mirror of
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The 34 `index.ts` re-export barrels inside `packages/cli/src/` were holdovers from the pre-fold multi-workspace structure. Post-fold-in they served no production purpose: external consumers go through the single package main entry, and in-repo callers mostly imported through them only because the path was short. Internally, knip flagged most barrel re-exports as production-dead (only reached via tests). This change: - Deletes every internal barrel except `packages/cli/src/index.ts` (the published package entry). - Rewrites ~270 source/test files to import each name directly from the file that defines it. - Moves `tools/warehouse-verification/index.ts` to `create-warehouse-verification-tools.ts` (the function it defined locally) and updates its single consumer. - Renames `search/backend-conformance.ts` → `.test-utils.ts` to match the existing test-helper file convention. - Deletes 13 dead test-only chains (dbt-descriptions/*, live-database/extracted-schema, live-database/structural-sync, relationship-* feedback/review chain) plus their tests and a cascading orphan integration test. - Updates test mocks that pointed at deleted barrel paths (notion-client, connector barrels in scan/local-scan-connectors tests) to mock the source files instead. - Points the maintainer benchmark script (`scripts/relationship-benchmark-report.mjs`) at source files instead of `dist/context/scan/index.js`. - Drops the barrel `!` entries from `knip.json`; adds explicit production entries only for the benchmark code reached via dist by the maintainer script. Net: 413 files changed, ~1.2k insertions, ~9.4k deletions. `pnpm run dead-code` (Biome + knip default + knip production) and `pnpm run type-check` are clean; 2277 tests pass.
280 lines
10 KiB
TypeScript
280 lines
10 KiB
TypeScript
import { readFile } from 'node:fs/promises';
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import { createDefaultLocalQueryExecutor } from './context/connections/local-query-executor.js';
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import type { KtxSqlQueryExecutorPort } from './context/connections/query-executor.js';
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import { KtxIngestEmbeddingPortAdapter } from './context/llm/embedding-port.js';
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import type { KtxEmbeddingPort } from './context/core/embedding.js';
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import type { KtxSemanticLayerComputePort } from './context/daemon/semantic-layer-compute.js';
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import { loadKtxProject, type KtxLocalProject } from './context/project/project.js';
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import { compileLocalSlQuery } from './context/sl/local-query.js';
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import { listLocalSlSources, readLocalSlSource, searchLocalSlSources as defaultSearchLocalSlSources, validateLocalSlSource, type LocalSlSourceSearchResult, type LocalSlSourceSummary } from './context/sl/local-sl.js';
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import type { SemanticLayerQueryInput } from './context/sl/types.js';
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import {
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resolveProjectEmbeddingProvider,
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type EmbeddingProviderResolution,
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} from './embedding-resolution.js';
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import type { PrintListColumn } from './io/print-list.js';
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import {
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createManagedPythonSemanticLayerComputePort,
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type KtxManagedPythonInstallPolicy,
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} from './managed-python-command.js';
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import { profileMark } from './startup-profile.js';
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profileMark('module:sl');
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type SlQueryFormat = 'json' | 'sql';
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export type KtxSlArgs =
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command: 'list';
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projectDir: string;
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connectionId?: string;
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output?: string;
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json?: boolean;
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cliVersion: string;
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}
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command: 'search';
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projectDir: string;
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connectionId?: string;
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query: string;
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limit?: number;
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output?: string;
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json?: boolean;
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cliVersion: string;
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}
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| { command: 'validate'; projectDir: string; connectionId: string; sourceName: string }
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| {
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command: 'query';
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projectDir: string;
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connectionId?: string;
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query?: SemanticLayerQueryInput;
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queryFile?: string;
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format: SlQueryFormat;
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execute: boolean;
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maxRows?: number;
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cliVersion: string;
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runtimeInstallPolicy: KtxManagedPythonInstallPolicy;
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};
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interface KtxSlIo {
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stdout: { write(chunk: string): void };
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stderr: { write(chunk: string): void };
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}
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interface KtxSlDeps {
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loadProject?: typeof loadKtxProject;
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resolveEmbeddingProvider?: typeof resolveProjectEmbeddingProvider;
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searchLocalSlSources?: typeof defaultSearchLocalSlSources;
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createSemanticLayerCompute?: () => KtxSemanticLayerComputePort;
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createManagedSemanticLayerCompute?: (options: {
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cliVersion: string;
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installPolicy: KtxManagedPythonInstallPolicy;
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io: KtxSlIo;
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}) => Promise<KtxSemanticLayerComputePort>;
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createQueryExecutor?: () => KtxSqlQueryExecutorPort;
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}
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function resolutionToEmbeddingPort(resolution: EmbeddingProviderResolution): KtxEmbeddingPort | null {
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if (
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resolution.kind === 'configured' ||
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resolution.kind === 'managed-running' ||
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resolution.kind === 'managed-started'
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) {
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return new KtxIngestEmbeddingPortAdapter(resolution.provider);
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}
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return null;
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}
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async function printSlSources(input: {
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rows: ReadonlyArray<LocalSlSourceSummary>;
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command: 'sl list';
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output?: string;
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json?: boolean;
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io: KtxSlIo;
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emptyMessage: string;
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emptyHint?: string;
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}): Promise<void>;
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async function printSlSources(input: {
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rows: ReadonlyArray<LocalSlSourceSearchResult>;
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command: 'sl search';
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output?: string;
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json?: boolean;
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io: KtxSlIo;
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emptyMessage: string;
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emptyHint?: string;
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}): Promise<void>;
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async function printSlSources(input: {
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rows: ReadonlyArray<LocalSlSourceSummary | LocalSlSourceSearchResult>;
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command: 'sl list' | 'sl search';
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output?: string;
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json?: boolean;
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io: KtxSlIo;
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emptyMessage: string;
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emptyHint?: string;
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}): Promise<void> {
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const { resolveOutputMode } = await import('./io/mode.js');
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const { createRankBadgeFormatter, printList } = await import('./io/print-list.js');
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const mode = resolveOutputMode({ explicit: input.output, json: input.json, io: input.io });
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if (input.command === 'sl search') {
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const searchColumns: ReadonlyArray<PrintListColumn<LocalSlSourceSearchResult>> = [
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{
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key: 'score',
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label: 'SCORE',
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plain: 'score=',
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role: 'badge',
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prettyFormat: createRankBadgeFormatter(input.rows as ReadonlyArray<LocalSlSourceSearchResult>),
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dim: true,
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},
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{ key: 'connectionId', label: 'CONNECTION', plain: '' },
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{ key: 'name', label: 'NAME', plain: '' },
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{ key: 'columnCount', label: 'COLS', plain: 'columns=', dim: true },
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{ key: 'measureCount', label: 'MEASURES', plain: 'measures=', dim: true },
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{ key: 'joinCount', label: 'JOINS', plain: 'joins=', dim: true },
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{ key: 'description', label: 'DESCRIPTION', plain: false, optional: true, dim: true },
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];
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printList<LocalSlSourceSearchResult>({
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rows: input.rows as ReadonlyArray<LocalSlSourceSearchResult>,
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columns: searchColumns,
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groupBy: 'connectionId',
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emptyMessage: input.emptyMessage,
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emptyHint: input.emptyHint,
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unit: 'source',
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command: input.command,
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mode,
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io: input.io,
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});
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return;
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}
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const listColumns: ReadonlyArray<PrintListColumn<LocalSlSourceSummary>> = [
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{ key: 'connectionId', label: 'CONNECTION', plain: '' },
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{ key: 'name', label: 'NAME', plain: '' },
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{ key: 'columnCount', label: 'COLS', plain: 'columns=', dim: true },
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{ key: 'measureCount', label: 'MEASURES', plain: 'measures=', dim: true },
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{ key: 'joinCount', label: 'JOINS', plain: 'joins=', dim: true },
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{ key: 'description', label: 'DESCRIPTION', plain: false, optional: true, dim: true },
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];
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printList<LocalSlSourceSummary>({
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rows: input.rows as ReadonlyArray<LocalSlSourceSummary>,
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columns: listColumns,
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groupBy: 'connectionId',
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emptyMessage: input.emptyMessage,
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emptyHint: input.emptyHint,
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unit: 'source',
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command: input.command,
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mode,
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io: input.io,
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});
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}
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async function readSlQueryFile(path: string): Promise<SemanticLayerQueryInput> {
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const parsed = JSON.parse(await readFile(path, 'utf-8')) as unknown;
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if (!parsed || typeof parsed !== 'object' || Array.isArray(parsed)) {
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throw new Error(`${path} must contain a JSON object.`);
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}
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return parsed as SemanticLayerQueryInput;
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}
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export async function runKtxSl(args: KtxSlArgs, io: KtxSlIo = process, deps: KtxSlDeps = {}): Promise<number> {
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try {
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const project = await (deps.loadProject ?? loadKtxProject)({ projectDir: args.projectDir });
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if (args.command === 'list') {
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const sources = await listLocalSlSources(project, { connectionId: args.connectionId });
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await printSlSources({
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rows: sources,
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emptyMessage: `No semantic-layer sources found in ${project.projectDir}`,
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command: 'sl list',
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output: args.output,
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json: args.json,
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io,
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});
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return 0;
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}
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if (args.command === 'search') {
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const resolver = deps.resolveEmbeddingProvider ?? resolveProjectEmbeddingProvider;
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const resolution = await resolver(project, {
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mode: 'use-if-running',
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cliVersion: args.cliVersion,
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io,
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});
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const embeddingService = resolutionToEmbeddingPort(resolution);
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const search = deps.searchLocalSlSources ?? defaultSearchLocalSlSources;
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const sources = await search(project, {
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connectionId: args.connectionId,
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query: args.query,
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embeddingService,
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limit: args.limit,
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});
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if (sources.length === 0 && resolution.kind === 'managed-unavailable' && !args.json) {
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const { SYMBOLS } = await import('./io/symbols.js');
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io.stderr.write(`embeddings: unavailable ${SYMBOLS.emDash} ${resolution.reason}\n`);
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}
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await printSlSources({
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rows: sources,
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emptyMessage: `No semantic-layer sources matched "${args.query}" in ${project.projectDir}`,
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emptyHint: 'Run `ktx sl` to inspect available sources.',
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command: 'sl search',
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output: args.output,
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json: args.json,
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io,
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});
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return 0;
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}
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if (args.command === 'validate') {
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const source = await readLocalSlSource(project, {
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connectionId: args.connectionId,
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sourceName: args.sourceName,
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});
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if (!source) {
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throw new Error(`Semantic-layer source "${args.connectionId}/${args.sourceName}" was not found`);
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}
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const result = await validateLocalSlSource(source.yaml, {
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project,
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connectionId: args.connectionId,
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sourceName: args.sourceName,
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});
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if (!result.valid) {
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for (const error of result.errors) {
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io.stderr.write(`${error}\n`);
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}
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return 1;
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}
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io.stdout.write(`Valid semantic-layer source: ${args.connectionId}/${args.sourceName}\n`);
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return 0;
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}
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if (args.command === 'query') {
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const query = args.query ?? (args.queryFile ? await readSlQueryFile(args.queryFile) : undefined);
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if (!query) {
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throw new Error('sl query requires query input from --query-file or at least one --measure');
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}
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const compute = deps.createSemanticLayerCompute
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? deps.createSemanticLayerCompute()
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: await (deps.createManagedSemanticLayerCompute ?? createManagedPythonSemanticLayerComputePort)({
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cliVersion: args.cliVersion,
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installPolicy: args.runtimeInstallPolicy,
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io,
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});
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const queryExecutor = args.execute ? (deps.createQueryExecutor ?? createDefaultLocalQueryExecutor)() : undefined;
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const result = await compileLocalSlQuery(project as KtxLocalProject, {
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connectionId: args.connectionId,
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query,
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compute,
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execute: args.execute,
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maxRows: args.maxRows,
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queryExecutor,
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});
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if (args.format === 'sql') {
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io.stdout.write(`${result.sql}\n`);
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return 0;
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}
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io.stdout.write(`${JSON.stringify(result, null, 2)}\n`);
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return 0;
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}
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const _exhaustive: never = args;
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throw new Error(`Unsupported sl command: ${JSON.stringify(_exhaustive)}`);
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} catch (error) {
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io.stderr.write(`${error instanceof Error ? error.message : String(error)}\n`);
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return 1;
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}
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}
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