Commit graph

9 commits

Author SHA1 Message Date
Ben Browning
94fcfb5674
fix: broken links on nvidia distro docs when rendered (#2446)
# What does this PR do?

The Nvidia distribution docs had some broken links when viewing the
rendered docs site, where the deep links they were attempting into our
code on GitHub weren't actually getting users to the intended
destination.

This updates those links to use the `{repopath}` helper we use elsewhere
to generate valid deep links into the Llama Stack repository.

## Test Plan

I generated the site locally after this change and ensured the links now
resolve to their intended destination.

Signed-off-by: Ben Browning <bbrownin@redhat.com>
2025-06-17 13:02:13 +05:30
Jash Gulabrai
40e2c97915
feat: Add Nvidia e2e beginner notebook and tool calling notebook (#1964)
# What does this PR do?
This PR contains two sets of notebooks that serve as reference material
for developers getting started with Llama Stack using the NVIDIA
Provider. Developers should be able to execute these notebooks
end-to-end, pointing to their NeMo Microservices deployment.
1. `beginner_e2e/`: Notebook that walks through a beginner end-to-end
workflow that covers creating datasets, running inference, customizing
and evaluating models, and running safety checks.
2. `tool_calling/`: Notebook that is ported over from the [Data Flywheel
& Tool Calling
notebook](https://github.com/NVIDIA/GenerativeAIExamples/tree/main/nemo/data-flywheel)
that is referenced in the NeMo Microservices docs. I updated the
notebook to use the Llama Stack client wherever possible, and added
relevant instructions.

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
- Both notebook folders contain READMEs with pre-requisites. To manually
test these notebooks, you'll need to have a deployment of the NeMo
Microservices Platform and update the `config.py` file with your
deployment's information.
- I've run through these notebooks manually end-to-end to verify each
step works.

[//]: # (## Documentation)

---------

Co-authored-by: Jash Gulabrai <jgulabrai@nvidia.com>
2025-06-16 11:29:01 -04:00
Charlie Doern
1ae61e8d5f
fix: replace all instances of --yaml-config with --config (#2196)
# What does this PR do?

start_stack.sh was using --yaml-config which is deprecated.

a bunch of distro docs also mentioned --yaml-config. Replaces all
instances and logic for --yaml-config with --config

resolves #2189

Signed-off-by: Charlie Doern <cdoern@redhat.com>
2025-05-16 14:31:12 -07:00
Jash Gulabrai
0d06c654d0
feat: Update NVIDIA to GA docs; remove notebook reference until ready (#1999)
# What does this PR do?
- Update NVIDIA documentation links to GA docs
- Remove reference to notebooks until merged

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]

[//]: # (## Documentation)

Co-authored-by: Jash Gulabrai <jgulabrai@nvidia.com>
2025-04-18 19:13:18 -04:00
Jash Gulabrai
2ae1d7f4e6
docs: Add NVIDIA platform distro docs (#1971)
# What does this PR do?
Add NVIDIA platform docs that serve as a starting point for Llama Stack
users and explains all supported microservices.

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
[Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.*]

[//]: # (## Documentation)

---------

Co-authored-by: Jash Gulabrai <jgulabrai@nvidia.com>
2025-04-17 05:54:30 -07:00
Hardik Shah
127bac6869
fix: Default to port 8321 everywhere (#1734)
As titled, moved all instances of 5001 to 8321
2025-03-20 15:50:41 -07:00
Hardik Shah
581e8ae562
fix: docker run with --pull always to fetch the latest image (#1733)
As titled
2025-03-20 15:35:48 -07:00
Ashwin Bharambe
04de2f84e9
fix: register provider model name and HF alias in run.yaml (#1304)
Each model known to the system has two identifiers: 

- the `provider_resource_id` (what the provider calls it) -- e.g.,
`accounts/fireworks/models/llama-v3p1-8b-instruct`
- the `identifier` (`model_id`) under which it is registered and gets
routed to the appropriate provider.

We have so far used the HuggingFace repo alias as the standardized
identifier you can use to refer to the model. So in the above example,
we'd use `meta-llama/Llama-3.1-8B-Instruct` as the name under which it
gets registered. This makes it convenient for users to refer to these
models across providers.

However, we forgot to register the _actual_ provider model ID also. You
should be able to route via `provider_resource_id` also, of course.

This change fixes this (somewhat grave) omission.

*Note*: this change is additive -- more aliases work now compared to
before.

## Test Plan

Run the following for distro=(ollama fireworks together)
```
LLAMA_STACK_CONFIG=$distro \
   pytest -s -v tests/client-sdk/inference/test_text_inference.py \
   --inference-model=meta-llama/Llama-3.1-8B-Instruct --vision-inference-model=""
```
2025-02-27 16:39:23 -08:00
cdgamarose-nv
b3202bcf77
add nvidia distribution (#565)
# What does this PR do?

adds nvidia template for creating a distribution using inference adapter
for NVIDIA NIMs.

## Test Plan

Please describe:
Build llama stack distribution for nvidia using the template, docker and
conda.
```bash
(.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client configure --endpoint http://localhost:5000
Done! You can now use the Llama Stack Client CLI with endpoint http://localhost:5000
(.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client models list
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┓
┃ identifier                       ┃ provider_id ┃ provider_resource_id       ┃ metadata ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━┩
│ Llama3.1-8B-Instruct             │ nvidia      │ meta/llama-3.1-8b-instruct │ {}       │
│ meta-llama/Llama-3.2-3B-Instruct │ nvidia      │ meta/llama-3.2-3b-instruct │ {}       │
└──────────────────────────────────┴─────────────┴────────────────────────────┴──────────┘
(.venv) local-cdgamarose@a4u8g-0006:~/llama-stack$ llama-stack-client inference chat-completion --message "hello, write me a 2 sentence poem"
ChatCompletionResponse(
    completion_message=CompletionMessage(
        content='Here is a 2 sentence poem:\n\nThe sun sets slow and paints the sky, \nA gentle hue of pink that makes me sigh.',
        role='assistant',
        stop_reason='end_of_turn',
        tool_calls=[]
    ),
    logprobs=None
)
```

## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Ran pre-commit to handle lint / formatting issues.
- [x] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [x] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.

---------

Co-authored-by: Matthew Farrellee <matt@cs.wisc.edu>
2025-01-15 14:04:43 -08:00