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chore: import upstream snapshot with attribution
2026-07-13 12:05:33 +08:00

85 lines
3.6 KiB
Python

import unittest
from lib import schema
class SchemaV3Tests(unittest.TestCase):
def test_report_roundtrip(self):
report = schema.Report(
topic="test topic",
range_from="2026-02-14",
range_to="2026-03-16",
generated_at="2026-03-16T00:00:00+00:00",
provider_runtime=schema.ProviderRuntime(
reasoning_provider="gemini",
planner_model="gemini-3.1-flash-lite",
rerank_model="gemini-3.1-flash-lite",
),
query_plan=schema.QueryPlan(
intent="breaking_news",
freshness_mode="strict_recent",
cluster_mode="story",
raw_topic="test topic",
subqueries=[schema.SubQuery(label="primary", search_query="test topic", ranking_query="What happened with test topic?", sources=["grounding"])],
source_weights={"grounding": 1.0},
),
clusters=[schema.Cluster(cluster_id="cluster-1", title="Title", candidate_ids=["c1"], representative_ids=["c1"], sources=["grounding"], score=90)],
ranked_candidates=[schema.Candidate(
candidate_id="c1",
item_id="i1",
source="grounding",
sources=["grounding", "reddit"],
title="Title",
url="https://example.com",
snippet="Snippet",
subquery_labels=["primary"],
native_ranks={"primary:grounding": 1},
local_relevance=0.8,
freshness=90,
engagement=None,
source_quality=1.0,
rrf_score=0.02,
rerank_score=91,
final_score=90,
source_items=[
schema.SourceItem(item_id="i1", source="grounding", title="Title", body="Body", url="https://example.com", published_at="2026-03-16")
],
)],
items_by_source={"grounding": [schema.SourceItem(item_id="i1", source="grounding", title="Title", body="Body", url="https://example.com")]},
errors_by_source={},
warnings=["warning"],
artifacts={"grounding": []},
)
restored = schema.report_from_dict(schema.to_dict(report))
self.assertEqual(report.topic, restored.topic)
self.assertEqual(report.provider_runtime.planner_model, restored.provider_runtime.planner_model)
self.assertEqual(report.ranked_candidates[0].candidate_id, restored.ranked_candidates[0].candidate_id)
self.assertEqual(report.ranked_candidates[0].sources, restored.ranked_candidates[0].sources)
self.assertEqual(report.items_by_source["grounding"][0].title, restored.items_by_source["grounding"][0].title)
def test_source_item_from_dict_preserves_zero_valued_signals(self):
item = schema.source_item_from_dict(
{
"item_id": "x1",
"source": "x",
"title": "Title",
"body": "Body",
"url": "https://example.com",
"relevance_hint": 0.0,
"local_relevance": 0.0,
"freshness": 0,
"engagement_score": 0,
"source_quality": 0.0,
"local_rank_score": 0.0,
}
)
self.assertEqual(0.0, item.relevance_hint)
self.assertEqual(0.0, item.local_relevance)
self.assertEqual(0, item.freshness)
self.assertEqual(0, item.engagement_score)
self.assertEqual(0.0, item.source_quality)
self.assertEqual(0.0, item.local_rank_score)
if __name__ == "__main__":
unittest.main()