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Practical Skills

API Basics

How to actually call an LLM from code, the mechanics every builder needs

What it is

LLM APIs expose model capabilities over HTTP. The standard pattern: send a POST request with your messages array (system + user turns), model selection, and parameters (temperature, max_tokens), receive a response containing the generated text and token usage.

Key parameters: temperature (0 = deterministic, 1+ = creative/random), max_tokens (caps response length), top_p (nucleus sampling). Streaming is available on all major APIs to return tokens as they're generated, improving perceived latency.

Cost is billed per token (input + output, often at different rates). At scale, token efficiency becomes a real engineering concern.

Why it matters

You can't build anything with AI without understanding how to call the API. Knowing the cost model prevents budget surprises. Understanding temperature helps you tune model behavior. Streaming matters for user-facing applications where latency is visible. This is table stakes for any technical work with LLMs.

Related concepts

Resources

How I Use LLMs (ChatGPT interaction under the hood)
youtube.com· Shows what actually happens when you send a message to ChatGPT: the API call, system prompt, tokens, temperature, and how responses are generated. Perfect conceptual intro before touching code.
10 min
OpenAI API Tutorial for Beginners
youtube.com· Hands-on walkthrough of making your first API call to OpenAI in Python. Covers API keys, chat completions, tokens, temperature, and max_tokens. Beginner-friendly with code.
25 min
How to use LLM APIs: OpenAI, Claude, Google
medium.com· Practical guide covering OpenAI, Anthropic, and Google APIs side-by-side. Shows synchronous vs async calls, with working Python code for each provider.
12 min
Calling LLM APIs: OpenAI, Anthropic & Structured Outputs
gyanbyte.com· Full hands-on guide covering SDKs, streaming, function calling, structured outputs, and error handling. More advanced than the Medium article but well-organized for reference.
15 min