Completions Api Openai Api

Leo Migdal

-Nov 22, 2025, 11:58 AM

The Chat Completions API provides text generation capabilities through a conversational message format. This is the previous standard API for generating text from OpenAI models (supported indefinitely), with the newer Responses API now serving as the primary interface. The Chat Completions API remains fully supported for applications that prefer message-based interactions or require compatibility with existing code. For information about the Assistants API (which provides stateful multi-turn conversations with tools), see Assistants API. For streaming architecture details, see Streaming and Event Handling. The Chat Completions API is accessed through the Completions resource, which is nested under the Chat resource in the client hierarchy.

The resource class provides the following methods: Sources: src/openai/resources/chat/completions/completions.py api.md45-98 tests/api_resources/chat/test_completions.py26-441 The OpenAI Completion API allows you to generate text completions using OpenAI's language models. This document provides an overview of the API endpoints, request parameters, and response structure. The request body should be a JSON object with the following parameters: The response body will be a JSON object containing the generated completions and other metadata.

For more details, refer to the OpenAI API documentation. There was an error while loading. Please reload this page. The Completions API is the most fundamental OpenAI model that provides a simple interface that’s extremely flexible and powerful. You give it a prompt and it returns a text completion, generated according to your instructions. You can think of it as very advanced autocomplete where the language model processes your text prompt and tries to predict what’s most likely to come next.

Although simple to use, Completions API is also very customizable and exposes various parameters that can be set to affect how completions are generated (for better or worse). This guide explains all the parameters with practical examples. After reading this guide you will have a deeper understanding of the Completion API and you will be able to practically apply this knowledge in your day-to-day work with OpenAI APIs. For the examples in this article, I will use Postman for sending HTTP requests. I suggest you to do the same, but you can follow along with just about any HTTP client. You can also generate and customize text completions in the OpenAI playground or code completions in OpenAI JavaScript Sandbox.

Although I will be using Postman for sending requests, I have written a guide on how to integrate OpenAI APIs in JavaScript projects. OpenAI API: Responses vs. Chat Completions. OpenAI released a bunch of new API platform features this morning under the headline "New tools for building agents" (their somewhat mushy interpretation of "agents" here is "systems that independently accomplish tasks on behalf... A particularly significant change is the introduction of a new Responses API, which is a slightly different shape from the Chat Completions API that they've offered for the past couple of years and which... In this guide they illustrate the differences, with a reassuring note that:

The Chat Completions API is an industry standard for building AI applications, and we intend to continue supporting this API indefinitely. We're introducing the Responses API to simplify workflows involving tool use, code execution, and state management. We believe this new API primitive will allow us to more effectively enhance the OpenAI platform into the future. An API that is going away is the Assistants API, a perpetual beta first launched at OpenAI DevDay in 2023. The new responses API solves effectively the same problems but better, and assistants will be sunset "in the first half of 2026". Access to this page requires authorization.

You can try signing in or changing directories. Access to this page requires authorization. You can try changing directories. This document refers to the Microsoft Foundry (classic) portal only. Stored completions allow you to capture the conversation history from chat completions sessions to use as datasets for evaluations and fine-tuning. As long as you're using the Chat Completions API for inferencing, you can leverage stored completions.

It is supported for all Azure OpenAI models, and in all supported regions (including global-only regions). Welcome! Today, you'll learn how to make your first request to the OpenAI Completions API using Python. This is the groundwork for learning more advanced techniques for building AI assistants, which we'll explore further in this course path. In this lesson, you'll discover how to send a prompt, get a response, and handle basic errors — essential skills for developing your own AI agents. By mastering these basics, you'll be prepared to tackle more complex assistant behaviors and applications as you progress through the course.

To use the OpenAI API, set up your Python environment with the openai library: Your API key should be set as the OPENAI_API_KEY environment variable. This key is required for authentication. Error handling is important. If something goes wrong — such as a network issue or a bad key — your program should handle it gracefully. You'll see how to do this with try and except blocks in the examples.

To interact with the API, send a request with a prompt. For chat models, the prompt is a list of messages, each with a role and content.

Completions Api Openai Api

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