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# -*- coding: utf-8 -*-
# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# pylint: disable=protected-access, g-multiple-import
"""System tests for Gen AI evaluation."""
from google import auth
from google.cloud import aiplatform
from tests.system.aiplatform import e2e_base
from vertexai.generative_models import GenerativeModel
from vertexai.preview.evaluation import EvalTask
from vertexai.preview.evaluation import (
MetricPromptTemplateExamples,
)
import pandas as pd
import pytest
_METRICS = [
"rouge_l_sum",
MetricPromptTemplateExamples.Pointwise.SAFETY,
]
_GEMINI_MODEL_NAME = "gemini-1.0-pro"
_EXPERIMENT_NAME = "test_experiment"
_EXPERIMENT__RUN_NAME = "test_experiment_run"
@pytest.mark.usefixtures(
"tear_down_resources",
)
class TestEvaluation(e2e_base.TestEndToEnd):
"""System tests for Gen AI evaluation."""
def setup_method(self):
super().setup_method()
credentials, _ = auth.default(
scopes=["https://www.googleapis.com/auth/cloud-platform"]
)
aiplatform.init(
project=e2e_base._PROJECT,
location=e2e_base._LOCATION,
credentials=credentials,
)
def test_run_eval_task(self):
test_eval_task = EvalTask(
dataset=pd.DataFrame(
{
"prompt": ["Why is sky blue?"],
"reference": [
"The sky appears blue due to a phenomenon called "
"Rayleigh scattering."
],
}
),
metrics=_METRICS,
experiment=_EXPERIMENT_NAME,
)
eval_result = test_eval_task.evaluate(
model=GenerativeModel(_GEMINI_MODEL_NAME),
experiment_run_name=_EXPERIMENT__RUN_NAME,
)
assert eval_result.summary_metrics["row_count"] == 1
assert set(eval_result.summary_metrics.keys()) == set(
[
"row_count",
"rouge_l_sum/mean",
"rouge_l_sum/std",
"safety/mean",
"safety/std",
]
)
assert set(eval_result.metrics_table.columns.values) == set(
[
"prompt",
"reference",
"response",
"rouge_l_sum/score",
"safety/score",
"safety/explanation",
]
)