Azure OpenAI

To use Azure OpenAI models, you can set the following configuration options:

import declarai

azure_model = declarai.azure_openai(
    azure_openai_key="<api-token>",
    azure_openai_api_base="<api-base>",
    deployment_name="<deployment-name>",
    api_version="<api-version>",
    headers={"<header-key>": "<header-value>"},
    timeout="<timeout>",
    request_timeout="<request_timeout>",
    stream="<stream>",
)

Argument	Env Variable	Required?
azure_openai_key	DECLARAI_AZURE_OPENAI_KEY	✅
azure_openai_api_base	DECLARAI_AZURE_OPENAI_API_BASE	✅
deployment_name	DECLARAI_AZURE_OPENAI_DEPLOYMENT_NAME	✅
api_version	DECLARAI_AZURE_OPENAI_API_VERSION
headers
timeout
request_timeout
stream

Getting an API key, API base, and Deployment name

To obtain the above settings, you will need to create an account on the Azure OpenAI website. Once you have created an account, you will need to create a resource.

Please follow the instructions on the Azure OpenAI

Setting the API key

You can set your API key at runtime like this:

import declarai

my_azure_model = declarai.azure_openai(
    deployment_name="my-model",
    azure_openai_key="<your API key>",
    azure_openai_api_base="https://<my-azure-domain>.com",
)

However, it is preferable to pass sensitive settings as an environment variable: DECLARAI_AZURE_OPENAI_API_KEY.

To establish your Azure OpenAI API key as an environment variable, launch your terminal and execute the following command, substituting with your actual key:

export DECLARAI_AZURE_OPENAI_KEY=<your API key>

This action will maintain the key for the duration of your terminal session. To ensure a longer retention, modify your terminal's settings or corresponding environment files.

Control LLM Parameters

OpenAI models have a number of parameters that can be tuned to control the output of the model. These parameters are passed to the declarai task/chat interface as a dictionary. The following parameters are supported:

Parameter	Type	Description	Default
temperature	float	Controls the randomness of the model. Lower values make the model more deterministic and repetitive. Higher values make the model more random and creative.	0
max_tokens	int	Controls the length of the output.	3000
top_p	float	Controls the diversity of the model. Lower values make the model more repetitive and conservative. Higher values make the model more random and creative.	1
frequency_penalty	float	Controls how often the model repeats itself. Lower values make the model more repetitive and conservative. Higher values make the model more random and creative.	0
presence_penalty	float	Controls how often the model generates new topics. Lower values make the model more repetitive and conservative. Higher values make the model more random and creative.	0

Pass your custom parameters to the declarai task/chat interface as a dictionary:

import declarai

azure_model = declarai.azure_openai(
    deployment_name="my-model",
    azure_openai_key="<your API key>",
    azure_openai_api_base="https://<my-azure-domain>.com",
    headers="<my-headers>"
)


@azure_model.task(llm_params={"temperature": 0.5, "max_tokens": 1000})  # (1)!
def generate_song():
    """
    Generate a song about declarai
    """

1. Pass only the parameters you want to change. The rest will be set to their default values.