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1028 lines
32 KiB
TypeScript
1028 lines
32 KiB
TypeScript
import type { AgentMessage } from "@mariozechner/pi-agent-core";
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import type { AssistantMessage, UserMessage, Usage } from "@mariozechner/pi-ai";
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import { beforeAll, beforeEach, describe, expect, it, vi } from "vitest";
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import {
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expectOpenAIResponsesStrictSanitizeCall,
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loadSanitizeSessionHistoryWithCleanMocks,
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makeMockSessionManager,
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makeInMemorySessionManager,
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makeModelSnapshotEntry,
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makeReasoningAssistantMessages,
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makeSimpleUserMessages,
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sanitizeSnapshotChangedOpenAIReasoning,
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type SanitizeSessionHistoryHarness,
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type SanitizeSessionHistoryFn,
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sanitizeWithOpenAIResponses,
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TEST_SESSION_ID,
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} from "./pi-embedded-runner.sanitize-session-history.test-harness.js";
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import { castAgentMessage, castAgentMessages } from "./test-helpers/agent-message-fixtures.js";
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import type { TranscriptPolicy } from "./transcript-policy.js";
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import { makeZeroUsageSnapshot } from "./usage.js";
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vi.mock("./pi-embedded-helpers.js", async () => ({
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...(await vi.importActual("./pi-embedded-helpers.js")),
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isGoogleModelApi: vi.fn(),
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sanitizeSessionMessagesImages: vi.fn(async (msgs) => msgs),
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}));
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vi.mock("../plugins/provider-runtime.js", async () => {
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const actual = await vi.importActual<typeof import("../plugins/provider-runtime.js")>(
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"../plugins/provider-runtime.js",
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);
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return {
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...actual,
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resolveProviderRuntimePlugin: ({ provider }: { provider?: string }) =>
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provider === "openrouter" || provider === "github-copilot"
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? {
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buildReplayPolicy: (context?: { modelId?: string | null }) => {
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const modelId = String(context?.modelId ?? "").toLowerCase();
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if (provider === "openrouter") {
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return {
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applyAssistantFirstOrderingFix: false,
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validateGeminiTurns: false,
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validateAnthropicTurns: false,
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...(modelId.includes("gemini")
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? {
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sanitizeThoughtSignatures: {
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allowBase64Only: true,
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includeCamelCase: true,
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},
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}
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: {}),
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};
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}
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if (provider === "github-copilot" && modelId.includes("claude")) {
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return {
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dropThinkingBlocks: true,
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};
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}
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return undefined;
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},
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}
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: undefined,
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sanitizeProviderReplayHistoryWithPlugin: vi.fn(
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async ({
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provider,
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context,
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}: {
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provider?: string;
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context: {
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messages: AgentMessage[];
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sessionState?: {
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appendCustomEntry(customType: string, data: unknown): void;
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};
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};
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}) => {
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if (
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provider &&
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provider.startsWith("google") &&
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context.messages[0]?.role === "assistant" &&
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context.sessionState
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) {
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context.sessionState.appendCustomEntry("google-turn-ordering-bootstrap", {
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timestamp: Date.now(),
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});
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return [
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{ role: "user", content: "(session bootstrap)" } as AgentMessage,
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...context.messages,
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];
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}
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return context.messages;
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},
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),
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validateProviderReplayTurnsWithPlugin: vi.fn(() => undefined),
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};
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});
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let sanitizeSessionHistory: SanitizeSessionHistoryFn;
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let mockedHelpers: SanitizeSessionHistoryHarness["mockedHelpers"];
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let testTimestamp = 1;
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const nextTimestamp = () => testTimestamp++;
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// We don't mock session-transcript-repair.js as it is a pure function and complicates mocking.
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// We rely on the real implementation which should pass through our simple messages.
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describe("sanitizeSessionHistory", () => {
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let mockSessionManager: ReturnType<typeof makeMockSessionManager>;
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const mockMessages = makeSimpleUserMessages();
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const setNonGoogleModelApi = () => {
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vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(false);
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};
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const sanitizeGithubCopilotHistory = async (params: {
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messages: AgentMessage[];
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modelApi?: string;
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modelId?: string;
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}) =>
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sanitizeSessionHistory({
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messages: params.messages,
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modelApi: params.modelApi ?? "openai-completions",
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provider: "github-copilot",
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modelId: params.modelId ?? "claude-opus-4.6",
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sessionManager: makeMockSessionManager(),
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sessionId: TEST_SESSION_ID,
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});
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const sanitizeAnthropicHistory = async (params: {
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messages: AgentMessage[];
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provider?: string;
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modelApi?: string;
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modelId?: string;
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policy?: TranscriptPolicy;
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}) =>
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sanitizeSessionHistory({
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messages: params.messages,
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modelApi: params.modelApi ?? "anthropic-messages",
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provider: params.provider ?? "anthropic",
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modelId: params.modelId ?? "claude-opus-4-6",
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sessionManager: makeMockSessionManager(),
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sessionId: TEST_SESSION_ID,
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policy: params.policy,
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});
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const getAssistantMessage = (messages: AgentMessage[]) => {
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expect(messages[1]?.role).toBe("assistant");
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return messages[1] as Extract<AgentMessage, { role: "assistant" }>;
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};
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const getAssistantContentTypes = (messages: AgentMessage[]) =>
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getAssistantMessage(messages).content.map((block: { type: string }) => block.type);
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const makeThinkingAndTextAssistantMessages = (
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thinkingSignature: string = "some_sig",
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): AgentMessage[] => {
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const user: UserMessage = {
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role: "user",
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content: "hello",
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timestamp: nextTimestamp(),
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};
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const assistant: AssistantMessage = {
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role: "assistant",
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content: [
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{
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type: "thinking",
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thinking: "internal",
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thinkingSignature,
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},
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{ type: "text", text: "hi" },
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],
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api: "openai-responses",
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provider: "openai",
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model: "gpt-5.4",
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usage: makeUsage(0, 0, 0),
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stopReason: "stop",
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timestamp: nextTimestamp(),
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};
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return [user, assistant];
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};
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const makeUsage = (input: number, output: number, totalTokens: number): Usage => ({
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input,
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output,
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cacheRead: 0,
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cacheWrite: 0,
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totalTokens,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
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});
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const makeAssistantUsageMessage = (params: {
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text: string;
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usage: ReturnType<typeof makeUsage>;
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timestamp?: number;
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}): AssistantMessage => ({
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role: "assistant",
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content: [{ type: "text", text: params.text }],
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api: "openai-responses",
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provider: "openai",
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model: "gpt-5.4",
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stopReason: "stop",
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timestamp: params.timestamp ?? nextTimestamp(),
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usage: params.usage,
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});
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const makeUserMessage = (content: string, timestamp = nextTimestamp()): UserMessage => ({
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role: "user",
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content,
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timestamp,
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});
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const makeAssistantMessage = (
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content: AssistantMessage["content"],
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params: {
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stopReason?: AssistantMessage["stopReason"];
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usage?: Usage;
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timestamp?: number;
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} = {},
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): AssistantMessage => ({
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role: "assistant",
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content,
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api: "openai-responses",
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provider: "openai",
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model: "gpt-5.4",
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usage: params.usage ?? makeUsage(0, 0, 0),
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stopReason: params.stopReason ?? "stop",
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timestamp: params.timestamp ?? nextTimestamp(),
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});
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const makeCompactionSummaryMessage = (tokensBefore: number, timestamp: string) =>
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castAgentMessage({
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role: "compactionSummary",
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summary: "compressed",
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tokensBefore,
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timestamp,
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});
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const sanitizeOpenAIHistory = async (
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messages: AgentMessage[],
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overrides: Partial<Parameters<SanitizeSessionHistoryFn>[0]> = {},
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) =>
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sanitizeSessionHistory({
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messages,
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modelApi: "openai-responses",
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provider: "openai",
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sessionManager: mockSessionManager,
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sessionId: TEST_SESSION_ID,
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...overrides,
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});
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const getAssistantMessages = (messages: AgentMessage[]) =>
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messages.filter((message) => message.role === "assistant") as Array<
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AgentMessage & { usage?: unknown; content?: unknown }
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>;
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const getSingleAssistantUsage = async (messages: AgentMessage[]) => {
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vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(false);
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const result = await sanitizeOpenAIHistory(messages);
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return result.find((message) => message.role === "assistant") as
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| (AgentMessage & { usage?: unknown })
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| undefined;
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};
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beforeAll(async () => {
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const harness = await loadSanitizeSessionHistoryWithCleanMocks();
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sanitizeSessionHistory = harness.sanitizeSessionHistory;
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mockedHelpers = harness.mockedHelpers;
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});
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beforeEach(() => {
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testTimestamp = 1;
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vi.clearAllMocks();
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vi.mocked(mockedHelpers.sanitizeSessionMessagesImages).mockImplementation(async (msgs) => msgs);
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mockSessionManager = makeMockSessionManager();
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});
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it("passes simple user-only history through for Google model APIs", async () => {
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vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(true);
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const result = await sanitizeSessionHistory({
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messages: mockMessages,
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modelApi: "google-generative-ai",
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provider: "google-vertex",
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sessionManager: mockSessionManager,
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sessionId: TEST_SESSION_ID,
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});
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expect(result).toEqual(mockMessages);
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});
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it("lets Google provider hooks prepend a bootstrap turn and persist a marker", async () => {
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vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(true);
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const sessionEntries: Array<{ type: string; customType: string; data: unknown }> = [];
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const sessionManager = makeInMemorySessionManager(sessionEntries);
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const result = await sanitizeSessionHistory({
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messages: castAgentMessages([
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{
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role: "assistant",
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content: [{ type: "text", text: "hello from previous turn" }],
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},
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]),
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modelApi: "google-generative-ai",
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provider: "google-vertex",
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sessionManager,
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sessionId: TEST_SESSION_ID,
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});
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expect(result[0]).toMatchObject({
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role: "user",
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content: "(session bootstrap)",
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});
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expect(
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sessionEntries.some((entry) => entry.customType === "google-turn-ordering-bootstrap"),
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).toBe(true);
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});
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it("passes simple user-only history through for Mistral models", async () => {
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setNonGoogleModelApi();
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const result = await sanitizeSessionHistory({
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messages: mockMessages,
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modelApi: "openai-responses",
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provider: "openrouter",
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modelId: "mistralai/devstral-2512:free",
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sessionManager: mockSessionManager,
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sessionId: TEST_SESSION_ID,
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});
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expect(result).toEqual(mockMessages);
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});
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it("passes simple user-only history through for Anthropic APIs", async () => {
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setNonGoogleModelApi();
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const result = await sanitizeSessionHistory({
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messages: mockMessages,
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modelApi: "anthropic-messages",
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provider: "anthropic",
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sessionManager: mockSessionManager,
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sessionId: TEST_SESSION_ID,
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});
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expect(result).toEqual(mockMessages);
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});
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it("passes simple user-only history through for openai-responses", async () => {
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setNonGoogleModelApi();
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const result = await sanitizeWithOpenAIResponses({
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sanitizeSessionHistory,
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messages: mockMessages,
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sessionManager: mockSessionManager,
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});
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expect(result).toEqual(mockMessages);
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});
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it("sanitizes tool call ids for OpenAI-compatible responses providers", async () => {
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setNonGoogleModelApi();
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await sanitizeSessionHistory({
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messages: mockMessages,
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modelApi: "openai-responses",
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provider: "custom",
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sessionManager: mockSessionManager,
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sessionId: TEST_SESSION_ID,
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});
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expectOpenAIResponsesStrictSanitizeCall(
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mockedHelpers.sanitizeSessionMessagesImages,
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mockMessages,
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);
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});
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it("sanitizes tool call ids for openai-completions", async () => {
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setNonGoogleModelApi();
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const result = await sanitizeSessionHistory({
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messages: mockMessages,
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modelApi: "openai-completions",
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provider: "openai",
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modelId: "gpt-5.4",
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sessionManager: mockSessionManager,
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sessionId: TEST_SESSION_ID,
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});
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expect(result).toEqual(mockMessages);
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});
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it("prepends a bootstrap user turn for strict OpenAI-compatible assistant-first history", async () => {
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setNonGoogleModelApi();
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const sessionEntries: Array<{ type: string; customType: string; data: unknown }> = [];
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const sessionManager = makeInMemorySessionManager(sessionEntries);
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const messages = castAgentMessages([
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{
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role: "assistant",
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content: [{ type: "text", text: "hello from previous turn" }],
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},
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]);
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const result = await sanitizeSessionHistory({
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messages,
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modelApi: "openai-completions",
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provider: "vllm",
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modelId: "gemma-3-27b",
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sessionManager,
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sessionId: TEST_SESSION_ID,
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});
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expect(result[0]?.role).toBe("user");
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expect((result[0] as { content?: unknown } | undefined)?.content).toBe("(session bootstrap)");
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expect(result[1]?.role).toBe("assistant");
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expect(
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sessionEntries.some((entry) => entry.customType === "google-turn-ordering-bootstrap"),
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).toBe(false);
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});
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it("annotates inter-session user messages before context sanitization", async () => {
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setNonGoogleModelApi();
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const messages: AgentMessage[] = [
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castAgentMessage({
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role: "user",
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content: "forwarded instruction",
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provenance: {
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kind: "inter_session",
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sourceSessionKey: "agent:main:req",
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sourceTool: "sessions_send",
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},
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}),
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];
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const result = await sanitizeSessionHistory({
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messages,
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modelApi: "openai-responses",
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provider: "openai",
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sessionManager: mockSessionManager,
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sessionId: TEST_SESSION_ID,
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});
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const first = result[0] as Extract<AgentMessage, { role: "user" }>;
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expect(first.role).toBe("user");
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expect(typeof first.content).toBe("string");
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expect(first.content as string).toContain("[Inter-session message]");
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expect(first.content as string).toContain("sourceSession=agent:main:req");
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});
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it("drops stale assistant usage snapshots kept before latest compaction summary", async () => {
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vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(false);
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const messages = castAgentMessages([
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{ role: "user", content: "old context" },
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makeAssistantUsageMessage({
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text: "old answer",
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usage: makeUsage(191_919, 2_000, 193_919),
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}),
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makeCompactionSummaryMessage(191_919, new Date().toISOString()),
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]);
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const result = await sanitizeOpenAIHistory(messages);
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const staleAssistant = result.find((message) => message.role === "assistant") as
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| (AgentMessage & { usage?: unknown })
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| undefined;
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expect(staleAssistant).toBeDefined();
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expect(staleAssistant?.usage).toEqual(makeZeroUsageSnapshot());
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});
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it("preserves fresh assistant usage snapshots created after latest compaction summary", async () => {
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vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(false);
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const messages = castAgentMessages([
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makeAssistantUsageMessage({
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text: "pre-compaction answer",
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usage: makeUsage(120_000, 3_000, 123_000),
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}),
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makeCompactionSummaryMessage(123_000, new Date().toISOString()),
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{ role: "user", content: "new question" },
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makeAssistantUsageMessage({
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text: "fresh answer",
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usage: makeUsage(1_000, 250, 1_250),
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}),
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]);
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const result = await sanitizeOpenAIHistory(messages);
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const assistants = getAssistantMessages(result);
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expect(assistants).toHaveLength(2);
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expect(assistants[0]?.usage).toEqual(makeZeroUsageSnapshot());
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expect(assistants[1]?.usage).toBeDefined();
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});
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it("adds a zeroed assistant usage snapshot when usage is missing", async () => {
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|
const assistant = await getSingleAssistantUsage(
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castAgentMessages([
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{ role: "user", content: "question" },
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|
{
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|
role: "assistant",
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|
content: [{ type: "text", text: "answer without usage" }],
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|
},
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]),
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);
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expect(assistant?.usage).toEqual(makeZeroUsageSnapshot());
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});
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|
|
|
it("normalizes mixed partial assistant usage fields to numeric totals", async () => {
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|
const assistant = await getSingleAssistantUsage(
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castAgentMessages([
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{ role: "user", content: "question" },
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{
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role: "assistant",
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content: [{ type: "text", text: "answer with partial usage" }],
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|
usage: {
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output: 3,
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cache_read_input_tokens: 9,
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},
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},
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]),
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);
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expect(assistant?.usage).toEqual({
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input: 0,
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output: 3,
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cacheRead: 9,
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cacheWrite: 0,
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totalTokens: 12,
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});
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});
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|
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it("preserves existing usage cost while normalizing token fields", async () => {
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const assistant = await getSingleAssistantUsage(
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castAgentMessages([
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{ role: "user", content: "question" },
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{
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role: "assistant",
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content: [{ type: "text", text: "answer with partial usage and cost" }],
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usage: {
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output: 3,
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cache_read_input_tokens: 9,
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cost: {
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input: 1.25,
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output: 2.5,
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cacheRead: 0.25,
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cacheWrite: 0,
|
|
total: 4,
|
|
},
|
|
},
|
|
},
|
|
]),
|
|
);
|
|
|
|
expect(assistant?.usage).toEqual({
|
|
...makeZeroUsageSnapshot(),
|
|
input: 0,
|
|
output: 3,
|
|
cacheRead: 9,
|
|
cacheWrite: 0,
|
|
totalTokens: 12,
|
|
cost: {
|
|
input: 1.25,
|
|
output: 2.5,
|
|
cacheRead: 0.25,
|
|
cacheWrite: 0,
|
|
total: 4,
|
|
},
|
|
});
|
|
});
|
|
|
|
it("preserves unknown cost when token fields already match", async () => {
|
|
const assistant = await getSingleAssistantUsage(
|
|
castAgentMessages([
|
|
{ role: "user", content: "question" },
|
|
{
|
|
role: "assistant",
|
|
content: [{ type: "text", text: "answer with complete numeric usage but no cost" }],
|
|
usage: {
|
|
input: 1,
|
|
output: 2,
|
|
cacheRead: 3,
|
|
cacheWrite: 4,
|
|
totalTokens: 10,
|
|
},
|
|
},
|
|
]),
|
|
);
|
|
|
|
expect(assistant?.usage).toEqual({
|
|
input: 1,
|
|
output: 2,
|
|
cacheRead: 3,
|
|
cacheWrite: 4,
|
|
totalTokens: 10,
|
|
});
|
|
expect((assistant?.usage as { cost?: unknown } | undefined)?.cost).toBeUndefined();
|
|
});
|
|
|
|
it("drops stale usage when compaction summary appears before kept assistant messages", async () => {
|
|
vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(false);
|
|
|
|
const compactionTs = Date.parse("2026-02-26T12:00:00.000Z");
|
|
const messages = castAgentMessages([
|
|
makeCompactionSummaryMessage(191_919, new Date(compactionTs).toISOString()),
|
|
makeAssistantUsageMessage({
|
|
text: "kept pre-compaction answer",
|
|
timestamp: compactionTs - 1_000,
|
|
usage: makeUsage(191_919, 2_000, 193_919),
|
|
}),
|
|
]);
|
|
|
|
const result = await sanitizeOpenAIHistory(messages);
|
|
|
|
const assistant = result.find((message) => message.role === "assistant") as
|
|
| (AgentMessage & { usage?: unknown })
|
|
| undefined;
|
|
expect(assistant?.usage).toEqual(makeZeroUsageSnapshot());
|
|
});
|
|
|
|
it("keeps fresh usage after compaction timestamp in summary-first ordering", async () => {
|
|
vi.mocked(mockedHelpers.isGoogleModelApi).mockReturnValue(false);
|
|
|
|
const compactionTs = Date.parse("2026-02-26T12:00:00.000Z");
|
|
const messages = castAgentMessages([
|
|
makeCompactionSummaryMessage(123_000, new Date(compactionTs).toISOString()),
|
|
makeAssistantUsageMessage({
|
|
text: "kept pre-compaction answer",
|
|
timestamp: compactionTs - 2_000,
|
|
usage: makeUsage(120_000, 3_000, 123_000),
|
|
}),
|
|
{ role: "user", content: "new question", timestamp: compactionTs + 1_000 },
|
|
makeAssistantUsageMessage({
|
|
text: "fresh answer",
|
|
timestamp: compactionTs + 2_000,
|
|
usage: makeUsage(1_000, 250, 1_250),
|
|
}),
|
|
]);
|
|
|
|
const result = await sanitizeOpenAIHistory(messages);
|
|
|
|
const assistants = getAssistantMessages(result);
|
|
const keptAssistant = assistants.find((message) =>
|
|
JSON.stringify(message.content).includes("kept pre-compaction answer"),
|
|
);
|
|
const freshAssistant = assistants.find((message) =>
|
|
JSON.stringify(message.content).includes("fresh answer"),
|
|
);
|
|
expect(keptAssistant?.usage).toEqual(makeZeroUsageSnapshot());
|
|
expect(freshAssistant?.usage).toBeDefined();
|
|
});
|
|
|
|
it("keeps reasoning-only assistant messages for openai-responses", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const messages: AgentMessage[] = [
|
|
makeUserMessage("hello"),
|
|
makeAssistantMessage(
|
|
[
|
|
{
|
|
type: "thinking",
|
|
thinking: "reasoning",
|
|
thinkingSignature: "sig",
|
|
},
|
|
],
|
|
{ stopReason: "aborted" },
|
|
),
|
|
];
|
|
|
|
const result = await sanitizeSessionHistory({
|
|
messages,
|
|
modelApi: "openai-responses",
|
|
provider: "openai",
|
|
sessionManager: mockSessionManager,
|
|
sessionId: TEST_SESSION_ID,
|
|
});
|
|
|
|
expect(result).toHaveLength(2);
|
|
expect(result[1]?.role).toBe("assistant");
|
|
});
|
|
|
|
it("synthesizes missing tool results for openai-responses after repair", async () => {
|
|
const messages: AgentMessage[] = [
|
|
makeAssistantMessage([{ type: "toolCall", id: "call_1", name: "read", arguments: {} }], {
|
|
stopReason: "toolUse",
|
|
}),
|
|
];
|
|
|
|
const result = await sanitizeOpenAIHistory(messages);
|
|
|
|
// repairToolUseResultPairing now runs for all providers (including OpenAI)
|
|
// to fix orphaned function_call_output items that OpenAI would reject.
|
|
expect(result).toHaveLength(2);
|
|
expect(result[0]?.role).toBe("assistant");
|
|
expect(result[1]?.role).toBe("toolResult");
|
|
});
|
|
|
|
it.each([
|
|
{
|
|
name: "missing input or arguments",
|
|
makeMessages: () =>
|
|
castAgentMessages([
|
|
castAgentMessage({
|
|
role: "assistant",
|
|
content: [{ type: "toolCall", id: "call_1", name: "read" }],
|
|
}),
|
|
makeUserMessage("hello"),
|
|
]),
|
|
overrides: { sessionId: "test-session" } as Partial<
|
|
Parameters<typeof sanitizeOpenAIHistory>[1]
|
|
>,
|
|
},
|
|
{
|
|
name: "invalid or overlong names",
|
|
makeMessages: () =>
|
|
castAgentMessages([
|
|
makeAssistantMessage(
|
|
[
|
|
{
|
|
type: "toolCall",
|
|
id: "call_bad",
|
|
name: 'toolu_01mvznfebfuu <|tool_call_argument_begin|> {"command"',
|
|
arguments: {},
|
|
},
|
|
{
|
|
type: "toolCall",
|
|
id: "call_long",
|
|
name: `read_${"x".repeat(80)}`,
|
|
arguments: {},
|
|
},
|
|
],
|
|
{ stopReason: "toolUse" },
|
|
),
|
|
makeUserMessage("hello"),
|
|
]),
|
|
overrides: {} as Partial<Parameters<typeof sanitizeOpenAIHistory>[1]>,
|
|
},
|
|
])("drops malformed tool calls: $name", async ({ makeMessages, overrides }) => {
|
|
const result = await sanitizeOpenAIHistory(makeMessages(), overrides);
|
|
expect(result.map((msg) => msg.role)).toEqual(["user"]);
|
|
});
|
|
|
|
it("drops tool calls that are not in the allowed tool set", async () => {
|
|
const messages: AgentMessage[] = [
|
|
makeAssistantMessage([{ type: "toolCall", id: "call_1", name: "write", arguments: {} }], {
|
|
stopReason: "toolUse",
|
|
}),
|
|
];
|
|
|
|
const result = await sanitizeOpenAIHistory(messages, {
|
|
allowedToolNames: ["read"],
|
|
});
|
|
|
|
expect(result).toEqual([]);
|
|
});
|
|
|
|
it("downgrades orphaned openai reasoning even when the model has not changed", async () => {
|
|
const sessionEntries = [
|
|
makeModelSnapshotEntry({
|
|
provider: "openai",
|
|
modelApi: "openai-responses",
|
|
modelId: "gpt-5.4",
|
|
}),
|
|
];
|
|
const sessionManager = makeInMemorySessionManager(sessionEntries);
|
|
const messages = makeReasoningAssistantMessages({ thinkingSignature: "json" });
|
|
|
|
const result = await sanitizeWithOpenAIResponses({
|
|
sanitizeSessionHistory,
|
|
messages,
|
|
modelId: "gpt-5.4",
|
|
sessionManager,
|
|
});
|
|
|
|
expect(result).toEqual([]);
|
|
});
|
|
|
|
it("downgrades orphaned openai reasoning when the model changes too", async () => {
|
|
const result = await sanitizeSnapshotChangedOpenAIReasoning({
|
|
sanitizeSessionHistory,
|
|
});
|
|
|
|
expect(result).toEqual([]);
|
|
});
|
|
|
|
it("drops orphaned toolResult entries when switching from openai history to anthropic", async () => {
|
|
const sessionEntries = [
|
|
makeModelSnapshotEntry({
|
|
provider: "openai",
|
|
modelApi: "openai-responses",
|
|
modelId: "gpt-5.4",
|
|
}),
|
|
];
|
|
const sessionManager = makeInMemorySessionManager(sessionEntries);
|
|
const messages: AgentMessage[] = [
|
|
makeAssistantMessage([{ type: "toolCall", id: "tool_abc123", name: "read", arguments: {} }], {
|
|
stopReason: "toolUse",
|
|
}),
|
|
{
|
|
role: "toolResult",
|
|
toolCallId: "tool_abc123",
|
|
toolName: "read",
|
|
content: [{ type: "text", text: "ok" }],
|
|
isError: false,
|
|
timestamp: nextTimestamp(),
|
|
},
|
|
makeUserMessage("continue"),
|
|
{
|
|
role: "toolResult",
|
|
toolCallId: "tool_01VihkDRptyLpX1ApUPe7ooU",
|
|
toolName: "read",
|
|
content: [{ type: "text", text: "stale result" }],
|
|
isError: false,
|
|
timestamp: nextTimestamp(),
|
|
},
|
|
];
|
|
|
|
const result = await sanitizeSessionHistory({
|
|
messages,
|
|
modelApi: "anthropic-messages",
|
|
provider: "anthropic",
|
|
modelId: "claude-opus-4-6",
|
|
sessionManager,
|
|
sessionId: TEST_SESSION_ID,
|
|
});
|
|
|
|
expect(result.map((msg) => msg.role)).toEqual(["assistant", "toolResult", "user"]);
|
|
expect(
|
|
result.some(
|
|
(msg) =>
|
|
msg.role === "toolResult" &&
|
|
(msg as { toolCallId?: string }).toolCallId === "tool_01VihkDRptyLpX1ApUPe7ooU",
|
|
),
|
|
).toBe(false);
|
|
});
|
|
|
|
it("preserves latest assistant thinking blocks for github-copilot models", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const messages = makeThinkingAndTextAssistantMessages("reasoning_text");
|
|
|
|
const result = await sanitizeGithubCopilotHistory({ messages });
|
|
const assistant = getAssistantMessage(result);
|
|
expect(assistant.content).toEqual([
|
|
{
|
|
type: "thinking",
|
|
thinking: "internal",
|
|
thinkingSignature: "reasoning_text",
|
|
},
|
|
{ type: "text", text: "hi" },
|
|
]);
|
|
});
|
|
|
|
it("preserves latest assistant turn when all content is thinking blocks (github-copilot)", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const messages: AgentMessage[] = [
|
|
makeUserMessage("hello"),
|
|
makeAssistantMessage([
|
|
{
|
|
type: "thinking",
|
|
thinking: "some reasoning",
|
|
thinkingSignature: "reasoning_text",
|
|
},
|
|
]),
|
|
makeUserMessage("follow up"),
|
|
];
|
|
|
|
const result = await sanitizeGithubCopilotHistory({ messages });
|
|
|
|
expect(result).toHaveLength(3);
|
|
const assistant = getAssistantMessage(result);
|
|
expect(assistant.content).toEqual([
|
|
{
|
|
type: "thinking",
|
|
thinking: "some reasoning",
|
|
thinkingSignature: "reasoning_text",
|
|
},
|
|
]);
|
|
});
|
|
|
|
it("preserves thinking blocks alongside tool_use blocks in latest assistant message (github-copilot)", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const messages: AgentMessage[] = [
|
|
makeUserMessage("read a file"),
|
|
makeAssistantMessage([
|
|
{
|
|
type: "thinking",
|
|
thinking: "I should use the read tool",
|
|
thinkingSignature: "reasoning_text",
|
|
},
|
|
{ type: "toolCall", id: "tool_123", name: "read", arguments: { path: "/tmp/test" } },
|
|
{ type: "text", text: "Let me read that file." },
|
|
]),
|
|
];
|
|
|
|
const result = await sanitizeGithubCopilotHistory({ messages });
|
|
const types = getAssistantContentTypes(result);
|
|
expect(types).toContain("thinking");
|
|
expect(types).toContain("toolCall");
|
|
expect(types).toContain("text");
|
|
});
|
|
|
|
it("preserves latest assistant thinking blocks for anthropic replay", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const messages = makeThinkingAndTextAssistantMessages();
|
|
|
|
const result = await sanitizeAnthropicHistory({ messages });
|
|
|
|
const assistant = getAssistantMessage(result);
|
|
expect(assistant.content).toEqual([
|
|
{
|
|
type: "thinking",
|
|
thinking: "internal",
|
|
thinkingSignature: "some_sig",
|
|
},
|
|
{ type: "text", text: "hi" },
|
|
]);
|
|
});
|
|
|
|
it("keeps the earlier anthropic replay prefix stable after a later subagent turn", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const priorToolId = "toolu_01ABCDEF1234567890";
|
|
const laterToolId = "toolu_01ZZZZZZ9999999999";
|
|
const nativeAnthropicPolicy: TranscriptPolicy = {
|
|
sanitizeMode: "full",
|
|
sanitizeToolCallIds: true,
|
|
toolCallIdMode: "strict",
|
|
preserveNativeAnthropicToolUseIds: true,
|
|
repairToolUseResultPairing: true,
|
|
preserveSignatures: true,
|
|
sanitizeThoughtSignatures: undefined,
|
|
sanitizeThinkingSignatures: false,
|
|
dropThinkingBlocks: true,
|
|
applyGoogleTurnOrdering: false,
|
|
validateGeminiTurns: false,
|
|
validateAnthropicTurns: true,
|
|
allowSyntheticToolResults: true,
|
|
};
|
|
const baseMessages = castAgentMessages([
|
|
makeUserMessage("Read IDENTITY.md"),
|
|
makeAssistantMessage(
|
|
[
|
|
{ type: "toolUse", id: priorToolId, name: "read", input: { path: "IDENTITY.md" } },
|
|
] as unknown as AssistantMessage["content"],
|
|
{ stopReason: "toolUse" },
|
|
),
|
|
{
|
|
role: "toolResult",
|
|
toolCallId: priorToolId,
|
|
toolUseId: priorToolId,
|
|
toolName: "read",
|
|
content: [{ type: "text", text: "ok" }],
|
|
isError: false,
|
|
},
|
|
makeAssistantMessage([{ type: "text", text: "done" }]),
|
|
]);
|
|
const withSubagentMessages = castAgentMessages([
|
|
...baseMessages,
|
|
makeUserMessage("Ask a subagent for an emoji"),
|
|
makeAssistantMessage(
|
|
[
|
|
{ type: "toolUse", id: laterToolId, name: "subagent", input: { prompt: "emoji" } },
|
|
] as unknown as AssistantMessage["content"],
|
|
{ stopReason: "toolUse" },
|
|
),
|
|
{
|
|
role: "toolResult",
|
|
toolCallId: laterToolId,
|
|
toolUseId: laterToolId,
|
|
toolName: "subagent",
|
|
content: [{ type: "text", text: "😀" }],
|
|
isError: false,
|
|
},
|
|
makeAssistantMessage([{ type: "text", text: "it was 😀" }]),
|
|
]);
|
|
|
|
const sanitizedBase = await sanitizeAnthropicHistory({
|
|
messages: baseMessages,
|
|
policy: nativeAnthropicPolicy,
|
|
});
|
|
const sanitizedWithSubagent = await sanitizeAnthropicHistory({
|
|
messages: withSubagentMessages,
|
|
policy: nativeAnthropicPolicy,
|
|
});
|
|
|
|
expect(sanitizedWithSubagent.slice(0, sanitizedBase.length)).toEqual(sanitizedBase);
|
|
expect((sanitizedBase[1] as Extract<AgentMessage, { role: "assistant" }>).content).toEqual([
|
|
{ type: "toolUse", id: priorToolId, name: "read", input: { path: "IDENTITY.md" } },
|
|
]);
|
|
expect(
|
|
(sanitizedBase[2] as Extract<AgentMessage, { role: "toolResult" }> & { toolUseId?: string })
|
|
.toolCallId,
|
|
).toBe(priorToolId);
|
|
});
|
|
|
|
it("preserves latest assistant thinking blocks for amazon-bedrock replay", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const messages = makeThinkingAndTextAssistantMessages();
|
|
|
|
const result = await sanitizeAnthropicHistory({
|
|
messages,
|
|
provider: "amazon-bedrock",
|
|
modelApi: "bedrock-converse-stream",
|
|
});
|
|
|
|
const assistant = getAssistantMessage(result);
|
|
expect(assistant.content).toEqual([
|
|
{
|
|
type: "thinking",
|
|
thinking: "internal",
|
|
thinkingSignature: "some_sig",
|
|
},
|
|
{ type: "text", text: "hi" },
|
|
]);
|
|
});
|
|
|
|
it("does not drop thinking blocks for non-claude copilot models", async () => {
|
|
setNonGoogleModelApi();
|
|
|
|
const messages = makeThinkingAndTextAssistantMessages();
|
|
|
|
const result = await sanitizeGithubCopilotHistory({ messages, modelId: "gpt-5.4" });
|
|
const types = getAssistantContentTypes(result);
|
|
expect(types).toContain("thinking");
|
|
});
|
|
});
|