import * as Core from 'openai/core'; import { APIPromise } from 'openai/core'; import { APIResource } from 'openai/resource'; import * as ChatCompletionsAPI from 'openai/resources/chat/completions'; import * as CompletionsAPI from 'openai/resources/completions'; import * as Shared from 'openai/resources/shared'; import { Stream } from 'openai/streaming'; export declare class Completions extends APIResource { /** * Creates a model response for the given chat conversation. */ create(body: ChatCompletionCreateParamsNonStreaming, options?: Core.RequestOptions): APIPromise; create(body: ChatCompletionCreateParamsStreaming, options?: Core.RequestOptions): APIPromise>; create(body: ChatCompletionCreateParamsBase, options?: Core.RequestOptions): APIPromise | 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; /** * 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'; /** * 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 | 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 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; /** * 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; } export declare namespace ChatCompletionAssistantMessageParam { /** * 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 be more than one if `n` is greater * than 1. */ choices: Array; /** * 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'; /** * 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; } 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 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; } namespace Delta { /** * 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 | 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; } 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 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; } export declare namespace ChatCompletionMessage { /** * 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'; 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 | null; /** * The log probability of this token. */ 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; } 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 | null; /** * The log probability of this token. */ logprob: number; } } export interface ChatCompletionTool { function: Shared.FunctionDefinition; /** * The type of the tool. Currently, only `function` is supported. */ type: 'function'; } /** * 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 * `{"type": "function", "function": {"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. */ export type ChatCompletionToolChoiceOption = 'none' | 'auto' | 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; /** * 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; /** * 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 & {}) | 'gpt-4-0125-preview' | 'gpt-4-turbo-preview' | 'gpt-4-1106-preview' | 'gpt-4-vision-preview' | 'gpt-4' | 'gpt-4-0314' | 'gpt-4-0613' | 'gpt-4-32k' | 'gpt-4-32k-0314' | 'gpt-4-32k-0613' | 'gpt-3.5-turbo' | 'gpt-3.5-turbo-16k' | 'gpt-3.5-turbo-0301' | 'gpt-3.5-turbo-0613' | 'gpt-3.5-turbo-1106' | 'gpt-3.5-turbo-16k-0613'; /** * 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; /** * 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 | 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`. This option is currently not available on the `gpt-4-vision-preview` * model. */ 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; /** * 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 * `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; /** * Up to 4 sequences where the API will stop generating further tokens. */ stop?: string | null | Array; /** * 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; /** * 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) 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 * `{"type": "function", "function": {"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. */ 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. */ tools?: Array; /** * An integer between 0 and 5 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 { 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/text-generation/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 * `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 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