File size: 2,831 Bytes
fc93158 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | import { describe, expect, it } from "vitest";
import type { SkynetCausalEpisode } from "../causal-valence/episode-ledger.js";
import {
buildSkynetRuntimeTrajectorySamples,
encodeSkynetRuntimeTrajectoryFeatures,
} from "./trajectory-builder.js";
import {
predictSkynetRuntimeObserverLabel,
trainSkynetRuntimeObserverModel,
} from "./trajectory-learner.js";
function buildEpisode(
index: number,
sessionKey: string,
bootstrapLabel: SkynetCausalEpisode["bootstrapLabel"],
kind: "noop" | "edit" | "delete",
): SkynetCausalEpisode {
const success = bootstrapLabel !== "damage";
return {
id: `${sessionKey}-${index}`,
sessionKey,
recordedAt: index,
context: {
continuityFreshness: bootstrapLabel === "stall" ? "aging" : "fresh",
failureStreak: bootstrapLabel === "damage" ? 2 : bootstrapLabel === "relief" ? 1 : 0,
targetCount: 1,
validationIntensity: kind === "noop" ? 0.2 : 0.9,
},
transition: {
targetPaths: ["src/app.ts"],
operations: [{ path: "src/app.ts", kind, isTarget: true }],
},
outcome: {
status: success ? "ok" : "error",
failureDomain: success ? "none" : "cognitive",
failureClass: success ? "none" : "validation_error",
targetSatisfied: bootstrapLabel === "progress" || bootstrapLabel === "relief",
validationPassed: success,
continuityDelta: bootstrapLabel === "progress" || bootstrapLabel === "relief" ? 0.7 : 0.05,
recoveryBurden: bootstrapLabel === "damage" ? 0.8 : 0.1,
collateralDamage: bootstrapLabel === "damage" ? 0.5 : 0,
},
bootstrapLabel,
};
}
describe("skynet runtime trajectory learner", () => {
it("encodes non-empty history-aware vectors", () => {
const samples = buildSkynetRuntimeTrajectorySamples({
episodes: [buildEpisode(1, "s", "stall", "noop"), buildEpisode(2, "s", "progress", "edit")],
});
expect(encodeSkynetRuntimeTrajectoryFeatures(samples[0]!).length).toBeGreaterThan(10);
});
it("predicts labels from a separable synthetic sequence dataset", () => {
const samples = buildSkynetRuntimeTrajectorySamples({
episodes: [
buildEpisode(1, "a", "stall", "noop"),
buildEpisode(2, "a", "progress", "edit"),
buildEpisode(3, "a", "stall", "noop"),
buildEpisode(4, "a", "progress", "edit"),
buildEpisode(10, "b", "damage", "delete"),
buildEpisode(11, "b", "stall", "noop"),
buildEpisode(12, "b", "damage", "delete"),
buildEpisode(13, "b", "stall", "noop"),
],
});
const model = trainSkynetRuntimeObserverModel(samples)!;
const prediction = predictSkynetRuntimeObserverLabel(model, samples[0]!);
expect(model.labels.length).toBeGreaterThanOrEqual(2);
expect(["progress", "stall", "damage"]).toContain(prediction.label);
});
});
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