forked from phoenix-oss/llama-stack-mirror
9e6561a1ec
# What does this PR do? The goal of this PR is code base modernization. Schema reflection code needed a minor adjustment to handle UnionTypes and collections.abc.AsyncIterator. (Both are preferred for latest Python releases.) Note to reviewers: almost all changes here are automatically generated by pyupgrade. Some additional unused imports were cleaned up. The only change worth of note can be found under `docs/openapi_generator` and `llama_stack/strong_typing/schema.py` where reflection code was updated to deal with "newer" types. Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
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
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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: dict[str, Any] | None = None,
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params: dict[str, Any] | None = None,
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json: dict[str, Any] | None = 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: str | None = None,
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provider_id: str | None = None,
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metadata: dict[str, Any] | None = 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: int | None = None,
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limit: int | None = 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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