mistral_common.protocol.base

BaseCompletionRequest(**data)

Bases: MistralBase

Base class for completion requests.

Attributes:

Name	Type	Description
temperature	float	Sampling temperature to use, 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.
top_p	float	Nucleus sampling parameter, top-p probability mass, between 0 and 1.
max_tokens	Optional[int]	Maximum number of tokens to generate.
random_seed	Optional[int]	Random seed for reproducibility.

Examples:

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

Source code in .venv/lib/python3.13/site-packages/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,
        )

UsageInfo(**data)

Bases: MistralBase

Usage statistics for a completion request.

Attributes:

Name	Type	Description
prompt_tokens	int	Number of tokens in the prompt.
completion_tokens	Optional[int]	Number of tokens in the generated completion.
total_tokens	int	Total number of tokens used in the request (prompt + completion).

Examples:

>>> info = UsageInfo(prompt_tokens=10, completion_tokens=20, total_tokens=30)

Source code in .venv/lib/python3.13/site-packages/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,
        )