> ## 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.

# Azure

Interact with your Azure models using LLM.

## Parameters

An Azure LLM interface can have the following parameters:

| Parameter           | Type  | Description                                    |
| ------------------- | ----- | ---------------------------------------------- |
| `temperature`       | float | The temperature parameter for the model.       |
| `max_tokens`        | int   | The maximum number of tokens to generate.      |
| `top_p`             | float | The top-p parameter for the model.             |
| `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 Azure models.

<Tabs>
  <Tab title="OpenAI Models">
    <Steps>
      <Step>
        Create a `config.yaml` file in the same directory as your code.

        1. 📁 src
           1. 🐍 PythonCode.py
           2. 🐍 PyNotebook.ipynb
           3. 📄 **config.yaml**
      </Step>

      <Step>
        Define your Azure OpenAI provider and models inside the `config.yaml` file.

        ```yaml theme={null}
            providers:
                azure:
                    id: azure
                    name: Azure
                    chat: true
                    embed: true
                    models:
                        YOUR_MODEL: <- Replace with your model name
                            mode: chat
                            max_tokens: ...
                            input_token_cost: ...
                            output_token_cost: ...
        ```

        <Tip>If you are not sure, you can leave `max_tokens`, `input_tokens` and the other parameters as **0**</Tip>
      </Step>

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

        ```python theme={null}
        llm = LLM('azure/YOUR_MODEL',
                api_key = YOUR_API_KEY,
                api_endpoint = YOUR_ENDPOINT,
                api_version = YOUR_API_VERSION)
        ```
      </Step>

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

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

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

  <Tab title="Other Models">
    <Steps>
      <Step>
        Create a `config.yaml` file in the same directory as your code.

        1. 📁 src
           1. 🐍 PythonCode.py
           2. 🐍 PyNotebook.ipynb
           3. 📄 **config.yaml**
      </Step>

      <Step>
        Define your Azure provider and models inside the `config.yaml` file.

        ```yaml theme={null}
            providers:
                azure:
                    id: azure
                    name: Azure
                    chat: true
                    embed: true
                    models:
                        YOUR_MODEL: <- Replace with your model name
                            mode: chat
                            max_tokens: ...
                            input_token_cost: ...
                            output_token_cost: ...
        ```

        <Tip>If you are not sure, you can leave `max_tokens`, `input_tokens` and the other parameters as **0**</Tip>
      </Step>

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

        ```python theme={null}
        llm = LLM('azure/YOUR_MODEL',
                   api_key = YOUR_API_KEY,
                   base_url = YOUR_ENDPOINT)
        ```
      </Step>

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

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

        <Check>You are done setting up your **Azure 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>