Mi|SSKJr SSKJr SSKJrJr SSKrSSKJ r SSK J r SSK J r JrJrJrJr SS KJrJrJrJr SS KJr SS KJrJr SS KJrJr SS KJ r SSK!J"r"J#r# SSK$J%r% SSK&J'r' SSK(J)r) SSK*J+r+ SS/r,"SS\5r-"SS\5r."SS5r/"SS5r0"SS5r1"SS5r2g)) annotations)List)LiteraloverloadN)_legacy_response)completion_create_params) NOT_GIVENBodyQueryHeadersNotGiven)is_given required_argsmaybe_transformasync_maybe_transform)cached_property)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper)DEFAULT_TIMEOUT)Stream AsyncStream)make_request_options) Completion) ModelParam) MetadataParam CompletionsAsyncCompletionsc \rSrSr\SSj5r\SSj5r\\\\\\\SSS\S. SSjj5r \\\\\\SSS\S. SSjj5r \\\\\\SSS\S. SS jj5r \ "/S Q/S Q5\\\\\\SSS\S. SS jj5r S r g)r c[U5$z 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 )CompletionsWithRawResponseselfs y/var/www/eduai.edurigo.com/storigo/production/storigo_env/lib/python3.13/site-packages/anthropic/resources/completions.pywith_raw_responseCompletions.with_raw_response!s*$//c[U5$z 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 ) CompletionsWithStreamingResponser&s r(with_streaming_response#Completions.with_streaming_response+s055r+N metadatastop_sequencesstream temperaturetop_ktop_p extra_headers extra_query extra_bodytimeoutc ga[[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. 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. 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 Nr'max_tokens_to_samplemodelpromptr2r3r4r5r6r7r8r9r:r;s r(createCompletions.create4L r+ r2r3r5r6r7r8r9r:r;c ga[[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`. 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 Nr>r'r@rArBr4r2r3r5r6r7r8r9r:r;s r(rCrDrEr+c grHr>rIs r(rCrDrEr+r@rArBr@rArBr4c [U 5(d URR[:XaSn UR S[ UUUUUUUUU S. 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[ R5IShvN [XXS9[U=(d S[[S9IShvN $N2N7frN) rrSr;rrTrr rUrrrr?s r(rCrts(  T\\%9%9_%LGZZ ,,@"$ (&4$#."" )??  )+Q[?U":.+      s$A$B&B '-BBBBr>)rVrn)rVrqrW)r@rXrArrBrYr4rbr2rZr3r[r5r\r6r]r7r\r8r^r9r_r:r`r;rarVzAsyncStream[Completion])r@rXrArrBrYr4rcr2rZr3r[r5r\r6r]r7r\r8r^r9r_r:r`r;rarV$Completion | AsyncStream[Completion])r@rXrArrBrYr2rZr3r[r4rer5r\r6r]r7r\r8r^r9r_r:r`r;rarVrzrfr>r+r(r r sg55;;.7/8,5(1 )"+)-$("&;D#e "e  e  e + e -e *e &e e  e &e "e  !e "9#e $ %e e N.7/8(1 )"+)-$("&;D#e "e  e  e  e +e -e &e e  e &e "e  !e "9#e $ !%e e N.7/8(1 )"+)-$("&;D#e "e  e  e  e +e -e &e e  e &e "e  !e "9#e $ .%e e N>@uv.7/8>     r+r~rCNrrrVNonergrhrirjrrkr>r+r(r%r% r+r%c\rSrSrSSjrSrg)rnicZXl[R"UR5Ulgr})r~rasync_to_raw_response_wrapperrCrs r(r(AsyncCompletionsWithRawResponse.__init__ s#'&DD     r+rNrr rVrrr>r+r(rnrnrr+rnc\rSrSrSSjrSrg)r.i(cDXl[UR5Ulgr})r~rrCrs r(r)CompletionsWithStreamingResponse.__init__)s'2     r+rNrrr>r+r(r.r.(rr+r.c\rSrSrSSjrSrg)rqi1cDXl[UR5Ulgr})r~rrCrs r(r.AsyncCompletionsWithStreamingResponse.__init__2s'8     r+rNrrr>r+r(rqrq1rr+rq)3 __future__rtypingrtyping_extensionsrrhttpxrtypesr _typesr r r r r_utilsrrrr_compatr _resourcerr _responserr _constantsr _streamingrr _base_clientrtypes.completionrtypes.model_paramrtypes.metadata_paramr__all__rr r%rnr.rqr>r+r(rs#/ ,>> &9X(,/)*0 , -x /x v x 'x v         r+