On-device query embedder for the Leonis AI maritime assistant (Android). This is intfloat/multilingual-e5-base exported to ONNX and dynamically quantized to int8, paired with a SentencePiece tokenizer baked into an onnxruntime-extensions graph so the model takes a raw "query: …" string.

It must match the model the desktop app indexes passages with, so query and passage vectors share one 768-dim space.

Pipeline: "query: " + text → tokenizer.onnx → model_int8.onnx → mean-pool (attention mask) → L2-normalize → 768-dim unit vector.

Verified parity vs the desktop sentence-transformers embedder: cosine 0.974–0.983 (full int8 chain), 1.000 for the fp32 export.

License: MIT (inherits from the base model).