Replace the @huggingface/transformers local embedder (~316MB ONNX cache) with an EmbeddingPort seam: graph.embeddingModel (nullable "provider:id" slug) selects an OpenRouter/OpenAI/Gemini adapter, resolved fresh per call from settings + the auth store so key rotations land immediately. - src/server/embeddings.ts rewritten: slug grammar, injected-fetch adapters (OpenRouter input_type, Gemini taskType batching, OpenAI index-ordered rows), honest resolution (null = skip-with-info, set model with missing key = honest error), embedNewNodes with model-change re-embed wipe + ghost pruning + usage steps, federated catalog (OpenRouter /api/v1/embeddings/models — VERIFIED live, the inverse path 404s; OpenAI text-embedding- filter; Gemini embedContent filter). - GET /api/models/embeddings: federated catalog, empty when no keys. - Extraction tail records stages.embedding usage into the run's money channel; EMBEDDING_PRICES overlay in core/prices.ts (outside the sync-generated block), callCost falls back to it; cost-summary folds the fourth stage; graph-context injection resolves its embedder per run, fails honestly when unconfigured, records query tokens. - Settings: GraphSettings.embeddingModel (null factory), section parser validates slug shape (id may contain colons — OpenRouter :free suffixes, live catalog fact). - Removal: @huggingface/transformers uninstalled, PATHS.modelCache and onnx tracing entries deleted, @huggingface tracing-excludes guard added, stale sharp/libvips comments updated to historical. Live-verified on port 3004: catalog federates 36 rows (33 OpenRouter + 3 OpenAI), embedNewNodes embedded 10 nodes via the free liquid/lfm-2.5 model (dim 1024, 435 prompt tokens, 1 call, $0), settings PUT rejects bad slugs with 400. Gates: typecheck, lint, 895/895 tests, build.
160 lines
6.7 KiB
TypeScript
160 lines
6.7 KiB
TypeScript
/**
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* Tests for src/core/cost-summary.ts — the graph cost pill's pure fold.
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* Same laws as the money channel everywhere: dollars INFERRED at read
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* time (core/prices.ts), unpriced models excluded-but-counted (render
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* "—", never a silent zero), tokens always sum.
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*/
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import assert from "node:assert/strict";
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import { describe, it as test } from "node:test";
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import {
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graphCostSummary,
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type CostSummaryInput,
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type GraphCostSummary,
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} from "../src/core/cost-summary.ts";
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import type { CallUsage, ExtractionRunUsage, NamingRunUsage } from "../src/core/contracts.ts";
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import { PRICES, callCost } from "../src/core/prices.ts";
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/** A model with full published pricing (from the generated registry). */
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const PRICED = "openrouter:z-ai/glm-5.3-flash";
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assert.ok(PRICES[PRICED], "fixture model must exist in PRICES");
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const step = (input: number, output: number): CallUsage => ({
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inputTokens: input,
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outputTokens: output,
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cacheReadTokens: 0,
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cacheWriteTokens: undefined,
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reasoningTokens: 0,
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});
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const extractionRun = (
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startedAt: number,
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extractorModel: string,
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auditorModel: string,
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stats?: ExtractionRunUsage["stats"],
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): ExtractionRunUsage => ({
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startedAt,
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at: new Date(startedAt).toISOString(),
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durationMs: 10_000,
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stages: {
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extractor: { model: extractorModel, steps: [step(1000, 200)] },
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auditor: { model: auditorModel, steps: [step(2000, 100)] },
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},
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...(stats ? { stats } : {}),
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});
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const namingRun = (startedAt: number, model: string, appended: number): NamingRunUsage => ({
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startedAt,
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at: new Date(startedAt).toISOString(),
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durationMs: 4_000,
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model,
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steps: [step(500, 50)],
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stats: { detected: 8, claimed: 6, named: 2, appended },
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});
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describe("graphCostSummary (the cost pill's fold)", () => {
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test("folds all three channels: stage totals, tokens, newest-first runs", () => {
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const input: CostSummaryInput = {
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chats: [{ title: "Testing session", extractions: [extractionRun(100, PRICED, PRICED)] }],
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sources: [{ filePath: "/vault/modal.md", extractions: [extractionRun(200, PRICED, PRICED)] }],
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naming: [namingRun(300, PRICED, 2)],
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};
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const s = graphCostSummary(input);
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const extStep = callCost(step(1000, 200), PRICED)!;
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const audStep = callCost(step(2000, 100), PRICED)!;
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assert.equal(s.stages.extraction.dollars, extStep * 2);
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assert.equal(s.stages.audit.dollars, audStep * 2);
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assert.equal(s.stages.naming.dollars, callCost(step(500, 50), PRICED));
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assert.equal(s.stages.extraction.runs, 2);
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assert.equal(s.stages.naming.runs, 1);
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assert.equal(s.stages.extraction.tokens.inputTokens, 2000);
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assert.equal(s.stages.audit.tokens.outputTokens, 200);
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assert.equal(s.totalDollars, extStep * 2 + audStep * 2 + callCost(step(500, 50), PRICED)!);
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// All three runs, newest first, titles joined per front door.
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assert.deepEqual(
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s.runs.map((r) => r.title),
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["Cluster naming", "/vault/modal.md", "Testing session"],
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);
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assert.equal(s.runs[0]!.labels, 2);
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assert.equal(s.runs[0]!.kind, "naming");
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assert.equal(s.unpricedRuns, 0);
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});
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test("unpriced models: excluded dollars, counted honestly, run null only when BOTH stages unpriced", () => {
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const s: GraphCostSummary = graphCostSummary({
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chats: [{ title: "partial", extractions: [extractionRun(100, PRICED, "unknown-model")] }],
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sources: [{ filePath: "/vault/x.md", extractions: [extractionRun(200, "unknown-model", "unknown-model")] }],
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naming: [],
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});
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assert.equal(s.stages.audit.unpricedRuns, 2);
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assert.equal(s.stages.audit.dollars, 0); // never a silent zero: unpricedRuns says it
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assert.equal(s.stages.extraction.unpricedRuns, 1);
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// The partial run still prices its extractor side; the fully
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// unpriced run renders "—". Newest first: 200 (both unpriced), 100.
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assert.equal(s.runs[0]!.dollars, null);
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assert.notEqual(s.runs[1]!.dollars, null);
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assert.equal(s.unpricedRuns, 1); // run-level: only the both-stages run
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});
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test("the embedding stage (wave 6): folds when present, absent when the run embedded nothing", () => {
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const EMBED_MODEL = "openai:text-embedding-3-small";
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const embStep = callCost(step(5000, 0), EMBED_MODEL)!;
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assert.ok(embStep > 0, "the overlay prices the known embedding models");
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const withEmbed = extractionRun(100, PRICED, PRICED);
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withEmbed.stages.embedding = { model: EMBED_MODEL, steps: [step(5000, 0)] };
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const s = graphCostSummary({
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chats: [{ title: "a", extractions: [withEmbed] }, { title: "b", extractions: [extractionRun(200, PRICED, PRICED)] }],
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sources: [],
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naming: [],
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});
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assert.equal(s.stages.embedding.runs, 1, "only the run that embedded");
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assert.equal(s.stages.embedding.dollars, embStep);
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assert.equal(s.stages.embedding.tokens.inputTokens, 5000);
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assert.equal(s.stages.extraction.runs, 2, "the two-stage era still folds");
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assert.equal(s.stages.extraction.runs, 2);
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// Run-level: the embedding dollars ride the run's total.
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const extStep = callCost(step(1000, 200), PRICED)!;
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const audStep = callCost(step(2000, 100), PRICED)!;
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assert.equal(s.runs.find((r) => r.startedAt === 100)!.dollars, extStep + audStep + embStep);
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assert.equal(s.runs.find((r) => r.startedAt === 200)!.dollars, extStep + audStep);
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assert.equal(s.totalDollars, (extStep + audStep) * 2 + embStep);
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});
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test("an UNPRICED embedding model stays honest: counted, never a silent zero; a priced sibling saves the run total", () => {
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const unpricedEmbed = extractionRun(100, PRICED, "unknown-model");
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unpricedEmbed.stages.embedding = { model: "some/new-embed", steps: [step(900, 0)] };
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const s = graphCostSummary({ chats: [{ title: "x", extractions: [unpricedEmbed] }], sources: [], naming: [] });
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assert.equal(s.stages.embedding.unpricedRuns, 1);
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assert.equal(s.stages.embedding.dollars, 0);
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assert.notEqual(s.runs[0]!.dollars, null, "the priced extractor saves the run total");
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});
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test("recent runs cap: newest survive", () => {
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const extractions = [1, 2, 3, 4].map((n) => extractionRun(n * 100, PRICED, PRICED));
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const s = graphCostSummary({
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chats: [{ title: "chat", extractions }],
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sources: [],
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naming: [],
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recentCap: 2,
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});
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assert.equal(s.runs.length, 2);
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assert.deepEqual(s.runs.map((r) => r.startedAt), [400, 300]);
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// stage totals still count EVERY run, cap is presentational.
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assert.equal(s.stages.extraction.runs, 4);
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});
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test("failed runs carry no merged stats; empty input folds to zero", () => {
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const s = graphCostSummary({
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chats: [{ title: "failed", extractions: [extractionRun(100, PRICED, PRICED)] }],
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sources: [],
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naming: [],
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});
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assert.equal(s.runs[0]!.merged, undefined);
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const empty = graphCostSummary({ chats: [], sources: [], naming: [] });
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assert.equal(empty.totalDollars, 0);
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assert.equal(empty.runs.length, 0);
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assert.equal(empty.stages.naming.runs, 0);
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assert.equal(empty.stages.extraction.tokens.inputTokens, undefined);
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});
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});
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