extract

marvin.fns.extract

Constants

PROMPT

PROMPT = "'\nYou are an expert entity extractor that always maintains as much semantic\nmeaning as possible. You use inference or deduction whenever necessary to\nsupply missing or omitted data. Examine the provided `data`, text, or\ninformation and generate a list of any entities or objects that match the\nrequested format.\n\n- When providing integers, do not write out any decimals at all\n- Use deduction where appropriate e.g. "3 dollars fifty cents" is a single\n    value [3.5] not two values [3, 50] unless the user specifically asks for\n    each part.'"

T

T = TypeVar('T')

Functions

extract

def extract(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) -> list[T]

Extracts entities of a specific type from the provided data.

This function uses a language model to identify and extract entities of the specified type from the input data. The extracted entities are returned as a list.

Args: data: The input data to extract entities from. Can be any type. target: The type of entities to extract. Defaults to str. instructions: Optional additional instructions to guide the extraction. Used to provide specific guidance about what to extract or how to process the data. Required when target is str. agent: Optional custom agent to use for extraction. 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.

Returns: A list of extracted entities of type T.

Raises: ValueError: If target is str and no instructions are provided.

extract_async

def extract_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) -> list[T]

Extracts entities of a specific type from the provided data.

This function uses a language model to identify and extract entities of the specified type from the input data. The extracted entities are returned as a list.

Args: data: The input data to extract entities from. Can be any type. target: The type of entities to extract. Defaults to str. instructions: Optional additional instructions to guide the extraction. Used to provide specific guidance about what to extract or how to process the data. Required when target is str. agent: Optional custom agent to use for extraction. 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.

Returns: A list of extracted entities of type T.

Raises: ValueError: If target is str and no instructions are provided.

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Parent Module: fns