fix: init_data.py补全缺失字段+userorgid为None兜底(空串),支持重复执行
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@ -54,7 +54,7 @@ async def batch_sync_call_fact(sor, source_table, batch_size=1000):
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if not rows:
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break
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print(f' [{source_table}] batch offset={offset} rows={len(rows)}')
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print(' [' + source_table + '] batch offset=' + str(offset) + ' rows=' + str(len(rows)))
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for r in rows:
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r = DictObject(r)
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@ -73,16 +73,21 @@ async def batch_sync_call_fact(sor, source_table, batch_size=1000):
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total_skipped += 1
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continue
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currency = getattr(r, 'amount_currency', None) or 'CNY'
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amount = getattr(r, 'amount', 0) or 0
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userorgid = getattr(r, 'userorgid', None)
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distributor_orgid = getattr(r, 'distributor_orgid', None)
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ns = {
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'id': getID(),
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'luid': r.id,
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'llmid': r.llmid,
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'model': r.llm_model,
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'model': r.llm_model or '',
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'catelogid': r.catelogid or '',
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'userid': r.userid,
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'userorgid': r.userorgid,
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'ownerid': r.ownerid,
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'providerid': r.providerid,
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'userid': r.userid or '',
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'userorgid': userorgid or '',
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'ownerid': r.ownerid or '',
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'providerid': r.providerid or '',
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'call_date': r.use_date or call_time.strftime('%Y-%m-%d'),
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'call_hour': call_time.hour,
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'call_time': r.use_time,
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@ -91,15 +96,18 @@ async def batch_sync_call_fact(sor, source_table, batch_size=1000):
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'prompt_tokens': prompt_tokens,
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'completion_tokens': completion_tokens,
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'status': r.status or 'SUCCEEDED',
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'amount': r.amount or 0,
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'currency': getattr(r, 'amount_currency', None) or 'CNY',
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'amount': amount,
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'currency': currency,
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'amount_cny': amount,
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'distributor_orgid': distributor_orgid or '',
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'sale_userid': '',
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}
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await sor.C('dm_model_call_fact', ns)
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total_inserted += 1
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offset += batch_size
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print(f' [{source_table}] done: inserted={total_inserted}, skipped={total_skipped}')
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print(' [' + source_table + '] done: inserted=' + str(total_inserted) + ', skipped=' + str(total_skipped))
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return total_inserted, total_skipped
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@ -112,7 +120,7 @@ async def batch_aggregate_history(sor):
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{}
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)
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dates = [r['call_date'].strftime('%Y-%m-%d') if hasattr(r['call_date'], 'strftime') else str(r['call_date']) for r in rows]
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print(f' aggregating {len(dates)} distinct dates...')
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print(' aggregating ' + str(len(dates)) + ' distinct dates...')
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for d in dates:
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await aggregate_daily_perf(sor, stat_date=d)
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