Merge pull request '恢复画布 Agent 默认处理并修正生图终态与预览闪白' (#49) from codex/agent-feedback-recovery-20261105 into main

app/(chat)/api/chat/_lib/image-generation-failure.ts

@@ -0,0 +1,47 @@
+import { saveMessages } from "@/lib/db/queries";
+import type { ImageGenerationStatusStreamPayload } from "@/lib/canvas/image-generation-status";
+import { formatRequestFailure, getRequestFailureDetails } from "@/lib/request-error";
+import { safeWriteStreamChunk, type StreamWriter, writeAssistantTextChunk, writeStructuredDataChunk } from "./stream";
+
+export async function reportImageGenerationFailure(params: {
+  writer: StreamWriter;
+  chatId: string;
+  userMessageId: string;
+  messageId: string;
+  error: unknown;
+  label: string;
+}) {
+  const failure = getRequestFailureDetails(params.error, "图片生成失败");
+  const status: ImageGenerationStatusStreamPayload = {
+    phase: "failed",
+    userMessageId: params.userMessageId,
+    requestId: params.messageId,
+    failure,
+  };
+  const text = formatRequestFailure(failure, params.messageId);
+  const parts = [
+    { type: "text", text },
+    { type: "data-imageGenerationStatus", data: status },
+  ];
+  writeStructuredDataChunk(params.writer, "data-imageGenerationStatus", status, `${params.label}:status`);
+  safeWriteStreamChunk(params.writer, {
+    type: "data-appendMessage",
+    data: JSON.stringify({ id: params.messageId, role: "assistant", parts }),
+  }, params.label);
+  writeAssistantTextChunk(params.writer, "<!-- IMAGE_GENERATION_END -->", `${params.label}:end`);
+  // History carries the same terminal state when the browser loses the stream.
+  await saveMessages({ messages: [{
+    id: params.messageId,
+    chatId: params.chatId,
+    role: "assistant",
+    parts,
+    attachments: [],
+    createdAt: new Date(),
+    videoStorageStatus: null,
+    temporaryVideoUrl: null,
+    permanentVideoUrl: null,
+    archivedAt: null,
+    videoMetadata: null,
+  }] });
+  return text;
+}

app/(chat)/api/chat/_lib/stream.ts

@@ -208,6 +208,7 @@ export function writeImageGenerationStatusChunk(
   writer: StreamWriter,
   params: {
     phase: "queued" | "processing" | "finalizing" | "failed" | "completed";
+    userMessageId?: string;
     providerType?: string | null;
     modelName?: string | null;
     imageCount?: number | null;
@@ -223,6 +224,7 @@ export function writeImageGenerationStatusChunk(
     "data-imageGenerationStatus",
     {
       phase: params.phase,
+      userMessageId: params.userMessageId,
       providerType: normalizeImageLoadingProviderType(params.providerType),
       modelName: String(params.modelName || "").trim() || undefined,
       imageCount:

app/(chat)/api/chat/route.ts

@@ -426,6 +426,8 @@ import {
   type VideoModeType,
 } from "./_lib/video-models";
 
+import { reportImageGenerationFailure } from "./_lib/image-generation-failure";
+
 const chatApiLogger = createLogger("chat.route");
 const createUIMessageStream: typeof createAiUIMessageStream = (options) =>
   createAiUIMessageStream({ ...options, execute: (writer) => trackRuntimeWork(() => options.execute(writer)) });
@@ -446,16 +448,6 @@ function assertGeneratedImageMarkdownHasImage(markdown: string, modelLabel: stri
   throw new Error(`${modelLabel} 未返回可用图片：${reason.slice(0, 160)}`);
 }
 
-function getPublicImageGenerationErrorText(error: unknown, requestId: string) {
-  const message = error instanceof Error ? error.message : String(error || "");
-  const publicMessage = getUserFacingImageGenerationErrorMessage(error);
-  if (!message || (publicMessage === message && INTERNAL_IMAGE_GENERATION_FAILURE_PATTERN.test(message))) {
-    return `图片生成失败，请稍后重试。若连续失败，请联系管理员。\n\n请求编号：${requestId}`;
-  }
-  return `${publicMessage}\n\n请求编号：${requestId}`;
-}
-
-
 const AGENT_REPLACEMENT_PARALLEL_WORKER_COUNT = Math.max(
   1,
   Math.min(8, Number(process.env.AGENT_REPLACEMENT_PARALLEL_WORKER_COUNT || 6) || 6),
@@ -5688,6 +5680,7 @@ export async function POST(request: Request) {
             writeImageGenerationStatusChunk(
               writer,
               {
+                userMessageId: message.id,
                 phase: "processing",
                 modelName: resolvedModelRef,
                 imageCount: replacementReferences.length,
@@ -6030,6 +6023,7 @@ export async function POST(request: Request) {
                           writeImageGenerationStatusChunk(
                             writer,
                             {
+                              userMessageId: message.id,
                               phase:
                                 queueStatus.status === "running"
                                   ? "processing"
@@ -6185,6 +6179,7 @@ export async function POST(request: Request) {
             writeImageGenerationStatusChunk(
               writer,
               {
+                userMessageId: message.id,
                 phase: successCount > 0 ? "completed" : "failed",
                 modelName: resolvedModelDisplayName,
                 imageCount: successCount,
@@ -6417,6 +6412,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "processing",
                   modelName:
                     selectedAgentPreset.defaultModel?.displayName ||
@@ -6968,6 +6964,7 @@ export async function POST(request: Request) {
                             writeImageGenerationStatusChunk(
                               writer,
                               {
+                                userMessageId: message.id,
                                 phase:
                                   queueStatus.status === "running"
                                     ? "processing"
@@ -7293,6 +7290,7 @@ export async function POST(request: Request) {
                         writeImageGenerationStatusChunk(
                           writer,
                           {
+                            userMessageId: message.id,
                             phase:
                               queueStatus.status === "running"
                                 ? "processing"
@@ -7521,6 +7519,7 @@ export async function POST(request: Request) {
                           writeImageGenerationStatusChunk(
                             writer,
                             {
+                              userMessageId: message.id,
                               phase:
                                 queueStatus.status === "running"
                                   ? "processing"
@@ -7839,6 +7838,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: successCount > 0 ? "completed" : "failed",
                   modelName:
                     selectedAgentPreset.defaultModel?.displayName ||
@@ -8048,6 +8048,7 @@ export async function POST(request: Request) {
             writeImageGenerationStatusChunk(
               writer,
               {
+                userMessageId: message.id,
                 phase: "processing",
                 providerType: requestedModelProviderType,
                 modelName: finalModelId,
@@ -8086,6 +8087,7 @@ export async function POST(request: Request) {
                   writeImageGenerationStatusChunk(
                     writer,
                     {
+                      userMessageId: message.id,
                       phase: "processing",
                       ...directImageStatusPayload,
                     },
@@ -8178,6 +8180,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "completed",
                   providerType: requestedModelProviderType,
                   modelName: directImageResult.model,
@@ -8198,42 +8201,16 @@ export async function POST(request: Request) {
             );
           } catch (directToolError) {
             chatApiLogger.error("[Chat API] Direct agent image generation failed:", directToolError);
-            const errorMessage = getDirectAgentToolErrorMessage(
+            const errorMessage = await reportImageGenerationFailure({
-              "generate_image",
+              writer, chatId: id, userMessageId: message.id,
-              directToolError,
+              messageId: assistantMessageId, error: directToolError,
-            );
+              label: "agent:generate_image:error",
-            await saveAssistantTextOnlyMessage({
-              chatId: id,
-              messageId: assistantMessageId,
-              text: errorMessage,
             });
-            writeAssistantTextChunk(
-              writer,
-              errorMessage,
-              "agent:generate_image:error",
-              assistantMessageId,
-            );
-            if (contextPayload?.source === "canvas") {
-              writeImageGenerationStatusChunk(
-                writer,
-                {
-                  phase: "failed",
-                  providerType: requestedModelProviderType,
-                  modelName: finalModelId,
-                },
-                "agent:generate_image:status-failed",
-              );
-            }
             writeAgentProgressChunk(
               writer,
               buildDirectAgentImageGenerateFailedProgress(errorMessage),
               "agent:generate_image:progress-failed",
             );
-            writeAssistantTextChunk(
-              writer,
-              "<!-- IMAGE_GENERATION_END -->",
-              "agent:generate_image:end-error",
-            );
           } finally {
             stopDirectImageKeepalive();
             if (stopDirectImageStatus) {
@@ -9195,6 +9172,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "processing",
                   providerType: (languageModel as any).provider,
                   modelName: currentModelConfig?.displayName || actualModelId,
@@ -9282,6 +9260,7 @@ export async function POST(request: Request) {
                     chatApiLogger.warn("[Chat API] Record Gemini fallback health failure failed:", healthError);
                   });
                   chatApiLogger.error(`[Chat API] ❌ Fallback model ${candidate.model.displayName} (${candidate.provider.type}) failed:`, fallbackError);
+                  if (!shouldFailoverAiModelError(fallbackError)) throw fallbackError;
                 }
               }
 
@@ -9356,6 +9335,7 @@ export async function POST(request: Request) {
                       chatApiLogger.warn("[Chat API] Record Gemini cross-provider health failure failed:", healthError);
                     });
                     chatApiLogger.error(`[Chat API] ❌ Gemini cross-provider fallback model ${candidate.model.displayName} (${candidate.provider.type}) failed:`, fallbackError);
+                    if (!shouldFailoverAiModelError(fallbackError)) throw fallbackError;
                   }
                 }
               }
@@ -9423,6 +9403,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "completed",
                   providerType: (languageModel as any).provider,
                   modelName: usedModelDisplayName,
@@ -9487,6 +9468,14 @@ export async function POST(request: Request) {
             }
           } catch (error) {
             chatApiLogger.error("[Chat API] Gemini generation error:", error);
+            let finalError = error;
+            if (!shouldFailoverAiModelError(error)) {
+              await reportImageGenerationFailure({
+                writer, chatId: id, userMessageId: message.id,
+                messageId: generateUUID(), error, label: "gemini:error",
+              });
+              return;
+            }
             chatApiLogger.info("[Chat API] Attempting failover to Volcano Vision...");
             
             // 故障转移：尝试使用火山引擎模型
@@ -9564,6 +9553,7 @@ export async function POST(request: Request) {
                       writeImageGenerationStatusChunk(
                         writer,
                         {
+                          userMessageId: message.id,
                           phase: "completed",
                           providerType: "volcano-vision",
                           modelName: volcanoModel.model.displayName || volcanoModel.model.modelId,
@@ -9629,47 +9619,14 @@ export async function POST(request: Request) {
               chatApiLogger.info("[Chat API] No Volcano Vision model available for failover");
             } catch (failoverError) {
               chatApiLogger.error("[Chat API] Failover to Volcano Vision also failed:", failoverError);
+              finalError = failoverError;
             }
             
             // 如果故障转移也失败，返回错误消息
-            const errorMessageId = generateUUID();
+            await reportImageGenerationFailure({
-            const errorText = getPublicImageGenerationErrorText(error, errorMessageId);
+              writer, chatId: id, userMessageId: message.id,
-            writeAssistantTextChunk(
+              messageId: generateUUID(), error: finalError, label: "gemini:error",
-              writer,
-              errorText,
-              "gemini:error",
-              errorMessageId,
-            );
-            
-            // 🆕 图片生成结束标记（失败）
-            writeAssistantTextChunk(
-              writer,
-              "<!-- IMAGE_GENERATION_END -->",
-              "gemini:image-end-failed",
-            );
-            
-            // 尝试保存错误消息
-            try {
-              await saveMessages({
-                messages: [
-                  {
-                    id: errorMessageId,
-                    chatId: id,
-                    role: "assistant",
-                    parts: [{ type: "text", text: errorText }],
-                    attachments: [],
-                    createdAt: new Date(),
-                    videoStorageStatus: null,
-                    temporaryVideoUrl: null,
-                    permanentVideoUrl: null,
-                    archivedAt: null,
-                    videoMetadata: null,
-                  },
-                ],
             });
-            } catch (saveError) {
-              chatApiLogger.error("[Chat API] Failed to save error message:", saveError);
-            }
           } finally {
             stopKeepalive?.();
           }
@@ -9867,6 +9824,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "queued",
                   providerType: "fal-image",
                   modelName: modelDisplayName,
@@ -9973,6 +9931,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "processing",
                   providerType: (languageModel as any).provider,
                   modelName: alibabaModelConfig?.displayName || actualModelId,
@@ -10070,6 +10029,7 @@ export async function POST(request: Request) {
                     chatApiLogger.warn("[Chat API] Record image fallback health failure failed:", healthError);
                   });
                   chatApiLogger.error(`[Chat API] ❌ Alibaba fallback model ${candidate.model.displayName} (${candidate.provider.type}) failed:`, fallbackError);
+                  if (!shouldFailoverAiModelError(fallbackError)) throw fallbackError;
                 }
               }
 
@@ -10204,6 +10164,7 @@ export async function POST(request: Request) {
                       chatApiLogger.warn("[Chat API] Record image cross-provider health failure failed:", healthError);
                     });
                     chatApiLogger.error(`[Chat API] ❌ Cross-provider failover failed: ${candidate.model.displayName} (${candidate.provider.type})`, crossError);
+                    if (!shouldFailoverAiModelError(crossError)) throw crossError;
                   }
                 }
               }
@@ -10271,6 +10232,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "completed",
                   providerType: (languageModel as any).provider,
                   modelName: usedModelDisplayName,
@@ -10335,43 +10297,10 @@ export async function POST(request: Request) {
             chatApiLogger.error("[Chat API] Alibaba generation error:", error);
             
             // 返回错误消息
-            const errorMessageId = generateUUID();
+            await reportImageGenerationFailure({
-            const errorText = getPublicImageGenerationErrorText(error, errorMessageId);
+              writer, chatId: id, userMessageId: message.id,
-            writeAssistantTextChunk(
+              messageId: generateUUID(), error, label: "alibaba:error",
-              writer,
-              errorText,
-              "alibaba:error",
-              errorMessageId,
-            );
-            
-            // 🆕 图片生成结束标记（失败）
-            writeAssistantTextChunk(
-              writer,
-              "<!-- IMAGE_GENERATION_END -->",
-              "alibaba:image-end-failed",
-            );
-            
-            try {
-              await saveMessages({
-                messages: [
-                  {
-                    id: errorMessageId,
-                    chatId: id,
-                    role: "assistant",
-                    parts: [{ type: "text", text: errorText }],
-                    attachments: [],
-                    createdAt: new Date(),
-                    videoStorageStatus: null,
-                    temporaryVideoUrl: null,
-                    permanentVideoUrl: null,
-                    archivedAt: null,
-                    videoMetadata: null,
-                  },
-                ],
             });
-            } catch (saveError) {
-              chatApiLogger.error("[Chat API] Failed to save error message:", saveError);
-            }
           } finally {
             stopKeepalive?.();
           }
@@ -10500,6 +10429,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "processing",
                   providerType: "volcano-vision",
                   modelName: volcanoModelConfig?.displayName || actualModelId,
@@ -10545,6 +10475,7 @@ export async function POST(request: Request) {
                     setImageFallbackModelCooldown(candidate.model.id, fallbackErrorMessage);
                   }
                   chatApiLogger.error(`[Chat API] ❌ Volcano fallback model ${candidate.model.displayName} (${candidate.provider.type}) failed:`, fallbackError);
+                  if (!shouldFailoverAiModelError(fallbackError)) throw fallbackError;
                 }
               }
               if (!fallbackSuccess) {
@@ -10711,6 +10642,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 writer,
                 {
+                  userMessageId: message.id,
                   phase: "completed",
                   providerType: "volcano-vision",
                   modelName: usedModelDisplayName,
@@ -10775,44 +10707,10 @@ export async function POST(request: Request) {
             }
           } catch (error) {
             chatApiLogger.error("[Chat API] Volcano Vision generation error:", error);
-            const errorMessageId = generateUUID();
+            await reportImageGenerationFailure({
-            const errorText = getPublicImageGenerationErrorText(error, errorMessageId);
+              writer, chatId: id, userMessageId: message.id,
-            writeAssistantTextChunk(
+              messageId: generateUUID(), error, label: "volcano:error",
-              writer,
-              errorText,
-              "volcano:error",
-              errorMessageId,
-            );
-            
-            // 🆕 图片生成结束标记（失败）
-            writeAssistantTextChunk(
-              writer,
-              "<!-- IMAGE_GENERATION_END -->",
-              "volcano:image-end-failed",
-            );
-            
-            // 尝试保存错误消息
-            try {
-              await saveMessages({
-                messages: [
-                  {
-                    id: errorMessageId,
-                    chatId: id,
-                    role: "assistant",
-                    parts: [{ type: "text", text: errorText }],
-                    attachments: [], // 必须提供 attachments 字段
-                    createdAt: new Date(),
-                    videoStorageStatus: null,
-                    temporaryVideoUrl: null,
-                    permanentVideoUrl: null,
-                    archivedAt: null,
-                    videoMetadata: null,
-                  },
-                ],
             });
-            } catch (saveError) {
-              chatApiLogger.error("[Chat API] Failed to save error message:", saveError);
-            }
           } finally {
             stopKeepalive?.();
           }
@@ -11385,6 +11283,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 dataStream as unknown as StreamWriter,
                 {
+                  userMessageId: message.id,
                   phase: "processing",
                   providerType: currentModelConfig?.providerId ? resolvedProviderType || providerType : providerType,
                   modelName: currentModelConfig?.displayName || actualModelId,
@@ -11476,6 +11375,7 @@ export async function POST(request: Request) {
                     setImageFallbackModelCooldown(candidate.model.id, fallbackErrorMessage);
                   }
                   chatApiLogger.error(`[Chat API] ❌ OpenAI-compatible fallback model ${candidate.model.displayName} (${candidate.provider.type}) failed:`, fallbackError);
+                  if (!shouldFailoverAiModelError(fallbackError)) throw fallbackError;
                 }
               }
 
@@ -11647,6 +11547,7 @@ export async function POST(request: Request) {
               writeImageGenerationStatusChunk(
                 dataStream as unknown as StreamWriter,
                 {
+                  userMessageId: message.id,
                   phase: "completed",
                   providerType: resolvedProviderType || providerType,
                   modelName: usedModelDisplayName,
@@ -11706,54 +11607,10 @@ export async function POST(request: Request) {
           } catch (error) {
             chatApiLogger.error("[Chat API] OpenAI-compatible image model generation error:", error);
 
-            const errorMessageId = generateUUID();
+            await reportImageGenerationFailure({
-            const errorText = getPublicImageGenerationErrorText(error, errorMessageId);
+              writer: dataStream as unknown as StreamWriter,
-
+              chatId: id, userMessageId: message.id,
-            dataStream.write({
+              messageId: generateUUID(), error, label: "openai-compat:error",
-              type: "data-appendMessage",
-              data: JSON.stringify({
-                id: errorMessageId,
-                role: "assistant",
-                parts: [{ type: "text", text: errorText }],
-              }),
-            });
-	            dataStream.write({
-	              type: "data-appendMessage",
-	              data: JSON.stringify({
-	                id: generateUUID(),
-	                role: "assistant",
-	                parts: [{ type: "text", text: "<!-- IMAGE_GENERATION_END -->" }],
-	              }),
-	            });
-            if (contextPayload?.source === "canvas") {
-              writeImageGenerationStatusChunk(
-                dataStream as unknown as StreamWriter,
-                {
-                  phase: "failed",
-                  providerType: resolvedProviderType || providerType,
-                  modelName: currentModelConfig?.displayName || actualModelId,
-                  imageCount: effectiveImageParams?.imageCount || 1,
-                },
-                "openai-compat:image-status-failed",
-              );
-            }
-
-            await saveMessages({
-              messages: [
-                {
-                  id: errorMessageId,
-                  role: "assistant",
-                  parts: [{ type: "text", text: errorText }],
-                  createdAt: new Date(),
-                  attachments: [],
-                  chatId: id,
-                  videoStorageStatus: null,
-                  temporaryVideoUrl: null,
-                  permanentVideoUrl: null,
-                  archivedAt: null,
-                  videoMetadata: null,
-                },
-              ],
             });
             return;
           }

app/api/canvas/[id]/capabilities/route.ts

@@ -2,6 +2,7 @@ import { NextResponse } from "next/server";
 import { ZodError } from "zod";
 
 import { auth } from "@/app/(auth)/auth";
+import { RmbgServiceError } from "@/lib/ai/rmbg/service";
 import { canvasCapabilityClientCommandSchema } from "@/lib/canvas/capabilities/client-command";
 import { CanvasCapabilityRuntimeError } from "@/lib/canvas/capabilities/context";
 import { getCanvasCapabilityManifest } from "@/lib/canvas/capabilities/registry";
@@ -90,7 +91,7 @@ export async function POST(
     const failure = getRequestFailureDetails(error, "执行画布能力失败");
     return NextResponse.json(
       { success: false, error: formatRequestFailure(failure, requestId), failure, requestId },
-      { status: 500 }
+      { status: error instanceof RmbgServiceError ? error.status : 500 }
     );
   }
 }

app/api/canvas/box-cutout/route.ts

@@ -1,100 +1,15 @@
-import { NextRequest, NextResponse } from "next/server";
+import { NextResponse } from "next/server";
 
 import { auth } from "@/app/(auth)/auth";
-import {
+import { executeBoxCutoutPOST } from "@/lib/canvas/operations/box-cutout";
-  BoxCutoutServiceError,
-  executeBoxCutoutJob,
-} from "@/lib/ai/box-cutout/service";
-import { RmbgServiceError } from "@/lib/ai/rmbg/service";
-import { getPointsSystemConfig } from "@/lib/db/queries";
-import { prepareFeaturePointsCharge } from "@/lib/points/feature-charge";
-import { getImageToolCreditCost } from "@/lib/points/config";
 
 export const runtime = "nodejs";
 export const maxDuration = 60;
 
-type BoxCutoutRequest = {
+export async function POST(request: Request) {
-  imageUrl?: string;
-  cropRect?: {
-    x?: number;
-    y?: number;
-    width?: number;
-    height?: number;
-  };
-  paddingRatio?: number;
-  prompt?: string;
-  chatId?: string | null;
-  messageId?: string | null;
-  skipGallerySave?: boolean;
-  sourceNodeId?: string;
-};
-
-export async function POST(request: NextRequest) {
-  try {
   const session = await auth();
   if (!session?.user?.id) {
     return NextResponse.json({ success: false, error: "未授权，请先登录" }, { status: 401 });
   }
-
+  return executeBoxCutoutPOST(request, session.user.id);
-    const body = (await request.json()) as BoxCutoutRequest;
-    const rawImageUrl = String(body.imageUrl || "").trim();
-    if (!rawImageUrl) {
-      return NextResponse.json({ success: false, error: "缺少 imageUrl 参数" }, { status: 400 });
-    }
-
-    const resolvedImageUrl = new URL(rawImageUrl, request.url).toString();
-    const pointsConfig = await getPointsSystemConfig();
-    const pointsCharge = await prepareFeaturePointsCharge({
-      userId: session.user.id,
-      unitCost: getImageToolCreditCost(pointsConfig, "box-cutout"),
-      reason: "image_box_cutout",
-      modelId: "box-cutout",
-      note: "框选抠图消耗积分",
-      pointsConfig,
-    });
-    if (!pointsCharge.ok) {
-      return NextResponse.json(pointsCharge.payload, { status: pointsCharge.status });
-    }
-
-    const result = await executeBoxCutoutJob({
-      userId: session.user.id,
-      imageUrl: resolvedImageUrl,
-      cropRect: body.cropRect || {},
-      paddingRatio: body.paddingRatio,
-      prompt: body.prompt || "框选抠图",
-      chatId: body.chatId || null,
-      messageId: body.messageId || null,
-      skipGallerySave: body.skipGallerySave === true,
-      sourceNodeId: body.sourceNodeId,
-    });
-
-    if (pointsCharge.chargeable) {
-      try {
-        await pointsCharge.consume();
-      } catch (pointsError) {
-        console.error("[Points] Failed to consume box cutout points:", pointsError);
-      }
-    }
-
-    return NextResponse.json(result);
-  } catch (error) {
-    if (error instanceof BoxCutoutServiceError || error instanceof RmbgServiceError) {
-      return NextResponse.json(
-        {
-          success: false,
-          error: error.detail || error.message,
-        },
-        { status: error.status },
-      );
-    }
-
-    console.error("[BoxCutout] 处理失败:", error);
-    return NextResponse.json(
-      {
-        success: false,
-        error: error instanceof Error ? error.message : "框选抠图失败",
-      },
-      { status: 500 },
-    );
-  }
 }

app/api/image-proxy/route.ts

@@ -3,6 +3,7 @@ import { isRetiredStorageUrl, normalizeLegacyAliyunStorageUrl, RETIRED_STORAGE_M
 import { NextRequest, NextResponse } from "next/server";
 import { formatDownloadFailure, getDownloadFailure } from "@/lib/canvas/download-error";
 import { createLogger } from "@/lib/observability/logger";
+import { buildImageProxyUrl, isAlibabaModelImageUrl } from "@/lib/image-delivery";
 
 export const runtime = "nodejs";
 const logger = createLogger("image.download");
@@ -242,6 +243,7 @@ function resolveDirectImageTarget(
   requestedQuality: number | null,
   requestedFormat: string | null
 ): URL | null {
+  if (isAlibabaModelImageUrl(target.toString())) return null;
   if (!isBrowserImageRequest(request)) {
     return null;
   }
@@ -336,6 +338,25 @@ export async function GET(request: NextRequest) {
     );
   }
 
+  if (!original && isAlibabaModelImageUrl(target.toString())) {
+    try {
+      const { getArchivedImageUrlMappings } = await import("@/lib/storage/image-archive-db");
+      const mappings = await getArchivedImageUrlMappings([target.toString()]);
+      const archived = mappings[target.toString()];
+      if (archived) {
+        const preview = buildImageProxyUrl(archived, {
+          width: width || undefined,
+          quality,
+          format: ["webp", "avif", "jpeg", "png"].includes(requestedFormat || "") ? requestedFormat as OutputFormat : undefined,
+        });
+        if (/^https?:\/\//i.test(preview)) return redirectToDirectImage(new URL(preview));
+        target = new URL(archived);
+      }
+    } catch (error) {
+      logger.warn("preview_archive_lookup_failed", error, { requestId });
+    }
+  }
+
   if (original && searchParams.get("download") === "resolve") {
     try {
       const { buildImageProxyUrl } = await import("@/lib/image-delivery");
@@ -388,7 +409,7 @@ export async function GET(request: NextRequest) {
 
   const fetchSignal = AbortSignal.any([
     request.signal,
-    AbortSignal.timeout(original ? 60_000 : width && width <= 256 ? SMALL_PREVIEW_FETCH_TIMEOUT_MS : FETCH_TIMEOUT_MS),
+    AbortSignal.timeout(original ? 60_000 : isAlibabaModelImageUrl(target.toString()) || width && width <= 256 ? SMALL_PREVIEW_FETCH_TIMEOUT_MS : FETCH_TIMEOUT_MS),
   ]);
   const upstreamFailure = (error: unknown) => {
     if (request.signal.aborted) return new NextResponse(null, { status: 499 });
@@ -399,6 +420,22 @@ export async function GET(request: NextRequest) {
       { status: timedOut ? 504 : 502 },
     );
   };
+  let contentType: string;
+  let originalBuffer: Buffer;
+  if (!original && isAlibabaModelImageUrl(target.toString())) {
+    try {
+      const { fetchImageBytes } = await import("@/lib/storage/image-byte-cache");
+      const data = await fetchImageBytes(target.toString(), { timeoutMs: SMALL_PREVIEW_FETCH_TIMEOUT_MS });
+      originalBuffer = data.buffer;
+      contentType = data.contentType;
+      if (request.signal.aborted) return new NextResponse(null, { status: 499 });
+      if (!contentType.toLowerCase().startsWith("image/")) {
+        return NextResponse.json({ error: "Upstream is not an image" }, { status: 400 });
+      }
+    } catch (error) {
+      return upstreamFailure(error);
+    }
+  } else {
     let upstreamResponse: Response;
     try {
       upstreamResponse = await fetch(target.toString(), {
@@ -418,19 +455,17 @@ export async function GET(request: NextRequest) {
         { status: 502 }
       );
     }
-
+    contentType = upstreamResponse.headers.get("content-type") || "application/octet-stream";
-  const contentType = upstreamResponse.headers.get("content-type") || "application/octet-stream";
     if (!contentType.toLowerCase().startsWith("image/")) {
       if (original) return downloadFailure("Source is not an image");
       return NextResponse.json({ error: "Upstream is not an image" }, { status: 400 });
     }
-
-  let originalBuffer: Buffer;
     try {
       originalBuffer = Buffer.from(await upstreamResponse.arrayBuffer());
     } catch (error) {
       return upstreamFailure(error);
     }
+  }
   if (original) {
     return buildImageResponse(originalBuffer, {
       contentType,

app/api/scene-fusion/route.ts

@@ -6,6 +6,7 @@
  */
 
 import { NextResponse } from "next/server";
+import { preprocessProductImageWithRmbg } from "@/lib/scene-fusion/preprocess-product";
 import { z } from "zod";
 import { auth } from "@/app/(auth)/auth";
 import { db } from "@/lib/db";
@@ -69,7 +70,6 @@ const SCENE_FUSION_REQUEST_STAGGER_MS = 350;
 const SCENE_FUSION_AGENT_TIMEOUT_MS = 20000;
 const SCENE_FUSION_AGENT_MAX_WORKERS = 3;
 const SCENE_FUSION_PROCESS_MAX_WORKERS = 4;
-const SCENE_FUSION_PRE_RMBG_TIMEOUT_MS = 60_000;
 const SCENE_FUSION_ECHO_HASH_TIMEOUT_MS = 20_000;
 const SCENE_FUSION_ECHO_HASH_THRESHOLD = 8;
 const SCENE_FUSION_REVIEW_TIMEOUT_MS = 25_000;
@@ -236,41 +236,6 @@ function isSceneFusionReviewRejectError(message: string): boolean {
   );
 }
 
-function buildPreRmbgCandidateUrls(request: Request): string[] {
-  const urls: string[] = [];
-  const requestUrl = new URL(request.url);
-  const requestHost = requestUrl.hostname.toLowerCase();
-  const requestProtocol = requestUrl.protocol.replace(":", "");
-  if (!(requestProtocol === "https" && (requestHost === "localhost" || requestHost === "127.0.0.1"))) {
-    urls.push(new URL("/api/rmbg", request.url).toString());
-  }
-
-  const host = request.headers.get("host")?.trim();
-  const protoHint = request.headers
-    .get("x-forwarded-proto")
-    ?.split(",")[0]
-    ?.trim()
-    .toLowerCase();
-  const protocol = protoHint === "https" || protoHint === "http" ? protoHint : requestUrl.protocol.replace(":", "");
-
-  if (host) {
-    const normalizedHost = host.split(":")[0]?.toLowerCase() || "";
-    const isLocalHost = normalizedHost === "localhost" || normalizedHost === "127.0.0.1";
-    if (!(protocol === "https" && isLocalHost)) {
-      urls.push(`${protocol}://${host}/api/rmbg`);
-    }
-    if (isLocalHost) {
-      urls.push(`http://${host}/api/rmbg`);
-    }
-  }
-
-  const localPort = requestUrl.port || process.env.PORT || "3125";
-  urls.push(`http://127.0.0.1:${localPort}/api/rmbg`);
-  urls.push(`http://localhost:${localPort}/api/rmbg`);
-
-  return Array.from(new Set(urls));
-}
-
 function normalizeUrlForCompare(input: string): string {
   try {
     const parsed = new URL(input);
@@ -988,102 +953,6 @@ async function getSceneFusionConfig() {
   };
 }
 
-async function preprocessProductImageWithRmbg(
-  request: Request,
-  requestId: string,
-  productImageUrl: string,
-  preRmbgEnabled: boolean
-): Promise<{
-  productImageUrl: string;
-  usedPreRmbg: boolean;
-  provider?: string;
-  reason?: string;
-}> {
-  if (!preRmbgEnabled) {
-    return {
-      productImageUrl,
-      usedPreRmbg: false,
-      reason: "disabled_by_config",
-    };
-  }
-
-  const cookie = request.headers.get("cookie");
-  if (!cookie) {
-    return {
-      productImageUrl,
-      usedPreRmbg: false,
-      reason: "missing_cookie",
-    };
-  }
-
-  const candidateUrls = buildPreRmbgCandidateUrls(request);
-  let lastReason = "no_candidate_url";
-
-  logger.info("pre_rmbg_started", {
-    requestId,
-    candidateCount: candidateUrls.length,
-  });
-
-  for (const rmbgUrl of candidateUrls) {
-    const controller = new AbortController();
-    const timeoutId = setTimeout(() => controller.abort(), SCENE_FUSION_PRE_RMBG_TIMEOUT_MS);
-    try {
-      const response = await fetch(rmbgUrl, {
-        method: "POST",
-        headers: {
-          "Content-Type": "application/json",
-          cookie,
-        },
-        body: JSON.stringify({
-          imageUrl: productImageUrl,
-          prompt: "场景裂变预处理-抠图",
-          skipGallerySave: true,
-        }),
-        signal: controller.signal,
-      });
-
-      const payload = await response.json().catch(() => null) as Record<string, unknown> | null;
-
-      if (!response.ok) {
-        lastReason = `request_failed_${response.status}`;
-        logger.warn("pre_rmbg_candidate_failed", {
-          requestId,
-          status: response.status,
-          detail: payload?.detail || payload?.error || "unknown",
-        });
-        continue;
-      }
-
-      const cleanedUrl = String(payload?.original_url || payload?.thumbnail_url || "").trim();
-      if (!cleanedUrl || cleanedUrl === productImageUrl) {
-        lastReason = cleanedUrl ? "same_as_source" : "empty_result";
-        logger.warn("pre_rmbg_candidate_invalid", {
-          requestId,
-          reason: lastReason,
-        });
-        continue;
-      }
-
-      return {
-        productImageUrl: cleanedUrl,
-        usedPreRmbg: true,
-        provider: String(payload?.provider || "unknown"),
-      };
-    } catch (error) {
-      lastReason = error instanceof Error ? error.message : "exception";
-      logger.warn("pre_rmbg_candidate_exception", error, { requestId });
-    } finally {
-      clearTimeout(timeoutId);
-    }
-  }
-
-  return {
-    productImageUrl,
-    usedPreRmbg: false,
-    reason: lastReason,
-  };
-}
-
 /**
  * 创建缩略图
  */
@@ -2436,12 +2305,13 @@ export async function POST(request: Request) {
       productImageUrl = await uploadBase64ToS3(productImage, "scene-fusion-product");
     }
     const shouldForcePreRmbg = resolvedSceneMode === "random-bg";
-    const preprocessedProduct = await preprocessProductImageWithRmbg(
+    const preprocessedProduct = await preprocessProductImageWithRmbg({
       request,
       requestId,
+      userId: session.user.id,
       productImageUrl,
-      shouldForcePreRmbg ? true : config.preRmbgEnabled
+      preRmbgEnabled: shouldForcePreRmbg ? true : config.preRmbgEnabled,
-    );
+    });
     const fusionProductImageUrl = preprocessedProduct.productImageUrl;
     logger.info("pre_rmbg_resolved", {
       requestId,

app/canvas/[id]/CanvasEditorLegacyPageClient.tsx

@@ -5196,6 +5196,7 @@ export default function CanvasEditorLegacyPage({
       }
 
       try {
+        const beforeRead = useCanvasStore.getState();
         const revisionResponse = await fetch(`/api/canvas/${id}/revision`, {
           cache: "no-store",
         });
@@ -5216,7 +5217,11 @@ export default function CanvasEditorLegacyPage({
         }
 
         const result = await canvasService.getProject(id);
-        if (cancelled || canvasRemoteOperationActive.current || !result.success || !result.data) return;
+        const current = useCanvasStore.getState();
+        if (
+          cancelled || canvasRemoteOperationActive.current || !result.success || !result.data ||
+          current.projectId !== id || current.nodes !== beforeRead.nodes || current.edges !== beforeRead.edges
+        ) return;
         useCanvasStore.getState().markAgentOperationRefresh();
         hydrateCanvasProject(result.data);
         lastLocalCanvasMutationAtRef.current = Date.now();

app/canvas/[id]/style-pro/page.tsx

@@ -48,8 +48,13 @@ export default function CanvasStyleProPage() {
       const canvasData = result.data.canvasData;
       const latestState = useCanvasStore.getState();
       setProject(result.data.id, result.data.title);
-      if (latestState.nodes.length === 0 && latestState.edges.length === 0) {
+      if (
+        latestState.projectId !== id ||
+        (latestState.nodes.length === 0 && latestState.edges.length === 0)
+      ) {
         loadCanvas(canvasData);
+        const revision = String(result.data.updatedAt || "");
+        useCanvasStore.getState().setCanvasRevision(revision, revision);
         return;
       }
 

components/canvas/CanvasChatPanel.tsx

@@ -67,6 +67,7 @@ import { toast } from "sonner";
 import { useCanvasStore } from "@/store/canvas";
 import { cn } from "@/lib/utils";
 import { getGatewayErrorPageMessage } from "@/lib/request-error";
+import { findImageGenerationFailure } from "@/lib/canvas/image-generation-status";
 import { fetcher, fetchWithErrorHandlers, generateUUID } from "@/lib/utils";
 import {
   fetchUploadWithRetry,
@@ -3340,6 +3341,7 @@ export function CanvasChatPanel({
   const activeChatIdRef = useRef<string>(requestedChatSessionId || chatId);
   const activeMessagesRef = useRef<ChatMessage[]>([]);
   const inFlightChatIdRef = useRef<string | null>(null);
+  const imageGenerationUserMessageIdsRef = useRef<Record<string, string>>({});
   const inFlightRawChatIdRef = useRef<string | null>(null);
   const [chatSessions, setChatSessions] = useState<CanvasChatSession[]>([]);
   const [isSessionMenuOpen, setIsSessionMenuOpen] = useState(false);
@@ -3642,17 +3644,20 @@ export function CanvasChatPanel({
 
   const setStreamImageGenerationStateForChat = useCallback(
     (chatSessionId: string, next: ImageGenerationStatusStreamPayload | null) => {
+      const userMessageId = imageGenerationUserMessageIdsRef.current[chatSessionId];
+      if (next?.userMessageId && userMessageId && next.userMessageId !== userMessageId) return;
       setStreamImageGenerationStateByChatId((prev) => ({
         ...prev,
-        [chatSessionId]: next,
+        [chatSessionId]: next ? { ...next, userMessageId: next.userMessageId || userMessageId } : null,
       }));
     },
     []
   );
 
-  const clearStreamImageGenerationStateForChat = useCallback((chatSessionId: string) => {
+  const clearStreamImageGenerationStateForChat = useCallback((chatSessionId: string, preserveFailure = false) => {
     setStreamImageGenerationStateByChatId((prev) => {
       if (!(chatSessionId in prev)) return prev;
+      if (preserveFailure && prev[chatSessionId]?.phase === "failed") return prev;
       const next = { ...prev };
       delete next[chatSessionId];
       return next;
@@ -6089,7 +6094,7 @@ export function CanvasChatPanel({
   const activeComposerMode = unifiedImageAgent && (rawComposerMode === "image" || rawComposerMode === "video")
     ? "agent" : rawComposerMode;
   const isImageAgentComposer = unifiedImageAgent && activeComposerMode === "agent";
-  const [imageAgentEnabled, setImageAgentEnabled] = useState(false);
+  const [imageAgentEnabled, setImageAgentEnabled] = useState(true);
   const imageAgentEnabledRef = useRef(imageAgentEnabled);
   imageAgentEnabledRef.current = imageAgentEnabled;
   const isVideoToolbarDark = isVideoWorkspace || activeComposerMode === "video";
@@ -8018,6 +8023,8 @@ export function CanvasChatPanel({
       api: "/api/chat",
       fetch: fetchWithErrorHandlers,
       async prepareSendMessagesRequest(request) {
+        const userMessageId = request.messages.findLast((item) => item.role === "user")?.id;
+        if (userMessageId) imageGenerationUserMessageIdsRef.current[request.id] = userMessageId;
         // 从 canvas-{uuid} 格式中提取纯 UUID，后端 schema 要求纯 UUID
         const rawId = request.id.startsWith('canvas-') 
           ? request.id.replace('canvas-', '') 
@@ -8130,20 +8137,27 @@ export function CanvasChatPanel({
           const payload: ImageGenerationStatusStreamPayload =
             typeof dataPart.data === "string" ? JSON.parse(dataPart.data) : dataPart.data;
           if (!payload || typeof payload !== "object") return;
+          const userMessageId = imageGenerationUserMessageIdsRef.current[eventChatId];
+          if (payload.userMessageId && userMessageId && payload.userMessageId !== userMessageId) return;
           if (payload.phase === "completed") {
             setStreamImageGenerationStateForChat(eventChatId, {
               phase: "finalizing",
+              userMessageId: payload.userMessageId,
               providerType: payload.providerType,
               modelName: getAgentSafeModelName(payload.modelName),
               imageCount: Number(payload.imageCount || 0) || undefined,
             });
             window.setTimeout(() => {
+              if (payload.userMessageId && imageGenerationUserMessageIdsRef.current[eventChatId] !== payload.userMessageId) return;
               clearStreamImageGenerationStateForChat(eventChatId);
             }, 30_000);
             return;
           }
           setStreamImageGenerationStateForChat(eventChatId, {
             phase: payload.phase || "processing",
+            userMessageId: payload.userMessageId,
+            requestId: payload.requestId,
+            failure: payload.failure,
             providerType: payload.providerType,
             modelName: getAgentSafeModelName(payload.modelName),
             imageCount: Number(payload.imageCount || 0) || undefined,
@@ -8411,6 +8425,11 @@ export function CanvasChatPanel({
               )
             : false;
           const normalizedParts = Array.isArray(messageData.parts) ? messageData.parts : [];
+          const failureStatus = findImageGenerationFailure(
+            [{ role: messageData.role, parts: normalizedParts }],
+            imageGenerationUserMessageIdsRef.current[eventChatId],
+          );
+          if (failureStatus) setStreamImageGenerationStateForChat(eventChatId, failureStatus);
           const normalizedAttachments = Array.isArray(messageData.attachments)
             ? messageData.attachments
             : [];
@@ -8479,7 +8498,7 @@ export function CanvasChatPanel({
             (hasImageGenEndMarker || incomingImageUrls.length > 0 || incomingVideoUrls.length > 0) &&
             !shouldDeferClearForActiveMedia
           ) {
-            clearStreamImageGenerationStateForChat(eventChatId);
+            clearStreamImageGenerationStateForChat(eventChatId, true);
           }
 
           if (!isEventForActiveChat) {
@@ -9202,7 +9221,7 @@ export function CanvasChatPanel({
 
   useEffect(() => {
     const streamState = streamImageGenerationStateByChatId[activeChatId];
-    if (!rawChatId || !streamState) return;
+    if (!rawChatId || !streamState || (streamState.phase === "failed" && streamState.failure?.outcome !== "unknown")) return;
 
     let cancelled = false;
     const poll = async () => {
@@ -9226,6 +9245,13 @@ export function CanvasChatPanel({
     const streamState = streamImageGenerationStateByChatId[activeChatId];
     if (!streamState || messages.length === 0) return;
 
+    const failure = findImageGenerationFailure(messages, streamState.userMessageId || "");
+    if (failure && streamState.phase !== "failed") {
+      setStreamImageGenerationStateForChat(activeChatId, failure);
+      return;
+    }
+    if (streamState.phase === "failed" && streamState.failure?.outcome !== "unknown") return;
+
     const lastUserIndex = [...messages]
       .map((message) => message.role)
       .lastIndexOf("user");
@@ -9242,8 +9268,7 @@ export function CanvasChatPanel({
         .join("\n");
       return (
         extractAssistantImageUrls(textContent).length > 0 ||
-        extractVideoUrls(textContent).length > 0 ||
+        extractVideoUrls(textContent).length > 0
-        /失败|超时|重试|error|failed/i.test(textContent)
       );
     });
 
@@ -9264,6 +9289,7 @@ export function CanvasChatPanel({
     messages,
     streamImageGenerationStateByChatId,
     clearStreamImageGenerationStateForChat,
+    setStreamImageGenerationStateForChat,
   ]);
 
   useEffect(() => {
@@ -13328,6 +13354,7 @@ export function CanvasChatPanel({
     });
     inFlightChatIdRef.current = activeChatId;
     inFlightRawChatIdRef.current = rawChatId;
+    imageGenerationUserMessageIdsRef.current[activeChatId] = userMessageId;
     clearStreamImageGenerationStateForChat(activeChatId);
     clearAgentProgressStateForChat(activeChatId);
     if (shouldShowOptimisticImageGeneration) {
@@ -15097,7 +15124,7 @@ export function CanvasChatPanel({
       !hasGenerationEnd &&
       Boolean(currentModel || activeComposerMode === "agent"));
   const hasActiveTypewriter = Object.keys(activeTypingSections).length > 0;
-  const shouldRenderImageLoading = shouldShowImageLoading && !hasActiveTypewriter;
+  const shouldRenderImageLoading = shouldShowImageLoading && streamImageGenerationState?.phase !== "failed" && !hasActiveTypewriter;
   const loadingImageCount = streamImageGenerationState?.imageCount || imageParams.imageCount || 1;
   const loadingProviderType =
     streamImageGenerationState?.providerType ||
@@ -15160,9 +15187,9 @@ export function CanvasChatPanel({
       phase === "queued"
         ? "等待开始生成"
         : phase === "finalizing"
-          ? "正在润饰细节"
+          ? "正在保存生成结果"
           : phase === "failed"
-            ? "生成失败"
+            ? streamState.failure?.message || "生成失败"
             : "正在创建图片";
     const status = phase === "failed" ? "failed" : "generating";
     const currentNodes = useCanvasStore.getState().nodes;
@@ -15218,14 +15245,10 @@ export function CanvasChatPanel({
       canvasGenerationPlaceholder: true,
       chatId: activeChatId,
       detailProgressLabel: label,
-      generationProgress:
+      generationProgress: undefined,
-        phase === "queued"
+      generationFailure: streamState.failure,
-          ? 12
+      generationRequestId: streamState.requestId,
-          : phase === "finalizing"
+      generationUserMessageId: streamState.userMessageId,
-            ? 96
-            : phase === "failed"
-              ? 100
-              : undefined,
       modelName: streamState.modelName || currentModel?.displayName || undefined,
       providerType: streamState.providerType || currentModel?.providerType || undefined,
       placementMode: "anchored-generation",
@@ -15319,6 +15342,7 @@ export function CanvasChatPanel({
 
       if (
         message.role === "assistant" &&
+        !rawParts.some((part: any) => part.type === "data-imageGenerationStatus" && part.data?.failure) &&
         isInternalCanvasImageGenerationFailureText(cleanedParts)
       ) {
         return acc;

components/canvas/chat-panel/canvas-agent-stream.ts

@@ -152,16 +152,7 @@ export function shouldRetryCanvasViewOperationAfterRefresh(
   );
 }
 
-export type ImageGenerationStatusStreamPayload = {
+export type { ImageGenerationStatusStreamPayload } from "@/lib/canvas/image-generation-status";
-  phase?: "queued" | "processing" | "finalizing" | "failed" | "completed";
-  providerType?: string;
-  modelName?: string;
-  imageCount?: number;
-  queuePosition?: number;
-  sameModelRunningCount?: number;
-  concurrencyLimit?: number;
-  estimatedWaitMs?: number;
-};
 
 export type AgentTargetLockRefPreview = {
   url: string;

components/canvas/nodes/ImageNode.tsx

@@ -1,4 +1,6 @@
 "use client";
+import { CanvasPreviewImage } from "./image-node/canvas-preview-image";
+import { canvasImagePreviewWidth } from "@/lib/canvas/image-preview-width";
 import { isRetiredStorageUrl, RETIRED_STORAGE_MESSAGE } from "@/lib/storage/retired-storage";
 
 import {
@@ -2502,13 +2504,13 @@ export function ImageNode({
     const densityMultiplier = shouldUseHighFidelityDisplayImage ? 1.35 : 1.05;
     const minWidth = shouldUseHighFidelityDisplayImage ? 960 : 640;
     const maxWidth = shouldUseHighFidelityDisplayImage ? 4096 : 2600;
-    return Math.max(
+    return canvasImagePreviewWidth(Math.max(
       minWidth,
       Math.min(
         maxWidth,
         Math.round((node.size.width || 320) * zoomMultiplier * devicePixelRatio * densityMultiplier)
       )
-    );
+    ), maxWidth);
   }, [node.size.width, shouldUseHighFidelityDisplayImage, viewportZoom]);
   const displayImageQuality = shouldUseHighFidelityDisplayImage ? 92 : 88;
   const displayImageSrc = useMemo(
@@ -4683,106 +4685,44 @@ export function ImageNode({
       return;
     }
 
-    setIsCreatingDetachedResultNode(true);
+    if (!projectId || !runCanvasRemoteOperation) {
+      toast.error("画布还在加载，请稍后再试");
+      return;
+    }
+
+    setIsCreatingDetachedResultNode(false);
     setIsProcessing(true);
     const actionName = "框选抠图";
-    const newNodeId = addNode({
-      type: "image",
-      position: {
-        x: node.position.x + node.size.width + 20,
-        y: node.position.y,
-      },
-      size: { width: node.size.width, height: node.size.height },
-      data: {
-        src: "",
-        status: "generating",
-        prompt: `${actionName}处理中...`,
-        title: `${displayTitle}-${actionName}`,
-        originalSrc: data.src,
-        metadata: {
-          cropRect: boxCutoutSelection,
-          paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
-        },
-      },
-      connections: [node.id],
-    });
 
     try {
-      const result = await imageGenerationService.boxCutout({
+      const command = createCanvasCapabilityClientCommand({
-        imageUrl: data.src,
+        capabilityId: "image.box_cutout",
-        cropRect: boxCutoutSelection,
+        nodeIds: [node.id],
+        projectId,
+        source: "toolbar",
+        args: {
+          ...boxCutoutSelection,
           paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
-        sourceNodeId: node.id,
-      });
-
-      if (result.success && result.data?.url) {
-        updateNode(newNodeId, {
-          data: {
-            src: result.data.url,
-            status: "completed",
-            prompt: `${actionName}结果`,
-            title: `${displayTitle}-${actionName}`,
-            originalSrc: data.src,
-            metadata: {
-              cropRect: boxCutoutSelection,
-              cropRectApplied: result.data.cropRectApplied,
-              paddedCropRectApplied: result.data.paddedCropRectApplied,
-              paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
-              editMode: "box-cutout",
-            },
         },
       });
+      await runCanvasRemoteOperation(() => executeCanvasToolbarCapability(command));
       toast.success(`${actionName}完成`);
-      } else {
-        updateNode(newNodeId, {
-          data: {
-            src: "",
-            status: "failed",
-            prompt: `${actionName}失败`,
-            title: `${displayTitle}-${actionName}-失败`,
-            originalSrc: data.src,
-            metadata: {
-              cropRect: boxCutoutSelection,
-              paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
-            },
-          },
-        });
-        toast.error(result.error || `${actionName}失败`);
-      }
     } catch (error) {
       console.error("框选抠图失败:", error);
-      updateNode(newNodeId, {
+      toast.error(error instanceof Error ? error.message : `${actionName}失败`);
-        data: {
-          src: "",
-          status: "failed",
-          prompt: `${actionName}失败`,
-          title: `${displayTitle}-${actionName}-失败`,
-          originalSrc: data.src,
-          metadata: {
-            cropRect: boxCutoutSelection,
-            paddingRatio: BOX_CUTOUT_DEFAULT_PADDING_RATIO,
-          },
-        },
-      });
-      toast.error(`${actionName}失败，请重试`);
     } finally {
       setIsCreatingDetachedResultNode(false);
       setIsProcessing(false);
       resetBoxCutoutState();
     }
   }, [
-    addNode,
     boxCutoutSelection,
     data.src,
-    displayTitle,
     isProcessing,
     node.id,
-    node.position.x,
+    projectId,
-    node.position.y,
-    node.size.height,
-    node.size.width,
     resetBoxCutoutState,
-    updateNode,
+    runCanvasRemoteOperation,
   ]);
 
   const animateAddToChat = useCallback(async (previewUrl?: string) => {
@@ -8461,12 +8401,13 @@ export function ImageNode({
                     }}
                   >
                     <div className="absolute inset-0 bg-slate-50 dark:bg-zinc-900" />
-                    <img
+                    <CanvasPreviewImage
+                      sourceKey={data.src}
                       alt={displayTitle}
                       className="absolute inset-0 h-full w-full object-cover"
                       decoding="async"
                       draggable={false}
-                      loading="lazy"
+                      loading="eager"
                       onError={(event) => {
                         if (event.currentTarget.src !== buildImageFallbackUrl(data.src)) {
                           event.currentTarget.src = buildImageFallbackUrl(data.src);
@@ -8490,12 +8431,13 @@ export function ImageNode({
                     }}
                   >
                     <div className="absolute inset-0 bg-slate-50 dark:bg-zinc-900" />
-                    <img
+                    <CanvasPreviewImage
+                      sourceKey={compareSource}
                       alt={`${displayTitle}-原图`}
                       className="absolute inset-0 h-full w-full object-cover"
                       decoding="async"
                       draggable={false}
-                      loading="lazy"
+                      loading="eager"
                       onError={(event) => {
                         if (event.currentTarget.src !== buildImageFallbackUrl(compareSource)) {
                           event.currentTarget.src = buildImageFallbackUrl(compareSource);
@@ -8540,7 +8482,8 @@ export function ImageNode({
               </div>
             ) : (
               <>
-                <img
+                <CanvasPreviewImage
+                  sourceKey={data.src}
                   alt={displayTitle}
                   className={cn(
                     "h-full w-full bg-slate-50 object-contain dark:bg-zinc-900",
@@ -8552,7 +8495,7 @@ export function ImageNode({
                   )}
                   decoding="async"
                   draggable={false}
-                  loading="lazy"
+                  loading="eager"
                   onClick={
                     isThisNodePicking && !boxCutoutMode
                       ? handlePickerClick
@@ -9482,6 +9425,8 @@ export function ImageNode({
         ) : (
           <ImageNodeEmptyState
             detailProgressLabel={detailProgressLabel}
+            failure={data.metadata?.generationFailure}
+            requestId={data.metadata?.generationRequestId}
             fileInputRef={fileInputRef}
             generationProgress={generationProgress}
             onImageUpload={handleImageUpload}

components/canvas/nodes/image-node/canvas-preview-image.tsx

@@ -0,0 +1,32 @@
+"use client";
+
+import { forwardRef, type ImgHTMLAttributes, useState } from "react";
+
+type Props = Omit<ImgHTMLAttributes<HTMLImageElement>, "src"> & { src: string; sourceKey: string };
+
+export const CanvasPreviewImage = forwardRef<HTMLImageElement, Props>(function CanvasPreviewImage(
+  { src, sourceKey, onLoad, style, ...props }, ref,
+) {
+  const [displayed, setDisplayed] = useState({ sourceKey, src });
+  const visibleSrc = displayed.sourceKey === sourceKey ? displayed.src : src;
+  const sources = visibleSrc === src ? [src] : [visibleSrc, src];
+  return <>{sources.map(candidate => {
+    const visible = candidate === visibleSrc;
+    return <img
+      {...props}
+      key={candidate}
+      ref={visible ? ref : undefined}
+      src={candidate}
+      alt={visible ? props.alt : ""}
+      aria-hidden={visible ? props["aria-hidden"] : true}
+      style={visible ? style : { ...style, position: "absolute", inset: 0, opacity: 0, pointerEvents: "none" }}
+      onLoad={event => {
+        const image = event.currentTarget;
+        onLoad?.(event);
+        void image.decode().then(() => {
+          if (image.isConnected && candidate === src) setDisplayed({ sourceKey, src: candidate });
+        }).catch(() => undefined);
+      }}
+    />;
+  })}</>;
+});

components/canvas/nodes/image-node/image-node-empty-state.tsx

@@ -3,11 +3,14 @@
 import { AlertCircle, ImagePlus, Loader2 } from "lucide-react";
 import type React from "react";
 import { GenerationDotPlaceholder } from "@/components/generation-dot-placeholder";
+import type { RequestFailureDetails } from "@/lib/request-error";
 
 interface ImageNodeEmptyStateProps {
   detailProgressLabel?: string;
   fileInputRef: React.Ref<HTMLInputElement>;
   generationProgress?: number | null;
+  failure?: RequestFailureDetails;
+  requestId?: string;
   onImageUpload: (event: React.ChangeEvent<HTMLInputElement>) => void;
   onSelectFile: (event: React.MouseEvent<HTMLButtonElement>) => void;
   status?: string;
@@ -52,6 +55,8 @@ export function ImageNodeEmptyState({
   detailProgressLabel,
   fileInputRef,
   generationProgress,
+  failure,
+  requestId,
   onImageUpload,
   onSelectFile,
   status,
@@ -89,7 +94,7 @@ export function ImageNodeEmptyState({
   if (status === "failed") {
     const failedTitle = detailProgressLabel || "生成失败";
     return (
-      <div className="flex h-full w-full select-none flex-col items-center justify-center bg-[#fff7f8] px-6 text-center dark:bg-red-950/40">
+      <div role="alert" className="flex h-full w-full flex-col items-center justify-center overflow-auto bg-[#fff7f8] px-6 text-center dark:bg-red-950/40">
         <span className="mb-3 flex h-12 w-12 items-center justify-center rounded-[18px] border border-[#f2d7dd] bg-white text-[#d24f63] shadow-[0_0_0_1px_rgba(242,215,221,0.22)]">
           <AlertCircle className="h-5 w-5" />
         </span>
@@ -97,8 +102,9 @@ export function ImageNodeEmptyState({
           {failedTitle}
         </span>
         <span className="mt-1 text-xs text-[#b77480]">
-          {failedTitle.includes("上传") ? "请重新选择文件" : "请重新上传或再试一次"}
+          {failure?.recommendation || (failedTitle.includes("上传") ? "请重新选择文件" : "请查看对话中的错误原因和处理建议")}
         </span>
+        {requestId ? <span className="mt-2 select-text break-all text-xs text-[#b77480]">请求编号：{requestId}</span> : null}
       </div>
     );
   }

components/generation-dot-placeholder.tsx

@@ -1,6 +1,5 @@
 "use client";
 
-import { useEffect, useMemo, useState } from "react";
 import { BloubAvatar } from "@/components/bloub-avatar";
 import type { StateId } from "@/lib/bloub-official/states";
 import { cn } from "@/lib/utils";
@@ -26,193 +25,17 @@ interface GenerationDotPlaceholderProps {
 const PHASE_TITLES: Record<GenerationPhase, string> = {
   idle: "正在创建图片",
   queued: "等待开始生成",
-  processing: "生成初稿中",
+  processing: "等待模型返回图片",
-  finalizing: "正在润饰细节",
+  finalizing: "正在保存生成结果",
   failed: "生成失败",
   completed: "生成完成",
 };
 
-const GENERATION_STATUS_TITLES = [
-  "正在理解画面关系",
-  "正在读取参考图片",
-  "正在分析主体轮廓",
-  "正在识别关键元素",
-  "正在整理构图线索",
-  "正在确认画面比例",
-  "正在匹配视觉风格",
-  "正在提取材质细节",
-  "正在梳理光影方向",
-  "正在构建初始画面",
-  "正在生成第一版构图",
-  "正在安排主体位置",
-  "正在校准画面重心",
-  "正在补全背景层次",
-  "正在保持主体一致",
-  "正在优化边缘结构",
-  "正在调整透视关系",
-  "正在细化空间层次",
-  "正在增强画面清晰度",
-  "正在统一色彩倾向",
-  "正在检查参考一致性",
-  "正在处理局部细节",
-  "正在补充纹理信息",
-  "正在修正不自然区域",
-  "正在平衡明暗对比",
-  "正在优化产品质感",
-  "正在调整阴影落点",
-  "正在整理背景干扰",
-  "正在增强真实感",
-  "正在重绘细小结构",
-  "正在合成高清结果",
-  "正在检查主体完整性",
-  "正在优化画面边缘",
-  "正在处理反光细节",
-  "正在提升材质表现",
-  "正在微调构图节奏",
-  "正在清理多余噪点",
-  "正在强化视觉焦点",
-  "正在校正颜色偏差",
-  "正在保留参考特征",
-  "正在生成高分辨率版本",
-  "正在压实画面层次",
-  "正在修饰局部瑕疵",
-  "正在检查文字与图形",
-  "正在稳定画面结构",
-  "正在优化细节密度",
-  "正在完善背景过渡",
-  "正在增强主体质感",
-  "正在统一整体光感",
-  "正在检查比例关系",
-  "正在修正边缘锯齿",
-  "正在提升清晰观感",
-  "正在处理最后细节",
-  "正在准备预览结果",
-  "正在同步生成进度",
-  "正在确认输出尺寸",
-  "正在整理结果文件",
-  "正在校验图片可用性",
-  "正在生成最终预览",
-  "正在完成高清渲染",
-  "正在保存生成结果",
-  "正在写入画布节点",
-  "正在同步到对话框",
-  "正在检查结果完整性",
-  "正在收尾生成任务",
-  "正在等待服务商返回",
-  "正在保持连接状态",
-  "正在确认生成结果",
-  "正在拉取图片地址",
-  "正在准备展示图片",
-  "正在完成最后处理",
-  "正在刷新画布内容",
-  "正在整理图片信息",
-  "正在完成本次生成",
-  "正在即将展示结果",
-];
-
-const LONG_WAIT_TITLE_THRESHOLD_MS = 5 * 60 * 1000;
-const LONG_WAIT_STATUS_TITLES = [
-  "服务繁忙，排队处理中",
-  "高峰期生成较慢，请耐心等候",
-  "仍在保持连接，等待模型返回",
-  "结果返回后会自动展示",
-];
-const STATUS_TITLE_DURATIONS_MS = GENERATION_STATUS_TITLES.map((_, index) => {
-  const rhythm = [3600, 5200, 4100, 6100, 3300, 4700, 5700, 3900, 6800, 4400];
-  return rhythm[index % rhythm.length];
-});
-const TYPEWRITER_START_DELAY_MS = 120;
-const TYPEWRITER_BASE_STEP_MS = 46;
-
 function clampProgress(value: number) {
   if (!Number.isFinite(value)) return 0;
   return Math.max(0, Math.min(100, Math.round(value)));
 }
 
-function estimateProgress(phase: GenerationPhase, elapsedMs: number) {
-  if (phase === "completed" || phase === "failed") return 100;
-  if (phase === "finalizing") return 96;
-  if (phase === "queued") {
-    return clampProgress(6 + Math.min(12, elapsedMs / 3500));
-  }
-  if (phase === "processing") {
-    const eased = 1 - Math.exp(-elapsedMs / 85_000);
-    return clampProgress(18 + eased * 78);
-  }
-  return clampProgress(Math.min(8, elapsedMs / 1000));
-}
-
-function getStatusTitleState(elapsedMs: number, initialTitle?: string) {
-  const titles = initialTitle
-    ? [
-        initialTitle,
-        ...GENERATION_STATUS_TITLES.filter((item) => item !== initialTitle),
-      ]
-    : GENERATION_STATUS_TITLES;
-  const durations = initialTitle
-    ? [4200, ...STATUS_TITLE_DURATIONS_MS]
-    : STATUS_TITLE_DURATIONS_MS;
-
-  let cursor = Math.max(0, elapsedMs);
-  for (let index = 0; index < titles.length; index += 1) {
-    const duration = durations[index] || 4600;
-    if (cursor < duration) {
-      return {
-        elapsedInTitle: cursor,
-        index,
-        title:
-          titles[index] ||
-          titles[titles.length - 1] ||
-          PHASE_TITLES.processing,
-      };
-    }
-    cursor -= duration;
-  }
-
-  return {
-    elapsedInTitle: durations[durations.length - 1] || 4600,
-    index: titles.length - 1,
-    title: titles[titles.length - 1] || PHASE_TITLES.processing,
-  };
-}
-
-function getLongWaitTitleState(elapsedMs: number, initialTitle?: string) {
-  const titles = initialTitle
-    ? [
-        initialTitle,
-        ...LONG_WAIT_STATUS_TITLES.filter((item) => item !== initialTitle),
-      ]
-    : LONG_WAIT_STATUS_TITLES;
-  const elapsedAfterThreshold = Math.max(
-    0,
-    elapsedMs - LONG_WAIT_TITLE_THRESHOLD_MS
-  );
-  const duration = 7600;
-  const index = Math.floor(elapsedAfterThreshold / duration) % titles.length;
-
-  return {
-    elapsedInTitle: elapsedAfterThreshold % duration,
-    index,
-    title: titles[index] || titles[0] || PHASE_TITLES.processing,
-  };
-}
-
-function getTypewriterText(text: string, elapsedInTitle: number, index: number) {
-  const chars = Array.from(text);
-  if (chars.length === 0) return "";
-  const step = TYPEWRITER_BASE_STEP_MS + (index % 5) * 8;
-  const visibleCount = Math.max(
-    1,
-    Math.min(
-      chars.length,
-      Math.floor(
-        Math.max(0, elapsedInTitle - TYPEWRITER_START_DELAY_MS) / step
-      ) + 1
-    )
-  );
-  return chars.slice(0, visibleCount).join("");
-}
-
 function getBloubState(phase: GenerationPhase): StateId {
   if (phase === "failed") return "alert";
   if (phase === "completed") return "wink";
@@ -228,39 +51,10 @@ export function GenerationDotPlaceholder({
   showProgress = true,
   title,
 }: GenerationDotPlaceholderProps) {
-  const [elapsedMs, setElapsedMs] = useState(0);
+  const resolvedProgress = typeof progress === "number" && Number.isFinite(progress)
-
+    ? clampProgress(progress) : null;
-  useEffect(() => {
+  const resolvedTitle = title || PHASE_TITLES[phase];
-    const startedAt = Date.now();
-    const timer = window.setInterval(() => {
-      setElapsedMs(Date.now() - startedAt);
-    }, 90);
-    return () => window.clearInterval(timer);
-  }, [phase]);
-
-  const resolvedProgress = clampProgress(
-    typeof progress === "number" ? progress : estimateProgress(phase, elapsedMs)
-  );
-  const isLongWaitTitle =
-    (phase === "processing" || phase === "finalizing") &&
-    elapsedMs >= LONG_WAIT_TITLE_THRESHOLD_MS;
-  const statusTitleState = isLongWaitTitle
-    ? getLongWaitTitleState(elapsedMs, title)
-    : getStatusTitleState(elapsedMs, title);
-  const rotatingTitle = getTypewriterText(
-    statusTitleState.title,
-    statusTitleState.elapsedInTitle,
-    statusTitleState.index
-  );
-  const resolvedTitle =
-    phase === "processing" || phase === "finalizing"
-      ? rotatingTitle
-      : title || PHASE_TITLES[phase];
   const playSequence = phase === "processing" || phase === "finalizing";
-  const progressStyle = useMemo(
-    () => ({ width: `${resolvedProgress}%` }),
-    [resolvedProgress]
-  );
 
   return (
     <div
@@ -281,10 +75,6 @@ export function GenerationDotPlaceholder({
           )}
         >
           {resolvedTitle}
-          <span
-            aria-hidden="true"
-            className="ml-1 inline-block h-[1em] w-[0.08em] translate-y-[0.15em] animate-[generationCursorBlink_1s_steps(1,end)_infinite] bg-current"
-          />
         </div>
 
         <div className="flex min-h-0 flex-1 items-center justify-center py-3">
@@ -297,13 +87,13 @@ export function GenerationDotPlaceholder({
           />
         </div>
 
-        {showProgress ? (
+        {showProgress && phase !== "completed" ? (
           <div className="space-y-2">
             <div className="flex items-center justify-between text-[12px] font-medium text-[#7d838b] dark:text-zinc-400">
-              <span>{phase === "failed" ? "已停止" : "生成进度"}</span>
+              <span>{phase === "failed" ? "已停止" : resolvedProgress === null ? "等待结果，返回后自动展示" : "生成进度"}</span>
-              <span>{resolvedProgress}%</span>
+              {resolvedProgress !== null ? <span>{resolvedProgress}%</span> : null}
             </div>
-            <div className="h-1.5 overflow-hidden rounded-full bg-white/80 shadow-[inset_0_0_0_1px_rgba(0,0,0,0.035)] dark:bg-white/10 dark:shadow-none">
+            {resolvedProgress !== null ? <div role="progressbar" aria-valuenow={resolvedProgress} aria-valuemin={0} aria-valuemax={100} className="h-1.5 overflow-hidden rounded-full bg-white/80 shadow-[inset_0_0_0_1px_rgba(0,0,0,0.035)] dark:bg-white/10 dark:shadow-none">
               <div
                 className={cn(
                   "h-full rounded-full transition-[width] duration-700 ease-out",
@@ -311,25 +101,12 @@ export function GenerationDotPlaceholder({
                     ? "bg-[#c7ccd3] dark:bg-zinc-600"
                     : "bg-[#0a0a0c] dark:bg-[#3ecf8e]"
                 )}
-                style={progressStyle}
+                style={{ width: `${resolvedProgress}%` }}
               />
-            </div>
+            </div> : null}
           </div>
         ) : null}
       </div>
-
-      <style jsx>{`
-        @keyframes generationCursorBlink {
-          0%,
-          48% {
-            opacity: 1;
-          }
-          49%,
-          100% {
-            opacity: 0;
-          }
-        }
-      `}</style>
     </div>
   );
 }

components/image-annotator.tsx

@@ -918,9 +918,9 @@ 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
+      const input = /^https?:\/\//i.test(originalImageUrl)
-      const base64Data = await imageUrlToBase64(originalImageUrl);
+        ? { imageUrl: originalImageUrl }
-      logger.debug("rmbg_source_prepared", { base64Length: base64Data.length });
+        : { image_base64: await imageUrlToBase64(originalImageUrl) };
 
       // 调用抠图API
       const response = await fetch("/api/rmbg", {
@@ -929,7 +929,7 @@ export function ImageAnnotator({
           "Content-Type": "application/json",
         },
         body: JSON.stringify({
-          image_base64: base64Data,
+          ...input,
           prompt: "画图标注-抠图处理", // 可选：添加提示词
         }),
       });

components/image-generation-loading.tsx

@@ -41,45 +41,11 @@ const PHASE_HINT: Record<NonNullable<ImageGenerationLoadingProps["phase"]>, stri
   idle: "任务已创建，正在初始化生成参数。",
   queued: "任务已进入队列，请稍候。",
   processing: "模型正在生成图片，请稍候。",
-  finalizing: "图片已生成完成，正在同步到对话。",
+  finalizing: "图片已返回，正在保存并同步到对话。",
-  failed: "生成失败，请重试。",
+  failed: "本次处理已停止，请查看对话中的原因和建议。",
 };
 
-const LONG_PROCESSING_HINTS = [
-  "正在读取参考图与文字需求。",
-  "正在分析主体、场景和构图关系。",
-  "正在提取画面中的关键视觉特征。",
-  "正在确认图片比例和输出尺寸。",
-  "正在匹配当前模型的最佳生成参数。",
-  "正在把参考图信息提交给模型。",
-  "正在等待模型完成第一阶段推理。",
-  "正在生成初始画面结构。",
-  "正在保持主体特征和参考一致。",
-  "正在补全画面中的空间层次。",
-  "正在调整光影方向和明暗关系。",
-  "正在优化主体边缘与背景融合。",
-  "正在细化材质、纹理和局部细节。",
-  "正在减少画面噪点和不自然区域。",
-  "正在提升清晰度与整体质感。",
-  "正在检查生成结果的完整性。",
-  "正在处理高分辨率输出。",
-  "正在等待服务商返回最终图片。",
-  "正在保存图片并同步到对话。",
-  "正在准备把结果显示到画布。",
-];
 const LONG_WAIT_SECONDS = 5 * 60;
-const LONG_WAIT_HINT =
-  "服务繁忙，模型可能正在排队或自动尝试备用通道，请耐心等候，结果返回后会自动同步到画布。";
-
-function getLongProcessingHint(phase: NonNullable<ImageGenerationLoadingProps["phase"]>, elapsedSeconds: number) {
-  if (phase !== "processing" && phase !== "finalizing") return PHASE_HINT[phase];
-  if (elapsedSeconds >= LONG_WAIT_SECONDS) return LONG_WAIT_HINT;
-  const index = Math.min(
-    LONG_PROCESSING_HINTS.length - 1,
-    Math.floor(Math.max(0, elapsedSeconds) / 15)
-  );
-  return LONG_PROCESSING_HINTS[index];
-}
 
 function formatImageQueueWaitLabel(estimatedWaitMs?: number) {
   const numeric = Number(estimatedWaitMs || 0);
@@ -138,16 +104,8 @@ export const ImageGenerationLoading = memo(
     const isLongWait =
       resolvedElapsedSeconds >= LONG_WAIT_SECONDS &&
       (phase === "processing" || phase === "finalizing");
-    const estimateRangeLabel = isLongWait
+    const elapsedLabel = resolvedElapsedSeconds > 0 ? `已等待 ${resolvedElapsedSeconds}s` : "";
-      ? "单次最长约10分钟"
+    const phaseHint = PHASE_HINT[phase];
-      : providerType === "grsai-gpt-image"
-        ? "2～5分钟"
-        : "60～120秒";
-    const elapsedLabel =
-      resolvedElapsedSeconds > 0
-        ? `已等待 ${resolvedElapsedSeconds}s`
-        : `预计 ${estimateRangeLabel}`;
-    const phaseHint = getLongProcessingHint(phase, resolvedElapsedSeconds);
     const queueLine =
       phase === "queued" && Number.isFinite(queuePosition)
         ? Math.max(0, Number(queuePosition || 0)) > 0
@@ -189,12 +147,12 @@ export const ImageGenerationLoading = memo(
             }
             compact={count > 1}
             phase={phase}
-            title={isLongWait ? "服务繁忙，排队处理中" : undefined}
+            title={isLongWait && phase === "processing" ? "模型尚未返回结果，请勿重复提交" : undefined}
           />
 
           <div className="space-y-0.5 text-[#9aa3b2]">
             <div className="text-[13px] font-medium">
-              使用 {resolvedModelName} 生成图片，预计 {estimateRangeLabel}
+              使用 {resolvedModelName} 生成图片
             </div>
             {queueLine ? <div className="text-[13px]">{queueLine}</div> : null}
             {queueDetailLine ? <div className="text-[13px]">{queueDetailLine}</div> : null}

lib/ai/box-cutout/service.ts

@@ -4,6 +4,9 @@ import {
   executeRmbgJob,
   fetchImageBufferFromUrl,
 } from "@/lib/ai/rmbg/service";
+import { createLogger } from "@/lib/observability/logger";
+
+const logger = createLogger("box-cutout-service");
 
 export type NormalizedCropRect = {
   x: number;
@@ -13,6 +16,7 @@ export type NormalizedCropRect = {
 };
 
 export interface ExecuteBoxCutoutJobParams {
+  requestId?: string;
   userId: string;
   imageUrl: string;
   cropRect: Partial<NormalizedCropRect>;
@@ -143,6 +147,7 @@ function applyPadding(
 export async function executeBoxCutoutJob(
   params: ExecuteBoxCutoutJobParams,
 ): Promise<ExecuteBoxCutoutJobResult> {
+  const requestId = params.requestId || crypto.randomUUID();
   const imageUrl = String(params.imageUrl || "").trim();
   if (!imageUrl) {
     throw new BoxCutoutServiceError("缺少 imageUrl 参数", 400);
@@ -150,7 +155,7 @@ export async function executeBoxCutoutJob(
 
   const cropRect = sanitizeNormalizedCropRect(params.cropRect);
   if (!cropRect) {
-    throw new BoxCutoutServiceError("缺少有效的 cropRect 参数", 400);
+    throw new BoxCutoutServiceError("框选范围无效，请重新框选需要抠出的区域后提交。", 400);
   }
 
   const paddingRatio = normalizeBoxCutoutPaddingRatio(params.paddingRatio);
@@ -170,7 +175,7 @@ export async function executeBoxCutoutJob(
 
   const cropRectPixels = toPixelRect(cropRect, sourceWidth, sourceHeight);
   if (cropRectPixels.width < MIN_CROP_EDGE_PX || cropRectPixels.height < MIN_CROP_EDGE_PX) {
-    throw new BoxCutoutServiceError("框选区域过小，请重新框选", 400);
+    throw new BoxCutoutServiceError("框选区域过小，宽、高均须至少 24 像素，请扩大框选范围后重新提交。", 400);
   }
 
   const paddedCropRect = applyPadding(cropRect, paddingRatio);
@@ -184,7 +189,18 @@ export async function executeBoxCutoutJob(
     })
     .toBuffer();
 
+  logger.info("crop_prepared", {
+    requestId,
+    sourceNodeId: params.sourceNodeId,
+    sourceWidth,
+    sourceHeight,
+    cropRectPixels,
+    paddedCropRectPixels,
+    inputBytes: croppedBuffer.length,
+  });
+
   const result = await executeRmbgJob({
+    requestId,
     userId: params.userId,
     imageBuffer: croppedBuffer,
     imageBase64: croppedBuffer.toString("base64"),

lib/ai/canvas-agent-runtime/video-image-functions.ts

@@ -72,6 +72,7 @@ export async function processVideoCanvasImage(
     const result = await executeRmbgJob({
       userId: params.userId,
       imageBuffer: await fetchImageBufferFromUrl(imageUrl),
+      inputImageUrl: imageUrl,
       sourceImageUrl: imageUrl,
       prompt: params.prompt,
     });

lib/ai/rmbg/service.ts

@@ -8,6 +8,7 @@ import { executeConfiguredVip98kTask } from "@/lib/ai/vip98k-runtime";
 import { db } from "@/lib/db";
 import { generatedImage } from "@/lib/db/schema";
 import { createLogger } from "@/lib/observability/logger";
+import { trackRuntimeWork } from "@/lib/observability/active-work";
 import { uploadFile } from "@/lib/storage/service";
 
 const logger = createLogger("rmbg-service");
@@ -27,6 +28,7 @@ type RmbgConfig = {
 };
 
 export type ExecuteRmbgJobParams = {
+  requestId?: string;
   userId: string;
   imageBuffer: Buffer;
   imageBase64?: string;
@@ -35,6 +37,8 @@ export type ExecuteRmbgJobParams = {
   chatId?: string | null;
   messageId?: string | null;
   skipGallerySave?: boolean;
+  // 仅当 imageBuffer 与 URL 对应的输入文件一致时提供。
+  inputImageUrl?: string | null;
   sourceImageUrl?: string | null;
 };
 
@@ -53,7 +57,7 @@ export class RmbgServiceError extends Error {
   detail?: string;
 
   constructor(message: string, status = 500, detail?: string) {
-    super(message);
+    super(detail && detail !== message ? `${message}：${detail}` : message);
     this.name = "RmbgServiceError";
     this.status = status;
     this.detail = detail;
@@ -61,7 +65,11 @@ export class RmbgServiceError extends Error {
 }
 
 const sleep = (ms: number) => new Promise((resolve) => setTimeout(resolve, ms));
+// https://picwish.cn/background-removal-api-doc
 const AOS_MAX_RESOLUTION = 4096;
+const AOS_MAX_INPUT_BYTES = 50 * 1024 * 1024;
+// The shared AOS state -5 documents a separate limit for image_url downloads.
+const AOS_MAX_URL_INPUT_BYTES = 30 * 1024 * 1024;
 const AOS_CREATE_TIMEOUT_MS = 120_000;
 const AOS_POLL_TIMEOUT_MS = 60_000;
 const AOS_DOWNLOAD_TIMEOUT_MS = 60_000;
@@ -147,6 +155,18 @@ const withTimeout = async <T,>(
   }
 };
 
+async function readAosResult<T>(read: (signal: AbortSignal) => Promise<T>, timeoutMs: number): Promise<T> {
+  for (let attempt = 0; ; attempt++) {
+    try {
+      return await withTimeout(read, timeoutMs);
+    } catch (error) {
+      const name = error instanceof Error ? error.name : "";
+      if (attempt >= 2 || (name !== "TypeError" && name !== "AbortError")) throw error;
+      await sleep(1000 * (attempt + 1));
+    }
+  }
+}
+
 function getAosFriendlyErrorMessage(detail: string): string | null {
   const resolutionMatch = detail.match(/resolution excess,\s*width=(\d+),\s*height=(\d+)/i);
   if (resolutionMatch) {
@@ -164,52 +184,44 @@ function getAosFriendlyErrorMessage(detail: string): string | null {
 async function prepareImageForAos(
   imageBuffer: Buffer
 ): Promise<{ buffer: Buffer; mimeType: string; filename: string }> {
+  if (imageBuffer.length > AOS_MAX_INPUT_BYTES) {
+    throw new RmbgServiceError(
+      `抠图参考图文件大小超限（${(imageBuffer.length / 1024 / 1024).toFixed(2)} MB），当前 AOS 上游最大支持 50 MB。`,
+      400
+    );
+  }
+
+  let metadata: import("sharp").Metadata;
   try {
     const sharp = await import("sharp");
-    const image = sharp.default(imageBuffer);
+    metadata = await sharp.default(imageBuffer, { limitInputPixels: false }).metadata();
-    const metadata = await image.metadata();
+  } catch (error) {
-    const width = metadata.width;
+    // AOS also accepts BMP/RAW/RGB formats that Sharp cannot identify.
-    const height = metadata.height;
+    logger.warn("aos_image_metadata_unavailable", error);
-    const format = (metadata.format || "png").toLowerCase();
+    return { buffer: imageBuffer, mimeType: "application/octet-stream", filename: "image" };
+  }
 
+  const { width, height } = metadata;
+  if (width && height && (width > AOS_MAX_RESOLUTION || height > AOS_MAX_RESOLUTION)) {
+    throw new RmbgServiceError(
+      `抠图参考图分辨率超限（${width}×${height} 像素），当前 AOS 上游要求宽、高均不超过 ${AOS_MAX_RESOLUTION} 像素。`,
+      400
+    );
+  }
+
+  const format = metadata.format || "";
+  if (["gif", "svg", "heif", "avif", "jp2", "jxl"].includes(format)) {
+    const name = format === "heif" ? "HEIF/AVIF" : format.toUpperCase();
+    throw new RmbgServiceError(`抠图参考图格式不支持（${name}），当前 AOS 上游不支持此格式。`, 400);
+  }
   const ext = format === "jpeg" ? "jpg" : format;
-    const filenameExt =
-      ext === "jpg" || ext === "png" || ext === "webp" || ext === "tiff" ? ext : "png";
-    const mimeType =
-      ext === "jpg"
-        ? "image/jpeg"
-        : ext === "webp"
-          ? "image/webp"
-          : ext === "tiff"
-            ? "image/tiff"
-            : "image/png";
-
-    if (!width || !height || (width <= AOS_MAX_RESOLUTION && height <= AOS_MAX_RESOLUTION)) {
   return {
     buffer: imageBuffer,
-        mimeType,
+    mimeType: format ? `image/${format}` : "application/octet-stream",
-        filename: `image.${filenameExt}`,
+    filename: ext ? `image.${ext}` : "image",
   };
 }
 
-    const resizedBuffer = await image
-      .resize(AOS_MAX_RESOLUTION, AOS_MAX_RESOLUTION, {
-        fit: "inside",
-        withoutEnlargement: true,
-      })
-      .toBuffer();
-
-    return {
-      buffer: resizedBuffer,
-      mimeType,
-      filename: `image.${filenameExt}`,
-    };
-  } catch (error) {
-    logger.warn("aos_image_preprocess_failed", error);
-    return { buffer: imageBuffer, mimeType: "image/png", filename: "image.png" };
-  }
-}
-
 async function processWithRMBG(
   imageBase64: string,
   config: { apiUrl: string; apiKey?: string }
@@ -369,20 +381,38 @@ async function processWithAosSegmentation(
     foregroundType?: "" | "person" | "object" | "stamp";
     crop?: 0 | 1;
     format?: "png" | "jpg";
+    inputImageUrl?: string | null;
+    requestId?: string;
   }
 ): Promise<{ success: boolean; imageBuffer?: Buffer; processing_time?: number; error?: string }> {
   const startTime = Date.now();
   const baseUrl = (config.apiBaseUrl || "https://techsz.aoscdn.com").replace(/\/+$/, "");
   const createUrl = `${baseUrl}/api/tasks/visual/segmentation`;
   const headers = { "X-API-KEY": config.apiKey };
+  let stage = "create";
+  let providerTaskId: string | undefined;
+  const sourceImage = await prepareImageForAos(imageBuffer);
 
   try {
-    const normalizedImage = await prepareImageForAos(imageBuffer);
     const createForm = new FormData();
-    const imageBlob = new Blob([new Uint8Array(normalizedImage.buffer)], {
+    let publicSourceUrl: string | null = null;
-      type: normalizedImage.mimeType,
+    if (config.inputImageUrl && imageBuffer.length <= AOS_MAX_URL_INPUT_BYTES) {
+      try {
+        const source = new URL(config.inputImageUrl);
+        const cdn = new URL(process.env.NEXT_PUBLIC_CANVAS_CDN_ORIGIN || "");
+        if (["http:", "https:"].includes(source.protocol) && source.hostname === cdn.hostname) {
+          publicSourceUrl = source.toString();
+        }
+      } catch { /* Uploaded files and other sources use the file API. */ }
+    }
+    if (publicSourceUrl) {
+      createForm.append("image_url", publicSourceUrl);
+    } else {
+      const imageBlob = new Blob([new Uint8Array(sourceImage.buffer)], {
+        type: sourceImage.mimeType,
       });
-    createForm.append("image_file", imageBlob, normalizedImage.filename);
+      createForm.append("image_file", imageBlob, sourceImage.filename);
+    }
     createForm.append("sync", "0");
     createForm.append("return_type", "1");
     createForm.append("output_type", "2");
@@ -392,6 +422,9 @@ async function processWithAosSegmentation(
       createForm.append("type", config.foregroundType);
     }
 
+    const createStartedAt = Date.now();
+    logger.info("aos_task_create_started", { requestId: config.requestId, sourceMode: publicSourceUrl ? "url" : "file", inputBytes: imageBuffer.length, uploadBytes: publicSourceUrl ? 0 : sourceImage.buffer.length });
+
     const createResponse = await withTimeout(
       (signal) =>
         fetch(createUrl, {
@@ -411,28 +444,37 @@ async function processWithAosSegmentation(
       });
       return {
         success: false,
-        error: `AOS任务创建失败: ${createPayload?.message || createResponse.statusText}`,
+        error: `AOS任务创建失败（HTTP ${createResponse.status}）: ${createPayload?.message || createResponse.statusText}`,
       };
     }
 
     const taskId = createPayload.data.task_id as string;
+    providerTaskId = taskId;
+    logger.info("aos_task_created", { requestId: config.requestId, taskId, createMs: Date.now() - createStartedAt });
     const taskUrl = `${createUrl}/${taskId}`;
     const maxPollCount = 60;
 
     for (let pollCount = 0; pollCount < maxPollCount; pollCount += 1) {
       await sleep(1000);
+      stage = "poll";
 
-      const pollResponse = await withTimeout(
+      const pollResponse = await readAosResult(
-        (signal) =>
+        async (signal) => {
-          fetch(taskUrl, {
+          const response = await fetch(taskUrl, {
             method: "GET",
             headers,
             signal,
-          }),
+          });
+          const payload = await response.json().catch((error) => {
+            if (error instanceof Error && error.name !== "SyntaxError") throw error;
+            return null;
+          });
+          return { ok: response.ok, status: response.status, statusText: response.statusText, payload };
+        },
         AOS_POLL_TIMEOUT_MS
       );
 
-      const pollPayload = await pollResponse.json().catch(() => null);
+      const pollPayload = pollResponse.payload;
       if (!pollResponse.ok || !pollPayload?.data) {
         logger.warn("aos_task_poll_failed", {
           hasPayload: pollPayload != null,
@@ -440,7 +482,7 @@ async function processWithAosSegmentation(
         });
         return {
           success: false,
-          error: `AOS任务查询失败: ${pollPayload?.message || pollResponse.statusText}`,
+          error: `AOS任务查询失败（HTTP ${pollResponse.status}，任务 ${taskId}）: ${pollPayload?.message || pollResponse.statusText}`,
         };
       }
 
@@ -454,12 +496,15 @@ async function processWithAosSegmentation(
           pollCount,
           taskId,
         });
-        const imageResponse = await withTimeout(
+        stage = "download";
-          (signal) =>
+        const imageResponse = await readAosResult(
-            fetch(imageUrl, {
+          async (signal) => {
+            const response = await fetch(imageUrl, {
               method: "GET",
               signal,
-            }),
+            });
+            return { ok: response.ok, status: response.status, statusText: response.statusText, buffer: response.ok ? Buffer.from(await response.arrayBuffer()) : null };
+          },
           AOS_DOWNLOAD_TIMEOUT_MS
         );
 
@@ -470,11 +515,11 @@ async function processWithAosSegmentation(
           });
           return {
             success: false,
-            error: `AOS结果下载失败: ${imageResponse.status} ${imageResponse.statusText}`,
+            error: `AOS结果下载失败（HTTP ${imageResponse.status}，任务 ${taskId}）: ${imageResponse.statusText}`,
           };
         }
 
-        const resultBuffer = Buffer.from(await imageResponse.arrayBuffer());
+        const resultBuffer = imageResponse.buffer!;
         return {
           success: true,
           imageBuffer: resultBuffer,
@@ -490,19 +535,30 @@ async function processWithAosSegmentation(
         });
         return {
           success: false,
-          error: `AOS任务失败: ${errMessage || stateDetail || pollPayload?.message || "状态异常"}`,
+          error: `AOS任务失败（状态 ${state}，任务 ${taskId}）: ${errMessage || stateDetail || pollPayload?.message || "未提供详情"}`,
         };
       }
     }
 
-    logger.warn("aos_task_timeout", { maxPollCount });
+    logger.warn("aos_task_timeout", { requestId: config.requestId, taskId, maxPollCount });
-    return { success: false, error: "AOS任务超时（最多60秒）" };
+    return { success: false, error: `AOS查询任务超时，结果尚未确认（任务 ${taskId}）` };
   } catch (error) {
     if (error instanceof Error && error.name === "AbortError") {
-      return { success: false, error: "AOS请求超时，请稍后重试" };
+      logger.warn("aos_request_timeout", { requestId: config.requestId, stage, taskId: providerTaskId, inputBytes: imageBuffer.length });
+      const message = stage === "create"
+        ? "AOS创建任务超时（120秒），结果尚未确认"
+        : stage === "poll"
+          ? `AOS查询任务超时，结果尚未确认（任务 ${providerTaskId}）`
+          : `AOS结果下载超时，任务已完成（任务 ${providerTaskId}）`;
+      return { success: false, error: message };
     }
-    logger.warn("aos_provider_request_error", error);
+    logger.warn("aos_provider_request_error", error, { requestId: config.requestId, stage, taskId: providerTaskId });
-    return { success: false, error: error instanceof Error ? error.message : "未知错误" };
+    const detail = error instanceof Error ? error.message : "未知错误";
+    return { success: false, error: stage === "create"
+      ? `AOS创建任务连接失败，结果尚未确认：${detail}`
+      : stage === "poll"
+        ? `AOS查询任务连接失败，结果尚未确认（任务 ${providerTaskId}）：${detail}`
+        : `AOS结果下载连接失败，任务已完成（任务 ${providerTaskId}）：${detail}` };
   }
 }
 
@@ -599,8 +655,15 @@ export async function fetchImageBufferFromUrl(imageUrl: string): Promise<Buffer>
 
 export async function executeRmbgJob(
   params: ExecuteRmbgJobParams
+): Promise<ExecuteRmbgJobResult> {
+  return trackRuntimeWork(() => runRmbgJob(params));
+}
+
+async function runRmbgJob(
+  params: ExecuteRmbgJobParams
 ): Promise<ExecuteRmbgJobResult> {
   const {
+    requestId = crypto.randomUUID(),
     userId,
     imageBuffer,
     imageBase64 = imageBuffer.toString("base64"),
@@ -609,11 +672,13 @@ export async function executeRmbgJob(
     chatId = null,
     messageId = null,
     skipGallerySave = false,
+    inputImageUrl = null,
     sourceImageUrl = null,
   } = params;
 
   const { provider, config } = await getValidatedRmbgConfig();
   logger.info("job_started", {
+    requestId,
     hasChatId: Boolean(chatId),
     hasMessageId: Boolean(messageId),
     hasSourceImageUrl: Boolean(sourceImageUrl),
@@ -657,6 +722,8 @@ export async function executeRmbgJob(
       foregroundType: foregroundType ?? config.aosForegroundType ?? "",
       crop: config.aosCrop === 1 ? 1 : 0,
       format: config.aosFormat === "jpg" ? "jpg" : "png",
+      inputImageUrl,
+      requestId,
     });
 
     if (!result.success || !result.imageBuffer) {
@@ -793,6 +860,7 @@ export async function executeRmbgJob(
       }
 
       logger.info("job_completed", {
+        requestId,
         generatedImageId: savedImage.id,
         mediaAssetId,
         processingSeconds: Number(processingTime.toFixed(2)),
@@ -815,6 +883,7 @@ export async function executeRmbgJob(
   }
 
   logger.info("job_completed", {
+    requestId,
     processingSeconds: Number(processingTime.toFixed(2)),
     provider,
     savedToGallery: false,

lib/ai/runtime/agent-image-failover.ts

@@ -3,6 +3,7 @@ import { agentModelFault, type AgentModelFault } from "./agent-model-failover";
 export function agentImageFailurePolicy(error: unknown): { retry: boolean; pause: AgentModelFault | null } {
   const value = error as { message?: string; providerOutcomeUnknown?: boolean; status?: number; statusCode?: number } | null;
   const message = String(value?.message || "").toLowerCase();
+  if (value?.providerOutcomeUnknown || ["AbortError", "TimeoutError"].includes(String((error as { name?: string })?.name || ""))) return { retry: false, pause: null };
   // A submitted image job may still succeed. Retain its task and reconcile it;
   // never submit another paid job just because a poll/connection timed out.
   const unknown = value?.providerOutcomeUnknown || /request_outcome_unknown|may still be running|outcome.unknown|timed out|timeout|超时|fetch failed|econnreset|socket hang up/.test(message);

lib/ai/runtime/direct-agent-image-edit-executor.ts

@@ -516,6 +516,7 @@ export async function executeDirectAgentImageEditTool(
     const result = await executeRmbgJob({
       userId: params.userId,
       imageBuffer: sourceBuffer,
+      inputImageUrl: params.sourceImageUrl,
       prompt: params.requestTextContent || "抠图处理",
       chatId: params.chatId,
       messageId: params.messageId,

lib/ai/runtime/model-health.ts

@@ -13,7 +13,7 @@ import {
   isMediaInputFailure,
   isNonProviderRequestStatus,
 } from "@/lib/ai/runtime/request-failure-classification";
-import { isGatewayResponseTimeout, isProviderBalanceError, isRateLimitError } from "@/lib/request-error";
+import { getRequestFailureDetails, isGatewayResponseTimeout, isProviderBalanceError, isRateLimitError } from "@/lib/request-error";
 
 export type AiModelHealthEventType =
   | "success"
@@ -344,7 +344,12 @@ export function classifyAiModelHealthFailure(error: unknown): {
 }
 
 export function shouldFailoverAiModelError(error: unknown) {
-  if (error instanceof ProviderTaskUncertainError || isGatewayResponseTimeout(error)) return false;
+  if (
+    error instanceof ProviderTaskUncertainError ||
+    isGatewayResponseTimeout(error) ||
+    getRequestFailureDetails(error).outcome === "unknown" ||
+    ["AbortError", "TimeoutError"].includes(String((error as { name?: string })?.name || ""))
+  ) return false;
   const classification = classifyAiModelHealthFailure(error);
   const normalized = getErrorMessage(error).toLowerCase();
   const imageProviderTaskFailed =

lib/canvas/capabilities/headless-executor.ts

@@ -1,16 +1,16 @@
-import {
+import { executeBoxCutoutJob } from "@/lib/ai/box-cutout/service";
-  executeBoxCutoutJob,
-} from "@/lib/ai/box-cutout/service";
 import { executeExtendJob } from "@/lib/ai/extend/service";
 import { executeLayerSplitJob } from "@/lib/ai/layer-split/service";
 import { executeResizeJob } from "@/lib/ai/resize/service";
 import {
   executeRmbgJob,
   fetchImageBufferFromUrl,
+  RmbgServiceError,
 } from "@/lib/ai/rmbg/service";
 import type { CanvasCapabilityClientCommand } from "@/lib/canvas/capabilities/client-command";
 import type { CanvasCapabilityTarget } from "@/lib/canvas/capabilities/context";
 import { resolveCanvasRuntimeEndpoint } from "@/lib/canvas/capabilities/internal-endpoint";
+import { executeBoxCutoutPOST } from "@/lib/canvas/operations/box-cutout";
 import { generateCanvasImage } from "@/lib/canvas/generate-image";
 import { requestLongTaskResult } from "@/lib/client/long-task";
 import {
@@ -128,8 +128,10 @@ async function executeForTarget(
   if (command.capabilityId === "image.remove_background") {
     const imageBuffer = await fetchImageBufferFromUrl(target.sourceImageUrl);
     const result = await executeRmbgJob({
+      requestId: command.requestId,
       userId: params.userId,
       imageBuffer,
+      inputImageUrl: target.sourceImageUrl,
       sourceImageUrl: target.sourceImageUrl,
       prompt: prompt || "抠图处理",
       skipGallerySave: false,
@@ -185,8 +187,7 @@ async function executeForTarget(
   }
 
   if (command.capabilityId === "image.box_cutout") {
-    const result = await executeBoxCutoutJob({
+    const job = {
-      userId: params.userId,
       imageUrl: target.sourceImageUrl,
       sourceNodeId: target.nodeId,
       cropRect: {
@@ -197,13 +198,30 @@ async function executeForTarget(
       },
       paddingRatio: asFiniteNumber(command.args.paddingRatio),
       prompt: prompt || "框选抠图",
-    });
+    };
+    let result;
+    if (command.source === "toolbar") {
+      const response = await executeBoxCutoutPOST(new Request(params.requestUrl, {
+        method: "POST",
+        headers: { "Content-Type": "application/json", "X-Request-ID": command.requestId },
+        body: JSON.stringify(job),
+      }), params.userId);
+      result = await response.json();
+      if (!response.ok || !result.success) {
+        throw new RmbgServiceError(result.detail || result.message || result.error || "框选抠图未能完成", response.status);
+      }
+    } else {
+      result = await executeBoxCutoutJob({ ...job, requestId: command.requestId, userId: params.userId });
+    }
     return [{
       ...common,
       assetId: result.mediaAssetId || undefined,
       metadata: {
+        editMode: "box-cutout",
         cropRectApplied: result.cropRectApplied,
         paddedCropRectApplied: result.paddedCropRectApplied,
+        cropRectPixels: result.cropRectPixels,
+        paddedCropRectPixels: result.paddedCropRectPixels,
       },
       title: `${target.title}-框选抠图`,
       url: result.original_url,

lib/canvas/generate-image.ts

@@ -44,7 +44,7 @@ import {
 } from "@/lib/ai/runtime/model-health";
 import { uploadFile } from "@/lib/storage/service";
 import { isImageModelBalanceBlocked, resolveConfiguredImageBalanceFallback } from "@/lib/ai/runtime/image-balance";
-import { isProviderBalanceError } from "@/lib/request-error";
+import { getRequestFailureDetails, isProviderBalanceError } from "@/lib/request-error";
 import { normalizeLegacyAliyunStorageUrl } from "@/lib/storage/retired-storage";
 
 export interface CanvasLocalEditCompositeRegion {
@@ -5663,7 +5663,11 @@ export async function generateCanvasImage(
   }
 
   // An accepted or uncertain request must not start another paid model/variant.
-  if (caughtError instanceof ProviderTaskUncertainError) throw caughtError;
+  if (caughtError && (
+    caughtError instanceof ProviderTaskUncertainError ||
+    getRequestFailureDetails(caughtError).outcome === "unknown" ||
+    ["AbortError", "TimeoutError"].includes(String((caughtError as { name?: string })?.name || ""))
+  )) throw caughtError;
 
   const retryVariants = Array.isArray(request.retryVariants)
     ? request.retryVariants

lib/canvas/image-generation-status.ts

@@ -0,0 +1,34 @@
+import type { RequestFailureDetails } from "@/lib/request-error";
+
+export type ImageGenerationStatusStreamPayload = {
+  phase?: "queued" | "processing" | "finalizing" | "failed" | "completed";
+  userMessageId?: string;
+  requestId?: string;
+  failure?: RequestFailureDetails;
+  providerType?: string;
+  modelName?: string;
+  imageCount?: number;
+  queuePosition?: number;
+  sameModelRunningCount?: number;
+  concurrencyLimit?: number;
+  estimatedWaitMs?: number;
+};
+
+export function findImageGenerationFailure(
+  messages: { role: string; parts?: unknown[] }[],
+  userMessageId: string,
+): ImageGenerationStatusStreamPayload | null {
+  if (!userMessageId) return null;
+  for (const message of [...messages].reverse()) {
+    if (message.role !== "assistant") continue;
+    for (const part of message.parts || []) {
+      const candidate = part as { type?: string; data?: ImageGenerationStatusStreamPayload };
+      if (candidate.type !== "data-imageGenerationStatus") continue;
+      const status = candidate.data;
+      if (status?.phase === "failed" && status.failure && status.userMessageId === userMessageId) {
+        return status;
+      }
+    }
+  }
+  return null;
+}

lib/canvas/image-preview-width.ts

@@ -0,0 +1,5 @@
+const PREVIEW_WIDTHS = [640, 960, 1280, 1600, 2048, 2600, 3200, 4096];
+
+export function canvasImagePreviewWidth(width: number, maxWidth: number) {
+  return Math.min(maxWidth, PREVIEW_WIDTHS.find(value => value >= width) || 4096);
+}

lib/canvas/operations/box-cutout.ts

@@ -0,0 +1,96 @@
+import "server-only";
+import { NextResponse } from "next/server";
+
+import {
+  BoxCutoutServiceError,
+  executeBoxCutoutJob,
+} from "@/lib/ai/box-cutout/service";
+import { RmbgServiceError } from "@/lib/ai/rmbg/service";
+import { getPointsSystemConfig } from "@/lib/db/queries";
+import { prepareFeaturePointsCharge } from "@/lib/points/feature-charge";
+import { getImageToolCreditCost } from "@/lib/points/config";
+import { formatRequestFailure, getRequestFailureDetails } from "@/lib/request-error";
+
+type BoxCutoutRequest = {
+  imageUrl?: string;
+  cropRect?: {
+    x?: number;
+    y?: number;
+    width?: number;
+    height?: number;
+  };
+  paddingRatio?: number;
+  prompt?: string;
+  chatId?: string | null;
+  messageId?: string | null;
+  skipGallerySave?: boolean;
+  sourceNodeId?: string;
+};
+
+export async function executeBoxCutoutPOST(request: Request, userId: string) {
+  const requestId = request.headers.get("x-request-id") || crypto.randomUUID();
+  try {
+    if (!userId) {
+      return NextResponse.json({ success: false, error: "未授权，请先登录" }, { status: 401 });
+    }
+
+    const body = (await request.json()) as BoxCutoutRequest;
+    const rawImageUrl = String(body.imageUrl || "").trim();
+    if (!rawImageUrl) {
+      throw new BoxCutoutServiceError("缺少原图链接，请重新选择图片后提交。", 400);
+    }
+
+    const resolvedImageUrl = new URL(rawImageUrl, request.url).toString();
+    const pointsConfig = await getPointsSystemConfig();
+    const pointsCharge = await prepareFeaturePointsCharge({
+      userId,
+      unitCost: getImageToolCreditCost(pointsConfig, "box-cutout"),
+      reason: "image_box_cutout",
+      modelId: "box-cutout",
+      note: "框选抠图消耗积分",
+      pointsConfig,
+    });
+    if (!pointsCharge.ok) {
+      return NextResponse.json(pointsCharge.payload, { status: pointsCharge.status });
+    }
+
+    const result = await executeBoxCutoutJob({
+      requestId,
+      userId,
+      imageUrl: resolvedImageUrl,
+      cropRect: body.cropRect || {},
+      paddingRatio: body.paddingRatio,
+      prompt: body.prompt || "框选抠图",
+      chatId: body.chatId || null,
+      messageId: body.messageId || null,
+      skipGallerySave: body.skipGallerySave === true,
+      sourceNodeId: body.sourceNodeId,
+    });
+
+    if (pointsCharge.chargeable) {
+      try {
+        await pointsCharge.consume();
+      } catch (pointsError) {
+        console.error("[Points] Failed to consume box cutout points:", pointsError);
+      }
+    }
+
+    return NextResponse.json({ ...result, requestId });
+  } catch (error) {
+    const failure = getRequestFailureDetails(error, "框选抠图未能完成");
+    const payload = {
+      success: false,
+      error: formatRequestFailure(failure, requestId),
+      detail: error instanceof Error ? error.message : "框选抠图未能完成",
+      code: failure.code,
+      failure,
+      requestId,
+    };
+    if (error instanceof BoxCutoutServiceError || error instanceof RmbgServiceError) {
+      return NextResponse.json(payload, { status: error.status });
+    }
+
+    console.error("[BoxCutout] 处理失败:", error);
+    return NextResponse.json(payload, { status: 500 });
+  }
+}

lib/canvas/operations/rmbg.ts

@@ -9,9 +9,11 @@ import {
 import { getPointsSystemConfig } from "@/lib/db/queries";
 import { prepareFeaturePointsCharge } from "@/lib/points/feature-charge";
 import { getImageToolCreditCost } from "@/lib/points/config";
+import { formatRequestFailure, getRequestFailureDetails } from "@/lib/request-error";
 
 
 export async function executeRemoveBackgroundPOST(request: Request, trustedUserId: string) {
+  const requestId = request.headers.get("x-request-id") || crypto.randomUUID();
   try {
     const session = { user: { id: trustedUserId } };
     if (!session?.user?.id) {
@@ -27,6 +29,7 @@ export async function executeRemoveBackgroundPOST(request: Request, trustedUserI
     let messageId: string | null = null;
     let skipGallerySave = false;
     let sourceImageUrl: string | null = null;
+    let inputImageUrl: string | null = null;
 
     if (contentType.includes("application/json")) {
       const body = await request.json();
@@ -40,6 +43,7 @@ export async function executeRemoveBackgroundPOST(request: Request, trustedUserI
 
       if (imageUrl) {
         sourceImageUrl = String(imageUrl);
+        inputImageUrl = sourceImageUrl;
         imageBuffer = await fetchImageBufferFromUrl(sourceImageUrl);
       } else if (body.image_base64) {
         imageBase64 = String(body.image_base64);
@@ -94,6 +98,7 @@ export async function executeRemoveBackgroundPOST(request: Request, trustedUserI
     }
 
     const result = await executeRmbgJob({
+      requestId,
       userId: session.user.id,
       imageBuffer,
       imageBase64,
@@ -101,6 +106,7 @@ export async function executeRemoveBackgroundPOST(request: Request, trustedUserI
       chatId,
       messageId,
       skipGallerySave,
+      inputImageUrl,
       sourceImageUrl,
     });
 
@@ -114,22 +120,29 @@ export async function executeRemoveBackgroundPOST(request: Request, trustedUserI
 
     return NextResponse.json({
       success: true,
+      requestId,
       ...result,
     });
   } catch (error) {
     if (error instanceof RmbgServiceError) {
+      const failure = getRequestFailureDetails(error);
       return NextResponse.json(
         {
-          error: error.message,
+          success: false,
+          error: formatRequestFailure(failure, requestId),
           detail: error.detail || error.message,
+          code: failure.code,
+          failure,
+          requestId,
         },
         { status: error.status }
       );
     }
 
     console.error("[RMBG API] 处理错误:", error);
+    const failure = getRequestFailureDetails(error, "抠图请求未能完成");
     return NextResponse.json(
-      { error: "服务器内部错误", detail: error instanceof Error ? error.message : "未知错误" },
+      { success: false, error: formatRequestFailure(failure, requestId), detail: error instanceof Error ? error.message : "未知错误", code: failure.code, failure, requestId },
       { status: 500 }
     );
   }

lib/canvas/scale-adjust-product-lock.ts

@@ -40,22 +40,6 @@ function clamp(value: number, min: number, max: number) {
   return Math.min(max, Math.max(min, value));
 }
 
-async function executeScaleAdjustRmbgJob(
-  params: Parameters<typeof executeRmbgJob>[0]
-) {
-  let lastError: unknown;
-  for (let attempt = 1; attempt <= 3; attempt += 1) {
-    try {
-      return await executeRmbgJob(params);
-    } catch (error) {
-      lastError = error;
-      if (attempt === 3) break;
-      await new Promise((resolve) => setTimeout(resolve, attempt * 800));
-    }
-  }
-  throw lastError;
-}
-
 function rectToPixelBox(
   rect: CanvasScaleAdjustRect,
   sourceWidth: number,
@@ -220,7 +204,7 @@ async function buildPersonExclusionAlpha(params: {
   userId: string;
 }) {
   try {
-    const person = await executeScaleAdjustRmbgJob({
+    const person = await executeRmbgJob({
       foregroundType: "person",
       imageBuffer: params.sourceBuffer,
       prompt: "比例调整人物保护蒙版",
@@ -330,7 +314,7 @@ export async function buildScaleAdjustProductLockAssets(params: {
       .png({ compressionLevel: 6 })
       .toBuffer();
     semanticSourceCropBuffers.push(cropBuffer);
-    const subject = await executeScaleAdjustRmbgJob({
+    const subject = await executeRmbgJob({
       imageBuffer: cropBuffer,
       prompt: "比例调整完整产品蒙版",
       skipGallerySave: true,

lib/image-delivery.ts

@@ -6,8 +6,9 @@ const IMAGE_PROXY_PATH = "/api/image-proxy";
 export function buildImageFallbackUrl(value: string | null | undefined): string {
   const source = value || "";
   const legacy = normalizeLegacyAliyunStorageUrl(source);
-  if (!legacy) return source;
+  const modelImage = isAlibabaModelImageUrl(source);
-  const proxy = buildImageProxyUrl(legacy);
+  if (!legacy && !modelImage) return source;
+  const proxy = buildImageProxyUrl(legacy || source, modelImage ? { width: 960, quality: 86, format: "webp" } : {});
   return typeof window === "undefined" ? proxy : new URL(proxy, window.location.origin).toString();
 }
 
@@ -90,6 +91,15 @@ function isAliyunOssImageHost(hostname: string): boolean {
   return normalized.endsWith(".aliyuncs.com") && normalized.includes(".oss-");
 }
 
+/** Model result buckets allow downloading objects but deny OSS image processing. */
+export function isAlibabaModelImageUrl(value: string): boolean {
+  try {
+    return /^dashscope(?:-[a-z0-9-]+)?\.oss-[a-z0-9-]+\.aliyuncs\.com$/i.test(new URL(value).hostname);
+  } catch {
+    return false;
+  }
+}
+
 function isTrustedDirectStorageImageHost(hostname: string): boolean {
   const normalized = hostname.trim().toLowerCase();
   let configuredCdnHost = "";
@@ -231,7 +241,7 @@ export function buildImageProxyUrl(url: string, options: ImageProxyOptions = {})
     return trustedDirectStorageUrl;
   }
 
-  if (options.delivery !== "proxy" && !normalizeLegacyAliyunStorageUrl(source)) {
+  if (options.delivery !== "proxy" && !normalizeLegacyAliyunStorageUrl(source) && !isAlibabaModelImageUrl(source)) {
     const directDisplayUrl = resolveAliyunOssDisplayUrl(source, options);
     if (directDisplayUrl) {
       return directDisplayUrl;

lib/request-error.ts

@@ -228,10 +228,72 @@ export function getRequestFailureDetails(
   const status = getRequestErrorStatus(error);
   const detail = (code: string, message: string, recommendation: string, outcome: "failed" | "unknown" = "failed") =>
     ({ code, message, recommendation, outcome });
+  if (/抠图参考图文件大小超限/.test(text)) {
+    return detail("RMBG_INPUT_TOO_LARGE", getRequestErrorMessage(error) || "抠图参考图超过 AOS 的 50 MB 上限。", "请手动压缩至 50 MB 以内后重新提交。本次未提交上游抠图任务。");
+  }
+  if (/抠图参考图分辨率超限/.test(text)) {
+    return detail("RMBG_INPUT_RESOLUTION_EXCEEDED", getRequestErrorMessage(error) || "抠图参考图超过 AOS 的 4096 像素上限。", "请手动将宽、高均调整至 4096 像素以内，再重新提交。本次未提交上游抠图任务。");
+  }
+  if (/抠图参考图格式不支持/.test(text)) {
+    return detail("RMBG_INPUT_FORMAT_UNSUPPORTED", getRequestErrorMessage(error) || "AOS 不支持此参考图格式。", "请导出为 JPG、PNG 或 WebP 后重新提交。本次未提交上游抠图任务。");
+  }
+  const aosResolution = text.match(/(?:resolution excess,\s*width=(\d+),\s*height=(\d+)|图片分辨率超限（(\d+)x(\d+)）)/i);
+  if (aosResolution) {
+    return detail("RMBG_PROVIDER_RESOLUTION_EXCEEDED", `AOS 拒绝了参考图：分辨率为 ${aosResolution[1] || aosResolution[3]}×${aosResolution[2] || aosResolution[4]} 像素，宽、高均须不超过 4096 像素。`, "请手动调整尺寸后重新提交。");
+  }
+  if (/AOS.*invalid file|图片文件无法识别/i.test(text)) {
+    return detail("RMBG_PROVIDER_INVALID_FILE", "AOS 无法识别参考图，文件可能损坏或格式不受支持。", "请确认原图可以正常打开，并导出为 JPG、PNG 或 WebP 后重新提交。");
+  }
+  const aosState = text.match(/AOS任务失败（状态 (-\d+)，/);
+  if (aosState) {
+    const state = Number(aosState[1]);
+    if (state === -5) return detail("RMBG_PROVIDER_URL_TOO_LARGE", "AOS 拒绝读取参考图：链接取图大小超过上游的 30 MB 上限。", "请联系管理员核对文件提交方式；不要连续点击。上游文件上传接口允许最大 50 MB。");
+    if (state === -7) return detail("RMBG_PROVIDER_INVALID_FILE", "AOS 无法识别参考图，文件可能损坏或格式不受支持。", "请确认原图可以正常打开，并导出为 JPG、PNG 或 WebP 后重新提交。");
+    if (state === -3) return detail("RMBG_PROVIDER_SOURCE_DOWNLOAD_FAILED", "AOS 下载参考图失败，未能读取原图。", "请确认原图链接可打开；若原图正常，请联系管理员检查上游取图线路，并提供请求编号。");
+    if (state === -2) return detail("RMBG_PROVIDER_RESULT_STORAGE_FAILED", "AOS 已完成处理，但上游保存结果图片失败。", "请联系管理员核对原任务结果，避免立即重复抠图。", "unknown");
+    if (state === -8) return detail("RMBG_PROVIDER_PROCESSING_TIMEOUT", "AOS 抠图处理超时，上游已返回失败状态。", "请稍后重试；若持续发生，请联系管理员并提供请求编号。");
+    if (state === -11) return detail("RMBG_PROVIDER_EMPTY_RESULT", "AOS 抠图结果为空，未能得到有效主体。", "请检查图片中的主体是否清晰，尝试使用主体更明确的图片。");
+    if ([-17, -16, -14, -10].includes(state)) return detail("RMBG_PROVIDER_INPUT_REJECTED", `AOS 拒绝处理参考图，图片内容未通过上游检查（状态 ${state}）。`, "请更换符合上游要求的参考图；如认为判断有误，请联系管理员核对请求编号。");
+    if (state === -15) return detail("RMBG_PROVIDER_RESOURCE_UNAVAILABLE", "AOS 处理资源不足，未能完成本次抠图。", "请稍后再试；持续失败时联系管理员检查上游服务。");
+    return detail("RMBG_PROVIDER_TASK_FAILED", getRequestErrorMessage(error) || `AOS 抠图任务失败（状态 ${state}）。`, "请联系管理员并提供请求编号，核对上游任务详情。");
+  }
+  if (/AOS任务创建失败（HTTP 413）/.test(text)) {
+    return detail("RMBG_PROVIDER_FILE_TOO_LARGE", "AOS 拒绝了参考图：文件超过上游大小限制（文件上传最大 50 MB）。", "请手动压缩文件后重新提交；若文件已小于限制，请联系管理员核对上游返回。");
+  }
+  if (/AOS任务创建失败（HTTP (400|401|404)）/.test(text)) {
+    return detail("RMBG_PROVIDER_REQUEST_REJECTED", getRequestErrorMessage(error) || "AOS 拒绝了抠图请求。", "请联系管理员核对上游参数、服务权限及接口配置，并提供请求编号。");
+  }
+  if (/AOS任务创建失败（HTTP (200|5\d\d)）/.test(text)) {
+    return detail("RMBG_PROVIDER_CREATE_UNCONFIRMED", getRequestErrorMessage(error) || "AOS 未能确认抠图任务是否创建成功。", "请联系管理员核对原请求，避免连续提交造成重复处理。", "unknown");
+  }
+  const aosReadFailure = text.match(/AOS(任务查询|结果下载)失败（HTTP (\d+)/);
+  if (aosReadFailure) {
+    return aosReadFailure[1] === "任务查询"
+      ? detail("RMBG_PROVIDER_POLL_FAILED", `AOS 查询抠图任务失败（HTTP ${aosReadFailure[2]}），原任务结果尚未确认。`, "请联系管理员核对原任务，不要重复提交。", "unknown")
+      : detail("RMBG_PROVIDER_RESULT_DOWNLOAD_FAILED", `抠图已完成，但结果图片下载失败（HTTP ${aosReadFailure[2]}）。`, "请联系管理员按请求编号取回原任务结果，避免重复抠图。", "unknown");
+  }
   if (isGatewayResponseTimeout(error)) {
     return detail("RESULT_UNCONFIRMED", "模型服务响应超时（HTTP 524），生成结果尚未确认。", "请先查看历史记录，避免重复提交。", "unknown");
   }
-  if ((isRecord(error) && error.providerOutcomeUnknown === true) || /结果(?:尚)?未确认|结果暂未确认|request_outcome_unknown|任务执行中断|may still be running/i.test(text)) {
+  if (/AOS创建任务超时/.test(text)) {
+    return detail("RMBG_CREATE_TIMEOUT", "抠图服务创建任务超时（120秒），结果尚未确认。", "请先查看原任务或联系管理员核对；不要连续点击，以免重复处理。", "unknown");
+  }
+  if (/AOS创建任务连接失败/.test(text)) {
+    return detail("RMBG_CREATE_CONNECTION_FAILED", "抠图服务创建任务时连接中断，结果尚未确认。", "请先查看原任务或联系管理员核对；不要连续点击，以免重复处理。", "unknown");
+  }
+  if (/AOS查询任务连接失败/.test(text)) {
+    return detail("RMBG_POLL_CONNECTION_FAILED", "抠图服务查询任务时连接中断，原任务可能仍在处理。", "请保留当前页面并联系管理员核对原任务，避免重新提交。", "unknown");
+  }
+  if (/AOS查询任务超时/.test(text)) {
+    return detail("RMBG_POLL_TIMEOUT", "抠图服务查询任务超时，原任务可能仍在处理。", "请保留当前页面并联系管理员核对原任务，避免重新提交。", "unknown");
+  }
+  if (/AOS结果下载连接失败/.test(text)) {
+    return detail("RMBG_RESULT_DOWNLOAD_CONNECTION_FAILED", "抠图已完成，但结果图片传输中断。", "请联系管理员按请求编号取回原任务结果，避免重复抠图。", "unknown");
+  }
+  if (/AOS结果下载超时/.test(text)) {
+    return detail("RMBG_RESULT_DOWNLOAD_TIMEOUT", "抠图已完成，但结果图片下载超时。", "请联系管理员按请求编号取回原任务结果，避免重复抠图。", "unknown");
+  }
+  if ((isRecord(error) && (error.providerOutcomeUnknown === true || ["AbortError", "TimeoutError"].includes(String(error.name)))) || /结果(?:尚)?未确认|结果暂未确认|request_outcome_unknown|任务执行中断|may still be running|operation was aborted/i.test(text)) {
     return detail("RESULT_UNCONFIRMED", "任务结果尚未确认，可能仍在处理。", "请先查看原任务或历史记录；持续没有结果时联系管理员，避免重复生成。", "unknown");
   }
   if (isProviderBalanceError(error)) {

lib/scene-fusion/preprocess-product.ts

@@ -0,0 +1,37 @@
+import { executeRemoveBackgroundPOST } from "@/lib/canvas/operations/rmbg";
+import { createLogger } from "@/lib/observability/logger";
+
+const logger = createLogger("scene-fusion");
+
+export async function preprocessProductImageWithRmbg(params: {
+  request: Request;
+  requestId: string;
+  userId: string;
+  productImageUrl: string;
+  preRmbgEnabled: boolean;
+}): Promise<{ productImageUrl: string; usedPreRmbg: boolean; provider?: string; reason?: string }> {
+  const { request, requestId, userId, productImageUrl, preRmbgEnabled } = params;
+  if (!preRmbgEnabled) return { productImageUrl, usedPreRmbg: false, reason: "disabled_by_config" };
+
+  logger.info("pre_rmbg_started", { requestId });
+  try {
+    const response = await executeRemoveBackgroundPOST(new Request(new URL("/api/rmbg", request.url), {
+      method: "POST",
+      headers: { "Content-Type": "application/json", "X-Request-ID": `${requestId}:pre-rmbg` },
+      body: JSON.stringify({ imageUrl: productImageUrl, prompt: "场景裂变预处理-抠图", skipGallerySave: true }),
+    }), userId);
+    const payload = await response.json();
+    if (!response.ok) {
+      logger.warn("pre_rmbg_failed", { requestId, status: response.status, code: payload?.failure?.code });
+      return { productImageUrl, usedPreRmbg: false, reason: String(payload?.error || `request_failed_${response.status}`) };
+    }
+    const cleanedUrl = String(payload?.original_url || payload?.thumbnail_url || "").trim();
+    if (!cleanedUrl || cleanedUrl === productImageUrl) {
+      return { productImageUrl, usedPreRmbg: false, reason: cleanedUrl ? "same_as_source" : "empty_result" };
+    }
+    return { productImageUrl: cleanedUrl, usedPreRmbg: true, provider: String(payload?.provider || "unknown") };
+  } catch (error) {
+    logger.warn("pre_rmbg_failed", error, { requestId });
+    return { productImageUrl, usedPreRmbg: false, reason: error instanceof Error ? error.message : "exception" };
+  }
+}

playwright.helpers.config.ts

@@ -3,6 +3,7 @@ import { defineConfig } from "@playwright/test";
 export default defineConfig({
   testDir: "./tests",
   testMatch: [
+    /routes\/rmbg-delivery\.test\.ts/,
     /routes\/legacy-oss-recovery\.test\.ts/,
     /routes\/retired-storage\.test\.ts/,
     /routes\/original-image-download\.test\.ts/,
@@ -20,6 +21,7 @@ export default defineConfig({
     /routes\/video-canvas-media-import\.test\.ts/,
     /routes\/video-canvas-toolbar-jobs\.test\.ts/,
     /routes\/image-provider-error-classification\.test\.ts/,
+    /routes\/image-generation-status\.test\.ts/,
     /routes\/canvas-agent-runtime-image-failover\.test\.ts/,
     /routes\/video-canvas-audio-remote\.test\.ts/,
     /routes\/video-canvas-groups-upscale\.test\.ts/,

services/canvas/index.ts

@@ -95,18 +95,19 @@ function normalizeRevisionText(value: unknown) {
   return String(value || "").trim();
 }
 
-function syncCanvasStoreRevisionFromUpdatedAt(updatedAt: unknown): void {
+function syncCanvasStoreRevisionFromUpdatedAt(projectId: string, updatedAt: unknown): void {
   if (typeof window === "undefined") return;
   const revision = normalizeRevisionText(updatedAt);
   if (!revision) return;
-  useCanvasStore.getState().setCanvasRevision(revision, revision);
+  const current = useCanvasStore.getState();
+  if (current.projectId === projectId) current.setCanvasRevision(revision, revision);
 }
 
 function syncCanvasStoreRevisionFromProject(
-  project?: { canvasData?: CanvasState | null; updatedAt?: Date | string } | null
+  project?: { id: string; canvasData?: CanvasState | null; updatedAt?: Date | string } | null
 ): void {
   if (!project?.canvasData) return;
-  syncCanvasStoreRevisionFromUpdatedAt(project.updatedAt);
+  syncCanvasStoreRevisionFromUpdatedAt(project.id, project.updatedAt);
 }
 
 export interface NormalizedCropRect {
@@ -203,9 +204,6 @@ export const canvasService = {
     try {
       const response = await fetch(`/api/canvas/${id}`);
       const data = await response.json();
-      if (data?.success) {
-        syncCanvasStoreRevisionFromProject(data.data);
-      }
       return data;
     } catch (error) {
       return { success: false, error: '获取画布失败' };
@@ -335,7 +333,7 @@ export const canvasService = {
         };
       }
       if (data?.success) {
-        syncCanvasStoreRevisionFromUpdatedAt(data?.data?.updatedAt);
+        syncCanvasStoreRevisionFromUpdatedAt(id, data?.data?.updatedAt);
       }
       return data as ApiResponse;
     } catch (error) {

tests/e2e/canvas-generation-feedback.test.ts

@@ -0,0 +1,119 @@
+import { expect, test, type Page } from "@playwright/test";
+
+test.setTimeout(30_000);
+const browserErrors = new WeakMap<Page, string[]>();
+test.beforeEach(({ page }) => {
+  const errors: string[] = [];
+  browserErrors.set(page, errors);
+  page.on("pageerror", error => errors.push(error.message));
+});
+test.afterEach(({ page }) => expect(browserErrors.get(page)).toEqual([]));
+
+const projectId = "24cce650-7cfb-48bb-aa65-b04f490ac978";
+const imageOrigin = "https://scqnycdn.jiansun.vip";
+const failure = {
+  phase: "failed", requestId: "failed-request", userMessageId: "",
+  failure: { code: "SOURCE_IMAGE_UNAVAILABLE", outcome: "failed", message: "参考图片无法读取。", recommendation: "请重新上传原图后再提交。" },
+};
+
+async function setup(page: Page, lostStream = false) {
+  const submissions: { path: string; body: any }[] = [];
+  let messages: any[] = [];
+  const canvasData = {
+    nodes: [{ id: "preview-image", type: "image", position: { x: 220, y: 160 }, size: { width: 640, height: 420 },
+      data: { status: "completed", src: `${imageOrigin}/uploads/feedback-preview.png`, title: "参考图片" } }],
+    edges: [], viewport: { x: 0, y: 0, zoom: 1 },
+  };
+  await page.context().addInitScript(() => localStorage.setItem("theme", "light"));
+  await page.context().route("**/api/**", async route => {
+    const request = route.request();
+    const path = new URL(request.url()).pathname;
+    let data: unknown = {};
+    if (["/api/chat", "/api/canvas/agent-chat"].includes(path) && request.method() === "POST") {
+      const body = request.postDataJSON();
+      submissions.push({ path, body });
+      const terminal = { ...failure, userMessageId: body.message.id };
+      const text = `${terminal.failure.message}${terminal.failure.recommendation}\n\n请求编号：${terminal.requestId}`;
+      const assistant = { id: "failed-assistant", role: "assistant", createdAt: new Date(Date.now() + 100).toISOString(),
+        parts: [{ type: "text", text }, { type: "data-imageGenerationStatus", data: terminal }] };
+      messages = [{ ...body.message, createdAt: new Date().toISOString() }, assistant];
+      const chunks: any[] = [{ type: "start", messageId: "stream-assistant" },
+        { type: "data-imageGenerationStatus", data: JSON.stringify({ phase: "processing", userMessageId: body.message.id }) }];
+      if (!lostStream) chunks.push(
+        { type: "data-imageGenerationStatus", data: JSON.stringify(terminal) },
+        { type: "data-appendMessage", data: JSON.stringify(assistant) },
+        { type: "data-appendMessage", data: JSON.stringify({ id: "end", role: "assistant", parts: [{ type: "text", text: "<!-- IMAGE_GENERATION_END -->" }] }) },
+      );
+      chunks.push({ type: "finish" });
+      await route.fulfill({ headers: { "content-type": "text/event-stream", "x-vercel-ai-ui-message-stream": "v1" },
+        body: `${chunks.map(chunk => `data: ${JSON.stringify(chunk)}\n\n`).join("")}data: [DONE]\n\n` });
+      return;
+    }
+    if (path.includes("validate-session")) data = { valid: true, success: true };
+    else if (path === "/api/auth/session") data = { user: { id: "feedback-user", name: "测试", type: "admin" }, expires: "2099-01-01" };
+    else if (path === "/api/site-settings") data = { canvasEnabled: true, agentEnabled: true, membershipEnabled: false };
+    else if (path === "/api/vote") data = [];
+    else if (path === "/api/models") data = { models: [{ id: "image-test", modelId: "gpt-image-2", providerType: "openai", name: "GPT Image", type: "image", enabled: true, supportsImageGen: true, imageGenConfig: { creditCostPerImage: 15 } }] };
+    else if (path === `/api/canvas/${projectId}` && request.method() === "GET") data = { success: true, data: { id: projectId, title: "反馈验收", canvasData } };
+    else if (path.includes("messages")) data = { messages };
+    else if (path.includes("sessions")) data = { sessions: [] };
+    else if (path.startsWith("/api/canvas/")) data = { success: true, runs: [] };
+    await route.fulfill({ status: 200, contentType: "application/json", body: JSON.stringify(data) });
+  });
+  await page.context().route(`${imageOrigin}/**`, async route => {
+    await new Promise(resolve => setTimeout(resolve, 200));
+    await route.fulfill({ contentType: "image/svg+xml", body: '<svg xmlns="http://www.w3.org/2000/svg" width="640" height="420"><rect width="640" height="420" fill="#43b9bd"/></svg>' });
+  });
+  await page.goto(`/canvas/${projectId}`, { waitUntil: "domcontentloaded" });
+  await expect(page.getByRole("button", { name: "关闭 Agent，直接使用生图模型", exact: true })).toBeVisible();
+  return submissions;
+}
+
+test("image workspaces start with Agent enabled and send requests to its planning runtime", async ({ page }) => {
+  const submissions = await setup(page);
+  await page.getByLabel("描述你的设计需求", { exact: true }).fill("请先分析参考图片，再规划处理步骤。");
+  await page.getByLabel("描述你的设计需求", { exact: true }).press("Enter");
+  await expect.poll(() => submissions.length).toBe(1);
+  expect(submissions[0].path).toBe("/api/canvas/agent-chat");
+  expect(submissions[0].body.composerMode).toBe("agent");
+});
+
+for (const lostStream of [false, true]) {
+  test(`image failure ends waiting and shows its cause${lostStream ? " after recovering history" : " from the stream"}`, async ({ page }) => {
+    const submissions = await setup(page, lostStream);
+    await page.getByRole("button", { name: "关闭 Agent，直接使用生图模型", exact: true }).click();
+    await page.getByLabel("描述你的设计需求", { exact: true }).fill("将参考图改成白色背景。");
+    await page.getByLabel("描述你的设计需求", { exact: true }).press("Enter");
+    const failedNode = page.locator('[data-canvas-node-id] [role="alert"]');
+    await expect(failedNode).toContainText("参考图片无法读取。");
+    await expect(failedNode).toContainText("请重新上传原图后再提交。");
+    await expect(failedNode).toContainText("请求编号：failed-request");
+    await expect(page.getByTestId("message-assistant-image-loading")).toHaveCount(0);
+    expect(submissions).toHaveLength(1);
+    expect(submissions[0].path).toBe("/api/chat");
+    await page.screenshot({ path: test.info().outputPath("terminal-failure.png") });
+  });
+}
+
+test("zoom and hover keep a loaded canvas image visible while a new preview loads", async ({ page }) => {
+  await setup(page);
+  const node = page.locator('[data-canvas-node-id="preview-image"]');
+  await expect.poll(() => node.locator("img").first().evaluate((image: HTMLImageElement) => image.naturalWidth)).toBeGreaterThan(0);
+  await page.evaluate(() => {
+    (window as any).blankPreviewFrames = 0;
+    const inspect = () => {
+      const node = document.querySelector('[data-canvas-node-id="preview-image"]');
+      if (node && !Array.from(node.querySelectorAll("img")).some(image => Number(getComputedStyle(image).opacity) > 0 && image.naturalWidth > 0)) (window as any).blankPreviewFrames++;
+      requestAnimationFrame(inspect);
+    };
+    requestAnimationFrame(inspect);
+  });
+  await page.mouse.move(500, 350);
+  for (let i = 0; i < 18; i++) {
+    await page.mouse.wheel(0, i < 9 ? -100 : 100);
+    await page.waitForTimeout(50);
+  }
+  await page.mouse.move(100, 100);
+  await page.waitForTimeout(500);
+  expect(await page.evaluate(() => (window as any).blankPreviewFrames)).toBe(0);
+});

tests/helpers/canvas-download-server-loader.ts

@@ -53,6 +53,7 @@ export function serverLoader(mocks: Record<string, unknown>, env: Record<string,
       ReadableStream,
       Headers,
       Blob,
+      FormData,
       Request,
       Date: mocks.Date || Date,
       document: mocks.document,

tests/routes/canvas-agent-runtime-image-failover.test.ts

@@ -71,6 +71,8 @@ test("a submitted task with an unknown outcome is not submitted again through a
   await expect(h.generate(h.request)).rejects.toThrow();
   expect(h.calls.map(c => c.id)).toEqual(["primary"]); expect(h.paused.size).toBe(0);
   expect(agentImageFailurePolicy(Object.assign(new Error("timeout"), { providerOutcomeUnknown: true })).retry).toBe(false);
+  expect(agentImageFailurePolicy(Object.assign(new Error("任务查询失败"), { providerOutcomeUnknown: true })).retry).toBe(false);
+  expect(agentImageFailurePolicy(Object.assign(new Error("This operation was aborted"), { name: "AbortError" })).retry).toBe(false);
   expect(agentImageFailurePolicy(new Error("VIP98K task failed: timeout")).retry).toBe(true);
 });
 

tests/routes/canvas-agent-runtime-image-preferences.test.ts

@@ -102,7 +102,7 @@ test("mixed-model batches bill and label only the delivered images using their a
 test("headless image features cannot substitute their default when a pinned model disappears", async () => {
   let generated = 0;
   const mocks: Record<string, any> = {
-    "@/lib/ai/box-cutout/service": {}, "@/lib/ai/extend/service": {}, "@/lib/ai/layer-split/service": {}, "@/lib/ai/resize/service": {}, "@/lib/ai/rmbg/service": {},
+    "@/lib/canvas/operations/box-cutout": {}, "@/lib/ai/box-cutout/service": {}, "@/lib/ai/extend/service": {}, "@/lib/ai/layer-split/service": {}, "@/lib/ai/resize/service": {}, "@/lib/ai/rmbg/service": {},
     "@/lib/canvas/capabilities/internal-endpoint": {}, "@/lib/client/long-task": {},
     "@/lib/canvas/generate-image": { generateCanvasImage: async () => { generated++; return { images: [] }; } },
     "@/lib/style-pro/model-options": { getStyleProImageModelEntries: async () => [{ model: { id: "default", modelId: "default", isDefault: true } }], sortStyleProImageModelEntries: (entries: any[]) => entries, findStyleProImageModelByRef: () => null },

tests/routes/canvas-chat-helpers.test.ts

@@ -808,6 +808,7 @@ test.describe("canvas chat pure helpers", () => {
   });
 
   test("canvas service save uses store revision fallback when options are omitted", async () => {
+    useCanvasStore.getState().setProject("11111111-1111-4111-8111-111111111111");
     const canvasData = {
       nodes: [],
       edges: [],
@@ -885,7 +886,7 @@ test.describe("canvas chat pure helpers", () => {
     });
   });
 
-  test("canvas service keeps store revision aligned after project load and save", async () => {
+  test("canvas revision advances after applying the fetched snapshot and saving the current project", async () => {
     const canvasData = {
       nodes: [],
       edges: [],
@@ -915,6 +916,7 @@ test.describe("canvas chat pure helpers", () => {
       },
     ];
 
+    useCanvasStore.getState().setProject("11111111-1111-4111-8111-111111111111");
     useCanvasStore.getState().setCanvasRevision(null, null);
     Object.defineProperty(globalThis, "window", {
       configurable: true,
@@ -929,7 +931,11 @@ test.describe("canvas chat pure helpers", () => {
       }) as Response) as typeof fetch;
 
     try {
-      await canvasService.getProject("11111111-1111-4111-8111-111111111111");
+      const result = await canvasService.getProject("11111111-1111-4111-8111-111111111111");
+      expect(useCanvasStore.getState().canvasRevision).toBeNull();
+      useCanvasStore.getState().loadCanvas(result.data!.canvasData);
+      const revision = String(result.data!.updatedAt);
+      useCanvasStore.getState().setCanvasRevision(revision, revision);
       expect(useCanvasStore.getState().canvasRevision).toBe(
         "2026-06-22T00:01:00.000Z"
       );

tests/routes/canvas-scale-adjust-intent.test.ts

@@ -236,8 +236,6 @@ test.describe("canvas scale adjust product lock", () => {
     const rmbg = readSource("lib/ai/rmbg/service.ts");
 
     expect(productLock).toContain('foregroundType: "person"');
-    expect(productLock).toContain("attempt <= 3");
-    expect(productLock).toContain("executeScaleAdjustRmbgJob({");
     expect(productLock).toContain("regionPersonExclusionAlpha");
     expect(productLock).toContain("overlapPixelCount >= overlapLimit");
     expect(productLock).toContain("目标产品被人物遮挡");

tests/routes/canvas-toolbar-capability.test.ts

@@ -4,6 +4,7 @@ import { executeCanvasToolbarCapability } from "@/lib/client/canvas-toolbar-capa
 import { createCanvasCapabilityClientCommand } from "@/lib/canvas/capabilities/client-command";
 import { useCanvasStore } from "@/store/canvas";
 import { canvasService } from "@/services/canvas";
+import { formatRequestFailure, getRequestFailureDetails } from "@/lib/request-error";
 
 const originalFetch = globalThis.fetch;
 const node = (id: string) => ({ id, type: "image", position: { x: 0, y: 0 },
@@ -86,6 +87,49 @@ test("a lost submission response polls the original task and never resubmits", a
   expect(useCanvasStore.getState().nodes.map(n => n.id)).toEqual(["source", "result"]);
 });
 
+test("a recovered matting rejection shows its dimensions and advice without changing the canvas or resubmitting", async () => {
+  const submitted = createCanvasCapabilityClientCommand({ projectId: "project-a", capabilityId: "image.remove_background", nodeIds: ["source"], source: "toolbar" });
+  const failure = getRequestFailureDetails("抠图参考图分辨率超限（5056×3392 像素），当前 AOS 上游要求宽、高均不超过 4096 像素。");
+  const message = formatRequestFailure(failure, submitted.requestId);
+  let posts = 0;
+  globalThis.fetch = (async (url, options) => {
+    if (options?.method === "POST") { posts++; return new Response(null, { status: 504 }); }
+    expect(String(url)).toContain(encodeURIComponent(submitted.requestId));
+    return Response.json({ success: true, task: { status: "failed", failure, error: message } });
+  }) as typeof fetch;
+  await expect(executeCanvasToolbarCapability(submitted)).rejects.toThrow(message);
+  expect(posts).toBe(1);
+  expect(useCanvasStore.getState().nodes.map(n => n.id)).toEqual(["source"]);
+  expect(useCanvasStore.getState().canvasRevision).toBe("r1");
+});
+
+test("a lost box-cutout response recovers the same selection into its original canvas with one submission", async () => {
+  const submitted = createCanvasCapabilityClientCommand({ projectId: "project-a", capabilityId: "image.box_cutout", nodeIds: ["source"], source: "toolbar", args: { x: 0.25, y: 0.2, width: 0.4, height: 0.5, paddingRatio: 0.08 } });
+  let posts = 0, polls = 0;
+  const selected = { ...node("cutout"), data: { src: "https://example.com/cutout.png", metadata: { editMode: "box-cutout", cropRectApplied: submitted.args } } };
+  globalThis.fetch = (async (url, options) => {
+    if (options?.method === "POST") {
+      posts++;
+      expect(JSON.parse(String(options.body))).toMatchObject({ capabilityId: "image.box_cutout", requestId: submitted.requestId, args: submitted.args });
+      useCanvasStore.getState().moveNode("source", { x: 20, y: 30 });
+      return new Response(null, { status: 524 });
+    }
+    if (String(url).includes("/capabilities?")) {
+      polls++;
+      expect(String(url)).toContain(encodeURIComponent(submitted.requestId));
+      return Response.json({ success: true, task: { status: "succeeded" } });
+    }
+    return Response.json({ success: true, data: { updatedAt: "r2", canvasData: { nodes: [node("source"), selected], edges: [] } } });
+  }) as typeof fetch;
+  await executeCanvasToolbarCapability(submitted);
+  expect({ posts, polls }).toEqual({ posts: 1, polls: 1 });
+  const state = useCanvasStore.getState();
+  expect(state.projectId).toBe("project-a");
+  expect(state.nodes.map(n => n.id)).toEqual(["source", "cutout"]);
+  expect(state.nodes[0].position).toEqual({ x: 20, y: 30 });
+  expect(state.nodes[1].data).toEqual(selected.data);
+});
+
 test("switching projects during processing does not load the old result into the new project", async () => {
   globalThis.fetch = (async (url) => {
     if (String(url).endsWith("/capabilities")) {
@@ -119,6 +163,71 @@ test("metadata changes never adopt an unseen remote canvas revision", async () =
   expect(useCanvasStore.getState().canvasRevision).toBe("r1");
 });
 
+test("reading a result without applying it cannot authorize an old snapshot to overwrite the result", async () => {
+  const previousWindow = Object.getOwnPropertyDescriptor(globalThis, "window");
+  Object.defineProperty(globalThis, "window", { configurable: true, value: {} });
+  let remoteNodes = [node("source"), node("result")];
+  globalThis.fetch = (async (_url, options) => {
+    if (options?.method === "PUT") {
+      const body = JSON.parse(String(options.body));
+      if (body.baseCanvasRevision !== "r2") return Response.json({ success: false, error: "画布已更新" }, { status: 409 });
+      remoteNodes = body.canvasData.nodes;
+      return Response.json({ success: true, data: { updatedAt: "r3" } });
+    }
+    return Response.json({ success: true, data: { id: "project-a", updatedAt: "r2", canvasData: { nodes: remoteNodes, edges: [] } } });
+  }) as typeof fetch;
+  try {
+    await canvasService.getProject("project-a");
+    const saved = await canvasService.saveCanvasState("project-a", useCanvasStore.getState().getCanvasState());
+    expect(saved).toMatchObject({ success: false, status: 409 });
+    expect(remoteNodes.map(n => n.id)).toEqual(["source", "result"]);
+    expect(useCanvasStore.getState().canvasRevision).toBe("r1");
+  } finally {
+    if (previousWindow) Object.defineProperty(globalThis, "window", previousWindow);
+    else Reflect.deleteProperty(globalThis, "window");
+  }
+});
+
+test("a delayed read cannot change the revision of a newly selected project", async () => {
+  const previousWindow = Object.getOwnPropertyDescriptor(globalThis, "window");
+  Object.defineProperty(globalThis, "window", { configurable: true, value: {} });
+  let complete!: (response: Response) => void;
+  globalThis.fetch = (() => new Promise<Response>(resolve => { complete = resolve; })) as typeof fetch;
+  try {
+    const pending = canvasService.getProject("project-a");
+    useCanvasStore.getState().setProject("project-b");
+    useCanvasStore.getState().loadCanvas({ nodes: [node("other") as any], edges: [] });
+    useCanvasStore.getState().setCanvasRevision("r9", "r9");
+    complete(Response.json({ success: true, data: { id: "project-a", updatedAt: "r2", canvasData: { nodes: [node("result")], edges: [] } } }));
+    await pending;
+    expect(useCanvasStore.getState().canvasRevision).toBe("r9");
+    expect(useCanvasStore.getState().nodes.map(n => n.id)).toEqual(["other"]);
+  } finally {
+    if (previousWindow) Object.defineProperty(globalThis, "window", previousWindow);
+    else Reflect.deleteProperty(globalThis, "window");
+  }
+});
+
+test("a delayed save cannot change the revision of a newly selected project", async () => {
+  const previousWindow = Object.getOwnPropertyDescriptor(globalThis, "window");
+  Object.defineProperty(globalThis, "window", { configurable: true, value: {} });
+  let complete!: (response: Response) => void;
+  globalThis.fetch = (() => new Promise<Response>(resolve => { complete = resolve; })) as typeof fetch;
+  try {
+    const pending = canvasService.saveCanvasState("project-a", useCanvasStore.getState().getCanvasState());
+    useCanvasStore.getState().setProject("project-b");
+    useCanvasStore.getState().loadCanvas({ nodes: [node("other") as any], edges: [] });
+    useCanvasStore.getState().setCanvasRevision("r9", "r9");
+    complete(Response.json({ success: true, data: { updatedAt: "r2" } }));
+    await pending;
+    expect(useCanvasStore.getState().canvasRevision).toBe("r9");
+    expect(useCanvasStore.getState().nodes.map(n => n.id)).toEqual(["other"]);
+  } finally {
+    if (previousWindow) Object.defineProperty(globalThis, "window", previousWindow);
+    else Reflect.deleteProperty(globalThis, "window");
+  }
+});
+
 test("a result merge conflict retains both the local edit and its original revision", async () => {
   globalThis.fetch = (async (url) => {
     if (String(url).endsWith("/capabilities")) {

tests/routes/image-delivery-qiniu.test.ts

@@ -3,8 +3,61 @@ import { NextRequest } from "next/server";
 import sharp from "sharp";
 import { GET } from "@/app/api/image-proxy/route";
 import { buildImageProxyUrl, getFullscreenPreviewSize, getImageDownloadExtension } from "@/lib/image-delivery";
+import { serverLoader } from "../helpers/canvas-download-server-loader";
+import { NextResponse } from "next/server";
 
 test.describe("Qiniu image delivery", () => {
+  test("model result buckets use our thumbnail endpoint without forbidden OSS transforms", () => {
+    const source = "https://dashscope-a717.oss-accelerate.aliyuncs.com/output.png";
+    const preview = new URL(buildImageProxyUrl(source, { width: 960, format: "webp" }), "https://app.example");
+    expect(preview.pathname).toBe("/api/image-proxy");
+    expect(preview.searchParams.get("url")).toBe(source);
+    expect(preview.searchParams.has("x-oss-process")).toBe(false);
+    expect(buildImageProxyUrl("https://other-bucket.oss-cn-shanghai.aliyuncs.com/image.png", { width: 960 })).toContain("x-oss-process=");
+  });
+
+  test("a completed archive serves old model-result references from Qiniu immediately", async () => {
+    const source = "https://dashscope-a717.oss-accelerate.aliyuncs.com/archived.png";
+    const route = serverLoader({
+      "next/server": { NextResponse },
+      "@/lib/storage/image-archive-db": { getArchivedImageUrlMappings: async () => ({ [source]: "https://yybb.top/archived.png" }) },
+      fetch: () => { throw new Error("Must use the completed archive"); },
+    })("app/api/image-proxy/route.ts");
+    const request = new URL("https://app.example/api/image-proxy");
+    request.searchParams.set("url", source); request.searchParams.set("w", "960"); request.searchParams.set("f", "webp");
+    const response = await route.GET(new NextRequest(request, { headers: { "sec-fetch-dest": "image" } }));
+    expect(response.status).toBe(307);
+    expect(response.headers.get("location")).toBe("https://yybb.top/archived.png?imageView2/2/w/960/format/webp/q/82");
+  });
+
+  test("unarchived model previews share one original fetch with archiving and return resized WebP", async () => {
+    const source = `https://dashscope-a717.oss-accelerate.aliyuncs.com/${crypto.randomUUID()}.png`;
+    const original = await sharp({ create: { width: 1024, height: 1024, channels: 3, background: "#345678" } }).png().toBuffer();
+    let requests = 0;
+    const load = serverLoader({
+      "next/server": { NextResponse },
+      "@/lib/storage/image-archive-db": { getArchivedImageUrlMappings: async () => ({}) },
+      fetch: async (url: string) => {
+        expect(url).toBe(source); requests++;
+        await new Promise(resolve => setTimeout(resolve, 30));
+        return new Response(original, { headers: { "content-type": "image/png" } });
+      },
+    });
+    const route = load("app/api/image-proxy/route.ts");
+    const archiveRead = load("lib/storage/image-byte-cache.ts").fetchImageBytes(source);
+    const responses = await Promise.all([100, 200].map(width => {
+      const request = new URL("https://app.example/api/image-proxy");
+      request.searchParams.set("url", source); request.searchParams.set("w", String(width)); request.searchParams.set("f", "webp");
+      return route.GET(new NextRequest(request, { headers: { "sec-fetch-dest": "image" } }));
+    }));
+    expect((await archiveRead).buffer.equals(original)).toBe(true);
+    expect(requests).toBe(1);
+    for (let i = 0; i < responses.length; i++) {
+      expect(responses[i].status).toBe(200);
+      expect(responses[i].headers.get("content-type")).toBe("image/webp");
+      expect((await sharp(Buffer.from(await responses[i].arrayBuffer())).metadata()).width).toBe([100, 200][i]);
+    }
+  });
   test("sizes a fullscreen square to its visible height and reuses the chat preview on standard density screens", () => {
     const size = getFullscreenPreviewSize({ imageWidth: 2048, imageHeight: 2048, viewportWidth: 1657, viewportHeight: 884 });
     expect(size.displayWidth).toBeCloseTo(839.8);

tests/routes/image-generation-status.test.ts

@@ -0,0 +1,39 @@
+import { expect, test } from "@playwright/test";
+import { findImageGenerationFailure } from "@/lib/canvas/image-generation-status";
+import { getRequestFailureDetails } from "@/lib/request-error";
+import { serverLoader } from "../helpers/canvas-download-server-loader";
+
+test("a terminal image error reaches the stream and persists for disconnected clients", async () => {
+  const chunks: any[] = [];
+  const saved: any[] = [];
+  const load = serverLoader({ "@/lib/db/queries": { saveMessages: async ({ messages }: any) => saved.push(...messages) } });
+  const { reportImageGenerationFailure } = load("app/(chat)/api/chat/_lib/image-generation-failure.ts");
+  await reportImageGenerationFailure({
+    writer: { write: (chunk: any) => chunks.push(chunk) },
+    chatId: "chat", userMessageId: "original-user", messageId: "request-id",
+    error: new Error("get image url failed"), label: "test",
+  });
+  const streamed = JSON.parse(chunks.find(chunk => chunk.type === "data-imageGenerationStatus").data);
+  const persisted = findImageGenerationFailure(saved, "original-user");
+  expect(persisted).toEqual(streamed);
+  expect(persisted).toMatchObject({ phase: "failed", requestId: "request-id", failure: { code: "SOURCE_IMAGE_UNAVAILABLE", outcome: "failed" } });
+  const text = saved[0].parts[0].text;
+  expect(text).toContain("重新上传原图");
+  expect(text).toContain("请求编号：request-id");
+  expect(JSON.parse(chunks.at(-1).data).parts[0].text).toContain("IMAGE_GENERATION_END");
+
+  await reportImageGenerationFailure({
+    writer: { write: () => { throw new Error("browser disconnected"); } },
+    chatId: "chat", userMessageId: "next-user", messageId: "next-request",
+    error: new Error("get image url failed"), label: "test",
+  });
+  expect(findImageGenerationFailure(saved, "next-user")?.requestId).toBe("next-request");
+});
+
+test("late failures remain associated with their original user request", () => {
+  const status = { phase: "failed" as const, userMessageId: "first", failure: getRequestFailureDetails(new Error("HTTP 524")) };
+  const messages = [{ role: "user", parts: [] }, { role: "assistant", parts: [{ type: "data-imageGenerationStatus", data: status }] }];
+  expect(findImageGenerationFailure(messages, "first")).toEqual(status);
+  expect(findImageGenerationFailure(messages, "second")).toBeNull();
+  expect(findImageGenerationFailure([{ role: "assistant", parts: [{ type: "text", text: "请分析失败原因" }] }], "second")).toBeNull();
+});

tests/routes/image-provider-error-classification.test.ts

@@ -69,6 +69,20 @@ test("HTTP 524 does not start another model while the original result is unconfi
   expect(health.shouldFailoverAiModelError(new Error("Service unavailable (HTTP 503)"))).toBe(true);
 });
 
+test("aborts and unconfirmed fallback results cannot start another paid generation", () => {
+  const { health } = healthHarness();
+  for (const error of [
+    Object.assign(new Error("This operation was aborted"), { name: "AbortError" }),
+    Object.assign(new Error("request timed out"), { name: "TimeoutError" }),
+    Object.assign(new Error("任务查询失败"), { providerOutcomeUnknown: true }),
+    new Error("图片上传到存储桶失败"),
+  ]) {
+    expect(getRequestFailureDetails(error).outcome).toBe("unknown");
+    expect(health.shouldFailoverAiModelError(error)).toBe(false);
+  }
+  expect(health.shouldFailoverAiModelError(new Error("Service unavailable (HTTP 503)"))).toBe(true);
+});
+
 test("the provider submits once when an HTTP 524 request cannot be located", async () => {
   let submissions = 0;
   const provider = serverLoader({

tests/routes/legacy-oss-recovery.test.ts

@@ -38,7 +38,7 @@ test("legacy display URLs go through archive resolution while other Alibaba buck
   const url = buildImageProxyUrl(legacy, { width: 400 });
   expect(url).toMatch(/^\/api\/image-proxy\?/);
   expect(new URL(url, "https://app.example").searchParams.get("url")).toBe(legacy);
-  expect(buildImageProxyUrl("https://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/result.png", { width: 400 })).toContain("x-oss-process=");
+  expect(buildImageProxyUrl("https://dashscope-result-bj.oss-cn-beijing.aliyuncs.com/result.png", { width: 400 })).toMatch(/^\/api\/image-proxy\?/);
 });
 
 test("browser image fallbacks remain on one stable archive URL instead of retrying the old source", () => {

tests/routes/rmbg-delivery.test.ts

@@ -0,0 +1,404 @@
+import { expect, test } from "@playwright/test";
+import sharp from "sharp";
+import { serverLoader } from "../helpers/canvas-download-server-loader";
+import { getRequestFailureDetails } from "@/lib/request-error";
+
+const cdn = "https://scqnycdn.jiansun.vip";
+
+test("box cutout submits exactly the padded selection and keeps the original URL as provenance", async () => {
+  const pixels = Buffer.alloc(120 * 80 * 3);
+  for (let y = 0; y < 80; y++) for (let x = 0; x < 120; x++) {
+    const offset = (y * 120 + x) * 3;
+    pixels[offset] = x * 2; pixels[offset + 1] = y * 3; pixels[offset + 2] = x + y;
+  }
+  const original = await sharp(pixels, { raw: { width: 120, height: 80, channels: 3 } }).png().toBuffer();
+  let submitted: any;
+  const box = serverLoader({
+    "@/lib/ai/rmbg/service": {
+      fetchImageBufferFromUrl: async () => original,
+      executeRmbgJob: async (params: any) => { submitted = params; return { original_url: `${cdn}/selected.png` }; },
+    },
+  })("lib/ai/box-cutout/service.ts");
+  const result = await box.executeBoxCutoutJob({ userId: "user-a", requestId: "box-a", sourceNodeId: "source", imageUrl: `${cdn}/original.png`, cropRect: { x: 0.25, y: 0.25, width: 0.5, height: 0.5 }, paddingRatio: 0.1 });
+  expect(result.cropRectPixels).toEqual({ left: 30, top: 20, width: 60, height: 40 });
+  expect(result.paddedCropRectPixels).toEqual({ left: 24, top: 16, width: 72, height: 48 });
+  expect(submitted).toMatchObject({ requestId: "box-a", sourceImageUrl: `${cdn}/original.png` });
+  expect(submitted.inputImageUrl).toBeUndefined();
+  const expected = await sharp(original).extract(result.paddedCropRectPixels).raw().toBuffer();
+  expect((await sharp(submitted.imageBuffer).raw().toBuffer()).equals(expected)).toBe(true);
+});
+
+test("box cutout shares the configured charge once after success and never charges a rejected input", async () => {
+  class InputError extends Error { status = 400; }
+  for (const rejected of [false, true]) {
+    let creates = 0, charges = 0;
+    const operation = serverLoader({
+      "@/lib/ai/box-cutout/service": { BoxCutoutServiceError: InputError, executeBoxCutoutJob: async (params: any) => {
+        creates++;
+        expect(params.requestId).toBe("box-a");
+        if (rejected) throw new InputError("抠图参考图分辨率超限（5000×3000 像素），当前 AOS 上游要求宽、高均不超过 4096 像素。");
+        return { success: true, original_url: `${cdn}/selected.png` };
+      } },
+      "@/lib/ai/rmbg/service": { RmbgServiceError: InputError },
+      "@/lib/db/queries": { getPointsSystemConfig: async () => ({ enabled: true, creditCostPerImageBoxCutout: 7 }) },
+      "@/lib/points/feature-charge": { prepareFeaturePointsCharge: async (params: any) => {
+        expect(params).toMatchObject({ userId: "user-a", unitCost: 7, reason: "image_box_cutout", modelId: "box-cutout" });
+        return { ok: true, chargeable: true, consume: async () => { charges++; } };
+      } },
+    })("lib/canvas/operations/box-cutout.ts");
+    const response = await operation.executeBoxCutoutPOST(new Request("https://example.com/api/canvas/box-cutout", { method: "POST", headers: { "Content-Type": "application/json", "X-Request-ID": "box-a" }, body: JSON.stringify({ imageUrl: `${cdn}/original.png`, cropRect: { x: 0, y: 0, width: 0.5, height: 0.5 } }) }), "user-a");
+    const result = await response.json();
+    expect({ creates, charges }).toEqual({ creates: 1, charges: rejected ? 0 : 1 });
+    expect(response.status).toBe(rejected ? 400 : 200);
+    if (rejected) {
+      expect(result.failure).toMatchObject({ code: "RMBG_INPUT_RESOLUTION_EXCEEDED", outcome: "failed" });
+      expect(result.error).toContain("5000×3000");
+      expect(result.error).toContain("本次未提交上游抠图任务");
+      expect(result.error).toContain("请求编号：box-a");
+    }
+  }
+});
+
+test("headless box cutout keeps its task identity, pixel bounds and input-rejection status", async () => {
+  class InputError extends Error {
+    status: number;
+    constructor(message: string, status: number) { super(message); this.status = status; }
+  }
+  let calls = 0;
+  let rejectInput = false;
+  const bounds = { left: 20, top: 30, width: 200, height: 300 };
+  const executor = serverLoader({
+    "@/lib/ai/box-cutout/service": {},
+    "@/lib/canvas/operations/box-cutout": { executeBoxCutoutPOST: async (request: Request, userId: string) => {
+      calls++;
+      expect(userId).toBe("user-a");
+      expect(request.headers.get("x-request-id")).toBe("box-a");
+      expect(await request.json()).toMatchObject({ sourceNodeId: "source", cropRect: { x: 0.1, y: 0.2, width: 0.3, height: 0.4 }, paddingRatio: 0.08 });
+      return rejectInput ? Response.json({ success: false, detail: "抠图参考图分辨率超限（5000×3000 像素）" }, { status: 400 })
+        : Response.json({ success: true, original_url: `${cdn}/cutout.png`, paddedCropRectPixels: bounds });
+    } },
+    "@/lib/ai/extend/service": {}, "@/lib/ai/layer-split/service": {}, "@/lib/ai/resize/service": {},
+    "@/lib/ai/rmbg/service": { RmbgServiceError: InputError },
+    "@/lib/canvas/capabilities/internal-endpoint": {}, "@/lib/client/long-task": {},
+    "@/lib/canvas/generate-image": {}, "@/lib/style-pro/model-options": {},
+  })("lib/canvas/capabilities/headless-executor.ts");
+  const params = { userId: "user-a", requestUrl: "https://example.com/api/canvas/project-a/capabilities", requestHeaders: new Headers(), command: { requestId: "box-a", capabilityId: "image.box_cutout", source: "toolbar", args: { x: 0.1, y: 0.2, width: 0.3, height: 0.4, paddingRatio: 0.08 } }, targets: [{ nodeId: "source", title: "原图", sourceImageUrl: `${cdn}/original.png` }] };
+  const results = await executor.executeCanvasCapabilityHeadlessly(params);
+  expect(calls).toBe(1);
+  expect(results).toMatchObject([{ sourceNodeId: "source", url: `${cdn}/cutout.png`, metadata: { editMode: "box-cutout", paddedCropRectPixels: bounds } }]);
+  rejectInput = true;
+  await expect(executor.executeCanvasCapabilityHeadlessly(params)).rejects.toMatchObject({ status: 400 });
+  expect(calls).toBe(2);
+});
+
+test("Agent and MCP box cutouts retain their existing billing path", async () => {
+  let jobs = 0, featureCharges = 0;
+  const executor = serverLoader({
+    "@/lib/ai/box-cutout/service": { executeBoxCutoutJob: async (params: any) => {
+      jobs++;
+      expect(params).toMatchObject({ userId: "user-a", requestId: "box-agent", sourceNodeId: "source" });
+      return { original_url: `${cdn}/cutout.png` };
+    } },
+    "@/lib/canvas/operations/box-cutout": { executeBoxCutoutPOST: async () => { featureCharges++; throw new Error("Unexpected toolbar charge"); } },
+    "@/lib/ai/extend/service": {}, "@/lib/ai/layer-split/service": {}, "@/lib/ai/resize/service": {}, "@/lib/ai/rmbg/service": {},
+    "@/lib/canvas/capabilities/internal-endpoint": {}, "@/lib/client/long-task": {},
+    "@/lib/canvas/generate-image": {}, "@/lib/style-pro/model-options": {},
+  })("lib/canvas/capabilities/headless-executor.ts");
+  for (const source of ["agent", "mcp", "system"]) {
+    await executor.executeCanvasCapabilityHeadlessly({ userId: "user-a", command: { requestId: "box-agent", capabilityId: "image.box_cutout", source, args: { x: 0, y: 0, width: 0.5, height: 0.5 } }, targets: [{ nodeId: "source", title: "原图", sourceImageUrl: `${cdn}/source.png` }] });
+  }
+  expect({ jobs, featureCharges }).toEqual({ jobs: 3, featureCharges: 0 });
+});
+
+function rmbgLoader(fetch: typeof globalThis.fetch, timer?: typeof setTimeout) {
+  return serverLoader({
+    "@/lib/db/queries": { getSystemSetting: async () => ({ value: { provider: "aoscdn", aosApiKey: "test-key" } }) },
+    "@/lib/db": { db: {} },
+    "@/lib/db/schema": { generatedImage: {} },
+    "@/lib/storage/service": { uploadFile: async (name: string) => ({ url: `${cdn}/${name}` }) },
+    "@/lib/observability/active-work": { trackRuntimeWork: async (execute: () => unknown) => execute() },
+    fetch,
+    setTimeout: timer || ((callback: () => void, ms: number) => setTimeout(callback, ms <= 2000 ? 0 : ms)),
+  }, { NEXT_PUBLIC_CANVAS_CDN_ORIGIN: cdn })("lib/ai/rmbg/service.ts");
+}
+
+test("AOS uses a public Qiniu original URL without uploading the image file again", async () => {
+  const image = await sharp({ create: { width: 1024, height: 768, channels: 3, background: "#abcdef" } }).png().toBuffer();
+  let creates = 0;
+  const source = `${cdn}/uploads/original.png`;
+  const service = rmbgLoader(async (input, options) => {
+    const url = String(input);
+    if (options?.method === "POST") {
+      creates++;
+      const form = options.body as FormData;
+      expect(form.get("image_url")).toBe(source);
+      expect(form.has("image_file")).toBe(false);
+      expect(form.get("sync")).toBe("0");
+      return Response.json({ data: { task_id: "task-url" } });
+    }
+    if (url.endsWith("/task-url")) return Response.json({ data: { state: 1, image: "https://output.example/image.png" } });
+    return new Response(image, { headers: { "content-type": "image/png" } });
+  });
+  const result = await service.executeRmbgJob({ userId: "test", imageBuffer: image, inputImageUrl: source, sourceImageUrl: source, skipGallerySave: true });
+  expect(creates).toBe(1);
+  expect(result.provider).toBe("aoscdn");
+  expect(result.original_url).toContain(cdn);
+});
+
+test("non-CDN sources upload the original file without changing its bytes or dimensions", async () => {
+  for (const [width, source] of [[4096, "http://127.0.0.1/private.png"], [1000, "https://other.example/image.png"]] as const) {
+    const image = await sharp({ create: { width, height: 20, channels: 3, background: "#abcdef" } }).png().toBuffer();
+    const service = rmbgLoader(async (input, options) => {
+      if (options?.method === "POST") {
+        const form = options.body as FormData;
+        expect(form.has("image_url")).toBe(false);
+        const file = form.get("image_file") as File;
+        const submitted = Buffer.from(await file.arrayBuffer());
+        expect(submitted.equals(image)).toBe(true);
+        expect((await sharp(submitted).metadata()).width).toBe(width);
+        return Response.json({ data: { task_id: "task-file" } });
+      }
+      if (String(input).endsWith("/task-file")) return Response.json({ data: { state: 1, image: "https://output.example/image.png" } });
+      return new Response(image, { headers: { "content-type": "image/png" } });
+    });
+    await service.executeRmbgJob({ userId: "test", imageBuffer: image, inputImageUrl: source, sourceImageUrl: source, skipGallerySave: true });
+  }
+});
+
+test("a cropped input uses its own bytes instead of the original provenance URL", async () => {
+  const original = await sharp({ create: { width: 120, height: 80, channels: 3, background: "#abcdef" } }).png().toBuffer();
+  const cropped = await sharp(original).extract({ left: 20, top: 10, width: 40, height: 20 }).png().toBuffer();
+  let submitted!: FormData;
+  const service = rmbgLoader(async (input, options) => {
+    if (options?.method === "POST") { submitted = options.body as FormData; return Response.json({ data: { task_id: "cropped-task" } }); }
+    if (String(input).endsWith("/cropped-task")) return Response.json({ data: { state: 1, image: "https://output.example/cropped.png" } });
+    return new Response(cropped, { headers: { "content-type": "image/png" } });
+  });
+  await service.executeRmbgJob({ userId: "test", imageBuffer: cropped, sourceImageUrl: `${cdn}/original.png`, skipGallerySave: true });
+  expect(submitted.has("image_url")).toBe(false);
+  const bytes = Buffer.from(await (submitted.get("image_file") as File).arrayBuffer());
+  expect(bytes.equals(cropped)).toBe(true);
+  expect(await sharp(bytes).metadata()).toMatchObject({ width: 40, height: 20 });
+});
+
+test("scale adjustment does not start a new matting job after an unconfirmed result", async () => {
+  let creates = 0;
+  const image = await sharp({ create: { width: 64, height: 64, channels: 3, background: "white" } }).png().toBuffer();
+  const scale = serverLoader({
+    "@/lib/ai/rmbg/service": { executeRmbgJob: async () => { creates++; throw new Error("AOS查询任务超时，结果尚未确认"); } },
+    setTimeout: (fn: () => void) => setTimeout(fn, 0),
+  })("lib/canvas/scale-adjust-product-lock.ts");
+  await expect(scale.buildScaleAdjustProductLockAssets({ userId: "test", sourceBuffer: image, sourceWidth: 64, sourceHeight: 64, sourceImageUrl: `${cdn}/source.png`, regions: [{ index: 0, rect: { x: 0.1, y: 0.1, width: 0.5, height: 0.5 }, targetRect: { x: 0.2, y: 0.2, width: 0.5, height: 0.5 } }] })).rejects.toThrow("结果尚未确认");
+  expect(creates).toBe(1);
+});
+
+test("scene preprocessing invokes matting once even when its result is unconfirmed or the call is interrupted", async () => {
+  for (const interrupted of [false, true]) {
+    let calls = 0, networkCalls = 0;
+    const scene = serverLoader({
+      "@/lib/canvas/operations/rmbg": { executeRemoveBackgroundPOST: async (request: Request, userId: string) => {
+        calls++;
+        expect(userId).toBe("user-a");
+        expect(request.headers.get("x-request-id")).toBe("scene-a:pre-rmbg");
+        expect(await request.json()).toMatchObject({ imageUrl: `${cdn}/source.png`, skipGallerySave: true });
+        if (interrupted) throw new TypeError("fetch failed");
+        return Response.json({ error: "抠图已完成，但结果图片下载失败，请核对原任务。", failure: { outcome: "unknown" } }, { status: 500 });
+      } },
+      fetch: async () => { networkCalls++; throw new Error("Unexpected HTTP resubmission"); },
+    })("lib/scene-fusion/preprocess-product.ts");
+    const result = await scene.preprocessProductImageWithRmbg({ request: new Request("https://example.com/api/scene-fusion"), requestId: "scene-a", userId: "user-a", productImageUrl: `${cdn}/source.png`, preRmbgEnabled: true });
+    expect(result).toMatchObject({ productImageUrl: `${cdn}/source.png`, usedPreRmbg: false });
+    expect({ calls, networkCalls }).toEqual({ calls: 1, networkCalls: 0 });
+  }
+});
+
+test("scene preprocessing retains the disabled setting and delivers a successful original result", async () => {
+  let calls = 0;
+  const scene = serverLoader({ "@/lib/canvas/operations/rmbg": { executeRemoveBackgroundPOST: async () => { calls++; return Response.json({ original_url: `${cdn}/result.png`, provider: "aoscdn" }); } } })("lib/scene-fusion/preprocess-product.ts");
+  const params = { request: new Request("https://example.com/api/scene-fusion"), requestId: "scene-a", userId: "user-a", productImageUrl: `${cdn}/source.png` };
+  expect(await scene.preprocessProductImageWithRmbg({ ...params, preRmbgEnabled: false })).toMatchObject({ usedPreRmbg: false });
+  expect(calls).toBe(0);
+  expect(await scene.preprocessProductImageWithRmbg({ ...params, preRmbgEnabled: true })).toMatchObject({ usedPreRmbg: true, productImageUrl: `${cdn}/result.png` });
+  expect(calls).toBe(1);
+});
+
+test("the standalone matting API returns the limit, recommendation and request ID", async () => {
+  class InputError extends Error { status = 400; }
+  let submitted: any;
+  const operation = serverLoader({
+    "@/lib/ai/rmbg/service": { RmbgServiceError: InputError, fetchImageBufferFromUrl: async () => Buffer.from("original"), executeRmbgJob: async (params: any) => { submitted = params; throw new InputError("抠图参考图分辨率超限（5056×3392 像素），当前 AOS 上游要求宽、高均不超过 4096 像素。"); } },
+    "@/lib/db/queries": { getPointsSystemConfig: async () => ({ enabled: false }) },
+    "@/lib/points/feature-charge": { prepareFeaturePointsCharge: async () => ({ ok: true, chargeable: false }) },
+  })("lib/canvas/operations/rmbg.ts");
+  const response = await operation.executeRemoveBackgroundPOST(new Request("https://example.com/api/rmbg", { method: "POST", headers: { "Content-Type": "application/json", "X-Request-ID": "request-a" }, body: JSON.stringify({ imageUrl: `${cdn}/source.png` }) }), "user-a");
+  const result = await response.json();
+  expect(response.status).toBe(400);
+  expect(submitted).toMatchObject({ requestId: "request-a", inputImageUrl: `${cdn}/source.png` });
+  expect(result).toMatchObject({ success: false, requestId: "request-a", failure: { code: "RMBG_INPUT_RESOLUTION_EXCEEDED", outcome: "failed" } });
+  expect(result.error).toContain("5056×3392");
+  expect(result.error).toContain("本次未提交上游抠图任务");
+  expect(result.error).toContain("请求编号：request-a");
+});
+
+test("AOS rejects either oversized dimension before creating a task and gives the exact dimensions", async () => {
+  for (const [width, height] of [[4097, 20], [20, 4097]]) {
+    const image = await sharp({ create: { width, height, channels: 3, background: "white" } }).png().toBuffer();
+    let creates = 0;
+    const service = rmbgLoader(async () => { creates++; throw new Error("Unexpected provider call"); });
+    let failure: Error | undefined;
+    try { await service.executeRmbgJob({ userId: "test", imageBuffer: image, sourceImageUrl: `${cdn}/large.png`, skipGallerySave: true }); }
+    catch (error) { failure = error as Error; }
+    expect(creates).toBe(0);
+    expect(failure).toMatchObject({ status: 400 });
+    expect(failure?.message).toContain(`${width}×${height}`);
+    const details = getRequestFailureDetails(failure);
+    expect(details).toMatchObject({ code: "RMBG_INPUT_RESOLUTION_EXCEEDED", outcome: "failed" });
+    expect(details.message).toContain("4096");
+    expect(details.recommendation).toContain("本次未提交上游抠图任务");
+  }
+});
+
+test("AOS accepts 4096 pixels and 50 MB but rejects a larger file without submitting it", async () => {
+  const output = await sharp({ create: { width: 4096, height: 20, channels: 3, background: "white" } }).png().toBuffer();
+  const boundary = Buffer.alloc(50 * 1024 * 1024);
+  output.copy(boundary);
+  let creates = 0;
+  const service = rmbgLoader(async (input, options) => {
+    if (options?.method === "POST") {
+      creates++;
+      const form = options.body as FormData;
+      expect(form.has("image_url")).toBe(false);
+      expect((form.get("image_file") as File).size).toBe(boundary.length);
+      return Response.json({ data: { task_id: "boundary-task" } });
+    }
+    if (String(input).endsWith("/boundary-task")) return Response.json({ data: { state: 1, image: "https://output.example/image.png" } });
+    return new Response(output, { headers: { "content-type": "image/png" } });
+  });
+  await service.executeRmbgJob({ userId: "test", imageBuffer: boundary, inputImageUrl: `${cdn}/boundary.png`, sourceImageUrl: `${cdn}/boundary.png`, skipGallerySave: true });
+  expect(creates).toBe(1);
+  let failure: Error | undefined;
+  try { await service.executeRmbgJob({ userId: "test", imageBuffer: Buffer.alloc(boundary.length + 1), skipGallerySave: true }); }
+  catch (error) { failure = error as Error; }
+  expect(creates).toBe(1);
+  expect(failure).toMatchObject({ status: 400 });
+  expect(getRequestFailureDetails(failure)).toMatchObject({ code: "RMBG_INPUT_TOO_LARGE", outcome: "failed" });
+  expect(getRequestFailureDetails(failure).message).toContain("50 MB");
+});
+
+test("formats unsupported by AOS are rejected explicitly without converting or submitting", async () => {
+  for (const format of ["gif", "avif"] as const) {
+    const image = await sharp({ create: { width: 16, height: 16, channels: 3, background: "white" } }).toFormat(format).toBuffer();
+    let creates = 0;
+    const service = rmbgLoader(async () => { creates++; throw new Error("Unexpected provider call"); });
+    let failure: Error | undefined;
+    try { await service.executeRmbgJob({ userId: "test", imageBuffer: image, skipGallerySave: true }); }
+    catch (error) { failure = error as Error; }
+    expect(creates).toBe(0);
+    const details = getRequestFailureDetails(failure);
+    expect(details).toMatchObject({ code: "RMBG_INPUT_FORMAT_UNSUPPORTED", outcome: "failed" });
+    expect(details.message).toContain(format.toUpperCase());
+    expect(details.recommendation).toContain("JPG、PNG 或 WebP");
+  }
+});
+
+test("AOS input rejections retain their cause instead of becoming a generic processing failure", () => {
+  const resolution = getRequestFailureDetails("抠图处理失败：图片分辨率超限（5000x3000），AOS要求宽高都不超过 4096px。请缩小后重试。");
+  expect(resolution).toMatchObject({ code: "RMBG_PROVIDER_RESOLUTION_EXCEEDED", outcome: "failed" });
+  expect(resolution.message).toContain("5000×3000");
+  expect(getRequestFailureDetails("抠图处理失败：图片文件无法识别，请尝试转换为 JPG/PNG 后重试。")).toMatchObject({ code: "RMBG_PROVIDER_INVALID_FILE", outcome: "failed" });
+  expect(getRequestFailureDetails("抠图处理失败：AOS任务创建失败（HTTP 413）: Payload Too Large")).toMatchObject({ code: "RMBG_PROVIDER_FILE_TOO_LARGE", outcome: "failed" });
+  for (const [state, code] of [[-3, "RMBG_PROVIDER_SOURCE_DOWNLOAD_FAILED"], [-5, "RMBG_PROVIDER_URL_TOO_LARGE"], [-7, "RMBG_PROVIDER_INVALID_FILE"], [-8, "RMBG_PROVIDER_PROCESSING_TIMEOUT"], [-11, "RMBG_PROVIDER_EMPTY_RESULT"]] as const) {
+    const details = getRequestFailureDetails(`抠图处理失败：AOS任务失败（状态 ${state}，任务 original-task）: Failed`);
+    expect(details).toMatchObject({ code, outcome: "failed" });
+    expect(details.recommendation).not.toBe("");
+  }
+});
+
+test("the canvas API returns input-limit errors as HTTP 400 and preserves the same advice when polling", async () => {
+  const service = rmbgLoader(async () => { throw new Error("Unexpected provider call"); });
+  const error = new service.RmbgServiceError("抠图参考图分辨率超限（5056×3392 像素），当前 AOS 上游要求宽、高均不超过 4096 像素。", 400);
+  const route = serverLoader({
+    "@/app/(auth)/auth": { auth: async () => ({ user: { id: "user-a" } }) },
+    "@/lib/ai/rmbg/service": { RmbgServiceError: service.RmbgServiceError },
+    "@/lib/canvas/capabilities/client-command": { canvasCapabilityClientCommandSchema: { parse: (v: unknown) => v } },
+    "@/lib/canvas/capabilities/context": { CanvasCapabilityRuntimeError: class extends Error {} },
+    "@/lib/canvas/agent-mutations": { CanvasAgentMutationError: class extends Error {} },
+    "@/lib/canvas/capabilities/registry": { getCanvasCapabilityManifest: () => [] },
+    "@/lib/canvas/capabilities/runtime": { executeCanvasCapabilityRuntime: async () => { throw error; } },
+    "@/lib/canvas/capabilities/task-store": { getCanvasCapabilityTask: async () => ({ id: "task-a", status: "failed", error: error.message }) },
+  })("app/api/canvas/[id]/capabilities/route.ts");
+  const params = { params: Promise.resolve({ id: "project-a" }) };
+  const response = await route.POST(new Request("https://example.com/api/canvas/project-a/capabilities", { method: "POST", body: JSON.stringify({ requestId: "request-a" }) }), params);
+  expect(response.status).toBe(400);
+  const submitted = await response.json();
+  expect(submitted.failure).toMatchObject({ code: "RMBG_INPUT_RESOLUTION_EXCEEDED", outcome: "failed" });
+  expect(submitted.error).toContain("5056×3392");
+  expect(submitted.error).toContain("本次未提交上游抠图任务");
+  const polled = await (await route.GET(new Request("https://example.com/api/canvas/project-a/capabilities?requestId=request-a"), params)).json();
+  expect(polled.task.failure).toEqual(submitted.failure);
+  expect(polled.task.error).toContain(submitted.failure.recommendation);
+});
+
+test("a create timeout preserves its cause and never creates another paid task", async () => {
+  const image = await sharp({ create: { width: 16, height: 16, channels: 3, background: "white" } }).png().toBuffer();
+  let creates = 0;
+  let abort: Error;
+  const service = rmbgLoader(async () => { creates++; throw abort; });
+  abort = new service.RmbgServiceError("request timed out");
+  abort.name = "AbortError";
+  let failure: Error | undefined;
+  try {
+    await service.executeRmbgJob({ userId: "test", imageBuffer: image, sourceImageUrl: `${cdn}/source.png`, skipGallerySave: true });
+  } catch (error) { failure = error as Error; }
+  expect(creates).toBe(1);
+  expect(failure?.message).toContain("AOS创建任务超时（120秒）");
+  expect(getRequestFailureDetails(failure)).toMatchObject({ code: "RMBG_CREATE_TIMEOUT", outcome: "unknown" });
+});
+
+test("poll and result download timeouts retain their original task and distinct advice", () => {
+  const poll = getRequestFailureDetails("抠图处理失败：AOS查询任务超时，结果尚未确认（任务 task-1）");
+  const download = getRequestFailureDetails("抠图处理失败：AOS结果下载超时，任务已完成（任务 task-1）");
+  expect(poll).toMatchObject({ code: "RMBG_POLL_TIMEOUT", outcome: "unknown" });
+  expect(download).toMatchObject({ code: "RMBG_RESULT_DOWNLOAD_TIMEOUT", outcome: "unknown" });
+  expect(download.recommendation).toContain("取回原任务结果");
+  expect(getRequestFailureDetails("抠图处理失败：AOS任务查询失败（HTTP 404，任务 task-1）: Not Found")).toMatchObject({ code: "RMBG_PROVIDER_POLL_FAILED", outcome: "unknown" });
+  expect(getRequestFailureDetails("抠图处理失败：AOS结果下载失败（HTTP 500，任务 task-1）: Internal Error")).toMatchObject({ code: "RMBG_PROVIDER_RESULT_DOWNLOAD_FAILED", outcome: "unknown" });
+  expect(getRequestFailureDetails("抠图处理失败：AOS任务创建失败（HTTP 500）: Internal Error")).toMatchObject({ code: "RMBG_PROVIDER_CREATE_UNCONFIRMED", outcome: "unknown" });
+});
+
+test("network and body interruptions retry only the original task reads", async () => {
+  const image = await sharp({ create: { width: 32, height: 32, channels: 4, background: "#abcdef00" } }).png().toBuffer();
+  let creates = 0, polls = 0, downloads = 0;
+  let networkError: Error;
+  const service = rmbgLoader(async (input, options) => {
+    if (options?.method === "POST") { creates++; return Response.json({ data: { task_id: "original-task" } }); }
+    if (String(input).endsWith("/original-task")) {
+      if (++polls === 1) throw networkError;
+      return Response.json({ data: { state: 1, image: "https://output.example/original.png" } });
+    }
+    if (++downloads === 1) return new Response(new ReadableStream({ start(controller) { controller.error(networkError); } }));
+    return new Response(image, { headers: { "content-type": "image/png" } });
+  });
+  networkError = new service.RmbgServiceError("fetch failed"); networkError.name = "TypeError";
+  const result = await service.executeRmbgJob({ userId: "test", imageBuffer: image, sourceImageUrl: `${cdn}/source.png`, skipGallerySave: true });
+  expect(result.original_url).toContain(cdn);
+  expect({ creates, polls, downloads }).toEqual({ creates: 1, polls: 2, downloads: 2 });
+});
+
+test("exhausted result reads preserve the completed task and never re-create it", async () => {
+  const image = await sharp({ create: { width: 16, height: 16, channels: 3, background: "white" } }).png().toBuffer();
+  let creates = 0, downloads = 0;
+  let networkError: Error;
+  const service = rmbgLoader(async (input, options) => {
+    if (options?.method === "POST") { creates++; return Response.json({ data: { task_id: "completed-task" } }); }
+    if (String(input).endsWith("/completed-task")) return Response.json({ data: { state: 1, image: "https://output.example/original.png" } });
+    downloads++; throw networkError;
+  });
+  networkError = new service.RmbgServiceError("fetch failed"); networkError.name = "TypeError";
+  let failure: Error | undefined;
+  try { await service.executeRmbgJob({ userId: "test", imageBuffer: image, sourceImageUrl: `${cdn}/source.png`, skipGallerySave: true }); }
+  catch (error) { failure = error as Error; }
+  expect({ creates, downloads }).toEqual({ creates: 1, downloads: 3 });
+  expect(failure?.message).toContain("completed-task");
+  expect(getRequestFailureDetails(failure)).toMatchObject({ code: "RMBG_RESULT_DOWNLOAD_CONNECTION_FAILED", outcome: "unknown" });
+});

tests/routes/runtime-active-work.test.ts

@@ -28,3 +28,24 @@ test("durable archive handoff is separate from unfinished original generation",
   complete(); await original;
   expect(records.at(-1)).toMatchObject({ active: 0, durable: 0 });
 });
+
+test("direct matting stays visible to release draining until the provider attempt fails", async () => {
+  const counts: number[] = [];
+  let rejectProvider!: (error: Error) => void;
+  let providerStarted!: () => void;
+  const started = new Promise<void>(resolve => { providerStarted = resolve; });
+  const service = serverLoader({
+    "node:fs": { writeFileSync: (_path: string, value: string) => counts.push(JSON.parse(value).active), unlinkSync() {} },
+    "@/lib/db/queries": { getSystemSetting: async () => ({ value: { provider: "rmbg", apiUrl: "https://provider.example/remove", apiKey: "test" } }) },
+    "@/lib/db": { db: {} }, "@/lib/db/schema": { generatedImage: {} },
+    "@/lib/storage/service": {},
+    fetch: async () => { providerStarted(); return new Promise<Response>((_resolve, reject) => { rejectProvider = reject; }); },
+  })("lib/ai/rmbg/service.ts");
+  const pending = service.executeRmbgJob({ userId: "user-a", imageBuffer: Buffer.from("image"), skipGallerySave: true });
+  const assertion = expect(pending).rejects.toThrow();
+  await started;
+  expect(counts).toEqual([1]);
+  rejectProvider(new Error("provider unavailable"));
+  await assertion;
+  expect(counts).toEqual([1, 0]);
+});