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28f702f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 | """Tests for the core AdFraudEnvironment."""
from counterfeint.models import AdReviewAction, AdReviewObservation, AdFraudState
from counterfeint.server.environment import AdFraudEnvironment
class TestReset:
def test_reset_returns_observation(self):
env = AdFraudEnvironment()
obs = env.reset(seed=42, task_id="task_1")
assert isinstance(obs, AdReviewObservation)
assert obs.done is False
assert obs.reward == 0.0
assert len(obs.available_ads) == 5
def test_reset_clears_state(self):
env = AdFraudEnvironment()
env.reset(seed=42, task_id="task_1")
env.step(AdReviewAction(
action_type="verdict", ad_id="ad_001",
verdict="approve", confidence=0.9,
))
obs = env.reset(seed=42, task_id="task_1")
state = env.state
assert state.step_count == 0
assert state.reviewed_count == 0
assert len(obs.available_ads) == 5
def test_reset_different_tasks(self):
env = AdFraudEnvironment()
for task_id, expected in [("task_1", 5), ("task_2", 12), ("task_3", 20)]:
obs = env.reset(seed=42, task_id=task_id)
assert len(obs.available_ads) == expected
class TestStep:
def test_investigate_returns_findings(self):
env = AdFraudEnvironment()
env.reset(seed=42, task_id="task_1")
obs = env.step(AdReviewAction(
action_type="investigate",
ad_id="ad_001",
investigation_target="advertiser_history",
))
assert obs.done is False
assert obs.reward == -0.02
assert "Advertiser" in obs.feedback or "Investigation complete" in obs.feedback
def test_verdict_correct_rejection(self):
env = AdFraudEnvironment()
env.reset(seed=42, task_id="task_1")
fraud_ads = [
a for a in env._episode.ads if a.ground_truth_label == "fraud"
]
assert len(fraud_ads) > 0
ad = fraud_ads[0]
obs = env.step(AdReviewAction(
action_type="verdict", ad_id=ad.ad_id,
verdict="reject", confidence=0.9,
))
assert obs.reward > 0
def test_verdict_false_negative_penalty(self):
env = AdFraudEnvironment()
env.reset(seed=42, task_id="task_1")
fraud_ads = [
a for a in env._episode.ads if a.ground_truth_label == "fraud"
]
ad = fraud_ads[0]
obs = env.step(AdReviewAction(
action_type="verdict", ad_id=ad.ad_id,
verdict="approve", confidence=0.9,
))
assert obs.reward < 0
def test_duplicate_verdict_rejected(self):
env = AdFraudEnvironment()
env.reset(seed=42, task_id="task_1")
env.step(AdReviewAction(
action_type="verdict", ad_id="ad_001",
verdict="approve", confidence=0.5,
))
obs = env.step(AdReviewAction(
action_type="verdict", ad_id="ad_001",
verdict="reject", confidence=0.9,
))
assert obs.reward == -0.02
def test_invalid_ad_id(self):
env = AdFraudEnvironment()
env.reset(seed=42, task_id="task_1")
obs = env.step(AdReviewAction(
action_type="investigate", ad_id="ad_999",
investigation_target="landing_page",
))
assert obs.reward == -0.05
assert "Invalid" in obs.feedback
def test_episode_ends_when_all_reviewed(self):
env = AdFraudEnvironment()
obs = env.reset(seed=42, task_id="task_1")
for ad_id in list(obs.available_ads):
obs = env.step(AdReviewAction(
action_type="verdict", ad_id=ad_id,
verdict="reject", confidence=0.5,
))
assert obs.done is True
def test_step_after_done_returns_done(self):
env = AdFraudEnvironment()
obs = env.reset(seed=42, task_id="task_1")
for ad_id in list(obs.available_ads):
obs = env.step(AdReviewAction(
action_type="verdict", ad_id=ad_id,
verdict="reject", confidence=0.5,
))
obs = env.step(AdReviewAction(
action_type="investigate", ad_id="ad_001",
investigation_target="landing_page",
))
assert obs.done is True
assert "already complete" in obs.feedback.lower()
class TestState:
def test_state_tracks_progress(self):
env = AdFraudEnvironment()
env.reset(seed=42, task_id="task_1")
state = env.state
assert state.task_id == "task_1"
assert state.total_ads == 5
assert state.remaining_budget == 25
assert state.step_count == 0
env.step(AdReviewAction(
action_type="investigate", ad_id="ad_001",
investigation_target="landing_page",
))
state = env.state
assert state.step_count == 1
assert state.remaining_budget == 24
def test_grader_score_set_on_completion(self):
env = AdFraudEnvironment()
obs = env.reset(seed=42, task_id="task_1")
for ad_id in list(obs.available_ads):
env.step(AdReviewAction(
action_type="verdict", ad_id=ad_id,
verdict="reject", confidence=0.5,
))
state = env.state
assert state.grader_score is not None
assert 0.0 <= state.grader_score <= 1.0
class TestAntiExploit:
def test_always_reject_scores_poorly(self):
"""Always-reject on task_2 (5 legit / 5 fraud / 2 escalate) should be punished."""
env = AdFraudEnvironment()
obs = env.reset(seed=42, task_id="task_2")
for ad_id in list(obs.available_ads):
env.step(AdReviewAction(
action_type="verdict", ad_id=ad_id,
verdict="reject", confidence=0.9,
))
score = env.state.grader_score
assert score < 0.7, f"Always-reject should score poorly, got {score}"
def test_always_escalate_scores_poorly(self):
env = AdFraudEnvironment()
obs = env.reset(seed=42, task_id="task_1")
for ad_id in list(obs.available_ads):
env.step(AdReviewAction(
action_type="verdict", ad_id=ad_id,
verdict="escalate", confidence=0.5,
))
score = env.state.grader_score
assert score < 0.7, f"Always-escalate should score poorly, got {score}"
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