GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #76
A Generative AI Engineer is creating an LLM-powered application that will need access to up-to- date news articles and stock prices. The design requires the use of stock prices which are stored in…
The correct answer is D. Create an agent with tools for SQL querying of Delta tables and web searching, provide retrieved. Option D is correct because it uses an agent architecture with two purpose-built tools: a SQL tool for querying Delta tables (stock prices) and a web search tool for retrieving up-to-date news articles. The agent routes each part of a query to the appropriate tool and provides…
Question
A Generative AI Engineer is creating an LLM-powered application that will need access to up-to- date news articles and stock prices. The design requires the use of stock prices which are stored in Delta tables and finding the latest relevant news articles by searching the internet. How should the Generative AI Engineer architect their LLM system?
Options
- AUse an LLM to summarize the latest news articles and lookup stock tickers from the summaries to
- BQuery the Delta table for volatile stock prices and use an LLM to generate a search query to
- CDownload and store news articles and stock price information in a vector store. Use a RAG
- DCreate an agent with tools for SQL querying of Delta tables and web searching, provide retrieved
How the community answered
(25 responses)- A8% (2)
- B4% (1)
- C4% (1)
- D84% (21)
Explanation
Option D is correct because it uses an agent architecture with two purpose-built tools: a SQL tool for querying Delta tables (stock prices) and a web search tool for retrieving up-to-date news articles. The agent routes each part of a query to the appropriate tool and provides the combined results as context to the LLM. Option A is backwards (LLM should not drive data lookup). Option B is a partial solution that does not properly address news retrieval. Option C (storing news in a vector store) cannot provide truly real-time news articles.
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