Quiz for LangGraph and Agentic AI module#
No. |
Training Unit |
Lecture |
Training content |
Question |
Level |
Mark |
Answer |
Answer Option A |
Answer Option B |
Answer Option C |
Answer Option D |
|---|---|---|---|---|---|---|---|---|---|---|---|
1 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
HITL |
What is a primary use case for “Human-in-the-Loop” (HITL) mechanisms? |
Easy |
1 |
A |
Approval of high-stakes actions (e.g., money transfers, data deletion). |
Increasing the speed of the agent’s responses. |
Reducing the number of tokens used by the LLM. |
Replacing the LLM for simple tasks. |
2 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Interrupts |
In LangGraph, where can you set an “Interrupt” to pause execution? |
Medium |
1 |
B |
Inside the LLM’s system prompt. |
In the |
Only at the very beginning of the graph. |
In the database configuration. |
3 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Persistence |
What is the role of a “Checkpointer” in a LangGraph application? |
Easy |
1 |
C |
To check the code for syntax errors. |
To maintain a list of active users. |
To automatically persist and restore the graph state between executions. |
To limit the rate of API calls. |
4 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Isolation |
How does LangGraph isolate different user conversations when using persistence? |
Medium |
1 |
B |
By using different Python scripts for each user. |
By using a unique |
By creating a new database for every single turn. |
By clearing the memory after every message. |
5 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Resuming |
How do you resume a graph execution after it has been paused for human approval? |
Medium |
1 |
C |
Restarting the script from the beginning. |
Calling a manual |
Invoking the graph again with the same |
The graph resumes automatically after a timeout. |
6 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
State Updates |
Which method allows an administrator to manually modify the state of a paused graph? |
Hard |
1 |
A |
|
|
|
|
7 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Time Travel |
What does “Time Travel” refer to in LangGraph checkpointers? |
Medium |
1 |
B |
Running the model with future data. |
Inspecting or replaying the graph state from a specific past checkpoint ID. |
Accelerating the LLM inference speed. |
predicting the next 10 user messages. |
8 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
MemorySaver |
What is the primary limitation of the |
Easy |
1 |
A |
All state data is lost when the process or server is restarted. |
It is too slow for use in development labs. |
It requires a complex PostgreSQL setup. |
It can only store one thread at a time. |
9 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Savers |
Which checkpointer is recommended for production environments requiring high availability and scalability? |
Medium |
1 |
D |
|
|
|
|
10 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
State Updates |
What is the specific purpose of the |
Hard |
1 |
B |
To rename a node in the graph. |
To simulate that the state update was generated by a specific node (e.g., for routing). |
To delete a node from the workflow. |
To create a temporary branch in the graph. |
11 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
HITL |
Why is HITL required for financial transfers? |
Easy |
1 |
C |
Grammar check. |
System speed. |
Oversight for irreversible actions. |
Model training. |
12 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Interrupts |
interrupt_after pauses execution… |
Medium |
1 |
D |
Before the first node. |
After the LLM thinks. |
When the API fails. |
After a specific node finishes. |
13 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Interrupts |
What happens at an interrupt point? |
Hard |
1 |
A |
Execution stops and returns to caller. |
The program crashes. |
Waits for keyboard input. |
History is deleted. |
14 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Savers |
Benefit of SQLiteSaver over MemorySaver? |
Medium |
1 |
B |
Distributed clusters. |
Persistence via local file. |
Native prompt execution. |
Zero disk space. |
15 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Isolation |
Every thread in a checkpointer is unique by… |
Medium |
1 |
C |
User IP. |
System prompt. |
thread_id. |
Timestamp. |
16 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
State Updates |
Manual state updates can… |
Hard |
1 |
D |
Crash the graph. |
Only be done by humans. |
Change LLM weights. |
Skip nodes or fix stuck workflows. |
17 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Time Travel |
To replay from a checkpoint, you need the… |
Hard |
1 |
A |
thread_id and checkpoint_id. |
Admin password. |
Graph source code. |
Python version. |
18 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Persistence |
A checkpoint contains state values and… |
Hard |
1 |
B |
Prompt templates. |
The next node to execute. |
User emails. |
API keys. |
19 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Persistence |
Long-term memory is often stored in… |
Medium |
1 |
C |
The checkpointer. |
System prompts. |
External Vector Databases. |
Python dictionaries. |
20 |
Unit 5: Human-in-the-Loop & Persistence |
Lec5 |
Savers |
High availability systems use… |
Easy |
1 |
D |
MemorySaver. |
FileSaver. |
thread_id only. |
PostgresSaver with pooling. |