response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "system",
"content": "You are a data science tutor."},
{"role": "user",
"content": "What is the difference between mutable and immutable objects?"}]
)
System: controls assistant's behavior
User: instruct the assistant
Assistant: response to user instruction
Providing examples
Steer model in the right direction
Providing assistant messages is a more structured form of shot-prompting
Example: Python Programming Tutor
Example user questions and answers
Providing examples
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "system",
"content": "You are a Python programming tutor who speaks concisely."},
{"role": "user",
"content": "How do you define a Python list?"},
{"role": "assistant",
"content": "Lists are defined by enclosing a comma-separated sequence of
objects inside square brackets [ ]."},
{"role": "user",
"content": "What is the difference between mutable and immutable objects?"}]
)
The response
print(response.choices[0].message.content)
Mutable objects can be changed after creation (e.g., lists, dictionaries). Immutable objects
cannot be altered once created (e.g., strings, tuples).
Experiment with the number of examples
System vs. assistant vs. user
System → important template formatting
Output the information in this format:
name | age | occupation
Assistant → example conversations
User → context required for the new input (often single-turn)
Create a job advert for an AI Engineer. Use this job advert as a template:
Job Title: Data Engineer
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