Swap the server engine to pi-ai/pi-agent-core (Band B+C of docs/pi-engine-swap.md)
The Vercel AI SDK survives only as Band D (useChat client + UIMessage
record types); @openrouter/ai-sdk-provider is uninstalled.
- src/agent/models.ts: PiEngine {model, streamFn} via createModels +
openrouterProvider subpath; thinkingLevelFor maps config effort none->off
- src/agent/lh-tool.ts: neutral LhTool (zod authoring, optional execute,
clientQuestion flag); toPiTool converts via z.toJSONSchema and re-runs
zod inside execute so refinements ride the error-result retry path
- src/server/pi/record-adapter.ts: UIMessage records -> pi Messages
(dangling tool calls get synthesized interrupted results)
- src/server/pi/ui-stream.ts: SSE bridge emitting AI-SDK-shaped chunks so
the useChat client parses unchanged (continuation id rule, question
tools never emit output, tool-input-error for bad authoring)
- teacher-agent.ts: stateless per-turn pi Agents; shouldStopAfterTurn
stops only when every question-tool call resolved cleanly (errors retry)
- chat-handler.ts: buildAgent(outgoing) factory seam (stateless doctrine);
assertValidUiMessages owns the retired SDK validation gate
- sub-agents via shared runSubagent (pi-run.ts); extraction stages stop
after a clean submit; visual-maker keeps its hand-rolled loop over
direct streamSimple calls; aborted model calls bill no usage
- tests: all model seams ported to pi-ai faux provider (scripted
FauxResponseSteps, agent factories); handleChatRequest second param
is now an agent factory
Gates: tsc, lint, build, 305/305. Live GLM smoke (disposable driver,
deleted): prober streaming + persistence, question seam, turn-2
continuation same message id, per-turn real token usage - ALL PASS.
Data wiped at the pivot (chats/graph/jobs, .gitkeeps kept).
This commit is contained in:
@@ -1,7 +1,9 @@
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import { ToolLoopAgent, stepCountIs, tool, type LanguageModel, type ToolSet } from "ai";
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import { z } from "zod";
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import { modelFor } from "../models.ts";
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import type { DemoResult, UsageStepLike } from "../../core/contracts.ts";
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import type { Usage } from "@earendil-works/pi-ai";
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import { lhTool, toPiTools, type LhTool } from "../lh-tool.ts";
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import type { PiEngine } from "../models.ts";
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import { runSubagent } from "./pi-run.ts";
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import type { DemoResult } from "../../core/contracts.ts";
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import { getHeadless, type DemoRunResult, type HeadlessApi } from "./headless.ts";
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/**
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@@ -11,7 +13,7 @@ import { getHeadless, type DemoRunResult, type HeadlessApi } from "./headless.ts
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* fix → re-run until clean — before anything reaches the lesson.
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*
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* Shape: a ToolLoopAgent with two executable tools (write_demo / run_demo) —
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* the model is injectable (tests use MockLanguageModelV4) and the headless
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* the engine is injectable (tests use a scripted faux engine) and the headless
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* API is injectable (tests use a fake; production uses system Chrome).
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*
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* Failure semantics (decided in the W6 brief): `tested: true` means "the
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@@ -26,7 +28,8 @@ export interface DemoBuilderInput {
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}
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export interface DemoBuilderOptions {
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model?: LanguageModel;
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/** Test seam: scripted engine; production uses the demoBuilder role. */
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engine?: PiEngine;
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headless?: HeadlessApi;
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/** Max agent steps (each write/run/fix is one step). Default 24 ≈ 6 cycles. */
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maxSteps?: number;
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@@ -35,7 +38,7 @@ export interface DemoBuilderOptions {
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/** Kills the run mid-model-call (2026-09 real-kill abort semantics). */
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abortSignal?: AbortSignal;
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/** Money channel: one call per agent step, folded into JobRecord.usage. */
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onUsage?: (usage: UsageStepLike) => void;
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onUsage?: (usage: Usage) => void;
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}
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const INSTRUCTIONS = `You are a demo builder — a specialist sub-agent inside a learning application. You
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@@ -78,13 +81,14 @@ export function createDemoBuilderTools(
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state: BuilderState,
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headless: HeadlessApi,
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onActivity?: (line: string) => void,
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): ToolSet {
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): Record<string, LhTool<any, any>> {
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return {
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write_demo: tool({
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write_demo: lhTool({
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name: "write_demo",
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description:
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"Write the complete self-contained HTML document for the demo (overwrites any previous version). " +
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"Always follow with run_demo to test it headlessly.",
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inputSchema: z.object({
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schema: z.object({
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html: z.string().describe("The complete HTML document: <!doctype html>…</html>, all JS inline."),
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}),
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execute: async ({ html }) => {
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@@ -94,11 +98,12 @@ export function createDemoBuilderTools(
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return `Saved (${html.length} bytes). Now call run_demo to test it — never deliver untested.`;
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},
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}),
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run_demo: tool({
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run_demo: lhTool({
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name: "run_demo",
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description:
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"Headlessly execute the current demo in Chrome and report console errors, uncaught errors, and failed requests. " +
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"Optionally pass a probe expression to assert on page state.",
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inputSchema: z.object({
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schema: z.object({
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probe: z
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.string()
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.optional()
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@@ -174,12 +179,6 @@ export async function runDemoBuilder(input: DemoBuilderInput, opts: DemoBuilderO
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}
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const state: BuilderState = { html: null, testedHtml: null, lastResult: null };
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const agent = new ToolLoopAgent({
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model: opts.model ?? modelFor("demoBuilder"),
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instructions: INSTRUCTIONS,
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tools: createDemoBuilderTools(state, headless, opts.onActivity),
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stopWhen: stepCountIs(opts.maxSteps ?? 24),
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});
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const prompt = [
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`Demo title: ${title}`,
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@@ -191,13 +190,15 @@ export async function runDemoBuilder(input: DemoBuilderInput, opts: DemoBuilderO
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let finalText = "";
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try {
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const result = await agent.generate({
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const result = await runSubagent(toPiTools(createDemoBuilderTools(state, headless, opts.onActivity)), {
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role: "demoBuilder",
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engine: opts.engine,
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systemPrompt: INSTRUCTIONS,
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prompt,
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maxTurns: opts.maxSteps ?? 24,
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abortSignal: opts.abortSignal,
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onStepFinish: ({ usage }) => opts.onUsage?.(usage),
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onToolExecutionStart: ({ toolCall }) => {
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opts.onActivity?.(toolCall.toolName);
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},
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onUsage: (usage) => opts.onUsage?.(usage),
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onToolStart: (toolName) => opts.onActivity?.(toolName),
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});
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finalText = result.text;
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} catch (err) {
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@@ -1,6 +1,9 @@
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import { ToolLoopAgent, stepCountIs, tool, type LanguageModel, type UIMessage } from "ai";
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import type { UIMessage } from "ai";
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import type { Usage } from "@earendil-works/pi-ai";
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import { z } from "zod";
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import { modelFor } from "../models.ts";
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import { lhTool, toPiTools } from "../lh-tool.ts";
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import type { PiEngine } from "../models.ts";
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import { runSubagent } from "./pi-run.ts";
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import type {
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AuditResult,
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CallUsage,
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@@ -207,19 +210,50 @@ transcript). The auditor rejects anything unbacked. When in doubt, report; the a
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Your entire deliverable is ONE submit_findings call.`;
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function createExtractor(model: LanguageModel) {
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return new ToolLoopAgent({
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model,
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instructions: EXTRACTOR_INSTRUCTIONS,
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tools: {
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submit_findings: tool({
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/** One extractor run: the whole deliverable is ONE zod-validated submit
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* call (a pi agent purely so the model can retry a schema-invalid call).
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* Returns the submitted findings — captured from the execute seam, which
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* only fires on a schema-valid call. */
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async function runExtractor(
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engine: PiEngine | undefined,
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prompt: string,
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signal: AbortSignal | undefined,
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onStep: (usage: Usage, model: string, step: number, finishReason: string, tools: string) => void,
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): Promise<SessionFindings> {
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let submitted: SessionFindings | undefined;
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const result = await runSubagent(
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toPiTools({
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submit_findings: lhTool({
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name: "submit_findings",
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description: "Submit the session findings.",
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inputSchema: findingsSchema,
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execute: async (findings) => findings,
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schema: findingsSchema,
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execute: async (findings) => {
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submitted = findings;
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return findings;
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},
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}),
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}),
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{
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role: "extractor",
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engine,
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systemPrompt: EXTRACTOR_INSTRUCTIONS,
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prompt,
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maxTurns: 4,
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abortSignal: signal,
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onAssistantMessage: (message, step) =>
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onStep(
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message.usage,
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message.model,
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step,
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message.stopReason,
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message.content.filter((c) => c.type === "toolCall").map((c) => (c as { name: string }).name).join(", ") || "(none)",
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),
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shouldStop: (_message, toolResults) => toolResults.some((r) => r.toolName === "submit_findings" && !r.isError),
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},
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stopWhen: stepCountIs(4),
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});
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);
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void result;
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if (!submitted) throw new Error("the extractor never submitted findings");
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return submitted;
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}
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// ─── the auditor ───────────────────────────────────────────────────────────
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@@ -290,19 +324,47 @@ function graphView(nodes: GraphNode[]): string {
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return lines.join("\n");
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}
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function createAuditor(model: LanguageModel) {
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return new ToolLoopAgent({
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model,
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instructions: AUDITOR_INSTRUCTIONS,
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tools: {
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submit_review: tool({
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/** One auditor run — same single-submit shape as the extractor. */
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async function runAuditor(
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engine: PiEngine | undefined,
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prompt: string,
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signal: AbortSignal | undefined,
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onStep: (usage: Usage, model: string, step: number, finishReason: string, tools: string) => void,
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): Promise<AuditResult> {
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let submitted: AuditResult | undefined;
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const result = await runSubagent(
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toPiTools({
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submit_review: lhTool({
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name: "submit_review",
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description: "Submit the verified findings subset (with identity verdicts) + the dropped list.",
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inputSchema: auditSchema,
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execute: async (review) => review,
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schema: auditSchema,
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execute: async (review) => {
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submitted = review;
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return review;
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},
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}),
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}),
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{
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role: "auditor",
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engine,
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systemPrompt: AUDITOR_INSTRUCTIONS,
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prompt,
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maxTurns: 4,
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abortSignal: signal,
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onAssistantMessage: (message, step) =>
|
||||
onStep(
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||||
message.usage,
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message.model,
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step,
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||||
message.stopReason,
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message.content.filter((c) => c.type === "toolCall").map((c) => (c as { name: string }).name).join(", ") || "(none)",
|
||||
),
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shouldStop: (_message, toolResults) => toolResults.some((r) => r.toolName === "submit_review" && !r.isError),
|
||||
},
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||||
stopWhen: stepCountIs(4),
|
||||
});
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||||
);
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void result;
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||||
if (!submitted) throw new Error("the auditor never submitted a review");
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return submitted;
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||||
}
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// ─── the pipeline status registry ─────────────────────────────────────────────
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@@ -346,10 +408,9 @@ export function abortExtraction(chatId: string): boolean {
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||||
// ─── the pipeline ───────────────────────────────────────────────────────────
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||||
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||||
export interface ExtractionModels {
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||||
/** The extractor's model (tests inject a MockLanguageModelV4). */
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extractor?: LanguageModel;
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/** The auditor's model. */
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||||
auditor?: LanguageModel;
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||||
/** Test seam: a scripted engine per stage (production uses the roles). */
|
||||
extractor?: PiEngine;
|
||||
auditor?: PiEngine;
|
||||
}
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||||
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||||
export interface ExtractionPipelineDeps extends GraphDeps, ExtractionModels {}
|
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@@ -362,8 +423,6 @@ export interface ExtractionPipeline {
|
||||
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||||
export function createExtractionPipeline(deps: ExtractionPipelineDeps): ExtractionPipeline {
|
||||
const { chatStore, graphStore } = deps;
|
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const extractorAgent = createExtractor(deps.extractor ?? modelFor("extractor"));
|
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const auditorAgent = createAuditor(deps.auditor ?? modelFor("auditor"));
|
||||
const inFlight = new Set<string>();
|
||||
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||||
function setPhase(chatId: string, phase: ExtractionPhase): void {
|
||||
@@ -385,22 +444,17 @@ export function createExtractionPipeline(deps: ExtractionPipelineDeps): Extracti
|
||||
run.usage[stage]!.steps.push(usage);
|
||||
}
|
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|
||||
/** The SDK's per-step usage, flattened to the persisted CallUsage fields
|
||||
/** pi's per-step usage, flattened to the persisted CallUsage fields
|
||||
* (the money channel's capture shape, contracts/chat.ts). */
|
||||
function callUsage(usage: {
|
||||
inputTokens: number | undefined;
|
||||
outputTokens: number | undefined;
|
||||
inputTokenDetails?: { cacheReadTokens?: number; cacheWriteTokens?: number };
|
||||
outputTokenDetails?: { reasoningTokens?: number };
|
||||
}): CallUsage {
|
||||
// Optional-chained: the SDK types the detail objects as required, but
|
||||
// providers (and mocks) may leave them unset.
|
||||
function callUsage(usage: Usage): CallUsage {
|
||||
return {
|
||||
inputTokens: usage.inputTokens,
|
||||
outputTokens: usage.outputTokens,
|
||||
cacheReadTokens: usage.inputTokenDetails?.cacheReadTokens,
|
||||
cacheWriteTokens: usage.inputTokenDetails?.cacheWriteTokens,
|
||||
reasoningTokens: usage.outputTokenDetails?.reasoningTokens,
|
||||
inputTokens: usage.input,
|
||||
outputTokens: usage.output,
|
||||
cacheReadTokens: usage.cacheRead,
|
||||
cacheWriteTokens: usage.cacheWrite,
|
||||
// Optional in pi's Usage (providers that never emit reasoning
|
||||
// tokens leave it unset) — persisted as 0, never dropped.
|
||||
reasoningTokens: usage.reasoning ?? 0,
|
||||
};
|
||||
}
|
||||
|
||||
@@ -413,23 +467,17 @@ export function createExtractionPipeline(deps: ExtractionPipelineDeps): Extracti
|
||||
console.info(`[extraction ${chatId}] extractor starting (${view.split("\n").length} transcript lines)`);
|
||||
const t0 = performance.now();
|
||||
|
||||
const extraction = await extractorAgent.generate({
|
||||
prompt: `Transcript:\n\n${view}`,
|
||||
abortSignal: signal,
|
||||
onStepFinish: (step) => {
|
||||
recordStep(chatId, "extractor", callUsage(step.usage), step.model.modelId);
|
||||
console.info(
|
||||
`[extraction] extractor step ${step.stepNumber}: ${step.finishReason}, tools: ${step.toolCalls.map((c) => c.toolName).join(", ") || "(none)"}`,
|
||||
);
|
||||
const findings = await runExtractor(
|
||||
deps.extractor,
|
||||
`Transcript:\n\n${view}`,
|
||||
signal,
|
||||
(usage, model, step, finishReason, tools) => {
|
||||
recordStep(chatId, "extractor", callUsage(usage), model);
|
||||
console.info(`[extraction] extractor step ${step}: ${finishReason}, tools: ${tools}`);
|
||||
},
|
||||
});
|
||||
for (const part of extraction.content) {
|
||||
if (part.type === "tool-result" && part.toolName === "submit_findings") {
|
||||
console.info(`[extraction ${chatId}] extractor done in ${Math.round(performance.now() - t0)}ms`);
|
||||
return part.output as SessionFindings;
|
||||
}
|
||||
}
|
||||
throw new Error("the extractor never submitted findings");
|
||||
);
|
||||
console.info(`[extraction ${chatId}] extractor done in ${Math.round(performance.now() - t0)}ms`);
|
||||
return findings;
|
||||
}
|
||||
|
||||
async function audit(chatId: string, findings: SessionFindings): Promise<AuditResult> {
|
||||
@@ -445,25 +493,16 @@ export function createExtractionPipeline(deps: ExtractionPipelineDeps): Extracti
|
||||
);
|
||||
const t0 = performance.now();
|
||||
|
||||
const review = await auditorAgent.generate({
|
||||
prompt:
|
||||
`Transcript:\n\n${view}\n\nProposed findings:\n\n${JSON.stringify(findings, null, 2)}\n\n` +
|
||||
const auditResult = await runAuditor(
|
||||
deps.auditor,
|
||||
`Transcript:\n\n${view}\n\nProposed findings:\n\n${JSON.stringify(findings, null, 2)}\n\n` +
|
||||
`Current knowledge graph (${graph.nodes.length} nodes):\n\n${graphView(graph.nodes)}`,
|
||||
abortSignal: signal,
|
||||
onStepFinish: (step) => {
|
||||
recordStep(chatId, "auditor", callUsage(step.usage), step.model.modelId);
|
||||
console.info(
|
||||
`[extraction] auditor step ${step.stepNumber}: ${step.finishReason}, tools: ${step.toolCalls.map((c) => c.toolName).join(", ") || "(none)"}`,
|
||||
);
|
||||
signal,
|
||||
(usage, model, step, finishReason, tools) => {
|
||||
recordStep(chatId, "auditor", callUsage(usage), model);
|
||||
console.info(`[extraction] auditor step ${step}: ${finishReason}, tools: ${tools}`);
|
||||
},
|
||||
});
|
||||
let auditResult: AuditResult | null = null;
|
||||
for (const part of review.content) {
|
||||
if (part.type === "tool-result" && part.toolName === "submit_review") {
|
||||
auditResult = part.output as AuditResult;
|
||||
}
|
||||
}
|
||||
if (!auditResult) throw new Error("the auditor never submitted a review");
|
||||
);
|
||||
if (auditResult.dropped.length > 0) {
|
||||
console.info(
|
||||
`[extraction ${chatId}] audit dropped ${auditResult.dropped.length}: ` +
|
||||
|
||||
@@ -0,0 +1,130 @@
|
||||
import { Agent, type AgentEvent, type AgentMessage, type AgentTool } from "@earendil-works/pi-agent-core";
|
||||
import type { AssistantMessage, ToolResultMessage, Usage } from "@earendil-works/pi-ai";
|
||||
import { openRouterApiKey, piEngineFor, thinkingLevelFor, type PiEngine } from "../models.ts";
|
||||
import type { ModelRole } from "../../../config.ts";
|
||||
|
||||
/**
|
||||
* The shared sub-agent runner (docs/pi-engine-swap.md §6): one helper every
|
||||
* background agent (researcher, demo-builder, visual-maker, extractor,
|
||||
* auditor) runs on — a stateless pi Agent built per call, driven to
|
||||
* completion, with the seams the job runner and the money channel need.
|
||||
*
|
||||
* Error semantics mirror the old ToolLoopAgent.generate: provider/loop
|
||||
* failures THROW (pi encodes them in the stream; this helper surfaces
|
||||
* them), and an abort throws an AbortError so every existing
|
||||
* `signal.aborted` early-return keeps working unchanged.
|
||||
*/
|
||||
|
||||
export interface SubagentRunOptions {
|
||||
/** The role whose engine (model + thinking level) this run uses. */
|
||||
role: ModelRole;
|
||||
/** Test seam: a scripted engine replaces the role's production one. */
|
||||
engine?: PiEngine;
|
||||
systemPrompt: string;
|
||||
/** Initial transcript (continuation semantics: ends user / toolResult). */
|
||||
messages?: AgentMessage[];
|
||||
/** Fresh-run prompt text (mutually exclusive with a continuation). */
|
||||
prompt?: string;
|
||||
/** Max model calls (the old stepCountIs safety net). */
|
||||
maxTurns: number;
|
||||
/** Abort mid-model-call (the real-kill semantics). */
|
||||
abortSignal?: AbortSignal;
|
||||
/** Money channel: one call per model request. */
|
||||
onUsage?: (usage: Usage) => void;
|
||||
/** Activity line per tool execution (job record progress). */
|
||||
onToolStart?: (toolName: string, args: unknown) => void;
|
||||
/** Per completed assistant message (extraction's step log). */
|
||||
onAssistantMessage?: (message: AssistantMessage, step: number) => void;
|
||||
/** Extra stop rule (extractor: stop after a clean submit). */
|
||||
shouldStop?: (message: AssistantMessage, toolResults: ToolResultMessage[]) => boolean;
|
||||
}
|
||||
|
||||
export interface SubagentRunResult {
|
||||
/** The messages this run added (assistant + tool results). */
|
||||
newMessages: AgentMessage[];
|
||||
/** The final assistant text (the deliverable). */
|
||||
text: string;
|
||||
}
|
||||
|
||||
export function subagentEngine(role: ModelRole, override?: PiEngine): PiEngine {
|
||||
return override ?? piEngineFor(role);
|
||||
}
|
||||
|
||||
export async function runSubagent(tools: AgentTool<any, any>[], opts: SubagentRunOptions): Promise<SubagentRunResult> {
|
||||
const engine = subagentEngine(opts.role, opts.engine);
|
||||
let turns = 0;
|
||||
const agent = new Agent({
|
||||
initialState: {
|
||||
systemPrompt: opts.systemPrompt,
|
||||
model: engine.model,
|
||||
thinkingLevel: thinkingLevelFor(opts.role),
|
||||
tools,
|
||||
messages: opts.messages ?? [],
|
||||
},
|
||||
streamFn: engine.streamFn,
|
||||
getApiKey: () => openRouterApiKey(),
|
||||
shouldStopAfterTurn: (context) => {
|
||||
turns++;
|
||||
return turns >= opts.maxTurns || opts.shouldStop?.(context.message, context.toolResults) === true;
|
||||
},
|
||||
});
|
||||
|
||||
const onAbort = () => agent.abort();
|
||||
opts.abortSignal?.addEventListener("abort", onAbort, { once: true });
|
||||
|
||||
const before = opts.messages?.length ?? 0;
|
||||
let step = 0;
|
||||
let errorMessage: string | undefined;
|
||||
let aborted = false;
|
||||
|
||||
try {
|
||||
agent.subscribe((event: AgentEvent) => {
|
||||
switch (event.type) {
|
||||
case "message_end":
|
||||
if ((event.message as { role?: string }).role === "assistant") {
|
||||
const m = event.message as AssistantMessage;
|
||||
if (m.stopReason === "aborted") {
|
||||
// The call was cancelled — no completed step, no billed
|
||||
// usage (the abort path asserts zero steps).
|
||||
aborted = true;
|
||||
break;
|
||||
}
|
||||
step++;
|
||||
opts.onUsage?.(m.usage);
|
||||
opts.onAssistantMessage?.(m, step);
|
||||
if (m.stopReason === "error") errorMessage = m.errorMessage;
|
||||
}
|
||||
break;
|
||||
case "tool_execution_start":
|
||||
opts.onToolStart?.(event.toolName, event.args);
|
||||
break;
|
||||
}
|
||||
});
|
||||
if (opts.prompt !== undefined) await agent.prompt({
|
||||
role: "user",
|
||||
content: opts.prompt,
|
||||
timestamp: Date.now(),
|
||||
});
|
||||
else await agent.continue();
|
||||
} finally {
|
||||
opts.abortSignal?.removeEventListener("abort", onAbort);
|
||||
}
|
||||
|
||||
if (aborted || opts.abortSignal?.aborted) {
|
||||
const err = new Error("aborted");
|
||||
err.name = "AbortError";
|
||||
throw err;
|
||||
}
|
||||
if (errorMessage !== undefined) throw new Error(errorMessage);
|
||||
|
||||
const newMessages = agent.state.messages.slice(before);
|
||||
const assistants = newMessages.filter((m) => (m as { role?: string }).role === "assistant") as AssistantMessage[];
|
||||
const last = assistants[assistants.length - 1];
|
||||
const text = last
|
||||
? last.content
|
||||
.filter((c): c is { type: "text"; text: string } => c.type === "text")
|
||||
.map((c) => c.text)
|
||||
.join("")
|
||||
: "";
|
||||
return { newMessages, text };
|
||||
}
|
||||
@@ -1,6 +1,9 @@
|
||||
import { ToolLoopAgent, stepCountIs, type LanguageModel } from "ai";
|
||||
import type { AgentTool } from "@earendil-works/pi-agent-core";
|
||||
import type { Usage } from "@earendil-works/pi-ai";
|
||||
import { webTools } from "../tools/web.ts";
|
||||
import { modelFor } from "../models.ts";
|
||||
import { toPiTools } from "../lh-tool.ts";
|
||||
import type { PiEngine } from "../models.ts";
|
||||
import { runSubagent } from "./pi-run.ts";
|
||||
|
||||
/**
|
||||
* The researcher sub-agent (vision §2.5): a SEPARATE ToolLoopAgent instance
|
||||
@@ -9,7 +12,7 @@ import { modelFor } from "../models.ts";
|
||||
*
|
||||
* System prompt adapted from the pi researcher agent
|
||||
* (~/.pi/agent/extensions/interactive-subagents/agents/researcher.md).
|
||||
* The model is injectable so tests run the loop with a MockLanguageModelV4.
|
||||
* The engine is injectable so tests run the loop with a scripted faux engine.
|
||||
*/
|
||||
|
||||
const INSTRUCTIONS = `You are a research specialist. You work for a teacher agent inside a learning
|
||||
@@ -57,13 +60,29 @@ Numbered findings with inline source citations:
|
||||
## Gaps
|
||||
What couldn't be answered. Suggested next steps.`;
|
||||
|
||||
export function createResearcherAgent(model?: LanguageModel) {
|
||||
return new ToolLoopAgent({
|
||||
model: model ?? modelFor("researcher"),
|
||||
instructions: INSTRUCTIONS,
|
||||
tools: webTools,
|
||||
stopWhen: stepCountIs(12),
|
||||
});
|
||||
export interface ResearcherRunOptions {
|
||||
engine?: PiEngine;
|
||||
abortSignal?: AbortSignal;
|
||||
onUsage?: (usage: Usage) => void;
|
||||
onToolStart?: (toolName: string, args: unknown) => void;
|
||||
}
|
||||
|
||||
export type ResearcherAgent = ReturnType<typeof createResearcherAgent>;
|
||||
/**
|
||||
* Run the researcher to completion: isolated context, web tools only, final
|
||||
* text = the brief. The engine is injectable so tests run the loop scripted.
|
||||
*/
|
||||
export async function runResearcherAgent(prompt: string, opts: ResearcherRunOptions = {}): Promise<string> {
|
||||
const { text } = await runSubagent(toPiTools(webTools) as AgentTool<any, any>[], {
|
||||
role: "researcher",
|
||||
prompt,
|
||||
engine: opts.engine,
|
||||
systemPrompt: INSTRUCTIONS,
|
||||
maxTurns: 12,
|
||||
abortSignal: opts.abortSignal,
|
||||
onUsage: opts.onUsage,
|
||||
onToolStart: opts.onToolStart,
|
||||
});
|
||||
return text;
|
||||
}
|
||||
|
||||
export type ResearcherAgent = ReturnType<typeof runResearcherAgent>;
|
||||
|
||||
@@ -1,7 +1,9 @@
|
||||
import { isToolUIPart, type LanguageModel, type UIMessage } from "ai";
|
||||
import { isToolUIPart, type UIMessage } from "ai";
|
||||
import type { PiEngine } from "../models.ts";
|
||||
import {
|
||||
accumulateJobUsage,
|
||||
buildSubagentSteer,
|
||||
piUsageToStep,
|
||||
type DemoResult,
|
||||
type DemoToolInput,
|
||||
type JobKind,
|
||||
@@ -18,7 +20,7 @@ import { registerJobAbort, unregisterJobAbort } from "./aborts.ts";
|
||||
import { MODELS } from "../../../config.ts";
|
||||
import type { ChatStore, JobStore } from "../../core/ports.ts";
|
||||
import { runDemoBuilder } from "./demo-builder.ts";
|
||||
import { createResearcherAgent } from "./researcher.ts";
|
||||
import { runResearcherAgent } from "./researcher.ts";
|
||||
import { runVisualMaker } from "./visual-maker.ts";
|
||||
|
||||
/**
|
||||
@@ -42,13 +44,13 @@ import { runVisualMaker } from "./visual-maker.ts";
|
||||
|
||||
/**
|
||||
* Test seam: the spawn wiring has no injection point at the tool layer, so
|
||||
* tests swap in a MockLanguageModelV4 here to keep job tests off the network.
|
||||
* tests swap in a scripted pi engine here to keep job tests off the network.
|
||||
* Undefined in production. (The jobs spawn through the module-level KIND
|
||||
* runners, which read these at call time.)
|
||||
*/
|
||||
export const researchModelOverride: { current?: LanguageModel } = {};
|
||||
export const demoModelOverride: { current?: LanguageModel } = {};
|
||||
export const visualModelOverride: { current?: LanguageModel } = {};
|
||||
export const researchModelOverride: { current?: PiEngine } = {};
|
||||
export const demoModelOverride: { current?: PiEngine } = {};
|
||||
export const visualModelOverride: { current?: PiEngine } = {};
|
||||
|
||||
/** The dispatch-time tool input (from src/agent/tools/jobs.ts schemas). */
|
||||
type JobToolInput = ResearchToolInput | DemoToolInput | VisualToolInput;
|
||||
@@ -232,7 +234,7 @@ export function createJobRunner(deps: JobRunnerDeps): JobRunner {
|
||||
|
||||
async function runResearchJob(
|
||||
jobId: string,
|
||||
model: LanguageModel | undefined,
|
||||
model: PiEngine | undefined,
|
||||
passedInput: JobToolInput | undefined,
|
||||
loop: LoopContext,
|
||||
): Promise<void> {
|
||||
@@ -253,28 +255,25 @@ export function createJobRunner(deps: JobRunnerDeps): JobRunner {
|
||||
.join("\n\n");
|
||||
|
||||
const fetchedUrls: string[] = [];
|
||||
const agent = createResearcherAgent(model);
|
||||
|
||||
try {
|
||||
jobStore.updateJob(jobId, { activity: "researching" });
|
||||
const result = await agent.generate({
|
||||
prompt,
|
||||
const brief = await runResearcherAgent(prompt, {
|
||||
engine: model,
|
||||
abortSignal: loop.abortSignal,
|
||||
// Money channel: each agent step is one model call — fold its
|
||||
// usage into the record as it completes (progress write).
|
||||
onStepFinish: ({ usage }) => loop.onUsage(usage),
|
||||
onToolExecutionStart: ({ toolCall }) => {
|
||||
const input = toolCall.input as { query?: string; url?: string } | undefined;
|
||||
if (toolCall.toolName === "web_fetch" && typeof input?.url === "string") {
|
||||
onUsage: (usage) => loop.onUsage(piUsageToStep(usage)),
|
||||
onToolStart: (toolName, args) => {
|
||||
const input = args as { query?: string; url?: string } | undefined;
|
||||
if (toolName === "web_fetch" && typeof input?.url === "string") {
|
||||
fetchedUrls.push(input.url);
|
||||
}
|
||||
jobStore.updateJob(jobId, { activity: activityLine(toolCall.toolName, input) });
|
||||
jobStore.updateJob(jobId, { activity: activityLine(toolName, input) });
|
||||
},
|
||||
});
|
||||
|
||||
const brief = result.text.trim();
|
||||
if (!brief) throw new Error("the researcher produced no text");
|
||||
const research: ResearchResult = { brief, sources: parseSources(brief, fetchedUrls) };
|
||||
if (!brief.trim()) throw new Error("the researcher produced no text");
|
||||
const research: ResearchResult = { brief: brief.trim(), sources: parseSources(brief.trim(), fetchedUrls) };
|
||||
await finishJob(jobId, research);
|
||||
} catch (err) {
|
||||
// Real-kill abort (2026-09): the abort path flipped the record and
|
||||
@@ -291,7 +290,7 @@ export function createJobRunner(deps: JobRunnerDeps): JobRunner {
|
||||
|
||||
async function runDemoJob(
|
||||
jobId: string,
|
||||
model: LanguageModel | undefined,
|
||||
model: PiEngine | undefined,
|
||||
passedInput: JobToolInput | undefined,
|
||||
loop: LoopContext,
|
||||
): Promise<void> {
|
||||
@@ -308,9 +307,9 @@ export function createJobRunner(deps: JobRunnerDeps): JobRunner {
|
||||
const result = await runDemoBuilder(
|
||||
{ title, brief },
|
||||
{
|
||||
model,
|
||||
engine: model,
|
||||
abortSignal: loop.abortSignal,
|
||||
onUsage: loop.onUsage,
|
||||
onUsage: (usage) => loop.onUsage(piUsageToStep(usage)),
|
||||
onActivity: (line) => jobStore.updateJob(jobId, { activity: line }),
|
||||
},
|
||||
);
|
||||
@@ -327,7 +326,7 @@ export function createJobRunner(deps: JobRunnerDeps): JobRunner {
|
||||
|
||||
async function runVisualJob(
|
||||
jobId: string,
|
||||
model: LanguageModel | undefined,
|
||||
model: PiEngine | undefined,
|
||||
passedInput: JobToolInput | undefined,
|
||||
loop: LoopContext,
|
||||
): Promise<void> {
|
||||
@@ -343,9 +342,9 @@ export function createJobRunner(deps: JobRunnerDeps): JobRunner {
|
||||
const result = await runVisualMaker(
|
||||
{ brief },
|
||||
{
|
||||
model,
|
||||
engine: model,
|
||||
abortSignal: loop.abortSignal,
|
||||
onUsage: loop.onUsage,
|
||||
onUsage: (usage) => loop.onUsage(piUsageToStep(usage)),
|
||||
onActivity: (line) => jobStore.updateJob(jobId, { activity: line }),
|
||||
},
|
||||
);
|
||||
|
||||
@@ -1,7 +1,8 @@
|
||||
import { generateText, tool, type LanguageModel, type ModelMessage, type ToolResultPart } from "ai";
|
||||
import type { AssistantMessage, Message, ToolResultMessage, Usage } from "@earendil-works/pi-ai";
|
||||
import { z } from "zod";
|
||||
import { modelFor } from "../models.ts";
|
||||
import type { UsageStepLike, VisualResult } from "../../core/contracts.ts";
|
||||
import { lhTool, piToolDeclarations, type LhTool } from "../lh-tool.ts";
|
||||
import { piEngineFor, thinkingLevelFor, type PiEngine } from "../models.ts";
|
||||
import type { VisualResult } from "../../core/contracts.ts";
|
||||
import { getHeadless, type HeadlessApi } from "./headless.ts";
|
||||
|
||||
/**
|
||||
@@ -31,7 +32,8 @@ export interface VisualMakerInput {
|
||||
}
|
||||
|
||||
export interface VisualMakerOptions {
|
||||
model?: LanguageModel;
|
||||
/** Test seam: scripted engine; production uses the visualMaker role. */
|
||||
engine?: PiEngine;
|
||||
headless?: HeadlessApi;
|
||||
/** Max model rounds (write/render cycles + final answer). Default 8. */
|
||||
maxIterations?: number;
|
||||
@@ -39,9 +41,9 @@ export interface VisualMakerOptions {
|
||||
onActivity?: (line: string) => void;
|
||||
/** Kills the run mid-model-call (2026-09 real-kill abort semantics). */
|
||||
abortSignal?: AbortSignal;
|
||||
/** Money channel: one call per loop iteration (generateText), folded
|
||||
/** Money channel: one call per loop iteration (streamSimple), folded
|
||||
* into JobRecord.usage. */
|
||||
onUsage?: (usage: UsageStepLike) => void;
|
||||
onUsage?: (usage: Usage) => void;
|
||||
}
|
||||
|
||||
const INSTRUCTIONS = `You are a visual maker — a diagram author + renderer for precise, spatial figures. You
|
||||
@@ -86,25 +88,28 @@ Your FINAL message: 1-2 sentences of notes for the teacher (what the figure show
|
||||
NEVER the SVG source itself. If you genuinely cannot make a correct picture of the brief, say exactly
|
||||
that in your final message and why.`;
|
||||
|
||||
export function createVisualTools() {
|
||||
export function createVisualTools(): Record<string, LhTool<any, any>> {
|
||||
return {
|
||||
write_svg: tool({
|
||||
write_svg: lhTool({
|
||||
name: "write_svg",
|
||||
description: "Write the complete SVG source for the figure (overwrites any previous version).",
|
||||
inputSchema: z.object({
|
||||
schema: z.object({
|
||||
svg: z.string().describe('Complete <svg xmlns="…">…</svg> markup.'),
|
||||
}),
|
||||
}),
|
||||
edit_svg: tool({
|
||||
edit_svg: lhTool({
|
||||
name: "edit_svg",
|
||||
description:
|
||||
"Replace one exact spot in the current SVG: old_text must appear EXACTLY ONCE and is replaced by new_text. Call write_svg first. For larger changes, write_svg the whole document.",
|
||||
inputSchema: z.object({
|
||||
schema: z.object({
|
||||
old_text: z.string().describe("The exact text to replace — must match exactly once in the current SVG."),
|
||||
new_text: z.string().describe("The replacement text."),
|
||||
}),
|
||||
}),
|
||||
}),
|
||||
render_svg: tool({
|
||||
render_svg: lhTool({
|
||||
name: "render_svg",
|
||||
description: "Render the current SVG to a PNG and show it to you for inspection. No arguments.",
|
||||
inputSchema: z.object({}),
|
||||
schema: z.object({}),
|
||||
}),
|
||||
};
|
||||
}
|
||||
@@ -125,6 +130,9 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
}
|
||||
|
||||
const tools = createVisualTools();
|
||||
const toolDeclarations = piToolDeclarations(tools);
|
||||
const engine = opts.engine ?? piEngineFor("visualMaker");
|
||||
const reasoning = thinkingLevelFor("visualMaker");
|
||||
const prompt = [
|
||||
"Brief for ONE precise figure (from the teacher, verbatim — it is everything you know):",
|
||||
brief,
|
||||
@@ -132,7 +140,7 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
"Author the SVG, render it, look at it, iterate until correct, then finish with your notes.",
|
||||
].join("\n");
|
||||
|
||||
let messages: ModelMessage[] = [{ role: "user", content: prompt }];
|
||||
let messages: Message[] = [{ role: "user", content: prompt, timestamp: Date.now() }];
|
||||
let currentSvg: string | null = null;
|
||||
/** The svg shown in the most recent render (null = never rendered). */
|
||||
let renderedSvg: string | null = null;
|
||||
@@ -140,20 +148,20 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
|
||||
try {
|
||||
for (let iteration = 0; iteration < maxIterations; iteration++) {
|
||||
const result = await generateText({
|
||||
model: opts.model ?? modelFor("visualMaker"),
|
||||
system: INSTRUCTIONS,
|
||||
messages,
|
||||
tools,
|
||||
abortSignal: opts.abortSignal,
|
||||
});
|
||||
// One model call per iteration (streamSimple, no agent loop — this
|
||||
// loop owns tool execution and the image-in-the-loop injection).
|
||||
const result = await streamOnce(engine, INSTRUCTIONS, messages, toolDeclarations, reasoning, opts.abortSignal);
|
||||
// Money channel: each iteration is one model call.
|
||||
opts.onUsage?.(result.usage);
|
||||
messages = [...messages, ...result.response.messages];
|
||||
messages = [...messages, result];
|
||||
|
||||
const toolCalls = result.toolCalls;
|
||||
const toolCalls = result.content.filter((c): c is Extract<typeof c, { type: "toolCall" }> => c.type === "toolCall");
|
||||
if (toolCalls.length === 0) {
|
||||
finalText = result.text.trim();
|
||||
finalText = result.content
|
||||
.filter((c): c is { type: "text"; text: string } => c.type === "text")
|
||||
.map((c) => c.text)
|
||||
.join("")
|
||||
.trim();
|
||||
// Doctrine gate: never deliver an unlooked SVG. If the current SVG
|
||||
// changed since its last render (or was never rendered), show it now
|
||||
// and make the model look before accepting the finish.
|
||||
@@ -169,41 +177,48 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
renderedSvg = currentSvg;
|
||||
messages = [
|
||||
...messages,
|
||||
{ role: "user", content: [{ type: "file", data: png, mediaType: "image/png" }, { type: "text", text: UNLOOKED_FINISH_MESSAGE }] },
|
||||
{
|
||||
role: "user",
|
||||
content: [
|
||||
{ type: "text", text: UNLOOKED_FINISH_MESSAGE },
|
||||
{ type: "image", data: png.toString("base64"), mimeType: "image/png" },
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
];
|
||||
continue;
|
||||
}
|
||||
return finish(currentSvg, finalText);
|
||||
}
|
||||
|
||||
const toolResults: ToolResultPart[] = [];
|
||||
const toolResults: ToolResultMessage[] = [];
|
||||
let renderPng: Buffer | null = null; // appended as the image message AFTER the tool results
|
||||
for (const call of toolCalls) {
|
||||
if (call.toolName === "write_svg") {
|
||||
const svg = (call.input as { svg?: unknown }).svg;
|
||||
if (call.name === "write_svg") {
|
||||
const svg = (call.arguments as { svg?: unknown }).svg;
|
||||
if (typeof svg !== "string" || !svg.includes("<svg")) {
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, "ERROR: expected a complete <svg>…</svg> document in the `svg` field."));
|
||||
toolResults.push(toolText(call.id, call.name, "ERROR: expected a complete <svg>…</svg> document in the `svg` field."));
|
||||
continue;
|
||||
}
|
||||
currentSvg = svg;
|
||||
opts.onActivity?.(`write_svg: ${(svg.length / 1024).toFixed(1)} KB`);
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, `Saved (${svg.length} bytes). Call render_svg to look at it.`));
|
||||
} else if (call.toolName === "edit_svg") {
|
||||
const edit = call.input as { old_text?: unknown; new_text?: unknown };
|
||||
toolResults.push(toolText(call.id, call.name, `Saved (${svg.length} bytes). Call render_svg to look at it.`));
|
||||
} else if (call.name === "edit_svg") {
|
||||
const edit = call.arguments as { old_text?: unknown; new_text?: unknown };
|
||||
if (!currentSvg) {
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, "ERROR: nothing to edit — call write_svg first."));
|
||||
toolResults.push(toolText(call.id, call.name, "ERROR: nothing to edit — call write_svg first."));
|
||||
continue;
|
||||
}
|
||||
if (typeof edit.old_text !== "string" || typeof edit.new_text !== "string" || !edit.old_text) {
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, "ERROR: expected old_text (non-empty) and new_text strings."));
|
||||
toolResults.push(toolText(call.id, call.name, "ERROR: expected old_text (non-empty) and new_text strings."));
|
||||
continue;
|
||||
}
|
||||
const occurrences = currentSvg.split(edit.old_text).length - 1;
|
||||
if (occurrences === 0) {
|
||||
toolResults.push(
|
||||
toolText(
|
||||
call.toolCallId,
|
||||
call.toolName,
|
||||
call.id,
|
||||
call.name,
|
||||
`ERROR: old_text not found. Closest line for reference:\n${snippetAround(currentSvg, edit.old_text)}`,
|
||||
),
|
||||
);
|
||||
@@ -211,16 +226,16 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
}
|
||||
if (occurrences > 1) {
|
||||
toolResults.push(
|
||||
toolText(call.toolCallId, call.toolName, `ERROR: old_text appears ${occurrences} times — it must match EXACTLY ONCE. Include more surrounding context to make it unique.`),
|
||||
toolText(call.id, call.name, `ERROR: old_text appears ${occurrences} times — it must match EXACTLY ONCE. Include more surrounding context to make it unique.`),
|
||||
);
|
||||
continue;
|
||||
}
|
||||
currentSvg = currentSvg.replace(edit.old_text, edit.new_text);
|
||||
opts.onActivity?.("edit_svg: applied");
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, "OK — replaced 1 occurrence. Call render_svg to look at the edited SVG."));
|
||||
} else if (call.toolName === "render_svg") {
|
||||
toolResults.push(toolText(call.id, call.name, "OK — replaced 1 occurrence. Call render_svg to look at the edited SVG."));
|
||||
} else if (call.name === "render_svg") {
|
||||
if (!currentSvg) {
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, "ERROR: nothing to render — call write_svg first."));
|
||||
toolResults.push(toolText(call.id, call.name, "ERROR: nothing to render — call write_svg first."));
|
||||
continue;
|
||||
}
|
||||
try {
|
||||
@@ -228,18 +243,18 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
renderPng = png;
|
||||
renderedSvg = currentSvg;
|
||||
opts.onActivity?.("render_svg: inspecting render");
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, "Rendered — the PNG follows in the next message. Look at it."));
|
||||
toolResults.push(toolText(call.id, call.name, "Rendered — the PNG follows in the next message. Look at it."));
|
||||
} catch (err) {
|
||||
const msg = err instanceof Error ? err.message : String(err);
|
||||
opts.onActivity?.("render_svg: render error");
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, `RENDER ERROR (the SVG may be malformed): ${msg}. Fix it with write_svg and render again.`));
|
||||
toolResults.push(toolText(call.id, call.name, `RENDER ERROR (the SVG may be malformed): ${msg}. Fix it with write_svg and render again.`));
|
||||
}
|
||||
} else {
|
||||
toolResults.push(toolText(call.toolCallId, call.toolName, `ERROR: unknown tool "${call.toolName}". Use write_svg, edit_svg, or render_svg.`));
|
||||
toolResults.push(toolText(call.id, call.name, `ERROR: unknown tool "${call.name}". Use write_svg, edit_svg, or render_svg.`));
|
||||
}
|
||||
}
|
||||
// Message order: assistant tool-calls → tool results → render image.
|
||||
messages = [...messages, { role: "tool", content: toolResults }];
|
||||
messages = [...messages, ...toolResults];
|
||||
if (renderPng) {
|
||||
messages = [
|
||||
...messages,
|
||||
@@ -247,8 +262,9 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
role: "user",
|
||||
content: [
|
||||
{ type: "text", text: LOOK_MESSAGE },
|
||||
{ type: "file", data: renderPng, mediaType: "image/png" },
|
||||
{ type: "image", data: renderPng.toString("base64"), mimeType: "image/png" },
|
||||
],
|
||||
timestamp: Date.now(),
|
||||
},
|
||||
];
|
||||
}
|
||||
@@ -265,8 +281,45 @@ export async function runVisualMaker(input: VisualMakerInput, opts: VisualMakerO
|
||||
return { svg: "", notes: `FAILED: iteration limit (${maxIterations}) reached without a verified SVG.` };
|
||||
}
|
||||
|
||||
function toolText(toolCallId: string, toolName: string, value: string): ToolResultPart {
|
||||
return { type: "tool-result", toolCallId, toolName, output: { type: "text", value } };
|
||||
function toolText(toolCallId: string, toolName: string, value: string): ToolResultMessage {
|
||||
return {
|
||||
role: "toolResult",
|
||||
toolCallId,
|
||||
toolName,
|
||||
content: [{ type: "text", text: value }],
|
||||
isError: value.startsWith("ERROR:") || value.startsWith("RENDER ERROR"),
|
||||
timestamp: Date.now(),
|
||||
};
|
||||
}
|
||||
|
||||
/** One raw model call (no agent loop): drain the event stream to the final
|
||||
* AssistantMessage; provider errors and aborts throw so the loop's catch
|
||||
* path keeps its old generateText semantics. */
|
||||
async function streamOnce(
|
||||
engine: PiEngine,
|
||||
systemPrompt: string,
|
||||
messages: Message[],
|
||||
tools: ReturnType<typeof piToolDeclarations>,
|
||||
reasoning: ReturnType<typeof thinkingLevelFor>,
|
||||
abortSignal?: AbortSignal,
|
||||
): Promise<AssistantMessage> {
|
||||
const stream = engine.streamFn(engine.model, { systemPrompt, messages, tools }, {
|
||||
reasoning: reasoning === "off" ? undefined : reasoning,
|
||||
apiKey: process.env.OPENROUTER_API_KEY || undefined,
|
||||
signal: abortSignal,
|
||||
} as never);
|
||||
for await (const event of stream) {
|
||||
if (event.type === "done") return event.message;
|
||||
if (event.type === "error") {
|
||||
if (event.reason === "aborted") {
|
||||
const err = new Error("aborted");
|
||||
err.name = "AbortError";
|
||||
throw err;
|
||||
}
|
||||
throw new Error(event.error.errorMessage ?? "the model call failed");
|
||||
}
|
||||
}
|
||||
throw new Error("the model stream ended without a result");
|
||||
}
|
||||
|
||||
/** A 3-line numbered context window around the closest fuzzy match for a
|
||||
|
||||
Reference in New Issue
Block a user