Lesson 389 of 2116
The Responses API: OpenAI's Modern Developer Surface
The Responses API is where OpenAI puts stateful conversations, multimodal inputs, tools, and structured outputs. Learn the shape before you build.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1One Surface for Text, Vision, State, and Tools
- 2Responses API
- 3Chat Completions
- 4stateful responses
Concept cluster
Terms to connect while reading
Section 1
One Surface for Text, Vision, State, and Tools
Chat Completions taught a generation of developers the messages array. The Responses API is the newer shape: it supports text and image inputs, text outputs, conversation state, built-in tools, and function calling in one API.
The simplest Responses call still looks like a normal model request.
import OpenAI from "openai";
const client = new OpenAI();
const response = await client.responses.create({
model: "gpt-5.5",
instructions: "Be concise and verify assumptions.",
input: "Draft an incident-summary template for a failed deploy.",
});
console.log(response.output_text);Compare the options
| Use Chat Completions when | Use Responses when |
|---|---|
| You maintain a stable legacy chat app | You need built-in tools or multimodal workflows |
| You cannot migrate everything yet | You need conversation state without rebuilding threads |
| The endpoint is already working and low risk | You are starting a new OpenAI integration |
| You only need simple message in, text out | You need structured output, tools, or future agent features |
- 1Wrap model calls behind one local client function.
- 2Move one low-risk flow to Responses.
- 3Add logging for latency, cost, and output quality.
- 4Then migrate flows that need tools, vision, or structured data.
- 5Keep old Chat Completions flows until they have a reason to move.
Key terms in this lesson
The big idea: new OpenAI apps should usually start with Responses, while old apps should migrate where the newer surface pays for itself.
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