UthddlmZddlmZmZmZmZmZddlm Z m Z ddl Z ddl m Z ddlmZddlmZmZmZmZmZdd lmZmZmZdd lmZdd lmZmZdd lm Z m!Z!dd l"m#Z#m$Z$ddl%m&Z&ddl'm(Z(ddl)m*Z*ddgZ+GddeZ,GddeZ-GddZ.GddZ/GddZ0GddZ1dS)) annotations)DictListUnionIterableOptional)LiteraloverloadN)_legacy_response)completion_create_params) NOT_GIVENBodyQueryHeadersNotGiven) 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.Zeeeeeeeeeeeeeeeeddded/dd8ZdS)?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$selfs p/var/www/html/mycamper/aliexpress-site/backend/venv/lib/python3.11/site-packages/openai/resources/completions.pywith_raw_responsezCompletions.with_raw_responses*$/// 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']]promptCUnion[str, List[str], Iterable[int], Iterable[Iterable[int]], None]r1Optional[int] | NotGivenr2Optional[bool] | NotGivenr3Optional[float] | NotGivenr4#Optional[Dict[str, int]] | NotGivenr5r6r7r8r9r:0Union[Optional[str], List[str], None] | NotGivenr;#Optional[Literal[False]] | NotGivenr<5Optional[ChatCompletionStreamOptionsParam] | NotGivenr=Optional[str] | NotGivenr>r?r@str | NotGivenrAHeaders | NonerB Query | NonerC Body | NonerD'float | httpx.Timeout | None | NotGivenrcdSu3 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(rErGr1r2r3r4r5r6r7r8r9r:r;r<r=r>r?r@rArBrCrDs r)createzCompletions.create/ r r+r1r2r3r4r5r6r7r8r9r:r<r=r>r?r@rArBrCrD 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 NrXr(rErGr;r1r2r3r4r5r6r7r8r9r:r<r=r>r?r@rArBrCrDs r)rZzCompletions.creater[r+boolCompletion | Stream[Completion]cdSr`rXras r)rZzCompletions.createer[r+rErGr;3Optional[Literal[False]] | Literal[True] | NotGivenc 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 /completionsrErGr1r2r3r4r5r6r7r8r9r:r;r<r=r>r?r@)rArBrCrDF)bodyoptionscast_tor; stream_cls)_postrr CompletionCreateParamsStreaming"CompletionCreateParamsNonStreamingrrrrYs r)rZzCompletions.creates]:zz  UfwD  ():  !* !*'(8DDf%nf ";!"U#$D%*Q(HH-P/2)+Q[el?Uj)A! ! ! r+)r#r$)r#r,.rErFrGrHr1rIr2rJr3rKr4rLr5rIr6rIr7rIr8rKr9rIr:rMr;rNr<rOr=rPr>rKr?rKr@rQrArRrBrSrCrTrDrUr#r).rErFrGrHr;r]r1rIr2rJr3rKr4rLr5rIr6rIr7rIr8rKr9rIr:rMr<rOr=rPr>rKr?rKr@rQrArRrBrSrCrTrDrUr#r^).rErFrGrHr;rbr1rIr2rJr3rKr4rLr5rIr6rIr7rIr8rKr9rIr:rMr<rOr=rPr>rKr?rKr@rQrArRrBrSrCrTrDrUr#rc).rErFrGrHr1rIr2rJr3rKr4rLr5rIr6rIr7rIr8rKr9rIr:rMr;rfr<rOr=rPr>rKr?rKr@rQrArRrBrSrCrTrDrUr#rc __name__ __module__ __qualname__rr*r/r rrZrrXr+r)r r s#000_0666_6 -6*38A:C-6/8&/7@)2AJ6?PY+42;,5()-$("&;D5X X X X X XX t-6*38A:C-6/8&/7@)2AJPY+42;,5()-$("&;D5X X X X X XX t-6*38A:C-6/8&/7@)2AJPY+42;,5()-$("&;D5X X X X X XX t]GX&(E(E(EFF -6*38A:C-6/8&/7@)2AJFOPY+42;,5()-$("&;D5= = = = = GF= = = r+cfeZdZed9dZed:dZeeeeeeeeeeeeeeeeedddedd;d.Zeeeeeeeeeeeeeeeeddded/dd8ZdS)?r!r#AsyncCompletionsWithRawResponsec t|Sr&)rvr's r)r*z"AsyncCompletions.with_raw_responseBs/t444r+%AsyncCompletionsWithStreamingResponsec t|Sr.)rxr's r)r/z(AsyncCompletions.with_streaming_responseLs5T:::r+Nr0rErFrGrHr1rIr2rJr3rKr4rLr5r6r7r8r9r:rMr;rNr<rOr=rPr>r?r@rQrArRrBrSrCrTrDrUrc KdSrWrXrYs r)rZzAsyncCompletions.createUr r+r\r]AsyncStream[Completion]c KdSr`rXras r)rZzAsyncCompletions.creater{r+rb$Completion | AsyncStream[Completion]c KdSr`rXras r)rZzAsyncCompletions.creater{r+rerfc ^K|dtid|d|d|d|d|d|d|d |d | d | d | d | d| d|d|d|d|d|i| r tjn tjd{Vt ||||t | pdtt d{VSrh)rmrr rnrorrrrYs r)rZzAsyncCompletions.create&s:ZZ ,UfwD  ():  !* !*'(8DDf%nf ";!"U#$D%*Q(HH-P/2)+Q[el?U":.A ! ! ! ! ! ! ! ! ! r+)r#rv)r#rxrp).rErFrGrHr;r]r1rIr2rJr3rKr4rLr5rIr6rIr7rIr8rKr9rIr:rMr<rOr=rPr>rKr?rKr@rQrArRrBrSrCrTrDrUr#r|).rErFrGrHr;rbr1rIr2rJr3rKr4rLr5rIr6rIr7rIr8rKr9rIr:rMr<rOr=rPr>rKr?rKr@rQrArRrBrSrCrTrDrUr#r~).rErFrGrHr1rIr2rJr3rKr4rLr5rIr6rIr7rIr8rKr9rIr:rMr;rfr<rOr=rPr>rKr?rKr@rQrArRrBrSrCrTrDrUr#r~rqrXr+r)r!r!As#555_5;;;_; -6*38A:C-6/8&/7@)2AJ6?PY+42;,5()-$("&;D5X X X X X XX t-6*38A:C-6/8&/7@)2AJPY+42;,5()-$("&;D5X X X X X XX t-6*38A:C-6/8&/7@)2AJPY+42;,5()-$("&;D5X X X X X XX t]GX&(E(E(EFF -6*38A:C-6/8&/7@)2AJFOPY+42;,5()-$("&;D5= = = = = GF= = = r+ceZdZddZdS)r$ completionsr r#NonecP||_tj|j|_dSN) _completionsr to_raw_response_wrapperrZr(rs r)__init__z#CompletionsWithRawResponse.__init__hs('&>     r+Nrr r#rrrrsrtrrXr+r)r$r$g(      r+r$ceZdZddZdS)rvrr!r#rcP||_tj|j|_dSr)rr async_to_raw_response_wrapperrZrs r)rz(AsyncCompletionsWithRawResponse.__init__qs('&D     r+Nrr!r#rrrXr+r)rvrvprr+rvceZdZddZdS)r,rr r#rcF||_t|j|_dSr)rrrZrs r)rz)CompletionsWithStreamingResponse.__init__zs%'2     r+NrrrXr+r)r,r,yrr+r,ceZdZddZdS)rxrr!r#rcF||_t|j|_dSr)rrrZrs r)rz.AsyncCompletionsWithStreamingResponse.__init__s%'8     r+NrrrXr+r)rxrxrr+rx)2 __future__rtypingrrrrrtyping_extensionsr r httpxr typesr _typesrrrrr_utilsrrr_compatr _resourcerr _responserr _streamingrr _base_clientrtypes.completionr/types.chat.chat_completion_stream_options_paramr__all__r r!r$rvr,rxrXr+r)rs#"""""88888888888888//////// ,,,,,,>>>>>>>>>>>>>>JJJJJJJJJJ%%%%%%99999999XXXXXXXX,,,,,,,,*)))))^^^^^^ , -c c c c c /c c c Lc c c c c 'c c c L                                  r+