wehub-resource-sync
107 lines
3.5 KiB
TypeScript
107 lines
3.5 KiB
TypeScript
import { beforeAll, describe, expect, test } from "bun:test";
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import type { Model } from "@oh-my-pi/pi-ai";
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import { buildModel } from "@oh-my-pi/pi-catalog/build";
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import { Settings } from "@oh-my-pi/pi-coding-agent/config/settings";
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import {
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buildBrowserItems,
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ModelBrowser,
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sortModelItems,
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} from "@oh-my-pi/pi-coding-agent/modes/components/model-browser";
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import { initTheme } from "@oh-my-pi/pi-coding-agent/modes/theme/theme";
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function makeModel(provider: string, id: string): Model {
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return buildModel({
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id,
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name: id,
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api: "ollama-chat",
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provider,
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baseUrl: "https://example.com",
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reasoning: false,
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input: ["text"],
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
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contextWindow: 128_000,
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maxTokens: 1024,
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});
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}
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/** Browser preloaded with `models`, MRU-sorted like the hub does on sync. */
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function makeBrowser(models: Model[], mruOrder: string[]): ModelBrowser {
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const browser = new ModelBrowser(Settings.isolated({}));
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const items = buildBrowserItems(models);
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sortModelItems(items, { mruOrder });
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browser.setMruOrder(mruOrder);
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browser.setItems(items);
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return browser;
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}
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describe("ModelBrowser search ranking", () => {
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test("an exact query match outranks the MRU model", () => {
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// Regression: with gpt-5.6-sol as the active (MRU) model, typing
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// "gpt-5.5" must select gpt-5.5, not keep the MRU pinned on top.
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const browser = makeBrowser(
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[
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makeModel("openai-codex", "gpt-5.6-sol"),
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makeModel("openai-codex", "gpt-5.6-luna"),
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makeModel("openai-codex", "gpt-5.5"),
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makeModel("openai-codex", "gpt-5.4"),
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],
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["openai-codex/gpt-5.6-sol", "openai-codex/gpt-5.6-luna"],
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);
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browser.setQuery("gpt-5.5");
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expect(browser.getSelected()?.selector).toBe("openai-codex/gpt-5.5");
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});
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test("MRU breaks ties between equally good matches", () => {
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// Same model id under two providers: match quality is identical, so
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// the recently used provider must win over alphabetical order.
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const browser = makeBrowser([makeModel("g0i", "gpt-5.5"), makeModel("zenmux", "gpt-5.5")], ["zenmux/gpt-5.5"]);
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browser.setQuery("gpt-5.5");
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expect(browser.getSelected()?.selector).toBe("zenmux/gpt-5.5");
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});
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});
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describe("ModelBrowser perf display", () => {
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beforeAll(async () => {
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// render() reads the global theme singleton.
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await initTheme(false);
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});
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function makePerfBrowser(): ModelBrowser {
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const browser = new ModelBrowser(Settings.isolated({}));
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browser.setItems(buildBrowserItems([makeModel("openai", "gpt-5")]));
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browser.setPerfStats(new Map([["openai/gpt-5", { samples: 12, tps: 118.4, ttftMs: 930 }]]));
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return browser;
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}
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function renderPlain(browser: ModelBrowser, width: number): string[] {
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return browser.render(width).map(line => Bun.stripANSI(line));
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}
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test("row perf column scales with width: off, TPS-only, TTFT+TPS", () => {
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const browser = makePerfBrowser();
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expect(renderPlain(browser, 70)[2]).not.toContain("t/s");
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expect(renderPlain(browser, 80)[2]).toContain("118t/s");
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const wideRow = renderPlain(browser, 120)[2];
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expect(wideRow).toContain("0.9s 118t/s");
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});
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test("detail line shows measured perf regardless of width", () => {
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const browser = makePerfBrowser();
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const lines = renderPlain(browser, 70);
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expect(lines[lines.length - 2]).toContain("~118t/s · 0.9s ttft");
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});
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test("models without measurements render no perf cell", () => {
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const browser = new ModelBrowser(Settings.isolated({}));
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browser.setItems(buildBrowserItems([makeModel("openai", "gpt-5")]));
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expect(renderPlain(browser, 120)[2]).not.toContain("t/s");
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});
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});
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