Learner source files, on the teacher's own terms (nothing auto-injects): - read tool (src/agent/tools/read.ts): pi-read port — path/offset/limit, 2000-line/50KB truncation with use-offset continuation notices, image files (jpg/png/gif/webp/bmp) returned as native image content parts (new LhToolImageResult escape hatch in lh-tool.ts). Always-on in both the prober and teacher registries (user-decided 2026-09). - pdf-reader sub-agent (JobKind 'pdf', toggleable, ack-and-steer): triage via pdf_info (pdfjs text layer: per-page text/image/math-density), targeted pdf_extract, regex pdf_search (hits count as consultation), and pdf_render — pages painted by pdfjs onto a canvas shim in headless Chrome (the pdfium viewer doesn't paint headless), screenshot fed back image-in-the-loop (visual-maker idiom, providerSafePng applied). The unread-finish gate bounces a zero-consultation brief once. Teacher gets a text brief with page citations only; renders never leave the loop. - MODELS.pdfReader = qwen/qwen3.8-flash (user override 2026-09-19: the look-at-renders workload wants the vision-proven model; catalog listed glm-5.3-flash as image-capable but qwen is the known-good daily driver). - UI: PdfCompleteBadge + PdfBriefCard (steer-card, job-card), dispatch card + activity-dock kind entries (type-forced, flagged for UI review). - Prompts: 'Learner source files' section in teacher/30-jobs.md; read line in prober/10-probe-doctrine.md. Doctrine rides tool descriptions per the self-contained-tools principle.
470 lines
19 KiB
TypeScript
470 lines
19 KiB
TypeScript
import { isToolUIPart, type UIMessage } from "ai";
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import type { PiEngine } from "../models.ts";
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import {
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accumulateJobUsage,
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buildSubagentSteer,
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piUsageToStep,
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type DemoResult,
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type DemoToolInput,
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type JobKind,
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type JobRecord,
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type JobUsage,
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type PdfResult,
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type PdfToolInput,
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type ResearchResult,
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type ResearchToolInput,
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type SubagentSteerMessage,
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type UsageStepLike,
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type VisualResult,
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type VisualToolInput,
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} from "../../core/contracts.ts";
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import { registerJobAbort, unregisterJobAbort } from "./aborts.ts";
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import { MODELS } from "../../../config.ts";
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import type { ChatStore, JobStore } from "../../core/ports.ts";
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import { runDemoBuilder } from "./demo-builder.ts";
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import { runPdfReaderAgent } from "./pdf-reader.ts";
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import { runResearcherAgent } from "./researcher.ts";
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import { runVisualMaker } from "./visual-maker.ts";
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/**
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* The background job runner (contracts.ts "THE ASYNC PROTOCOL" §2–3), created
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* via createJobRunner({ chatStore, jobStore, deliver }) — the composition root
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* (chat-handler) injects the storage ports and the WAKE SEAM (the server-side
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* steer delivery, src/server/jobs.ts); this module never imports an adapter.
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*
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* runJob(jobId) — runs the kind's sub-agent loop in the background
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* (the job tools' execute fires this via the spawn seam, fire-and-forget),
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* updating the job's activity line on every iteration. On completion the
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* runner builds the STEER MESSAGE (buildSubagentSteer) and hands it to
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* `deliver`; the wake pipeline fires the server-side teacher turn and
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* flips the job to done/error when the lesson has actually resumed.
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*
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* On failure the result is the failure shape (empty html/svg + "FAILED: …"
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* notes; research: failure brief) — and it STILL steers, because the
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* teacher must learn the outcome. If delivery itself fails, the job is
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* marked error (the learner's activity card shows it).
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*/
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/**
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* Test seam: the spawn wiring has no injection point at the tool layer, so
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* tests swap in a scripted pi engine here to keep job tests off the network.
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* Undefined in production. (The jobs spawn through the module-level KIND
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* runners, which read these at call time.)
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*/
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export const researchModelOverride: { current?: PiEngine } = {};
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export const demoModelOverride: { current?: PiEngine } = {};
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export const visualModelOverride: { current?: PiEngine } = {};
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export const pdfModelOverride: { current?: PiEngine } = {};
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/** The dispatch-time tool input (from src/agent/tools/jobs.ts schemas). */
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type JobToolInput = ResearchToolInput | DemoToolInput | VisualToolInput | PdfToolInput;
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export interface JobRunnerDeps {
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chatStore: ChatStore;
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jobStore: JobStore;
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/**
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* Hand a finished job's steer to the wake pipeline — resolves when the
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* steer is delivered (the wake turn completed and the job status
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* flipped); rejects when delivery fails unrecoverably.
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*/
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deliver: (steer: SubagentSteerMessage) => Promise<void>;
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}
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export interface JobRunner {
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/** Run one job's sub-agent loop to completion (background; never throws).
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* The tool input rides along from dispatch (the spawn fires mid-stream,
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* before the tool part is persisted — only crash-recovery re-spawns
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* resolve the input from the transcript). */
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runJob(jobId: string, input?: JobToolInput): Promise<void>;
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}
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/** One job loop's injected machinery: the kill switch (real abort, 2026-09
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* semantics) and the usage tap (money channel — every model call folds into
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* JobRecord.usage as it completes). */
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interface LoopContext {
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/** Fires when abortJob kills the run; abortSignal is passed into every
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* model call so the spend stops mid-call, not at the next loop check. */
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abortSignal: AbortSignal;
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/** Fold one model call's usage into the job record (progress write). */
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onUsage: (step: UsageStepLike) => void;
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}
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/** The OpenRouter model id for a job kind — JobUsage.model. The kind→role
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* table mirrors MODELS in config.ts (research→researcher, demo→demoBuilder,
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* visual→visualMaker); the id is taken from config so a price-table sync
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* re-prices jobs for free. Model overrides (tests) still bill under the
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* configured model — usage is what is being captured, not which instance.
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* Context-injection jobs make NO model call ("" — onUsage never fires for
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* them; the kind is deliberately absent from the runners below). */
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const KIND_MODEL: Record<JobKind, string> = {
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research: MODELS.researcher.model,
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demo: MODELS.demoBuilder.model,
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visual: MODELS.visualMaker.model,
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pdf: MODELS.pdfReader.model,
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"graph-context": "",
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};
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export function createJobRunner(deps: JobRunnerDeps): JobRunner {
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const { chatStore, jobStore, deliver } = deps;
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/** Running usage totals per live job (the loop's onUsage folds here,
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* then writes through the job store so the poll sees progress). */
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const usageTotals = new Map<string, JobUsage>();
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function makeLoopContext(jobId: string, kind: JobKind): LoopContext {
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const model = KIND_MODEL[kind];
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// Real-kill wiring (2026-09 abort semantics): the controller is what
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// the abort endpoint fires (agent/subagents/aborts.ts registry); the
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// signal rides into every model call of the loop.
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const controller = new AbortController();
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registerJobAbort(jobId, controller);
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return {
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abortSignal: controller.signal,
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onUsage: (step) => {
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const next = accumulateJobUsage(usageTotals.get(jobId), model, step);
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usageTotals.set(jobId, next);
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jobStore.updateJob(jobId, { usage: next }); // merge patch — status untouched
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},
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};
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}
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/** True while the job may still write terminal state (result, error,
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* steer). False once abortJob has flipped it to error ("Aborted by learner") —
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* the runner then unwinds silently; the abort path owns the record and
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* the abort steer. */
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function stillRunning(jobId: string): boolean {
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return jobStore.getJob(jobId)?.status === "running";
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}
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/** The kind→runner map: one sub-agent loop per SUB-AGENT kind.
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* graph-context is deliberately absent: injection jobs are not
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* sub-agent loops (no model, graph deps instead) — their spawn and
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* crash-respawn seam is subagents/graph-context.ts, and runJob refuses
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* them below rather than guessing wrong. */
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// Each kind's runner narrows the union input itself (dispatch-time inputs
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// are kind-correct by construction; transcript fallbacks are cast after).
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const KIND_RUNNERS: Record<
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Exclude<JobKind, "graph-context">,
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(jobId: string, input: JobToolInput | undefined, loop: LoopContext) => Promise<void>
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> = {
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research: (jobId, input, loop) => runResearchJob(jobId, researchModelOverride.current, input, loop),
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demo: (jobId, input, loop) => runDemoJob(jobId, demoModelOverride.current, input, loop),
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visual: (jobId, input, loop) => runVisualJob(jobId, visualModelOverride.current, input, loop),
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pdf: (jobId, input, loop) => runPdfJob(jobId, pdfModelOverride.current, input, loop),
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};
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async function runJob(jobId: string, input?: JobToolInput): Promise<void> {
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const job = jobStore.getJob(jobId);
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if (!job) {
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console.error(`[job ${jobId}] not found — nothing to run`);
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return;
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}
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if (job.status !== "running") return; // already finished / re-run after crash recovery
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if (job.kind === "graph-context") {
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// Not a sub-agent: the injection's own respawn seam
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// (setContextRespawn → runGraphContextJob) owns these records.
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console.error(`[job ${jobId}] graph-context job reached the sub-agent runner — wrong seam`);
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return;
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}
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const run = KIND_RUNNERS[job.kind];
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if (!run) {
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console.error(`[job ${jobId}] unknown kind: ${job.kind}`);
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jobStore.updateJob(jobId, { status: "error", error: `unknown kind ${job.kind}`, activity: "failed" });
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return;
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}
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try {
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await run(jobId, input, makeLoopContext(jobId, job.kind));
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} finally {
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unregisterJobAbort(jobId);
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// The last usage write may have been mid-flight when the loop died;
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// persist what was folded (the abort path patches only status, so
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// this never resurrects an aborted job — merge patch).
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const usage = usageTotals.get(jobId);
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if (usage) jobStore.updateJob(jobId, { usage });
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usageTotals.delete(jobId);
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}
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}
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/** Resolve the job's tool input: dispatch passes it directly; only a
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* crash-recovery re-spawn (no input) falls back to scanning the
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* transcript (by then onFinish has long persisted the part). */
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function resolveInput(
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job: JobRecord,
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input: JobToolInput | undefined,
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): JobToolInput | undefined {
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if (input) return input;
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const chat = chatStore.getChat(job.chatId);
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if (!chat) return undefined;
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return (findToolPart(chat.messages, job.toolCallId)?.input ?? undefined) as JobToolInput | undefined;
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}
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// ─── shared plumbing ────────────────────────────────────────────────────
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function findToolPart(messages: UIMessage[], toolCallId: string) {
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for (const m of messages) {
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for (const part of m.parts) {
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if (isToolUIPart(part) && part.toolCallId === toolCallId) return part;
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}
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}
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return null;
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}
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/**
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* The tail of every job: store the result, build the steer, hand it to
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* the wake pipeline. The pipeline flips the status when the lesson has
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* actually resumed — until then the job reads "running" so the client's
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* activity card keeps polling and re-syncs once, at the end.
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*/
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async function finishJob(jobId: string, result: ResearchResult | DemoResult | VisualResult | PdfResult): Promise<void> {
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const job = jobStore.getJob(jobId);
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if (!job) return;
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// Aborted mid-run or mid-delivery (abortJob flips the record before
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// the loop unwinds): no result write, no steer — the abort path owns
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// the record and queues the abort steer itself.
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if (job.status !== "running") return;
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jobStore.updateJob(jobId, { result, activity: "delivering result" });
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const steer = buildSubagentSteer(job, result);
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try {
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await deliver(steer);
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} catch (err) {
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const reason = err instanceof Error ? err.message : String(err);
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console.error(`[job ${jobId}] steer delivery failed:`, err);
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jobStore.updateJob(jobId, { status: "error", error: reason, activity: "delivery failed" });
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}
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}
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/** Chat-record + input resolution shared by all three runners. */
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function jobContext(jobId: string): { job: JobRecord; chatId: string } | null {
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const job = jobStore.getJob(jobId);
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if (!job || job.status !== "running") return null;
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const chat = chatStore.getChat(job.chatId);
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if (!chat) {
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jobStore.updateJob(jobId, { status: "error", error: `Chat not found: ${job.chatId}`, activity: "failed" });
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return null;
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}
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return { job, chatId: job.chatId };
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}
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// ─── research ───────────────────────────────────────────────────────────
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async function runResearchJob(
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jobId: string,
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model: PiEngine | undefined,
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passedInput: JobToolInput | undefined,
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loop: LoopContext,
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): Promise<void> {
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const ctx = jobContext(jobId);
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if (!ctx) return;
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const { job } = ctx;
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const input = (passedInput ?? resolveInput(job, passedInput)) as ResearchToolInput | undefined;
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const question = typeof input?.question === "string" && input.question.trim() ? input.question : "(no question)";
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const context = typeof input?.context === "string" && input.context.trim() ? input.context : undefined;
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const prompt = [
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`Research question: ${question}`,
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context ? `Context (what this is needed for): ${context}` : null,
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"Produce your final brief in the required format.",
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]
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.filter(Boolean)
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.join("\n\n");
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const fetchedUrls: string[] = [];
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try {
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jobStore.updateJob(jobId, { activity: "researching" });
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const brief = await runResearcherAgent(prompt, {
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engine: model,
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abortSignal: loop.abortSignal,
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// Money channel: each agent step is one model call — fold its
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// usage into the record as it completes (progress write).
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onUsage: (usage) => loop.onUsage(piUsageToStep(usage)),
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onToolStart: (toolName, args) => {
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const input = args as { query?: string; url?: string } | undefined;
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if (toolName === "web_fetch" && typeof input?.url === "string") {
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fetchedUrls.push(input.url);
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}
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jobStore.updateJob(jobId, { activity: activityLine(toolName, input) });
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},
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});
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if (!brief.trim()) throw new Error("the researcher produced no text");
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const research: ResearchResult = { brief: brief.trim(), sources: parseSources(brief.trim(), fetchedUrls) };
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await finishJob(jobId, research);
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} catch (err) {
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// Real-kill abort (2026-09): the abort path flipped the record and
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// queued the abort steer — unwind silently, keep the usage
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// folded so far (flushed by runJob's finally).
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if (loop.abortSignal.aborted) return;
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const reason = err instanceof Error ? err.message : String(err);
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if (stillRunning(jobId)) jobStore.updateJob(jobId, { error: reason });
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await finishJob(jobId, { brief: `Research failed: ${reason}`, sources: [] });
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}
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}
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// ─── demo + visual ──────────────────────────────────────────────────────
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async function runDemoJob(
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jobId: string,
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model: PiEngine | undefined,
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passedInput: JobToolInput | undefined,
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loop: LoopContext,
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): Promise<void> {
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const ctx = jobContext(jobId);
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if (!ctx) return;
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const { job } = ctx;
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const input = (passedInput ?? resolveInput(job, passedInput)) as DemoToolInput | undefined;
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const title = typeof input?.title === "string" && input.title.trim() ? input.title : "Interactive demo";
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const brief = typeof input?.brief === "string" ? input.brief : "";
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try {
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jobStore.updateJob(jobId, { activity: "building demo" });
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const result = await runDemoBuilder(
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{ title, brief },
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{
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engine: model,
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abortSignal: loop.abortSignal,
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onUsage: (usage) => loop.onUsage(piUsageToStep(usage)),
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onActivity: (line) => jobStore.updateJob(jobId, { activity: line }),
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},
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);
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if (isDemoFailure(result) && stillRunning(jobId))
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jobStore.updateJob(jobId, { error: result.notes ?? "demo build failed" });
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await finishJob(jobId, result);
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} catch (err) {
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if (loop.abortSignal.aborted) return;
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const reason = err instanceof Error ? err.message : String(err);
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if (stillRunning(jobId)) jobStore.updateJob(jobId, { error: reason });
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await finishJob(jobId, { title, html: "", tested: true, notes: `FAILED: ${reason}` });
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}
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}
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async function runVisualJob(
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jobId: string,
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model: PiEngine | undefined,
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passedInput: JobToolInput | undefined,
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loop: LoopContext,
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): Promise<void> {
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const ctx = jobContext(jobId);
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if (!ctx) return;
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const { job } = ctx;
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const input = (passedInput ?? resolveInput(job, passedInput)) as VisualToolInput | undefined;
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const brief = typeof input?.brief === "string" ? input.brief : "";
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try {
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jobStore.updateJob(jobId, { activity: "drawing figure" });
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const result = await runVisualMaker(
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{ brief },
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{
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engine: model,
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abortSignal: loop.abortSignal,
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onUsage: (usage) => loop.onUsage(piUsageToStep(usage)),
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onActivity: (line) => jobStore.updateJob(jobId, { activity: line }),
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},
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);
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if (isVisualFailure(result) && stillRunning(jobId))
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jobStore.updateJob(jobId, { error: result.notes ?? "visual build failed" });
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await finishJob(jobId, result);
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} catch (err) {
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if (loop.abortSignal.aborted) return;
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const reason = err instanceof Error ? err.message : String(err);
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if (stillRunning(jobId)) jobStore.updateJob(jobId, { error: reason });
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await finishJob(jobId, { svg: "", notes: `FAILED: ${reason}` });
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}
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}
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// ─── pdf reading (sources v0) ────────────────────────────────────────────
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async function runPdfJob(
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jobId: string,
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model: PiEngine | undefined,
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passedInput: JobToolInput | undefined,
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loop: LoopContext,
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): Promise<void> {
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const ctx = jobContext(jobId);
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if (!ctx) return;
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const { job } = ctx;
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const input = (passedInput ?? resolveInput(job, passedInput)) as PdfToolInput | undefined;
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const path = typeof input?.path === "string" && input.path.trim() ? input.path.trim() : "";
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const question = typeof input?.question === "string" ? input.question : "";
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try {
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jobStore.updateJob(jobId, { activity: "reading pdf" });
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const result = await runPdfReaderAgent(
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{ path, question },
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{
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engine: model,
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abortSignal: loop.abortSignal,
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onUsage: (usage) => loop.onUsage(piUsageToStep(usage)),
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onActivity: (line) => jobStore.updateJob(jobId, { activity: line }),
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},
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);
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if (isPdfFailure(result) && stillRunning(jobId))
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jobStore.updateJob(jobId, { error: result.brief.replace(/^PDF failed:\s*/i, "") });
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await finishJob(jobId, result);
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} catch (err) {
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if (loop.abortSignal.aborted) return;
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const reason = err instanceof Error ? err.message : String(err);
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if (stillRunning(jobId)) jobStore.updateJob(jobId, { error: reason });
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await finishJob(jobId, { path, question, brief: `PDF failed: ${reason}`, pagesConsulted: [] });
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}
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}
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return { runJob };
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}
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// ─── module-level pure helpers ──────────────────────────────────────────────
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/** Failure shape (W6 brief): html === "" with "FAILED: …" notes. */
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function isDemoFailure(result: DemoResult): boolean {
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return typeof result.html !== "string" || result.html.length === 0;
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}
|
||
|
||
function isVisualFailure(result: VisualResult): boolean {
|
||
return typeof result.svg !== "string" || result.svg.length === 0;
|
||
}
|
||
|
||
/** The pdf-reader's failure brief (mirrors the research failure shape). */
|
||
function isPdfFailure(result: PdfResult): boolean {
|
||
return /^PDF failed:/i.test(result.brief);
|
||
}
|
||
|
||
/** The activity line shown in the UI: `web_search: "query"` / `web_fetch: host`. */
|
||
function activityLine(toolName: string, input: { query?: string; url?: string } | undefined): string {
|
||
if (toolName === "web_search") return `web_search: "${input?.query ?? ""}"`;
|
||
if (toolName === "web_fetch") return `web_fetch: ${hostOf(input?.url)}`;
|
||
return toolName;
|
||
}
|
||
|
||
function hostOf(url: string | undefined): string {
|
||
if (!url) return "(no url)";
|
||
try {
|
||
return new URL(url).hostname;
|
||
} catch {
|
||
return url.slice(0, 40);
|
||
}
|
||
}
|
||
|
||
/** Sources for the result: markdown links cited in the brief, else fetched URLs. */
|
||
function parseSources(brief: string, fetchedUrls: string[]): ResearchResult["sources"] {
|
||
const sources: ResearchResult["sources"] = [];
|
||
const seen = new Set<string>();
|
||
for (const match of brief.matchAll(/\[([^\]]+)\]\((https?:\/\/[^)\s]+)\)/g)) {
|
||
const title = (match[1] ?? "").trim();
|
||
const url = match[2]!;
|
||
if (!title || seen.has(url)) continue;
|
||
seen.add(url);
|
||
sources.push({ title, url });
|
||
}
|
||
if (sources.length === 0) {
|
||
for (const url of fetchedUrls) {
|
||
if (seen.has(url)) continue;
|
||
seen.add(url);
|
||
sources.push({ title: hostOf(url), url });
|
||
}
|
||
}
|
||
return sources.slice(0, 10);
|
||
}
|