943 lines
46 KiB
Python
943 lines
46 KiB
Python
# File generated from our OpenAPI spec by Stainless.
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from __future__ import annotations
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from typing import TYPE_CHECKING, Dict, List, Union, Optional, overload
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from typing_extensions import Literal
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from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven
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from ..._utils import required_args, maybe_transform
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from ..._resource import SyncAPIResource, AsyncAPIResource
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from ..._response import to_raw_response_wrapper, async_to_raw_response_wrapper
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from ..._streaming import Stream, AsyncStream
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from ...types.chat import (
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ChatCompletion,
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ChatCompletionChunk,
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ChatCompletionMessageParam,
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completion_create_params,
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)
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from ..._base_client import make_request_options
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if TYPE_CHECKING:
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from ..._client import OpenAI, AsyncOpenAI
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__all__ = ["Completions", "AsyncCompletions"]
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class Completions(SyncAPIResource):
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with_raw_response: CompletionsWithRawResponse
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def __init__(self, client: OpenAI) -> None:
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super().__init__(client)
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self.with_raw_response = CompletionsWithRawResponse(self)
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@overload
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def create(
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self,
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*,
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messages: List[ChatCompletionMessageParam],
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model: Union[
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str,
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Literal[
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"gpt-4",
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"gpt-4-0314",
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"gpt-4-0613",
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"gpt-4-32k",
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"gpt-4-32k-0314",
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"gpt-4-32k-0613",
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"gpt-3.5-turbo",
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"gpt-3.5-turbo-16k",
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"gpt-3.5-turbo-0301",
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"gpt-3.5-turbo-0613",
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"gpt-3.5-turbo-16k-0613",
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],
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],
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frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
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function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
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functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
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logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
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max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
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n: Optional[int] | NotGiven = NOT_GIVEN,
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presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
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stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
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stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN,
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temperature: Optional[float] | NotGiven = NOT_GIVEN,
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top_p: Optional[float] | NotGiven = NOT_GIVEN,
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user: str | NotGiven = NOT_GIVEN,
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# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
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# The extra values given here take precedence over values defined on the client or passed to this method.
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extra_headers: Headers | None = None,
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extra_query: Query | None = None,
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extra_body: Body | None = None,
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timeout: float | None | NotGiven = NOT_GIVEN,
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) -> ChatCompletion:
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"""
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Creates a model response for the given chat conversation.
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Args:
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messages: A list of messages comprising the conversation so far.
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[Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
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model: ID of the model to use. See the
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[model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
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table for details on which models work with the Chat API.
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frequency_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on their
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|
existing frequency in the text so far, decreasing the model's likelihood to
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repeat the same line verbatim.
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[See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/gpt/parameter-details)
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function_call: Controls how the model calls functions. "none" means the model will not call a
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function and instead generates a message. "auto" means the model can pick
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between generating a message or calling a function. Specifying a particular
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function via `{"name": "my_function"}` forces the model to call that function.
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"none" is the default when no functions are present. "auto" is the default if
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functions are present.
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functions: A list of functions the model may generate JSON inputs for.
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|
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logit_bias: Modify the likelihood of specified tokens appearing in the completion.
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|
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Accepts a json object that maps tokens (specified by their token ID in the
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|
tokenizer) to an associated bias value from -100 to 100. 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
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or exclusive selection of the relevant token.
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max_tokens: The maximum number of [tokens](/tokenizer) to generate in the chat completion.
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The total length of input tokens and generated tokens is limited by the model's
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context length.
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[Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken)
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for counting tokens.
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n: How many chat completion choices to generate for each input message.
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presence_penalty: Number between -2.0 and 2.0. Positive values penalize new tokens based on
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|
whether they appear in the text so far, increasing the model's likelihood to
|
|
talk about new topics.
|
|
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|
[See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/gpt/parameter-details)
|
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stop: Up to 4 sequences where the API will stop generating further tokens.
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stream: If set, partial message deltas will be sent, like in ChatGPT. Tokens will be
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sent as data-only
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[server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
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as they become available, with the stream terminated by a `data: [DONE]`
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message.
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[Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).
|
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temperature: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will
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|
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.
|
|
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|
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.
|
|
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|
We generally recommend altering this or `temperature` but not both.
|
|
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user: A unique identifier representing your end-user, which can help OpenAI to monitor
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and detect abuse.
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[Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
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extra_headers: Send extra headers
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extra_query: Add additional query parameters to the request
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extra_body: Add additional JSON properties to the request
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timeout: Override the client-level default timeout for this request, in seconds
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"""
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...
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@overload
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def create(
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self,
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*,
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messages: List[ChatCompletionMessageParam],
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model: Union[
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|
str,
|
|
Literal[
|
|
"gpt-4",
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|
"gpt-4-0314",
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|
"gpt-4-0613",
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"gpt-4-32k",
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"gpt-4-32k-0314",
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"gpt-4-32k-0613",
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"gpt-3.5-turbo",
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"gpt-3.5-turbo-16k",
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"gpt-3.5-turbo-0301",
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"gpt-3.5-turbo-0613",
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"gpt-3.5-turbo-16k-0613",
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],
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],
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stream: Literal[True],
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frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
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function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
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functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
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logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
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max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
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n: Optional[int] | NotGiven = NOT_GIVEN,
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presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
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stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
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temperature: Optional[float] | NotGiven = NOT_GIVEN,
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top_p: Optional[float] | NotGiven = NOT_GIVEN,
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user: str | NotGiven = NOT_GIVEN,
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# Use the following arguments if you need to pass additional parameters to the API that aren't available via kwargs.
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# The extra values given here take precedence over values defined on the client or passed to this method.
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extra_headers: Headers | None = None,
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extra_query: Query | None = None,
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extra_body: Body | None = None,
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timeout: float | None | NotGiven = NOT_GIVEN,
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) -> Stream[ChatCompletionChunk]:
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"""
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|
Creates a model response for the given chat conversation.
|
|
|
|
Args:
|
|
messages: A list of messages comprising the conversation so far.
|
|
[Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
|
|
|
|
model: ID of the model to use. See the
|
|
[model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
|
|
table for details on which models work with the Chat API.
|
|
|
|
stream: If set, partial message deltas will be sent, like in ChatGPT. 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).
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
function_call: Controls how the model calls functions. "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: A list of functions the model may generate JSON inputs for.
|
|
|
|
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
|
|
tokenizer) to an associated bias value from -100 to 100. 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.
|
|
|
|
max_tokens: The maximum number of [tokens](/tokenizer) to generate in the chat completion.
|
|
|
|
The total length of input tokens and generated tokens is limited by 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 chat completion choices to generate for each input message.
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
stop: Up to 4 sequences where the API will stop generating further tokens.
|
|
|
|
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
|
|
"""
|
|
...
|
|
|
|
@overload
|
|
def create(
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|
self,
|
|
*,
|
|
messages: List[ChatCompletionMessageParam],
|
|
model: Union[
|
|
str,
|
|
Literal[
|
|
"gpt-4",
|
|
"gpt-4-0314",
|
|
"gpt-4-0613",
|
|
"gpt-4-32k",
|
|
"gpt-4-32k-0314",
|
|
"gpt-4-32k-0613",
|
|
"gpt-3.5-turbo",
|
|
"gpt-3.5-turbo-16k",
|
|
"gpt-3.5-turbo-0301",
|
|
"gpt-3.5-turbo-0613",
|
|
"gpt-3.5-turbo-16k-0613",
|
|
],
|
|
],
|
|
stream: bool,
|
|
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
|
|
functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
|
|
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
|
|
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
|
|
temperature: Optional[float] | NotGiven = NOT_GIVEN,
|
|
top_p: Optional[float] | NotGiven = NOT_GIVEN,
|
|
user: 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 | 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.
|
|
[Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
|
|
|
|
model: ID of the model to use. See the
|
|
[model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
|
|
table for details on which models work with the Chat API.
|
|
|
|
stream: If set, partial message deltas will be sent, like in ChatGPT. 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).
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
function_call: Controls how the model calls functions. "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: A list of functions the model may generate JSON inputs for.
|
|
|
|
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
|
|
tokenizer) to an associated bias value from -100 to 100. 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.
|
|
|
|
max_tokens: The maximum number of [tokens](/tokenizer) to generate in the chat completion.
|
|
|
|
The total length of input tokens and generated tokens is limited by 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 chat completion choices to generate for each input message.
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
stop: Up to 4 sequences where the API will stop generating further tokens.
|
|
|
|
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
|
|
"""
|
|
...
|
|
|
|
@required_args(["messages", "model"], ["messages", "model", "stream"])
|
|
def create(
|
|
self,
|
|
*,
|
|
messages: List[ChatCompletionMessageParam],
|
|
model: Union[
|
|
str,
|
|
Literal[
|
|
"gpt-4",
|
|
"gpt-4-0314",
|
|
"gpt-4-0613",
|
|
"gpt-4-32k",
|
|
"gpt-4-32k-0314",
|
|
"gpt-4-32k-0613",
|
|
"gpt-3.5-turbo",
|
|
"gpt-3.5-turbo-16k",
|
|
"gpt-3.5-turbo-0301",
|
|
"gpt-3.5-turbo-0613",
|
|
"gpt-3.5-turbo-16k-0613",
|
|
],
|
|
],
|
|
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
|
|
functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
|
|
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
|
|
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
|
|
stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
|
|
temperature: Optional[float] | NotGiven = NOT_GIVEN,
|
|
top_p: Optional[float] | NotGiven = NOT_GIVEN,
|
|
user: 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 | None | NotGiven = NOT_GIVEN,
|
|
) -> ChatCompletion | Stream[ChatCompletionChunk]:
|
|
return self._post(
|
|
"/chat/completions",
|
|
body=maybe_transform(
|
|
{
|
|
"messages": messages,
|
|
"model": model,
|
|
"frequency_penalty": frequency_penalty,
|
|
"function_call": function_call,
|
|
"functions": functions,
|
|
"logit_bias": logit_bias,
|
|
"max_tokens": max_tokens,
|
|
"n": n,
|
|
"presence_penalty": presence_penalty,
|
|
"stop": stop,
|
|
"stream": stream,
|
|
"temperature": temperature,
|
|
"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):
|
|
with_raw_response: AsyncCompletionsWithRawResponse
|
|
|
|
def __init__(self, client: AsyncOpenAI) -> None:
|
|
super().__init__(client)
|
|
self.with_raw_response = AsyncCompletionsWithRawResponse(self)
|
|
|
|
@overload
|
|
async def create(
|
|
self,
|
|
*,
|
|
messages: List[ChatCompletionMessageParam],
|
|
model: Union[
|
|
str,
|
|
Literal[
|
|
"gpt-4",
|
|
"gpt-4-0314",
|
|
"gpt-4-0613",
|
|
"gpt-4-32k",
|
|
"gpt-4-32k-0314",
|
|
"gpt-4-32k-0613",
|
|
"gpt-3.5-turbo",
|
|
"gpt-3.5-turbo-16k",
|
|
"gpt-3.5-turbo-0301",
|
|
"gpt-3.5-turbo-0613",
|
|
"gpt-3.5-turbo-16k-0613",
|
|
],
|
|
],
|
|
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
|
|
functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
|
|
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
|
|
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
|
|
stream: Optional[Literal[False]] | NotGiven = NOT_GIVEN,
|
|
temperature: Optional[float] | NotGiven = NOT_GIVEN,
|
|
top_p: Optional[float] | NotGiven = NOT_GIVEN,
|
|
user: 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 | None | NotGiven = NOT_GIVEN,
|
|
) -> ChatCompletion:
|
|
"""
|
|
Creates a model response for the given chat conversation.
|
|
|
|
Args:
|
|
messages: A list of messages comprising the conversation so far.
|
|
[Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
|
|
|
|
model: ID of the model to use. See the
|
|
[model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
|
|
table for details on which models work with the Chat API.
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
function_call: Controls how the model calls functions. "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: A list of functions the model may generate JSON inputs for.
|
|
|
|
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
|
|
tokenizer) to an associated bias value from -100 to 100. 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.
|
|
|
|
max_tokens: The maximum number of [tokens](/tokenizer) to generate in the chat completion.
|
|
|
|
The total length of input tokens and generated tokens is limited by 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 chat completion choices to generate for each input message.
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
stop: Up to 4 sequences where the API will stop generating further tokens.
|
|
|
|
stream: If set, partial message deltas will be sent, like in ChatGPT. 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).
|
|
|
|
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
|
|
"""
|
|
...
|
|
|
|
@overload
|
|
async def create(
|
|
self,
|
|
*,
|
|
messages: List[ChatCompletionMessageParam],
|
|
model: Union[
|
|
str,
|
|
Literal[
|
|
"gpt-4",
|
|
"gpt-4-0314",
|
|
"gpt-4-0613",
|
|
"gpt-4-32k",
|
|
"gpt-4-32k-0314",
|
|
"gpt-4-32k-0613",
|
|
"gpt-3.5-turbo",
|
|
"gpt-3.5-turbo-16k",
|
|
"gpt-3.5-turbo-0301",
|
|
"gpt-3.5-turbo-0613",
|
|
"gpt-3.5-turbo-16k-0613",
|
|
],
|
|
],
|
|
stream: Literal[True],
|
|
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
|
|
functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
|
|
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
|
|
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
|
|
temperature: Optional[float] | NotGiven = NOT_GIVEN,
|
|
top_p: Optional[float] | NotGiven = NOT_GIVEN,
|
|
user: 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 | None | NotGiven = NOT_GIVEN,
|
|
) -> AsyncStream[ChatCompletionChunk]:
|
|
"""
|
|
Creates a model response for the given chat conversation.
|
|
|
|
Args:
|
|
messages: A list of messages comprising the conversation so far.
|
|
[Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
|
|
|
|
model: ID of the model to use. See the
|
|
[model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
|
|
table for details on which models work with the Chat API.
|
|
|
|
stream: If set, partial message deltas will be sent, like in ChatGPT. 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).
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
function_call: Controls how the model calls functions. "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: A list of functions the model may generate JSON inputs for.
|
|
|
|
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
|
|
tokenizer) to an associated bias value from -100 to 100. 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.
|
|
|
|
max_tokens: The maximum number of [tokens](/tokenizer) to generate in the chat completion.
|
|
|
|
The total length of input tokens and generated tokens is limited by 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 chat completion choices to generate for each input message.
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
stop: Up to 4 sequences where the API will stop generating further tokens.
|
|
|
|
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
|
|
"""
|
|
...
|
|
|
|
@overload
|
|
async def create(
|
|
self,
|
|
*,
|
|
messages: List[ChatCompletionMessageParam],
|
|
model: Union[
|
|
str,
|
|
Literal[
|
|
"gpt-4",
|
|
"gpt-4-0314",
|
|
"gpt-4-0613",
|
|
"gpt-4-32k",
|
|
"gpt-4-32k-0314",
|
|
"gpt-4-32k-0613",
|
|
"gpt-3.5-turbo",
|
|
"gpt-3.5-turbo-16k",
|
|
"gpt-3.5-turbo-0301",
|
|
"gpt-3.5-turbo-0613",
|
|
"gpt-3.5-turbo-16k-0613",
|
|
],
|
|
],
|
|
stream: bool,
|
|
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
|
|
functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
|
|
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
|
|
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
|
|
temperature: Optional[float] | NotGiven = NOT_GIVEN,
|
|
top_p: Optional[float] | NotGiven = NOT_GIVEN,
|
|
user: 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 | 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.
|
|
[Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
|
|
|
|
model: ID of the model to use. See the
|
|
[model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)
|
|
table for details on which models work with the Chat API.
|
|
|
|
stream: If set, partial message deltas will be sent, like in ChatGPT. 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).
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
function_call: Controls how the model calls functions. "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: A list of functions the model may generate JSON inputs for.
|
|
|
|
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
|
|
tokenizer) to an associated bias value from -100 to 100. 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.
|
|
|
|
max_tokens: The maximum number of [tokens](/tokenizer) to generate in the chat completion.
|
|
|
|
The total length of input tokens and generated tokens is limited by 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 chat completion choices to generate for each input message.
|
|
|
|
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/gpt/parameter-details)
|
|
|
|
stop: Up to 4 sequences where the API will stop generating further tokens.
|
|
|
|
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
|
|
"""
|
|
...
|
|
|
|
@required_args(["messages", "model"], ["messages", "model", "stream"])
|
|
async def create(
|
|
self,
|
|
*,
|
|
messages: List[ChatCompletionMessageParam],
|
|
model: Union[
|
|
str,
|
|
Literal[
|
|
"gpt-4",
|
|
"gpt-4-0314",
|
|
"gpt-4-0613",
|
|
"gpt-4-32k",
|
|
"gpt-4-32k-0314",
|
|
"gpt-4-32k-0613",
|
|
"gpt-3.5-turbo",
|
|
"gpt-3.5-turbo-16k",
|
|
"gpt-3.5-turbo-0301",
|
|
"gpt-3.5-turbo-0613",
|
|
"gpt-3.5-turbo-16k-0613",
|
|
],
|
|
],
|
|
frequency_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
function_call: completion_create_params.FunctionCall | NotGiven = NOT_GIVEN,
|
|
functions: List[completion_create_params.Function] | NotGiven = NOT_GIVEN,
|
|
logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
|
|
max_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | NotGiven = NOT_GIVEN,
|
|
stream: Optional[Literal[False]] | Literal[True] | NotGiven = NOT_GIVEN,
|
|
temperature: Optional[float] | NotGiven = NOT_GIVEN,
|
|
top_p: Optional[float] | NotGiven = NOT_GIVEN,
|
|
user: 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 | None | NotGiven = NOT_GIVEN,
|
|
) -> ChatCompletion | AsyncStream[ChatCompletionChunk]:
|
|
return await self._post(
|
|
"/chat/completions",
|
|
body=maybe_transform(
|
|
{
|
|
"messages": messages,
|
|
"model": model,
|
|
"frequency_penalty": frequency_penalty,
|
|
"function_call": function_call,
|
|
"functions": functions,
|
|
"logit_bias": logit_bias,
|
|
"max_tokens": max_tokens,
|
|
"n": n,
|
|
"presence_penalty": presence_penalty,
|
|
"stop": stop,
|
|
"stream": stream,
|
|
"temperature": temperature,
|
|
"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.create = to_raw_response_wrapper(
|
|
completions.create,
|
|
)
|
|
|
|
|
|
class AsyncCompletionsWithRawResponse:
|
|
def __init__(self, completions: AsyncCompletions) -> None:
|
|
self.create = async_to_raw_response_wrapper(
|
|
completions.create,
|
|
)
|