A Generative AI Engineer is using LangGraph to define multiple tools in a single agentic application. They want to enable the main orchestrator LLM to decide on its own which tools are most appropriate to call for a given prompt. To do this, they must determine the general flow of the code. Which sequence will do this?

• A. 1. Define or import the tools 2. Add tools and LLM to the agent 3. Create the ReAct agent
• B. 1. Define or import the tools 2. Define the agent 3. Initialize the agent with ReAct, the LLM, and the tools
• C. 1. Define the tools inside the agents 2. Load the agents into the LLM 3. Instruct the LLM to use COT reasoning to determine the appropriate agent
• D. 1. Define the tools 2. Load each tool into a separate agent 3. Instruct the LLM to use ReAct to call the appropriate agent

A Generative AI Engineer is building an LLM to generate article summaries in the form of a type of poem, such as a haiku, given the article content. However, the initial output from the LLM does not match the desired tone or style.
Which approach will NOT improve the LLM's response to achieve the desired response?

• A. Use a neutralizer to normalize the tone and style of the underlying documents
• B. Provide the LLM with a prompt that explicitly instructs it to generate text in the desired tone and style
• C. Include few-shot examples in the prompt to the LLM
• D. Fine-tune the LLM on a dataset of desired tone and style

A Generative AI Engineer received the following business requirements for an external chatbot.
The chatbot needs to know what types of questions the user asks and routes to appropriate models to answer the questions. For example, the user might ask about upcoming event details. Another user might ask about purchasing tickets for a particular event.
What is an ideal workflow for such a chatbot?

• A. The chatbot should only look at previous event information
• B. There should be two different chatbots handling different types of user queries.
• C. The chatbot should only process payments
• D. The chatbot should be implemented as a multi-step LLM workflow. First, identify the type of question asked, then route the question to the appropriate model. If it's an upcoming event question, send the query to a text-to-SQL model. If it's about ticket purchasing, the customer should be redirected to a payment platform.

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?

• A. Use an LLM to summarize the latest news articles and lookup stock tickers from the summaries to find stock prices.
• B. Download and store news articles and stock price information in a vector store. Use a RAG architecture to retrieve and generate at runtime.
• C. Create an agent with tools for SQL querying of Delta tables and web searching, provide retrieved values to an LLM for generation of response.
• D. Query the Delta table for volatile stock prices and use an LLM to generate a search query to investigate potential causes of the stock volatility.