`marvin.fns.cast`

into the specified target type, maintaining as much semantic meaning as possible.

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`

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

top level

agents

beta

cli

database

defaults

engine

fns

handlers

instructions

memory

prompts

settings

tasks

thread

tools

utilities

cast

`marvin.fns.cast`

Functions

`cast`

`cast_async`

​marvin.fns.cast

​Functions

​cast

​cast_async

`marvin.fns.cast`

Functions

`cast`

`cast_async`