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# ---------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# ---------------------------------------------------------
import pytest
from unittest.mock import Mock, MagicMock, patch
import pandas as pd
from typing import List, Any
from azure.ai.evaluation._evaluate._evaluate_aoai import (
_get_single_run_results,
OAIEvalRunCreationInfo,
_wait_for_run_conclusion,
)
from azure.ai.evaluation._exceptions import EvaluationException
class MockOutputItem:
"""Mock class for output items"""
def __init__(self, id: str, datasource_item_id: int, results: List[dict]):
self.id = id
self.datasource_item_id = datasource_item_id
self.results = results
class MockOutputItemsList:
"""Mock class for paginated results"""
def __init__(self, data: List[MockOutputItem], has_more: bool = False):
self.data = data
self.has_more = has_more
class TestAOAIPagination:
"""Test pagination functionality in AOAI evaluation results"""
def test_single_page_results(self):
"""Test handling of single page results (no pagination needed)"""
# Mock client and run info
mock_client = Mock()
run_info = OAIEvalRunCreationInfo(
client=mock_client,
eval_group_id="test-group",
eval_run_id="test-run",
grader_name_map={"grader-1": "test_grader"},
expected_rows=10,
)
# Mock the wait_for_run_conclusion response
mock_run_results = Mock()
mock_run_results.status = "completed"
mock_run_results.per_testing_criteria_results = [Mock(testing_criteria="grader-1", passed=8, failed=2)]
# Mock single page of results
mock_output_items = [
MockOutputItem(
id=f"item-{i}",
datasource_item_id=i,
results=[
{
"name": "grader-1",
"passed": i % 2 == 0,
"score": 0.8 if i % 2 == 0 else 0.2,
"sample": f"Sample {i}",
}
],
)
for i in range(10)
]
mock_list_response = MockOutputItemsList(data=mock_output_items, has_more=False)
mock_client.evals.runs.output_items.list.return_value = mock_list_response
with patch(
"azure.ai.evaluation._evaluate._evaluate_aoai._wait_for_run_conclusion", return_value=mock_run_results
):
df, metrics = _get_single_run_results(run_info)
# Verify results
assert len(df) == 10
assert "outputs.test_grader.passed" in df.columns
assert "outputs.test_grader.score" in df.columns
assert metrics["test_grader.pass_rate"] == 0.8
# Verify list was called once (no pagination)
assert mock_client.evals.runs.output_items.list.call_count == 1
def test_multi_page_results(self):
"""Test handling of multi-page results with pagination"""
mock_client = Mock()
run_info = OAIEvalRunCreationInfo(
client=mock_client,
eval_group_id="test-group",
eval_run_id="test-run",
grader_name_map={"grader-1": "test_grader"},
expected_rows=250,
)
# Mock run results
mock_run_results = Mock()
mock_run_results.status = "completed"
mock_run_results.per_testing_criteria_results = [Mock(testing_criteria="grader-1", passed=80, failed=20)]
# Create 3 pages of results
page1_items = [
MockOutputItem(
id=f"item-{i}",
datasource_item_id=i,
results=[{"name": "grader-1", "passed": True, "score": 0.9, "sample": f"Sample {i}"}],
)
for i in range(100)
]
page2_items = [
MockOutputItem(
id=f"item-{i}",
datasource_item_id=i,
results=[{"name": "grader-1", "passed": True, "score": 0.85, "sample": f"Sample {i}"}],
)
for i in range(100, 200)
]
page3_items = [
MockOutputItem(
id=f"item-{i}",
datasource_item_id=i,
results=[{"name": "grader-1", "passed": False, "score": 0.3, "sample": f"Sample {i}"}],
)
for i in range(200, 250)
]
# Mock paginated responses
responses = [
MockOutputItemsList(data=page1_items, has_more=True),
MockOutputItemsList(data=page2_items, has_more=True),
MockOutputItemsList(data=page3_items, has_more=False),
]
mock_client.evals.runs.output_items.list.side_effect = responses
with patch(
"azure.ai.evaluation._evaluate._evaluate_aoai._wait_for_run_conclusion", return_value=mock_run_results
):
df, metrics = _get_single_run_results(run_info)
# Verify all results were collected
assert len(df) == 250
assert mock_client.evals.runs.output_items.list.call_count == 3
# Verify pagination parameters
calls = mock_client.evals.runs.output_items.list.call_args_list
assert calls[0][1]["eval_id"] == "test-group"
assert calls[0][1]["run_id"] == "test-run"
assert calls[0][1]["limit"] == 100
assert "after" not in calls[0][1]
assert calls[1][1]["after"] == "item-99" # Last item ID from page 1
assert calls[2][1]["after"] == "item-199" # Last item ID from page 2
def test_empty_page_handling(self):
"""Test handling of empty pages in pagination"""
mock_client = Mock()
run_info = OAIEvalRunCreationInfo(
client=mock_client,
eval_group_id="test-group",
eval_run_id="test-run",
grader_name_map={"grader-1": "test_grader"},
expected_rows=5,
)
mock_run_results = Mock()
mock_run_results.status = "completed"
mock_run_results.per_testing_criteria_results = [Mock(testing_criteria="grader-1", passed=5, failed=0)]
# First page has data, second page is empty but has_more=True, third page breaks loop
responses = [
MockOutputItemsList(
data=[
MockOutputItem(
id=f"item-{i}",
datasource_item_id=i,
results=[{"name": "grader-1", "passed": True, "score": 1.0}],
)
for i in range(5)
],
has_more=True,
),
MockOutputItemsList(data=[], has_more=True), # Empty page
MockOutputItemsList(data=[], has_more=False),
]
mock_client.evals.runs.output_items.list.side_effect = responses
with patch(
"azure.ai.evaluation._evaluate._evaluate_aoai._wait_for_run_conclusion", return_value=mock_run_results
):
df, metrics = _get_single_run_results(run_info)
assert len(df) == 5
assert metrics["test_grader.pass_rate"] == 1.0
def test_result_ordering_preservation(self):
"""Test that results maintain proper ordering after pagination"""
mock_client = Mock()
run_info = OAIEvalRunCreationInfo(
client=mock_client,
eval_group_id="test-group",
eval_run_id="test-run",
grader_name_map={"grader-1": "test_grader"},
expected_rows=10,
)
mock_run_results = Mock()
mock_run_results.status = "completed"
mock_run_results.per_testing_criteria_results = [Mock(testing_criteria="grader-1", passed=20, failed=0)]
# Create results in non-sequential order across pages, covering ids 0..9 exactly
page1_items = [
MockOutputItem(
id=f"item-{i}",
datasource_item_id=i, # was i * 2
results=[{"name": "grader-1", "passed": True, "score": i}],
)
for i in [5, 3, 8, 1, 9]
]
page2_items = [
MockOutputItem(
id=f"item-{i}",
datasource_item_id=i, # was i * 2
results=[{"name": "grader-1", "passed": True, "score": i}],
)
for i in [2, 7, 4, 6, 0]
]
responses = [
MockOutputItemsList(data=page1_items, has_more=True),
MockOutputItemsList(data=page2_items, has_more=False),
]
mock_client.evals.runs.output_items.list.side_effect = responses
with patch(
"azure.ai.evaluation._evaluate._evaluate_aoai._wait_for_run_conclusion", return_value=mock_run_results
):
df, metrics = _get_single_run_results(run_info)
# Verify results are sorted by datasource_item_id (0..9)
scores = df["outputs.test_grader.score"].tolist()
expected_scores = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
assert scores == expected_scores
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