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learnharness/src/core/contracts/jobs.ts
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/**
* Sub-agent job contracts — the async ack-and-steer protocol
*
* Part of the domain-split contracts (src/core/contracts/): each domain file
* is owned outright by its stream — cross-domain schema changes go through
* master. Pure types + protocol docs + tiny pure helpers; type-only imports
* of "ai" (safe everywhere: server, client, tests). See docs/vision.md.
*/
import type { UIMessage } from "ai";
// ─── Async sub-agent jobs (vision §2.5; plan.md Wave 0 protocol) ────────────
export type JobKind = "research" | "demo" | "visual";
export type JobStatus = "running" | "done" | "error";
export interface JobRecord {
id: string;
kind: JobKind;
chatId: string;
/** The tool part this job fulfills. */
toolCallId: string;
status: JobStatus;
/** Latest human-readable activity line, e.g. `web_search: "sigma.js v3"`. */
activity: string;
createdAt: string;
updatedAt: string;
/** The sub-agent's result (steer-artifact payload). */
result?: unknown;
error?: string;
}
/**
* THE ASYNC PROTOCOL — "ack now, steer later" (the pi sub-agents model,
* vision §2.5):
*
* 1. Job tools (research / demo / visual) are SERVER-EXECUTED. The model
* calls one MID-TURN; execute creates the job record, fires the
* background runner, and resolves IMMEDIATELY with an acknowledgement
* ("dispatched — continue your turn"). The teacher's turn does NOT end
* at the call: it keeps teaching, may dispatch other independent jobs
* (full parallelism), and ends whenever it ends. The tool part's output
* is the ack, forever.
*
* 2. The background runner (src/agent/subagents/runner.ts) runs the kind's
* sub-agent loop — isolated context, modelFor(role), the
* verify-never-one-shot doctrine (headless-tested demos, looked-at SVGs,
* sourced briefs) — tracking a live activity line in the job record.
* ONE central client poll of GET /api/jobs?chatId=… (in Chat) drives every
* job surface: the transcript dispatch cards (live activity by
* toolCallId, quiet one-liner after delivery), the sub-agents sidebar
* panel, and the single re-sync when a job settles.
*
* 3. On completion the runner builds a STEER MESSAGE (buildSubagentSteer)
* and hands it to the wake pipeline (src/server/jobs.ts): a user-role
* UIMessage carrying the result — a text part with what the MODEL needs
* (the research brief, the builder's notes), plus a data-subagent-artifact
* part with what the UI renders (the full result: brief + sources /
* SVG / demo HTML). Provider conversion drops data parts, so artifact
* payloads never enter the teacher's context. metadata.subagentResult
* identifies the job; the UI renders these as sub-agent result cards,
* NEVER as learner interjections.
*
* 4. The wake pipeline delivers the steer by firing a SERVER-SIDE teacher
* turn through the same turn composition as a client request
* (handleChatRequest) — write-ahead persist, turn liveness, extraction
* trigger: one code path. A per-chat serialized queue: a steer waits
* while a turn is in flight OR a question tool part is pending (an
* unanswered client-side tool call breaks provider conversion — the
* steer fires right after the learner's continuation), then fires; a 409
* (a client turn raced in) retries. Delivery is idempotent per jobId, so
* a crashed wake can be re-entered by the stale-job recovery sweep. The
* job's status flips to done/error only AFTER the wake turn completes —
* a polling client that sees the flip re-syncs once and gets the
* finished record.
*
* CONTINUATION COALESCING: the idle window above can starve — a
* quiz-chaining teacher ends every turn with a new pending check, so
* the gates never stay open long enough for a wake to fire. The fix:
* when a client turn wins the turn registry, the handler CLAIMS every
* queued, undelivered steer (jobs.ts claimSteers) and appends it after
* the learner's answer in that very turn — conversion-safe, because the
* answered quiz carries its output. Every answer flushes pending
* steers immediately; the wake pump remains for turns that end with no
* pending question. The pump re-checks steerDelivered right before
* firing, so a claim racing the pump converges to exactly one delivery.
*
* 5. No pending job parts ever exist, so the composer never gates on jobs
* (the learner can interject mid-job; the steer queues behind their
* turn) and job tool outputs never trigger the client-side
* sendAutomatically continuation — that mechanism stays quiz/ask-only.
*/
export interface ResearchToolInput {
question: string;
/** What the teacher needs it for — focuses the research brief. */
context?: string;
}
export interface ResearchResult {
brief: string;
sources: { title: string; url: string }[];
}
export interface DemoToolInput {
title: string;
/** Precise brief: concept, parameters/interactions, visual style. */
brief: string;
}
export interface DemoResult {
title: string;
/** Self-contained single-file HTML/JS document (sandboxed-iframe ready). */
html: string;
/** The builder sub-agent headlessly executed the demo before delivery. */
tested: true;
notes?: string;
}
export interface VisualToolInput {
/** Precise brief for ONE visual (what it must show, exactly). */
brief: string;
}
export interface VisualResult {
/** Complete SVG markup (verified by the maker looking at the render). */
svg: string;
notes?: string;
}
// ─── Sub-agent steer messages (THE ASYNC PROTOCOL §3–4) ─────────────────────
/** Message metadata marking a sub-agent steer (contracts.ts §3). */
export interface SubagentResultMeta {
jobId: string;
kind: JobKind;
toolCallId: string;
}
/** The data-subagent-artifact part payload: what the UI renders. */
export interface SubagentArtifactData {
kind: JobKind;
result: ResearchResult | DemoResult | VisualResult;
}
/**
* The steer message: user-role on the wire (UIMessage roles are fixed), but
* NEVER a learner interjection — metadata.subagentResult is the marker the
* UI branches on, and the artifact rides the data part (stripped by provider
* conversion, so the model sees only the text part).
*/
export interface SubagentSteerMessage extends UIMessage {
role: "user";
metadata: { subagentResult: SubagentResultMeta };
parts: [
{ type: "text"; text: string },
{ type: "data-subagent-artifact"; data: SubagentArtifactData },
];
}
/** Whether a result is the failure shape (html/svg empty, failure brief). */
export function isSubagentFailure(kind: JobKind, result: ResearchResult | DemoResult | VisualResult): boolean {
if (kind === "research") {
const r = result as ResearchResult;
return r.sources.length === 0 && /^Research failed:/i.test(r.brief);
}
if (kind === "demo") {
const r = result as DemoResult;
return typeof r.html !== "string" || r.html.length === 0;
}
const r = result as VisualResult;
return typeof r.svg !== "string" || r.svg.length === 0;
}
/** The model-facing text of a steer: what the result IS, what to do with it. */
function steerText(kind: JobKind, result: ResearchResult | DemoResult | VisualResult): string {
if (isSubagentFailure(kind, result)) {
if (kind === "research")
return `${(result as ResearchResult).brief}\n\nContinue with what you can establish and flag the uncertainty to the learner.`;
if (kind === "demo")
return `The demo "${(result as DemoResult).title}" could not be built: ${
(result as DemoResult).notes ?? "unknown reason"
}. Fall back to explaining in prose; if the brief was the problem, re-call demo with a tighter one.`;
return `The figure could not be made: ${(result as VisualResult).notes ?? "unknown reason"}. Fall back to prose or mermaid, or re-call visual with a tighter brief.`;
}
if (kind === "research")
return `Research complete — the researcher's full brief follows. Weave it into the lesson and cite its sources when you use its findings:\n\n${(result as ResearchResult).brief}`;
if (kind === "demo")
return `The demo "${(result as DemoResult).title}" is built, headlessly tested, and rendered in the lesson. Builder notes: ${
(result as DemoResult).notes ?? "(none)"
}.\nTeach with it — reference its controls by name and point the learner at what to try.`;
return `The figure is drawn, verified by inspection, and rendered in the lesson. Maker notes: ${
(result as VisualResult).notes ?? "(none)"
}.\nReference its elements as you teach.`;
}
/**
* Build the steer message for a finished job (pure — shared by the runner,
* the wake pipeline, and tests). Deterministic id per job makes re-delivery
* idempotent.
*/
export function buildSubagentSteer(
job: Pick<JobRecord, "id" | "kind" | "toolCallId">,
result: ResearchResult | DemoResult | VisualResult,
): SubagentSteerMessage {
return {
id: `steer_${job.id}`,
role: "user",
metadata: { subagentResult: { jobId: job.id, kind: job.kind, toolCallId: job.toolCallId } },
parts: [
{ type: "text", text: steerText(job.kind, result) },
{ type: "data-subagent-artifact", data: { kind: job.kind, result } },
],
};
}
/** True when the transcript already carries this job's steer (idempotent delivery). */
export function steerDelivered(messages: UIMessage[], jobId: string): boolean {
return messages.some(
(m) => (m.metadata as { subagentResult?: { jobId?: string } } | undefined)?.subagentResult?.jobId === jobId,
);
}