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refactor: extract pagination logic into shared helper function

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Move pagination logic from LocalFS and HuggingFace implementations into
a common helper function to ensure consistent pagination behavior across
providers. This reduces code duplication and centralizes pagination
logic in one place.

Signed-off-by: Sébastien Han <seb@redhat.com>
This commit is contained in:
Sébastien Han 2025-03-24 17:49:19 +01:00
parent 9b478f3756
commit 8e15e3c1b8
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9 changed files with 130 additions and 73 deletions
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21
llama_stack/providers/inline/datasetio/localfs/datasetio.py
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@ -7,9 +7,11 @@ from typing import Any, Dict, List, Optional
import pandas
from llama_stack.apis.datasetio import DatasetIO, IterrowsResponse
from llama_stack.apis.common.responses import PaginatedResponse
from llama_stack.apis.datasetio import DatasetIO
from llama_stack.apis.datasets import Dataset
from llama_stack.providers.datatypes import DatasetsProtocolPrivate
from llama_stack.providers.utils.datasetio.pagination import paginate_records
from llama_stack.providers.utils.datasetio.url_utils import get_dataframe_from_uri
from llama_stack.providers.utils.kvstore import kvstore_impl
@ -92,24 +94,13 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
dataset_id: str,
start_index: Optional[int] = None,
limit: Optional[int] = None,
) -> IterrowsResponse:
) -> PaginatedResponse:
dataset_def = self.dataset_infos[dataset_id]
dataset_impl = PandasDataframeDataset(dataset_def)
await dataset_impl.load()
start_index = start_index or 0
if limit is None or limit == -1:
end = len(dataset_impl)
else:
end = min(start_index + limit, len(dataset_impl))
rows = dataset_impl[start_index:end]
return IterrowsResponse(
data=rows,
next_start_index=end if end < len(dataset_impl) else None,
)
records = dataset_impl.df.to_dict("records")
return paginate_records(records, start_index, limit)
async def append_rows(self, dataset_id: str, rows: List[Dict[str, Any]]) -> None:
dataset_def = self.dataset_infos[dataset_id]