o {$f>O@s4ddlmZddlmZmZmZmZmZddlm Z ddl m Z ddl Z ddl mZmZmZmZmZddlmZmZdd lmZdd lmZdd lmZmZmZm Z!dd l"m#Z#dd l$m%Z%m&Z&ddl'm(Z(ddl)m*Z*ddl+m,Z,ddl-m.Z.ddl/m0Z0ddl1m2Z2ddgZ3GdddeZ4GdddeZ5dS)) annotations)DictListUnionIterableOptional)partial)LiteralN) NOT_GIVENBodyQueryHeadersNotGiven)SyncAPIResourceAsyncAPIResource)Stream)completion_create_params)ResponseFormatTvalidate_input_toolsparse_chat_completiontype_to_response_format_param) ChatModel)ChatCompletionStreamManager AsyncChatCompletionStreamManager)ChatCompletionChunk)ParsedChatCompletion)ChatCompletionToolParam)ChatCompletionMessageParam) ChatCompletionStreamOptionsParam)#ChatCompletionToolChoiceOptionParam CompletionsAsyncCompletionsc@eZdZeeeeeeeeeeeeeeeeeeeedddedd9d3d4Zeeeeeeeeeeeeeeeeeeeedddedd:d7d8ZdS);r!Nresponse_formatfrequency_penalty function_call functions logit_biaslogprobs max_tokensnparallel_tool_callspresence_penaltyseed service_tierstopstream_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] | NotGivenr)#Optional[Dict[str, int]] | NotGivenr*Optional[bool] | NotGivenr+Optional[int] | NotGivenr,r-bool | NotGivenr.r/r0/Optional[Literal['auto', 'default']] | NotGivenr1*Union[Optional[str], List[str]] | NotGivenr25Optional[ChatCompletionStreamOptionsParam] | NotGivenr3r4.ChatCompletionToolChoiceOptionParam | NotGivenr5,Iterable[ChatCompletionToolParam] | NotGivenr6r7r8str | NotGivenr9Headers | Noner: Query | Noner; Body | Noner<'float | httpx.Timeout | None | NotGivenreturn%ParsedChatCompletion[ResponseFormatT]cCst|ddi|p i}|jjjjdid|d|dt|d|d|d|d |d |d | d | d | d| d| d|d|d|d|d|d|d|d|d|d|d|d|d|}t|||dS) 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.parser=r?r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<r%chat_completion input_toolsN_validate_input_tools_clientchat completionscreate_type_to_response_format_parse_chat_completionselfr=r?r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<raw_completionrZrZ\/var/www/html/dev/env/lib/python3.10/site-packages/openai/resources/beta/chat/completions.pyparse"s~J     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|}t|||dS) 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.content, 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. rUbeta.chat.completions.streamr=r?streamTr%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<r%rY)rr]r^r_r`rarrdr=r?r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r< api_requestrZrZrfrks7      zCompletions.stream6r=r>r?r@r%rAr&rBr'rCr(rDr)rEr*rFr+rGr,rGr-rHr.rBr/rGr0rIr1rJr2rKr3rBr4rLr5rMr6rGr7rBr8rNr9rOr:rPr;rQr<rRrSrT)6r=r>r?r@r%rhr&rBr'rCr(rDr)rEr*rFr+rGr,rGr-rHr.rBr/rGr0rIr1rJr2rKr3rBr4rLr5rMr6rGr7rBr8rNr9rOr:rPr;rQr<rRrSri__name__ __module__ __qualname__r rgrkrZrZrZrfr!!fxc@r#);r"Nr$r=r>r?r@r%rAr&rBr'rCr(rDr)rEr*rFr+rGr,r-rHr.r/r0rIr1rJr2rKr3r4rLr5rMr6r7r8rNr9rOr:rPr;rQr<rRrSrTcst|ddi|p i}|jjjjdid|d|dt|d|d|d|d |d |d | d | d | d| d| d|d|d|d|d|d|d|d|d|d|d|d|d|IdH}t|||dS) 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) ``` rUrVr=r?r%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<NrWrZr[rcrZrZrfrgsJ      zAsyncCompletions.parserh1AsyncChatCompletionStreamManager[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|}t|||dS)"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.content, 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. rUrjr=r?rkTr%r&r'r(r)r*r+r,r-r.r/r0r1r2r3r4r5r6r7r8r9r:r;r<rlNrZ)r\r]r^r_r`rarrmrZrZrfrkis6     zAsyncCompletions.streamro)6r=r>r?r@r%rhr&rBr'rCr(rDr)rEr*rFr+rGr,rGr-rHr.rBr/rGr0rIr1rJr2rKr3rBr4rLr5rMr6rGr7rBr8rNr9rOr:rPr;rQr<rRrSrurprZrZrZrfr"rt)6 __future__rtypingrrrrr functoolsrtyping_extensionsr httpx_typesr r r rr _resourcerr _streamingr types.chatr lib._parsingrrr\rrbrratypes.chat_modelrlib.streaming.chatrr 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_paramr3types.chat.chat_completion_tool_choice_option_paramr __all__r!r"rZrZrZrfs,            U