cneicy
ceddfd3d6b
Sync production source including routing, billing, Astra detection and public uptime. Update custom build instructions and license packaging.
997 lines
50 KiB
JavaScript
997 lines
50 KiB
JavaScript
// Protocol capabilities, not prices. Keep defaults and validation shared by
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// native requests, compatibility protocols, and submission billing facts.
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const WAN_MODELS = {
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"wan3.0-video": { kind: "all", resolutions: ["480P", "720P", "1080P"], defaultResolution: "1080P", maxDuration: 30 },
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"wan3.0-video-prime": { kind: "all", resolutions: ["480P", "720P", "1080P"], defaultResolution: "1080P", maxDuration: 30 },
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"wan2.7-t2v": { kind: "t2v", resolutions: ["720P", "1080P"], defaultResolution: "1080P", maxDuration: 15 },
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"wan2.7-i2v": { kind: "media", resolutions: ["720P", "1080P"], defaultResolution: "1080P", maxDuration: 15 },
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"wan2.6-t2v": { kind: "size", resolutions: ["720P", "1080P"], defaultResolution: "1080P", maxDuration: 15 },
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"wan2.6-t2v-us": { kind: "size", resolutions: ["720P", "1080P"], defaultResolution: "1080P", durations: [5, 10, 15] },
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"wan2.6-i2v": { kind: "image", resolutions: ["720P", "1080P"], defaultResolution: "1080P", maxDuration: 15 },
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"wan2.6-i2v-flash": { kind: "image", resolutions: ["720P", "1080P"], defaultResolution: "1080P", maxDuration: 15 },
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"wan2.6-i2v-us": { kind: "image", resolutions: ["720P", "1080P"], defaultResolution: "1080P", durations: [5, 10, 15] },
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"wan2.5-t2v-preview": { kind: "size", resolutions: ["480P", "720P", "1080P"], defaultResolution: "1080P", durations: [5, 10] },
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"wan2.5-i2v-preview": { kind: "image", resolutions: ["480P", "720P", "1080P"], defaultResolution: "1080P", durations: [5, 10] },
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"wan2.2-t2v-plus": { kind: "size", resolutions: ["480P", "1080P"], defaultResolution: "1080P", durations: [5] },
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"wan2.2-i2v-flash": { kind: "image", resolutions: ["480P", "720P", "1080P"], defaultResolution: "720P", durations: [5] },
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"wan2.2-i2v-plus": { kind: "image", resolutions: ["480P", "1080P"], defaultResolution: "1080P", durations: [5] },
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"wan2.2-kf2v-flash": { kind: "frames", resolutions: ["480P", "720P", "1080P"], defaultResolution: "720P", durations: [5] },
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"wan2.2-s2v": { kind: "speech", resolutions: ["480P", "720P"], defaultResolution: "480P" },
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"wanx2.1-t2v-plus": { kind: "size", resolutions: ["720P"], defaultResolution: "720P", durations: [5] },
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"wanx2.1-t2v-turbo": { kind: "size", resolutions: ["480P", "720P"], defaultResolution: "720P", durations: [5] },
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"wanx2.1-i2v-plus": { kind: "image", resolutions: ["720P"], defaultResolution: "720P", durations: [5] },
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"wanx2.1-i2v-turbo": { kind: "image", resolutions: ["480P", "720P"], defaultResolution: "720P", durations: [3, 4, 5] },
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};
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// HTTP contracts (SDK synchronous calls can also wrap polling):
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// https://help.aliyun.com/zh/model-studio/text-to-image-v2-api-reference
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// https://help.aliyun.com/zh/model-studio/wan-image-generation-api-reference
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// https://help.aliyun.com/zh/model-studio/wan-image-generation-and-editing-api-reference
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const WAN_IMAGE_MODELS = {
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"wan2.7-image-pro": "image27",
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"wan2.7-image": "image27",
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"wan2.6-image": "image26",
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"wan2.6-t2i": "t2i",
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"wan2.5-t2i-preview": "legacy",
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"wan2.2-t2i-flash": "legacy",
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"wan2.2-t2i-plus": "legacy",
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"wanx2.1-t2i-turbo": "legacy",
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"wanx2.1-t2i-plus": "legacy",
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"wanx2.0-t2i-turbo": "legacy",
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};
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const WAN_IMAGE_USAGE_SCHEMA = {
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image_count: {
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type: "number",
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unit: "count",
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unitLabel: { en: "image", zh: "张", "zh-TW": "張", fr: "image", ja: "枚", ru: "изображение", vi: "ảnh" },
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description: { en: "Image generation unit price", zh: "图片生成单价" },
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},
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};
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const WAN_VIDEO_USAGE_SCHEMA = {
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// Billable seconds: output duration, or input + output for Wan3.
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seconds: {
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type: "number",
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unit: "second",
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description: { en: "Video generation unit price", zh: "视频生成单价" },
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},
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// Requested output video resolution.
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resolution: {
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enum: ["480P", "720P", "1080P"],
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enumLabels: { "480P": { en: "480P", zh: "480P" }, "720P": { en: "720P", zh: "720P" }, "1080P": { en: "1080P", zh: "1080P" } },
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description: { en: "Output video resolution", zh: "输出视频分辨率" },
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},
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};
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export const meta = {
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apiVersion: 1,
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key: "alibaba",
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name: "Alibaba Bailian",
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icon: "Bailian.Color",
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description: {
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en: "Alibaba Cloud Bailian Wanxiang image and video generation",
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zh: "阿里云百炼万相图片与视频生成",
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},
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version: "1.3.0",
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author: { name: "QuantumNous" },
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channelTypes: [17],
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// Literal metadata also supports the dashboard's static script preview.
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models: [
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"wan3.0-video",
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"wan3.0-video-prime",
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"wan2.7-t2v",
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"wan2.7-t2v-2026-04-25",
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"wan2.7-t2v-2026-06-12",
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"wan2.7-i2v",
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"wan2.7-i2v-2026-04-25",
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"wan2.6-t2v",
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"wan2.6-t2v-us",
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"wan2.6-i2v",
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"wan2.6-i2v-flash",
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"wan2.6-i2v-us",
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"wan2.5-t2v-preview",
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"wan2.5-i2v-preview",
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"wan2.2-t2v-plus",
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"wan2.2-i2v-flash",
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"wan2.2-i2v-plus",
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"wan2.2-kf2v-flash",
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"wan2.2-s2v",
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"wanx2.1-t2v-plus",
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"wanx2.1-t2v-turbo",
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"wanx2.1-i2v-plus",
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"wanx2.1-i2v-turbo",
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"wan2.7-image-pro",
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"wan2.7-image",
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"wan2.6-image",
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"wan2.6-t2i",
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"wan2.5-t2i-preview",
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"wan2.2-t2i-flash",
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"wan2.2-t2i-plus",
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"wanx2.1-t2i-turbo",
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"wanx2.1-t2i-plus",
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"wanx2.0-t2i-turbo",
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],
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fetchMode: "per_task",
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submitResponseTypes: ["json", "sse"],
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requiredCapabilities: ["json-clone@1", "submit-sse-delta@1"],
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usageSchema: { ...WAN_IMAGE_USAGE_SCHEMA, ...WAN_VIDEO_USAGE_SCHEMA },
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usageProfiles: [
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{
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models: Object.keys(WAN_IMAGE_MODELS),
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schema: WAN_IMAGE_USAGE_SCHEMA,
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},
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{
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models: Object.keys(WAN_MODELS).concat(["wan2.7-t2v-2026-04-25", "wan2.7-t2v-2026-06-12", "wan2.7-i2v-2026-04-25"]),
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schema: WAN_VIDEO_USAGE_SCHEMA,
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},
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],
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routes: [
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{ method: "POST", path: "/ali/api/v1/services/aigc/multimodal-generation/generation", type: "submit", models: ["wan2.7-image-pro", "wan2.7-image", "wan2.6-image", "wan2.6-t2i"], decode: "createImageTask", render: "imageCreated" },
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{ method: "POST", path: "/ali/api/v1/services/aigc/image-generation/generation", type: "submit", models: ["wan2.7-image-pro", "wan2.7-image", "wan2.6-image", "wan2.6-t2i"], decode: "createImageTask", render: "taskCreated" },
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{ method: "POST", path: "/ali/api/v1/services/aigc/text2image/image-synthesis", type: "submit", models: ["wan2.5-t2i-preview", "wan2.2-t2i-flash", "wan2.2-t2i-plus", "wanx2.1-t2i-turbo", "wanx2.1-t2i-plus", "wanx2.0-t2i-turbo"], decode: "createImageTask", render: "taskCreated" },
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{ method: "POST", path: "/ali/api/v1/services/aigc/video-generation/video-synthesis", type: "submit", decode: "createVideoTask", render: "taskCreated" },
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{ method: "POST", path: "/ali/api/v1/services/aigc/image2video/video-synthesis", type: "submit", decode: "createVideoTask", render: "taskCreated" },
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{ method: "GET", path: "/ali/api/v1/tasks/:task_id", type: "query", render: "taskStatus" },
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],
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protocols: [
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{ name: "openai_responses", supports: ["stream", "sync", "background"] },
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{ name: "openai_video", models: Object.keys(WAN_MODELS).concat(["wan2.7-t2v-2026-04-25", "wan2.7-t2v-2026-06-12", "wan2.7-i2v-2026-04-25"]) },
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],
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};
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function trimmed(value) {
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return String(value || "").trim();
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}
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function firstImage(req) {
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if (trimmed(req.image)) return trimmed(req.image);
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for (const image of req.images || []) if (trimmed(image)) return trimmed(image);
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return trimmed(req.input_reference);
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}
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function secondImage(req) {
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let count = 0;
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for (const image of req.images || []) {
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if (!trimmed(image)) continue;
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count++;
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if (count === 2) return trimmed(image);
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}
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return "";
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}
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const LEGACY_SIZES = {
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"480P": { "16:9": "832*480", "9:16": "480*832", "1:1": "624*624" },
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"720P": { "16:9": "1280*720", "9:16": "720*1280", "1:1": "960*960", "4:3": "1088*832", "3:4": "832*1088" },
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"1080P": { "16:9": "1920*1080", "9:16": "1080*1920", "1:1": "1440*1440", "4:3": "1632*1248", "3:4": "1248*1632" },
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};
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// Wan2.7 changed the pixel sizes for 4:3 and 3:4. Legacy sizes remain valid
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// compatibility inputs, but never replace the target model's native sizes.
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const MODERN_SIZES = {
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"720P": { "16:9": "1280*720", "9:16": "720*1280", "1:1": "960*960", "4:3": "1104*832", "3:4": "832*1104" },
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"1080P": { "16:9": "1920*1080", "9:16": "1080*1920", "1:1": "1440*1440", "4:3": "1648*1248", "3:4": "1248*1648" },
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};
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function modelKey(model) {
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return String(model || "").replace(/-\d{4}-\d{2}-\d{2}$/, "").replace(/^wan2\.1-/, "wanx2.1-");
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}
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function modelProfile(model) {
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const key = modelKey(model);
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if (!Object.prototype.hasOwnProperty.call(WAN_MODELS, key)) throw new Error("unsupported Wan model: " + model);
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return WAN_MODELS[key];
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}
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function imageModel(ctx) {
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const key = modelKey(ctx.upstreamModel || ctx.model || (ctx.requestBody || {}).model);
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return Object.prototype.hasOwnProperty.call(WAN_IMAGE_MODELS, key) ? WAN_IMAGE_MODELS[key] : undefined;
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}
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function convertImage(ctx) {
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const req = ctx.requestBody || {};
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const model = ctx.upstreamModel || req.model;
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const profile = imageModel(ctx);
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if (!profile) throw new Error("unsupported Wan image model: " + model);
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const metadata = objectValue(req.metadata, "metadata");
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if (metadata.model !== undefined && metadata.model !== model) throw new Error("can't change model with metadata");
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const mode = metadata.upstream_mode ?? "async";
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if (mode !== "sync" && mode !== "async") throw new Error("upstream_mode must be sync or async");
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if (profile === "legacy" && mode === "sync") throw new Error("this image model only supports asynchronous HTTP calls");
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const parameters = {};
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for (const key of ["n", "size", "negative_prompt", "prompt_extend", "watermark", "seed", "enable_interleave", "max_images", "enable_sequential", "thinking_mode", "bbox_list", "color_palette"]) {
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if (req[key] !== undefined) parameters[key] = req[key];
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}
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Object.assign(parameters, objectValue(metadata.parameters, "metadata.parameters"));
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for (const key of ["prompt_extend", "watermark", "enable_interleave", "enable_sequential", "thinking_mode", "stream"]) {
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if (parameters[key] !== undefined && typeof parameters[key] !== "boolean") throw new Error(key + " must be a boolean");
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}
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if (parameters.stream === true && (mode !== "sync" || profile !== "image26" || !parameters.enable_interleave))
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throw new Error("upstream streaming requires synchronous wan2.6-image interleaved output");
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if (parameters.enable_interleave && profile !== "image26") throw new Error("enable_interleave is only supported by wan2.6-image");
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if (parameters.enable_sequential && profile !== "image27") throw new Error("enable_sequential is only supported by wan2.7-image models");
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if (parameters.enable_interleave && mode === "sync") parameters.stream = true;
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const maxN = parameters.enable_interleave ? 1 : parameters.enable_sequential ? 12 : 4;
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parameters.n = parameters.n ?? (mode === "sync" || parameters.enable_interleave ? 1 : profile === "image27" ? (parameters.enable_sequential ? 12 : 1) : 4);
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// Provider limits are stricter than the host's dto.MaxImageN count ceiling.
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if (!Number.isInteger(parameters.n) || parameters.n < 1 || parameters.n > maxN) throw new Error("n must be an integer between 1 and " + maxN);
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if (parameters.max_images !== undefined && (!Number.isInteger(parameters.max_images) || parameters.max_images < 1 || parameters.max_images > 5))
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throw new Error("max_images must be an integer between 1 and 5");
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if (parameters.enable_interleave) parameters.max_images = parameters.max_images ?? 5;
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if (parameters.seed !== undefined && (!Number.isInteger(parameters.seed) || parameters.seed < 0 || parameters.seed > 2147483647))
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throw new Error("seed must be an integer between 0 and 2147483647");
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const input = Object.assign({}, objectValue(metadata.input, "metadata.input"));
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if (profile === "legacy") {
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input.prompt = input.prompt ?? req.prompt;
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if (typeof input.prompt !== "string" || !input.prompt.trim()) throw new Error("prompt is required");
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if (input.messages !== undefined || firstImage(req)) throw new Error("this model only supports text-to-image input");
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if (parameters.negative_prompt !== undefined) {
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input.negative_prompt = parameters.negative_prompt;
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delete parameters.negative_prompt;
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}
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} else if (input.messages === undefined) {
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const content = [];
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if (req.images !== undefined && !Array.isArray(req.images)) throw new Error("images must be an array");
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const images = req.images || (firstImage(req) ? [firstImage(req)] : []);
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for (const image of images) content.push({ image: image });
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content.push({ text: req.prompt });
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input.messages = [{ role: "user", content: content }];
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}
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let imageCount = 0;
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if (profile !== "legacy") {
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if (!Array.isArray(input.messages) || input.messages.length !== 1 || !input.messages[0] || input.messages[0].role !== "user" || !Array.isArray(input.messages[0].content))
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throw new Error("input.messages must contain one user message with a content array");
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let texts = 0;
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for (const part of input.messages[0].content) {
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if (!part || typeof part !== "object" || Array.isArray(part)) throw new Error("invalid image message content");
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if (part.text !== undefined) {
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if (typeof part.text !== "string" || !part.text.trim()) throw new Error("text must be a non-empty string");
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texts++;
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}
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if (part.image !== undefined) {
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if (typeof part.image !== "string" || !/^(https?:\/\/|data:image\/)/i.test(part.image)) throw new Error("image must be an HTTP URL or Base64 data URL");
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imageCount++;
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}
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}
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if (texts !== 1) throw new Error("input.messages must contain exactly one text prompt");
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const maxInput = profile === "image27" ? 9 : profile === "image26" ? (parameters.enable_interleave ? 1 : 4) : 0;
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if (imageCount > maxInput) throw new Error("too many input images for this model");
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if (profile === "image26" && !parameters.enable_interleave && imageCount === 0) throw new Error("wan2.6-image editing requires a reference image; use wan2.6-t2i for text-to-image");
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}
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if (parameters.size !== undefined) {
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if (typeof parameters.size !== "string") throw new Error("size must be a string");
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parameters.size = parameters.size.replace(/x/i, "*");
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const supports4K = modelKey(model) === "wan2.7-image-pro" && !imageCount && !parameters.enable_sequential;
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if (["1K", "2K", "4K"].includes(parameters.size)) {
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if ((profile !== "image26" && profile !== "image27") || parameters.enable_interleave) throw new Error("this model requires a width*height image size");
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if (parameters.size === "4K" && !supports4K) throw new Error("4K is only supported by wan2.7-image-pro text-to-image without sequential output");
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} else {
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const match = /^(\d+)\*(\d+)$/.exec(parameters.size);
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if (!match) throw new Error("size must be width*height or a supported resolution preset");
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const width = Number(match[1]), height = Number(match[2]);
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const legacySize = profile === "legacy" && modelKey(model) !== "wan2.5-t2i-preview";
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const maxPixels = profile === "image27" ? (supports4K ? 4096 * 4096 : 2048 * 2048)
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: profile === "image26" ? (parameters.enable_interleave ? 1280 * 1280 : 2048 * 2048) : 1440 * 1440;
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const ratio = profile === "image27" ? 8 : 4;
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if (!Number.isSafeInteger(width) || !Number.isSafeInteger(height) || width <= 0 || height <= 0
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|| (legacySize ? width < 512 || height < 512 || width > 1440 || height > 1440
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: width * height > maxPixels || width / height > ratio || height / width > ratio))
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throw new Error("size is outside the model's pixel and aspect-ratio limits");
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}
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}
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const service = profile === "legacy" ? "text2image/image-synthesis" : mode === "sync" ? "multimodal-generation/generation" : "image-generation/generation";
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return {
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body: { model: model, input: input, parameters: parameters },
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service: service,
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synchronous: mode === "sync",
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action: imageCount ? "image_to_image" : "text_to_image",
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};
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}
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function imageContent(body) {
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const output = (body && body.output) || {};
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const content = [];
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for (const result of Array.isArray(output.results) ? output.results : []) {
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if (result && typeof result.url === "string" && result.url) content.push({ image: result.url });
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}
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for (const choice of Array.isArray(output.choices) ? output.choices : []) {
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for (const part of (choice && choice.message && Array.isArray(choice.message.content)) ? choice.message.content : []) {
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if (part && typeof part.image === "string" && part.image) content.push({ image: part.image });
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else if (part && typeof part.text === "string") content.push({ text: part.text });
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}
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}
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return content;
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}
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function imageUsage(body) {
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const count = (body.usage || {}).image_count;
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const content = imageContent(body);
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const images = content.filter(function (part) { return part.image; });
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if (count !== undefined) {
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// Do not let fractional, negative or oversized upstream counts change billing.
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if (!Number.isInteger(count) || count < 0 || count > 12 || (images.length && count === 0)) throw new Error("invalid upstream image_count");
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return { image_count: count };
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}
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if (images.length > 12) throw new Error("too many output images");
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return content.length ? { image_count: images.length } : {};
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}
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function objectValue(value, name) {
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if (value === undefined || value === null) return {};
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if (typeof value !== "object" || Array.isArray(value)) throw new Error(name + " must be an object");
|
|
return value;
|
|
}
|
|
|
|
// The host rejects negative canonical duration/seconds facts before any hook
|
|
// runs, so wan3.0's "-1 = smart duration" sentinel travels as a boolean marker.
|
|
function normalizeRequest(value) {
|
|
const req = Object.assign({}, value);
|
|
const metadata = objectValue(req.metadata, "metadata");
|
|
const parameters = Object.assign({}, objectValue(metadata.parameters, "metadata.parameters"));
|
|
if (req.metadata !== undefined) {
|
|
req.metadata = Object.assign({}, metadata, { parameters: parameters });
|
|
objectValue(metadata.input, "metadata.input");
|
|
}
|
|
const duration = parameters.duration ?? req.duration ?? req.seconds ?? (req.auto_duration === true ? -1 : undefined);
|
|
for (const key of ["duration", "seconds"]) {
|
|
if (Number(req[key]) === -1) delete req[key];
|
|
}
|
|
if (Number(parameters.duration) === -1) delete parameters.duration;
|
|
if (Number(duration) === -1) {
|
|
req.auto_duration = true;
|
|
delete req.duration;
|
|
delete req.seconds;
|
|
} else delete req.auto_duration;
|
|
// Normalize enum facts for host validation against the model's usage schema.
|
|
if (req.resolution != null) req.resolution = normalizeResolution(req.resolution);
|
|
if (parameters.resolution != null) parameters.resolution = normalizeResolution(parameters.resolution);
|
|
return req;
|
|
}
|
|
|
|
function normalizeResolution(value) {
|
|
let resolution = trimmed(value).toUpperCase();
|
|
if (!resolution) return "";
|
|
if (!resolution.endsWith("P")) resolution += "P";
|
|
return resolution;
|
|
}
|
|
|
|
function videoSize(value) {
|
|
const size = trimmed(value).replace(/x/i, "*");
|
|
if (!size.includes("*")) return { resolution: normalizeResolution(size) };
|
|
for (const sizes of [LEGACY_SIZES, MODERN_SIZES]) {
|
|
for (const resolution of Object.keys(sizes)) {
|
|
for (const ratio of Object.keys(sizes[resolution])) {
|
|
if (sizes[resolution][ratio] === size) return { resolution: resolution, ratio: ratio };
|
|
}
|
|
}
|
|
}
|
|
throw new Error("invalid size: " + size);
|
|
}
|
|
|
|
function videoAction(req) {
|
|
const input = objectValue((req.metadata || {}).input, "metadata.input");
|
|
for (const source of [req, input]) {
|
|
if (firstImage(source) || trimmed(source.img_url) || trimmed(source.image_url) || trimmed(source.first_frame_url) || (Array.isArray(source.media) && source.media.length))
|
|
return "image_to_video";
|
|
}
|
|
return "text_to_video";
|
|
}
|
|
|
|
function convert(ctx) {
|
|
const req = ctx.requestBody;
|
|
const upstreamModel = ctx.upstreamModel || req.model;
|
|
const profile = modelProfile(upstreamModel);
|
|
const metadata = objectValue(req.metadata, "metadata");
|
|
if (metadata.model !== undefined && metadata.model !== upstreamModel) throw new Error("can't change model with metadata");
|
|
const input = {};
|
|
for (const key of ["prompt", "negative_prompt", "img_url", "image_url", "first_frame_url", "last_frame_url", "audio_url", "template", "media"]) {
|
|
if (req[key] !== undefined) input[key] = req[key];
|
|
}
|
|
const image = firstImage(req);
|
|
if (image && input.img_url === undefined) input.img_url = image;
|
|
Object.assign(input, objectValue(metadata.input, "metadata.input"));
|
|
const nativeParameters = objectValue(metadata.parameters, "metadata.parameters");
|
|
const parameters = profile.kind === "speech" ? {} : { prompt_extend: true };
|
|
for (const key of ["resolution", "ratio", "prompt_extend", "watermark", "audio", "seed", "shot_type"]) {
|
|
if (req[key] !== undefined) parameters[key] = req[key];
|
|
}
|
|
Object.assign(parameters, nativeParameters);
|
|
for (const key of ["prompt_extend", "watermark", "audio"]) {
|
|
if (parameters[key] != null && typeof parameters[key] !== "boolean") throw new Error(key + " must be a boolean");
|
|
}
|
|
if (parameters.seed != null && (!Number.isInteger(parameters.seed) || parameters.seed < (profile.kind === "all" ? -1 : 0) || parameters.seed > 2147483647))
|
|
throw new Error("seed must be an integer between " + (profile.kind === "all" ? -1 : 0) + " and 2147483647");
|
|
|
|
const sizeValue = nativeParameters.size ?? req.size;
|
|
const size = sizeValue == null || sizeValue === "" ? {} : videoSize(sizeValue);
|
|
let resolution = normalizeResolution(parameters.resolution ?? size.resolution ?? profile.defaultResolution);
|
|
let ratio = parameters.ratio ?? size.ratio ?? (profile.kind === "all" ? "adaptive" : "16:9");
|
|
// In the legacy T2V protocol the explicit native size is authoritative.
|
|
if (profile.kind === "size" && nativeParameters.size != null && nativeParameters.size !== "") {
|
|
resolution = size.resolution;
|
|
ratio = size.ratio ?? parameters.ratio ?? "16:9";
|
|
}
|
|
if (!profile.resolutions.includes(resolution)) throw new Error(upstreamModel + " resolution must be one of " + profile.resolutions.join(", "));
|
|
if (profile.kind === "size" || profile.kind === "t2v" || profile.kind === "all") {
|
|
const ratios = ["16:9", "9:16", "1:1", "4:3", "3:4"];
|
|
if (profile.kind === "all") ratios.push("adaptive");
|
|
if (!ratios.includes(ratio)) throw new Error(upstreamModel + " ratio must be one of " + ratios.join(", "));
|
|
}
|
|
if (profile.kind === "size") {
|
|
const pixelSize = LEGACY_SIZES[resolution][ratio];
|
|
if (!pixelSize) throw new Error("unsupported ratio for " + resolution + ": " + ratio);
|
|
parameters.size = pixelSize;
|
|
delete parameters.resolution;
|
|
delete parameters.ratio;
|
|
} else {
|
|
parameters.resolution = resolution;
|
|
delete parameters.size;
|
|
if (profile.kind === "t2v" || profile.kind === "all") parameters.ratio = ratio;
|
|
else delete parameters.ratio; // Image-derived aspect ratios are not configurable.
|
|
}
|
|
|
|
const rawDuration = nativeParameters.duration ?? (req.auto_duration === true ? -1 : (req.duration ?? req.seconds));
|
|
if (rawDuration != null && ((typeof rawDuration !== "number" && typeof rawDuration !== "string") || String(rawDuration).trim() === ""))
|
|
throw new Error("duration must be a number");
|
|
const duration = rawDuration == null ? 5 : Number(rawDuration);
|
|
if (duration === -1 && profile.kind !== "all") throw new Error("duration -1 (smart duration) is only supported by wan3.0 models");
|
|
if (profile.kind === "speech") {
|
|
if (rawDuration != null && (!Number.isFinite(duration) || duration <= 0 || duration >= 20)) throw new Error("wan2.2-s2v duration must be positive and less than 20 seconds; output follows the audio");
|
|
delete parameters.duration;
|
|
} else {
|
|
if (profile.durations) {
|
|
if (!profile.durations.includes(duration)) throw new Error(upstreamModel + " duration must be one of " + profile.durations.join(", "));
|
|
} else if (!(profile.kind === "all" && duration === -1) && (!Number.isInteger(duration) || duration < 2 || duration > profile.maxDuration)) {
|
|
throw new Error(upstreamModel + " duration must be " + (profile.kind === "all" ? "-1 or " : "") + "an integer between 2 and " + profile.maxDuration);
|
|
}
|
|
parameters.duration = duration;
|
|
}
|
|
|
|
if (profile.kind === "media" || profile.kind === "all") {
|
|
if (input.media !== undefined && !Array.isArray(input.media)) throw new Error("input.media must be an array");
|
|
if (!input.media || input.media.length === 0) {
|
|
input.media = [];
|
|
const first = trimmed(input.first_frame_url) || trimmed(input.img_url) || firstImage(req);
|
|
const last = trimmed(input.last_frame_url) || secondImage(req);
|
|
if (first) input.media.push({ type: "first_frame", url: first });
|
|
if (last) input.media.push({ type: "last_frame", url: last });
|
|
if (trimmed(input.audio_url)) input.media.push({ type: profile.kind === "media" ? "driving_audio" : "reference_audio", url: input.audio_url });
|
|
}
|
|
const counts = {};
|
|
const limits =
|
|
profile.kind === "media"
|
|
? { first_frame: 1, last_frame: 1, driving_audio: 1, first_clip: 1 }
|
|
: { first_frame: 1, last_frame: 1, reference_image: 10, reference_video: 5, reference_audio: 5, file: 1, link: 1 };
|
|
for (const media of input.media) {
|
|
if (!media || !Object.prototype.hasOwnProperty.call(limits, media.type) || !trimmed(media.url)) throw new Error("invalid input.media type or url");
|
|
counts[media.type] = (counts[media.type] || 0) + 1;
|
|
if (counts[media.type] > limits[media.type]) throw new Error("too many input.media entries for " + media.type);
|
|
}
|
|
if (profile.kind === "media") {
|
|
if ((!counts.first_frame && !counts.first_clip) || (counts.first_clip && (counts.first_frame || counts.driving_audio)))
|
|
throw new Error("wan2.7-i2v requires first_frame or first_clip with a supported media combination");
|
|
} else {
|
|
const frames = counts.first_frame || counts.last_frame;
|
|
const references = counts.reference_image || counts.reference_video || counts.reference_audio || counts.file || counts.link;
|
|
if ((frames && references) || (counts.file && counts.link) || (counts.last_frame && !counts.first_frame)) throw new Error("unsupported wan3.0 input.media combination");
|
|
if (!trimmed(input.prompt) && !input.media.length) throw new Error("wan3.0-video requires prompt or input.media");
|
|
}
|
|
if (!input.media.length) delete input.media;
|
|
delete input.img_url;
|
|
delete input.first_frame_url;
|
|
delete input.last_frame_url;
|
|
delete input.audio_url;
|
|
} else if (profile.kind === "frames") {
|
|
input.first_frame_url = trimmed(input.first_frame_url) || trimmed(input.img_url);
|
|
if (!input.first_frame_url) throw new Error(upstreamModel + " requires first_frame_url or image");
|
|
if (!input.last_frame_url && secondImage(req)) input.last_frame_url = secondImage(req);
|
|
delete input.img_url;
|
|
} else if (profile.kind === "speech") {
|
|
input.image_url = trimmed(input.image_url) || trimmed(input.img_url);
|
|
if (!input.image_url || !trimmed(input.audio_url)) throw new Error("wan2.2-s2v requires image_url and audio_url");
|
|
delete input.img_url;
|
|
if (!trimmed(input.prompt)) delete input.prompt;
|
|
} else if (profile.kind === "image") {
|
|
if (!trimmed(input.img_url)) throw new Error(upstreamModel + " requires img_url or image");
|
|
} else if (!trimmed(input.prompt)) {
|
|
throw new Error("input is required");
|
|
}
|
|
return { model: upstreamModel, input: input, parameters: parameters };
|
|
}
|
|
|
|
function resolutionRatio(body) {
|
|
const resolution = body.parameters.size ? videoSize(body.parameters.size).resolution : body.parameters.resolution;
|
|
const ratios = {
|
|
"wan3.0-video": { "480P": 1, "720P": 2, "1080P": 4 },
|
|
"wan3.0-video-prime": { "480P": 1, "720P": 2, "1080P": 4 },
|
|
"wan2.6-i2v": { "720P": 1, "1080P": 1 / 0.6 },
|
|
"wan2.5-t2v-preview": { "480P": 1, "720P": 2, "1080P": 1 / 0.3 },
|
|
"wan2.2-t2v-plus": { "480P": 1, "1080P": 5 },
|
|
"wan2.5-i2v-preview": { "480P": 1, "720P": 2, "1080P": 1 / 0.3 },
|
|
"wan2.2-i2v-plus": { "480P": 1, "1080P": 5 },
|
|
"wan2.2-kf2v-flash": { "480P": 1, "720P": 2, "1080P": 4.8 },
|
|
"wan2.2-i2v-flash": { "480P": 1, "720P": 2 },
|
|
"wan2.2-s2v": { "480P": 1, "720P": 1.8 },
|
|
};
|
|
const model = modelKey(body.model);
|
|
return ratios[model] ? { key: "resolution-" + resolution, value: ratios[model][resolution] } : null;
|
|
}
|
|
|
|
function responsesInput(req) {
|
|
const texts = [],
|
|
images = [];
|
|
const input = req.input;
|
|
if (typeof input === "string") texts.push(input);
|
|
else if (Array.isArray(input)) {
|
|
for (const item of input) {
|
|
if (typeof item === "string") {
|
|
texts.push(item);
|
|
continue;
|
|
}
|
|
if (!item || typeof item !== "object" || Array.isArray(item)) continue;
|
|
const content = item.content === undefined ? [item] : Array.isArray(item.content) ? item.content : [item.content];
|
|
for (const part of content) {
|
|
if (typeof part === "string") {
|
|
texts.push(part);
|
|
continue;
|
|
}
|
|
if (!part || typeof part !== "object" || Array.isArray(part)) continue;
|
|
if (["input_text", "text"].includes(part.type) && typeof part.text === "string") texts.push(part.text);
|
|
if (["input_image", "image_url"].includes(part.type)) {
|
|
let image = part.image_url;
|
|
if (image && typeof image === "object") image = image.url;
|
|
if (trimmed(image)) images.push(trimmed(image));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
return {
|
|
prompt: texts
|
|
.filter(function (text) {
|
|
return trimmed(text);
|
|
})
|
|
.join("\n"),
|
|
images: images,
|
|
};
|
|
}
|
|
|
|
function responsesVideoText(ctx) {
|
|
const artifact = ctx && ctx.artifacts && ctx.artifacts.video;
|
|
const url = trimmed(artifact && artifact.url);
|
|
if (!url) throw new Error("video artifact is unavailable");
|
|
const escaped = url.replace(/&/g, "&").replace(/\u0022/g, """).replace(/</g, "<").replace(/>/g, ">");
|
|
return '<video controls src="' + escaped + '"></video>';
|
|
}
|
|
|
|
function responsesOutputText(ctx, task) {
|
|
const content = imageContent(artifactData(task));
|
|
if (!content.length) return responsesVideoText(ctx);
|
|
const parts = [];
|
|
let index = 0;
|
|
for (const part of content) {
|
|
if (part.image) {
|
|
const key = "image-" + (++index);
|
|
const artifact = (ctx.artifacts || {})[key];
|
|
if (!artifact || !artifact.url) throw new Error("image artifact is unavailable");
|
|
parts.push("![Image " + index + "](<" + artifact.url + ">)");
|
|
} else parts.push(part.text);
|
|
}
|
|
return parts.join("\n\n");
|
|
}
|
|
|
|
export function buildSubmitRequest(ctx) {
|
|
if (imageModel(ctx)) {
|
|
const converted = convertImage(ctx);
|
|
const headers = { Authorization: "Bearer " + ctx.apiKey, "Content-Type": "application/json" };
|
|
if (!converted.synchronous) headers["X-DashScope-Async"] = "enable";
|
|
const streaming = converted.synchronous && converted.body.parameters.enable_interleave === true;
|
|
if (streaming) headers["X-DashScope-Sse"] = "enable";
|
|
return { url: ctx.baseUrl + "/api/v1/services/aigc/" + converted.service, method: "POST", headers: headers, body: converted.body, action: converted.action, responseType: streaming ? "sse" : "json" };
|
|
}
|
|
const body = convert(ctx);
|
|
const kind = modelProfile(body.model).kind;
|
|
const service = kind === "frames" || kind === "speech" ? "image2video" : "video-generation";
|
|
return {
|
|
url: ctx.baseUrl + "/api/v1/services/aigc/" + service + "/video-synthesis",
|
|
method: "POST",
|
|
headers: { Authorization: "Bearer " + ctx.apiKey, "Content-Type": "application/json", "X-DashScope-Async": "enable" },
|
|
body: body,
|
|
action: videoAction(body.input),
|
|
};
|
|
}
|
|
|
|
// DashScope sends text/image deltas but cumulative usage. The host applies
|
|
// generic JSON changes; vendor completion and usage semantics remain here.
|
|
export function parseSubmitEventDelta(ctx, event, previousState) {
|
|
const body = JSON.parse(event.data);
|
|
if (!body || typeof body !== "object" || Array.isArray(body)) throw new Error("invalid DashScope stream event");
|
|
if (body.code || event.event === "error") throw new Error((body.code || "upstream_error") + ": " + (body.message || "stream failed"));
|
|
const state = utils.json.clone(previousState || { choices: [], hasUsage: false });
|
|
const changes = [];
|
|
if (!previousState) changes.push({ op: "set", path: [], value: { output: { choices: [], finished: false } } });
|
|
if (body.request_id) changes.push({ op: "set", path: ["request_id"], value: body.request_id });
|
|
if (body.usage) {
|
|
if (!state.hasUsage) {
|
|
changes.push({ op: "set", path: ["usage"], value: {} });
|
|
state.hasUsage = true;
|
|
}
|
|
for (const key of Object.keys(body.usage)) changes.push({ op: "set", path: ["usage", key], value: body.usage[key] });
|
|
}
|
|
const choices = (body.output || {}).choices || [];
|
|
for (let index = 0; index < choices.length; index++) {
|
|
const choice = choices[index];
|
|
if (!choice || !choice.message || !Array.isArray(choice.message.content)) throw new Error("invalid DashScope stream choice");
|
|
if (!state.choices[index]) {
|
|
state.choices.push({ count: 0, lastText: false, finishReason: "" });
|
|
changes.push({ op: "append", path: ["output", "choices"], value: { message: { role: "assistant", content: [] } } });
|
|
}
|
|
const control = state.choices[index];
|
|
for (const part of choice.message.content) {
|
|
if (!part || typeof part !== "object") throw new Error("invalid DashScope stream content");
|
|
if (typeof part.text === "string" && control.lastText) {
|
|
changes.push({ op: "appendText", path: ["output", "choices", index, "message", "content", control.count - 1, "text"], value: part.text });
|
|
} else {
|
|
changes.push({ op: "append", path: ["output", "choices", index, "message", "content"], value: part });
|
|
control.count++;
|
|
control.lastText = typeof part.text === "string";
|
|
}
|
|
}
|
|
if (choice.finish_reason && choice.finish_reason !== "null") {
|
|
control.finishReason = choice.finish_reason;
|
|
changes.push({ op: "set", path: ["output", "choices", index, "finish_reason"], value: choice.finish_reason });
|
|
}
|
|
}
|
|
// Some intermediate frames carry finished:true; only terminal finish reasons
|
|
// make the complete output ready for parsing and billing.
|
|
const done =
|
|
state.choices.length > 0 &&
|
|
state.choices.every(function (choice) {
|
|
return choice.finishReason === "stop";
|
|
});
|
|
changes.push({ op: "set", path: ["output", "finished"], value: done });
|
|
return { changes: changes, state: state, done: done };
|
|
}
|
|
|
|
export function parseSubmitResponse(ctx, resp) {
|
|
const body = resp.body || {};
|
|
if (body.code) throw new Error(body.code + ": " + (body.message || ""));
|
|
if (imageModel(ctx) && convertImage(ctx).synchronous) {
|
|
const content = imageContent(body);
|
|
const images = content.filter(function (part) { return part.image; });
|
|
const interleaved = convertImage(ctx).body.parameters.enable_interleave === true;
|
|
if ((!images.length && !(interleaved && content.length)) || (body.output || {}).finished === false)
|
|
throw new Error("synchronous image response has no completed output");
|
|
// No vendor task exists for a synchronous HTTP response. The host already
|
|
// allocated a public ID; retain that identity without inventing a pollable ID.
|
|
const taskId = ctx.publicTaskId || body.request_id;
|
|
if (!taskId) throw new Error("missing synchronous image request id");
|
|
return { taskId: taskId, taskData: body, immediate: { status: "SUCCESS", progress: "100%", url: images.length ? images[0].image : "" } };
|
|
}
|
|
if (!body.output || !body.output.task_id) throw new Error("task_id is empty");
|
|
return { taskId: body.output.task_id, taskData: body };
|
|
}
|
|
|
|
export function extractUsage(ctx) {
|
|
if (imageModel(ctx)) {
|
|
const parameters = convertImage(ctx).body.parameters;
|
|
return { image_count: parameters.enable_interleave ? parameters.max_images : parameters.n };
|
|
}
|
|
const body = convert(ctx);
|
|
const kind = modelProfile(body.model).kind;
|
|
const hasVideo = (body.input.media || []).some(function (media) {
|
|
return media.type === "reference_video";
|
|
});
|
|
let seconds = body.parameters.duration;
|
|
if (kind === "speech") seconds = 20;
|
|
else if (kind === "all" && (hasVideo || seconds === -1)) seconds = 30;
|
|
if (ctx.usagePurpose === "billing_ratios") {
|
|
const ratios = { seconds: seconds };
|
|
const resolution = resolutionRatio(body);
|
|
if (resolution && resolution.value !== undefined) ratios[resolution.key] = resolution.value;
|
|
return ratios;
|
|
}
|
|
const resolution = body.parameters.size ? videoSize(body.parameters.size).resolution : body.parameters.resolution;
|
|
return { seconds: seconds, resolution: resolution };
|
|
}
|
|
|
|
export function extractUsageOnSubmit(ctx, body) {
|
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// Legacy ratio pricing uses this hook; task expressions use the same actual
|
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// facts through extractUsageOnComplete for both immediate and polled results.
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return imageModel(ctx) && convertImage(ctx).synchronous ? imageUsage(body) : {};
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}
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export function extractUsageOnComplete(task, taskResult, body) {
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if (imageModel(task)) return imageUsage(body || {});
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const output = (body && body.output) || {};
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const usage = (body && body.usage) || {};
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|
const facts = {};
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const model = modelKey(task && (task.upstreamModel || task.model));
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if (model === "wan3.0-video" || model === "wan3.0-video-prime" || (!model && usage.input_video_duration != null)) {
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const inputSeconds = usage.input_video_duration;
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const outputSeconds = usage.output_video_duration ?? usage.duration;
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// Partial Wan3 statistics cannot establish the total billable duration.
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// Keep the reservation when either side is missing. Invalid supplied facts
|
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// reach the host validator unchanged, which logs and rejects them.
|
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if (inputSeconds != null && outputSeconds != null) {
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if (typeof inputSeconds !== "number" || !Number.isFinite(inputSeconds) || inputSeconds < 0) facts.seconds = inputSeconds;
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else if (typeof outputSeconds !== "number" || !Number.isFinite(outputSeconds) || outputSeconds < 0) facts.seconds = outputSeconds;
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else facts.seconds = inputSeconds + outputSeconds;
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}
|
|
} else {
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const seconds = usage.duration ?? usage.output_video_duration ?? output.duration ?? output.duration_seconds;
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|
if (seconds != null) facts.seconds = seconds;
|
|
}
|
|
const resolution = usage.SR ?? output.resolution;
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|
if (resolution != null) facts.resolution = normalizeResolution(resolution);
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|
return facts;
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}
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|
|
|
export function buildQueryRequest(ctx) {
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return { url: ctx.baseUrl + "/api/v1/tasks/" + ctx.taskId, method: "GET", headers: { Authorization: "Bearer " + ctx.apiKey } };
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}
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|
|
|
export function parseTaskResult(ctx, body) {
|
|
const output = body.output || {};
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if (output.task_status === "PENDING") return { status: "QUEUED" };
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if (output.task_status === "RUNNING") return { status: "IN_PROGRESS" };
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|
if (output.task_status === "SUCCEEDED") {
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if (imageModel(ctx)) {
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|
const content = imageContent(body);
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const images = content.filter(function (part) { return part.image; });
|
|
if (!images.length) {
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if (imageModel(ctx) === "image26" && content.some(function (part) { return trimmed(part.text); })) return { status: "SUCCESS" };
|
|
return { status: "FAILURE", reason: "image task succeeded without any images" };
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|
}
|
|
return { status: "SUCCESS", url: images[0].image };
|
|
}
|
|
return { status: "SUCCESS", url: videoURL(body) };
|
|
}
|
|
if (["FAILED", "CANCELED", "UNKNOWN"].includes(output.task_status)) {
|
|
let reason = body.message || "";
|
|
if (!reason && output.message) reason = "task failed, code: " + (output.code || "") + " , message: " + output.message;
|
|
if (!reason) reason = "task failed";
|
|
return { status: "FAILURE", reason: reason };
|
|
}
|
|
return { status: "UNKNOWN", reason: "unrecognized status: " + String(output.task_status || "") };
|
|
}
|
|
|
|
function artifactData(ctx) {
|
|
const data = (ctx && ctx.data) || {};
|
|
if (data.data && typeof data.data === "object" && data.data.task_id && Object.prototype.hasOwnProperty.call(data.data, "data")) return data.data.data || {};
|
|
return data;
|
|
}
|
|
|
|
function videoURL(body) {
|
|
const output = (body && body.output) || {};
|
|
return trimmed(output.video_url) || trimmed((output.results || {}).video_url);
|
|
}
|
|
|
|
export function listArtifacts(task) {
|
|
if (task.status !== "SUCCESS") return [];
|
|
const body = artifactData(task);
|
|
const images = imageContent(body).filter(function (part) { return part.image; });
|
|
if (images.length) return images.map(function (_, index) { return { key: "image-" + (index + 1), type: "image" }; });
|
|
return videoURL(body) ? [{ key: "video", type: "video" }] : [];
|
|
}
|
|
|
|
export function buildContentRequest(ctx) {
|
|
let url;
|
|
if (ctx.artifactKey === "video") url = videoURL(artifactData(ctx));
|
|
else {
|
|
const images = imageContent(artifactData(ctx)).filter(function (part) { return part.image; });
|
|
const index = images.findIndex(function (_, index) { return ctx.artifactKey === "image-" + (index + 1); });
|
|
url = index >= 0 ? images[index].image : "";
|
|
}
|
|
if (!url) throw new Error("artifact_not_found");
|
|
return { url: url, method: ctx.clientRequest.method, credentialless: true };
|
|
}
|
|
|
|
export const native = {
|
|
createImageTask: function (ctx) {
|
|
if (!ctx.body || ctx.body.kind !== "json" || !ctx.body.value || typeof ctx.body.value !== "object" || Array.isArray(ctx.body.value)) throw new Error("JSON object required");
|
|
const req = ctx.body.value;
|
|
if (req.stream !== undefined && req.stream !== false) throw new Error("native task responses are aggregated JSON; configure upstream streaming in parameters");
|
|
const requestBody = {
|
|
model: req.model,
|
|
metadata: {
|
|
input: objectValue(req.input, "input"),
|
|
parameters: objectValue(req.parameters, "parameters"),
|
|
upstream_mode: String(ctx.path || "").includes("/multimodal-generation/") ? "sync" : "async",
|
|
},
|
|
};
|
|
return { kind: "submit", model: req.model, requestBody: requestBody };
|
|
},
|
|
imageCreated: function (ctx, task) {
|
|
return task.data || {};
|
|
},
|
|
createVideoTask: function (ctx) {
|
|
if (!ctx.body || ctx.body.kind !== "json" || !ctx.body.value || typeof ctx.body.value !== "object" || Array.isArray(ctx.body.value)) throw new Error("JSON object required");
|
|
const req = ctx.body.value,
|
|
input = objectValue(req.input, "input"),
|
|
parameters = objectValue(req.parameters, "parameters");
|
|
const requestBody = {
|
|
model: req.model,
|
|
metadata: { input: input, parameters: parameters },
|
|
};
|
|
if (input.prompt !== undefined) requestBody.prompt = input.prompt;
|
|
const image = input.img_url || input.image_url || input.first_frame_url;
|
|
if (image !== undefined) requestBody.image = image;
|
|
return {
|
|
kind: "submit",
|
|
model: req.model,
|
|
action: videoAction(requestBody),
|
|
requestBody: normalizeRequest(requestBody),
|
|
};
|
|
},
|
|
taskCreated: function (ctx, task) {
|
|
const data = task.data || {};
|
|
return { request_id: data.request_id || "", output: { task_id: task.task_id, task_status: "PENDING" } };
|
|
},
|
|
taskStatus: function (ctx, task) {
|
|
const data = task.data || {},
|
|
output = Object.assign({}, data.output || {}, { task_id: task.task_id });
|
|
return Object.assign({}, data, { output: output });
|
|
},
|
|
error: function (ctx, error) {
|
|
return { code: error.code, message: error.message, request_id: "" };
|
|
},
|
|
};
|
|
|
|
export const protocols = {
|
|
openai_responses: {
|
|
decodeRequest: function (ctx) {
|
|
if (!ctx.body || ctx.body.kind !== "json") throw new Error("JSON body required");
|
|
const req = ctx.body.value;
|
|
if (!req || typeof req !== "object" || Array.isArray(req)) throw new Error("request body must be an object");
|
|
const model = trimmed(ctx.model);
|
|
if (!model) throw new Error("model is required");
|
|
if (req.input !== undefined && typeof req.input !== "string" && !Array.isArray(req.input)) throw new Error("input must be a string or array");
|
|
const input = responsesInput(req);
|
|
const prompt = input.prompt || trimmed(req.prompt);
|
|
let requestBody = { model: model, prompt: prompt };
|
|
if (trimmed(req.image)) requestBody.image = trimmed(req.image);
|
|
if (req.images !== undefined && !Array.isArray(req.images)) throw new Error("images must be an array");
|
|
const images = [];
|
|
for (const image of req.images || []) if (trimmed(image) && !images.includes(trimmed(image))) images.push(trimmed(image));
|
|
for (const image of input.images) if (!images.includes(image)) images.push(image);
|
|
if (images.length) requestBody.images = images;
|
|
if (trimmed(req.input_reference)) requestBody.input_reference = trimmed(req.input_reference);
|
|
for (const key of [
|
|
"size", "resolution", "ratio", "duration", "seconds", "auto_duration",
|
|
"prompt_extend", "watermark", "audio", "seed", "shot_type", "negative_prompt",
|
|
"img_url", "image_url", "first_frame_url", "last_frame_url", "audio_url", "template", "media",
|
|
]) {
|
|
if (Object.prototype.hasOwnProperty.call(req, key)) requestBody[key] = req[key];
|
|
}
|
|
if (Object.prototype.hasOwnProperty.call(req, "metadata")) requestBody.metadata = req.metadata;
|
|
if (imageModel({ upstreamModel: ctx.upstreamModel, model: model })) {
|
|
for (const key of ["n", "enable_interleave", "max_images", "enable_sequential", "thinking_mode", "bbox_list", "color_palette"]) {
|
|
if (Object.prototype.hasOwnProperty.call(req, key)) requestBody[key] = req[key];
|
|
}
|
|
// The model may be a mapped alias; final validation runs after channel selection.
|
|
return { kind: "submit", model: model, action: firstImage(requestBody) ? "image_to_image" : "text_to_image", requestBody: requestBody };
|
|
}
|
|
requestBody = normalizeRequest(requestBody);
|
|
const action = videoAction(requestBody);
|
|
const profile = WAN_MODELS[modelKey(ctx.upstreamModel || model)];
|
|
const nativeInput = objectValue((requestBody.metadata || {}).input, "metadata.input");
|
|
if (!trimmed(nativeInput.prompt ?? prompt) && (action === "text_to_video" || (profile && (profile.kind === "size" || profile.kind === "t2v"))))
|
|
throw new Error("input is required");
|
|
return { kind: "submit", model: model, action: action, requestBody: requestBody };
|
|
},
|
|
renderEvents: function (ctx, task, previousState) {
|
|
const status = String(task.status || "UNKNOWN").toUpperCase();
|
|
const value = Number(String(task.progress || "").replace("%", ""));
|
|
const progress = Number.isFinite(value) && value >= 0 && value <= 100 ? value : null;
|
|
const state = { status: status, progress: progress };
|
|
if (status === "SUCCESS") {
|
|
const text = responsesOutputText(ctx, task);
|
|
const events = previousState && previousState.status === status ? [] : text ? [{ type: "output", data: text }] : [];
|
|
return { events: events, state: state, done: true };
|
|
}
|
|
if (status === "FAILURE") {
|
|
return { events: [{ type: "error", code: "task_failed", message: "task failed" }], state: state, done: true };
|
|
}
|
|
if (previousState && previousState.status === status && previousState.progress === progress) {
|
|
return { events: [], state: state, done: false };
|
|
}
|
|
const event = { type: "progress", message: status.toLowerCase() };
|
|
if (progress !== null) event.progress = progress;
|
|
return { events: [event], state: state, done: false };
|
|
},
|
|
renderFinal: function (ctx, task) {
|
|
return {
|
|
output: [
|
|
{
|
|
type: "message",
|
|
status: "completed",
|
|
role: "assistant",
|
|
content: [
|
|
{
|
|
type: "output_text",
|
|
text: responsesOutputText(ctx, task),
|
|
annotations: [],
|
|
logprobs: [],
|
|
},
|
|
],
|
|
},
|
|
],
|
|
metadata: { vendor: "ali" },
|
|
};
|
|
},
|
|
},
|
|
openai_video: {
|
|
decodeRequest: function (ctx) {
|
|
let req;
|
|
if (ctx.body && ctx.body.kind === "json") req = ctx.body.value;
|
|
else if (ctx.body && ctx.body.kind === "multipart") {
|
|
if ((ctx.body.files || []).length) throw new Error("Alibaba requires image references to be URLs");
|
|
const first = function (name) {
|
|
const values = (ctx.body.fields || {})[name] || [];
|
|
if (values.length > 1) throw new Error(name + " must be provided once");
|
|
return values[0];
|
|
};
|
|
req = {};
|
|
const fields = ctx.body.fields || {};
|
|
for (const name of Object.keys(fields)) {
|
|
if (name === "images") req.images = fields[name] || [];
|
|
else req[name] = first(name);
|
|
}
|
|
if (req.metadata !== undefined) {
|
|
let parsed;
|
|
try {
|
|
parsed = JSON.parse(req.metadata);
|
|
} catch (e) {
|
|
throw new Error("metadata must be a JSON object string");
|
|
}
|
|
if (!parsed || typeof parsed !== "object" || Array.isArray(parsed)) throw new Error("metadata must be a JSON object string");
|
|
req.metadata = parsed;
|
|
}
|
|
if (req.seconds !== undefined) req.seconds = Number(req.seconds);
|
|
else if (req.duration !== undefined) req.seconds = Number(req.duration);
|
|
if (req.duration !== undefined) req.duration = Number(req.duration);
|
|
if (req.seed !== undefined) req.seed = Number(req.seed);
|
|
for (const key of ["prompt_extend", "watermark", "audio", "auto_duration"]) {
|
|
if (req[key] === undefined) continue;
|
|
if (req[key] !== "true" && req[key] !== "false") throw new Error(key + " must be true or false");
|
|
req[key] = req[key] === "true";
|
|
}
|
|
} else throw new Error("JSON or multipart body required");
|
|
if (!req || typeof req !== "object" || Array.isArray(req)) throw new Error("request body must be an object");
|
|
if (req.images !== undefined && !Array.isArray(req.images)) throw new Error("images must be an array");
|
|
const requestBody = normalizeRequest(Object.assign({}, req, { model: ctx.model }));
|
|
return {
|
|
kind: "submit",
|
|
model: ctx.model,
|
|
action: videoAction(requestBody),
|
|
requestBody: requestBody,
|
|
};
|
|
},
|
|
render: function (ctx, task) {
|
|
const data = task.data || {},
|
|
outputData = data.output || {};
|
|
const statuses = {
|
|
PENDING: "queued",
|
|
RUNNING: "in_progress",
|
|
SUCCEEDED: "completed",
|
|
FAILED: "failed",
|
|
CANCELED: "failed",
|
|
UNKNOWN: "failed",
|
|
};
|
|
const output = {
|
|
id: task.task_id,
|
|
object: "video",
|
|
model: task.properties ? task.properties.origin_model_name || "" : "",
|
|
status: statuses[outputData.task_status] || "unknown",
|
|
progress: Number(String(task.progress || "0").replace("%", "")),
|
|
created_at: task.created_at,
|
|
completed_at: task.updated_at,
|
|
};
|
|
if (data.code) output.error = { code: data.code, message: data.message || "" };
|
|
else if (outputData.code) output.error = { code: outputData.code, message: outputData.message || "" };
|
|
return output;
|
|
},
|
|
},
|
|
};
|