llama-stack-mirror/llama_toolchain/memory/router
Ashwin Bharambe b6a3ef51da Introduce a "Router" layer for providers
Some providers need to be factorized and considered as thin routing
layers on top of other providers. Consider two examples:

- The inference API should be a routing layer over inference providers,
  routed using the "model" key
- The memory banks API is another instance where various memory bank
  types will be provided by independent providers (e.g., a vector store
  is served by Chroma while a keyvalue memory can be served by Redis or
  PGVector)

This commit introduces a generalized routing layer for this purpose.
2024-09-16 17:04:45 -07:00
..
__init__.py Introduce a "Router" layer for providers 2024-09-16 17:04:45 -07:00
router.py Introduce a "Router" layer for providers 2024-09-16 17:04:45 -07:00