​
OutlinesConverter

class OutlinesConverter(BaseConverter):

OutlinesConverter is a class that converts a string or a function into a BaseModel schema.

Parameters:

  • model_type (str, optional): The model type to be used.
  • platform (str, optional): The platform to be used. 1. transformers 2. mamba 3. vllm 4. llamacpp 5. mlx (default: “transformers”) **kwargs: The keyword arguments to be used. See the outlines documentation for more details. See
  • https: //dottxt-ai.github.io/outlines/latest/reference/models/models/

​
init

def __init__(
    self,
    model_type: str,
    platform: Literal['vllm', 'transformers', 'mamba', 'llamacpp', 'mlx'] = 'transformers',
    **kwargs: Any
):

​
convert_regex

def convert_regex(self, content: str, regex_pattern: str):

Convert the content to the specified regex pattern.

Parameters:

  • content (str): The content to be converted.
  • regex_pattern (str): The regex pattern to be used.

Returns:

str: The converted content.

​
convert_json

def convert_json(self, content: str, output_schema: Union[str, Callable]):

Convert the content to the specified JSON schema given by output_schema.

Parameters:

  • content (str): The content to be converted.
  • output_schema (Union[str, Callable]): The expected format of the response.

Returns:

dict: The converted content in JSON format.

​
convert_pydantic

def convert_pydantic(self, content: str, output_schema: Type[BaseModel]):

Convert the content to the specified Pydantic schema.

Parameters:

  • content (str): The content to be converted.
  • output_schema (Type[BaseModel]): The expected format of the response.

Returns:

BaseModel: The converted content in pydantic model format.

​
convert_type

def convert_type(self, content: str, type_name: type):

Convert the content to the specified type.

The following types are currently available:

  1. int
  2. float
  3. bool
  4. datetime.date
  5. datetime.time
  6. datetime.datetime
  7. custom types (https://dottxt-ai.github.io/outlines/latest/reference/generation/types/)

Parameters:

  • content (str): The content to be converted.
  • type_name (type): The type to be used.

Returns:

str: The converted content.

​
convert_choice

def convert_choice(self, content: str, choices: List[str]):

Convert the content to the specified choice.

Parameters:

  • content (str): The content to be converted.
  • choices (List[str]): The choices to be used.

Returns:

str: The converted content.

​
convert_grammar

def convert_grammar(self, content: str, grammar: str):

Convert the content to the specified grammar.

Parameters:

  • content (str): The content to be converted.
  • grammar (str): The grammar to be used.

Returns:

str: The converted content.

​
convert

def convert(
    self,
    content: str,
    type: Literal['regex', 'json', 'type', 'choice', 'grammar'],
    **kwargs
):

Formats the input content into the expected BaseModel.

Parameters:

  • type (Literal["regex", "json", "type", "choice", "grammar"]): The type of conversion to perform. Options are: - “regex”: Match the content against a regex pattern. - “pydantic”: Convert the content into a pydantic model. - “json”: Convert the content into a JSON based on a schema. - “type”: Convert the content into a specified type. - “choice”: Match the content against a list of valid choices. - “grammar”: Convert the content using a specified grammar.
  • content (str): The content to be formatted. **kwargs: Additional keyword arguments specific to the conversion type. - For “regex”:
  • regex_pattern (str): The regex pattern to use for matching. - For “pydantic”:
  • output_schema (Type[BaseModel]): The schema to validate and format the pydantic model. - For “json”:
  • output_schema (Union[str, Callable]): The schema to validate and format the JSON object. - For “type”:
  • type_name (str): The target type name for the conversion. - For “choice”:
  • choices (List[str]): A list of valid choices to match against. - For “grammar”:
  • grammar (str): The grammar definition to use for content conversion.