Chat completions endpoint in Prompt Engineering / GenAI - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to send a chat message using the completions endpoint.

Prompt Engineering / GenAI

response = client.chat.completions.create(model="gpt-4o-mini", messages=[{"role": "user", "content": [1]])

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

A"Hello, how are you?"

BHello, how are you?

C'Hello, how are you?'

DHello how are you

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting to put the message content inside quotes.

Using single quotes instead of double quotes in JSON.

The message content must be a string enclosed in quotes. Double quotes are standard for JSON strings.

2fill in blank

medium

Complete the code to extract the chat completion text from the response.

Prompt Engineering / GenAI

completion_text = response.choices[0].[1].content

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

Aresponse

Btext

Ccontent

Dmessage

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'text' instead of 'message'.

Trying to access 'content' directly from choices[0].

The chat completions API returns the message inside the 'message' attribute of the first choice.

3fill in blank

hard

Fix the error in the code to correctly send multiple messages in the chat completion request.

Prompt Engineering / GenAI

messages = [
    {"role": "system", "content": "You are a helpful assistant."},
    {"role": "user", "content": [1]
]
response = client.chat.completions.create(model="gpt-4o-mini", messages=messages)

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

AWhat is the weather today?

B'What is the weather today?'

C"What is the weather today?"

DWhat is the weather today

Attempts:

3 left

💡 Hint

Common Mistakes

Omitting quotes around the message content.

Using single quotes instead of double quotes.

The content must be a string enclosed in double quotes to be valid JSON.

4fill in blank

hard

Fill both blanks to create a chat completion request with a system and user message.

Prompt Engineering / GenAI

messages = [
    {"role": [1], "content": "You are a friendly bot."},
    {"role": [2], "content": "Tell me a joke."}
]
response = client.chat.completions.create(model="gpt-4o-mini", messages=messages)

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

A"system"

B"assistant"

C"user"

D"bot"

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'assistant' or 'bot' as the user role.

Not quoting the role strings.

The first message role is 'system' and the second is 'user' to represent the user input.

5fill in blank

hard

Fill all three blanks to extract the chat completion text and print it.

Prompt Engineering / GenAI

response = client.chat.completions.create(model="gpt-4o-mini", messages=[{"role": "user", "content": "Hello!"}])
completion = response.[1][0].[2].[3]
print(completion)

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

Achoices

Bmessage

Ccontent

Dresults

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'results' instead of 'choices'.

Accessing 'content' directly from choices[0].

Missing the 'message' attribute.

The response has a 'choices' list; each choice has a 'message' object with 'content' text.

Practice

1. What is the main purpose of the chat completions endpoint in GenAI?

easy

A. To send messages and receive AI-generated replies in a conversation format

B. To train a new AI model from scratch

C. To upload datasets for AI training

D. To visualize AI model architecture

Solution

1. Step 1: Understand the endpoint's function

   The chat completions endpoint is designed to handle conversations by sending messages and getting AI replies.

2. Step 2: Compare options with the endpoint's purpose

   Only To send messages and receive AI-generated replies in a conversation format describes sending messages and receiving replies, which matches the chat completions endpoint.

3. Final Answer:

   To send messages and receive AI-generated replies in a conversation format -> Option A

4. Quick Check:

   Chat completions endpoint = conversation replies [OK]

Hint: Chat completions = chat messages in, AI replies out [OK]

Common Mistakes:

• Confusing chat completions with model training
• Thinking it uploads data instead of chatting
• Assuming it visualizes model details

2. Which of the following is the correct way to format messages sent to the chat completions endpoint?

easy

A. [{"content": "Hello!"}, {"content": "Hi! How can I help?"}]

B. ["Hello!", "Hi! How can I help?"]

C. {"user": "Hello!", "assistant": "Hi! How can I help?"}

D. [{"role": "user", "content": "Hello!"}, {"role": "assistant", "content": "Hi! How can I help?"}]

Solution

1. Step 1: Recall message format requirements

   The chat completions endpoint expects a list of messages, each with a role and content.

2. Step 2: Match options to the required format

   [{"role": "user", "content": "Hello!"}, {"role": "assistant", "content": "Hi! How can I help?"}] correctly uses a list of dictionaries with "role" and "content" keys, matching the expected format.

3. Final Answer:

   [{"role": "user", "content": "Hello!"}, {"role": "assistant", "content": "Hi! How can I help?"}] -> Option D

4. Quick Check:

   Messages need role and content keys [OK]

Hint: Messages need both role and content keys [OK]

Common Mistakes:

• Sending messages as plain strings without roles
• Using incorrect JSON object structure
• Omitting the role field in messages

3. Given this code snippet using the chat completions endpoint, what will be the output's role and content?

messages = [{"role": "user", "content": "What's the weather?"}]
response = chat_completions(messages=messages, temperature=0.5)
print(response.choices[0].message)

medium

A. {"role": "system", "content": "Weather info not available."}

B. {"role": "user", "content": "What's the weather?"}

C. {"role": "assistant", "content": "I don't have weather data."}

D. An error because temperature is invalid

Solution

1. Step 1: Understand the response structure

   The chat completions endpoint returns a response with choices, each containing a message with role and content.

2. Step 2: Identify the role of the returned message

   The returned message role is "assistant" because the AI replies to the user message.

3. Final Answer:

   {"role": "assistant", "content": "I don't have weather data."} -> Option C

4. Quick Check:

   Response role = assistant, content = AI reply [OK]

Hint: AI replies have role 'assistant' in response [OK]

Common Mistakes:

• Confusing user message with AI reply
• Expecting system role in output
• Thinking temperature causes error here

4. You wrote this code but get an error:

messages = [{"content": "Hello!"}]
response = chat_completions(messages=messages)
print(response.choices[0].message)

What is the likely cause of the error?

medium

A. The messages list should be a string, not a list

B. Missing the 'role' key in the message dictionary

C. The chat_completions function requires a 'temperature' argument

D. The print statement syntax is incorrect

Solution

1. Step 1: Check message format requirements

   Each message must have both 'role' and 'content' keys to be valid.

2. Step 2: Identify missing key in the code

   The message dictionary only has 'content' but lacks the required 'role' key, causing the error.

3. Final Answer:

   Missing the 'role' key in the message dictionary -> Option B

4. Quick Check:

   Every message needs role and content keys [OK]

Hint: Always include 'role' in each message dictionary [OK]

Common Mistakes:

• Assuming temperature is mandatory
• Thinking messages should be a string
• Blaming print statement syntax

5. You want the AI to give more creative and varied answers using the chat completions endpoint. Which parameter should you adjust and how?

hard

A. Increase the temperature value closer to 1 to make responses more creative

B. Decrease the max_tokens to limit response length

C. Set temperature to 0 to get random answers

D. Remove the messages parameter to let AI decide context

Solution

1. Step 1: Understand the role of temperature

   The temperature parameter controls randomness; higher values produce more creative and varied outputs.

2. Step 2: Choose the correct adjustment for creativity

   Increasing temperature closer to 1 encourages creativity, while 0 makes responses deterministic.

3. Final Answer:

   Increase the temperature value closer to 1 to make responses more creative -> Option A

4. Quick Check:

   Higher temperature = more creative answers [OK]

Hint: Higher temperature means more creative AI replies [OK]

Common Mistakes:

• Setting temperature to 0 expecting creativity
• Confusing max_tokens with creativity control
• Removing messages causes loss of context