langchain.prompts.example_selector.length_based.LengthBasedExampleSelector¶
class langchain.prompts.example_selector.length_based.LengthBasedExampleSelector[source]¶
Bases: BaseExampleSelector, BaseModel
Select examples based on length.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param example_prompt: langchain.prompts.prompt.PromptTemplate [Required]¶
Prompt template used to format the examples.
param examples: List[dict] [Required]¶
A list of the examples that the prompt template expects.
param get_text_length: Callable[[str], int] = <function _get_length_based>¶
Function to measure prompt length. Defaults to word count.
param max_length: int = 2048¶
Max length for the prompt, beyond which examples are cut.
add_example(example: Dict[str, str]) → None[source]¶
Add new example to list.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include – fields to include in new model
exclude – fields to exclude from new model, as with values this takes precedence over include