File size: 4,978 Bytes
3c98117 effafc0 3c98117 effafc0 | 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 | """Tests for scripts.evaluation artifact assembly."""
from sage.core.models import EvalCase, EvalCaseProvenance, MetricsReport
import scripts.evaluation as evaluation_script
def _case(
*,
query: str,
query_id: str,
source_type: str,
category: str,
intent: str,
subset_tags: tuple[str, ...],
query_slice_tags: tuple[str, ...],
origin_family: str,
curation_mode: str,
) -> EvalCase:
return EvalCase(
query=query,
relevant_items={"ASIN1": 3.0},
query_id=query_id,
source_type=source_type,
category=category,
intent=intent,
subset_tags=subset_tags,
query_slice_tags=query_slice_tags,
provenance=EvalCaseProvenance(
schema_version="query_provenance_v1",
origin_family=origin_family,
curation_mode=curation_mode,
source_dataset="amazon_esci",
source_split="test",
selection_policy="corpus_overlap_min_relevant_items_v1",
subset_assignment_policy="normalized_query_sha256_v1",
),
)
def test_build_primary_evaluation_artifact_adds_metadata_breakdowns(monkeypatch):
cases = [
_case(
query="wireless keyboard",
query_id="qb_001",
source_type="amazon_esci",
category="keyboards",
intent="use_case",
subset_tags=("retrieval_eval",),
query_slice_tags=(),
origin_family="amazon_esci_overlap",
curation_mode="pure_import",
),
_case(
query="latest earbuds to avoid",
query_id="qb_002",
source_type="manual_seed",
category="audio",
intent="problem_solving",
subset_tags=("retrieval_eval", "special_probe"),
query_slice_tags=(
"recency_sensitive_query",
"negative_problem_query",
),
origin_family="manual_seed",
curation_mode="candidate_bootstrap",
),
]
case_results = []
for case, recommended_ids, metrics in [
(
cases[0],
["ASIN1", "ASIN3"],
{
"ndcg": 1.0,
"hit": 1.0,
"mrr": 1.0,
"precision": 0.5,
"recall": 1.0,
"diversity": 0.2,
"novelty": 2.0,
},
),
(
cases[1],
["ASIN4", "ASIN1"],
{
"ndcg": 0.6309,
"hit": 1.0,
"mrr": 0.5,
"precision": 0.5,
"recall": 1.0,
"diversity": 0.6,
"novelty": 3.0,
},
),
]:
row = case.to_dict()
row["recommended_product_ids"] = recommended_ids
row["relevant_item_count"] = 1
row["relevant_hits"] = [
{
"product_id": "ASIN1",
"rank": recommended_ids.index("ASIN1") + 1,
"relevance": 3.0,
}
]
row["first_relevant_rank"] = recommended_ids.index("ASIN1") + 1
row["metrics"] = metrics
case_results.append(row)
monkeypatch.setattr(
evaluation_script,
"evaluate_recommendations_with_details",
lambda **_kwargs: (
MetricsReport(
n_cases=2,
ndcg_at_k=0.8154,
hit_at_k=1.0,
mrr=0.75,
precision_at_k=0.5,
recall_at_k=1.0,
diversity=0.4,
coverage=0.6,
novelty=2.5,
k=10,
),
case_results,
),
)
artifact = evaluation_script.build_primary_evaluation_artifact(
cases,
item_embeddings={},
item_popularity={},
total_items=5,
)
assert artifact["metrics"]["ndcg_at_10"] == 0.8154
assert artifact["case_metadata_summary"]["total_cases"] == 2
assert artifact["case_metadata_summary"]["by_origin_family"] == {
"amazon_esci_overlap": 1,
"manual_seed": 1,
}
assert artifact["case_metadata_summary"]["by_query_slice_tag"] == {
"recency_sensitive_query": 1,
"negative_problem_query": 1,
}
assert (
artifact["metric_breakdowns"]["by_curation_mode"]["candidate_bootstrap"][
"n_cases"
]
== 1
)
assert (
artifact["metric_breakdowns"]["by_query_slice_tag"]["recency_sensitive_query"][
"n_cases"
]
== 1
)
assert (
artifact["metric_breakdowns"]["by_query_slice_tag"]["recency_sensitive_query"][
"coverage"
]
== 0.4
)
assert (
artifact["metric_breakdowns"]["by_subset_tag"]["retrieval_eval"]["n_cases"] == 2
)
assert "subset_tags" in artifact["breakdown_methodology"]["multi_membership_fields"]
|