846 lines
36 KiB
Python
846 lines
36 KiB
Python
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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from typing import List
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from typing_extensions import Literal, overload
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import httpx
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from .. import _legacy_response
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from ..types import completion_create_params
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from .._types import Body, Omit, Query, Headers, NotGiven, SequenceNotStr, omit, not_given
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from .._utils import is_given, required_args, maybe_transform, strip_not_given, async_maybe_transform
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from .._compat import cached_property
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from .._resource import SyncAPIResource, AsyncAPIResource
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from .._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
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from .._constants import DEFAULT_TIMEOUT
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from .._streaming import Stream, AsyncStream
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from .._base_client import make_request_options
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from ..types.completion import Completion
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from ..types.model_param import ModelParam
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from ..types.metadata_param import MetadataParam
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from ..types.anthropic_beta_param import AnthropicBetaParam
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__all__ = ["Completions", "AsyncCompletions"]
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class Completions(SyncAPIResource):
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@cached_property
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def with_raw_response(self) -> CompletionsWithRawResponse:
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"""
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This property can be used as a prefix for any HTTP method call to return
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the raw response object instead of the parsed content.
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For more information, see https://www.github.com/anthropics/anthropic-sdk-python#accessing-raw-response-data-eg-headers
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"""
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return CompletionsWithRawResponse(self)
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@cached_property
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def with_streaming_response(self) -> CompletionsWithStreamingResponse:
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"""
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An alternative to `.with_raw_response` that doesn't eagerly read the response body.
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For more information, see https://www.github.com/anthropics/anthropic-sdk-python#with_streaming_response
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"""
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return CompletionsWithStreamingResponse(self)
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@overload
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def create(
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self,
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*,
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max_tokens_to_sample: int,
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model: ModelParam,
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prompt: str,
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metadata: MetadataParam | Omit = omit,
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stop_sequences: SequenceNotStr[str] | Omit = omit,
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stream: Literal[False] | Omit = omit,
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temperature: float | Omit = omit,
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top_k: int | Omit = omit,
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top_p: float | Omit = omit,
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betas: List[AnthropicBetaParam] | Omit = omit,
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# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
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# The extra values given here take precedence over values defined on the client or passed to this method.
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extra_headers: Headers | None = None,
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extra_query: Query | None = None,
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extra_body: Body | None = None,
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timeout: float | httpx.Timeout | None | NotGiven = not_given,
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) -> Completion:
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"""[Legacy] Create a Text Completion.
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The Text Completions API is a legacy API.
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We recommend using the
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[Messages API](https://docs.claude.com/en/api/messages) going forward.
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Future models and features will not be compatible with Text Completions. See our
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[migration guide](https://docs.claude.com/en/api/migrating-from-text-completions-to-messages)
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for guidance in migrating from Text Completions to Messages.
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Args:
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max_tokens_to_sample: The maximum number of tokens to generate before stopping.
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Note that our models may stop _before_ reaching this maximum. This parameter
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only specifies the absolute maximum number of tokens to generate.
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model: The model that will complete your prompt.\n\nSee
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[models](https://docs.anthropic.com/en/docs/models-overview) for additional
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details and options.
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prompt: The prompt that you want Claude to complete.
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For proper response generation you will need to format your prompt using
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alternating `\n\nHuman:` and `\n\nAssistant:` conversational turns. For example:
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```
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"\n\nHuman: {userQuestion}\n\nAssistant:"
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```
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See [prompt validation](https://docs.claude.com/en/api/prompt-validation) and
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our guide to [prompt design](https://docs.claude.com/en/docs/intro-to-prompting)
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for more details.
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metadata: An object describing metadata about the request.
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stop_sequences: Sequences that will cause the model to stop generating.
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Our models stop on `"\n\nHuman:"`, and may include additional built-in stop
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sequences in the future. By providing the stop_sequences parameter, you may
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include additional strings that will cause the model to stop generating.
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stream: Whether to incrementally stream the response using server-sent events.
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See [streaming](https://docs.claude.com/en/api/streaming) for details.
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temperature: Amount of randomness injected into the response.
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Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
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for analytical / multiple choice, and closer to `1.0` for creative and
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generative tasks.
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Note that even with `temperature` of `0.0`, the results will not be fully
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deterministic.
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top_k: Only sample from the top K options for each subsequent token.
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Used to remove "long tail" low probability responses.
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[Learn more technical details here](https://towardsdatascience.com/how-to-sample-from-language-models-682bceb97277).
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Recommended for advanced use cases only. You usually only need to use
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`temperature`.
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top_p: Use nucleus sampling.
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In nucleus sampling, we compute the cumulative distribution over all the options
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for each subsequent token in decreasing probability order and cut it off once it
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reaches a particular probability specified by `top_p`. You should either alter
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`temperature` or `top_p`, but not both.
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Recommended for advanced use cases only. You usually only need to use
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`temperature`.
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betas: Optional header to specify the beta version(s) you want to use.
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extra_headers: Send extra headers
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extra_query: Add additional query parameters to the request
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extra_body: Add additional JSON properties to the request
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timeout: Override the client-level default timeout for this request, in seconds
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"""
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...
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@overload
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def create(
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self,
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*,
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max_tokens_to_sample: int,
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model: ModelParam,
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prompt: str,
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stream: Literal[True],
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metadata: MetadataParam | Omit = omit,
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stop_sequences: SequenceNotStr[str] | Omit = omit,
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temperature: float | Omit = omit,
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top_k: int | Omit = omit,
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top_p: float | Omit = omit,
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betas: List[AnthropicBetaParam] | Omit = omit,
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# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
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# The extra values given here take precedence over values defined on the client or passed to this method.
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extra_headers: Headers | None = None,
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extra_query: Query | None = None,
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extra_body: Body | None = None,
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timeout: float | httpx.Timeout | None | NotGiven = not_given,
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) -> Stream[Completion]:
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"""[Legacy] Create a Text Completion.
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The Text Completions API is a legacy API.
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|
|
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We recommend using the
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[Messages API](https://docs.claude.com/en/api/messages) going forward.
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|
|
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||
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Future models and features will not be compatible with Text Completions. See our
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[migration guide](https://docs.claude.com/en/api/migrating-from-text-completions-to-messages)
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for guidance in migrating from Text Completions to Messages.
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Args:
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max_tokens_to_sample: The maximum number of tokens to generate before stopping.
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|
|
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Note that our models may stop _before_ reaching this maximum. This parameter
|
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|
|
only specifies the absolute maximum number of tokens to generate.
|
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|
|
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||
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|
model: The model that will complete your prompt.\n\nSee
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|
[models](https://docs.anthropic.com/en/docs/models-overview) for additional
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|
|
details and options.
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|
|
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prompt: The prompt that you want Claude to complete.
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|
|
|
||
|
|
For proper response generation you will need to format your prompt using
|
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|
|
alternating `\n\nHuman:` and `\n\nAssistant:` conversational turns. For example:
|
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|
|
|
||
|
|
```
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|
"\n\nHuman: {userQuestion}\n\nAssistant:"
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```
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|
|
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||
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See [prompt validation](https://docs.claude.com/en/api/prompt-validation) and
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our guide to [prompt design](https://docs.claude.com/en/docs/intro-to-prompting)
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for more details.
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|
|
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||
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stream: Whether to incrementally stream the response using server-sent events.
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See [streaming](https://docs.claude.com/en/api/streaming) for details.
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metadata: An object describing metadata about the request.
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|
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stop_sequences: Sequences that will cause the model to stop generating.
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|
|
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||
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|
Our models stop on `"\n\nHuman:"`, and may include additional built-in stop
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||
|
|
sequences in the future. By providing the stop_sequences parameter, you may
|
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|
|
include additional strings that will cause the model to stop generating.
|
||
|
|
|
||
|
|
temperature: Amount of randomness injected into the response.
|
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|
|
|
||
|
|
Defaults to `1.0`. Ranges from `0.0` to `1.0`. Use `temperature` closer to `0.0`
|
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|
|
for analytical / multiple choice, and closer to `1.0` for creative and
|
||
|
|
generative tasks.
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|
|
|
||
|
|
Note that even with `temperature` of `0.0`, the results will not be fully
|
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|
|
deterministic.
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|
|
|
||
|
|
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
|
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|
|
`temperature`.
|
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|
|
|
||
|
|
top_p: Use nucleus sampling.
|
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|
|
|
||
|
|
In nucleus sampling, we compute the cumulative distribution over all the options
|
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|
|
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`.
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|
|
|
||
|
|
betas: Optional header to specify the beta version(s) you want to use.
|
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|
|
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extra_headers: Send extra headers
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|
|
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extra_query: Add additional query parameters to the request
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extra_body: Add additional JSON properties to the request
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timeout: Override the client-level default timeout for this request, in seconds
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"""
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...
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@overload
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def create(
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self,
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|
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*,
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|
|
max_tokens_to_sample: int,
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|
|
model: ModelParam,
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|
|
prompt: str,
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|
|
stream: bool,
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|
|
metadata: MetadataParam | Omit = omit,
|
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|
|
stop_sequences: SequenceNotStr[str] | Omit = omit,
|
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|
|
temperature: float | Omit = omit,
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|
|
top_k: int | Omit = omit,
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|
|
top_p: float | Omit = omit,
|
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|
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betas: List[AnthropicBetaParam] | Omit = omit,
|
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|
|
# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
|
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|
|
# 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.claude.com/en/api/messages) going forward.
|
||
|
|
|
||
|
|
Future models and features will not be compatible with Text Completions. See our
|
||
|
|
[migration guide](https://docs.claude.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.claude.com/en/api/prompt-validation) and
|
||
|
|
our guide to [prompt design](https://docs.claude.com/en/docs/intro-to-prompting)
|
||
|
|
for more details.
|
||
|
|
|
||
|
|
stream: Whether to incrementally stream the response using server-sent events.
|
||
|
|
|
||
|
|
See [streaming](https://docs.claude.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
|
||
|
|
"""
|
||
|
|
...
|
||
|
|
|
||
|
|
@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 | Omit = omit,
|
||
|
|
stop_sequences: SequenceNotStr[str] | Omit = omit,
|
||
|
|
stream: Literal[False] | Literal[True] | Omit = omit,
|
||
|
|
temperature: float | Omit = omit,
|
||
|
|
top_k: int | Omit = omit,
|
||
|
|
top_p: float | Omit = omit,
|
||
|
|
betas: List[AnthropicBetaParam] | 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 | Stream[Completion]:
|
||
|
|
if not is_given(timeout) and self._client.timeout == DEFAULT_TIMEOUT:
|
||
|
|
timeout = 600
|
||
|
|
extra_headers = {
|
||
|
|
**strip_not_given({"anthropic-beta": ",".join(str(e) for e in betas) if is_given(betas) else not_given}),
|
||
|
|
**(extra_headers or {}),
|
||
|
|
}
|
||
|
|
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.CompletionCreateParamsStreaming
|
||
|
|
if stream
|
||
|
|
else completion_create_params.CompletionCreateParamsNonStreaming,
|
||
|
|
),
|
||
|
|
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 | Omit = omit,
|
||
|
|
stop_sequences: SequenceNotStr[str] | Omit = omit,
|
||
|
|
stream: Literal[False] | Omit = omit,
|
||
|
|
temperature: float | Omit = omit,
|
||
|
|
top_k: int | Omit = omit,
|
||
|
|
top_p: float | Omit = omit,
|
||
|
|
betas: List[AnthropicBetaParam] | 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:
|
||
|
|
"""[Legacy] Create a Text Completion.
|
||
|
|
|
||
|
|
The Text Completions API is a legacy API.
|
||
|
|
|
||
|
|
We recommend using the
|
||
|
|
[Messages API](https://docs.claude.com/en/api/messages) going forward.
|
||
|
|
|
||
|
|
Future models and features will not be compatible with Text Completions. See our
|
||
|
|
[migration guide](https://docs.claude.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.claude.com/en/api/prompt-validation) and
|
||
|
|
our guide to [prompt design](https://docs.claude.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.claude.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`.
|
||
|
|
|
||
|
|
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
|
||
|
|
"""
|
||
|
|
...
|
||
|
|
|
||
|
|
@overload
|
||
|
|
async def create(
|
||
|
|
self,
|
||
|
|
*,
|
||
|
|
max_tokens_to_sample: int,
|
||
|
|
model: ModelParam,
|
||
|
|
prompt: str,
|
||
|
|
stream: Literal[True],
|
||
|
|
metadata: MetadataParam | Omit = omit,
|
||
|
|
stop_sequences: SequenceNotStr[str] | Omit = omit,
|
||
|
|
temperature: float | Omit = omit,
|
||
|
|
top_k: int | Omit = omit,
|
||
|
|
top_p: float | Omit = omit,
|
||
|
|
betas: List[AnthropicBetaParam] | 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,
|
||
|
|
) -> AsyncStream[Completion]:
|
||
|
|
"""[Legacy] Create a Text Completion.
|
||
|
|
|
||
|
|
The Text Completions API is a legacy API.
|
||
|
|
|
||
|
|
We recommend using the
|
||
|
|
[Messages API](https://docs.claude.com/en/api/messages) going forward.
|
||
|
|
|
||
|
|
Future models and features will not be compatible with Text Completions. See our
|
||
|
|
[migration guide](https://docs.claude.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.claude.com/en/api/prompt-validation) and
|
||
|
|
our guide to [prompt design](https://docs.claude.com/en/docs/intro-to-prompting)
|
||
|
|
for more details.
|
||
|
|
|
||
|
|
stream: Whether to incrementally stream the response using server-sent events.
|
||
|
|
|
||
|
|
See [streaming](https://docs.claude.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
|
||
|
|
"""
|
||
|
|
...
|
||
|
|
|
||
|
|
@overload
|
||
|
|
async def create(
|
||
|
|
self,
|
||
|
|
*,
|
||
|
|
max_tokens_to_sample: int,
|
||
|
|
model: ModelParam,
|
||
|
|
prompt: str,
|
||
|
|
stream: bool,
|
||
|
|
metadata: MetadataParam | Omit = omit,
|
||
|
|
stop_sequences: SequenceNotStr[str] | Omit = omit,
|
||
|
|
temperature: float | Omit = omit,
|
||
|
|
top_k: int | Omit = omit,
|
||
|
|
top_p: float | Omit = omit,
|
||
|
|
betas: List[AnthropicBetaParam] | 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 | AsyncStream[Completion]:
|
||
|
|
"""[Legacy] Create a Text Completion.
|
||
|
|
|
||
|
|
The Text Completions API is a legacy API.
|
||
|
|
|
||
|
|
We recommend using the
|
||
|
|
[Messages API](https://docs.claude.com/en/api/messages) going forward.
|
||
|
|
|
||
|
|
Future models and features will not be compatible with Text Completions. See our
|
||
|
|
[migration guide](https://docs.claude.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.claude.com/en/api/prompt-validation) and
|
||
|
|
our guide to [prompt design](https://docs.claude.com/en/docs/intro-to-prompting)
|
||
|
|
for more details.
|
||
|
|
|
||
|
|
stream: Whether to incrementally stream the response using server-sent events.
|
||
|
|
|
||
|
|
See [streaming](https://docs.claude.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
|
||
|
|
"""
|
||
|
|
...
|
||
|
|
|
||
|
|
@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 | Omit = omit,
|
||
|
|
stop_sequences: SequenceNotStr[str] | Omit = omit,
|
||
|
|
stream: Literal[False] | Literal[True] | Omit = omit,
|
||
|
|
temperature: float | Omit = omit,
|
||
|
|
top_k: int | Omit = omit,
|
||
|
|
top_p: float | Omit = omit,
|
||
|
|
betas: List[AnthropicBetaParam] | 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 | AsyncStream[Completion]:
|
||
|
|
if not is_given(timeout) and self._client.timeout == DEFAULT_TIMEOUT:
|
||
|
|
timeout = 600
|
||
|
|
extra_headers = {
|
||
|
|
**strip_not_given({"anthropic-beta": ",".join(str(e) for e in betas) if is_given(betas) else not_given}),
|
||
|
|
**(extra_headers or {}),
|
||
|
|
}
|
||
|
|
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.CompletionCreateParamsStreaming
|
||
|
|
if stream
|
||
|
|
else completion_create_params.CompletionCreateParamsNonStreaming,
|
||
|
|
),
|
||
|
|
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,
|
||
|
|
)
|