GENERATIVE-AI-ENGINEER-ASSOCIATE Question #28: Real Exam Question with Answer & Explanation

The correct answer is A: Vector Stores. Vector Stores are essential for knowledge retrieval in an LLM-enabled chat application. They store vector representations of data (e.g., documents or user queries) and facilitate semantic search, allowing the application to retrieve relevant knowledge based on the conversation Co

LLM Application Development and Orchestration

Question

Which TWO chain components are required for building a basic LLM-enabled chat application that includes conversational capabilities, knowledge retrieval, and contextual memory? (Choose two.)

Options

AVector Stores
BConversation Buffer Memory
CExternal tools
DChat loaders
EReact Components

Explanation

Vector Stores are essential for knowledge retrieval in an LLM-enabled chat application. They store vector representations of data (e.g., documents or user queries) and facilitate semantic search, allowing the application to retrieve relevant knowledge based on the conversation Conversation Buffer Memory is crucial for maintaining contextual memory within the chat. It helps the application track and store the history of the conversation, ensuring that the model can

Topics

#LLM Application Components#Conversational Memory#Retrieval Augmented Generation (RAG)#Chatbot Architecture

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