Handling retrieval failures gracefully in Agentic AI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to catch retrieval errors and return None.

Agentic AI

try:
    result = retrieve_data(query)
except [1]:
    result = None

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

ATypeError

BException

CKeyError

DValueError

Attempts:

3 left

💡 Hint

Common Mistakes

Catching only specific errors like KeyError may miss other failures.

Not catching any error causes the program to crash on failure.

Using Exception catches all errors during retrieval, allowing graceful failure.

2fill in blank

medium

Complete the code to retry retrieval up to 3 times on failure.

Agentic AI

for attempt in range(3):
    try:
        data = retrieve_data(query)
        break
    except [1]:
        continue

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

AException

BTimeoutError

CIndexError

DAttributeError

Attempts:

3 left

💡 Hint

Common Mistakes

Using a narrow exception may miss some errors and stop retries.

Not using try-except inside the loop causes crashes.

Using Exception ensures all errors trigger a retry.

3fill in blank

hard

Fix the error in the retrieval fallback code to handle missing keys.

Agentic AI

try:
    value = data['key']
except [1]:
    value = default_value

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

AValueError

BTypeError

CKeyError

DIndexError

Attempts:

3 left

💡 Hint

Common Mistakes

Catching the wrong error type causes the fallback to fail.

Not catching any error leads to program crash on missing keys.

KeyError is raised when a dictionary key is missing, so catching it allows fallback.

4fill in blank

hard

Fill both blanks to log retrieval failure and return fallback data.

Agentic AI

try:
    result = retrieve_data(query)
except [1] as e:
    logger.[2](f"Retrieval failed: {e}")
    result = fallback_data

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

AException

Berror

Dwarning

Attempts:

3 left

💡 Hint

Common Mistakes

Using a narrow exception misses some errors.

Logging with wrong method name causes runtime errors.

Catching Exception logs the error as a warning and returns fallback data.

5fill in blank

hard

Fill all three blanks to implement a safe retrieval with retry and fallback.

Agentic AI

for attempt in range(3):
    try:
        data = retrieve_data(query)
        break
    except [1]:
        logger.[2](f"Attempt {attempt + 1} failed.")
else:
    data = [3]

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

AException

Bwarning

Cfallback_data

Derror

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong exception type causes missed retries.

Logging with wrong method name causes errors.

Not providing fallback data leads to undefined variables.

This code retries retrieval catching all exceptions, logs warnings on failure, and uses fallback data if all attempts fail.

Practice

1. Why is it important to handle retrieval failures gracefully in agentic AI systems?

easy

A. To keep the AI running smoothly without crashing

B. To make the AI run faster

C. To increase the size of the data retrieved

D. To avoid using any default values

Solution

1. Step 1: Understand retrieval failures

   Retrieval failures happen when the AI cannot get the needed data, which can cause errors.

2. Step 2: Importance of graceful handling

   Handling failures gracefully means preventing crashes and keeping the AI working by managing errors properly.

3. Final Answer:

   To keep the AI running smoothly without crashing -> Option A

4. Quick Check:

   Graceful failure handling = prevent crashes [OK]

Hint: Think about avoiding crashes by handling errors safely [OK]

Common Mistakes:

• Assuming failures speed up the AI
• Ignoring the need for default values
• Believing more data is always retrieved

2. Which Python syntax correctly handles a retrieval failure using try-except?

easy

A. try:
data = retrieve_info()
except Exception:
data = None

B. if data == None:
retrieve_info()
else:
pass

C. try:
data = retrieve_info()
finally:
data = None

D. data = retrieve_info() if data else None

Solution

1. Step 1: Identify try-except usage

   try: data = retrieve_info() except Exception: data = None uses try-except to catch errors during retrieval and sets data to None if an error occurs.

2. Step 2: Check other options for correctness

   Options A, B, and C misuse syntax or logic for error handling.

3. Final Answer:

   try: data = retrieve_info() except Exception: data = None -> Option A

4. Quick Check:

   try-except for errors = try: data = retrieve_info() except Exception: data = None [OK]

Hint: Look for try-except blocks catching exceptions [OK]

Common Mistakes:

• Using if without try-except for errors
• Misusing finally block to handle errors
• Incorrect conditional expressions

3. What will be the output of this code snippet?

def get_data():
    try:
        return None
    except:
        return 'Error'

result = get_data() or 'Default'
print(result)

medium

A. None

B. Default

C. Error

D. Exception

Solution

1. Step 1: Analyze get_data function

   The function returns None without raising an exception, so except block is skipped.

2. Step 2: Evaluate result assignment

   Since get_data() returns None (which is falsey), the expression uses 'Default' instead.

3. Final Answer:

   Default -> Option B

4. Quick Check:

   None or 'Default' = 'Default' [OK]

Hint: Remember None is falsey, so 'or' picks the default [OK]

Common Mistakes:

• Thinking None prints as 'None' string
• Assuming except block runs without error
• Confusing return values with exceptions

4. Identify the error in this code that tries to handle retrieval failure:

def fetch_data():
    try:
        data = retrieve()
    except:
        data = None
    return data

result = fetch_data()
print(result)

medium

A. Data variable is not defined

B. Missing parentheses in retrieve call

C. No return statement in function

D. No specific exception caught in except block

Solution

1. Step 1: Check function structure

   The function calls retrieve() correctly and returns data, so no missing parentheses or return issues.

2. Step 2: Analyze except block

   The except block catches all exceptions without specifying which, which is bad practice and can hide bugs.

3. Final Answer:

   No specific exception caught in except block -> Option D

4. Quick Check:

   Use specific exceptions, not bare except [OK]

Hint: Avoid bare except; specify exceptions to catch [OK]

Common Mistakes:

• Thinking missing parentheses cause error
• Ignoring importance of specific exceptions
• Assuming data is undefined

5. You want your AI agent to retrieve user info but return a safe default if retrieval fails. Which approach is best?

def get_user_info(user_id):
    try:
        info = retrieve_user(user_id)
        if info is None:
            return {'name': 'Guest', 'id': 0}
        return info
    except RetrievalError:
        return {'name': 'Guest', 'id': 0}

hard

A. Return None on failure and handle later

B. Raise error immediately without handling

C. Use try-except and return a default dict on failure or missing data

D. Return empty string on failure

Solution

1. Step 1: Understand retrieval and failure cases

   The function tries to get user info, checks if data is missing (None), and handles exceptions.

2. Step 2: Evaluate handling strategy

   Returning a default dictionary for missing or failed retrieval keeps AI stable and predictable.

3. Final Answer:

   Use try-except and return a default dict on failure or missing data -> Option C

4. Quick Check:

   Safe defaults on failure = Use try-except and return a default dict on failure or missing data [OK]

Hint: Return safe defaults inside try-except for smooth AI [OK]

Common Mistakes:

• Returning None and not handling later
• Raising errors without fallback
• Returning empty strings instead of structured defaults