phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2025-08-07 11:08:20 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

better test

Browse source
This commit is contained in:
Xi Yan 2025-03-15 16:45:01 -07:00
parent 8afadc6829
commit bb25509c37
3 changed files with 4 additions and 13 deletions
Download patch file Download diff file Expand all files Collapse all files

8
llama_stack/providers/inline/datasetio/localfs/datasetio.py
View file

@ -44,9 +44,7 @@ class PandasDataframeDataset:
elif self.dataset_def.source.type == "rows":
self.df = pandas.DataFrame(self.dataset_def.source.rows)
else:
raise ValueError(
f"Unsupported dataset source type: {self.dataset_def.source.type}"
)
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}")
@ -119,6 +117,4 @@ class LocalFSDatasetIOImpl(DatasetIO, DatasetsProtocolPrivate):
dataset_impl.load()
new_rows_df = pandas.DataFrame(rows)
dataset_impl.df = pandas.concat(
[dataset_impl.df, new_rows_df], ignore_index=True
)
dataset_impl.df = pandas.concat([dataset_impl.df, new_rows_df], ignore_index=True)

1
llama_stack/providers/utils/datasetio/url_utils.py
View file

@ -10,7 +10,6 @@ from urllib.parse import unquote
import pandas
from llama_stack.apis.common.content_types import URL
from llama_stack.providers.utils.memory.vector_store import parse_data_url

8
tests/integration/datasets/test_datasets.py
View file

@ -70,9 +70,7 @@ def data_url_from_file(file_path: str) -> str:
"eval/messages-answer",
{
"type": "uri",
"uri": data_url_from_file(
os.path.join(os.path.dirname(__file__), "test_dataset.csv")
),
"uri": data_url_from_file(os.path.join(os.path.dirname(__file__), "test_dataset.csv")),
},
"localfs",
5,
@ -86,9 +84,7 @@ def test_register_and_iterrows(llama_stack_client, purpose, source, provider_id,
)
assert dataset.identifier is not None
assert dataset.provider_id == provider_id
iterrow_response = llama_stack_client.datasets.iterrows(
dataset.identifier, limit=limit
)
iterrow_response = llama_stack_client.datasets.iterrows(dataset.identifier, limit=limit)
assert len(iterrow_response.data) == limit
dataset_list = llama_stack_client.datasets.list()