ktx/packages/cli/test/context/sl/tools/sl-validate.tool.test.ts

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import { describe, expect, it, vi } from 'vitest';
test: split cli tests from source tree (#216) * 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
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import type { ToolSession } from '../../../../src/context/tools/tool-session.js';
import { createTouchedSlSources } from '../../../../src/context/tools/touched-sl-sources.js';
import type { ToolContext } from '../../../../src/context/tools/base-tool.js';
import type { SemanticLayerService } from '../../../../src/context/sl/semantic-layer.service.js';
import type { SemanticLayerSource } from '../../../../src/context/sl/types.js';
import { SlValidateTool, validateSemanticLayerEndpoint } from '../../../../src/context/sl/tools/sl-validate.tool.js';
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describe('validateSemanticLayerEndpoint', () => {
it('uses the connection warehouse dialect, not hardcoded postgres', async () => {
const serviceMock = {
validateSourcesForConnection: vi.fn().mockResolvedValue({ errors: [], warnings: [] }),
};
await validateSemanticLayerEndpoint('conn-1', serviceMock as unknown as SemanticLayerService);
expect(serviceMock.validateSourcesForConnection).toHaveBeenCalledWith('conn-1');
});
it('short-circuits when there are no validatable sources', async () => {
const serviceMock = {
validateSourcesForConnection: vi.fn().mockResolvedValue({ errors: [], warnings: [] }),
};
const result = await validateSemanticLayerEndpoint('conn-1', serviceMock as unknown as SemanticLayerService);
expect(result).toEqual({ errors: [], warnings: [] });
});
});
describe('SlValidateTool — session-aware touched-set filtering', () => {
it('when session present, only returns errors/warnings that mention touched sources', async () => {
const sources: SemanticLayerSource[] = [
{ name: 'orders', table: 'x.orders', grain: ['id'], columns: [], joins: [], measures: [] },
{ name: 'customers', table: 'x.customers', grain: ['id'], columns: [], joins: [], measures: [] },
];
const serviceMock = {
fix(context): merge overlay columns onto manifest columns by name (#94) * fix(context): merge overlay columns onto manifest columns by name composeOverlay was appending overlay columns to the manifest column list, producing duplicate entries when dbt/metabase overlays declared a column just to attach descriptions. The duplicates carried no `type`, so the pydantic SourceDefinition rejected them at semantic-query time and broke `ktx sl query` for every overlay-backed measure. Now overlay columns match base columns by name (case-insensitive): same-name entries merge onto the manifest (overlay fields win, type/role fall back to the base, descriptions merge per source key) and only new names append. * refactor(sl): split overlay columns from column_overrides and enforce TS/Python wire contract Overlay sources now have two distinct collections: `columns:` for computed columns (requiring `expr` + `type`) and `column_overrides:` for metadata patches to inherited manifest columns. Composing or loading an overlay that mixes the two — or references an unknown column — fails with a typed error. Introduce `ResolvedSemanticLayerSource` / `resolvedSourceSchema` / `toResolvedWire` as the strict shape sent to the Python engine, and add a schema contract test that diffs Zod against the Pydantic JSON schema dumped by `python -m semantic_layer dump-schema`. `SourceDefinition` is now `extra="forbid"` on the Python side. `loadAllSources` surfaces per-file load errors instead of swallowing them, so validation/query paths can report manifest shard parse failures. * fix(context): make scan description generation resilient and quiet A transient sampleTable failure during ingest used to take out every table in a connection: generateTableDescription returned a hardcoded 'Table not found' string into descriptions.ai, and KtxDescriptionGenerator was constructed without a logger, so the failure left no trail anywhere. - sampleTable / sampleColumn calls retry 3x with 200/400/800ms backoff, honouring KtxScanContext.signal via a new KtxAbortedError. - On retry exhaustion or missing capability, table generation falls back to a metadata-only prompt built from column name / native type / comment / rawDescriptions. The column path follows the same rule -- call the LLM when any of samples or rawDescriptions are available; skip only when both are absent. - Logger is now threaded from KtxScanContext into the generator. Failures emit structured KtxScanWarning entries (new description_fallback_used code, plus existing sampling_failed / enrichment_failed / connector_capability_missing). ktx scan groups warnings by code so a batch of identical failures collapses to one summary line plus sample. - Returns null on failure instead of the 'Table not found' sentinel; the manifest writer's existing guard already skips empty descriptions, so schema YAML no longer carries misleading text. SCAN_MANAGED_DESCRIPTION_KEYS already strips stale 'ai' on merge, so existing YAML clears on next run. Also suppress AI SDK v6 'system in messages' warning: pull system messages out of KtxMessageBuilder.wrapSimple's output via a new splitKtxSystemMessages helper and pass them top-level to generateText (preserves cacheControl providerOptions on the SystemModelMessage). Agent-runner's local splitSystemPromptMessages dedupes onto the shared helper. * test(docs): align examples-docs assertions with revamped docs PR #103 (setup/guide doc revamp) reworded several CLI examples and connection labels; the assertions in scripts/examples-docs.test.mjs still referenced the pre-revamp wording and were failing in CI on main. Update the regexes to match the post-revamp content: - drop the `--json` flag from the sl-query example expectation - move the `Driver:` / `Status: ok` probe to the connection reference, which is where that output now lives (driver id is lowercase `postgres`, not the display name `PostgreSQL`) - drop the obsolete `Install \`uv\`...` troubleshooting line - accept `<connectionId>` everywhere; the docs no longer use the hyphenated `<connection-id>` form - match the `warehouse` connection id used in the quickstart instead of the `postgres-warehouse` id only used in the README and setup ref * fix(sl): skip TS/Python schema contract test when uv is unavailable The TypeScript checks CI job does not install uv or Python, so the module-level `execFileSync('uv', ...)` in schemas.contract.test.ts threw ENOENT and failed the suite. Wrap the schema dump in a try/catch and guard the describe block with `describe.skipIf` so the test skips in environments without uv. Local dev and any CI job that has uv on PATH still runs the cross-language contract assertion.
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loadAllSources: vi.fn().mockResolvedValue({ sources, loadErrors: [] }),
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validateSourcesForConnection: vi.fn().mockResolvedValue({
errors: ['orders: missing join target', 'customers: invalid grain'],
warnings: ['orders: disconnected-components warning'],
}),
};
const tool = new SlValidateTool({
semanticLayerService: serviceMock as never,
slSearchService: {} as never,
authorResolver: { resolve: vi.fn() },
});
const session: ToolSession = {
connectionId: 'conn-1',
isWorktreeScoped: true,
preHead: null,
touchedSlSources: createTouchedSlSources([{ connectionId: 'conn-1', sourceName: 'orders' }]),
actions: [],
semanticLayerService: serviceMock as any,
wikiService: {} as any,
configService: {} as any,
gitService: {} as any,
};
const context: ToolContext = { sourceId: 's', messageId: 'm', userId: 'u', session };
const result = await tool.call({ connectionId: 'conn-1' } as any, context);
expect(result.structured.validationErrors).toEqual(['orders: missing join target']);
expect(result.structured.validationWarnings).toEqual(['orders: disconnected-components warning']);
});
});