Why this change is needed:
Offline tests were failing with "ModuleNotFoundError: No module named 'qdrant_client'"
because test_e2e_multi_instance.py was being imported during test collection, even
though it's an E2E test that shouldn't run in offline mode. Pytest imports all test
files during collection phase regardless of marks, causing import errors for missing
E2E dependencies (qdrant_client, asyncpg, etc.).
Additionally, the test mocks for PostgreSQL migration were too permissive - they
accepted any parameter format without validation, which allowed bugs (like passing
dict instead of positional args to AsyncPG execute()) to slip through undetected.
How it solves it:
1. E2E Import Fix:
- Use pytest.importorskip() to conditionally import qdrant_client
- E2E tests are now skipped cleanly when dependencies are missing
- Offline tests can collect and run without E2E dependencies
2. Stricter Test Mocks:
- Enhanced mock_pg_db fixture to validate AsyncPG parameter format
- Mock execute() now raises TypeError if dict/list passed as single argument
- Ensures tests catch parameter passing bugs that would fail in production
3. Parameter Validation Test:
- Added test_postgres_migration_params.py for explicit parameter validation
- Verifies migration passes positional args correctly to AsyncPG
- Provides detailed output for debugging parameter issues
Impact:
- Offline tests no longer fail due to missing E2E dependencies
- Future bugs in AsyncPG parameter passing will be caught by tests
- Better test isolation between offline and E2E test suites
- Improved test coverage for migration parameter handling
Testing:
- Verified with `pytest tests/ -m offline -v` - no import errors
- All PostgreSQL migration tests pass (6/6 unit + 1 strict validation)
- Pre-commit hooks pass (ruff-format, ruff)
Why this change is needed:
PostgreSQLDB class doesn't have a fetch() method. The migration code
was incorrectly using db.fetch() for batch data retrieval, causing
AttributeError during E2E tests.
How it solves it:
1. Changed db.fetch(sql, params) to db.query(sql, params, multirows=True)
2. Updated all test mocks to support the multirows parameter
3. Consolidated mock_query implementation to handle both single and multi-row queries
Impact:
- PostgreSQL legacy data migration now works correctly in E2E tests
- All unit tests pass (6/6)
- Aligns with PostgreSQLDB's actual API
Testing:
- pytest tests/test_postgres_migration.py -v (6/6 passed)
- Updated test_postgres_migration_trigger mock
- Updated test_scenario_2_legacy_upgrade_migration mock
- Updated base mock_pg_db fixture
Why this change is needed:
PostgreSQL vector storage needs model isolation to prevent dimension
conflicts when different workspaces use different embedding models.
Without this, the first workspace locks the vector dimension for all
subsequent workspaces, causing failures.
How it solves it:
- Implements dynamic table naming with model suffix: {table}_{model}_{dim}d
- Adds setup_table() method mirroring Qdrant's approach for consistency
- Implements 4-branch migration logic: both exist -> warn, only new -> use,
neither -> create, only legacy -> migrate
- Batch migration: 500 records/batch (same as Qdrant)
- No automatic rollback to support idempotent re-runs
Impact:
- PostgreSQL tables now isolated by embedding model and dimension
- Automatic data migration from legacy tables on startup
- Backward compatible: model_name=None defaults to "unknown"
- All SQL operations use dynamic table names
Testing:
- 6 new tests for PostgreSQL migration (100% pass)
- Tests cover: naming, migration trigger, scenarios 1-3
- 3 additional scenario tests added for Qdrant completeness
Co-Authored-By: Claude <noreply@anthropic.com>
