OpenAI
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
# get a token: https://platform.openai.com/account/api-keys
from getpass import getpass
OPENAI_API_KEY = getpass()
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
from langchain_core.prompts import PromptTemplate
from langchain_openai import OpenAI
template = """Question: {question}
Answer: Let's think step by step."""
prompt = PromptTemplate.from_template(template)
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.
llm_chain = prompt | llm
question = "What NFL team won the Super Bowl in the year Justin Beiber was born?"
llm_chain.invoke(question)
' Justin Bieber was born on March 1, 1994. The Super Bowl is typically played in late January or early February. So, we need to look at the Super Bowl from 1994. In 1994, the Super Bowl was Super Bowl XXVIII, played on January 30, 1994. The winning team of that Super Bowl was the Dallas Cowboys.'
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"))
Related
- LLM conceptual guide
- LLM how-to guides