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
112 lines
3.7 KiB
Python
112 lines
3.7 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from typing import Any, Dict, List, Optional
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import aiohttp
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from llama_stack.apis.common.content_types import URL
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from llama_stack.apis.common.responses import PaginatedResponse
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from llama_stack.apis.common.type_system import ParamType
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from llama_stack.apis.datasets import Dataset
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from .config import NvidiaDatasetIOConfig
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class NvidiaDatasetIOAdapter:
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"""Nvidia NeMo DatasetIO API."""
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def __init__(self, config: NvidiaDatasetIOConfig):
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self.config = config
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self.headers = {}
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async def _make_request(
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self,
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method: str,
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path: str,
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headers: Optional[Dict[str, Any]] = None,
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params: Optional[Dict[str, Any]] = None,
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json: Optional[Dict[str, Any]] = None,
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**kwargs,
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) -> Dict[str, Any]:
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"""Helper method to make HTTP requests to the Customizer API."""
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url = f"{self.config.datasets_url}{path}"
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request_headers = self.headers.copy()
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if headers:
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request_headers.update(headers)
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async with aiohttp.ClientSession(headers=request_headers) as session:
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async with session.request(method, url, params=params, json=json, **kwargs) as response:
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if response.status != 200:
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error_data = await response.json()
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raise Exception(f"API request failed: {error_data}")
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return await response.json()
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async def register_dataset(
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self,
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dataset_def: Dataset,
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) -> Dataset:
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"""Register a new dataset.
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Args:
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dataset_def [Dataset]: The dataset definition.
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dataset_id [str]: The ID of the dataset.
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source [DataSource]: The source of the dataset.
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metadata [Dict[str, Any]]: The metadata of the dataset.
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format [str]: The format of the dataset.
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description [str]: The description of the dataset.
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Returns:
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Dataset
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"""
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## add warnings for unsupported params
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request_body = {
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"name": dataset_def.identifier,
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"namespace": self.config.dataset_namespace,
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"files_url": dataset_def.source.uri,
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"project": self.config.project_id,
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}
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if dataset_def.metadata:
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request_body["format"] = dataset_def.metadata.get("format")
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request_body["description"] = dataset_def.metadata.get("description")
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await self._make_request(
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"POST",
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"/v1/datasets",
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json=request_body,
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)
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return dataset_def
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async def update_dataset(
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self,
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dataset_id: str,
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dataset_schema: Dict[str, ParamType],
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url: URL,
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provider_dataset_id: Optional[str] = None,
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provider_id: Optional[str] = None,
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metadata: Optional[Dict[str, Any]] = None,
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) -> None:
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raise NotImplementedError("Not implemented")
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async def unregister_dataset(
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self,
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dataset_id: str,
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) -> None:
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await self._make_request(
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"DELETE",
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f"/v1/datasets/{self.config.dataset_namespace}/{dataset_id}",
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headers={"Accept": "application/json", "Content-Type": "application/json"},
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)
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async def iterrows(
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self,
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dataset_id: str,
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start_index: Optional[int] = None,
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limit: Optional[int] = None,
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) -> PaginatedResponse:
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raise NotImplementedError("Not implemented")
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async def append_rows(self, dataset_id: str, rows: List[Dict[str, Any]]) -> None:
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raise NotImplementedError("Not implemented")
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