File: /var/www/ai-notam/node_modules/openai/resources/chat/completions.d.ts
import { APIResource } from "../../resource.js";
import { APIPromise } from "../../core.js";
import * as Core from "../../core.js";
import * as ChatCompletionsAPI from "./completions.js";
import * as CompletionsAPI from "../completions.js";
import * as Shared from "../shared.js";
import * as ChatAPI from "./chat.js";
import { Stream } from "../../streaming.js";
export declare class Completions extends APIResource {
/**
* Creates a model response for the given chat conversation.
*/
create(body: ChatCompletionCreateParamsNonStreaming, options?: Core.RequestOptions): APIPromise<ChatCompletion>;
create(body: ChatCompletionCreateParamsStreaming, options?: Core.RequestOptions): APIPromise<Stream<ChatCompletionChunk>>;
create(body: ChatCompletionCreateParamsBase, options?: Core.RequestOptions): APIPromise<Stream<ChatCompletionChunk> | ChatCompletion>;
}
/**
* Represents a chat completion response returned by model, based on the provided
* input.
*/
export interface ChatCompletion {
/**
* A unique identifier for the chat completion.
*/
id: string;
/**
* A list of chat completion choices. Can be more than one if `n` is greater
* than 1.
*/
choices: Array<ChatCompletion.Choice>;
/**
* The Unix timestamp (in seconds) of when the chat completion was created.
*/
created: number;
/**
* The model used for the chat completion.
*/
model: string;
/**
* The object type, which is always `chat.completion`.
*/
object: 'chat.completion';
/**
* The service tier used for processing the request. This field is only included if
* the `service_tier` parameter is specified in the request.
*/
service_tier?: 'scale' | 'default' | null;
/**
* This fingerprint represents the backend configuration that the model runs with.
*
* Can be used in conjunction with the `seed` request parameter to understand when
* backend changes have been made that might impact determinism.
*/
system_fingerprint?: string;
/**
* Usage statistics for the completion request.
*/
usage?: CompletionsAPI.CompletionUsage;
}
export declare namespace ChatCompletion {
interface Choice {
/**
* The reason the model stopped generating tokens. This will be `stop` if the model
* hit a natural stop point or a provided stop sequence, `length` if the maximum
* number of tokens specified in the request was reached, `content_filter` if
* content was omitted due to a flag from our content filters, `tool_calls` if the
* model called a tool, or `function_call` (deprecated) if the model called a
* function.
*/
finish_reason: 'stop' | 'length' | 'tool_calls' | 'content_filter' | 'function_call';
/**
* The index of the choice in the list of choices.
*/
index: number;
/**
* Log probability information for the choice.
*/
logprobs: Choice.Logprobs | null;
/**
* A chat completion message generated by the model.
*/
message: ChatCompletionsAPI.ChatCompletionMessage;
}
namespace Choice {
/**
* Log probability information for the choice.
*/
interface Logprobs {
/**
* A list of message content tokens with log probability information.
*/
content: Array<ChatCompletionsAPI.ChatCompletionTokenLogprob> | null;
}
}
}
export interface ChatCompletionAssistantMessageParam {
/**
* The role of the messages author, in this case `assistant`.
*/
role: 'assistant';
/**
* The contents of the assistant message. Required unless `tool_calls` or
* `function_call` is specified.
*/
content?: string | null;
/**
* @deprecated: Deprecated and replaced by `tool_calls`. The name and arguments of
* a function that should be called, as generated by the model.
*/
function_call?: ChatCompletionAssistantMessageParam.FunctionCall | null;
/**
* An optional name for the participant. Provides the model information to
* differentiate between participants of the same role.
*/
name?: string;
/**
* The tool calls generated by the model, such as function calls.
*/
tool_calls?: Array<ChatCompletionMessageToolCall>;
}
export declare namespace ChatCompletionAssistantMessageParam {
/**
* @deprecated: Deprecated and replaced by `tool_calls`. The name and arguments of
* a function that should be called, as generated by the model.
*/
interface FunctionCall {
/**
* The arguments to call the function with, as generated by the model in JSON
* format. Note that the model does not always generate valid JSON, and may
* hallucinate parameters not defined by your function schema. Validate the
* arguments in your code before calling your function.
*/
arguments: string;
/**
* The name of the function to call.
*/
name: string;
}
}
/**
* Represents a streamed chunk of a chat completion response returned by model,
* based on the provided input.
*/
export interface ChatCompletionChunk {
/**
* A unique identifier for the chat completion. Each chunk has the same ID.
*/
id: string;
/**
* A list of chat completion choices. Can contain more than one elements if `n` is
* greater than 1. Can also be empty for the last chunk if you set
* `stream_options: {"include_usage": true}`.
*/
choices: Array<ChatCompletionChunk.Choice>;
/**
* The Unix timestamp (in seconds) of when the chat completion was created. Each
* chunk has the same timestamp.
*/
created: number;
/**
* The model to generate the completion.
*/
model: string;
/**
* The object type, which is always `chat.completion.chunk`.
*/
object: 'chat.completion.chunk';
/**
* The service tier used for processing the request. This field is only included if
* the `service_tier` parameter is specified in the request.
*/
service_tier?: 'scale' | 'default' | null;
/**
* This fingerprint represents the backend configuration that the model runs with.
* Can be used in conjunction with the `seed` request parameter to understand when
* backend changes have been made that might impact determinism.
*/
system_fingerprint?: string;
/**
* An optional field that will only be present when you set
* `stream_options: {"include_usage": true}` in your request. When present, it
* contains a null value except for the last chunk which contains the token usage
* statistics for the entire request.
*/
usage?: CompletionsAPI.CompletionUsage;
}
export declare namespace ChatCompletionChunk {
interface Choice {
/**
* A chat completion delta generated by streamed model responses.
*/
delta: Choice.Delta;
/**
* The reason the model stopped generating tokens. This will be `stop` if the model
* hit a natural stop point or a provided stop sequence, `length` if the maximum
* number of tokens specified in the request was reached, `content_filter` if
* content was omitted due to a flag from our content filters, `tool_calls` if the
* model called a tool, or `function_call` (deprecated) if the model called a
* function.
*/
finish_reason: 'stop' | 'length' | 'tool_calls' | 'content_filter' | 'function_call' | null;
/**
* The index of the choice in the list of choices.
*/
index: number;
/**
* Log probability information for the choice.
*/
logprobs?: Choice.Logprobs | null;
}
namespace Choice {
/**
* A chat completion delta generated by streamed model responses.
*/
interface Delta {
/**
* The contents of the chunk message.
*/
content?: string | null;
/**
* @deprecated: Deprecated and replaced by `tool_calls`. The name and arguments of
* a function that should be called, as generated by the model.
*/
function_call?: Delta.FunctionCall;
/**
* The role of the author of this message.
*/
role?: 'system' | 'user' | 'assistant' | 'tool';
tool_calls?: Array<Delta.ToolCall>;
}
namespace Delta {
/**
* @deprecated: Deprecated and replaced by `tool_calls`. The name and arguments of
* a function that should be called, as generated by the model.
*/
interface FunctionCall {
/**
* The arguments to call the function with, as generated by the model in JSON
* format. Note that the model does not always generate valid JSON, and may
* hallucinate parameters not defined by your function schema. Validate the
* arguments in your code before calling your function.
*/
arguments?: string;
/**
* The name of the function to call.
*/
name?: string;
}
interface ToolCall {
index: number;
/**
* The ID of the tool call.
*/
id?: string;
function?: ToolCall.Function;
/**
* The type of the tool. Currently, only `function` is supported.
*/
type?: 'function';
}
namespace ToolCall {
interface Function {
/**
* The arguments to call the function with, as generated by the model in JSON
* format. Note that the model does not always generate valid JSON, and may
* hallucinate parameters not defined by your function schema. Validate the
* arguments in your code before calling your function.
*/
arguments?: string;
/**
* The name of the function to call.
*/
name?: string;
}
}
}
/**
* Log probability information for the choice.
*/
interface Logprobs {
/**
* A list of message content tokens with log probability information.
*/
content: Array<ChatCompletionsAPI.ChatCompletionTokenLogprob> | null;
}
}
}
export type ChatCompletionContentPart = ChatCompletionContentPartText | ChatCompletionContentPartImage;
export interface ChatCompletionContentPartImage {
image_url: ChatCompletionContentPartImage.ImageURL;
/**
* The type of the content part.
*/
type: 'image_url';
}
export declare namespace ChatCompletionContentPartImage {
interface ImageURL {
/**
* Either a URL of the image or the base64 encoded image data.
*/
url: string;
/**
* Specifies the detail level of the image. Learn more in the
* [Vision guide](https://platform.openai.com/docs/guides/vision/low-or-high-fidelity-image-understanding).
*/
detail?: 'auto' | 'low' | 'high';
}
}
export interface ChatCompletionContentPartText {
/**
* The text content.
*/
text: string;
/**
* The type of the content part.
*/
type: 'text';
}
/**
* Specifying a particular function via `{"name": "my_function"}` forces the model
* to call that function.
*/
export interface ChatCompletionFunctionCallOption {
/**
* The name of the function to call.
*/
name: string;
}
/**
* @deprecated
*/
export interface ChatCompletionFunctionMessageParam {
/**
* The contents of the function message.
*/
content: string | null;
/**
* The name of the function to call.
*/
name: string;
/**
* The role of the messages author, in this case `function`.
*/
role: 'function';
}
/**
* A chat completion message generated by the model.
*/
export interface ChatCompletionMessage {
/**
* The contents of the message.
*/
content: string | null;
/**
* The role of the author of this message.
*/
role: 'assistant';
/**
* @deprecated: Deprecated and replaced by `tool_calls`. The name and arguments of
* a function that should be called, as generated by the model.
*/
function_call?: ChatCompletionMessage.FunctionCall;
/**
* The tool calls generated by the model, such as function calls.
*/
tool_calls?: Array<ChatCompletionMessageToolCall>;
}
export declare namespace ChatCompletionMessage {
/**
* @deprecated: Deprecated and replaced by `tool_calls`. The name and arguments of
* a function that should be called, as generated by the model.
*/
interface FunctionCall {
/**
* The arguments to call the function with, as generated by the model in JSON
* format. Note that the model does not always generate valid JSON, and may
* hallucinate parameters not defined by your function schema. Validate the
* arguments in your code before calling your function.
*/
arguments: string;
/**
* The name of the function to call.
*/
name: string;
}
}
export type ChatCompletionMessageParam = ChatCompletionSystemMessageParam | ChatCompletionUserMessageParam | ChatCompletionAssistantMessageParam | ChatCompletionToolMessageParam | ChatCompletionFunctionMessageParam;
export interface ChatCompletionMessageToolCall {
/**
* The ID of the tool call.
*/
id: string;
/**
* The function that the model called.
*/
function: ChatCompletionMessageToolCall.Function;
/**
* The type of the tool. Currently, only `function` is supported.
*/
type: 'function';
}
export declare namespace ChatCompletionMessageToolCall {
/**
* The function that the model called.
*/
interface Function {
/**
* The arguments to call the function with, as generated by the model in JSON
* format. Note that the model does not always generate valid JSON, and may
* hallucinate parameters not defined by your function schema. Validate the
* arguments in your code before calling your function.
*/
arguments: string;
/**
* The name of the function to call.
*/
name: string;
}
}
/**
* Specifies a tool the model should use. Use to force the model to call a specific
* function.
*/
export interface ChatCompletionNamedToolChoice {
function: ChatCompletionNamedToolChoice.Function;
/**
* The type of the tool. Currently, only `function` is supported.
*/
type: 'function';
}
export declare namespace ChatCompletionNamedToolChoice {
interface Function {
/**
* The name of the function to call.
*/
name: string;
}
}
/**
* The role of the author of a message
*/
export type ChatCompletionRole = 'system' | 'user' | 'assistant' | 'tool' | 'function';
/**
* Options for streaming response. Only set this when you set `stream: true`.
*/
export interface ChatCompletionStreamOptions {
/**
* If set, an additional chunk will be streamed before the `data: [DONE]` message.
* The `usage` field on this chunk shows the token usage statistics for the entire
* request, and the `choices` field will always be an empty array. All other chunks
* will also include a `usage` field, but with a null value.
*/
include_usage?: boolean;
}
export interface ChatCompletionSystemMessageParam {
/**
* The contents of the system message.
*/
content: string;
/**
* The role of the messages author, in this case `system`.
*/
role: 'system';
/**
* An optional name for the participant. Provides the model information to
* differentiate between participants of the same role.
*/
name?: string;
}
export interface ChatCompletionTokenLogprob {
/**
* The token.
*/
token: string;
/**
* A list of integers representing the UTF-8 bytes representation of the token.
* Useful in instances where characters are represented by multiple tokens and
* their byte representations must be combined to generate the correct text
* representation. Can be `null` if there is no bytes representation for the token.
*/
bytes: Array<number> | null;
/**
* The log probability of this token, if it is within the top 20 most likely
* tokens. Otherwise, the value `-9999.0` is used to signify that the token is very
* unlikely.
*/
logprob: number;
/**
* List of the most likely tokens and their log probability, at this token
* position. In rare cases, there may be fewer than the number of requested
* `top_logprobs` returned.
*/
top_logprobs: Array<ChatCompletionTokenLogprob.TopLogprob>;
}
export declare namespace ChatCompletionTokenLogprob {
interface TopLogprob {
/**
* The token.
*/
token: string;
/**
* A list of integers representing the UTF-8 bytes representation of the token.
* Useful in instances where characters are represented by multiple tokens and
* their byte representations must be combined to generate the correct text
* representation. Can be `null` if there is no bytes representation for the token.
*/
bytes: Array<number> | null;
/**
* The log probability of this token, if it is within the top 20 most likely
* tokens. Otherwise, the value `-9999.0` is used to signify that the token is very
* unlikely.
*/
logprob: number;
}
}
export interface ChatCompletionTool {
function: Shared.FunctionDefinition;
/**
* The type of the tool. Currently, only `function` is supported.
*/
type: 'function';
}
/**
* 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.
*/
export type ChatCompletionToolChoiceOption = 'none' | 'auto' | 'required' | ChatCompletionNamedToolChoice;
export interface ChatCompletionToolMessageParam {
/**
* The contents of the tool message.
*/
content: string;
/**
* The role of the messages author, in this case `tool`.
*/
role: 'tool';
/**
* Tool call that this message is responding to.
*/
tool_call_id: string;
}
export interface ChatCompletionUserMessageParam {
/**
* The contents of the user message.
*/
content: string | Array<ChatCompletionContentPart>;
/**
* The role of the messages author, in this case `user`.
*/
role: 'user';
/**
* An optional name for the participant. Provides the model information to
* differentiate between participants of the same role.
*/
name?: string;
}
/**
* @deprecated ChatCompletionMessageParam should be used instead
*/
export type CreateChatCompletionRequestMessage = ChatCompletionMessageParam;
export type ChatCompletionCreateParams = ChatCompletionCreateParamsNonStreaming | ChatCompletionCreateParamsStreaming;
export interface ChatCompletionCreateParamsBase {
/**
* A list of messages comprising the conversation so far.
* [Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
*/
messages: Array<ChatCompletionMessageParam>;
/**
* 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.
*/
model: (string & {}) | ChatAPI.ChatModel;
/**
* 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)
*/
frequency_penalty?: number | null;
/**
* 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.
*/
function_call?: 'none' | 'auto' | ChatCompletionFunctionCallOption;
/**
* Deprecated in favor of `tools`.
*
* A list of functions the model may generate JSON inputs for.
*/
functions?: Array<ChatCompletionCreateParams.Function>;
/**
* 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.
*/
logit_bias?: Record<string, number> | null;
/**
* 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`.
*/
logprobs?: boolean | null;
/**
* 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.
*/
max_tokens?: number | null;
/**
* 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.
*/
n?: number | null;
/**
* Whether to enable
* [parallel function calling](https://platform.openai.com/docs/guides/function-calling/parallel-function-calling)
* during tool use.
*/
parallel_tool_calls?: boolean;
/**
* 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)
*/
presence_penalty?: number | null;
/**
* 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.
*/
response_format?: ChatCompletionCreateParams.ResponseFormat;
/**
* 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.
*/
seed?: number | null;
/**
* Specifies the latency tier to use for processing the request. This parameter is
* relevant for customers subscribed to the scale tier service:
*
* - If set to 'auto', the system will utilize scale tier credits until they are
* exhausted.
* - If set to 'default', the request will be processed using the default service
* tier with a lower uptime SLA and no latency guarentee.
*
* When this parameter is set, the response body will include the `service_tier`
* utilized.
*/
service_tier?: 'auto' | 'default' | null;
/**
* Up to 4 sequences where the API will stop generating further tokens.
*/
stop?: string | null | Array<string>;
/**
* 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).
*/
stream?: boolean | null;
/**
* Options for streaming response. Only set this when you set `stream: true`.
*/
stream_options?: ChatCompletionStreamOptions | null;
/**
* 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.
*/
temperature?: number | null;
/**
* 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.
*/
tool_choice?: ChatCompletionToolChoiceOption;
/**
* 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.
*/
tools?: Array<ChatCompletionTool>;
/**
* 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_logprobs?: number | null;
/**
* 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.
*/
top_p?: number | null;
/**
* 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).
*/
user?: string;
}
export declare namespace ChatCompletionCreateParams {
/**
* @deprecated
*/
interface Function {
/**
* The name of the function to be called. Must be a-z, A-Z, 0-9, or contain
* underscores and dashes, with a maximum length of 64.
*/
name: string;
/**
* A description of what the function does, used by the model to choose when and
* how to call the function.
*/
description?: string;
/**
* The parameters the functions accepts, described as a JSON Schema object. See the
* [guide](https://platform.openai.com/docs/guides/function-calling) for examples,
* and the
* [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for
* documentation about the format.
*
* Omitting `parameters` defines a function with an empty parameter list.
*/
parameters?: Shared.FunctionParameters;
}
/**
* 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.
*/
interface ResponseFormat {
/**
* Must be one of `text` or `json_object`.
*/
type?: 'text' | 'json_object';
}
type ChatCompletionCreateParamsNonStreaming = ChatCompletionsAPI.ChatCompletionCreateParamsNonStreaming;
type ChatCompletionCreateParamsStreaming = ChatCompletionsAPI.ChatCompletionCreateParamsStreaming;
}
/**
* @deprecated Use ChatCompletionCreateParams instead
*/
export type CompletionCreateParams = ChatCompletionCreateParams;
export interface ChatCompletionCreateParamsNonStreaming extends ChatCompletionCreateParamsBase {
/**
* 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).
*/
stream?: false | null;
}
/**
* @deprecated Use ChatCompletionCreateParamsNonStreaming instead
*/
export type CompletionCreateParamsNonStreaming = ChatCompletionCreateParamsNonStreaming;
export interface ChatCompletionCreateParamsStreaming extends ChatCompletionCreateParamsBase {
/**
* 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).
*/
stream: true;
}
/**
* @deprecated Use ChatCompletionCreateParamsStreaming instead
*/
export type CompletionCreateParamsStreaming = ChatCompletionCreateParamsStreaming;
export declare namespace Completions {
export import ChatCompletion = ChatCompletionsAPI.ChatCompletion;
export import ChatCompletionAssistantMessageParam = ChatCompletionsAPI.ChatCompletionAssistantMessageParam;
export import ChatCompletionChunk = ChatCompletionsAPI.ChatCompletionChunk;
export import ChatCompletionContentPart = ChatCompletionsAPI.ChatCompletionContentPart;
export import ChatCompletionContentPartImage = ChatCompletionsAPI.ChatCompletionContentPartImage;
export import ChatCompletionContentPartText = ChatCompletionsAPI.ChatCompletionContentPartText;
export import ChatCompletionFunctionCallOption = ChatCompletionsAPI.ChatCompletionFunctionCallOption;
export import ChatCompletionFunctionMessageParam = ChatCompletionsAPI.ChatCompletionFunctionMessageParam;
export import ChatCompletionMessage = ChatCompletionsAPI.ChatCompletionMessage;
export import ChatCompletionMessageParam = ChatCompletionsAPI.ChatCompletionMessageParam;
export import ChatCompletionMessageToolCall = ChatCompletionsAPI.ChatCompletionMessageToolCall;
export import ChatCompletionNamedToolChoice = ChatCompletionsAPI.ChatCompletionNamedToolChoice;
export import ChatCompletionRole = ChatCompletionsAPI.ChatCompletionRole;
export import ChatCompletionStreamOptions = ChatCompletionsAPI.ChatCompletionStreamOptions;
export import ChatCompletionSystemMessageParam = ChatCompletionsAPI.ChatCompletionSystemMessageParam;
export import ChatCompletionTokenLogprob = ChatCompletionsAPI.ChatCompletionTokenLogprob;
export import ChatCompletionTool = ChatCompletionsAPI.ChatCompletionTool;
export import ChatCompletionToolChoiceOption = ChatCompletionsAPI.ChatCompletionToolChoiceOption;
export import ChatCompletionToolMessageParam = ChatCompletionsAPI.ChatCompletionToolMessageParam;
export import ChatCompletionUserMessageParam = ChatCompletionsAPI.ChatCompletionUserMessageParam;
/**
* @deprecated ChatCompletionMessageParam should be used instead
*/
export import CreateChatCompletionRequestMessage = ChatCompletionsAPI.CreateChatCompletionRequestMessage;
export import ChatCompletionCreateParams = ChatCompletionsAPI.ChatCompletionCreateParams;
export import CompletionCreateParams = ChatCompletionsAPI.CompletionCreateParams;
export import ChatCompletionCreateParamsNonStreaming = ChatCompletionsAPI.ChatCompletionCreateParamsNonStreaming;
export import CompletionCreateParamsNonStreaming = ChatCompletionsAPI.CompletionCreateParamsNonStreaming;
export import ChatCompletionCreateParamsStreaming = ChatCompletionsAPI.ChatCompletionCreateParamsStreaming;
export import CompletionCreateParamsStreaming = ChatCompletionsAPI.CompletionCreateParamsStreaming;
}
//# sourceMappingURL=completions.d.ts.map