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AlphaPulse/backend/tests/test_news_tuning.py
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fix(news): compact large synthesis inputs by package
2026-11-02 19:17:14 +08:00

137 lines
7.4 KiB
Python

"""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