llama-stack-mirror/llama_stack/providers/inline
Ben Browning 92fdf6d0c9 Use our own pydantic models for OpenAI Server APIs
Importing the models from the OpenAI client library required a
top-level dependency on the openai python package, and also was
incompatible with our API generation code due to some quirks in how
the OpenAI pydantic models are defined.

So, this creates our own stubs of those pydantic models so that we're
in more direct control of our API surface for this OpenAI-compatible
API, so that it works with our code generation, and so that the openai
python client isn't a hard requirement of Llama Stack's API.
2025-04-09 15:47:02 -04:00
..
agents chore: remove unused tempdir in agent (#1896) 2025-04-09 09:43:48 +02:00
datasetio refactor: extract pagination logic into shared helper function (#1770) 2025-03-31 13:08:29 -07:00
eval fix: fix jobs api literal return type (#1757) 2025-03-21 14:04:21 -07:00
inference Use our own pydantic models for OpenAI Server APIs 2025-04-09 15:47:02 -04:00
ios/inference chore: removed executorch submodule (#1265) 2025-02-25 21:57:21 -08:00
post_training refactor: move all llama code to models/llama out of meta reference (#1887) 2025-04-07 15:03:58 -07:00
safety refactor: move all llama code to models/llama out of meta reference (#1887) 2025-04-07 15:03:58 -07:00
scoring fix: a couple of tests were broken and not yet exercised by our per-PR test workflow 2025-03-21 12:12:14 -07:00
telemetry feat: introduce llama4 support (#1877) 2025-04-05 11:53:35 -07:00
tool_runtime fix(api): don't return list for runtime tools (#1686) 2025-04-01 09:53:11 +02:00
vector_io chore: Updating sqlite-vec to make non-blocking calls (#1762) 2025-03-23 17:25:44 -07:00
__init__.py impls -> inline, adapters -> remote (#381) 2024-11-06 14:54:05 -08:00