feat: v3.0.0 - intelligent search, GitHub person/project mode, ELI5, 13+ sources

v3 rewrites the search engine from the ground up: - Intelligent pre-research: resolves X handles, GitHub repos, subreddits, TikTok hashtags, and YouTube channels before searching - GitHub person-mode: PR velocity, top repos by stars, release notes - GitHub project-mode: live star counts, README, releases, top issues - ELI5 mode: plain language synthesis, no jargon - 13+ sources: Reddit, X, YouTube, TikTok, Instagram, HN, Polymarket, GitHub, Threads, Pinterest, Perplexity, Bluesky, Web - Free Reddit comments via public JSON (no API key needed) - Fun judge v2: humor scoring baked into narrative - Cookie consent before browser scanning - 10,000 free ScrapeCreators calls - 1,012 tests Thank you to the community contributors whose issues and PRs shaped v3: @uppinote20 (#143), @zerone0x (#134, #136), @thinkun (#116), @thomasmktong (#124), @fanispoulinakisai-boop (#100), @pejmanjohn (#78), @zl190 (#115), @hnshah (#84, #85, #86) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-08 10:52:23 -07:00
parent 61904b31e3
commit 0a9ff16dfc
397 changed files with 21427 additions and 53106 deletions
@@ -0,0 +1,89 @@
+import sys
+import unittest
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "scripts"))
+
+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-preview",
+                rerank_model="gemini-3.1-flash-lite-preview",
+            ),
+            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()