Working with APIs

Introduction

Integrating AI into your applications typically involves interacting with APIs provided by companies like OpenAI, Anthropic, or Google. You'll learn how to authenticate, send prompts, and parse responses programmatically.

Making API Requests

import os
from openai import OpenAI

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))

response = client.chat.completions.create(
    model="gpt-3.5-turbo",
    messages=[
        {"role": "system", "content": "You are a helpful coding assistant."},
        {"role": "user", "content": "Explain recursion in Python in one sentence."}
    ]
)

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

In this example, we define roles (system, user) to contextually steer the LLM's behavior.

Understanding Tokens

LLMs process text in chunks called tokens. A token can be a word, part of a word, or just a single character. APIs charge based on token usage (both input and output tokens), so optimizing your prompts can save money and improve performance.

Assignment