All functionality related to OpenAI
OpenAI is American artificial intelligence (AI) research laboratory consisting of the non-profit OpenAI Incorporated and its for-profit subsidiary corporation OpenAI Limited Partnership. OpenAI conducts AI research with the declared intention of promoting and developing a friendly AI. OpenAI systems run on an Azure-based supercomputing platform from Microsoft. The OpenAI API is powered by a diverse set of models with different capabilities and price points. ChatGPT is the Artificial Intelligence (AI) chatbot developed by OpenAI.

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Installation and Setup

Install the integration package with: 
pip install langchain-openai
Get an OpenAI api key and set it as an environment variable (OPENAI_API_KEY)

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Chat model

See a usage example. 
from langchain_openai import ChatOpenAI
If you are using a model hosted on Azure, you should use different wrapper for that: 
from langchain_openai import AzureChatOpenAI
For a more detailed walkthrough of the Azure wrapper, see here.

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LLM

See a usage example. 
from langchain_openai import OpenAI
If you are using a model hosted on Azure, you should use different wrapper for that: 
from langchain_openai import AzureOpenAI
For a more detailed walkthrough of the Azure wrapper, see here.

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Embedding Model

See a usage example 
from langchain_openai import OpenAIEmbeddings

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Document Loader

See a usage example. 
from langchain_community.document_loaders.chatgpt import ChatGPTLoader

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Retriever

See a usage example. 
from langchain.retrievers import ChatGPTPluginRetriever

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Tools

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Dall-E Image Generator

OpenAI Dall-E are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions, called “prompts”.
See a usage example. 
from langchain_community.utilities.dalle_image_generator import DallEAPIWrapper

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Adapter

See a usage example. 
from langchain.adapters import openai as lc_openai

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Tokenizer

There are several places you can use the tiktoken tokenizer. By default, it is used to count tokens for OpenAI LLMs. You can also use it to count tokens when splitting documents with 
from langchain.text_splitter import CharacterTextSplitter
CharacterTextSplitter.from_tiktoken_encoder(...)
For a more detailed walkthrough of this, see this notebook

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Chain

See a usage example. 
from langchain.chains import OpenAIModerationChain