Challenge - 5 Problems

🎖️

Agent API Mastery

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Test your skills under time pressure!

🧠 conceptual

intermediate

2:00remaining

Understanding the role of the 'Planner' in Agent API design

In an agent API design pattern, what is the primary role of the 'Planner' component?

AIt executes the actions decided by the agent without modification.

BIt decides the sequence of actions the agent should take to achieve its goal.

CIt stores the agent's memory and past interactions for future reference.

DIt handles the user interface and visual representation of the agent.

Attempts:

2 left

💻 code output

intermediate

2:00remaining

Output of agent action execution with error handling

What will be the output of the following agent API code snippet when the action 'fetch_data' fails?

Agentic_ai

class Agent:
    def __init__(self):
        self.actions = {'fetch_data': self.fetch_data}
    def fetch_data(self):
        raise Exception('Network error')
    def execute(self, action_name):
        try:
            return self.actions[action_name]()
        except Exception as e:
            return f'Error: {e}'
agent = Agent()
result = agent.execute('fetch_data')
print(result)

ANetwork error

BException: Network error

CNone

DError: Network error

Attempts:

2 left

❓ model choice

advanced

2:00remaining

Choosing the best agent API pattern for dynamic task switching

Which agent API design pattern best supports dynamic switching between multiple tasks based on real-time input?

AHierarchical pattern with layered decision-making and task delegation.

BReactive pattern that immediately responds to inputs without internal state.

CBatch processing pattern that queues tasks and processes them sequentially.

DStatic pipeline pattern with fixed sequence of operations.

Attempts:

2 left

❓ hyperparameter

advanced

2:00remaining

Impact of 'timeout' hyperparameter in agent API calls

In an agent API design, setting a 'timeout' hyperparameter controls:

AThe maximum time the agent waits for an action to complete before aborting.

BThe number of retries the agent makes after a failed action.

CThe priority level of the agent's tasks in the queue.

DThe size of the memory buffer storing past interactions.

Attempts:

2 left

🔧 debug

expert

3:00remaining

Debugging unexpected agent response in API design

An agent API is designed to return a JSON response with keys 'status' and 'result'. The following code snippet returns {'status': 'success'} but misses 'result'. What is the likely cause?

def agent_response(data):
    if data:
        return {'status': 'success'}
    else:
        return {'status': 'fail', 'result': None}
response = agent_response({'task': 'run'})
print(response)

AThe print statement is missing the 'result' key access.

BThe input data is empty, so the else branch is not executed.

CThe function does not include 'result' in the success case, causing incomplete response.

DThe function should return a string, not a dictionary.

Attempts:

2 left