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LangChain and AI Application DevelopmenteasyMultiple ChoiceObjective-mapped

1Z0-1127-25 LangChain and AI Application Development Practice Question

Which LangChain abstraction is responsible for storing and retrieving conversation history to maintain context across multiple turns in a chatbot?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Memory

Memory in LangChain is designed to store and retrieve conversation history, enabling context-aware responses. Models generate text, chains orchestrate steps, and agents decide actions — none handle history directly.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Memory

    Why this is correct

    Memory explicitly stores and manages conversation history for context across turns.

  • Agent

    Why it's wrong here

    Agents decide which tools to use but delegate history management to Memory.

  • Chain

    Why it's wrong here

    Chains compose sequences of calls but do not manage history themselves; they rely on Memory.

  • Model

    Why it's wrong here

    Models generate text but do not inherently store conversation history.

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