Why API access enables integration in Prompt Engineering / GenAI - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to call an API endpoint using Python's requests library.

Prompt Engineering / GenAI

import requests
response = requests.[1]('https://api.example.com/data')
print(response.status_code)

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

Aget

Bpost

Cput

Ddelete

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'post' instead of 'get' when only fetching data.

The get method is used to retrieve data from an API endpoint.

2fill in blank

medium

Complete the code to extract JSON data from the API response.

Prompt Engineering / GenAI

import requests
response = requests.get('https://api.example.com/data')
data = response.[1]()
print(data)

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

Atext

Bcontent

Cjson

Draw

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'text' returns raw string, not parsed JSON.

The json() method parses the response content as JSON, which is common for API data.

3fill in blank

hard

Fix the error in the code to send a POST request with JSON data.

Prompt Engineering / GenAI

import requests
payload = {'name': 'Alice', 'age': 30}
response = requests.post('https://api.example.com/users', [1]=payload)
print(response.status_code)

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

Adata

Bjson

Cparams

Dheaders

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'data' sends form data, not JSON, causing API errors.

Using the json parameter sends the payload as JSON, which APIs expect for POST data.

4fill in blank

hard

Fill both blanks to check if the API response was successful and print the JSON content.

Prompt Engineering / GenAI

import requests
response = requests.get('https://api.example.com/data')
if response.[1] == [2]:
    print(response.json())

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

Astatus_code

B200

Cok

Djson

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ok' which is a boolean, not a numeric code.

The status_code attribute holds the HTTP status code. 200 means success.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that filters API data for items with 'active' status.

Prompt Engineering / GenAI

data = [{'id': 1, 'status': 'active'}, {'id': 2, 'status': 'inactive'}, {'id': 3, 'status': 'active'}]
active_items = {item['id']: item for item in data if item[1]'status'] [2] [3]
print(active_items)

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

A[

B==

C'active'

D['

Attempts:

3 left

💡 Hint

Common Mistakes

Using parentheses instead of brackets for dictionary keys.

The code checks if item['status'] == 'active' to filter active items.

Practice

1. Why does API access make it easier to add AI features to existing software?

easy

A. Because it allows software to talk to AI services without building AI from scratch

B. Because it requires rewriting the entire software code

C. Because it only works with one programming language

D. Because it stores all data locally on the user's device

Solution

1. Step 1: Understand what API access means

   API access lets software send requests and get responses from AI services easily.

2. Step 2: Connect API access to software integration

   This means developers can add AI features without building AI themselves, saving time and effort.

3. Final Answer:

   Because it allows software to talk to AI services without building AI from scratch -> Option A

4. Quick Check:

   API access enables easy AI integration [OK]

Hint: API means easy connection without rebuilding AI [OK]

Common Mistakes:

• Thinking API requires rewriting all code
• Believing API works only with one language
• Assuming API stores data locally

2. Which of the following is the correct way to call an AI API in Python?

easy

A. response = api.call['generate_text', prompt='Hello']

B. response = api.call generate_text prompt='Hello'

C. response = api.call('generate_text' prompt='Hello')

D. response = api.call('generate_text', prompt='Hello')

Solution

1. Step 1: Review Python function call syntax

   Functions are called with parentheses and arguments inside, separated by commas.

2. Step 2: Check each option for correct syntax

   response = api.call('generate_text', prompt='Hello') uses correct parentheses and argument format. Others miss commas, parentheses, or use wrong brackets.

3. Final Answer:

   response = api.call('generate_text', prompt='Hello') -> Option D

4. Quick Check:

   Correct Python function call syntax [OK]

Hint: Look for parentheses and commas in function calls [OK]

Common Mistakes:

• Missing commas between arguments
• Using square brackets instead of parentheses
• Omitting parentheses around arguments

3. Given this Python code calling an AI API:

response = api.call('translate', text='Hello', target_lang='es')
print(response)

What is the expected output if the API works correctly?

medium

A. 'Hola'

B. 'Hello'

C. Error: missing target language

D. 'Bonjour'

Solution

1. Step 1: Understand the API call parameters

   The API is asked to translate 'Hello' into Spanish (target_lang='es').

2. Step 2: Identify the correct translation output

   'Hola' is the Spanish word for 'Hello', so the API should return 'Hola'.

3. Final Answer:

   'Hola' -> Option A

4. Quick Check:

   Translate 'Hello' to Spanish = 'Hola' [OK]

Hint: Match target language code to correct translation [OK]

Common Mistakes:

• Confusing language codes
• Expecting original text as output
• Assuming error without missing parameters

4. This code tries to call an AI API but causes an error:

response = api.call('summarize', text='Long article')
print(response['summary'])

What is the likely cause of the error?

medium

A. The function call syntax is incorrect

B. The 'text' parameter is missing

C. The API response is not a dictionary with 'summary' key

D. The API call is missing authentication

Solution

1. Step 1: Analyze the code's access to response

   The code tries to get response['summary'], assuming response is a dictionary with that key.

2. Step 2: Consider API response format

   If the API returns a string or different structure, accessing ['summary'] causes an error.

3. Final Answer:

   The API response is not a dictionary with 'summary' key -> Option C

4. Quick Check:

   Accessing missing key causes error [OK]

Hint: Check if response is dict before accessing keys [OK]

Common Mistakes:

• Assuming all API responses are dicts
• Ignoring missing parameters
• Blaming syntax without checking response type

5. You want to integrate an AI chatbot into your website using API access. Which approach best ensures easy updates and scaling?

hard

A. Download AI software and run it only on one user's device

B. Use a cloud-based AI API service that handles updates and scaling automatically

C. Embed AI code directly into your website without API calls

D. Build your own AI model from scratch and host it on your local server

Solution

1. Step 1: Understand integration needs for updates and scaling

   Easy updates and scaling require the AI system to be managed externally and accessible via API.

2. Step 2: Evaluate each option for update and scaling ease

   Cloud-based AI API services automatically update and scale. Other options require manual work or limit access.

3. Final Answer:

   Use a cloud-based AI API service that handles updates and scaling automatically -> Option B

4. Quick Check:

   Cloud API services simplify updates and scaling [OK]

Hint: Cloud APIs handle updates and scaling for you [OK]

Common Mistakes:

• Thinking local hosting is easier to scale
• Embedding AI code limits flexibility
• Running AI on one device limits users