Add Comprehensive Test Coverage for vector_store.py

[brylie]

Objective

Develop a thorough test suite for the vector_store.py module, which handles vector storage and retrieval operations. Aim for 80-90% test coverage to ensure reliability and correctness of vector store interactions.

Description

The vector_store.py module contains the VectorStore abstract base class and its implementations (e.g., ChromaDBStore, MockVectorStore). We need to create a comprehensive set of tests to cover all critical paths and ensure each implementation works correctly under various scenarios.

Tasks

1. Create a test file test_vector_store.py in the tests/ directory.
2. Implement unit tests for the following components:
   • VectorStore abstract base class (to ensure it defines the correct interface)
   • ChromaDBStore implementation
   • MockVectorStore implementation
   • Any other vector store implementations present in the module
3. For ChromaDBStore:
   • Mock the ChromaDB client to avoid actual database operations during testing
   • Test the initialization process, including error handling for missing API keys
   • Test the query method with various input scenarios
4. For MockVectorStore:
   • Test that it correctly simulates vector store behavior
   • Verify randomness and consistency of returned results
5. Test various scenarios including:
   • Successful query operations
   • Edge cases (e.g., empty query, no results found)
   • Error handling (e.g., database connection issues)
6. Verify that the returned results match the expected VectorStoreResult structure.
7. Test any utility functions or helper methods present in the module.

Acceptance Criteria

• All tests pass successfully.
• Test coverage is between 80-90% as measured by a coverage tool.
• All public methods of each vector store implementation are thoroughly tested.
• Mocking is used appropriately to avoid actual database operations during testing.
• Tests verify both the structure and content of returned results.
• Edge cases and potential error scenarios are adequately covered.
• The MockVectorStore behaves consistently with the real implementations in terms of interface and result structure.

Additional Notes

• Use pytest as the testing framework.
• Use pytest-asyncio for testing asynchronous code.
• Use pytest-cov to measure test coverage.
• Ensure tests are independent and can run in any order.
• Consider using parameterized tests for functions with multiple input scenarios.
• Pay special attention to testing the ChromaDB integration, ensuring all ChromaDB-specific features are covered.