> ## Documentation Index
> Fetch the complete documentation index at: https://docs.llmstudio.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Openai

Interact with your OpenAI models using LLM.

## Supported models

1. `gpt-4o`
2. `gpt-4-turbo`
3. `gpt-4`
4. `gpt-3.5-turbo`
5. `gpt-3.5-turbo-instruct`

## Parameters

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.        |

## Usage

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

<Tabs>
  <Tab title="w/ .env">
    <Steps>
      <Step>
        Create a `.env` file with you `OPENAI_API_KEY`

        <Warning>Make sure you call your environment variable OPENAI\_API\_KEY</Warning>

        ```bash theme={null}
        OPENAI_API_KEY="YOUR-KEY"
        ```
      </Step>

      <Step>
        In your python code, import LLM from llmstudio.

        ```python theme={null}
        from llmstudio import LLM
        ```
      </Step>

      <Step>
        Create your **llm** instance.

        ```python theme={null}
        llm = LLM('openai/{model}')
        ```
      </Step>

      <Step>
        **Optional:** You can add your parameters as follows:

        ```python theme={null}
        llm = LLM('openai/model', 
        temperature= ...,
        max_tokens= ...,
        top_p= ...,
        frequency_penalty= ...,
        presence_penalty= ...)
        ```

        <Check>You are done setting up your **OpenAI LLM**!</Check>
      </Step>
    </Steps>
  </Tab>

  <Tab title="w/o .env">
    <Steps>
      <Step>
        In your python code, import LLM from llmstudio.

        ```python theme={null}
        from llmstudio import LLM
        ```
      </Step>

      <Step>
        Create your **llm** instance.

        ```python theme={null}
        llm = LLM('openai/{model}',api_key="YOUR_API_KEY")
        ```
      </Step>

      <Step>
        **Optional:** You can add your parameters as follows:

        ```python theme={null}
        llm = LLM('openai/model', 
        temperature= ...,
        max_tokens= ...,
        top_p= ...,
        frequency_penalty= ...,
        presence_penalty= ...)
        ```

        <Check>You are done setting up your **OpenAI LLM**!</Check>
      </Step>
    </Steps>
  </Tab>
</Tabs>

## What's next?

<CardGroup cols={2}>
  <Card title="LLM.chat()" icon="link" href="../chat">
    Learn how to send messeges and recieve responses next!
  </Card>

  <Card title="Tool calling Agent" icon="link" href="../../../how-to/build-a-tool-agent">
    Learn how to build a tool calling agent using llmstudio.
  </Card>
</CardGroup>