fix(agent): recover unavailable automatic image choices and correct regression fixtures
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@ -205,7 +205,7 @@ export async function buildCanvasRuntimeTools(params: {
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const pinnedModel = resolveUserImageModel(params.objective || "", models, params.imagePreferences?.modelId);
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const requestedModel = pinnedModel || input.modelId || params.preferredModelId;
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const requestedEntry = requestedModel ? models.find(({ model }) => model.healthStatus !== "auto_disabled" && (model.id === requestedModel || model.modelId === requestedModel)) : null;
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if (requestedModel && !requestedEntry) throw new Error("指定的图片模型不可用，未切换到其他模型收费生成");
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if (pinnedModel && !requestedEntry) throw new Error("指定的图片模型不可用，未切换到其他模型收费生成");
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const chosen = requestedEntry || models.find(
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({ model }) => model.id === route?.id && model.healthStatus !== "auto_disabled",
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) ||
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@ -1,486 +1,103 @@
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import {
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executeBoxCutoutJob,
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} from "@/lib/ai/box-cutout/service";
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import { executeExtendJob } from "@/lib/ai/extend/service";
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import { executeLayerSplitJob } from "@/lib/ai/layer-split/service";
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import { executeResizeJob } from "@/lib/ai/resize/service";
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import {
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executeRmbgJob,
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fetchImageBufferFromUrl,
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} from "@/lib/ai/rmbg/service";
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import type { CanvasCapabilityClientCommand } from "@/lib/canvas/capabilities/client-command";
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import type { CanvasCapabilityTarget } from "@/lib/canvas/capabilities/context";
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import { resolveCanvasRuntimeEndpoint } from "@/lib/canvas/capabilities/internal-endpoint";
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import { generateCanvasImage } from "@/lib/canvas/generate-image";
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import { requestLongTaskResult } from "@/lib/client/long-task";
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import {
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findStyleProImageModelByRef,
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getStyleProImageModelEntries,
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sortStyleProImageModelEntries,
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} from "@/lib/style-pro/model-options";
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import { expect, test } from "@playwright/test";
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import { serverLoader } from "../helpers/canvas-download-server-loader";
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import { applyAgentImagePreferences, agentProviderImageParameters } from "@/lib/ai/canvas-agent-runtime/image-preferences";
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export type CanvasCapabilityMediaResult = {
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assetId?: string;
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height?: number;
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metadata?: Record<string, unknown>;
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nodeType?: "image" | "model3d" | "world3d";
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prompt?: string;
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sourceNodeId: string;
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title: string;
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url: string;
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width?: number;
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const preferences = {
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modelId: "user-image-model",
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parameters: { imageCount: 3, aspectRatio: "3:4", imageSize: "4K", negativePrompt: "不要文字",
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quality: "high" as const, size: "1536*2048", promptExtend: false, watermark: false, seed: 0 },
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};
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type HeadlessExecutorParams = {
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command: CanvasCapabilityClientCommand;
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requestHeaders: Headers;
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requestUrl: string;
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targets: CanvasCapabilityTarget[];
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userId: string;
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};
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function asFiniteNumber(value: unknown) {
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const number = Number(value);
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return Number.isFinite(number) ? number : undefined;
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}
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function getCookieHeaders(headers: Headers) {
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const cookie = headers.get("cookie") || "";
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return cookie ? { cookie } : undefined;
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}
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async function postRuntimeEndpoint(params: {
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body: Record<string, unknown>;
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path: string;
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requestHeaders: Headers;
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requestUrl: string;
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timeoutMs?: number;
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}) {
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const response = await fetch(resolveCanvasRuntimeEndpoint(params.path, params.requestUrl), {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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...getCookieHeaders(params.requestHeaders),
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function harness(results?: any[]) {
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const saved: any[] = [];
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const generated: any[] = [];
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const operations: any[] = [];
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const mock = serverLoader({
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"@/lib/canvas/capabilities/ai-sdk-tools": { createCanvasCapabilityTools: async () => ({ editTargetImage: {} }) },
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"@/lib/canvas/capabilities/registry": { CANVAS_CAPABILITY_REGISTRY: [{ id: "image.prompt_regenerate", title: "重绘", risk: "external", agent: { toolName: "editTargetImage" } }] },
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"@/lib/canvas/agent-mutations": { applyCanvasOperationPlan: async (value: any) => { operations.push(value); return { createdNodeIds: ["new-image"] }; } },
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"@/lib/canvas/generate-image": { generateCanvasImage: async (value: any) => { generated.push(value); return { modelRef: results ? "backup" : value.model, images: results || [{ originalUrl: "https://test.example/result.png", thumbnailUrl: "https://test.example/thumb.png" }] }; } },
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"@/lib/ai/runtime/generated-image-persistence": { saveGeneratedImages: async (...args: any[]) => { saved.push(args); } },
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"@/lib/ai/model-router": { routeToModel: async () => ({ id: "system-default" }) },
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"@/lib/db/queries": { checkUserImageQuota: async () => ({ allowed: true, remaining: 10 }), getPointsSystemConfig: async () => ({ enabled: false }), getUserById: async () => ({}) },
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"@/lib/style-pro/model-options": {
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getStyleProImageModelEntries: async () => ["system-default", "user-image-model"].map(id => ({ model: { id, modelId: id, isDefault: id === "system-default", imageGenConfig: {} } })),
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sortStyleProImageModelEntries: (entries: any) => entries,
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},
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body: JSON.stringify(params.body),
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signal: AbortSignal.timeout(params.timeoutMs || 20 * 60 * 1000),
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"./canvas": { readOwnedCanvas: async () => ({ nodes: [{ id: "reference", type: "image" }] }), readCanvasImages: async () => [{ id: "reference", data: { src: "https://test.example/reference.png" } }] },
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"./review": {},
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"./image-access-tools": { registerImageCanvasAccessTools() {} },
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});
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const payload = await response.json().catch(() => null);
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if (!response.ok || payload?.success === false || payload?.error) {
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throw new Error(
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String(payload?.error || payload?.detail || `能力服务返回 ${response.status}`)
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);
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}
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return payload as Record<string, any>;
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}
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async function postRuntimeFormData(params: {
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formData: FormData;
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path: string;
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requestHeaders: Headers;
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requestUrl: string;
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timeoutMs?: number;
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}) {
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const response = await fetch(resolveCanvasRuntimeEndpoint(params.path, params.requestUrl), {
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method: "POST",
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headers: getCookieHeaders(params.requestHeaders),
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body: params.formData,
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signal: AbortSignal.timeout(params.timeoutMs || 20 * 60 * 1000),
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const build = async (imagePreferences: any = preferences) => mock("lib/ai/canvas-agent-runtime/tools.ts").buildCanvasRuntimeTools({
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userId: "u", chatId: "c", projectId: "p", runId: "r", assistantMessageId: "a", selectedNodeIds: ["reference"],
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request: new Request("https://test.example/api/canvas/agent-chat"), model: {}, supportsVision: true,
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preferredModelId: "system-default", imagePreferences, emit() {},
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});
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const payload = await response.json().catch(() => null);
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if (!response.ok || payload?.success === false || payload?.error) {
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throw new Error(
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String(payload?.error || payload?.detail || `能力服务返回 ${response.status}`)
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);
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}
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return payload as Record<string, any>;
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return { build, generated, operations, saved };
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}
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test("explicit controls override conflicting planner settings without losing false or zero values", () => {
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const resolved = applyAgentImagePreferences({ modelId: "planner-choice", imageCount: 1, imageSize: "1K", aspectRatio: "1:1", prompt: "产品图" }, preferences);
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expect(resolved).toMatchObject({ ...preferences.parameters, modelId: preferences.modelId, prompt: "产品图" });
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expect(agentProviderImageParameters(resolved)).toEqual({ quality: "high", size: "1536*2048", watermark: false, seed: 0 });
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});
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test("real generation tool honors the chosen image model and all parameters despite another default and planner choice", async () => {
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const h = harness(); const tools = await h.build();
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const output = await tools.executable.generateCanvasImages.execute({ prompt: "生成产品图", modelId: "planner-choice", imageCount: 1, imageSize: "1K", aspectRatio: "1:1" }, "call-1");
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expect(h.generated).toHaveLength(1);
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expect(h.generated[0]).toMatchObject({ prompt: "生成产品图", model: "user-image-model", imageCount: 3, imageSize: "4K", aspectRatio: "3:4", negativePrompt: "不要文字", promptExtend: false, allowFailover: false,
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providerImageParams: { quality: "high", size: "1536*2048", watermark: false, seed: 0 } });
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expect(output.appliedImagePreferences).toEqual({ modelId: "user-image-model", imageCount: 3, imageSize: "4K", aspectRatio: "3:4" });
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});
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test("redraw and a corrective retry inherit the same user model, batch and image controls", async () => {
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const h = harness(); const tools = await h.build();
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await tools.executable.editTargetImage.execute({ nodeIds: ["reference"], args: { prompt: "换背景", modelId: "system-default" } }, "edit-1");
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await tools.executable.generateCanvasImages.execute({ prompt: "修正背景", modelId: "system-default" }, "retry-1");
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expect(h.generated).toHaveLength(2);
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for (const invocation of h.generated) expect(invocation).toMatchObject({ model: preferences.modelId, imageSize: "4K", imageCount: 3, aspectRatio: "3:4", allowFailover: false });
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});
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test("an unavailable explicit choice never silently generates or charges through the default", async () => {
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const h = harness(); const tools = await h.build({ ...preferences, modelId: "disabled-or-missing" });
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await expect(tools.executable.generateCanvasImages.execute({ prompt: "画图" }, "bad")).rejects.toThrow("指定的图片模型不可用");
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expect(h.generated).toHaveLength(0); expect(h.operations).toHaveLength(0);
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});
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test("Auto selection retains routing and the n count alias without overriding a supplied planner ratio", async () => {
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const h = harness(); const tools = await h.build({ parameters: { n: 2, imageSize: "8K" } });
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await tools.executable.generateCanvasImages.execute({ prompt: "画图", aspectRatio: "16:9" }, "auto");
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expect(h.generated[0]).toMatchObject({ model: "system-default", imageCount: 2, imageSize: "8K", aspectRatio: "16:9", allowFailover: true });
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});
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function inferTripoImageType(imageUrl: string) {
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try {
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const extension = new URL(imageUrl).pathname.split(".").pop()?.toLowerCase();
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if (extension === "png" || extension === "webp") return extension;
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} catch {}
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return "jpg";
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}
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test("planning uses the image count for generation tasks but does not turn analysis into an image task", async () => {
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const h = harness(); const tools = await h.build();
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const plan = { steps: ["查看画布"], visualCriteria: [] };
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const analysis = await tools.executable.planCanvasTask.execute(plan, "analysis-plan");
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expect(analysis.expectedImageCount).toBeUndefined();
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const generation = await tools.executable.planCanvasTask.execute({ ...plan, expectedImageCount: 1, aspectRatio: "1:1" }, "generation-plan");
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expect(generation).toMatchObject({ expectedImageCount: 3, aspectRatio: "3:4" });
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expect(h.generated).toHaveLength(0);
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});
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async function resolveImageModel(modelRef?: unknown) {
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const entries = sortStyleProImageModelEntries(
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await getStyleProImageModelEntries({ includeHidden: false })
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);
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const requested = findStyleProImageModelByRef(entries, String(modelRef || ""));
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const selected = requested || entries.find((entry) => entry.model.isDefault) || entries[0];
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if (!selected) throw new Error("系统未配置可用的图片生成模型");
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return selected;
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}
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test("an explicit model in the user's words pins generation, while the planner's own choice does not", async () => {
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const { resolveUserImageModel } = await import("@/lib/ai/canvas-agent-runtime/image-preferences");
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const entries = [{ model: { id: "pinned", modelId: "nano-banana-pro", displayName: "Banana Pro" } }];
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expect(resolveUserImageModel("请使用 nano banana pro 画一只小猫", entries)).toBe("pinned");
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expect(resolveUserImageModel("不要用nano-banana-pro，自动画图", entries)).toBeUndefined();
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expect(resolveUserImageModel("不用nano-banana-pro，自动画图", entries)).toBeUndefined();
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expect(resolveUserImageModel("先使用nano-banana-pro，改用other-image", [...entries, { model: { id: "later", modelId: "other-image" } }])).toBe("later");
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expect(resolveUserImageModel("画一只小猫", entries)).toBeUndefined();
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expect(resolveUserImageModel("使用nano-banana-pro", entries, "manual-control")).toBe("manual-control");
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});
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async function executeForTarget(
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params: HeadlessExecutorParams,
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target: CanvasCapabilityTarget
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): Promise<CanvasCapabilityMediaResult[]> {
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const { command } = params;
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const prompt = String(command.args.prompt || "").trim();
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const common = {
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sourceNodeId: target.nodeId,
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prompt: prompt || undefined,
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};
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if (command.capabilityId === "image.remove_background") {
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const imageBuffer = await fetchImageBufferFromUrl(target.sourceImageUrl);
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const result = await executeRmbgJob({
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userId: params.userId,
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imageBuffer,
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sourceImageUrl: target.sourceImageUrl,
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prompt: prompt || "抠图处理",
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skipGallerySave: false,
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});
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return [{
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...common,
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assetId: result.mediaAssetId || undefined,
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title: `${target.title}-抠图`,
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url: result.original_url,
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}];
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}
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if (command.capabilityId === "image.extend") {
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const result = await executeExtendJob({
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userId: params.userId,
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imageUrl: target.sourceImageUrl,
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sourceImageUrl: target.sourceImageUrl,
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prompt: prompt || "图像拓展处理",
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xScale: asFiniteNumber(command.args.xScale),
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yScale: asFiniteNumber(command.args.yScale),
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requestId: command.requestId,
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});
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return [{
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...common,
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assetId: result.mediaAssetId || undefined,
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title: `${target.title}-扩图`,
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url: result.original_url,
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}];
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}
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if (command.capabilityId === "image.resize") {
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const width = asFiniteNumber(command.args.width);
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const height = asFiniteNumber(command.args.height);
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if (!width || !height) throw new Error("请提供完整的目标宽度和高度");
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const result = await executeResizeJob({
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userId: params.userId,
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imageUrl: target.sourceImageUrl,
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sourceImageUrl: target.sourceImageUrl,
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canvasWidth: Math.round(width),
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canvasHeight: Math.round(height),
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backgroundColor: String(command.args.backgroundColor || "").trim() || undefined,
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transparentBackground: command.args.transparentBackground === true,
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mimeType: String(command.args.mimeType || "").trim() || undefined,
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});
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return [{
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...common,
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assetId: result.mediaAssetId || undefined,
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height: result.canvas_height,
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title: `${target.title}-${result.canvas_width}x${result.canvas_height}`,
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url: result.original_url,
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width: result.canvas_width,
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}];
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}
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if (command.capabilityId === "image.box_cutout") {
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const result = await executeBoxCutoutJob({
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userId: params.userId,
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imageUrl: target.sourceImageUrl,
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sourceNodeId: target.nodeId,
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cropRect: {
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x: asFiniteNumber(command.args.x),
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y: asFiniteNumber(command.args.y),
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width: asFiniteNumber(command.args.width),
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height: asFiniteNumber(command.args.height),
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},
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paddingRatio: asFiniteNumber(command.args.paddingRatio),
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prompt: prompt || "框选抠图",
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});
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return [{
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...common,
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assetId: result.mediaAssetId || undefined,
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metadata: {
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cropRectApplied: result.cropRectApplied,
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paddedCropRectApplied: result.paddedCropRectApplied,
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},
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title: `${target.title}-框选抠图`,
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url: result.original_url,
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}];
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}
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if (command.capabilityId === "image.layer_split") {
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const result = await executeLayerSplitJob({
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userId: params.userId,
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imageUrl: target.sourceImageUrl,
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sourceNodeId: target.nodeId,
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prompt: prompt || undefined,
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});
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return result.layers.map((layer) => ({
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...common,
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assetId: layer.mediaAssetId || undefined,
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metadata: {
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bounds: layer.bounds || null,
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layerIndex: layer.layerIndex,
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model: result.model,
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provider: result.provider,
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totalLayers: layer.totalLayers,
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},
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title: layer.title || `${target.title}-图层${layer.layerIndex + 1}`,
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url: layer.originalUrl,
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}));
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}
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if (command.capabilityId === "image.enhance") {
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const result = await requestLongTaskResult({
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endpoint: resolveCanvasRuntimeEndpoint("/api/enhance", params.requestUrl),
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payload: {
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imageUrl: target.sourceImageUrl,
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prompt: prompt || "图像增强处理",
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scaleFactor: asFiniteNumber(command.args.scaleFactor),
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},
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pollingParams: {
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prompt: prompt || "图像增强处理",
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sourceImageUrl: target.sourceImageUrl,
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},
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timeoutMs: 10 * 60 * 1000,
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headers: getCookieHeaders(params.requestHeaders),
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});
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if (!result?.success || !result.original_url) {
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throw new Error(String(result?.error || result?.detail || "图像增强失败"));
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}
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return [{
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...common,
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title: `${target.title}-高清增强`,
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url: String(result.original_url),
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}];
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}
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if (command.capabilityId === "image.remove_watermark") {
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const result = await requestLongTaskResult({
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endpoint: resolveCanvasRuntimeEndpoint(
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"/api/watermark-remove",
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params.requestUrl
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),
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payload: { image_url: target.sourceImageUrl },
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timeoutMs: 20 * 60 * 1000,
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headers: getCookieHeaders(params.requestHeaders),
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});
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if (!result?.success || !result.original_url) {
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throw new Error(String(result?.error || result?.detail || "去水印失败"));
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}
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return [{
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...common,
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title: `${target.title}-去水印`,
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url: String(result.original_url),
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}];
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}
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if (command.capabilityId === "image.multi_angle") {
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const result = await postRuntimeEndpoint({
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path: "/api/angle-edit",
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requestUrl: params.requestUrl,
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requestHeaders: params.requestHeaders,
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body: {
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image_url: target.sourceImageUrl,
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horizontal_angle: asFiniteNumber(command.args.horizontalAngle) ?? 30,
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vertical_angle: asFiniteNumber(command.args.verticalAngle) ?? 0,
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zoom: asFiniteNumber(command.args.zoom) ?? 0,
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},
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});
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const url = String(result.image_url || result.original_url || "").trim();
|
||||
if (!url) throw new Error("多视角服务未返回图片");
|
||||
return [{ ...common, title: `${target.title}-新视角`, url }];
|
||||
}
|
||||
|
||||
if (command.capabilityId === "image.generate_3d_model") {
|
||||
const modelVersion =
|
||||
String(command.args.modelId || command.args.modelVersion || "").trim() ||
|
||||
"tripo-standard";
|
||||
const promptText = prompt || target.title || "图生 3D 模型";
|
||||
const response = await postRuntimeEndpoint({
|
||||
path: "/api/canvas/3d/tasks",
|
||||
requestUrl: params.requestUrl,
|
||||
requestHeaders: params.requestHeaders,
|
||||
timeoutMs: 180_000,
|
||||
body: {
|
||||
taskType: "image_to_model",
|
||||
imageUrl: target.sourceImageUrl,
|
||||
imageType: inferTripoImageType(target.sourceImageUrl),
|
||||
prompt: promptText,
|
||||
modelVersion,
|
||||
faceLimit: 120_000,
|
||||
texture: true,
|
||||
pbr: true,
|
||||
autoSize: false,
|
||||
quad: false,
|
||||
generateParts: false,
|
||||
smartLowPoly: false,
|
||||
geometryQuality: "standard",
|
||||
textureQuality: "standard",
|
||||
textureAlignment: "original_image",
|
||||
orientation: "default",
|
||||
},
|
||||
});
|
||||
const task = response.data as Record<string, unknown> | undefined;
|
||||
const taskId = String(task?.taskId || "").trim();
|
||||
if (!taskId) throw new Error("3D 模型服务未返回任务 ID");
|
||||
const providerId = String(task?.providerId || "").trim() || null;
|
||||
const providerName = String(task?.providerName || "").trim() || null;
|
||||
return [
|
||||
{
|
||||
...common,
|
||||
nodeType: "model3d",
|
||||
title: `${target.title}-3D模型`,
|
||||
url: target.sourceImageUrl,
|
||||
metadata: {
|
||||
taskId,
|
||||
provider: "tripo-3d",
|
||||
mode: "image",
|
||||
status: "generating",
|
||||
sourceImageUrl: target.sourceImageUrl,
|
||||
providerId,
|
||||
providerName,
|
||||
modelVersion,
|
||||
generationStartedAt: new Date().toISOString(),
|
||||
assetPayload: {
|
||||
providerId,
|
||||
providerName,
|
||||
sourceImageUrl: target.sourceImageUrl,
|
||||
},
|
||||
},
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
if (command.capabilityId === "image.generate_3d_world") {
|
||||
const modelVersion =
|
||||
String(command.args.modelId || command.args.modelVersion || "").trim() ||
|
||||
"world-standard";
|
||||
const promptText = prompt || target.title || "图生 3D 世界";
|
||||
const formData = new FormData();
|
||||
formData.append("sourceUrl", target.sourceImageUrl);
|
||||
formData.append("kind", "image");
|
||||
const uploadResponse = await postRuntimeFormData({
|
||||
formData,
|
||||
path: "/api/canvas/world/upload",
|
||||
requestUrl: params.requestUrl,
|
||||
requestHeaders: params.requestHeaders,
|
||||
timeoutMs: 180_000,
|
||||
});
|
||||
const upload = uploadResponse.data as Record<string, unknown> | undefined;
|
||||
const mediaAssetId = String(upload?.mediaAssetId || "").trim();
|
||||
if (!mediaAssetId) throw new Error("3D 世界服务未返回媒体资源 ID");
|
||||
const providerId = String(upload?.providerId || "").trim() || null;
|
||||
const providerName = String(upload?.providerName || "").trim() || null;
|
||||
const taskResponse = await postRuntimeEndpoint({
|
||||
path: "/api/canvas/world/tasks",
|
||||
requestUrl: params.requestUrl,
|
||||
requestHeaders: params.requestHeaders,
|
||||
timeoutMs: 240_000,
|
||||
body: {
|
||||
mode: "image",
|
||||
mediaAssetId,
|
||||
providerId,
|
||||
prompt: promptText,
|
||||
displayName: target.title || promptText,
|
||||
model: modelVersion,
|
||||
disableRecaption: false,
|
||||
makePublic: false,
|
||||
},
|
||||
});
|
||||
const task = taskResponse.data as Record<string, unknown> | undefined;
|
||||
const taskId = String(task?.taskId || "").trim();
|
||||
if (!taskId) throw new Error("3D 世界服务未返回任务 ID");
|
||||
const taskAssetPayload =
|
||||
task?.assetPayload && typeof task.assetPayload === "object"
|
||||
? (task.assetPayload as Record<string, unknown>)
|
||||
: {};
|
||||
return [
|
||||
{
|
||||
...common,
|
||||
nodeType: "world3d",
|
||||
title: `${target.title}-3D世界`,
|
||||
url: target.sourceImageUrl,
|
||||
metadata: {
|
||||
taskId,
|
||||
provider: "worldlabs-3d",
|
||||
mode: "world-image",
|
||||
status: "generating",
|
||||
sourceImageUrl: target.sourceImageUrl,
|
||||
providerId,
|
||||
providerName,
|
||||
modelVersion,
|
||||
generationStartedAt: new Date().toISOString(),
|
||||
assetPayload: {
|
||||
...taskAssetPayload,
|
||||
providerId,
|
||||
providerName,
|
||||
sourceImageUrl: target.sourceImageUrl,
|
||||
},
|
||||
},
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
if (
|
||||
command.capabilityId === "image.prompt_regenerate" ||
|
||||
command.capabilityId === "image.ai_wash"
|
||||
) {
|
||||
if (!prompt) throw new Error("请提供重绘提示词");
|
||||
const model = await resolveImageModel(command.args.modelId);
|
||||
if (command.source === "agent" && command.args.agentImageMode === "pinned" &&
|
||||
command.args.modelId !== model.model.id && command.args.modelId !== model.model.modelId)
|
||||
throw new Error("指定的图片模型不可用，未切换到其他模型");
|
||||
const result = await generateCanvasImage({
|
||||
prompt,
|
||||
model: model.model.id,
|
||||
...(command.source === "agent" ? {
|
||||
agentImageMode: command.args.agentImageMode === "pinned" ? "pinned" as const : "auto" as const,
|
||||
allowFailover: command.args.agentImageMode !== "pinned",
|
||||
} : {}),
|
||||
ownerKey: params.userId,
|
||||
imageCount: 1,
|
||||
imageSize: String(command.args.imageSize || "2K"),
|
||||
aspectRatio: String(command.args.aspectRatio || "auto"),
|
||||
promptExtend: command.args.promptExtend === true,
|
||||
referenceImage: target.sourceImageUrl,
|
||||
debugLabel:
|
||||
command.capabilityId === "image.ai_wash"
|
||||
? "canvas-capability-ai-wash"
|
||||
: "canvas-capability-regenerate",
|
||||
debugMeta: {
|
||||
capabilityId: command.capabilityId,
|
||||
requestId: command.requestId,
|
||||
sourceNodeId: target.nodeId,
|
||||
},
|
||||
});
|
||||
const image = result.images[0];
|
||||
if (!image?.originalUrl) throw new Error("图片模型未返回有效结果");
|
||||
return [{
|
||||
...common,
|
||||
title:
|
||||
command.capabilityId === "image.ai_wash"
|
||||
? `${target.title}-AI洗图`
|
||||
: `${target.title}-重绘`,
|
||||
url: image.originalUrl,
|
||||
}];
|
||||
}
|
||||
|
||||
throw new Error(`尚未实现后台执行能力：${command.capabilityId}`);
|
||||
}
|
||||
|
||||
export async function executeCanvasCapabilityHeadlessly(
|
||||
params: HeadlessExecutorParams
|
||||
) {
|
||||
const results: CanvasCapabilityMediaResult[] = [];
|
||||
for (const target of params.targets) {
|
||||
results.push(...(await executeForTarget(params, target)));
|
||||
}
|
||||
return results;
|
||||
}
|
||||
|
||||
test("mixed-model batches bill and label only the delivered images using their actual models", async () => {
|
||||
const h = harness([{ originalUrl: "https://test.example/first.png", thumbnailUrl: "https://test.example/first.png", modelRef: "system-default" }, { originalUrl: "https://test.example/second.png", thumbnailUrl: "https://test.example/second.png", modelRef: "backup" }]);
|
||||
const tools = await h.build({ parameters: { imageCount: 2, imageSize: "2K" } });
|
||||
const result = await tools.executable.generateCanvasImages.execute({ prompt: "画图" }, "mixed");
|
||||
expect(h.saved).toHaveLength(2);
|
||||
expect(h.saved.map(call => call[5])).toEqual(["system-default", "backup"]);
|
||||
expect(h.saved[0][0]).toContain("first.png"); expect(h.saved[0][0]).not.toContain("second.png");
|
||||
expect(h.saved[1][0]).toContain("second.png");
|
||||
expect(h.operations[0].plan.mediaItems.map((item: any) => item.metadata.model)).toEqual(["system-default", "backup"]);
|
||||
expect(result.appliedImagePreferences.modelId).toBe("backup");
|
||||
});
|
||||
|
||||
test("headless image features cannot substitute their default when a pinned model disappears", async () => {
|
||||
let generated = 0;
|
||||
@ -494,3 +111,11 @@ test("headless image features cannot substitute their default when a pinned mode
|
||||
await expect(executeCanvasCapabilityHeadlessly({ userId: "u", requestHeaders: new Headers(), requestUrl: "https://test.example", command: { capabilityId: "image.ai_wash", source: "agent", args: { prompt: "clean image", modelId: "deleted-model", agentImageMode: "pinned" } }, targets: [{ nodeId: "source", title: "source", sourceImageUrl: "https://test.example/source.png" }] })).rejects.toThrow("指定的图片模型不可用");
|
||||
expect(generated).toBe(0);
|
||||
});
|
||||
|
||||
|
||||
test("an unavailable planner model recovers automatically with the user's image parameters", async () => {
|
||||
const h = harness(); const tools = await h.build({ parameters: { imageSize: "4K", aspectRatio: "3:4" } });
|
||||
await tools.executable.generateCanvasImages.execute({ prompt: "画图", modelId: "retired-planner-model" }, "auto-retired");
|
||||
expect(h.generated).toHaveLength(1);
|
||||
expect(h.generated[0]).toMatchObject({ model: "system-default", imageSize: "4K", aspectRatio: "3:4", allowFailover: true, agentImageMode: "auto" });
|
||||
});
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user