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Three million developers build with OpenAI. Our API platform offers our latest models and guides for safety best practices.
Jun 11, 2020 · We’re releasing an API for accessing new AI models developed by OpenAI. Unlike most AI systems which are designed for one use-case, the API today provides a general-purpose “text in, text out” interface, allowing users to try it on virtually any English language task.
Explore resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's developer platform.
Instant answers. Greater productivity. Endless inspiration. Try ChatGPT. We believe our research will eventually lead to artificial general intelligence, a system that can solve human-level problems. Building safe and beneficial AGI is our mission.
Explore resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's developer platform.
The OpenAI API provides a simple interface for developers to create an intelligence layer in their applications, powered by OpenAI's state of the art models. The Chat Completions endpoint powers ChatGPT and provides a simple way to take text as input and use a model like GPT-4o to generate an output.
Example code and guides for accomplishing common tasks with the OpenAI API. To run these examples, you'll need an OpenAI account and associated API key ( create a free account here ). Set an environment variable called OPENAI_API_KEY with your API key.
Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.
OpenAI Python API library. The OpenAI Python library provides convenient access to the OpenAI REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by httpx.
6 days ago · GPT-4o mini in the API is the first model to apply our instruction hierarchy (opens in a new window) method, which helps to improve the model’s ability to resist jailbreaks, prompt injections, and system prompt extractions. This makes the model’s responses more reliable and helps make it safer to use in applications at scale.
