2026-05-10 23:12:26 +02:00
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import { mkdtemp, rm } from 'node:fs/promises';
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import { tmpdir } from 'node:os';
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import { join } from 'node:path';
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import { afterEach, beforeEach, describe, expect, it, vi } from 'vitest';
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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
2026-05-26 08:49:05 +02:00
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import type { KtxSemanticLayerComputePort } from '../../../src/context/daemon/semantic-layer-compute.js';
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feat: query_policy semantic-layer-only restricts agents to predefined semantic-layer measures (#334)
* feat(sl): add predefined_measures_only guard to semantic query planning
SemanticQuery gains a predefined_measures_only flag; the planner rejects
any measure resolved with Provenance.COMPOSED (runtime aggregate
expressions and query-time derivations) while predefined measures,
predefined derived chains, dimensions, filters, and segments pass.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(config): add per-connection query_policy to warehouse connections
query_policy: semantic-layer-only | read-only-sql (default) on the
warehouse connection schema, plus a policy module with the raw-SQL
guard, federated member restriction lookup, and the project-level
predicate used to gate sql_execution registration.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(cli): enforce query_policy on raw SQL through one shared executor
ktx sql and the MCP sql_execution tool now share executeProjectRawSql
(resolve, policy check, read-only validation, execute), collapsing
their duplicated validate-then-execute paths. Restricted connections
are rejected before validation; federated raw SQL is rejected when any
member is restricted. sql_execution is not registered when every SQL
connection is restricted, and connection_list marks restricted
connections so agents route to sl_query. executeProjectReadOnlySql
stays generic for ktx-internal SQL (scan, ingest, SL-generated).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(sl): compile queries with predefined_measures_only from query_policy
compileLocalSlQuery injects the flag from the connection's query_policy,
never from caller input, covering both ktx sl query and the MCP
sl_query tool through the daemon compile path.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* docs: document query_policy semantic-layer-only
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* fix(sl): close semantic-layer-only bypasses via filters and federated hint
The predefined_measures_only guard only inspected query.measures, so a
composed aggregate written into `filters` slipped through _classify_filters
into a HAVING clause untouched — letting a restricted agent evaluate
arbitrary aggregates (e.g. threshold-probing `sum(x) BETWEEN a AND b`).
Reject filter clauses that compose an aggregate function; a HAVING that
compares a predefined measure by name (`orders.revenue > 100`) still works.
Also make the federated sl_query error policy-aware: when a member is
restricted, raw federated SQL is disabled too, so stop directing the agent
to `ktx sql -c _ktx_federated` / sql_execution (a guaranteed failure) and
point to per-connection semantic-layer queries instead.
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
2026-07-03 01:54:17 -07:00
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import { FEDERATED_CONNECTION_ID } from '../../../src/context/connections/federation.js';
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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
2026-05-26 08:49:05 +02:00
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import { initKtxProject, type KtxLocalProject } from '../../../src/context/project/project.js';
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import { compileLocalSlQuery } from '../../../src/context/sl/local-query.js';
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2026-05-10 23:12:26 +02:00
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describe('compileLocalSlQuery', () => {
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let tempDir: string;
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2026-05-10 23:51:24 +02:00
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let project: KtxLocalProject;
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let compute: KtxSemanticLayerComputePort;
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2026-05-10 23:12:26 +02:00
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beforeEach(async () => {
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2026-05-10 23:51:24 +02:00
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tempDir = await mkdtemp(join(tmpdir(), 'ktx-local-query-'));
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2026-05-14 17:39:31 +02:00
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project = await initKtxProject({ projectDir: join(tempDir, 'project') });
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2026-05-13 19:37:25 +02:00
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project.config.connections.warehouse = { driver: 'postgres' };
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2026-05-10 23:12:26 +02:00
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await project.fileStore.writeFile(
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'semantic-layer/warehouse/orders.yaml',
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`name: orders
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table: public.orders
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grain:
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- id
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columns:
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- name: id
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type: number
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- name: status
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type: string
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measures:
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- name: order_count
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expr: count(*)
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joins: []
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`,
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2026-05-10 23:51:24 +02:00
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'ktx',
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'ktx@example.com',
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2026-05-10 23:12:26 +02:00
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'Add orders source',
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);
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await project.fileStore.writeFile(
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'semantic-layer/warehouse/orders_overlay.yaml',
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`name: orders_overlay
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inherits_columns_from: orders
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columns:
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- name: paid_at
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type: timestamp
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joins: []
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measures: []
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grain: []
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`,
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2026-05-10 23:51:24 +02:00
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'ktx',
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'ktx@example.com',
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2026-05-10 23:12:26 +02:00
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'Add overlay source',
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);
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compute = {
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query: vi.fn(async (input) => ({
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sql: 'select status, count(*) as order_count from public.orders group by status',
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dialect: input.dialect,
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columns: [{ name: 'orders.status' }, { name: 'orders.order_count' }],
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plan: { measures: input.query.measures, dimensions: input.query.dimensions },
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})),
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validateSources: vi.fn(),
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generateSources: vi.fn(),
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};
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});
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afterEach(async () => {
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await rm(tempDir, { recursive: true, force: true });
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});
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feat: query_policy semantic-layer-only restricts agents to predefined semantic-layer measures (#334)
* feat(sl): add predefined_measures_only guard to semantic query planning
SemanticQuery gains a predefined_measures_only flag; the planner rejects
any measure resolved with Provenance.COMPOSED (runtime aggregate
expressions and query-time derivations) while predefined measures,
predefined derived chains, dimensions, filters, and segments pass.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(config): add per-connection query_policy to warehouse connections
query_policy: semantic-layer-only | read-only-sql (default) on the
warehouse connection schema, plus a policy module with the raw-SQL
guard, federated member restriction lookup, and the project-level
predicate used to gate sql_execution registration.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(cli): enforce query_policy on raw SQL through one shared executor
ktx sql and the MCP sql_execution tool now share executeProjectRawSql
(resolve, policy check, read-only validation, execute), collapsing
their duplicated validate-then-execute paths. Restricted connections
are rejected before validation; federated raw SQL is rejected when any
member is restricted. sql_execution is not registered when every SQL
connection is restricted, and connection_list marks restricted
connections so agents route to sl_query. executeProjectReadOnlySql
stays generic for ktx-internal SQL (scan, ingest, SL-generated).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(sl): compile queries with predefined_measures_only from query_policy
compileLocalSlQuery injects the flag from the connection's query_policy,
never from caller input, covering both ktx sl query and the MCP
sl_query tool through the daemon compile path.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* docs: document query_policy semantic-layer-only
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* fix(sl): close semantic-layer-only bypasses via filters and federated hint
The predefined_measures_only guard only inspected query.measures, so a
composed aggregate written into `filters` slipped through _classify_filters
into a HAVING clause untouched — letting a restricted agent evaluate
arbitrary aggregates (e.g. threshold-probing `sum(x) BETWEEN a AND b`).
Reject filter clauses that compose an aggregate function; a HAVING that
compares a predefined measure by name (`orders.revenue > 100`) still works.
Also make the federated sl_query error policy-aware: when a member is
restricted, raw federated SQL is disabled too, so stop directing the agent
to `ktx sql -c _ktx_federated` / sql_execution (a guaranteed failure) and
point to per-connection semantic-layer queries instead.
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
2026-07-03 01:54:17 -07:00
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it('injects predefined_measures_only when the connection query_policy is semantic-layer-only', async () => {
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project.config.connections.warehouse = { driver: 'postgres', query_policy: 'semantic-layer-only' };
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await compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: { measures: ['orders.order_count'], dimensions: [], limit: 10 },
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compute,
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});
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expect(compute.query).toHaveBeenCalledWith(
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expect.objectContaining({
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query: expect.objectContaining({ predefined_measures_only: true }),
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}),
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);
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});
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it('rejects a federated sl_query, pointing to per-connection SL when a member is restricted', async () => {
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project.config.connections.warehouse = { driver: 'postgres', query_policy: 'semantic-layer-only' };
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project.config.connections.analytics = { driver: 'postgres' };
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let message = '';
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try {
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await compileLocalSlQuery(project, {
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connectionId: FEDERATED_CONNECTION_ID,
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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});
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throw new Error('expected compileLocalSlQuery to reject');
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} catch (e) {
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message = (e as Error).message;
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}
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expect(message).toContain("member connection(s) 'warehouse'");
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expect(message).toContain('query_policy: semantic-layer-only');
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// Must not send the agent down the raw-SQL path that assertRawSqlAllowed rejects.
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expect(message).not.toContain(`ktx sql -c ${FEDERATED_CONNECTION_ID}`);
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expect(message).not.toContain('sql_execution');
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expect(compute.query).not.toHaveBeenCalled();
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});
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it('rejects a federated sl_query, pointing to raw federated SQL when no member is restricted', async () => {
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project.config.connections.analytics = { driver: 'postgres' };
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await expect(
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compileLocalSlQuery(project, {
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connectionId: FEDERATED_CONNECTION_ID,
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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}),
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).rejects.toThrow(`ktx sql -c ${FEDERATED_CONNECTION_ID}`);
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expect(compute.query).not.toHaveBeenCalled();
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});
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feat(connectors): add MongoDB connector (#305) (#310)
* refactor(connectors): split KtxDialect into core and KtxSqlDialect
Separate the dialect contract into a driver-agnostic core (display/ref
formatting and type mapping) and a SQL-only extension (query generators).
The catalog and entity-details paths resolve the core dialect for any
snapshot driver, so it must stay free of SQL generation; this is the
prerequisite refactor for adding non-SQL primary sources.
- KtxDialect keeps type, formatDisplayRef, parseDisplayRef,
columnDisplayTablePartCount, mapDataType, mapToDimensionType
- KtxSqlDialect extends it with quoteIdentifier, formatTableName, and the
query/sample/statistics generators; the 7 SQL dialects implement it
- add getSqlDialectForDriver for SQL drivers; the 7 connectors and the
relationship-benchmark harness consume it
- thread the relationship pipeline (profiling/validation/composite/
discovery) as KtxSqlDialect | null so a non-SQL source skips coverage SQL
and its candidates stay in review; local-enrichment builds the SQL
dialect only when the connector advertises readOnlySql
Pure extraction: no behavior change for the existing 7 drivers.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* feat(connectors): add MongoDB connector for issue #305
Add a read-only MongoDB connector that treats a database as a primary
context source: collections map to tables and inferred top-level fields to
columns. MongoDB is the first non-SQL source (readOnlySql: false), so
ktx sql and metric compilation do not apply, but its collections flow
through ingest, descriptions, and relationship discovery.
- schema-inference: infer a flat column schema from the most recent
sample_size documents (by _id desc, or order_by for non-ObjectId keys).
Union BSON types per field, mark multi-type fields mixed (string), keep
sub-documents/arrays as a single opaque json column, derive nullability
from presence, treat _id as the primary key
- connector: KtxMongoDbScanConnector behind an injectable client seam;
strictly read-only (find/listCollections/estimatedDocumentCount only),
no executeReadOnly; resolves env:/file: via resolveKtxConfigReference
- core-only KtxMongoDbDialect and a live-database introspection adapter
- wire the mongodb driver: driver union, dialect registry, driver
registration (scopeConfigKey databases), mongodbConnectionSchema,
connection-drivers, normalizeDriver, the live-database route, and the
ktx setup picker. ktx sql is refused by the read-only SQL capability gate
- tests: schema inference, connector snapshot via a fake client, dialect,
driver-schema parsing, and the ktx sql rejection
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs(integrations): document the MongoDB primary source
Add a MongoDB section to the primary-sources reference: connection config
(url, databases, enabled_tables, sample_size, order_by), mongodb+srv/TLS/
Atlas notes, the schema-inference explainer, a features matrix, and the
non-SQL caveat. Update the frontmatter and connection field reference.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* fix(connectors): address review blockers on the MongoDB connector
- introspect: skip estimatedDocumentCount for views. The count command is
rejected on a MongoDB view (CommandNotSupportedOnView), so counting a view
aborted introspect for the whole connection; compute estimatedRows only for
real collections, as ClickHouse does.
- sl: refuse a semantic-layer query against a non-SQL connection instead of
defaulting it to the Postgres dialect. compileLocalSlQuery (the shared CLI +
MCP path) now rejects a driver with no SQL dialect via the new
isSqlQueryableDriver authority, keeping MongoDB context-only per issue #305.
- tests: cover input.tableScope and the empty-scope skip for the Mongo
connector (the scan layer does not post-filter), the view no-count path, and
the ktx sl query refusal for a mongodb connection.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* polish(mongodb): compute sampled nullCount and document sampling caveats
Address the non-blocking review notes:
- sampleColumn now counts null/absent values over the sampled window instead of
returning nullCount: null, since the documents are already in hand
- warn that a custom order_by must be indexed (an unindexed sort hits MongoDB's
in-memory sort limit on large collections) in the connection schema and docs
- note that sampled values for nested fields are stringified, not faithfully
serialized, so the json opacity is deliberate
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* docs(examples): add a MongoDB connector example
A manual, container-backed example mirroring examples/postgres-historic:
- docker-compose.yml + init/seed.js seed a representative dataset (nested
documents, arrays, a Decimal128, a mixed-type field, a nullable field, an
ObjectId reference, and a view) on first container start
- scripts/smoke.sh + introspect-smoke.mjs assert the connector's inferred
schema with no LLM credentials — the same introspection entry point ktx
ingest's database-schema stage uses, including the view-no-count path
- README.md documents the smoke and a full keyless ktx ingest run
(claude-code LLM + managed sentence-transformers embeddings)
Works with Docker Compose or podman compose. Verified end to end.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
* chore: ignore examples/** in knip to fix dead-code false positives
The MongoDB connector example files (examples/mongodb/init/seed.js and
examples/mongodb/scripts/introspect-smoke.mjs) are used at runtime but were
flagged as unused by knip. Add examples/** to the ignore array, matching the
existing .context/** entry.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0114qQV8fJ5a5ME3XbMVRzbL
* fix(mongodb): refuse non-SQL connections before SQL analysis
`ktx sql` and the MCP sql_execution tool resolved a SQL-analysis dialect
(falling back to Postgres for a non-SQL driver) and ran read-only
validation before the connector capability gate refused the connection.
For a MongoDB connection that spun up the parser/daemon and produced
Postgres parser diagnostics instead of a clean non-SQL refusal.
Route both entry points through a shared assertSqlQueryableConnection
guard before dialect selection, mirroring compileLocalSlQuery. The
federated duckdb path has no driver and is exempted at each call site.
Add CLI and MCP regression tests asserting validation/connector work
never starts for a MongoDB connection.
* fix(mongodb): pass CI gates (dialect boundary, secrets, setup test)
Three latent failures in the connector surfaced once CI ran on the branch:
- connector.ts imported the concrete KtxMongoDbDialect, which the connector
dialect-import boundary forbids. Route it through getDialectForDriver('mongodb')
and widen inferKtxMongoCollectionColumns to the base KtxDialect (it only uses
mapDataType/mapToDimensionType).
- detect-secrets flagged a test ObjectId hex and the mongodb+srv example URL;
annotate both with allowlist pragmas.
- the "shows every supported database" setup test omitted the new MongoDB option.
---------
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Luca Martial <48870843+luca-martial@users.noreply.github.com>
Co-authored-by: Luca Martial <lucamrtl@gmail.com>
Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
2026-06-29 15:17:56 +02:00
|
|
|
it('refuses a non-SQL (context-only) connection instead of compiling it as Postgres', async () => {
|
|
|
|
|
project.config.connections['mongo-prod'] = { driver: 'mongodb', url: 'mongodb://localhost:27017/app' };
|
|
|
|
|
await expect(
|
|
|
|
|
compileLocalSlQuery(project, {
|
|
|
|
|
connectionId: 'mongo-prod',
|
|
|
|
|
query: { measures: ['orders.order_count'], dimensions: ['orders.status'], limit: 25 },
|
|
|
|
|
compute,
|
|
|
|
|
}),
|
|
|
|
|
).rejects.toThrow(/non-SQL driver 'mongodb'|require a SQL warehouse connection/);
|
|
|
|
|
expect(compute.query).not.toHaveBeenCalled();
|
|
|
|
|
});
|
|
|
|
|
|
2026-05-10 23:12:26 +02:00
|
|
|
it('compiles a local semantic-layer query with computable sources only', async () => {
|
|
|
|
|
const result = await compileLocalSlQuery(project, {
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
query: {
|
|
|
|
|
measures: ['orders.order_count'],
|
|
|
|
|
dimensions: ['orders.status'],
|
|
|
|
|
limit: 25,
|
|
|
|
|
},
|
|
|
|
|
compute,
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
expect(compute.query).toHaveBeenCalledWith({
|
|
|
|
|
sources: [
|
|
|
|
|
{
|
|
|
|
|
name: 'orders',
|
|
|
|
|
table: 'public.orders',
|
|
|
|
|
grain: ['id'],
|
|
|
|
|
columns: [
|
|
|
|
|
{ name: 'id', type: 'number' },
|
|
|
|
|
{ name: 'status', type: 'string' },
|
|
|
|
|
],
|
|
|
|
|
measures: [{ name: 'order_count', expr: 'count(*)' }],
|
|
|
|
|
joins: [],
|
|
|
|
|
},
|
|
|
|
|
],
|
|
|
|
|
dialect: 'postgres',
|
|
|
|
|
query: {
|
|
|
|
|
measures: ['orders.order_count'],
|
|
|
|
|
dimensions: ['orders.status'],
|
|
|
|
|
limit: 25,
|
feat: query_policy semantic-layer-only restricts agents to predefined semantic-layer measures (#334)
* feat(sl): add predefined_measures_only guard to semantic query planning
SemanticQuery gains a predefined_measures_only flag; the planner rejects
any measure resolved with Provenance.COMPOSED (runtime aggregate
expressions and query-time derivations) while predefined measures,
predefined derived chains, dimensions, filters, and segments pass.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(config): add per-connection query_policy to warehouse connections
query_policy: semantic-layer-only | read-only-sql (default) on the
warehouse connection schema, plus a policy module with the raw-SQL
guard, federated member restriction lookup, and the project-level
predicate used to gate sql_execution registration.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(cli): enforce query_policy on raw SQL through one shared executor
ktx sql and the MCP sql_execution tool now share executeProjectRawSql
(resolve, policy check, read-only validation, execute), collapsing
their duplicated validate-then-execute paths. Restricted connections
are rejected before validation; federated raw SQL is rejected when any
member is restricted. sql_execution is not registered when every SQL
connection is restricted, and connection_list marks restricted
connections so agents route to sl_query. executeProjectReadOnlySql
stays generic for ktx-internal SQL (scan, ingest, SL-generated).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(sl): compile queries with predefined_measures_only from query_policy
compileLocalSlQuery injects the flag from the connection's query_policy,
never from caller input, covering both ktx sl query and the MCP
sl_query tool through the daemon compile path.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* docs: document query_policy semantic-layer-only
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* fix(sl): close semantic-layer-only bypasses via filters and federated hint
The predefined_measures_only guard only inspected query.measures, so a
composed aggregate written into `filters` slipped through _classify_filters
into a HAVING clause untouched — letting a restricted agent evaluate
arbitrary aggregates (e.g. threshold-probing `sum(x) BETWEEN a AND b`).
Reject filter clauses that compose an aggregate function; a HAVING that
compares a predefined measure by name (`orders.revenue > 100`) still works.
Also make the federated sl_query error policy-aware: when a member is
restricted, raw federated SQL is disabled too, so stop directing the agent
to `ktx sql -c _ktx_federated` / sql_execution (a guaranteed failure) and
point to per-connection semantic-layer queries instead.
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
2026-07-03 01:54:17 -07:00
|
|
|
predefined_measures_only: false,
|
2026-05-10 23:12:26 +02:00
|
|
|
},
|
|
|
|
|
});
|
|
|
|
|
expect(result).toEqual({
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
dialect: 'postgres',
|
|
|
|
|
sql: 'select status, count(*) as order_count from public.orders group by status',
|
|
|
|
|
headers: ['orders.status', 'orders.order_count'],
|
|
|
|
|
rows: [],
|
|
|
|
|
totalRows: 0,
|
|
|
|
|
plan: {
|
|
|
|
|
measures: ['orders.order_count'],
|
|
|
|
|
dimensions: ['orders.status'],
|
|
|
|
|
execution: {
|
|
|
|
|
mode: 'compile_only',
|
|
|
|
|
reason: 'Local semantic-layer query compiled SQL but no data-source execution adapter is configured.',
|
|
|
|
|
},
|
|
|
|
|
},
|
|
|
|
|
});
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
it('compiles a local semantic-layer query from manifest-backed scan sources', async () => {
|
|
|
|
|
await project.fileStore.writeFile(
|
|
|
|
|
'semantic-layer/warehouse/_schema/public.yaml',
|
|
|
|
|
`tables:
|
|
|
|
|
payments:
|
|
|
|
|
table: public.payments
|
|
|
|
|
columns:
|
|
|
|
|
- name: payment_id
|
|
|
|
|
type: number
|
|
|
|
|
pk: true
|
|
|
|
|
- name: amount
|
|
|
|
|
type: number
|
|
|
|
|
`,
|
2026-05-10 23:51:24 +02:00
|
|
|
'ktx',
|
|
|
|
|
'ktx@example.com',
|
2026-05-10 23:12:26 +02:00
|
|
|
'Add manifest shard',
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
|
await compileLocalSlQuery(project, {
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
query: {
|
|
|
|
|
measures: ['sum(payments.amount)'],
|
|
|
|
|
dimensions: [],
|
|
|
|
|
},
|
|
|
|
|
compute,
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
expect(compute.query).toHaveBeenLastCalledWith({
|
|
|
|
|
sources: expect.arrayContaining([
|
|
|
|
|
{
|
|
|
|
|
name: 'payments',
|
|
|
|
|
table: 'public.payments',
|
|
|
|
|
grain: ['payment_id'],
|
|
|
|
|
columns: [
|
|
|
|
|
{
|
|
|
|
|
name: 'payment_id',
|
|
|
|
|
type: 'number',
|
|
|
|
|
role: undefined,
|
|
|
|
|
descriptions: undefined,
|
|
|
|
|
constraints: undefined,
|
|
|
|
|
enum_values: undefined,
|
|
|
|
|
tests: undefined,
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
name: 'amount',
|
|
|
|
|
type: 'number',
|
|
|
|
|
role: undefined,
|
|
|
|
|
descriptions: undefined,
|
|
|
|
|
constraints: undefined,
|
|
|
|
|
enum_values: undefined,
|
|
|
|
|
tests: undefined,
|
|
|
|
|
},
|
|
|
|
|
],
|
|
|
|
|
joins: [],
|
|
|
|
|
measures: [],
|
|
|
|
|
},
|
|
|
|
|
]),
|
|
|
|
|
dialect: 'postgres',
|
|
|
|
|
query: {
|
|
|
|
|
measures: ['sum(payments.amount)'],
|
|
|
|
|
dimensions: [],
|
feat: query_policy semantic-layer-only restricts agents to predefined semantic-layer measures (#334)
* feat(sl): add predefined_measures_only guard to semantic query planning
SemanticQuery gains a predefined_measures_only flag; the planner rejects
any measure resolved with Provenance.COMPOSED (runtime aggregate
expressions and query-time derivations) while predefined measures,
predefined derived chains, dimensions, filters, and segments pass.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(config): add per-connection query_policy to warehouse connections
query_policy: semantic-layer-only | read-only-sql (default) on the
warehouse connection schema, plus a policy module with the raw-SQL
guard, federated member restriction lookup, and the project-level
predicate used to gate sql_execution registration.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(cli): enforce query_policy on raw SQL through one shared executor
ktx sql and the MCP sql_execution tool now share executeProjectRawSql
(resolve, policy check, read-only validation, execute), collapsing
their duplicated validate-then-execute paths. Restricted connections
are rejected before validation; federated raw SQL is rejected when any
member is restricted. sql_execution is not registered when every SQL
connection is restricted, and connection_list marks restricted
connections so agents route to sl_query. executeProjectReadOnlySql
stays generic for ktx-internal SQL (scan, ingest, SL-generated).
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* feat(sl): compile queries with predefined_measures_only from query_policy
compileLocalSlQuery injects the flag from the connection's query_policy,
never from caller input, covering both ktx sl query and the MCP
sl_query tool through the daemon compile path.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* docs: document query_policy semantic-layer-only
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
* fix(sl): close semantic-layer-only bypasses via filters and federated hint
The predefined_measures_only guard only inspected query.measures, so a
composed aggregate written into `filters` slipped through _classify_filters
into a HAVING clause untouched — letting a restricted agent evaluate
arbitrary aggregates (e.g. threshold-probing `sum(x) BETWEEN a AND b`).
Reject filter clauses that compose an aggregate function; a HAVING that
compares a predefined measure by name (`orders.revenue > 100`) still works.
Also make the federated sl_query error policy-aware: when a member is
restricted, raw federated SQL is disabled too, so stop directing the agent
to `ktx sql -c _ktx_federated` / sql_execution (a guaranteed failure) and
point to per-connection semantic-layer queries instead.
---------
Co-authored-by: Claude Fable 5 <noreply@anthropic.com>
Co-authored-by: Andrey Avtomonov <andreybavt@gmail.com>
2026-07-03 01:54:17 -07:00
|
|
|
predefined_measures_only: false,
|
2026-05-10 23:12:26 +02:00
|
|
|
},
|
|
|
|
|
});
|
|
|
|
|
});
|
|
|
|
|
|
feat(setup): add Claude Desktop target and MCP-first agent setup (#114)
* feat(setup): add Claude Desktop target and MCP-first agent setup
Adds `ktx mcp stdio` and a `claude-desktop` setup target that generates a
local plugin ZIP wiring the analytics skill and a stdio MCP config. Replaces
the CLI-only agent install mode with MCP+analytics (default) and an optional
admin CLI skill, renames the research skill to analytics, and lets interactive
setup pick project vs global scope when every target supports it. Extracts a
shared MCP server factory used by both HTTP and stdio entrypoints.
* Add MCP agent client setup support
* Polish setup output formatting
* Add MCP tool polish design spec
Design for slimming the MCP-registered surface from 25 to 11 tools,
introducing memory_ingest, applying the per-tool polish kit (annotations,
outputSchema, .describe(), in-band error wrapping, union-drift fixes,
type-narrowed jsonToolResult), emitting progress notifications on
sql_execution + sl_query, and refining the ktx-analytics SKILL.md to
match.
* Refine MCP tool polish design spec after adversarial review iteration 1
* Refine MCP tool polish design spec after adversarial review iteration 2
* Refine MCP tool polish design spec after adversarial review iteration 3
* refactor(context): rename memory capture service to ingest
* feat(mcp): slim research tool surface
* refactor(mcp): remove admin ports from server factory
* refactor(cli): rename text ingest memory port
* docs: update analytics skill for memory ingest
* chore: verify mcp surface rename
* Add MCP tool polish v1 surface change plan
* feat(context): polish mcp tool metadata
* fix(context): enforce resolved semantic layer compute sources
* feat(context): emit mcp query progress stages
* fix(context): keep mcp progress event internal
* Add MCP tool polish v1 metadata & progress plan
* Fix CI snapshot and docs checks
2026-05-16 11:39:55 +02:00
|
|
|
it('strips authoring-only fields (usage, inherits_columns_from) before sending sources to the daemon', async () => {
|
|
|
|
|
await project.fileStore.writeFile(
|
|
|
|
|
'semantic-layer/warehouse/_schema/public.yaml',
|
|
|
|
|
`tables:
|
|
|
|
|
invoices:
|
|
|
|
|
table: public.invoices
|
|
|
|
|
columns:
|
|
|
|
|
- name: invoice_id
|
|
|
|
|
type: number
|
|
|
|
|
pk: true
|
|
|
|
|
- name: amount
|
|
|
|
|
type: number
|
|
|
|
|
usage:
|
|
|
|
|
narrative: Activation policy windows table for invoice analytics.
|
|
|
|
|
frequencyTier: mid
|
|
|
|
|
commonFilters:
|
|
|
|
|
- amount
|
|
|
|
|
commonGroupBys: []
|
|
|
|
|
commonJoins: []
|
|
|
|
|
staleSince: null
|
|
|
|
|
`,
|
|
|
|
|
'ktx',
|
|
|
|
|
'ktx@example.com',
|
|
|
|
|
'Add manifest shard with usage',
|
|
|
|
|
);
|
|
|
|
|
|
|
|
|
|
await compileLocalSlQuery(project, {
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
query: { measures: ['sum(invoices.amount)'], dimensions: [] },
|
|
|
|
|
compute,
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
const lastCall = (compute.query as ReturnType<typeof vi.fn>).mock.calls.at(-1)?.[0];
|
|
|
|
|
const invoices = lastCall?.sources.find((s: Record<string, unknown>) => s.name === 'invoices');
|
|
|
|
|
expect(invoices).toBeDefined();
|
|
|
|
|
expect(invoices).not.toHaveProperty('usage');
|
|
|
|
|
expect(invoices).not.toHaveProperty('inherits_columns_from');
|
|
|
|
|
expect(invoices).not.toHaveProperty('source_type');
|
|
|
|
|
});
|
|
|
|
|
|
2026-05-10 23:12:26 +02:00
|
|
|
it('resolves the only configured connection when connectionId is omitted', async () => {
|
|
|
|
|
await compileLocalSlQuery(project, {
|
|
|
|
|
query: { measures: ['orders.order_count'], dimensions: [] },
|
|
|
|
|
compute,
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
expect(compute.query).toHaveBeenCalledWith(
|
|
|
|
|
expect.objectContaining({
|
|
|
|
|
dialect: 'postgres',
|
|
|
|
|
}),
|
|
|
|
|
);
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
it('executes compiled SQL through a local query executor when requested', async () => {
|
|
|
|
|
const queryExecutor = {
|
|
|
|
|
execute: vi.fn(async () => ({
|
|
|
|
|
headers: ['status', 'order_count'],
|
|
|
|
|
rows: [['paid', 2]],
|
|
|
|
|
totalRows: 1,
|
|
|
|
|
command: 'SELECT',
|
|
|
|
|
rowCount: 1,
|
|
|
|
|
})),
|
|
|
|
|
};
|
|
|
|
|
|
|
|
|
|
const result = await compileLocalSlQuery(project, {
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
query: {
|
|
|
|
|
measures: ['orders.order_count'],
|
|
|
|
|
dimensions: ['orders.status'],
|
|
|
|
|
limit: 25,
|
|
|
|
|
},
|
|
|
|
|
compute,
|
|
|
|
|
execute: true,
|
|
|
|
|
maxRows: 10,
|
|
|
|
|
queryExecutor,
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
expect(queryExecutor.execute).toHaveBeenCalledWith({
|
|
|
|
|
connectionId: 'warehouse',
|
|
|
|
|
projectDir: project.projectDir,
|
2026-05-13 19:37:25 +02:00
|
|
|
connection: { driver: 'postgres' },
|
2026-05-10 23:12:26 +02:00
|
|
|
sql: 'select status, count(*) as order_count from public.orders group by status',
|
|
|
|
|
maxRows: 10,
|
|
|
|
|
});
|
|
|
|
|
expect(result.rows).toEqual([['paid', 2]]);
|
|
|
|
|
expect(result.totalRows).toBe(1);
|
|
|
|
|
expect(result.plan.execution).toEqual({
|
|
|
|
|
mode: 'executed',
|
|
|
|
|
driver: 'postgres',
|
|
|
|
|
maxRows: 10,
|
|
|
|
|
rowCount: 1,
|
|
|
|
|
});
|
|
|
|
|
});
|
|
|
|
|
|
feat(setup): add Claude Desktop target and MCP-first agent setup (#114)
* feat(setup): add Claude Desktop target and MCP-first agent setup
Adds `ktx mcp stdio` and a `claude-desktop` setup target that generates a
local plugin ZIP wiring the analytics skill and a stdio MCP config. Replaces
the CLI-only agent install mode with MCP+analytics (default) and an optional
admin CLI skill, renames the research skill to analytics, and lets interactive
setup pick project vs global scope when every target supports it. Extracts a
shared MCP server factory used by both HTTP and stdio entrypoints.
* Add MCP agent client setup support
* Polish setup output formatting
* Add MCP tool polish design spec
Design for slimming the MCP-registered surface from 25 to 11 tools,
introducing memory_ingest, applying the per-tool polish kit (annotations,
outputSchema, .describe(), in-band error wrapping, union-drift fixes,
type-narrowed jsonToolResult), emitting progress notifications on
sql_execution + sl_query, and refining the ktx-analytics SKILL.md to
match.
* Refine MCP tool polish design spec after adversarial review iteration 1
* Refine MCP tool polish design spec after adversarial review iteration 2
* Refine MCP tool polish design spec after adversarial review iteration 3
* refactor(context): rename memory capture service to ingest
* feat(mcp): slim research tool surface
* refactor(mcp): remove admin ports from server factory
* refactor(cli): rename text ingest memory port
* docs: update analytics skill for memory ingest
* chore: verify mcp surface rename
* Add MCP tool polish v1 surface change plan
* feat(context): polish mcp tool metadata
* fix(context): enforce resolved semantic layer compute sources
* feat(context): emit mcp query progress stages
* fix(context): keep mcp progress event internal
* Add MCP tool polish v1 metadata & progress plan
* Fix CI snapshot and docs checks
2026-05-16 11:39:55 +02:00
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it('emits progress while compiling and executing a local semantic-layer query', async () => {
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const progress: Array<{ progress: number; message: string }> = [];
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const queryExecutor = {
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execute: vi.fn(async () => ({
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headers: ['status', 'order_count'],
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rows: [['paid', 2]],
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totalRows: 1,
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command: 'SELECT',
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rowCount: 1,
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})),
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};
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const result = await compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: {
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measures: ['orders.order_count'],
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dimensions: ['orders.status'],
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limit: 25,
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},
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compute,
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execute: true,
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maxRows: 10,
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queryExecutor,
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onProgress: (event) => {
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progress.push({ progress: event.progress, message: event.message });
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},
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});
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expect(result.totalRows).toBe(1);
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expect(progress).toEqual([
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{ progress: 0, message: 'Compiling query' },
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{ progress: 0.3, message: 'Generating SQL' },
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{ progress: 0.6, message: 'Executing' },
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{ progress: 1, message: 'Fetched 1 rows' },
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]);
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});
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2026-05-10 23:12:26 +02:00
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it('requires a query executor for executed mode', async () => {
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await expect(
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compileLocalSlQuery(project, {
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connectionId: 'warehouse',
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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execute: true,
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}),
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).rejects.toThrow('Local semantic-layer execution requires a query executor.');
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});
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2026-06-15 14:38:44 +02:00
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it('requires connectionId, listing the configured connections, when several exist', async () => {
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2026-05-13 19:37:25 +02:00
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project.config.connections.analytics = { driver: 'bigquery' };
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2026-05-10 23:12:26 +02:00
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await expect(
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compileLocalSlQuery(project, {
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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}),
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2026-06-15 14:38:44 +02:00
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).rejects.toThrow('connectionId is required. Configured connections: analytics, warehouse.');
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});
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it('rejects a connectionId that is not configured, listing the configured connections', async () => {
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await expect(
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compileLocalSlQuery(project, {
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connectionId: 'DIG_SMART_REP',
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query: { measures: ['orders.order_count'], dimensions: [] },
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compute,
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}),
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).rejects.toThrow('Connection "DIG_SMART_REP" is not configured in ktx.yaml. Configured connections: warehouse.');
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2026-05-10 23:12:26 +02:00
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});
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});
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