* feat: add Amazon Nova 2 multimodal embeddings support
Adds support for `amazon.nova-2-multimodal-embeddings-v1:0` via the
new `NovaEmbeddingsModel` class, using the `taskType`/`singleEmbeddingParams`
request format documented in the Nova 2 user guide.
- Supports single and batch text inputs
- Respects the `dimensions` parameter (256/512/1024/2048/3072, default 3072)
- Supports `float` and `base64` encoding formats
- Includes `test_nova_embed.py` for quick end-to-end verification
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* chore: remove test script from repo
Test script moved to PR description instead.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: validate Nova embedding dimensions and fix falsy-zero bug
- Add VALID_DIMENSIONS set and upfront validation with a clear error message
- Fix `dimensions or DEFAULT` which would incorrectly ignore dimensions=0
- Add inline comment explaining approximate token counting (Nova API
does not return token counts in the response)
* fix: address PR review comments for NovaEmbeddingsModel
- Fix VALID_DIMENSIONS to {256, 384, 1024, 3072} per Nova embeddings schema docs
(previous values 512/2048 were mistakenly referenced from Titan embedding model docs)
- Replace str(item) fallback with HTTPException(400) to avoid silent garbage embeddings
- Update schema.py dimensions comment: 'not used' -> 'Used by Nova embeddings'
- Replace getattr() with direct .dimensions access on Pydantic model
- Move dimension validation before the loop (validates once, not per-text)
- Add enumerate to batch loop; include input index in error detail
- Switch isinstance(item, Iterable) to isinstance(item, list) for precise matching
- Add comment explaining embeddingPurpose hardcoded to GENERIC_INDEX
---------
Co-authored-by: Gabriel <gabrielkoo@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
