mateo-berri aef209963a fix(s3_vectors): embed registered-store ingests with the store's embedding model ... The S3 Vectors ingestion embedded every chunk with the request's embedding.model or the default, never the embedding_model the store was registered with, while search on the same store embeds with the registered model. A registered store uploaded to by id alone therefore embedded with the wrong model and AWS rejected the vectors on the dimension mismatch. The store's embedding model now wins for S3 Vectors ingestion through a helper next to the one search already uses		2026-09-19 04:31:15 -07:00
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ingestion	fix(s3_vectors): embed registered-store ingests with the store's embedding model	2026-09-19 04:31:15 -07:00
__init__.py	fix(rag): track LLM completion usage and spend for /v1/rag/query (#32438)	2026-07-17 17:45:27 +00:00
test_main.py	Merge remote-tracking branch 'origin/main' into litellm_bedrock_rag_retrieval_filter	2026-09-15 15:21:57 -07:00