You are currently on a page documenting the use of OpenAI text completion models. The latest and most popular OpenAI models are chat completion models.Unless you are specifically using gpt-3.5-turbo-instruct, you are probably looking for this page instead.
OpenAI offers a spectrum of models with different levels of power suitable for different tasks. This example goes over how to use LangChain to interact with OpenAI models

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Overview

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Integration details

ClassPackageLocalSerializableJS supportPackage downloadsPackage latest
ChatOpenAIlangchain-openai❌beta✅PyPI - DownloadsPyPI - Version

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Setup

To access OpenAI models you’ll need to create an OpenAI account, get an API key, and install the langchain-openai integration package.

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Credentials

Head to https://platform.openai.com to sign up to OpenAI and generate an API key. Once you’ve done this set the OPENAI_API_KEY environment variable: 
import getpass
import os

if "OPENAI_API_KEY" not in os.environ:
    os.environ["OPENAI_API_KEY"] = getpass.getpass("Enter your OpenAI API key: ")
To enable automated tracing of your model calls, set your LangSmith API key: 
# os.environ["LANGSMITH_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")
# os.environ["LANGSMITH_TRACING"] = "true"

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Installation

The LangChain OpenAI integration lives in the langchain-openai package: 
%pip install -qU langchain-openai
Should you need to specify your organization ID, you can use the following cell. However, it is not required if you are only part of a single organization or intend to use your default organization. You can check your default organization here. To specify your organization, you can use this: 
OPENAI_ORGANIZATION = getpass()

os.environ["OPENAI_ORGANIZATION"] = OPENAI_ORGANIZATION

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Instantiation

Now we can instantiate our model object and generate chat completions: 
from langchain_openai import OpenAI

llm = OpenAI()

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Invocation

llm.invoke("Hello how are you?")

'\n\nI am an AI and do not have emotions like humans do, so I am always functioning at my optimal level. Thank you for asking! How can I assist you today?'

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Chaining

from langchain_core.prompts import PromptTemplate

prompt = PromptTemplate.from_template("How to say {input} in {output_language}:\n")

chain = prompt | llm
chain.invoke(
    {
        "output_language": "German",
        "input": "I love programming.",
    }
)

'\nIch liebe Programmieren.'

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Using a proxy

If you are behind an explicit proxy, you can specify the http_client to pass through 
%pip install httpx

import httpx

openai = OpenAI(
    model_name="gpt-3.5-turbo-instruct",
    http_client=httpx.Client(proxies="http://proxy.yourcompany.com:8080"),
)

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API reference

For detailed documentation of all OpenAI llm features and configurations head to the API reference: https://python.langchain.com/api_reference/openai/llms/langchain_openai.llms.base.OpenAI.html