forked from phoenix-oss/llama-stack-mirror
53 lines
1.7 KiB
Python
53 lines
1.7 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, Protocol, runtime_checkable
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from pydantic import BaseModel
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from llama_stack.apis.datasets import Dataset
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from llama_stack.schema_utils import json_schema_type, webmethod
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@json_schema_type
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class IterrowsResponse(BaseModel):
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"""
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A paginated list of rows from a dataset.
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:param data: The rows in the current page.
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:param next_index: Index into dataset for the first row in the next page. None if there are no more rows.
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"""
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data: List[Dict[str, Any]]
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next_index: Optional[int] = None
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class DatasetStore(Protocol):
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def get_dataset(self, dataset_id: str) -> Dataset: ...
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@runtime_checkable
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class DatasetIO(Protocol):
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# keeping for aligning with inference/safety, but this is not used
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dataset_store: DatasetStore
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@webmethod(route="/datasets/{dataset_id}/iterrows", method="GET")
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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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) -> IterrowsResponse:
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"""Get a paginated list of rows from a dataset. Uses cursor-based pagination.
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:param dataset_id: The ID of the dataset to get the rows from.
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:param start_index: Index into dataset for the first row to get. Get all rows if None.
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:param limit: The number of rows to get per page.
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"""
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...
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@webmethod(route="/datasets/{dataset_id}/append-rows", method="POST")
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async def append_rows(self, dataset_id: str, rows: List[Dict[str, Any]]) -> None: ...
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