/opt/canhelp/node_modules/openai/resources
Edit: /opt/canhelp/node_modules/openai/resources/completions.d.mts (13780B)
import { APIResource } from "../core/resource.mjs";
import * as CompletionsAPI from "./completions.mjs";
import * as ChatCompletionsAPI from "./chat/completions/completions.mjs";
import { APIPromise } from "../core/api-promise.mjs";
import { Stream } from "../core/streaming.mjs";
import { RequestOptions } from "../internal/request-options.mjs";
/**
* Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position.
*/
export declare class Completions extends APIResource {
/**
* Creates a completion for the provided prompt and parameters.
*
* Returns a completion object, or a sequence of completion objects if the request
* is streamed.
*
* @example
* ```ts
* const completion = await client.completions.create({
* model: 'string',
* prompt: 'This is a test.',
* });
* ```
*/
create(body: CompletionCreateParamsNonStreaming, options?: RequestOptions): APIPromise
;
create(body: CompletionCreateParamsStreaming, options?: RequestOptions): APIPromise>;
create(body: CompletionCreateParamsBase, options?: RequestOptions): APIPromise | 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;
/**
* 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;
token_logprobs?: Array;
tokens?: Array;
top_logprobs?: Array<{
[key: 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;
/**
* Breakdown of tokens used in a completion.
*/
completion_tokens_details?: CompletionUsage.CompletionTokensDetails;
/**
* Breakdown of tokens used in the prompt.
*/
prompt_tokens_details?: CompletionUsage.PromptTokensDetails;
}
export declare namespace CompletionUsage {
/**
* Breakdown of tokens used in a completion.
*/
interface CompletionTokensDetails {
/**
* When using Predicted Outputs, the number of tokens in the prediction that
* appeared in the completion.
*/
accepted_prediction_tokens?: number;
/**
* Audio input tokens generated by the model.
*/
audio_tokens?: number;
/**
* Tokens generated by the model for reasoning.
*/
reasoning_tokens?: number;
/**
* When using Predicted Outputs, the number of tokens in the prediction that did
* not appear in the completion. However, like reasoning tokens, these tokens are
* still counted in the total completion tokens for purposes of billing, output,
* and context window limits.
*/
rejected_prediction_tokens?: number;
}
/**
* Breakdown of tokens used in the prompt.
*/
interface PromptTokensDetails {
/**
* Audio input tokens present in the prompt.
*/
audio_tokens?: number;
/**
* Cached tokens present in the prompt.
*/
cached_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) 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 | Array | Array> | 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)
*/
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?: {
[key: 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)
*/
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;
/**
* Not supported with latest reasoning models `o3` and `o4-mini`.
*
* 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;
/**
* 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;
/**
* Options for streaming response. Only set this when you set `stream: true`.
*/
stream_options?: ChatCompletionsAPI.ChatCompletionStreamOptions | null;
/**
* The suffix that comes after a completion of inserted text.
*
* This parameter is only supported for `gpt-3.5-turbo-instruct`.
*/
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 { type Completion as Completion, type CompletionChoice as CompletionChoice, type CompletionUsage as CompletionUsage, type CompletionCreateParams as CompletionCreateParams, type CompletionCreateParamsNonStreaming as CompletionCreateParamsNonStreaming, type CompletionCreateParamsStreaming as CompletionCreateParamsStreaming, };
}
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