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474b50b422
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 |
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| .. | ||
| agents | ||
| datasetio | ||
| eval | ||
| files/localfs | ||
| inference | ||
| ios/inference | ||
| post_training | ||
| safety | ||
| scoring | ||
| telemetry | ||
| tool_runtime | ||
| vector_io | ||
| __init__.py | ||