"""Workflow tuning preserves evidence boundaries and limits expensive work.""" import asyncio from types import SimpleNamespace as N from unittest.mock import AsyncMock, MagicMock import pytest def test_keyword_queries_match_independently_and_escape_literals(trading): from sqlalchemy import select from sqlalchemy.dialects.postgresql import dialect from alphapulse.models.risk import NewsSummary from alphapulse.news_risk.retrieval import terms_for, matching terms = terms_for('小鹏 交付 50%') condition, score = matching(NewsSummary, terms) query = select(NewsSummary.id).where(condition).order_by(score.desc()).compile(dialect=dialect()) assert ' OR ' in str(query) assert any('50/%' in str(v) for v in query.params.values()) assert terms_for('ignored', ['央行']) == ['央行','中国人民银行'] with pytest.raises(ValueError): terms_for(' ') def test_low_star_shortlist_rotates_domains_and_keeps_recent(trading): from alphapulse.news_risk.briefing import shortlist items = [{'id':i,'category':str(i%4),'importance_stars':2,'updated_at':f'2026-11-{i+1:02}'} for i in range(24)] chosen = shortlist(items) assert len(chosen) == 12 assert len({p['category'] for p in chosen[:4]}) == 4 assert chosen[0]['id'] == 23 def test_plan_time_is_distinct_from_occurrence(trading): from alphapulse.news_risk.contracts import PackageTimePoint point = dict(occurred_at=None,time_precision='unknown',time_text='明天',reported_at=None, description='拟发布',verification='partial',evidence_refs=[{'article_id':1,'quote':'明天'}]) value=PackageTimePoint(**point,planned_at='2026-11-03T00:00:00+08:00',planned_precision='day',period_text='2026年10月') assert value.occurred_at is None and value.planned_at.day == 3 with pytest.raises(ValueError): PackageTimePoint(**point,planned_precision='day') def test_attempted_selection_needs_no_date_range(trading): from alphapulse.api.risk import ReprocessIn assert ReprocessIn(selection='attempted',modes=['review']).start is None with pytest.raises(ValueError): ReprocessIn(modes=['review']) def test_exclusive_grouping_does_not_admit_realtime(trading,monkeypatch): from alphapulse.news_risk import scheduler,worker session=MagicMock() session.__aenter__=AsyncMock(return_value=session); session.__aexit__=AsyncMock() session.get=AsyncMock(return_value=N(enabled=True,start_at='configured')) job=N(id=7,settings={'request':{'run_mode':'history_only'}}) session.scalar=AsyncMock(side_effect=[job,1,job]) session.scalars=AsyncMock(return_value=N(all=lambda:[])) monkeypatch.setattr(scheduler,'SessionLocal',lambda:session) enqueue=AsyncMock();outlook=AsyncMock() monkeypatch.setattr(worker,'enqueue',enqueue);monkeypatch.setattr(worker,'outlook',outlook) assert asyncio.run(scheduler.candidate(set(),0)) is None enqueue.assert_not_awaited();outlook.assert_not_awaited() @pytest.mark.parametrize('snapshot_state', [None, 'processing', 'done', 'failed']) def test_exclusive_completion_waits_for_reading_and_then_pauses(trading,snapshot_state,monkeypatch): from alphapulse.news_risk.backfill import reconcile from alphapulse.models.risk import ReprocessJob job=N(id=7,state='running',settings={'request':{'run_mode':'history_only'},'configurations':{'outlook':{'rules':{}}}},failures=[]) from alphapulse.news_risk import events monkeypatch.setattr(events,'reading_inputs',AsyncMock(return_value=[])) settings=N(enabled=True) session=MagicMock() session.get=AsyncMock(side_effect=lambda model,*a,**k: job if model is ReprocessJob else settings) session.scalars=AsyncMock(return_value=N(all=lambda:[])) snapshot=None if snapshot_state is None else N(id=9,state=snapshot_state,error='Synthetic',quotes={}) session.scalar=AsyncMock(side_effect=[None,snapshot]) session.commit=AsyncMock() asyncio.run(reconcile(session,job)) if snapshot_state in (None,'processing'): assert job.state=='running' and settings.enabled else: assert job.state==('done' if snapshot_state=='done' else 'failed') assert not settings.enabled def test_expired_exclusive_preview_never_calls_paid_validation(trading,monkeypatch): from fastapi import HTTPException from alphapulse.api import risk from alphapulse.news_risk import backfill from alphapulse.core import db gate=MagicMock();gate.__aenter__=AsyncMock(return_value=gate);gate.__aexit__=AsyncMock(return_value=False) gate.scalar=AsyncMock(return_value=True);gate.commit=AsyncMock();gate.execute=AsyncMock() monkeypatch.setattr(db,'engine',N(connect=lambda:gate)) monkeypatch.setattr(risk,'default_settings',AsyncMock(return_value=N(enabled=False))) monkeypatch.setattr(backfill,'prepare_start',AsyncMock(side_effect=ValueError('预览已过期'))) validate=AsyncMock();monkeypatch.setattr(risk,'validate_enable',validate) with pytest.raises(HTTPException) as error: asyncio.run(risk.reprocess_start(risk.ReprocessStart(preview_id='a'*24,run_mode='history_only'),MagicMock())) assert error.value.status_code==409 validate.assert_not_awaited() gate.execute.assert_awaited_once() def test_ranking_only_skips_synthesis_and_synthesis_reuses_priority(trading,monkeypatch): from alphapulse.news_risk import briefing inputs=[{'id':1,'revision':2,'importance_stars':3,'result':{'summary':'Synthetic'}}] calls=[] async def complete(provider,system,payload,schema): calls.append(payload['task']) reading={'id':1,'revision':2,'priority':70,'reason':'Verified update'} if schema is briefing.Ranked: return schema(reading=[reading],notes='Synthetic'),{} trend={'summary':'Unknown','conditions':'Unknown','counter_evidence':'Unknown','watchpoints':'Unknown'} return schema(summary='Synthetic',market='Unknown',short_term=trend,medium_term=trend, references=[{**reading,'priority':99,'reason':'Changed'}]),{} monkeypatch.setattr(briefing,'complete',complete) provider=N(max_tokens=100,context_window=20000) ranked=asyncio.run(briefing.generate(provider,'rules',inputs,ranking_only=True)) assert calls==['ranking'] result=asyncio.run(briefing.generate(provider,'rules',inputs,rankings=ranked['reading'])) assert calls==['ranking','synthesis'] assert result['synthesis']['references']==ranked['reading'] def test_large_synthesis_compacts_package_notes_in_batches(trading,monkeypatch): import json from alphapulse.news_risk import briefing inputs=[{'id':i,'revision':1,'importance_stars':3,'result':{'summary':'x'*800}} for i in range(3)] rankings=[{'kind':'package','id':i,'revision':1,'priority':50,'reason':'Read'} for i in range(3)] calls=[] def fits(provider,system,payload,schema): return len(json.dumps(payload)) < 1600 async def complete(provider,system,payload,schema): calls.append(payload['task']) if schema is briefing.Notes: return schema(notes='Compacted'),{} trend={'summary':'Unknown','conditions':'Unknown','counter_evidence':'Unknown','watchpoints':'Unknown'} return schema(summary='Synthetic',market='Unknown',short_term=trend,medium_term=trend,references=[]),{} monkeypatch.setattr(briefing,'fits_context',fits);monkeypatch.setattr(briefing,'complete',complete) result=asyncio.run(briefing.generate(N(),'rules',inputs,rankings=rankings)) assert calls==['synthesis_notes']*3+['synthesis'] assert len(result['reading'])==3