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feat: associated models API with post_training

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there are likely scenarios where admins of a stack only want to allow clients to fine-tune certain models, register certain models to be fine-tuned. etc
introduce the post_training router and post_training_models as the associated type. A different model type needs to be used for inference vs post_training due to the structure of the router currently.

Signed-off-by: Charlie Doern <cdoern@redhat.com>
This commit is contained in:
Charlie Doern 2025-05-30 12:05:33 -04:00
parent 63a9f08c9e
commit 71caa271ad
11 changed files with 393 additions and 23 deletions
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8
llama_stack/distribution/resolver.py
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@ -67,6 +67,7 @@ def api_protocol_map() -> dict[Api, Any]:
Api.vector_io: VectorIO,
Api.vector_dbs: VectorDBs,
Api.models: Models,
Api.post_training_models: Models,
Api.safety: Safety,
Api.shields: Shields,
Api.telemetry: Telemetry,
@ -93,6 +94,7 @@ def api_protocol_map_for_compliance_check() -> dict[Api, Any]:
def additional_protocols_map() -> dict[Api, Any]:
return {
Api.inference: (ModelsProtocolPrivate, Models, Api.models),
Api.post_training: (ModelsProtocolPrivate, Models, Api.post_training_models),
Api.tool_groups: (ToolGroupsProtocolPrivate, ToolGroups, Api.tool_groups),
Api.vector_io: (VectorDBsProtocolPrivate, VectorDBs, Api.vector_dbs),
Api.safety: (ShieldsProtocolPrivate, Shields, Api.shields),
@ -251,6 +253,8 @@ async def instantiate_providers(
"""Instantiates providers asynchronously while managing dependencies."""
impls: dict[Api, Any] = {}
inner_impls_by_provider_id: dict[str, dict[str, Any]] = {f"inner-{x.value}": {} for x in router_apis}
# First pass: instantiate all providers
for api_str, provider in sorted_providers:
deps = {a: impls[a] for a in provider.spec.api_dependencies}
for a in provider.spec.optional_api_dependencies:
@ -269,6 +273,10 @@ async def instantiate_providers(
api = Api(api_str)
impls[api] = impl
# Second pass: connect routing tables
if Api.models in impls and Api.post_training_models in impls:
impls[Api.models].post_training_models_table = impls[Api.post_training_models]
return impls