langchain/docs/extras/integrations/llms/openai.ipynb

OpenAI

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

In [1]:

# get a token: https://platform.openai.com/account/api-keys

from getpass import getpass

OPENAI_API_KEY = getpass()

In [2]:

import os

os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY

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

In [3]:

from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain

In [4]:

template = """Question: {question}

Answer: Let's think step by step."""

prompt = PromptTemplate(template=template, input_variables=["question"])

In [5]:

llm = OpenAI()

If you manually want to specify your OpenAI API key and/or organization ID, you can use the following:

llm = OpenAI(openai_api_key="YOUR_API_KEY", openai_organization="YOUR_ORGANIZATION_ID")

Remove the openai_organization parameter should it not apply to you.

In [6]:

llm_chain = LLMChain(prompt=prompt, llm=llm)

In [7]:

question = "What NFL team won the Super Bowl in the year Justin Beiber was born?"

llm_chain.run(question)

Out [7]:

' Justin Bieber was born in 1994, so the NFL team that won the Super Bowl in 1994 was the Dallas Cowboys.'

If you are behind an explicit proxy, you can use the OPENAI_PROXY environment variable to pass through

In [8]:

os.environ["OPENAI_PROXY"] = "http://proxy.yourcompany.com:8080"