wehub-resource-sync
104 lines
3.0 KiB
TypeScript
104 lines
3.0 KiB
TypeScript
import test from "node:test";
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import assert from "node:assert/strict";
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import {
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resolveHfPipelineTag,
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sortHfSuggestedModels,
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type HfModelSummary,
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} from "../../open-sse/services/hfModelSuggestions.ts";
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test("resolveHfPipelineTag: maps the 'image' kind to HF's text-to-image pipeline_tag", () => {
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assert.equal(resolveHfPipelineTag("image"), "text-to-image");
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});
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test("resolveHfPipelineTag: returns null for an unmapped kind", () => {
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assert.equal(resolveHfPipelineTag("video"), null);
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assert.equal(resolveHfPipelineTag("does-not-exist"), null);
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});
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test("sortHfSuggestedModels: sorts descending by downloads (default)", () => {
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const models: HfModelSummary[] = [
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{ id: "a/low", downloads: 10, likes: 500 },
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{ id: "b/high", downloads: 1000, likes: 1 },
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{ id: "c/mid", downloads: 100, likes: 50 },
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];
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const result = sortHfSuggestedModels(models);
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assert.deepEqual(
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result.map((m) => m.id),
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["b/high", "c/mid", "a/low"]
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);
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});
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test("sortHfSuggestedModels: sorts descending by likes when requested", () => {
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const models: HfModelSummary[] = [
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{ id: "a/low", downloads: 10, likes: 500 },
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{ id: "b/high", downloads: 1000, likes: 1 },
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{ id: "c/mid", downloads: 100, likes: 50 },
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];
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const result = sortHfSuggestedModels(models, "likes");
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assert.deepEqual(
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result.map((m) => m.id),
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["a/low", "c/mid", "b/high"]
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);
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});
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test("sortHfSuggestedModels: caps results at the requested limit", () => {
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const models: HfModelSummary[] = Array.from({ length: 30 }, (_, i) => ({
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id: `model/${i}`,
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downloads: i,
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}));
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const result = sortHfSuggestedModels(models, "downloads", 5);
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assert.equal(result.length, 5);
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// Highest downloads (29..25) come first
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assert.deepEqual(
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result.map((m) => m.id),
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["model/29", "model/28", "model/27", "model/26", "model/25"]
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);
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});
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test("sortHfSuggestedModels: drops entries without a usable string id", () => {
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const models = [
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{ id: "", downloads: 999 },
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{ id: " ", downloads: 998 },
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{ downloads: 997 },
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{ id: "valid/model", downloads: 1 },
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] as HfModelSummary[];
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const result = sortHfSuggestedModels(models);
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assert.deepEqual(
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result.map((m) => m.id),
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["valid/model"]
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);
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});
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test("sortHfSuggestedModels: treats missing/non-numeric metric values as 0 (no throw)", () => {
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const models = [
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{ id: "a/no-metric" },
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{ id: "b/has-metric", downloads: 5 },
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{ id: "c/nan-metric", downloads: Number.NaN },
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] as HfModelSummary[];
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const result = sortHfSuggestedModels(models, "downloads");
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assert.deepEqual(
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result.map((m) => m.id),
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["b/has-metric", "a/no-metric", "c/nan-metric"]
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);
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});
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test("sortHfSuggestedModels: handles an empty input array", () => {
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assert.deepEqual(sortHfSuggestedModels([]), []);
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});
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test("sortHfSuggestedModels: falls back to a default limit for an invalid limit value", () => {
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const models: HfModelSummary[] = Array.from({ length: 25 }, (_, i) => ({
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id: `model/${i}`,
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downloads: i,
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}));
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const result = sortHfSuggestedModels(models, "downloads", 0);
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assert.equal(result.length, 20);
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});
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