113 lines
2.8 KiB
Plaintext
113 lines
2.8 KiB
Plaintext
# Quick Self-Check (ungraded) [[quiz2]]
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What?! Another Quiz? We know, we know, ... 😅 But this short, ungraded quiz is here to **help you reinforce key concepts you've just learned**.
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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?
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<Question
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choices={[
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{
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text: "To run one or more agents with tools",
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explain: "Yes, the AgentWorkflow is the main way to quickly create a system with one or more agents.",
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correct: true
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},
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{
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text: "To create a single agent that can query your data without memory",
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explain: "No, the AgentWorkflow is more capable than that, the QueryEngine is for simple queries over your data.",
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},
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{
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text: "To automatically build tools for agents",
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explain: "The AgentWorkflow does not build tools, that is the job of the developer.",
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},
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{
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text: "To manage agent memory and state",
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explain: "Managing memory and state is not the primary purpose of AgentWorkflow.",
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}
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]}
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/>
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---
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### Q2: What object is used for keeping track of the state of the workflow?
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<Question
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choices={[
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{
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text: "State",
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explain: "State is not the correct object for workflow state management.",
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},
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{
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text: "Context",
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explain: "Context is the correct object used for keeping track of workflow state.",
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correct: true
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},
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{
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text: "WorkflowState",
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explain: "WorkflowState is not the correct object.",
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},
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{
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text: "Management",
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explain: "Management is not a valid object for workflow state.",
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}
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]}
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/>
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---
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### Q3: Which method should be used if you want an agent to remember previous interactions?
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<Question
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choices={[
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{
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text: "run(query_str)",
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explain: ".run(query_str) does not maintain conversation history.",
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},
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{
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text: "chat(query_str, ctx=ctx)",
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explain: "chat() is not a valid method on workflows.",
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},
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{
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text: "interact(query_str)",
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explain: "interact() is not a valid method for agent interactions.",
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},
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{
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text: "run(query_str, ctx=ctx",
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explain: "By passing in and maintaining the context, we can maintain state!",
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correct: true
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}
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]}
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/>
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---
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### Q4: What is a key feature of Agentic RAG?
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<Question
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choices={[
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{
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text: "It can only use document-based tools, to answer questions in a RAG workflow",
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explain: "Agentic RAG can use different tools, including document-based tools.",
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},
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{
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text: "It automatically answers questions without tools, like a chatbot",
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explain: "Agentic RAG does use tools to answer questions.",
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},
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{
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text: "It can decide to use any tool to answer questions, including RAG tools",
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explain: "Agentic RAG has the flexibility to use different tools to answer questions.",
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correct: true
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},
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{
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text: "It only works with Function Calling Agents",
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explain: "Agentic RAG is not limited to Function Calling Agents.",
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}
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]}
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/>
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---
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Got it? Great! Now let's **do a brief recap of the unit!**
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