-2iAddlmZddlmZmZmZmZddlmZm Z ddl Z ddl m Z ddl mZddlmZmZmZmZmZmZmZmZdd lmZmZmZdd lmZdd lmZm Z dd l!m"Z"m#Z#dd l$m%Z%m&Z&ddl'm(Z(ddl)m*Z*ddl+m,Z,ddgZ-GddeZ.Gdde Z/GddZ0GddZ1GddZ2GddZ3dS)) annotations)DictUnionIterableOptional)LiteraloverloadN)_legacy_response)completion_create_params)BodyOmitQueryHeadersNotGivenSequenceNotStromit not_given) required_argsmaybe_transformasync_maybe_transform)cached_property)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper)Stream AsyncStream)make_request_options) Completion) ChatCompletionStreamOptionsParam CompletionsAsyncCompletionscfeZdZed9dZed:dZeeeeeeeeeeeeeeeeedddedd;d.Z eeeeeeeeeeeeeeeeddded/dd8Z dS)?r"returnCompletionsWithRawResponsec t|Sa This property can be used as a prefix for any HTTP method call to return the raw response object instead of the parsed content. For more information, see https://www.github.com/openai/openai-python#accessing-raw-response-data-eg-headers )r&selfs [/var/www/html/pixcura-vrs/venv/lib/python3.11/site-packages/openai/resources/completions.pywith_raw_responsezCompletions.with_raw_responses*$/// CompletionsWithStreamingResponsec t|Sz An alternative to `.with_raw_response` that doesn't eagerly read the response body. For more information, see https://www.github.com/openai/openai-python#with_streaming_response )r.r)s r+with_streaming_responsez#Completions.with_streaming_response&s0555r-Nbest_ofechofrequency_penalty logit_biaslogprobs max_tokensnpresence_penaltyseedstopstreamstream_optionssuffix temperaturetop_puser extra_headers extra_query extra_bodytimeoutmodelKUnion[str, Literal['gpt-3.5-turbo-instruct', 'davinci-002', 'babbage-002']]promptMUnion[str, SequenceNotStr[str], Iterable[int], Iterable[Iterable[int]], None]r3Optional[int] | Omitr4Optional[bool] | Omitr5Optional[float] | Omitr6Optional[Dict[str, int]] | Omitr7r8r9r:r;r<6Union[Optional[str], SequenceNotStr[str], None] | Omitr=Optional[Literal[False]] | Omitr>1Optional[ChatCompletionStreamOptionsParam] | Omitr?Optional[str] | Omitr@rArB str | OmitrCHeaders | NonerD Query | NonerE Body | NonerF'float | httpx.Timeout | None | NotGivenr cdSu3 Creates a completion for the provided prompt and parameters. Args: model: ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them. prompt: The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays. Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document. best_of: Generates `best_of` completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed. When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how many to return – `best_of` must be greater than `n`. **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`. echo: Echo back the prompt in addition to the completion frequency_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation) logit_bias: Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being generated. logprobs: Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response. The maximum value for `logprobs` is 5. max_tokens: The maximum number of [tokens](/tokenizer) that can be generated in the completion. The token count of your prompt plus `max_tokens` cannot exceed the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens. n: How many completions to generate for each prompt. **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`. presence_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation) seed: If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result. Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend. stop: Not supported with latest reasoning models `o3` and `o4-mini`. Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. stream: Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions). stream_options: Options for streaming response. Only set this when you set `stream: true`. suffix: The suffix that comes after a completion of inserted text. This parameter is only supported for `gpt-3.5-turbo-instruct`. temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or `top_p` but not both. top_p: An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both. user: A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids). 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*rGrIr3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDrErFs r+createzCompletions.create/ r r-r3r4r5r6r7r8r9r:r;r<r>r?r@rArBrCrDrErF Literal[True]Stream[Completion]cdSu3 Creates a completion for the provided prompt and parameters. Args: model: ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models) for descriptions of them. prompt: The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays. Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document. stream: Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions). best_of: Generates `best_of` completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed. When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how many to return – `best_of` must be greater than `n`. **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`. echo: Echo back the prompt in addition to the completion frequency_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation) logit_bias: Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token. As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being generated. logprobs: Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response. The maximum value for `logprobs` is 5. max_tokens: The maximum number of [tokens](/tokenizer) that can be generated in the completion. The token count of your prompt plus `max_tokens` cannot exceed the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens. n: How many completions to generate for each prompt. **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`. presence_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation) seed: If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result. Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend. stop: Not supported with latest reasoning models `o3` and `o4-mini`. Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence. stream_options: Options for streaming response. Only set this when you set `stream: true`. suffix: The suffix that comes after a completion of inserted text. This parameter is only supported for `gpt-3.5-turbo-instruct`. temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or `top_p` but not both. top_p: An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or `temperature` but not both. user: A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids). 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 NrZr*rGrIr=r3r4r5r6r7r8r9r:r;r<r>r?r@rArBrCrDrErFs r+r\zCompletions.creater]r-boolCompletion | Stream[Completion]cdSrbrZrcs r+r\zCompletions.createer]r-rGrIr=/Optional[Literal[False]] | Literal[True] | Omitc B|dtid|d|d|d|d|d|d|d |d | d | d | d | d| d|d|d|d|d|i| r tjn tjt ||||t | pdtt SNz /completionsrGrIr3r4r5r6r7r8r9r:r;r<r=r>r?r@rArB)rCrDrErFF)bodyoptionscast_tor= stream_cls)_postrr CompletionCreateParamsStreaming"CompletionCreateParamsNonStreamingrr rr[s r+r\zCompletions.creates]:zz  UfwD  ():  !* !*'(8DDf%nf ";!"U#$D%*Q(HH-P/2)+Q[el?Uj)A! ! ! r-)r%r&)r%r..rGrHrIrJr3rKr4rLr5rMr6rNr7rKr8rKr9rKr:rMr;rKr<rOr=rPr>rQr?rRr@rMrArMrBrSrCrTrDrUrErVrFrWr%r ).rGrHrIrJr=r_r3rKr4rLr5rMr6rNr7rKr8rKr9rKr:rMr;rKr<rOr>rQr?rRr@rMrArMrBrSrCrTrDrUrErVrFrWr%r`).rGrHrIrJr=rdr3rKr4rLr5rMr6rNr7rKr8rKr9rKr:rMr;rKr<rOr>rQr?rRr@rMrArMrBrSrCrTrDrUrErVrFrWr%re).rGrHrIrJr3rKr4rLr5rMr6rNr7rKr8rKr9rKr:rMr;rKr<rOr=rhr>rQr?rRr@rMrArMrBrSrCrTrDrUrErVrFrWr%re __name__ __module__ __qualname__rr,r1r rrr\rrZr-r+r"r"s#000_0666_6 )-&*486:)-+/"&37%)GK26LP'+.2(,)-$("&;D5X X X X X XX t)-&*486:)-+/"&37%)GKLP'+.2(,)-$("&;D5X X X X X XX t)-&*486:)-+/"&37%)GKLP'+.2(,)-$("&;D5X X X X X XX t]GX&(E(E(EFF )-&*486:)-+/"&37%)GKBFLP'+.2(,)-$("&;D5= = = = = GF= = = r-cfeZdZed9dZed:dZeeeeeeeeeeeeeeeeedddedd;d.Z eeeeeeeeeeeeeeeeddded/dd8Z dS)?r#r%AsyncCompletionsWithRawResponsec t|Sr()rxr)s r+r,z"AsyncCompletions.with_raw_responseBs/t444r-%AsyncCompletionsWithStreamingResponsec t|Sr0)rzr)s r+r1z(AsyncCompletions.with_streaming_responseLs5T:::r-Nr2rGrHrIrJr3rKr4rLr5rMr6rNr7r8r9r:r;r<rOr=rPr>rQr?rRr@rArBrSrCrTrDrUrErVrFrWr c KdSrYrZr[s r+r\zAsyncCompletions.createUr r-r^r_AsyncStream[Completion]c KdSrbrZrcs r+r\zAsyncCompletions.creater}r-rd$Completion | AsyncStream[Completion]c KdSrbrZrcs r+r\zAsyncCompletions.creater}r-rgrhc ^K|dtid|d|d|d|d|d|d|d |d | d | d | d | d| d|d|d|d|d|i| r tjn tjd{Vt ||||t | pdtt d{VSrj)rorr rprqrr rr[s r+r\zAsyncCompletions.create&s:ZZ ,UfwD  ():  !* !*'(8DDf%nf ";!"U#$D%*Q(HH-P/2)+Q[el?U":.A ! ! ! ! ! ! ! ! ! r-)r%rx)r%rzrr).rGrHrIrJr=r_r3rKr4rLr5rMr6rNr7rKr8rKr9rKr:rMr;rKr<rOr>rQr?rRr@rMrArMrBrSrCrTrDrUrErVrFrWr%r~).rGrHrIrJr=rdr3rKr4rLr5rMr6rNr7rKr8rKr9rKr:rMr;rKr<rOr>rQr?rRr@rMrArMrBrSrCrTrDrUrErVrFrWr%r).rGrHrIrJr3rKr4rLr5rMr6rNr7rKr8rKr9rKr:rMr;rKr<rOr=rhr>rQr?rRr@rMrArMrBrSrCrTrDrUrErVrFrWr%rrsrZr-r+r#r#As#555_5;;;_; )-&*486:)-+/"&37%)GK26LP'+.2(,)-$("&;D5X X X X X XX t)-&*486:)-+/"&37%)GKLP'+.2(,)-$("&;D5X X X X X XX t)-&*486:)-+/"&37%)GKLP'+.2(,)-$("&;D5X X X X X XX t]GX&(E(E(EFF )-&*486:)-+/"&37%)GKBFLP'+.2(,)-$("&;D5= = = = = GF= = = r-ceZdZddZdS)r& completionsr"r%NonecP||_tj|j|_dSN) _completionsr to_raw_response_wrapperr\r*rs r+__init__z#CompletionsWithRawResponse.__init__hs('&>     r-Nrr"r%rrtrurvrrZr-r+r&r&g(      r-r&ceZdZddZdS)rxrr#r%rcP||_tj|j|_dSr)rr async_to_raw_response_wrapperr\rs r+rz(AsyncCompletionsWithRawResponse.__init__qs('&D     r-Nrr#r%rrrZr-r+rxrxprr-rxceZdZddZdS)r.rr"r%rcF||_t|j|_dSr)rrr\rs r+rz)CompletionsWithStreamingResponse.__init__zs%'2     r-NrrrZr-r+r.r.yrr-r.ceZdZddZdS)rzrr#r%rcF||_t|j|_dSr)rrr\rs r+rz.AsyncCompletionsWithStreamingResponse.__init__s%'8     r-NrrrZr-r+rzrzrr-rz)4 __future__rtypingrrrrtyping_extensionsrr httpxr typesr _typesr rrrrrrr_utilsrrr_compatr _resourcerr _responserr _streamingrr _base_clientrtypes.completionr /types.chat.chat_completion_stream_options_paramr!__all__r"r#r&rxr.rzrZr-r+rs#"""""222222222222//////// ,,,,,,ZZZZZZZZZZZZZZZZZZZZJJJJJJJJJJ%%%%%%99999999XXXXXXXX,,,,,,,,*)))))^^^^^^ , -c c c c c /c c c Lc c c c c 'c c c L                                  r-