mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-06-27 18:50:41 +00:00
43c1f39bd6
# What does this PR do?
This commit significantly improves the environment variable substitution
functionality in Llama Stack configuration files:
* The version field in configuration files has been changed from string
to integer type for better type consistency across build and run
configurations.
* The environment variable substitution system for ${env.FOO:} was fixed
and properly returns an error
* The environment variable substitution system for ${env.FOO+} returns
None instead of an empty strings, it better matches type annotations in
config fields
* The system includes automatic type conversion for boolean, integer,
and float values.
* The error messages have been enhanced to provide clearer guidance when
environment variables are missing, including suggestions for using
default values or conditional syntax.
* Comprehensive documentation has been added to the configuration guide
explaining all supported syntax patterns, best practices, and runtime
override capabilities.
* Multiple provider configurations have been updated to use the new
conditional syntax for optional API keys, making the system more
flexible for different deployment scenarios. The telemetry configuration
has been improved to properly handle optional endpoints with appropriate
validation, ensuring that required endpoints are specified when their
corresponding sinks are enabled.
* There were many instances of ${env.NVIDIA_API_KEY:} that should have
caused the code to fail. However, due to a bug, the distro server was
still being started, and early validation wasn’t triggered. As a result,
failures were likely being handled downstream by the providers. I’ve
maintained similar behavior by using ${env.NVIDIA_API_KEY:+}, though I
believe this is incorrect for many configurations. I’ll leave it to each
provider to correct it as needed.
* Environment variable substitution now uses the same syntax as Bash
parameter expansion.
Signed-off-by: Sébastien Han <seb@redhat.com>
|
||
|---|---|---|
| .. | ||
| __init__.py | ||
| config.py | ||
| datasetio.py | ||
| README.md | ||
NVIDIA DatasetIO Provider for LlamaStack
This provider enables dataset management using NVIDIA's NeMo Customizer service.
Features
- Register datasets for fine-tuning LLMs
- Unregister datasets
Getting Started
Prerequisites
- LlamaStack with NVIDIA configuration
- Access to Hosted NVIDIA NeMo Microservice
- API key for authentication with the NVIDIA service
Setup
Build the NVIDIA environment:
llama stack build --template nvidia --image-type conda
Basic Usage using the LlamaStack Python Client
Initialize the client
import os
os.environ["NVIDIA_API_KEY"] = "your-api-key"
os.environ["NVIDIA_CUSTOMIZER_URL"] = "http://nemo.test"
os.environ["NVIDIA_DATASET_NAMESPACE"] = "default"
os.environ["NVIDIA_PROJECT_ID"] = "test-project"
from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
client = LlamaStackAsLibraryClient("nvidia")
client.initialize()
Register a dataset
client.datasets.register(
purpose="post-training/messages",
dataset_id="my-training-dataset",
source={"type": "uri", "uri": "hf://datasets/default/sample-dataset"},
metadata={
"format": "json",
"description": "Dataset for LLM fine-tuning",
"provider": "nvidia",
},
)
Get a list of all registered datasets
datasets = client.datasets.list()
for dataset in datasets:
print(f"Dataset ID: {dataset.identifier}")
print(f"Description: {dataset.metadata.get('description', '')}")
print(f"Source: {dataset.source.uri}")
print("---")
Unregister a dataset
client.datasets.unregister(dataset_id="my-training-dataset")