# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.

from __future__ import annotations

from typing import Dict, List, Union, Iterable, Optional, overload
from typing_extensions import Literal

import httpx

from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven
from ..._utils import (
    maybe_transform,
    async_maybe_transform,
)
from ..._compat import cached_property
from ..._resource import SyncAPIResource, AsyncAPIResource
from ..._response import (
    to_raw_response_wrapper,
    to_streamed_response_wrapper,
    async_to_raw_response_wrapper,
    async_to_streamed_response_wrapper,
)
from ..._streaming import Stream, AsyncStream
from ...types.chat import completion_create_params
from ..._base_client import (
    make_request_options,
)
from ...types.chat.chat_completion import ChatCompletion
from ...types.chat.chat_completion_chunk import ChatCompletionChunk
from ...types.chat.chat_completion_tool_param import ChatCompletionToolParam
from ...types.chat.chat_completion_message_param import ChatCompletionMessageParam
from ...types.chat.chat_completion_tool_choice_option_param import ChatCompletionToolChoiceOptionParam

__all__ = ["Completions", "AsyncCompletions"]


class Completions(SyncAPIResource):
    @cached_property
    def with_raw_response(self) -> CompletionsWithRawResponse:
        return CompletionsWithRawResponse(self)

    @cached_property
    def with_streaming_response(self) -> CompletionsWithStreamingResponse:
        return CompletionsWithStreamingResponse(self)

    @overload
    def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: str,
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> ChatCompletion:
        ...

    @overload
    def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: str,
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: Literal[True],
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> Stream[ChatCompletionChunk]:
        ...

    @overload
    def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: str,
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: bool,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> ChatCompletion | Stream[ChatCompletionChunk]:
        ...

    def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: Union[str, Literal["gemma-7b-it", "llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768"]],
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> ChatCompletion | Stream[ChatCompletionChunk]:
        """
        Creates a model response for the given chat conversation.

        Args:
          messages: A list of messages comprising the conversation so far.

          model: ID of the model to use. For details on which models are compatible with the Chat
              API, see available [models](/docs/models)

          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.

          function_call: Deprecated in favor of `tool_choice`.

              Controls which (if any) function is called by the model. `none` means the model
              will not call a function and instead generates a message. `auto` means the model
              can pick between generating a message or calling a function. Specifying a
              particular function via `{"name": "my_function"}` forces the model to call that
              function.

              `none` is the default when no functions are present. `auto` is the default if
              functions are present.

          functions: Deprecated in favor of `tools`.

              A list of functions the model may generate JSON inputs for.

          logit_bias: This is not yet supported by any of our models. Modify the likelihood of
              specified tokens appearing in the completion.

          logprobs: This is not yet supported by any of our models. Whether to return log
              probabilities of the output tokens or not. If true, returns the log
              probabilities of each output token returned in the `content` of `message`.

          max_tokens: The maximum number of tokens that can be generated in the chat completion. The
              total length of input tokens and generated tokens is limited by the model's
              context length.

          n: How many chat completion choices to generate for each input message. Note that
              the current moment, only n=1 is supported. Other values will result in a 400
              response.

          parallel_tool_calls: Whether to enable parallel function calling during tool use.

          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.

          response_format: An object specifying the format that the model must output.

              Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
              message the model generates is valid JSON.

              **Important:** when using JSON mode, you **must** also instruct the model to
              produce JSON yourself via a system or user message.

          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: Up to 4 sequences where the API will stop generating further tokens. The
              returned text will not contain the stop sequence.

          stream: If set, partial message deltas will be sent. 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 code](/docs/text-chat#streaming-a-chat-completion).

          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

          tool_choice: Controls which (if any) tool is called by the model. `none` means the model will
              not call any tool and instead generates a message. `auto` means the model can
              pick between generating a message or calling one or more tools. `required` means
              the model must call one or more tools. Specifying a particular tool via
              `{"type": "function", "function": {"name": "my_function"}}` forces the model to
              call that tool.

              `none` is the default when no tools are present. `auto` is the default if tools
              are present.

          tools: A list of tools the model may call. Currently, only functions are supported as a
              tool. Use this to provide a list of functions the model may generate JSON inputs
              for. A max of 128 functions are supported.

          top_logprobs: This is not yet supported by any of our models. An integer between 0 and 20
              specifying the number of most likely tokens to return at each token position,
              each with an associated log probability. `logprobs` must be set to `true` if
              this parameter is used.

          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 us monitor and
              detect abuse.

          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
        """
        return self._post(
            "/openai/v1/chat/completions",
            body=maybe_transform(
                {
                    "messages": messages,
                    "model": model,
                    "frequency_penalty": frequency_penalty,
                    "function_call": function_call,
                    "functions": functions,
                    "logit_bias": logit_bias,
                    "logprobs": logprobs,
                    "max_tokens": max_tokens,
                    "n": n,
                    "parallel_tool_calls": parallel_tool_calls,
                    "presence_penalty": presence_penalty,
                    "response_format": response_format,
                    "seed": seed,
                    "stop": stop,
                    "stream": stream,
                    "temperature": temperature,
                    "tool_choice": tool_choice,
                    "tools": tools,
                    "top_logprobs": top_logprobs,
                    "top_p": top_p,
                    "user": user,
                },
                completion_create_params.CompletionCreateParams,
            ),
            options=make_request_options(
                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
            ),
            cast_to=ChatCompletion,
            stream=stream or False,
            stream_cls=Stream[ChatCompletionChunk],
        )


class AsyncCompletions(AsyncAPIResource):
    @cached_property
    def with_raw_response(self) -> AsyncCompletionsWithRawResponse:
        return AsyncCompletionsWithRawResponse(self)

    @cached_property
    def with_streaming_response(self) -> AsyncCompletionsWithStreamingResponse:
        return AsyncCompletionsWithStreamingResponse(self)

    @overload
    async def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: str,
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> ChatCompletion:
        ...

    @overload
    async def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: str,
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: Literal[True],
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> AsyncStream[ChatCompletionChunk]:
        ...

    @overload
    async def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: str,
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: bool,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> ChatCompletion | AsyncStream[ChatCompletionChunk]:
        ...

    async def create(
        self,
        *,
        messages: Iterable[ChatCompletionMessageParam],
        model: Union[str, Literal["gemma-7b-it", "llama3-70b-8192", "llama3-8b-8192", "mixtral-8x7b-32768"]],
        frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        function_call: Optional[completion_create_params.FunctionCall] | NotGiven = NOT_GIVEN,
        functions: Optional[Iterable[completion_create_params.Function]] | NotGiven = NOT_GIVEN,
        logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
        logprobs: Optional[bool] | NotGiven = NOT_GIVEN,
        max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
        n: Optional[int] | NotGiven = NOT_GIVEN,
        parallel_tool_calls: Optional[bool] | NotGiven = NOT_GIVEN,
        presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
        response_format: Optional[completion_create_params.ResponseFormat] | NotGiven = NOT_GIVEN,
        seed: Optional[int] | NotGiven = NOT_GIVEN,
        stop: Union[Optional[str], List[str], None] | NotGiven = NOT_GIVEN,
        stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
        temperature: Optional[float] | NotGiven = NOT_GIVEN,
        tool_choice: Optional[ChatCompletionToolChoiceOptionParam] | NotGiven = NOT_GIVEN,
        tools: Optional[Iterable[ChatCompletionToolParam]] | NotGiven = NOT_GIVEN,
        top_logprobs: Optional[int] | NotGiven = NOT_GIVEN,
        top_p: Optional[float] | NotGiven = NOT_GIVEN,
        user: Optional[str] | 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,
    ) -> ChatCompletion | AsyncStream[ChatCompletionChunk]:
        """
        Creates a model response for the given chat conversation.

        Args:
          messages: A list of messages comprising the conversation so far.

          model: ID of the model to use. For details on which models are compatible with the Chat
              API, see available [models](/docs/models)

          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.

          function_call: Deprecated in favor of `tool_choice`.

              Controls which (if any) function is called by the model. `none` means the model
              will not call a function and instead generates a message. `auto` means the model
              can pick between generating a message or calling a function. Specifying a
              particular function via `{"name": "my_function"}` forces the model to call that
              function.

              `none` is the default when no functions are present. `auto` is the default if
              functions are present.

          functions: Deprecated in favor of `tools`.

              A list of functions the model may generate JSON inputs for.

          logit_bias: This is not yet supported by any of our models. Modify the likelihood of
              specified tokens appearing in the completion.

          logprobs: This is not yet supported by any of our models. Whether to return log
              probabilities of the output tokens or not. If true, returns the log
              probabilities of each output token returned in the `content` of `message`.

          max_tokens: The maximum number of tokens that can be generated in the chat completion. The
              total length of input tokens and generated tokens is limited by the model's
              context length.

          n: How many chat completion choices to generate for each input message. Note that
              the current moment, only n=1 is supported. Other values will result in a 400
              response.

          parallel_tool_calls: Whether to enable parallel function calling during tool use.

          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.

          response_format: An object specifying the format that the model must output.

              Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
              message the model generates is valid JSON.

              **Important:** when using JSON mode, you **must** also instruct the model to
              produce JSON yourself via a system or user message.

          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: Up to 4 sequences where the API will stop generating further tokens. The
              returned text will not contain the stop sequence.

          stream: If set, partial message deltas will be sent. 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 code](/docs/text-chat#streaming-a-chat-completion).

          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

          tool_choice: Controls which (if any) tool is called by the model. `none` means the model will
              not call any tool and instead generates a message. `auto` means the model can
              pick between generating a message or calling one or more tools. `required` means
              the model must call one or more tools. Specifying a particular tool via
              `{"type": "function", "function": {"name": "my_function"}}` forces the model to
              call that tool.

              `none` is the default when no tools are present. `auto` is the default if tools
              are present.

          tools: A list of tools the model may call. Currently, only functions are supported as a
              tool. Use this to provide a list of functions the model may generate JSON inputs
              for. A max of 128 functions are supported.

          top_logprobs: This is not yet supported by any of our models. An integer between 0 and 20
              specifying the number of most likely tokens to return at each token position,
              each with an associated log probability. `logprobs` must be set to `true` if
              this parameter is used.

          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 us monitor and
              detect abuse.

          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
        """
        return await self._post(
            "/openai/v1/chat/completions",
            body=await async_maybe_transform(
                {
                    "messages": messages,
                    "model": model,
                    "frequency_penalty": frequency_penalty,
                    "function_call": function_call,
                    "functions": functions,
                    "logit_bias": logit_bias,
                    "logprobs": logprobs,
                    "max_tokens": max_tokens,
                    "n": n,
                    "parallel_tool_calls": parallel_tool_calls,
                    "presence_penalty": presence_penalty,
                    "response_format": response_format,
                    "seed": seed,
                    "stop": stop,
                    "stream": stream,
                    "temperature": temperature,
                    "tool_choice": tool_choice,
                    "tools": tools,
                    "top_logprobs": top_logprobs,
                    "top_p": top_p,
                    "user": user,
                },
                completion_create_params.CompletionCreateParams,
            ),
            options=make_request_options(
                extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
            ),
            cast_to=ChatCompletion,
            stream=stream or False,
            stream_cls=AsyncStream[ChatCompletionChunk],
        )


class CompletionsWithRawResponse:
    def __init__(self, completions: Completions) -> None:
        self._completions = completions

        self.create = to_raw_response_wrapper(
            completions.create,
        )


class AsyncCompletionsWithRawResponse:
    def __init__(self, completions: AsyncCompletions) -> None:
        self._completions = completions

        self.create = async_to_raw_response_wrapper(
            completions.create,
        )


class CompletionsWithStreamingResponse:
    def __init__(self, completions: Completions) -> None:
        self._completions = completions

        self.create = to_streamed_response_wrapper(
            completions.create,
        )


class AsyncCompletionsWithStreamingResponse:
    def __init__(self, completions: AsyncCompletions) -> None:
        self._completions = completions

        self.create = async_to_streamed_response_wrapper(
            completions.create,
        )
