Retry and fallback logic in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to retry a function call once if it fails.

Agentic AI

try:
    result = perform_task()
except Exception:
    result = [1]()

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

Aretry_task

Bperform_task

Cfallback_task

Dhandle_error

Attempts:

3 left

💡 Hint

Common Mistakes

Calling a fallback function instead of retrying the main task.

Not retrying the function at all.

The code retries the same function 'perform_task' once after catching an exception.

2fill in blank

medium

Complete the code to fallback to an alternative function if the main task fails.

Agentic AI

try:
    result = main_task()
except Exception:
    result = [1]()

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

Aalternative_task

Bmain_task

Cretry_task

Dlog_error

Attempts:

3 left

💡 Hint

Common Mistakes

Retrying the main task instead of falling back.

Logging error instead of handling fallback.

On failure, the code falls back to 'alternative_task' as a backup.

3fill in blank

hard

Fix the error in the retry loop to stop after 3 attempts.

Agentic AI

attempts = 0
while attempts < 3:
    try:
        result = task()
        break
    except Exception:
        attempts [1] 1

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

A+=

B-=

C*=

D/=

Attempts:

3 left

💡 Hint

Common Mistakes

Decreasing the attempts counter causing infinite loop.

Using multiplication or division operators incorrectly.

The attempts counter should increase by 1 each time to limit retries.

4fill in blank

hard

Fill both blanks to implement retry with fallback after 3 failed attempts.

Agentic AI

attempts = 0
while attempts < 3:
    try:
        result = [1]()
        break
    except Exception:
        attempts [2] 1
else:
    result = fallback()

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

Amain_task

Balternative_task

C+=

D-=

Attempts:

3 left

💡 Hint

Common Mistakes

Using fallback function inside the retry loop.

Decreasing attempts counter causing infinite retries.

The code retries 'main_task' increasing attempts by 1, then falls back after 3 failures.

5fill in blank

hard

Fill all three blanks to log errors, retry twice, then fallback.

Agentic AI

import logging
attempts = 0
while attempts < [1]:
    try:
        result = [2]()
        break
    except Exception as e:
        logging.error(str(e))
        attempts [3] 1
else:
    result = fallback()

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

A1

B2

C+=

Dmain_task

Attempts:

3 left

💡 Hint

Common Mistakes

Setting retry count to 1 causing only one attempt.

Not logging errors properly.

Using wrong operator to update attempts.

The code retries 'main_task' twice, logs errors, increments attempts, then falls back.