openai

Open AI

What is Open AI?

OpenAI is a private research laboratory that aims to develop and direct artificial intelligence (AI) in ways that benefit humanity as a whole. The company was founded by Elon Musk, Sam Altman and others in 2015 and is headquartered in San Francisco.

The OpenAI API can be applied to virtually any task. We offer a range of models with different capabilities and price points, as well as the ability to fine-tune custom models.

OpenAI’s text generation models (often referred to as generative pre-trained transformers or “GPT” models for short), like GPT-4 and GPT-3.5, have been trained to understand natural and formal language. Models like GPT-4 allows text outputs in response to their inputs. The inputs to these models are also referred to as “prompts”. Designing a prompt is essentially how you “program” a model like GPT-4, usually by providing instructions or some examples of how to successfully complete a task. Models like GPT-4 can be used across a great variety of tasks including content or code generation, summarization, conversation, creative writing, and more. Read more in our introductory text generation guide and in our prompt engineering guide.

Assistants refer to entities, which in the case of the OpenAI API are powered by large language models like GPT-4, that are capable of performing tasks for users. These assistants operate based on the instructions embedded within the context window of the model. They also usually have access to tools which allows the assistants to perform more complex tasks like running code or retrieving information from a file. Read more about assistants in our Assistants API Overview.

An embedding is a vector representation of a piece of data (e.g. some text) that is meant to preserve aspects of its content and/or its meaning. Chunks of data that are similar in some way will tend to have embeddings that are closer together than unrelated data. OpenAI offers text embedding models that take as input a text string and produce as output an embedding vector. Embeddings are useful for search, clustering, recommendations, anomaly detection, classification, and more. Read more about embeddings in our embeddings guide.

Text generation and embeddings models process text in chunks called tokens. Tokens represent commonly occurring sequences of characters. For example, the string ” tokenization” is decomposed as ” token” and “ization”, while a short and common word like ” the” is represented as a single token. Note that in a sentence, the first token of each word typically starts with a space character. Check out our tokenizer tool to test specific strings and see how they are translated into tokens. As a rough rule of thumb, 1 token is approximately 4 characters or 0.75 words for English text.

One limitation to keep in mind is that for a text generation model the prompt and the generated output combined must be no more than the model’s maximum context length. For embeddings models (which do not output tokens), the input must be shorter than the model’s maximum context length. The maximum context lengths for each text generation and embeddings model can be found in the model index.

Quickstart for developer

Go to Open AI and then to  Quick Start

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-4 to generate an output.

This quickstart is designed to help get your local development environment setup and send your first API request. If you are an experienced developer or want to just dive into using the OpenAI API, the API reference of GPT guide are a great place to start. Throughout this quickstart, you will learn:

• How to setup your development environment
• How to install the latest SDKs
• Some of the basic concepts of the OpenAI API
• How to send your first API request

First, create an OpenAI account or sign in. Next, navigate to the API key page and “Create new secret key”, optionally naming the key. Make sure to save this somewhere safe and do not share it with anyone.

Select the tool or language you want to get started using the OpenAI API with.

python -m venv openai-env

openai-env\Scripts\activate

pip install --upgrade openai

setx OPENAI_API_KEY "your-api-key-here"

# Once you add your API key below, make sure to not share it with anyone! The API key should remain private.
OPENAI_API_KEY=abc123

from openai import OpenAI

client = OpenAI()
# defaults to getting the key using os.environ.get("OPENAI_API_KEY")
# if you saved the key under a different environment variable name, you can do something like:
# client = OpenAI(
#   api_key=os.environ.get("CUSTOM_ENV_NAME"),
# )

from openai import OpenAI
client = OpenAI()

completion = client.chat.completions.create(
  model="gpt-3.5-turbo",
  messages=[
    {"role": "system", "content": "You are a poetic assistant, skilled in explaining complex programming concepts with creative flair."},
    {"role": "user", "content": "Compose a poem that explains the concept of recursion in programming."}
  ]
)

print(completion.choices[0].message)

{
    "id": "generated-text-123",
    "model": "gpt-3.5-turbo",
    "text": "This is an example of generated text based on the prompt provided to the API."
}