dataset validation

llama_stack/providers/impls/meta_reference/datasetio/datasetio.py

@@ -62,10 +62,15 @@ class PandasDataframeDataset(BaseDataset):
         if self.df is None:
             self.load()
 
-        print(self.dataset_def.dataset_schema)
+        assert self.df is not None, "Dataset loading failed. Please check logs."
-        # get columns names
+
-        # columns = self.df[self.dataset_def.dataset_schema.keys()]
+        self.df = self.df[self.dataset_def.dataset_schema.keys()]
-        print(self.df.columns)
+
+        # check all columns in dataset schema are present
+        assert len(self.df.columns) == len(self.dataset_def.dataset_schema)
+
+        # check all types match
+        print(self.df.dtypes)
 
     def load(self) -> None:
         if self.df is not None:

llama_stack/providers/tests/datasetio/test_dataset.csv

@@ -0,0 +1,6 @@
+input_query,generated_answer,expected_answer
+What is the capital of France?,London,Paris
+Who is the CEO of Meta?,Mark Zuckerberg,Mark Zuckerberg
+What is the largest planet in our solar system?,Jupiter,Jupiter
+What is the smallest country in the world?,China,Vatican City
+What is the currency of Japan?,Yen,Yen

llama_stack/providers/tests/datasetio/test_dataset.jsonl

@@ -1,5 +0,0 @@
-{"input_query": "What is the capital of France?", "generated_answer": "London", "expected_answer": "Paris"}
-{"input_query": "Who is the CEO of Meta?", "generated_answer": "Mark Zuckerberg", "expected_answer": "Mark Zuckerberg"}
-{"input_query": "What is the largest planet in our solar system?", "generated_answer": "Jupiter", "expected_answer": "Jupiter"}
-{"input_query": "What is the smallest country in the world?", "generated_answer": "China", "expected_answer": "Vatican City"}
-{"input_query": "What is the currency of Japan?", "generated_answer": "Yen", "expected_answer": "Yen"}

llama_stack/providers/tests/datasetio/test_datasetio.py

@@ -63,25 +63,13 @@ def data_url_from_file(file_path: str) -> str:
 
 
 async def register_dataset(datasets_impl: Datasets):
+    test_file = Path(os.path.abspath(__file__)).parent / "test_dataset.csv"
+    test_url = data_url_from_file(str(test_file))
     dataset = DatasetDefWithProvider(
         identifier="test_dataset",
         provider_id=os.environ["PROVIDER_ID"],
         url=URL(
-            uri="https://openaipublic.blob.core.windows.net/simple-evals/mmlu.csv",
+            uri=test_url,
-        ),
-        dataset_schema={},
-    )
-    await datasets_impl.register_dataset(dataset)
-
-
-async def register_local_dataset(datasets_impl: Datasets):
-    test_file = Path(os.path.abspath(__file__)).parent / "test_dataset.jsonl"
-    test_jsonl_url = data_url_from_file(str(test_file))
-    dataset = DatasetDefWithProvider(
-        identifier="test_dataset",
-        provider_id=os.environ["PROVIDER_ID"],
-        url=URL(
-            uri=test_jsonl_url,
         ),
         dataset_schema={
             "generated_answer": StringType(),
@@ -92,60 +80,60 @@ async def register_local_dataset(datasets_impl: Datasets):
     await datasets_impl.register_dataset(dataset)
 
 
-# @pytest.mark.asyncio
+@pytest.mark.asyncio
-# async def test_datasets_list(datasetio_settings):
+async def test_datasets_list(datasetio_settings):
-#     # NOTE: this needs you to ensure that you are starting from a clean state
+    # NOTE: this needs you to ensure that you are starting from a clean state
-#     # but so far we don't have an unregister API unfortunately, so be careful
+    # but so far we don't have an unregister API unfortunately, so be careful
-#     datasets_impl = datasetio_settings["datasets_impl"]
+    datasets_impl = datasetio_settings["datasets_impl"]
-#     response = await datasets_impl.list_datasets()
+    response = await datasets_impl.list_datasets()
-#     assert isinstance(response, list)
+    assert isinstance(response, list)
-#     assert len(response) == 0
+    assert len(response) == 0
 
 
-# @pytest.mark.asyncio
+@pytest.mark.asyncio
-# async def test_datasets_register(datasetio_settings):
+async def test_datasets_register(datasetio_settings):
-#     # NOTE: this needs you to ensure that you are starting from a clean state
+    # NOTE: this needs you to ensure that you are starting from a clean state
-#     # but so far we don't have an unregister API unfortunately, so be careful
+    # but so far we don't have an unregister API unfortunately, so be careful
-#     datasets_impl = datasetio_settings["datasets_impl"]
+    datasets_impl = datasetio_settings["datasets_impl"]
-#     await register_dataset(datasets_impl)
+    await register_dataset(datasets_impl)
 
-#     response = await datasets_impl.list_datasets()
+    response = await datasets_impl.list_datasets()
-#     assert isinstance(response, list)
+    assert isinstance(response, list)
-#     assert len(response) == 1
+    assert len(response) == 1
 
-#     # register same dataset with same id again will fail
+    # register same dataset with same id again will fail
-#     await register_dataset(datasets_impl)
+    await register_dataset(datasets_impl)
-#     response = await datasets_impl.list_datasets()
+    response = await datasets_impl.list_datasets()
-#     assert isinstance(response, list)
+    assert isinstance(response, list)
-#     assert len(response) == 1
+    assert len(response) == 1
-#     assert response[0].identifier == "test_dataset"
+    assert response[0].identifier == "test_dataset"
 
 
-# @pytest.mark.asyncio
+@pytest.mark.asyncio
-# async def test_get_rows_paginated(datasetio_settings):
+async def test_get_rows_paginated(datasetio_settings):
-#     datasetio_impl = datasetio_settings["datasetio_impl"]
+    datasetio_impl = datasetio_settings["datasetio_impl"]
-#     datasets_impl = datasetio_settings["datasets_impl"]
+    datasets_impl = datasetio_settings["datasets_impl"]
-#     await register_dataset(datasets_impl)
+    await register_dataset(datasets_impl)
 
-#     response = await datasetio_impl.get_rows_paginated(
+    response = await datasetio_impl.get_rows_paginated(
-#         dataset_id="test_dataset",
+        dataset_id="test_dataset",
-#         rows_in_page=3,
+        rows_in_page=3,
-#     )
+    )
 
-#     assert isinstance(response.rows, list)
+    assert isinstance(response.rows, list)
-#     assert len(response.rows) == 3
+    assert len(response.rows) == 3
-#     assert response.next_page_token == "3"
+    assert response.next_page_token == "3"
 
-#     # iterate over all rows
+    # iterate over all rows
-#     response = await datasetio_impl.get_rows_paginated(
+    response = await datasetio_impl.get_rows_paginated(
-#         dataset_id="test_dataset",
+        dataset_id="test_dataset",
-#         rows_in_page=10,
+        rows_in_page=2,
-#         page_token=response.next_page_token,
+        page_token=response.next_page_token,
-#     )
+    )
 
-#     assert isinstance(response.rows, list)
+    assert isinstance(response.rows, list)
-#     assert len(response.rows) == 10
+    assert len(response.rows) == 2
-#     assert response.next_page_token == "13"
+    assert response.next_page_token == "5"
 
 
 @pytest.mark.asyncio
@@ -153,4 +141,4 @@ async def test_datasets_validation(datasetio_settings):
     # NOTE: this needs you to ensure that you are starting from a clean state
     # but so far we don't have an unregister API unfortunately, so be careful
     datasets_impl = datasetio_settings["datasets_impl"]
-    await register_local_dataset(datasets_impl)
+    await register_dataset(datasets_impl)