class allms.models.AzureMistralModel API
Methods
__init__(
config: AzureSelfDeployedConfiguration,
temperature: float = 0.0,
top_p: float = 1.0,
max_output_tokens: int = 1024,
model_total_max_tokens: int = 8192,
max_concurrency: int = 1000,
max_retries: int = 8
)
Parameters
config(AzureSelfDeployedConfiguration): an instance ofAzureSelfDeployedConfigurationclasstemperature(float): The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. Default:0.0.top_p(float): Default:1.0.max_output_tokens(int): The maximum number of tokens to generate by the model. The total length of input tokens and generated tokens is limited by the model's context length. Default:1024.model_total_max_tokens(int): Context length of the model - maximum number of input plus generated tokens. Default:8192.max_concurrency(int): Maximum number of concurrent requests. Default:1000.max_retries(int): Maximum number of retries if a request fails. Default:8.
generate(
prompt: str,
input_data: typing.Optional[typing.List[InputData]] = None,
output_data_model_class: typing.Optional[typing.Type[BaseModel]] = None
) -> typing.List[ResponseData]:
Parameters
prompt(str): Prompt to use to query the model.input_data(Optional[List[InputData]]): If prompt contains symbolic variables you can use this parameter to generate model responses for batch of examples. Each symbolic variable from the prompt should have mapping provided in theinput_mappingsofInputData.output_data_model_class(Optional[Type[BaseModel]]): Generated response is automatically parsed to this class. WARNING: You need to manually provide the JSON format instructions in the prompt, they are not injected for this model.
Note that Mistral-based models currently don't support system prompts.
Returns
List[ResponseData]: Each ResponseData contains the response for a single example from input_data. If input_data
is not provided, the length of this list is equal 1, and the first element is the response for the raw prompt.
class allms.domain.configuration.AzureSelfDeployedConfiguration API
AzureSelfDeployedConfiguration(
api_key: str,
endpoint_url: str,
deployment: str
)
Parameters
api_key(str): Authentication key for the endpoint.endpoint_url(str): URL of pre-existing endpoint.deployment(str): The name under which the model was deployed.
Example usage
from allms.models import AzureMistralModel
from allms.domain.configuration import AzureSelfDeployedConfiguration
configuration = AzureSelfDeployedConfiguration(
api_key="<AZURE_API_KEY>",
endpoint_url="<AZURE_ENDPOINT_URL>",
deployment="<AZURE_DEPLOYMENT_NAME>"
)
mistral_model = AzureMistralModel(config=configuration)
mistral_response = mistral_model.generate("2+2 is?")