LLM APIs - lesson 6 | HackIndia Skills

LLM APIs - lesson 6 | HackIndia Skills | HackIndia

Example

Log usage

Add one small log line after your server route gets a response. Keep this on the backend, along with your API key.

Field names can vary by SDK response shape, so log the full usage object first. Then store only the numbers your app needs.

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
});

export async function POST(req) {
  const { question } = await req.json();

  const response = await client.responses.create({
    model: "gpt-4o-mini",
    instructions: "Answer like a helpful project mentor. Keep it short.",
    input: question,
    max_output_tokens: 300,
  });

  console.log("openai_usage", {
    response_id: response.id,
    usage: response.usage,
  });

  return Response.json({
    answer: response.output_text,
    usage: response.usage,
  });
}

Example

Simple cost note

Put a short note in your README so reviewers know you thought about cost. Do not hard-code prices unless you plan to keep them updated.

Cost and token tracking

This app calls OpenAI from a backend route only.
Each request sets max_output_tokens.
The server logs the response id, model, route name, and usage object.
Cost should be estimated using the current OpenAI pricing page for the selected model.
During testing, also check the OpenAI Usage Dashboard.

Track tokens and cost

One habit

What tokens mean

Old token names

Log usage

Add a budget guard

Estimate before building

Simple cost note

Do this now

Quick check