can1357
ce4ebad726
- Extended `AgentTool.concurrency` to accept per-call resolver functions and resolved concurrency mode from each tool call, falling back to exclusive on resolver errors. - Updated BashTool to schedule non-PTY calls as shared and PTY calls as exclusive so non-interactive bash calls can run in parallel within one message. - Tracked in-use persistent shell sessions in the bash executor and routed overlapping calls on the same session key to isolated one-shot shells while preserving owner session availability.
1445 lines
50 KiB
TypeScript
1445 lines
50 KiB
TypeScript
import { describe, expect, it } from "bun:test";
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import { agentLoop, agentLoopContinue, agentLoopDetailed, INTENT_FIELD } from "@oh-my-pi/pi-agent-core/agent-loop";
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import type {
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AgentContext,
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AgentEvent,
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AgentLoopConfig,
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AgentMessage,
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AgentTool,
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AgentToolContext,
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ToolCallContext,
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} from "@oh-my-pi/pi-agent-core/types";
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import type { AssistantMessage, AssistantMessageEvent, Message, ToolResultMessage } 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 * as z from "zod/v4";
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import { createAssistantMessage, createUserMessage } from "./helpers";
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// Simple identity converter for tests - just passes through standard messages
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function identityConverter(messages: AgentMessage[]): Message[] {
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return messages.filter(m => m.role === "user" || m.role === "assistant" || m.role === "toolResult") as Message[];
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}
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describe("agentLoop with AgentMessage", () => {
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it("should emit events with AgentMessage types", async () => {
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [],
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tools: [],
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};
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const mock = createMockModel({ responses: [{ content: ["Hi there!"] }] });
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
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const events: AgentEvent[] = [];
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const stream = agentLoop([createUserMessage("Hello")], context, config, undefined, mock.stream);
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for await (const event of stream) {
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events.push(event);
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}
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const messages = await stream.result();
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// Should have user message and assistant message
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expect(messages.length).toBe(2);
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expect(messages[0].role).toBe("user");
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expect(messages[1].role).toBe("assistant");
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// Verify event sequence
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const eventTypes = events.map(e => e.type);
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expect(eventTypes).toContain("agent_start");
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expect(eventTypes).toContain("turn_start");
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expect(eventTypes).toContain("message_start");
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expect(eventTypes).toContain("message_end");
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expect(eventTypes).toContain("turn_end");
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expect(eventTypes).toContain("agent_end");
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});
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it("returns detailed telemetry when awaiting detailed() directly", async () => {
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [],
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tools: [],
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};
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const mock = createMockModel({ responses: [{ content: ["Hi there!"] }] });
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
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const { detailed } = agentLoopDetailed([createUserMessage("Hello")], context, config, undefined, mock.stream);
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const result = await detailed();
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expect(result.messages).toHaveLength(2);
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expect(result.telemetry?.stepCount).toBe(1);
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expect(result.telemetry?.chats.total).toBe(1);
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expect(result.coverage?.modelsUsed).toEqual([mock.model.id]);
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});
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it("retries when harmony leakage reaches the committed assistant message (openai-codex)", async () => {
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [],
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tools: [],
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};
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// First response leaks a harmony payload as visible assistant text; the
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// retry is clean. Mitigation only engages for openai-codex.
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const leak = "Some prose. analysis to=functions.edit code 大发官网";
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const mock = createMockModel({
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provider: "openai-codex",
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responses: [{ content: [leak] }, { content: ["clean retry response"] }],
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});
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
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const events: AgentEvent[] = [];
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const stream = agentLoop([createUserMessage("Hello")], context, config, undefined, mock.stream);
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for await (const event of stream) {
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events.push(event);
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}
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const messages = await stream.result();
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// The leaked attempt was retried, not committed.
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expect(mock.calls).toHaveLength(2);
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expect(messages).toHaveLength(2);
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const final = messages[1];
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if (final.role !== "assistant") throw new Error("expected assistant message");
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expect(final.content).toEqual([{ type: "text", text: "clean retry response" }]);
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expect(JSON.stringify(messages)).not.toContain("to=functions.");
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});
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it("does not hard-abort a codex tool call whose argument legitimately carries the marker", async () => {
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// A legit edit of a file (e.g. these harmony fixtures) whose content carries
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// `to=functions.*` next to a channel word + non-Latin script. tool_arg is
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// gated on the trailing-garbage `T` co-signal, and the loop supplies no parse
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// boundary, so the call commits + executes once instead of being detected as
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// a leak and retried/escalated.
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const toolSchema = z.object({ input: z.string() });
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const executed: string[] = [];
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const tool: AgentTool<typeof toolSchema, { input: string }> = {
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name: "edit",
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label: "Edit",
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description: "Edit tool",
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parameters: toolSchema,
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async execute(_toolCallId, params) {
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executed.push(params.input);
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return { content: [{ type: "text", text: "ok" }], details: { input: params.input } };
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},
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};
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const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
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const leakyArg = "@fixtures/corpus.json\n+\tanalysis to=functions.edit code 大发官网\n";
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const mock = createMockModel({
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provider: "openai-codex",
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responses: [
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{ content: [{ type: "toolCall", id: "tool-1", name: "edit", arguments: { input: leakyArg } }] },
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{ content: ["done"] },
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],
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});
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
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const stream = agentLoop([createUserMessage("edit a fixture")], context, config, undefined, mock.stream);
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for await (const _event of stream) {
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// drain
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}
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// The tool ran on the original (unmodified) argument and the turn was not
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// retried — a hard-abort would have left `executed` empty and consumed the
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// "done" response as a clean retry instead.
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expect(executed).toEqual([leakyArg]);
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expect(mock.calls).toHaveLength(2);
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});
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it("emits an aborted assistant message when cancellation happens before provider events", async () => {
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [],
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tools: [],
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};
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const mock = createMockModel();
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
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const controller = new AbortController();
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// The mock provider would reject without a configured response; we want the
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// agent's abort path to kick in before any event is emitted. Use a raw stream
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// that never emits anything.
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const streamFn = () => new AssistantMessageEventStream();
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const events: AgentEvent[] = [];
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const stream = agentLoop([createUserMessage("Hello")], context, config, controller.signal, streamFn);
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queueMicrotask(() => controller.abort());
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for await (const event of stream) {
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events.push(event);
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}
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const messages = await stream.result();
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const finalMessage = messages[messages.length - 1];
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expect(finalMessage.role).toBe("assistant");
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if (finalMessage.role !== "assistant") throw new Error("Expected assistant message");
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expect(finalMessage.stopReason).toBe("aborted");
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expect(finalMessage.errorMessage).toBe("Request was aborted");
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expect(events.map(event => event.type)).toContain("agent_end");
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});
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it("does not wait for provider iterator cleanup when aborting a stalled response", async () => {
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [],
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tools: [],
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};
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const mock = createMockModel();
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
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const controller = new AbortController();
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let returnCalled = false;
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const streamFn = () =>
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({
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result: () => Promise.withResolvers<AssistantMessage>().promise,
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[Symbol.asyncIterator]: () => ({
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next: () => Promise.withResolvers<IteratorResult<AssistantMessageEvent>>().promise,
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return: () => {
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returnCalled = true;
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return Promise.withResolvers<IteratorResult<AssistantMessageEvent>>().promise;
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},
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}),
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}) as AssistantMessageEventStream;
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const stream = agentLoop([createUserMessage("Hello")], context, config, controller.signal, streamFn);
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queueMicrotask(() => controller.abort("stop now"));
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const messages = await stream.result();
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expect(returnCalled).toBe(true);
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const finalMessage = messages[messages.length - 1];
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expect(finalMessage.role).toBe("assistant");
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if (finalMessage.role !== "assistant") throw new Error("Expected assistant message");
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expect(finalMessage.stopReason).toBe("aborted");
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expect(finalMessage.errorMessage).toBe("stop now");
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});
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it("surfaces a custom abort reason on the synthesized aborted message", async () => {
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [],
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tools: [],
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};
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const mock = createMockModel();
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
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const controller = new AbortController();
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const streamFn = () => new AssistantMessageEventStream();
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const stream = agentLoop([createUserMessage("Hello")], context, config, controller.signal, streamFn);
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// Abort with a reason (as the coding agent does for a user Esc interrupt).
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queueMicrotask(() => controller.abort("Interrupted by user"));
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for await (const _event of stream) {
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// drain
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}
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const messages = await stream.result();
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const finalMessage = messages[messages.length - 1];
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expect(finalMessage.role).toBe("assistant");
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if (finalMessage.role !== "assistant") throw new Error("Expected assistant message");
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expect(finalMessage.stopReason).toBe("aborted");
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// The reason rides AbortController.abort(reason) onto the message verbatim,
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// instead of the generic "Request was aborted" default.
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expect(finalMessage.errorMessage).toBe("Interrupted by user");
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});
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it("should handle custom message types via convertToLlm", async () => {
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// Create a custom message type
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interface CustomNotification {
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role: "notification";
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text: string;
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timestamp: number;
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}
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const notification: CustomNotification = {
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role: "notification",
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text: "This is a notification",
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timestamp: Date.now(),
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};
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [notification as unknown as AgentMessage], // Custom message in context
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tools: [],
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};
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let convertedMessages: Message[] = [];
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const mock = createMockModel({ responses: [{ content: ["Response"] }] });
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const config: AgentLoopConfig = {
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model: mock.model,
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convertToLlm: messages => {
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// Filter out notifications, convert rest
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convertedMessages = messages
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.filter(m => (m as { role: string }).role !== "notification")
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.filter(m => m.role === "user" || m.role === "assistant" || m.role === "toolResult") as Message[];
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return convertedMessages;
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},
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};
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const stream = agentLoop([createUserMessage("Hello")], context, config, undefined, mock.stream);
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for await (const _ of stream) {
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// drain
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}
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// The notification should have been filtered out in convertToLlm
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expect(convertedMessages.length).toBe(1); // Only user message
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expect(convertedMessages[0].role).toBe("user");
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});
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it("should apply transformContext before convertToLlm", async () => {
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const context: AgentContext = {
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systemPrompt: ["You are helpful."],
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messages: [
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createUserMessage("old message 1"),
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createAssistantMessage([{ type: "text", text: "old response 1" }]),
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createUserMessage("old message 2"),
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createAssistantMessage([{ type: "text", text: "old response 2" }]),
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],
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tools: [],
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};
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let transformedMessages: AgentMessage[] = [];
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let convertedMessages: Message[] = [];
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const mock = createMockModel({ responses: [{ content: ["Response"] }] });
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const config: AgentLoopConfig = {
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model: mock.model,
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transformContext: async messages => {
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// Keep only last 2 messages (prune old ones)
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transformedMessages = messages.slice(-2);
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return transformedMessages;
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},
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convertToLlm: messages => {
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convertedMessages = messages.filter(
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m => m.role === "user" || m.role === "assistant" || m.role === "toolResult",
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) as Message[];
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return convertedMessages;
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},
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};
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const stream = agentLoop([createUserMessage("new message")], context, config, undefined, mock.stream);
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for await (const _ of stream) {
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// drain
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}
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// transformContext should have been called first, keeping only last 2
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expect(transformedMessages.length).toBe(2);
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// Then convertToLlm receives the pruned messages
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expect(convertedMessages.length).toBe(2);
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});
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it("provides tool call batch context", async () => {
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const toolSchema = z.object({ value: z.string() });
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const contexts: ToolCallContext[] = [];
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const tool: AgentTool<typeof toolSchema, { value: string }> = {
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name: "echo",
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label: "Echo",
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description: "Echo tool",
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parameters: toolSchema,
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async execute(_toolCallId, params, _signal, _onUpdate, ctx) {
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const toolCall = (ctx as { toolCall?: ToolCallContext })?.toolCall;
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if (toolCall) {
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contexts.push(toolCall);
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}
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return {
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content: [{ type: "text", text: `echoed: ${params.value}` }],
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details: { value: params.value },
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};
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},
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};
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const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
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const mock = createMockModel({
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responses: [
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{
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content: [
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{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } },
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{ type: "toolCall", id: "tool-2", name: "echo", arguments: { value: "world" } },
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],
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},
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{ content: ["done"] },
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],
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});
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const config: AgentLoopConfig = {
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model: mock.model,
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convertToLlm: identityConverter,
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getToolContext: toolCall => ({ toolCall }) as AgentToolContext,
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};
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const stream = agentLoop([createUserMessage("echo something")], context, config, undefined, mock.stream);
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for await (const _ of stream) {
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// drain
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}
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expect(contexts).toHaveLength(2);
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expect(contexts[0]?.batchId).toBe(contexts[1]?.batchId);
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expect(contexts[0]?.total).toBe(2);
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expect(contexts[0]?.toolCalls).toEqual([
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{ id: "tool-1", name: "echo" },
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{ id: "tool-2", name: "echo" },
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]);
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expect(contexts[0]?.index).toBe(0);
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expect(contexts[1]?.index).toBe(1);
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});
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it("should handle tool calls and results", async () => {
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const toolSchema = z.object({ value: z.string() });
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const executed: string[] = [];
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const tool: AgentTool<typeof toolSchema, { value: string }> = {
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name: "echo",
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label: "Echo",
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description: "Echo tool",
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parameters: toolSchema,
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async execute(_toolCallId, params) {
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executed.push(params.value);
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return {
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content: [{ type: "text", text: `echoed: ${params.value}` }],
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details: { value: params.value },
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};
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},
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};
|
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|
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const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
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const mock = createMockModel({
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responses: [
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{ content: [{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }] },
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{ content: ["done"] },
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],
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});
|
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const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
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const events: AgentEvent[] = [];
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const stream = agentLoop([createUserMessage("echo something")], context, config, undefined, mock.stream);
|
|
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for await (const event of stream) {
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events.push(event);
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}
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|
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// Tool should have been executed
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expect(executed).toEqual(["hello"]);
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|
|
// Should have tool execution events
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const toolStart = events.find(e => e.type === "tool_execution_start");
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const toolEnd = events.find(e => e.type === "tool_execution_end");
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expect(toolStart).toBeDefined();
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|
expect(toolEnd).toBeDefined();
|
|
if (toolEnd?.type === "tool_execution_end") {
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expect(toolEnd.isError).toBeFalsy();
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|
}
|
|
});
|
|
|
|
it("injects and strips intent when intent tracing is enabled", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const executedParams: Record<string, unknown>[] = [];
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
executedParams.push(params as Record<string, unknown>);
|
|
return {
|
|
content: [{ type: "text", text: `echoed: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{
|
|
content: [
|
|
{
|
|
type: "toolCall",
|
|
id: "tool-1",
|
|
name: "echo",
|
|
arguments: { value: "hello", [INTENT_FIELD]: "Read one file" },
|
|
},
|
|
],
|
|
},
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
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|
intentTracing: true,
|
|
};
|
|
|
|
const stream = agentLoop([createUserMessage("run")], context, config, undefined, mock.stream);
|
|
for await (const _ of stream) {
|
|
// drain
|
|
}
|
|
const messages = await stream.result();
|
|
const assistantWithToolCall = messages.find(
|
|
message => message.role === "assistant" && message.content.some(content => content.type === "toolCall"),
|
|
) as AssistantMessage | undefined;
|
|
const tracedToolCall = assistantWithToolCall?.content.find(content => content.type === "toolCall");
|
|
|
|
const firstRequestToolSchema = mock.calls[0]?.context.tools?.[0]?.parameters as
|
|
| { properties?: Record<string, unknown>; required?: string[] }
|
|
| undefined;
|
|
expect(firstRequestToolSchema?.properties).toMatchObject({
|
|
value: { type: "string" },
|
|
[INTENT_FIELD]: { type: "string" },
|
|
});
|
|
expect(firstRequestToolSchema?.required).toEqual(expect.arrayContaining([INTENT_FIELD]));
|
|
expect(executedParams).toEqual([{ value: "hello" }]);
|
|
expect(tracedToolCall?.type).toBe("toolCall");
|
|
if (tracedToolCall?.type === "toolCall") {
|
|
expect(tracedToolCall.intent).toBe("Read one file");
|
|
}
|
|
});
|
|
|
|
it("runs shared tools in parallel and emits completion-ordered results", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const startTimes: Record<string, number> = {};
|
|
const finishTimes: Record<string, number> = {};
|
|
const { promise: slowContinue, resolve: slowResolve } = Promise.withResolvers<void>();
|
|
const { promise: slowStarted, resolve: slowStartedResolve } = Promise.withResolvers<void>();
|
|
const { promise: fastFinished, resolve: fastFinishedResolve } = Promise.withResolvers<void>();
|
|
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
if (params.value === "slow") {
|
|
startTimes.slow = Bun.nanoseconds();
|
|
slowStartedResolve();
|
|
await slowContinue;
|
|
finishTimes.slow = Bun.nanoseconds();
|
|
} else {
|
|
await slowStarted;
|
|
startTimes.fast = Bun.nanoseconds();
|
|
finishTimes.fast = Bun.nanoseconds();
|
|
fastFinishedResolve();
|
|
}
|
|
return {
|
|
content: [{ type: "text", text: `echoed: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{
|
|
content: [
|
|
{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "slow" } },
|
|
{ type: "toolCall", id: "tool-2", name: "echo", arguments: { value: "fast" } },
|
|
],
|
|
},
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("start")], context, config, undefined, mock.stream);
|
|
const streamTask = (async () => {
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
})();
|
|
|
|
await fastFinished;
|
|
slowResolve();
|
|
await streamTask;
|
|
|
|
expect(startTimes.fast).toBeDefined();
|
|
expect(startTimes.slow).toBeDefined();
|
|
expect(finishTimes.fast).toBeDefined();
|
|
expect(finishTimes.slow).toBeDefined();
|
|
expect(startTimes.fast).toBeLessThan(finishTimes.slow);
|
|
expect(finishTimes.fast).toBeLessThan(finishTimes.slow);
|
|
|
|
const toolResultStarts = events.filter(
|
|
(e): e is Extract<AgentEvent, { type: "message_start" }> =>
|
|
e.type === "message_start" && e.message.role === "toolResult",
|
|
);
|
|
expect(toolResultStarts).toHaveLength(2);
|
|
expect((toolResultStarts[0].message as ToolResultMessage).toolCallId).toBe("tool-2");
|
|
expect((toolResultStarts[1].message as ToolResultMessage).toolCallId).toBe("tool-1");
|
|
|
|
const turnEndEvent = events.find((e): e is Extract<AgentEvent, { type: "turn_end" }> => e.type === "turn_end");
|
|
expect(turnEndEvent).toBeDefined();
|
|
if (!turnEndEvent) return;
|
|
expect(turnEndEvent.toolResults.map(result => result.toolCallId)).toEqual(["tool-2", "tool-1"]);
|
|
});
|
|
|
|
it("resolves function-form concurrency per call", async () => {
|
|
const toolSchema = z.object({ value: z.string(), exclusive: z.boolean().optional() });
|
|
const startTimes: Record<string, number> = {};
|
|
const finishTimes: Record<string, number> = {};
|
|
const { promise: slowContinue, resolve: slowResolve } = Promise.withResolvers<void>();
|
|
const { promise: slowStarted, resolve: slowStartedResolve } = Promise.withResolvers<void>();
|
|
const { promise: fastFinished, resolve: fastFinishedResolve } = Promise.withResolvers<void>();
|
|
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
concurrency: args => (args.exclusive === true ? "exclusive" : "shared"),
|
|
async execute(_toolCallId, params) {
|
|
if (params.value === "slow") {
|
|
startTimes.slow = Bun.nanoseconds();
|
|
slowStartedResolve();
|
|
await slowContinue;
|
|
finishTimes.slow = Bun.nanoseconds();
|
|
} else if (params.value === "fast") {
|
|
await slowStarted;
|
|
startTimes.fast = Bun.nanoseconds();
|
|
finishTimes.fast = Bun.nanoseconds();
|
|
fastFinishedResolve();
|
|
} else {
|
|
startTimes.exclusive = Bun.nanoseconds();
|
|
finishTimes.exclusive = Bun.nanoseconds();
|
|
}
|
|
return {
|
|
content: [{ type: "text", text: `echoed: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{
|
|
content: [
|
|
{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "slow" } },
|
|
{ type: "toolCall", id: "tool-2", name: "echo", arguments: { value: "fast" } },
|
|
{
|
|
type: "toolCall",
|
|
id: "tool-3",
|
|
name: "echo",
|
|
arguments: { value: "last", exclusive: true },
|
|
},
|
|
],
|
|
},
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("start")], context, config, undefined, mock.stream);
|
|
const streamTask = (async () => {
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
})();
|
|
|
|
await fastFinished;
|
|
slowResolve();
|
|
await streamTask;
|
|
|
|
// Both shared calls overlapped: fast started and finished while slow was running.
|
|
expect(startTimes.fast).toBeLessThan(finishTimes.slow);
|
|
expect(finishTimes.fast).toBeLessThan(finishTimes.slow);
|
|
// The exclusive call waited for every shared call to finish.
|
|
expect(startTimes.exclusive).toBeGreaterThan(finishTimes.slow);
|
|
expect(startTimes.exclusive).toBeGreaterThan(finishTimes.fast);
|
|
});
|
|
|
|
it("drops incomplete tool calls when assistant aborts before toolcall_end", async () => {
|
|
const context: AgentContext = {
|
|
systemPrompt: ["You are helpful."],
|
|
messages: [],
|
|
tools: [],
|
|
};
|
|
|
|
const abortController = new AbortController();
|
|
const mock = createMockModel();
|
|
const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
|
|
// Custom stream: emit a partial assistant that already contains a tool
|
|
// call, then abort before any `toolcall_end` event proves that the args
|
|
// completed. The agent must not synthesize a toolResult for that partial
|
|
// call; replaying it would preserve unsafe/incomplete arguments.
|
|
const streamFn = () => {
|
|
const stream = new AssistantMessageEventStream();
|
|
queueMicrotask(() => {
|
|
const partial = createAssistantMessage(
|
|
[{ type: "toolCall", id: "tool-1", name: "yield", arguments: { data: { ok: true } } }],
|
|
"toolUse",
|
|
);
|
|
stream.push({ type: "start", partial });
|
|
setTimeout(() => {
|
|
abortController.abort();
|
|
stream.push({ type: "done", reason: "toolUse", message: partial });
|
|
}, 0);
|
|
});
|
|
return stream;
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("start")], context, config, abortController.signal, streamFn);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
const toolResultEvent = events.find(
|
|
(e): e is Extract<AgentEvent, { type: "message_end" }> =>
|
|
e.type === "message_end" && e.message.role === "toolResult",
|
|
);
|
|
expect(toolResultEvent).toBeUndefined();
|
|
|
|
const assistantEnd = events.find(
|
|
(e): e is Extract<AgentEvent, { type: "message_end" }> =>
|
|
e.type === "message_end" && e.message.role === "assistant",
|
|
);
|
|
expect(assistantEnd).toBeDefined();
|
|
if (assistantEnd?.message.role !== "assistant") return;
|
|
expect(assistantEnd.message.stopReason).toBe("aborted");
|
|
expect(assistantEnd.message.content.some(block => block.type === "toolCall")).toBe(false);
|
|
});
|
|
|
|
it("should skip remaining tool calls when steering is queued", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const executed: string[] = [];
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
concurrency: "exclusive",
|
|
async execute(_toolCallId, params) {
|
|
executed.push(params.value);
|
|
return {
|
|
content: [{ type: "text", text: `ok:${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const queuedUserMessage = createUserMessage("interrupt");
|
|
let queuedDelivered = false;
|
|
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{
|
|
content: [
|
|
{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "first" } },
|
|
{ type: "toolCall", id: "tool-2", name: "echo", arguments: { value: "second" } },
|
|
],
|
|
},
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
interruptMode: "immediate",
|
|
getSteeringMessages: async () => {
|
|
// Return steering message after tool execution has started
|
|
if (executed.length >= 1 && !queuedDelivered) {
|
|
queuedDelivered = true;
|
|
return [queuedUserMessage];
|
|
}
|
|
return [];
|
|
},
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("start")], context, config, undefined, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
// Only the first tool should execute; the second is skipped after steering is queued.
|
|
expect(executed).toEqual(["first"]);
|
|
|
|
const toolEnds = events.filter(
|
|
(e): e is Extract<AgentEvent, { type: "tool_execution_end" }> => e.type === "tool_execution_end",
|
|
);
|
|
expect(toolEnds.length).toBe(2);
|
|
expect(toolEnds[0].isError).toBe(false);
|
|
expect(toolEnds[1].isError).toBe(true);
|
|
if (toolEnds[1].result.content[0]?.type === "text") {
|
|
expect(toolEnds[1].result.content[0].text).toContain("Skipped due to queued user message");
|
|
}
|
|
|
|
// Queued message should appear in events after the tool results and before the next model call.
|
|
const eventSequence = events.flatMap(event => {
|
|
if (event.type !== "message_start") return [];
|
|
if (event.message.role === "toolResult") return [`tool:${event.message.toolCallId}`];
|
|
if (event.message.role === "user" && typeof event.message.content === "string") {
|
|
return [event.message.content];
|
|
}
|
|
return [];
|
|
});
|
|
expect(eventSequence).toContain("interrupt");
|
|
expect(eventSequence.indexOf("tool:tool-1")).toBeLessThan(eventSequence.indexOf("interrupt"));
|
|
expect(eventSequence.indexOf("tool:tool-2")).toBeLessThan(eventSequence.indexOf("interrupt"));
|
|
|
|
// Interrupt message should be in context when second LLM call is made
|
|
const sawInterruptInContext = mock.calls[1]?.context.messages.some(
|
|
m => m.role === "user" && typeof m.content === "string" && m.content === "interrupt",
|
|
);
|
|
expect(sawInterruptInContext).toBe(true);
|
|
});
|
|
|
|
it("injects aside messages at the step boundary without interrupting tools", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const executed: string[] = [];
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
executed.push(params.value);
|
|
return {
|
|
content: [{ type: "text", text: `echoed: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{
|
|
content: [
|
|
{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "first" } },
|
|
{ type: "toolCall", id: "tool-2", name: "echo", arguments: { value: "second" } },
|
|
],
|
|
},
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
|
|
const asideMessage = createUserMessage("bg-job-complete");
|
|
let asideDelivered = false;
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
interruptMode: "immediate",
|
|
getAsideMessages: async () => {
|
|
if (!asideDelivered && executed.length >= 1) {
|
|
asideDelivered = true;
|
|
return [asideMessage];
|
|
}
|
|
return [];
|
|
},
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("start")], context, config, undefined, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
// Asides are non-interrupting: BOTH tools in the batch run (steering would skip the 2nd).
|
|
expect(executed).toEqual(["first", "second"]);
|
|
|
|
// The aside lands after the tool results, before the next model call.
|
|
const seq = events.flatMap(event => {
|
|
if (event.type !== "message_start") return [];
|
|
if (event.message.role === "toolResult") return [`tool:${event.message.toolCallId}`];
|
|
if (event.message.role === "user" && typeof event.message.content === "string") {
|
|
return [event.message.content];
|
|
}
|
|
return [];
|
|
});
|
|
expect(seq).toContain("bg-job-complete");
|
|
expect(seq.indexOf("tool:tool-2")).toBeLessThan(seq.indexOf("bg-job-complete"));
|
|
|
|
// The model saw it on the very next request — delivered mid-run, no yield required.
|
|
const sawAsideInContext = mock.calls[1]?.context.messages.some(
|
|
m => m.role === "user" && typeof m.content === "string" && m.content === "bg-job-complete",
|
|
);
|
|
expect(sawAsideInContext).toBe(true);
|
|
});
|
|
|
|
it("evaluates aside thunks at injection and skips ones that return null", async () => {
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [] };
|
|
const mock = createMockModel({ responses: [{ content: ["done"] }] });
|
|
let polls = 0;
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
// A lazy aside that decides, at injection time, NOT to inject (e.g. superseded).
|
|
getAsideMessages: async () => {
|
|
polls++;
|
|
return [() => null];
|
|
},
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("hi")], context, config, undefined, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
// The thunk was consulted...
|
|
expect(polls).toBeGreaterThan(0);
|
|
// ...but a null result injects nothing and triggers no wasted continuation turn.
|
|
const userStarts = events.filter(e => e.type === "message_start" && e.message.role === "user");
|
|
expect(userStarts).toHaveLength(1); // only the original prompt
|
|
expect(mock.calls).toHaveLength(1);
|
|
});
|
|
});
|
|
|
|
it("refreshes tools and system prompt between same-turn model calls", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
let activeSystemPrompt = "prompt-one";
|
|
let activeTools: Array<AgentTool<typeof toolSchema, { value: string }>> = [];
|
|
const betaTool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "beta",
|
|
label: "Beta",
|
|
description: "Beta tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
return {
|
|
content: [{ type: "text", text: `beta:${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
const alphaTool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "alpha",
|
|
label: "Alpha",
|
|
description: "Alpha tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
activeSystemPrompt = "prompt-two";
|
|
activeTools = [alphaTool, betaTool];
|
|
return {
|
|
content: [{ type: "text", text: `alpha:${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
activeTools = [alphaTool];
|
|
|
|
const context: AgentContext = {
|
|
systemPrompt: [activeSystemPrompt],
|
|
messages: [],
|
|
tools: activeTools,
|
|
};
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{ content: [{ type: "toolCall", id: "tool-1", name: "alpha", arguments: { value: "hello" } }] },
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
syncContextBeforeModelCall: async currentContext => {
|
|
currentContext.systemPrompt = [activeSystemPrompt];
|
|
currentContext.tools = activeTools;
|
|
},
|
|
};
|
|
|
|
const stream = agentLoop([createUserMessage("refresh tools")], context, config, undefined, mock.stream);
|
|
for await (const _ of stream) {
|
|
// drain
|
|
}
|
|
|
|
expect(mock.calls).toHaveLength(2);
|
|
expect(mock.calls[0]?.context.systemPrompt).toEqual(["prompt-one"]);
|
|
expect(mock.calls[0]?.context.tools?.map(tool => tool.name)).toEqual(["alpha"]);
|
|
expect(mock.calls[1]?.context.systemPrompt).toEqual(["prompt-two"]);
|
|
expect(mock.calls[1]?.context.tools?.map(tool => tool.name)).toEqual(["alpha", "beta"]);
|
|
});
|
|
|
|
describe("agentLoopContinue with AgentMessage", () => {
|
|
it("should throw when context has no messages", () => {
|
|
const context: AgentContext = {
|
|
systemPrompt: ["You are helpful."],
|
|
messages: [],
|
|
tools: [],
|
|
};
|
|
|
|
const mock = createMockModel();
|
|
const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
|
|
expect(() => agentLoopContinue(context, config)).toThrow("Cannot continue: no messages in context");
|
|
});
|
|
|
|
it("should continue from existing context without emitting user message events", async () => {
|
|
const userMessage = createUserMessage("Hello");
|
|
|
|
const context: AgentContext = {
|
|
systemPrompt: ["You are helpful."],
|
|
messages: [userMessage],
|
|
tools: [],
|
|
};
|
|
|
|
const mock = createMockModel({ responses: [{ content: ["Response"] }] });
|
|
const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoopContinue(context, config, undefined, mock.stream);
|
|
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
const messages = await stream.result();
|
|
|
|
// Should only return the new assistant message (not the existing user message)
|
|
expect(messages.length).toBe(1);
|
|
expect(messages[0].role).toBe("assistant");
|
|
|
|
// Should NOT have user message events (that's the key difference from agentLoop)
|
|
const messageEndEvents = events.filter(e => e.type === "message_end");
|
|
expect(messageEndEvents.length).toBe(1);
|
|
const firstEnd = messageEndEvents[0];
|
|
if (firstEnd?.type !== "message_end") throw new Error("Expected message_end");
|
|
expect(firstEnd.message.role).toBe("assistant");
|
|
});
|
|
|
|
it("should allow custom message types as last message (caller responsibility)", async () => {
|
|
// Custom message that will be converted to user message by convertToLlm
|
|
interface HookMessage {
|
|
role: "hookMessage";
|
|
text: string;
|
|
timestamp: number;
|
|
}
|
|
|
|
const hookMessage: HookMessage = {
|
|
role: "hookMessage",
|
|
text: "Hook content",
|
|
timestamp: Date.now(),
|
|
};
|
|
|
|
const context: AgentContext = {
|
|
systemPrompt: ["You are helpful."],
|
|
messages: [hookMessage as unknown as AgentMessage],
|
|
tools: [],
|
|
};
|
|
|
|
const mock = createMockModel({ responses: [{ content: ["Response to hook"] }] });
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: messages => {
|
|
// Convert hookMessage to user message
|
|
return messages
|
|
.map(m => {
|
|
const candidate = m as unknown as Partial<HookMessage>;
|
|
if (candidate.role === "hookMessage") {
|
|
return {
|
|
role: "user" as const,
|
|
content: candidate.text ?? "",
|
|
timestamp: candidate.timestamp ?? Date.now(),
|
|
};
|
|
}
|
|
return m;
|
|
})
|
|
.filter(m => m.role === "user" || m.role === "assistant" || m.role === "toolResult") as Message[];
|
|
},
|
|
};
|
|
|
|
// Should not throw - the hookMessage will be converted to user message
|
|
const stream = agentLoopContinue(context, config, undefined, mock.stream);
|
|
|
|
const events: AgentEvent[] = [];
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
const messages = await stream.result();
|
|
expect(messages.length).toBe(1);
|
|
expect(messages[0].role).toBe("assistant");
|
|
});
|
|
|
|
it("blocks tool execution when beforeToolCall returns block", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const executed: string[] = [];
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
executed.push(params.value);
|
|
return {
|
|
content: [{ type: "text", text: `echoed: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{ content: [{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }] },
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
beforeToolCall: async () => ({ block: true, reason: "policy: blocked" }),
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("echo something")], context, config, undefined, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
expect(executed).toEqual([]);
|
|
const toolEnd = events.find(e => e.type === "tool_execution_end");
|
|
expect(toolEnd).toBeDefined();
|
|
if (toolEnd?.type === "tool_execution_end") {
|
|
expect(toolEnd.isError).toBe(true);
|
|
expect(JSON.stringify(toolEnd.result)).toContain("policy: blocked");
|
|
}
|
|
});
|
|
|
|
it("passes beforeToolCall args mutations into tool.execute without revalidation", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const executed: Array<string | number> = [];
|
|
const tool: AgentTool<typeof toolSchema, { value: string | number }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
executed.push(params.value as string | number);
|
|
return {
|
|
content: [{ type: "text", text: `echoed: ${String(params.value)}` }],
|
|
details: { value: params.value as string | number },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{ content: [{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }] },
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
beforeToolCall: async ({ args }) => {
|
|
(args as { value: string | number }).value = 123;
|
|
return undefined;
|
|
},
|
|
};
|
|
|
|
const stream = agentLoop([createUserMessage("echo something")], context, config, undefined, mock.stream);
|
|
for await (const _ of stream) {
|
|
// drain
|
|
}
|
|
|
|
expect(executed).toEqual([123]);
|
|
});
|
|
|
|
it("afterToolCall overrides content and isError on the emitted tool result", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
return {
|
|
content: [{ type: "text", text: `original: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const seen: Array<{ args: unknown; isError: boolean }> = [];
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{ content: [{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }] },
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
afterToolCall: async ({ args, isError }) => {
|
|
seen.push({ args, isError });
|
|
return {
|
|
content: [{ type: "text", text: "rewritten" }],
|
|
isError: true,
|
|
};
|
|
},
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("echo something")], context, config, undefined, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
expect(seen).toEqual([{ args: { value: "hello" }, isError: false }]);
|
|
|
|
const toolEnd = events.find(e => e.type === "tool_execution_end");
|
|
expect(toolEnd).toBeDefined();
|
|
if (toolEnd?.type === "tool_execution_end") {
|
|
expect(toolEnd.isError).toBe(true);
|
|
expect(toolEnd.result.content).toEqual([{ type: "text", text: "rewritten" }]);
|
|
// details preserved when override omits the field
|
|
expect(toolEnd.result.details).toEqual({ value: "hello" });
|
|
}
|
|
|
|
const toolResultMessage = events
|
|
.filter(e => e.type === "message_start")
|
|
.map(e => (e.type === "message_start" ? e.message : undefined))
|
|
.find((m): m is AgentMessage => m !== undefined && m.role === "toolResult");
|
|
expect(toolResultMessage).toBeDefined();
|
|
if (toolResultMessage && toolResultMessage.role === "toolResult") {
|
|
expect(toolResultMessage.isError).toBe(true);
|
|
expect(toolResultMessage.content).toEqual([{ type: "text", text: "rewritten" }]);
|
|
}
|
|
});
|
|
|
|
it("runs afterToolCall for a completed result even when the run aborts before the hook", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const controller = new AbortController();
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
controller.abort("stop after tool");
|
|
return {
|
|
content: [{ type: "text", text: `original: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
let hookSawAbortedSignal = false;
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{ content: [{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }] },
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
afterToolCall: async (_context, signal) => {
|
|
hookSawAbortedSignal = signal?.aborted === true;
|
|
return { content: [{ type: "text", text: "rewritten after abort" }] };
|
|
},
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("echo")], context, config, controller.signal, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
expect(hookSawAbortedSignal).toBe(true);
|
|
const toolEnd = events.find(e => e.type === "tool_execution_end");
|
|
expect(toolEnd).toBeDefined();
|
|
if (toolEnd?.type === "tool_execution_end") {
|
|
expect(toolEnd.isError).toBe(false);
|
|
expect(toolEnd.result.content).toEqual([{ type: "text", text: "rewritten after abort" }]);
|
|
}
|
|
});
|
|
|
|
it("surfaces afterToolCall errors as a tool error result", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo",
|
|
parameters: toolSchema,
|
|
async execute(_toolCallId, params) {
|
|
return {
|
|
content: [{ type: "text", text: `ok: ${params.value}` }],
|
|
details: { value: params.value },
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{ content: [{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }] },
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
afterToolCall: async () => {
|
|
throw new Error("hook exploded");
|
|
},
|
|
};
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("echo")], context, config, undefined, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
const toolEnd = events.find(e => e.type === "tool_execution_end");
|
|
expect(toolEnd).toBeDefined();
|
|
if (toolEnd?.type === "tool_execution_end") {
|
|
expect(toolEnd.isError).toBe(true);
|
|
expect(JSON.stringify(toolEnd.result)).toContain("hook exploded");
|
|
}
|
|
});
|
|
it("runs onBeforeYield before polling follow-up messages", async () => {
|
|
const context: AgentContext = {
|
|
systemPrompt: ["You are helpful."],
|
|
messages: [],
|
|
tools: [],
|
|
};
|
|
const queuedFollowUps: AgentMessage[] = [];
|
|
let hookCalls = 0;
|
|
const mock = createMockModel({
|
|
responses: [{ content: ["first"] }, { content: ["second"] }],
|
|
});
|
|
const config: AgentLoopConfig = {
|
|
model: mock.model,
|
|
convertToLlm: identityConverter,
|
|
onBeforeYield: () => {
|
|
hookCalls++;
|
|
if (hookCalls === 1) {
|
|
queuedFollowUps.push(createUserMessage("follow-up"));
|
|
}
|
|
},
|
|
getFollowUpMessages: async () => queuedFollowUps.splice(0),
|
|
};
|
|
|
|
const stream = agentLoop([createUserMessage("initial")], context, config, undefined, mock.stream);
|
|
for await (const _ of stream) {
|
|
// drain
|
|
}
|
|
|
|
const messages = await stream.result();
|
|
expect(hookCalls).toBe(2);
|
|
expect(messages.map(message => message.role)).toEqual(["user", "assistant", "user", "assistant"]);
|
|
expect(messages[2]).toMatchObject({ role: "user", content: "follow-up" });
|
|
});
|
|
|
|
it("skips tool calls when the assistant turn was truncated by max_tokens (stop_reason: length) and tells the model to chunk", async () => {
|
|
// Regression for issue #1785 (`write` tool crash on >1020-line content).
|
|
// When a model emits a `write` call whose `content` argument exceeds the
|
|
// model's `max_tokens` output cap, the provider cuts the stream off mid-
|
|
// arguments and reports `stop_reason: length`. The agent must NOT execute
|
|
// the truncated call (its `content` is a partial string), AND the synthetic
|
|
// tool result must guide the model towards a chunked retry — otherwise the
|
|
// auto-continue loop re-emits the same oversized payload and the file never
|
|
// gets written ("write tool crash" from the reporter's POV).
|
|
const writeSchema = z.object({ path: z.string(), content: z.string() });
|
|
const executed: { path: string; content: string }[] = [];
|
|
const writeTool: AgentTool<typeof writeSchema, { path: string }> = {
|
|
name: "write",
|
|
label: "Write",
|
|
description: "Write tool",
|
|
parameters: writeSchema,
|
|
async execute(_id, params) {
|
|
executed.push({ path: params.path, content: params.content });
|
|
return { content: [{ type: "text", text: "ok" }], details: { path: params.path } };
|
|
},
|
|
};
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [writeTool] };
|
|
|
|
// The model emits one write tool call, then the stream ends with
|
|
// stop_reason: "length". The arguments field carries a truncated content
|
|
// payload — exactly what the streaming JSON parser produces when the
|
|
// closing quote/brace never arrive.
|
|
const truncatedContent = "line 1\nline 2\n... (cut off mid-string"; // no closing quote
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{
|
|
content: [
|
|
{
|
|
type: "toolCall",
|
|
id: "tc-write-1",
|
|
name: "write",
|
|
arguments: { path: "/tmp/huge.ts", content: truncatedContent },
|
|
},
|
|
],
|
|
stopReason: "length",
|
|
},
|
|
{
|
|
content: ["ok, I will split the write into smaller chunks"],
|
|
},
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
const stream = agentLoop([createUserMessage("write huge file")], context, config, undefined, mock.stream);
|
|
for await (const _event of stream) {
|
|
// drain
|
|
}
|
|
const messages = await stream.result();
|
|
|
|
// The tool MUST NOT have been executed — the arguments are mid-string and
|
|
// running them would persist a half-written file.
|
|
expect(executed).toEqual([]);
|
|
|
|
// The synthetic tool result must surface the truncation cause so the model
|
|
// can recover by chunking instead of re-emitting the same payload.
|
|
const toolResult = messages.find(m => m.role === "toolResult");
|
|
expect(toolResult).toBeDefined();
|
|
if (toolResult?.role !== "toolResult") throw new Error("expected tool result");
|
|
expect(toolResult.toolCallId).toBe("tc-write-1");
|
|
expect(toolResult.isError).toBe(true);
|
|
const text = toolResult.content
|
|
.filter((c): c is { type: "text"; text: string } => c.type === "text")
|
|
.map(c => c.text)
|
|
.join("\n");
|
|
expect(text).toContain("stop_reason: length");
|
|
expect(text).toMatch(/split|chunk/i);
|
|
});
|
|
it("fills whitespace-only error tool results so Anthropic does not 400", async () => {
|
|
const toolSchema = z.object({ value: z.string() });
|
|
const tool: AgentTool<typeof toolSchema, { value: string }> = {
|
|
name: "echo",
|
|
label: "Echo",
|
|
description: "Echo tool",
|
|
parameters: toolSchema,
|
|
async execute() {
|
|
return {
|
|
content: [{ type: "text", text: "\n\n\n\n\n" }],
|
|
isError: true,
|
|
};
|
|
},
|
|
};
|
|
|
|
const context: AgentContext = { systemPrompt: [""], messages: [], tools: [tool] };
|
|
const mock = createMockModel({
|
|
responses: [
|
|
{ content: [{ type: "toolCall", id: "tool-1", name: "echo", arguments: { value: "hello" } }] },
|
|
{ content: ["done"] },
|
|
],
|
|
});
|
|
const config: AgentLoopConfig = { model: mock.model, convertToLlm: identityConverter };
|
|
|
|
const events: AgentEvent[] = [];
|
|
const stream = agentLoop([createUserMessage("echo something")], context, config, undefined, mock.stream);
|
|
for await (const event of stream) {
|
|
events.push(event);
|
|
}
|
|
|
|
const toolEnd = events.find(e => e.type === "tool_execution_end");
|
|
expect(toolEnd).toBeDefined();
|
|
if (toolEnd?.type === "tool_execution_end") {
|
|
expect(toolEnd.isError).toBe(true);
|
|
expect(toolEnd.result.content).toEqual([{ type: "text", text: "Tool failed with no output." }]);
|
|
}
|
|
});
|
|
});
|