llama-stack-mirror/llama_stack/providers/inline
Charlie Doern 71caa271ad feat: associated models API with post_training
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>
2025-05-30 13:32:11 -04:00
..
agents feat(responses): add output_text delta events to responses (#2265) 2025-05-27 13:07:14 -07:00
datasetio chore(refact): move paginate_records fn outside of datasetio (#2137) 2025-05-12 10:56:14 -07:00
eval feat: implementation for agent/session list and describe (#1606) 2025-05-07 14:49:23 +02:00
inference chore: make cprint write to stderr (#2250) 2025-05-24 23:39:57 -07:00
ios/inference chore: removed executorch submodule (#1265) 2025-02-25 21:57:21 -08:00
post_training feat: associated models API with post_training 2025-05-30 13:32:11 -04:00
safety chore: enable pyupgrade fixes (#1806) 2025-05-01 14:23:50 -07:00
scoring chore: enable pyupgrade fixes (#1806) 2025-05-01 14:23:50 -07:00
telemetry fix(telemetry): get rid of annoying sqlite span export error (#2245) 2025-05-24 20:24:34 -07:00
tool_runtime fix(tools): do not index tools, only index toolgroups (#2261) 2025-05-25 13:27:52 -07:00
vector_io feat(sqlite-vec): enable keyword search for sqlite-vec (#1439) 2025-05-21 15:24:24 -04:00
__init__.py impls -> inline, adapters -> remote (#381) 2024-11-06 14:54:05 -08:00