chore(api): add mypy coverage to localfs

Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>

llama_stack/providers/inline/datasetio/localfs/datasetio.py

@@ -12,7 +12,7 @@ from llama_stack.apis.datasetio import DatasetIO
 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_uri
-from llama_stack.providers.utils.kvstore import kvstore_impl
+from llama_stack.providers.utils.kvstore import KVStore, kvstore_impl
 from llama_stack.providers.utils.pagination import paginate_records
 
 from .config import LocalFSDatasetIOConfig
@@ -27,11 +27,13 @@ class PandasDataframeDataset:
         self.df = None
 
     def __len__(self) -> int:
-        assert self.df is not None, "Dataset not loaded. Please call .load() first"
+        if self.df is None:
+            raise RuntimeError("Dataset not loaded. Please call .load() first")
         return len(self.df)
 
     def __getitem__(self, idx):
-        assert self.df is not None, "Dataset not loaded. Please call .load() first"
+        if self.df is None:
+            raise RuntimeError("Dataset not loaded. Please call .load() first")
         if isinstance(idx, slice):
             return self.df.iloc[idx].to_dict(orient="records")
         else:
@@ -49,15 +51,27 @@ class PandasDataframeDataset:
             raise ValueError(f"Unsupported dataset source type: {self.dataset_def.source.type}")
 
         if self.df is None:
-            raise ValueError(f"Failed to load dataset from {self.dataset_def.url}")
+            if self.dataset_def.source.type == "uri":
+                raise ValueError(f"Failed to load dataset from {self.dataset_def.source.uri}")
+            else:
+                raise ValueError("Failed to load dataset from rows")
+
+
+class DatasetStore:
+    def __init__(self, dataset_infos: dict[str, Dataset]) -> None:
+        self.dataset_infos = dataset_infos
+
+    def get_dataset(self, dataset_id: str) -> Dataset:
+        return self.dataset_infos[dataset_id]
 
 
 class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
     def __init__(self, config: LocalFSDatasetIOConfig) -> None:
         self.config = config
         # local registry for keeping track of datasets within the provider
-        self.dataset_infos = {}
-        self.kvstore = None
+        self.dataset_infos: dict[str, Dataset] = {}
+        self.kvstore: KVStore | None = None
+        self.dataset_store = DatasetStore(self.dataset_infos)
 
     async def initialize(self) -> None:
         self.kvstore = await kvstore_impl(self.config.kvstore)
@@ -66,8 +80,8 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
         end_key = f"{DATASETS_PREFIX}\xff"
         stored_datasets = await self.kvstore.values_in_range(start_key, end_key)
 
-        for dataset in stored_datasets:
-            dataset = Dataset.model_validate_json(dataset)
+        for dataset_json in stored_datasets:
+            dataset = Dataset.model_validate_json(dataset_json)
             self.dataset_infos[dataset.identifier] = dataset
 
     async def shutdown(self) -> None: ...
@@ -78,6 +92,8 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
     ) -> None:
         # Store in kvstore
         key = f"{DATASETS_PREFIX}{dataset_def.identifier}"
+        if self.kvstore is None:
+            raise RuntimeError("KVStore not initialized. Please call initialize() first")
         await self.kvstore.set(
             key=key,
             value=dataset_def.model_dump_json(),
@@ -86,6 +102,8 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
 
     async def unregister_dataset(self, dataset_id: str) -> None:
         key = f"{DATASETS_PREFIX}{dataset_id}"
+        if self.kvstore is None:
+            raise RuntimeError("KVStore not initialized. Please call initialize() first")
         await self.kvstore.delete(key=key)
         del self.dataset_infos[dataset_id]
 
@@ -99,6 +117,8 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
         dataset_impl = PandasDataframeDataset(dataset_def)
         await dataset_impl.load()
 
+        if dataset_impl.df is None:
+            raise RuntimeError("Failed to load dataset dataframe")
         records = dataset_impl.df.to_dict("records")
         return paginate_records(records, start_index, limit)
 
@@ -108,4 +128,6 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
         await dataset_impl.load()
 
         new_rows_df = pandas.DataFrame(rows)
+        if dataset_impl.df is None:
+            raise RuntimeError("Failed to load dataset dataframe")
         dataset_impl.df = pandas.concat([dataset_impl.df, new_rows_df], ignore_index=True)

pyproject.toml

@@ -245,7 +245,7 @@ exclude = [
     "^llama_stack/providers/inline/agents/meta_reference/",
     "^llama_stack/providers/inline/agents/meta_reference/agent_instance\\.py$",
     "^llama_stack/providers/inline/agents/meta_reference/agents\\.py$",
-    "^llama_stack/providers/inline/datasetio/localfs/",
+    "^llama_stack/providers/inline/agents/meta_reference/safety\\.py$",
     "^llama_stack/providers/inline/eval/meta_reference/eval\\.py$",
     "^llama_stack/providers/inline/inference/meta_reference/inference\\.py$",
     "^llama_stack/models/llama/llama3/generation\\.py$",