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# 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> |
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.. | ||
__init__.py | ||
config.py | ||
eval.py | ||
README.md |
NVIDIA NeMo Evaluator Eval Provider
Overview
For the first integration, Benchmarks are mapped to Evaluation Configs on in the NeMo Evaluator. The full evaluation config object is provided as part of the meta-data. The dataset_id
and scoring_functions
are not used.
Below are a few examples of how to register a benchmark, which in turn will create an evaluation config in NeMo Evaluator and how to trigger an evaluation.
Example for register an academic benchmark
POST /eval/benchmarks
{
"benchmark_id": "mmlu",
"dataset_id": "",
"scoring_functions": [],
"metadata": {
"type": "mmlu"
}
}
Example for register a custom evaluation
POST /eval/benchmarks
{
"benchmark_id": "my-custom-benchmark",
"dataset_id": "",
"scoring_functions": [],
"metadata": {
"type": "custom",
"params": {
"parallelism": 8
},
"tasks": {
"qa": {
"type": "completion",
"params": {
"template": {
"prompt": "{{prompt}}",
"max_tokens": 200
}
},
"dataset": {
"files_url": "hf://datasets/default/sample-basic-test/testing/testing.jsonl"
},
"metrics": {
"bleu": {
"type": "bleu",
"params": {
"references": [
"{{ideal_response}}"
]
}
}
}
}
}
}
}
Example for triggering a benchmark/custom evaluation
POST /eval/benchmarks/{benchmark_id}/jobs
{
"benchmark_id": "my-custom-benchmark",
"benchmark_config": {
"eval_candidate": {
"type": "model",
"model": "meta-llama/Llama3.1-8B-Instruct",
"sampling_params": {
"max_tokens": 100,
"temperature": 0.7
}
},
"scoring_params": {}
}
}
Response example:
{
"job_id": "eval-1234",
"status": "in_progress"
}
Example for getting the status of a job
GET /eval/benchmarks/{benchmark_id}/jobs/{job_id}
Response example:
{
"job_id": "eval-1234",
"status": "in_progress"
}
Example for cancelling a job
POST /eval/benchmarks/{benchmark_id}/jobs/{job_id}/cancel
Example for getting the results
GET /eval/benchmarks/{benchmark_id}/results
{
"generations": [],
"scores": {
"{benchmark_id}": {
"score_rows": [],
"aggregated_results": {
"tasks": {},
"groups": {}
}
}
}
}