Amos
5dab8d12d4
quizInputSchema now enforces (via pure quizInputProblems + superRefine) that correctAnswer resolves against option values, options are non-empty and unique, and multi-answer requires multiSelect — schema-valid now implies gradeable. The AI SDK already returns invalid tool input to the model as a tool-error part (verified in ai@7 run loop), so the teacher retries in the same turn. chat-handler onError passes tool-input validation messages through to the client (masked 'An error occurred.' for everything else). Covers the Gate 3 GLM failure: correctAnswer slug matching no option.
66 lines
2.9 KiB
TypeScript
66 lines
2.9 KiB
TypeScript
import { createAgentUIStreamResponse, InvalidToolInputError, NoSuchToolError, type UIMessage } from "ai";
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import { createTeacherAgent, type TeacherAgent } from "../agent/teacher-agent.ts";
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import { createJobRunner } from "../agent/subagents/runner.ts";
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import { createExtractionPipeline } from "../agent/subagents/extraction.ts";
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import { createTeacherTools } from "../agent/tools.ts";
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import { stores } from "./stores.ts";
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import { buildTeacherContext, persistTurn, spawnTurnJobs, triggerExtraction } from "./turn-service.ts";
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/**
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* One chat turn: run the teacher agent over the client's message list and
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* stream the UI message stream back. Framework-free (plain Request/Response)
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* so tests can drive it directly with a scripted mock model — the Next route
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* handler in app/api/chat is a one-line wrapper.
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*
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* This module is the TURN COMPOSITION ROOT: it wires the storage ports, the
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* job runner, the teacher tools, and the turn services (turn-service.ts)
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* together — all actual work lives behind those seams. The background job
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* runner closes over the same port objects the services see.
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*/
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const jobRunner = createJobRunner(stores);
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const extraction = createExtractionPipeline(stores);
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export async function handleChatRequest(req: Request, agent?: TeacherAgent): Promise<Response> {
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let body: { chatId?: unknown; messages?: unknown };
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try {
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body = await req.json();
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} catch {
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return Response.json({ error: "Invalid JSON body" }, { status: 400 });
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}
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const chatId = typeof body.chatId === "string" ? body.chatId : "";
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if (!chatId || !stores.chatStore.getChat(chatId)) {
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return Response.json({ error: "Unknown chat" }, { status: 404 });
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}
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if (!Array.isArray(body.messages)) {
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return Response.json({ error: "messages must be an array" }, { status: 400 });
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}
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return createAgentUIStreamResponse({
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agent:
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agent ??
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createTeacherAgent(
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undefined,
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createTeacherTools({ chatId, chatStore: stores.chatStore }),
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buildTeacherContext(stores.graphStore, chatId),
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),
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uiMessages: body.messages as UIMessage[],
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// Tool-call validation failures are messages OUR schemas authored (the
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// quiz authoring contract, unknown tools) — safe and useful in the
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// transcript: they are exactly what the teacher saw and retried on. The
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// tool loop delivers them as plain strings (what the model received) or
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// as the original error object; expose both, and keep everything else
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// (provider/transport internals) masked, as the SDK defaults.
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onError: (error) => {
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if (typeof error === "string") return error;
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if (InvalidToolInputError.isInstance(error) || NoSuchToolError.isInstance(error)) return error.message;
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return "An error occurred.";
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},
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onFinish: ({ messages, isAborted }) => {
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persistTurn(stores.chatStore, chatId, messages as UIMessage[], isAborted);
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spawnTurnJobs(jobRunner, chatId, messages as UIMessage[]);
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triggerExtraction(stores, extraction, chatId);
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},
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});
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}
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