Chatbot development basics in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to initialize a chatbot model using a pre-trained transformer.

Prompt Engineering / GenAI

model = [1]('gpt-3.5-turbo')

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

Ainitialize

BChatbotModel

Ctransformer

Dload_model

Attempts:

3 left

💡 Hint

Common Mistakes

Using a class name instead of a function to load the model.

Using an undefined function like 'initialize'.

The function to load a pre-trained model is usually called load_model or similar. Here, load_model is the correct choice to initialize the chatbot.

2fill in blank

medium

Complete the code to generate a response from the chatbot given a user input.

Prompt Engineering / GenAI

response = model.[1](user_input)

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

Afit

Btrain

Cgenerate

Dpredict

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'train' or 'fit' which are for model training, not response generation.

Using 'predict' which is common in ML but less typical for text generation.

To get a chatbot's reply, we use the generate method which produces text based on input.

3fill in blank

hard

Fix the error in the code to correctly preprocess user input by converting it to lowercase.

Prompt Engineering / GenAI

processed_input = user_input.[1]()

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

Alower

BtoLowerCase

Clowercase

Ddowncase

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'lowercase' which is not a method.

Using JavaScript style 'toLowerCase'.

In Python, the correct method to convert a string to lowercase is 'lower()'.

4fill in blank

hard

Fill both blanks to create a dictionary that maps user intents to responses.

Prompt Engineering / GenAI

responses = { [1]: 'Hello!', [2]: 'Goodbye!'}

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

A'greeting'

B'farewell'

C'hello'

D'bye'

Attempts:

3 left

💡 Hint

Common Mistakes

Using response words as keys instead of intent names.

Using informal keys like 'hello' or 'bye' which are less clear.

The keys should be user intents like 'greeting' and 'farewell' to map to appropriate responses.

5fill in blank

hard

Fill all three blanks to filter user messages that contain the word 'help' and convert them to lowercase.

Prompt Engineering / GenAI

filtered = [msg.[1]() for msg in messages if '[2]' in msg.[3]()]

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

Alower

Bhelp

Clowercase

DHelp

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'lowercase' which is not a valid method.

Checking for 'Help' with uppercase H which misses lowercase matches.

We convert messages to lowercase with 'lower()' and check if 'help' is in the lowercase message.

Practice

1. What is the main purpose of a chatbot in simple terms?

easy

A. To help computers talk with people easily

B. To store large amounts of data

C. To create images from text

D. To run complex math calculations

Solution

1. Step 1: Understand chatbot function

   A chatbot is designed to communicate with people using text or voice.

2. Step 2: Match purpose with options

   Only To help computers talk with people easily describes helping computers talk with people easily.

3. Final Answer:

   To help computers talk with people easily -> Option A

4. Quick Check:

   Chatbot purpose = talk with people [OK]

Hint: Chatbots are for chatting, not storing or calculating [OK]

Common Mistakes:

• Confusing chatbots with data storage systems
• Thinking chatbots create images
• Assuming chatbots do math calculations

2. Which of the following is the correct way to define a simple chatbot response in Python?

easy

A. response = (hello: 'Hi there!')

B. response = {'hello': 'Hi there!'}

C. response = ['hello' => 'Hi there!']

D. response = 'hello' = 'Hi there!'

Solution

1. Step 1: Recall Python dictionary syntax

   Python uses curly braces {} with key: value pairs for dictionaries.

2. Step 2: Check each option

   response = {'hello': 'Hi there!'} uses correct syntax with {'hello': 'Hi there!'}; others use invalid syntax.

3. Final Answer:

   response = {'hello': 'Hi there!'} -> Option B

4. Quick Check:

   Python dict = {'key': 'value'} [OK]

Hint: Python dict uses curly braces and colon for key-value [OK]

Common Mistakes:

• Using => instead of : in Python dictionaries
• Using parentheses instead of braces
• Trying to assign string with = inside quotes

3. What will be the output of this Python code snippet for a chatbot?

responses = {'hi': 'Hello!', 'bye': 'Goodbye!'}
user_input = 'hi'
print(responses.get(user_input, 'I do not understand'))

medium

A. Error

B. Goodbye!

C. I do not understand

D. Hello!

Solution

1. Step 1: Understand dictionary get method

   responses.get(user_input, default) returns value for key or default if key missing.

2. Step 2: Check user_input key in dictionary

   user_input is 'hi', which exists in responses with value 'Hello!'.

3. Final Answer:

   Hello! -> Option D

4. Quick Check:

   Key 'hi' found = 'Hello!' [OK]

Hint: dict.get(key, default) returns value or default if missing [OK]

Common Mistakes:

• Assuming default message prints even if key exists
• Confusing keys 'hi' and 'bye'
• Expecting an error from get method

4. Identify the error in this chatbot code snippet:

responses = {'hello': 'Hi!'}
user_input = input('Say something: ')
print(responses[user_input])

medium

A. print statement is incorrect

B. Syntax error in dictionary definition

C. Missing default response if input not in dictionary

D. input() function is not allowed in chatbot

Solution

1. Step 1: Analyze dictionary access

   Accessing responses[user_input] causes error if user_input key not found.

2. Step 2: Check for default handling

   Code lacks default fallback; should use get() or try-except to avoid crash.

3. Final Answer:

   Missing default response if input not in dictionary -> Option C

4. Quick Check:

   Direct dict access needs key check [OK]

Hint: Use dict.get() to avoid key errors from unknown input [OK]

Common Mistakes:

• Thinking input() is disallowed in chatbot
• Believing dictionary syntax is wrong
• Assuming print statement is incorrect

5. You want your chatbot to answer "Good morning!" when the user says "morning" or "good morning". Which Python code snippet correctly handles this?

hard

A. responses = {'morning': 'Good morning!', 'good morning': 'Good morning!'}

B. responses = {'morning' or 'good morning': 'Good morning!'}

C. responses = {'morning' & 'good morning': 'Good morning!'}

D. responses = {'morning' + 'good morning': 'Good morning!'}

Solution

1. Step 1: Understand dictionary keys for multiple inputs

   Each key must be separate to match different user inputs.

2. Step 2: Evaluate options for correct syntax

   responses = {'morning': 'Good morning!', 'good morning': 'Good morning!'} defines two keys separately; others use invalid Python expressions as keys.

3. Final Answer:

   responses = {'morning': 'Good morning!', 'good morning': 'Good morning!'} -> Option A

4. Quick Check:

   Separate keys for inputs = responses = {'morning': 'Good morning!', 'good morning': 'Good morning!'} [OK]

Hint: Use separate keys for each input phrase in dictionary [OK]

Common Mistakes:

• Trying to combine keys with or/&/+ operators
• Using invalid syntax for dictionary keys
• Assuming one key can match multiple phrases