Maswali yanayounganishwa na mwongozo · Kati Kiwango

Maswali ya LangChain

Gundua muundo wa LangChain, mtiririko wa udhibiti wa hali ya juu wa LangGraph, ukatizaji wa binadamu na tathmini ya LangSmith kwa programu za LLM.

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Ni wazo gani kuu nyuma ya LangChain?

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Majibu na maelezo huonekana unapojibu maswali.

  1. Ni wazo gani kuu nyuma ya LangChain?
    • Kutunga na kupanga programu zinazoendeshwa na LLM zenye hatua nyingi
    • Kufundisha mifano mikubwa ya lugha kutoka mwanzo
    • Kupangisha GPU kwa makisio ya mfano
    • Inazalisha picha kutoka kwa vidokezo vya maandishi
  2. Nani aliunda LangChain na takriban lini?
    • Sam Altman mnamo 2020
    • Harrison Chase mwishoni mwa 2022
    • Lukas Biewald mnamo 2017
    • Jerry Liu mnamo 2023
  3. LangGraph inatumika kwa nini ndani ya mfumo ikolojia wa LangChain?
    • Kuchora chati za vipimo vya mafunzo
    • Vidokezo vya kubana ili kuhifadhi tokeni
    • Kuunda mtiririko wa kazi wa wakala wa hali na udhibiti kama grafu
    • Kubadilisha msimbo kati ya lugha za programu
  4. Jukumu kuu la LangSmith ni nini?
    • Inazalisha seti za data sanisi
    • Kutumikia kurasa za wavuti
    • Inasimba funguo za API
    • Kufuatilia, kurekebisha, na kutathmini programu za LLM
  5. Katika LangChain, syntax ya bomba 'huhimiza nini | mfano | wachanganuzi' wanawakilisha?
    • Kutunga vipengele kupitia kiolesura cha Runnable kilichoshirikiwa
    • Amri ya ganda la kuendesha hati
    • Swali la hifadhidata
    • Njia ya kufuta minyororo
  6. What happens when a LangGraph node invokes interrupt() with a checkpointer configured?
    • The graph discards its state and restarts training
    • The graph pauses with state saved, then can resume after external input
    • The graph converts the interrupt into a stateless chain
    • The graph changes the base model weights
  7. What kind of evaluation does LangSmith describe as monitoring application traces in production?
    • Offline evaluation on a fixed pre-deployment dataset only
    • A test that fine-tunes the application’s foundation model
    • Online evaluation that checks selected production runs for quality signals
    • An evaluation that reports only GPU training throughput
  8. What does an offline LangSmith evaluation test?
    • Only GPU utilization during model training
    • Every production user response with no reference examples
    • A guarantee of correctness on unseen inputs
    • An application against a curated dataset before deployment