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v2.2.0
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Added
Metadata filtering : New filter_by_metadata() method for efficient key-value filtering using SQLite's JSON_EXTRACT
Metadata counting : New count_by_metadata() method to count records matching metadata filters
Combined search : New similarity_search_with_filter() method combining vector similarity with metadata filtering
Support for nested JSON paths in metadata filters (e.g., {"author.name": "Alice"})
Pagination support in filter_by_metadata() with limit and offset parameters
New validation function validate_metadata_filters() for secure filter validation
New utility function build_metadata_where_clause() for safe SQL generation
Comprehensive test coverage for metadata filtering (unit, integration, and security tests)
New example advanced_metadata_queries.py demonstrating nested paths and complex queries
Updated metadata_filtering.py example with new filtering methods
Export/import functionality : New methods for data portability
export_to_json() - Export records to JSON Lines format
import_from_json() - Import records from JSON Lines format
export_to_csv() - Export records to CSV format
import_from_csv() - Import records from CSV format
Support for filtered exports using metadata filters
Batch processing for memory-efficient import/export of large datasets
Optional embedding inclusion in exports
New io module with import/export utilities
Comprehensive tests for import/export functionality
New example export_import_example.py demonstrating backup/restore workflows
Security
SQL injection prevention in metadata filter keys
Validation of JSON paths to prevent malicious queries
Parameterized queries for all metadata filtering operations
Improved
Data migration workflows now much easier
Backup and restore capabilities for production use
Interoperability with external systems via CSV/JSON
Documentation
Added "Metadata Filtering" section to README with examples
Added "Export/Import" section to README with examples
Updated examples list in README
Added comprehensive docstrings for new methods
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