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3d027cb 4454894 3d027cb 4454894 3d027cb 4454894 3d027cb 4454894 520796c 4454894 520796c 3d027cb 4454894 3d027cb | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 | """Tests for evaluation metrics, harness, and report generation."""
from __future__ import annotations
import pytest
from agent_bench.agents.orchestrator import AgentResponse, SourceReference
from agent_bench.core.types import TokenUsage
from agent_bench.evaluation.harness import EvalResult, load_golden_dataset
from agent_bench.evaluation.metrics import (
calculator_used_when_expected,
citation_accuracy,
grounded_refusal,
keyword_hit_rate,
retrieval_precision_at_k,
retrieval_recall_at_k,
source_presence,
)
from agent_bench.evaluation.report import generate_report
# --- Metrics tests ---
class TestRetrievalMetrics:
def test_precision_at_k_perfect(self):
assert retrieval_precision_at_k(["a.md", "b.md"], ["a.md", "b.md"]) == 1.0
def test_precision_at_k_partial(self):
assert retrieval_precision_at_k(["a.md", "b.md", "c.md"], ["a.md"]) == pytest.approx(1 / 3)
def test_precision_at_k_empty_retrieved(self):
assert retrieval_precision_at_k([], ["a.md"]) == 0.0
def test_recall_at_k_perfect(self):
assert retrieval_recall_at_k(["a.md", "b.md", "c.md"], ["a.md", "b.md"]) == 1.0
def test_recall_at_k_partial(self):
assert retrieval_recall_at_k(["a.md"], ["a.md", "b.md"]) == 0.5
def test_recall_at_k_empty_expected(self):
assert retrieval_recall_at_k(["a.md"], []) == 0.0
def test_precision_uses_ranked_sources_with_duplicates(self):
"""Ranked sources may have duplicates — precision should count correctly."""
retrieved = ["a.md", "a.md", "b.md", "c.md", "d.md"]
expected = ["a.md"]
# 2 out of 5 retrieved are "a.md"
assert retrieval_precision_at_k(retrieved, expected, k=5) == pytest.approx(2 / 5)
class TestKeywordMetrics:
def test_keyword_hit_rate_all_match(self):
assert keyword_hit_rate("curly braces in path", ["curly braces", "path"]) == 1.0
def test_keyword_hit_rate_none_match(self):
assert keyword_hit_rate("something else", ["curly", "braces"]) == 0.0
def test_keyword_hit_rate_case_insensitive(self):
assert keyword_hit_rate("CORSMiddleware", ["corsmiddleware"]) == 1.0
class TestSourcePresence:
def test_has_sources(self):
resp = AgentResponse(
answer="test",
sources=[SourceReference(source="a.md")],
iterations=1,
usage=TokenUsage(input_tokens=0, output_tokens=0, estimated_cost_usd=0),
latency_ms=1.0,
)
assert source_presence(resp) is True
def test_no_sources(self):
resp = AgentResponse(
answer="test",
sources=[],
iterations=1,
usage=TokenUsage(input_tokens=0, output_tokens=0, estimated_cost_usd=0),
latency_ms=1.0,
)
assert source_presence(resp) is False
class TestGroundedRefusal:
def test_out_of_scope_with_refusal_no_citations(self):
"""Refusal phrase + no [source:] citations in answer text = passes."""
assert (
grounded_refusal("The documentation does not contain this info.", "out_of_scope")
is True
)
def test_out_of_scope_without_refusal(self):
assert grounded_refusal("Here is how you do it...", "out_of_scope") is False
def test_out_of_scope_refusal_with_citation_in_answer_fails(self):
"""Refusal phrase + [source:] citation in answer text = NOT a grounded refusal.
The metric inspects the answer text for citations rather than the
retrieved-sources list — a correct flavor-A refusal retrieves
candidates, inspects them, and explicitly declines to cite any of
them, which is the behavior the metric is designed to measure.
"""
answer = (
"The documentation does not contain this info. "
"[source: some_doc.md]"
)
assert grounded_refusal(answer, "out_of_scope") is False
def test_out_of_scope_refusal_no_citation_passes_even_with_retrieval(self):
"""Flavor-A refusal: agent retrieved candidates but answer cites none."""
answer = (
"The retrieved context does not contain information about Jaeger "
"sidecar injection. I cannot provide an answer."
)
# Under the old signature this test would have failed because the
# retrieved-sources list was non-empty. The fix moves the check to
# the answer text where the actual citations live.
assert grounded_refusal(answer, "out_of_scope") is True
def test_canonical_refusal_phrasing_recognized(self):
"""System-prompt-taught shape "not in the {label} documentation" passes.
core/prompts.py:17-18 instructs the agent to say "the answer is not
in the {corpus_label} documentation and stop" on out-of-scope queries.
The metric must recognize that canonical form.
"""
answer = "The answer is not in the Kubernetes documentation."
assert grounded_refusal(answer, "out_of_scope") is True
def test_not_in_the_is_not_substring_refusal(self):
"""Bare "not in the" fragment must NOT count as refusal.
Pins the design choice to match the canonical shape via a narrow
regex anchored on "documentation" rather than a loose substring.
A future refactor that widens the matcher to substring "not in the"
will break this test — that is the point.
"""
answer = "The rate limit is not in the same scope as the request timeout."
assert grounded_refusal(answer, "out_of_scope") is False
def test_in_scope_always_true(self):
assert grounded_refusal("any answer", "retrieval") is True
class TestCitationAccuracy:
def test_all_citations_valid(self):
answer = "Info from [source: a.md] and [source: b.md]."
assert citation_accuracy(answer, ["a.md", "b.md"]) == 1.0
def test_hallucinated_citation(self):
answer = "Info from [source: fake.md]."
assert citation_accuracy(answer, ["a.md"]) == 0.0
def test_no_citations(self):
assert citation_accuracy("No citations here.", ["a.md"]) == 1.0
class TestCalculatorMetric:
def test_calculator_used_when_required(self):
resp = AgentResponse(
answer="9",
tools_used=["search_documents", "calculator"],
iterations=2,
usage=TokenUsage(input_tokens=0, output_tokens=0, estimated_cost_usd=0),
latency_ms=1.0,
)
assert calculator_used_when_expected(resp, requires_calculator=True) is True
def test_calculator_not_used_when_required(self):
resp = AgentResponse(
answer="9",
tools_used=["search_documents"],
iterations=1,
usage=TokenUsage(input_tokens=0, output_tokens=0, estimated_cost_usd=0),
latency_ms=1.0,
)
assert calculator_used_when_expected(resp, requires_calculator=True) is False
def test_not_required_always_true(self):
resp = AgentResponse(
answer="test",
tools_used=[],
iterations=1,
usage=TokenUsage(input_tokens=0, output_tokens=0, estimated_cost_usd=0),
latency_ms=1.0,
)
assert calculator_used_when_expected(resp, requires_calculator=False) is True
# --- Golden dataset loading ---
class TestGoldenDataset:
def test_load_golden_dataset(self):
questions = load_golden_dataset("agent_bench/evaluation/datasets/tech_docs_golden.json")
assert len(questions) == 27
# Check distribution
categories = [q.category for q in questions]
assert categories.count("out_of_scope") == 5
assert categories.count("calculation") == 3
# All have required fields
for q in questions:
assert q.id
assert q.question
assert q.expected_answer_keywords
# --- Report generation ---
class TestReportGeneration:
def _make_results(self) -> list[EvalResult]:
usage = TokenUsage(input_tokens=100, output_tokens=50, estimated_cost_usd=0.001)
return [
EvalResult(
question_id="q001",
question="Test question?",
category="retrieval",
difficulty="easy",
retrieval_precision=0.8,
retrieval_recall=1.0,
keyword_hit_rate=0.75,
has_source_citation=True,
grounded_refusal=True,
citation_accuracy=1.0,
calculator_used_correctly=True,
tool_calls_made=2,
latency_ms=100.0,
tokens_used=usage,
answer="Test answer",
retrieved_sources=["a.md"],
),
EvalResult(
question_id="q002",
question="Out of scope?",
category="out_of_scope",
difficulty="easy",
retrieval_precision=0.0,
retrieval_recall=0.0,
keyword_hit_rate=0.5,
has_source_citation=False,
grounded_refusal=True,
citation_accuracy=1.0,
calculator_used_correctly=True,
tool_calls_made=1,
latency_ms=50.0,
tokens_used=usage,
answer="Does not contain",
retrieved_sources=[],
),
]
def test_report_contains_required_sections(self):
report = generate_report(self._make_results(), provider_name="test")
assert "## Aggregate Metrics" in report
assert "## By Category" in report
assert "## By Difficulty" in report
assert "## Chunking Strategy Comparison" in report
assert "## Failure Analysis" in report
assert "## Per-Question Results" in report
def test_report_contains_metrics(self):
report = generate_report(self._make_results(), provider_name="test")
assert "Retrieval P@5" in report
assert "Grounded Refusal Rate" in report
assert "Citation Accuracy" in report
|