two version of R2R are here HEAD master

1 files changed, 823 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/anthropic/resources/completions.py b/.venv/lib/python3.12/site-packages/anthropic/resources/completions.py
new file mode 100644
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+++ b/.venv/lib/python3.12/site-packages/anthropic/resources/completions.py
@@ -0,0 +1,823 @@
+# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
+
+from __future__ import annotations
+
+from typing import List
+from typing_extensions import Literal, overload
+
+import httpx
+
+from .. import _legacy_response
+from ..types import completion_create_params
+from .._types import NOT_GIVEN, Body, Query, Headers, NotGiven
+from .._utils import (
+    is_given,
+    required_args,
+    maybe_transform,
+    async_maybe_transform,
+)
+from .._compat import cached_property
+from .._resource import SyncAPIResource, AsyncAPIResource
+from .._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
+from .._constants import DEFAULT_TIMEOUT
+from .._streaming import Stream, AsyncStream
+from .._base_client import make_request_options
+from ..types.completion import Completion
+from ..types.model_param import ModelParam
+from ..types.metadata_param import MetadataParam
+
+__all__ = ["Completions", "AsyncCompletions"]
+
+
+class Completions(SyncAPIResource):
+    @cached_property
+    def with_raw_response(self) -> CompletionsWithRawResponse:
+        """
+        This property can be used as a prefix for any HTTP method call to return
+        the raw response object instead of the parsed content.
+
+        For more information, see https://www.github.com/anthropics/anthropic-sdk-python#accessing-raw-response-data-eg-headers
+        """
+        return CompletionsWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> CompletionsWithStreamingResponse:
+        """
+        An alternative to `.with_raw_response` that doesn't eagerly read the response body.
+
+        For more information, see https://www.github.com/anthropics/anthropic-sdk-python#with_streaming_response
+        """
+        return CompletionsWithStreamingResponse(self)
+
+    @overload
+    def create(
+        self,
+        *,
+        max_tokens_to_sample: int,
+        model: ModelParam,
+        prompt: str,
+        metadata: MetadataParam | NotGiven = NOT_GIVEN,
+        stop_sequences: List[str] | NotGiven = NOT_GIVEN,
+        stream: Literal[False] | NotGiven = NOT_GIVEN,
+        temperature: float | NotGiven = NOT_GIVEN,
+        top_k: int | NotGiven = NOT_GIVEN,
+        top_p: float | 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,
+    ) -> 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.
+
+          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.
+
+          stream: Whether to incrementally stream the response using server-sent events.
+
+              See [streaming](https://docs.anthropic.com/en/api/streaming) for details.
+
+          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`.
+
+          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
+        """
+        ...
+
+    @overload
+    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,
+        # 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`.
+
+          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
+        """
+        ...
+
+    @overload
+    def create(
+        self,
+        *,
+        max_tokens_to_sample: int,
+        model: ModelParam,
+        prompt: str,
+        stream: bool,
+        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,
+        # 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 | 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`.
+
+          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
+        """
+        ...
+
+    @required_args(["max_tokens_to_sample", "model", "prompt"], ["max_tokens_to_sample", "model", "prompt", "stream"])
+    def create(
+        self,
+        *,
+        max_tokens_to_sample: int,
+        model: ModelParam,
+        prompt: str,
+        metadata: MetadataParam | NotGiven = NOT_GIVEN,
+        stop_sequences: List[str] | NotGiven = NOT_GIVEN,
+        stream: Literal[False] | Literal[True] | NotGiven = NOT_GIVEN,
+        temperature: float | NotGiven = NOT_GIVEN,
+        top_k: int | NotGiven = NOT_GIVEN,
+        top_p: float | 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,
+    ) -> Completion | Stream[Completion]:
+        if not is_given(timeout) and self._client.timeout == DEFAULT_TIMEOUT:
+            timeout = 600
+        return self._post(
+            "/v1/complete",
+            body=maybe_transform(
+                {
+                    "max_tokens_to_sample": max_tokens_to_sample,
+                    "model": model,
+                    "prompt": prompt,
+                    "metadata": metadata,
+                    "stop_sequences": stop_sequences,
+                    "stream": stream,
+                    "temperature": temperature,
+                    "top_k": top_k,
+                    "top_p": top_p,
+                },
+                completion_create_params.CompletionCreateParams,
+            ),
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=Completion,
+            stream=stream or False,
+            stream_cls=Stream[Completion],
+        )
+
+
+class AsyncCompletions(AsyncAPIResource):
+    @cached_property
+    def with_raw_response(self) -> AsyncCompletionsWithRawResponse:
+        """
+        This property can be used as a prefix for any HTTP method call to return
+        the raw response object instead of the parsed content.
+
+        For more information, see https://www.github.com/anthropics/anthropic-sdk-python#accessing-raw-response-data-eg-headers
+        """
+        return AsyncCompletionsWithRawResponse(self)
+
+    @cached_property
+    def with_streaming_response(self) -> AsyncCompletionsWithStreamingResponse:
+        """
+        An alternative to `.with_raw_response` that doesn't eagerly read the response body.
+
+        For more information, see https://www.github.com/anthropics/anthropic-sdk-python#with_streaming_response
+        """
+        return AsyncCompletionsWithStreamingResponse(self)
+
+    @overload
+    async def create(
+        self,
+        *,
+        max_tokens_to_sample: int,
+        model: ModelParam,
+        prompt: str,
+        metadata: MetadataParam | NotGiven = NOT_GIVEN,
+        stop_sequences: List[str] | NotGiven = NOT_GIVEN,
+        stream: Literal[False] | NotGiven = NOT_GIVEN,
+        temperature: float | NotGiven = NOT_GIVEN,
+        top_k: int | NotGiven = NOT_GIVEN,
+        top_p: float | 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,
+    ) -> 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.
+
+          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.
+
+          stream: Whether to incrementally stream the response using server-sent events.
+
+              See [streaming](https://docs.anthropic.com/en/api/streaming) for details.
+
+          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`.
+
+          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
+        """
+        ...
+
+    @overload
+    async 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,
+        # 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,
+    ) -> AsyncStream[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`.
+
+          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
+        """
+        ...
+
+    @overload
+    async def create(
+        self,
+        *,
+        max_tokens_to_sample: int,
+        model: ModelParam,
+        prompt: str,
+        stream: bool,
+        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,
+        # 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 | AsyncStream[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`.
+
+          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
+        """
+        ...
+
+    @required_args(["max_tokens_to_sample", "model", "prompt"], ["max_tokens_to_sample", "model", "prompt", "stream"])
+    async def create(
+        self,
+        *,
+        max_tokens_to_sample: int,
+        model: ModelParam,
+        prompt: str,
+        metadata: MetadataParam | NotGiven = NOT_GIVEN,
+        stop_sequences: List[str] | NotGiven = NOT_GIVEN,
+        stream: Literal[False] | Literal[True] | NotGiven = NOT_GIVEN,
+        temperature: float | NotGiven = NOT_GIVEN,
+        top_k: int | NotGiven = NOT_GIVEN,
+        top_p: float | 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,
+    ) -> Completion | AsyncStream[Completion]:
+        if not is_given(timeout) and self._client.timeout == DEFAULT_TIMEOUT:
+            timeout = 600
+        return await self._post(
+            "/v1/complete",
+            body=await async_maybe_transform(
+                {
+                    "max_tokens_to_sample": max_tokens_to_sample,
+                    "model": model,
+                    "prompt": prompt,
+                    "metadata": metadata,
+                    "stop_sequences": stop_sequences,
+                    "stream": stream,
+                    "temperature": temperature,
+                    "top_k": top_k,
+                    "top_p": top_p,
+                },
+                completion_create_params.CompletionCreateParams,
+            ),
+            options=make_request_options(
+                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
+            ),
+            cast_to=Completion,
+            stream=stream or False,
+            stream_cls=AsyncStream[Completion],
+        )
+
+
+class CompletionsWithRawResponse:
+    def __init__(self, completions: Completions) -> None:
+        self._completions = completions
+
+        self.create = _legacy_response.to_raw_response_wrapper(
+            completions.create,
+        )
+
+
+class AsyncCompletionsWithRawResponse:
+    def __init__(self, completions: AsyncCompletions) -> None:
+        self._completions = completions
+
+        self.create = _legacy_response.async_to_raw_response_wrapper(
+            completions.create,
+        )
+
+
+class CompletionsWithStreamingResponse:
+    def __init__(self, completions: Completions) -> None:
+        self._completions = completions
+
+        self.create = to_streamed_response_wrapper(
+            completions.create,
+        )
+
+
+class AsyncCompletionsWithStreamingResponse:
+    def __init__(self, completions: AsyncCompletions) -> None:
+        self._completions = completions
+
+        self.create = async_to_streamed_response_wrapper(
+            completions.create,
+        )