Add Stage 2.8 recall, quality gate, retries, and publish idempotency

tests/test_candidate_recall.py

@@ -0,0 +1,79 @@
+import unittest
+
+from ai_daily_report.candidate_recall import recall_semantic_candidates
+from ai_daily_report.models import NewsItem
+from ai_daily_report.normalize import normalize_title
+
+
+def item(item_id, title, summary):
+    return NewsItem(
+        id=item_id,
+        source_group="AI HOT",
+        source_label="AI HOT",
+        source_role="primary",
+        source_priority=10,
+        title_raw=title,
+        title_norm=normalize_title(title),
+        summary_raw=summary,
+        url=f"https://example.com/{item_id}",
+        canonical_url=f"https://example.com/{item_id}",
+    )
+
+
+class CandidateRecallTests(unittest.TestCase):
+    def test_recalls_shared_event_entities_when_titles_are_not_stage2_similar(self):
+        items = [
+            item(
+                "a",
+                "Anthropic 被曝开发 Claude Fable",
+                "Anthropic 正在开发名为 Claude Fable 和 Claude Mythos 的新产品。",
+            ),
+            item(
+                "b",
+                "Claude Mythos 进入内部测试",
+                "Anthropic 的 Claude Mythos 与 Claude Fable 面向内容生成场景。",
+            ),
+            item(
+                "c",
+                "Gemini CLI 发布更新",
+                "Google 为 Gemini CLI 增加新的开发者命令。",
+            ),
+        ]
+
+        candidates, report = recall_semantic_candidates(items, existing_candidates=[])
+
+        candidate_sets = [set(candidate["item_ids"]) for candidate in candidates]
+        self.assertIn({"a", "b"}, candidate_sets)
+        self.assertNotIn({"a", "c"}, candidate_sets)
+        self.assertEqual(report["candidate_group_count"], 1)
+        self.assertEqual(candidates[0]["reason"], "strong_entity_overlap")
+
+    def test_does_not_group_same_company_different_products_without_event_overlap(self):
+        items = [
+            item("gemini", "Google 发布 Gemini CLI", "Google 发布面向开发者的 Gemini CLI 工具。"),
+            item("gemma", "Google 开源 Gemma 3n", "Google 开源 Gemma 3n 模型，面向端侧部署。"),
+        ]
+
+        candidates, report = recall_semantic_candidates(items, existing_candidates=[])
+
+        self.assertEqual(candidates, [])
+        self.assertEqual(report["candidate_group_count"], 0)
+
+    def test_preserves_existing_candidates_and_adds_new_ones_without_duplicates(self):
+        items = [
+            item("a", "Anthropic 发布 Claude Fable", "Claude Fable 与 Claude Mythos 同时曝光。"),
+            item("b", "Claude Mythos 新功能曝光", "Claude Mythos 和 Claude Fable 是 Anthropic 新项目。"),
+        ]
+
+        candidates, report = recall_semantic_candidates(
+            items,
+            existing_candidates=[{"item_ids": ["a", "b"], "reason": "title_similarity"}],
+        )
+
+        self.assertEqual(len(candidates), 1)
+        self.assertEqual(candidates[0]["reason"], "title_similarity")
+        self.assertEqual(report["existing_candidate_group_count"], 1)
+
+
+if __name__ == "__main__":
+    unittest.main()