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https://github.com/Kaelio/ktx.git
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* feat(cli): define full warehouse dialect contract
* test(cli): keep dialect edge tests focused
* fix(cli): stabilize dialect contract foundation
* refactor(connectors): own read-only query preparation
* refactor(connectors): resolve dialects through registry
* refactor(connectors): keep concrete dialect classes internal
* chore(workspace): enforce dialect import boundary
* refactor(cli): resolve relationship dialect at scan boundary
* refactor(cli): use dialect display parsing for entity details
* refactor(cli): use dialect display parsing for warehouse catalog
* refactor(cli): use dialect SQL in relationship workflows
* test(cli): verify solid dialect scan workflow closure
* test: split cli tests from source tree
* refactor(cli): standardize BigQuery scope listing
* feat(sqlite): implement connector scope listing
* test(connectors): cover required table listing
* feat(cli): add warehouse driver registry
* refactor(setup): route scope discovery through driver registry
* refactor(cli): route local query execution through driver registry
* refactor(historic-sql): route dialect support through driver registry
* refactor(cli): test warehouse connections through driver registry
* fix(cli): close driver registry type export gaps
* Improve setup daemon diagnostics
* refactor(setup): centralize rail-prefixed diagnostics + query-history fallback
Extract errorMessage, writePrefixedLines, and flushPrefixedBufferedCommandOutput
into clack.ts so the setup wizard, managed daemons, and embedding/agent steps
share one rail-formatted writer. setup-databases.ts also adds a
"disable query history and retry" option when the schema-context build fails
and query history is the likely culprit, surfaced via a new
failed-query-history-unavailable status.
* fix(cli): carry catalog through the picker so BigQuery/Snowflake/SQL Server scope filters match
The setup picker's KtxTableListEntry was a 2-level { schema, name }, so
qualifiedTableId always wrote db.name into enabled_tables. When BigQuery,
Snowflake, or SQL Server later ran fast ingest, their introspect step filtered
the scope set with scopedTableNames(scope, { catalog: projectId|database, db })
— catalog was non-null on the introspect side but null in the scope refs, so
every entry was rejected, the live-database adapter staged zero table files,
and detect() failed with 'Adapter "live-database" did not recognize fetched
source output'.
Align the picker boundary with the canonical 3-level KtxTableRef:
- Add catalog: string | null to KtxTableListEntry.
- BigQuery/Snowflake/SQL Server listTables populate catalog from the
resolved projectId / database; Postgres/MySQL/ClickHouse/SQLite set null.
- qualifiedTableId emits catalog.schema.name when catalog is non-null
(resolveEnabledTables already accepts the 3-part shape) and
schemasFromEnabledTables now goes through parseDottedTableEntry so it
recovers the schema correctly from both 2-part and 3-part entries.
- Export parseDottedTableEntry from enabled-tables.ts (@internal) for picker
reuse.
Update listTables expectations in all seven connector tests and the setup /
picker test fixtures. Add a picker regression test that covers the
catalog-bearing round-trip (save + refine).
* fix(cli): allow debug telemetry under opt-out env
137 lines
5.2 KiB
TypeScript
137 lines
5.2 KiB
TypeScript
import type { MemoryFlowEvent, MemoryFlowReplayInput } from '../src/context/ingest/memory-flow/types.js';
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import { describe, expect, it } from 'vitest';
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import {
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buildDemoMetrics,
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formatCost,
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formatDuration,
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formatEta,
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formatTokens,
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formatTokensPerSec,
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progressBar,
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} from '../src/demo-metrics.js';
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function snapshot(events: MemoryFlowEvent[], overrides: Partial<MemoryFlowReplayInput> = {}): MemoryFlowReplayInput {
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return {
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runId: 'run-1',
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connectionId: 'orbit_demo',
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adapter: 'live-database',
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status: 'running',
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sourceDir: null,
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syncId: 'sync-1',
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errors: [],
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events,
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plannedWorkUnits: [],
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details: { actions: [], provenance: [], transcripts: [] },
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...overrides,
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};
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}
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describe('buildDemoMetrics', () => {
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it('estimates elapsed, agent steps, tool calls, and cost from event stream', () => {
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const start = Date.UTC(2026, 0, 1, 0, 0, 0);
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const input = snapshot(
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[
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{ type: 'source_acquired', adapter: 'live-database', trigger: 'demo_full', fileCount: 5, emittedAt: new Date(start).toISOString() },
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{ type: 'work_unit_started', unitKey: 'orders', skills: [], stepBudget: 40, emittedAt: new Date(start + 1000).toISOString() },
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{ type: 'work_unit_step', unitKey: 'orders', stepIndex: 6, stepBudget: 40, emittedAt: new Date(start + 6000).toISOString() },
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],
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{
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plannedWorkUnits: [
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{ unitKey: 'orders', rawFiles: [], peerFileCount: 0, dependencyCount: 0 },
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{ unitKey: 'customers', rawFiles: [], peerFileCount: 0, dependencyCount: 0 },
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],
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details: {
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actions: [],
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provenance: [],
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transcripts: [{ unitKey: 'orders', path: '/tmp/orders.jsonl', toolCallCount: 3, errorCount: 0, toolNames: ['x'] }],
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},
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},
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);
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const metrics = buildDemoMetrics(input, { now: () => start + 10_000 });
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expect(metrics.elapsedMs).toBe(10_000);
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expect(metrics.agentSteps).toBe(6);
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expect(metrics.agentStepBudget).toBe(40);
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expect(metrics.toolCalls).toBe(3);
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expect(metrics.workUnitsTotal).toBe(2);
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expect(metrics.estimatedTokens).toBeGreaterThan(0);
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expect(metrics.estimatedCostUsd).toBeGreaterThan(0);
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expect(metrics.isCostEstimated).toBe(true);
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});
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it('returns null ETA before the first work unit completes', () => {
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const input = snapshot([{ type: 'source_acquired', adapter: 'live-database', trigger: 'x', fileCount: 1 }]);
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const metrics = buildDemoMetrics(input, { now: () => Date.now() });
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expect(metrics.etaMs).toBeNull();
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});
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it('extrapolates ETA from completed/total ratio when at least one unit finishes', () => {
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const start = Date.UTC(2026, 0, 1);
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const input = snapshot(
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[
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{ type: 'source_acquired', adapter: 'a', trigger: 't', fileCount: 1, emittedAt: new Date(start).toISOString() },
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{ type: 'work_unit_started', unitKey: 'a', skills: [], stepBudget: 10, emittedAt: new Date(start + 1000).toISOString() },
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{ type: 'work_unit_finished', unitKey: 'a', status: 'success', emittedAt: new Date(start + 5000).toISOString() },
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],
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{
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plannedWorkUnits: [
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{ unitKey: 'a', rawFiles: [], peerFileCount: 0, dependencyCount: 0 },
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{ unitKey: 'b', rawFiles: [], peerFileCount: 0, dependencyCount: 0 },
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{ unitKey: 'c', rawFiles: [], peerFileCount: 0, dependencyCount: 0 },
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],
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},
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);
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const metrics = buildDemoMetrics(input, { now: () => start + 6_000 });
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expect(metrics.etaMs).toBe(12_000);
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});
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it('reports ETA=0 when the run is finished', () => {
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const input = snapshot([], { status: 'done' });
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const metrics = buildDemoMetrics(input, { now: () => Date.now() });
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expect(metrics.etaMs).toBe(0);
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});
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});
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describe('format helpers', () => {
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it('formats duration in s/m/h cascades', () => {
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expect(formatDuration(5_000)).toBe('5s');
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expect(formatDuration(95_000)).toBe('1m35s');
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expect(formatDuration(3_700_000)).toBe('1h01m');
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expect(formatDuration(-1)).toBe('--');
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});
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it('formats ETA as estimating before any data and as duration once running', () => {
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expect(formatEta(null, 'running')).toBe('estimating...');
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expect(formatEta(8_000, 'running')).toBe('8s');
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expect(formatEta(8_000, 'done')).toBe('done');
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});
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it('formats cost with sub-cent guard', () => {
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expect(formatCost(0)).toBe('$0.000');
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expect(formatCost(0.0005)).toBe('<$0.001');
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expect(formatCost(0.012)).toBe('$0.012');
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expect(formatCost(2.5)).toBe('$2.50');
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});
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it('formats token counts with K/M abbreviations', () => {
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expect(formatTokens(0)).toBe('0');
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expect(formatTokens(450)).toBe('450');
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expect(formatTokens(2_300)).toBe('2.3K');
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expect(formatTokens(1_500_000)).toBe('1.50M');
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});
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it('formats tokens per second', () => {
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expect(formatTokensPerSec(0)).toBe('0/s');
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expect(formatTokensPerSec(450)).toBe('450/s');
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expect(formatTokensPerSec(2300)).toBe('2.3K/s');
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});
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it('renders a deterministic progress bar with hash and dash characters', () => {
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expect(progressBar(0, 10)).toBe('----------');
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expect(progressBar(0.5, 10)).toBe('#####-----');
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expect(progressBar(1, 10)).toBe('##########');
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expect(progressBar(1.4, 10)).toBe('##########');
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});
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});
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