fix: retry on HF Failure

HF Datasets downloads can fail due to ratelimits, if any of the following:

                FileNotFoundError,
                RepositoryNotFoundError,
                EntryNotFoundError,
                RevisionNotFoundError,
                GatedRepoError,

are raised, retry. These are the exceptions the downloader catches and raises on failures.

Signed-off-by: Charlie Doern <cdoern@redhat.com>

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

@@ -3,14 +3,17 @@
 #
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
+import time
 from typing import Any
 from urllib.parse import parse_qs, urlparse
 
 import datasets as hf_datasets
+from huggingface_hub.utils import EntryNotFoundError, GatedRepoError, RepositoryNotFoundError, RevisionNotFoundError
 
 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.log import get_logger
 from llama_stack.providers.datatypes import DatasetsProtocolPrivate
 from llama_stack.providers.utils.kvstore import kvstore_impl
 from llama_stack.providers.utils.pagination import paginate_records
@@ -18,6 +21,10 @@ from llama_stack.providers.utils.pagination import paginate_records
 from .config import HuggingfaceDatasetIOConfig
 
 DATASETS_PREFIX = "datasets:"
+MAX_RETRIES = 3
+RETRY_DELAY = 5
+
+logger = get_logger(name=__name__, category="datasets")
 
 
 def parse_hf_params(dataset_def: Dataset):
@@ -75,10 +82,24 @@ class HuggingfaceDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
     ) -> PaginatedResponse:
         dataset_def = self.dataset_infos[dataset_id]
         path, params = parse_hf_params(dataset_def)
-        loaded_dataset = hf_datasets.load_dataset(path, **params)
+        for attempt in range(1, MAX_RETRIES + 1):
-
+            try:
-        records = [loaded_dataset[i] for i in range(len(loaded_dataset))]
+                loaded_dataset = hf_datasets.load_dataset(path, **params)
-        return paginate_records(records, start_index, limit)
+                records = [loaded_dataset[i] for i in range(len(loaded_dataset))]
+                return paginate_records(records, start_index, limit)
+            except (
+                FileNotFoundError,
+                RepositoryNotFoundError,
+                EntryNotFoundError,
+                RevisionNotFoundError,
+                GatedRepoError,
+            ) as e:
+                if attempt == MAX_RETRIES:
+                    raise  # Re-raise the last exception
+                logger.error(
+                    f"Attempt {attempt} to download HF Dataset failed with error: {e}. Retrying in {RETRY_DELAY} seconds..."
+                )
+                time.sleep(RETRY_DELAY)
 
     async def append_rows(self, dataset_id: str, rows: list[dict[str, Any]]) -> None:
         dataset_def = self.dataset_infos[dataset_id]