265 lines
11 KiB
TypeScript
265 lines
11 KiB
TypeScript
|
import * as Core from 'openai/core';
|
|||
|
|
import { APIPromise } from 'openai/core';
|
|||
|
|
import { APIResource } from 'openai/resource';
|
|||
|
|
import * as CompletionsAPI from 'openai/resources/completions';
|
|||
|
|
import { Stream } from 'openai/streaming';
|
|||
|
|
export declare class Completions extends APIResource {
|
|||
|
|
/**
|
|||
|
|
* Creates a completion for the provided prompt and parameters.
|
|||
|
|
*/
|
|||
|
|
create(body: CompletionCreateParamsNonStreaming, options?: Core.RequestOptions): APIPromise<Completion>;
|
|||
|
|
create(body: CompletionCreateParamsStreaming, options?: Core.RequestOptions): APIPromise<Stream<Completion>>;
|
|||
|
|
create(body: CompletionCreateParamsBase, options?: Core.RequestOptions): APIPromise<Stream<Completion> | Completion>;
|
|||
|
|
}
|
|||
|
|
/**
|
|||
|
|
* Represents a completion response from the API. Note: both the streamed and
|
|||
|
|
* non-streamed response objects share the same shape (unlike the chat endpoint).
|
|||
|
|
*/
|
|||
|
|
export interface Completion {
|
|||
|
|
/**
|
|||
|
|
* A unique identifier for the completion.
|
|||
|
|
*/
|
|||
|
|
id: string;
|
|||
|
|
/**
|
|||
|
|
* The list of completion choices the model generated for the input prompt.
|
|||
|
|
*/
|
|||
|
|
choices: Array<CompletionChoice>;
|
|||
|
|
/**
|
|||
|
|
* The Unix timestamp (in seconds) of when the completion was created.
|
|||
|
|
*/
|
|||
|
|
created: number;
|
|||
|
|
/**
|
|||
|
|
* The model used for completion.
|
|||
|
|
*/
|
|||
|
|
model: string;
|
|||
|
|
/**
|
|||
|
|
* The object type, which is always "text_completion"
|
|||
|
|
*/
|
|||
|
|
object: 'text_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?: CompletionUsage;
|
|||
|
|
}
|
|||
|
|
export interface CompletionChoice {
|
|||
|
|
/**
|
|||
|
|
* 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, or `content_filter` if
|
|||
|
|
* content was omitted due to a flag from our content filters.
|
|||
|
|
*/
|
|||
|
|
finish_reason: 'stop' | 'length' | 'content_filter';
|
|||
|
|
index: number;
|
|||
|
|
logprobs: CompletionChoice.Logprobs | null;
|
|||
|
|
text: string;
|
|||
|
|
}
|
|||
|
|
export declare namespace CompletionChoice {
|
|||
|
|
interface Logprobs {
|
|||
|
|
text_offset?: Array<number>;
|
|||
|
|
token_logprobs?: Array<number>;
|
|||
|
|
tokens?: Array<string>;
|
|||
|
|
top_logprobs?: Array<Record<string, number>>;
|
|||
|
|
}
|
|||
|
|
}
|
|||
|
|
/**
|
|||
|
|
* Usage statistics for the completion request.
|
|||
|
|
*/
|
|||
|
|
export interface CompletionUsage {
|
|||
|
|
/**
|
|||
|
|
* Number of tokens in the generated completion.
|
|||
|
|
*/
|
|||
|
|
completion_tokens: number;
|
|||
|
|
/**
|
|||
|
|
* Number of tokens in the prompt.
|
|||
|
|
*/
|
|||
|
|
prompt_tokens: number;
|
|||
|
|
/**
|
|||
|
|
* Total number of tokens used in the request (prompt + completion).
|
|||
|
|
*/
|
|||
|
|
total_tokens: number;
|
|||
|
|
}
|
|||
|
|
export type CompletionCreateParams = CompletionCreateParamsNonStreaming | CompletionCreateParamsStreaming;
|
|||
|
|
export interface CompletionCreateParamsBase {
|
|||
|
|
/**
|
|||
|
|
* ID of the model to use. You can use the
|
|||
|
|
* [List models](https://platform.openai.com/docs/api-reference/models/list) API to
|
|||
|
|
* see all of your available models, or see our
|
|||
|
|
* [Model overview](https://platform.openai.com/docs/models/overview) for
|
|||
|
|
* descriptions of them.
|
|||
|
|
*/
|
|||
|
|
model: (string & {}) | 'gpt-3.5-turbo-instruct' | 'davinci-002' | 'babbage-002';
|
|||
|
|
/**
|
|||
|
|
* The prompt(s) to generate completions for, encoded as a string, array of
|
|||
|
|
* strings, array of tokens, or array of token arrays.
|
|||
|
|
*
|
|||
|
|
* Note that <|endoftext|> is the document separator that the model sees during
|
|||
|
|
* training, so if a prompt is not specified the model will generate as if from the
|
|||
|
|
* beginning of a new document.
|
|||
|
|
*/
|
|||
|
|
prompt: string | Array<string> | Array<number> | Array<Array<number>> | null;
|
|||
|
|
/**
|
|||
|
|
* Generates `best_of` completions server-side and returns the "best" (the one with
|
|||
|
|
* the highest log probability per token). Results cannot be streamed.
|
|||
|
|
*
|
|||
|
|
* When used with `n`, `best_of` controls the number of candidate completions and
|
|||
|
|
* `n` specifies how many to return – `best_of` must be greater than `n`.
|
|||
|
|
*
|
|||
|
|
* **Note:** Because this parameter generates many completions, it can quickly
|
|||
|
|
* consume your token quota. Use carefully and ensure that you have reasonable
|
|||
|
|
* settings for `max_tokens` and `stop`.
|
|||
|
|
*/
|
|||
|
|
best_of?: number | null;
|
|||
|
|
/**
|
|||
|
|
* Echo back the prompt in addition to the completion
|
|||
|
|
*/
|
|||
|
|
echo?: boolean | null;
|
|||
|
|
/**
|
|||
|
|
* 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;
|
|||
|
|
/**
|
|||
|
|
* Modify the likelihood of specified tokens appearing in the completion.
|
|||
|
|
*
|
|||
|
|
* Accepts a JSON object that maps tokens (specified by their token ID in the GPT
|
|||
|
|
* tokenizer) to an associated bias value from -100 to 100. You can use this
|
|||
|
|
* [tokenizer tool](/tokenizer?view=bpe) to convert text to token IDs.
|
|||
|
|
* 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.
|
|||
|
|
*
|
|||
|
|
* As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token
|
|||
|
|
* from being generated.
|
|||
|
|
*/
|
|||
|
|
logit_bias?: Record<string, number> | null;
|
|||
|
|
/**
|
|||
|
|
* Include the log probabilities on the `logprobs` most likely output tokens, as
|
|||
|
|
* well the chosen tokens. For example, if `logprobs` is 5, the API will return a
|
|||
|
|
* list of the 5 most likely tokens. The API will always return the `logprob` of
|
|||
|
|
* the sampled token, so there may be up to `logprobs+1` elements in the response.
|
|||
|
|
*
|
|||
|
|
* The maximum value for `logprobs` is 5.
|
|||
|
|
*/
|
|||
|
|
logprobs?: number | null;
|
|||
|
|
/**
|
|||
|
|
* The maximum number of [tokens](/tokenizer) that can be generated in the
|
|||
|
|
* completion.
|
|||
|
|
*
|
|||
|
|
* The token count of your prompt plus `max_tokens` cannot exceed 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 completions to generate for each prompt.
|
|||
|
|
*
|
|||
|
|
* **Note:** Because this parameter generates many completions, it can quickly
|
|||
|
|
* consume your token quota. Use carefully and ensure that you have reasonable
|
|||
|
|
* settings for `max_tokens` and `stop`.
|
|||
|
|
*/
|
|||
|
|
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;
|
|||
|
|
/**
|
|||
|
|
* 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. The
|
|||
|
|
* returned text will not contain the stop sequence.
|
|||
|
|
*/
|
|||
|
|
stop?: string | null | Array<string>;
|
|||
|
|
/**
|
|||
|
|
* Whether to stream back partial progress. If set, 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;
|
|||
|
|
/**
|
|||
|
|
* The suffix that comes after a completion of inserted text.
|
|||
|
|
*/
|
|||
|
|
suffix?: string | 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;
|
|||
|
|
/**
|
|||
|
|
* 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 CompletionCreateParams {
|
|||
|
|
type CompletionCreateParamsNonStreaming = CompletionsAPI.CompletionCreateParamsNonStreaming;
|
|||
|
|
type CompletionCreateParamsStreaming = CompletionsAPI.CompletionCreateParamsStreaming;
|
|||
|
|
}
|
|||
|
|
export interface CompletionCreateParamsNonStreaming extends CompletionCreateParamsBase {
|
|||
|
|
/**
|
|||
|
|
* Whether to stream back partial progress. If set, 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;
|
|||
|
|
}
|
|||
|
|
export interface CompletionCreateParamsStreaming extends CompletionCreateParamsBase {
|
|||
|
|
/**
|
|||
|
|
* Whether to stream back partial progress. If set, 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;
|
|||
|
|
}
|
|||
|
|
export declare namespace Completions {
|
|||
|
|
export import Completion = CompletionsAPI.Completion;
|
|||
|
|
export import CompletionChoice = CompletionsAPI.CompletionChoice;
|
|||
|
|
export import CompletionUsage = CompletionsAPI.CompletionUsage;
|
|||
|
|
export import CompletionCreateParams = CompletionsAPI.CompletionCreateParams;
|
|||
|
|
export import CompletionCreateParamsNonStreaming = CompletionsAPI.CompletionCreateParamsNonStreaming;
|
|||
|
|
export import CompletionCreateParamsStreaming = CompletionsAPI.CompletionCreateParamsStreaming;
|
|||
|
|
}
|
|||
|
|
//# sourceMappingURL=completions.d.ts.map
|