src/openai/resources/beta/chat/completions.py [63:156]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - self, *, messages: Iterable[ChatCompletionMessageParam], model: Union[str, ChatModel], audio: Optional[ChatCompletionAudioParam] | NotGiven = NOT_GIVEN, response_format: type[ResponseFormatT] | NotGiven = NOT_GIVEN, frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN, functions: Iterable[completion_create_params.Function] | NotGiven = NOT_GIVEN, logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, logprobs: Optional[bool] | NotGiven = NOT_GIVEN, max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN, max_tokens: Optional[int] | NotGiven = NOT_GIVEN, metadata: Optional[Metadata] | NotGiven = NOT_GIVEN, modalities: Optional[List[Literal["text", "audio"]]] | NotGiven = NOT_GIVEN, n: Optional[int] | NotGiven = NOT_GIVEN, parallel_tool_calls: bool | NotGiven = NOT_GIVEN, prediction: Optional[ChatCompletionPredictionContentParam] | NotGiven = NOT_GIVEN, presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, reasoning_effort: Optional[ReasoningEffort] | NotGiven = NOT_GIVEN, seed: Optional[int] | NotGiven = NOT_GIVEN, service_tier: Optional[Literal["auto", "default", "flex"]] | NotGiven = NOT_GIVEN, stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN, store: Optional[bool] | NotGiven = NOT_GIVEN, stream_options: Optional[ChatCompletionStreamOptionsParam] | NotGiven = NOT_GIVEN, temperature: Optional[float] | NotGiven = NOT_GIVEN, tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, top_p: Optional[float] | NotGiven = NOT_GIVEN, user: str | NotGiven = NOT_GIVEN, web_search_options: completion_create_params.WebSearchOptions | NotGiven = NOT_GIVEN, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> ParsedChatCompletion[ResponseFormatT]: """Wrapper 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) ``` """ _validate_input_tools(tools) extra_headers = { "X-Stainless-Helper-Method": "beta.chat.completions.parse", **(extra_headers or {}), } def parser(raw_completion: ChatCompletion) -> ParsedChatCompletion[ResponseFormatT]: return _parse_chat_completion( response_format=response_format, chat_completion=raw_completion, input_tools=tools, ) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - src/openai/resources/beta/chat/completions.py [342:435]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - self, *, messages: Iterable[ChatCompletionMessageParam], model: Union[str, ChatModel], audio: Optional[ChatCompletionAudioParam] | NotGiven = NOT_GIVEN, response_format: type[ResponseFormatT] | NotGiven = NOT_GIVEN, frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN, function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN, functions: Iterable[completion_create_params.Function] | NotGiven = NOT_GIVEN, logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN, logprobs: Optional[bool] | NotGiven = NOT_GIVEN, max_completion_tokens: Optional[int] | NotGiven = NOT_GIVEN, max_tokens: Optional[int] | NotGiven = NOT_GIVEN, metadata: Optional[Metadata] | NotGiven = NOT_GIVEN, modalities: Optional[List[Literal["text", "audio"]]] | NotGiven = NOT_GIVEN, n: Optional[int] | NotGiven = NOT_GIVEN, parallel_tool_calls: bool | NotGiven = NOT_GIVEN, prediction: Optional[ChatCompletionPredictionContentParam] | NotGiven = NOT_GIVEN, presence_penalty: Optional[float] | NotGiven = NOT_GIVEN, reasoning_effort: Optional[ReasoningEffort] | NotGiven = NOT_GIVEN, seed: Optional[int] | NotGiven = NOT_GIVEN, service_tier: Optional[Literal["auto", "default", "flex"]] | NotGiven = NOT_GIVEN, stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN, store: Optional[bool] | NotGiven = NOT_GIVEN, stream_options: Optional[ChatCompletionStreamOptionsParam] | NotGiven = NOT_GIVEN, temperature: Optional[float] | NotGiven = NOT_GIVEN, tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN, tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN, top_logprobs: Optional[int] | NotGiven = NOT_GIVEN, top_p: Optional[float] | NotGiven = NOT_GIVEN, user: str | NotGiven = NOT_GIVEN, web_search_options: completion_create_params.WebSearchOptions | NotGiven = NOT_GIVEN, # Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs. # The extra values given here take precedence over values defined on the client or passed to this method. extra_headers: Headers | None = None, extra_query: Query | None = None, extra_body: Body | None = None, timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN, ) -> ParsedChatCompletion[ResponseFormatT]: """Wrapper 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) ``` """ _validate_input_tools(tools) extra_headers = { "X-Stainless-Helper-Method": "beta.chat.completions.parse", **(extra_headers or {}), } def parser(raw_completion: ChatCompletion) -> ParsedChatCompletion[ResponseFormatT]: return _parse_chat_completion( response_format=response_format, chat_completion=raw_completion, input_tools=tools, ) - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -