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LlmBot

dandy.llm.BaseLlmBot

Bases: BaseLlmProcessor, ABC, Generic[IntelType]

config = 'DEFAULT' class-attribute instance-attribute

config_options = LlmConfigOptions() class-attribute instance-attribute

instructions_prompt = Prompt("You're a helpful assistant please follow the users instructions.") class-attribute instance-attribute

intel_class = DefaultLlmIntel class-attribute instance-attribute

process_prompt_to_intel classmethod

Source code in dandy/llm/bot/llm_bot.py 
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@classmethod
def process_prompt_to_intel(
        cls,
        prompt: Union[Prompt, str],
        intel_class: Union[Type[IntelType], None] = None,
        intel_object: Union[IntelType, None] = None,
        images: Union[List[str], None] = None,
        image_files: Union[List[str | Path], None] = None,
        include_fields: Union[IncEx, None] = None,
        exclude_fields: Union[IncEx, None] = None,
        postfix_system_prompt: Union[Prompt, None] = None
) -> IntelType:

    if intel_class is None and intel_object is None:
        intel_class = cls.intel_class

    if image_files:
        images = [] if images is None else images

        for image_file in image_files:
            images.append(encode_file_to_base64(image_file))

    system_prompt = Prompt()
    system_prompt.prompt(cls.instructions_prompt)

    if postfix_system_prompt:
        system_prompt.line_break()
        system_prompt.prompt(postfix_system_prompt)

    return llm_configs[cls.config].generate_service(
        llm_options=cls.config_options
    ).process_prompt_to_intel(
        prompt=prompt if isinstance(prompt, Prompt) else Prompt(prompt),
        intel_class=intel_class,
        intel_object=intel_object,
        images=images,
        include_fields=include_fields,
        exclude_fields=exclude_fields,
        system_prompt=system_prompt
    )

process_to_future classmethod

Source code in dandy/llm/bot/llm_bot.py 
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@classmethod
def process_to_future(cls, *args, **kwargs) -> AsyncFuture[IntelType]:
    return AsyncFuture[IntelType](cls.process, *args, **kwargs)

dandy.llm.LlmBot

Bases: BaseLlmBot, Generic[IntelType]

intel_class = DefaultLlmIntel class-attribute instance-attribute

process classmethod

Source code in dandy/llm/bot/llm_bot.py 
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@classmethod
def process(
        cls,
        prompt: Union[Prompt, str],
        intel_class: Union[Type[IntelType], None] = None,
        intel_object: Union[IntelType, None] = None,
        images: Union[List[str], None] = None,
        image_files: Union[List[str | Path], None] = None,
        include_fields: Union[IncEx, None] = None,
        exclude_fields: Union[IncEx, None] = None,
        postfix_system_prompt: Union[Prompt, None] = None
) -> IntelType:

    return cls.process_prompt_to_intel(
        prompt=prompt,
        intel_class= intel_class or cls.intel_class,
        intel_object=intel_object,
        images=images,
        image_files=image_files,
        include_fields=include_fields,
        exclude_fields=exclude_fields,
        postfix_system_prompt=postfix_system_prompt
    )