LLM

OpenAIModel

Bases: Model

A class to interface with OpenAI's language models using the Weave framework.

This class provides methods to create structured messages and generate predictions using OpenAI's chat completion API. It is designed to work with both single and multiple user prompts, and optionally includes a system prompt to guide the model's responses.

Parameters:

Name	Type	Description	Default
model_name	str	The name of the OpenAI model to be used for predictions.	'gpt-4o'

Source code in guardrails_genie/llm.py

class OpenAIModel(weave.Model):
    """
    A class to interface with OpenAI's language models using the Weave framework.

    This class provides methods to create structured messages and generate predictions
    using OpenAI's chat completion API. It is designed to work with both single and
    multiple user prompts, and optionally includes a system prompt to guide the model's
    responses.

    Args:
        model_name (str): The name of the OpenAI model to be used for predictions.
    """

    model_name: str
    _openai_client: OpenAI

    def __init__(self, model_name: str = "gpt-4o") -> None:
        super().__init__(model_name=model_name)
        self._openai_client = OpenAI()

    @weave.op()
    def create_messages(
        self,
        user_prompts: Union[str, list[str]],
        system_prompt: Optional[str] = None,
        messages: Optional[list[dict]] = None,
    ) -> list[dict]:
        """
        Create a list of messages for the OpenAI chat completion API.

        This function constructs a list of messages in the format required by the
        OpenAI chat completion API. It takes user prompts, an optional system prompt,
        and an optional list of existing messages, and combines them into a single
        list of messages.

        Args:
            user_prompts (Union[str, list[str]]): A single user prompt or a list of
                user prompts to be included in the messages.
            system_prompt (Optional[str]): An optional system prompt to guide the
                model's responses. If provided, it will be added at the beginning
                of the messages list.
            messages (Optional[list[dict]]): An optional list of existing messages
                to which the new prompts will be appended. If not provided, a new
                list will be created.

        Returns:
            list[dict]: A list of messages formatted for the OpenAI chat completion API.
        """
        user_prompts = [user_prompts] if isinstance(user_prompts, str) else user_prompts
        messages = list(messages) if isinstance(messages, dict) else []
        for user_prompt in user_prompts:
            messages.append({"role": "user", "content": user_prompt})
        if system_prompt is not None:
            messages = [{"role": "system", "content": system_prompt}] + messages
        return messages

    @weave.op()
    def predict(
        self,
        user_prompts: Union[str, list[str]],
        system_prompt: Optional[str] = None,
        messages: Optional[list[dict]] = None,
        **kwargs,
    ) -> ChatCompletion:
        """
        Generate a chat completion response using the OpenAI API.

        This function takes user prompts, an optional system prompt, and an optional
        list of existing messages to create a list of messages formatted for the
        OpenAI chat completion API. It then sends these messages to the OpenAI API
        to generate a chat completion response.

        Args:
            user_prompts (Union[str, list[str]]): A single user prompt or a list of
                user prompts to be included in the messages.
            system_prompt (Optional[str]): An optional system prompt to guide the
                model's responses. If provided, it will be added at the beginning
                of the messages list.
            messages (Optional[list[dict]]): An optional list of existing messages
                to which the new prompts will be appended. If not provided, a new
                list will be created.
            **kwargs: Additional keyword arguments to be passed to the OpenAI API
                for chat completion.

        Returns:
            ChatCompletion: The chat completion response from the OpenAI API.
        """
        messages = self.create_messages(user_prompts, system_prompt, messages)
        if "response_format" in kwargs:
            response = self._openai_client.beta.chat.completions.parse(
                model=self.model_name, messages=messages, **kwargs
            )
        else:
            response = self._openai_client.chat.completions.create(
                model=self.model_name, messages=messages, **kwargs
            )
        return response

create_messages(user_prompts, system_prompt=None, messages=None)

Create a list of messages for the OpenAI chat completion API.

This function constructs a list of messages in the format required by the OpenAI chat completion API. It takes user prompts, an optional system prompt, and an optional list of existing messages, and combines them into a single list of messages.

Parameters:

Name	Type	Description	Default
user_prompts	Union[str, list[str]]	A single user prompt or a list of user prompts to be included in the messages.	required
system_prompt	Optional[str]	An optional system prompt to guide the model's responses. If provided, it will be added at the beginning of the messages list.	None
messages	Optional[list[dict]]	An optional list of existing messages to which the new prompts will be appended. If not provided, a new list will be created.	None

Returns:

Type	Description
list[dict]	list[dict]: A list of messages formatted for the OpenAI chat completion API.

Source code in guardrails_genie/llm.py

@weave.op()
def create_messages(
    self,
    user_prompts: Union[str, list[str]],
    system_prompt: Optional[str] = None,
    messages: Optional[list[dict]] = None,
) -> list[dict]:
    """
    Create a list of messages for the OpenAI chat completion API.

    This function constructs a list of messages in the format required by the
    OpenAI chat completion API. It takes user prompts, an optional system prompt,
    and an optional list of existing messages, and combines them into a single
    list of messages.

    Args:
        user_prompts (Union[str, list[str]]): A single user prompt or a list of
            user prompts to be included in the messages.
        system_prompt (Optional[str]): An optional system prompt to guide the
            model's responses. If provided, it will be added at the beginning
            of the messages list.
        messages (Optional[list[dict]]): An optional list of existing messages
            to which the new prompts will be appended. If not provided, a new
            list will be created.

    Returns:
        list[dict]: A list of messages formatted for the OpenAI chat completion API.
    """
    user_prompts = [user_prompts] if isinstance(user_prompts, str) else user_prompts
    messages = list(messages) if isinstance(messages, dict) else []
    for user_prompt in user_prompts:
        messages.append({"role": "user", "content": user_prompt})
    if system_prompt is not None:
        messages = [{"role": "system", "content": system_prompt}] + messages
    return messages

predict(user_prompts, system_prompt=None, messages=None, **kwargs)

Generate a chat completion response using the OpenAI API.

This function takes user prompts, an optional system prompt, and an optional list of existing messages to create a list of messages formatted for the OpenAI chat completion API. It then sends these messages to the OpenAI API to generate a chat completion response.

Parameters:

Name	Type	Description	Default
user_prompts	Union[str, list[str]]	A single user prompt or a list of user prompts to be included in the messages.	required
system_prompt	Optional[str]	An optional system prompt to guide the model's responses. If provided, it will be added at the beginning of the messages list.	None
messages	Optional[list[dict]]	An optional list of existing messages to which the new prompts will be appended. If not provided, a new list will be created.	None
**kwargs		Additional keyword arguments to be passed to the OpenAI API for chat completion.	{}

Returns:

Name	Type	Description
ChatCompletion	ChatCompletion	The chat completion response from the OpenAI API.

Source code in guardrails_genie/llm.py

@weave.op()
def predict(
    self,
    user_prompts: Union[str, list[str]],
    system_prompt: Optional[str] = None,
    messages: Optional[list[dict]] = None,
    **kwargs,
) -> ChatCompletion:
    """
    Generate a chat completion response using the OpenAI API.

    This function takes user prompts, an optional system prompt, and an optional
    list of existing messages to create a list of messages formatted for the
    OpenAI chat completion API. It then sends these messages to the OpenAI API
    to generate a chat completion response.

    Args:
        user_prompts (Union[str, list[str]]): A single user prompt or a list of
            user prompts to be included in the messages.
        system_prompt (Optional[str]): An optional system prompt to guide the
            model's responses. If provided, it will be added at the beginning
            of the messages list.
        messages (Optional[list[dict]]): An optional list of existing messages
            to which the new prompts will be appended. If not provided, a new
            list will be created.
        **kwargs: Additional keyword arguments to be passed to the OpenAI API
            for chat completion.

    Returns:
        ChatCompletion: The chat completion response from the OpenAI API.
    """
    messages = self.create_messages(user_prompts, system_prompt, messages)
    if "response_format" in kwargs:
        response = self._openai_client.beta.chat.completions.parse(
            model=self.model_name, messages=messages, **kwargs
        )
    else:
        response = self._openai_client.chat.completions.create(
            model=self.model_name, messages=messages, **kwargs
        )
    return response