Hardcode is_incognito: true in the Perplexity request and remove the toggle surface: the incognito tool parameter, PI_PERPLEXITY_INCOGNITO env var, config file field, /perplexity-config prompt, and TUI status indicators. Config and resolveDefaultModel are now model-only. Supersedes the incognito portion of PR #4. Co-authored-by: Ivan Pereira <183991+ivanrvpereira@users.noreply.github.com>
118 lines
4.0 KiB
TypeScript
118 lines
4.0 KiB
TypeScript
import { afterEach, beforeEach, describe, expect, test } from "./test-helpers.js";
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import { mkdtemp, readFile, rm, stat, writeFile } from "node:fs/promises";
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import { tmpdir } from "node:os";
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import { join } from "node:path";
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let loadConfig: (configPath?: string) => Promise<import("../src/config.js").PerplexityConfig>;
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let saveConfig: (config: import("../src/config.js").PerplexityConfig, configPath?: string) => Promise<void>;
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let resolveDefaultModel: (
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config: import("../src/config.js").PerplexityConfig,
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) => string;
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let tempDir: string;
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let configPath: string;
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beforeEach(async () => {
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tempDir = await mkdtemp(join(tmpdir(), "pi-perplexity-test-"));
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configPath = join(tempDir, "config.json");
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const mod = await import(`../src/config.js?t=${Date.now()}`);
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loadConfig = mod.loadConfig;
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saveConfig = mod.saveConfig;
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resolveDefaultModel = mod.resolveDefaultModel;
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});
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afterEach(async () => {
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await rm(tempDir, { recursive: true, force: true });
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});
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describe("loadConfig", () => {
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test("returns empty object when file is missing", async () => {
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const config = await loadConfig(configPath);
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expect(config).toEqual({});
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});
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test("returns parsed config from file", async () => {
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await writeFile(configPath, JSON.stringify({ model: "gpt54" }));
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const config = await loadConfig(configPath);
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expect(config.model).toBe("gpt54");
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});
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test("throws on invalid JSON", async () => {
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await writeFile(configPath, "not json");
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await expect(loadConfig(configPath)).rejects.toThrow();
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});
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test("throws on non-object JSON", async () => {
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await writeFile(configPath, '"just a string"');
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await expect(loadConfig(configPath)).rejects.toThrow("must contain a JSON object");
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});
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test("ignores unknown fields", async () => {
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await writeFile(configPath, JSON.stringify({ model: "gpt54", unknown: true, incognito: false }));
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const config = await loadConfig(configPath);
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expect(config.model).toBe("gpt54");
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expect(config).not.toHaveProperty("unknown");
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expect(config).not.toHaveProperty("incognito");
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});
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test("ignores empty model string", async () => {
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await writeFile(configPath, JSON.stringify({ model: "" }));
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const config = await loadConfig(configPath);
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expect(config).not.toHaveProperty("model");
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});
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});
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describe("saveConfig", () => {
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test("writes file with 0600 permissions", async () => {
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await saveConfig({ model: "claude46sonnetthinking" }, configPath);
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const raw = await readFile(configPath, "utf8");
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const parsed = JSON.parse(raw);
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expect(parsed.model).toBe("claude46sonnetthinking");
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const stats = await stat(configPath);
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expect(stats.mode & 0o777).toBe(0o600);
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});
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test("creates parent directories", async () => {
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const nested = join(tempDir, "a", "b", "config.json");
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await saveConfig({ model: "gpt54" }, nested);
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const raw = await readFile(nested, "utf8");
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expect(JSON.parse(raw).model).toBe("gpt54");
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});
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});
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describe("resolveDefaultModel", () => {
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test("returns hardcoded default when no config or env", () => {
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expect(resolveDefaultModel({})).toBe("pplx_pro_upgraded");
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});
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test("config file model overrides default", () => {
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expect(resolveDefaultModel({ model: "gpt54" })).toBe("gpt54");
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});
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test("env var overrides config file", () => {
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const originalModel = process.env.PI_PERPLEXITY_MODEL;
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try {
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process.env.PI_PERPLEXITY_MODEL = "experimental";
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expect(resolveDefaultModel({ model: "gpt54" })).toBe("experimental");
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} finally {
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if (originalModel === undefined) delete process.env.PI_PERPLEXITY_MODEL;
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else process.env.PI_PERPLEXITY_MODEL = originalModel;
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}
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});
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test("whitespace-only model env var falls back to config", () => {
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const originalModel = process.env.PI_PERPLEXITY_MODEL;
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try {
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process.env.PI_PERPLEXITY_MODEL = " ";
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expect(resolveDefaultModel({ model: "gpt54" })).toBe("gpt54");
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} finally {
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if (originalModel === undefined) delete process.env.PI_PERPLEXITY_MODEL;
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else process.env.PI_PERPLEXITY_MODEL = originalModel;
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}
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});
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});
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