Databricks Certified Generative AI Engineer Associate — Question 66

A Generative AI Engineer needs to design an LLM pipeline to conduct multi-stage reasoning that leverages external tools. To be effective at this, the LLM will need to plan and adapt actions while performing complex reasoning tasks.

Which approach will do this?

Answer options

• A. Train the LLM to generate a single, comprehensive response without interacting with any external tools, relying solely on its pre-trained knowledge.
• B. Use a Chain-of-Thought (CoT) prompting technique to guide the LLM through a series of reasoning steps, then manually input the results from external tools for the final answer.
• C. Implement a framework like ReAct, which allows the LLM to generate reasoning traces and perform task-specific actions that leverage external tools if necessary.
• D. Encourage the LLM to make multiple API calls in sequence without planning or structuring the calls, allowing the LLM to decide when and how to use external tools spontaneously.

Correct answer: C

Explanation

The correct answer, C, describes the ReAct framework, which enables the LLM to create reasoning traces and engage with external tools effectively. Option A is ineffective because it doesn't utilize external tools at all, while B relies on manual input for results, which is not as efficient. Option D lacks structure and planning, which is essential for complex reasoning tasks.