1229 lines
66 KiB
Python
1229 lines
66 KiB
Python
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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from typing import Dict, List, Union, Iterable, Optional, overload
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from typing_extensions import Literal
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import httpx
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from ... import _legacy_response
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from ..._types import NOT_GIVEN, Body, Query, Headers, NotGiven
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from ..._utils import (
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required_args,
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maybe_transform,
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async_maybe_transform,
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)
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from ..._compat import cached_property
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from ..._resource import SyncAPIResource, AsyncAPIResource
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from ..._response import to_streamed_response_wrapper, async_to_streamed_response_wrapper
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from ..._streaming import Stream, AsyncStream
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from ...types.chat import completion_create_params
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from ..._base_client import (
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make_request_options,
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)
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from ...types.chat_model import ChatModel
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from ...types.chat.chat_completion import ChatCompletion
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from ...types.chat.chat_completion_chunk import ChatCompletionChunk
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from ...types.chat.chat_completion_tool_param import ChatCompletionToolParam
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from ...types.chat.chat_completion_message_param import ChatCompletionMessageParam
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from ...types.chat.chat_completion_tool_choice_option_param import ChatCompletionToolChoiceOptionParam
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__all__ = ["Completions", "AsyncCompletions"]
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class Completions(SyncAPIResource):
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@cached_property
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def with_raw_response(self) -> CompletionsWithRawResponse:
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return CompletionsWithRawResponse(self)
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@cached_property
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def with_streaming_response(self) -> CompletionsWithStreamingResponse:
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return CompletionsWithStreamingResponse(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: Iterable[ChatCompletionMessageParam],
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model: Union[str, ChatModel],
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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: Iterable[completion_create_params.Function] | NotGiven = NOT_GIVEN,
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logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
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logprobs: Optional[bool] | 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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response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
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seed: Optional[int] | 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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tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN,
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tools: Iterable[ChatCompletionToolParam] | NotGiven = NOT_GIVEN,
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top_logprobs: Optional[int] | 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 | httpx.Timeout | 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/text-generation/parameter-details)
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function_call: Deprecated in favor of `tool_choice`.
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Controls which (if any) function is called by the model. `none` means the model
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will not call a function and instead generates a message. `auto` means the model
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can pick between generating a message or calling a function. Specifying a
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particular function via `{"name": "my_function"}` forces the model to call that
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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: Deprecated in favor of `tools`.
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A list of functions the model may generate JSON inputs for.
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logit_bias: Modify the likelihood of specified tokens appearing in the completion.
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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.
|
|
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logprobs: Whether to return log probabilities of the output tokens or not. If true,
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returns the log probabilities of each output token returned in the `content` of
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`message`.
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max_tokens: The maximum number of [tokens](/tokenizer) that can be generated in the chat
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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. Note that
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you will be charged based on the number of generated tokens across all of the
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choices. Keep `n` as `1` to minimize costs.
|
|
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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.
|
|
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[See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
|
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response_format: An object specifying the format that the model must output. Compatible with
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[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and
|
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all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.
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Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the
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message the model generates is valid JSON.
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|
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**Important:** when using JSON mode, you **must** also instruct the model to
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|
produce JSON yourself via a system or user message. Without this, the model may
|
|
generate an unending stream of whitespace until the generation reaches the token
|
|
limit, resulting in a long-running and seemingly "stuck" request. Also note that
|
|
the message content may be partially cut off if `finish_reason="length"`, which
|
|
indicates the generation exceeded `max_tokens` or the conversation exceeded the
|
|
max context length.
|
|
|
|
seed: This feature is in Beta. 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.
|
|
|
|
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)
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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).
|
|
|
|
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: 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 OpenAI to monitor
|
|
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: Iterable[ChatCompletionMessageParam],
|
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model: Union[str, ChatModel],
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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: Iterable[completion_create_params.Function] | NotGiven = NOT_GIVEN,
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logit_bias: Optional[Dict[str, int]] | NotGiven = NOT_GIVEN,
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logprobs: Optional[bool] | 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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response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
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seed: Optional[int] | 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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tool_choice: ChatCompletionToolChoiceOptionParam | NotGiven = NOT_GIVEN,
|
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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,
|
|
# 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]:
|
|
"""
|
|
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/text-generation/parameter-details)
|
|
|
|
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: 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.
|
|
|
|
logprobs: 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](/tokenizer) 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.
|
|
[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. Note that
|
|
you will be charged based on the number of generated tokens across all of the
|
|
choices. Keep `n` as `1` to minimize costs.
|
|
|
|
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/text-generation/parameter-details)
|
|
|
|
response_format: An object specifying the format that the model must output. Compatible with
|
|
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and
|
|
all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.
|
|
|
|
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. Without this, the model may
|
|
generate an unending stream of whitespace until the generation reaches the token
|
|
limit, resulting in a long-running and seemingly "stuck" request. Also note that
|
|
the message content may be partially cut off if `finish_reason="length"`, which
|
|
indicates the generation exceeded `max_tokens` or the conversation exceeded the
|
|
max context length.
|
|
|
|
seed: This feature is in Beta. 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.
|
|
|
|
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: 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 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(
|
|
self,
|
|
*,
|
|
messages: Iterable[ChatCompletionMessageParam],
|
|
model: Union[str, ChatModel],
|
|
stream: bool,
|
|
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_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
|
|
seed: Optional[int] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | 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,
|
|
# 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.
|
|
[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/text-generation/parameter-details)
|
|
|
|
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: 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.
|
|
|
|
logprobs: 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](/tokenizer) 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.
|
|
[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. Note that
|
|
you will be charged based on the number of generated tokens across all of the
|
|
choices. Keep `n` as `1` to minimize costs.
|
|
|
|
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/text-generation/parameter-details)
|
|
|
|
response_format: An object specifying the format that the model must output. Compatible with
|
|
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and
|
|
all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.
|
|
|
|
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. Without this, the model may
|
|
generate an unending stream of whitespace until the generation reaches the token
|
|
limit, resulting in a long-running and seemingly "stuck" request. Also note that
|
|
the message content may be partially cut off if `finish_reason="length"`, which
|
|
indicates the generation exceeded `max_tokens` or the conversation exceeded the
|
|
max context length.
|
|
|
|
seed: This feature is in Beta. 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.
|
|
|
|
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: 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 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: Iterable[ChatCompletionMessageParam],
|
|
model: Union[str, ChatModel],
|
|
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_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
|
|
seed: Optional[int] | 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,
|
|
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,
|
|
# 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]:
|
|
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,
|
|
"logprobs": logprobs,
|
|
"max_tokens": max_tokens,
|
|
"n": n,
|
|
"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: Union[str, ChatModel],
|
|
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_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
|
|
seed: Optional[int] | 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,
|
|
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,
|
|
# 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:
|
|
"""
|
|
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/text-generation/parameter-details)
|
|
|
|
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: 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.
|
|
|
|
logprobs: 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](/tokenizer) 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.
|
|
[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. Note that
|
|
you will be charged based on the number of generated tokens across all of the
|
|
choices. Keep `n` as `1` to minimize costs.
|
|
|
|
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/text-generation/parameter-details)
|
|
|
|
response_format: An object specifying the format that the model must output. Compatible with
|
|
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and
|
|
all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.
|
|
|
|
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. Without this, the model may
|
|
generate an unending stream of whitespace until the generation reaches the token
|
|
limit, resulting in a long-running and seemingly "stuck" request. Also note that
|
|
the message content may be partially cut off if `finish_reason="length"`, which
|
|
indicates the generation exceeded `max_tokens` or the conversation exceeded the
|
|
max context length.
|
|
|
|
seed: This feature is in Beta. 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.
|
|
|
|
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.
|
|
|
|
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: 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 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: Iterable[ChatCompletionMessageParam],
|
|
model: Union[str, ChatModel],
|
|
stream: Literal[True],
|
|
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_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
|
|
seed: Optional[int] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | 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,
|
|
# 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]:
|
|
"""
|
|
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/text-generation/parameter-details)
|
|
|
|
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: 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.
|
|
|
|
logprobs: 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](/tokenizer) 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.
|
|
[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. Note that
|
|
you will be charged based on the number of generated tokens across all of the
|
|
choices. Keep `n` as `1` to minimize costs.
|
|
|
|
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/text-generation/parameter-details)
|
|
|
|
response_format: An object specifying the format that the model must output. Compatible with
|
|
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and
|
|
all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.
|
|
|
|
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. Without this, the model may
|
|
generate an unending stream of whitespace until the generation reaches the token
|
|
limit, resulting in a long-running and seemingly "stuck" request. Also note that
|
|
the message content may be partially cut off if `finish_reason="length"`, which
|
|
indicates the generation exceeded `max_tokens` or the conversation exceeded the
|
|
max context length.
|
|
|
|
seed: This feature is in Beta. 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.
|
|
|
|
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: 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 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: Iterable[ChatCompletionMessageParam],
|
|
model: Union[str, ChatModel],
|
|
stream: bool,
|
|
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_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
|
|
seed: Optional[int] | NotGiven = NOT_GIVEN,
|
|
stop: Union[Optional[str], List[str]] | 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,
|
|
# 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.
|
|
[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/text-generation/parameter-details)
|
|
|
|
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: 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.
|
|
|
|
logprobs: 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](/tokenizer) 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.
|
|
[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. Note that
|
|
you will be charged based on the number of generated tokens across all of the
|
|
choices. Keep `n` as `1` to minimize costs.
|
|
|
|
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/text-generation/parameter-details)
|
|
|
|
response_format: An object specifying the format that the model must output. Compatible with
|
|
[GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) and
|
|
all GPT-3.5 Turbo models newer than `gpt-3.5-turbo-1106`.
|
|
|
|
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. Without this, the model may
|
|
generate an unending stream of whitespace until the generation reaches the token
|
|
limit, resulting in a long-running and seemingly "stuck" request. Also note that
|
|
the message content may be partially cut off if `finish_reason="length"`, which
|
|
indicates the generation exceeded `max_tokens` or the conversation exceeded the
|
|
max context length.
|
|
|
|
seed: This feature is in Beta. 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.
|
|
|
|
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: 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 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: Iterable[ChatCompletionMessageParam],
|
|
model: Union[str, ChatModel],
|
|
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_tokens: Optional[int] | NotGiven = NOT_GIVEN,
|
|
n: Optional[int] | NotGiven = NOT_GIVEN,
|
|
presence_penalty: Optional[float] | NotGiven = NOT_GIVEN,
|
|
response_format: completion_create_params.ResponseFormat | NotGiven = NOT_GIVEN,
|
|
seed: Optional[int] | 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,
|
|
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,
|
|
# 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]:
|
|
return await self._post(
|
|
"/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,
|
|
"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 = _legacy_response.to_raw_response_wrapper(
|
|
completions.create,
|
|
)
|
|
|
|
|
|
class AsyncCompletionsWithRawResponse:
|
|
def __init__(self, completions: AsyncCompletions) -> None:
|
|
self._completions = completions
|
|
|
|
self.create = _legacy_response.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,
|
|
)
|