Version 0.1.0

Added

• Initial implementation of high-performance brute-force cosine similarity search with a Rust backend and Python bindings via PyO3.
• cosine_similarity() function exposed to Python: computes cosine similarity between a query vector and multiple candidate vectors and returns the top-k most similar candidates.
• SIMD-accelerated (wide::f32x8) routines for dot product and norm calculations to maximize performance on modern CPUs.
• Adaptive parallel scoring of candidate vectors using Rayon for efficient multi-threaded computation.
• Inline, heap-based top-k selection algorithm for efficient retrieval of the k most similar candidates.
• Strict validation of C-contiguous memory layout for all vector inputs to ensure optimal performance.
• Python compare() interface: simple, type-safe wrapper that allows direct vector comparison and batching from Python.
• Utility functions for diagnostics (e.g., thread count, SIMD support) in the Rust backend.
• Benchmarks comparing package performance to NumPy and scikit-learn cosine similarity implementations.