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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
43 lines
1.9 KiB
TypeScript
43 lines
1.9 KiB
TypeScript
import { describe, expect, it, vi } from 'vitest';
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import { z } from 'zod';
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import { createAiSdkToolSet, createClaudeSdkTools, normalizeKtxRuntimeToolOutput } from '../../../src/context/llm/runtime-tools.js';
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import type { KtxRuntimeToolDescriptor } from '../../../src/context/llm/runtime-port.js';
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describe('runtime tool descriptors', () => {
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const descriptor: KtxRuntimeToolDescriptor<{ id: string }, { ok: boolean }> = {
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name: 'read_thing',
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description: 'Read one thing.',
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inputSchema: z.object({ id: z.string() }),
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execute: vi.fn(async (input) => ({
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markdown: `Read ${input.id}`,
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structured: { ok: true },
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})),
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};
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it('normalizes string and object tool outputs into markdown plus optional structured payload', () => {
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expect(normalizeKtxRuntimeToolOutput('plain text')).toEqual({ markdown: 'plain text' });
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expect(normalizeKtxRuntimeToolOutput({ markdown: 'shown', structured: { id: 1 } })).toEqual({
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markdown: 'shown',
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structured: { id: 1 },
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});
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expect(normalizeKtxRuntimeToolOutput({ name: 'skill', content: 'body' })).toEqual({
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markdown: '```json\n{\n "name": "skill",\n "content": "body"\n}\n```',
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structured: { name: 'skill', content: 'body' },
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});
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});
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it('builds AI SDK tools that expose markdown to the model', async () => {
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const tools = createAiSdkToolSet({ read_thing: descriptor });
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const output = await tools.read_thing.execute?.({ id: 'a' }, { toolCallId: 'call-1', messages: [] } as never);
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const modelOutput = tools.read_thing.toModelOutput?.({ output } as never);
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expect(modelOutput).toEqual({ type: 'text', value: 'Read a' });
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});
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it('builds Claude SDK tools that return text content only', async () => {
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const tools = createClaudeSdkTools({ read_thing: descriptor });
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const result = await tools[0].handler({ id: 'b' } as never, {});
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expect(result).toEqual({ content: [{ type: 'text', text: 'Read b' }] });
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});
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});
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