Method create

src/openai/resources/completions.py:52–207

Creates a completion for the provided prompt and parameters. Returns a completion object, or a sequence of completion objects if the request is streamed. Args: model: ID of the model to use. You can use the [List models](https://platform.ope

(
        self,
        *,
        model: Union[str, Literal["gpt-3.5-turbo-instruct", "davinci-002", "babbage-002"]],
        prompt: Union[str, SequenceNotStr[str], Iterable[int], Iterable[Iterable[int]], None],
        best_of: Optional[int] | Omit = omit,
        echo: Optional[bool] | Omit = omit,
        frequency_penalty: Optional[float] | Omit = omit,
        logit_bias: Optional[Dict[str, int]] | Omit = omit,
        logprobs: Optional[int] | Omit = omit,
        max_tokens: Optional[int] | Omit = omit,
        n: Optional[int] | Omit = omit,
        presence_penalty: Optional[float] | Omit = omit,
        seed: Optional[int] | Omit = omit,
        stop: Union[Optional[str], SequenceNotStr[str], None] | Omit = omit,
        stream: Optional[Literal[False]] | Omit = omit,
        stream_options: Optional[ChatCompletionStreamOptionsParam] | Omit = omit,
        suffix: Optional[str] | Omit = omit,
        temperature: Optional[float] | Omit = omit,
        top_p: Optional[float] | Omit = omit,
        user: str | Omit = omit,
        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
        # The extra values given here take precedence over values defined on the client or passed to this method.
        extra_headers: Headers | None = None,
        extra_query: Query | None = None,
        extra_body: Body | None = None,
        timeout: float | httpx.Timeout | None | NotGiven = not_given,
    )

    @overload
    def create(
        self,
        *,
        model: Union[str, Literal["gpt-3.5-turbo-instruct", "davinci-002", "babbage-002"]],
        prompt: Union[str, SequenceNotStr[str], Iterable[int], Iterable[Iterable[int]], None],
        best_of: Optional[int] | Omit = omit,
        echo: Optional[bool] | Omit = omit,
        frequency_penalty: Optional[float] | Omit = omit,
        logit_bias: Optional[Dict[str, int]] | Omit = omit,
        logprobs: Optional[int] | Omit = omit,
        max_tokens: Optional[int] | Omit = omit,
        n: Optional[int] | Omit = omit,
        presence_penalty: Optional[float] | Omit = omit,
        seed: Optional[int] | Omit = omit,
        stop: Union[Optional[str], SequenceNotStr[str], None] | Omit = omit,
        stream: Optional[Literal[False]] | Omit = omit,
        stream_options: Optional[ChatCompletionStreamOptionsParam] | Omit = omit,
        suffix: Optional[str] | Omit = omit,
        temperature: Optional[float] | Omit = omit,
        top_p: Optional[float] | Omit = omit,
        user: str | Omit = omit,
        # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
        # The extra values given here take precedence over values defined on the client or passed to this method.
        extra_headers: Headers | None = None,
        extra_query: Query | None = None,
        extra_body: Body | None = None,
        timeout: float | httpx.Timeout | None | NotGiven = not_given,
    ) -> Completion:
        """
        Creates a completion for the provided prompt and parameters.

        Returns a completion object, or a sequence of completion objects if the request
        is streamed.

        Args:
          model: ID of the model to use. You can use the
              [List models](https://platform.openai.com/docs/api-reference/models/list) API to
              see all of your available models, or see our
              [Model overview](https://platform.openai.com/docs/models) for descriptions of
              them.

          prompt: The prompt(s) to generate completions for, encoded as a string, array of
              strings, array of tokens, or array of token arrays.

              Note that <|endoftext|> is the document separator that the model sees during
              training, so if a prompt is not specified the model will generate as if from the
              beginning of a new document.

          best_of: Generates `best_of` completions server-side and returns the "best" (the one with
              the highest log probability per token). Results cannot be streamed.

              When used with `n`, `best_of` controls the number of candidate completions and
              `n` specifies how many to return – `best_of` must be greater than `n`.

              **Note:** Because this parameter generates many completions, it can quickly
              consume your token quota. Use carefully and ensure that you have reasonable
              settings for `max_tokens` and `stop`.