未知+LAMP阳性 不一致", "unknown", "positive", false},
{"LAMP无效 不一致", "sick", "invalid", false},
{"无AI记录 不一致", "", "positive", false},
}
@@ -28,8 +29,8 @@ func TestCrossValidate(t *testing.T) {
}
func TestAIClassFromDetections(t *testing.T) {
- if got := AIClassFromDetections(nil); got != "" {
- t.Errorf("空检测应为空，实际 %s", got)
+ if got := AIClassFromDetections(nil); got != "unknown" {
+ t.Errorf("空检测应为 unknown，实际 %s", got)
}
if got := AIClassFromDetections([]AIDetection{{ClassName: "healthy", Confidence: 0.9}}); got != "healthy" {
t.Errorf("全健康应为 healthy，实际 %s", got)
@@ -37,4 +38,7 @@ func TestAIClassFromDetections(t *testing.T) {
if got := AIClassFromDetections([]AIDetection{{ClassName: "healthy"}, {ClassName: "sick", Confidence: 0.6}}); got != "sick" {
t.Errorf("含 sick 应为 sick，实际 %s", got)
}
+ if got := AIClassFromDetections([]AIDetection{{ClassName: "unknown", Confidence: 0.6}}); got != "unknown" {
+ t.Errorf("unknown 应为 unknown，实际 %s", got)
+ }
}
diff --git a/server-go/internal/service/risk.go b/server-go/internal/service/risk.go
index 5b054f9..1d322f6 100644
--- a/server-go/internal/service/risk.go
+++ b/server-go/internal/service/risk.go
@@ -1,21 +1,117 @@
package service
-import "math"
+import (
+ "math"
+ "strings"
+)
-// RiskInput 风险评分输入（各系数取值 0~1）
+// RiskRuleVersion 当前风险规则版本；权重仍沿用试点公式，待数据校准后升版。
+const RiskRuleVersion = "risk-v2-2026.08.14"
+
+// RiskInput 风险评分输入。nil 表示未采集，不能按 0 参与归一化。
type RiskInput struct {
- AI float64 // AI 识别置信度（权重 0.5）
- Env float64 // 环境风险系数（权重 0.2）
- Stage float64 // 饲养阶段风险系数（权重 0.15）
- Uniformity float64 // 群体整齐度偏离度（权重 0.15）
+ AI *float64 // AI 异常概率（权重 0.5）
+ Env *float64 // 环境风险系数（权重 0.2）
+ Stage *float64 // 饲养阶段风险系数（权重 0.15）
+ Uniformity *float64 // 群体整齐度偏离度（权重 0.15）
+ ModelVersion string
}
-// ComputeRiskScore 按规格书 3.1.4 公式计算 0~100 风险分：
-// 风险分 = 0.5×AI置信度 + 0.2×环境系数 + 0.15×阶段系数 + 0.15×整齐度偏离度
-func ComputeRiskScore(in RiskInput) float64 {
- score := 0.5*in.AI + 0.2*in.Env + 0.15*in.Stage + 0.15*in.Uniformity
- score = math.Max(0, math.Min(1, score))
- return score * 100
+// RiskAssessment 可解释风险输出。
+type RiskAssessment struct {
+ Score float64 `json:"score"`
+ Level string `json:"level"`
+ Confidence string `json:"confidence"`
+ ModelVersion string `json:"modelVersion"`
+ RuleVersion string `json:"ruleVersion"`
+ Components map[string]*float64 `json:"components"`
+ Missing []string `json:"missing"`
+}
+
+// ComputeRiskScore 按可用权重归一化计算 0~100 风险分，缺失组件返回 null。
+// 当前 0.5/0.2/0.15/0.15 是待试点校准规则，不是科学结论。
+func ComputeRiskScore(in RiskInput) RiskAssessment {
+ defs := []struct {
+ key string
+ weight float64
+ value *float64
+ }{
+ {"aiAbnormalProbability", 0.5, in.AI},
+ {"environment", 0.2, in.Env},
+ {"stage", 0.15, in.Stage},
+ {"uniformity", 0.15, in.Uniformity},
+ }
+ components := make(map[string]*float64, len(defs))
+ missing := make([]string, 0, len(defs))
+ weighted := 0.0
+ totalWeight := 0.0
+ for _, def := range defs {
+ if def.value == nil {
+ components[def.key] = nil
+ missing = append(missing, def.key)
+ continue
+ }
+ value := clamp01(*def.value)
+ components[def.key] = &value
+ weighted += def.weight * value
+ totalWeight += def.weight
+ }
+
+ score := 0.0
+ if totalWeight > 0 {
+ score = math.Round(clamp01(weighted/totalWeight)*10000) / 100
+ }
+ return RiskAssessment{
+ Score: score,
+ Level: RiskLevel(score),
+ Confidence: RiskConfidence(in),
+ ModelVersion: in.ModelVersion,
+ RuleVersion: RiskRuleVersion,
+ Components: components,
+ Missing: missing,
+ }
+}
+
+// RiskConfidence 当前仅给出 low/medium/unknown，避免把未校准规则描述为 high。
+func RiskConfidence(in RiskInput) string {
+ if in.AI == nil {
+ return "unknown"
+ }
+ if *in.AI >= 0.25 {
+ return "medium"
+ }
+ return "low"
+}
+
+// AbnormalProbability 从 AI 检测结果计算异常概率：healthy/unknown 不贡献风险。
+// abnormalClasses 可选；缺省时任一非 healthy/unknown 类别都视为异常类别。
+func AbnormalProbability(detections []AIDetection, abnormalClasses ...string) float64 {
+ configured := make(map[string]struct{}, len(abnormalClasses))
+ for _, class := range abnormalClasses {
+ if class = strings.ToLower(strings.TrimSpace(class)); class != "" {
+ configured[class] = struct{}{}
+ }
+ }
+ best := 0.0
+ for _, d := range detections {
+ class := strings.ToLower(strings.TrimSpace(d.ClassName))
+ if class == "" || class == "healthy" || class == "unknown" {
+ continue
+ }
+ if len(configured) > 0 {
+ if _, ok := configured[class]; !ok {
+ continue
+ }
+ }
+ if d.Confidence > best {
+ best = d.Confidence
+ }
+ }
+ return clamp01(best)
+}
+
+func clamp01(v float64) float64 {
+ return math.Max(0, math.Min(1, v))
}
// RiskLevel 按规格书 3.1.4 分级：绿 0-30 / 黄 31-60 / 橙 61-80 / 红 81-100
diff --git a/server-go/internal/service/risk_test.go b/server-go/internal/service/risk_test.go
index 0fa67bd..4124a6e 100644
--- a/server-go/internal/service/risk_test.go
+++ b/server-go/internal/service/risk_test.go
@@ -1,43 +1,120 @@
package service
-import "testing"
+import (
+ "math"
+ "testing"
+)
-func f(v float64) *float64 { return &v }
+func ptr(v float64) *float64 { return &v }
func TestComputeRiskScoreWeights(t *testing.T) {
- // 全 1：0.5*1 + 0.2*1 + 0.15*1 + 0.15*1 = 1 → 100
- if s := ComputeRiskScore(RiskInput{AI: 1, Env: 1, Stage: 1, Uniformity: 1}); s != 100 {
- t.Errorf("全 1 应得 100，实际 %.2f", s)
+ got := ComputeRiskScore(RiskInput{AI: ptr(1), Env: ptr(1), Stage: ptr(1), Uniformity: ptr(1)})
+ if got.Score != 100 {
+ t.Errorf("全 1 应得 100，实际 %.2f", got.Score)
}
- // 仅 AI 置信度 1：0.5*1 = 0.5 → 50
- if s := ComputeRiskScore(RiskInput{AI: 1}); s != 50 {
- t.Errorf("仅 AI=1 应得 50，实际 %.2f", s)
+ if len(got.Missing) != 0 {
+ t.Errorf("全组件可用时不应有 missing，实际 %v", got.Missing)
}
- // 0.5*0.8 + 0.2*0.5 = 0.5
- if s := ComputeRiskScore(RiskInput{AI: 0.8, Env: 0.5}); s != 50 {
- t.Errorf("0.8/0.5 应得 50，实际 %.2f", s)
+ if got.Components["aiAbnormalProbability"] == nil || got.Components["uniformity"] == nil {
+ t.Errorf("全组件可用时 components 不应为 null: %v", got.Components)
+ }
+}
+
+func TestComputeRiskScoreNormalizesMissingComponents(t *testing.T) {
+ got := ComputeRiskScore(RiskInput{AI: ptr(1)})
+ if got.Score != 100 {
+ t.Errorf("仅 AI=1 归一化后应得 100，实际 %.2f", got.Score)
+ }
+ if len(got.Missing) != 3 {
+ t.Errorf("missing 应为 environment/stage/uniformity，实际 %v", got.Missing)
+ }
+ if got.Components["environment"] != nil {
+ t.Error("缺失 environment 应序列化为 null")
+ }
+}
+
+func TestHealthyHighConfidenceDoesNotIncreaseRisk(t *testing.T) {
+ got := AbnormalProbability([]AIDetection{{ClassName: "healthy", Confidence: .95}})
+ if got != 0 {
+ t.Fatalf("healthy 高置信度不应产生异常概率，实际 %v", got)
+ }
+ assessment := ComputeRiskScore(RiskInput{AI: ptr(got)})
+ if assessment.Score != 0 {
+ t.Fatalf("healthy 高置信度风险分应为 0，实际 %.2f", assessment.Score)
+ }
+}
+
+func TestSickHighConfidenceIncreasesRisk(t *testing.T) {
+ got := AbnormalProbability([]AIDetection{{ClassName: "sick", Confidence: .9}})
+ if got != .9 {
+ t.Fatalf("sick 高置信度异常概率应为 0.9，实际 %v", got)
+ }
+ assessment := ComputeRiskScore(RiskInput{AI: ptr(got)})
+ if assessment.Score != 90 {
+ t.Fatalf("仅 AI=0.9 归一化后风险分应为 90，实际 %.2f", assessment.Score)
+ }
+}
+
+func TestAbnormalProbabilityIgnoresUnknown(t *testing.T) {
+ if got := AbnormalProbability([]AIDetection{{ClassName: "unknown", Confidence: .9}}); got != 0 {
+ t.Errorf("unknown 不应贡献异常概率，实际 %v", got)
+ }
+}
+
+func TestComputeRiskScoreMissingAll(t *testing.T) {
+ got := ComputeRiskScore(RiskInput{})
+ if got.Score != 0 {
+ t.Errorf("无任何组件时分数应为 0，实际 %.2f", got.Score)
+ }
+ if got.Confidence != "unknown" {
+ t.Errorf("无 AI 组件时 confidence 应为 unknown，实际 %s", got.Confidence)
+ }
+ if len(got.Missing) != 4 {
+ t.Errorf("missing 应为 4 项，实际 %v", got.Missing)
}
}
func TestComputeRiskScoreClamps(t *testing.T) {
- if s := ComputeRiskScore(RiskInput{AI: 2, Env: 2, Stage: 2, Uniformity: 2}); s > 100 {
- t.Errorf("应钳制到 100，实际 %.2f", s)
+ got := ComputeRiskScore(RiskInput{AI: ptr(2), Env: ptr(2), Stage: ptr(2), Uniformity: ptr(2)})
+ if got.Score > 100 {
+ t.Errorf("应钳制到 100，实际 %.2f", got.Score)
}
- if s := ComputeRiskScore(RiskInput{AI: -1}); s < 0 {
- t.Errorf("应钳制到 0，实际 %.2f", s)
+ if got := ComputeRiskScore(RiskInput{AI: ptr(-1)}).Score; got < 0 {
+ t.Errorf("应钳制到 0，实际 %.2f", got)
+ }
+}
+
+func TestRiskConfidenceLowMediumUnknown(t *testing.T) {
+ if got := RiskConfidence(RiskInput{}); got != "unknown" {
+ t.Errorf("无 AI 应为 unknown，实际 %s", got)
+ }
+ if got := RiskConfidence(RiskInput{AI: ptr(0.2)}); got != "low" {
+ t.Errorf("低异常概率应为 low，实际 %s", got)
+ }
+ if got := RiskConfidence(RiskInput{AI: ptr(0.9)}); got != "medium" {
+ t.Errorf("高异常概率当前最多应为 medium，实际 %s", got)
+ }
+}
+
+func TestComputeRiskScoreBoundaryUsesWeightNormalization(t *testing.T) {
+ // 0.5*0.8 + 0.2*0.5 的可用权重为 0.7：0.5/0.7 = 71.43
+ got := ComputeRiskScore(RiskInput{AI: ptr(0.8), Env: ptr(0.5)})
+ want := 50.0 / 0.7
+ if math.Abs(got.Score-want) > 0.01 {
+ t.Errorf("归一化应得 %.2f，实际 %.2f", want, got.Score)
}
}
func TestRiskLevelBoundaries(t *testing.T) {
cases := map[float64]string{
- 0: "green",
- 30: "green",
+ 0: "green",
+ 30: "green",
30.5: "yellow",
- 60: "yellow",
- 61: "orange",
- 80: "orange",
- 81: "red",
- 100: "red",
+ 60: "yellow",
+ 61: "orange",
+ 80: "orange",
+ 81: "red",
+ 100: "red",
}
for score, want := range cases {
if got := RiskLevel(score); got != want {
@@ -63,19 +140,19 @@ func TestStageCoefficientMapping(t *testing.T) {
func TestEnvCoefficientRules(t *testing.T) {
// 湿度 >=80 → 高（真菌病）
- if c := EnvCoefficient(f(25), f(85)); c < 0.7 {
+ if c := EnvCoefficient(ptr(25), ptr(85)); c < 0.7 {
t.Errorf("湿度 85 应 ≥0.7，实际 %.2f", c)
}
// 湿度 75-80 → 中
- if c := EnvCoefficient(f(25), f(78)); c < 0.3 {
+ if c := EnvCoefficient(ptr(25), ptr(78)); c < 0.3 {
t.Errorf("湿度 78 应 ≥0.3，实际 %.2f", c)
}
// 温度突变 >30 → 中（核型多角体病诱发）
- if c := EnvCoefficient(f(32), f(60)); c < 0.3 {
+ if c := EnvCoefficient(ptr(32), ptr(60)); c < 0.3 {
t.Errorf("温度 32 应 ≥0.3，实际 %.2f", c)
}
// 舒适环境 → 0
- if c := EnvCoefficient(f(25), f(60)); c != 0 {
+ if c := EnvCoefficient(ptr(25), ptr(60)); c != 0 {
t.Errorf("舒适环境应为 0，实际 %.2f", c)
}
// 缺数据 → 0
diff --git a/server-go/migrations/000002_risk_assessment.down.sql b/server-go/migrations/000002_risk_assessment.down.sql
new file mode 100644
index 0000000..508977e
--- /dev/null
+++ b/server-go/migrations/000002_risk_assessment.down.sql
@@ -0,0 +1,6 @@
+DROP INDEX IF EXISTS idx_inspection_records_mock_created_at;
+
+ALTER TABLE inspection_records
+ DROP COLUMN IF EXISTS is_mock,
+ DROP COLUMN IF EXISTS model_version,
+ DROP COLUMN IF EXISTS risk_assessment;
diff --git a/server-go/migrations/000002_risk_assessment.up.sql b/server-go/migrations/000002_risk_assessment.up.sql
new file mode 100644
index 0000000..bd17fdf
--- /dev/null
+++ b/server-go/migrations/000002_risk_assessment.up.sql
@@ -0,0 +1,7 @@
+ALTER TABLE inspection_records
+ ADD COLUMN IF NOT EXISTS risk_assessment jsonb,
+ ADD COLUMN IF NOT EXISTS model_version varchar(64),
+ ADD COLUMN IF NOT EXISTS is_mock boolean NOT NULL DEFAULT false;
+
+CREATE INDEX IF NOT EXISTS idx_inspection_records_mock_created_at
+ ON inspection_records (is_mock, created_at);
diff --git a/web/src/dal/inspections.ts b/web/src/dal/inspections.ts
index c2064fd..9cbb6af 100644
--- a/web/src/dal/inspections.ts
+++ b/web/src/dal/inspections.ts
@@ -15,6 +15,17 @@ export interface InspectionRecord {
detections?: AIDetection[];
riskScore?: number;
riskLevel?: string;
+ riskAssessment?: {
+ score: number;
+ level: string;
+ confidence: string;
+ modelVersion: string;
+ ruleVersion: string;
+ components: Record;
+ missing: string[];
+ };
+ modelVersion?: string;
+ isMock?: boolean;
aiStatus: string;
createdAt?: string;
}
diff --git a/web/src/pages/Inspections.tsx b/web/src/pages/Inspections.tsx
index 1cb5aaf..88aba8d 100644
--- a/web/src/pages/Inspections.tsx
+++ b/web/src/pages/Inspections.tsx
@@ -60,7 +60,17 @@ export default function InspectionsPage() {
width: 80,
render: (_, r) => (r.imageUrl ? : '-'),
},
- { title: '状态', dataIndex: 'aiStatus', search: false, render: (_, r) => (r.aiStatus === 'done' ? 成功 : 失败) },
+ {
+ title: '状态',
+ dataIndex: 'aiStatus',
+ search: false,
+ render: (_, r) => (
+ <>
+ {r.aiStatus === 'done' ? 成功 : 失败}
+ {r.isMock ? Mock : null}
+
+ ),
+ },
{
title: '操作',
valueType: 'option',
@@ -101,6 +111,8 @@ export default function InspectionsPage() {
状态：{detail.aiStatus === 'done' ? '检测成功' : '检测失败'}
+ 数据：{detail.isMock ? '联调 Mock，不计入生产统计' : detail.modelVersion || '未知模型'}
+
风险分：{detail.riskScore !== undefined ? Math.round(detail.riskScore) : '-'}（
{detail.riskLevel ? riskLevelLabel(detail.riskLevel) : '-'}）
diff --git a/后续工作计划.md b/后续工作计划.md
index 74d3dc1..e1299ef 100644
--- a/后续工作计划.md
+++ b/后续工作计划.md
@@ -1,6 +1,6 @@
# 后续工作计划
-> **完成状态（2026-08-13 更新）**：#5-#24、#27 已完成（详见 `开发交接记录.md`）；#1-4 因物理机问题挂起；#23/#26 骨架完成；微信/天气真实数据待凭证。
+> **完成状态（2026-08-14 更新）**：#5-#24、#27 已完成，Task 0/1/2/4/5/6 整改代码完成（详见 `开发交接记录.md`）；#1-4 因物理机问题挂起；#23/#26 骨架完成；微信/天气真实数据待凭证。
## 整改实施计划 Wave 0-4（2026-08-13 启动）
@@ -14,7 +14,7 @@
| Wave 1 | P0 安全与正确性 | Task 3 移除默认密钥与默认管理员密码 | 延后到最后（跳过） | 用户 2026-08-13 明确要求跳过并留到最后 |
| Wave 1 | P0 安全与正确性 | Task 4 收口视频访问与摄像头密钥输出 | 部分可用 | 待开发服务器部署联调 |
| Wave 1 | P0 安全与正确性 | Task 5 修复 WebSocket 越权与 AI 流 SSRF | 部分可用 | 待开发服务器部署与真实 WS/AI 联调 |
-| Wave 1 | P0 安全与正确性 | Task 6 修复 AI 风险语义并隔离 Mock 数据 | 未开始 | 无 |
+| Wave 1 | P0 安全与正确性 | Task 6 修复 AI 风险语义并隔离 Mock 数据 | 部分可用 | 待开发服务器迁移部署与真实模型接入；历史数据待人工审阅 |
| Wave 1 | P0 安全与正确性 | Task 7 修订 qPCR 判读与检测质控 | 未开始 | 需领域专家确认 |
| Wave 2 | 工程可靠性 | Task 8 建立可靠通知、吊销与跨实例状态 | 未开始 | 无 |
| Wave 2 | 工程可靠性 | Task 9 建立统一检测任务、样本链与发病事件 | 未开始 | 无 |
diff --git a/开发交接记录.md b/开发交接记录.md
index 6a4d61b..49b3570 100644
--- a/开发交接记录.md
+++ b/开发交接记录.md
@@ -921,3 +921,33 @@ MVP 沿用 IoTDB（现状）；TDengine 作为生产规模化候选（先基准
- 本任务前分支提交为 `1a29def`；回滚可还原 Task 5 提交；
- WS/AI 改动无数据库 schema 变更；若已部署，恢复旧二进制并重启即可，但需同步回滚客户端 WS 连接方式。
+
+## 2026-08-14 整改 Task 6：修复 AI 风险语义并隔离 Mock 数据
+
+### 做了什么
+
+- AI 服务 `/detect` 响应新增 `modelVersion`、`isMock`、`status`、`abnormalProbability`；`healthy` 高置信度不再贡献异常概率，空检测或 `unknown` 返回 `unknown`，不自动当健康；
+- Go 风险评分改为只消费 AI 异常概率：`RiskInput` 四个组件全部可空，缺失项不填 0；可用权重归一化后输出 `RiskAssessment`（score/level/confidence/modelVersion/ruleVersion/components/missing）；
+- 巡检记录新增 `risk_assessment`、`model_version`、`is_mock` 字段和 `000002_risk_assessment` 迁移；健康画像统计默认排除 mock，Mock 结果不触发微信告警；
+- `APP_ENV=production` 时收到 `isMock=true` 按失败记录并输出 error 日志，避免把联调数据当作生产检测结论；
+- Web/小程序巡检页显示 Mock 标识；交叉验证中空检测/`unknown` 不再被当作 healthy；
+- 新增只读历史评估 SQL `scripts/risk_historical_review.sql`，统计历史 healthy 高置信度记录与风险分布，未执行批量重算。
+
+### 设计思路与决策依据
+
+- 规格书 AI-INS-002 要求只用 `abnormalProbability` 计算 AI 风险，因此修复了原先取最大 confidence 导致 healthy=0.95 也能得 47.5 分的问题；
+- RISK-002 要求缺失数据不能以 0 冒充正常，所以环境/阶段/整齐度改为指针输入，缺失项进入 `missing` 并在 JSON 中返回 null；
+- 权重沿用 0.5/0.2/0.15/0.15 并标记为 `risk-v2-2026.08.14` 待试点校准规则；`confidence` 只输出 low/medium/unknown，不声称未校准结论为 high；
+- `000007_inspection_idempotency` 未另建迁移，因为 `000001_baseline` 已包含 `idempotency_key` 唯一索引；本次只补风险语义相关字段。
+- 历史旧记录没有 `is_mock` 标识，不能自动判别是否来自 mock；只读 SQL 报告用于人工审阅，未批量重算或改写旧数据。
+
+### 验证结果
+
+- `scripts/verify.ps1` exit 0：Go test/vet/build、Web test/lint/build、小程序 typecheck/build、APP typecheck/lint、AI pytest 15/15 均通过；
+- 新增测试覆盖 healthy/sick/unknown 异常概率、缺失组件归一化、风险分级边界、AI 响应解析、空检测 unknown、handler 风险输入和迁移版本；
+- 未部署开发服务器，未对现有库执行 `000002` 迁移；历史只读 SQL 报告未执行。
+
+### 回滚点
+
+- 本任务前分支提交为 `839ba91`；回滚可还原 Task 6 提交；
+- 数据库回滚执行 `migrate -path ... -database ... down 1` 或手工执行 `000002_risk_assessment.down.sql`，可移除新增三列和索引；`risk_score/risk_level` 仍保留，历史数据不回写。