v0.0.0

• Added core functionality for building and querying vector databases
• Implemented document storage and retrieval using vector embeddings
• Added support for multiple cache backends (memory, Redis, SQLite)
• Included text splitting capabilities (character-based and semantic)
• Provided integration with Ollama for embedding generation
• Added comprehensive test suite covering all major components
• Included documentation and usage examples in README
• Implemented support for tags and collections management
• Added utilities for mathematical operations and text processing
• Configured build and packaging infrastructure with Rakefile and gemspec
• Set up continuous integration with Docker-based testing environment
• Added support for different embedding models and configuration options
• Implemented search functionality with similarity scoring
• Added support for filtering search results by tags and text size/count
• Included debugging and logging capabilities
• Provided command-line interface for basic operations
• Added support for batch processing of documents
• Implemented memory-efficient handling of large datasets
• Included proper error handling and validation
• Added support for different text processing strategies
• Implemented caching layer with automatic cleanup
• Added support for custom embedding models
• Included performance optimizations for large-scale operations
• Added comprehensive error reporting and debugging tools
• Implemented proper resource management and cleanup
• Added support for concurrent access patterns
• Included benchmarking and performance testing utilities
• Added support for different database backends
• Implemented proper versioning and dependency management
• Added support for environment-specific configurations
• Included comprehensive logging and monitoring capabilities
• Added support for custom preprocessing and postprocessing steps
• Implemented proper security measures and data protection
• Added support for internationalization and localization
• Included comprehensive API documentation
• Added support for extension and customization
• Implemented proper testing coverage and quality assurance
• Added support for different deployment scenarios
• Included performance profiling and optimization tools
• Added support for backup and recovery mechanisms
• Implemented proper data validation and sanitization
• Added support for different data formats and encodings
• Included comprehensive troubleshooting and debugging guides
• Added support for automated testing and continuous integration
• Implemented proper error recovery and fault tolerance
• Added support for different network configurations
• Included comprehensive security audit and compliance checks