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OpenAIModel

class OpenAIModel(BaseModelBackend):
OpenAI API in a unified BaseModelBackend interface. Parameters:
  • model_type (Union[ModelType, str]): Model for which a backend is created, one of GPT_* series.
  • model_config_dict (Optional[Dict[str, Any]], optional): A dictionary that will be fed into:obj:openai.ChatCompletion.create(). If :obj:None, :obj:ChatGPTConfig().as_dict() will be used. (default: :obj:None)
  • api_key (Optional[str], optional): The API key for authenticating with the OpenAI service. (default: :obj:None)
  • url (Optional[str], optional): The url to the OpenAI service. (default: :obj:None)
  • token_counter (Optional[BaseTokenCounter], optional): Token counter to use for the model. If not provided, :obj:OpenAITokenCounter will be used. (default: :obj:None)
  • timeout (Optional[float], optional): The timeout value in seconds for API calls. If not provided, will fall back to the MODEL_TIMEOUT environment variable or default to 180 seconds. (default: :obj:None)
  • max_retries (int, optional): Maximum number of retries for API calls. (default: :obj:3) **kwargs (Any): Additional arguments to pass to the OpenAI client initialization. These can include parameters like ‘organization’, ‘default_headers’, ‘http_client’, etc.

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init

def __init__(
    self,
    model_type: Union[ModelType, str],
    model_config_dict: Optional[Dict[str, Any]] = None,
    api_key: Optional[str] = None,
    url: Optional[str] = None,
    token_counter: Optional[BaseTokenCounter] = None,
    timeout: Optional[float] = None,
    max_retries: int = 3,
    **kwargs: Any
):

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_sanitize_config

def _sanitize_config(self, config_dict: Dict[str, Any]):
Sanitize the model configuration for O1 models.

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_adapt_messages_for_o1_models

def _adapt_messages_for_o1_models(self, messages: List[OpenAIMessage]):
Adjust message roles to comply with O1 model requirements by converting ‘system’ or ‘developer’ to ‘user’ role. Parameters:
  • messages (List[OpenAIMessage]): Message list with the chat history in OpenAI API format.
Returns: processed_messages (List[OpenAIMessage]): Return a new list of messages to avoid mutating input.

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token_counter

def token_counter(self):
Returns: BaseTokenCounter: The token counter following the model’s tokenization style.

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_run

def _run(
    self,
    messages: List[OpenAIMessage],
    response_format: Optional[Type[BaseModel]] = None,
    tools: Optional[List[Dict[str, Any]]] = None
):
Runs inference of OpenAI chat completion. Parameters:
  • messages (List[OpenAIMessage]): Message list with the chat history in OpenAI API format.
  • response_format (Optional[Type[BaseModel]]): The format of the response.
  • tools (Optional[List[Dict[str, Any]]]): The schema of the tools to use for the request.
Returns: Union[ChatCompletion, Stream[ChatCompletionChunk], ChatCompletionStreamManager[BaseModel]]: ChatCompletion in the non-stream mode, Stream[ChatCompletionChunk]in the stream mode, or ChatCompletionStreamManager[BaseModel] for structured output streaming.

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_request_chat_completion

def _request_chat_completion(
    self,
    messages: List[OpenAIMessage],
    tools: Optional[List[Dict[str, Any]]] = None
):

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_request_parse

def _request_parse(
    self,
    messages: List[OpenAIMessage],
    response_format: Type[BaseModel],
    tools: Optional[List[Dict[str, Any]]] = None
):

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_request_stream_parse

def _request_stream_parse(
    self,
    messages: List[OpenAIMessage],
    response_format: Type[BaseModel],
    tools: Optional[List[Dict[str, Any]]] = None
):
Request streaming structured output parsing.

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stream

def stream(self):
Returns: bool: Whether the model is in stream mode.