#
Quick Self-Check (ungraded)

What?! Another Quiz? We know, we know, … 😅 But this short, ungraded quiz is here to help you reinforce key concepts you’ve just learned.

This quiz covers agent workflows and interactions - essential components for building effective AI agents.

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Q1: What is the purpose of AgentWorkflow in LlamaIndex?

To run one or more agents with tools To create a single agent that can query your data without memory To automatically build tools for agents To manage agent memory and state

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Q2: What object is used for keeping track of the state of the workflow?

State Context WorkflowState Management

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Q3: Which method should be used if you want an agent to remember previous interactions?

run(query_str) chat(query_str, ctx=ctx) interact(query_str) run(query_str, ctx=ctx)

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Q4: What is a key feature of Agentic RAG?

It can only use document-based tools, to answer questions in a RAG workflow It automatically answers questions without tools, like a chatbot It can decide to use any tool to answer questions, including RAG tools It only works with Function Calling Agents

Got it? Great! Now let’s do a brief recap of the unit!

Update on GitHub