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llama-stack-mirror/llama_stack/core/routers
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skamenan7 32930868de tightened vector store embedding model validation 
includes:
- require models to exist in registry before use
- make default_embedding_dimension mandatory when setting default model
- use first available model fallback instead of hardcoded all-MiniLM-L6-v2
- add tests for error cases and update docs
2025-09-18 10:51:50 -04:00
..
__init__.py chore: introduce write queue for inference_store (#3383) 2025-09-10 11:57:42 -07:00
datasets.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
eval_scoring.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
inference.py chore: introduce write queue for inference_store (#3383) 2025-09-10 11:57:42 -07:00
safety.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
tool_runtime.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
vector_io.py tightened vector store embedding model validation 2025-09-18 10:51:50 -04:00