llama-stack/llama_stack/providers/tests/datasetio/test_datasetio.py
Xi Yan 821810657f
[Evals API][2/n] datasets / datasetio meta-reference implementation (#288)
* skeleton dataset / datasetio

* dataset datasetio

* config

* address comments

* delete dataset_utils

* address comments

* naming fix
2024-10-22 16:12:16 -07:00

109 lines
3.5 KiB
Python

# 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.
import os
import pytest
import pytest_asyncio
from llama_stack.apis.datasetio import * # noqa: F403
from llama_stack.distribution.datatypes import * # noqa: F403
from llama_stack.providers.tests.resolver import resolve_impls_for_test
# How to run this test:
#
# 1. Ensure you have a conda with the right dependencies installed. This is a bit tricky
# since it depends on the provider you are testing. On top of that you need
# `pytest` and `pytest-asyncio` installed.
#
# 2. Copy and modify the provider_config_example.yaml depending on the provider you are testing.
#
# 3. Run:
#
# ```bash
# PROVIDER_ID=<your_provider> \
# PROVIDER_CONFIG=provider_config.yaml \
# pytest -s llama_stack/providers/tests/datasetio/test_datasetio.py \
# --tb=short --disable-warnings
# ```
@pytest_asyncio.fixture(scope="session")
async def datasetio_settings():
impls = await resolve_impls_for_test(
Api.datasetio,
)
return {
"datasetio_impl": impls[Api.datasetio],
"datasets_impl": impls[Api.datasets],
}
async def register_dataset(datasets_impl: Datasets):
dataset = DatasetDefWithProvider(
identifier="test_dataset",
provider_id=os.environ["PROVIDER_ID"],
url=URL(
uri="https://openaipublic.blob.core.windows.net/simple-evals/mmlu.csv",
),
columns_schema={},
)
await datasets_impl.register_dataset(dataset)
@pytest.mark.asyncio
async def test_datasets_list(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"]
response = await datasets_impl.list_datasets()
assert isinstance(response, list)
assert len(response) == 0
@pytest.mark.asyncio
async def test_datasets_register(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_dataset(datasets_impl)
response = await datasets_impl.list_datasets()
assert isinstance(response, list)
assert len(response) == 1
# register same dataset with same id again will fail
await register_dataset(datasets_impl)
response = await datasets_impl.list_datasets()
assert isinstance(response, list)
assert len(response) == 1
assert response[0].identifier == "test_dataset"
@pytest.mark.asyncio
async def test_get_rows_paginated(datasetio_settings):
datasetio_impl = datasetio_settings["datasetio_impl"]
datasets_impl = datasetio_settings["datasets_impl"]
await register_dataset(datasets_impl)
response = await datasetio_impl.get_rows_paginated(
dataset_id="test_dataset",
rows_in_page=3,
)
assert isinstance(response.rows, list)
assert len(response.rows) == 3
assert response.next_page_token == "3"
# iterate over all rows
response = await datasetio_impl.get_rows_paginated(
dataset_id="test_dataset",
rows_in_page=10,
page_token=response.next_page_token,
)
assert isinstance(response.rows, list)
assert len(response.rows) == 10
assert response.next_page_token == "13"