Merge pull request '复用画布识图原图并区分提交前后超时' (#60) from codex/canvas-reference-read-timeout into main

app/api/canvas/agent-chat/route.ts

@@ -329,6 +329,7 @@ export async function POST(request: Request) {
                 withModel,
                 imageSize: snapshot.imagePreferences?.parameters?.imageSize,
                 imagePreferences: snapshot.imagePreferences,
+                priorCalls: snapshot.calls,
                 preferredModelId: snapshot.imagePreferences?.modelId || (preset?.type === "image" ? preset.defaultModelId || undefined : undefined),
                 operationSelectedNodeIds: selectedNodeIds,
                 objective: [snapshot.objective, ...snapshot.inputs.map((input) => input.text)].join(

app/canvas/[id]/CanvasEditorLegacyPageClient.tsx

@@ -5,6 +5,7 @@ import { readCanvasDraft, writeCanvasDraft, clearCanvasDraft } from "@/lib/clien
 import { mergeCanvasSnapshots } from "@/lib/video-canvas/merge-snapshot";
 import { BEFORE_PAGE_REFRESH, type PageRefreshRequest } from "@/lib/client/page-refresh";
 import { CanvasRemoteOperationContext, type CanvasRemoteOperation, type CanvasRemoteOperationResult } from "@/components/canvas/CanvasRemoteOperationContext";
+import equal from "fast-deep-equal";
 import {
   AlertCircle,
   AlertTriangle,
@@ -171,6 +172,7 @@ import {
   type VideoCanvasSymbolMarkerId,
 } from "@/lib/canvas/video-canvas-markers";
 import {
+  isCanvasImageUploadPending,
   LOCAL_UPLOAD_PENDING_METADATA_KEY,
   LOCAL_UPLOAD_PREVIEW_METADATA_KEY,
 } from "@/lib/canvas/local-upload-state";
@@ -5127,13 +5129,14 @@ export default function CanvasEditorLegacyPage({
   canvasPersistenceScope.current = id;
   const hasUnsavedCanvasChanges = useCallback(() => {
     if (!canvasReadyRef.current || useCanvasStore.getState().projectId !== id || savedCanvasSnapshotRef.current?.id !== id) return false;
+    if (useCanvasStore.getState().nodes.some(isCanvasImageUploadPending)) return true;
     const saved = JSON.parse(savedCanvasSnapshotRef.current.snapshot).canvasData as CanvasState;
-    const current = buildPersistedCanvasData();
+    const current = JSON.parse(JSON.stringify(buildPersistedCanvasData())) as CanvasState;
     const content = (value: CanvasState) => [value.nodes.map(node => {
       const { updatedAt: _updatedAt, ...nodeData } = node;
       return { ...nodeData, connections: node.connections || [] };
-    }), value.edges, value.suppressedMediaKeys || [], normalizeStyleProPersistedState(value.styleProState)];
+    }), value.edges || [], value.suppressedMediaKeys || [], normalizeStyleProPersistedState(value.styleProState)];
-    return JSON.stringify(content(saved)) !== JSON.stringify(content(current));
+    return !equal(content(saved), content(current));
   }, [buildPersistedCanvasData, id]);
   const requestCanvasLeave = useCallback((url: string) => {
     if (hasUnsavedCanvasChanges()) {
@@ -5176,7 +5179,7 @@ export default function CanvasEditorLegacyPage({
       try {
         let canvasData = buildPersistedCanvasData();
         let snapshot = JSON.stringify({ canvasData });
-        if (savedCanvasSnapshotRef.current?.id === id && savedCanvasSnapshotRef.current.snapshot === snapshot) {
+        if (savedCanvasSnapshotRef.current?.id === id && equal(JSON.parse(savedCanvasSnapshotRef.current.snapshot), JSON.parse(snapshot))) {
           clearCanvasDraft(id);
           return true;
         }
@@ -5224,8 +5227,8 @@ export default function CanvasEditorLegacyPage({
             snapshot: JSON.stringify({ canvasData: buildPersistedCanvasData() }),
           });
           canvasSyncErrorRef.current = result.status === 409
-            ? "画布同步发生冲突，本次任务未提交，改动已保留。请在画布上方选择保留本页或云端的冲突内容，再继续操作。"
+            ? "画布同步发生冲突，改动已保留。请在画布上方选择保留本页或云端的冲突内容，再继续操作。"
-            : `画布自动同步失败${result.status ? `（HTTP ${result.status}）` : "（网络连接失败）"}，本次任务未提交。${retained ? "本地草稿已保留，请检查网络后再次发送。" : "请保留当前页面，检查网络后再次发送，暂勿刷新。"}`;
+            : `画布自动同步失败${result.status ? `（HTTP ${result.status}）` : "（网络连接失败）"}。${retained ? "本地草稿已保留，系统会继续自动同步，也可稍后重试。" : "请保留当前页面，检查网络后重试同步，暂勿刷新。"}`;
           console.error(`[Canvas] ${reason} save failed:`, result.error);
         } else {
           canvasSyncErrorRef.current = "";
@@ -5258,6 +5261,10 @@ export default function CanvasEditorLegacyPage({
   const finishCanvasLeave = useCallback(async (save: boolean) => {
     if (!canvasLeaveUrl || isSavingBeforeLeave) return;
     setCanvasLeaveError("");
+    if (save && useCanvasStore.getState().nodes.some(isCanvasImageUploadPending)) {
+      setCanvasLeaveError("还有图片未上传成功。请等待上传完成；若上传失败，请重新上传或移除该图片后再保存并离开。");
+      return;
+    }
     if (canvasAutosaveTimer.current) {
       clearTimeout(canvasAutosaveTimer.current);
       canvasAutosaveTimer.current = null;
@@ -5321,7 +5328,7 @@ export default function CanvasEditorLegacyPage({
       return canvasSaveQueue.current!.enqueueOperation(
         async () => {
           const saved = await persistCanvasStateNow("autosave");
-          if (!saved) throw new Error(canvasSyncErrorRef.current || "画布尚未完成加载，本次处理未提交，请等待加载完成后重试。");
+          if (!saved) throw new Error(canvasSyncErrorRef.current ? `${canvasSyncErrorRef.current} 本次处理未提交。` : "画布尚未完成加载，本次处理未提交，请等待加载完成后重试。");
           return true;
         },
         async () => {
@@ -5343,20 +5350,18 @@ export default function CanvasEditorLegacyPage({
 
   const persistCanvasBeforeAgent = useCallback(async () => {
     if (!canvasReadyRef.current || useCanvasStore.getState().projectId !== id || externalCanvasConflictRef.current)
-      throw new Error(canvasSyncErrorRef.current || "画布尚未完成同步，本次任务未提交，请保留当前页面并重试同步。");
+      throw new Error(canvasSyncErrorRef.current ? `${canvasSyncErrorRef.current} 本次任务未提交。` : "画布尚未完成同步，本次任务未提交，请保留当前页面并重试同步。");
     if (savedCanvasSnapshotRef.current?.id === id) {
-      const saved = JSON.parse(savedCanvasSnapshotRef.current.snapshot).canvasData;
+      if (!hasUnsavedCanvasChanges()) return true;
-      const current = buildPersistedCanvasData();
-      if (JSON.stringify(saved.nodes) === JSON.stringify(current.nodes) && JSON.stringify(saved.edges) === JSON.stringify(current.edges)) return true;
     }
     // Flush the pending local edit once instead of racing its scheduled autosave.
     if (canvasAutosaveTimer.current) {
       clearTimeout(canvasAutosaveTimer.current);
       canvasAutosaveTimer.current = null;
     }
-    if (!(await persistCanvasState("autosave"))) throw new Error(canvasSyncErrorRef.current || "画布尚未完成加载，本次任务未提交；请等待加载完成后再次发送。");
+    if (!(await persistCanvasState("autosave"))) throw new Error(canvasSyncErrorRef.current ? `${canvasSyncErrorRef.current} 本次任务未提交。` : "画布尚未完成加载，本次任务未提交；请等待加载完成后再次发送。");
     return true;
-  }, [persistCanvasState, buildPersistedCanvasData, id]);
+  }, [persistCanvasState, hasUnsavedCanvasChanges, id]);
 
   const canvasRemoteOperationContext = useMemo(() => ({
     run: runCanvasRemoteOperation,
@@ -5367,6 +5372,10 @@ export default function CanvasEditorLegacyPage({
     if (isVideoMode) return;
     const beforeRefresh = (event: Event) => {
       const request = (event as CustomEvent<PageRefreshRequest>).detail;
+      if (!isAgentMode && useCanvasStore.getState().nodes.some(isCanvasImageUploadPending)) {
+        request.block("还有图片未上传成功。请等待上传完成；若上传失败，请重新上传或移除该图片后再刷新。");
+        return;
+      }
       if (useCanvasStore.getState().isGenerating) {
         request.block("当前图片任务仍在处理中，请等待结果返回后再刷新。");
         return;
@@ -5543,7 +5552,7 @@ export default function CanvasEditorLegacyPage({
     const handleBeforeUnload = (event: BeforeUnloadEvent) => {
       if (!retainDraft()) return;
       event.preventDefault();
-      event.returnValue = "";
+      event.returnValue = "true";
     };
     const handlePageHide = () => {
       try {

components/app-update-notice.tsx

@@ -68,6 +68,7 @@ export function AppUpdateNotice() {
       </AlertDialogHeader>
       {error ? <p role="alert" className="text-sm text-destructive">{error}</p> : null}
       <AlertDialogFooter>
+        {error ? <Button variant="outline" disabled={refreshing} onClick={() => { setAvailableVersion(""); setError(""); }}>返回处理</Button> : null}
         <Button disabled={refreshing} onClick={() => void refresh()}>{refreshing ? "正在同步内容…" : "同步并刷新"}</Button>
       </AlertDialogFooter>
     </AlertDialogContent>

components/canvas/CanvasChatPanel.tsx

@@ -8972,6 +8972,10 @@ export function CanvasChatPanel({
   useEffect(() => {
     const beforeRefresh = (event: Event) => {
       const request = (event as CustomEvent<PageRefreshRequest>).detail;
+      if (composerUploadProgress) {
+        request.block("素材仍在上传，请等待上传完成后再刷新。当前页面和输入已保留。");
+        return;
+      }
       if (isCanvasAgentRunning || isClawdSubmitting || isDetailGenerating || status === "streaming" || status === "submitted" || Object.values(sendGuardRef.current).some(guard => guard.inFlight)) {
         request.block("当前对话任务仍在处理中，请等待结果返回后再刷新。原任务会继续执行，无需重新提交。");
         return;
@@ -8981,9 +8985,17 @@ export function CanvasChatPanel({
           throw new Error("浏览器无法保存当前输入，请保留此页并检查浏览器存储空间后重试。");
       });
     };
+    const beforeUnload = (event: BeforeUnloadEvent) => {
+      event.preventDefault();
+      event.returnValue = "true";
+    };
     window.addEventListener(BEFORE_PAGE_REFRESH, beforeRefresh);
-    return () => window.removeEventListener(BEFORE_PAGE_REFRESH, beforeRefresh);
+    if (composerUploadProgress) window.addEventListener("beforeunload", beforeUnload);
-  }, [activeChatId, input, attachments, isCanvasAgentRunning, isClawdSubmitting, isDetailGenerating, status]);
+    return () => {
+      window.removeEventListener(BEFORE_PAGE_REFRESH, beforeRefresh);
+      window.removeEventListener("beforeunload", beforeUnload);
+    };
+  }, [activeChatId, input, attachments, composerUploadProgress, isCanvasAgentRunning, isClawdSubmitting, isDetailGenerating, status]);
 
   const restorePendingClawdRequestToComposer = useCallback(
     (snapshot: PendingClawdRequestRestoreSnapshot) => {

lib/ai/canvas-agent-runtime/image-preferences.ts

@@ -13,13 +13,18 @@ export type AgentImageParameters = {
 };
 export type AgentImagePreferences = { modelId?: string; parameters?: AgentImageParameters };
 
+export function selectedAgentImageCount(preferences?: AgentImagePreferences) {
+  const count = preferences?.parameters?.imageCount ?? preferences?.parameters?.n;
+  return count === undefined ? undefined : Math.floor(count);
+}
+
 export function applyAgentImagePreferences<T extends Record<string, unknown>>(
   input: T,
   preferences?: AgentImagePreferences,
 ): T & AgentImageParameters & { modelId?: string } {
   const parameters = Object.fromEntries(Object.entries(preferences?.parameters || {})
     .filter(([, value]) => value !== undefined));
-  const count = preferences?.parameters?.imageCount ?? preferences?.parameters?.n;
+  const count = selectedAgentImageCount(preferences);
   return {
     ...input,
     ...parameters,

lib/ai/canvas-agent-runtime/results.ts

@@ -1,5 +1,14 @@
 import type { AgentCallRecord, AgentRunSnapshot } from "./protocol";
 
+export function countAgentGeneratedImages(calls: AgentCallRecord[]) {
+  return calls.reduce((count, call) => {
+    const output = call.output;
+    if (call.status !== "succeeded" || !output?.appliedImagePreferences ||
+      !Array.isArray(output.createdNodeIds)) return count;
+    return count + output.createdNodeIds.length;
+  }, 0);
+}
+
 // A spontaneous download command is not an unfinished image edit. Keep genuine
 // download requests and all editor panels waiting for their actual interaction.
 export function isAncillaryDownload(snapshot: AgentRunSnapshot, call: AgentCallRecord) {

lib/ai/canvas-agent-runtime/review.ts

@@ -5,7 +5,8 @@ import sharp from "sharp";
 import { z } from "zod";
 import { readCanvasImages, readOwnedCanvas, type RuntimeImageNode } from "./canvas";
 import type { AgentRunSnapshot } from "./protocol";
-import { finalResultNodeIds, originalSourceNodeIds, requiresCanvasInteraction } from "./results";
+import { countAgentGeneratedImages, finalResultNodeIds, originalSourceNodeIds, requiresCanvasInteraction } from "./results";
+import { selectedAgentImageCount } from "./image-preferences";
 import { isCompletedSimpleCutout } from "./cutout-completion";
 
 export async function inspectImageAlpha(source: Buffer) {
@@ -124,14 +125,16 @@ export async function verifyCanvasAgentResults(params: {
     (call) =>
       call.status !== "succeeded" ||
       requiresCanvasInteraction(snapshot, call) ||
-      (typeof call.output?.status === "string" && call.output.status !== "succeeded"),
+      (typeof call.output?.status === "string" && call.output.status !== "succeeded" &&
+        !(call.output.status === "partial" && call.output.appliedImagePreferences)),
   );
   if (incomplete.length) return { passed: false, issues: ["部分操作仍在等待交互或未完成"] };
   const plan = calls.filter((call) => call.name === "planCanvasTask").at(-1)?.output;
   if (!plan) return { passed: false, issues: ["缺少明确的任务验收计划"] };
   // Intermediate images consumed by later write tools do not count as final deliverables.
   const finalIds = finalResultNodeIds(snapshot);
-  const expectedCount = snapshot.requirements?.expectedImageCount ?? plan.expectedImageCount;
+  const expectedCount = snapshot.requirements?.expectedImageCount ?? plan.expectedImageCount ??
+    (countAgentGeneratedImages(calls) > 0 ? selectedAgentImageCount(snapshot.imagePreferences) : undefined);
   if (expectedCount && finalIds.length !== expectedCount) {
     return {
       passed: false,

lib/ai/canvas-agent-runtime/tools.ts

@@ -1,5 +1,11 @@
 import type { AgentVisionExecutor } from "../runtime/agent-vision-failover";
-import { resolveUserImageModel, applyAgentImagePreferences, agentProviderImageParameters, type AgentImagePreferences } from "./image-preferences";
+import {
+  agentProviderImageParameters,
+  applyAgentImagePreferences,
+  resolveUserImageModel,
+  selectedAgentImageCount,
+  type AgentImagePreferences,
+} from "./image-preferences";
 import { tool, type LanguageModel, type ToolSet } from "ai";
 import { z } from "zod";
 import { createCanvasCapabilityTools } from "@/lib/canvas/capabilities/ai-sdk-tools";
@@ -18,6 +24,8 @@ import {
   sortStyleProImageModelEntries,
 } from "@/lib/style-pro/model-options";
 import type { CanvasAgentLoopPorts, CanvasAgentTool } from "./loop";
+import { AgentToolRejectedError, type AgentCallRecord } from "./protocol";
+import { countAgentGeneratedImages } from "./results";
 import { readCanvasImages, readOwnedCanvas } from "./canvas";
 import { analyzeRuntimeImages } from "./review";
 import { isExplicitDestructiveIntent } from "./capability-access";
@@ -37,11 +45,13 @@ export async function buildCanvasRuntimeTools(params: {
   imageSize?: string;
   preferredModelId?: string;
   imagePreferences?: AgentImagePreferences;
+  priorCalls?: AgentCallRecord[];
   emit: (type: string, data: unknown) => void;
   objective?: string;
   operationSelectedNodeIds?: string[];
 }) {
   const { nodes } = await readOwnedCanvas(params.userId, params.projectId);
+  const selectedImageCount = selectedAgentImageCount(params.imagePreferences);
   const imageNodeIds = nodes.filter((node) => node.type === "image").map((node) => node.id);
   const defaults = params.selectedNodeIds.filter((id) => imageNodeIds.includes(id));
   const sdk = await createCanvasCapabilityTools({
@@ -128,8 +138,8 @@ export async function buildCanvasRuntimeTools(params: {
       visualCriteria: z.array(z.string().max(200)).max(10),
     }),
     async (input) => ({ ...input,
-      ...(input.expectedImageCount !== undefined && params.imagePreferences?.parameters?.imageCount !== undefined
+      ...(input.expectedImageCount !== undefined && selectedImageCount !== undefined
-        ? { expectedImageCount: params.imagePreferences.parameters.imageCount } : {}),
+        ? { expectedImageCount: selectedImageCount } : {}),
       ...(params.imagePreferences?.parameters?.aspectRatio && params.imagePreferences.parameters.aspectRatio !== "auto"
         ? { aspectRatio: params.imagePreferences.parameters.aspectRatio } : {}),
     }),
@@ -163,6 +173,8 @@ export async function buildCanvasRuntimeTools(params: {
       };
     },
   );
+  const inspectedImages = new Map<string, Buffer>();
+  let inspectedImageBytes = 0;
   register(
     "analyzeCanvasImages",
     "检查图片",
@@ -171,10 +183,28 @@ export async function buildCanvasRuntimeTools(params: {
       nodeIds: z.array(z.string().min(1).max(180)).min(1).max(4),
       question: z.string().min(1).max(2000),
     }),
-    async (input) => analyzeRuntimeImages({ ...params, ...input }),
+    async (input) => analyzeRuntimeImages({
+      ...params,
+      ...input,
+      reviewPorts: {
+        readImage: async (url) => {
+          const cached = inspectedImages.get(url);
+          if (cached) return cached;
+          const { fetchImageBufferFromUrl } = await import("@/lib/ai/rmbg/service");
+          const original = await fetchImageBufferFromUrl(url);
+          if (!inspectedImages.has(url) && inspectedImageBytes + original.length <= 32 * 1024 * 1024) {
+            inspectedImages.set(url, original);
+            inspectedImageBytes += original.length;
+          }
+          return original;
+        },
+      },
+    }),
   );
 
-  let generatedCount = 0;
+  let submittedCount = 0;
+  let occupiedImageSlots = countAgentGeneratedImages(params.priorCalls ?? []);
+  const countLimitMessage = "本次设定的生成张数已占满，请先查看正在生成或已经生成的结果。";
   register(
     "generateCanvasImages",
     "生成图片",
@@ -189,9 +219,8 @@ export async function buildCanvasRuntimeTools(params: {
     }),
     async (toolInput, callId) => {
       const input = applyAgentImagePreferences(toolInput, params.imagePreferences);
-      // Bound per-task spend without introducing any global/model concurrency queue.
+      if (selectedImageCount !== undefined && occupiedImageSlots >= selectedImageCount)
-      if (generatedCount + input.imageCount > 24)
+        throw new AgentToolRejectedError(countLimitMessage);
-        throw new Error("本次任务已达到 24 张生成预算，请检查结果后继续。");
       const sources = await readCanvasImages(
         params.userId,
         params.projectId,
@@ -214,10 +243,17 @@ export async function buildCanvasRuntimeTools(params: {
       if (!chosen) throw new Error("系统未配置可用的图片生成模型");
       const imageSize = input.imageSize || params.imageSize || "2K";
       const quota = await checkUserImageQuota(params.userId);
-      if (!quota.allowed || (quota.remaining !== null && input.imageCount > quota.remaining))
-        throw new Error("本月图片生成配额不足。");
       const points = await getPointsSystemConfig();
       const user = await getUserById({ id: params.userId });
+      // Reserve the remaining slots before dispatch, including calls still in flight.
+      if (selectedImageCount !== undefined) {
+        input.imageCount = Math.min(input.imageCount, selectedImageCount - occupiedImageSlots);
+        if (input.imageCount < 1) throw new AgentToolRejectedError(countLimitMessage);
+      }
+      if (submittedCount + input.imageCount > 24)
+        throw new AgentToolRejectedError("本次任务已达到 24 张生成预算，请检查结果后继续。");
+      if (!quota.allowed || (quota.remaining !== null && input.imageCount > quota.remaining))
+        throw new Error("本月图片生成配额不足。");
       const cost =
         getModelGenerationCreditCost(
           { imageGenConfig: chosen.model.imageGenConfig as DiscountableImageGenConfigLike | null },
@@ -231,7 +267,8 @@ export async function buildCanvasRuntimeTools(params: {
         (user?.pointsBalance ?? 0) < cost
       )
         throw new Error("积分不足，请充值或联系管理员。");
-      generatedCount += input.imageCount;
+      submittedCount += input.imageCount;
+      occupiedImageSlots += input.imageCount;
       const result = await generateCanvasImage({
         prompt: input.prompt,
         model: chosen.model.id,
@@ -247,6 +284,7 @@ export async function buildCanvasRuntimeTools(params: {
           ? Math.max(0, user?.pointsBalance ?? 0) / input.imageCount : undefined,
         ownerKey: params.userId,
         referenceImages: sources.map((node) => node.data.src || node.data.url!),
+        referenceImageBuffers: inspectedImages,
         debugLabel: "canvas-agent-runtime",
         debugMeta: { runId: params.runId, callId },
       });
@@ -311,6 +349,7 @@ export async function buildCanvasRuntimeTools(params: {
         },
       );
       }
+      occupiedImageSlots += result.images.length - input.imageCount;
       return {
         status: result.images.length < input.imageCount ? "partial" : "succeeded",
         appliedImagePreferences: { modelId: result.modelRef, imageSize, aspectRatio: input.aspectRatio, imageCount: input.imageCount },

lib/ai/providers/alibaba-image.ts

@@ -12,6 +12,7 @@ import sharp from "sharp";
 import { constrainImageDimensions } from "@/lib/ai/image-size-constraints";
 import { isAlibabaImageTextToImageModelId } from "@/lib/ai/model-classification";
 import { buildReferenceImageOrderPrompt } from "@/lib/ai/providers/reference-image-order";
+import { ImageReferenceReadTimeoutError } from "@/lib/ai/runtime/image-generation-error";
 import { createDeferredUploadedImage } from "@/lib/storage/image-archive";
 import { uploadFile } from "@/lib/storage/service";
 import { normalizeLegacyAliyunStorageUrl } from "@/lib/storage/retired-storage";
@@ -165,7 +166,7 @@ async function fetchImageBufferWithRetry(
     }
   }
 
-  throw lastError instanceof Error ? lastError : new Error(String(lastError || "下载图片失败"));
+  throw lastError ?? new Error("下载图片失败");
 }
 
 function calculateAlibabaSizeByAspect(aspectValue: number, baseSize: number): string {
@@ -289,12 +290,20 @@ async function prepareAlibabaInputImageUrl(
   imageUrl: string,
   modelId: string,
   inputRole?: AlibabaImageInputRole,
+  original?: Buffer,
 ): Promise<string> {
   const normalizedUrl = String(imageUrl || "").trim();
   if (!/^https?:\/\//i.test(normalizedUrl)) return normalizedUrl;
 
   const maxInputBytes = getAlibabaMaxInputBytes(modelId);
-  const { buffer, contentType } = await fetchImageBufferWithRetry(normalizedUrl);
+  const { buffer, contentType } = original
+    ? { buffer: original, contentType: null }
+    : await fetchImageBufferWithRetry(normalizedUrl).catch((error) => {
+        if (["AbortError", "TimeoutError"].includes(error?.name)) {
+          throw new ImageReferenceReadTimeoutError();
+        }
+        throw error;
+      });
   let metadata: sharp.Metadata;
   try {
     metadata = await sharp(buffer, { failOn: "none" }).metadata();
@@ -561,7 +570,7 @@ async function sendAlibabaImageAsyncRequest(params: {
     url: params.requestURL,
   });
   const taskId = String(submitted.output?.task_id || "").trim();
-  if (!taskId) throw new Error("阿里图片异步任务未返回 task_id");
+  if (!taskId) throw new Error("阿里图片异步任务未返回 task_id，结果尚未确认");
 
   const taskURL = resolveAlibabaImageTaskEndpoint(params.requestURL, taskId);
   const startedAt = Date.now();
@@ -585,7 +594,7 @@ async function sendAlibabaImageAsyncRequest(params: {
         console.log("[Alibaba Image] Async task completed:", taskId);
         return task;
       }
-      if (["FAILED", "CANCELED", "UNKNOWN"].includes(taskStatus)) {
+      if (["FAILED", "CANCELED"].includes(taskStatus)) {
         const reason = task.output?.message || task.message || `阿里图片任务${taskStatus || "失败"}`;
         const code = task.output?.code || task.code;
         throw new AlibabaImageTerminalTaskError(
@@ -601,7 +610,7 @@ async function sendAlibabaImageAsyncRequest(params: {
         error.status < 500 &&
         ![408, 425, 429].includes(error.status)
       ) {
-        throw error;
+        throw new Error(`阿里图片任务已提交，结果尚未确认（task_id: ${taskId}）`, { cause: error });
       }
       lastPollError = error;
       console.warn("[Alibaba Image] Async task poll failed; retrying:", {
@@ -723,6 +732,7 @@ export function createAlibabaImage({ apiKey, baseURL }: AlibabaImageConfig) {
       doGenerate: async (options: {
         messages: Array<{ role: string; content: string | Array<{ type: string; text?: string; image?: string }> }>;
         imageParams?: AlibabaImageParams & { aspectRatio?: string; imageSize?: string; imageCount?: number };
+        referenceImageBuffers?: ReadonlyMap<string, Buffer>;
         modelDisplayName?: string; // 🆕 模型显示名称，用于错误提示
         overrideModelId?: string; // 🆕 备用模型 ID
       }) => {
@@ -798,6 +808,7 @@ export function createAlibabaImage({ apiKey, baseURL }: AlibabaImageConfig) {
                 imageUrl,
                 activeModelId,
                 options.imageParams?.inputImageRoleByUrl?.[imageUrl],
+                options.referenceImageBuffers?.get(imageUrl),
               ),
             ),
           );
@@ -938,7 +949,9 @@ export function createAlibabaImage({ apiKey, baseURL }: AlibabaImageConfig) {
           );
           
           // 处理响应
-          const images = await processResponse(response);
+          const images = await processResponse(response).catch((error) => {
+            throw new Error("阿里图片任务已提交，结果尚未确认。", { cause: error });
+          });
           const markdownText = formatImageResponse(images, params.size, imageSize);
           
           console.log(`[Alibaba Image] Generated ${images.length} images successfully`);

lib/ai/runtime/image-generation-error.ts

@@ -8,6 +8,12 @@ export class AgentImageGenerationError extends Error {
   constructor(message: string, readonly confirmedNoResult: boolean) { super(message); }
 }
 
+export class ImageReferenceReadTimeoutError extends AgentImageGenerationError {
+  constructor() {
+    super("提交生图前读取参考图超时，任务尚未提交，可以稍后重试。", true);
+  }
+}
+
 /** Preserve outcome evidence when replacing upstream diagnostics with safe UI text. */
 export function agentImageGenerationError(error: unknown, mode: "auto" | "pinned") {
   const rejected = error instanceof ImageSubmissionRejectedError;

lib/ai/zcode-agent/task.ts

@@ -7,7 +7,8 @@ import type { CanvasAgentTool } from "@/lib/ai/canvas-agent-runtime/loop";
 import { AgentToolRejectedError, publicAgentError, type AgentCallRecord, type AgentRunSnapshot, type CanvasAgentRunStatus } from "@/lib/ai/canvas-agent-runtime/protocol";
 import { formatRequestFailure, getRequestFailureDetails } from "@/lib/request-error";
 import { isCompletedSimpleCutout } from "@/lib/ai/canvas-agent-runtime/cutout-completion";
-import { requiresCanvasInteraction } from "@/lib/ai/canvas-agent-runtime/results";
+import { countAgentGeneratedImages, requiresCanvasInteraction } from "@/lib/ai/canvas-agent-runtime/results";
+import { selectedAgentImageCount } from "@/lib/ai/canvas-agent-runtime/image-preferences";
 import { AgentImageGenerationError } from "@/lib/ai/runtime/image-generation-error";
 import { publicAssistantText } from "./assistant-output";
 
@@ -49,6 +50,16 @@ export async function runZcodeCanvasTask(ports: Ports): Promise<CanvasAgentRunSt
     if (!details.recommendation) details.recommendation = "请联系管理员并提供请求编号，核对该步骤的错误。";
     return `${call.title || "创作工具"}：${formatRequestFailure(details, ports.runId)}`;
   }
+  function imageCountReached() {
+    const count = snapshot.workspace === "video" ? undefined : selectedAgentImageCount(snapshot.imagePreferences);
+    return count !== undefined && countAgentGeneratedImages(snapshot.calls) >= count;
+  }
+  function reviewMessage(issues: string[]) {
+    const summary = `结果待核对：${issues.join("；")}`;
+    return imageCountReached()
+      ? `${summary}\n\n已保留本次生成的图片。如需再生成，请发送新指令。`
+      : summary;
+  }
   let modelError = "";
   let toolFailure = "";
   let nativeFailed = false;
@@ -84,6 +95,7 @@ export async function runZcodeCanvasTask(ports: Ports): Promise<CanvasAgentRunSt
       `可用业务工具：${tools.join("、")}。工具名称带 mcp__canvas__ 前缀。`,
       "原生文件、Bash、记忆及子任务能力仅作用于此任务的私有工作区，不能通过 shell 直接访问模型服务商或本站后台；业务操作使用 MCP。",
       "用户只要求生图或改图时，把结果写入画布并验收即可。除非用户明确要求下载或导出，不要主动调用 image_download，也不要为收尾打开交互面板。",
+      "用户设置的生成张数是本次任务的总数，包括验收未通过的已生成图片。达到张数后，保留结果并说明问题；如需再次生成，等待用户发送新指令。",
       "用户指定的生图模型被明确拒绝时，停止本轮收费操作，询问用户希望切换生图模型还是稍后重试。切换需用户确认并更新模型选择；结果未知的超时必须先核对原任务，不可直接换模型重发。不要为普通图片编辑调用 appearance.post 或其他无关业务接口。",
       "imagePreferences 是用户在输入框选择的生图模型和图片参数，与当前规划模型不同。生成和编辑图片优先用 generateCanvasImages；用户选定的模型不得被技能默认值、你选的其他模型或重试覆盖。自动选择生图模型时，图片工具内部会在明确失败后切换备用模型并补齐结果，不要自行重放付费操作；用户明确指定模型时禁止故障切换。比例、尺寸、数量、反向提示词等控件必须传入；不要通过其他生成接口绕过用户选择。分析、问答、排版等不需要出图的任务无需生成图片。",
       "转正面、换角度、旋转主体视角时，直接用 generateCanvasImages，referenceNodeIds 指向要编辑的真实图片，提示词描述目标视角并保留产品结构和未要求修改的细节。旧多视角功能、angleEditImage 和 image.multi_angle 已废弃，即使历史对话用过也不得再调用或打开旧面板。",
@@ -277,12 +289,12 @@ export async function runZcodeCanvasTask(ports: Ports): Promise<CanvasAgentRunSt
       const verification = await ports.verify(reviewSnapshot); snapshot.verification = verification;
       snapshot.inputTokens = reviewSnapshot.inputTokens; snapshot.outputTokens = reviewSnapshot.outputTokens;
       if (verification.passed) return await save(result.response || "任务完成，结果已写入画布。", "completed");
-      if (verification.retryable && snapshot.repairs < 2) {
+      if (verification.retryable && snapshot.repairs < 2 && !imageCountReached()) {
         snapshot.repairs++;
         prompt = `验收需要定点修复：${JSON.stringify(verification)}。只处理失败结果，禁止整批重新生成；保留所有通过结果。`;
         continue;
       }
-      return await save(`结果待核对：${verification.issues.join("；")}`, "needs_review");
+      return await save(reviewMessage(verification.issues), "needs_review");
     }
   } catch (error) {
     if (snapshot.nativeRuntime) snapshot.nativeRuntime.state = "stopped";
@@ -306,7 +318,7 @@ export async function runZcodeCanvasTask(ports: Ports): Promise<CanvasAgentRunSt
         if (control.cancelled || ports.signal.aborted) return await save("已停止后续步骤，完成的结果保留在画布。", "cancelled");
         if (inputs !== JSON.stringify(snapshot.inputs)) return await save("已收到新的补充要求，图片已保留，请继续处理。", "needs_review");
         return await save(verification.passed ? "图片已完成并通过检查，结果已保留在画布。"
-          : `图片已返回画布，结果待核对：${verification.issues.join("；")}`, verification.passed ? "completed" : "needs_review");
+          : `图片已返回画布，${reviewMessage(verification.issues)}`, verification.passed ? "completed" : "needs_review");
       } catch { /* Keep the original interruption if independent inspection also fails. */ }
     }
     return await save(cancelled ? "已停止后续步骤，完成的结果保留在画布。" : toolFailure || modelError || publicAgentError(error), cancelled ? "cancelled" : "needs_review");

lib/canvas/generate-image.ts

@@ -5,7 +5,7 @@ import sharp from "sharp";
 import { agentImageCircuitStore } from "@/lib/ai/runtime/agent-model-circuit-store";
 import { getModelGenerationCreditCost, type DiscountableImageGenConfigLike } from "@/lib/ai/image-model-pricing";
 import { agentImageFailurePolicy } from "@/lib/ai/runtime/agent-image-failover";
-import { agentImageGenerationError } from "@/lib/ai/runtime/image-generation-error";
+import { agentImageGenerationError, ImageReferenceReadTimeoutError } from "@/lib/ai/runtime/image-generation-error";
 import { getAiModelById, getEnabledAiModelsWithProvider } from "@/lib/db/queries";
 import { fetchImageBufferFromUrl } from "@/lib/ai/rmbg/service";
 import { createGeminiImage } from "@/lib/ai/providers/gemini-image";
@@ -181,6 +181,7 @@ export interface CanvasGenerateImageRequest {
   providerImageParams?: Record<string, unknown>;
   referenceImage?: string;
   referenceImages?: string[];
+  referenceImageBuffers?: ReadonlyMap<string, Buffer>;
   billingFeature?: "multi-view" | "repaint";
   requiredReferenceImageCount?: number;
   ownerKey?: string;
@@ -5121,8 +5122,11 @@ export async function generateCanvasImage(
     });
   }
 
-  const { kept: reachableReferenceImages, dropped: unreachableReferenceImages } =
+  const referenceImageBuffers = provider.type === "alibaba-image" ? request.referenceImageBuffers : undefined;
-    await filterReachableRemoteUrls(normalizedReferenceImages, { timeoutMs: 3000 });
+  const referencesToCheck = normalizedReferenceImages.filter(url => !referenceImageBuffers?.has(url));
+  const { kept, dropped: unreachableReferenceImages } =
+    await filterReachableRemoteUrls(referencesToCheck, { timeoutMs: 3000 });
+  const reachableReferenceImages = normalizedReferenceImages.filter(url => referenceImageBuffers?.has(url) || kept.includes(url));
   const effectiveReferenceImages = selectCanvasReferenceImages({
     requested: normalizedReferenceImages, reachable: reachableReferenceImages,
     requiredCount: request.requiredReferenceImageCount,
@@ -5233,6 +5237,7 @@ export async function generateCanvasImage(
     executeGenerateBatch = async (batchImageCount) => {
       const result = await modelInstance.doGenerate({
         messages,
+        referenceImageBuffers,
         imageParams: {
           ...imageParams,
           imageCount: batchImageCount,
@@ -5662,6 +5667,11 @@ export async function generateCanvasImage(
     await slot.release();
   }
 
+  if (caughtError instanceof ImageReferenceReadTimeoutError) {
+    if (!collectedImages.length) throw caughtError;
+    return { images: collectedImages, model: selectedModel.model.displayName, modelRef: selectedModel.model.id, prompt: resultPrompt };
+  }
+
   // An accepted or uncertain request must not start another paid model/variant.
   if (caughtError && (
     caughtError instanceof ProviderTaskUncertainError ||

lib/request-error.ts

@@ -293,6 +293,9 @@ export function getRequestFailureDetails(
   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 (/提交生图前读取参考图超时/.test(text)) {
+    return detail("IMAGE_REFERENCE_READ_TIMEOUT", "提交生图前读取参考图超时，任务尚未提交。", "可以稍后重试。");
+  }
   const errorName = isRecord(error) ? String(error.name || "") : "";
   if (["AbortError", "TimeoutError"].includes(errorName) || /operation was aborted/i.test(text)) {
     return detail("RESULT_UNCONFIRMED", errorName === "TimeoutError" ? "请求等待超时，任务结果尚未确认。" : "本次请求连接已中止，任务结果尚未确认。", "请先核对原任务或历史记录；持续没有结果时联系管理员，避免重复生成。", "unknown");

tests/e2e/canvas-autosync.test.ts

@@ -13,9 +13,13 @@ async function setup(page: Page, failRead = false) {
     writes: [] as any[], metadataWrites: 0, submissions: [] as any[], capabilitySubmissions: [] as any[],
     appVersion: "development", holdRequest: false, finishRequest: null as (() => void) | null,
     nativeResultNext: false,
+    holdUpload: false, uploadStarted: 0, finishUpload: null as (() => void) | null,
   };
   const revision = () => new Date(Date.UTC(2026, 10, 6, 0, 0, state.revision)).toISOString();
-  const project = () => ({ id: projectId, title: "同步验证", canvasData: state.canvasData, updatedAt: revision() });
+  const project = () => ({ id: projectId, title: "同步验证", canvasData: JSON.parse(JSON.stringify(state.canvasData, (_key, value) =>
+    value && typeof value === "object" && !Array.isArray(value)
+      ? Object.fromEntries(Object.entries(value).sort(([a], [b]) => a.localeCompare(b)))
+      : value)), updatedAt: revision() });
   const errors: string[] = [];
   page.on("pageerror", error => errors.push(error.message));
   await page.context().addInitScript(() => localStorage.setItem("theme", "light"));
@@ -24,6 +28,10 @@ async function setup(page: Page, failRead = false) {
     const path = new URL(request.url()).pathname;
     let data: unknown = {};
     let status = 200;
+    if (path.startsWith("/api/files/") && request.method() === "POST" && state.holdUpload) {
+      state.uploadStarted++;
+      await new Promise<void>(resolve => { state.finishUpload = resolve; });
+    }
     if (path === `/api/canvas/${projectId}`) {
       if (request.method() === "GET") {
         status = state.failRead ? 500 : 200;
@@ -108,8 +116,9 @@ async function moveImage(page: Page) {
 
 const unloadWouldBeBlocked = (page: Page) => page.evaluate(() => {
   const event = new Event("beforeunload", { cancelable: true });
+  Object.defineProperty(event, "returnValue", { value: "", writable: true });
   window.dispatchEvent(event);
-  return event.defaultPrevented;
+  return event.defaultPrevented && Boolean(event.returnValue);
 });
 
 test("background saving recovers when the network returns without a manual save", async ({ page }) => {
@@ -127,6 +136,18 @@ test("background saving recovers when the network returns without a manual save"
   expect(errors).toEqual([]);
 });
 
+test("selecting a saved image does not require another save before an Agent message", async ({ page }) => {
+  const { state, errors } = await setup(page);
+  await page.locator('[data-canvas-node-id="source"]').click();
+  state.failSave = true;
+  const editor = page.getByLabel("描述你的设计需求", { exact: true });
+  await editor.fill("分析这张已经保存的图片");
+  await editor.press("Enter");
+  await expect.poll(() => state.submissions.length).toBe(1);
+  expect(state.canvasData.nodes.map(node => node.id)).toEqual(["source"]);
+  expect(errors).toEqual([]);
+});
+
 test("only unsaved content blocks closing and beforeunload does not issue duplicate saves", async ({ page }) => {
   const { state, errors } = await setup(page);
   expect(await unloadWouldBeBlocked(page)).toBe(false);
@@ -259,6 +280,7 @@ test("toolbar save failures show the cause and recover without a paid submission
   state.failSave = true;
   await page.locator('[data-tool-key="enhance"]').click();
   await expect(page.getByText(/画布自动同步失败（HTTP 503）/)).toBeVisible();
+  await expect(page.getByText(/本次处理未提交/)).toBeVisible();
   expect(state.capabilitySubmissions).toHaveLength(0);
   state.failSave = false;
   await page.locator('[data-tool-key="enhance"]').click();
@@ -430,6 +452,70 @@ async function countRefreshes(page: Page, state: { appVersion: string }) {
   return () => navigations;
 }
 
+test("unfinished image uploads remain on the page even after their canvas placeholder was saved", async ({ page }) => {
+  const { state, errors } = await setup(page);
+  const refreshes = await countRefreshes(page, state);
+  state.holdUpload = true;
+  await page.mouse.click(100, 90);
+  await page.evaluate(() => {
+    const bytes = Uint8Array.from(atob("iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mP8/x8AAwMCAO+j2d0AAAAASUVORK5CYII="), c => c.charCodeAt(0));
+    const transfer = new DataTransfer();
+    transfer.items.add(new File([bytes], "上传保护.png", { type: "image/png" }));
+    window.dispatchEvent(new ClipboardEvent("paste", { clipboardData: transfer, bubbles: true, cancelable: true }));
+  });
+  await expect.poll(() => state.uploadStarted).toBeGreaterThan(0);
+  await expect.poll(() => state.canvasData.nodes.filter(node => node.data.src === "").length).toBe(1);
+  expect(await unloadWouldBeBlocked(page)).toBe(true);
+  await page.getByRole("button", { name: "返回首页", exact: true }).click();
+  const dialog = page.getByRole("dialog", { name: "离开前保存画布？" });
+  await dialog.getByRole("button", { name: "保存并离开", exact: true }).click();
+  await expect(dialog.getByRole("alert")).toContainText("还有图片未上传成功");
+  await dialog.getByRole("button", { name: "继续编辑", exact: true }).click();
+  await showUpdate(page, state);
+  await page.getByRole("button", { name: "同步并刷新", exact: true }).click();
+  await expect(page.getByRole("alertdialog")).toContainText("还有图片未上传成功");
+  expect(refreshes()).toBe(0);
+  state.holdUpload = false;
+  state.finishUpload?.();
+  await expect.poll(() => state.canvasData.nodes.some(node => node.data.src.includes("uploaded.png"))).toBe(true);
+  await page.getByRole("button", { name: "同步并刷新", exact: true }).click();
+  await expect.poll(refreshes).toBe(1);
+  expect(state.canvasData.nodes).toHaveLength(2);
+  expect(state.submissions).toHaveLength(0);
+  expect(errors).toEqual([]);
+});
+
+test("a composer upload blocks release refresh and closing until the image and input are retained", async ({ page }) => {
+  const { state, errors } = await setup(page);
+  const refreshes = await countRefreshes(page, state);
+  state.holdUpload = true;
+  const editor = page.getByLabel("描述你的设计需求", { exact: true });
+  await editor.fill("上传后保留这条输入");
+  await editor.evaluate(element => {
+    const transfer = new DataTransfer();
+    transfer.items.add(new File([new Uint8Array([137, 80, 78, 71])], "聊天上传保护.png", { type: "image/png" }));
+    element.dispatchEvent(new ClipboardEvent("paste", { clipboardData: transfer, bubbles: true, cancelable: true }));
+  });
+  await expect.poll(() => state.uploadStarted).toBeGreaterThan(0);
+  await expect(page.getByText("聊天上传保护.png", { exact: true })).toBeVisible();
+  expect(await unloadWouldBeBlocked(page)).toBe(true);
+  await showUpdate(page, state);
+  await page.getByRole("button", { name: "同步并刷新", exact: true }).click();
+  await expect(page.getByRole("alertdialog")).toContainText("素材仍在上传");
+  expect(refreshes()).toBe(0);
+  state.holdUpload = false;
+  state.finishUpload?.();
+  await expect.poll(() => state.canvasData.nodes.some(node => node.data.src.includes("uploaded.png"))).toBe(true);
+  await expect(page.getByText("聊天上传保护.png", { exact: true })).toHaveCount(1);
+  await page.getByRole("button", { name: "同步并刷新", exact: true }).click();
+  await expect.poll(refreshes).toBe(1);
+  await expect(editor).toContainText("上传后保留这条输入");
+  await expect(editor.getByText("聊天上传保护.png", { exact: true })).toBeVisible();
+  expect(state.canvasData.nodes).toHaveLength(2);
+  expect(state.submissions).toHaveLength(0);
+  expect(errors).toEqual([]);
+});
+
 test("an older browser without AbortSignal static helpers receives the release notice", async ({ page }) => {
   await page.context().addInitScript(() => {
     Object.defineProperty(AbortSignal, "any", { value: undefined, configurable: true });
@@ -504,9 +590,19 @@ test("an update keeps the current page when automatic synchronization fails", as
   await showUpdate(page, state);
   await page.getByRole("button", { name: "同步并刷新", exact: true }).click();
   await expect(page.getByRole("alertdialog")).toContainText("HTTP 503");
+  await expect(page.getByRole("alertdialog")).not.toContainText("本次任务未提交");
+  await expect(page.getByRole("alertdialog")).not.toContainText("再次发送");
   expect(refreshes()).toBe(0);
   expect(state.submissions).toHaveLength(0);
+  await page.screenshot({ path: test.info().outputPath("update-error-desktop.png"), animations: "disabled" });
+  await page.setViewportSize({ width: 390, height: 844 });
+  await page.screenshot({ path: test.info().outputPath("update-error-mobile.png"), animations: "disabled" });
+  await page.setViewportSize({ width: 1440, height: 900 });
+  await page.getByRole("button", { name: "返回处理", exact: true }).click();
+  await expect(page.getByRole("alertdialog")).toHaveCount(0);
+  await expect(page.locator('[data-canvas-node-id="source"]')).toBeVisible();
   state.failSave = false;
+  await showUpdate(page, state);
   await page.getByRole("button", { name: "同步并刷新", exact: true }).click();
   await expect.poll(refreshes).toBe(1);
   expect(state.canvasData.nodes[0].position.x).toBeGreaterThan(160);

tests/routes/alibaba-task-errors.test.ts

@@ -32,6 +32,7 @@ test("Qwen 3 sends reference bytes directly with the right MIME and keeps auto r
   const jpeg = await sharp(png).jpeg().toBuffer();
   const webp = await sharp(png).webp().toBuffer();
   const originals = [png, jpeg, webp];
+  const downloads: number[] = [];
   let submitted: any;
   let posts = 0;
   const loader = serverLoader({
@@ -41,14 +42,16 @@ test("Qwen 3 sends reference bytes directly with the right MIME and keeps auto r
       if (init.method === "POST") { posts++; submitted = JSON.parse(String(init.body)); return Response.json({ output: { task_id: "inline-task", task_status: "PENDING" } }); }
       if (url.includes("/tasks/")) return Response.json({ output: { task_status: "FAILED", message: "transport-inspection-complete" } });
       const index = Number(new URL(url).pathname.slice(1));
+      downloads.push(index);
       return new Response(originals[index], { headers: { "content-type": ["image/png", "image/jpeg", "image/webp"][index] } });
     },
   });
   const provider = loader("lib/ai/providers/alibaba-image.ts").createAlibabaImage({ apiKey: "fixture-key", baseURL: "https://dashscope.example" });
   await expect(provider.chat("qwen-image-3.0").doGenerate({ messages: [{ role: "user", content: [
     { type: "text", text: "fixture" }, ...originals.map((_bytes, index) => ({ type: "image", image: `https://source.example/${index}` })),
-  ] }], imageParams: { aspectRatio: "auto", imageSize: "2K" } })).rejects.toThrow("transport-inspection-complete");
+  ] }], imageParams: { aspectRatio: "auto", imageSize: "2K" }, referenceImageBuffers: new Map([["https://source.example/0", png]]) })).rejects.toThrow("transport-inspection-complete");
   expect(posts).toBe(1);
+  expect(downloads).toEqual([1, 2]);
   expect(submitted.parameters.size).toBe("1024*2048");
   const images = submitted.input.messages[0].content.filter((part: any) => part.image).map((part: any) => part.image);
   expect(images).toHaveLength(3);
@@ -57,3 +60,43 @@ test("Qwen 3 sends reference bytes directly with the right MIME and keeps auto r
     expect(Buffer.from(value.split(",")[1], "base64").equals(originals[index])).toBe(true);
   });
 });
+
+test("a timed out reference read is safe to retry because no generation was submitted", async () => {
+  const methods: string[] = [];
+  const loader = serverLoader({
+    "@/lib/storage/image-archive": {}, "@/lib/storage/service": {},
+    setTimeout: (callback: () => void, ms: number) => setTimeout(callback, ms === 500 ? 0 : ms),
+    fetch: async (_url: string, init: RequestInit = {}) => {
+      methods.push(init.method || "GET");
+      throw new DOMException("This operation was aborted", "AbortError");
+    },
+  });
+  const provider = loader("lib/ai/providers/alibaba-image.ts").createAlibabaImage({ apiKey: "fixture-key", baseURL: "https://dashscope.example" });
+  const error = await provider.chat("qwen-image-3.0").doGenerate({ messages: [{ role: "user", content: [
+    { type: "text", text: "fixture" }, { type: "image", image: "https://source.example/slow.png" },
+  ] }] }).catch((error: unknown) => error);
+  expect(methods).toEqual(["GET", "GET"]);
+  expect(error).toMatchObject({ confirmedNoResult: true });
+  expect(loader("lib/request-error.ts").getRequestFailureDetails(error)).toMatchObject({
+    code: "IMAGE_REFERENCE_READ_TIMEOUT", outcome: "failed", recommendation: "可以稍后重试。",
+  });
+});
+
+test("a failed status lookup after Alibaba accepts the request keeps its outcome unknown", async () => {
+  const methods: string[] = [];
+  const loader = serverLoader({
+    "@/lib/storage/image-archive": {}, "@/lib/storage/service": {},
+    setTimeout: (callback: () => void, ms: number) => setTimeout(callback, ms === 5000 ? 0 : ms),
+    fetch: async (_url: string, init: RequestInit = {}) => {
+      methods.push(init.method || "GET");
+      return init.method === "POST"
+        ? Response.json({ output: { task_id: "accepted-task", task_status: "PENDING" } })
+        : Response.json({ code: "NotFound", message: "Task lookup failed" }, { status: 404 });
+    },
+  });
+  const provider = loader("lib/ai/providers/alibaba-image.ts").createAlibabaImage({ apiKey: "fixture-key", baseURL: "https://dashscope.example" });
+  const error = await provider.chat("qwen-image-3.0").doGenerate({ messages: [{ role: "user", content: "fixture" }] }).catch((error: unknown) => error);
+  expect(methods).toEqual(["POST", "GET"]);
+  expect(String(error)).toContain("accepted-task");
+  expect(loader("lib/request-error.ts").getRequestFailureDetails(error)).toMatchObject({ code: "RESULT_UNCONFIRMED", outcome: "unknown" });
+});

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

@@ -1,21 +1,38 @@
 import { expect, test } from "@playwright/test";
 import { serverLoader } from "../helpers/canvas-download-server-loader";
 import { applyAgentImagePreferences, agentProviderImageParameters } from "@/lib/ai/canvas-agent-runtime/image-preferences";
+import type { AgentCallRecord } from "@/lib/ai/canvas-agent-runtime/protocol";
 
 const preferences = {
   modelId: "user-image-model",
   parameters: { imageCount: 3, aspectRatio: "3:4", imageSize: "4K", negativePrompt: "不要文字",
     quality: "high" as const, size: "1536*2048", promptExtend: false, watermark: false, seed: 0 },
 };
-function harness(results?: any[]) {
+function harness(results?: any[] | ((count: number) => any[])) {
   const saved: any[] = [];
   const generated: any[] = [];
   const operations: any[] = [];
+  const referenceUrl = "https://test.example/reference.png";
+  const original = Buffer.from("original reference bytes");
   const mock = serverLoader({
     "@/lib/canvas/capabilities/ai-sdk-tools": { createCanvasCapabilityTools: async () => ({ editTargetImage: {} }) },
     "@/lib/canvas/capabilities/registry": { CANVAS_CAPABILITY_REGISTRY: [{ id: "image.prompt_regenerate", title: "重绘", risk: "external", agent: { toolName: "editTargetImage" } }] },
-    "@/lib/canvas/agent-mutations": { applyCanvasOperationPlan: async (value: any) => { operations.push(value); return { createdNodeIds: ["new-image"] }; } },
+    "@/lib/canvas/agent-mutations": {
-    "@/lib/canvas/generate-image": { generateCanvasImage: async (value: any) => { generated.push(value); return { modelRef: results ? "backup" : value.model, images: results || [{ originalUrl: "https://test.example/result.png", thumbnailUrl: "https://test.example/thumb.png" }] }; } },
+      applyCanvasOperationPlan: async (value: any) => {
+        operations.push(value);
+        return { createdNodeIds: value.plan.mediaItems.map((item: { mediaItemId: string }) => item.mediaItemId) };
+      },
+    },
+    "@/lib/canvas/generate-image": {
+      generateCanvasImage: async (value: any) => {
+        generated.push(value);
+        const images = typeof results === "function" ? results(value.imageCount) : results;
+        return {
+          modelRef: Array.isArray(results) ? "backup" : value.model,
+          images: images ?? [{ originalUrl: "https://test.example/result.png", thumbnailUrl: "https://test.example/thumb.png" }],
+        };
+      },
+    },
     "@/lib/ai/runtime/generated-image-persistence": { saveGeneratedImages: async (...args: any[]) => { saved.push(args); } },
     "@/lib/ai/model-router": { routeToModel: async () => ({ id: "system-default" }) },
     "@/lib/db/queries": { checkUserImageQuota: async () => ({ allowed: true, remaining: 10 }), getPointsSystemConfig: async () => ({ enabled: false }), getUserById: async () => ({}) },
@@ -23,17 +40,30 @@ function harness(results?: any[]) {
       getStyleProImageModelEntries: async () => ["system-default", "user-image-model"].map(id => ({ model: { id, modelId: id, isDefault: id === "system-default", imageGenConfig: {} } })),
       sortStyleProImageModelEntries: (entries: any) => entries,
     },
-    "./canvas": { readOwnedCanvas: async () => ({ nodes: [{ id: "reference", type: "image" }] }), readCanvasImages: async () => [{ id: "reference", data: { src: "https://test.example/reference.png" } }] },
+    "./canvas": { readOwnedCanvas: async () => ({ nodes: [{ id: "reference", type: "image" }] }), readCanvasImages: async () => [{ id: "reference", data: { src: referenceUrl } }] },
-    "./review": {},
+    "./review": { analyzeRuntimeImages: async ({ reviewPorts }: { reviewPorts: { readImage(url: string): Promise<Buffer> } }) => ({ bytes: (await reviewPorts.readImage(referenceUrl)).length }) },
+    "@/lib/ai/rmbg/service": { fetchImageBufferFromUrl: async () => original },
     "./image-access-tools": { registerImageCanvasAccessTools() {} },
   });
-  const build = async (imagePreferences: any = preferences) => mock("lib/ai/canvas-agent-runtime/tools.ts").buildCanvasRuntimeTools({
+  const build = async (imagePreferences: any = preferences, priorCalls?: AgentCallRecord[]) => mock("lib/ai/canvas-agent-runtime/tools.ts").buildCanvasRuntimeTools({
     userId: "u", chatId: "c", projectId: "p", runId: "r", assistantMessageId: "a", selectedNodeIds: ["reference"],
     request: new Request("https://test.example/api/canvas/agent-chat"), model: {}, supportsVision: true,
-    preferredModelId: "system-default", imagePreferences, emit() {},
+    preferredModelId: "system-default", imagePreferences, priorCalls, emit() {},
   });
-  return { build, generated, operations, saved };
+  return { build, generated, operations, saved, referenceUrl, original };
 }
+
+test("the generation tool can reuse original bytes read by inspection within the same task", async () => {
+  const h = harness();
+  const selection = { parameters: { imageCount: 1 } };
+  const tools = await h.build(selection);
+  await tools.executable.analyzeCanvasImages.execute({ nodeIds: ["reference"], question: "识别素材" }, "inspect");
+  await tools.executable.generateCanvasImages.execute({ prompt: "修改参考图", referenceNodeIds: ["reference"] }, "generate");
+  expect(h.generated[0].referenceImageBuffers.get(h.referenceUrl)).toBe(h.original);
+  const nextTask = await h.build(selection);
+  await nextTask.executable.generateCanvasImages.execute({ prompt: "修改参考图", referenceNodeIds: ["reference"] }, "next");
+  expect(h.generated[1].referenceImageBuffers.has(h.referenceUrl)).toBe(false);
+});
 test("explicit controls override conflicting planner settings without losing false or zero values", () => {
   const resolved = applyAgentImagePreferences({ modelId: "planner-choice", imageCount: 1, imageSize: "1K", aspectRatio: "1:1", prompt: "产品图" }, preferences);
   expect(resolved).toMatchObject({ ...preferences.parameters, modelId: preferences.modelId, prompt: "产品图" });
@@ -47,12 +77,35 @@ test("real generation tool honors the chosen image model and all parameters desp
     providerImageParams: { quality: "high", size: "1536*2048", watermark: false, seed: 0 } });
   expect(output.appliedImagePreferences).toEqual({ modelId: "user-image-model", imageCount: 3, imageSize: "4K", aspectRatio: "3:4" });
 });
-test("redraw and a corrective retry inherit the same user model, batch and image controls", async () => {
+test("redraw and generation share the task limit and only fill the missing images", async () => {
-  const h = harness(); const tools = await h.build();
+  const image = { originalUrl: "https://test.example/result.png", thumbnailUrl: "https://test.example/thumb.png" };
-  await tools.executable.editTargetImage.execute({ nodeIds: ["reference"], args: { prompt: "换背景", modelId: "system-default" } }, "edit-1");
+  const h = harness(count => Array.from({ length: count === 3 ? 1 : count }, () => image));
-  await tools.executable.generateCanvasImages.execute({ prompt: "修正背景", modelId: "system-default" }, "retry-1");
+  const tools = await h.build();
+  const first = await tools.executable.editTargetImage.execute({ nodeIds: ["reference"], args: { prompt: "换背景", modelId: "system-default" } }, "edit-1");
+  expect(first.status).toBe("partial");
+  const filled = await tools.executable.generateCanvasImages.execute({ prompt: "补齐图片", modelId: "system-default" }, "fill-1");
+  expect(filled.status).toBe("succeeded");
+  await expect(tools.executable.generateCanvasImages.execute({ prompt: "再次修正" }, "retry-1")).rejects.toThrow("张数已占满");
+  expect(h.generated).toHaveLength(2);
+  expect(h.generated.map(call => call.imageCount)).toEqual([3, 2]);
+  for (const invocation of h.generated) expect(invocation).toMatchObject({ model: preferences.modelId, imageSize: "4K", aspectRatio: "3:4", allowFailover: false });
+});
+
+test("one selected image allows only one submission even when calls overlap or the task resumes", async () => {
+  const h = harness();
+  const selection = { parameters: { imageCount: 1 } };
+  const tools = await h.build(selection);
+  const generate = (callId: string) => tools.executable.generateCanvasImages.execute({ prompt: "修改图片" }, callId);
+  const [first, duplicate] = await Promise.allSettled([generate("original"), generate("parallel")]);
+  expect(first.status).toBe("fulfilled");
+  expect(duplicate.status).toBe("rejected");
+  if (first.status !== "fulfilled") throw first.reason;
+  const resumed = await h.build(selection, [{ id: "original", name: "generateCanvasImages", input: {}, status: "succeeded", output: first.value }]);
+  await expect(resumed.executable.generateCanvasImages.execute({ prompt: "继续" }, "resume")).rejects.toThrow("张数已占满");
+  expect(h.generated).toHaveLength(1);
+  const next = await h.build(selection);
+  await next.executable.generateCanvasImages.execute({ prompt: "用户新指令" }, "next");
   expect(h.generated).toHaveLength(2);
-  for (const invocation of h.generated) expect(invocation).toMatchObject({ model: preferences.modelId, imageSize: "4K", imageCount: 3, aspectRatio: "3:4", allowFailover: false });
 });
 test("an unavailable explicit choice never silently generates or charges through the default", async () => {
   const h = harness(); const tools = await h.build({ ...preferences, modelId: "disabled-or-missing" });

tests/routes/canvas-agent-runtime-review.test.ts

@@ -94,6 +94,17 @@ test("checks real image bytes and compares results to their source images", asyn
   expect(result.issues).toEqual([]);
 });
 
+test("a partial image batch can be filled and verified without discarding the first result", async () => {
+  const f = await fixture('{"passed":true,"issues":[],"failedNodeIds":[]}');
+  const { snapshot } = f.params;
+  snapshot.requirements = { expectedImageCount: 2 };
+  snapshot.calls[1].output = { status: "partial", createdNodeIds: ["result"], appliedImagePreferences: { imageCount: 2 } };
+  await expect(verifyCanvasAgentResults(f.params)).resolves.toMatchObject({ passed: false, retryable: true });
+  snapshot.resultNodeIds.push("remaining-result");
+  snapshot.calls.push({ id: "fill", name: "generateCanvasImages", input: {}, status: "succeeded", output: { status: "succeeded", createdNodeIds: ["remaining-result"] } });
+  await expect(verifyCanvasAgentResults(f.params)).resolves.toMatchObject({ passed: true });
+});
+
 test("malformed vision JSON switches models, while a valid failed review never triggers failover", async () => {
   const bad = await fixture("not JSON");
   const validNegative = await fixture('{"passed":false,"issues":["主体不一致"],"failedNodeIds":["result"]}');

tests/routes/zcode-agent-task.test.ts

@@ -25,11 +25,31 @@ function fixture() {
     consumeInputs: async () => ({ cancelled: false }), isCancelled: async () => false,
     verify: async () => ({ passed: true, issues: [] }),
   };
-  return { ports, run, snapshot };
+  return { ports, run, snapshot, load };
 }
 
 const result = { type: "result", sessionId: "test-session", response: "已完成" };
 
+test("a failed quality check keeps the single generated image without opening a repair round", async () => {
+  const { ports, run, snapshot } = fixture();
+  snapshot.imagePreferences = { parameters: { imageCount: 1 } };
+  let attempts = 0;
+  ports.tools.generateCanvasImages.execute = async () => ({
+    createdNodeIds: ["generated-image"], appliedImagePreferences: { imageCount: 1 },
+  });
+  ports.native = async options => {
+    attempts++;
+    await options.execute("planCanvasTask", {}, "plan", options.signal!);
+    await options.execute("generateCanvasImages", { referenceNodeIds: ["original"] }, "gen", options.signal!);
+    return { ...result, response: "图片已生成，正在检查" };
+  };
+  ports.verify = async () => ({ passed: false, issues: ["主体细节不符"], retryable: true, failedNodeIds: ["generated-image"] });
+  expect(await run(ports)).toBe("needs_review");
+  expect(attempts).toBe(1);
+  expect(snapshot.resultNodeIds).toEqual(["generated-image"]);
+  expect(snapshot.message).toMatch(/主体细节不符[\s\S]*如需再生成，请发送新指令/);
+});
+
 test("an unconfirmed paid tool stops the planner and immediately preserves the reason and original request ID", async () => {
   const { ports, run, snapshot } = fixture();
   const emitted: string[] = [], saved: string[] = [];
@@ -61,6 +81,26 @@ test("an unconfirmed paid tool stops the planner and immediately preserves the r
   expect(submissions).toBe(1);
 });
 
+test("a pre-submission reference timeout offers a safe retry without an automatic resubmission", async () => {
+  const { ports, run, snapshot, load } = fixture();
+  const { ImageReferenceReadTimeoutError } = load("lib/ai/runtime/image-generation-error.ts");
+  let attempts = 0;
+  ports.tools.generateCanvasImages.execute = async () => {
+    attempts++;
+    throw new ImageReferenceReadTimeoutError();
+  };
+  ports.native = async options => {
+    await options.execute("planCanvasTask", {}, "plan", options.signal!);
+    await options.execute("generateCanvasImages", { referenceNodeIds: ["original"] }, "timeout", options.signal!);
+    return result;
+  };
+  expect(await run(ports)).toBe("needs_review");
+  expect(attempts).toBe(1);
+  expect(snapshot.calls.find(call => call.id === "timeout")).toMatchObject({ confirmedNoResult: true, uncertain: false });
+  expect(snapshot.message).toContain("任务尚未提交，可以稍后重试");
+  expect(snapshot.message).toContain(ports.runId);
+});
+
 test("repairing a failed result permits original images as references without admitting another passed target", async () => {
   const { ports, run, snapshot } = fixture();
   let submissions = 0;