fix(video): harden volcano model routing and request retries
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b1ac60a629
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46b3f4b081
@ -238,6 +238,103 @@ function startStreamKeepalive(writer: StreamWriter, label: string, intervalMs =
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return () => clearInterval(timer);
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}
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type VideoModeType = "text-to-video" | "first-frame" | "first-last-frame" | "reference-images";
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function inferSupportedVideoModesByModelId(modelId: string): VideoModeType[] {
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const normalized = modelId.toLowerCase();
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if (normalized.includes("lite-t2v")) {
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return ["text-to-video"];
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}
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if (normalized.includes("lite-i2v")) {
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return ["first-frame", "first-last-frame", "reference-images"];
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}
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if (normalized.includes("pro-fast")) {
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return ["text-to-video", "first-frame"];
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}
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if (normalized.includes("-pro-") || normalized.endsWith("-pro")) {
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return ["text-to-video", "first-frame", "first-last-frame"];
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}
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return ["text-to-video", "first-frame", "first-last-frame", "reference-images"];
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}
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function getSupportedVideoModesForModel(model: any): VideoModeType[] {
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const capabilityModes = (((model?.capabilities as any)?.supportedModes ?? []) as string[])
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.filter((mode): mode is VideoModeType =>
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mode === "text-to-video" ||
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mode === "first-frame" ||
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mode === "first-last-frame" ||
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mode === "reference-images"
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);
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if (capabilityModes.length > 0) {
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return capabilityModes;
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}
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const modelId = String(model?.modelId || "");
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return inferSupportedVideoModesByModelId(modelId);
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}
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function scoreVideoSubModelForMode(modelId: string, mode: VideoModeType): number {
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const normalized = modelId.toLowerCase();
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const isProFast = normalized.includes("pro-fast");
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const isLiteT2V = normalized.includes("lite-t2v");
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const isLiteI2V = normalized.includes("lite-i2v");
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const isPro = (normalized.includes("-pro-") || normalized.endsWith("-pro")) && !isProFast;
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const isV15Pro = normalized.includes("seedance-1-5-pro");
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switch (mode) {
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case "first-last-frame":
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if (isV15Pro) return 150;
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if (isPro) return 120;
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if (isLiteI2V) return 90;
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if (isProFast) return -1000;
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if (isLiteT2V) return -1000;
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return 10;
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case "first-frame":
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if (isV15Pro) return 140;
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if (isProFast) return 130;
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if (isPro) return 120;
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if (isLiteI2V) return 100;
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if (isLiteT2V) return 20;
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return 10;
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case "reference-images":
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if (isV15Pro) return 150;
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if (isLiteI2V) return 140;
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if (isPro) return 110;
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if (isProFast || isLiteT2V) return -1000;
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return 10;
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case "text-to-video":
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default:
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if (isV15Pro) return 140;
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if (isLiteT2V) return 130;
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if (isProFast) return 120;
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if (isPro) return 100;
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if (isLiteI2V) return 80;
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return 10;
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}
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}
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function selectBestVideoSubModelForMode(
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subModels: Array<{ model: any }>,
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mode: VideoModeType,
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): { model: any } | null {
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const compatible = subModels.filter(({ model }) => {
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const supportedModes = getSupportedVideoModesForModel(model);
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return supportedModes.includes(mode);
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});
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const candidates = compatible.length > 0 ? compatible : subModels;
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if (candidates.length === 0) return null;
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return [...candidates].sort((a, b) => {
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const scoreA = scoreVideoSubModelForMode(String(a.model?.modelId || ""), mode);
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const scoreB = scoreVideoSubModelForMode(String(b.model?.modelId || ""), mode);
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return scoreB - scoreA;
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})[0];
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}
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async function replayAssistantMessagesForDuplicateRequest({
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chatId,
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userMessageId,
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@ -2118,41 +2215,18 @@ export async function POST(request: Request) {
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console.log("[Chat API] Video params:", videoParams);
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// 如果没有 videoParams 或没有 mode，使用默认模式
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const mode = videoParams?.mode || "text-to-video";
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const mode = (videoParams?.mode || "text-to-video") as VideoModeType;
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console.log("[Chat API] Using mode:", mode);
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// 根据模式选择对应的子模型
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const modeToModelMap: Record<string, string> = {
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"text-to-video": "lite-t2v", // 文生视频 → Lite T2V
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"first-last-frame": "pro", // 首尾帧 → Pro
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"first-frame": "pro-fast", // 智能多帧 → Pro Fast
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"reference-images": "lite-i2v", // 主体参考 → Lite I2V
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};
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const targetSubModelKey = modeToModelMap[mode];
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if (targetSubModelKey) {
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// 查找匹配的子模型（通过 modelId 中包含的关键字）
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const compatibleSubModels = subModels.filter(({ model }) => {
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const supportedModes = ((model.capabilities as any)?.supportedModes ?? []) as string[];
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return supportedModes.length === 0 || supportedModes.includes(mode);
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});
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const matchedSubModel = compatibleSubModels.find(({ model }) =>
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model.modelId.toLowerCase().includes(targetSubModelKey)
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const matchedSubModel = selectBestVideoSubModelForMode(subModels as any, mode);
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if (matchedSubModel) {
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console.log(
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`[Chat API] 视频模式 ${mode} → 选择子模型: ${matchedSubModel.model.displayName} (${matchedSubModel.model.modelId})`
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);
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if (matchedSubModel) {
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console.log(`[Chat API] 视频模式 ${mode} → 选择子模型: ${matchedSubModel.model.displayName}`);
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targetModelId = matchedSubModel.model.id;
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} else if (compatibleSubModels.length > 0) {
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console.warn(
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`[Chat API] 未找到匹配关键字子模型: ${targetSubModelKey}，使用兼容子模型 ${compatibleSubModels[0].model.displayName}`
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);
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targetModelId = compatibleSubModels[0].model.id;
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} else {
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console.warn(`[Chat API] 未找到匹配的子模型: ${targetSubModelKey}，将使用第一个可用子模型`);
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// 如果没找到匹配的，使用第一个子模型作为后备
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targetModelId = subModels[0].model.id;
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}
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targetModelId = matchedSubModel.model.id;
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} else {
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console.warn(`[Chat API] 未找到可用子模型，继续使用主模型`);
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}
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}
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}
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@ -3724,6 +3798,8 @@ export async function POST(request: Request) {
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videoParams: effectiveVideoParams,
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});
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const videoMode = (effectiveVideoParams?.mode || "text-to-video") as VideoModeType;
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// 🆕 重新执行子模型选择逻辑，确定要使用的模型 UUID
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let videoModelId = finalModelId; // 默认使用选择的模型 ID
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@ -3741,37 +3817,16 @@ export async function POST(request: Request) {
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console.log(`[Chat API] Video: Found ${videoSubModels.length} sub-models for master model`);
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if (videoSubModels.length > 0) {
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const videoMode = effectiveVideoParams?.mode || "text-to-video";
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const modeToModelMap: Record<string, string> = {
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"text-to-video": "lite-t2v",
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"first-last-frame": "pro",
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"first-frame": "pro-fast",
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"reference-images": "lite-i2v",
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};
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const targetKey = modeToModelMap[videoMode];
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const compatibleModels = videoSubModels.filter(({ model }) => {
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const supportedModes = ((model.capabilities as any)?.supportedModes ?? []) as string[];
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return supportedModes.length === 0 || supportedModes.includes(videoMode);
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});
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const matchedModel = compatibleModels.find(({ model }) =>
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model.modelId.toLowerCase().includes(targetKey)
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);
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const matchedModel = selectBestVideoSubModelForMode(videoSubModels as any, videoMode);
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if (matchedModel) {
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videoModelId = matchedModel.model.id;
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console.log(
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`[Chat API] Video: Selected sub-model ${matchedModel.model.displayName} for mode ${videoMode}`
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);
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} else if (compatibleModels.length > 0) {
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videoModelId = compatibleModels[0].model.id;
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console.log(
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`[Chat API] Video: Fallback to compatible sub-model ${compatibleModels[0].model.displayName} for mode ${videoMode}`
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`[Chat API] Video: Selected sub-model ${matchedModel.model.displayName} (${matchedModel.model.modelId}) for mode ${videoMode}`
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);
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} else {
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videoModelId = videoSubModels[0].model.id;
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console.log(
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`[Chat API] Video: No compatible sub-model found for mode ${videoMode}, using ${videoSubModels[0].model.displayName}`
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`[Chat API] Video: No compatible sub-model found for mode ${videoMode}, keep current model`
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);
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}
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}
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@ -3783,14 +3838,50 @@ export async function POST(request: Request) {
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throw new Error("视频模型配置未找到");
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}
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// 若用户手动选了不兼容模式的子模型，自动回退到同父模型兼容子模型
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const selectedSupportsMode = getSupportedVideoModesForModel(aiModelData as any).includes(videoMode);
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if (!selectedSupportsMode) {
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let fallbackModel: { model: any } | null = null;
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if (aiModelData.parentModelId) {
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const siblingSubModels = await getSubModelsByParentModelId(aiModelData.parentModelId);
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fallbackModel = selectBestVideoSubModelForMode(siblingSubModels as any, videoMode);
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} else if (selectedModelProvider?.type === "volcano-video") {
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const enabledModels = await getEnabledAiModelsWithProvider();
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const sameProviderModels = enabledModels
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.filter(
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({ model, provider }) =>
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provider.type === "volcano-video" &&
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model.isEnabled &&
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model.id !== aiModelData.id,
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)
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.map(({ model }) => ({ model }));
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fallbackModel = selectBestVideoSubModelForMode(sameProviderModels as any, videoMode);
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}
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if (fallbackModel) {
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console.warn(
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`[Chat API] Video: Model ${aiModelData.modelId} does not support ${videoMode}, fallback to ${fallbackModel.model.modelId}`
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);
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videoModelId = fallbackModel.model.id;
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}
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}
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const finalVideoModelData = videoModelId === aiModelData.id
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? aiModelData
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: await getAiModelById({ id: videoModelId });
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if (!finalVideoModelData) {
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throw new Error("视频模型配置未找到");
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}
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// 如果是子模型，获取父模型的 Provider 配置
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let providerModelData = aiModelData;
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if (aiModelData.isSubModel && aiModelData.parentModelId) {
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let providerModelData = finalVideoModelData;
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if (finalVideoModelData.isSubModel && finalVideoModelData.parentModelId) {
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console.log(
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"[Chat API] This is a sub-model, getting parent model config:",
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aiModelData.parentModelId
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finalVideoModelData.parentModelId
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);
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const parentModel = await getAiModelById({ id: aiModelData.parentModelId });
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const parentModel = await getAiModelById({ id: finalVideoModelData.parentModelId });
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if (parentModel) {
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providerModelData = parentModel;
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}
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@ -3802,13 +3893,13 @@ export async function POST(request: Request) {
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throw new Error("Provider 配置未找到");
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}
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const actualVideoModelId = aiModelData.modelId;
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const actualVideoModelId = finalVideoModelData.modelId;
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// 构建视频生成选项
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const videoOptions: any = {
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model: actualVideoModelId,
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prompt: prompt || "生成视频",
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mode: effectiveVideoParams?.mode || "text-to-video",
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mode: videoMode,
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resolution: effectiveVideoParams?.resolution || "720p",
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ratio: effectiveVideoParams?.ratio || "16:9",
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duration: effectiveVideoParams?.duration || 5,
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@ -11,33 +11,138 @@ import type {
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} from "@/types/ai";
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import { uploadFile } from "@/lib/storage/service";
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const RETRYABLE_HTTP_STATUS = new Set([408, 425, 429, 500, 502, 503, 504]);
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const RETRYABLE_FETCH_CODES = new Set([
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"UND_ERR_HEADERS_TIMEOUT",
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"UND_ERR_CONNECT_TIMEOUT",
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"UND_ERR_BODY_TIMEOUT",
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"UND_ERR_SOCKET",
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"ETIMEDOUT",
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"ECONNRESET",
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"ECONNREFUSED",
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"EAI_AGAIN",
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"ENOTFOUND",
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]);
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function sleep(ms: number) {
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return new Promise((resolve) => setTimeout(resolve, ms));
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}
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function isRetryableFetchError(error: any): boolean {
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const code = error?.code || error?.cause?.code;
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if (typeof code === "string" && RETRYABLE_FETCH_CODES.has(code)) {
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return true;
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}
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if (error?.name === "AbortError") {
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return true;
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}
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const message = String(error?.message || "").toLowerCase();
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return (
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message.includes("timeout") ||
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message.includes("timed out") ||
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message.includes("fetch failed")
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);
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}
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async function fetchWithRetry(
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url: string,
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init: RequestInit,
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options: {
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label: string;
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timeoutMs: number;
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retries: number;
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retryDelayMs?: number;
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}
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): Promise<Response> {
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const { label, timeoutMs, retries, retryDelayMs = 1500 } = options;
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let attempt = 0;
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while (attempt <= retries) {
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const controller = new AbortController();
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const timer = setTimeout(() => controller.abort(), timeoutMs);
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try {
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const response = await fetch(url, {
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...init,
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signal: controller.signal,
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});
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clearTimeout(timer);
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if (
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RETRYABLE_HTTP_STATUS.has(response.status) &&
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attempt < retries
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) {
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const bodyText = await response.text().catch(() => "");
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console.warn(
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`[Volcano Video] ${label} transient status ${response.status}, retry ${attempt + 1}/${retries}`,
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bodyText?.slice(0, 300)
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);
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await sleep(retryDelayMs * (attempt + 1));
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attempt += 1;
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continue;
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}
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return response;
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} catch (error: any) {
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clearTimeout(timer);
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if (isRetryableFetchError(error) && attempt < retries) {
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console.warn(
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`[Volcano Video] ${label} request failed, retry ${attempt + 1}/${retries}`,
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error?.cause?.code || error?.code || error?.message
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);
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await sleep(retryDelayMs * (attempt + 1));
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attempt += 1;
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continue;
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}
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throw error;
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}
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}
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throw new Error(`[Volcano Video] ${label} request failed after retries`);
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}
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/**
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* 将图片 URL 转换为 Base64（火山引擎 API 要求）
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* 规范化图片地址为可公开访问 URL（优先直传 URL，避免大体积 base64）
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*/
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async function convertImageUrlToBase64(imageUrl: string): Promise<{
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permanentUrl: string;
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base64: string;
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}> {
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async function normalizeImageUrlForVolcano(imageUrl: string): Promise<string> {
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try {
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// 如果已经是 Base64，直接返回
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// Base64 输入：上传到 S3，返回永久 URL
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if (imageUrl.startsWith("data:image/")) {
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const matches = imageUrl.match(/^data:image\/(\w+);base64,(.+)$/);
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const matches = imageUrl.match(/^data:(image\/[a-zA-Z0-9.+-]+);base64,(.+)$/);
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if (!matches) {
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throw new Error("Invalid base64 image format");
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}
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// 上传到 S3 获取永久 URL
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const mimeType = matches[1];
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const ext = mimeType.split("/")[1]?.toLowerCase() || "jpg";
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const buffer = Buffer.from(matches[2], "base64");
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const filename = `volcano-video-input-${Date.now()}.${matches[1]}`;
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const filename = `volcano-video-input-${Date.now()}.${ext}`;
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const { url: permanentUrl } = await uploadFile(filename, buffer as any);
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return { permanentUrl, base64: matches[2] };
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return permanentUrl;
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}
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// 下载图片
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// 已经是公网 URL，直接使用
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if (imageUrl.startsWith("http://") || imageUrl.startsWith("https://")) {
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return imageUrl;
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}
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// 其他格式：下载后上传到 S3，返回永久 URL
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console.log(`[Volcano Video] Downloading image: ${imageUrl}`);
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const response = await fetch(imageUrl);
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const response = await fetchWithRetry(
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imageUrl,
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{ method: "GET" },
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{
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label: "download-image",
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timeoutMs: 30000,
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retries: 2,
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}
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);
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if (!response.ok) {
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throw new Error(`Failed to download image: ${response.statusText}`);
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}
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@ -51,10 +156,7 @@ async function convertImageUrlToBase64(imageUrl: string): Promise<{
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console.log(`[Volcano Video] Image uploaded to S3: ${permanentUrl}`);
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// 转换为 Base64
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const base64 = bufferNode.toString("base64");
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return { permanentUrl, base64 };
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return permanentUrl;
|
||||
} catch (error) {
|
||||
console.error("[Volcano Video] Image processing failed:", error);
|
||||
throw new Error("图片处理失败，请重试");
|
||||
@ -175,15 +277,13 @@ async function createVideoTask(
|
||||
// 2. 处理图片输入（根据模式）
|
||||
if (options.mode === "first-frame" && options.firstFrameImage) {
|
||||
// 首帧模式
|
||||
const { permanentUrl, base64 } = await convertImageUrlToBase64(
|
||||
options.firstFrameImage
|
||||
);
|
||||
inputImageUrls.firstFrame = permanentUrl;
|
||||
const firstFrameUrl = await normalizeImageUrlForVolcano(options.firstFrameImage);
|
||||
inputImageUrls.firstFrame = firstFrameUrl;
|
||||
|
||||
content.push({
|
||||
type: "image_url",
|
||||
image_url: {
|
||||
url: `data:image/jpeg;base64,${base64}`,
|
||||
url: firstFrameUrl,
|
||||
},
|
||||
role: "first_frame",
|
||||
});
|
||||
@ -193,24 +293,24 @@ async function createVideoTask(
|
||||
options.lastFrameImage
|
||||
) {
|
||||
// 首尾帧模式
|
||||
const firstFrame = await convertImageUrlToBase64(options.firstFrameImage);
|
||||
const lastFrame = await convertImageUrlToBase64(options.lastFrameImage);
|
||||
const firstFrameUrl = await normalizeImageUrlForVolcano(options.firstFrameImage);
|
||||
const lastFrameUrl = await normalizeImageUrlForVolcano(options.lastFrameImage);
|
||||
|
||||
inputImageUrls.firstFrame = firstFrame.permanentUrl;
|
||||
inputImageUrls.lastFrame = lastFrame.permanentUrl;
|
||||
inputImageUrls.firstFrame = firstFrameUrl;
|
||||
inputImageUrls.lastFrame = lastFrameUrl;
|
||||
|
||||
content.push(
|
||||
{
|
||||
type: "image_url",
|
||||
image_url: {
|
||||
url: `data:image/jpeg;base64,${firstFrame.base64}`,
|
||||
url: firstFrameUrl,
|
||||
},
|
||||
role: "first_frame",
|
||||
},
|
||||
{
|
||||
type: "image_url",
|
||||
image_url: {
|
||||
url: `data:image/jpeg;base64,${lastFrame.base64}`,
|
||||
url: lastFrameUrl,
|
||||
},
|
||||
role: "last_frame",
|
||||
}
|
||||
@ -220,13 +320,13 @@ async function createVideoTask(
|
||||
inputImageUrls.references = [];
|
||||
|
||||
for (const imageUrl of options.referenceImages) {
|
||||
const { permanentUrl, base64 } = await convertImageUrlToBase64(imageUrl);
|
||||
inputImageUrls.references.push(permanentUrl);
|
||||
const normalizedUrl = await normalizeImageUrlForVolcano(imageUrl);
|
||||
inputImageUrls.references.push(normalizedUrl);
|
||||
|
||||
content.push({
|
||||
type: "image_url",
|
||||
image_url: {
|
||||
url: `data:image/jpeg;base64,${base64}`,
|
||||
url: normalizedUrl,
|
||||
},
|
||||
role: "reference_image",
|
||||
});
|
||||
@ -238,6 +338,15 @@ async function createVideoTask(
|
||||
model: options.model,
|
||||
content: content, // 直接传content数组，不使用messages包装
|
||||
};
|
||||
|
||||
// 显式指定 task_type，避免服务端推断错误
|
||||
const taskTypeMap: Record<string, string> = {
|
||||
"text-to-video": "t2v",
|
||||
"first-frame": "i2v",
|
||||
"first-last-frame": "flf2v",
|
||||
"reference-images": "i2v",
|
||||
};
|
||||
requestBody.task_type = taskTypeMap[options.mode] || "t2v";
|
||||
|
||||
// 可选参数：返回尾帧（用于连续生成视频）
|
||||
if (options.returnLastFrame) {
|
||||
@ -257,14 +366,22 @@ async function createVideoTask(
|
||||
console.log("[Volcano Video] 🔍 Request method: POST");
|
||||
console.log("[Volcano Video] 🔍 Request body:", JSON.stringify(requestBody, null, 2));
|
||||
|
||||
const response = await fetch(url, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
const response = await fetchWithRetry(
|
||||
url,
|
||||
{
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
},
|
||||
body: JSON.stringify(requestBody),
|
||||
},
|
||||
body: JSON.stringify(requestBody),
|
||||
});
|
||||
{
|
||||
label: "create-task",
|
||||
timeoutMs: 90000,
|
||||
retries: 2,
|
||||
}
|
||||
);
|
||||
|
||||
console.log("[Volcano Video] 🔍 Response status:", response.status);
|
||||
console.log("[Volcano Video] 🔍 Response headers:", JSON.stringify(Object.fromEntries(response.headers.entries())));
|
||||
@ -302,12 +419,20 @@ async function fetchTaskStatus(
|
||||
): Promise<any> {
|
||||
const url = `${baseURL}/contents/generations/tasks/${taskId}`;
|
||||
|
||||
const response = await fetch(url, {
|
||||
method: "GET",
|
||||
headers: {
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
const response = await fetchWithRetry(
|
||||
url,
|
||||
{
|
||||
method: "GET",
|
||||
headers: {
|
||||
Authorization: `Bearer ${apiKey}`,
|
||||
},
|
||||
},
|
||||
});
|
||||
{
|
||||
label: `task-status:${taskId}`,
|
||||
timeoutMs: 45000,
|
||||
retries: 2,
|
||||
}
|
||||
);
|
||||
|
||||
if (!response.ok) {
|
||||
const errorText = await response.text();
|
||||
@ -330,7 +455,20 @@ async function pollTaskStatus(
|
||||
console.log("[Volcano Video] Polling task:", taskId);
|
||||
|
||||
for (let i = 0; i < maxRetries; i++) {
|
||||
const status = await fetchTaskStatus(baseURL, apiKey, taskId);
|
||||
let status: any;
|
||||
try {
|
||||
status = await fetchTaskStatus(baseURL, apiKey, taskId);
|
||||
} catch (error: any) {
|
||||
if (isRetryableFetchError(error)) {
|
||||
console.warn(
|
||||
`[Volcano Video] Poll ${i + 1}/${maxRetries} transient error, continue waiting:`,
|
||||
error?.cause?.code || error?.code || error?.message
|
||||
);
|
||||
await sleep(pollInterval);
|
||||
continue;
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
|
||||
console.log(
|
||||
`[Volcano Video] Poll ${i + 1}/${maxRetries}, status: ${status.status}`
|
||||
@ -371,7 +509,7 @@ async function pollTaskStatus(
|
||||
}
|
||||
|
||||
// 继续等待
|
||||
await new Promise((resolve) => setTimeout(resolve, pollInterval));
|
||||
await sleep(pollInterval);
|
||||
}
|
||||
|
||||
throw new Error("视频生成超时，请稍后重试");
|
||||
@ -454,7 +592,20 @@ export async function* doGenerateStream(
|
||||
const pollInterval = 10000;
|
||||
|
||||
for (let i = 0; i < maxRetries; i++) {
|
||||
const status = await fetchTaskStatus(baseURL, apiKey, taskId);
|
||||
let status: any;
|
||||
try {
|
||||
status = await fetchTaskStatus(baseURL, apiKey, taskId);
|
||||
} catch (error: any) {
|
||||
if (isRetryableFetchError(error)) {
|
||||
console.warn(
|
||||
`[Volcano Video] Stream poll ${i + 1}/${maxRetries} transient error, continue waiting:`,
|
||||
error?.cause?.code || error?.code || error?.message
|
||||
);
|
||||
await sleep(pollInterval);
|
||||
continue;
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
|
||||
if (status.status === "succeeded") {
|
||||
// 火山引擎API返回格式：status.content.video_url
|
||||
@ -504,7 +655,7 @@ export async function* doGenerateStream(
|
||||
}
|
||||
|
||||
// 静默等待，不输出进度文字
|
||||
await new Promise((resolve) => setTimeout(resolve, pollInterval));
|
||||
await sleep(pollInterval);
|
||||
}
|
||||
|
||||
throw new Error("视频生成超时，请稍后重试");
|
||||
@ -514,4 +665,3 @@ export async function* doGenerateStream(
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@ -16,6 +16,27 @@ import type {
|
||||
VideoGenerationOptions,
|
||||
} from "@/types/ai";
|
||||
|
||||
function inferSupportedModesFromModelId(modelId: string): VideoGenerationMode[] {
|
||||
const normalized = modelId.toLowerCase();
|
||||
|
||||
if (normalized.includes("lite-t2v")) return ["text-to-video"];
|
||||
if (normalized.includes("lite-i2v")) return ["first-frame", "first-last-frame", "reference-images"];
|
||||
if (normalized.includes("pro-fast")) return ["text-to-video", "first-frame"];
|
||||
if (normalized.includes("-pro-") || normalized.endsWith("-pro")) {
|
||||
return ["text-to-video", "first-frame", "first-last-frame"];
|
||||
}
|
||||
|
||||
return ["text-to-video", "first-frame", "first-last-frame", "reference-images"];
|
||||
}
|
||||
|
||||
function getSupportedModes(caps: Partial<VideoModelCapabilities> | undefined, modelId: string): VideoGenerationMode[] {
|
||||
const modes = (caps?.supportedModes || []) as VideoGenerationMode[];
|
||||
if (Array.isArray(modes) && modes.length > 0) {
|
||||
return modes;
|
||||
}
|
||||
return inferSupportedModesFromModelId(modelId);
|
||||
}
|
||||
|
||||
/**
|
||||
* 🆕 智能选择最佳子模型
|
||||
* 根据用户选择的模式和参数，从子模型列表中选择最合适的模型
|
||||
@ -37,11 +58,11 @@ async function selectBestSubModel(
|
||||
// 筛选支持指定模式的子模型
|
||||
const compatibleModels = subModels.filter((m) => {
|
||||
const caps = m.model.capabilities as VideoModelCapabilities;
|
||||
const supportsMode = caps.supportedModes?.includes(mode);
|
||||
const supportsMode = getSupportedModes(caps, m.model.modelId).includes(mode);
|
||||
|
||||
// 检查分辨率支持（如果用户指定了分辨率）
|
||||
const supportsResolution = !params.resolution ||
|
||||
caps.supportedResolutions?.includes(params.resolution);
|
||||
const supportedResolutions = caps.supportedResolutions || ["480p", "720p", "1080p"];
|
||||
const supportsResolution = !params.resolution || supportedResolutions.includes(params.resolution);
|
||||
|
||||
return supportsMode && supportsResolution;
|
||||
});
|
||||
@ -104,7 +125,7 @@ async function getCompatibleModel(
|
||||
|
||||
const compatibleModels = volcanoVideoModels.filter((m) => {
|
||||
const caps = m.model.capabilities as VideoModelCapabilities;
|
||||
return caps.supportedModes?.includes(mode);
|
||||
return getSupportedModes(caps, m.model.modelId).includes(mode);
|
||||
});
|
||||
|
||||
if (compatibleModels.length === 0) {
|
||||
@ -357,4 +378,3 @@ export function generateVideo({ dataStream }: { dataStream: any }) {
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user