AI APIs & Tools

Modern AI systems are primarily accessed through APIs (Application Programming Interfaces). Understanding how to integrate AI into applications, manage tokens and costs, and use vector databases for enhanced retrieval is essential for building AI-powered products.

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How AI APIs Work

AI API Request Flow:
+--------------+    HTTPS POST    +------------------+
| Your         |----------------->| AI Provider      |
| Application  |                  | (e.g. Anthropic) |
|              |<-----------------|                  |
|              |    JSON Response  |  +------------+ |
+--------------+                  |  | LLM Model  | |
                                  |  +------------+ |
                                  +------------------+

A typical call involves: authentication (API key in headers), a request body (model, messages, parameters), and a JSON response (generated text plus metadata).

Example API Call

import anthropic

client = anthropic.Anthropic(api_key="your-api-key-here")

message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    system="You are a helpful assistant that explains concepts clearly.",
    messages=[
        {"role": "user", "content": "What is photosynthesis?"}
    ]
)

print(message.content[0].text)

Common API Parameters