chore: expand canvas log hygiene coverage

app/api/canvas/auto-title/route.ts

@@ -1,25 +1,27 @@
 import { NextRequest, NextResponse } from "next/server";
 import { auth } from "@/app/(auth)/auth";
 import { callQwen3Vl } from "@/lib/ai/qwen3-vl";
+import { createLogger } from "@/lib/observability/logger";
+
+const logger = createLogger("canvas-auto-title");
 
 export async function POST(request: NextRequest) {
-  console.log("[Auto-title] API called");
+  logger.debug("request_received");
   
   try {
     const session = await auth();
     if (!session?.user?.id) {
-      console.log("[Auto-title] Unauthorized");
+      logger.warn("unauthorized");
       return NextResponse.json({ error: "Unauthorized" }, { status: 401 });
     }
 
     const { imageUrl } = await request.json();
-    console.log("[Auto-title] Image URL:", imageUrl);
 
     if (!imageUrl) {
       return NextResponse.json({ error: "Image URL is required" }, { status: 400 });
     }
 
-    console.log("[Auto-title] 使用硬编码模型: qwen3-vl");
+    logger.debug("model_selected", { model: "qwen3-vl" });
 
     // 构造 Prompt
     const prompt = "请用2-4个字概括这张图片的主体内容，作为文件标题。直接返回标题，不要包含任何标点符号或其他文字。";
@@ -35,11 +37,11 @@ export async function POST(request: NextRequest) {
     title = title.replace(/[\s\p{P}\p{S}]+/gu, "");
     if (title.length > 4) title = title.slice(0, 4);
     if (title.length < 2) title = "新画布";
-    console.log("[Auto-title] Generated title:", title, "model:", model);
+    logger.info("title_generated", { model, titleLength: title.length });
     return NextResponse.json({ title });
 
   } catch (error) {
-    console.error("[Auto-title] Error:", error);
+    logger.error("auto_title_failed", error);
     // 失败时返回默认标题，不报错中断流程
     return NextResponse.json({ title: "新画布" });
   }

app/api/canvas/detail-plan/route.ts

@@ -17,6 +17,7 @@ import {
   type DetailKimiGenerateOptions,
 } from "@/lib/ai/detail-agent-kimi-profile";
 import { inlineVisionImages } from "@/lib/ai/vision-inline";
+import { createLogger } from "@/lib/observability/logger";
 import { filterReachableRemoteUrls } from "@/lib/net/url-access";
 import {
   buildDetailUiProtocol,
@@ -47,6 +48,7 @@ const DETAIL_PLAN_INLINE_TIMEOUT_MS = 4000;
 const DETAIL_PLAN_INLINE_RETRIES = 1;
 const DETAIL_PLAN_MAIN_TIMEOUT_MS = 45000;
 const DETAIL_PLAN_PREFLIGHT_TIMEOUT_MS = 10000;
+const logger = createLogger("canvas-detail-plan");
 
 function isAbortError(error: unknown): boolean {
   const target = error as {
@@ -1774,7 +1776,7 @@ async function runDualDirectorPlanPreflight(params: {
       candidateScreens,
     };
   } catch (error) {
-    console.error("[Canvas Detail Plan] preflight error:", error);
+    logger.warn("preflight_failed", error);
     return defaultResult;
   }
 }
@@ -1808,19 +1810,17 @@ export async function POST(request: Request) {
     const bundleImageUrls = bundleImageCheck.kept.slice(0, 3);
     const modelImageUrl = modelImageCheck.kept[0] || "";
     if (referenceImageCheck.dropped.length > 0) {
-      console.warn("[Canvas Detail Plan] Dropping unreachable referenceImages:", {
+      logger.warn("reference_images_dropped", {
         count: referenceImageCheck.dropped.length,
-        urls: referenceImageCheck.dropped.slice(0, 6),
       });
     }
     if (bundleImageCheck.dropped.length > 0) {
-      console.warn("[Canvas Detail Plan] Dropping unreachable bundleImageUrls:", {
+      logger.warn("bundle_images_dropped", {
         count: bundleImageCheck.dropped.length,
-        urls: bundleImageCheck.dropped.slice(0, 3),
       });
     }
     if (modelImageUrlRaw && !modelImageUrl) {
-      console.warn("[Canvas Detail Plan] modelImageUrl unreachable, ignore this run:", modelImageUrlRaw);
+      logger.warn("model_image_dropped");
     }
     const effectiveReferenceImageNotes =
       referenceImages.length === referenceImagesRaw.length ? referenceImageNotes : [];
@@ -1935,7 +1935,7 @@ export async function POST(request: Request) {
       isLocalMoonshot: Boolean(localDetailAgentResolved),
     });
 
-    console.log("[Canvas Detail Plan] Planner model selected:", {
+    logger.info("planner_model_selected", {
       id: selectedModelRef.id,
       displayName: selectedModelRef.displayName,
       modelId: selectedModelRef.modelId,
@@ -2030,10 +2030,9 @@ export async function POST(request: Request) {
         }
       } catch (error) {
         if (isReferenceImageDownloadError(error) || isTransientNetworkError(error)) {
-          console.warn(
+          logger.warn("vision_input_preprocessing_failed", error, {
-            "[Canvas Detail Plan] Vision input preprocessing failed, retry without reference images:",
+            referenceImageCount: referenceImages.length,
-            error
+          });
-          );
           imageInputs = [];
         } else {
           throw error;
@@ -2125,10 +2124,9 @@ export async function POST(request: Request) {
         if (!shouldRetryWithoutImages) {
           throw firstError;
         }
-        console.warn(
+        logger.warn("planner_retry_without_reference_images", firstError, {
-          "[Canvas Detail Plan] Primary planning with reference images failed, retrying without reference images:",
+          imageInputCount: imageInputs.length,
-          firstError
+        });
-        );
         const retryResult = await runPlanner([]);
         text = String(retryResult?.text || "");
       }
@@ -2141,7 +2139,7 @@ export async function POST(request: Request) {
         isTransientNetworkError(error) ||
         /operationtimeouterror|timed out|timeout/i.test(message)
       ) {
-        console.error("[Canvas Detail Plan] Primary planning aborted, fallback applied:", error);
+        logger.error("primary_planning_fallback_applied", error);
         const fallbackReason = /invalid scheme/i.test(message)
           ? "规划模型图片输入协议不兼容，已回退到稳定分镜模板。"
           : isReferenceImageDownloadError(error)
@@ -2384,7 +2382,7 @@ export async function POST(request: Request) {
 
     return NextResponse.json({ success: true, data: response });
   } catch (error) {
-    console.error("[Canvas Detail Plan] Error:", error);
+    logger.error("detail_plan_failed", error);
     return NextResponse.json(
       { success: false, error: error instanceof Error ? error.message : "详情规划失败" },
       { status: 500 },

app/api/canvas/text-detect/route.ts

@@ -2,6 +2,7 @@ import { NextResponse } from "next/server";
 import { z } from "zod";
 import { auth } from "@/app/(auth)/auth";
 import { callQwen3Vl } from "@/lib/ai/qwen3-vl";
+import { createLogger } from "@/lib/observability/logger";
 import sharp from "sharp";
 
 export const runtime = "nodejs";
@@ -13,6 +14,7 @@ const requestSchema = z.object({
 
 const OCR_IMAGE_FETCH_TIMEOUT_MS = 15000;
 const OCR_IMAGE_MAX_SIDE = 1400;
+const logger = createLogger("canvas-text-detect");
 
 interface OcrItem {
   id: string;
@@ -145,7 +147,7 @@ export async function POST(request: Request) {
       return NextResponse.json({ success: false, error: "仅支持 URL 图片，不允许 base64 传输" }, { status: 400 });
     }
 
-    console.log("[Canvas Text Detect] 使用硬编码模型: qwen3-vl");
+    logger.debug("model_selected", { model: "qwen3-vl" });
     const prompt = [
       "你是图片文字识别助手。",
       "请识别图片中可见文字并按阅读顺序输出 JSON。",
@@ -172,7 +174,9 @@ export async function POST(request: Request) {
         throw error;
       }
 
-      console.warn("[Canvas Text Detect] URL 拉图超时，切换 data URL 兜底");
+      logger.warn("vision_url_fallback", {
+        reason: error instanceof Error ? error.message : "unknown",
+      });
       const dataUrl = await buildVisionDataUrl(imageUrl);
       const fallbackResult = await callQwen3Vl({
         imageUrl: dataUrl,
@@ -205,7 +209,7 @@ export async function POST(request: Request) {
       },
     });
   } catch (error) {
-    console.error("[Canvas Text Detect] Error:", error);
+    logger.error("text_detect_failed", error);
     return NextResponse.json(
       {
         success: false,

app/api/scene-fusion/route.ts

@@ -32,6 +32,7 @@ import {
   type SceneFusionImageGenConfig,
 } from "@/lib/scene-fusion/output-capabilities";
 import { acquireCanvasImageModelSlot } from "@/lib/canvas/image-concurrency";
+import { createLogger } from "@/lib/observability/logger";
 
 // 请求体 Schema
 const sceneFusionRequestSchema = z.object({
@@ -70,6 +71,7 @@ const SCENE_FUSION_RANDOM_BG_PROMPT_TAIL =
   "硬性要求：背景必须与原图明显不同（颜色、结构、元素至少两项显著变化），禁止保留原背景纹理或直接回传原图；仅保留产品主体并保证主体结构、轮廓比例、部件关系和边缘完整自然，允许为新背景调整朝向、角度和透视。";
 let sceneFusionRoundRobinCursor = 0;
 type SceneFusionModelCooldown = Map<string, number>;
+const logger = createLogger("scene-fusion");
 
 interface SceneFusionModelCandidate {
   model: {
@@ -304,8 +306,7 @@ async function getAverageHashBits(
     hashCache.set(imageUrl, hashBits);
     return hashBits;
   } catch (error) {
-    console.warn("[SceneFusion] Echo hash compute skipped:", {
+    logger.warn("echo_hash_compute_skipped", {
-      imageUrl: imageUrl.slice(0, 120),
       error: error instanceof Error ? error.message : "unknown",
     });
     return null;
@@ -357,9 +358,12 @@ async function detectEchoedProductResult(
 
   const distance = hammingDistanceBits(productHash, generatedHash);
   if (distance <= SCENE_FUSION_ECHO_HASH_THRESHOLD) {
-    console.warn(
+    logger.warn("echo_guard_hit", {
-      `[SceneFusion][${params.requestId}] Echo-guard hit: scene#${params.sceneIndex + 1}, model=${params.modelName}, distance=${distance}`
+      requestId: params.requestId,
-    );
+      sceneIndex: params.sceneIndex + 1,
+      modelName: params.modelName,
+      distance,
+    });
     return {
       tooSimilar: true,
       reason: "hash_too_close",
@@ -603,7 +607,8 @@ async function reviewSceneFusionResult(params: {
       suspectedEcho !== true &&
       score >= 0.5;
 
-    console.log(`[SceneFusion][${params.requestId}] Review result:`, {
+    logger.info("review_result", {
+      requestId: params.requestId,
       sceneIndex: params.sceneIndex + 1,
       candidate: params.modelName,
       passed,
@@ -621,7 +626,8 @@ async function reviewSceneFusionResult(params: {
       model,
     };
   } catch (error) {
-    console.warn(`[SceneFusion][${params.requestId}] Review skipped:`, {
+    logger.warn("review_skipped", {
+      requestId: params.requestId,
       sceneIndex: params.sceneIndex + 1,
       candidate: params.modelName,
       error: error instanceof Error ? error.message : "unknown",
@@ -745,10 +751,10 @@ async function enrichRandomBackgroundScenesWithAgent(params: {
           scene.customPrompt = mergeCustomPrompt(scene.customPrompt, `场景建议：${generatedPrompt}`);
         }
       } catch (error) {
-        console.warn(
+        logger.warn("random_prompt_enhance_skipped", error, {
-          `[SceneFusion][${params.requestId}] Random scene prompt enhance skipped: scene=${scene.id}`,
+          requestId: params.requestId,
-          error
+          sceneId: scene.id,
-        );
+        });
       }
     }
   });
@@ -809,7 +815,7 @@ async function enrichSceneLabelsWithAgent(params: {
       meta.productModel = productDetected.model;
     }
   } catch (error) {
-    console.warn(`[SceneFusion][${params.requestId}] Product detect skipped:`, error);
+    logger.warn("product_detect_skipped", error, { requestId: params.requestId });
   }
 
   const unresolvedIndexes = clonedScenes
@@ -858,10 +864,10 @@ async function enrichSceneLabelsWithAgent(params: {
           metaScene.model = targetDetected.model;
         }
       } catch (error) {
-        console.warn(
+        logger.warn("scene_target_detect_skipped", error, {
-          `[SceneFusion][${params.requestId}] Scene target detect skipped: scene=${scene.id}`,
+          requestId: params.requestId,
-          error
+          sceneId: scene.id,
-        );
+        });
       }
     }
   });
@@ -957,7 +963,7 @@ async function getSceneFusionConfig() {
       };
     }
   } catch (error) {
-    console.error("[SceneFusion] Failed to load config:", error);
+    logger.error("config_load_failed", error);
   }
   
   return {
@@ -1000,9 +1006,10 @@ async function preprocessProductImageWithRmbg(
   const candidateUrls = buildPreRmbgCandidateUrls(request);
   let lastReason = "no_candidate_url";
 
-  console.log(
+  logger.info("pre_rmbg_started", {
-    `[SceneFusion][${requestId}] Pre-RMBG start: ${productImageUrl.substring(0, 120)}..., candidates=${candidateUrls.join(" | ")}`
+    requestId,
-  );
+    candidateCount: candidateUrls.length,
+  });
 
   for (const rmbgUrl of candidateUrls) {
     const controller = new AbortController();
@@ -1026,7 +1033,8 @@ async function preprocessProductImageWithRmbg(
 
       if (!response.ok) {
         lastReason = `request_failed_${response.status}`;
-        console.warn(`[SceneFusion][${requestId}] Pre-RMBG candidate failed: ${rmbgUrl}`, {
+        logger.warn("pre_rmbg_candidate_failed", {
+          requestId,
           status: response.status,
           detail: payload?.detail || payload?.error || "unknown",
         });
@@ -1036,7 +1044,8 @@ async function preprocessProductImageWithRmbg(
       const cleanedUrl = String(payload?.original_url || payload?.thumbnail_url || "").trim();
       if (!cleanedUrl || cleanedUrl === productImageUrl) {
         lastReason = cleanedUrl ? "same_as_source" : "empty_result";
-        console.warn(`[SceneFusion][${requestId}] Pre-RMBG candidate invalid result: ${rmbgUrl}`, {
+        logger.warn("pre_rmbg_candidate_invalid", {
+          requestId,
           reason: lastReason,
         });
         continue;
@@ -1049,7 +1058,7 @@ async function preprocessProductImageWithRmbg(
       };
     } catch (error) {
       lastReason = error instanceof Error ? error.message : "exception";
-      console.warn(`[SceneFusion][${requestId}] Pre-RMBG candidate exception: ${rmbgUrl}`, error);
+      logger.warn("pre_rmbg_candidate_exception", error, { requestId });
     } finally {
       clearTimeout(timeoutId);
     }
@@ -1073,7 +1082,7 @@ async function createThumbnail(buffer: Buffer): Promise<Buffer> {
       .toBuffer();
     return thumbnailBuffer;
   } catch (error) {
-    console.error("[SceneFusion] Failed to create thumbnail:", error);
+    logger.error("thumbnail_create_failed", error);
     return buffer;
   }
 }
@@ -1098,10 +1107,10 @@ async function uploadBase64ToS3(base64Data: string, prefix: string = "scene-fusi
     
     const filename = generateFilename(`${prefix}-ref`, "png");
     const result = await uploadFile(filename, buffer.buffer.slice(buffer.byteOffset, buffer.byteOffset + buffer.byteLength));
-    console.log(`[SceneFusion] Uploaded reference image to: ${result.url}`);
+    logger.info("reference_image_uploaded", { prefix, bytes: buffer.byteLength });
     return result.url;
   } catch (error) {
-    console.error("[SceneFusion] Failed to upload reference image:", error);
+    logger.error("reference_image_upload_failed", error, { prefix });
     throw error;
   }
 }
@@ -1114,15 +1123,15 @@ async function downloadAndUploadToS3(
   prefix: string = "scene-fusion"
 ): Promise<{ thumbnail: string; original: string }> {
   try {
-    console.log("[SceneFusion] Downloading image from:", imageUrl.substring(0, 100) + "...");
+    logger.debug("download_upload_started", { prefix });
-    
+
     const response = await fetch(imageUrl);
     if (!response.ok) {
       throw new Error(`Failed to download image: ${response.status}`);
     }
     
     const buffer = Buffer.from(await response.arrayBuffer());
-    console.log(`[SceneFusion] Downloaded image, size: ${buffer.length} bytes`);
+    logger.debug("image_downloaded", { prefix, bytes: buffer.length });
     
     // 创建缩略图
     const thumbnailBuffer = await createThumbnail(buffer);
@@ -1130,20 +1139,20 @@ async function downloadAndUploadToS3(
     // 上传原图
     const originalFilename = generateFilename(`${prefix}-orig`, "png");
     const originalResult = await uploadFile(originalFilename, buffer.buffer.slice(buffer.byteOffset, buffer.byteOffset + buffer.byteLength));
-    console.log(`[SceneFusion] Uploaded original to: ${originalResult.url}`);
+    logger.debug("original_uploaded", { prefix, bytes: buffer.byteLength });
     
     // 上传缩略图
     const thumbnailFilename = generateFilename(`${prefix}-thumb`, "jpg");
     const thumbnailArrayBuffer = new Uint8Array(thumbnailBuffer).buffer;
     const thumbnailResult = await uploadFile(thumbnailFilename, thumbnailArrayBuffer);
-    console.log(`[SceneFusion] Uploaded thumbnail to: ${thumbnailResult.url}`);
+    logger.debug("thumbnail_uploaded", { prefix, bytes: thumbnailBuffer.byteLength });
     
     return {
       original: originalResult.url,
       thumbnail: thumbnailResult.url,
     };
   } catch (error) {
-    console.error("[SceneFusion] Failed to download/upload image:", error);
+    logger.error("download_upload_failed", error, { prefix });
     throw error;
   }
 }
@@ -1229,7 +1238,7 @@ async function saveSceneFusionImageRecord(params: {
       }
     }
   } catch (assetError) {
-    console.error("[SceneFusion] ⚠️ MediaAsset 注册失败:", assetError);
+    logger.error("media_asset_register_failed", assetError);
   }
 }
 
@@ -1318,13 +1327,13 @@ async function callAlibabaImageAPI(
     },
   };
   
-  console.log(`[SceneFusion][${modelId}] Request Debug:
+  logger.debug("alibaba_request_prepared", {
-    - Index: Scene ${sceneImageUrl.substring(sceneImageUrl.length-15)}
+    modelId,
-    - Product URL: ${productImageUrl}
+    size: size || "auto",
-    - Scene URL: ${sceneImageUrl}
+    productImageCount: productImageUrl ? 1 : 0,
-    - Size: ${size || 'auto'}
+    sceneImageCount: sceneImageUrl ? 1 : 0,
-    - Prompt: ${prompt}
+    promptLength: prompt.length,
-  `);
+  });
   
   const response = await fetch(baseURL, {
     method: "POST",
@@ -1337,23 +1346,35 @@ async function callAlibabaImageAPI(
   
   const data = await response.json();
   
-  // 打印完整响应用于调试
+  logger.debug("alibaba_response_received", {
-  console.log(`[SceneFusion][${modelId}] Full API Response:`, JSON.stringify(data, null, 2));
+    modelId,
+    ok: response.ok,
+    code: data?.code ?? null,
+    hasOutput: Boolean(data?.output),
+  });
   
   if (!response.ok || data.code) {
-    console.error("[SceneFusion] API Error Response:", JSON.stringify(data, null, 2));
+    logger.error("alibaba_response_error", {
+      modelId,
+      status: response.status,
+      code: data?.code ?? null,
+      message: data?.message ?? null,
+    });
     throw new Error(data.message || (data.code ? `Error ${data.code}: ${data.message}` : `API request failed: ${response.status}`));
   }
   
   // 提取生成的图片 URL
   const choices = data.output?.choices;
   if (!choices || choices.length === 0) {
-    console.error("[SceneFusion] No choices in response, output:", data.output);
+    logger.error("alibaba_no_choices", { modelId, hasOutput: Boolean(data?.output) });
     throw new Error("No images in response");
   }
   
   const imageContent = choices[0]?.message?.content;
-  console.log(`[SceneFusion] Image content array:`, JSON.stringify(imageContent, null, 2));
+  logger.debug("alibaba_image_content_received", {
+    modelId,
+    contentCount: Array.isArray(imageContent) ? imageContent.length : 0,
+  });
   
   if (!imageContent || imageContent.length === 0) {
     throw new Error("No image content in response");
@@ -1364,25 +1385,25 @@ async function callAlibabaImageAPI(
   for (const item of imageContent) {
     if (item.image) {
       generatedImageUrl = item.image;
-      console.log(`[SceneFusion] Found image URL in content item`);
+      logger.debug("alibaba_image_url_found", { modelId });
       break;
     }
   }
   
   if (!generatedImageUrl) {
-    console.error("[SceneFusion] No image URL found in content:", imageContent);
+    logger.error("alibaba_image_url_missing", {
+      modelId,
+      contentCount: Array.isArray(imageContent) ? imageContent.length : 0,
+    });
     throw new Error("No image URL in response");
   }
   
   // 检查返回的图片 URL 是否与输入相同（可能是 API 返回了原图）
   if (generatedImageUrl === productImageUrl || generatedImageUrl === sceneImageUrl) {
-    console.warn(`[SceneFusion] ⚠️ WARNING: API returned same URL as input!`);
+    logger.warn("alibaba_returned_input_url", { modelId });
-    console.warn(`[SceneFusion] - Generated URL: ${generatedImageUrl}`);
-    console.warn(`[SceneFusion] - Product URL: ${productImageUrl}`);
-    console.warn(`[SceneFusion] - Scene URL: ${sceneImageUrl}`);
   }
   
-  console.log("[SceneFusion] Generated image URL:", generatedImageUrl.substring(0, 100) + "...");
+  logger.debug("alibaba_image_generated", { modelId });
   return generatedImageUrl;
 }
 
@@ -1468,8 +1489,11 @@ async function processSceneWithProvider(
     sceneMode
   );
   
-  console.log(`[SceneFusion] Built prompt: ${prompt}`);
+  logger.debug("provider_prompt_built", {
-  console.log(`[SceneFusion] Provider type: ${provider.type}`);
+    providerType: provider.type,
+    promptLength: prompt.length,
+    sceneMode,
+  });
   
   // 根据 provider 类型选择不同的处理逻辑
   switch (provider.type) {
@@ -1541,7 +1565,7 @@ async function processWithGemini(
   aspectRatio?: string,
   imageSize?: string
 ): Promise<{ thumbnail: string; original: string; prompt: string }> {
-  console.log(`[SceneFusion][Gemini] Processing with model: ${modelId}`);
+  logger.info("provider_processing", { providerType: "gemini", modelId });
   
   // 创建 Gemini provider
   const geminiProvider = createGeminiImage({
@@ -1589,7 +1613,7 @@ async function processWithRuxaImage(
   aspectRatio?: string,
   imageSize?: string
 ): Promise<{ thumbnail: string; original: string; prompt: string }> {
-  console.log(`[SceneFusion][RUXA] Processing with model: ${modelId}`);
+  logger.info("provider_processing", { providerType: "ruxa-image", modelId });
 
   const ruxaProvider = createRuxaImage({
     baseURL: provider.baseUrl,
@@ -1629,7 +1653,7 @@ async function processWithFalImage(
   aspectRatio?: string,
   imageSize?: string
 ): Promise<{ thumbnail: string; original: string; prompt: string }> {
-  console.log(`[SceneFusion][FAL] Processing with model: ${modelId}`);
+  logger.info("provider_processing", { providerType: "fal-image", modelId });
 
   const falProvider = createFalImage({
     baseURL: provider.baseUrl,
@@ -1669,7 +1693,7 @@ async function processWithOpenAIImage(
   aspectRatio?: string,
   imageSize?: string
 ): Promise<{ thumbnail: string; original: string; prompt: string }> {
-  console.log(`[SceneFusion][OpenAI Image] Processing with model: ${modelId}`);
+  logger.info("provider_processing", { providerType: "openai-image", modelId });
 
   const openAIImageProvider = createOpenAIImage({
     baseURL: provider.baseUrl,
@@ -1712,7 +1736,7 @@ async function processWithVolcanoVision(
   aspectRatio?: string,
   imageSize?: string
 ): Promise<{ thumbnail: string; original: string; prompt: string }> {
-  console.log(`[SceneFusion][Volcano] Processing with model: ${modelId}`);
+  logger.info("provider_processing", { providerType: "volcano-vision", modelId });
   
   // 创建 Volcano Vision provider
   const volcanoProvider = createVolcanoVision({
@@ -1753,7 +1777,7 @@ async function processWithVolcanoVision(
  * 格式: ![thumb|||originalUrl|||size](thumbnailUrl)
  */
 function parseImageFromMarkdown(markdown: string): { thumbnail: string; original: string } {
-  console.log(`[SceneFusion] Parsing markdown: ${markdown.substring(0, 200)}...`);
+  logger.debug("markdown_parse_started", { markdownLength: markdown.length });
   
   // 匹配 ![thumb|||originalUrl|||size](thumbnailUrl) 格式
   const match = markdown.match(/!\[thumb\|\|\|([^|]+)\|\|\|[^\]]*\]\(([^)]+)\)/);
@@ -1805,7 +1829,7 @@ async function processScene(
     sceneMode
   );
   
-  console.log(`[SceneFusion] Built prompt: ${prompt}`);
+  logger.debug("legacy_prompt_built", { promptLength: prompt.length, sceneMode });
   
   // 调用阿里生图 API
   const generatedImageUrl = await callAlibabaImageAPI(
@@ -1890,14 +1914,15 @@ async function processSceneWithDiversity(
   const attemptCandidates =
     orderedHealthyCandidates.length > 0 ? orderedHealthyCandidates : orderedFallbackCandidates;
 
-  console.log(
+  logger.debug("candidate_order_resolved", {
-    `[SceneFusion][${params.requestId}] Scene#${params.sceneIndex + 1} candidate order: ${attemptCandidates
+    requestId: params.requestId,
-      .map(
+    sceneIndex: params.sceneIndex + 1,
-        (candidate) =>
+    candidates: attemptCandidates.map((candidate) => ({
-          `${candidate.model.displayName}/${candidate.provider.type}/score=${getSceneFusionCandidatePriority(candidate)}`
+      modelId: candidate.model.modelId,
-      )
+      providerType: candidate.provider.type,
-      .join(" -> ")}`
+      score: getSceneFusionCandidatePriority(candidate),
-  );
+    })),
+  });
 
   const failureReasons: string[] = [];
 
@@ -1909,9 +1934,12 @@ async function processSceneWithDiversity(
         imageSize: params.imageSize,
       });
       if (normalizedOutputParams.changed) {
-        console.log(
+        logger.info("candidate_output_params_normalized", {
-          `[SceneFusion][${params.requestId}] Candidate ${candidate.model.displayName} output params normalized: ${normalizedOutputParams.changes.join(", ")}`
+          requestId: params.requestId,
-        );
+          sceneIndex: params.sceneIndex + 1,
+          modelId: candidate.model.modelId,
+          changes: normalizedOutputParams.changes,
+        });
       }
 
       const modelSlot = await acquireCanvasImageModelSlot({
@@ -2000,17 +2028,19 @@ async function processSceneWithDiversity(
       markSceneFusionCandidateFailed(candidate, params.modelCooldown);
       // Batch processing can fail because of per-image inputs, review gates, or echo checks.
       // Keep these failures local to this request so they do not auto-disable shared models.
-      const logCandidateFailure = isSceneFusionReviewRejectError(errorMessage)
+      const failureMeta = {
-        ? console.warn
-        : console.error;
-      logCandidateFailure("[SceneFusion] Candidate failed, try next:", {
         requestId: params.requestId,
         sceneIndex: params.sceneIndex,
         attempt: attemptIndex + 1,
         model: candidate.model.modelId,
         provider: candidate.provider.type,
         error: errorMessage,
-      });
+      };
+      if (isSceneFusionReviewRejectError(errorMessage)) {
+        logger.warn("candidate_review_rejected", failureMeta);
+      } else {
+        logger.error("candidate_failed", failureMeta);
+      }
     }
   }
 
@@ -2060,7 +2090,16 @@ export async function POST(request: Request) {
     
     // 计算输出尺寸
     const size = calculateSize(aspectRatio || "auto", imageSize || "2K");
-    console.log(`[SceneFusion] Output settings: aspectRatio=${aspectRatio || 'auto'}, imageSize=${imageSize || '2K'}, calculated size=${size || 'auto'}`);
+    logger.info("request_received", {
+      requestId,
+      aspectRatio: aspectRatio || "auto",
+      imageSize: imageSize || "2K",
+      size: size || "auto",
+      sceneCount: scenes.length,
+      sceneMode: resolvedSceneMode,
+      hasProductName: Boolean(productName),
+      preferredModelId: config.modelId || null,
+    });
     
     // 检查场景数量限制
     const effectiveMaxScenes = Math.min(config.maxScenes, SCENE_FUSION_MAX_ITEMS);
@@ -2071,19 +2110,11 @@ export async function POST(request: Request) {
       );
     }
     
-    console.log(`[SceneFusion] Processing ${scenes.length} scenes for user ${session.user.id}`);
-    console.log(`[SceneFusion] Product name: ${productName || '(not specified)'}`);
-    console.log(`[SceneFusion] Scene mode: ${resolvedSceneMode}`);
-    console.log(`[SceneFusion] Using default prompt: ${config.defaultPrompt.substring(0, 50)}...`);
-    console.log(`[SceneFusion] Preferred model ID: ${config.modelId || '(none)'}`);
-    
     // 4. 获取生图模型池（固定多样性模式）
     const allModels = await getEnabledAiModelsWithProvider();
     const candidateModels = buildSceneFusionCandidatePool(allModels, config.modelId);
     if (config.modelId && !candidateModels.some((candidate) => candidate.model.id === config.modelId)) {
-      console.warn(
+      logger.warn("preferred_model_unavailable", { requestId, modelId: config.modelId });
-        `[SceneFusion] Preferred model ${config.modelId} not available, fallback to full diversity pool`
-      );
     }
 
     if (candidateModels.length === 0) {
@@ -2093,37 +2124,39 @@ export async function POST(request: Request) {
       );
     }
 
-    console.log(
+    logger.info("candidate_pool_resolved", {
-      `[SceneFusion] Diversity candidates: ${candidateModels
+      requestId,
-        .map((candidate) => `${candidate.model.displayName}(${candidate.provider.type})`)
+      candidateCount: candidateModels.length,
-        .join(", ")}`
+      providers: [...new Set(candidateModels.map((candidate) => candidate.provider.type))],
-    );
+    });
     const unsupportedCandidates = candidateModels.filter(
       (candidate) => !canProcessSceneFusionProviderType(candidate.provider.type)
     );
     if (unsupportedCandidates.length > 0) {
-      console.warn(
+      logger.warn("unsupported_candidates_present", {
-        `[SceneFusion] Skip unsupported providers for scene fusion: ${unsupportedCandidates
+        requestId,
-          .map((candidate) => `${candidate.model.displayName}(${candidate.provider.type})`)
+        count: unsupportedCandidates.length,
-          .join(", ")}`
+        providers: [...new Set(unsupportedCandidates.map((candidate) => candidate.provider.type))],
-      );
+      });
     }
     const nonVisionCandidates = candidateModels.filter(
       (candidate) => !candidate.model.supportsVision
     );
     if (nonVisionCandidates.length > 0) {
-      console.warn(
+      logger.warn("non_vision_candidates_present", {
-        `[SceneFusion] Models without supportsVision are included for failover diversity: ${nonVisionCandidates
+        requestId,
-          .map((candidate) => `${candidate.model.displayName}(${candidate.provider.type})`)
+        count: nonVisionCandidates.length,
-          .join(", ")}`
+      });
-      );
     }
     const requestOffset = getNextSceneFusionRoundRobinOffset(
       Math.max(1, candidateModels.length)
     );
-    console.log(
+    logger.debug("round_robin_offset_resolved", {
-      `[SceneFusion][${requestId}] Round-robin offset=${requestOffset}, scenes=${scenes.length}, candidates=${candidateModels.length}`
+      requestId,
-    );
+      requestOffset,
+      sceneCount: scenes.length,
+      candidateCount: candidateModels.length,
+    });
     
     // 5. 预处理：将 Base64 图片上传到 S3
     let productImageUrl = productImage;
@@ -2138,9 +2171,12 @@ export async function POST(request: Request) {
       shouldForcePreRmbg ? true : config.preRmbgEnabled
     );
     const fusionProductImageUrl = preprocessedProduct.productImageUrl;
-    console.log(
+    logger.info("pre_rmbg_resolved", {
-      `[SceneFusion][${requestId}] Pre-RMBG result: used=${preprocessedProduct.usedPreRmbg}, provider=${preprocessedProduct.provider || "-"}, reason=${preprocessedProduct.reason || "-"}`
+      requestId,
-    );
+      used: preprocessedProduct.usedPreRmbg,
+      provider: preprocessedProduct.provider || null,
+      reason: preprocessedProduct.reason || null,
+    });
     
     const processedScenes = await Promise.all(
       scenes.map(async (scene) => {
@@ -2175,17 +2211,18 @@ export async function POST(request: Request) {
     const imageHashCache = new Map<string, string>();
     const modelCooldown: SceneFusionModelCooldown = new Map();
 
-    console.log(
+    logger.info("agent_labels_resolved", {
-      `[SceneFusion][${requestId}] Agent labels: product=${resolvedProductName || "(none)"}; targets=${resolvedScenes
+      requestId,
-        .map((scene) => `${scene.id}:${scene.targetName || "-"}`)
+      hasProductName: Boolean(resolvedProductName),
-        .join(", ")}`
+      targetCount: resolvedScenes.filter((scene) => Boolean(scene.targetName)).length,
-    );
+      sceneCount: resolvedScenes.length,
+    });
     if (resolvedSceneMode === "random-bg") {
-      console.log(
+      logger.debug("random_bg_prompts_resolved", {
-        `[SceneFusion][${requestId}] Random-bg prompts: ${resolvedScenes
+        requestId,
-          .map((scene) => `${scene.id}:${(scene.customPrompt || "").slice(0, 80) || "-"}`)
+        sceneCount: resolvedScenes.length,
-          .join(" | ")}`
+        promptCount: resolvedScenes.filter((scene) => Boolean(scene.customPrompt)).length,
-      );
+      });
     }
 
     // 6. 创建流式响应，每完成一张图就立即发送给前端
@@ -2199,7 +2236,7 @@ export async function POST(request: Request) {
           try {
             controller.close();
           } catch (closeError) {
-            console.warn("[SceneFusion] Stream close skipped:", closeError);
+            logger.warn("stream_close_skipped", closeError, { requestId });
           }
         };
         const enqueue = (payload: Record<string, unknown>) => {
@@ -2209,7 +2246,7 @@ export async function POST(request: Request) {
             return true;
           } catch (enqueueError) {
             streamClosed = true;
-            console.warn("[SceneFusion] Stream enqueue skipped:", enqueueError);
+            logger.warn("stream_enqueue_skipped", enqueueError, { requestId });
             return false;
           }
         };
@@ -2258,27 +2295,16 @@ export async function POST(request: Request) {
               const resolvedMetaScene =
                 enriched.meta.sceneTargets.find((item) => item.id === resolvedScene.id) || null;
 
-              console.log(
+              logger.info("scene_processing_started", {
-                `[SceneFusion] ========== Processing scene ${currentIndex + 1}/${processedScenes.length} ==========`
+                requestId,
-              );
+                sceneId: scene.id,
-              console.log(`[SceneFusion] Scene ID: ${scene.id}`);
+                sceneIndex: currentIndex + 1,
-              console.log(
+                total: processedScenes.length,
-                `[SceneFusion] Product Image URL: ${fusionProductImageUrl.substring(0, 80)}...`
+                hasTargetName: Boolean(resolvedScene.targetName),
-              );
+                hasPositionHint: Boolean(resolvedMetaScene?.positionHint),
-              console.log(
+                hasReplaceCue: Boolean(resolvedMetaScene?.replaceCue),
-                `[SceneFusion] Scene Image URL: ${scene.imageUrl.substring(0, 80)}...`
+                hasCustomPrompt: Boolean(resolvedScene.customPrompt),
-              );
+              });
-              console.log(
-                `[SceneFusion] Target Name: ${resolvedScene.targetName || "(not specified)"}`
-              );
-              if (resolvedMetaScene?.positionHint || resolvedMetaScene?.replaceCue) {
-                console.log(
-                  `[SceneFusion] Target Hints: position=${resolvedMetaScene?.positionHint || "-"}, cue=${resolvedMetaScene?.replaceCue || "-"}`
-                );
-              }
-              console.log(
-                `[SceneFusion] Custom Prompt: ${resolvedScene.customPrompt || "(none)"}`
-              );
 
               try {
                 const { result, candidate, attempts } = await processSceneWithDiversity({
@@ -2333,9 +2359,13 @@ export async function POST(request: Request) {
                   modelId: candidate.model.modelId,
                   sourceImageUrls: [fusionProductImageUrl, resolvedScene.imageUrl],
                 });
-                console.log(
+                logger.info("scene_saved", {
-                  `[SceneFusion] ✅ Saved image to gallery: ${result.original.substring(0, 80)}...`
+                  requestId,
-                );
+                  sceneId: scene.id,
+                  modelId: candidate.model.modelId,
+                  providerType: candidate.provider.type,
+                  attempts,
+                });
 
                 successCount += 1;
                 if (!enqueue({
@@ -2356,7 +2386,11 @@ export async function POST(request: Request) {
                   break;
                 }
               } catch (error) {
-                console.error(`[SceneFusion] Failed to process scene ${scene.id}:`, error);
+                logger.error("scene_processing_failed", error, {
+                  requestId,
+                  sceneId: scene.id,
+                  sceneIndex: currentIndex + 1,
+                });
                 failCount += 1;
                 if (!enqueue({
                   type: "result",
@@ -2375,7 +2409,12 @@ export async function POST(request: Request) {
           await Promise.all(workers);
           
           // 发送完成消息
-          console.log(`[SceneFusion] Completed: ${successCount} success, ${failCount} failed`);
+          logger.info("request_completed", {
+            requestId,
+            total: processedScenes.length,
+            success: successCount,
+            failed: failCount,
+          });
           enqueue({
             type: "done",
             summary: {
@@ -2386,7 +2425,7 @@ export async function POST(request: Request) {
           });
           
         } catch (error) {
-          console.error("[SceneFusion] Stream error:", error);
+          logger.error("stream_failed", error, { requestId });
           // 发送错误消息
           if (!streamClosed) {
             enqueue({
@@ -2408,7 +2447,7 @@ export async function POST(request: Request) {
       },
     });
   } catch (error) {
-    console.error("[SceneFusion] Unexpected error:", error);
+    logger.error("request_failed", error);
     return NextResponse.json(
       { error: error instanceof Error ? error.message : "处理失败" },
       { status: 500 }

components/image-annotator.tsx

@@ -55,6 +55,7 @@ import {
 import { requestLongTaskResult } from "@/lib/client/long-task";
 import { fetchUploadWithRetry } from "@/lib/client/upload-with-retry";
 import { buildImageProxyUrl } from "@/lib/image-delivery";
+import { createClientLogger } from "@/lib/observability/client-logger";
 import { cn } from "@/lib/utils";
 import { AngleEditDialog } from "./angle-edit-dialog";
 import { SceneFusionView } from "./scene-fusion-view";
@@ -64,6 +65,8 @@ import { Slider } from "./ui/slider";
 
 type Tool = "pen" | "arrow" | "circle" | "text";
 
+const logger = createClientLogger("image-annotator");
+
 type DrawingAction = {
   type: Tool;
   color: string;
@@ -315,17 +318,14 @@ export function ImageAnnotator({
           const localImage = await localPreviewPromise;
           setImage(localImage);
         } catch (previewError) {
-          console.warn(
+          logger.warn("local_preview_failed", previewError);
-            "[ImageAnnotator] Local preview failed, fallback to uploaded url:",
-            previewError
-          );
           const uploadedImage = await loadImageFromSource(uploadResult.url);
           setImage(uploadedImage);
         }
 
         toast.success("图片上传成功");
       } catch (error) {
-        console.error("[ImageAnnotator] 上传图片失败:", error);
+        logger.error("upload_failed", error);
         const message =
           error instanceof Error ? error.message : "上传失败，请重试";
         toast.error(message);
@@ -517,7 +517,7 @@ export function ImageAnnotator({
         if (data.siteLogoDark) setSiteLogoDark(data.siteLogoDark);
       })
       .catch((err) => {
-        console.error("[ImageAnnotator] Failed to fetch site settings:", err);
+        logger.warn("site_settings_fetch_failed", err);
       });
   }, []);
 
@@ -559,7 +559,7 @@ export function ImageAnnotator({
         setSelectedAspectRatio(null);
       } catch (error) {
         if (cancelled) return;
-        console.error("初始化图片加载失败:", error);
+        logger.error("initial_image_load_failed", error);
         setImage(null);
         setIsLoading(false);
         toast.error("当前图片加载失败，请重试");
@@ -892,9 +892,8 @@ export function ImageAnnotator({
     setIsRemovingBg(true);
     try {
       // 使用原图URL获取原图数据，而不是canvas的预览图
-      console.log("[抠图] 使用原图URL获取数据:", originalImageUrl);
       const base64Data = await imageUrlToBase64(originalImageUrl);
-      console.log("[抠图] 原图Base64长度:", base64Data.length, "字符");
+      logger.debug("rmbg_source_prepared", { base64Length: base64Data.length });
 
       // 调用抠图API
       const response = await fetch("/api/rmbg", {
@@ -917,23 +916,18 @@ export function ImageAnnotator({
 
       if (result.success && result.image_base64) {
         // 保存处理后的图片URL和Base64（优先使用original_url，确保下载的是原图）
-        console.log("[抠图] API返回结果:", {
+        logger.info("rmbg_completed", {
           hasOriginalUrl: !!result.original_url,
           hasThumbnailUrl: !!result.thumbnail_url,
-          originalUrl: result.original_url?.substring(0, 100),
+          base64Length: String(result.image_base64 || "").length,
-          thumbnailUrl: result.thumbnail_url?.substring(0, 100),
         });
         if (result.original_url) {
-          console.log("[抠图] ✅ 使用原图URL:", result.original_url);
           setProcessedImageUrl(result.original_url);
         } else if (result.thumbnail_url) {
-          console.warn(
+          logger.warn("rmbg_original_url_missing", { hasThumbnailUrl: true });
-            "[抠图] ⚠️ 未找到original_url，使用thumbnail_url作为备选:",
-            result.thumbnail_url
-          );
           setProcessedImageUrl(result.thumbnail_url);
         } else {
-          console.warn("[抠图] ⚠️ 未找到图片URL");
+          logger.warn("rmbg_image_url_missing");
           setProcessedImageUrl(null);
         }
         setProcessedImageBase64(result.image_base64);
@@ -946,7 +940,7 @@ export function ImageAnnotator({
         throw new Error(result.error || result.detail || "抠图处理失败");
       }
     } catch (error) {
-      console.error("[抠图] 错误:", error);
+      logger.error("rmbg_failed", error);
       toast.error(
         error instanceof Error ? error.message : "抠图失败，请稍后重试"
       );
@@ -961,8 +955,6 @@ export function ImageAnnotator({
 
     setIsRemovingWatermark(true);
     try {
-      console.log("[去水印] 使用原图URL:", originalImageUrl);
-
       const result = await requestLongTaskResult({
         endpoint: "/api/watermark-remove",
         payload: {
@@ -971,9 +963,9 @@ export function ImageAnnotator({
       });
 
       if (result.success && result.original_url) {
-        console.log("[去水印] API返回结果:", {
+        logger.info("watermark_remove_completed", {
-          originalUrl: result.original_url?.substring(0, 100),
+          hasOriginalUrl: !!result.original_url,
-          thumbnailUrl: result.thumbnail_url?.substring(0, 100),
+          hasThumbnailUrl: !!result.thumbnail_url,
         });
 
         setProcessedImageUrl(result.original_url);
@@ -988,7 +980,7 @@ export function ImageAnnotator({
           };
           reader.readAsDataURL(blob);
         } catch {
-          console.warn("[去水印] 无法获取Base64，仅使用URL");
+          logger.warn("watermark_remove_base64_fetch_failed");
         }
         setProcessType("watermark");
 
@@ -999,7 +991,7 @@ export function ImageAnnotator({
         throw new Error(result.error || "去水印处理失败");
       }
     } catch (error) {
-      console.error("[去水印] 错误:", error);
+      logger.error("watermark_remove_failed", error);
       toast.error(
         error instanceof Error ? error.message : "去水印失败，请稍后重试"
       );
@@ -1015,9 +1007,8 @@ export function ImageAnnotator({
     setIsEnhancing(true);
     try {
       // 使用原图URL获取原图数据，而不是canvas的预览图
-      console.log("[变清晰] 使用原图URL获取数据:", originalImageUrl);
       const base64Data = await imageUrlToBase64(originalImageUrl);
-      console.log("[变清晰] 原图Base64长度:", base64Data.length, "字符");
+      logger.debug("enhance_source_prepared", { base64Length: base64Data.length });
 
       const result = await requestLongTaskResult({
         endpoint: "/api/enhance",
@@ -1032,40 +1023,28 @@ export function ImageAnnotator({
 
       if (result.success && result.image_base64) {
         // 保存处理后的图片URL和Base64（优先使用original_url，确保下载的是处理后的原图）
-        console.log("[变清晰] API返回结果:", {
+        logger.info("enhance_completed", {
           hasOriginalUrl: !!result.original_url,
           hasThumbnailUrl: !!result.thumbnail_url,
-          originalUrl: result.original_url,
-          thumbnailUrl: result.thumbnail_url,
           base64Length: result.image_base64?.length || 0,
         });
 
         // ✅ 验证：检查返回的URL是否是处理后的图片
         if (result.original_url) {
-          console.log("[变清晰] ✅ 使用处理后的原图URL:", result.original_url);
-          console.log(
-            "[变清晰] ✅ URL应该包含 'enhance-orig' 标识，确认是处理后的图片"
-          );
-
           // 验证URL格式（应该包含enhance-orig）
           if (
             !result.original_url.includes("enhance-orig") &&
             !result.original_url.includes("enhance-orig")
           ) {
-            console.warn(
+            logger.warn("enhance_result_marker_missing");
-              "[变清晰] ⚠️ 警告：URL不包含 'enhance-orig' 标识，可能不是处理后的图片！"
-            );
           }
 
           setProcessedImageUrl(result.original_url);
         } else if (result.thumbnail_url) {
-          console.warn(
+          logger.warn("enhance_original_url_missing", { hasThumbnailUrl: true });
-            "[变清晰] ⚠️ 未找到original_url，使用thumbnail_url作为备选:",
-            result.thumbnail_url
-          );
           setProcessedImageUrl(result.thumbnail_url);
         } else {
-          console.warn("[变清晰] ⚠️ 未找到图片URL");
+          logger.warn("enhance_image_url_missing");
           setProcessedImageUrl(null);
         }
         setProcessedImageBase64(result.image_base64);
@@ -1078,7 +1057,7 @@ export function ImageAnnotator({
         throw new Error(result.error || result.detail || "变清晰处理失败");
       }
     } catch (error) {
-      console.error("[变清晰] 错误:", error);
+      logger.error("enhance_failed", error);
       toast.error(
         error instanceof Error ? error.message : "变清晰失败，请稍后重试"
       );
@@ -1359,7 +1338,7 @@ export function ImageAnnotator({
         const finalResultUrl = result.original_url || dataUrl;
 
         if (result.original_url) {
-          console.log("[尺寸调整] 原图URL:", result.original_url);
+          logger.info("resize_completed", { hasOriginalUrl: true });
           setProcessedImageUrl(result.original_url);
         } else {
           setProcessedImageUrl(null);
@@ -1372,7 +1351,7 @@ export function ImageAnnotator({
         throw new Error(result.error || "尺寸调整处理失败");
       }
     } catch (error) {
-      console.error("[尺寸调整] 错误:", error);
+      logger.error("resize_failed", error);
       toast.error(
         error instanceof Error ? error.message : "尺寸调整失败，请稍后重试"
       );
@@ -1388,8 +1367,6 @@ export function ImageAnnotator({
     setIsExtending(true);
     try {
       // 直接使用原图URL，而不是转换为base64
-      console.log("[图像拓展] 使用原图URL:", originalImageUrl);
-
       // 调用图像拓展API（直接发送URL）
       const response = await fetch("/api/extend", {
         method: "POST",
@@ -1413,15 +1390,17 @@ export function ImageAnnotator({
       if (result.success) {
         // 保存处理后的图片URL和Base64（优先使用original_url，确保下载的是原图）
         if (result.original_url) {
-          console.log("[图像拓展] 原图URL:", result.original_url);
+          logger.info("extend_completed", {
+            hasOriginalUrl: true,
+            hasThumbnailUrl: !!result.thumbnail_url,
+            hasBase64: !!result.base64,
+          });
           setProcessedImageUrl(result.original_url);
         } else if (result.thumbnail_url) {
-          console.warn(
+          logger.warn("extend_original_url_missing", { hasThumbnailUrl: true });
-            "[图像拓展] ⚠️ 未找到original_url，使用thumbnail_url作为备选"
-          );
           setProcessedImageUrl(result.thumbnail_url);
         } else {
-          console.warn("[图像拓展] ⚠️ 未找到图片URL");
+          logger.warn("extend_image_url_missing");
           setProcessedImageUrl(null);
         }
         // 优先使用返回的base64，如果没有则使用thumbnail_url或original_url
@@ -1435,7 +1414,7 @@ export function ImageAnnotator({
         throw new Error(result.error || result.detail || "图像拓展处理失败");
       }
     } catch (error) {
-      console.error("[图像拓展] 错误:", error);
+      logger.error("extend_failed", error);
       toast.error(
         error instanceof Error ? error.message : "图像拓展失败，请稍后重试"
       );
@@ -1507,9 +1486,7 @@ export function ImageAnnotator({
       }
 
       // ✅ 验证：确认下载的是处理后的图片URL
-      console.log("[下载] 📥 开始下载，processType:", processType);
+      logger.debug("download_started", { processType });
-      console.log("[下载] 📥 processedImageUrl:", processedImageUrl);
-      console.log("[下载] 📥 这个URL应该是处理后的图片，不是原图！");
 
       // 确保使用的是处理后的原图URL（检查URL中是否包含thumb标识）
       let downloadUrl = processedImageUrl;
@@ -1526,7 +1503,7 @@ export function ImageAnnotator({
           .replace(/-thumb\./g, "-orig.")
           .replace(/\/thumb\//g, "/orig/")
           .replace(/thumbnail/g, "original");
-        console.warn("[下载] ⚠️ 检测到缩略图URL，已转换为原图URL:", downloadUrl);
+        logger.warn("download_thumbnail_url_rewritten", { processType });
       }
 
       // 如果转换后的URL仍然包含thumb标识，尝试更激进的转换
@@ -1538,18 +1515,20 @@ export function ImageAnnotator({
           if (pathname.includes("thumb")) {
             const newPathname = pathname.replace(/thumb/g, "orig");
             downloadUrl = downloadUrl.replace(pathname, newPathname);
-            console.warn("[下载] ⚠️ 二次转换原图URL:", downloadUrl);
+            logger.warn("download_thumbnail_url_rewritten_again", { processType });
           }
         } catch (urlError) {
           // 如果URL解析失败，尝试简单的字符串替换
           downloadUrl = downloadUrl.replace(/thumb/g, "orig");
-          console.warn("[下载] ⚠️ 使用简单替换转换原图URL:", downloadUrl);
+          logger.warn("download_thumbnail_url_string_rewrite", {
+            processType,
+            reason: urlError instanceof Error ? urlError.message : "unknown",
+          });
         }
       }
 
       // ✅ 验证：确认下载URL是正确的
-      console.log("[下载] ✅ 最终下载URL:", downloadUrl);
+      logger.debug("download_url_resolved", { processType });
-      console.log("[下载] ✅ 这个URL应该指向处理后的图片（不是原图）");
 
       // 如果是变清晰，验证URL应该包含enhance相关标识
       if (
@@ -1557,9 +1536,7 @@ export function ImageAnnotator({
         !downloadUrl.includes("enhance") &&
         !downloadUrl.includes("1767358346590")
       ) {
-        console.warn(
+        logger.warn("download_enhance_marker_missing");
-          "[下载] ⚠️ 警告：变清晰下载URL不包含 'enhance' 标识，可能下载了错误的图片！"
-        );
       }
 
       // 从原图URL下载（原图已上传到S3）
@@ -1570,7 +1547,7 @@ export function ImageAnnotator({
         );
       }
       const blob = await response.blob();
-      console.log("[下载] 下载的图片大小:", blob.size, "bytes");
+      logger.info("download_blob_ready", { bytes: blob.size, processType });
       const url = window.URL.createObjectURL(blob);
       const link = document.createElement("a");
       link.href = url;
@@ -1582,7 +1559,7 @@ export function ImageAnnotator({
 
       toast.success("原图下载成功");
     } catch (error) {
-      console.error("[下载] 错误:", error);
+      logger.error("download_failed", error);
       toast.error(
         `下载失败: ${error instanceof Error ? error.message : "请稍后重试"}`
       );
@@ -1615,7 +1592,7 @@ export function ImageAnnotator({
       }
       return uploadResult.url;
     } catch (error) {
-      console.error("上传图片失败:", error);
+      logger.error("server_upload_failed", error);
       throw error;
     }
   };

scripts/check-log-hygiene.mjs

@@ -10,6 +10,12 @@ const files = [
   "lib/ai/providers/gemini-image.ts",
   "lib/ai/providers/volcano-vision.ts",
   "lib/ai/providers/qianwen-video.ts",
+  "services/canvas/index.ts",
+  "components/image-annotator.tsx",
+  "app/api/canvas/auto-title/route.ts",
+  "app/api/canvas/text-detect/route.ts",
+  "app/api/canvas/detail-plan/route.ts",
+  "app/api/scene-fusion/route.ts",
 ];
 
 const consolePattern = /\bconsole\.(log|warn|error|info|debug)\b/g;

services/canvas/index.ts

@@ -14,7 +14,7 @@ import type {
   EnhanceProOutputFormat,
   EnhanceProSubjectDetection,
 } from '@/lib/enhance-pro/config';
-import { createLogger } from '@/lib/logger';
+import { createLogger } from '@/lib/observability/logger';
 
 const log = createLogger("Canvas");
 
@@ -267,7 +267,7 @@ export const imageGenerationService = {
         } 
       };
     } catch (error) {
-      console.error('[Canvas] 图片上传失败:', error);
+      logCatch(error, "image_upload");
       return { success: false, error: '图片上传失败' };
     }
   },
@@ -374,7 +374,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '局部编辑提交失败' };
     } catch (error) {
-      console.error('[Canvas] 局部编辑提交失败:', error);
+      logCatch(error, "local_edit_submit");
       return { success: false, error: '局部编辑提交失败' };
     }
   },
@@ -403,7 +403,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '查询生图任务失败' };
     } catch (error) {
-      console.error('[Canvas] 查询生图任务失败:', error);
+      logCatch(error, "image_task_fetch", { taskId });
       return { success: false, error: '查询生图任务失败' };
     }
   },
@@ -422,7 +422,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '抠图失败' };
     } catch (error) {
-      console.error('[Canvas] 抠图失败:', error);
+      logCatch(error, "remove_background");
       return { success: false, error: '抠图失败' };
     }
   },
@@ -458,7 +458,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '框选抠图失败' };
     } catch (error) {
-      console.error('[Canvas] 框选抠图失败:', error);
+      logCatch(error, "box_cutout");
       return { success: false, error: '框选抠图失败' };
     }
   },
@@ -477,7 +477,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '去水印失败' };
     } catch (error) {
-      console.error('[Canvas] 去水印失败:', error);
+      logCatch(error, "remove_watermark");
       return { success: false, error: '去水印失败' };
     }
   },
@@ -504,7 +504,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '图片增强失败' };
     } catch (error) {
-      console.error('[Canvas] 图片增强失败:', error);
+      logCatch(error, "enhance_image");
       return { success: false, error: '图片增强失败' };
     }
   },
@@ -559,7 +559,7 @@ export const imageGenerationService = {
         },
       };
     } catch (error) {
-      console.error('[Canvas] 图像增强 Pro 失败:', error);
+      logCatch(error, "enhance_image_pro");
       if (error instanceof Error && /failed to fetch|network/i.test(error.message)) {
         return {
           success: false,
@@ -612,7 +612,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || data.detail || '图片扩展失败' };
     } catch (error) {
-      console.error('[Canvas] 图片扩展失败:', error);
+      logCatch(error, "extend_image");
       return { success: false, error: '图片扩展失败' };
     }
   },
@@ -658,7 +658,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '图层拆分失败' };
     } catch (error) {
-      console.error('[Canvas] 图层拆分失败:', error);
+      logCatch(error, "split_image_layers");
       return { success: false, error: '图层拆分失败' };
     }
   },
@@ -714,7 +714,7 @@ export const imageGenerationService = {
       }
       return { success: false, error: data.error || '尺寸调整失败' };
     } catch (error) {
-      console.error('[Canvas] 尺寸调整失败:', error);
+      logCatch(error, "resize_image", { width, height });
       return { success: false, error: '尺寸调整失败' };
     }
   },
@@ -796,7 +796,7 @@ export const imageGenerationService = {
       const data = await response.json();
       return data;
     } catch (error) {
-      console.error('[Canvas] 文字识别失败:', error);
+      logCatch(error, "detect_canvas_text");
       return { success: false, error: '文字识别失败' };
     }
   },
@@ -826,7 +826,7 @@ export const imageGenerationService = {
       const data = await response.json();
       return data;
     } catch (error) {
-      console.error('[Canvas] 文案建议生成失败:', error);
+      logCatch(error, "text_suggestions");
       return { success: false, error: '文案建议生成失败' };
     }
   },
@@ -845,7 +845,7 @@ export const imageGenerationService = {
       const data = await response.json();
       return data;
     } catch (error) {
-      console.error('[Canvas] 文字替换失败:', error);
+      logCatch(error, "edit_canvas_text", { itemCount: params.items.length });
       return { success: false, error: '文字替换失败' };
     }
   },