feat: organize news packages into verified event timelines

Add optional events, evidence-backed timelines, versioned package corrections and bounded historical reprocessing. Keep independent packages readable and isolate retries by failed stage. Configure reasoning effort per model stage and refresh default news Skill drafts without publishing.

scripts/smoke_risk.py

@@ -12,7 +12,7 @@ from alphapulse.ai.skills import create_node, add_version, published_skills
 from alphapulse.api.settings import delete_provider
 from alphapulse.core.db import SessionLocal, engine
 from alphapulse.models import AiProvider, NewsItem, SkillNode, SkillVersion
-from alphapulse.models.risk import RiskSettings, RiskSnapshot, ArticleAnalysis, NewsSummary, SummaryArticle, SummaryVersion, PackageEvidence
+from alphapulse.models.risk import RiskSettings, RiskSnapshot, ArticleAnalysis, NewsSummary, SummaryArticle, SummaryVersion, PackageEvidence, GroupingVersion
 from alphapulse.news_risk import service, pipeline, worker, briefing
 
 
@@ -35,7 +35,8 @@ async def main():
         await session.flush()
         assert not await published_skills(session), 'News skills leaked into Chat or trading'
         session.add(RiskSettings(id=1, enabled=True, provider_id=provider_id, model='luna', second_provider_id=provider_id,
-            second_model='reviewer', third_provider_id=provider_id, third_model='senior', start_at=now-timedelta(minutes=2), **skill_ids))
+            second_model='reviewer', third_provider_id=provider_id, third_model='senior',
+            reasoning_effort='low', second_reasoning_effort='high', third_reasoning_effort='xhigh', start_at=now-timedelta(minutes=2), **skill_ids))
         for key, at, content in [('old', now-timedelta(days=1), 'old'), ('first', now-timedelta(minutes=1), 'original'),
                                   ('duplicate', now-timedelta(seconds=30), 'repost')]:
             session.add(NewsItem(source_code='wscn_news', external_id='ci-news-'+key, url='https://example.invalid/'+key,
@@ -47,6 +48,7 @@ async def main():
     finish_during_grouping = False
     async def stream(provider, system, messages, tools, effort):
         nonlocal inject_update, finish_during_grouping
+        assert effort == {'luna': 'low', 'reviewer': 'high', 'senior': 'xhigh'}[provider.model]
         data = json.loads(messages[0]['text']); calls.append((provider.model, data))
         if 'article' in data:
             assert provider.model == 'luna'
@@ -54,8 +56,8 @@ async def main():
                 finish_during_grouping = False
                 await worker.summarize()
             candidates = data['candidates']
-            result = pipeline.Grouping( reason='Financial event', events=[pipeline.Match(
-                event_id=candidates[0]['id'] if candidates else None, group_key=None if candidates else 'security',
+            result = pipeline.Grouping( reason='Financial event', packages=[pipeline.Match(
+                package_id=candidates[0]['id'] if candidates else None, group_key=None if candidates else 'security',
                 title='Exchange security incident', category='security', entities=['Exchange'], fact='incident',
                 evidence=data['article']['title'], urgent=True, tags=['Exchange'], content_kind='report')])
         elif data.get('task') == 'event':
@@ -71,7 +73,7 @@ async def main():
             result = pipeline.EventResult(id=data['id'], title='Exchange security incident', summary='Correction' if correction else 'Incident',
                 category='security', entities=['Exchange'], risk_stars=1 if correction else 5, importance_stars=5, direction='unknown',
                 verification='refuted' if correction else 'reported', confidence='low', reasoning='Synthetic', uncertainty='Synthetic',
-                facts='Synthetic', timeline='Synthetic',
+                timeline_points=[dict(occurred_at=None, time_precision='unknown', time_text='Unknown', reported_at=None, description='Synthetic', verification='insufficient', evidence_refs=[{'article_id':a['id'],'quote':a['title']} for a in data['articles']])], facts='Synthetic', timeline='Synthetic',
                 asset_impacts='Exchange', opinions='Uncertain', counter_evidence='Unknown', watchpoints='Updates', claims=[pipeline.Claim(statement='Synthetic', verdict='insufficient', evidence_refs=[])], related_packages=[], excluded_article_ids=[],
                 evidence_refs=[pipeline.Evidence(article_id=a['id'], quote=a['title']) for a in data['articles']])
         elif data.get('task') == 'ranking':
@@ -161,7 +163,7 @@ async def main():
         print('Three-stage packages: scope, cutoff, grouping, reposts, revisions, corrections, peak risk, retained success, outlook and provider isolation passed')
     finally:
         async with SessionLocal() as session:
-            for model in (PackageEvidence, SummaryVersion, SummaryArticle, NewsSummary, ArticleAnalysis, RiskSnapshot, RiskSettings):
+            for model in (GroupingVersion, PackageEvidence, SummaryVersion, SummaryArticle, NewsSummary, ArticleAnalysis, RiskSnapshot, RiskSettings):
                 await session.execute(delete(model))
             await session.execute(delete(NewsItem).where(NewsItem.external_id.startswith('ci-news-')))
             await session.execute(delete(AiProvider).where(AiProvider.id == provider_id))