can1357
1399 lines
43 KiB
TypeScript
1399 lines
43 KiB
TypeScript
/**
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* Tests for AgentSession concurrent prompt guard.
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*/
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import { afterEach, beforeEach, describe, expect, it, vi } from "bun:test";
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import * as fs from "node:fs";
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import * as os from "node:os";
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import * as path from "node:path";
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import { Agent, AgentBusyError, type AgentTool } from "@oh-my-pi/pi-agent-core";
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import { type AssistantMessage, getBundledModel, type Message, type ToolCall } from "@oh-my-pi/pi-ai";
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import { createMockModel } from "@oh-my-pi/pi-ai/providers/mock";
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import { AssistantMessageEventStream } from "@oh-my-pi/pi-ai/utils/event-stream";
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import { AsyncJobManager } from "@oh-my-pi/pi-coding-agent/async";
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import type { Rule } from "@oh-my-pi/pi-coding-agent/capability/rule";
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import { ModelRegistry } from "@oh-my-pi/pi-coding-agent/config/model-registry";
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import { Settings } from "@oh-my-pi/pi-coding-agent/config/settings";
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import { TtsrManager } from "@oh-my-pi/pi-coding-agent/export/ttsr";
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import { AgentSession } from "@oh-my-pi/pi-coding-agent/session/agent-session";
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import { AuthStorage } from "@oh-my-pi/pi-coding-agent/session/auth-storage";
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import { convertToLlm } from "@oh-my-pi/pi-coding-agent/session/messages";
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import { SessionManager } from "@oh-my-pi/pi-coding-agent/session/session-manager";
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import { Snowflake } from "@oh-my-pi/pi-utils";
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import * as z from "zod/v4";
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import { createAssistantMessage } from "./helpers/agent-session-setup";
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// Mock stream that mimics AssistantMessageEventStream
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describe("AgentSession concurrent prompt guard", () => {
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let session: AgentSession;
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let tempDir: string;
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const authStorages: AuthStorage[] = [];
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beforeEach(() => {
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tempDir = path.join(os.tmpdir(), `pi-concurrent-test-${Snowflake.next()}`);
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fs.mkdirSync(tempDir, { recursive: true });
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});
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afterEach(async () => {
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if (session) {
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await session.dispose();
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}
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for (const authStorage of authStorages.splice(0)) {
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authStorage.close();
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}
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if (tempDir && fs.existsSync(tempDir)) {
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fs.rmSync(tempDir, { recursive: true });
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}
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vi.restoreAllMocks();
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AsyncJobManager.resetForTests();
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});
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async function createSession() {
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const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
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let abortSignal: AbortSignal | undefined;
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// Use a stream function that responds to abort
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const agent = new Agent({
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getApiKey: () => "test-key",
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initialState: {
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model,
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systemPrompt: ["Test"],
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tools: [],
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},
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streamFn: (_model, _context, options) => {
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abortSignal = options?.signal;
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const stream = new AssistantMessageEventStream();
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queueMicrotask(() => {
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stream.push({ type: "start", partial: createAssistantMessage("") });
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if (abortSignal) {
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abortSignal.addEventListener(
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"abort",
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() => {
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stream.push({ type: "error", reason: "aborted", error: createAssistantMessage("Aborted") });
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},
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{ once: true },
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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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const sessionManager = SessionManager.inMemory();
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const settings = Settings.isolated();
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const authStorage = await AuthStorage.create(path.join(tempDir, "testauth.db"));
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authStorages.push(authStorage);
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const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
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authStorage.setRuntimeApiKey("anthropic", "test-key");
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session = new AgentSession({
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agent,
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sessionManager,
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settings,
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modelRegistry,
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});
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return session;
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}
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async function waitFor(predicate: () => boolean, timeoutMs = 500): Promise<void> {
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const deadline = Date.now() + timeoutMs;
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while (Date.now() < deadline) {
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if (predicate()) return;
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await Bun.sleep(10);
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}
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throw new Error("Timed out waiting for condition");
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}
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it("should throw when prompt() called while streaming", async () => {
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await createSession();
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// Start first prompt (don't await, it will block until abort)
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const firstPrompt = session.prompt("First message");
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await waitFor(() => session.isStreaming);
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// Second prompt should reject
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await expect(session.prompt("Second message")).rejects.toBeInstanceOf(AgentBusyError);
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// Cleanup
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await session.abort();
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await firstPrompt.catch(() => {}); // Ignore abort error
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});
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it("should allow steer() while streaming", async () => {
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await createSession();
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// Start first prompt
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const firstPrompt = session.prompt("First message");
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await waitFor(() => session.isStreaming);
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// steer should work while streaming
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expect(() => session.steer("Steering message")).not.toThrow();
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expect(session.queuedMessageCount).toBe(1);
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// Cleanup
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await session.abort();
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await firstPrompt.catch(() => {});
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});
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it("should allow followUp() while streaming", async () => {
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await createSession();
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// Start first prompt
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const firstPrompt = session.prompt("First message");
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await waitFor(() => session.isStreaming);
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// followUp should work while streaming
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expect(() => session.followUp("Follow-up message")).not.toThrow();
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expect(session.queuedMessageCount).toBe(1);
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// Cleanup
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await session.abort();
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await firstPrompt.catch(() => {});
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});
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it("delivers hidden nextTurn stop reactions through the next LLM call without exposing them in the visible queue", async () => {
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const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
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let firstStream: AssistantMessageEventStream | undefined;
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const callMessages: Message[][] = [];
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const agent = new Agent({
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getApiKey: () => "test-key",
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initialState: {
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model,
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systemPrompt: ["Test"],
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tools: [],
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},
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convertToLlm,
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streamFn: (_model, context) => {
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callMessages.push([...context.messages]);
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const stream = new AssistantMessageEventStream();
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queueMicrotask(() => {
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stream.push({ type: "start", partial: createAssistantMessage("") });
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if (callMessages.length > 1) {
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stream.push({ type: "done", reason: "stop", message: createAssistantMessage("Resumed") });
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return;
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}
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});
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firstStream = stream;
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return stream;
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},
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});
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const sessionManager = SessionManager.inMemory();
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const settings = Settings.isolated();
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const authStorage = await AuthStorage.create(path.join(tempDir, "testauth.db"));
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authStorages.push(authStorage);
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const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
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authStorage.setRuntimeApiKey("anthropic", "test-key");
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session = new AgentSession({
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agent,
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sessionManager,
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settings,
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modelRegistry,
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});
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const firstPrompt = session.prompt("First message");
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await waitFor(() => session.isStreaming && firstStream !== undefined && callMessages.length === 1);
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await session.sendCustomMessage(
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{
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customType: "autoresearch-resume",
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content: "Hidden stop reaction",
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display: false,
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attribution: "agent",
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},
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{ deliverAs: "nextTurn", triggerTurn: true },
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);
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expect(session.queuedMessageCount).toBe(0);
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expect(session.getQueuedMessages()).toEqual({ steering: [], followUp: [] });
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firstStream?.push({ type: "done", reason: "stop", message: createAssistantMessage("Done") });
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await firstPrompt;
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await session.waitForIdle();
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expect(callMessages).toHaveLength(2);
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expect(
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callMessages[1]?.some(message => {
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if (typeof message.content === "string") {
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return message.content.includes("Hidden stop reaction");
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}
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return message.content.some(
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content => content.type === "text" && content.text.includes("Hidden stop reaction"),
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);
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}),
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).toBe(true);
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});
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it("should allow prompt() after previous completes", async () => {
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// Create session with a stream that completes immediately
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const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
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const mock = createMockModel({ handler: () => ({ content: ["Done"] }) });
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const agent = new Agent({
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getApiKey: () => "test-key",
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initialState: {
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model,
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systemPrompt: ["Test"],
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tools: [],
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},
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streamFn: mock.stream,
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});
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const sessionManager = SessionManager.inMemory();
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const settings = Settings.isolated();
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const authStorage = await AuthStorage.create(path.join(tempDir, "testauth.db"));
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authStorages.push(authStorage);
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const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
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authStorage.setRuntimeApiKey("anthropic", "test-key");
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session = new AgentSession({
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agent,
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sessionManager,
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settings,
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modelRegistry,
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});
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// First prompt completes
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await session.prompt("First message");
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// Should not be streaming anymore
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expect(session.isStreaming).toBe(false);
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// Second prompt should work
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await expect(session.prompt("Second message")).resolves.toBeUndefined();
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});
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it("queues extension follow-up user messages on an idle session without starting a turn", async () => {
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const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
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const mock = createMockModel({ handler: () => ({ content: ["Done"] }) });
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const agent = new Agent({
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getApiKey: () => "test-key",
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initialState: {
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model,
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systemPrompt: ["Test"],
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tools: [],
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},
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streamFn: mock.stream,
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});
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const sessionManager = SessionManager.inMemory();
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const settings = Settings.isolated();
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const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-idle-followup.db"));
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authStorages.push(authStorage);
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const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models-idle-followup.yml"));
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authStorage.setRuntimeApiKey("anthropic", "test-key");
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session = new AgentSession({
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agent,
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sessionManager,
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settings,
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modelRegistry,
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});
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await session.sendUserMessage("hello from session_start", { deliverAs: "followUp" });
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expect(mock.calls).toHaveLength(0);
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expect(session.queuedMessageCount).toBe(1);
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});
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// Regression: a subscriber that fires the next prompt synchronously from the
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// agent_end listener (the shape every wire transport ends up in — rpc-mode
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// stdout subscriber, ACP bridge, Cursor exec) must not collide with the
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// outgoing turn's still-unwinding in-flight bookkeeping. Before the wire-level
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// agent_end was deferred until #promptInFlightCount drops to 0, the
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// subscriber observed agent_end while Session.isStreaming was still true (the
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// agent's own `isStreaming` had flipped, but #promptWithMessage's finally had
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// not yet decremented the prompt-in-flight counter), and the next prompt
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// threw AgentBusyError. Surfaced as `RpcCommandError: prompt: Agent is
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// already processing` from omp-rpc clients (robomp triage reminder path).
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it("subscriber may prompt() synchronously from agent_end without AgentBusyError", async () => {
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const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
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const mock = createMockModel({ handler: () => ({ content: ["Done"] }) });
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const agent = new Agent({
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getApiKey: () => "test-key",
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initialState: { model, systemPrompt: ["Test"], tools: [] },
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streamFn: mock.stream,
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});
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const sessionManager = SessionManager.inMemory();
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const settings = Settings.isolated();
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const authStorage = await AuthStorage.create(path.join(tempDir, "testauth.db"));
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authStorages.push(authStorage);
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const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
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authStorage.setRuntimeApiKey("anthropic", "test-key");
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session = new AgentSession({ agent, sessionManager, settings, modelRegistry });
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const observedIsStreamingAtAgentEnd: boolean[] = [];
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const reentrantPromptResults: Array<"resolved" | { error: string }> = [];
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let reentrantPrompted = false;
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session.subscribe(event => {
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if (event.type !== "agent_end") return;
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observedIsStreamingAtAgentEnd.push(session.isStreaming);
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if (reentrantPrompted) return;
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reentrantPrompted = true;
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void session
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.prompt("Second message")
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.then(() => reentrantPromptResults.push("resolved"))
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.catch((err: Error) => reentrantPromptResults.push({ error: err.message }));
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});
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await session.prompt("First message");
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await waitFor(() => reentrantPromptResults.length > 0, 2000);
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await session.waitForIdle();
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expect(observedIsStreamingAtAgentEnd).not.toContain(true);
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expect(reentrantPromptResults).toEqual(["resolved"]);
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});
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it("queues idle ACP client-triggered custom messages instead of starting an ownerless turn", async () => {
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const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
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const mock = createMockModel({ handler: () => ({ content: ["Done"] }) });
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const agent = new Agent({
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getApiKey: () => "test-key",
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initialState: {
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model,
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systemPrompt: ["Test"],
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tools: [],
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},
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convertToLlm,
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streamFn: mock.stream,
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});
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const sessionManager = SessionManager.inMemory();
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const settings = Settings.isolated();
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const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-acp-idle.db"));
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authStorages.push(authStorage);
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const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models-acp-idle.yml"));
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authStorage.setRuntimeApiKey("anthropic", "test-key");
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session = new AgentSession({
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agent,
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sessionManager,
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settings,
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modelRegistry,
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});
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session.setClientBridge({
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capabilities: {},
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deferAgentInitiatedTurns: true,
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});
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await session.prompt("First message");
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expect(session.isStreaming).toBe(false);
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const callsAfterFirstPrompt = mock.calls.length;
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await session.sendCustomMessage(
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{
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customType: "async-result",
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content: "Background result",
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display: true,
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attribution: "agent",
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},
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{ deliverAs: "followUp", triggerTurn: true },
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);
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expect(mock.calls).toHaveLength(callsAfterFirstPrompt);
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expect(session.isStreaming).toBe(false);
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await session.prompt("Next user prompt");
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await session.dispose();
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session = undefined as unknown as AgentSession;
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expect(mock.calls).toHaveLength(callsAfterFirstPrompt + 1);
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expect(
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mock.calls.at(-1)?.context.messages.some(message => {
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if (typeof message.content === "string") {
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return message.content.includes("Background result");
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}
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return message.content.some(
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content => content.type === "text" && content.text.includes("Background result"),
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);
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}),
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).toBe(true);
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});
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it("runs drained ACP async completions as owned follow-up turns despite deferred client turns", async () => {
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const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
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const mock = createMockModel({ handler: () => ({ content: ["Done"] }) });
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const agent = new Agent({
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getApiKey: () => "test-key",
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initialState: {
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model,
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systemPrompt: ["Test"],
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tools: [],
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},
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convertToLlm,
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streamFn: mock.stream,
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});
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const sessionManager = SessionManager.inMemory();
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const settings = Settings.isolated();
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const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-acp-async.db"));
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authStorages.push(authStorage);
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const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models-acp-async.yml"));
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authStorage.setRuntimeApiKey("anthropic", "test-key");
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const ownerId = "acp-session-a";
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const deliveryGate = Promise.withResolvers<void>();
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let deliveryStarted = false;
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const asyncJobManager = new AsyncJobManager({
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maxRunningJobs: 2,
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retentionMs: 1_000,
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onJobComplete: async () => {
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deliveryStarted = true;
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await deliveryGate.promise;
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await session.sendCustomMessage(
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{
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customType: "async-result",
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content: "Background result",
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display: true,
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attribution: "agent",
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},
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{ deliverAs: "followUp", triggerTurn: true },
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);
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},
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});
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AsyncJobManager.setInstance(asyncJobManager);
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session = new AgentSession({
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agent,
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sessionManager,
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settings,
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modelRegistry,
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agentId: ownerId,
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ownedAsyncJobManager: asyncJobManager,
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});
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session.setClientBridge({
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capabilities: {},
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deferAgentInitiatedTurns: true,
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});
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await session.prompt("First message");
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expect(session.isStreaming).toBe(false);
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const callsAfterFirstPrompt = mock.calls.length;
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try {
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asyncJobManager.register("bash", "owned job", async () => "Background result", {
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id: "owned-job",
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ownerId,
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});
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await waitFor(() => deliveryStarted);
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const drainedPromise = session.drainAsyncJobDeliveriesForAcp({ timeoutMs: 1_000 });
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await waitFor(() => asyncJobManager.getDeliveryState({ ownerId }).delivering);
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deliveryGate.resolve();
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await expect(drainedPromise).resolves.toBe(true);
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await session.waitForIdle();
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expect(mock.calls).toHaveLength(callsAfterFirstPrompt + 1);
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expect(
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mock.calls.at(-1)?.context.messages.some(message => {
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if (typeof message.content === "string") {
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return message.content.includes("Background result");
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}
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return message.content.some(
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content => content.type === "text" && content.text.includes("Background result"),
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);
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}),
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).toBe(true);
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} finally {
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deliveryGate.resolve();
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}
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});
|
|
|
|
it("scopes ACP async job snapshots and drains to the owning session id", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-acp-scope.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models-acp-scope.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
const settings = Settings.isolated();
|
|
const deliveryGate = Promise.withResolvers<void>();
|
|
const delivered: string[] = [];
|
|
const started = new Set<string>();
|
|
const asyncJobManager = new AsyncJobManager({
|
|
maxRunningJobs: 3,
|
|
retentionMs: 1_000,
|
|
onJobComplete: async jobId => {
|
|
started.add(jobId);
|
|
if (jobId === "job-a") {
|
|
await deliveryGate.promise;
|
|
}
|
|
delivered.push(jobId);
|
|
},
|
|
});
|
|
AsyncJobManager.setInstance(asyncJobManager);
|
|
|
|
const agentA = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [] },
|
|
streamFn: createMockModel({ handler: () => ({ content: ["Done"] }) }).stream,
|
|
});
|
|
const agentB = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [] },
|
|
streamFn: createMockModel({ handler: () => ({ content: ["Done"] }) }).stream,
|
|
});
|
|
const sessionB = new AgentSession({
|
|
agent: agentB,
|
|
sessionManager: SessionManager.inMemory(),
|
|
settings,
|
|
modelRegistry,
|
|
agentId: "acp-session-b",
|
|
asyncJobManager,
|
|
});
|
|
session = new AgentSession({
|
|
agent: agentA,
|
|
sessionManager: SessionManager.inMemory(),
|
|
settings,
|
|
modelRegistry,
|
|
agentId: "acp-session-a",
|
|
ownedAsyncJobManager: asyncJobManager,
|
|
});
|
|
|
|
try {
|
|
asyncJobManager.register("bash", "A", async () => "A", { id: "job-a", ownerId: "acp-session-a" });
|
|
await waitFor(() => started.has("job-a"));
|
|
asyncJobManager.register("bash", "B", async () => "B", { id: "job-b", ownerId: "acp-session-b" });
|
|
await waitFor(() => asyncJobManager.getDeliveryState({ ownerId: "acp-session-b" }).queued > 0);
|
|
|
|
expect(sessionB.getAsyncJobSnapshot()?.delivery.pendingJobIds).not.toContain("job-a");
|
|
await expect(sessionB.drainAsyncJobDeliveriesForAcp({ timeoutMs: 1_000 })).resolves.toBe(true);
|
|
expect(delivered).toEqual(["job-b"]);
|
|
} finally {
|
|
deliveryGate.resolve();
|
|
await sessionB.dispose();
|
|
}
|
|
});
|
|
});
|
|
|
|
describe("AgentSession TTSR resume gate", () => {
|
|
let session: AgentSession;
|
|
let tempDir: string;
|
|
const authStorages: AuthStorage[] = [];
|
|
|
|
beforeEach(() => {
|
|
tempDir = path.join(os.tmpdir(), `pi-ttsr-gate-test-${Snowflake.next()}`);
|
|
fs.mkdirSync(tempDir, { recursive: true });
|
|
});
|
|
|
|
afterEach(async () => {
|
|
if (session) {
|
|
await session.dispose();
|
|
}
|
|
for (const authStorage of authStorages.splice(0)) {
|
|
authStorage.close();
|
|
}
|
|
if (tempDir && fs.existsSync(tempDir)) {
|
|
fs.rmSync(tempDir, { recursive: true });
|
|
}
|
|
});
|
|
|
|
async function waitFor(predicate: () => boolean, timeoutMs = 500): Promise<void> {
|
|
const deadline = Date.now() + timeoutMs;
|
|
while (Date.now() < deadline) {
|
|
if (predicate()) return;
|
|
await Bun.sleep(10);
|
|
}
|
|
|
|
throw new Error("Timed out waiting for condition");
|
|
}
|
|
const testRule: Rule = {
|
|
name: "no-unwrap",
|
|
path: "/tmp/no-unwrap.md",
|
|
content: "Do not use .unwrap()",
|
|
condition: ["\\.unwrap\\("],
|
|
_source: { provider: "test", providerName: "test", path: "/tmp/no-unwrap.md", level: "project" },
|
|
};
|
|
|
|
function makeMsg(text: string, stopReason: "stop" | "aborted" = "stop"): AssistantMessage {
|
|
return {
|
|
role: "assistant",
|
|
content: [{ type: "text", text }],
|
|
api: "anthropic-messages",
|
|
provider: "anthropic",
|
|
model: "mock",
|
|
usage: {
|
|
input: 0,
|
|
output: 0,
|
|
cacheRead: 0,
|
|
cacheWrite: 0,
|
|
totalTokens: 0,
|
|
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
|
},
|
|
stopReason,
|
|
timestamp: Date.now(),
|
|
};
|
|
}
|
|
|
|
function pushContinuationStream(stream: AssistantMessageEventStream, onComplete: () => void): void {
|
|
queueMicrotask(() => {
|
|
const partial = makeMsg("");
|
|
stream.push({ type: "start", partial });
|
|
onComplete();
|
|
stream.push({
|
|
type: "done",
|
|
reason: "stop",
|
|
message: makeMsg('Fixed: let val = result.expect("msg")'),
|
|
});
|
|
});
|
|
}
|
|
|
|
function pushAbortableTtsrStream(stream: AssistantMessageEventStream, signal: AbortSignal | undefined): void {
|
|
queueMicrotask(() => {
|
|
const partial = makeMsg("");
|
|
stream.push({ type: "start", partial });
|
|
stream.push({
|
|
type: "text_delta",
|
|
contentIndex: 0,
|
|
delta: "let val = result.unwrap(",
|
|
partial: makeMsg("let val = result.unwrap("),
|
|
});
|
|
if (signal) {
|
|
signal.addEventListener(
|
|
"abort",
|
|
() => {
|
|
stream.push({
|
|
type: "error",
|
|
reason: "aborted",
|
|
error: makeMsg("let val = result.unwrap(", "aborted"),
|
|
});
|
|
},
|
|
{ once: true },
|
|
);
|
|
}
|
|
});
|
|
}
|
|
|
|
it("prompt() blocks until TTSR interrupt continuation completes", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
let streamCallCount = 0;
|
|
let continuationCompleted = false;
|
|
|
|
const ttsrManager = new TtsrManager({
|
|
enabled: true,
|
|
contextMode: "discard",
|
|
interruptMode: "always",
|
|
repeatMode: "once",
|
|
repeatGap: 10,
|
|
});
|
|
ttsrManager.addRule(testRule);
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [] },
|
|
streamFn: (_model, _context, options) => {
|
|
streamCallCount++;
|
|
const stream = new AssistantMessageEventStream();
|
|
const signal = options?.signal;
|
|
|
|
if (streamCallCount === 1) {
|
|
// First stream: emit text that triggers TTSR, then respond to abort
|
|
pushAbortableTtsrStream(stream, signal);
|
|
} else {
|
|
// Continuation stream: complete normally after a delay
|
|
pushContinuationStream(stream, () => {
|
|
continuationCompleted = true;
|
|
});
|
|
}
|
|
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
const sessionManager = SessionManager.inMemory();
|
|
const settings = Settings.isolated();
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-int.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
|
|
session = new AgentSession({
|
|
agent,
|
|
sessionManager,
|
|
settings,
|
|
modelRegistry,
|
|
ttsrManager,
|
|
});
|
|
|
|
// prompt() must block until the TTSR continuation completes
|
|
await session.prompt("Write some Rust code");
|
|
|
|
// By the time prompt() returns, the continuation must have finished
|
|
expect(continuationCompleted).toBe(true);
|
|
expect(streamCallCount).toBeGreaterThanOrEqual(2);
|
|
expect(session.isStreaming).toBe(false);
|
|
});
|
|
|
|
it("relativizes the rule file path in the TTSR interrupt injection (no absolute leak)", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
let streamCallCount = 0;
|
|
|
|
const sessionManager = SessionManager.inMemory();
|
|
const cwd = sessionManager.getCwd();
|
|
const ruleAbsPath = path.join(cwd, ".omp", "rules", "no-unwrap.md");
|
|
const expectedRel = path.relative(cwd, ruleAbsPath);
|
|
const rule: Rule = {
|
|
name: "no-unwrap",
|
|
path: ruleAbsPath,
|
|
content: "Do not use .unwrap()",
|
|
condition: ["\\.unwrap\\("],
|
|
_source: { provider: "test", providerName: "test", path: ruleAbsPath, level: "project" },
|
|
};
|
|
|
|
const ttsrManager = new TtsrManager({
|
|
enabled: true,
|
|
contextMode: "discard",
|
|
interruptMode: "always",
|
|
repeatMode: "once",
|
|
repeatGap: 10,
|
|
});
|
|
ttsrManager.addRule(rule);
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [] },
|
|
streamFn: (_model, _context, options) => {
|
|
streamCallCount++;
|
|
const stream = new AssistantMessageEventStream();
|
|
if (streamCallCount === 1) {
|
|
pushAbortableTtsrStream(stream, options?.signal);
|
|
} else {
|
|
pushContinuationStream(stream, () => {});
|
|
}
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
const settings = Settings.isolated();
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-rel.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
|
|
session = new AgentSession({ agent, sessionManager, settings, modelRegistry, ttsrManager });
|
|
|
|
await session.prompt("Write some Rust code");
|
|
|
|
const injection = sessionManager
|
|
.getEntries()
|
|
.find(e => e.type === "custom_message" && e.customType === "ttsr-injection");
|
|
expect(injection?.type).toBe("custom_message");
|
|
const content = injection?.type === "custom_message" ? injection.content : undefined;
|
|
expect(typeof content).toBe("string");
|
|
const text = content as string;
|
|
// The rendered interrupt the model receives references the rule by a
|
|
// project-relative path, never the absolute home path.
|
|
expect(text).toContain('reason="rule_violation"');
|
|
expect(text).toContain(`path="${expectedRel}"`);
|
|
expect(text).not.toContain(ruleAbsPath);
|
|
});
|
|
|
|
it("prompt() blocks until TTSR deferred continuation completes", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
let streamCallCount = 0;
|
|
let continuationCompleted = false;
|
|
|
|
// interruptMode: "never" -> TTSR match queues deferred injection instead of aborting
|
|
const ttsrManager = new TtsrManager({
|
|
enabled: true,
|
|
contextMode: "discard",
|
|
interruptMode: "never",
|
|
repeatMode: "once",
|
|
repeatGap: 10,
|
|
});
|
|
ttsrManager.addRule(testRule);
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [] },
|
|
streamFn: (_model, _context, _options) => {
|
|
streamCallCount++;
|
|
const stream = new AssistantMessageEventStream();
|
|
|
|
if (streamCallCount === 1) {
|
|
// First stream: emit matching text and complete normally
|
|
queueMicrotask(() => {
|
|
const partial = makeMsg("");
|
|
stream.push({ type: "start", partial });
|
|
stream.push({
|
|
type: "text_delta",
|
|
contentIndex: 0,
|
|
delta: "let val = result.unwrap(",
|
|
partial: makeMsg("let val = result.unwrap("),
|
|
});
|
|
// Complete normally (no abort) -- deferred path
|
|
stream.push({
|
|
type: "done",
|
|
reason: "stop",
|
|
message: makeMsg("let val = result.unwrap()"),
|
|
});
|
|
});
|
|
} else {
|
|
// Continuation stream after deferred TTSR injection
|
|
pushContinuationStream(stream, () => {
|
|
continuationCompleted = true;
|
|
});
|
|
}
|
|
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
const sessionManager = SessionManager.inMemory();
|
|
const settings = Settings.isolated();
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-def.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
|
|
session = new AgentSession({
|
|
agent,
|
|
sessionManager,
|
|
settings,
|
|
modelRegistry,
|
|
ttsrManager,
|
|
});
|
|
|
|
// prompt() must block until the deferred TTSR continuation completes
|
|
await session.prompt("Write some Rust code");
|
|
|
|
// By the time prompt() returns, the deferred continuation must have finished
|
|
expect(continuationCompleted).toBe(true);
|
|
expect(streamCallCount).toBeGreaterThanOrEqual(2);
|
|
expect(session.isStreaming).toBe(false);
|
|
});
|
|
|
|
it("prompt() returns immediately when session is aborted during TTSR wait", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
|
|
const ttsrManager = new TtsrManager({
|
|
enabled: true,
|
|
contextMode: "discard",
|
|
interruptMode: "always",
|
|
repeatMode: "once",
|
|
repeatGap: 10,
|
|
});
|
|
ttsrManager.addRule(testRule);
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [] },
|
|
streamFn: (_model, _context, options) => {
|
|
const stream = new AssistantMessageEventStream();
|
|
const signal = options?.signal;
|
|
|
|
queueMicrotask(() => {
|
|
const partial = makeMsg("");
|
|
stream.push({ type: "start", partial });
|
|
stream.push({
|
|
type: "text_delta",
|
|
contentIndex: 0,
|
|
delta: "result.unwrap(",
|
|
partial: makeMsg("result.unwrap("),
|
|
});
|
|
if (signal) {
|
|
signal.addEventListener(
|
|
"abort",
|
|
() => {
|
|
stream.push({
|
|
type: "error",
|
|
reason: "aborted",
|
|
error: makeMsg("result.unwrap(", "aborted"),
|
|
});
|
|
},
|
|
{ once: true },
|
|
);
|
|
}
|
|
});
|
|
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
const sessionManager = SessionManager.inMemory();
|
|
const settings = Settings.isolated();
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-abt.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
|
|
session = new AgentSession({
|
|
agent,
|
|
sessionManager,
|
|
settings,
|
|
modelRegistry,
|
|
ttsrManager,
|
|
});
|
|
|
|
// Start prompt (will trigger TTSR and create resume gate)
|
|
const promptPromise = session.prompt("Write some Rust code");
|
|
await waitFor(() => session.isStreaming);
|
|
|
|
// Abort session — prompt() should unblock
|
|
await session.abort();
|
|
await promptPromise;
|
|
|
|
expect(session.isStreaming).toBe(false);
|
|
});
|
|
|
|
it("prompt() waits for TTSR continuation with tool calls to finish", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
let streamCallCount = 0;
|
|
let toolExecutionFinished = false;
|
|
let allTurnsCompleted = false;
|
|
|
|
const ttsrManager = new TtsrManager({
|
|
enabled: true,
|
|
contextMode: "discard",
|
|
interruptMode: "always",
|
|
repeatMode: "once",
|
|
repeatGap: 10,
|
|
});
|
|
ttsrManager.addRule(testRule);
|
|
|
|
const mockTool: AgentTool = {
|
|
name: "mock_edit",
|
|
label: "Mock Edit",
|
|
description: "A mock edit tool",
|
|
parameters: z.object({}),
|
|
execute: async () => {
|
|
toolExecutionFinished = true;
|
|
return { content: [{ type: "text" as const, text: "edit applied" }] };
|
|
},
|
|
};
|
|
|
|
const toolCallContent: ToolCall = {
|
|
type: "toolCall",
|
|
id: "call_test_001",
|
|
name: "mock_edit",
|
|
arguments: {},
|
|
};
|
|
|
|
function makeToolCallMsg(): AssistantMessage {
|
|
return {
|
|
role: "assistant",
|
|
content: [toolCallContent],
|
|
api: "anthropic-messages",
|
|
provider: "anthropic",
|
|
model: "mock",
|
|
usage: {
|
|
input: 0,
|
|
output: 0,
|
|
cacheRead: 0,
|
|
cacheWrite: 0,
|
|
totalTokens: 0,
|
|
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
|
},
|
|
stopReason: "toolUse",
|
|
timestamp: Date.now(),
|
|
};
|
|
}
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [mockTool] },
|
|
streamFn: (_model, _context, options) => {
|
|
streamCallCount++;
|
|
const stream = new AssistantMessageEventStream();
|
|
const signal = options?.signal;
|
|
|
|
if (streamCallCount === 1) {
|
|
// First stream: emit text that triggers TTSR, then respond to abort
|
|
pushAbortableTtsrStream(stream, signal);
|
|
} else if (streamCallCount === 2) {
|
|
// Continuation: return assistant message with a tool call
|
|
queueMicrotask(() => {
|
|
const msg = makeToolCallMsg();
|
|
stream.push({ type: "start", partial: msg });
|
|
stream.push({ type: "done", reason: "toolUse", message: msg });
|
|
});
|
|
} else {
|
|
// After tool execution: return final response
|
|
queueMicrotask(() => {
|
|
allTurnsCompleted = true;
|
|
const msg = makeMsg('Fixed: let val = result.expect("msg")');
|
|
stream.push({ type: "start", partial: msg });
|
|
stream.push({ type: "done", reason: "stop", message: msg });
|
|
});
|
|
}
|
|
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
const sessionManager = SessionManager.inMemory();
|
|
const settings = Settings.isolated();
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-tool.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
|
|
session = new AgentSession({
|
|
agent,
|
|
sessionManager,
|
|
settings,
|
|
modelRegistry,
|
|
ttsrManager,
|
|
});
|
|
|
|
// prompt() must block until the TTSR continuation (including tool execution) completes.
|
|
// Before the fix, prompt() returned after the continuation's first assistant message_end,
|
|
// while the agent was still executing tool calls in the background.
|
|
await session.prompt("Write some Rust code");
|
|
|
|
// By the time prompt() returns, ALL turns must have completed
|
|
expect(toolExecutionFinished).toBe(true);
|
|
expect(allTurnsCompleted).toBe(true);
|
|
expect(streamCallCount).toBeGreaterThanOrEqual(3);
|
|
expect(session.isStreaming).toBe(false);
|
|
});
|
|
it("interruptMode never folds tool-match reminder into the toolResult instead of driving an extra turn", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
let streamCallCount = 0;
|
|
let toolExecuted = false;
|
|
|
|
const ttsrManager = new TtsrManager({
|
|
enabled: true,
|
|
contextMode: "discard",
|
|
interruptMode: "never",
|
|
repeatMode: "once",
|
|
repeatGap: 10,
|
|
});
|
|
ttsrManager.addRule(testRule);
|
|
|
|
const mockTool: AgentTool = {
|
|
name: "mock_edit",
|
|
label: "Mock Edit",
|
|
description: "A mock edit tool",
|
|
parameters: z.object({ snippet: z.string().optional() }),
|
|
execute: async () => {
|
|
toolExecuted = true;
|
|
return { content: [{ type: "text" as const, text: "edit applied" }] };
|
|
},
|
|
};
|
|
|
|
const toolCallContent: ToolCall = {
|
|
type: "toolCall",
|
|
id: "call_never_001",
|
|
name: "mock_edit",
|
|
arguments: { snippet: "let val = result.unwrap()" },
|
|
};
|
|
|
|
const makeToolCallMsg = (): AssistantMessage => ({
|
|
role: "assistant",
|
|
content: [toolCallContent],
|
|
api: "anthropic-messages",
|
|
provider: "anthropic",
|
|
model: "mock",
|
|
usage: {
|
|
input: 0,
|
|
output: 0,
|
|
cacheRead: 0,
|
|
cacheWrite: 0,
|
|
totalTokens: 0,
|
|
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
|
},
|
|
stopReason: "toolUse",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [mockTool] },
|
|
streamFn: () => {
|
|
streamCallCount++;
|
|
const stream = new AssistantMessageEventStream();
|
|
if (streamCallCount === 1) {
|
|
// Emit a tool call whose argument delta matches the TTSR rule.
|
|
queueMicrotask(() => {
|
|
const partial = makeToolCallMsg();
|
|
stream.push({ type: "start", partial });
|
|
stream.push({ type: "toolcall_start", contentIndex: 0, partial });
|
|
stream.push({
|
|
type: "toolcall_delta",
|
|
contentIndex: 0,
|
|
delta: 'let val = result.unwrap("oops")',
|
|
partial,
|
|
});
|
|
stream.push({ type: "toolcall_end", contentIndex: 0, toolCall: toolCallContent, partial });
|
|
stream.push({ type: "done", reason: "toolUse", message: partial });
|
|
});
|
|
} else {
|
|
// Continuation after tool result; finish cleanly.
|
|
queueMicrotask(() => {
|
|
const done = makeMsg("ok");
|
|
stream.push({ type: "start", partial: done });
|
|
stream.push({ type: "done", reason: "stop", message: done });
|
|
});
|
|
}
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
const sessionManager = SessionManager.inMemory();
|
|
const settings = Settings.isolated();
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-never-tool.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
|
|
session = new AgentSession({
|
|
agent,
|
|
sessionManager,
|
|
settings,
|
|
modelRegistry,
|
|
ttsrManager,
|
|
});
|
|
|
|
await session.prompt("Write some Rust code");
|
|
|
|
// Tool ran (no interrupt) and the loop didn't spawn an extra follow-up turn for injection.
|
|
expect(toolExecuted).toBe(true);
|
|
expect(streamCallCount).toBe(2);
|
|
|
|
// The matched tool's result must carry the in-band reminder.
|
|
const toolResult = agent.state.messages.find(
|
|
(m): m is Extract<typeof m, { role: "toolResult" }> =>
|
|
m.role === "toolResult" && m.toolCallId === toolCallContent.id,
|
|
);
|
|
expect(toolResult).toBeDefined();
|
|
const text = Array.isArray(toolResult?.content)
|
|
? toolResult.content
|
|
.filter((c): c is { type: "text"; text: string } => c.type === "text")
|
|
.map(c => c.text)
|
|
.join("\n")
|
|
: "";
|
|
expect(text).toContain("<system-reminder");
|
|
expect(text).toContain('rule="no-unwrap"');
|
|
expect(text).toContain("Do not use .unwrap()");
|
|
expect(text.indexOf("<system-reminder")).toBeLessThan(text.indexOf("edit applied"));
|
|
});
|
|
|
|
it("interruptMode never deduplicates the reminder across sibling tool calls in one batch", async () => {
|
|
const model = getBundledModel("anthropic", "claude-sonnet-4-5")!;
|
|
let streamCallCount = 0;
|
|
let executedCount = 0;
|
|
|
|
const ttsrManager = new TtsrManager({
|
|
enabled: true,
|
|
contextMode: "discard",
|
|
interruptMode: "never",
|
|
repeatMode: "once",
|
|
repeatGap: 10,
|
|
});
|
|
ttsrManager.addRule(testRule);
|
|
|
|
const mockTool: AgentTool = {
|
|
name: "mock_edit",
|
|
label: "Mock Edit",
|
|
description: "A mock edit tool",
|
|
parameters: z.object({ snippet: z.string().optional() }),
|
|
execute: async () => {
|
|
executedCount++;
|
|
return { content: [{ type: "text" as const, text: "edit applied" }] };
|
|
},
|
|
};
|
|
|
|
const toolCallA: ToolCall = {
|
|
type: "toolCall",
|
|
id: "call_dup_A",
|
|
name: "mock_edit",
|
|
arguments: { snippet: "a.unwrap()" },
|
|
};
|
|
const toolCallB: ToolCall = {
|
|
type: "toolCall",
|
|
id: "call_dup_B",
|
|
name: "mock_edit",
|
|
arguments: { snippet: "b.unwrap()" },
|
|
};
|
|
const toolCallC: ToolCall = {
|
|
type: "toolCall",
|
|
id: "call_dup_C",
|
|
name: "mock_edit",
|
|
arguments: { snippet: "c.unwrap()" },
|
|
};
|
|
|
|
const makeBatchMsg = (): AssistantMessage => ({
|
|
role: "assistant",
|
|
content: [toolCallA, toolCallB, toolCallC],
|
|
api: "anthropic-messages",
|
|
provider: "anthropic",
|
|
model: "mock",
|
|
usage: {
|
|
input: 0,
|
|
output: 0,
|
|
cacheRead: 0,
|
|
cacheWrite: 0,
|
|
totalTokens: 0,
|
|
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
|
},
|
|
stopReason: "toolUse",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model, systemPrompt: ["Test"], tools: [mockTool] },
|
|
streamFn: () => {
|
|
streamCallCount++;
|
|
const stream = new AssistantMessageEventStream();
|
|
if (streamCallCount === 1) {
|
|
queueMicrotask(() => {
|
|
const partial = makeBatchMsg();
|
|
stream.push({ type: "start", partial });
|
|
const calls: ToolCall[] = [toolCallA, toolCallB, toolCallC];
|
|
for (let i = 0; i < calls.length; i++) {
|
|
const call = calls[i]!;
|
|
stream.push({ type: "toolcall_start", contentIndex: i, partial });
|
|
stream.push({
|
|
type: "toolcall_delta",
|
|
contentIndex: i,
|
|
delta: `let val = result.unwrap("oops-${call.id}")`,
|
|
partial,
|
|
});
|
|
stream.push({ type: "toolcall_end", contentIndex: i, toolCall: call, partial });
|
|
}
|
|
stream.push({ type: "done", reason: "toolUse", message: partial });
|
|
});
|
|
} else {
|
|
queueMicrotask(() => {
|
|
const done = makeMsg("ok");
|
|
stream.push({ type: "start", partial: done });
|
|
stream.push({ type: "done", reason: "stop", message: done });
|
|
});
|
|
}
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
const sessionManager = SessionManager.inMemory();
|
|
const settings = Settings.isolated();
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-dup.db"));
|
|
authStorages.push(authStorage);
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
authStorage.setRuntimeApiKey("anthropic", "test-key");
|
|
|
|
session = new AgentSession({
|
|
agent,
|
|
sessionManager,
|
|
settings,
|
|
modelRegistry,
|
|
ttsrManager,
|
|
});
|
|
|
|
await session.prompt("Write some Rust code");
|
|
|
|
expect(executedCount).toBe(3);
|
|
const toolResults = agent.state.messages.filter(
|
|
(m): m is Extract<typeof m, { role: "toolResult" }> => m.role === "toolResult",
|
|
);
|
|
expect(toolResults).toHaveLength(3);
|
|
const withReminder = toolResults.filter(r =>
|
|
Array.isArray(r.content)
|
|
? r.content.some(c => c.type === "text" && c.text.includes("<system-reminder"))
|
|
: false,
|
|
);
|
|
expect(withReminder).toHaveLength(1);
|
|
});
|
|
|
|
it("prompt() waits for context-promotion continuation to finish", async () => {
|
|
const authStorage = await AuthStorage.create(path.join(tempDir, "testauth-promo.db"));
|
|
authStorages.push(authStorage);
|
|
authStorage.setRuntimeApiKey("openai-codex", "test-key");
|
|
const modelRegistry = new ModelRegistry(authStorage, path.join(tempDir, "models.yml"));
|
|
|
|
const sparkModel = modelRegistry.find("openai-codex", "gpt-5.3-codex-spark");
|
|
const codexModel = modelRegistry.find("openai-codex", "gpt-5.5");
|
|
if (!sparkModel || !codexModel) {
|
|
throw new Error("Expected codex spark and codex models to exist");
|
|
}
|
|
|
|
let streamCallCount = 0;
|
|
let continuationCompleted = false;
|
|
|
|
const makeOverflowMessage = (): AssistantMessage => ({
|
|
role: "assistant",
|
|
content: [{ type: "text", text: "" }],
|
|
api: sparkModel.api,
|
|
provider: sparkModel.provider,
|
|
model: sparkModel.id,
|
|
usage: {
|
|
input: 0,
|
|
output: 0,
|
|
cacheRead: 0,
|
|
cacheWrite: 0,
|
|
totalTokens: 0,
|
|
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
|
},
|
|
stopReason: "error",
|
|
errorMessage: "context_length_exceeded: Your input exceeds the context window of this model.",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
const makeSuccessMessage = (): AssistantMessage => ({
|
|
role: "assistant",
|
|
content: [{ type: "text", text: "Recovered after promotion" }],
|
|
api: codexModel.api,
|
|
provider: codexModel.provider,
|
|
model: codexModel.id,
|
|
usage: {
|
|
input: 0,
|
|
output: 0,
|
|
cacheRead: 0,
|
|
cacheWrite: 0,
|
|
totalTokens: 0,
|
|
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
|
|
},
|
|
stopReason: "stop",
|
|
timestamp: Date.now(),
|
|
});
|
|
|
|
const agent = new Agent({
|
|
getApiKey: () => "test-key",
|
|
initialState: { model: sparkModel, systemPrompt: ["Test"], tools: [] },
|
|
streamFn: () => {
|
|
streamCallCount++;
|
|
const stream = new AssistantMessageEventStream();
|
|
if (streamCallCount === 1) {
|
|
queueMicrotask(() => {
|
|
const message = makeOverflowMessage();
|
|
stream.push({ type: "start", partial: message });
|
|
stream.push({ type: "error", reason: "error", error: message });
|
|
});
|
|
} else {
|
|
queueMicrotask(() => {
|
|
continuationCompleted = true;
|
|
const message = makeSuccessMessage();
|
|
stream.push({ type: "start", partial: message });
|
|
stream.push({ type: "done", reason: "stop", message });
|
|
});
|
|
}
|
|
return stream;
|
|
},
|
|
});
|
|
|
|
session = new AgentSession({
|
|
agent,
|
|
sessionManager: SessionManager.inMemory(),
|
|
settings: Settings.isolated({ "compaction.enabled": false, "contextPromotion.enabled": true }),
|
|
modelRegistry,
|
|
});
|
|
|
|
await session.prompt("Handle overflow");
|
|
|
|
expect(continuationCompleted).toBe(true);
|
|
expect(streamCallCount).toBeGreaterThanOrEqual(2);
|
|
expect(session.model?.id).toBe(codexModel.id);
|
|
expect(session.isStreaming).toBe(false);
|
|
});
|
|
});
|