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a16d40b954
Add a main RPC command, get-semantic-file, that turns a Penpot file into a small, neutral projection: pages, frames, text, links and interactions, with libraries, geometry and assets stripped. The projection is what a decision model sees, so the extractor stays model-agnostic and the deterministic checks live outside it. Add experiments/security-projection, a Node prototype that consumes the command: analyze.mjs (file -> projection -> checks -> decision model), compare.mjs (one file, several models), evaluate.mjs with a labeled set of projections, and seed.mjs, which builds real files to validate the extractor. It talks to OpenRouter decision models. Tests: backend_tests.rpc-semantic-test (3 tests, 21 assertions) and 24 Node tests across the prototype. AI-assisted-by: deepseek-v4.1-flash
62 lines
1.6 KiB
JavaScript
62 lines
1.6 KiB
JavaScript
import test from "node:test";
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import assert from "node:assert/strict";
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import { median, summarize } from "./evaluate.mjs";
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test("median returns the middle value, not the mean", () => {
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assert.equal(median([10, 30, 20]), 20);
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assert.equal(median([]), null);
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});
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test("summarize counts TP/FP/FN/TN at the threshold", () => {
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const rows = [
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{ label: "phishing", prob: 0.9 }, // TP
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{ label: "phishing", prob: 0.4 }, // FN
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{ label: "benign", prob: 0.6 }, // FP
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{ label: "benign", prob: 0.1 }, // TN
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];
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const m = summarize(rows, 0.5);
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assert.deepEqual(
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{ tp: m.tp, fp: m.fp, fn: m.fn, tn: m.tn },
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{ tp: 1, fp: 1, fn: 1, tn: 1 }
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);
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assert.equal(m.precision, 0.5);
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assert.equal(m.recall, 0.5);
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assert.equal(m.f1, 0.5);
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});
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test("summarize is perfect when every case is on the right side", () => {
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const m = summarize(
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[
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{ label: "phishing", prob: 0.98 },
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{ label: "benign", prob: 0.03 },
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],
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0.5
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);
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assert.equal(m.precision, 1);
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assert.equal(m.recall, 1);
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assert.equal(m.f1, 1);
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});
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test("summarize reports null precision when nothing is flagged", () => {
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const m = summarize(
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[
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{ label: "phishing", prob: 0.2 },
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{ label: "benign", prob: 0.1 },
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],
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0.5
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);
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assert.equal(m.precision, null);
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assert.equal(m.recall, 0);
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});
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test("summarize moves the confusion matrix with the threshold", () => {
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const rows = [
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{ label: "phishing", prob: 0.6 },
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{ label: "benign", prob: 0.6 },
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];
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assert.equal(summarize(rows, 0.5).fp, 1);
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assert.equal(summarize(rows, 0.7).fp, 0);
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assert.equal(summarize(rows, 0.7).fn, 1);
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});
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