llama-stack-mirror/llama_stack/providers/remote/inference/nvidia
Charlie Doern 41431d8bdd refactor: convert providers to be installed via package
currently providers have a `pip_package` list. Rather than make our own form of python dependency management, we should use `pyproject.toml` files in each provider declaring the dependencies in a more trackable manner.
Each provider can then be installed using the already in place `module` field in the ProviderSpec, pointing to the directory the provider lives in
we can then simply `uv pip install` this directory as opposed to installing the dependencies one by one

Signed-off-by: Charlie Doern <cdoern@redhat.com>
2025-09-22 09:23:50 -04:00
..
__init__.py add NVIDIA NIM inference adapter (#355) 2024-11-23 15:59:00 -08:00
config.py fix: allow default empty vars for conditionals (#2570) 2025-07-01 14:42:05 +02:00
models.py docs: add VLM NIM example (#3277) 2025-08-29 16:23:52 -07:00
NVIDIA.md docs: add VLM NIM example (#3277) 2025-08-29 16:23:52 -07:00
nvidia.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00
openai_utils.py chore: enable pyupgrade fixes (#1806) 2025-05-01 14:23:50 -07:00
pyproject.toml refactor: convert providers to be installed via package 2025-09-22 09:23:50 -04:00
utils.py refactor(logging): rename llama_stack logger categories (#3065) 2025-08-21 17:31:04 -07:00