o #`^hf@sddlmZddlmZmZmZmZmZmZm Z ddl m Z ddl m Z ddlZddlmZddlmZmZmZmZmZdd lmZmZdd lmZdd lmZmZdd lm Z m!Z!dd l"m#Z#ddl$m%Z%ddl&m'Z'ddl(m)Z)m*Z+m,Z-m.Z/ddl0m1Z1ddl2m3Z3m4Z4ddl5m6Z6ddl7m8Z8ddl9m:Z:ddl;mZ>ddl?m@Z@ddlAmBZBddgZCGdddeZDGdddeZEGdddZFGd d!d!ZGGd"d#d#ZHGd$d%d%ZIdS)&) annotations)DictListTypeUnionIterableOptionalcast)partial)LiteralN)_legacy_response) NOT_GIVENBodyQueryHeadersNotGiven)maybe_transformasync_maybe_transform)cached_property)SyncAPIResourceAsyncAPIResource)to_streamed_response_wrapper"async_to_streamed_response_wrapper)Stream)completion_create_params)make_request_options)ResponseFormatTvalidate_input_toolsparse_chat_completiontype_to_response_format_param) ChatModel)ChatCompletionStreamManager AsyncChatCompletionStreamManager)ChatCompletion)ChatCompletionChunk)ParsedChatCompletion)ChatCompletionToolParam)ChatCompletionMessageParam) ChatCompletionStreamOptionsParam)#ChatCompletionToolChoiceOptionParam CompletionsAsyncCompletionsc@eZdZedCddZedDddZeeeeeeeeeeeeeeeeeeeeeeeddded dEd=d>Zeeeeeeeeeeeeeeeeeeeeeeeddded dFdAdBZdS)Gr+returnCompletionsWithRawResponsecCt|Sa This property can be used as a prefix for any HTTP method call to return the 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/selfr4d/home/air/shanriGPT/back/venv/lib/python3.10/site-packages/openai/resources/beta/chat/completions.pywith_raw_response(zCompletions.with_raw_response CompletionsWithStreamingResponsecCr0z 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 )r8r2r4r4r5with_streaming_response2z#Completions.with_streaming_responseNresponse_formatfrequency_penalty function_call functions logit_biaslogprobsmax_completion_tokens max_tokensmetadatanparallel_tool_callspresence_penaltyseed service_tierstopstorestream_options temperature tool_choicetools top_logprobstop_puser extra_headers extra_query extra_bodytimeoutmessages$Iterable[ChatCompletionMessageParam]modelUnion[str, ChatModel]r= type[ResponseFormatT] | NotGivenr>Optional[float] | NotGivenr?0completion_create_params.FunctionCall | NotGivenr@6Iterable[completion_create_params.Function] | NotGivenrA#Optional[Dict[str, int]] | NotGivenrBOptional[bool] | NotGivenrCOptional[int] | NotGivenrDrE#Optional[Dict[str, str]] | NotGivenrFrGbool | NotGivenrHrIrJ/Optional[Literal['auto', 'default']] | NotGivenrK*Union[Optional[str], List[str]] | NotGivenrLrM5Optional[ChatCompletionStreamOptionsParam] | NotGivenrNrO.ChatCompletionToolChoiceOptionParam | NotGivenrP,Iterable[ChatCompletionToolParam] | NotGivenrQrRrSstr | NotGivenrTHeaders | NonerU Query | NonerV Body | NonerW'float | httpx.Timeout | None | NotGiven%ParsedChatCompletion[ResponseFormatT]cstddi|p i}d fdd }|jd tid |d |d |d |d|d|d|d| d| d| d| d| d|dtd|d|d||d||||||d tjt|||||dttt t t ddS)!aWrapper over the `client.chat.completions.create()` method that provides richer integrations with Python specific types & returns a `ParsedChatCompletion` object, which is a subclass of the standard `ChatCompletion` class. You can pass a pydantic model to this method and it will automatically convert the model into a JSON schema, send it to the API and parse the response content back into the given model. This method will also automatically parse `function` tool calls if: - You use the `openai.pydantic_function_tool()` helper method - You mark your tool schema with `"strict": True` Example usage: ```py from pydantic import BaseModel from openai import OpenAI class Step(BaseModel): explanation: str output: str class MathResponse(BaseModel): steps: List[Step] final_answer: str client = OpenAI() completion = client.beta.chat.completions.parse( model="gpt-4o-2024-08-06", messages=[ {"role": "system", "content": "You are a helpful math tutor."}, {"role": "user", "content": "solve 8x + 31 = 2"}, ], response_format=MathResponse, ) message = completion.choices[0].message if message.parsed: print(message.parsed.steps) print("answer: ", message.parsed.final_answer) ``` X-Stainless-Helper-Methodbeta.chat.completions.parseraw_completionr$r.roct|dSN)r=chat_completion input_tools_parse_chat_completionrrr=rPr4r5parser z!Completions.parse..parser/chat/completionsrXrZr>r?r@rArBrCrDrErFrGrHr=rIrJrKF) rLstreamrMrNrOrPrQrRrSrTrUrVrW post_parserbodyoptionscast_tor~Nrrr$r.ro) _validate_input_tools_postr_type_to_response_formatrCompletionCreateParamsrr rr&rr$r3rXrZr=r>r?r@rArBrCrDrErFrGrHrIrJrKrLrMrNrOrPrQrRrSrTrUrVrWr{r4rzr5parse;sM      zCompletions.parseJcompletion_create_params.ResponseFormat | type[ResponseFormatT] | NotGiven,ChatCompletionStreamManager[ResponseFormatT]cCsddi|pi}t|jjjjfid|d|dddt|d|d |d |d |d |d | d| d| d| d| d|d|d|d|d|d|d|d|d|d|d|d|d|d|d |d!|}t|||d"S)#aWrapper over the `client.chat.completions.create(stream=True)` method that provides a more granular event API and automatic accumulation of each delta. This also supports all of the parsing utilities that `.parse()` does. Unlike `.create(stream=True)`, the `.stream()` method requires usage within a context manager to prevent accidental leakage of the response: ```py with client.beta.chat.completions.stream( model="gpt-4o-2024-08-06", messages=[...], ) as stream: for event in stream: if event.type == "content.delta": print(event.delta, flush=True, end="") ``` When the context manager is entered, a `ChatCompletionStream` instance is returned which, like `.create(stream=True)` is an iterator. The full list of events that are yielded by the iterator are outlined in [these docs](https://github.com/openai/openai-python/blob/main/helpers.md#chat-completions-events). When the context manager exits, the response will be closed, however the `stream` instance is still available outside the context manager. rpbeta.chat.completions.streamrXrZr~Tr=r>r?r@rArBrCrDrErFrGrHrIrJrLrKrMrNrOrPrQrRrSrTrUrVrWr=rv)r _clientchat completionscreaterr"r3rXrZr=r>r?r@rArBrCrDrErFrGrHrIrJrKrLrMrNrOrPrQrRrSrTrUrVrW api_requestr4r4r5r~s:      !zCompletions.stream)r.r/)r.r8r]r?r^r@r_rAr`rBrarCrbrDrbrErcrFrbrGrdrHr]rIrbrJrerKrfrLrarMrgrNr]rOrhrPrirQrbrRr]rSrjrTrkrUrlrVrmrWrnr.ro)r]r?r^r@r_rAr`rBrarCrbrDrbrErcrFrbrGrdrHr]rIrbrJrerKrfrLrarMrgrNr]rOrhrPrirQrbrRr]rSrjrTrkrUrlrVrmrWrnr.r __name__ __module__ __qualname__rr6r:rrr~r4r4r4r5r+'|   c@r-)Gr,r.AsyncCompletionsWithRawResponsecCr0r1)rr2r4r4r5r6+r7z"AsyncCompletions.with_raw_response%AsyncCompletionsWithStreamingResponsecCr0r9)rr2r4r4r5r:5r;z(AsyncCompletions.with_streaming_responseNr<rXrYrZr[r=r\r>r]r?r^r@r_rAr`rBrarCrbrDrErcrFrGrdrHrIrJrerKrfrLrMrgrNrOrhrPrirQrRrSrjrTrkrUrlrVrmrWrnrocstddi|p i}d fdd }|jd tid |d |d |d |d|d|d|d| d| d| d| d| d|dtd|d|d||d||||||d tjIdHt|||||dttt t t ddIdHS)!aWrapper over the `client.chat.completions.create()` method that provides richer integrations with Python specific types & returns a `ParsedChatCompletion` object, which is a subclass of the standard `ChatCompletion` class. You can pass a pydantic model to this method and it will automatically convert the model into a JSON schema, send it to the API and parse the response content back into the given model. This method will also automatically parse `function` tool calls if: - You use the `openai.pydantic_function_tool()` helper method - You mark your tool schema with `"strict": True` Example usage: ```py from pydantic import BaseModel from openai import AsyncOpenAI class Step(BaseModel): explanation: str output: str class MathResponse(BaseModel): steps: List[Step] final_answer: str client = AsyncOpenAI() completion = await client.beta.chat.completions.parse( model="gpt-4o-2024-08-06", messages=[ {"role": "system", "content": "You are a helpful math tutor."}, {"role": "user", "content": "solve 8x + 31 = 2"}, ], response_format=MathResponse, ) message = completion.choices[0].message if message.parsed: print(message.parsed.steps) print("answer: ", message.parsed.final_answer) ``` rprqrrr$r.rocrsrtrwryrzr4r5r{r|z&AsyncCompletions.parse..parserr}rXrZr>r?r@rArBrCrDrErFrGrHr=rIrJrLF) rKr~rMrNrOrPrQrRrSNrrr) rrrrrrrr rr&rr$rr4rzr5r>sM       zAsyncCompletions.parser1AsyncChatCompletionStreamManager[ResponseFormatT]cCst|ddi|p i}|jjjjd$id|d|dddt|d|d |d |d |d |d | d| d| d| d| d|d|d|d|d|d|d|d|d|d|d|d|d|d|d |d!|}t|||d"S)%aWrapper over the `client.chat.completions.create(stream=True)` method that provides a more granular event API and automatic accumulation of each delta. This also supports all of the parsing utilities that `.parse()` does. Unlike `.create(stream=True)`, the `.stream()` method requires usage within a context manager to prevent accidental leakage of the response: ```py async with client.beta.chat.completions.stream( model="gpt-4o-2024-08-06", messages=[...], ) as stream: async for event in stream: if event.type == "content.delta": print(event.delta, flush=True, end="") ``` When the context manager is entered, an `AsyncChatCompletionStream` instance is returned which, like `.create(stream=True)` is an async iterator. The full list of events that are yielded by the iterator are outlined in [these docs](https://github.com/openai/openai-python/blob/main/helpers.md#chat-completions-events). When the context manager exits, the response will be closed, however the `stream` instance is still available outside the context manager. rprrXrZr~Tr=r>r?r@rArBrCrDrErFrGrHrIrJrKrLrMrNrOrPrQrRrSrTrUrVrWrNr4)rrrrrrr#rr4r4r5r~s9      zAsyncCompletions.stream)r.r)r.rr)r]r?r^r@r_rAr`rBrarCrbrDrbrErcrFrbrGrdrHr]rIrbrJrerKrfrLrarMrgrNr]rOrhrPrirQrbrRr]rSrjrTrkrUrlrVrmrWrnr.rrr4r4r4r5r,*rc@eZdZdddZdS) r/rr+r.NonecC||_t|j|_dSN) _completionsr to_raw_response_wrapperrr3rr4r4r5__init__/ z#CompletionsWithRawResponse.__init__Nrr+r.rrrrrr4r4r4r5r/.r/c@r) rrr,r.rcCrr)rr async_to_raw_response_wrapperrrr4r4r5r8rz(AsyncCompletionsWithRawResponse.__init__Nrr,r.rrr4r4r4r5r7rrc@r) r8rr+r.rcC||_t|j|_dSr)rrrrr4r4r5rA z)CompletionsWithStreamingResponse.__init__Nrrr4r4r4r5r8@rr8c@r) rrr,r.rcCrr)rrrrr4r4r5rJrz.AsyncCompletionsWithStreamingResponse.__init__Nrrr4r4r4r5rIrr)J __future__rtypingrrrrrrr functoolsr typing_extensionsr httpxr _typesrrrrr_utilsrr_compatr _resourcerr _responserr _streamingr types.chatr _base_clientr lib._parsingrrrrrxr rtypes.chat_modelr!lib.streaming.chatr"r#types.chat.chat_completionr$ types.chat.chat_completion_chunkr%!types.chat.parsed_chat_completionr&%types.chat.chat_completion_tool_paramr'(types.chat.chat_completion_message_paramr(/types.chat.chat_completion_stream_options_paramr)3types.chat.chat_completion_tool_choice_option_paramr*__all__r+r,r/rr8rr4r4r4r5sF $