OpenAI

OpenAIExecutor

Class representing an interface to the Azure OpenAI API.

Source code in ragfit/models/openai_executor.py

class OpenAIExecutor:
    """
    Class representing an interface to the Azure OpenAI API.
    """

    def __init__(
        self,
        azure_endpoint: str,
        api_key: str = None,
        api_version: str = "2024-02-15-preview",
        model: str = "GPT-4-32k-Bot",
        chat_parameters: dict = None,
        delay: int = 1,
    ):
        """
        Initialize the OpenAIExecutor.

        Args:
            azure_endpoint (str): The Azure endpoint.
            api_key (str): The API key, can also read of ENV variable.
            api_version (str): The API version.
            model (str): The model to use, sometimes called deployment or engine.
            chat_parameters (dict): The chat parameters.
            delay (int): delay between calls.
        """
        self.delay = delay
        self.model = model
        self.chat_parameters = dict(
            temperature=0.7,
            max_tokens=200,
            top_p=0.95,
            frequency_penalty=0,
            presence_penalty=0,
            stop=None,
        )
        if chat_parameters:
            self.chat_parameters.update(chat_parameters)

        self.client = AzureOpenAI(
            azure_endpoint=azure_endpoint,
            api_key=api_key or os.getenv("AZURE_OPENAI_API_KEY"),
            api_version=api_version,
        )

    def chat(self, prompt: Union[List, str], instruction: str = None) -> str:
        """
        Chat with the OpenAI API.

        Args:
            prompt (Union[List, str]): The prompt to chat.
            instruction (str): The instruction to use.

        Returns:
            str: The response. Empty string if error.
        """
        if isinstance(prompt, str):
            prompt = [
                {
                    "role": "system",
                    "content": (
                        instruction
                        or "You are an AI assistant that helps people find information."
                    ),
                },
                {"role": "user", "content": prompt},
            ]

        if self.delay:
            time.sleep(self.delay)

        try:
            completion = self.client.chat.completions.create(
                model=self.model,
                messages=prompt,
                **self.chat_parameters,
            )
            message_obj = completion.choices[0].message

            if hasattr(message_obj, "content"):
                answer = message_obj.content
                return answer or ""
            else:
                return ""

        except Exception as e:
            logging.info(f"OPENAI error:\n{e}")
            return ""

__init__(azure_endpoint: str, api_key: str = None, api_version: str = '2024-02-15-preview', model: str = 'GPT-4-32k-Bot', chat_parameters: dict = None, delay: int = 1)

Initialize the OpenAIExecutor.

Parameters:

• azure_endpoint (str) –

  The Azure endpoint.

• api_key (str, default: None ) –

  The API key, can also read of ENV variable.

• api_version (str, default: '2024-02-15-preview' ) –

  The API version.

• model (str, default: 'GPT-4-32k-Bot' ) –

  The model to use, sometimes called deployment or engine.

• chat_parameters (dict, default: None ) –

  The chat parameters.

• delay (int, default: 1 ) –

  delay between calls.

Source code in ragfit/models/openai_executor.py

def __init__(
    self,
    azure_endpoint: str,
    api_key: str = None,
    api_version: str = "2024-02-15-preview",
    model: str = "GPT-4-32k-Bot",
    chat_parameters: dict = None,
    delay: int = 1,
):
    """
    Initialize the OpenAIExecutor.

    Args:
        azure_endpoint (str): The Azure endpoint.
        api_key (str): The API key, can also read of ENV variable.
        api_version (str): The API version.
        model (str): The model to use, sometimes called deployment or engine.
        chat_parameters (dict): The chat parameters.
        delay (int): delay between calls.
    """
    self.delay = delay
    self.model = model
    self.chat_parameters = dict(
        temperature=0.7,
        max_tokens=200,
        top_p=0.95,
        frequency_penalty=0,
        presence_penalty=0,
        stop=None,
    )
    if chat_parameters:
        self.chat_parameters.update(chat_parameters)

    self.client = AzureOpenAI(
        azure_endpoint=azure_endpoint,
        api_key=api_key or os.getenv("AZURE_OPENAI_API_KEY"),
        api_version=api_version,
    )

chat(prompt: Union[List, str], instruction: str = None) -> str

Chat with the OpenAI API.

Parameters:

• prompt (Union[List, str]) –

  The prompt to chat.

• instruction (str, default: None ) –

  The instruction to use.

Returns:

• str ( str ) –

  The response. Empty string if error.

Source code in ragfit/models/openai_executor.py

def chat(self, prompt: Union[List, str], instruction: str = None) -> str:
    """
    Chat with the OpenAI API.

    Args:
        prompt (Union[List, str]): The prompt to chat.
        instruction (str): The instruction to use.

    Returns:
        str: The response. Empty string if error.
    """
    if isinstance(prompt, str):
        prompt = [
            {
                "role": "system",
                "content": (
                    instruction
                    or "You are an AI assistant that helps people find information."
                ),
            },
            {"role": "user", "content": prompt},
        ]

    if self.delay:
        time.sleep(self.delay)

    try:
        completion = self.client.chat.completions.create(
            model=self.model,
            messages=prompt,
            **self.chat_parameters,
        )
        message_obj = completion.choices[0].message

        if hasattr(message_obj, "content"):
            answer = message_obj.content
            return answer or ""
        else:
            return ""

    except Exception as e:
        logging.info(f"OPENAI error:\n{e}")
        return ""