refactor(src): split oversized modules
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161
src/agents/pi-embedded-runner.applygoogleturnorderingfix.test.ts
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161
src/agents/pi-embedded-runner.applygoogleturnorderingfix.test.ts
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import fs from "node:fs/promises";
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import type { AgentMessage } from "@mariozechner/pi-agent-core";
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import { SessionManager } from "@mariozechner/pi-coding-agent";
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import { describe, expect, it, vi } from "vitest";
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import type { ClawdbotConfig } from "../config/config.js";
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import { ensureClawdbotModelsJson } from "./models-config.js";
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import { applyGoogleTurnOrderingFix } from "./pi-embedded-runner.js";
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vi.mock("@mariozechner/pi-ai", async () => {
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const actual = await vi.importActual<typeof import("@mariozechner/pi-ai")>(
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"@mariozechner/pi-ai",
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);
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return {
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...actual,
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streamSimple: (model: { api: string; provider: string; id: string }) => {
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if (model.id === "mock-error") {
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throw new Error("boom");
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}
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const stream = new actual.AssistantMessageEventStream();
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queueMicrotask(() => {
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stream.push({
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type: "done",
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reason: "stop",
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message: {
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role: "assistant",
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content: [{ type: "text", text: "ok" }],
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stopReason: "stop",
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api: model.api,
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provider: model.provider,
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model: model.id,
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usage: {
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input: 1,
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output: 1,
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cacheRead: 0,
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cacheWrite: 0,
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totalTokens: 2,
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cost: {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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total: 0,
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},
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},
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timestamp: Date.now(),
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},
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});
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});
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return stream;
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},
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};
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});
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const _makeOpenAiConfig = (modelIds: string[]) =>
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({
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models: {
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providers: {
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openai: {
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api: "openai-responses",
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apiKey: "sk-test",
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baseUrl: "https://example.com",
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models: modelIds.map((id) => ({
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id,
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name: `Mock ${id}`,
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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: 16_000,
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maxTokens: 2048,
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})),
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},
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},
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},
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}) satisfies ClawdbotConfig;
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const _ensureModels = (cfg: ClawdbotConfig, agentDir: string) =>
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ensureClawdbotModelsJson(cfg, agentDir);
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const _textFromContent = (content: unknown) => {
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if (typeof content === "string") return content;
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if (Array.isArray(content) && content[0]?.type === "text") {
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return (content[0] as { text?: string }).text;
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}
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return undefined;
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};
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const _readSessionMessages = async (sessionFile: string) => {
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const raw = await fs.readFile(sessionFile, "utf-8");
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return raw
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.split(/\r?\n/)
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.filter(Boolean)
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.map(
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(line) =>
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JSON.parse(line) as {
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type?: string;
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message?: { role?: string; content?: unknown };
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},
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)
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.filter((entry) => entry.type === "message")
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.map((entry) => entry.message as { role?: string; content?: unknown });
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};
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describe("applyGoogleTurnOrderingFix", () => {
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const makeAssistantFirst = () =>
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[
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{
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role: "assistant",
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content: [
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{ type: "toolCall", id: "call_1", name: "exec", arguments: {} },
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],
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},
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] satisfies AgentMessage[];
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it("prepends a bootstrap once and records a marker for Google models", () => {
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const sessionManager = SessionManager.inMemory();
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const warn = vi.fn();
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const input = makeAssistantFirst();
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const first = applyGoogleTurnOrderingFix({
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messages: input,
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modelApi: "google-generative-ai",
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sessionManager,
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sessionId: "session:1",
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warn,
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});
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expect(first.messages[0]?.role).toBe("user");
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expect(first.messages[1]?.role).toBe("assistant");
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expect(warn).toHaveBeenCalledTimes(1);
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expect(
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sessionManager
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.getEntries()
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.some(
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(entry) =>
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entry.type === "custom" &&
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entry.customType === "google-turn-ordering-bootstrap",
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),
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).toBe(true);
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applyGoogleTurnOrderingFix({
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messages: input,
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modelApi: "google-generative-ai",
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sessionManager,
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sessionId: "session:1",
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warn,
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});
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expect(warn).toHaveBeenCalledTimes(1);
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});
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it("skips non-Google models", () => {
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const sessionManager = SessionManager.inMemory();
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const warn = vi.fn();
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const input = makeAssistantFirst();
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const result = applyGoogleTurnOrderingFix({
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messages: input,
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modelApi: "openai",
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sessionManager,
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sessionId: "session:2",
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warn,
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});
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expect(result.messages).toBe(input);
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expect(warn).not.toHaveBeenCalled();
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});
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});
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