feat(dataset api): (1.4/n) fix resolver signature mismatch (#1658)

# What does this PR do?
- fix datasets api signature mis-match so that llama stack run can start

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
```
llama stack run
```
<img width="626" alt="image"
src="https://github.com/user-attachments/assets/59072d1a-ccb6-453a-80e8-d87419896c41"
/>


[//]: # (## Documentation)

llama_stack/providers/remote/datasetio/huggingface/huggingface.py

@@ -7,7 +7,7 @@ from typing import Any, Dict, List, Optional
 
 import datasets as hf_datasets
 
-from llama_stack.apis.datasetio import DatasetIO, PaginatedRowsResult
+from llama_stack.apis.datasetio import DatasetIO, IterrowsResponse
 from llama_stack.apis.datasets import Dataset
 from llama_stack.providers.datatypes import DatasetsProtocolPrivate
 from llama_stack.providers.utils.datasetio.url_utils import get_dataframe_from_url
@@ -73,36 +73,27 @@ class HuggingfaceDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
         await self.kvstore.delete(key=key)
         del self.dataset_infos[dataset_id]
 
-    async def get_rows_paginated(
+    async def iterrows(
         self,
         dataset_id: str,
-        rows_in_page: int,
-        page_token: Optional[str] = None,
-        filter_condition: Optional[str] = None,
-    ) -> PaginatedRowsResult:
+        start_index: Optional[int] = None,
+        limit: Optional[int] = None,
+    ) -> IterrowsResponse:
         dataset_def = self.dataset_infos[dataset_id]
         loaded_dataset = load_hf_dataset(dataset_def)
 
-        if page_token and not page_token.isnumeric():
-            raise ValueError("Invalid page_token")
+        start_index = start_index or 0
 
-        if page_token is None or len(page_token) == 0:
-            next_page_token = 0
-        else:
-            next_page_token = int(page_token)
-
-        start = next_page_token
-        if rows_in_page == -1:
+        if limit is None or limit == -1:
             end = len(loaded_dataset)
         else:
-            end = min(start + rows_in_page, len(loaded_dataset))
+            end = min(start_index + limit, len(loaded_dataset))
 
-        rows = [loaded_dataset[i] for i in range(start, end)]
+        rows = [loaded_dataset[i] for i in range(start_index, end)]
 
-        return PaginatedRowsResult(
-            rows=rows,
-            total_count=len(rows),
-            next_page_token=str(end),
+        return IterrowsResponse(
+            data=rows,
+            next_index=end if end < len(loaded_dataset) else None,
         )
 
     async def append_rows(self, dataset_id: str, rows: List[Dict[str, Any]]) -> None: