`mistral_common.protocol.base`

`BaseCompletionRequest(**data)`

Bases: MistralBase

Base class for completion requests.

Holds sampling parameters shared by all completion request types (chat, FIM, transcription, speech).

Attributes:

Name	Type	Description
`temperature`	`float`	Sampling temperature in [0, 1]. Higher values (e.g., 0.8) make the output more random; lower values (e.g., 0.2) make it more focused and deterministic. Defaults to 0.7.
`top_p`	`float`	Nucleus sampling probability mass in [0, 1]. The model samples from the smallest set of tokens whose cumulative probability exceeds `top_p`. Defaults to 1.0 (no truncation).
`max_tokens`	`int \| None`	Maximum number of tokens to generate. If `None`, the model generates until a stop condition (e.g., EOS) is reached.
`random_seed`	`int \| None`	Seed for reproducible sampling. If `None`, sampling is not reproducible.

Examples:

>>> request = BaseCompletionRequest(temperature=0.7, top_p=0.9, max_tokens=100, random_seed=42)

Source code in pydantic/main.py

def __init__(self, /, **data: Any) -> None:
    """Create a new model by parsing and validating input data from keyword arguments.

    Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be
    validated to form a valid model.

    `self` is explicitly positional-only to allow `self` as a field name.
    """
    # `__tracebackhide__` tells pytest and some other tools to omit this function from tracebacks
    __tracebackhide__ = True
    validated_self = self.__pydantic_validator__.validate_python(data, self_instance=self)
    if self is not validated_self:
        warnings.warn(
            'A custom validator is returning a value other than `self`.\n'
            "Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.\n"
            'See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.',
            stacklevel=2,
        )