v1.4.0 — Tokenizer save/load & encode_texts

Quality-of-life: tokenizer persistence and a corpus-embedding helper. Additive and
backward-compatible.

Added

• BPETokenizer.save / BPETokenizer.load (and to_dict / from_dict):
  serialize a trained BPE tokenizer (vocabulary + merges + end-of-word marker) to a
  versioned JSON file and reconstruct it exactly, encoding/decoding identically.
• encode_texts (polaris.inference): batch-embed a sequence of texts with a
  TextEmbedder, returning a (len(texts), embedding_dim) NumPy array — the
  corpus-embedding step of a dense retriever.