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openai - npm Package Compare versions
Comparing version 4.0.0-beta.7 to 4.0.0-beta.8
@@ -213,3 +213,3 @@ import { APIError } from './error.js'; | ||
| * | ||
| * Will return an empty string if the environment variable doesn't exist or cannot be accessed. | ||
| * Will return undefined if the environment variable doesn't exist or cannot be accessed. | ||
| */ | ||
@@ -225,2 +225,3 @@ export declare const readEnv: (env: string) => string | undefined; | ||
| export declare function hasOwn(obj: Object, key: string): boolean; | ||
| export declare const isRunningInBrowser: () => boolean; | ||
| export interface HeadersProtocol { | ||
@@ -227,0 +228,0 @@ get: (header: string) => string | null | undefined; |
70
core.js
@@ -34,2 +34,3 @@ 'use strict'; | ||
| exports.isHeadersProtocol = | ||
| exports.isRunningInBrowser = | ||
| exports.hasOwn = | ||
@@ -554,3 +555,14 @@ exports.isEmptyObj = | ||
| } | ||
| // TODO add support for Cloudflare workers, browsers, etc. | ||
| const browserInfo = getBrowserInfo(); | ||
| if (browserInfo) { | ||
| return { | ||
| 'X-Stainless-Lang': 'js', | ||
| 'X-Stainless-Package-Version': version_1.VERSION, | ||
| 'X-Stainless-OS': 'Unknown', | ||
| 'X-Stainless-Arch': 'unknown', | ||
| 'X-Stainless-Runtime': `browser:${browserInfo.browser}`, | ||
| 'X-Stainless-Runtime-Version': browserInfo.version, | ||
| }; | ||
| } | ||
| // TODO add support for Cloudflare workers, etc. | ||
| return { | ||
@@ -565,2 +577,28 @@ 'X-Stainless-Lang': 'js', | ||
| }; | ||
| // Note: modified from https://github.com/JS-DevTools/host-environment/blob/b1ab79ecde37db5d6e163c050e54fe7d287d7c92/src/isomorphic.browser.ts | ||
| function getBrowserInfo() { | ||
| if (!navigator || typeof navigator === 'undefined') { | ||
| return null; | ||
| } | ||
| // NOTE: The order matters here! | ||
| const browserPatterns = [ | ||
| { key: 'edge', pattern: /Edge(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'ie', pattern: /MSIE(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'ie', pattern: /Trident(?:.*rv\:(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'chrome', pattern: /Chrome(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'firefox', pattern: /Firefox(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'safari', pattern: /(?:Version\W+(\d+)\.(\d+)(?:\.(\d+))?)?(?:\W+Mobile\S*)?\W+Safari/ }, | ||
| ]; | ||
| // Find the FIRST matching browser | ||
| for (const { key, pattern } of browserPatterns) { | ||
| const match = pattern.exec(navigator.userAgent); | ||
| if (match) { | ||
| const major = match[1] || 0; | ||
| const minor = match[2] || 0; | ||
| const patch = match[3] || 0; | ||
| return { browser: key, version: `${major}.${minor}.${patch}` }; | ||
| } | ||
| } | ||
| return null; | ||
| } | ||
| const normalizeArch = (arch) => { | ||
@@ -620,3 +658,3 @@ // Node docs: | ||
| const validatePositiveInteger = (name, n) => { | ||
| if (!Number.isInteger(n)) { | ||
| if (typeof n !== 'number' || !Number.isInteger(n)) { | ||
| throw new Error(`${name} must be an integer`); | ||
@@ -642,10 +680,17 @@ } | ||
| * | ||
| * Will return an empty string if the environment variable doesn't exist or cannot be accessed. | ||
| * Will return undefined if the environment variable doesn't exist or cannot be accessed. | ||
| */ | ||
| const readEnv = (env) => { | ||
| var _a; | ||
| if (typeof process === 'undefined') { | ||
| return undefined; | ||
| var _a, _b, _c, _d; | ||
| if (typeof process !== 'undefined') { | ||
| return (_b = (_a = process.env) === null || _a === void 0 ? void 0 : _a[env]) !== null && _b !== void 0 ? | ||
| _b | ||
| : undefined; | ||
| } | ||
| return (_a = process.env[env]) !== null && _a !== void 0 ? _a : undefined; | ||
| if (typeof Deno !== 'undefined') { | ||
| return (_d = (_c = Deno.env) === null || _c === void 0 ? void 0 : _c.get) === null || _d === void 0 ? | ||
| void 0 | ||
| : _d.call(_c, env); | ||
| } | ||
| return undefined; | ||
| }; | ||
@@ -714,2 +759,13 @@ exports.readEnv = readEnv; | ||
| }; | ||
| const isRunningInBrowser = () => { | ||
| return ( | ||
| // @ts-ignore | ||
| typeof window !== 'undefined' && | ||
| // @ts-ignore | ||
| typeof window.document !== 'undefined' && | ||
| // @ts-ignore | ||
| typeof navigator !== 'undefined' | ||
| ); | ||
| }; | ||
| exports.isRunningInBrowser = isRunningInBrowser; | ||
| const isHeadersProtocol = (headers) => { | ||
@@ -716,0 +772,0 @@ return typeof (headers === null || headers === void 0 ? void 0 : headers.get) === 'function'; |
@@ -59,2 +59,7 @@ import * as Core from './core.js'; | ||
| defaultQuery?: Core.DefaultQuery; | ||
| /** | ||
| * By default, client-side use of this library is not allowed, as it risks exposing your secret API credentials to attackers. | ||
| * Only set this option to `true` if you understand the risks and have appropriate mitigations in place. | ||
| */ | ||
| dangerouslyAllowBrowser?: boolean; | ||
| organization?: string | null; | ||
@@ -118,2 +123,4 @@ } | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| export import Chat = API.Chat; | ||
@@ -154,4 +161,6 @@ export import Edits = API.Edits; | ||
| export import FineTuneListEventsParams = API.FineTuneListEventsParams; | ||
| export import FineTuneListEventsParamsNonStreaming = API.FineTuneListEventsParamsNonStreaming; | ||
| export import FineTuneListEventsParamsStreaming = API.FineTuneListEventsParamsStreaming; | ||
| } | ||
| export default OpenAI; | ||
| //# sourceMappingURL=index.d.ts.map |
@@ -86,2 +86,7 @@ 'use strict'; | ||
| }; | ||
| if (!options.dangerouslyAllowBrowser && Core.isRunningInBrowser()) { | ||
| throw new Error( | ||
| "It looks like you're running in a browser-like environment.\n\nThis is disabled by default, as it risks exposing your secret API credentials to attackers. \nIf you understand the risks and have appropriate mitigations in place,\nyou can set the `dangerouslyAllowBrowser` option to `true`, e.g.,\n\nnew OpenAI({ apiKey, dangerouslyAllowBrowser: true });\n\nhttps://help.openai.com/en/articles/5112595-best-practices-for-api-key-safety\n", | ||
| ); | ||
| } | ||
| super({ | ||
@@ -88,0 +93,0 @@ baseURL: options.baseURL, |
| { | ||
| "name": "openai", | ||
| "version": "4.0.0-beta.7", | ||
| "version": "4.0.0-beta.8", | ||
| "description": "Client library for the OpenAI API", | ||
@@ -5,0 +5,0 @@ "author": "OpenAI <support@openai.com>", |
@@ -233,8 +233,12 @@ # OpenAI Node API Library | ||
| ## Status | ||
| ## Semantic Versioning | ||
| This package is in beta. Its internals and interfaces are not stable | ||
| and subject to change without a major semver bump; | ||
| please reach out if you rely on any undocumented behavior. | ||
| This package generally attempts to follow [SemVer](https://semver.org/spec/v2.0.0.html) conventions, though certain backwards-incompatible changes may be released as minor versions: | ||
| 1. Changes that only affect static types, without breaking runtime behavior. | ||
| 2. Changes to library internals which are technically public but not intended or documented for external use. _(Please open a GitHub issue to let us know if you are relying on such internals)_. | ||
| 3. Changes that we do not expect to impact the vast majority of users in practice. | ||
| We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience. | ||
| We are keen for your feedback; please open an [issue](https://www.github.com/openai/openai-node/issues) with questions, bugs, or suggestions. | ||
@@ -241,0 +245,0 @@ |
@@ -13,3 +13,5 @@ import { APIResource } from 'openai/resource'; | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } | ||
| //# sourceMappingURL=chat.d.ts.map |
@@ -10,9 +10,13 @@ import * as Core from 'openai/core'; | ||
| create( | ||
| body: CompletionCreateParams.CreateChatCompletionRequestNonStreaming, | ||
| body: CompletionCreateParamsNonStreaming, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<ChatCompletion>>; | ||
| create( | ||
| body: CompletionCreateParams.CreateChatCompletionRequestStreaming, | ||
| body: CompletionCreateParamsStreaming, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Stream<ChatCompletionChunk>>>; | ||
| create( | ||
| body: CompletionCreateParams, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<ChatCompletion | Stream<ChatCompletionChunk>>>; | ||
| } | ||
@@ -168,297 +172,168 @@ export interface ChatCompletion { | ||
| } | ||
| export type CompletionCreateParams = | ||
| | CompletionCreateParams.CreateChatCompletionRequestNonStreaming | ||
| | CompletionCreateParams.CreateChatCompletionRequestStreaming; | ||
| export interface CompletionCreateParams { | ||
| /** | ||
| * A list of messages comprising the conversation so far. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). | ||
| */ | ||
| messages: Array<CreateChatCompletionRequestMessage>; | ||
| /** | ||
| * ID of the model to use. See the | ||
| * [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table | ||
| * for details on which models work with the Chat API. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | '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-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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| frequency_penalty?: number | null; | ||
| /** | ||
| * Controls how the model responds to function calls. "none" means the model does | ||
| * not call a function, and responds to the end-user. "auto" means the model can | ||
| * pick between an end-user 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' | CompletionCreateParams.FunctionCallOption; | ||
| /** | ||
| * A list of functions the model may generate JSON inputs for. | ||
| */ | ||
| functions?: Array<CompletionCreateParams.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; | ||
| /** | ||
| * The maximum number of [tokens](/tokenizer) to generate 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * for counting tokens. | ||
| */ | ||
| max_tokens?: number; | ||
| /** | ||
| * How many chat completion choices to generate for each input message. | ||
| */ | ||
| 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: number | 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| 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; | ||
| /** | ||
| * 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| export declare namespace CompletionCreateParams { | ||
| interface CreateChatCompletionRequestNonStreaming { | ||
| interface FunctionCallOption { | ||
| /** | ||
| * A list of messages comprising the conversation so far. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). | ||
| * The name of the function to call. | ||
| */ | ||
| messages: Array<CreateChatCompletionRequestMessage>; | ||
| /** | ||
| * ID of the model to use. See the | ||
| * [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table | ||
| * for details on which models work with the Chat API. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | '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-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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| frequency_penalty?: number | null; | ||
| /** | ||
| * Controls how the model responds to function calls. "none" means the model does | ||
| * not call a function, and responds to the end-user. "auto" means the model can | ||
| * pick between an end-user 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' | ||
| | CompletionCreateParams.CreateChatCompletionRequestNonStreaming.FunctionCallOption; | ||
| /** | ||
| * A list of functions the model may generate JSON inputs for. | ||
| */ | ||
| functions?: Array<CompletionCreateParams.CreateChatCompletionRequestNonStreaming.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; | ||
| /** | ||
| * The maximum number of [tokens](/tokenizer) to generate 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * for counting tokens. | ||
| */ | ||
| max_tokens?: number; | ||
| /** | ||
| * How many chat completion choices to generate for each input message. | ||
| */ | ||
| 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: number | 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| name: string; | ||
| } | ||
| namespace CreateChatCompletionRequestNonStreaming { | ||
| interface FunctionCallOption { | ||
| /** | ||
| * The name of the function to call. | ||
| */ | ||
| name: string; | ||
| } | ||
| 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; | ||
| /** | ||
| * The parameters the functions accepts, described as a JSON Schema object. See the | ||
| * [guide](/docs/guides/gpt/function-calling) for examples, and the | ||
| * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for | ||
| * documentation about the format. | ||
| * | ||
| * To describe a function that accepts no parameters, provide the value | ||
| * `{"type": "object", "properties": {}}`. | ||
| */ | ||
| parameters: Record<string, unknown>; | ||
| /** | ||
| * A description of what the function does, used by the model to choose when and | ||
| * how to call the function. | ||
| */ | ||
| description?: string; | ||
| } | ||
| } | ||
| interface CreateChatCompletionRequestStreaming { | ||
| interface Function { | ||
| /** | ||
| * A list of messages comprising the conversation so far. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). | ||
| * 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. | ||
| */ | ||
| messages: Array<CreateChatCompletionRequestMessage>; | ||
| name: string; | ||
| /** | ||
| * ID of the model to use. See the | ||
| * [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table | ||
| * for details on which models work with the Chat API. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | '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-16k-0613'; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| /** | ||
| * 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. | ||
| * The parameters the functions accepts, described as a JSON Schema object. See the | ||
| * [guide](/docs/guides/gpt/function-calling) for examples, and the | ||
| * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for | ||
| * documentation about the format. | ||
| * | ||
| * [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details) | ||
| * To describe a function that accepts no parameters, provide the value | ||
| * `{"type": "object", "properties": {}}`. | ||
| */ | ||
| frequency_penalty?: number | null; | ||
| parameters: Record<string, unknown>; | ||
| /** | ||
| * Controls how the model responds to function calls. "none" means the model does | ||
| * not call a function, and responds to the end-user. "auto" means the model can | ||
| * pick between an end-user 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. | ||
| * A description of what the function does, used by the model to choose when and | ||
| * how to call the function. | ||
| */ | ||
| function_call?: | ||
| | 'none' | ||
| | 'auto' | ||
| | CompletionCreateParams.CreateChatCompletionRequestStreaming.FunctionCallOption; | ||
| /** | ||
| * A list of functions the model may generate JSON inputs for. | ||
| */ | ||
| functions?: Array<CompletionCreateParams.CreateChatCompletionRequestStreaming.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; | ||
| /** | ||
| * The maximum number of [tokens](/tokenizer) to generate 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * for counting tokens. | ||
| */ | ||
| max_tokens?: number; | ||
| /** | ||
| * How many chat completion choices to generate for each input message. | ||
| */ | ||
| 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: number | null; | ||
| /** | ||
| * Up to 4 sequences where the API will stop generating further tokens. | ||
| */ | ||
| stop?: string | null | Array<string>; | ||
| /** | ||
| * 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| description?: string; | ||
| } | ||
| namespace CreateChatCompletionRequestStreaming { | ||
| interface FunctionCallOption { | ||
| /** | ||
| * The name of the function to call. | ||
| */ | ||
| name: string; | ||
| } | ||
| 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; | ||
| /** | ||
| * The parameters the functions accepts, described as a JSON Schema object. See the | ||
| * [guide](/docs/guides/gpt/function-calling) for examples, and the | ||
| * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for | ||
| * documentation about the format. | ||
| * | ||
| * To describe a function that accepts no parameters, provide the value | ||
| * `{"type": "object", "properties": {}}`. | ||
| */ | ||
| parameters: Record<string, unknown>; | ||
| /** | ||
| * A description of what the function does, used by the model to choose when and | ||
| * how to call the function. | ||
| */ | ||
| description?: string; | ||
| } | ||
| } | ||
| type CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| type CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } | ||
| export interface CompletionCreateParamsNonStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | null; | ||
| } | ||
| export interface CompletionCreateParamsStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| } | ||
| export declare namespace Completions { | ||
@@ -469,3 +344,5 @@ export import ChatCompletion = API.ChatCompletion; | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } | ||
| //# sourceMappingURL=completions.d.ts.map |
@@ -7,4 +7,6 @@ export { Chat } from './chat.js'; | ||
| CompletionCreateParams, | ||
| CompletionCreateParamsNonStreaming, | ||
| CompletionCreateParamsStreaming, | ||
| Completions, | ||
| } from './completions.js'; | ||
| //# sourceMappingURL=index.d.ts.map |
@@ -10,9 +10,13 @@ import * as Core from 'openai/core'; | ||
| create( | ||
| body: CompletionCreateParams.CreateCompletionRequestNonStreaming, | ||
| body: CompletionCreateParamsNonStreaming, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Completion>>; | ||
| create( | ||
| body: CompletionCreateParams.CreateCompletionRequestStreaming, | ||
| body: CompletionCreateParamsStreaming, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Stream<Completion>>>; | ||
| create( | ||
| body: CompletionCreateParams, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Completion | Stream<Completion>>>; | ||
| } | ||
@@ -48,285 +52,167 @@ export interface Completion { | ||
| } | ||
| export type CompletionCreateParams = | ||
| | CompletionCreateParams.CreateCompletionRequestNonStreaming | ||
| | CompletionCreateParams.CreateCompletionRequestStreaming; | ||
| export interface CompletionCreateParams { | ||
| /** | ||
| * ID of the model to use. You can use the | ||
| * [List models](/docs/api-reference/models/list) API to see all of your available | ||
| * models, or see our [Model overview](/docs/models/overview) for descriptions of | ||
| * them. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | 'text-davinci-003' | ||
| | 'text-davinci-002' | ||
| | 'text-davinci-001' | ||
| | 'code-davinci-002' | ||
| | 'text-curie-001' | ||
| | 'text-babbage-001' | ||
| | 'text-ada-001'; | ||
| /** | ||
| * 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.](/docs/api-reference/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) (which works for both GPT-2 and GPT-3) 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 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) to generate in the completion. | ||
| * | ||
| * The token count of your prompt plus `max_tokens` cannot exceed the model's | ||
| * context length. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| export declare namespace CompletionCreateParams { | ||
| interface CreateCompletionRequestNonStreaming { | ||
| /** | ||
| * ID of the model to use. You can use the | ||
| * [List models](/docs/api-reference/models/list) API to see all of your available | ||
| * models, or see our [Model overview](/docs/models/overview) for descriptions of | ||
| * them. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | 'text-davinci-003' | ||
| | 'text-davinci-002' | ||
| | 'text-davinci-001' | ||
| | 'code-davinci-002' | ||
| | 'text-curie-001' | ||
| | 'text-babbage-001' | ||
| | 'text-ada-001'; | ||
| /** | ||
| * 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.](/docs/api-reference/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) (which works for both GPT-2 and GPT-3) 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 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) to generate in the completion. | ||
| * | ||
| * The token count of your prompt plus `max_tokens` cannot exceed the model's | ||
| * context length. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| interface CreateCompletionRequestStreaming { | ||
| /** | ||
| * ID of the model to use. You can use the | ||
| * [List models](/docs/api-reference/models/list) API to see all of your available | ||
| * models, or see our [Model overview](/docs/models/overview) for descriptions of | ||
| * them. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | 'text-davinci-003' | ||
| | 'text-davinci-002' | ||
| | 'text-davinci-001' | ||
| | 'code-davinci-002' | ||
| | 'text-curie-001' | ||
| | 'text-babbage-001' | ||
| | 'text-ada-001'; | ||
| /** | ||
| * 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; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| /** | ||
| * 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.](/docs/api-reference/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) (which works for both GPT-2 and GPT-3) 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 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) to generate in the completion. | ||
| * | ||
| * The token count of your prompt plus `max_tokens` cannot exceed the model's | ||
| * context length. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: 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>; | ||
| /** | ||
| * 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| type CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| type CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } | ||
| export interface CompletionCreateParamsNonStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | null; | ||
| } | ||
| export interface CompletionCreateParamsStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| } | ||
| export declare namespace Completions { | ||
@@ -336,3 +222,5 @@ export import Completion = API.Completion; | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } | ||
| //# sourceMappingURL=completions.d.ts.map |
@@ -36,3 +36,3 @@ import * as Core from 'openai/core'; | ||
| fineTuneId: string, | ||
| query?: FineTuneListEventsParams.ListEventsRequestNonStreaming, | ||
| query?: FineTuneListEventsParamsNonStreaming, | ||
| options?: Core.RequestOptions, | ||
@@ -42,5 +42,10 @@ ): Promise<Core.APIResponse<FineTuneEventsListResponse>>; | ||
| fineTuneId: string, | ||
| query: FineTuneListEventsParams.ListEventsRequestStreaming, | ||
| query: FineTuneListEventsParamsStreaming, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Stream<FineTuneEvent>>>; | ||
| listEvents( | ||
| fineTuneId: string, | ||
| query?: FineTuneListEventsParams, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<FineTuneEventsListResponse | Stream<FineTuneEvent>>>; | ||
| } | ||
@@ -203,31 +208,42 @@ /** | ||
| } | ||
| export type FineTuneListEventsParams = | ||
| | FineTuneListEventsParams.ListEventsRequestNonStreaming | ||
| | FineTuneListEventsParams.ListEventsRequestStreaming; | ||
| export interface FineTuneListEventsParams { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream?: boolean; | ||
| } | ||
| export declare namespace FineTuneListEventsParams { | ||
| interface ListEventsRequestNonStreaming { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream?: false; | ||
| } | ||
| interface ListEventsRequestStreaming { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream: true; | ||
| } | ||
| type FineTuneListEventsParamsNonStreaming = API.FineTuneListEventsParamsNonStreaming; | ||
| type FineTuneListEventsParamsStreaming = API.FineTuneListEventsParamsStreaming; | ||
| } | ||
| export interface FineTuneListEventsParamsNonStreaming extends FineTuneListEventsParams { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream?: false; | ||
| } | ||
| export interface FineTuneListEventsParamsStreaming extends FineTuneListEventsParams { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream: true; | ||
| } | ||
| export declare namespace FineTunes { | ||
@@ -240,4 +256,6 @@ export import FineTune = API.FineTune; | ||
| export import FineTuneListEventsParams = API.FineTuneListEventsParams; | ||
| export import FineTuneListEventsParamsNonStreaming = API.FineTuneListEventsParamsNonStreaming; | ||
| export import FineTuneListEventsParamsStreaming = API.FineTuneListEventsParamsStreaming; | ||
| } | ||
| export {}; | ||
| //# sourceMappingURL=fine-tunes.d.ts.map |
| export { Audio } from './audio/audio.js'; | ||
| export { Chat } from './chat/chat.js'; | ||
| export { Completion, CompletionChoice, CompletionCreateParams, Completions } from './completions.js'; | ||
| export { | ||
| Completion, | ||
| CompletionChoice, | ||
| CompletionCreateParams, | ||
| CompletionCreateParamsNonStreaming, | ||
| CompletionCreateParamsStreaming, | ||
| Completions, | ||
| } from './completions.js'; | ||
| export { Edit, EditCreateParams, Edits } from './edits.js'; | ||
@@ -13,2 +20,4 @@ export { Embedding, EmbeddingCreateParams, Embeddings } from './embeddings.js'; | ||
| FineTuneListEventsParams, | ||
| FineTuneListEventsParamsNonStreaming, | ||
| FineTuneListEventsParamsStreaming, | ||
| FineTunesPage, | ||
@@ -15,0 +24,0 @@ FineTunes, |
@@ -638,2 +638,3 @@ import { VERSION } from './version'; | ||
| | 'Unknown'; | ||
| type Browser = 'ie' | 'edge' | 'chrome' | 'firefox' | 'safari'; | ||
| type PlatformProperties = { | ||
@@ -644,3 +645,3 @@ 'X-Stainless-Lang': 'js'; | ||
| 'X-Stainless-Arch': Arch; | ||
| 'X-Stainless-Runtime': 'node' | 'deno' | 'edge' | 'unknown'; | ||
| 'X-Stainless-Runtime': 'node' | 'deno' | 'edge' | `browser:${Browser}` | 'unknown'; | ||
| 'X-Stainless-Runtime-Version': string; | ||
@@ -680,3 +681,16 @@ }; | ||
| } | ||
| // TODO add support for Cloudflare workers, browsers, etc. | ||
| const browserInfo = getBrowserInfo(); | ||
| if (browserInfo) { | ||
| return { | ||
| 'X-Stainless-Lang': 'js', | ||
| 'X-Stainless-Package-Version': VERSION, | ||
| 'X-Stainless-OS': 'Unknown', | ||
| 'X-Stainless-Arch': 'unknown', | ||
| 'X-Stainless-Runtime': `browser:${browserInfo.browser}`, | ||
| 'X-Stainless-Runtime-Version': browserInfo.version, | ||
| }; | ||
| } | ||
| // TODO add support for Cloudflare workers, etc. | ||
| return { | ||
@@ -692,2 +706,40 @@ 'X-Stainless-Lang': 'js', | ||
| type BrowserInfo = { | ||
| browser: Browser; | ||
| version: string; | ||
| }; | ||
| declare const navigator: { userAgent: string } | undefined; | ||
| // Note: modified from https://github.com/JS-DevTools/host-environment/blob/b1ab79ecde37db5d6e163c050e54fe7d287d7c92/src/isomorphic.browser.ts | ||
| function getBrowserInfo(): BrowserInfo | null { | ||
| if (!navigator || typeof navigator === 'undefined') { | ||
| return null; | ||
| } | ||
| // NOTE: The order matters here! | ||
| const browserPatterns = [ | ||
| { key: 'edge' as const, pattern: /Edge(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'ie' as const, pattern: /MSIE(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'ie' as const, pattern: /Trident(?:.*rv\:(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'chrome' as const, pattern: /Chrome(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'firefox' as const, pattern: /Firefox(?:\W+(\d+)\.(\d+)(?:\.(\d+))?)?/ }, | ||
| { key: 'safari' as const, pattern: /(?:Version\W+(\d+)\.(\d+)(?:\.(\d+))?)?(?:\W+Mobile\S*)?\W+Safari/ }, | ||
| ]; | ||
| // Find the FIRST matching browser | ||
| for (const { key, pattern } of browserPatterns) { | ||
| const match = pattern.exec(navigator.userAgent); | ||
| if (match) { | ||
| const major = match[1] || 0; | ||
| const minor = match[2] || 0; | ||
| const patch = match[3] || 0; | ||
| return { browser: key, version: `${major}.${minor}.${patch}` }; | ||
| } | ||
| } | ||
| return null; | ||
| } | ||
| const normalizeArch = (arch: string): Arch => { | ||
@@ -751,4 +803,4 @@ // Node docs: | ||
| const validatePositiveInteger = (name: string, n: number) => { | ||
| if (!Number.isInteger(n)) { | ||
| const validatePositiveInteger = (name: string, n: unknown): number => { | ||
| if (typeof n !== 'number' || !Number.isInteger(n)) { | ||
| throw new Error(`${name} must be an integer`); | ||
@@ -775,10 +827,12 @@ } | ||
| * | ||
| * Will return an empty string if the environment variable doesn't exist or cannot be accessed. | ||
| * Will return undefined if the environment variable doesn't exist or cannot be accessed. | ||
| */ | ||
| export const readEnv = (env: string): string | undefined => { | ||
| if (typeof process === 'undefined') { | ||
| return undefined; | ||
| if (typeof process !== 'undefined') { | ||
| return process.env?.[env] ?? undefined; | ||
| } | ||
| return process.env[env] ?? undefined; | ||
| if (typeof Deno !== 'undefined') { | ||
| return Deno.env?.get?.(env); | ||
| } | ||
| return undefined; | ||
| }; | ||
@@ -850,2 +904,13 @@ | ||
| export const isRunningInBrowser = () => { | ||
| return ( | ||
| // @ts-ignore | ||
| typeof window !== 'undefined' && | ||
| // @ts-ignore | ||
| typeof window.document !== 'undefined' && | ||
| // @ts-ignore | ||
| typeof navigator !== 'undefined' | ||
| ); | ||
| }; | ||
| export interface HeadersProtocol { | ||
@@ -852,0 +917,0 @@ get: (header: string) => string | null | undefined; |
@@ -70,2 +70,8 @@ // File generated from our OpenAPI spec by Stainless. | ||
| /** | ||
| * By default, client-side use of this library is not allowed, as it risks exposing your secret API credentials to attackers. | ||
| * Only set this option to `true` if you understand the risks and have appropriate mitigations in place. | ||
| */ | ||
| dangerouslyAllowBrowser?: boolean; | ||
| organization?: string | null; | ||
@@ -99,2 +105,8 @@ } | ||
| if (!options.dangerouslyAllowBrowser && Core.isRunningInBrowser()) { | ||
| throw new Error( | ||
| "It looks like you're running in a browser-like environment.\n\nThis is disabled by default, as it risks exposing your secret API credentials to attackers. \nIf you understand the risks and have appropriate mitigations in place,\nyou can set the `dangerouslyAllowBrowser` option to `true`, e.g.,\n\nnew OpenAI({ apiKey, dangerouslyAllowBrowser: true });\n\nhttps://help.openai.com/en/articles/5112595-best-practices-for-api-key-safety\n", | ||
| ); | ||
| } | ||
| super({ | ||
@@ -186,2 +198,4 @@ baseURL: options.baseURL!, | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
@@ -231,4 +245,6 @@ export import Chat = API.Chat; | ||
| export import FineTuneListEventsParams = API.FineTuneListEventsParams; | ||
| export import FineTuneListEventsParamsNonStreaming = API.FineTuneListEventsParamsNonStreaming; | ||
| export import FineTuneListEventsParamsStreaming = API.FineTuneListEventsParamsStreaming; | ||
| } | ||
| export default OpenAI; |
@@ -6,3 +6,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { Translations } from './translations'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
@@ -9,0 +9,0 @@ export class Audio extends APIResource { |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { type Uploadable, multipartFormRequestOptions } from '../../core'; | ||
@@ -8,0 +8,0 @@ |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { type Uploadable, multipartFormRequestOptions } from '../../core'; | ||
@@ -8,0 +8,0 @@ |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { Completions } from './completions'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
@@ -18,2 +18,4 @@ export class Chat extends APIResource { | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { Stream } from '../../streaming'; | ||
@@ -14,7 +14,7 @@ | ||
| create( | ||
| body: CompletionCreateParams.CreateChatCompletionRequestNonStreaming, | ||
| body: CompletionCreateParamsNonStreaming, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<ChatCompletion>>; | ||
| create( | ||
| body: CompletionCreateParams.CreateChatCompletionRequestStreaming, | ||
| body: CompletionCreateParamsStreaming, | ||
| options?: Core.RequestOptions, | ||
@@ -25,2 +25,6 @@ ): Promise<Core.APIResponse<Stream<ChatCompletionChunk>>>; | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<ChatCompletion | Stream<ChatCompletionChunk>>>; | ||
| create( | ||
| body: CompletionCreateParams, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<ChatCompletion | Stream<ChatCompletionChunk>>> { | ||
@@ -216,332 +220,187 @@ return this.post('/chat/completions', { body, ...options, stream: body.stream ?? false }); | ||
| export type CompletionCreateParams = | ||
| | CompletionCreateParams.CreateChatCompletionRequestNonStreaming | ||
| | CompletionCreateParams.CreateChatCompletionRequestStreaming; | ||
| export interface CompletionCreateParams { | ||
| /** | ||
| * A list of messages comprising the conversation so far. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). | ||
| */ | ||
| messages: Array<CreateChatCompletionRequestMessage>; | ||
| export namespace CompletionCreateParams { | ||
| export interface CreateChatCompletionRequestNonStreaming { | ||
| /** | ||
| * A list of messages comprising the conversation so far. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). | ||
| */ | ||
| messages: Array<CreateChatCompletionRequestMessage>; | ||
| /** | ||
| * ID of the model to use. See the | ||
| * [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table | ||
| * for details on which models work with the Chat API. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | '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-16k-0613'; | ||
| /** | ||
| * ID of the model to use. See the | ||
| * [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table | ||
| * for details on which models work with the Chat API. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | '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-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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| frequency_penalty?: number | 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| frequency_penalty?: number | null; | ||
| /** | ||
| * Controls how the model responds to function calls. "none" means the model does | ||
| * not call a function, and responds to the end-user. "auto" means the model can | ||
| * pick between an end-user 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' | CompletionCreateParams.FunctionCallOption; | ||
| /** | ||
| * Controls how the model responds to function calls. "none" means the model does | ||
| * not call a function, and responds to the end-user. "auto" means the model can | ||
| * pick between an end-user 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' | ||
| | CompletionCreateParams.CreateChatCompletionRequestNonStreaming.FunctionCallOption; | ||
| /** | ||
| * A list of functions the model may generate JSON inputs for. | ||
| */ | ||
| functions?: Array<CompletionCreateParams.Function>; | ||
| /** | ||
| * A list of functions the model may generate JSON inputs for. | ||
| */ | ||
| functions?: Array<CompletionCreateParams.CreateChatCompletionRequestNonStreaming.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; | ||
| /** | ||
| * 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; | ||
| /** | ||
| * The maximum number of [tokens](/tokenizer) to generate 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * for counting tokens. | ||
| */ | ||
| max_tokens?: number; | ||
| /** | ||
| * The maximum number of [tokens](/tokenizer) to generate 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * for counting tokens. | ||
| */ | ||
| max_tokens?: number; | ||
| /** | ||
| * How many chat completion choices to generate for each input message. | ||
| */ | ||
| n?: number | null; | ||
| /** | ||
| * How many chat completion choices to generate for each input message. | ||
| */ | ||
| 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: number | null; | ||
| /** | ||
| * Up to 4 sequences where the API will stop generating further tokens. | ||
| */ | ||
| stop?: string | null | Array<string>; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: boolean | null; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | 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; | ||
| /** | ||
| * 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; | ||
| /** | ||
| * 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| export namespace CompletionCreateParams { | ||
| export interface FunctionCallOption { | ||
| /** | ||
| * A unique identifier representing your end-user, which can help OpenAI to monitor | ||
| * and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids). | ||
| * The name of the function to call. | ||
| */ | ||
| user?: string; | ||
| name: string; | ||
| } | ||
| export namespace CreateChatCompletionRequestNonStreaming { | ||
| export interface FunctionCallOption { | ||
| /** | ||
| * The name of the function to call. | ||
| */ | ||
| name: string; | ||
| } | ||
| export 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; | ||
| /** | ||
| * The parameters the functions accepts, described as a JSON Schema object. See the | ||
| * [guide](/docs/guides/gpt/function-calling) for examples, and the | ||
| * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for | ||
| * documentation about the format. | ||
| * | ||
| * To describe a function that accepts no parameters, provide the value | ||
| * `{"type": "object", "properties": {}}`. | ||
| */ | ||
| parameters: Record<string, unknown>; | ||
| /** | ||
| * A description of what the function does, used by the model to choose when and | ||
| * how to call the function. | ||
| */ | ||
| description?: string; | ||
| } | ||
| } | ||
| export interface CreateChatCompletionRequestStreaming { | ||
| export interface Function { | ||
| /** | ||
| * A list of messages comprising the conversation so far. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb). | ||
| * 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. | ||
| */ | ||
| messages: Array<CreateChatCompletionRequestMessage>; | ||
| name: string; | ||
| /** | ||
| * ID of the model to use. See the | ||
| * [model endpoint compatibility](/docs/models/model-endpoint-compatibility) table | ||
| * for details on which models work with the Chat API. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | '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-16k-0613'; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| /** | ||
| * 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. | ||
| * The parameters the functions accepts, described as a JSON Schema object. See the | ||
| * [guide](/docs/guides/gpt/function-calling) for examples, and the | ||
| * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for | ||
| * documentation about the format. | ||
| * | ||
| * [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details) | ||
| * To describe a function that accepts no parameters, provide the value | ||
| * `{"type": "object", "properties": {}}`. | ||
| */ | ||
| frequency_penalty?: number | null; | ||
| parameters: Record<string, unknown>; | ||
| /** | ||
| * Controls how the model responds to function calls. "none" means the model does | ||
| * not call a function, and responds to the end-user. "auto" means the model can | ||
| * pick between an end-user 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. | ||
| * A description of what the function does, used by the model to choose when and | ||
| * how to call the function. | ||
| */ | ||
| function_call?: | ||
| | 'none' | ||
| | 'auto' | ||
| | CompletionCreateParams.CreateChatCompletionRequestStreaming.FunctionCallOption; | ||
| /** | ||
| * A list of functions the model may generate JSON inputs for. | ||
| */ | ||
| functions?: Array<CompletionCreateParams.CreateChatCompletionRequestStreaming.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; | ||
| /** | ||
| * The maximum number of [tokens](/tokenizer) to generate 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * for counting tokens. | ||
| */ | ||
| max_tokens?: number; | ||
| /** | ||
| * How many chat completion choices to generate for each input message. | ||
| */ | ||
| 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: number | null; | ||
| /** | ||
| * Up to 4 sequences where the API will stop generating further tokens. | ||
| */ | ||
| stop?: string | null | Array<string>; | ||
| /** | ||
| * 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| description?: string; | ||
| } | ||
| export namespace CreateChatCompletionRequestStreaming { | ||
| export interface FunctionCallOption { | ||
| /** | ||
| * The name of the function to call. | ||
| */ | ||
| name: string; | ||
| } | ||
| export type CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export type CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } | ||
| export 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; | ||
| export interface CompletionCreateParamsNonStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | null; | ||
| } | ||
| /** | ||
| * The parameters the functions accepts, described as a JSON Schema object. See the | ||
| * [guide](/docs/guides/gpt/function-calling) for examples, and the | ||
| * [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for | ||
| * documentation about the format. | ||
| * | ||
| * To describe a function that accepts no parameters, provide the value | ||
| * `{"type": "object", "properties": {}}`. | ||
| */ | ||
| parameters: Record<string, unknown>; | ||
| /** | ||
| * A description of what the function does, used by the model to choose when and | ||
| * how to call the function. | ||
| */ | ||
| description?: string; | ||
| } | ||
| } | ||
| export interface CompletionCreateParamsStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| } | ||
@@ -554,2 +413,4 @@ | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } |
@@ -9,3 +9,5 @@ // File generated from our OpenAPI spec by Stainless. | ||
| CompletionCreateParams, | ||
| CompletionCreateParamsNonStreaming, | ||
| CompletionCreateParamsStreaming, | ||
| Completions, | ||
| } from './completions'; |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { Stream } from '../streaming'; | ||
@@ -14,7 +14,7 @@ | ||
| create( | ||
| body: CompletionCreateParams.CreateCompletionRequestNonStreaming, | ||
| body: CompletionCreateParamsNonStreaming, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Completion>>; | ||
| create( | ||
| body: CompletionCreateParams.CreateCompletionRequestStreaming, | ||
| body: CompletionCreateParamsStreaming, | ||
| options?: Core.RequestOptions, | ||
@@ -25,2 +25,6 @@ ): Promise<Core.APIResponse<Stream<Completion>>>; | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Completion | Stream<Completion>>>; | ||
| create( | ||
| body: CompletionCreateParams, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<Completion | Stream<Completion>>> { | ||
@@ -77,316 +81,184 @@ return this.post('/completions', { body, ...options, stream: body.stream ?? false }); | ||
| export type CompletionCreateParams = | ||
| | CompletionCreateParams.CreateCompletionRequestNonStreaming | ||
| | CompletionCreateParams.CreateCompletionRequestStreaming; | ||
| export interface CompletionCreateParams { | ||
| /** | ||
| * ID of the model to use. You can use the | ||
| * [List models](/docs/api-reference/models/list) API to see all of your available | ||
| * models, or see our [Model overview](/docs/models/overview) for descriptions of | ||
| * them. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | 'text-davinci-003' | ||
| | 'text-davinci-002' | ||
| | 'text-davinci-001' | ||
| | 'code-davinci-002' | ||
| | 'text-curie-001' | ||
| | 'text-babbage-001' | ||
| | 'text-ada-001'; | ||
| export namespace CompletionCreateParams { | ||
| export interface CreateCompletionRequestNonStreaming { | ||
| /** | ||
| * ID of the model to use. You can use the | ||
| * [List models](/docs/api-reference/models/list) API to see all of your available | ||
| * models, or see our [Model overview](/docs/models/overview) for descriptions of | ||
| * them. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | 'text-davinci-003' | ||
| | 'text-davinci-002' | ||
| | 'text-davinci-001' | ||
| | 'code-davinci-002' | ||
| | 'text-curie-001' | ||
| | 'text-babbage-001' | ||
| | 'text-ada-001'; | ||
| /** | ||
| * 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; | ||
| /** | ||
| * 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; | ||
| /** | ||
| * 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; | ||
| /** | ||
| * 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| frequency_penalty?: number | 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.](/docs/api-reference/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) (which works for both GPT-2 and GPT-3) 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; | ||
| /** | ||
| * 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) (which works for both GPT-2 and GPT-3) 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 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; | ||
| /** | ||
| * Include the log probabilities on the `logprobs` most likely 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) to generate in the completion. | ||
| * | ||
| * The token count of your prompt plus `max_tokens` cannot exceed the model's | ||
| * context length. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * for counting tokens. | ||
| */ | ||
| max_tokens?: number | null; | ||
| /** | ||
| * The maximum number of [tokens](/tokenizer) to generate in the completion. | ||
| * | ||
| * The token count of your prompt plus `max_tokens` cannot exceed the model's | ||
| * context length. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * 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; | ||
| /** | ||
| * 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: 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>; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: boolean | null; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | null; | ||
| /** | ||
| * The suffix that comes after a completion of inserted text. | ||
| */ | ||
| suffix?: string | 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; | ||
| /** | ||
| * 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; | ||
| /** | ||
| * 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| /** | ||
| * A unique identifier representing your end-user, which can help OpenAI to monitor | ||
| * and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| export namespace CompletionCreateParams { | ||
| export type CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export type CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } | ||
| export interface CreateCompletionRequestStreaming { | ||
| /** | ||
| * ID of the model to use. You can use the | ||
| * [List models](/docs/api-reference/models/list) API to see all of your available | ||
| * models, or see our [Model overview](/docs/models/overview) for descriptions of | ||
| * them. | ||
| */ | ||
| model: | ||
| | (string & {}) | ||
| | 'text-davinci-003' | ||
| | 'text-davinci-002' | ||
| | 'text-davinci-001' | ||
| | 'code-davinci-002' | ||
| | 'text-curie-001' | ||
| | 'text-babbage-001' | ||
| | 'text-ada-001'; | ||
| export interface CompletionCreateParamsNonStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream?: false | null; | ||
| } | ||
| /** | ||
| * 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; | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| /** | ||
| * 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.](/docs/api-reference/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) (which works for both GPT-2 and GPT-3) 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 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) to generate in the completion. | ||
| * | ||
| * The token count of your prompt plus `max_tokens` cannot exceed the model's | ||
| * context length. | ||
| * [Example Python code](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb) | ||
| * 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.](/docs/api-reference/parameter-details) | ||
| */ | ||
| presence_penalty?: 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>; | ||
| /** | ||
| * 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](/docs/guides/safety-best-practices/end-user-ids). | ||
| */ | ||
| user?: string; | ||
| } | ||
| export interface CompletionCreateParamsStreaming extends CompletionCreateParams { | ||
| /** | ||
| * 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://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb). | ||
| */ | ||
| stream: true; | ||
| } | ||
@@ -398,2 +270,4 @@ | ||
| export import CompletionCreateParams = API.CompletionCreateParams; | ||
| export import CompletionCreateParamsNonStreaming = API.CompletionCreateParamsNonStreaming; | ||
| export import CompletionCreateParamsStreaming = API.CompletionCreateParamsStreaming; | ||
| } |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
@@ -8,0 +8,0 @@ export class Edits extends APIResource { |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
@@ -8,0 +8,0 @@ export class Embeddings extends APIResource { |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { type Uploadable, multipartFormRequestOptions } from '../core'; | ||
@@ -8,0 +8,0 @@ import { Page } from '../pagination'; |
@@ -6,3 +6,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import * as Files from './files'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { Page } from '../pagination'; | ||
@@ -52,3 +52,3 @@ import { Stream } from '../streaming'; | ||
| fineTuneId: string, | ||
| query?: FineTuneListEventsParams.ListEventsRequestNonStreaming, | ||
| query?: FineTuneListEventsParamsNonStreaming, | ||
| options?: Core.RequestOptions, | ||
@@ -58,3 +58,3 @@ ): Promise<Core.APIResponse<FineTuneEventsListResponse>>; | ||
| fineTuneId: string, | ||
| query: FineTuneListEventsParams.ListEventsRequestStreaming, | ||
| query: FineTuneListEventsParamsStreaming, | ||
| options?: Core.RequestOptions, | ||
@@ -64,2 +64,7 @@ ): Promise<Core.APIResponse<Stream<FineTuneEvent>>>; | ||
| fineTuneId: string, | ||
| query?: FineTuneListEventsParams, | ||
| options?: Core.RequestOptions, | ||
| ): Promise<Core.APIResponse<FineTuneEventsListResponse | Stream<FineTuneEvent>>>; | ||
| listEvents( | ||
| fineTuneId: string, | ||
| query?: FineTuneListEventsParams | undefined, | ||
@@ -273,34 +278,46 @@ options?: Core.RequestOptions, | ||
| export type FineTuneListEventsParams = | ||
| | FineTuneListEventsParams.ListEventsRequestNonStreaming | ||
| | FineTuneListEventsParams.ListEventsRequestStreaming; | ||
| export interface FineTuneListEventsParams { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream?: boolean; | ||
| } | ||
| export namespace FineTuneListEventsParams { | ||
| export interface ListEventsRequestNonStreaming { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream?: false; | ||
| } | ||
| export type FineTuneListEventsParamsNonStreaming = API.FineTuneListEventsParamsNonStreaming; | ||
| export type FineTuneListEventsParamsStreaming = API.FineTuneListEventsParamsStreaming; | ||
| } | ||
| export interface ListEventsRequestStreaming { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream: true; | ||
| } | ||
| export interface FineTuneListEventsParamsNonStreaming extends FineTuneListEventsParams { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream?: false; | ||
| } | ||
| export interface FineTuneListEventsParamsStreaming extends FineTuneListEventsParams { | ||
| /** | ||
| * Whether to stream events for the fine-tune job. If set to true, events 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. The stream will terminate with a `data: [DONE]` | ||
| * message when the job is finished (succeeded, cancelled, or failed). | ||
| * | ||
| * If set to false, only events generated so far will be returned. | ||
| */ | ||
| stream: true; | ||
| } | ||
| export namespace FineTunes { | ||
@@ -313,2 +330,4 @@ export import FineTune = API.FineTune; | ||
| export import FineTuneListEventsParams = API.FineTuneListEventsParams; | ||
| export import FineTuneListEventsParamsNonStreaming = API.FineTuneListEventsParamsNonStreaming; | ||
| export import FineTuneListEventsParamsStreaming = API.FineTuneListEventsParamsStreaming; | ||
| } |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { type Uploadable, multipartFormRequestOptions } from '../core'; | ||
@@ -8,0 +8,0 @@ |
@@ -5,3 +5,10 @@ // File generated from our OpenAPI spec by Stainless. | ||
| export { Chat } from './chat/chat'; | ||
| export { Completion, CompletionChoice, CompletionCreateParams, Completions } from './completions'; | ||
| export { | ||
| Completion, | ||
| CompletionChoice, | ||
| CompletionCreateParams, | ||
| CompletionCreateParamsNonStreaming, | ||
| CompletionCreateParamsStreaming, | ||
| Completions, | ||
| } from './completions'; | ||
| export { Edit, EditCreateParams, Edits } from './edits'; | ||
@@ -16,2 +23,4 @@ export { Embedding, EmbeddingCreateParams, Embeddings } from './embeddings'; | ||
| FineTuneListEventsParams, | ||
| FineTuneListEventsParamsNonStreaming, | ||
| FineTuneListEventsParamsStreaming, | ||
| FineTunesPage, | ||
@@ -18,0 +27,0 @@ FineTunes, |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
| import { Page } from '../pagination'; | ||
@@ -8,0 +8,0 @@ |
@@ -5,3 +5,3 @@ // File generated from our OpenAPI spec by Stainless. | ||
| import { APIResource } from '../resource'; | ||
| import * as API from '.'; | ||
| import * as API from './index'; | ||
@@ -8,0 +8,0 @@ export class Moderations extends APIResource { |
| import type { Response } from './_shims/fetch.js'; | ||
| import { ReadableStream } from './_shims/ReadableStream.js'; | ||
@@ -81,2 +82,34 @@ import { APIResponse, Headers, createResponseHeaders } from './core'; | ||
| } | ||
| toReadableStream(): ReadableStream { | ||
| const self = this; | ||
| let iter: AsyncIterator<Item>; | ||
| const encoder = new TextEncoder(); | ||
| return new ReadableStream({ | ||
| async start() { | ||
| iter = self[Symbol.asyncIterator](); | ||
| }, | ||
| async pull(ctrl) { | ||
| try { | ||
| const { value, done } = await iter.next(); | ||
| if (done) return ctrl.close(); | ||
| const str = | ||
| typeof value === 'string' ? value : ( | ||
| // Add a newline after JSON to make it easier to parse newline-separated JSON on the frontend. | ||
| JSON.stringify(value) + '\n' | ||
| ); | ||
| const bytes = encoder.encode(str); | ||
| ctrl.enqueue(bytes); | ||
| } catch (err) { | ||
| ctrl.error(err); | ||
| } | ||
| }, | ||
| async cancel() { | ||
| await iter.return?.(); | ||
| }, | ||
| }); | ||
| } | ||
| } | ||
@@ -83,0 +116,0 @@ |
| import { type RequestOptions } from './core'; | ||
| import { type Readable } from './_shims/node-readable'; | ||
| import { type BodyInit } from './_shims/fetch.js'; | ||
| import { FormData, File, type FilePropertyBag } from './_shims/formdata.js'; | ||
| import { FormData, File, type Blob, type FilePropertyBag } from './_shims/formdata.js'; | ||
| import { getMultipartRequestOptions } from './_shims/getMultipartRequestOptions'; | ||
@@ -11,3 +11,4 @@ import { fileFromPath } from './_shims/fileFromPath'; | ||
| export type BlobPart = string | ArrayBuffer | ArrayBufferView | BlobLike | Uint8Array | DataView; | ||
| type BlobLikePart = string | ArrayBuffer | ArrayBufferView | BlobLike | Uint8Array | DataView; | ||
| export type BlobPart = string | ArrayBuffer | ArrayBufferView | Blob | Uint8Array | DataView; | ||
@@ -88,7 +89,7 @@ /** | ||
| export type ToFileInput = Uploadable | Exclude<BlobPart, string> | AsyncIterable<BlobPart>; | ||
| export type ToFileInput = Uploadable | Exclude<BlobLikePart, string> | AsyncIterable<BlobLikePart>; | ||
| /** | ||
| * Helper for creating a {@link File} to pass to an SDK upload method from a variety of different data formats | ||
| * @param value the raw content of the file. Can be an {@link Uploadable}, {@link BlobPart}, or {@link AsyncIterable} of {@link BlobPart}s | ||
| * @param value the raw content of the file. Can be an {@link Uploadable}, {@link BlobLikePart}, or {@link AsyncIterable} of {@link BlobLikePart}s | ||
| * @param {string=} name the name of the file. If omitted, toFile will try to determine a file name from bits if possible | ||
@@ -236,6 +237,6 @@ * @param {Object=} options additional properties | ||
| if (typeof value === 'string' || typeof value === 'number' || typeof value === 'boolean') { | ||
| form.append(key, value); | ||
| form.append(key, String(value)); | ||
| } else if (isUploadable(value)) { | ||
| const file = await toFile(value); | ||
| form.append(key, file); | ||
| form.append(key, file as File); | ||
| } else if (Array.isArray(value)) { | ||
@@ -242,0 +243,0 @@ await Promise.all(value.map((entry) => addFormValue(form, key + '[]', entry))); |
@@ -1,1 +0,1 @@ | ||
| export const VERSION = '4.0.0-beta.7'; | ||
| export const VERSION = '4.0.0-beta.8'; |
| import type { Response } from 'openai/_shims/fetch'; | ||
| import { ReadableStream } from 'openai/_shims/ReadableStream'; | ||
| import { APIResponse, Headers } from './core.js'; | ||
@@ -13,3 +14,4 @@ export declare class Stream<Item> implements AsyncIterable<Item>, APIResponse<Stream<Item>> { | ||
| [Symbol.asyncIterator](): AsyncIterator<Item, any, undefined>; | ||
| toReadableStream(): ReadableStream; | ||
| } | ||
| //# sourceMappingURL=streaming.d.ts.map |
| 'use strict'; | ||
| Object.defineProperty(exports, '__esModule', { value: true }); | ||
| exports.Stream = void 0; | ||
| const ReadableStream_1 = require('openai/_shims/ReadableStream'); | ||
| const core_1 = require('./core.js'); | ||
@@ -59,2 +60,31 @@ class Stream { | ||
| } | ||
| toReadableStream() { | ||
| const self = this; | ||
| let iter; | ||
| const encoder = new TextEncoder(); | ||
| return new ReadableStream_1.ReadableStream({ | ||
| async start() { | ||
| iter = self[Symbol.asyncIterator](); | ||
| }, | ||
| async pull(ctrl) { | ||
| try { | ||
| const { value, done } = await iter.next(); | ||
| if (done) return ctrl.close(); | ||
| const str = | ||
| typeof value === 'string' ? value : ( | ||
| // Add a newline after JSON to make it easier to parse newline-separated JSON on the frontend. | ||
| JSON.stringify(value) + '\n' | ||
| ); | ||
| const bytes = encoder.encode(str); | ||
| ctrl.enqueue(bytes); | ||
| } catch (err) { | ||
| ctrl.error(err); | ||
| } | ||
| }, | ||
| async cancel() { | ||
| var _a; | ||
| await ((_a = iter.return) === null || _a === void 0 ? void 0 : _a.call(iter)); | ||
| }, | ||
| }); | ||
| } | ||
| } | ||
@@ -61,0 +91,0 @@ exports.Stream = Stream; |
| import { type RequestOptions } from './core.js'; | ||
| import { type Readable } from 'openai/_shims/node-readable'; | ||
| import { type BodyInit } from 'openai/_shims/fetch'; | ||
| import { FormData, type FilePropertyBag } from 'openai/_shims/formdata'; | ||
| import { FormData, type Blob, type FilePropertyBag } from 'openai/_shims/formdata'; | ||
| import { fileFromPath } from 'openai/_shims/fileFromPath'; | ||
| import { type FsReadStream } from 'openai/_shims/node-readable'; | ||
| export { fileFromPath }; | ||
| export type BlobPart = string | ArrayBuffer | ArrayBufferView | BlobLike | Uint8Array | DataView; | ||
| type BlobLikePart = string | ArrayBuffer | ArrayBufferView | BlobLike | Uint8Array | DataView; | ||
| export type BlobPart = string | ArrayBuffer | ArrayBufferView | Blob | Uint8Array | DataView; | ||
| /** | ||
@@ -58,6 +59,6 @@ * Typically, this is a native "File" class. | ||
| export declare const isUploadable: (value: any) => value is Uploadable; | ||
| export type ToFileInput = Uploadable | Exclude<BlobPart, string> | AsyncIterable<BlobPart>; | ||
| export type ToFileInput = Uploadable | Exclude<BlobLikePart, string> | AsyncIterable<BlobLikePart>; | ||
| /** | ||
| * Helper for creating a {@link File} to pass to an SDK upload method from a variety of different data formats | ||
| * @param value the raw content of the file. Can be an {@link Uploadable}, {@link BlobPart}, or {@link AsyncIterable} of {@link BlobPart}s | ||
| * @param value the raw content of the file. Can be an {@link Uploadable}, {@link BlobLikePart}, or {@link AsyncIterable} of {@link BlobLikePart}s | ||
| * @param {string=} name the name of the file. If omitted, toFile will try to determine a file name from bits if possible | ||
@@ -64,0 +65,0 @@ * @param {Object=} options additional properties |
@@ -61,3 +61,3 @@ 'use strict'; | ||
| * Helper for creating a {@link File} to pass to an SDK upload method from a variety of different data formats | ||
| * @param value the raw content of the file. Can be an {@link Uploadable}, {@link BlobPart}, or {@link AsyncIterable} of {@link BlobPart}s | ||
| * @param value the raw content of the file. Can be an {@link Uploadable}, {@link BlobLikePart}, or {@link AsyncIterable} of {@link BlobLikePart}s | ||
| * @param {string=} name the name of the file. If omitted, toFile will try to determine a file name from bits if possible | ||
@@ -193,3 +193,3 @@ * @param {Object=} options additional properties | ||
| if (typeof value === 'string' || typeof value === 'number' || typeof value === 'boolean') { | ||
| form.append(key, value); | ||
| form.append(key, String(value)); | ||
| } else if ((0, exports.isUploadable)(value)) { | ||
@@ -196,0 +196,0 @@ const file = await toFile(value); |
@@ -1,2 +0,2 @@ | ||
| export declare const VERSION = '4.0.0-beta.7'; | ||
| export declare const VERSION = '4.0.0-beta.8'; | ||
| //# sourceMappingURL=version.d.ts.map |
| 'use strict'; | ||
| Object.defineProperty(exports, '__esModule', { value: true }); | ||
| exports.VERSION = void 0; | ||
| exports.VERSION = '4.0.0-beta.7'; | ||
| exports.VERSION = '4.0.0-beta.8'; | ||
| //# sourceMappingURL=version.js.map |
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Improved metrics
- Total package byte prevSize
- increased by1.12%
555648
- Number of package files
- increased by5.95%
267
- Lines of code
- increased by0.35%
10270
- Number of lines in readme file
- increased by1.6%
254
- Published versions last two months
- increased by4%
26
- Published versions last week
- increased by100%
2
Worsened metrics
- Number of versions
- decreased by-0.48%
208
- Published versions last months
- decreased by-7.69%
12
- Published versions last year
- decreased by-0.76%
130
No dependency changes