Merge pull request '对齐详情替换模型并支持整套图片' (#68) from codex/detail-replacement-full-set into main

app/(chat)/api/chat/_lib/detail-replacement.ts

@@ -4,7 +4,8 @@ import { fetchImageBufferFromUrl } from "@/lib/ai/rmbg/service";
 import { getLanguageModelById } from "@/lib/ai/dynamic-provider";
 import {
   DETAIL_REPLACEMENT_IMAGE_MODEL_CONFIG_KEY,
-  normalizeDetailReplacementImageModelConfig,
+  findConfiguredDetailReplacementImageModel,
+  isDetailReplacementImageModel,
 } from "@/lib/ai/detail-replacement-image-model-config";
 import {
   compositeReplacementWithReferenceLocks,
@@ -29,7 +30,6 @@ import {
 } from "@/lib/db/queries";
 import { uploadFile } from "@/lib/storage/service";
 import { bufferToArrayBuffer } from "./persistence";
-import { isVideoProviderType } from "./video-models";
 import type { AgentPresetMessageImagePart } from "./agent-scene-workflow";
 import type { PostRequestBody } from "../schema";
 
@@ -2161,22 +2161,10 @@ export async function resolveDirectReplacementModelRef(params: {
   models?: Awaited<ReturnType<typeof getEnabledAiModelsWithProvider>>;
 }) {
   const models = params.models || (await getEnabledAiModelsWithProvider(false));
-  const imageModels = models.filter(
-    ({ model, provider }) =>
-      model.supportsImageGen &&
-      !model.isSubModel &&
-      !isVideoProviderType(provider?.type, model),
-  );
   const configuredModelSetting = await getSystemSetting({
     key: DETAIL_REPLACEMENT_IMAGE_MODEL_CONFIG_KEY,
   }).catch(() => null);
-  const configuredModelId = normalizeDetailReplacementImageModelConfig(
+  const configuredModel = findConfiguredDetailReplacementImageModel(models, configuredModelSetting?.value);
-    configuredModelSetting?.value,
-  ).modelId;
-  const configuredModel = imageModels.find(
-    ({ model }) =>
-      model.id === configuredModelId || model.modelId === configuredModelId,
-  );
   if (configuredModel) {
     return configuredModel.model.id;
   }
@@ -2190,6 +2178,7 @@ export async function resolveDirectReplacementModelRef(params: {
     return routedModel;
   }
 
+  const imageModels = models.filter(isDetailReplacementImageModel);
   const preferred =
     imageModels.find(({ model }) => model.isDefault) ||
     imageModels.find(({ provider }) => String(provider?.type || "").includes("image")) ||

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

@@ -10,6 +10,10 @@ import {
 } from "@/lib/db/queries";
 import { getAiModelFrontendAvailability } from "@/lib/ai/model-frontend-availability";
 import { buildVideoToolCapability } from "@/lib/ai/video-tool-capability";
+import {
+  DETAIL_REPLACEMENT_IMAGE_MODEL_CONFIG_KEY,
+  findConfiguredDetailReplacementImageModel,
+} from "@/lib/ai/detail-replacement-image-model-config";
 import {
   isImageGenerationModelDescriptor,
   isVideoModelDescriptor,
@@ -157,10 +161,17 @@ export async function GET(request: Request) {
       : await getEnabledAiModelsWithProvider(false, true);
     const agentModelWithProvider = await getAgentAiModelWithProvider();
     const defaultModel = await getDefaultAiModel();
-    const [siteSettings, agentWorkflowUiConfigSetting] = await Promise.all([
+    const [siteSettings, agentWorkflowUiConfigSetting, detailReplacementModelSetting] = await Promise.all([
       getSiteSettings(),
       getSystemSetting({ key: AGENT_WORKFLOW_UI_CONFIG_KEY }).catch(() => null),
+      getSystemSetting({ key: DETAIL_REPLACEMENT_IMAGE_MODEL_CONFIG_KEY }).catch(() => null),
     ]);
+    const detailReplacementModel = findConfiguredDetailReplacementImageModel(
+      includeUnavailable ? modelsWithProvider.filter(({ model, provider }) =>
+        provider.isEnabled && model.isEnabled && getAiModelFrontendAvailability(model).selectable !== false
+      ) : modelsWithProvider,
+      detailReplacementModelSetting?.value,
+    );
     type ModelWithProvider = (typeof modelsWithProvider)[number];
     const serializeModel = ({ model, provider }: ModelWithProvider) => ({
       id: model.id,
@@ -309,6 +320,7 @@ export async function GET(request: Request) {
         : null,
       agentWorkflowDefaultModelId: agentWorkflowDefaultModel?.model.id || null,
       agentWorkflowConfiguredModels,
+      detailReplacementModel: detailReplacementModel ? serializeModel(detailReplacementModel) : null,
       agentModel: agentModelWithProvider
         ? {
             id: agentModelWithProvider.model.id,

app/api/agents/detail-replacement/batches/route.ts

@@ -4,6 +4,7 @@ import { auth } from "@/app/(auth)/auth";
 import { db } from "@/lib/db";
 import { canvasImageTask, canvasProject, message } from "@/lib/db/schema";
 import { extractAgentProjectStateFromCanvasData, isAgentProjectRow } from "@/lib/agents/agent-project-compat";
+import { MAX_DETAIL_REPLACEMENT_REFERENCES } from "@/lib/agents/mode-workspace-state";
 import {
   createCanvasImageTask,
   enqueueCanvasImageTask,
@@ -146,6 +147,14 @@ export async function POST(request: Request) {
         .map((item) => [String(item.id), String(item.imageUrl)]),
     );
     const requested = Array.isArray(body.references) ? body.references : [];
+    if (requested.length === 0) {
+      return NextResponse.json({ error: "请先选择详情参考图" }, { status: 400 });
+    }
+    if (requested.length > MAX_DETAIL_REPLACEMENT_REFERENCES) {
+      return NextResponse.json({
+        error: `本次选中了 ${requested.length} 张详情参考图，一次最多替换 ${MAX_DETAIL_REPLACEMENT_REFERENCES} 张，请减少本次选择后重试`,
+      }, { status: 400 });
+    }
     const references: DetailReplacementBatchReference[] = requested.map((raw: unknown) => {
       const item = raw && typeof raw === "object" ? raw as Record<string, unknown> : {};
       return {
@@ -160,7 +169,6 @@ export async function POST(request: Request) {
       };
     });
     if (
-      references.length === 0 || references.length > 40 ||
       new Set(references.map((item) => item.id)).size !== references.length ||
       references.some((item) => !item.id || knownReferences.get(item.id) !== item.imageUrl)
     ) {
@@ -187,6 +195,12 @@ export async function POST(request: Request) {
     if (!model || model === "auto" || !models.some((entry) => entry.model.id === model)) {
       return NextResponse.json({ error: "详情替换模型不可用，请检查模型配置" }, { status: 400 });
     }
+    if (typeof body.expectedModelId === "string" && body.expectedModelId !== model) {
+      return NextResponse.json({
+        code: "DETAIL_REPLACEMENT_MODEL_CHANGED",
+        error: "详情替换模型已更新，请确认页面显示的模型后重新提交",
+      }, { status: 409 });
+    }
     const quota = await checkUserImageQuota(session.user.id);
     if (!quota.allowed) {
       return NextResponse.json({ error: "本月图片生成配额已用完" }, { status: 429 });

app/canvas/[id]/CanvasEditorLegacyPageClient.tsx

@@ -2294,8 +2294,9 @@ export default function CanvasEditorLegacyPage({
     loadedAgentProjectId === agentProjectId;
   const [workflowTemplateMarker, setWorkflowTemplateMarker] = useState<HTMLDivElement | null>(null);
   const [workflowTemplatesRequested, setWorkflowTemplatesRequested] = useState(false);
+  const hasWorkflowBase = Boolean(siteSettingsData?.agentWorkflowUiConfig);
   useEffect(() => {
-    if (!isAgentMode || !hasActiveAgentProject || workflowTemplatesRequested) return;
+    if (!isAgentMode || !hasActiveAgentProject || !hasWorkflowBase || workflowTemplatesRequested) return;
     const element = workflowTemplateMarker;
     if (!element) return;
     const observer = new IntersectionObserver(([entry]) => {
@@ -2303,11 +2304,11 @@ export default function CanvasEditorLegacyPage({
     });
     observer.observe(element);
     return () => observer.disconnect();
-  }, [hasActiveAgentProject, isAgentMode, workflowTemplateMarker, workflowTemplatesRequested]);
+  }, [hasActiveAgentProject, hasWorkflowBase, isAgentMode, workflowTemplateMarker, workflowTemplatesRequested]);
   const { data: workflowTemplates, error: workflowTemplatesError, isValidating: workflowTemplatesLoading, mutate: reloadWorkflowTemplates } = useSWR<{
     steps: AgentWorkflowUiConfig["steps"];
   }>(
-    isAgentMode && hasActiveAgentProject && siteSettingsData?.agentWorkflowUiConfig && workflowTemplatesRequested
+    isAgentMode && hasActiveAgentProject && hasWorkflowBase && workflowTemplatesRequested
       ? "/api/site-settings?scope=agent-workflow-templates"
       : null,
     fetchCanvasSiteSettings,

components/agents/AgentGenerationWorkspaceDarkV2.tsx

@@ -159,6 +159,7 @@ import type {
 } from "@/types/agent";
 import {
   createEmptyAgentModeWorkspaceState,
+  MAX_DETAIL_REPLACEMENT_REFERENCES,
 } from "@/lib/agents/mode-workspace-state";
 import {
   createEmptyAgentGenerationProjectWorkspaceState,
@@ -213,6 +214,7 @@ export interface AgentGenerationWorkspaceDarkV2Props {
 interface AgentWorkflowModelOption {
   id: string;
   displayName: string;
+  providerName?: string;
   providerType: string;
   supportsImageGen?: boolean;
   isMultimodal?: boolean;
@@ -2643,7 +2645,9 @@ function getStoredAgentPendingGenerations(): LocalGenerationPendingState[] {
           ? record.requestedCardIds
               .map((entry) => String(entry || "").trim())
               .filter(Boolean)
-              .slice(0, MAX_AGENT_MODE_REFERENCE_COUNT)
+              .slice(0, record.modeType === "detail_replacement"
+                ? MAX_DETAIL_REPLACEMENT_REFERENCES
+                : MAX_AGENT_MODE_REFERENCE_COUNT)
           : null,
       } satisfies LocalGenerationPendingState;
     });
@@ -3384,12 +3388,13 @@ export function AgentGenerationWorkspaceDarkV2({
     }
   );
 
-  const { data: modelsData } = useSWR<{
+  const { data: modelsData, error: modelsError, mutate: refreshModels } = useSWR<{
     models: AgentWorkflowModelOption[];
     defaultModelId?: string | null;
     agentWorkflowConfiguredDefaultModelId?: string | null;
     agentWorkflowDefaultModelId?: string | null;
     agentWorkflowConfiguredModels?: AgentWorkflowModelOption[];
+    detailReplacementModel?: AgentWorkflowModelOption | null;
     agentModel?: any;
   }>("/api/models", fetcher);
 
@@ -3435,17 +3440,6 @@ export function AgentGenerationWorkspaceDarkV2({
   const activeBusinessModeDefaultModelId = !requiresPresetSelection
     ? String(activeBusinessMode?.defaultModelId || "").trim() || null
     : null;
-  const lockedWorkflowModelId =
-    activeBusinessModeDefaultModelId ||
-    selectedAgentPreset?.defaultModelId ||
-    modelsData?.agentWorkflowConfiguredDefaultModelId ||
-    modelsData?.agentWorkflowDefaultModelId ||
-    null;
-  const isWorkflowModelLocked = Boolean(lockedWorkflowModelId);
-  const effectiveDefaultModelId =
-    lockedWorkflowModelId ||
-    modelsData?.defaultModelId ||
-    null;
   const presetDrivenResultModeType: AgentGenerationResultModeType =
     selectedAgentPreset?.type === "image" && presetModeConfig.modeType === "detail_replacement"
       ? detailReplacementMethod === "ai_detail_generate"
@@ -3461,6 +3455,19 @@ export function AgentGenerationWorkspaceDarkV2({
   const currentResultModeType: AgentGenerationResultModeType = requiresPresetSelection
     ? presetDrivenResultModeType
     : businessModeResultModeType;
+  const detailReplacementModel = currentResultModeType === "detail_replacement"
+    ? modelsData?.detailReplacementModel
+    : null;
+  const isDetailReplacementModelLoading = currentResultModeType === "detail_replacement" && !modelsData;
+  const lockedWorkflowModelId =
+    detailReplacementModel?.id ||
+    activeBusinessModeDefaultModelId ||
+    selectedAgentPreset?.defaultModelId ||
+    modelsData?.agentWorkflowConfiguredDefaultModelId ||
+    modelsData?.agentWorkflowDefaultModelId ||
+    null;
+  const isWorkflowModelLocked = Boolean(lockedWorkflowModelId);
+  const effectiveDefaultModelId = lockedWorkflowModelId || modelsData?.defaultModelId || null;
   const isSceneGenerationPreset = currentResultModeType === "scene_generation";
   const isDetailReplacementPreset =
     currentResultModeType === "detail_replacement" ||
@@ -4112,12 +4119,15 @@ export function AgentGenerationWorkspaceDarkV2({
   );
   const executableModelOptions = useMemo(() => {
     const seen = new Set<string>();
-    return [...selectableModels, ...configuredWorkflowModels].filter((model) => {
+    const workflowModels = detailReplacementModel
+      ? [detailReplacementModel, ...configuredWorkflowModels]
+      : configuredWorkflowModels;
+    return [...selectableModels, ...workflowModels].filter((model) => {
       if (seen.has(model.id)) return false;
       seen.add(model.id);
       return true;
     });
-  }, [configuredWorkflowModels, selectableModels]);
+  }, [configuredWorkflowModels, detailReplacementModel, selectableModels]);
   const executableModelIdSet = useMemo(
     () => new Set(executableModelOptions.map((model) => model.id)),
     [executableModelOptions]
@@ -4136,8 +4146,9 @@ export function AgentGenerationWorkspaceDarkV2({
       selectableModels[0],
     [executableModelOptions, lockedWorkflowModel, selectableModels, selectedModelId]
   );
-  const lockedWorkflowModelLabel =
+  const lockedWorkflowModelLabel = detailReplacementModel?.providerName
-    lockedWorkflowModel?.displayName ||
+    ? `${detailReplacementModel.displayName} 「${detailReplacementModel.providerName}」`
+    : lockedWorkflowModel?.displayName ||
     selectedAgentPreset?.defaultModel?.displayName ||
     (lockedWorkflowModelId ? `配置模型不可用（${lockedWorkflowModelId}）` : "未配置");
   const [activeToolStep, setActiveToolStep] = useState<ToolStepKey>("settings");
@@ -6316,6 +6327,15 @@ export function AgentGenerationWorkspaceDarkV2({
       toast.error(`请先查询并选择${detailReferenceSourceLabel}参考图`);
       return;
     }
+    if (isDetailReplacementModelLoading) {
+      if (modelsError) {
+        toast.error("详情替换模型加载失败，正在重新读取");
+        void refreshModels().catch(() => {});
+      } else {
+        toast.info("正在读取详情替换模型，请稍候");
+      }
+      return;
+    }
     if (isSkuReplacementPreset && skuReplacementReferenceCards.length === 0) {
       toast.error(`请先查询并选择${skuReferenceSourceLabel}参考图`);
       return;
@@ -6383,6 +6403,10 @@ export function AgentGenerationWorkspaceDarkV2({
     }
     if (replacementModeType === "detail_replacement") {
       if (detailBatchSubmittingRef.current) return;
+      if (replacementExecutionCards.length > MAX_DETAIL_REPLACEMENT_REFERENCES) {
+        toast.error(`本次选中了 ${replacementExecutionCards.length} 张详情参考图，一次最多替换 ${MAX_DETAIL_REPLACEMENT_REFERENCES} 张，请减少本次选择后重试`);
+        return;
+      }
       if (!isValidChatUuid(projectId)) {
         toast.error("当前风格化项目尚未保存，请先保存项目后再执行详情替换");
         return;
@@ -6403,13 +6427,14 @@ export function AgentGenerationWorkspaceDarkV2({
           const saved = await onPersistProject?.();
           if (saved === false) throw new Error("项目尚未保存，请重试");
           const requestId = generateUUID();
-          const response = await fetchWithErrorHandlers("/api/agents/detail-replacement/batches", {
+          const response = await fetch("/api/agents/detail-replacement/batches", {
             method: "POST",
             headers: { "Content-Type": "application/json" },
             body: JSON.stringify({
               projectId,
               requestId,
               model: resolvedModelId,
+              expectedModelId: resolvedModelId === "auto" ? undefined : resolvedModelId,
               imageSize: imageParams.imageSize,
               replacementStrategy: detailReplacementStrategy,
               prompt: detailReplacementStrategy === "product_only"
@@ -6433,6 +6458,7 @@ export function AgentGenerationWorkspaceDarkV2({
           });
           const payload = await response.json().catch(() => ({}));
           if (!response.ok || !payload?.task?.id) {
+            if (payload?.code === "DETAIL_REPLACEMENT_MODEL_CHANGED") void refreshModels().catch(() => {});
             throw new Error(payload?.error || "详情替换任务提交失败");
           }
           setPendingGeneration({
@@ -6620,6 +6646,8 @@ export function AgentGenerationWorkspaceDarkV2({
     input,
     isDetailAiGenerationMethod,
     isDetailReplacementPreset,
+    isDetailReplacementModelLoading,
+    modelsError,
     isSelectedBusinessModeUnavailable,
     isSkuReplacementPreset,
     effectiveDefaultModelId,
@@ -6647,6 +6675,7 @@ export function AgentGenerationWorkspaceDarkV2({
     onPersistProject,
     projectId,
     refreshDetailBatch,
+    refreshModels,
   ]);
   const handleStopGeneration = useCallback(() => {
     detailGenerationCancelRef.current = true;
@@ -9419,9 +9448,11 @@ export function AgentGenerationWorkspaceDarkV2({
                         </Select>
                       ) : (
                         <div className="rounded-[24px] border border-white/10 bg-black/30 px-4 py-3 text-sm text-white/70">
-                          {isWorkflowModelLocked ? "后台已锁定生图模型：" : "当前生图模式使用默认模型："}
+                          {isDetailReplacementModelLoading
+                            ? modelsError ? "详情替换模型加载失败，点击批量替换可重试" : "正在读取详情替换模型"
+                            : isWorkflowModelLocked ? "后台已锁定生图模型：" : "当前生图模式使用默认模型："}
                           <span className="ml-2 font-medium text-white">
-                            {isWorkflowModelLocked
+                            {isDetailReplacementModelLoading ? null : isWorkflowModelLocked
                               ? lockedWorkflowModelLabel
                               : currentModel?.displayName || "自动选择"}
                           </span>

lib/agents/mode-workspace-state.ts

@@ -14,6 +14,8 @@ import {
   sanitizeAgentDetailBrief,
 } from "@/lib/agents/detail-generation-config";
 
+export const MAX_DETAIL_REPLACEMENT_REFERENCES = 64;
+
 export function createEmptyAgentModeWorkspaceState(): AgentModeWorkspaceState {
   return {
     detailReplacement: {

lib/ai/detail-replacement-image-model-config.ts

@@ -1,3 +1,5 @@
+import { isVideoModelDescriptor } from "@/lib/ai/model-classification";
+
 export const DETAIL_REPLACEMENT_IMAGE_MODEL_CONFIG_KEY =
   "detail_replacement_image_model_config";
 
@@ -20,3 +22,28 @@ export function normalizeDetailReplacementImageModelConfig(
     modelId: modelId || DEFAULT_DETAIL_REPLACEMENT_IMAGE_MODEL_ID,
   };
 }
+
+export function isDetailReplacementImageModel({
+  model,
+  provider,
+}: {
+  model: { modelId: string; supportsImageGen: boolean; isSubModel: boolean; capabilities?: unknown };
+  provider?: { type?: string | null } | null;
+}) {
+  return model.supportsImageGen && !model.isSubModel && !isVideoModelDescriptor({
+    providerType: provider?.type,
+    modelId: model.modelId,
+    capabilities: model.capabilities,
+    supportsImageGen: model.supportsImageGen,
+  });
+}
+
+export function findConfiguredDetailReplacementImageModel<
+  T extends Parameters<typeof isDetailReplacementImageModel>[0] & { model: { id: string } },
+>(models: T[], setting: unknown): T | undefined {
+  const { modelId } = normalizeDetailReplacementImageModelConfig(setting);
+  return models.find((entry) =>
+    (entry.model.id === modelId || entry.model.modelId === modelId) &&
+    isDetailReplacementImageModel(entry)
+  );
+}

lib/ai/extend/fal-outpaint.ts

@@ -1,37 +1,52 @@
 import { createFalClient } from "@fal-ai/client";
 import sharp from "sharp";
 
-export const FIBO_EXPAND_MODEL = "bria/fibo-edit-1.5/expand";
+export const FAL_OUTPAINT_MODEL = "fal-ai/flux-2-pro/outpaint";
-export const FIBO_EXPAND_PROMPT = "Continue the same scene edge to edge, matching the existing lighting, colors, texture, perspective and cut lines. Preserve the original subject and all lettering; continue any caption background that reaches the side edges.";
 
-export function getFiboGeometry(width: number, height: number, xScale: number, yScale: number) {
+export function getOutpaintGeometry(width: number, height: number, xScale: number, yScale: number) {
   const targetWidth = Math.round(width * xScale);
   const targetHeight = Math.round(height * yScale);
-  const ratio = Math.min(1, Math.sqrt(24_000_000 / (targetWidth * targetHeight)));
+  const ratio = Math.min(1, 2048 / Math.max(targetWidth, targetHeight));
   const modelWidth = Math.max(1, Math.floor(targetWidth * ratio));
   const modelHeight = Math.max(1, Math.floor(targetHeight * ratio));
   const sourceWidth = Math.max(1, Math.round(width * modelWidth / targetWidth));
   const sourceHeight = Math.max(1, Math.round(height * modelHeight / targetHeight));
   const left = Math.floor((targetWidth - width) / 2);
   const top = Math.floor((targetHeight - height) / 2);
+  const modelLeft = Math.round(left * modelWidth / targetWidth);
+  const modelTop = Math.round(top * modelHeight / targetHeight);
+  // Align the model canvas to its 16-pixel grid, then remove the extra border.
+  const extraWidth = (16 - modelWidth % 16) % 16;
+  const extraHeight = (16 - modelHeight % 16) % 16;
+  const cropLeft = Math.floor(extraWidth / 2);
+  const cropTop = Math.floor(extraHeight / 2);
   return {
     targetWidth, targetHeight, left, top, modelWidth, modelHeight, sourceWidth, sourceHeight,
-    modelLeft: Math.round(left * modelWidth / targetWidth),
+    paddedWidth: modelWidth + extraWidth,
-    modelTop: Math.round(top * modelHeight / targetHeight),
+    paddedHeight: modelHeight + extraHeight,
+    cropLeft,
+    cropTop,
+    expandLeft: modelLeft + cropLeft,
+    expandRight: modelWidth - sourceWidth - modelLeft + extraWidth - cropLeft,
+    expandTop: modelTop + cropTop,
+    expandBottom: modelHeight - sourceHeight - modelTop + extraHeight - cropTop,
   };
 }
 
-export async function composeFiboExpansion(source: Buffer, expanded: Buffer, geometry: ReturnType<typeof getFiboGeometry>) {
+export async function composeOutpaint(source: Buffer, expanded: Buffer, geometry: ReturnType<typeof getOutpaintGeometry>) {
-  const { targetWidth, targetHeight, left, top, modelWidth, modelHeight } = geometry;
+  const { targetWidth, targetHeight, left, top, modelWidth, modelHeight, paddedWidth, paddedHeight, cropLeft, cropTop } = geometry;
   const modelImage = sharp(expanded);
   const info = await modelImage.metadata();
-  if (info.width !== modelWidth || info.height !== modelHeight) {
+  if (info.width !== paddedWidth || info.height !== paddedHeight) {
     throw new Error("扩图服务返回的图片尺寸不正确");
   }
 
   // Copy the source rectangle, including transparent pixels, without blending or resizing it.
   const { data: original, info: sourceInfo } = await sharp(source).toColourspace("srgb").ensureAlpha().raw().toBuffer({ resolveWithObject: true });
-  const result = await modelImage.resize(targetWidth, targetHeight, { fit: "fill" }).toColourspace("srgb").ensureAlpha().raw().toBuffer();
+  const result = await modelImage
+    .extract({ left: cropLeft, top: cropTop, width: modelWidth, height: modelHeight })
+    .resize(targetWidth, targetHeight, { fit: "fill" })
+    .toColourspace("srgb").ensureAlpha().raw().toBuffer();
   const stride = sourceInfo.width * 4;
   for (let row = 0; row < sourceInfo.height; row++) {
     original.copy(result, ((top + row) * targetWidth + left) * 4, row * stride, (row + 1) * stride);
@@ -39,7 +54,7 @@ export async function composeFiboExpansion(source: Buffer, expanded: Buffer, geo
   return sharp(result, { raw: { width: targetWidth, height: targetHeight, channels: 4 } }).png().toBuffer();
 }
 
-export async function expandWithFibo({ imageUrl, apiKey, xScale, yScale }: {
+export async function expandWithFalOutpaint({ imageUrl, apiKey, xScale, yScale }: {
   imageUrl: string;
   apiKey: string;
   xScale: number;
@@ -49,26 +64,30 @@ export async function expandWithFibo({ imageUrl, apiKey, xScale, yScale }: {
   if (!response.ok) throw new Error("无法读取待扩展的原图");
   const { data: source, info } = await sharp(Buffer.from(await response.arrayBuffer()))
     .rotate().png().toBuffer({ resolveWithObject: true });
-  const geometry = getFiboGeometry(info.width, info.height, xScale, yScale);
+  const geometry = getOutpaintGeometry(info.width, info.height, xScale, yScale);
   if (geometry.targetWidth * geometry.targetHeight > 64_000_000) {
     throw new Error("扩图后的尺寸过大，请降低扩展倍数");
   }
   const fal = createFalClient({ credentials: apiKey });
-  const image = await fal.storage.upload(new Blob([new Uint8Array(source)], { type: "image/png" }));
+  const modelSource = geometry.sourceWidth === info.width && geometry.sourceHeight === info.height
-  const { data } = await fal.subscribe(FIBO_EXPAND_MODEL, {
+    ? source
+    : await sharp(source).resize(geometry.sourceWidth, geometry.sourceHeight, { fit: "fill" }).png().toBuffer();
+  const image = await fal.storage.upload(new Blob([new Uint8Array(modelSource)], { type: "image/png" }));
+  const { data } = await fal.subscribe(FAL_OUTPAINT_MODEL, {
     input: {
       image_url: image,
-      canvas_size: [geometry.modelWidth, geometry.modelHeight],
+      expand_left: geometry.expandLeft,
-      original_image_size: [geometry.sourceWidth, geometry.sourceHeight],
+      expand_right: geometry.expandRight,
-      original_image_location: [geometry.modelLeft, geometry.modelTop],
+      expand_top: geometry.expandTop,
-      retain_original_quality: true,
+      expand_bottom: geometry.expandBottom,
-      prompt: FIBO_EXPAND_PROMPT,
+      mode: "high",
+      output_format: "png",
     },
     timeout: 90_000,
   });
-  const outputUrl = (data as { image?: { url?: string } }).image?.url;
+  const outputUrl = (data as { images?: Array<{ url?: string }> }).images?.[0]?.url;
   if (!outputUrl) throw new Error("扩图服务未返回图片");
   const output = await fetch(outputUrl, { signal: AbortSignal.timeout(25_000) });
   if (!output.ok) throw new Error("无法读取扩图结果");
-  return composeFiboExpansion(source, Buffer.from(await output.arrayBuffer()), geometry);
+  return composeOutpaint(source, Buffer.from(await output.arrayBuffer()), geometry);
 }

lib/ai/extend/service.ts

@@ -6,7 +6,7 @@ import {
   upsertMediaAsset,
 } from "@/lib/db/queries";
 import { type ExtendProvider, resolveAlibabaExtendApiKey, resolveFalExtendApiKey } from "@/lib/ai/extend/config";
-import { expandWithFibo, FIBO_EXPAND_MODEL } from "@/lib/ai/extend/fibo";
+import { expandWithFalOutpaint, FAL_OUTPAINT_MODEL } from "@/lib/ai/extend/fal-outpaint";
 import { executeConfiguredVip98kTask } from "@/lib/ai/vip98k-runtime";
 import { db } from "@/lib/db";
 import { generatedImage } from "@/lib/db/schema";
@@ -536,8 +536,8 @@ export async function executeExtendJob(
   let buffer: Buffer;
   let modelId: string;
   if (config.provider === "fal") {
-    buffer = await expandWithFibo({ imageUrl: inputImageUrl, apiKey: config.apiKey!, xScale, yScale });
+    buffer = await expandWithFalOutpaint({ imageUrl: inputImageUrl, apiKey: config.apiKey!, xScale, yScale });
-    modelId = FIBO_EXPAND_MODEL;
+    modelId = FAL_OUTPAINT_MODEL;
   } else {
     const prepared = config.provider === "vip98k" ? inputImageUrl : await normalizeDashscopeExpansionInput(inputImageUrl);
     const url = await extendImage(prepared, config, xScale, yScale, requestId);

tests/routes/agent-project-recovery.test.ts

@@ -72,6 +72,85 @@ function projectRoute() {
   return { route: load("app/api/agent-projects/route.ts"), projects, setUser: (value: string | null) => { userId = value; } };
 }
 
+test("a saved full detail set is queued, while overflow and changed references have distinct errors", async () => {
+  const references = Array.from({ length: 65 }, (_, index) => ({
+    id: `detail-${index + 1}`,
+    imageUrl: `https://example.test/detail-${index + 1}.webp`,
+  }));
+  const project = {
+    id, userId: owner, title: "全套详情", workspaceType: "agent",
+    canvasData: { agentProjectState: { workflowState: {
+      agentModeState: { detailReplacement: { references } },
+    } } },
+  };
+  const canvasProject = { id: "id", userId: "userId" };
+  const created: Array<{ id: string; request: { references: typeof references }; status: string }> = [];
+  const queued: string[] = [];
+  const db = {
+    select: () => ({ from: (table: unknown) => ({
+      where: () => ({
+        limit: async () => table === canvasProject ? [project] : [],
+        orderBy: () => ({ limit: async () => [] }),
+      }),
+    }) }),
+    insert: () => ({ values: () => ({ onConflictDoNothing: async () => {} }) }),
+  };
+  const route = loadRuntime({
+    "@/app/(auth)/auth": { auth: async () => ({ user: { id: owner } }) },
+    "@/lib/db": { db },
+    "@/lib/db/schema": { canvasProject, canvasImageTask: { request: "request" }, message: { id: "id" } },
+    "drizzle-orm": { eq: () => null, and: () => null, inArray: () => null, desc: () => null, sql: () => null },
+    "@/lib/canvas/image-task-queue": {
+      createCanvasImageTask: async ({ taskId, request }: { taskId: string; request: { references: typeof references } }) => {
+        const task = { id: taskId, request, status: "pending" };
+        created.push(task);
+        return task;
+      },
+      getCanvasImageTaskForUser: async ({ taskId }: { taskId: string }) => created.find((task) => task.id === taskId),
+      enqueueCanvasImageTask: async (taskId: string) => { queued.push(taskId); },
+    },
+    "@/lib/db/queries": {
+      getEnabledAiModelsWithProvider: async () => [{ model: { id: "fixture-model" } }],
+      checkUserImageQuota: async () => ({ allowed: true, limit: null }),
+      getPointsSystemConfig: async () => ({ enabled: false }),
+      getChatById: async () => ({ userId: owner }),
+    },
+    "@/app/(chat)/api/chat/_lib/detail-replacement": { resolveDirectReplacementModelRef: async () => "fixture-model" },
+    "@/app/(chat)/api/chat/_lib/agent-scene-workflow": {
+      buildAgentSlotPrompt: ({ workflowPrompt }: { workflowPrompt: string }) => workflowPrompt,
+      normalizeAgentSupplementPrompt: () => "",
+    },
+  })("app/api/agents/detail-replacement/batches/route.ts");
+  const post = (items: typeof references, replacementStrategy = "product_only", expectedModelId = "fixture-model") => route.POST(
+    new Request("http://localhost/api/agents/detail-replacement/batches", {
+      method: "POST",
+      body: JSON.stringify({
+        projectId: id, requestId: randomUUID(), references: items, replacementStrategy, expectedModelId,
+        prompt: "沿用品牌场景", productImageUrls: ["https://example.test/product.webp"],
+      }),
+    }),
+  );
+
+  for (const [count, strategy] of [[48, "product_only"], [64, "scene_replace"]] as const) {
+    const expectedIds = references.slice(0, count).map((ref) => ref.id);
+    const response = await post(references.slice(0, count), strategy);
+    expect(response.status).toBe(200);
+    expect((await response.json()).task.requestedCardIds).toEqual(expectedIds);
+    expect(created.at(-1)?.request.references.map((ref) => ref.id)).toEqual(expectedIds);
+  }
+  const overflow = await post(references);
+  expect(overflow.status).toBe(400);
+  expect((await overflow.json()).error).toContain("一次最多替换 64 张");
+  const changed = await post([{ ...references[0], imageUrl: "https://example.test/changed.webp" }]);
+  expect(changed.status).toBe(400);
+  expect((await changed.json()).error).toContain("尚未保存或已发生变化");
+  const changedModel = await post(references.slice(0, 48), "scene_replace", "outdated-model");
+  expect(changedModel.status).toBe(409);
+  expect((await changedModel.json()).code).toBe("DETAIL_REPLACEMENT_MODEL_CHANGED");
+  expect(queued).toEqual(created.map((task) => task.id));
+  expect(queued).toHaveLength(2);
+});
+
 test("duplicate POSTs return one project without overwriting saved state", async () => {
   const { route, projects } = projectRoute();
   const post = (title: string) => route.POST(new Request("http://localhost/api/agent-projects", { method: "POST", body: JSON.stringify({ id, title }) }));

tests/routes/extend-provider-config.test.ts

@@ -1,7 +1,7 @@
 import { expect, test } from "@playwright/test";
 import sharp from "sharp";
 import { resolveAlibabaExtendApiKey, resolveFalExtendApiKey } from "@/lib/ai/extend/config";
-import { composeFiboExpansion, getFiboGeometry } from "@/lib/ai/extend/fibo";
+import { composeOutpaint, getOutpaintGeometry } from "@/lib/ai/extend/fal-outpaint";
 
 test.describe("image extension provider configuration", () => {
   test("uses the most recently updated Alibaba image provider key", () => {
@@ -35,22 +35,24 @@ test.describe("image extension provider configuration", () => {
 });
 
 test("outpainting restores every original pixel in place and keeps the generated border", async () => {
-  const geometry = getFiboGeometry(13, 9, 1.5, 1.5);
+  const geometry = getOutpaintGeometry(13, 9, 1.5, 1.5);
-  const { targetWidth, targetHeight, left, top } = geometry;
+  const { paddedWidth, paddedHeight, left, top } = geometry;
   const pixel = Buffer.from([42, 93, 190, 255, 30, 80, 20, 75]);
   const raw = Buffer.concat(Array.from({ length: 59 }, () => pixel)).subarray(0, 13 * 9 * 4);
   const source = await sharp(raw, { raw: { width: 13, height: 9, channels: 4 } }).png().toBuffer();
-  const expanded = await sharp({ create: { width: targetWidth, height: targetHeight, channels: 3, background: "#d8bc9e" } }).png().toBuffer();
+  const expanded = await sharp({ create: { width: paddedWidth, height: paddedHeight, channels: 3, background: "#d8bc9e" } }).png().toBuffer();
-  const composed = await composeFiboExpansion(source, expanded, geometry);
+  const composed = await composeOutpaint(source, expanded, geometry);
   const area = await sharp(composed).extract({ left, top, width: 13, height: 9 }).raw().toBuffer();
   expect(area.equals(raw)).toBe(true);
   expect([...await sharp(composed).extract({ left: 0, top: 0, width: 1, height: 1 }).raw().toBuffer()]).toEqual([216, 188, 158, 255]);
-  await expect(composeFiboExpansion(source, source, geometry)).rejects.toThrow("尺寸不正确");
+  await expect(composeOutpaint(source, source, geometry)).rejects.toThrow("尺寸不正确");
 });
 
 test("a 4K source keeps its target output size while the model works within its limit", () => {
-  const g = getFiboGeometry(4096, 4096, 1.5, 1.5);
+  const g = getOutpaintGeometry(4096, 4096, 1.5, 1.5);
   expect([g.targetWidth, g.targetHeight, g.left, g.top]).toEqual([6144, 6144, 1024, 1024]);
-  expect(g.modelWidth * g.modelHeight).toBeLessThan(25_000_000);
+  expect([g.paddedWidth, g.paddedHeight]).toEqual([2048, 2048]);
-  expect(g.modelLeft * 2 + g.sourceWidth).toBeCloseTo(g.modelWidth, -1);
+  expect(g.expandLeft + g.sourceWidth + g.expandRight).toBe(g.paddedWidth);
+  expect(g.expandTop + g.sourceHeight + g.expandBottom).toBe(g.paddedHeight);
+  expect(Math.abs(g.expandLeft - g.expandRight)).toBeLessThanOrEqual(1);
 });