Camel.schemas.outlines converter

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OutlinesConverter

class OutlinesConverter(BaseConverter):

• 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/

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init

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

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convert_regex

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

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

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convert_json

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

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

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convert_pydantic

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

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

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convert_type

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

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/)

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

​

convert_choice

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

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

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convert_grammar

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

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

​

convert

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

• 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.