huggingface provider

llama_stack/providers/inline/huggingface/datasetio/__init__.py

@@ -0,0 +1,18 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .config import HuggingfaceDatasetIOConfig
+
+
+async def get_provider_impl(
+    config: HuggingfaceDatasetIOConfig,
+    _deps,
+):
+    from .huggingface import HuggingfaceDatasetIOImpl
+
+    impl = HuggingfaceDatasetIOImpl(config)
+    await impl.initialize()
+    return impl

llama_stack/providers/inline/huggingface/datasetio/config.py

@@ -0,0 +1,9 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+from llama_stack.apis.datasetio import *  # noqa: F401, F403
+
+
+class HuggingfaceDatasetIOConfig(BaseModel): ...

llama_stack/providers/inline/huggingface/datasetio/huggingface.py

@@ -0,0 +1,82 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+from typing import List, Optional
+
+from llama_models.llama3.api.datatypes import *  # noqa: F403
+
+from llama_stack.apis.datasetio import *  # noqa: F403
+
+from datasets import load_dataset
+
+from llama_stack.apis.common.type_system import StringType
+from llama_stack.providers.datatypes import DatasetsProtocolPrivate
+
+from .config import HuggingfaceDatasetIOConfig
+
+
+class HuggingfaceDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
+    def __init__(self, config: HuggingfaceDatasetIOConfig) -> None:
+        self.config = config
+        # local registry for keeping track of datasets within the provider
+        self.dataset_infos = {}
+
+    async def initialize(self) -> None:
+        # pre-registered benchmark datasets
+        self.dataset_infos = {
+            "mmlu": DatasetDef(
+                identifier="mmlu",
+                url=URL(uri="https://huggingface.co/datasets/yanxi0830/ls-mmlu"),
+                dataset_schema={
+                    "expected_answer": StringType(),
+                    "input_query": StringType(),
+                    "generated_answer": StringType(),
+                },
+                metadata={"path": "yanxi0830/ls-mmlu", "split": "train"},
+            )
+        }
+
+    async def shutdown(self) -> None: ...
+
+    async def register_dataset(
+        self,
+        dataset_def: DatasetDef,
+    ) -> None:
+        self.dataset_infos[dataset_def.identifier] = dataset_def
+
+    async def list_datasets(self) -> List[DatasetDef]:
+        return list(self.dataset_infos.values())
+
+    async def get_rows_paginated(
+        self,
+        dataset_id: str,
+        rows_in_page: int,
+        page_token: Optional[str] = None,
+        filter_condition: Optional[str] = None,
+    ) -> PaginatedRowsResult:
+        dataset_def = self.dataset_infos[dataset_id]
+        loaded_dataset = load_dataset(**dataset_def.metadata)
+
+        if page_token and not page_token.isnumeric():
+            raise ValueError("Invalid page_token")
+
+        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:
+            end = len(loaded_dataset)
+        else:
+            end = min(start + rows_in_page, len(loaded_dataset))
+
+        rows = [loaded_dataset[i] for i in range(start, end)]
+
+        return PaginatedRowsResult(
+            rows=rows,
+            total_count=len(rows),
+            next_page_token=str(end),
+        )

llama_stack/providers/registry/datasetio.py

@@ -19,4 +19,12 @@ def available_providers() -> List[ProviderSpec]:
             config_class="llama_stack.providers.inline.meta_reference.datasetio.MetaReferenceDatasetIOConfig",
             api_dependencies=[],
         ),
+        InlineProviderSpec(
+            api=Api.datasetio,
+            provider_type="huggingface",
+            pip_packages=["datasets"],
+            module="llama_stack.providers.inline.huggingface.datasetio",
+            config_class="llama_stack.providers.inline.huggingface.datasetio.HuggingfaceDatasetIOConfig",
+            api_dependencies=[],
+        ),
     ]