chore: harden pick object logging

app/api/pick-object/route.ts

@@ -1,12 +1,15 @@
 import { NextResponse } from "next/server";
 import { auth } from "@/app/(auth)/auth";
-import { uploadFile } from "@/lib/storage/service";
 import { callQwen3Vl } from "@/lib/ai/qwen3-vl";
+import { createLogger } from "@/lib/observability/logger";
+import { uploadFile } from "@/lib/storage/service";
 import sharp from "sharp";
 
 export const runtime = "nodejs";
 export const maxDuration = 30;
 
+const logger = createLogger("pick-object");
+
 // 位置词库
 const POSITION_OPTIONS = [
   '左上区域', '中央顶部', '右上区域',
@@ -106,11 +109,12 @@ async function uploadVisionAnalysisImage(buffer: Buffer, filenamePrefix: string)
   const { buffer: processedBuffer, ext, width, height } = await downscaleImageForVision(buffer);
   const filename = `${filenamePrefix}-${Date.now()}.${ext}`;
   const uploaded = await uploadFile(filename, processedBuffer as any);
-  console.log("[PickObject] 视觉分析图片已缩放:", {
+  logger.info("vision image prepared", {
     originalWidth: width,
     originalHeight: height,
     maxSide: MAX_VISION_SIDE,
     outputExt: ext,
+    outputBytes: processedBuffer.length,
   });
   return uploaded.url;
 }
@@ -172,7 +176,11 @@ export async function POST(request: Request) {
     const body: PickObjectRequest = await request.json();
     const { imageData, clickX, clickY } = body;
     
-    console.log('[PickObject] 收到请求:', { imageDataLength: imageData?.length, clickX, clickY });
+    logger.info("request received", {
+      imageDataLength: imageData?.length,
+      clickX,
+      clickY,
+    });
     
     // 验证参数
     if (!imageData) {
@@ -198,7 +206,7 @@ export async function POST(request: Request) {
     
     const normalizedImage = await normalizeImageInput(imageData);
 
-    console.log("[PickObject] 使用硬编码模型: qwen3-vl");
+    logger.info("vision model selected", { model: "qwen3-vl" });
     
     // 构建 prompt - AI 通过红色标记来识别用户选择的物品
     const prompt = `
@@ -225,7 +233,7 @@ export async function POST(request: Request) {
 ${POSITION_OPTIONS.join('、')}
 `.trim();
 
-    console.log('[PickObject] 调用视觉模型...');
+    logger.info("vision model call started");
 
     // 调用视觉模型，发送带红色标记的图片
     const { text: responseText, model } = await callQwen3Vl({
@@ -235,7 +243,10 @@ ${POSITION_OPTIONS.join('、')}
       maxTokens: 300,
     });
     
-    console.log('[PickObject] 模型返回内容:', model, responseText?.substring(0, 200));
+    logger.info("vision model call completed", {
+      model,
+      responseLength: responseText?.length || 0,
+    });
     
     if (!responseText) {
       return NextResponse.json({
@@ -287,7 +298,10 @@ ${POSITION_OPTIONS.join('、')}
       };
       
     } catch (parseError) {
-      console.error('[PickObject] JSON parse error:', parseError, 'Content:', responseText);
+      logger.warn("model response parse failed", {
+        error: parseError,
+        responseLength: responseText.length,
+      });
       
       // 返回默认结果
       const posX = clickX < 0.33 ? '左' : clickX > 0.66 ? '右' : '中央';
@@ -304,7 +318,11 @@ ${POSITION_OPTIONS.join('、')}
       };
     }
     
-    console.log('[PickObject] 识别结果:', result);
+    logger.info("object picked", {
+      nameLength: result.name.length,
+      position: result.position,
+      confidence: result.confidence,
+    });
     
     return NextResponse.json({
       success: true,
@@ -317,7 +335,7 @@ ${POSITION_OPTIONS.join('、')}
     });
     
   } catch (error) {
-    console.error('[PickObject] Error:', error);
+    logger.error("pick object failed", error);
     return NextResponse.json({
       success: false,
       error: `识别失败: ${error instanceof Error ? error.message : '未知错误'}`,

scripts/check-log-hygiene.mjs

@@ -31,6 +31,7 @@ const files = [
   "app/api/canvas/text-detect/route.ts",
   "app/api/canvas/detail-plan/route.ts",
   "app/api/scene-fusion/route.ts",
+  "app/api/pick-object/route.ts",
 ];
 
 const consolePattern = /\bconsole\.(log|warn|error|info|debug)\b/g;