Working with AI APIs

AI APIs are the primary interface for integrating large language models into your applications. This lesson covers how to make API calls using both REST and SDKs, understand the message format, stream responses, and handle errors gracefully.

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The Chat Completions Pattern

Most modern LLM APIs use a chat completions interface. You send a list of messages (conversation history) and receive a model-generated response.

Message Roles

Role	Purpose
system	Sets the model's behaviour, persona, or instructions
user	The human user's input
assistant	The model's previous responses (for context)

Basic Request Structure

messages = [
    {"role": "system", "content": "You are a concise coding assistant."},
    {"role": "user", "content": "Write a Python function to reverse a string."},
]

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Using the OpenAI SDK

from openai import OpenAI

client = OpenAI()

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is the capital of France?"},
    ],
    temperature=0.7,
    max_tokens=256,
)

answer = response.choices[0].message.content
print(answer)

Key Parameters