Real-world agent applications in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize a real-world agent with a task description.

Agentic AI

agent = RealWorldAgent(task_description=[1])

Drag options to blanks, or click blank then click option'

A12345

BNone

CTrue

D"Schedule meetings"

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number instead of a string

Passing None instead of a description

The task_description should be a string describing the agent's task, such as "Schedule meetings".

2fill in blank

medium

Complete the code to make the agent perform its task and return the result.

Agentic AI

result = agent.[1]()

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Aexecute

Breset

Cinitialize

Dstop

Attempts:

3 left

💡 Hint

Common Mistakes

Using initialize instead of execute

Using stop which ends the agent

The method to perform the agent's task is usually called execute or run; here, execute is correct.

3fill in blank

hard

Fix the error in the code to correctly check if the agent completed the task.

Agentic AI

if agent.status == [1]:
    print("Task completed")

Drag options to blanks, or click blank then click option'

A"done"

B1

C"completed"

DTrue

Attempts:

3 left

💡 Hint

Common Mistakes

Using True instead of 'completed'

Using 'done' which is incorrect

The agent's status is a string 'completed' when the task is done, so the check must be against "completed".

4fill in blank

hard

Fill both blanks to create a dictionary of task results where keys are task names and values are their statuses.

Agentic AI

task_results = {task: agent.[1](task) for task in tasks if agent.[2](task)}

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Aget_status

Bis_active

Crun_task

Dstop_task

Attempts:

3 left

💡 Hint

Common Mistakes

Using run_task instead of get_status

Using stop_task instead of is_active

get_status(task) returns the status, and is_active(task) checks if the task is active.

5fill in blank

hard

Fill all three blanks to filter tasks with priority above 5 and create a summary dictionary with task names and priorities.

Agentic AI

summary = {task[1]: agent.get_priority([2]) for task in tasks if agent.get_priority(task) [3] 5}

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A.upper()

Btask

C>

Dtask.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using .upper() instead of .lower()

Using < instead of > in filter

task.lower() is used for the key, task for the get_priority argument, and the filter uses > 5.