forked from phoenix-oss/llama-stack-mirror
e6bbf8d20b
# What does this PR do? Implemetation of NeMO Datastore register, unregister API. Open Issues: - provider_id gets set to `localfs` in client.datasets.register() as it is specified in routing_tables.py: DatasetsRoutingTable see: #1860 Currently I have passed `"provider_id":"nvidia"` in metadata and have parsed that in `DatasetsRoutingTable` (Not the best approach, but just a quick workaround to make it work for now.) ## Test Plan - Unit test cases: `pytest tests/unit/providers/nvidia/test_datastore.py` ```bash ========================================================== test session starts =========================================================== platform linux -- Python 3.10.0, pytest-8.3.5, pluggy-1.5.0 rootdir: /home/ubuntu/llama-stack configfile: pyproject.toml plugins: anyio-4.9.0, asyncio-0.26.0, nbval-0.11.0, metadata-3.1.1, html-4.1.1, cov-6.1.0 asyncio: mode=strict, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function collected 2 items tests/unit/providers/nvidia/test_datastore.py .. [100%] ============================================================ warnings summary ============================================================ ====================================================== 2 passed, 1 warning in 0.84s ====================================================== ``` cc: @dglogo, @mattf, @yanxi0830
26 lines
537 B
YAML
26 lines
537 B
YAML
version: '2'
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distribution_spec:
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description: Use NVIDIA NIM for running LLM inference, evaluation and safety
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providers:
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inference:
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- remote::nvidia
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vector_io:
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- inline::faiss
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safety:
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- remote::nvidia
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agents:
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- inline::meta-reference
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telemetry:
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- inline::meta-reference
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eval:
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- remote::nvidia
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post_training:
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- remote::nvidia
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datasetio:
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- inline::localfs
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- remote::nvidia
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scoring:
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- inline::basic
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tool_runtime:
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- inline::rag-runtime
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image_type: conda
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