Workflow orchestration across agents in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize a workflow orchestrator with a list of agents.

Agentic AI

orchestrator = WorkflowOrchestrator(agents=[1])

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

Aagent1, agent2, agent3

B'agent1, agent2, agent3'

C{'agent1', 'agent2', 'agent3'}

D['agent1', 'agent2', 'agent3']

Attempts:

3 left

💡 Hint

Common Mistakes

Passing agents as a single string instead of a list.

Using curly braces which create a set, not a list.

The agents parameter expects a list of agent names, so a list literal with strings is correct.

2fill in blank

medium

Complete the code to add a task to the orchestrator's workflow.

Agentic AI

orchestrator.add_task([1])

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

A['data_cleaning']

Bdata_cleaning

C'data_cleaning'

D{'data_cleaning'}

Attempts:

3 left

💡 Hint

Common Mistakes

Passing task name without quotes causing a NameError.

Passing a list or set instead of a string.

The add_task method expects the task name as a string, so it must be quoted.

3fill in blank

hard

Fix the error in the code to execute the workflow and get results.

Agentic AI

results = orchestrator.[1]()

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

Arun

Bexecute

Cstart

Dlaunch

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'run()' which is not defined in the orchestrator.

Using 'start()' or 'launch()' which are invalid method names.

The correct method to start the workflow execution is 'execute()'.

4fill in blank

hard

Fill both blanks to create a dictionary mapping agent names to their statuses.

Agentic AI

status_map = [1]: [2] for [1] in agents

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

Aagent

Bget_status(agent)

Cstatus

Dagent_status

Attempts:

3 left

💡 Hint

Common Mistakes

Using the same variable name for key and value without function call.

Using undefined variables like 'status' or 'agent_status'.

We use 'agent' as the loop variable and call 'get_status(agent)' to get each agent's status.

5fill in blank

hard

Fill all three blanks to filter tasks that are completed and create a list of their names.

Agentic AI

completed_tasks = [task[1] for task in tasks if task.status [2] 'completed' and task.priority [3] 1]

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

A.name

B==

C<=

D!=

Attempts:

3 left

💡 Hint

Common Mistakes

Using '!=' instead of '==' for status check.

Using wrong comparison operators for priority.

Forgetting to access the task name with '.name'.

We access task.name, check if status equals 'completed', and priority less or equal to 1.

Practice

1. What is the main purpose of workflow orchestration across AI agents?

easy

A. To replace human decision-making completely

B. To organize tasks and coordinate multiple AI agents step-by-step

C. To store large amounts of data for AI agents

D. To train a single AI model faster

Solution

1. Step 1: Understand workflow orchestration

   Workflow orchestration means managing how different AI agents work together in order.

2. Step 2: Identify the main goal

   The goal is to organize tasks and share data smoothly between agents, not just training or storage.

3. Final Answer:

   To organize tasks and coordinate multiple AI agents step-by-step -> Option B

4. Quick Check:

   Workflow orchestration = Organize tasks [OK]

Hint: Think: Who manages the team of AI agents? [OK]

Common Mistakes:

• Confusing orchestration with data storage
• Thinking it only speeds up training
• Assuming it replaces humans fully

2. Which syntax correctly defines a simple orchestrator function that calls two agents sequentially in Python?

easy

A. def orchestrate():\n agent1()\n agent2()

B. function orchestrate { agent1(); agent2(); }

C. orchestrate() => { agent1(); agent2(); }

D. def orchestrate[]: agent1() agent2()

Solution

1. Step 1: Identify correct Python function syntax

   Python functions use 'def name():' and indentation for the body.

2. Step 2: Check each option

   def orchestrate():\n agent1()\n agent2() uses correct Python syntax; others use JavaScript or invalid syntax.

3. Final Answer:

   def orchestrate():\n agent1()\n agent2() -> Option A

4. Quick Check:

   Python function = def + colon + indent [OK]

Hint: Python functions start with 'def' and use indentation [OK]

Common Mistakes:

• Using JavaScript or other language syntax in Python
• Missing colon after function name
• Not indenting function body

3. Given this Python code for orchestrating agents:

def agent1():
    return 'data1'
def agent2(input_data):
    return input_data + '_processed'
def orchestrate():
    d1 = agent1()
    d2 = agent2(d1)
    return d2
print(orchestrate())

What is the output?

medium

A. data1_processed

B. data1

C. processed_data1

D. None

Solution

1. Step 1: Trace agent1() output

   agent1() returns 'data1', stored in d1.

2. Step 2: Trace agent2(d1) output

   agent2('data1') returns 'data1_processed', stored in d2.

3. Step 3: Return and print d2

   orchestrate() returns 'data1_processed', which is printed.

4. Final Answer:

   data1_processed -> Option A

5. Quick Check:

   agent2 output = input + '_processed' [OK]

Hint: Follow data flow step-by-step through functions [OK]

Common Mistakes:

• Ignoring return values
• Confusing input and output of agents
• Assuming print shows None

4. This orchestrator code has an error:

def agent1():
    return 'step1'
def agent2(data):
    return data + ' step2'
def orchestrate():
    d1 = agent1
    d2 = agent2(d1)
    return d2
print(orchestrate())

What is the error and how to fix it?

medium

A. agent2 should not take any arguments; remove data parameter

B. print statement syntax is wrong; use print[orchestrate()]

C. orchestrate() should not return anything; remove return

D. agent1 is missing parentheses; fix by calling agent1()

Solution

1. Step 1: Identify how agent1 is used

   agent1 is assigned without parentheses, so d1 is a function, not a string.

2. Step 2: Fix by calling agent1()

   Change d1 = agent1 to d1 = agent1() to get the return value.

3. Final Answer:

   agent1 is missing parentheses; fix by calling agent1() -> Option D

4. Quick Check:

   Function call needs () [OK]

Hint: Remember: functions need () to run and return values [OK]

Common Mistakes:

• Confusing function object with function call
• Changing unrelated parts like print syntax
• Removing needed parameters

5. You want to design a workflow where Agent A fetches data, Agent B cleans it, and Agent C analyzes it. Which orchestration approach best ensures data flows correctly and each step waits for the previous one?

hard

A. Call Agent C first, then Agent B, then Agent A

B. Run all agents in parallel without waiting for outputs

C. Use a sequential orchestrator that calls Agent A, then B with A's output, then C with B's output

D. Let each agent run independently and save results to separate files

Solution

1. Step 1: Understand the workflow dependencies

   Agent B needs data from Agent A, and Agent C needs data from Agent B, so order matters.

2. Step 2: Choose orchestration that respects order

   Sequential orchestration ensures each agent runs after the previous finishes and passes data forward.

3. Final Answer:

   Use a sequential orchestrator that calls Agent A, then B with A's output, then C with B's output -> Option C

4. Quick Check:

   Sequential calls = correct data flow [OK]

Hint: Follow data dependencies step-by-step in order [OK]

Common Mistakes:

• Running agents in parallel ignoring dependencies
• Reversing the order of agents
• Letting agents save results separately without coordination