fix: validate AtlasCloud frontend model requests
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@ -18,6 +18,11 @@ const ALLOWED_UPLOAD_IMAGE_TYPES = new Set([
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"image/heic",
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"image/heif",
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]);
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const ALLOWED_ATLASCLOUD_VIDEO_TYPES = new Set([
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"video/mp4",
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"video/quicktime",
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"video/webm",
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]);
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const HEIC_UPLOAD_TYPES = new Set(["image/heic", "image/heif"]);
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@ -197,6 +202,9 @@ export async function POST(request: Request) {
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let filename = originalFilename;
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let contentType = originalContentType;
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const uploadPurpose = String(formData.get("purpose") || "");
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const isAtlasCloudReferenceVideo =
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uploadPurpose === "canvas-video-process" &&
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ALLOWED_ATLASCLOUD_VIDEO_TYPES.has(contentType);
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const clientUploadId =
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String(formData.get("clientUploadId") || "").trim() || null;
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const isSvgUpload = contentType === "image/svg+xml";
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@ -227,7 +235,10 @@ export async function POST(request: Request) {
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return NextResponse.json({ error: errorMessage }, { status: 400 });
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}
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if (!ALLOWED_UPLOAD_IMAGE_TYPES.has(contentType)) {
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if (
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!ALLOWED_UPLOAD_IMAGE_TYPES.has(contentType) &&
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!isAtlasCloudReferenceVideo
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) {
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const errorMessage = createUnsupportedImageTypeMessage(contentType, filename);
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logger.warn("[Upload API] Unsupported upload content type", {
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contentType,
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@ -361,18 +372,19 @@ export async function POST(request: Request) {
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try {
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const asset = await upsertMediaAsset({
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userId: session.user.id,
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mediaType: "image",
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mediaType: isAtlasCloudReferenceVideo ? "video" : "image",
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sourceType: "upload",
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status: "ready",
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originalUrl: data.url,
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previewUrl: data.url,
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thumbnailUrl: data.url,
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previewUrl: isAtlasCloudReferenceVideo ? null : data.url,
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thumbnailUrl: isAtlasCloudReferenceVideo ? null : data.url,
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mimeType: data.contentType || contentType || null,
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displayName: filename,
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sourceTable: "upload",
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metadata: {
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pathname: data.pathname,
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size: optimizedBuffer.length,
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purpose: uploadPurpose || null,
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clientUploadId,
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convertedFrom,
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},
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@ -2197,6 +2197,39 @@ function isLikelyVideoAttachment(url: string, contentType: string) {
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);
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}
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function collectMessageVideoAttachments(message: ChatMessage) {
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const attachments: PickedObjectAttachment[] = [];
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const seenUrls = new Set<string>();
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const append = (value: any, fallbackName: string) => {
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const url = String(value?.url || value?.data || "").trim();
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if (!isValidChatHttpUrl(url) || seenUrls.has(url)) return;
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const contentType = normalizeChatMediaType(
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value?.contentType || value?.mediaType || value?.mimeType
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);
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if (!isLikelyVideoAttachment(url, contentType)) return;
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const attachment = sanitizeChatAttachment({
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url,
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name: normalizeChatAttachmentName(value?.name || fallbackName),
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contentType,
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assetId:
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typeof value?.assetId === "string" && value.assetId.trim()
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? value.assetId.trim()
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: undefined,
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} as PickedObjectAttachment);
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if (!attachment) return;
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seenUrls.add(url);
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attachments.push(attachment);
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};
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(message.parts || []).forEach((part: any, index: number) => {
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if (part?.type === "file") append(part, `参考视频-${index + 1}.mp4`);
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});
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((message as any).attachments || []).forEach((attachment: any, index: number) => {
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append(attachment, `参考视频-${index + 1}.mp4`);
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});
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return attachments;
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}
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function buildCopiedMessageAttachment(
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value: any,
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fallbackName: string
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@ -4206,6 +4239,7 @@ export function CanvasChatPanel({
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videoToolCapability?: VideoToolCapabilityContract | null;
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imageGenConfig?: {
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maxImages?: number;
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maxVideoReferences?: number;
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supportsSize?: boolean;
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supports1K?: boolean;
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supports2K?: boolean;
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@ -4234,6 +4268,7 @@ export function CanvasChatPanel({
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isMultimodal?: boolean;
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imageGenConfig?: {
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maxImages?: number;
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maxVideoReferences?: number;
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supportsSize?: boolean;
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supports1K?: boolean;
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supports2K?: boolean;
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@ -4731,6 +4766,25 @@ export function CanvasChatPanel({
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[visualModels]
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);
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const currentModel = allModels.find((model) => model.id === selectedModelId);
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const atlasVideoReferenceLimit =
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currentModel?.providerType === "atlascloud"
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? Math.max(
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0,
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Math.min(
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4,
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Number(
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currentModel.capabilities?.maxVideoReferences ||
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currentModel.imageGenConfig?.maxVideoReferences ||
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0
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)
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)
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)
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: 0;
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const supportsAtlasVideoReference = atlasVideoReferenceLimit > 0;
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const requiresAtlasVideoReference = Boolean(
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supportsAtlasVideoReference &&
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currentModel?.capabilities?.requiresVideoReference === true
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);
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const isCanvasVideoModel = useCallback(
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(model?: (typeof allModels)[number] | null) =>
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Boolean(
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@ -11295,6 +11349,20 @@ export function CanvasChatPanel({
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let effectiveAttachments = attachments
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.map((attachment) => sanitizeChatAttachment(attachment))
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.filter((attachment): attachment is PickedObjectAttachment => Boolean(attachment));
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if (supportsAtlasVideoReference) {
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let keptVideoCount = 0;
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effectiveAttachments = effectiveAttachments.filter((attachment) => {
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if (!isLikelyVideoAttachment(attachment.url, attachment.contentType)) {
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return true;
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}
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keptVideoCount += 1;
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return keptVideoCount <= atlasVideoReferenceLimit;
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});
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if (requiresAtlasVideoReference && keptVideoCount === 0) {
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toast.error("当前模型需要先上传 1 个参考视频");
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return;
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}
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}
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if (hasAgentUploadSlots) {
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if (effectiveAttachments.length > agentRequiredUploadCount) {
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effectiveAttachments = effectiveAttachments.slice(0, agentRequiredUploadCount);
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@ -11918,6 +11986,57 @@ export function CanvasChatPanel({
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}
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}, [clearComposerUploadProgress, updateComposerUploadProgress]);
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const uploadVideoFileForComposerAttachment = useCallback(async (
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file: File,
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progressOptions?: CanvasUploadProgressOptions
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): Promise<ComposerUploadedImage | null> => {
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if (!file.type.startsWith("video/")) {
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toast.error("请选择视频文件");
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return null;
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}
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if (file.size > 15 * 1024 * 1024) {
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toast.error("参考视频大小不能超过 15MB");
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return null;
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}
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try {
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const formData = new FormData();
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formData.append("file", file);
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formData.append("purpose", "canvas-video-process");
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if (progressOptions) {
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updateComposerUploadProgress(progressOptions);
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}
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const response = await fetchUploadWithRetry(
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formData,
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progressOptions
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? {
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onProgress: (progress) => {
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updateComposerUploadProgress(progressOptions, progress);
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},
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}
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: undefined
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);
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if (!response.ok) {
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throw new Error("上传失败");
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}
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const data = await response.json();
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clearComposerUploadProgress(250);
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return {
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imageUrl: String(data.url || ""),
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name: file.name || `参考视频-${Date.now()}.mp4`,
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contentType: file.type || "video/mp4",
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assetId:
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typeof data.assetId === "string" && data.assetId.trim()
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? data.assetId.trim()
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: undefined,
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};
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} catch (_error) {
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toast.error("参考视频上传失败");
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return null;
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}
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}, [clearComposerUploadProgress, updateComposerUploadProgress]);
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const handlePastedImages = useCallback(async (files: File[]) => {
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if (files.length === 0) return;
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@ -12251,6 +12370,58 @@ export function CanvasChatPanel({
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return;
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}
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if (supportsAtlasVideoReference) {
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const selectedVideoFiles = selectedFiles.filter((file) =>
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file.type.startsWith("video/")
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);
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const existingVideoCount = attachments.filter((attachment) =>
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isLikelyVideoAttachment(attachment.url, attachment.contentType)
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).length;
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const availableVideoSlots = Math.max(
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0,
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atlasVideoReferenceLimit - existingVideoCount
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);
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const acceptedVideoFiles = selectedVideoFiles.slice(0, availableVideoSlots);
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if (selectedVideoFiles.length > acceptedVideoFiles.length) {
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toast.info(`当前模型最多支持 ${atlasVideoReferenceLimit} 个参考视频`);
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}
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if (acceptedVideoFiles.length > 0) {
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let uploadedCount = 0;
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try {
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for (const [index, file] of acceptedVideoFiles.entries()) {
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const uploaded = await uploadVideoFileForComposerAttachment(file, {
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title: "正在上传参考视频",
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fileName: file.name,
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fileIndex: index,
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fileTotal: acceptedVideoFiles.length,
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target: "composer-reference",
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});
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if (!uploaded?.imageUrl) continue;
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addUploadedImageAttachmentToComposer(uploaded);
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uploadedCount += 1;
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}
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} finally {
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clearComposerUploadProgress(450);
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}
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if (uploadedCount > 0) {
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toast.success(
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uploadedCount === 1
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? "参考视频已添加到对话"
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: `已添加 ${uploadedCount} 个参考视频`
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);
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}
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}
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selectedFiles = selectedFiles.filter(
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(file) => !file.type.startsWith("video/")
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);
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if (selectedFiles.length === 0) {
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e.target.value = "";
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return;
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}
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}
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let firstImageUrl: string | null = null;
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// 记录本次上传开始时的节点数量，用于计算新图片位置
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const baseNodeCount = nodes.length;
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@ -13802,6 +13973,10 @@ export function CanvasChatPanel({
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message.role === "user"
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? collectMessageImageAttachments(message as any)
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: [];
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const userVideoAttachments =
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message.role === "user"
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? collectMessageVideoAttachments(message as any)
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: [];
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const assistantTextParts = message.role === "assistant"
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? (message.parts || []).filter((part: any) => part.type === "text" && part.text)
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: [];
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@ -13954,6 +14129,25 @@ export function CanvasChatPanel({
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);
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});
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userVideoAttachments.forEach((attachment, idx) => {
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renderedUserParts.push(
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<span
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key={`video-${attachment.url}-${idx}`}
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className={cn(
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"inline-flex items-center gap-1 rounded-[var(--ui-radius-control)] px-1.5 py-1 text-[11px]",
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isVideoWorkspace
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? "border border-border/60 bg-background"
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: "border border-black/5 bg-white/90 text-[#334155] dark:border-white/10 dark:bg-white/10 dark:text-zinc-100"
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)}
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>
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<Video className="h-4 w-4 shrink-0" />
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<span className="max-w-[72px] truncate text-current">
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{attachment.name || "参考视频"}
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</span>
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</span>
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);
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});
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message.parts?.forEach((part: any, idx: number) => {
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if (part.type === 'text' && part.text) {
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const text = String(part.text)
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@ -15619,8 +15813,8 @@ export function CanvasChatPanel({
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className="relative flex h-8 w-8 shrink-0 items-center justify-center overflow-hidden rounded-full border border-dashed border-[#d9dde4] bg-[#f3f3f4] text-[#8f97a3] transition-colors hover:border-[#c6ccd6] hover:bg-[#ececee] hover:text-[#20242a] disabled:cursor-not-allowed disabled:opacity-60 dark:border-white/12 dark:bg-white/8 dark:text-zinc-400 dark:hover:border-white/20 dark:hover:bg-white/12 dark:hover:text-white"
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onClick={() => fileInputRef.current?.click()}
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disabled={isSubmitting}
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title="添加图片"
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aria-label="添加图片"
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title={supportsAtlasVideoReference ? "添加图片或参考视频" : "添加图片"}
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aria-label={supportsAtlasVideoReference ? "添加图片或参考视频" : "添加图片"}
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>
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<Plus className="h-4 w-4" />
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{composerReferenceUploadProgress ? (
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@ -15926,7 +16120,13 @@ export function CanvasChatPanel({
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<input
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ref={fileInputRef}
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type="file"
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accept={isClawdMode ? `image/*,${CLAWD_TABLE_ACCEPT}` : "image/*"}
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accept={
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isClawdMode
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? `image/*,${CLAWD_TABLE_ACCEPT}`
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: supportsAtlasVideoReference
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? "image/*,video/mp4,video/quicktime,video/webm"
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: "image/*"
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}
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multiple
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className="hidden"
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onChange={handleFileSelect}
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@ -17,6 +17,10 @@ const ALLOWED_CHAT_MEDIA_TYPES = new Set([
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"image/jpg",
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"image/bmp",
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"image/svg+xml",
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"video/mp4",
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"video/quicktime",
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"video/webm",
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"video/x-matroska",
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]);
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const GENERIC_CANVAS_PROMPT_SET = new Set([
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@ -60,11 +60,18 @@ export interface AtlasCloudRuntimeConfig {
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}>;
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imageInputKey?: string;
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imageInputMode?: "array" | "single";
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videoClipInput?: {
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key: string;
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maxItems: number;
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required: boolean;
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itemDefaults: Record<string, string | number | boolean>;
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};
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resolutionKey?: string;
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aspectRatioKey?: string;
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outputCountKey?: string;
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aspectRatioValueMap: Record<string, string>;
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maxReferenceImages: number;
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maxVideoReferences: number;
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maxImages: number;
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defaults: Record<string, string | number | boolean>;
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enums: Record<string, Array<string | number>>;
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@ -196,6 +203,39 @@ function getImageInputs(properties: JsonRecord, requiredFields: string[]) {
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.sort((a, b) => Number(b.required) - Number(a.required));
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}
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function getVideoClipInput(properties: JsonRecord, requiredFields: string[]) {
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const entry = Object.entries(properties).find(([key, property]) => {
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const normalizedKey = key.toLowerCase();
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const record = asRecord(property);
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const itemProperties = asRecord(asRecord(record.items).properties);
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return (
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record.type === "array" &&
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normalizedKey.includes("video") &&
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("url" in itemProperties || normalizedKey.includes("clip"))
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);
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});
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if (!entry) return undefined;
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const [key, property] = entry;
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const record = asRecord(property);
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const itemProperties = asRecord(asRecord(record.items).properties);
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const itemDefaults: Record<string, string | number | boolean> = {};
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for (const [itemKey, itemProperty] of Object.entries(itemProperties)) {
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if (itemKey === "url") continue;
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const value = asRecord(itemProperty).default;
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if (["string", "number", "boolean"].includes(typeof value)) {
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itemDefaults[itemKey] = value;
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}
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}
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return {
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key,
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maxItems: Math.max(1, Math.min(4, Number(record.maxItems || 1))),
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required: requiredFields.includes(key),
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itemDefaults,
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};
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}
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function getEnumValues(property: unknown) {
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const record = asRecord(property);
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const values = Array.isArray(record.enum) ? record.enum : [];
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@ -396,6 +436,7 @@ export function createAtlasCloudImagePreset(
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const properties = asRecord(input.properties);
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const requiredFields = uniqueStrings(Array.isArray(input.required) ? input.required : []);
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const imageInputs = getImageInputs(properties, requiredFields);
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const videoClipInput = getVideoClipInput(properties, requiredFields);
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const imageInputKey = imageInputs[0]?.key;
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const resolutionKey = RESOLUTION_KEYS.find((key) => {
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if (!(key in properties)) return false;
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@ -420,6 +461,7 @@ export function createAtlasCloudImagePreset(
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14,
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imageInputs.reduce((total, input) => total + input.maxItems, 0)
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);
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const maxVideoReferences = videoClipInput?.maxItems || 0;
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const maxImages = deriveMaxImages(properties, outputCountKey);
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const categories = uniqueStrings(catalogModel.categories || []).map((value) =>
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value.toLowerCase()
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@ -436,6 +478,7 @@ export function createAtlasCloudImagePreset(
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categories.some((value) => value.includes("image-to-image"))
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? ["image-edit", "reference-images"]
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: []),
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...(videoClipInput ? ["reference-video"] : []),
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];
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if (mediaKind === "image" && supportedModes.length === 0) {
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supportedModes.push("text-to-image");
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@ -449,11 +492,13 @@ export function createAtlasCloudImagePreset(
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imageInputs,
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imageInputKey,
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imageInputMode: imageProperty.type === "array" ? "array" : "single",
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videoClipInput,
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resolutionKey,
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aspectRatioKey,
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outputCountKey,
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aspectRatioValueMap: aspectRatioConfig.map,
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maxReferenceImages,
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maxVideoReferences,
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maxImages,
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defaults: buildScalarDefaults(properties),
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enums: buildEnums(properties),
|
||||
@ -495,7 +540,10 @@ export function createAtlasCloudImagePreset(
|
||||
mediaType: mediaKind,
|
||||
supportedModes,
|
||||
maxReferenceImages,
|
||||
maxVideoReferences,
|
||||
supportsMultiImageReference: maxReferenceImages > 1,
|
||||
supportsVideoReference: maxVideoReferences > 0,
|
||||
requiresVideoReference: videoClipInput?.required === true,
|
||||
provider: "atlascloud",
|
||||
schemaUrl: catalogModel.schema || null,
|
||||
},
|
||||
@ -509,6 +557,7 @@ export function createAtlasCloudImagePreset(
|
||||
apiFormat: "atlascloud-unified-image",
|
||||
maxImages,
|
||||
maxReferenceImages,
|
||||
maxVideoReferences,
|
||||
supportsSize,
|
||||
supports1K: supportedImageSizes.includes("1K"),
|
||||
supports2K: supportedImageSizes.includes("2K"),
|
||||
|
||||
209
lib/ai/atlascloud-request.ts
Normal file
209
lib/ai/atlascloud-request.ts
Normal file
@ -0,0 +1,209 @@
|
||||
import type { AtlasCloudRuntimeConfig } from "@/lib/ai/atlascloud-models";
|
||||
|
||||
export interface AtlasCloudImageParams {
|
||||
aspectRatio?: string;
|
||||
imageSize?: string;
|
||||
imageCount?: number;
|
||||
negativePrompt?: string;
|
||||
promptExtend?: boolean;
|
||||
quality?: string;
|
||||
seed?: number;
|
||||
watermark?: boolean;
|
||||
}
|
||||
|
||||
export interface AtlasCloudModelConfig {
|
||||
maxReferenceImages?: number;
|
||||
maxVideoReferences?: number;
|
||||
supportedAspectRatios?: string[];
|
||||
supportedImageSizes?: string[];
|
||||
atlasCloud?: AtlasCloudRuntimeConfig;
|
||||
}
|
||||
|
||||
function normalizeAspectRatio(
|
||||
requested: string | undefined,
|
||||
supported: string[] | undefined
|
||||
) {
|
||||
const values = (supported || []).map(String);
|
||||
const normalized = String(requested || "auto").trim().toLowerCase();
|
||||
const exact = values.find((value) => value.toLowerCase() === normalized);
|
||||
if (exact) return exact;
|
||||
return (
|
||||
values.find((value) => value === "auto") ||
|
||||
values.find((value) => value === "1:1") ||
|
||||
values[0] ||
|
||||
"1:1"
|
||||
);
|
||||
}
|
||||
|
||||
function normalizeImageSize(requested: string | undefined, supported?: string[]) {
|
||||
const values = (supported || []).map((value) => String(value).trim().toUpperCase());
|
||||
const normalized = String(requested || "2K").trim().toUpperCase();
|
||||
if (values.includes(normalized)) return normalized;
|
||||
return values.includes("2K") ? "2K" : values[0] || normalized;
|
||||
}
|
||||
|
||||
function matchEnumValue(values: Array<string | number> | undefined, value: unknown) {
|
||||
if (!values?.length) return value;
|
||||
const normalized = String(value || "").trim().toLowerCase();
|
||||
return values.find(
|
||||
(item) => String(item).trim().toLowerCase() === normalized
|
||||
);
|
||||
}
|
||||
|
||||
function parseRatio(value: string) {
|
||||
const match = value.match(/^(\d+):(\d+)$/);
|
||||
if (!match) return 1;
|
||||
return Number(match[1]) / Number(match[2]);
|
||||
}
|
||||
|
||||
function pickClosestSizeValue(
|
||||
map: Record<string, Record<string, string>>,
|
||||
imageSize: string,
|
||||
aspectRatio: string
|
||||
) {
|
||||
const tiers = [imageSize, "2K", "1K", "4K"];
|
||||
const values = tiers.map((tier) => map[tier]).find(Boolean);
|
||||
if (!values) return undefined;
|
||||
if (values[aspectRatio]) return values[aspectRatio];
|
||||
const target = parseRatio(aspectRatio);
|
||||
return Object.entries(values).sort(
|
||||
([a], [b]) =>
|
||||
Math.abs(Math.log(target / parseRatio(a))) -
|
||||
Math.abs(Math.log(target / parseRatio(b)))
|
||||
)[0]?.[1];
|
||||
}
|
||||
|
||||
export function createAtlasCloudRequestBody(params: {
|
||||
modelId: string;
|
||||
prompt: string;
|
||||
referenceImages: string[];
|
||||
referenceVideos?: string[];
|
||||
imageParams?: AtlasCloudImageParams;
|
||||
modelConfig: AtlasCloudModelConfig;
|
||||
}) {
|
||||
const runtime = params.modelConfig.atlasCloud;
|
||||
if (!runtime) {
|
||||
throw new Error("Atlas Cloud 模型运行参数缺失，请重新同步模型");
|
||||
}
|
||||
const body: Record<string, unknown> = { ...runtime.defaults };
|
||||
if (
|
||||
runtime.propertyNames.includes("model") ||
|
||||
runtime.requiredFields.includes("model")
|
||||
) {
|
||||
body.model = params.modelId;
|
||||
}
|
||||
if (
|
||||
runtime.propertyNames.includes("prompt") ||
|
||||
runtime.requiredFields.includes("prompt")
|
||||
) {
|
||||
body.prompt = params.prompt;
|
||||
}
|
||||
|
||||
const aspectRatio = normalizeAspectRatio(
|
||||
params.imageParams?.aspectRatio,
|
||||
params.modelConfig.supportedAspectRatios
|
||||
);
|
||||
const imageSize = normalizeImageSize(
|
||||
params.imageParams?.imageSize,
|
||||
params.modelConfig.supportedImageSizes
|
||||
);
|
||||
|
||||
if (runtime.aspectRatioKey) {
|
||||
body[runtime.aspectRatioKey] =
|
||||
runtime.aspectRatioValueMap?.[aspectRatio] ||
|
||||
matchEnumValue(runtime.enums[runtime.aspectRatioKey], aspectRatio) ||
|
||||
aspectRatio;
|
||||
}
|
||||
if (runtime.resolutionKey) {
|
||||
body[runtime.resolutionKey] =
|
||||
matchEnumValue(runtime.enums[runtime.resolutionKey], imageSize.toLowerCase()) ||
|
||||
matchEnumValue(runtime.enums[runtime.resolutionKey], imageSize) ||
|
||||
imageSize.toLowerCase();
|
||||
} else {
|
||||
const sizeValue = pickClosestSizeValue(
|
||||
runtime.sizeValueMap,
|
||||
imageSize,
|
||||
aspectRatio === "auto" ? "1:1" : aspectRatio
|
||||
);
|
||||
if (sizeValue) body.size = sizeValue;
|
||||
}
|
||||
|
||||
const imageInputs = runtime.imageInputs?.length
|
||||
? runtime.imageInputs
|
||||
: runtime.imageInputKey
|
||||
? [
|
||||
{
|
||||
key: runtime.imageInputKey,
|
||||
mode: runtime.imageInputMode || ("single" as const),
|
||||
maxItems: Math.max(1, runtime.maxReferenceImages || 1),
|
||||
required: runtime.requiredFields.includes(runtime.imageInputKey),
|
||||
},
|
||||
]
|
||||
: [];
|
||||
let referenceCursor = 0;
|
||||
for (const input of imageInputs) {
|
||||
const values = params.referenceImages.slice(
|
||||
referenceCursor,
|
||||
referenceCursor + input.maxItems
|
||||
);
|
||||
if (values.length > 0) {
|
||||
body[input.key] = input.mode === "single" ? values[0] : values;
|
||||
referenceCursor += values.length;
|
||||
} else if (input.required) {
|
||||
throw new Error(
|
||||
`该 Atlas Cloud 模型至少需要 ${referenceCursor + 1} 张参考图`
|
||||
);
|
||||
}
|
||||
}
|
||||
if (imageInputs.length === 0 && params.referenceImages.length > 0) {
|
||||
throw new Error("当前 Atlas Cloud 模型不支持参考图，请选择图片编辑模型");
|
||||
}
|
||||
|
||||
const referenceVideos = params.referenceVideos || [];
|
||||
if (runtime.videoClipInput) {
|
||||
const values = referenceVideos.slice(0, runtime.videoClipInput.maxItems);
|
||||
if (values.length > 0) {
|
||||
body[runtime.videoClipInput.key] = values.map((url) => ({
|
||||
...runtime.videoClipInput?.itemDefaults,
|
||||
url,
|
||||
}));
|
||||
} else if (runtime.videoClipInput.required) {
|
||||
throw new Error("该 Atlas Cloud 模型至少需要 1 个参考视频");
|
||||
}
|
||||
} else if (referenceVideos.length > 0) {
|
||||
throw new Error("当前 Atlas Cloud 模型不支持参考视频");
|
||||
}
|
||||
|
||||
if (runtime.outputCountKey) {
|
||||
const requestedCount = Math.max(1, params.imageParams?.imageCount || 1);
|
||||
body[runtime.outputCountKey] = Math.min(runtime.maxImages, requestedCount);
|
||||
}
|
||||
const optionalParams: Array<[string, unknown]> = [
|
||||
["negative_prompt", params.imageParams?.negativePrompt],
|
||||
["prompt_extend", params.imageParams?.promptExtend],
|
||||
["quality", params.imageParams?.quality],
|
||||
["seed", params.imageParams?.seed],
|
||||
["watermark", params.imageParams?.watermark],
|
||||
];
|
||||
for (const [key, value] of optionalParams) {
|
||||
if (value !== undefined && runtime.propertyNames.includes(key)) {
|
||||
body[key] = matchEnumValue(runtime.enums[key], value) ?? value;
|
||||
}
|
||||
}
|
||||
if (runtime.propertyNames.includes("enable_sync_mode")) {
|
||||
body.enable_sync_mode = false;
|
||||
}
|
||||
if (runtime.propertyNames.includes("enable_base64_output")) {
|
||||
body.enable_base64_output = false;
|
||||
}
|
||||
|
||||
const unsupportedRequiredFields = runtime.requiredFields.filter(
|
||||
(key) => body[key] === undefined
|
||||
);
|
||||
if (unsupportedRequiredFields.length > 0) {
|
||||
throw new Error(
|
||||
`当前界面暂不支持该 Atlas Cloud 模型的必填参数：${unsupportedRequiredFields.join(", ")}`
|
||||
);
|
||||
}
|
||||
return { body, imageSize };
|
||||
}
|
||||
@ -1,10 +1,12 @@
|
||||
import "server-only";
|
||||
|
||||
import sharp from "sharp";
|
||||
import { ATLASCLOUD_BASE_URL } from "@/lib/ai/atlascloud-models";
|
||||
import {
|
||||
ATLASCLOUD_BASE_URL,
|
||||
type AtlasCloudRuntimeConfig,
|
||||
} from "@/lib/ai/atlascloud-models";
|
||||
createAtlasCloudRequestBody,
|
||||
type AtlasCloudImageParams,
|
||||
type AtlasCloudModelConfig,
|
||||
} from "@/lib/ai/atlascloud-request";
|
||||
import { createDeferredUploadedImage } from "@/lib/storage/image-archive";
|
||||
import { uploadFile } from "@/lib/storage/service";
|
||||
|
||||
@ -13,24 +15,6 @@ interface AtlasCloudConfig {
|
||||
baseURL?: string;
|
||||
}
|
||||
|
||||
interface AtlasCloudImageParams {
|
||||
aspectRatio?: string;
|
||||
imageSize?: string;
|
||||
imageCount?: number;
|
||||
negativePrompt?: string;
|
||||
promptExtend?: boolean;
|
||||
quality?: string;
|
||||
seed?: number;
|
||||
watermark?: boolean;
|
||||
}
|
||||
|
||||
interface AtlasCloudModelConfig {
|
||||
maxReferenceImages?: number;
|
||||
supportedAspectRatios?: string[];
|
||||
supportedImageSizes?: string[];
|
||||
atlasCloud?: AtlasCloudRuntimeConfig;
|
||||
}
|
||||
|
||||
interface UploadedImage {
|
||||
thumbnail: string;
|
||||
original: string;
|
||||
@ -116,18 +100,19 @@ function extractOutputUrls(payload: any) {
|
||||
return urls;
|
||||
}
|
||||
|
||||
function extractPromptAndImages(
|
||||
function extractPromptAndMedia(
|
||||
messages: Array<{ role: string; content?: any; parts?: any[] }>
|
||||
) {
|
||||
const message = messages.filter((item) => item.role === "user").pop();
|
||||
if (!message) throw new Error("未找到用户消息");
|
||||
const texts: string[] = [];
|
||||
const imageUrls: string[] = [];
|
||||
const videoUrls: string[] = [];
|
||||
|
||||
const pushText = (value: unknown) => {
|
||||
if (typeof value === "string" && value.trim()) texts.push(value.trim());
|
||||
};
|
||||
const pushImage = (value: unknown) => {
|
||||
const pushMedia = (value: unknown, mediaType?: unknown) => {
|
||||
const url = String(
|
||||
typeof value === "string"
|
||||
? value
|
||||
@ -137,24 +122,31 @@ function extractPromptAndImages(
|
||||
(value as any)?.src ||
|
||||
""
|
||||
).trim();
|
||||
if (
|
||||
url &&
|
||||
(/^https?:\/\//i.test(url) || url.startsWith("data:image/")) &&
|
||||
!imageUrls.includes(url)
|
||||
) {
|
||||
imageUrls.push(url);
|
||||
}
|
||||
if (!url || !/^(?:https?:\/\/|data:)/i.test(url)) return;
|
||||
const normalizedMediaType = String(mediaType || "").toLowerCase();
|
||||
const isVideo =
|
||||
normalizedMediaType.startsWith("video/") ||
|
||||
url.startsWith("data:video/") ||
|
||||
/\.(?:mp4|mov|webm|m4v)(?:[?#].*)?$/i.test(url);
|
||||
const target = isVideo ? videoUrls : imageUrls;
|
||||
if (!target.includes(url)) target.push(url);
|
||||
};
|
||||
const visitPart = (part: any) => {
|
||||
if (!part) return;
|
||||
if (typeof part === "string") return pushText(part);
|
||||
if (part.type === "text" || typeof part.text === "string") pushText(part.text);
|
||||
if (part.type === "image_url") pushImage(part.image_url);
|
||||
if (part.type === "image") pushImage(part.image || part.url);
|
||||
if (part.type === "file") pushImage(part.url || part.file || part.data);
|
||||
if (part.type === "image_url") pushMedia(part.image_url, "image/jpeg");
|
||||
if (part.type === "image") pushMedia(part.image || part.url, "image/jpeg");
|
||||
if (part.type === "file") {
|
||||
pushMedia(
|
||||
part.url || part.file || part.data,
|
||||
part.mediaType || part.contentType || part.mimeType
|
||||
);
|
||||
}
|
||||
if (part.inlineData?.data) {
|
||||
pushImage(
|
||||
`data:${part.inlineData.mimeType || "image/png"};base64,${part.inlineData.data}`
|
||||
pushMedia(
|
||||
`data:${part.inlineData.mimeType || "image/png"};base64,${part.inlineData.data}`,
|
||||
part.inlineData.mimeType
|
||||
);
|
||||
}
|
||||
};
|
||||
@ -165,31 +157,31 @@ function extractPromptAndImages(
|
||||
|
||||
const prompt = texts.join("\n").trim();
|
||||
if (!prompt) throw new Error("请输入图片生成或编辑要求");
|
||||
return { prompt, imageUrls };
|
||||
return { prompt, imageUrls, videoUrls };
|
||||
}
|
||||
|
||||
function parseDataUrl(value: string) {
|
||||
const match = value.match(/^data:([^;,]+);base64,(.+)$/s);
|
||||
if (!match) throw new Error("Atlas Cloud 参考图 Base64 格式无效");
|
||||
if (!match) throw new Error("Atlas Cloud 参考素材 Base64 格式无效");
|
||||
return {
|
||||
mimeType: match[1] || "image/png",
|
||||
buffer: Buffer.from(match[2] || "", "base64"),
|
||||
};
|
||||
}
|
||||
|
||||
async function loadImageSource(imageUrl: string) {
|
||||
if (imageUrl.startsWith("data:")) return parseDataUrl(imageUrl);
|
||||
const response = await fetch(imageUrl, {
|
||||
async function loadMediaSource(mediaUrl: string) {
|
||||
if (mediaUrl.startsWith("data:")) return parseDataUrl(mediaUrl);
|
||||
const response = await fetch(mediaUrl, {
|
||||
cache: "no-store",
|
||||
redirect: "follow",
|
||||
signal: AbortSignal.timeout(DOWNLOAD_TIMEOUT_MS),
|
||||
headers: {
|
||||
Accept: "image/avif,image/webp,image/png,image/jpeg,image/*,*/*;q=0.8",
|
||||
Accept: "image/*,video/*,*/*;q=0.8",
|
||||
"User-Agent": "yedir-ai-atlascloud/1.0",
|
||||
},
|
||||
});
|
||||
if (!response.ok) {
|
||||
throw new Error(`Atlas Cloud 参考图下载失败（HTTP ${response.status}）`);
|
||||
throw new Error(`Atlas Cloud 参考素材下载失败（HTTP ${response.status}）`);
|
||||
}
|
||||
return {
|
||||
mimeType: response.headers.get("content-type")?.split(";")[0] || "image/png",
|
||||
@ -201,16 +193,19 @@ function detectExtension(mimeType: string) {
|
||||
if (/jpe?g/i.test(mimeType)) return "jpg";
|
||||
if (/webp/i.test(mimeType)) return "webp";
|
||||
if (/gif/i.test(mimeType)) return "gif";
|
||||
if (/quicktime/i.test(mimeType)) return "mov";
|
||||
if (/webm/i.test(mimeType)) return "webm";
|
||||
if (/mp4/i.test(mimeType)) return "mp4";
|
||||
return "png";
|
||||
}
|
||||
|
||||
async function uploadReferenceImage(
|
||||
async function uploadReferenceMedia(
|
||||
baseURL: string | undefined,
|
||||
apiKey: string,
|
||||
imageUrl: string
|
||||
mediaUrl: string
|
||||
) {
|
||||
if (/^https:\/\//i.test(imageUrl)) return imageUrl;
|
||||
const source = await loadImageSource(imageUrl);
|
||||
if (/^https:\/\//i.test(mediaUrl)) return mediaUrl;
|
||||
const source = await loadMediaSource(mediaUrl);
|
||||
const form = new FormData();
|
||||
form.append(
|
||||
"file",
|
||||
@ -226,171 +221,17 @@ async function uploadReferenceImage(
|
||||
const payload = await parseJsonResponse(response);
|
||||
if (!response.ok) {
|
||||
throw new Error(
|
||||
`${extractErrorMessage(payload, "Atlas Cloud 参考图上传失败")}（HTTP ${response.status}）`
|
||||
`${extractErrorMessage(payload, "Atlas Cloud 参考素材上传失败")}（HTTP ${response.status}）`
|
||||
);
|
||||
}
|
||||
const data = payload?.data && typeof payload.data === "object" ? payload.data : payload;
|
||||
const url = String(
|
||||
data?.url || data?.file_url || data?.fileUrl || data?.media_url || data?.mediaUrl || ""
|
||||
).trim();
|
||||
if (!url) throw new Error("Atlas Cloud 参考图上传成功但未返回文件地址");
|
||||
if (!url) throw new Error("Atlas Cloud 参考素材上传成功但未返回文件地址");
|
||||
return url;
|
||||
}
|
||||
|
||||
function normalizeAspectRatio(
|
||||
requested: string | undefined,
|
||||
supported: string[] | undefined
|
||||
) {
|
||||
const values = (supported || []).map(String);
|
||||
const normalized = String(requested || "auto").trim().toLowerCase();
|
||||
const exact = values.find((value) => value.toLowerCase() === normalized);
|
||||
if (exact) return exact;
|
||||
return values.find((value) => value === "auto") || values.find((value) => value === "1:1") || values[0] || "1:1";
|
||||
}
|
||||
|
||||
function normalizeImageSize(requested: string | undefined, supported?: string[]) {
|
||||
const values = (supported || []).map((value) => String(value).trim().toUpperCase());
|
||||
const normalized = String(requested || "2K").trim().toUpperCase();
|
||||
if (values.includes(normalized)) return normalized;
|
||||
return values.includes("2K") ? "2K" : values[0] || normalized;
|
||||
}
|
||||
|
||||
function matchEnumValue(values: Array<string | number> | undefined, value: unknown) {
|
||||
if (!values?.length) return value;
|
||||
const normalized = String(value || "").trim().toLowerCase();
|
||||
return values.find((item) => String(item).trim().toLowerCase() === normalized);
|
||||
}
|
||||
|
||||
function parseRatio(value: string) {
|
||||
const match = value.match(/^(\d+):(\d+)$/);
|
||||
if (!match) return 1;
|
||||
return Number(match[1]) / Number(match[2]);
|
||||
}
|
||||
|
||||
function pickClosestSizeValue(
|
||||
map: Record<string, Record<string, string>>,
|
||||
imageSize: string,
|
||||
aspectRatio: string
|
||||
) {
|
||||
const tiers = [imageSize, "2K", "1K", "4K"];
|
||||
const values = tiers.map((tier) => map[tier]).find(Boolean);
|
||||
if (!values) return undefined;
|
||||
if (values[aspectRatio]) return values[aspectRatio];
|
||||
const target = parseRatio(aspectRatio);
|
||||
return Object.entries(values).sort(
|
||||
([a], [b]) =>
|
||||
Math.abs(Math.log(target / parseRatio(a))) -
|
||||
Math.abs(Math.log(target / parseRatio(b)))
|
||||
)[0]?.[1];
|
||||
}
|
||||
|
||||
function createRequestBody(params: {
|
||||
modelId: string;
|
||||
prompt: string;
|
||||
referenceImages: string[];
|
||||
imageParams?: AtlasCloudImageParams;
|
||||
modelConfig: AtlasCloudModelConfig;
|
||||
}) {
|
||||
const runtime = params.modelConfig.atlasCloud;
|
||||
if (!runtime) throw new Error("Atlas Cloud 模型运行参数缺失，请重新同步模型");
|
||||
const body: Record<string, unknown> = {
|
||||
...runtime.defaults,
|
||||
};
|
||||
if (runtime.propertyNames.includes("model")) body.model = params.modelId;
|
||||
if (runtime.propertyNames.includes("prompt")) body.prompt = params.prompt;
|
||||
const aspectRatio = normalizeAspectRatio(
|
||||
params.imageParams?.aspectRatio,
|
||||
params.modelConfig.supportedAspectRatios
|
||||
);
|
||||
const imageSize = normalizeImageSize(
|
||||
params.imageParams?.imageSize,
|
||||
params.modelConfig.supportedImageSizes
|
||||
);
|
||||
|
||||
if (runtime.aspectRatioKey) {
|
||||
body[runtime.aspectRatioKey] =
|
||||
runtime.aspectRatioValueMap?.[aspectRatio] ||
|
||||
matchEnumValue(runtime.enums[runtime.aspectRatioKey], aspectRatio) || aspectRatio;
|
||||
}
|
||||
if (runtime.resolutionKey) {
|
||||
const resolutionValue =
|
||||
matchEnumValue(runtime.enums[runtime.resolutionKey], imageSize.toLowerCase()) ||
|
||||
matchEnumValue(runtime.enums[runtime.resolutionKey], imageSize) ||
|
||||
imageSize.toLowerCase();
|
||||
body[runtime.resolutionKey] = resolutionValue;
|
||||
} else {
|
||||
const sizeValue = pickClosestSizeValue(
|
||||
runtime.sizeValueMap,
|
||||
imageSize,
|
||||
aspectRatio === "auto" ? "1:1" : aspectRatio
|
||||
);
|
||||
if (sizeValue) body.size = sizeValue;
|
||||
}
|
||||
|
||||
const imageInputs = runtime.imageInputs?.length
|
||||
? runtime.imageInputs
|
||||
: runtime.imageInputKey
|
||||
? [
|
||||
{
|
||||
key: runtime.imageInputKey,
|
||||
mode: runtime.imageInputMode || "single",
|
||||
maxItems: Math.max(1, runtime.maxReferenceImages || 1),
|
||||
required: runtime.requiredFields.includes(runtime.imageInputKey),
|
||||
},
|
||||
]
|
||||
: [];
|
||||
let referenceCursor = 0;
|
||||
for (const input of imageInputs) {
|
||||
const values = params.referenceImages.slice(
|
||||
referenceCursor,
|
||||
referenceCursor + input.maxItems
|
||||
);
|
||||
if (values.length > 0) {
|
||||
body[input.key] = input.mode === "single" ? values[0] : values;
|
||||
referenceCursor += values.length;
|
||||
} else if (input.required) {
|
||||
throw new Error(
|
||||
`该 Atlas Cloud 模型至少需要 ${referenceCursor + 1} 张参考图`
|
||||
);
|
||||
}
|
||||
}
|
||||
if (imageInputs.length === 0 && params.referenceImages.length > 0) {
|
||||
throw new Error("当前 Atlas Cloud 模型不支持参考图，请选择图片编辑模型");
|
||||
}
|
||||
|
||||
if (runtime.outputCountKey) {
|
||||
const requestedCount = Math.max(1, params.imageParams?.imageCount || 1);
|
||||
body[runtime.outputCountKey] = Math.min(runtime.maxImages, requestedCount);
|
||||
}
|
||||
const optionalParams: Array<[string, unknown]> = [
|
||||
["negative_prompt", params.imageParams?.negativePrompt],
|
||||
["prompt_extend", params.imageParams?.promptExtend],
|
||||
["quality", params.imageParams?.quality],
|
||||
["seed", params.imageParams?.seed],
|
||||
["watermark", params.imageParams?.watermark],
|
||||
];
|
||||
for (const [key, value] of optionalParams) {
|
||||
if (value !== undefined && runtime.propertyNames.includes(key)) {
|
||||
body[key] = matchEnumValue(runtime.enums[key], value) ?? value;
|
||||
}
|
||||
}
|
||||
if (runtime.propertyNames.includes("enable_sync_mode")) {
|
||||
body.enable_sync_mode = false;
|
||||
}
|
||||
if (runtime.propertyNames.includes("enable_base64_output")) {
|
||||
body.enable_base64_output = false;
|
||||
}
|
||||
const unsupportedRequiredFields = runtime.requiredFields.filter(
|
||||
(key) => body[key] === undefined
|
||||
);
|
||||
if (unsupportedRequiredFields.length > 0) {
|
||||
throw new Error(
|
||||
`当前界面暂不支持该 Atlas Cloud 模型的必填参数：${unsupportedRequiredFields.join(", ")}`
|
||||
);
|
||||
}
|
||||
return { body, imageSize };
|
||||
}
|
||||
|
||||
async function submitTask(params: {
|
||||
apiKey: string;
|
||||
baseURL?: string;
|
||||
@ -540,7 +381,9 @@ export function createAtlasCloud({ apiKey, baseURL }: AtlasCloudConfig) {
|
||||
if (!modelConfig.atlasCloud) {
|
||||
throw new Error("Atlas Cloud 模型能力配置缺失，请在系统设置中重新同步模型");
|
||||
}
|
||||
const { prompt, imageUrls } = extractPromptAndImages(options.messages);
|
||||
const { prompt, imageUrls, videoUrls } = extractPromptAndMedia(
|
||||
options.messages
|
||||
);
|
||||
const maxReferenceImages = Math.max(
|
||||
0,
|
||||
Math.min(14, modelConfig.maxReferenceImages ?? modelConfig.atlasCloud.maxReferenceImages)
|
||||
@ -548,12 +391,27 @@ export function createAtlasCloud({ apiKey, baseURL }: AtlasCloudConfig) {
|
||||
const referenceImages = await Promise.all(
|
||||
imageUrls
|
||||
.slice(0, maxReferenceImages)
|
||||
.map((url) => uploadReferenceImage(baseURL, apiKey, url))
|
||||
.map((url) => uploadReferenceMedia(baseURL, apiKey, url))
|
||||
);
|
||||
const { body, imageSize } = createRequestBody({
|
||||
const maxVideoReferences = Math.max(
|
||||
0,
|
||||
Math.min(
|
||||
4,
|
||||
modelConfig.maxVideoReferences ??
|
||||
modelConfig.atlasCloud.maxVideoReferences ??
|
||||
0
|
||||
)
|
||||
);
|
||||
const referenceVideos = await Promise.all(
|
||||
videoUrls
|
||||
.slice(0, maxVideoReferences)
|
||||
.map((url) => uploadReferenceMedia(baseURL, apiKey, url))
|
||||
);
|
||||
const { body, imageSize } = createAtlasCloudRequestBody({
|
||||
modelId: runtimeModelId,
|
||||
prompt,
|
||||
referenceImages,
|
||||
referenceVideos,
|
||||
imageParams: options.imageParams,
|
||||
modelConfig,
|
||||
});
|
||||
|
||||
92
scripts/sync-atlascloud-models.ts
Normal file
92
scripts/sync-atlascloud-models.ts
Normal file
@ -0,0 +1,92 @@
|
||||
import { and, eq } from "drizzle-orm";
|
||||
import { fetchAtlasCloudImagePresets } from "../lib/ai/atlascloud-models";
|
||||
import { db } from "../lib/db";
|
||||
import { aiModel, aiProvider } from "../lib/db/schema";
|
||||
|
||||
async function main() {
|
||||
const providers = await db
|
||||
.select()
|
||||
.from(aiProvider)
|
||||
.where(and(eq(aiProvider.type, "atlascloud"), eq(aiProvider.isEnabled, true)));
|
||||
if (providers.length === 0) {
|
||||
throw new Error("没有找到已启用的 AtlasCloud 服务商");
|
||||
}
|
||||
|
||||
const catalog = await fetchAtlasCloudImagePresets();
|
||||
if (catalog.errors.length > 0) {
|
||||
throw new Error(
|
||||
`AtlasCloud 目录有 ${catalog.errors.length} 个 schema 加载失败：${catalog.errors
|
||||
.map((item) => item.modelId)
|
||||
.join(", ")}`
|
||||
);
|
||||
}
|
||||
|
||||
const summaries = [];
|
||||
for (const provider of providers) {
|
||||
let added = 0;
|
||||
let updated = 0;
|
||||
for (const preset of catalog.presets) {
|
||||
const existing = await db.query.aiModel.findFirst({
|
||||
where: and(
|
||||
eq(aiModel.providerId, provider.id),
|
||||
eq(aiModel.modelId, preset.modelId)
|
||||
),
|
||||
});
|
||||
const values = {
|
||||
displayName: preset.displayName,
|
||||
avatarUrl: preset.avatarUrl || null,
|
||||
description: preset.description,
|
||||
supportsVision: preset.supportsVision,
|
||||
supportsImageGen: preset.supportsImageGen,
|
||||
isEnabled: true,
|
||||
isHidden: false,
|
||||
sortOrder: preset.sortOrder,
|
||||
capabilities: preset.capabilities,
|
||||
defaultParams: preset.defaultParams,
|
||||
imageGenConfig: preset.imageGenConfig,
|
||||
updatedAt: new Date(),
|
||||
};
|
||||
|
||||
if (existing) {
|
||||
await db
|
||||
.update(aiModel)
|
||||
.set(values)
|
||||
.where(eq(aiModel.id, existing.id));
|
||||
updated += 1;
|
||||
} else {
|
||||
await db.insert(aiModel).values({
|
||||
providerId: provider.id,
|
||||
modelId: preset.modelId,
|
||||
...values,
|
||||
isDefault: false,
|
||||
isSubModel: false,
|
||||
parentModelId: null,
|
||||
});
|
||||
added += 1;
|
||||
}
|
||||
}
|
||||
summaries.push({
|
||||
providerId: provider.id,
|
||||
providerName: provider.name,
|
||||
added,
|
||||
updated,
|
||||
});
|
||||
}
|
||||
|
||||
console.log(
|
||||
JSON.stringify(
|
||||
{
|
||||
catalogModels: catalog.catalogCount,
|
||||
availableModels: catalog.presets.length,
|
||||
providers: summaries,
|
||||
},
|
||||
null,
|
||||
2
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
void main().catch((error) => {
|
||||
console.error(error instanceof Error ? error.message : String(error));
|
||||
process.exitCode = 1;
|
||||
});
|
||||
204
scripts/verify-atlascloud-frontend.ts
Normal file
204
scripts/verify-atlascloud-frontend.ts
Normal file
@ -0,0 +1,204 @@
|
||||
import { fetchAtlasCloudImagePresets } from "../lib/ai/atlascloud-models";
|
||||
import { createAtlasCloudRequestBody } from "../lib/ai/atlascloud-request";
|
||||
import {
|
||||
is3DModelDescriptor,
|
||||
isImageGenerationModelDescriptor,
|
||||
isVideoModelDescriptor,
|
||||
} from "../lib/ai/model-classification";
|
||||
|
||||
const FAKE_IMAGES = Array.from(
|
||||
{ length: 14 },
|
||||
(_, index) => `https://example.com/reference-${index + 1}.png`
|
||||
);
|
||||
const FAKE_VIDEOS = Array.from(
|
||||
{ length: 4 },
|
||||
(_, index) => `https://example.com/reference-${index + 1}.mp4`
|
||||
);
|
||||
|
||||
type Failure = {
|
||||
modelId: string;
|
||||
scenario: string;
|
||||
error: string;
|
||||
};
|
||||
|
||||
function validateBody(
|
||||
body: Record<string, unknown>,
|
||||
runtime: any
|
||||
) {
|
||||
const missing = runtime.requiredFields.filter(
|
||||
(key: string) => body[key] === undefined
|
||||
);
|
||||
if (missing.length > 0) {
|
||||
throw new Error(`缺少必填参数：${missing.join(", ")}`);
|
||||
}
|
||||
for (const [key, values] of Object.entries(
|
||||
runtime.enums as Record<string, Array<string | number>>
|
||||
)) {
|
||||
if (body[key] === undefined || !values.length) continue;
|
||||
if (!values.some((value) => String(value) === String(body[key]))) {
|
||||
throw new Error(`${key}=${String(body[key])} 不在官方枚举中`);
|
||||
}
|
||||
}
|
||||
if (runtime.videoClipInput && body[runtime.videoClipInput.key] !== undefined) {
|
||||
const clips = body[runtime.videoClipInput.key];
|
||||
if (!Array.isArray(clips) || clips.length === 0) {
|
||||
throw new Error("video_clips 请求格式无效");
|
||||
}
|
||||
for (const clip of clips) {
|
||||
if (!clip || typeof clip !== "object" || !("url" in clip)) {
|
||||
throw new Error("video_clips 缺少 url");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
async function main() {
|
||||
const catalog = await fetchAtlasCloudImagePresets();
|
||||
const failures: Failure[] = catalog.errors.map((item) => ({
|
||||
modelId: item.modelId,
|
||||
scenario: "catalog-schema",
|
||||
error: item.error,
|
||||
}));
|
||||
let simulatedCases = 0;
|
||||
let imageModels = 0;
|
||||
let model3dModels = 0;
|
||||
let videoReferenceModels = 0;
|
||||
|
||||
for (const preset of catalog.presets) {
|
||||
const capabilities = preset.capabilities as Record<string, any>;
|
||||
const descriptor = {
|
||||
providerType: "atlascloud",
|
||||
modelId: preset.modelId,
|
||||
capabilities,
|
||||
supportsImageGen: preset.supportsImageGen,
|
||||
};
|
||||
const mediaType = String(capabilities.mediaType || "");
|
||||
|
||||
if (mediaType === "3d") {
|
||||
model3dModels += 1;
|
||||
simulatedCases += 1;
|
||||
if (
|
||||
!is3DModelDescriptor(descriptor) ||
|
||||
isImageGenerationModelDescriptor(descriptor) ||
|
||||
isVideoModelDescriptor(descriptor)
|
||||
) {
|
||||
failures.push({
|
||||
modelId: preset.modelId,
|
||||
scenario: "3d-classification",
|
||||
error: "3D 模型被错误归入图片或视频模型",
|
||||
});
|
||||
}
|
||||
continue;
|
||||
}
|
||||
|
||||
imageModels += 1;
|
||||
if (
|
||||
!isImageGenerationModelDescriptor(descriptor) ||
|
||||
is3DModelDescriptor(descriptor) ||
|
||||
isVideoModelDescriptor(descriptor)
|
||||
) {
|
||||
failures.push({
|
||||
modelId: preset.modelId,
|
||||
scenario: "image-classification",
|
||||
error: "图片模型分类不正确",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
const imageGenConfig = preset.imageGenConfig as Record<string, any>;
|
||||
const runtime = imageGenConfig.atlasCloud;
|
||||
if (!runtime) {
|
||||
failures.push({
|
||||
modelId: preset.modelId,
|
||||
scenario: "runtime-config",
|
||||
error: "缺少 AtlasCloud 运行配置",
|
||||
});
|
||||
continue;
|
||||
}
|
||||
|
||||
const ratios = imageGenConfig.supportedAspectRatios?.length
|
||||
? imageGenConfig.supportedAspectRatios
|
||||
: [String(preset.defaultParams.aspectRatio || "1:1")];
|
||||
const sizes = imageGenConfig.supportedImageSizes?.length
|
||||
? imageGenConfig.supportedImageSizes
|
||||
: [String(preset.defaultParams.imageSize || "1K")];
|
||||
const counts = runtime.outputCountKey && runtime.maxImages > 1
|
||||
? [1, runtime.maxImages]
|
||||
: [1];
|
||||
const requiredImageCount = runtime.imageInputs
|
||||
.filter((input: any) => input.required)
|
||||
.reduce((total: number, input: any) => total + input.maxItems, 0);
|
||||
const imageReferenceCounts = new Set<number>([
|
||||
requiredImageCount,
|
||||
...(runtime.maxReferenceImages > requiredImageCount
|
||||
? [runtime.maxReferenceImages]
|
||||
: []),
|
||||
]);
|
||||
const requiredVideoCount = runtime.videoClipInput?.required
|
||||
? runtime.videoClipInput.maxItems
|
||||
: 0;
|
||||
const videoReferenceCounts = new Set<number>([
|
||||
requiredVideoCount,
|
||||
...(runtime.maxVideoReferences > requiredVideoCount
|
||||
? [runtime.maxVideoReferences]
|
||||
: []),
|
||||
]);
|
||||
if (runtime.maxVideoReferences > 0) videoReferenceModels += 1;
|
||||
|
||||
for (const ratio of ratios) {
|
||||
for (const size of sizes) {
|
||||
for (const imageCount of counts) {
|
||||
for (const referenceImageCount of imageReferenceCounts) {
|
||||
for (const referenceVideoCount of videoReferenceCounts) {
|
||||
const scenario = [
|
||||
`ratio=${ratio}`,
|
||||
`size=${size}`,
|
||||
`count=${imageCount}`,
|
||||
`images=${referenceImageCount}`,
|
||||
`videos=${referenceVideoCount}`,
|
||||
].join(",");
|
||||
simulatedCases += 1;
|
||||
try {
|
||||
const { body } = createAtlasCloudRequestBody({
|
||||
modelId: preset.modelId,
|
||||
prompt: "AtlasCloud 前端请求模拟测试",
|
||||
referenceImages: FAKE_IMAGES.slice(0, referenceImageCount),
|
||||
referenceVideos: FAKE_VIDEOS.slice(0, referenceVideoCount),
|
||||
imageParams: {
|
||||
aspectRatio: ratio,
|
||||
imageSize: size,
|
||||
imageCount,
|
||||
},
|
||||
modelConfig: imageGenConfig,
|
||||
});
|
||||
validateBody(body, runtime);
|
||||
} catch (error) {
|
||||
failures.push({
|
||||
modelId: preset.modelId,
|
||||
scenario,
|
||||
error: error instanceof Error ? error.message : String(error),
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const summary = {
|
||||
catalogModels: catalog.catalogCount,
|
||||
availableModels: catalog.presets.length,
|
||||
imageModels,
|
||||
model3dModels,
|
||||
videoReferenceModels,
|
||||
simulatedCases,
|
||||
passedCases: simulatedCases - failures.length,
|
||||
failedCases: failures.length,
|
||||
failures,
|
||||
};
|
||||
console.log(JSON.stringify(summary, null, 2));
|
||||
if (failures.length > 0) process.exitCode = 1;
|
||||
}
|
||||
|
||||
void main();
|
||||
@ -3,6 +3,7 @@ import {
|
||||
createAtlasCloudImagePreset,
|
||||
inferAtlasCloudMediaKind,
|
||||
} from "@/lib/ai/atlascloud-models";
|
||||
import { createAtlasCloudRequestBody } from "@/lib/ai/atlascloud-request";
|
||||
import {
|
||||
is3DModelDescriptor,
|
||||
isImageGenerationModelDescriptor,
|
||||
@ -120,4 +121,71 @@ test.describe("AI model media classification", () => {
|
||||
expect(isVideoModelDescriptor(videoDescriptor)).toBe(true);
|
||||
expect(isImageGenerationModelDescriptor(videoDescriptor)).toBe(false);
|
||||
});
|
||||
|
||||
test("maps Atlas reference-video image models to a valid frontend request", () => {
|
||||
const preset = createAtlasCloudImagePreset(
|
||||
{
|
||||
model: "google/nano-banana-2/reference-to-image",
|
||||
type: "Image",
|
||||
displayName: "Nano Banana 2 Reference to Image",
|
||||
categories: ["IMAGE-TO-IMAGE"],
|
||||
},
|
||||
{
|
||||
paths: {
|
||||
"/api/v1/model/generateImage": { post: {} },
|
||||
"/api/v1/model/prediction/{request_id}": { get: {} },
|
||||
},
|
||||
components: {
|
||||
schemas: {
|
||||
Input: {
|
||||
type: "object",
|
||||
properties: {
|
||||
model: { type: "string" },
|
||||
prompt: { type: "string" },
|
||||
resolution: { type: "string", enum: ["1k", "2k", "4k"] },
|
||||
video_clips: {
|
||||
type: "array",
|
||||
minItems: 1,
|
||||
maxItems: 1,
|
||||
items: {
|
||||
type: "object",
|
||||
properties: {
|
||||
url: { type: "string" },
|
||||
start: { type: "number", default: 0 },
|
||||
ends: { type: "number", default: 0 },
|
||||
fps: { type: "number", default: 1 },
|
||||
},
|
||||
},
|
||||
},
|
||||
},
|
||||
required: ["model", "prompt", "video_clips"],
|
||||
},
|
||||
},
|
||||
},
|
||||
}
|
||||
);
|
||||
|
||||
expect(preset.capabilities).toMatchObject({
|
||||
mediaType: "image",
|
||||
supportsVideoReference: true,
|
||||
requiresVideoReference: true,
|
||||
maxVideoReferences: 1,
|
||||
});
|
||||
const { body } = createAtlasCloudRequestBody({
|
||||
modelId: preset.modelId,
|
||||
prompt: "参考视频生成商品图",
|
||||
referenceImages: [],
|
||||
referenceVideos: ["https://example.com/reference.mp4"],
|
||||
imageParams: { imageSize: "2K", aspectRatio: "1:1" },
|
||||
modelConfig: preset.imageGenConfig,
|
||||
});
|
||||
expect(body.video_clips).toEqual([
|
||||
{
|
||||
url: "https://example.com/reference.mp4",
|
||||
start: 0,
|
||||
ends: 0,
|
||||
fps: 1,
|
||||
},
|
||||
]);
|
||||
});
|
||||
});
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user