skamenan7 474b50b422 Add configurable embedding models for vector IO providers ... This change lets users configure default embedding models at the provider level instead of always relying on system defaults. Each vector store provider can now specify an embedding_model and optional embedding_dimension in their config. Key features: - Auto-dimension lookup for standard models from the registry - Support for Matryoshka embeddings with custom dimensions - Three-tier priority: explicit params > provider config > system fallback - Full backward compatibility - existing setups work unchanged - Comprehensive test coverage with 20 test cases Updated all vector IO providers (FAISS, Chroma, Milvus, Qdrant, etc.) with the new config fields and added detailed documentation with examples. Fixes #2729		2025-07-15 16:46:40 -04:00
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__init__.py	feat: Add ChunkMetadata to Chunk (#2497)	2025-06-25 15:55:23 -04:00
chunk_utils.py	chore: Updating chunk id generation to ensure uniqueness (#2618)	2025-07-04 10:26:35 +05:30
embedding_utils.py	Add configurable embedding models for vector IO providers	2025-07-15 16:46:40 -04:00