import { createAgentUIStreamResponse, type UIMessage } from "ai"; import { createTeacherAgent, type TeacherAgent } from "../agent/teacher-agent.ts"; import { createJobRunner } from "../agent/subagents/runner.ts"; import { createTeacherTools } from "../agent/tools.ts"; import { stores } from "./stores.ts"; import { buildTeacherContext, foldTurnIntoGraph, persistTurn, spawnTurnJobs } from "./turn-service.ts"; /** * One chat turn: run the teacher agent over the client's message list and * stream the UI message stream back. Framework-free (plain Request/Response) * so tests can drive it directly with a scripted mock model — the Next route * handler in app/api/chat is a one-line wrapper. * * This module is the TURN COMPOSITION ROOT: it wires the storage ports, the * job runner, the teacher tools, and the turn services (turn-service.ts) * together — all actual work lives behind those seams. The background job * runner closes over the same port objects the services see. */ const jobRunner = createJobRunner(stores); export async function handleChatRequest(req: Request, agent?: TeacherAgent): Promise { let body: { chatId?: unknown; messages?: unknown }; try { body = await req.json(); } catch { return Response.json({ error: "Invalid JSON body" }, { status: 400 }); } const chatId = typeof body.chatId === "string" ? body.chatId : ""; if (!chatId || !stores.chatStore.getChat(chatId)) { return Response.json({ error: "Unknown chat" }, { status: 404 }); } if (!Array.isArray(body.messages)) { return Response.json({ error: "messages must be an array" }, { status: 400 }); } return createAgentUIStreamResponse({ agent: agent ?? createTeacherAgent( undefined, createTeacherTools({ chatId, chatStore: stores.chatStore }), buildTeacherContext(stores.graphStore, chatId), ), uiMessages: body.messages as UIMessage[], onFinish: ({ messages, isAborted }) => { persistTurn(stores.chatStore, chatId, messages as UIMessage[], isAborted); spawnTurnJobs(jobRunner, chatId, messages as UIMessage[]); foldTurnIntoGraph(stores, chatId); }, }); }