Openai

Interact with your OpenAI models using LLM.

Supported models

An OpenAI LLM interface can have the following parameters:

Parameter	Type	Description
`api_key`	str	The API key for authentication.
`temperature`	float	The temperature parameter for the model.
`top_p`	float	The top-p parameter for the model.
`max_tokens`	int	The maximum number of tokens for the model’s output.
`frequency_penalty`	float	The frequency penalty parameter for the model.
`presence_penalty`	float	The presence penalty parameter for the model.

Here is how you setup an interface to interact with your OpenAI models.

Create a .env file with you OPENAI_API_KEY

Make sure you call your environment variable OPENAI_API_KEY

OPENAI_API_KEY="YOUR-KEY"

In your python code, import LLM from llmstudio.

from llmstudio import LLM

Create your llm instance.

llm = LLM('openai/{model}')

Optional: You can add your parameters as follows:

llm = LLM('openai/model', 
temperature= ...,
max_tokens= ...,
top_p= ...,
frequency_penalty= ...,
presence_penalty= ...)

You are done setting up your OpenAI LLM!

In your python code, import LLM from llmstudio.

from llmstudio import LLM

Create your llm instance.

llm = LLM('openai/{model}',api_key="YOUR_API_KEY")

Optional: You can add your parameters as follows:

llm = LLM('openai/model', 
temperature= ...,
max_tokens= ...,
top_p= ...,
frequency_penalty= ...,
presence_penalty= ...)

You are done setting up your OpenAI LLM!

Learn how to send messeges and recieve responses next!

Learn how to build a tool calling agent using llmstudio.