import { mkdtemp, rm } from "node:fs/promises"; import { join } from "node:path"; import { tmpdir } from "node:os"; import { afterEach, describe, expect, it, vi } from "vitest"; import { AppDatabase } from "../../src/main/database"; import { createBudgetEnforcementService } from "../../src/main/budget-enforcement-service"; import { createRunDispatch } from "../../src/main/orchestration/run-dispatch"; import { createTaskRunner } from "../../src/main/orchestration/task-runner"; const tempDirs: string[] = []; async function createTempDir(prefix: string) { const dir = await mkdtemp(join(tmpdir(), prefix)); tempDirs.push(dir); return dir; } afterEach(async () => { await Promise.all(tempDirs.splice(0).map((dir) => rm(dir, { recursive: true, force: true }))); }); const logger = { debug: vi.fn(), info: vi.fn(), warn: vi.fn(), error: vi.fn(), }; function createHarness(db: AppDatabase) { const enqueueWorkerRun = vi.fn(); const budgetService = createBudgetEnforcementService({ db, logger, notify: vi.fn(), publishDomainChanged: vi.fn(), }); const deps = { db, logger, publishDomainChanged: vi.fn(), emitEvent: vi.fn(), notify: vi.fn(), createRunToken: () => "token", getApiPort: () => 3210, dispatchAutomation: vi.fn(), hasWorkerReady: () => true, enqueueWorkerRun, isQuitting: () => false, listRuntimeSkillEntries: () => [], budgetService, checkpointEngine: { shouldPauseHeartbeat: () => false }, }; const runDispatch = createRunDispatch(deps); const taskRunner = createTaskRunner( deps, runDispatch.resolveWorkspace, runDispatch.getRunEligibilityFailure, runDispatch.dispatchRunToWorker, (filter) => db.core.runs.hasActiveRun(filter), ); return { enqueueWorkerRun, taskRunner }; } describe("agent model switching", () => { it("uses the agent's updated model for subsequent runtime dispatches", async () => { const profileDir = await createTempDir("agentcompany-model-switching-"); const db = new AppDatabase(profileDir); db.init(); db.core.connectors.updateConnectorHealth({ id: "openai-codex", status: "ready", authState: "authenticated", version: "test", lastError: null, }); const companyId = db.core.company.saveCompany({ name: "Model Switch Co", description: "Tests post-hire model switching", status: "active", }); const workspaceId = db.core.workspaces.saveWorkspace({ companyId, name: "Primary", localPath: profileDir, repoUrl: "", repoRef: "", isPrimary: true, }); const agentId = db.core.agents.saveAgent({ companyId, name: "Engineer", role: "Engineer", title: "Frontend Engineer", status: "idle", reportsTo: null, connectorId: "openai-codex", workspaceId, model: "gpt-5.4", capabilities: "Build frontend features", budgetMonthlyUsd: 200, }); const { enqueueWorkerRun, taskRunner } = createHarness(db); const firstTaskId = db.core.tasks.saveTask({ companyId, title: "Initial model task", description: "Use the first model for this run.", assigneeAgentId: agentId, workspaceId, priority: "high", status: "todo", }); const firstRun = taskRunner.queueTaskRun(firstTaskId, "manual", "board"); expect(firstRun.ok).toBe(true); expect(enqueueWorkerRun).toHaveBeenCalledTimes(1); expect(enqueueWorkerRun.mock.calls[0]?.[0]?.model).toBe("gpt-5.4"); if (!firstRun.ok) { throw new Error("Expected first run to queue successfully."); } db.core.runs.finishRun({ runId: firstRun.data, status: "succeeded", summary: "Done", errorMessage: null, exitCode: 0, signal: null, model: "gpt-5.4", unattributedCost: true, }); db.core.agents.saveAgent({ id: agentId, companyId, name: "Engineer", role: "Engineer", title: "Frontend Engineer", status: "idle", reportsTo: null, connectorId: "openai-codex", workspaceId, model: "gpt-5.3-codex", capabilities: "Build frontend features", budgetMonthlyUsd: 200, }); const secondTaskId = db.core.tasks.saveTask({ companyId, title: "Updated model task", description: "Use the new model for this run.", assigneeAgentId: agentId, workspaceId, priority: "high", status: "todo", }); const secondRun = taskRunner.queueTaskRun(secondTaskId, "manual", "board"); expect(secondRun.ok).toBe(true); expect(enqueueWorkerRun).toHaveBeenCalledTimes(2); expect(enqueueWorkerRun.mock.calls[1]?.[0]?.model).toBe("gpt-5.3-codex"); db.close(); }); });