Yaowei Zheng
1156 lines
49 KiB
TypeScript
1156 lines
49 KiB
TypeScript
/**
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* Context compaction tests.
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*
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* - Trigger: context usage (the request.total of the most recent token_usage) or the session's
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* cumulative turn count **reaching** the threshold (>=); the check runs after every LLM
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* request emits token_usage, both mid-task and at the wrap-up round (reaching the threshold at
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* task end triggers compaction immediately, without waiting for the next task).
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* - summarize: appends a compaction prompt to the old LLM (merging in all of this round's tool
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* results first if mid-task); the summary is wrapped as a `[context_summary]` user text and fed
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* as the first input to the new LLM instance; on failure the original context is kept, never downgraded to discard.
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* The compaction request carries the session's toolset unchanged (the prompt-cache prefix must
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* stay byte-identical, #84), and a completed response only counts as success with a valid
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* summary — non-empty extracted text and no tool calls (issue #83). A rejected response has its
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* tool calls answered by synthesized failed outputs (pairing repair) and is retried under a
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* dedicated cap of 5 rejections; then the compaction fails. Transport timeout/malformed
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* attempts keep the shared reconnect cap.
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* - discard: deferred until task end if mid-task; sends no compaction request, just swaps in a new LLM instance directly.
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* - Process visibility: the compaction request's streamed output is never surfaced to the human,
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* only the paired compaction events are emitted; the dialogue is written to the old trace, and
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* on success the trace rotates into a new file (index+1, the new file starts with session_meta;
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* rotation is deferred until the new context has its first message to write).
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*/
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import { mkdtemp, rm, access, readdir } from "node:fs/promises";
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import { tmpdir } from "node:os";
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import { dirname, join } from "node:path";
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import { afterEach, beforeEach, describe, expect, it } from "vitest";
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import {
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assistantText,
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sessionMeta,
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thinkingMessage,
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tokenUsage,
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toolCall,
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toolCallOutput,
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userText,
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} from "../src/omnimessage/index.js";
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import type {
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CompactionBeginPayload,
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CompactionEndPayload,
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OmniMessage,
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TextPayload,
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TokenCounts,
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TokenUsagePayload,
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} from "../src/omnimessage/index.js";
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import type {
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ApproveFn,
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EnvironmentInterface,
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GenerativeModelParameters,
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LLMInterface,
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LLMOutcome,
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} from "../src/interfaces.js";
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import { ContextEngine } from "../src/engine/context-engine.js";
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import type { CompactionSettings } from "../src/engine/context-engine.js";
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import { GenerativeModel } from "../src/llm/index.js";
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import type { UniConfig, UniEvent, UniMessage } from "@prismshadow/agenthub";
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import { Writer, readTrace } from "../src/trace/index.js";
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// ---------------------------------------------------------------------------
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// Test fixtures
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// ---------------------------------------------------------------------------
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interface ScriptedResponse {
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messages: OmniMessage[];
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outcome?: LLMOutcome;
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}
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/** Fake LLM that responds according to a script, recording each input it receives. */
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class ScriptedLLM implements LLMInterface {
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calls: OmniMessage[][] = [];
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constructor(
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private readonly responses: ScriptedResponse[],
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readonly label = "llm",
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) {}
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async *streamGenerate(
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params: GenerativeModelParameters,
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): AsyncGenerator<OmniMessage, LLMOutcome> {
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this.calls.push(params.newMessages);
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const next = this.responses.shift();
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if (!next) {
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return { status: "failed", message: `${this.label}: no scripted response` };
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}
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for (const msg of next.messages) yield msg;
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return next.outcome ?? { status: "completed" };
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}
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}
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/** Fake Environment that never runs real commands: any tool call returns a fixed output. */
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const fakeEnvironment: EnvironmentInterface = {
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async listTools() {
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return [];
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},
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async *executeTool({ toolCall: tc }) {
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yield toolCallOutput({
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output: "tool ran",
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toolCallId: tc.payload.tool_call_id,
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});
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},
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toolPermission() {
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return "rw";
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},
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};
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const allowAll: ApproveFn = async () => "allow";
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/** Builds a token_usage: request.total is the context-usage figure, session.total is the cumulative one. */
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const usage = (requestTotal: number, sessionTotal: number): OmniMessage =>
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tokenUsage(
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{ cache_read: 0, cache_write: 0, output: 0, total: sessionTotal },
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{ cache_read: 0, cache_write: 0, output: 0, total: requestTotal },
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);
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const settings = (over: Partial<CompactionSettings> = {}): CompactionSettings => ({
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maxContextLength: 100,
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maxSessionTurns: -1,
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mode: "summarize",
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prompt: "COMPACT NOW",
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...over,
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});
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const metaMessage = sessionMeta({
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session_id: "sess_compact",
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provider: "custom",
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model_id: "test-model",
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model_context_window: 200000,
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system_prompt: "sp",
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tools: [],
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agent_state: "/tmp/state",
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workspace: "/tmp/ws",
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});
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async function collect(gen: AsyncGenerator<OmniMessage>): Promise<OmniMessage[]> {
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const all: OmniMessage[] = [];
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for await (const msg of gen) all.push(msg);
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return all;
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}
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type CompactionEventPayload = CompactionBeginPayload | CompactionEndPayload;
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const compactionEvents = (msgs: OmniMessage[]): CompactionEventPayload[] =>
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msgs
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.filter((m) => {
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const t = (m.payload as { type?: string }).type ?? "";
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return t === "compaction_begin" || t === "compaction_end";
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})
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.map((m) => m.payload as CompactionEventPayload);
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const payloadTypes = (msgs: OmniMessage[]): (string | undefined)[] =>
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msgs.map((m) => (m.payload as { type?: string }).type);
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const textOf = (m: OmniMessage): string => (m.payload as TextPayload).text;
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// ---------------------------------------------------------------------------
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// Tests
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// ---------------------------------------------------------------------------
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describe("context compaction", () => {
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let traces: string;
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beforeEach(async () => {
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traces = await mkdtemp(join(tmpdir(), "penguin-compaction-"));
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});
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afterEach(async () => {
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await rm(traces, { recursive: true, force: true });
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});
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it("summarize at task boundary: paired events, hidden dialogue, trace rotation, summary joins next prompt", async () => {
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const llm1 = new ScriptedLLM(
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[
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// Task 1's final reply: context usage 150 > threshold 100 -> triggers at the boundary.
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{ messages: [assistantText("answer one"), usage(150, 150)] },
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// Compaction request: summary + usage (counted into the session cumulative total).
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{
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messages: [assistantText("[summary]the distilled summary[/summary]"), usage(160, 310)],
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},
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],
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"llm1",
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);
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const llm2 = new ScriptedLLM(
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[{ messages: [assistantText("answer two"), usage(20, 330)] }],
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"llm2",
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);
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let factoryTokens: TokenCounts | null = null;
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const trace = new Writer({ tracesDir: traces, sessionId: "sess_compact" });
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const engine = new ContextEngine({
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llm: llm1,
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environment: fakeEnvironment,
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trace,
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sessionMeta: metaMessage,
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compaction: settings(),
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createLLM: (tokens) => {
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factoryTokens = tokens;
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return llm2;
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},
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});
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const oldPath = trace.currentPath();
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const out1 = await collect(engine.run([userText("task one")], { approve: allowAll }));
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// Paired compaction events: start carries reason/mode/context/turns, stop carries status.
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const events = compactionEvents(out1);
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expect(events).toHaveLength(2);
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expect(events[0]).toMatchObject({
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type: "compaction_begin",
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reason: "context",
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mode: "summarize",
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context: 150,
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turns: 1,
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});
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expect(events[1]).toMatchObject({ type: "compaction_end", status: "completed" });
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// The compaction process is invisible to the human: the compaction prompt and summary text are never pushed to the output stream.
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const texts = out1.filter((m) => (m.payload as { type?: string }).type === "text").map(textOf);
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expect(texts.some((t) => t.includes("COMPACT NOW"))).toBe(false);
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expect(texts.some((t) => t.includes("distilled"))).toBe(false);
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// Exception: the compaction request's token_usage IS pushed to the output stream, sitting between the paired compaction events (the frontend counts it in stats).
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const types1 = payloadTypes(out1);
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const between = out1.slice(
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types1.indexOf("compaction_begin") + 1,
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types1.lastIndexOf("compaction_end"),
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);
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const usageBetween = between.filter(
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(m) => (m.payload as { type?: string }).type === "token_usage",
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);
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expect(usageBetween).toHaveLength(1);
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expect((usageBetween[0]!.payload as TokenUsagePayload).request.total).toBe(160);
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// The new LLM instance carries over the session's cumulative tokens (including compaction request usage).
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expect(factoryTokens).toMatchObject({ total: 310 });
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// The summary is merged with the next user prompt as the new LLM instance's first input.
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await collect(engine.run([userText("task two")], { approve: allowAll }));
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expect(llm1.calls).toHaveLength(2);
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expect(llm2.calls).toHaveLength(1);
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const firstInput = llm2.calls[0]!.map(textOf);
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expect(firstInput[0]).toBe("[context_summary]\nthe distilled summary\n[/context_summary]");
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expect(firstInput[1]).toBe("task two");
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// Trace splits into files: the old file contains the compaction dialogue and paired events; the new file starts with session_meta.
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const oldTrace = await readTrace(oldPath);
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const oldTypes = payloadTypes(oldTrace);
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expect(oldTypes.filter((t) => t?.startsWith("compaction_"))).toHaveLength(2);
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expect(oldTrace.some((m) => (m.payload as { text?: string }).text === "COMPACT NOW")).toBe(
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true,
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);
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const newTrace = await readTrace(trace.currentPath());
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expect(trace.currentPath()).not.toBe(oldPath);
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expect(newTrace[0]!.type).toBe("session_meta");
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expect(
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newTrace.some((m) =>
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((m.payload as { text?: string }).text ?? "").startsWith("[context_summary]"),
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),
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).toBe(true);
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});
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it("summarize mid-task: tool outputs pair into the compaction request, summary alone feeds the new LLM", async () => {
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const llm1 = new ScriptedLLM(
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[
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// Round 1: tool call + over-threshold usage -> triggers mid-task.
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{
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messages: [toolCall({ name: "t", arguments: "{}", toolCallId: "c1" }), usage(150, 150)],
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},
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// Compaction request (should include c1's tool_call_output plus the compaction prompt).
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{ messages: [assistantText("[summary]continue: finish step 2[/summary]")] },
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],
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"llm1",
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);
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const llm2 = new ScriptedLLM(
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[{ messages: [assistantText("task done"), usage(30, 200)] }],
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"llm2",
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);
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const engine = new ContextEngine({
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llm: llm1,
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environment: fakeEnvironment,
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sessionMeta: metaMessage,
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compaction: settings(),
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createLLM: () => llm2,
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});
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const out = await collect(engine.run([userText("do task")], { approve: allowAll }));
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// Compaction request: all of this round's tool results, paired with their tool_calls, are sent to the old instance along with the compaction prompt.
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expect(llm1.calls).toHaveLength(2);
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const compactionInput = llm1.calls[1]!;
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const inputTypes = payloadTypes(compactionInput);
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expect(inputTypes).toEqual(["tool_call_output", "text"]);
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expect((compactionInput[1]!.payload as TextPayload).text).toBe("COMPACT NOW");
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// The summary itself is the new instance's first input (no hardcoded continuation instruction appended); the task is finished by the new context.
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expect(llm2.calls).toHaveLength(1);
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expect(llm2.calls[0]!.map(textOf)).toEqual([
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"[context_summary]\ncontinue: finish step 2\n[/context_summary]",
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]);
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const finalTexts = out
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.filter((m) => (m.payload as { type?: string }).type === "text")
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.map(textOf);
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expect(finalTexts).toContain("task done");
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expect(compactionEvents(out).map((e) => e.type)).toEqual([
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"compaction_begin",
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"compaction_end",
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]);
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});
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it("summarize failure keeps the old context and does NOT downgrade to discard", async () => {
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const llm1 = new ScriptedLLM(
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[
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{
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messages: [toolCall({ name: "t", arguments: "{}", toolCallId: "c1" }), usage(150, 150)],
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},
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// Compaction request fails (not retryable).
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{ messages: [], outcome: { status: "failed", message: "auth error" } },
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// Original context is kept: the task continues, tool outputs feed back into the old instance as usual (context usage keeps growing).
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{ messages: [assistantText("finished on old context"), usage(190, 340)] },
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// Second trigger (context still over the limit) -> retries compaction at the boundary, this time succeeding.
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{ messages: [assistantText("[summary]second try[/summary]")] },
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],
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"llm1",
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);
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const llm2 = new ScriptedLLM([], "llm2");
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let created = 0;
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const trace = new Writer({ tracesDir: traces, sessionId: "sess_keep" });
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const engine = new ContextEngine({
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llm: llm1,
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environment: fakeEnvironment,
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trace,
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sessionMeta: metaMessage,
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compaction: settings(),
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createLLM: () => {
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created += 1;
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return llm2;
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},
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});
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const oldPath = trace.currentPath();
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const out = await collect(engine.run([userText("go")], { approve: allowAll }));
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// Two event pairs: the first has stop=failed (abandoned, original context kept), the second succeeds.
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const events = compactionEvents(out);
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expect(
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events.map((e) => `${e.type}:${(e as Partial<CompactionEndPayload>).status ?? ""}`),
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).toEqual([
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"compaction_begin:",
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"compaction_end:failed",
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"compaction_begin:",
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"compaction_end:completed",
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]);
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// No LLM swap and no trace file split at the moment of failure; rotation happens only after success.
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expect(created).toBe(1);
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expect(llm1.calls).toHaveLength(4);
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// After the failure, the input fed back into the old instance is this round's tool output.
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expect(payloadTypes(llm1.calls[2]!)).toEqual(["tool_call_output"]);
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const oldTrace = await readTrace(oldPath);
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// Still written to the same file after a failed stop (the failed compaction attempt stays auditable); the old file is closed off only after success.
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expect(payloadTypes(oldTrace).filter((t) => t?.startsWith("compaction_"))).toHaveLength(4);
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// Trace rotation is deferred until the next message to write: the current path is unchanged right after a successful compaction.
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expect(trace.currentPath()).toBe(oldPath);
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});
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it("defers trace rotation after boundary compaction until the next run writes", async () => {
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const llm1 = new ScriptedLLM(
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[
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{ messages: [assistantText("answer"), usage(150, 150)] },
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{ messages: [assistantText("[summary]s[/summary]")] },
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],
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"llm1",
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);
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const llm2 = new ScriptedLLM(
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[{ messages: [assistantText("next done"), usage(10, 160)] }],
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"llm2",
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);
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const trace = new Writer({ tracesDir: traces, sessionId: "sess_lazy" });
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const engine = new ContextEngine({
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llm: llm1,
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environment: fakeEnvironment,
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trace,
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sessionMeta: metaMessage,
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compaction: settings(),
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createLLM: () => llm2,
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});
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const oldPath = trace.currentPath();
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await collect(engine.run([userText("task 1")], { approve: allowAll }));
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// A new file is not created right after boundary compaction completes: the current path is unchanged, and only the old file exists on disk.
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expect(trace.currentPath()).toBe(oldPath);
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expect(await readdir(dirname(oldPath))).toEqual(["sess_lazy_001.jsonl"]);
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await collect(engine.run([userText("task 2")], { approve: allowAll }));
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// Rotation happens only once the next round has a message to write: the new file opens with session_meta, followed by the summary and the new prompt.
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expect(trace.currentPath()).not.toBe(oldPath);
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const newTrace = await readTrace(trace.currentPath());
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expect(newTrace[0]!.type).toBe("session_meta");
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expect(
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((newTrace[1]!.payload as { text?: string }).text ?? "").startsWith("[context_summary]"),
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).toBe(true);
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expect((newTrace[2]!.payload as { text?: string }).text).toBe("task 2");
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});
|
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it("reconnect exhaustion on the compaction request converges to failed", async () => {
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const llm1 = new ScriptedLLM(
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[
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{ messages: [assistantText("answer"), usage(150, 150)] },
|
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{ messages: [], outcome: { status: "timeout" } },
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{ messages: [], outcome: { status: "timeout" } },
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],
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"llm1",
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);
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const engine = new ContextEngine({
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llm: llm1,
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environment: fakeEnvironment,
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compaction: settings(),
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createLLM: () => llm1,
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compactionMaxReconnects: 1,
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reconnectBackoffMs: 1,
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});
|
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const out = await collect(engine.run([userText("go")], { approve: allowAll }));
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const events = compactionEvents(out);
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expect(events[1]).toMatchObject({ type: "compaction_end", status: "failed" });
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// The retry resends the original input (tool results + prompt; here there are no tool results, just the prompt).
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expect(llm1.calls).toHaveLength(3);
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expect(payloadTypes(llm1.calls[2]!)).toEqual(["text"]);
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});
|
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it("the compaction loop uses its own cap, not the shared maxReconnects ladder", async () => {
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// Compaction failure has graceful semantics (the original context is kept, compaction
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// retries on the next trigger), so it fails fast: with compactionMaxReconnects=2, the
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// compaction request runs 1+2 attempts and gives up — even though maxReconnects is far
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// larger and would have kept the session stalled through the full exponential ladder.
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const llm1 = new ScriptedLLM(
|
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[
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{ messages: [assistantText("answer"), usage(150, 150)] },
|
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{ messages: [], outcome: { status: "timeout" } },
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|
{ messages: [], outcome: { status: "timeout" } },
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{ messages: [], outcome: { status: "timeout" } },
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// Never reached: the compaction cap stops at 3 compaction attempts in total.
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{ messages: [assistantText("[summary]late[/summary]")] },
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],
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"llm1",
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);
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const recorded: OmniMessage[] = [];
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const engine = new ContextEngine({
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llm: llm1,
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environment: fakeEnvironment,
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compaction: settings(),
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createLLM: () => llm1,
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maxReconnects: 8,
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compactionMaxReconnects: 2,
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reconnectBackoffMs: 1,
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trace: {
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write: async (m) => {
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recorded.push(m);
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},
|
|
},
|
|
});
|
|
|
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const out = await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
const events = compactionEvents(out);
|
|
expect(events[1]).toMatchObject({ type: "compaction_end", status: "failed" });
|
|
// 1 turn request + 3 compaction attempts (initial + compactionMaxReconnects retries).
|
|
expect(llm1.calls).toHaveLength(4);
|
|
// The Trace-written compaction request_ends announce the planned backoff under the
|
|
// COMPACTION cap (base 1ms: 1, then 2), with none on the final failure — these events
|
|
// are never streamed, so the value lands in the Trace record only.
|
|
const retryPlans = recorded
|
|
.filter((m) => (m.payload as { type?: string }).type === "request_end")
|
|
.map((m) => (m.payload as { retry_in_ms?: number }).retry_in_ms);
|
|
expect(retryPlans).toEqual([undefined, 1, 2, undefined]);
|
|
});
|
|
|
|
it("an empty compaction response (thinking only, no text) is rejected: 5 attempts, then failed with the context kept", async () => {
|
|
// Issue #83: the compaction request completes but yields no text. Committing the empty
|
|
// summary would discard the whole context and lose the task state — the response is
|
|
// rejected and retried under the dedicated rejection cap (5 attempts, #84), then the
|
|
// compaction fails while the original context and Trace file stay current.
|
|
const empty = (n: number): ScriptedResponse => ({
|
|
messages: [thinkingMessage(`pondering, attempt ${n}, no text`)],
|
|
});
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
{ messages: [assistantText("answer one"), usage(150, 150)] },
|
|
// Five completed-but-empty compaction attempts: the dedicated cap allows exactly 5
|
|
// rejections. compactionMaxReconnects is 1 here on purpose — rejections must NOT
|
|
// consume the transport reconnect budget, or the loop would stop after 2 attempts.
|
|
empty(1),
|
|
empty(2),
|
|
empty(3),
|
|
empty(4),
|
|
empty(5),
|
|
// Original context kept: the next run stays on this instance (usage under the
|
|
// threshold here so the failed compaction isn't immediately retriggered).
|
|
{ messages: [assistantText("continuing on the old context"), usage(60, 370)] },
|
|
],
|
|
"llm1",
|
|
);
|
|
let created = 0;
|
|
const trace = new Writer({ tracesDir: traces, sessionId: "sess_empty" });
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
trace,
|
|
sessionMeta: metaMessage,
|
|
compaction: settings(),
|
|
createLLM: () => {
|
|
created += 1;
|
|
return new ScriptedLLM([], "llm2");
|
|
},
|
|
compactionMaxReconnects: 1,
|
|
reconnectBackoffMs: 1,
|
|
});
|
|
const oldPath = trace.currentPath();
|
|
|
|
const out1 = await collect(engine.run([userText("task one")], { approve: allowAll }));
|
|
|
|
// Exactly one event pair, ending failed — an empty summary is never a completed compaction.
|
|
const events = compactionEvents(out1);
|
|
expect(
|
|
events.map((e) => `${e.type}:${(e as Partial<CompactionEndPayload>).status ?? ""}`),
|
|
).toEqual(["compaction_begin:", "compaction_end:failed"]);
|
|
// No rejected attempt's token_usage is surfaced (only a successful compaction yields
|
|
// its usage between the paired events).
|
|
const types1 = payloadTypes(out1);
|
|
const between = out1.slice(
|
|
types1.indexOf("compaction_begin") + 1,
|
|
types1.lastIndexOf("compaction_end"),
|
|
);
|
|
expect(between.filter((m) => (m.payload as { type?: string }).type === "token_usage")).toEqual(
|
|
[],
|
|
);
|
|
// Turn + exactly five compaction attempts (the 5th rejection exhausts the cap, no 6th
|
|
// request), each resending the prompt unchanged — an empty rejection needs no repair.
|
|
expect(llm1.calls).toHaveLength(6);
|
|
for (let i = 1; i <= 5; i += 1) {
|
|
expect(llm1.calls[i]!.map(textOf)).toEqual(["COMPACT NOW"]);
|
|
}
|
|
// Rejection resends are immediate, never announced: no compaction request_end carries a
|
|
// retry_in_ms (they all end `completed`, unlike the transport ladder's timeout ends).
|
|
const rejectionPlans = (await readTrace(oldPath))
|
|
.filter((m) => (m.payload as { type?: string }).type === "request_end")
|
|
.map((m) => (m.payload as { retry_in_ms?: number }).retry_in_ms);
|
|
expect(rejectionPlans.every((p) => p === undefined)).toBe(true);
|
|
// No LLM swap and no Trace rotation: the old file is still current.
|
|
expect(created).toBe(0);
|
|
expect(trace.currentPath()).toBe(oldPath);
|
|
|
|
// Subsequent turns still run on the original context: the same instance serves the next
|
|
// run and its input is the plain new prompt — no [context_summary] injected.
|
|
await collect(engine.run([userText("task two")], { approve: allowAll }));
|
|
expect(llm1.calls).toHaveLength(7);
|
|
expect(llm1.calls[6]!.map(textOf)).toEqual(["task two"]);
|
|
expect(trace.currentPath()).toBe(oldPath);
|
|
expect(await readdir(dirname(oldPath))).toEqual(["sess_empty_001.jsonl"]);
|
|
});
|
|
|
|
it("tool-calling rejections exhaust the 5-attempt cap: every call is paired, and the next ordinary turn stays clean", async () => {
|
|
// A tool-calling response is not a summary — even when it also carries plausible summary
|
|
// text — but its assistant turn IS committed on the live LLM object. Each rejection's
|
|
// calls are answered with synthesized failed outputs (written to Trace, prepended to the
|
|
// retried input), so no tool_use ever dangles: after the compaction fails, the same
|
|
// object must still serve ordinary turns with a well-formed history (#84 review).
|
|
const callWith = (id: string): ScriptedResponse => ({
|
|
messages: [
|
|
assistantText("[summary]looks plausible[/summary]"),
|
|
toolCall({ name: "t", arguments: "{}", toolCallId: id }),
|
|
],
|
|
});
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
{ messages: [assistantText("answer"), usage(150, 150)] },
|
|
callWith("c1"),
|
|
callWith("c2"),
|
|
callWith("c3"),
|
|
callWith("c4"),
|
|
callWith("c5"),
|
|
{ messages: [assistantText("still on the old context"), usage(60, 300)] },
|
|
],
|
|
"llm1",
|
|
);
|
|
let created = 0;
|
|
const trace = new Writer({ tracesDir: traces, sessionId: "sess_paired" });
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
trace,
|
|
sessionMeta: metaMessage,
|
|
compaction: settings(),
|
|
createLLM: () => {
|
|
created += 1;
|
|
return new ScriptedLLM([], "llm2");
|
|
},
|
|
compactionMaxReconnects: 1,
|
|
reconnectBackoffMs: 1,
|
|
});
|
|
const oldPath = trace.currentPath();
|
|
|
|
const out = await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
const events = compactionEvents(out);
|
|
expect(events[1]).toMatchObject({ type: "compaction_end", status: "failed" });
|
|
// The rejected tool calls are never approved or executed, and nothing of the compaction
|
|
// dialogue (repairs included) reaches the output stream.
|
|
expect(payloadTypes(out)).not.toContain("approval_decision");
|
|
expect(payloadTypes(out)).not.toContain("tool_call_output");
|
|
expect(created).toBe(0);
|
|
|
|
// Five attempts; from the second on, the input leads with the repair answering the
|
|
// previous rejection's call, then re-issues the prompt.
|
|
expect(llm1.calls).toHaveLength(6);
|
|
for (let attempt = 2; attempt <= 5; attempt += 1) {
|
|
const retry = llm1.calls[attempt]!;
|
|
expect(payloadTypes(retry)).toEqual(["tool_call_output", "text"]);
|
|
const repair = retry[0]!.payload as {
|
|
tool_call_id: string;
|
|
output: string;
|
|
stop_reason?: string;
|
|
};
|
|
expect(repair.tool_call_id).toBe(`c${attempt - 1}`);
|
|
expect(repair.output).toBe(
|
|
"[tool error] the compaction request expects a summary, not tool calls",
|
|
);
|
|
expect(repair.stop_reason).toBe("failed");
|
|
expect(textOf(retry[1]!)).toBe("COMPACT NOW");
|
|
}
|
|
|
|
// All five synthesized repairs are written to the (old) Trace for replay to mirror.
|
|
const repairIds = (await readTrace(oldPath))
|
|
.filter((m) => {
|
|
const p = m.payload as { type?: string; output?: string };
|
|
return (
|
|
p.type === "tool_call_output" &&
|
|
p.output === "[tool error] the compaction request expects a summary, not tool calls"
|
|
);
|
|
})
|
|
.map((m) => (m.payload as { tool_call_id: string }).tool_call_id);
|
|
expect(repairIds).toEqual(["c1", "c2", "c3", "c4", "c5"]);
|
|
|
|
// The next ordinary turn on the SAME engine runs cleanly: the final rejection's repair is
|
|
// held as carry-over and leads the next request, so the committed history the LLM sees
|
|
// never leaves c5's tool_use unanswered — no dangling pairing, no [context_summary].
|
|
await collect(engine.run([userText("next")], { approve: allowAll }));
|
|
expect(llm1.calls).toHaveLength(7);
|
|
const nextTurn = llm1.calls[6]!;
|
|
expect(payloadTypes(nextTurn)).toEqual(["tool_call_output", "text"]);
|
|
expect((nextTurn[0]!.payload as { tool_call_id: string }).tool_call_id).toBe("c5");
|
|
expect(textOf(nextTurn[1]!)).toBe("next");
|
|
// Carry-over is spent: it does not leak into later runs.
|
|
await collect(engine.run([userText("later")], { approve: allowAll }));
|
|
expect(llm1.calls[7]!.map(textOf)).toEqual(["later"]);
|
|
});
|
|
|
|
it("a valid summary on the 5th and final allowed attempt completes the compaction", async () => {
|
|
// Counting pin for the rejection cap: four rejected attempts spend the budget but the 5th
|
|
// attempt still gets its chance — a valid summary there succeeds (5 rejections would fail).
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
{ messages: [assistantText("answer"), usage(150, 150)] },
|
|
// Attempts 1-4: empty (thinking only) -> rejected, retried.
|
|
{ messages: [thinkingMessage("blank stare 1"), usage(160, 310)] },
|
|
{ messages: [thinkingMessage("blank stare 2")] },
|
|
{ messages: [thinkingMessage("blank stare 3")] },
|
|
{ messages: [thinkingMessage("blank stare 4")] },
|
|
// Attempt 5: a real summary -> the compaction completes with THIS attempt's output.
|
|
{ messages: [assistantText("[summary]fifth attempt wins[/summary]"), usage(170, 480)] },
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("fresh"), usage(20, 500)] }], "llm2");
|
|
let factoryTokens: TokenCounts | null = null;
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
createLLM: (tokens) => {
|
|
factoryTokens = tokens;
|
|
return llm2;
|
|
},
|
|
maxReconnects: 1,
|
|
reconnectBackoffMs: 1,
|
|
});
|
|
|
|
const out = await collect(engine.run([userText("task one")], { approve: allowAll }));
|
|
const events = compactionEvents(out);
|
|
expect(events).toHaveLength(2);
|
|
expect(events[1]).toMatchObject({ type: "compaction_end", status: "completed" });
|
|
// Only the adopted attempt's token_usage is surfaced between the paired events; rejected
|
|
// attempts' usage still feeds the Session cumulative totals (see below) but is not shown.
|
|
const types = payloadTypes(out);
|
|
const between = out.slice(
|
|
types.indexOf("compaction_begin") + 1,
|
|
types.lastIndexOf("compaction_end"),
|
|
);
|
|
const usageBetween = between.filter(
|
|
(m) => (m.payload as { type?: string }).type === "token_usage",
|
|
);
|
|
expect(usageBetween).toHaveLength(1);
|
|
expect((usageBetween[0]!.payload as TokenUsagePayload).request.total).toBe(170);
|
|
// Session cumulative tokens carried into the new instance include the rejected attempts' usage.
|
|
expect(factoryTokens).toMatchObject({ total: 480 });
|
|
|
|
// The new context opens with the 5th attempt's summary.
|
|
await collect(engine.run([userText("task two")], { approve: allowAll }));
|
|
expect(llm1.calls).toHaveLength(6);
|
|
expect(llm2.calls[0]!.map(textOf)).toEqual([
|
|
"[context_summary]\nfifth attempt wins\n[/context_summary]",
|
|
"task two",
|
|
]);
|
|
});
|
|
|
|
it("a tool-calling rejection is repaired and the retry's summary completes the compaction", async () => {
|
|
// The pairing repair (#84 review): the rejected attempt's assistant turn — committed by
|
|
// the stateful LLM — ends in tool_use blocks that were never dispatched. Before retrying,
|
|
// the engine answers each with a synthesized failed tool_call_output (written to Trace),
|
|
// prepended to the retried input so the provider sees tool_use/tool_result paired, and
|
|
// the retry then has a real chance to summarize.
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
{ messages: [assistantText("answer"), usage(150, 150)] },
|
|
// Attempt 1: rejected — the model reached for a tool instead of summarizing.
|
|
{
|
|
messages: [
|
|
assistantText("[summary]tempting[/summary]"),
|
|
toolCall({ name: "t", arguments: "{}", toolCallId: "c1" }),
|
|
],
|
|
},
|
|
// Attempt 2 (carrying the repair): a real summary.
|
|
{ messages: [assistantText("[summary]real summary[/summary]"), usage(170, 400)] },
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("fresh"), usage(20, 420)] }], "llm2");
|
|
const trace = new Writer({ tracesDir: traces, sessionId: "sess_repair" });
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
trace,
|
|
sessionMeta: metaMessage,
|
|
compaction: settings(),
|
|
createLLM: () => llm2,
|
|
reconnectBackoffMs: 1,
|
|
});
|
|
const oldPath = trace.currentPath();
|
|
|
|
const out = await collect(engine.run([userText("task one")], { approve: allowAll }));
|
|
expect(compactionEvents(out)[1]).toMatchObject({
|
|
type: "compaction_end",
|
|
status: "completed",
|
|
});
|
|
|
|
// The retried input answers the rejected attempt's call first, then re-issues the prompt.
|
|
expect(llm1.calls).toHaveLength(3);
|
|
const retry = llm1.calls[2]!;
|
|
expect(payloadTypes(retry)).toEqual(["tool_call_output", "text"]);
|
|
const repair = retry[0]!.payload as {
|
|
tool_call_id: string;
|
|
output: string;
|
|
stop_reason?: string;
|
|
};
|
|
expect(repair.tool_call_id).toBe("c1");
|
|
expect(repair.output).toBe(
|
|
"[tool error] the compaction request expects a summary, not tool calls",
|
|
);
|
|
expect(repair.stop_reason).toBe("failed");
|
|
expect(textOf(retry[1]!)).toBe("COMPACT NOW");
|
|
|
|
// The repair belongs to the compaction dialogue: written to the old Trace (so replay
|
|
// mirrors the pairing), never pushed to the output stream.
|
|
const repairsInTrace = (await readTrace(oldPath)).filter((m) => {
|
|
const p = m.payload as { type?: string; tool_call_id?: string };
|
|
return p.type === "tool_call_output" && p.tool_call_id === "c1";
|
|
});
|
|
expect(repairsInTrace).toHaveLength(1);
|
|
expect(payloadTypes(out)).not.toContain("tool_call_output");
|
|
|
|
// The new context opens with the retry's summary.
|
|
await collect(engine.run([userText("task two")], { approve: allowAll }));
|
|
expect(llm2.calls[0]!.map(textOf)).toEqual([
|
|
"[context_summary]\nreal summary\n[/context_summary]",
|
|
"task two",
|
|
]);
|
|
});
|
|
|
|
it("a non-completed tool_call (interruption-closure shape) does not reject the summary", async () => {
|
|
// Same filter as the ordinary turn loop: only stop_reason === "completed" tool_calls are
|
|
// real requests. A tool_call synthesized to close out an interruption carries the
|
|
// interruption reason — it is structural, gets no synthesized repair, and must not cost
|
|
// a rejection attempt.
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
{ messages: [assistantText("answer"), usage(150, 150)] },
|
|
{
|
|
messages: [
|
|
toolCall({ name: "t", arguments: "", toolCallId: "cz", stopReason: "timeout" }),
|
|
assistantText("[summary]still fine[/summary]"),
|
|
],
|
|
},
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("ok"), usage(10, 200)] }], "llm2");
|
|
const trace = new Writer({ tracesDir: traces, sessionId: "sess_closure" });
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
trace,
|
|
sessionMeta: metaMessage,
|
|
compaction: settings(),
|
|
createLLM: () => llm2,
|
|
});
|
|
const oldPath = trace.currentPath();
|
|
|
|
const out = await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
expect(compactionEvents(out)[1]).toMatchObject({
|
|
type: "compaction_end",
|
|
status: "completed",
|
|
});
|
|
// One compaction attempt, no retry, and no repair synthesized for the closure call.
|
|
expect(llm1.calls).toHaveLength(2);
|
|
const closureRepairs = (await readTrace(oldPath)).filter((m) => {
|
|
const p = m.payload as { type?: string; tool_call_id?: string };
|
|
return p.type === "tool_call_output" && p.tool_call_id === "cz";
|
|
});
|
|
expect(closureRepairs).toEqual([]);
|
|
});
|
|
|
|
it("the compaction request carries exactly the same tools as ordinary requests (prompt-cache pin)", async () => {
|
|
// Owner constraint (#84): compaction runs exactly when the context is at its largest, and
|
|
// the provider's prompt cache only holds if the request prefix — the tool list included —
|
|
// stays byte-identical to the ordinary turns'. The engine passes no per-request tool
|
|
// override of any kind, and GenerativeModel serves every request from the same frozen
|
|
// config, so the compaction request's tools are the session's tools, verbatim.
|
|
const configs: (UniConfig | undefined)[] = [];
|
|
const scripted = [
|
|
// Turn 1 answer: usage above the compaction threshold (total 151 >= 100).
|
|
{ text: "answer one", promptTokens: 150 },
|
|
// Compaction request: a valid summary.
|
|
{ text: "[summary]s[/summary]", promptTokens: 160 },
|
|
];
|
|
class CapturingModel extends GenerativeModel {
|
|
protected override openStream(
|
|
_uni: UniMessage,
|
|
_signal: AbortSignal,
|
|
config?: UniConfig,
|
|
): AsyncIterable<UniEvent> {
|
|
configs.push(config);
|
|
const next = scripted.shift()!;
|
|
return (async function* () {
|
|
const event: UniEvent = {
|
|
role: "assistant",
|
|
event_type: "delta",
|
|
content_items: [{ type: "text", text: next.text }],
|
|
finish_reason: "stop",
|
|
usage_metadata: {
|
|
cached_tokens: 0,
|
|
prompt_tokens: next.promptTokens,
|
|
thoughts_tokens: 0,
|
|
response_tokens: 1,
|
|
},
|
|
};
|
|
yield event;
|
|
})();
|
|
}
|
|
}
|
|
const model = new CapturingModel({
|
|
modelId: "claude-sonnet-4-6",
|
|
tools: [
|
|
{ name: "exec_command", description: "run a command" },
|
|
{ name: "read_file", description: "read a file" },
|
|
],
|
|
});
|
|
const engine = new ContextEngine({
|
|
llm: model,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
createLLM: () => new ScriptedLLM([], "llm2"),
|
|
});
|
|
|
|
const out = await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
expect(compactionEvents(out)[1]).toMatchObject({
|
|
type: "compaction_end",
|
|
status: "completed",
|
|
});
|
|
expect(configs).toHaveLength(2);
|
|
// Identical config object -> identical serialized prefix; the tool list is present and
|
|
// unchanged (not omitted, not [], no tool_choice override).
|
|
expect(configs[1]).toBe(configs[0]);
|
|
expect(configs[1]?.tools?.map((t) => t.name)).toEqual(["exec_command", "read_file"]);
|
|
expect(configs[1] !== undefined && "tool_choice" in configs[1]).toBe(false);
|
|
});
|
|
|
|
it("session turns reaching (==) the threshold compact at task end — no waiting for the next task", async () => {
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
// Task 1: two LLM requests (a tool round + the final reply).
|
|
// After round 1, turns=1 < 2 doesn't trigger; round 2 (task wrap-up), turns=2 >= 2 -> compacts immediately.
|
|
{
|
|
messages: [toolCall({ name: "t", arguments: "{}", toolCallId: "c1" }), usage(10, 10)],
|
|
},
|
|
{ messages: [assistantText("t1 done"), usage(10, 20)] },
|
|
// Compaction request (sent out immediately when task 1 ends).
|
|
{ messages: [assistantText("[summary]s[/summary]")] },
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("t2 done"), usage(10, 30)] }], "llm2");
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings({ maxContextLength: -1, maxSessionTurns: 2 }),
|
|
createLLM: () => llm2,
|
|
});
|
|
|
|
// Triggers right at task 1's wrap-up (compacts as soon as the threshold is reached, without waiting for the next task); the summary request goes to the old instance.
|
|
const out1 = await collect(engine.run([userText("task 1")], { approve: allowAll }));
|
|
const events = compactionEvents(out1);
|
|
expect(events[0]).toMatchObject({ type: "compaction_begin", reason: "turns", turns: 2 });
|
|
expect(events[1]).toMatchObject({ type: "compaction_end", status: "completed" });
|
|
expect(llm1.calls).toHaveLength(3);
|
|
|
|
// The counter resets after compaction completes: task 2 is picked up by the new instance (summary + new prompt), and no further trigger fires.
|
|
const out2 = await collect(engine.run([userText("task 2")], { approve: allowAll }));
|
|
expect(compactionEvents(out2)).toHaveLength(0);
|
|
expect(llm2.calls).toHaveLength(1);
|
|
expect(llm2.calls[0]!.map(textOf)).toEqual([
|
|
"[context_summary]\ns\n[/context_summary]",
|
|
"task 2",
|
|
]);
|
|
});
|
|
|
|
it("context usage exactly equal to the threshold triggers compaction (>=, not >)", async () => {
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
// Wrap-up round context usage 100 == threshold 100 -> triggers.
|
|
{ messages: [assistantText("answer"), usage(100, 100)] },
|
|
{ messages: [assistantText("[summary]eq[/summary]")] },
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([], "llm2");
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
createLLM: () => llm2,
|
|
});
|
|
|
|
const out = await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
const events = compactionEvents(out);
|
|
expect(events[0]).toMatchObject({
|
|
type: "compaction_begin",
|
|
reason: "context",
|
|
context: 100,
|
|
});
|
|
expect(events[1]).toMatchObject({ type: "compaction_end", status: "completed" });
|
|
});
|
|
|
|
it("discard defers mid-task, then swaps the LLM at task end without a compaction request", async () => {
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
// Round 1: over the limit, but the task is still in progress -> deferred.
|
|
{
|
|
messages: [toolCall({ name: "t", arguments: "{}", toolCallId: "c1" }), usage(150, 150)],
|
|
},
|
|
// Round 2: task ends -> performs discard (no compaction request sent).
|
|
{ messages: [assistantText("done"), usage(160, 310)] },
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("fresh"), usage(10, 320)] }], "llm2");
|
|
const trace = new Writer({ tracesDir: traces, sessionId: "sess_discard" });
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
trace,
|
|
sessionMeta: metaMessage,
|
|
compaction: settings({ mode: "discard" }),
|
|
createLLM: () => llm2,
|
|
});
|
|
const oldPath = trace.currentPath();
|
|
|
|
const out = await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
|
|
// Triggers exactly once, at task end; the old LLM is called exactly twice (no compaction request).
|
|
const events = compactionEvents(out);
|
|
expect(events.map((e) => `${e.type}:${e.mode}`)).toEqual([
|
|
"compaction_begin:discard",
|
|
"compaction_end:discard",
|
|
]);
|
|
expect(llm1.calls).toHaveLength(2);
|
|
|
|
// The next round's input is used as-is as the new instance's first input (no [context_summary]).
|
|
await collect(engine.run([userText("next task")], { approve: allowAll }));
|
|
expect(llm2.calls[0]!.map(textOf)).toEqual(["next task"]);
|
|
|
|
// Trace splits into files: the new file starts with session_meta.
|
|
const newTrace = await readTrace(trace.currentPath());
|
|
expect(trace.currentPath()).not.toBe(oldPath);
|
|
expect(newTrace[0]!.type).toBe("session_meta");
|
|
});
|
|
|
|
it("lenient extraction: output without [summary] tags is used verbatim", async () => {
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
{ messages: [assistantText("answer"), usage(150, 150)] },
|
|
{ messages: [assistantText("plain summary text without tags")] },
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("ok"), usage(10, 160)] }], "llm2");
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
createLLM: () => llm2,
|
|
});
|
|
|
|
await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
await collect(engine.run([userText("next")], { approve: allowAll }));
|
|
expect(textOf(llm2.calls[0]![0]!)).toBe(
|
|
"[context_summary]\nplain summary text without tags\n[/context_summary]",
|
|
);
|
|
});
|
|
|
|
it("manual compaction skips threshold checks and reuses the same flow", async () => {
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
// One ordinary task (well under the limit).
|
|
{ messages: [assistantText("small"), usage(10, 10)] },
|
|
// Manual compaction request.
|
|
{ messages: [assistantText("[summary]manual s[/summary]")] },
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("after"), usage(5, 20)] }], "llm2");
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
createLLM: () => llm2,
|
|
});
|
|
|
|
await collect(engine.run([userText("hi")], { approve: allowAll }));
|
|
const out = await collect(engine.compact());
|
|
const events = compactionEvents(out);
|
|
expect(events[0]).toMatchObject({ type: "compaction_begin", reason: "manual" });
|
|
expect(events[1]).toMatchObject({ type: "compaction_end", status: "completed" });
|
|
|
|
await collect(engine.run([userText("next")], { approve: allowAll }));
|
|
expect(llm2.calls[0]!.map(textOf)).toEqual([
|
|
"[context_summary]\nmanual s\n[/context_summary]",
|
|
"next",
|
|
]);
|
|
});
|
|
|
|
it("no compaction capability (createLLM missing) means thresholds never fire and compact() is a no-op", async () => {
|
|
const llm1 = new ScriptedLLM(
|
|
[{ messages: [assistantText("big"), usage(999999, 999999)] }],
|
|
"llm1",
|
|
);
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
});
|
|
const out = await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
expect(compactionEvents(out)).toHaveLength(0);
|
|
expect(await collect(engine.compact())).toHaveLength(0);
|
|
expect(llm1.calls).toHaveLength(1);
|
|
});
|
|
|
|
it('compactability(): reports each specific "cannot compact" reason instead of a blanket false', async () => {
|
|
// compact() emits **zero messages** when there is nothing compactable. The caller (Web / CLI)
|
|
// must be able to ask ahead of time, otherwise it can only wait forever for a compaction
|
|
// banner that never comes -- exactly how "no response from /compact after interrupting on the
|
|
// web" happens: interrupt the first request -> token_usage is never received -> sessionTurns
|
|
// stays at 0 -> compact() returns immediately.
|
|
// The reason also needs to distinguish "just compacted" from "haven't chatted yet" -- both
|
|
// have sessionTurns == 0, but they're two completely different messages to the user: telling
|
|
// someone who just finished compacting that there's "no completed conversation turn yet" is
|
|
// effectively saying nothing useful.
|
|
// The compaction request goes to the **current** LLM (the script's second entry); createLLM
|
|
// supplies the LLM used for the new context after compaction.
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
// Usage is kept under maxContextLength (100 per settings()) so automatic compaction doesn't jump in first and reset sessionTurns.
|
|
{ messages: [assistantText("hi"), usage(10, 10)] },
|
|
{ messages: [assistantText("[summary]s[/summary]")] }, // manual compaction request
|
|
],
|
|
"llm1",
|
|
);
|
|
const llm2 = new ScriptedLLM([{ messages: [assistantText("after"), usage(5, 20)] }], "llm2");
|
|
|
|
// (1) No compaction capability configured (no compaction / createLLM).
|
|
const noCap = new ContextEngine({ llm: llm1, environment: fakeEnvironment });
|
|
expect(noCap.compactability()).toBe("unsupported");
|
|
|
|
// (2) Capability configured, but the current context hasn't finished a single round yet: not compactable, and compact() indeed emits no messages.
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
createLLM: () => llm2,
|
|
});
|
|
expect(engine.compactability()).toBe("empty");
|
|
expect(await collect(engine.compact())).toHaveLength(0);
|
|
|
|
// (3) Compactable only after a round finishes (token_usage received).
|
|
await collect(engine.run([userText("go")], { approve: allowAll }));
|
|
expect(engine.compactability()).toBe("ok");
|
|
expect(compactionEvents(await collect(engine.compact()))).not.toHaveLength(0);
|
|
|
|
// (4) Compacting again right after a compaction: also not compactable (the new context is
|
|
// empty), but the reason is "just compacted" -- it must not say "no completed conversation
|
|
// turn yet" again, since the user clearly just finished a whole round.
|
|
expect(engine.compactability()).toBe("just_compacted");
|
|
expect(await collect(engine.compact())).toHaveLength(0);
|
|
|
|
// (5) Compactable again once a round finishes in the new context.
|
|
await collect(engine.run([userText("next")], { approve: allowAll }));
|
|
expect(engine.compactability()).toBe("ok");
|
|
});
|
|
|
|
it("user abort during the compaction request keeps the context and carries tool outputs over", async () => {
|
|
const controller = new AbortController();
|
|
const llm1 = new ScriptedLLM(
|
|
[
|
|
{
|
|
messages: [toolCall({ name: "t", arguments: "{}", toolCallId: "c1" }), usage(150, 150)],
|
|
},
|
|
{ messages: [], outcome: { status: "aborted" } },
|
|
],
|
|
"llm1",
|
|
);
|
|
const engine = new ContextEngine({
|
|
llm: llm1,
|
|
environment: fakeEnvironment,
|
|
compaction: settings(),
|
|
createLLM: () => llm1,
|
|
});
|
|
// The abort signal is already pending before the compaction request: the fake LLM finishes straight to aborted.
|
|
const approveThenAbort: ApproveFn = async () => "allow";
|
|
const runGen = engine.run([userText("go")], {
|
|
approve: approveThenAbort,
|
|
signal: controller.signal,
|
|
});
|
|
const out: OmniMessage[] = [];
|
|
for await (const msg of runGen) {
|
|
out.push(msg);
|
|
// Simulates a user abort right after the compaction start event (the compaction request then returns aborted).
|
|
const p = msg.payload as { type?: string };
|
|
if (p.type === "compaction_begin") controller.abort();
|
|
}
|
|
|
|
const events = compactionEvents(out);
|
|
expect(events[1]).toMatchObject({ type: "compaction_end", status: "aborted" });
|
|
// Interrupt cleanup: the tool output is held as carry-over per case A, and the run wraps up with an abort event.
|
|
expect(payloadTypes(out)).toContain("abort");
|
|
});
|
|
});
|