refactor: extract pagination logic into shared helper function (#1770)

# 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>

llama_stack/apis/datasetio/datasetio.py

@@ -6,23 +6,9 @@
 
 from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
 
-from pydantic import BaseModel
-
+from llama_stack.apis.common.responses import PaginatedResponse
 from llama_stack.apis.datasets import Dataset
-from llama_stack.schema_utils import json_schema_type, webmethod
-
-
-@json_schema_type
-class IterrowsResponse(BaseModel):
-    """
-    A paginated list of rows from a dataset.
-
-    :param data: The rows in the current page.
-    :param next_start_index: Index into dataset for the first row in the next page. None if there are no more rows.
-    """
-
-    data: List[Dict[str, Any]]
-    next_start_index: Optional[int] = None
+from llama_stack.schema_utils import webmethod
 
 
 class DatasetStore(Protocol):
@@ -34,15 +20,22 @@ class DatasetIO(Protocol):
     # keeping for aligning with inference/safety, but this is not used
     dataset_store: DatasetStore
 
-    # TODO(xiyan): there's a flakiness here where setting route to "/datasets/" here will not result in proper routing
     @webmethod(route="/datasetio/iterrows/{dataset_id:path}", method="GET")
     async def iterrows(
         self,
         dataset_id: str,
         start_index: Optional[int] = None,
         limit: Optional[int] = None,
-    ) -> IterrowsResponse:
-        """Get a paginated list of rows from a dataset. Uses cursor-based pagination.
+    ) -> PaginatedResponse:
+        """Get a paginated list of rows from a dataset.
+
+        Uses offset-based pagination where:
+        - start_index: The starting index (0-based). If None, starts from beginning.
+        - limit: Number of items to return. If None or -1, returns all items.
+
+        The response includes:
+        - data: List of items for the current page
+        - has_more: Whether there are more items available after this set
 
         :param dataset_id: The ID of the dataset to get the rows from.
         :param start_index: Index into dataset for the first row to get. Get all rows if None.