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marvin.fns.cast
Cast is a function that uses a language model to analyze the input data and transform it
into the specified target type, maintaining as much semantic meaning as possible.
Constants
DEFAULT_PROMPT
DEFAULT_PROMPT = "'\nYou are an expert data converter that always maintains as much semantic\nmeaning as possible. You use inference or deduction whenever necessary to\nunderstand and transform the input data. Examine the provided `data`, text,\nor information and transform it into a single entity of the requested type.\n\n- When providing integers, do not write out any decimals at all\n- Use deduction where appropriate e.g. "3 dollars fifty cents" should be\n converted to 3.5 when casting to a float\n- Preserve as much of the original meaning and structure as possible while\n conforming to the target type\n- When providing a string response, do not return JSON or a quoted string\n unless they provided instructions requiring it. If you do return JSON, it\n must be valid and parseable including double quotes.\n- When converting to bool, treat "truthy" values as true'"
PROMPT
Functions
cast
def cast(data: Any, target: TargetType[T] | None = None, instructions: str | None = None, agent: Agent | None = None, thread: Thread | str | None = None, context: dict[str, Any] | None = None, handlers: list[Handler | AsyncHandler] | None = None, prompt: str | None = None) -> T
Transforms input data into a specific type using a language model.
This function uses a language model to analyze the input data and transform it
into the specified target type, maintaining as much semantic meaning as possible.
Args:
data: The input data to transform. Can be any type.
target: The type to transform the data into. Defaults to str.
instructions: Optional additional instructions to guide the transformation.
Used to provide specific guidance about how to interpret or transform
the data.
agent: Optional custom agent to use for transformation. If not provided,
the default agent will be used.
thread: Optional thread for maintaining conversation context. Can be
either a Thread object or a string thread ID.
context: Optional dictionary of additional context to include in the task.
handlers: Optional list of handlers to use for the task.
prompt: Optional prompt to use for the task. If not provided, the default
prompt will be used.
Returns:
The transformed data of type T.
Examples:
from marvin import cast
cast(123, str) # '123'
cast("three point five", float, instructions="Convert words to numbers") # 3.5
cast("yes", bool) # True
cast_async
def cast_async(data: Any, target: TargetType[T] | None = None, instructions: str | None = None, agent: Agent | None = None, thread: Thread | str | None = None, context: dict[str, Any] | None = None, handlers: list[Handler | AsyncHandler] | None = None, prompt: str | None = None) -> T
Asynchronously transforms input data into a specific type using a language model.
This function uses a language model to analyze the input data and transform it
into the specified target type, maintaining as much semantic meaning as possible.
Args:
data: The input data to transform. Can be any type.
target: The type to transform the data into. Defaults to str.
instructions: Optional additional instructions to guide the transformation.
Used to provide specific guidance about how to interpret or transform
the data.
agent: Optional custom agent to use for transformation. If not provided,
the default agent will be used.
thread: Optional thread for maintaining conversation context. Can be
either a Thread object or a string thread ID.
context: Optional dictionary of additional context to include in the task.
handlers: Optional list of handlers to use for the task.
prompt: Optional prompt to use for the task. If not provided, the default
prompt will be used.
Returns:
The transformed data of type T.
Examples:
from marvin import cast_async
await cast_async("whats the answer to it all?, int) # 42
await cast_async("three point five", float, instructions="Convert words to numbers") # 3.5
await cast_async("yes", bool) # True
Parent Module: fns