def create(
        self,
        *,
        max_tokens_to_sample: int,
        model: ModelParam,
        prompt: str,
        stream: Literal[True],
        metadata: MetadataParam | NotGiven = NOT_GIVEN,
        stop_sequences: List[str] | NotGiven = NOT_GIVEN,
        temperature: float | NotGiven = NOT_GIVEN,
        top_k: int | NotGiven = NOT_GIVEN,
        top_p: float | NotGiven = NOT_GIVEN,
        betas: List[AnthropicBetaParam] | NotGiven = NOT_GIVEN,
        # 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,
    ) -> Stream[Completion]:
        """[Legacy] Create a Text Completion.

        The Text Completions API is a legacy API.

        We recommend using the
        [Messages API](https://docs.anthropic.com/en/api/messages) going forward.

        Future models and features will not be compatible with Text Completions. See our
        [migration guide](https://docs.anthropic.com/en/api/migrating-from-text-completions-to-messages)
        for guidance in migrating from Text Completions to Messages.

        Args:
          max_tokens_to_sample: The maximum number of tokens to generate before stopping.

              Note that our models may stop _before_ reaching this maximum. This parameter
              only specifies the absolute maximum number of tokens to generate.

          model: The model that will complete your prompt.\n\nSee
              [models](https://docs.anthropic.com/en/docs/models-overview) for additional
              details and options.

          prompt: The prompt that you want Claude to complete.

              For proper response generation you will need to format your prompt using
              alternating `\n\nHuman:` and `\n\nAssistant:` conversational turns. For example:

              ```
              "\n\nHuman: {userQuestion}\n\nAssistant:"
              ```

              See [prompt validation](https://docs.anthropic.com/en/api/prompt-validation) and
              our guide to
              [prompt design](https://docs.anthropic.com/en/docs/intro-to-prompting) for more
              details.

          stream: Whether to incrementally stream the response using server-sent events.

              See [streaming](https://docs.anthropic.com/en/api/streaming) for details.

          metadata: An object describing metadata about the request.

          stop_sequences: Sequences that will cause the model to stop generating.

              Our models stop on `"\n\nHuman:"`, and may include additional built-in stop
              sequences in the future. By providing the stop_sequences parameter, you may
              include additional strings that will cause the model to stop generating.

          temperature: Amount of randomness injected into the response.

              Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
              for analytical / multiple choice, and closer to `1.0` for creative and
              generative tasks.

              Note that even with `temperature` of `0.0`, the results will not be fully
              deterministic.

          top_k: Only sample from the top K options for each subsequent token.

              Used to remove "long tail" low probability responses.
              [Learn more technical details here](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277).

              Recommended for advanced use cases only. You usually only need to use
              `temperature`.

          top_p: Use nucleus sampling.

              In nucleus sampling, we compute the cumulative distribution over all the options
              for each subsequent token in decreasing probability order and cut it off once it
              reaches a particular probability specified by `top_p`. You should either alter
              `temperature` or `top_p`, but not both.

              Recommended for advanced use cases only. You usually only need to use
              `temperature`.

          betas: Optional header to specify the beta version(s) you want to use.

          extra_headers: Send extra headers

          extra_query: Add additional query parameters to the request

          extra_body: Add additional JSON properties to the request

          timeout: Override the client-level default timeout for this request, in seconds
        """
        ...
[Legacy] Create a Text Completion.

        The Text Completions API is a legacy API.

        We recommend using the
        [Messages API](https://docs.anthropic.com/en/api/messages) going forward.

        Future models and features will not be compatible with Text Completions. See our
        [migration guide](https://docs.anthropic.com/en/api/migrating-from-text-completions-to-messages)
        for guidance in migrating from Text Completions to Messages.

        Args:
          max_tokens_to_sample: The maximum number of tokens to generate before stopping.

              Note that our models may stop _before_ reaching this maximum. This parameter
              only specifies the absolute maximum number of tokens to generate.

          model: The model that will complete your prompt.

See
              [models](https://docs.anthropic.com/en/docs/models-overview) for additional
              details and options.

          prompt: The prompt that you want Claude to complete.

              For proper response generation you will need to format your prompt using
              alternating `

Human:` and `

Assistant:` conversational turns. For example:

              ```
              "

Human: {userQuestion}

Assistant:"
              ```

              See [prompt validation](https://docs.anthropic.com/en/api/prompt-validation) and
              our guide to
              [prompt design](https://docs.anthropic.com/en/docs/intro-to-prompting) for more
              details.

          stream: Whether to incrementally stream the response using server-sent events.

              See [streaming](https://docs.anthropic.com/en/api/streaming) for details.

          metadata: An object describing metadata about the request.

          stop_sequences: Sequences that will cause the model to stop generating.

              Our models stop on `"

Human:"`, and may include additional built-in stop
              sequences in the future. By providing the stop_sequences parameter, you may
              include additional strings that will cause the model to stop generating.

          temperature: Amount of randomness injected into the response.

              Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
              for analytical / multiple choice, and closer to `1.0` for creative and
              generative tasks.

              Note that even with `temperature` of `0.0`, the results will not be fully
              deterministic.

          top_k: Only sample from the top K options for each subsequent token.

              Used to remove "long tail" low probability responses.
              [Learn more technical details here](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277).

              Recommended for advanced use cases only. You usually only need to use
              `temperature`.

          top_p: Use nucleus sampling.

              In nucleus sampling, we compute the cumulative distribution over all the options
              for each subsequent token in decreasing probability order and cut it off once it
              reaches a particular probability specified by `top_p`. You should either alter
              `temperature` or `top_p`, but not both.

              Recommended for advanced use cases only. You usually only need to use
              `temperature`.

          betas: Optional header to specify the beta version(s) you want to use.

          extra_headers: Send extra headers

          extra_query: Add additional query parameters to the request

          extra_body: Add additional JSON properties to the request

          timeout: Override the client-level default timeout for this request, in seconds
        
src/anthropic/resources/completions.py