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adk-python/tests/unittests/evaluation/test_trajectory_evaluator.py
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2025-11-12 09:10:34 -08:00

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# Copyright 2025 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.
"""Testings for the Trajectory Evaluator."""
from google.adk.evaluation.eval_case import IntermediateData
from google.adk.evaluation.eval_case import Invocation
from google.adk.evaluation.eval_metrics import EvalMetric
from google.adk.evaluation.eval_metrics import PrebuiltMetrics
from google.adk.evaluation.eval_metrics import ToolTrajectoryCriterion
from google.adk.evaluation.evaluator import EvalStatus
from google.adk.evaluation.trajectory_evaluator import TrajectoryEvaluator
from google.genai import types as genai_types
import pytest
_USER_CONTENT = genai_types.Content(
parts=[genai_types.Part(text="User input here.")]
)
def test_get_metric_info():
"""Test get_metric_info function for tool trajectory avg metric."""
metric_info = TrajectoryEvaluator.get_metric_info()
assert (
metric_info.metric_name == PrebuiltMetrics.TOOL_TRAJECTORY_AVG_SCORE.value
)
assert metric_info.metric_value_info.interval.min_value == 0.0
assert metric_info.metric_value_info.interval.max_value == 1.0
@pytest.fixture
def evaluator() -> TrajectoryEvaluator:
"""Returns a TrajectoryEvaluator."""
return TrajectoryEvaluator(
eval_metric=EvalMetric(
threshold=0.5,
metric_name=PrebuiltMetrics.TOOL_TRAJECTORY_AVG_SCORE.value,
criterion=ToolTrajectoryCriterion(
threshold=0.5,
match_type=ToolTrajectoryCriterion.MatchType.EXACT,
),
)
)
def test_evaluate_invocations_equal_tool_calls(evaluator: TrajectoryEvaluator):
"""Tests evaluate_invocations with equal tool calls."""
tool_call = genai_types.FunctionCall(name="test_func", args={"arg1": "val1"})
intermediate_data = IntermediateData(tool_uses=[tool_call])
invocation = Invocation(
user_content=_USER_CONTENT, intermediate_data=intermediate_data
)
result = evaluator.evaluate_invocations([invocation], [invocation])
assert result.overall_score == 1.0
assert result.overall_eval_status == EvalStatus.PASSED
assert len(result.per_invocation_results) == 1
assert result.per_invocation_results[0].score == 1.0
assert result.per_invocation_results[0].eval_status == EvalStatus.PASSED
def test_evaluate_invocations_different_tool_call_names(
evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with different tool call names."""
tool_call1 = genai_types.FunctionCall(
name="test_func1", args={"arg1": "val1"}
)
tool_call2 = genai_types.FunctionCall(
name="test_func2", args={"arg1": "val1"}
)
invocation1 = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call1]),
)
invocation2 = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call2]),
)
result = evaluator.evaluate_invocations([invocation1], [invocation2])
assert result.overall_score == 0.0
assert result.overall_eval_status == EvalStatus.FAILED
assert result.per_invocation_results[0].score == 0.0
assert result.per_invocation_results[0].eval_status == EvalStatus.FAILED
def test_evaluate_invocations_different_tool_call_args(
evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with different tool call args."""
tool_call1 = genai_types.FunctionCall(name="test_func", args={"arg1": "val1"})
tool_call2 = genai_types.FunctionCall(name="test_func", args={"arg1": "val2"})
invocation1 = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call1]),
)
invocation2 = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call2]),
)
result = evaluator.evaluate_invocations([invocation1], [invocation2])
assert result.overall_score == 0.0
assert result.overall_eval_status == EvalStatus.FAILED
assert result.per_invocation_results[0].score == 0.0
assert result.per_invocation_results[0].eval_status == EvalStatus.FAILED
def test_evaluate_invocations_different_number_of_tool_calls(
evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with different number of tool calls."""
tool_call1 = genai_types.FunctionCall(name="test_func", args={"arg1": "val1"})
tool_call2 = genai_types.FunctionCall(name="test_func", args={"arg1": "val1"})
invocation1 = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call1]),
)
invocation2 = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call1, tool_call2]),
)
result = evaluator.evaluate_invocations([invocation1], [invocation2])
assert result.overall_score == 0.0
assert result.overall_eval_status == EvalStatus.FAILED
assert result.per_invocation_results[0].score == 0.0
assert result.per_invocation_results[0].eval_status == EvalStatus.FAILED
def test_evaluate_invocations_no_tool_calls(evaluator: TrajectoryEvaluator):
"""Tests evaluate_invocations with no tool calls."""
invocation = Invocation(
user_content=_USER_CONTENT, intermediate_data=IntermediateData()
)
result = evaluator.evaluate_invocations([invocation], [invocation])
assert result.overall_score == 1.0
assert result.overall_eval_status == EvalStatus.PASSED
assert result.per_invocation_results[0].score == 1.0
assert result.per_invocation_results[0].eval_status == EvalStatus.PASSED
def test_evaluate_invocations_multiple_invocations(
evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with multiple invocations."""
tool_call1 = genai_types.FunctionCall(
name="test_func1", args={"arg1": "val1"}
)
tool_call2 = genai_types.FunctionCall(
name="test_func2", args={"arg1": "val1"}
)
inv1_actual = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call1]),
)
inv1_expected = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call1]),
)
inv2_actual = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call1]),
)
inv2_expected = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[tool_call2]),
)
result = evaluator.evaluate_invocations(
[inv1_actual, inv2_actual], [inv1_expected, inv2_expected]
)
assert result.overall_score == 0.5
assert result.overall_eval_status == EvalStatus.PASSED
assert len(result.per_invocation_results) == 2
assert result.per_invocation_results[0].score == 1.0
assert result.per_invocation_results[0].eval_status == EvalStatus.PASSED
assert result.per_invocation_results[1].score == 0.0
assert result.per_invocation_results[1].eval_status == EvalStatus.FAILED
@pytest.fixture
def in_order_evaluator() -> TrajectoryEvaluator:
"""Returns a TrajectoryEvaluator for IN_ORDER match."""
return TrajectoryEvaluator(
eval_metric=EvalMetric(
threshold=0.5,
metric_name=PrebuiltMetrics.TOOL_TRAJECTORY_AVG_SCORE.value,
criterion=ToolTrajectoryCriterion(
threshold=0.5,
match_type=ToolTrajectoryCriterion.MatchType.IN_ORDER,
),
)
)
def test_evaluate_invocations_in_order_match_with_extra_tool_calls(
in_order_evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with IN_ORDER match type and extra tool calls."""
t1 = genai_types.FunctionCall(name="t1", args={})
t1_1 = genai_types.FunctionCall(name="t1_1", args={})
t2 = genai_types.FunctionCall(name="t2", args={})
t2_1 = genai_types.FunctionCall(name="t2_1", args={})
t3 = genai_types.FunctionCall(name="t3", args={})
t3_1 = genai_types.FunctionCall(name="t3_1", args={})
actual_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(
tool_uses=[t1, t1_1, t2, t2_1, t3, t3_1]
),
)
expected_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t3]),
)
result = in_order_evaluator.evaluate_invocations(
[actual_invocation], [expected_invocation]
)
assert result.overall_score == 1.0
assert result.overall_eval_status == EvalStatus.PASSED
assert result.per_invocation_results[0].score == 1.0
assert result.per_invocation_results[0].eval_status == EvalStatus.PASSED
def test_evaluate_invocations_in_order_match_fails_with_missing_tool_call(
in_order_evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with IN_ORDER match type and missing tool call."""
t1 = genai_types.FunctionCall(name="t1", args={})
t1_1 = genai_types.FunctionCall(name="t1_1", args={})
t2 = genai_types.FunctionCall(name="t2", args={})
t2_1 = genai_types.FunctionCall(name="t2_1", args={})
t3_1 = genai_types.FunctionCall(name="t3_1", args={})
t4 = genai_types.FunctionCall(name="t4", args={})
actual_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t1_1, t2, t2_1, t3_1]),
)
expected_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t4]),
)
result = in_order_evaluator.evaluate_invocations(
[actual_invocation], [expected_invocation]
)
assert result.overall_score == 0.0
assert result.overall_eval_status == EvalStatus.FAILED
assert result.per_invocation_results[0].score == 0.0
assert result.per_invocation_results[0].eval_status == EvalStatus.FAILED
def test_evaluate_invocations_in_order_match_fails_with_wrong_order(
in_order_evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with IN_ORDER match type and wrong order."""
t1 = genai_types.FunctionCall(name="t1", args={})
t2 = genai_types.FunctionCall(name="t2", args={})
t3 = genai_types.FunctionCall(name="t3", args={})
actual_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t3, t2]),
)
expected_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t3]),
)
result = in_order_evaluator.evaluate_invocations(
[actual_invocation], [expected_invocation]
)
assert result.overall_score == 0.0
assert result.overall_eval_status == EvalStatus.FAILED
assert result.per_invocation_results[0].score == 0.0
assert result.per_invocation_results[0].eval_status == EvalStatus.FAILED
@pytest.fixture
def any_order_evaluator() -> TrajectoryEvaluator:
"""Returns a TrajectoryEvaluator for ANY_ORDER match."""
return TrajectoryEvaluator(
eval_metric=EvalMetric(
threshold=0.5,
metric_name=PrebuiltMetrics.TOOL_TRAJECTORY_AVG_SCORE.value,
criterion=ToolTrajectoryCriterion(
threshold=0.5,
match_type=ToolTrajectoryCriterion.MatchType.ANY_ORDER,
),
)
)
def test_evaluate_invocations_any_order_match_with_extra_tool_calls_different_order(
any_order_evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with ANY_ORDER match type and extra tool calls."""
t1 = genai_types.FunctionCall(name="t1", args={})
t1_1 = genai_types.FunctionCall(name="t1_1", args={})
t2 = genai_types.FunctionCall(name="t2", args={})
t2_1 = genai_types.FunctionCall(name="t2_1", args={})
t3 = genai_types.FunctionCall(name="t3", args={})
t3_1 = genai_types.FunctionCall(name="t3_1", args={})
actual_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(
tool_uses=[t2, t2_1, t1, t1_1, t3, t3_1]
),
)
expected_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t3]),
)
result = any_order_evaluator.evaluate_invocations(
[actual_invocation], [expected_invocation]
)
assert result.overall_score == 1.0
assert result.overall_eval_status == EvalStatus.PASSED
assert result.per_invocation_results[0].score == 1.0
assert result.per_invocation_results[0].eval_status == EvalStatus.PASSED
def test_evaluate_invocations_any_order_match_fails_with_missing_tool_call(
any_order_evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with ANY_ORDER match type and missing tool call."""
t1 = genai_types.FunctionCall(name="t1", args={})
t1_1 = genai_types.FunctionCall(name="t1_1", args={})
t2 = genai_types.FunctionCall(name="t2", args={})
t2_1 = genai_types.FunctionCall(name="t2_1", args={})
t3_1 = genai_types.FunctionCall(name="t3_1", args={})
t4 = genai_types.FunctionCall(name="t4", args={})
actual_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t1_1, t2, t2_1, t3_1]),
)
expected_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t4]),
)
result = any_order_evaluator.evaluate_invocations(
[actual_invocation], [expected_invocation]
)
assert result.overall_score == 0.0
assert result.overall_eval_status == EvalStatus.FAILED
assert result.per_invocation_results[0].score == 0.0
assert result.per_invocation_results[0].eval_status == EvalStatus.FAILED
def test_evaluate_invocations_any_order_match_with_duplicates(
any_order_evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with ANY_ORDER match type with duplicates."""
t1 = genai_types.FunctionCall(name="t1", args={})
t2 = genai_types.FunctionCall(name="t2", args={})
t3 = genai_types.FunctionCall(name="t3", args={})
actual_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t3, t1]),
)
expected_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t1]),
)
result = any_order_evaluator.evaluate_invocations(
[actual_invocation], [expected_invocation]
)
assert result.overall_score == 1.0
assert result.overall_eval_status == EvalStatus.PASSED
assert result.per_invocation_results[0].score == 1.0
assert result.per_invocation_results[0].eval_status == EvalStatus.PASSED
def test_evaluate_invocations_any_order_match_fails_with_duplicates_missing(
any_order_evaluator: TrajectoryEvaluator,
):
"""Tests evaluate_invocations with ANY_ORDER match type with missing duplicates."""
t1 = genai_types.FunctionCall(name="t1", args={})
t2 = genai_types.FunctionCall(name="t2", args={})
t3 = genai_types.FunctionCall(name="t3", args={})
actual_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t3]),
)
expected_invocation = Invocation(
user_content=_USER_CONTENT,
intermediate_data=IntermediateData(tool_uses=[t1, t2, t1]),
)
result = any_order_evaluator.evaluate_invocations(
[actual_invocation], [expected_invocation]
)
assert result.overall_score == 0.0
assert result.overall_eval_status == EvalStatus.FAILED
assert result.per_invocation_results[0].score == 0.0
assert result.per_invocation_results[0].eval_status == EvalStatus.FAILED
def test_evaluate_invocations_no_invocations(evaluator: TrajectoryEvaluator):
"""Tests evaluate_invocations with no invocations."""
result = evaluator.evaluate_invocations([], [])
assert result.overall_score is None
assert result.overall_eval_status == EvalStatus.NOT_EVALUATED
assert not result.per_invocation_results