The graph becomes raw reasoning chains only. Quiz outcomes and understanding observations are no longer formalized; assessment moves to the future practice module. Events ledger removed end-to-end: LedgerEvent/LedgerEventKind/ UnderstandingLevel/ExtractionAttribution/AuditResult.dropped and snapshot nodeObservations deleted from contracts; quizEvent builder and the events step of mergeFindings gone; appendEvent/readEvents dropped from the port and store; LEDGER_FILES loses events.jsonl with a one-time purge of a stale file next to the nodes ledger; graph-deletion and the delete dialog lose event purge + quiz-answer impact counts; GraphSessionProposition becomes a pure birth list. Whole-session markdown source view: new core/session-markdown.ts is the shared formatting engine (id-anchored speaker blocks, quiz/ recall/question blocks, tool one-liners) — the extractor's prompt view and the future user-facing export render from one engine. Coverage fingerprints deliberately stay on the old line format (content-hash semantics; re-formatting never re-opens covered history). The whole session goes to the extractor — no phase cut. Auditor refocused as the identity linker: never sees the source; explores the graph via new auditor-specific tools in agent/tools/graph.ts (find — glob over name/statement/aliases; list_sessions; list_propositions with full statement text; no timestamps) instead of an injected full-graph dump; equivalence bias — paraphrases merge, only genuinely distinct propositions stay apart; no drop channel, the extractor is fully trusted; may draw bridging edges (typed follows/supports) between existing nodes and the batch, resolved by the merger with chat-scoped message-less provenance. Agentic loop, maxTurns 16. UI: the node detail card gains an edges section above the sessions list (follows-from / supported-by / what-follows / what-it-supports, rendered only when present, click-to-select neighbors); the understanding-note chips are gone. Prober list_propositions reworded to what a session covered — names only, no levels. docs/architecture.md + README updated to the as-built pipeline. Gates: typecheck, 1059/1059, lint, build.
307 lines
12 KiB
TypeScript
307 lines
12 KiB
TypeScript
/**
|
|
* Usage-accounting tests — the money channel's pure helpers (core/prices.ts)
|
|
* and the ChatStore usage-log seam (appendTurnUsage).
|
|
*
|
|
* Pure helper tests are pure. The store test uses the real fs chatStore with
|
|
* a fixture chat, cleaned up in after().
|
|
*/
|
|
import assert from "node:assert/strict";
|
|
import test from "node:test";
|
|
import * as fs from "node:fs";
|
|
|
|
import { chatStore } from "../src/store/chats.ts";
|
|
import { graphStore } from "../src/store/graph.ts";
|
|
import { PATHS, SOURCES_FILE } from "../config.ts";
|
|
import { callCost, contextWindow, jobCost, sessionCost, sumSteps, turnCost } from "../src/core/prices.ts";
|
|
import type { CallUsage, ExtractionRunUsage, JobRecord, TurnUsage } from "../src/core/contracts.ts";
|
|
|
|
const call = (over: Partial<CallUsage> = {}): CallUsage => ({
|
|
inputTokens: 0,
|
|
outputTokens: 0,
|
|
cacheReadTokens: undefined,
|
|
cacheWriteTokens: undefined,
|
|
reasoningTokens: undefined,
|
|
...over,
|
|
});
|
|
|
|
test("sumSteps folds steps; absent stays absent until a value appears", () => {
|
|
const sum = sumSteps([
|
|
call({ inputTokens: 100, outputTokens: 20 }),
|
|
call({ inputTokens: 50, outputTokens: 10, cacheReadTokens: 30 }),
|
|
]);
|
|
assert.equal(sum.inputTokens, 150);
|
|
assert.equal(sum.outputTokens, 30);
|
|
assert.equal(sum.cacheReadTokens, 30);
|
|
assert.equal(sum.cacheWriteTokens, undefined); // never reported → stays undefined
|
|
// all-absent → all-undefined (helper defaults input/output to 0, so
|
|
// explicit undefined here)
|
|
const empty = sumSteps([call({ inputTokens: undefined, outputTokens: undefined }), call({ inputTokens: undefined, outputTokens: undefined })]);
|
|
assert.equal(empty.inputTokens, undefined);
|
|
});
|
|
|
|
test("callCost: glm-5.3-flash math — fresh input, cached read, output", () => {
|
|
const cost = callCost(call({ inputTokens: 100_000, outputTokens: 20_000, cacheReadTokens: 10_000 }), "openrouter:z-ai/glm-5.3-flash");
|
|
assert.ok(cost !== null);
|
|
// fresh 90k @ $0.075/M + cached 10k @ $0.015/M + output 20k @ $0.25/M
|
|
// (pi-ai catalog prices — regenerated tables, scripts/sync-pricing)
|
|
assert.ok(Math.abs(cost! - (0.00675 + 0.00015 + 0.005)) < 1e-9);
|
|
});
|
|
|
|
test("callCost: cache writes bill at the cacheWrite rate", () => {
|
|
const cost = callCost(
|
|
call({ inputTokens: 1_000_000, outputTokens: 0, cacheWriteTokens: 500_000 }),
|
|
"openrouter:qwen/qwen3.8-max-0902",
|
|
);
|
|
assert.ok(cost !== null);
|
|
// fresh 1M @ $2/M + cache write 500k @ $2.5/M
|
|
assert.ok(Math.abs(cost! - (2 + 1.25)) < 1e-9);
|
|
});
|
|
|
|
test("callCost: unknown model and absent fields are null, never zero", () => {
|
|
assert.equal(callCost(call({ inputTokens: 100, outputTokens: 5 }), "not/a-model"), null);
|
|
assert.equal(callCost(call({ inputTokens: 100, outputTokens: undefined }), "openrouter:z-ai/glm-5.3-flash"), null);
|
|
});
|
|
|
|
test("turnCost sums steps; sessionCost reports unpriced turns", () => {
|
|
const turn: TurnUsage = {
|
|
id: "t1",
|
|
messageId: "m1",
|
|
at: "2026-09-09T00:00:00Z",
|
|
model: "openrouter:z-ai/glm-5.3-flash",
|
|
steps: [call({ inputTokens: 10_000, outputTokens: 2_000 }), call({ inputTokens: 12_000, outputTokens: 1_000 })],
|
|
};
|
|
assert.ok(turnCost(turn) !== null);
|
|
const totals = sessionCost({
|
|
turns: [turn, { id: "t2", messageId: "m2", at: "x", model: "not/a-model", steps: [call({ inputTokens: 1, outputTokens: 1 })] }],
|
|
});
|
|
assert.equal(totals.unpriced, 1);
|
|
assert.ok(totals.cost > 0);
|
|
});
|
|
|
|
test("contextWindow: last call's footprint against the live index's limit", () => {
|
|
const limits = new Map([["openrouter:z-ai/glm-5.3-flash", 1_048_576]]);
|
|
const cw = contextWindow(
|
|
{
|
|
turns: [
|
|
{ id: "t1", messageId: "m1", at: "x", model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 9_000, outputTokens: 1_000 })] },
|
|
{ id: "t2", messageId: "m2", at: "x", model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 90_000, outputTokens: 10_000 })] },
|
|
],
|
|
},
|
|
limits,
|
|
);
|
|
assert.ok(cw);
|
|
assert.equal(cw.model, "openrouter:z-ai/glm-5.3-flash");
|
|
assert.equal(cw.usedTokens, 100_000);
|
|
assert.equal(cw.limit, 1_048_576);
|
|
assert.equal(contextWindow({ turns: [] }, limits), null);
|
|
});
|
|
|
|
test("contextWindow NUMERATOR: cache tokens count (owner audit, 2026-09-23)", () => {
|
|
// The audit's live case: a cache-heavy session read 40k on the meter
|
|
// while the real footprint was ~190k — provider `input` EXCLUDES the
|
|
// cached portion, so input+output alone is wildly low. The fold is
|
|
// pi's totalTokens semantics: all four fields.
|
|
const limits = new Map([["openrouter:z-ai/glm-5.3-flash", 1_048_576]]);
|
|
const cw = contextWindow(
|
|
{
|
|
turns: [
|
|
{
|
|
id: "t1",
|
|
messageId: "m1",
|
|
at: "x",
|
|
model: "openrouter:z-ai/glm-5.3-flash",
|
|
steps: [call({ inputTokens: 40_000, outputTokens: 1_000, cacheReadTokens: 145_000, cacheWriteTokens: 4_000 })],
|
|
},
|
|
],
|
|
},
|
|
limits,
|
|
);
|
|
assert.ok(cw);
|
|
assert.equal(cw.usedTokens, 40_000 + 1_000 + 145_000 + 4_000, "input + output + cacheRead + cacheWrite");
|
|
// Cache fields absent (non-caching providers): the fold is unchanged.
|
|
const plain = contextWindow(
|
|
{ turns: [{ id: "t1", messageId: "m1", at: "x", model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 9_000, outputTokens: 1_000 })] }] },
|
|
limits,
|
|
);
|
|
assert.ok(plain);
|
|
assert.equal(plain.usedTokens, 10_000);
|
|
});
|
|
|
|
test("contextWindow DENOMINATOR: the live index is the ONLY source — no fallback (owner amendment, 2026-09-23)", () => {
|
|
const turns = [
|
|
{ id: "t1", messageId: "m1", at: "x", model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 10_000, outputTokens: 1_000 })] },
|
|
];
|
|
const live = new Map([["openrouter:z-ai/glm-5.3-flash", 65_536]]);
|
|
const cw = contextWindow({ turns }, live);
|
|
assert.ok(cw);
|
|
assert.equal(cw.limit, 65_536, "pi's catalog, via the index, is the one source");
|
|
// No index at all (a client that hasn't fetched the catalog): the
|
|
// meter renders usage-only — limit null, never a guessed window.
|
|
const noIndex = contextWindow({ turns });
|
|
assert.ok(noIndex);
|
|
assert.equal(noIndex.usedTokens, 11_000);
|
|
assert.equal(noIndex.limit, null);
|
|
const emptyIndex = contextWindow({ turns }, new Map<string, number>());
|
|
assert.ok(emptyIndex);
|
|
assert.equal(emptyIndex.limit, null, "an empty index (failed fetch) is usage-only too");
|
|
// A model missing from the live catalog (historical session, package
|
|
// update removed it): usage-only, never a fake window.
|
|
const missing = contextWindow({ turns: [{ ...turns[0]!, model: "nope/gone-model" }] }, live);
|
|
assert.ok(missing);
|
|
assert.equal(missing.limit, null);
|
|
assert.equal(missing.usedTokens, 11_000, "the footprint still reads honestly");
|
|
});
|
|
|
|
test("contextWindow ride-along: a zeroed/aborted last step falls back to the previous step", () => {
|
|
// An aborted last call reports zeroed usage — that is not the session
|
|
// footprint. The honest reading is the previous step's usage.
|
|
const limits = new Map([["openrouter:z-ai/glm-5.3-flash", 1_048_576]]);
|
|
const cw = contextWindow(
|
|
{
|
|
turns: [
|
|
{
|
|
id: "t1",
|
|
messageId: "m1",
|
|
at: "x",
|
|
model: "openrouter:z-ai/glm-5.3-flash",
|
|
steps: [
|
|
call({ inputTokens: 80_000, outputTokens: 5_000 }),
|
|
call({ inputTokens: 0, outputTokens: 0 }), // aborted — zeroed
|
|
],
|
|
},
|
|
],
|
|
},
|
|
limits,
|
|
);
|
|
assert.ok(cw);
|
|
assert.equal(cw.usedTokens, 85_000, "the previous step's footprint, not a bogus tiny meter");
|
|
// ALL steps zeroed (a first-call abort): no reading at all — null.
|
|
assert.equal(
|
|
contextWindow(
|
|
{ turns: [{ id: "t1", messageId: "m1", at: "x", model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 0, outputTokens: 0 })] }] },
|
|
limits,
|
|
),
|
|
null,
|
|
);
|
|
});
|
|
|
|
test("jobCost: null without usage, computed with it", () => {
|
|
assert.equal(jobCost({}), null);
|
|
const job: Pick<JobRecord, "usage"> = {
|
|
usage: {
|
|
model: "openrouter:z-ai/glm-5.3-flash",
|
|
inputTokens: 1_000_000,
|
|
outputTokens: 100_000,
|
|
cacheReadTokens: 0,
|
|
cacheWriteTokens: 0,
|
|
reasoningTokens: 0,
|
|
steps: 4,
|
|
},
|
|
};
|
|
assert.ok(jobCost(job) !== null);
|
|
assert.ok(jobCost(job)! > 0);
|
|
});
|
|
|
|
// ─── the store seam ──────────────────────────────────────────────────────────
|
|
|
|
test("appendTurnUsage: appends, idempotent per turn id, continuation turns (same message) all kept, survives saveMessages", () => {
|
|
const record = chatStore.createChat("usage test chat");
|
|
const entry: TurnUsage = {
|
|
id: "turn_1",
|
|
messageId: "msg_a",
|
|
at: "2026-09-09T00:00:00Z",
|
|
model: "openrouter:z-ai/glm-5.3-flash",
|
|
steps: [call({ inputTokens: 100, outputTokens: 10 })],
|
|
};
|
|
chatStore.appendTurnUsage(record.id, entry);
|
|
chatStore.appendTurnUsage(record.id, entry); // replay (abort/retry) → no-op
|
|
// continuation turn: SAME response message (SDK coalesces), new turn id —
|
|
// usage must survive, not collapse into the first entry
|
|
chatStore.appendTurnUsage(record.id, { ...entry, id: "turn_2" });
|
|
let reread = chatStore.getChat(record.id);
|
|
assert.equal(reread?.turns?.length, 2);
|
|
|
|
// saveMessages must not clobber the log (read-mutate-write record) —
|
|
// Wave B: a NATIVE message list (the record holds agent history).
|
|
chatStore.saveMessages(record.id, [
|
|
{ id: "msg_a", role: "user", content: "native", timestamp: Date.now() } as never,
|
|
]);
|
|
reread = chatStore.getChat(record.id);
|
|
assert.equal(reread?.turns?.length, 2);
|
|
|
|
// and the list payload must NOT leak turns
|
|
const listed = chatStore.listChats().find((c) => c.id === record.id);
|
|
assert.ok(listed);
|
|
assert.equal("turns" in listed, false);
|
|
|
|
fs.unlinkSync(`${PATHS.chats}/${record.id}.json`);
|
|
});
|
|
|
|
test("appendExtractionUsage: appends, idempotent per startedAt, not in list payload", () => {
|
|
const record = chatStore.createChat("extraction usage test chat");
|
|
const runEntry = (startedAt: number): ExtractionRunUsage => ({
|
|
startedAt,
|
|
at: "2026-09-09T00:00:00Z",
|
|
durationMs: 42_000,
|
|
stats: { nodes: 1, edges: 2 },
|
|
stages: {
|
|
extractor: { model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 100, outputTokens: 10 })] },
|
|
auditor: { model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 50, outputTokens: 5 })] },
|
|
},
|
|
});
|
|
chatStore.appendExtractionUsage(record.id, runEntry(1));
|
|
chatStore.appendExtractionUsage(record.id, runEntry(1)); // same run appended twice → no-op
|
|
chatStore.appendExtractionUsage(record.id, runEntry(2)); // a retried run is a NEW spend
|
|
let reread = chatStore.getChat(record.id);
|
|
assert.equal(reread?.extractions?.length, 2);
|
|
// failed runs (stats absent) persist with usage — money was spent
|
|
chatStore.appendExtractionUsage(record.id, { ...runEntry(3), stats: undefined });
|
|
reread = chatStore.getChat(record.id);
|
|
assert.equal(reread?.extractions?.length, 3);
|
|
assert.equal(reread?.extractions?.at(-1)?.stats, undefined);
|
|
|
|
// the list payload must NOT leak the extractions log
|
|
const listed = chatStore.listChats().find((c) => c.id === record.id);
|
|
assert.ok(listed);
|
|
assert.equal("extractions" in listed, false);
|
|
|
|
fs.unlinkSync(`${PATHS.chats}/${record.id}.json`);
|
|
});
|
|
|
|
test("appendSourceUsage: appends to the source record, idempotent per startedAt, upsert keeps history", () => {
|
|
// The real fs graphStore — sources.json backed up and restored around
|
|
// this test (same discipline as the chat fixture files).
|
|
fs.mkdirSync(PATHS.graph, { recursive: true });
|
|
let bak: string | undefined;
|
|
if (fs.existsSync(SOURCES_FILE)) bak = `${SOURCES_FILE}.w5test.bak`;
|
|
if (bak) fs.renameSync(SOURCES_FILE, bak);
|
|
try {
|
|
const runEntry = (startedAt: number): ExtractionRunUsage => ({
|
|
startedAt,
|
|
at: "2026-09-13T00:00:00Z",
|
|
durationMs: 42_000,
|
|
stats: { nodes: 1, edges: 2 },
|
|
stages: {
|
|
extractor: { model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 100, outputTokens: 10 })] },
|
|
auditor: { model: "openrouter:z-ai/glm-5.3-flash", steps: [call({ inputTokens: 50, outputTokens: 5 })] },
|
|
},
|
|
});
|
|
const id = "src_usagetest01";
|
|
graphStore.upsertSource({ id, filePath: "/vault/usagetest.md", importedAt: "2026-09-13T00:00:00Z" });
|
|
graphStore.appendSourceUsage(id, runEntry(1));
|
|
graphStore.appendSourceUsage(id, runEntry(1)); // same run appended twice → no-op
|
|
graphStore.appendSourceUsage(id, runEntry(2)); // a retried run is a NEW spend
|
|
assert.equal(graphStore.readSources().find((s) => s.id === id)?.extractions?.length, 2);
|
|
|
|
// An upsert (re-import) KEEPS the usage history.
|
|
graphStore.upsertSource({ id, filePath: "/vault/usagetest.md", importedAt: "2026-09-14T00:00:00Z" });
|
|
assert.equal(graphStore.readSources().find((s) => s.id === id)?.extractions?.length, 2);
|
|
|
|
// Unknown ids are a silent no-op (nothing to bill against).
|
|
graphStore.appendSourceUsage("src_nope", runEntry(1));
|
|
} finally {
|
|
fs.rmSync(SOURCES_FILE, { force: true });
|
|
if (bak) fs.renameSync(bak, SOURCES_FILE);
|
|
}
|
|
});
|