+ ~jj^RIHt^RIHt^RIHtHt^RIt^RIH t ^RI H t ^RI H t HtHtHtHtHtHtHt^RIHtHtHtHtHt^R IHt^R IHtHt^R I H!t!H"t"^R I#H$t$^R I%H&t&H't'^RI(H)t)^RI*H+t+^RI,H-t-^RI.H/t/^RI0H1t1RR.t2!RR]4t3!RR]4t4!RR4t5!RR4t6!RR4t7!RR4t8R#)) annotations)List)LiteraloverloadN)_legacy_response)completion_create_params)BodyOmitQueryHeadersNotGivenSequenceNotStromit not_given)is_given required_argsmaybe_transformstrip_not_givenasync_maybe_transform)cached_property)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper)DEFAULT_TIMEOUT)Stream AsyncStream)make_request_options) Completion) ModelParam) MetadataParam)AnthropicBetaParam CompletionsAsyncCompletionsch]tRt^t]RRl4t]RRl4t]R]R]R]R]R ]R ]R ]R R RR RR R] / RRll4t ]R]R]R]R ]R ]R ]R R RR RR R] / RRll4t ]R]R]R]R ]R ]R ]R R RR RR R] / RRll4t ] !.RO.RO4R]R]R]R]R ]R ]R ]R R RR RR R] / RRll4t Rt R #)r#cV^8dQhRR/#)returnCompletionsWithRawResponse)formats"t/Users/mitch_tango/dev/rabbit-r1-livekit/agent/.venv/lib/python3.14/site-packages/anthropic/resources/completions.py __annotate__Completions.__annotate__s00#=0c \V4#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 )r)selfs&r,with_raw_responseCompletions.with_raw_responses*$//r/cV^8dQhRR/#)r'r( CompletionsWithStreamingResponser*)r+s"r,r-r.(s66)I6r/c \V4#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 )r7r2s&r,with_streaming_response#Completions.with_streaming_response's055r/metadatastop_sequencesstream temperaturetop_ktop_pbetas extra_headersN extra_query extra_bodytimeoutcTV^8dQhRRRRRRRRR R R R R RRRRRRRRRRRRRRRRR/#r'max_tokens_to_sampleintmodelr promptstrr<MetadataParam | Omitr=SequenceNotStr[str] | Omitr>zLiteral[False] | Omitr? float | Omitr@ int | OmitrArBList[AnthropicBetaParam] | OmitrCHeaders | NonerD Query | NonerE Body | NonerF'float | httpx.Timeout | None | NotGivenr(rr*)r+s"r,r-r.1d d "d  d  d ' d 3d &d "d d d /d &d "!d " #d $9%d & 'd r/c R#a [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. 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.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 `" 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.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. 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`. Recommended for advanced use cases only. 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 Nr*r3rIrKrLr<r=r>r?r@rArBrCrDrErFs&$$$$$$$$$$$$$$r,createCompletions.create0J r/cTV^8dQhRRRRRRRRR R R R R RRRRRRRRRRRRRRRRR/#)r'rIrJrKr rLrMr> Literal[True]r<rNr=rOr?rPr@rQrArBrRrCrSrDrTrErUrFrVr(zStream[Completion]r*)r+s"r,r-r.sd d "d  d  d  d 'd 3d "d d d /d &d "!d " #d $9%d & 'd r/c R#a [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. 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.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 `" 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. 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`. 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