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Quiz for LangGraph and Agentic AI module

No.Training UnitLectureTraining contentQuestionLevelMarkAnswerAnswer Option AAnswer Option BAnswer Option CAnswer Option D
1Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2ReAct PatternWhat does "ReAct" stand for when describing agentic reasoning loops?Easy1AReasoning and Acting.Reading and Acting.Researching and Actuating.Repeating and Acknowledging.
2Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2ReAct PatternIn a standard ReAct loop, what is the "Observe" step specifically responsible for?Medium1CThinking about the next step.Generating a new plan.Receiving and analyzing the results from a tool execution.Synthesizing the final answer for the user.
3Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Multi-Expert AgentsWhy use a "Multi-Expert" pattern (specialized tools) over a single generic web search tool?Medium1BIt reduces API costs and improves speed.It provides specialized domain knowledge and structured reasoning.It simplifies the prompt engineering process.It removes the need for a reasoning-capable LLM.
4Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Prebuilt ComponentsWhat is a major advantage of using the prebuilt ToolNode in LangGraph?Medium1DIt is the only technical way to invoke tools.It provides unlimited free API calls.it executes asynchronous code faster than custom nodes.It automatically handles tool execution, parsing, and error management.
5Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2CoordinatorWhat is the main responsibility of the "Coordinator" node in a multi-expert system?Medium1ATo analyze the query and route it to the correct expert tool or agent.To execute the underlying Python logic of the tools.To only summarize the final answer once all tools finish.To manage the database connection for persistence.
6Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Control FlowHow do you standardly prevent an agent from entering an infinite ReAct loop?Easy1CBy switching to a faster LLM model.By disabling the tool execution node.By implementing a max_iterations check in the routing logic.By only allowing HumanMessage inputs.
7Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Expert ToolsIn a Multi-Expert architecture, how is a specialized "Expert" typically implemented as a tool?Hard1BAs a hardcoded Python logic script.As a tool that invokes a specialized LLM with a domain-specific system prompt.As a separate physical server deployment.As a raw SQL query to a knowledge base.
8Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Message ProtocolWhat specific content in an AIMessage signals that the agent wants to use a tool?Medium1BThe content string contains the word "tool".The tool_calls parameter is populated with tool details.It is followed immediately by a SystemMessage.The role is set to "assistant_tool".
9Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Planning AgentWhat is the role of a "Planning Agent" in advanced agentic workflows?Hard1DTo execute the final code.To store the memory of the conversation.To check for grammar errors.To break down a complex query and decide on a sequence of actions for the coordinator.
10Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2ReflectionWhat does the "Reflection" pattern involve in agentic AI?Medium1AThe agent reviewing its own output or steps to identify and fix errors.The agent showing its thoughts to the user.The database reflecting the latest state.The coordinator mirroring the user's input.
11Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Multi-Expert AgentsWhy is Multi-Expert better than Web Search for analysis?Medium1BLower token cost.Consistent reasoning and synthesis.No knowledge cutoff.Faster execution.
12Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2CoordinatorWhat does the "Think" phase of the Coordinator LLM involve?Medium1AAnalyzing if help is needed and who to call.Writing Python code.Google searching.Saving checkpoints.
13Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2CoordinatorWhich method does a Coordinator use to bind tools?Easy1Dapp.compile()workflow.add_node()llm.invoke()llm.bind_tools([...])
14Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Control FlowWhich variable tracks reasoning loops in the State?Easy1Cmessagesuser_idcurrent_iterationcheckpoint_id
15Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Control FlowWhich condition forces a ReAct agent to END?Medium1ANo tool_calls or max_iterations reached.User stops typing.API key expires.After every tool call.
16Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2CoordinatorHow does a Coordinator execute parallel consultations?Hard1BOpening multiple prompts.Populating multiple items in tool_calls.Re-running the graph.Parallel execution is not supported.
17Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Planning AgentWhat architectural issue does a Planning Agent solve?Medium1CHigh latency.Local hardware limits.Coordinator overload from too many tasks.Bypassing checkpointers.
18Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Multi-Expert AgentsHow does dynamic expert selection work in advanced systems?Hard1DBrowser history check.Random assignment.Exact keyword mapping.Routing prompt returns best expert name.
19Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Multi-Expert AgentsWhat is the purpose of structured synthesis?Easy1ATo combine expert insights into a unified response.To compress JSON state.To translate output to code.To hide tool errors.
20Unit 2: Agentic Patterns: Multi-Expert Research AgentLec2Multi-Expert AgentsWhat is a major trade-off of the Multi-Expert Pattern?Medium1BLower accuracy.Higher cost and latency.No LangGraph support.Requires C++ code.