2569718930@qq.com
51 lines
1.7 KiB
TypeScript
51 lines
1.7 KiB
TypeScript
import fs from "node:fs";
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import path from "node:path";
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function assert(condition: unknown, message: string) {
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if (!condition) throw new Error(message);
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}
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export function runTests() {
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const projectRoot = process.cwd();
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const workspacePath = path.join(
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projectRoot,
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"components",
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"dashboard",
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"scan-terminal",
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"use-ai-pinned-city-workspace.ts",
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);
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const storePath = path.join(projectRoot, "hooks", "useDashboardStore.tsx");
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const cardPath = path.join(
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projectRoot,
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"components",
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"dashboard",
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"scan-terminal",
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"AiPinnedCityCard.tsx",
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);
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const source = fs.readFileSync(workspacePath, "utf8");
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const storeSource = fs.readFileSync(storePath, "utf8");
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const cardSource = fs.readFileSync(cardPath, "utf8");
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assert(
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!source.includes("waitForDeepAnalysisQueue"),
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"decision-card deep analysis hydration must not add an artificial queue delay",
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);
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assert(
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/store\.ensureCityDetail\(\s*nextCity,\s*false,\s*"full",?\s*\)/.test(source),
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"automatic deep analysis hydration should use cache-friendly full detail requests",
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);
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assert(
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storeSource.includes("row.model_cluster_sources") &&
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storeSource.includes("deb_prediction") &&
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storeSource.includes("multi_model: multiModel"),
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"decision-card preload must hydrate model cluster and DEB data from the scan row",
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);
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assert(
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cardSource.includes("getRowModelEntries") &&
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cardSource.includes("row?.ai_predicted_max") &&
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cardSource.includes("row?.cluster_median") &&
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cardSource.includes("detailModelEntries.length ? detailModelEntries : getRowModelEntries(row)"),
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"decision card should render model support and AI predicted max from the row before full detail/AI stream arrives",
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);
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}
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