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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
93 lines
2.9 KiB
TypeScript
93 lines
2.9 KiB
TypeScript
import { NoSuchToolError, type LanguageModel } from 'ai';
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import { describe, expect, it, vi } from 'vitest';
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import { createKtxToolCallRepairHandler } from '../../src/llm/repair.js';
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const repairModel = { modelId: 'claude-repair', provider: 'anthropic' } as LanguageModel;
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describe('createKtxToolCallRepairHandler', () => {
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it('returns null for NoSuchToolError', async () => {
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const handler = createKtxToolCallRepairHandler({
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source: 'unit',
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getRepairModel: () => repairModel,
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generateText: vi.fn(),
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});
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await expect(
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handler({
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system: undefined,
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messages: [],
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toolCall: { type: 'tool-call', toolName: 'missing', toolCallId: 'tc_1', input: '{}' },
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tools: {},
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inputSchema: async () => ({}),
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error: new NoSuchToolError({ toolName: 'missing' }),
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}),
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).resolves.toBeNull();
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});
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it('repairs string input by local JSON extraction without an LLM call', async () => {
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const generateText = vi.fn();
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const handler = createKtxToolCallRepairHandler({
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source: 'unit',
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getRepairModel: () => repairModel,
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generateText,
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});
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await expect(
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handler({
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system: undefined,
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messages: [],
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toolCall: {
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type: 'tool-call',
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toolName: 'write_source',
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toolCallId: 'tc_2',
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input: 'prefix {"path":"orders.yaml"} suffix',
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},
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tools: { write_source: {} as never },
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inputSchema: async () => ({ type: 'object' }),
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error: new Error('Invalid tool input') as never,
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}),
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).resolves.toEqual({
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type: 'tool-call',
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toolName: 'write_source',
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toolCallId: 'tc_2',
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input: '{"path":"orders.yaml"}',
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});
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expect(generateText).not.toHaveBeenCalled();
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});
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it('falls back to the repair model when local extraction fails', async () => {
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const generateText = vi.fn().mockResolvedValue({ text: '{"path":"customers.yaml"}' });
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const handler = createKtxToolCallRepairHandler({
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source: 'unit',
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getRepairModel: () => repairModel,
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generateText,
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});
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await expect(
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handler({
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system: undefined,
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messages: [],
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toolCall: {
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type: 'tool-call',
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toolName: 'write_source',
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toolCallId: 'tc_3',
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input: 'not json',
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},
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tools: { write_source: {} as never },
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inputSchema: async () => ({ type: 'object', properties: { path: { type: 'string' } } }),
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error: new Error('Invalid tool input') as never,
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}),
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).resolves.toEqual({
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type: 'tool-call',
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toolName: 'write_source',
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toolCallId: 'tc_3',
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input: '{"path":"customers.yaml"}',
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});
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expect(generateText).toHaveBeenCalledWith(
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expect.objectContaining({
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model: repairModel,
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prompt: expect.stringContaining('The model tried to call the tool "write_source"'),
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}),
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);
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});
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});
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