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.

llama_toolchain/cli/stack/build.py

@@ -46,7 +46,7 @@ class StackBuild(Subcommand):
 
         from llama_toolchain.common.config_dirs import DISTRIBS_BASE_DIR
         from llama_toolchain.common.serialize import EnumEncoder
-        from llama_toolchain.core.package import ApiInput, build_package, ImageType
+        from llama_toolchain.core.package import ApiInput, build_image, ImageType
         from termcolor import cprint
 
         # save build.yaml spec for building same distribution again
@@ -66,7 +66,7 @@ class StackBuild(Subcommand):
             to_write = json.loads(json.dumps(build_config.dict(), cls=EnumEncoder))
             f.write(yaml.dump(to_write, sort_keys=False))
 
-        build_package(build_config, build_file_path)
+        build_image(build_config, build_file_path)
 
         cprint(
             f"Build spec configuration saved at {str(build_file_path)}",