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# What does this PR do? 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. ## Test Plan Run this script: ``` from llama_stack_client import LlamaStackClient # Initialize the client client = LlamaStackClient(base_url="http://localhost:8321") # Register a dataset response = client.datasets.register( purpose="eval/messages-answer", # or "eval/question-answer" or "post-training/messages" source={"type": "uri", "uri": "huggingface://datasets/llamastack/simpleqa?split=train"}, dataset_id="my_dataset", # optional, will be auto-generated if not provided metadata={"description": "My evaluation dataset"}, # optional ) # Verify the dataset was registered by listing all datasets datasets = client.datasets.list() print(f"Registered datasets: {[d.identifier for d in datasets]}") # You can then access the data using the datasetio API # rows = client.datasets.iterrows(dataset_id="my_dataset", start_index=1, limit=2) rows = client.datasets.iterrows(dataset_id="my_dataset") print(f"Data: {rows.data}") ``` And play with `start_index` and `limit`. [//]: # (## Documentation) Signed-off-by: Sébastien Han <seb@redhat.com>
23 lines
636 B
Python
23 lines
636 B
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
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from pydantic import BaseModel
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from llama_stack.schema_utils import json_schema_type
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@json_schema_type
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class PaginatedResponse(BaseModel):
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"""A generic paginated response that follows a simple format.
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:param data: The list of items for the current page
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:param has_more: Whether there are more items available after this set
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"""
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data: List[Dict[str, Any]]
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has_more: bool
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