import { beforeAll, describe, expect, test } from "bun:test";
import type { Model } from "@oh-my-pi/pi-ai";
import { buildModel } from "@oh-my-pi/pi-catalog/build";
import { Settings } from "@oh-my-pi/pi-coding-agent/config/settings";
import {
	buildBrowserItems,
	ModelBrowser,
	sortModelItems,
} from "@oh-my-pi/pi-coding-agent/modes/components/model-browser";
import { initTheme } from "@oh-my-pi/pi-coding-agent/modes/theme/theme";

function makeModel(provider: string, id: string): Model {
	return buildModel({
		id,
		name: id,
		api: "ollama-chat",
		provider,
		baseUrl: "https://example.com",
		reasoning: false,
		input: ["text"],
		cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
		contextWindow: 128_000,
		maxTokens: 1024,
	});
}

/** Browser preloaded with `models`, MRU-sorted like the hub does on sync. */
function makeBrowser(models: Model[], mruOrder: string[]): ModelBrowser {
	const browser = new ModelBrowser(Settings.isolated({}));
	const items = buildBrowserItems(models);
	sortModelItems(items, { mruOrder });
	browser.setMruOrder(mruOrder);
	browser.setItems(items);
	return browser;
}

describe("ModelBrowser search ranking", () => {
	test("an exact query match outranks the MRU model", () => {
		// Regression: with gpt-5.6-sol as the active (MRU) model, typing
		// "gpt-5.5" must select gpt-5.5, not keep the MRU pinned on top.
		const browser = makeBrowser(
			[
				makeModel("openai-codex", "gpt-5.6-sol"),
				makeModel("openai-codex", "gpt-5.6-luna"),
				makeModel("openai-codex", "gpt-5.5"),
				makeModel("openai-codex", "gpt-5.4"),
			],
			["openai-codex/gpt-5.6-sol", "openai-codex/gpt-5.6-luna"],
		);

		browser.setQuery("gpt-5.5");

		expect(browser.getSelected()?.selector).toBe("openai-codex/gpt-5.5");
	});

	test("MRU breaks ties between equally good matches", () => {
		// Same model id under two providers: match quality is identical, so
		// the recently used provider must win over alphabetical order.
		const browser = makeBrowser([makeModel("g0i", "gpt-5.5"), makeModel("zenmux", "gpt-5.5")], ["zenmux/gpt-5.5"]);

		browser.setQuery("gpt-5.5");

		expect(browser.getSelected()?.selector).toBe("zenmux/gpt-5.5");
	});
});

describe("ModelBrowser perf display", () => {
	beforeAll(async () => {
		// render() reads the global theme singleton.
		await initTheme(false);
	});

	function makePerfBrowser(): ModelBrowser {
		const browser = new ModelBrowser(Settings.isolated({}));
		browser.setItems(buildBrowserItems([makeModel("openai", "gpt-5")]));
		browser.setPerfStats(new Map([["openai/gpt-5", { samples: 12, tps: 118.4, ttftMs: 930 }]]));
		return browser;
	}

	function renderPlain(browser: ModelBrowser, width: number): string[] {
		return browser.render(width).map(line => Bun.stripANSI(line));
	}

	test("row perf column scales with width: off, TPS-only, TTFT+TPS", () => {
		const browser = makePerfBrowser();

		expect(renderPlain(browser, 70)[2]).not.toContain("t/s");
		expect(renderPlain(browser, 80)[2]).toContain("118t/s");
		const wideRow = renderPlain(browser, 120)[2];
		expect(wideRow).toContain("0.9s 118t/s");
	});

	test("detail line shows measured perf regardless of width", () => {
		const browser = makePerfBrowser();

		const lines = renderPlain(browser, 70);
		expect(lines[lines.length - 2]).toContain("~118t/s · 0.9s ttft");
	});

	test("models without measurements render no perf cell", () => {
		const browser = new ModelBrowser(Settings.isolated({}));
		browser.setItems(buildBrowserItems([makeModel("openai", "gpt-5")]));

		expect(renderPlain(browser, 120)[2]).not.toContain("t/s");
	});
});