Initialize repository with harness code and assets
Initial import of all source code, config, and README assets: the packages workspace (cli, core, server, web, docs, landing, skills), build scripts, tooling config, and CI workflows. Includes the data-layout revision made on this branch: the local data root defaults to ~/.penguin/data (PENGUIN_HOME still overrides; the installer keeps its binaries in ~/.penguin), and every Agent lives under <project>/agents/<agent>/ — path helpers, the three agent-enumeration scans, the system prompt, built-in Skills, tests and docs all follow the new layout. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_018ihk8iQuo3kv2aPjAYEPuR
This commit is contained in:
Yaowei Zheng
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/**
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* Session title generation unit tests: prompt shape, sanitization rules, single-shot request
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* driving (fake LLM), and Session.generateTitle's composition-layer wiring (no real requests sent).
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*/
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import { describe, it, expect } from "vitest";
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import {
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assistantText,
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buildTitlePrompt,
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emptyTokenCounts,
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generateTitleWithLLM,
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sanitizeTitle,
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Session,
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thinkingMessage,
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tokenUsage,
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userText,
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} from "../src/index.js";
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import type {
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EnvironmentInterface,
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LLMInterface,
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LLMOutcome,
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OmniMessage,
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SessionMetaPayload,
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} from "../src/index.js";
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/** A fake LLM: yields the given messages and finishes with the outcome; records the prompt received. */
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function fakeLLM(
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outputs: OmniMessage[],
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outcome: LLMOutcome = { status: "completed" },
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seenPrompts: string[] = [],
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): LLMInterface {
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return {
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async *streamGenerate({ newMessages }) {
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const first = newMessages[0];
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if (first) seenPrompts.push((first.payload as { text: string }).text);
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for (const msg of outputs) yield msg;
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return outcome;
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},
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};
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}
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const fakeEnvironment: EnvironmentInterface = {
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listTools: async () => [],
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// eslint-disable-next-line require-yield
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executeTool: async function* () {
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throw new Error("not used");
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},
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toolPermission: () => undefined,
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};
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const META: SessionMetaPayload = {
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session_id: "session-title-1",
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provider: "custom",
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model_id: "m1",
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model_context_window: 1000,
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system_prompt: "sp",
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tools: [],
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thinking_level: "default",
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agent_state: "/tmp/state",
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workspace: "/tmp/w",
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};
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describe("session-title", () => {
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it("generateTitleWithLLM：收集模型 text 与用量，清洗后返回", async () => {
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const seen: string[] = [];
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const result = await generateTitleWithLLM(
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fakeLLM(
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[
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thinkingMessage("想一下"), // thinking does not count
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assistantText("「Tailwind 主题配置」。"),
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tokenUsage(emptyTokenCounts(), { cache_read: 1, cache_write: 2, output: 3, total: 6 }),
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],
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{ status: "completed" },
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seen,
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),
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{ userText: "解释 @theme", assistantText: "好的……" },
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);
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expect(result.title).toBe("Tailwind 主题配置");
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expect(result.usage).toEqual({ cache_read: 1, cache_write: 2, output: 3, total: 6 });
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expect(seen[0]).toBe(buildTitlePrompt("解释 @theme", "好的……"));
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expect(seen[0]).toContain("SAME language");
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});
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it("素材为空不发请求；outcome 非 completed 时 title 为 null（usage 保留）", async () => {
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const seen: string[] = [];
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const empty = await generateTitleWithLLM(fakeLLM([], { status: "completed" }, seen), {
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userText: " ",
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assistantText: "a",
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});
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expect(empty).toEqual({ title: null, usage: null });
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expect(seen).toHaveLength(0);
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const failed = await generateTitleWithLLM(
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fakeLLM(
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[
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assistantText("半截"),
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tokenUsage(emptyTokenCounts(), { cache_read: 0, cache_write: 0, output: 1, total: 1 }),
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],
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{ status: "failed", message: "401" },
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),
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{ userText: "u", assistantText: "a" },
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);
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expect(failed.title).toBeNull();
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expect(failed.usage?.total).toBe(1);
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});
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it("助手素材为空也生成（纯工具轮次）：只据用户请求，prompt 省去助手段", async () => {
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const seen: string[] = [];
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const result = await generateTitleWithLLM(
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fakeLLM([assistantText("配置 Tailwind 主题")], { status: "completed" }, seen),
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{ userText: "帮我配置 @theme", assistantText: "" },
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);
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expect(result.title).toBe("配置 Tailwind 主题");
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expect(seen[0]).toBe(buildTitlePrompt("帮我配置 @theme", ""));
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expect(seen[0]).not.toContain("[Assistant]");
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});
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it("sanitizeTitle：剥引号与句读到稳定、折叠空白、超长截断、空返回 null", () => {
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expect(sanitizeTitle("“ 构建配置 说明 。”")).toBe("构建配置 说明");
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expect(sanitizeTitle("『标题』！")).toBe("标题");
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expect(sanitizeTitle(" \n ")).toBeNull();
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expect(sanitizeTitle("x".repeat(50))).toHaveLength(30);
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});
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it("Session.generateTitle：经 createBareLLM 发起；未提供工厂时返回 null", async () => {
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const withFactory = new Session({
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meta: META,
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llm: fakeLLM([]),
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environment: fakeEnvironment,
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createBareLLM: () => fakeLLM([assistantText("标题 A")]),
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});
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expect(
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await withFactory.generateTitle({ material: { userText: "u", assistantText: "a" } }),
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).toEqual({
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title: "标题 A",
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usage: null,
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});
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const withoutFactory = new Session({
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meta: META,
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llm: fakeLLM([]),
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environment: fakeEnvironment,
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});
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expect(await withoutFactory.generateTitle()).toEqual({
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title: null,
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usage: null,
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});
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});
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it("Session.generateTitle：素材自采（run 收集用户输入与模型正文），无需调用方提供", async () => {
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const seen: string[] = [];
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const session = new Session({
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meta: META,
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llm: fakeLLM([thinkingMessage("想想"), assistantText("答案正文")]),
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environment: fakeEnvironment,
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createBareLLM: () => fakeLLM([assistantText("标题 B")], { status: "completed" }, seen),
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});
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for await (const _ of session.run([userText("用户问题")])) {
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void _; // Drains the output stream; once run finishes, the material is settled
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}
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const res = await session.generateTitle();
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expect(res.title).toBe("标题 B");
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// Material = the first Task's user text + model text (thinking does not count), matching
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// buildTitlePrompt's shape.
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expect(seen[0]).toBe(buildTitlePrompt("用户问题", "答案正文"));
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// No request is sent when no material has been collected (run was never called).
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const idle = new Session({
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meta: META,
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llm: fakeLLM([]),
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environment: fakeEnvironment,
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createBareLLM: () => fakeLLM([assistantText("不应产生")]),
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});
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expect(await idle.generateTitle()).toEqual({ title: null, usage: null });
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});
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});
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