Mohamed Boudra
29ce6653fd
Keep sheet text inputs native-owned to avoid React Native controlled input flicker during fast typing. Add reset keys for fields that need programmatic clears, and move model, mode, and thinking pickers onto shared combobox rows with fuzzy ranked search and native virtualization.
120 lines
3.1 KiB
TypeScript
120 lines
3.1 KiB
TypeScript
import { describe, expect, it } from "vitest";
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import type { AgentModelDefinition } from "@server/server/agent/agent-sdk-types";
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import {
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buildModelRows,
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buildSelectedTriggerLabel,
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filterAndRankModelRows,
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matchesSearch,
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resolveProviderLabel,
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} from "./combined-model-selector.utils";
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describe("combined model selector helpers", () => {
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const providerDefinitions = [
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{
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id: "claude",
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label: "Claude",
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description: "Claude provider",
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defaultModeId: "default",
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modes: [],
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},
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{
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id: "codex",
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label: "Codex",
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description: "Codex provider",
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defaultModeId: "auto",
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modes: [],
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},
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];
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const claudeModels: AgentModelDefinition[] = [
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{
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provider: "claude",
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id: "sonnet-4.6",
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label: "Sonnet 4.6",
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},
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];
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const codexModels: AgentModelDefinition[] = [
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{
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provider: "codex",
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id: "gpt-5.4",
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label: "GPT-5.4",
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},
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];
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it("keeps enough data to search by model and provider name", async () => {
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const rows = buildModelRows(
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providerDefinitions,
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new Map([
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["claude", claudeModels],
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["codex", codexModels],
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]),
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);
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expect(rows).toEqual([
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expect.objectContaining({
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providerLabel: "Claude",
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modelLabel: "Sonnet 4.6",
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modelId: "sonnet-4.6",
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}),
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expect.objectContaining({
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providerLabel: "Codex",
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modelLabel: "GPT-5.4",
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modelId: "gpt-5.4",
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}),
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]);
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expect(matchesSearch(rows[0], "claude")).toBe(true);
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expect(matchesSearch(rows[1], "gpt-5.4")).toBe(true);
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});
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it("matches across label, provider, and description with multi-token fuzzy search", () => {
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const row = {
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favoriteKey: "opencode:opencode-zen/kimi-k2.5",
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provider: "opencode",
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providerLabel: "OpenCode",
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modelId: "opencode-zen/kimi-k2.5",
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modelLabel: "Kimi K2.5",
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description: "OpenCode Zen - kimi",
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};
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expect(matchesSearch(row, "kimi zen")).toBe(true);
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expect(matchesSearch(row, "zen kimi")).toBe(true);
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expect(matchesSearch(row, "k2.5 zen")).toBe(true);
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expect(matchesSearch(row, "kimi gemini")).toBe(false);
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});
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it("ranks model search results by fuzzy match quality", () => {
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const rows = [
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{
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favoriteKey: "openai:gpt-4.1",
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provider: "openai",
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providerLabel: "OpenAI",
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modelId: "gpt-4.1",
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modelLabel: "GPT-4.1",
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},
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{
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favoriteKey: "openai:gpt-5.4",
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provider: "openai",
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providerLabel: "OpenAI",
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modelId: "gpt-5.4",
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modelLabel: "GPT-5.4",
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},
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{
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favoriteKey: "google:gemini",
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provider: "google",
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providerLabel: "Google",
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modelId: "gemini",
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modelLabel: "Gemini",
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},
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];
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expect(filterAndRankModelRows(rows, "gpt54").map((row) => row.modelId)).toEqual(["gpt-5.4"]);
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});
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it("keeps the selected trigger label model-only", () => {
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expect(resolveProviderLabel(providerDefinitions, "codex")).toBe("Codex");
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expect(buildSelectedTriggerLabel("GPT-5.4")).toBe("GPT-5.4");
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});
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});
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