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feat: 智能模式，添加群管、试图、联网搜索、发图、发音乐和视频等功能 (#488)

Browse source 
* fix: 2.7 dev start

* feat: 初步支持function call（WIP）

* fix: syntax error

* fix: syntax error

* feat: 群聊上下文

* fix: 暂时阉割掉全员禁言功能

* fix: 修改禁言时间范围

* fix: 修复一些功能易用性

* fix: 只有管理员和群主才能用jinyan和kickout

* fix: 加回来禁言和踢出

* fix: 修复管理员权限判断问题（可能吧）

* fix: 试图优化逻辑

* fix: fuck openai documents

* fix: 删掉认主不然一直禁言我烦死了

* fix: 哔哩哔哩封面损坏问题

* fix: 加个天气小工具

* fix: 天气不存在城市

* fix: website工具用浏览器

* feat: serp tool

* feat: 增加一个google搜索源

* fix: 加一句描述

* feat: 增加搜索来源选项

* feat: 搜图和发图

* fix: groupId format error

* fix: add a image caption tool

* fix: 修改一些提示。tool太多机器人开始混乱了

* fix: 一些极端的措施

* fix: 增加一些提示和一个暂时的公共接口

* fix: 收拾一下

* fix: 修改命令正则

* fix: 修改一些提示

* fix: move send avatar into send picture tool

* fix: 修复解除禁言的bug
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495
utils/openai/chatgpt-api.js Normal file
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var __assign = (this && this.__assign) || function () {
__assign = Object.assign || function(t) {
for (var s, i = 1, n = arguments.length; i < n; i++) {
s = arguments[i];
for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p))
t[p] = s[p];
}
return t;
};
return __assign.apply(this, arguments);
};
var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
return new (P || (P = Promise))(function (resolve, reject) {
function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
step((generator = generator.apply(thisArg, _arguments || [])).next());
});
};
var __generator = (this && this.__generator) || function (thisArg, body) {
var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;
return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
function verb(n) { return function (v) { return step([n, v]); }; }
function step(op) {
if (f) throw new TypeError("Generator is already executing.");
while (g && (g = 0, op[0] && (_ = 0)), _) try {
if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
if (y = 0, t) op = [op[0] & 2, t.value];
switch (op[0]) {
case 0: case 1: t = op; break;
case 4: _.label++; return { value: op[1], done: false };
case 5: _.label++; y = op[1]; op = [0]; continue;
case 7: op = _.ops.pop(); _.trys.pop(); continue;
default:
if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
if (t[2]) _.ops.pop();
_.trys.pop(); continue;
}
op = body.call(thisArg, _);
} catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
}
};
var __spreadArray = (this && this.__spreadArray) || function (to, from, pack) {
if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {
if (ar || !(i in from)) {
if (!ar) ar = Array.prototype.slice.call(from, 0, i);
ar[i] = from[i];
}
}
return to.concat(ar || Array.prototype.slice.call(from));
};
import Keyv from 'keyv';
import pTimeout from 'p-timeout';
import QuickLRU from 'quick-lru';
import { v4 as uuidv4 } from 'uuid';
import * as tokenizer from './tokenizer.js';
import * as types from './types.js';
import globalFetch from 'node-fetch';
import { fetchSSE } from './fetch-sse.js';
var CHATGPT_MODEL = 'gpt-3.5-turbo-0613';
var USER_LABEL_DEFAULT = 'User';
var ASSISTANT_LABEL_DEFAULT = 'ChatGPT';
var ChatGPTAPI = /** @class */ (function () {
/**
* Creates a new client wrapper around OpenAI's chat completion API, mimicing the official ChatGPT webapp's functionality as closely as possible.
*
* @param apiKey - OpenAI API key (required).
* @param apiOrg - Optional OpenAI API organization (optional).
* @param apiBaseUrl - Optional override for the OpenAI API base URL.
* @param debug - Optional enables logging debugging info to stdout.
* @param completionParams - Param overrides to send to the [OpenAI chat completion API](https://platform.openai.com/docs/api-reference/chat/create). Options like `temperature` and `presence_penalty` can be tweaked to change the personality of the assistant.
* @param maxModelTokens - Optional override for the maximum number of tokens allowed by the model's context. Defaults to 4096.
* @param maxResponseTokens - Optional override for the minimum number of tokens allowed for the model's response. Defaults to 1000.
* @param messageStore - Optional [Keyv](https://github.com/jaredwray/keyv) store to persist chat messages to. If not provided, messages will be lost when the process exits.
* @param getMessageById - Optional function to retrieve a message by its ID. If not provided, the default implementation will be used (using an in-memory `messageStore`).
* @param upsertMessage - Optional function to insert or update a message. If not provided, the default implementation will be used (using an in-memory `messageStore`).
* @param fetch - Optional override for the `fetch` implementation to use. Defaults to the global `fetch` function.
*/
function ChatGPTAPI(opts) {
var apiKey = opts.apiKey, apiOrg = opts.apiOrg, _a = opts.apiBaseUrl, apiBaseUrl = _a === void 0 ? 'https://api.openai.com/v1' : _a, _b = opts.debug, debug = _b === void 0 ? false : _b, messageStore = opts.messageStore, completionParams = opts.completionParams, systemMessage = opts.systemMessage, _c = opts.maxModelTokens, maxModelTokens = _c === void 0 ? 4000 : _c, _d = opts.maxResponseTokens, maxResponseTokens = _d === void 0 ? 1000 : _d, getMessageById = opts.getMessageById, upsertMessage = opts.upsertMessage, _e = opts.fetch, fetch = _e === void 0 ? globalFetch : _e;
this._apiKey = apiKey;
this._apiOrg = apiOrg;
this._apiBaseUrl = apiBaseUrl;
this._debug = !!debug;
this._fetch = fetch;
this._completionParams = __assign({ model: CHATGPT_MODEL, temperature: 0.8, top_p: 1.0, presence_penalty: 1.0 }, completionParams);
this._systemMessage = systemMessage;
if (this._systemMessage === undefined) {
var currentDate = new Date().toISOString().split('T')[0];
this._systemMessage = "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.\nKnowledge cutoff: 2021-09-01\nCurrent date: ".concat(currentDate);
}
this._maxModelTokens = maxModelTokens;
this._maxResponseTokens = maxResponseTokens;
this._getMessageById = getMessageById !== null && getMessageById !== void 0 ? getMessageById : this._defaultGetMessageById;
this._upsertMessage = upsertMessage !== null && upsertMessage !== void 0 ? upsertMessage : this._defaultUpsertMessage;
if (messageStore) {
this._messageStore = messageStore;
}
else {
this._messageStore = new Keyv({
store: new QuickLRU({ maxSize: 10000 })
});
}
if (!this._apiKey) {
throw new Error('OpenAI missing required apiKey');
}
if (!this._fetch) {
throw new Error('Invalid environment; fetch is not defined');
}
if (typeof this._fetch !== 'function') {
throw new Error('Invalid "fetch" is not a function');
}
}
/**
* Sends a message to the OpenAI chat completions endpoint, waits for the response
* to resolve, and returns the response.
*
* If you want your response to have historical context, you must provide a valid `parentMessageId`.
*
* If you want to receive a stream of partial responses, use `opts.onProgress`.
*
* Set `debug: true` in the `ChatGPTAPI` constructor to log more info on the full prompt sent to the OpenAI chat completions API. You can override the `systemMessage` in `opts` to customize the assistant's instructions.
*
* @param message - The prompt message to send
* @param opts.parentMessageId - Optional ID of the previous message in the conversation (defaults to `undefined`)
* @param opts.conversationId - Optional ID of the conversation (defaults to `undefined`)
* @param opts.messageId - Optional ID of the message to send (defaults to a random UUID)
* @param opts.systemMessage - Optional override for the chat "system message" which acts as instructions to the model (defaults to the ChatGPT system message)
* @param opts.timeoutMs - Optional timeout in milliseconds (defaults to no timeout)
* @param opts.onProgress - Optional callback which will be invoked every time the partial response is updated
* @param opts.abortSignal - Optional callback used to abort the underlying `fetch` call using an [AbortController](https://developer.mozilla.org/en-US/docs/Web/API/AbortController)
* @param completionParams - Optional overrides to send to the [OpenAI chat completion API](https://platform.openai.com/docs/api-reference/chat/create). Options like `temperature` and `presence_penalty` can be tweaked to change the personality of the assistant.
*
* @returns The response from ChatGPT
*/
ChatGPTAPI.prototype.sendMessage = function (text, opts, role) {
if (opts === void 0) { opts = {}; }
if (role === void 0) { role = 'user'; }
return __awaiter(this, void 0, void 0, function () {
var parentMessageId, _a, messageId, timeoutMs, onProgress, _b, stream, completionParams, conversationId, abortSignal, abortController, message, latestQuestion, _c, messages, maxTokens, numTokens, result, responseP;
var _this = this;
return __generator(this, function (_d) {
switch (_d.label) {
case 0:
parentMessageId = opts.parentMessageId, _a = opts.messageId, messageId = _a === void 0 ? uuidv4() : _a, timeoutMs = opts.timeoutMs, onProgress = opts.onProgress, _b = opts.stream, stream = _b === void 0 ? onProgress ? true : false : _b, completionParams = opts.completionParams, conversationId = opts.conversationId;
abortSignal = opts.abortSignal;
abortController = null;
if (timeoutMs && !abortSignal) {
abortController = new AbortController();
abortSignal = abortController.signal;
}
message = {
role: role,
id: messageId,
conversationId: conversationId,
parentMessageId: parentMessageId,
text: text,
name: opts.name
};
latestQuestion = message;
return [4 /*yield*/, this._buildMessages(text, role, opts)];
case 1:
_c = _d.sent(), messages = _c.messages, maxTokens = _c.maxTokens, numTokens = _c.numTokens;
result = {
role: 'assistant',
id: uuidv4(),
conversationId: conversationId,
parentMessageId: messageId,
text: '',
functionCall: null
};
responseP = new Promise(function (resolve, reject) { return __awaiter(_this, void 0, void 0, function () {
var url, headers, body, res, reason, msg, error, response, message_1, res_1, err_1;
var _a, _b;
return __generator(this, function (_c) {
switch (_c.label) {
case 0:
url = "".concat(this._apiBaseUrl, "/chat/completions");
headers = {
'Content-Type': 'application/json',
Authorization: "Bearer ".concat(this._apiKey)
};
body = __assign(__assign(__assign({ max_tokens: maxTokens }, this._completionParams), completionParams), { messages: messages, stream: stream });
// Support multiple organizations
// See https://platform.openai.com/docs/api-reference/authentication
if (this._apiOrg) {
headers['OpenAI-Organization'] = this._apiOrg;
}
if (this._debug) {
// console.log(JSON.stringify(body))
console.log("sendMessage (".concat(numTokens, " tokens)"), body);
}
if (!stream) return [3 /*break*/, 1];
fetchSSE(url, {
method: 'POST',
headers: headers,
body: JSON.stringify(body),
signal: abortSignal,
onMessage: function (data) {
var _a;
if (data === '[DONE]') {
result.text = result.text.trim();
return resolve(result);
}
try {
var response = JSON.parse(data);
if (response.id) {
result.id = response.id;
}
if ((_a = response.choices) === null || _a === void 0 ? void 0 : _a.length) {
var delta = response.choices[0].delta;
if (delta.function_call) {
if (delta.function_call.name) {
result.functionCall = {
name: delta.function_call.name,
arguments: delta.function_call.arguments
};
}
else {
result.functionCall.arguments = result.functionCall.arguments || '' + delta.function_call.arguments;
}
}
else {
result.delta = delta.content;
if (delta === null || delta === void 0 ? void 0 : delta.content)
result.text += delta.content;
}
if (delta.role) {
result.role = delta.role;
}
result.detail = response;
onProgress === null || onProgress === void 0 ? void 0 : onProgress(result);
}
}
catch (err) {
console.warn('OpenAI stream SEE event unexpected error', err);
return reject(err);
}
}
}, this._fetch).catch(reject);
return [3 /*break*/, 7];
case 1:
_c.trys.push([1, 6, , 7]);
return [4 /*yield*/, this._fetch(url, {
method: 'POST',
headers: headers,
body: JSON.stringify(body),
signal: abortSignal
})];
case 2:
res = _c.sent();
if (!!res.ok) return [3 /*break*/, 4];
return [4 /*yield*/, res.text()];
case 3:
reason = _c.sent();
msg = "OpenAI error ".concat(res.status || res.statusText, ": ").concat(reason);
error = new types.ChatGPTError(msg, { cause: res });
error.statusCode = res.status;
error.statusText = res.statusText;
return [2 /*return*/, reject(error)];
case 4: return [4 /*yield*/, res.json()];
case 5:
response = _c.sent();
if (this._debug) {
console.log(response);
}
if (response === null || response === void 0 ? void 0 : response.id) {
result.id = response.id;
}
if ((_a = response === null || response === void 0 ? void 0 : response.choices) === null || _a === void 0 ? void 0 : _a.length) {
message_1 = response.choices[0].message;
if (message_1.content) {
result.text = message_1.content;
}
else if (message_1.function_call) {
result.functionCall = message_1.function_call;
}
if (message_1.role) {
result.role = message_1.role;
}
}
else {
res_1 = response;
return [2 /*return*/, reject(new Error("OpenAI error: ".concat(((_b = res_1 === null || res_1 === void 0 ? void 0 : res_1.detail) === null || _b === void 0 ? void 0 : _b.message) || (res_1 === null || res_1 === void 0 ? void 0 : res_1.detail) || 'unknown')))];
}
result.detail = response;
return [2 /*return*/, resolve(result)];
case 6:
err_1 = _c.sent();
return [2 /*return*/, reject(err_1)];
case 7: return [2 /*return*/];
}
});
}); }).then(function (message) { return __awaiter(_this, void 0, void 0, function () {
var promptTokens, completionTokens, err_2;
return __generator(this, function (_a) {
switch (_a.label) {
case 0:
if (!(message.detail && !message.detail.usage)) return [3 /*break*/, 4];
_a.label = 1;
case 1:
_a.trys.push([1, 3, , 4]);
promptTokens = numTokens;
return [4 /*yield*/, this._getTokenCount(message.text)];
case 2:
completionTokens = _a.sent();
message.detail.usage = {
prompt_tokens: promptTokens,
completion_tokens: completionTokens,
total_tokens: promptTokens + completionTokens,
estimated: true
};
return [3 /*break*/, 4];
case 3:
err_2 = _a.sent();
return [3 /*break*/, 4];
case 4: return [2 /*return*/, Promise.all([
this._upsertMessage(latestQuestion),
this._upsertMessage(message)
]).then(function () { return message; })];
}
});
}); });
if (timeoutMs) {
if (abortController) {
// This will be called when a timeout occurs in order for us to forcibly
// ensure that the underlying HTTP request is aborted.
;
responseP.cancel = function () {
abortController.abort();
};
}
return [2 /*return*/, pTimeout(responseP, {
milliseconds: timeoutMs,
message: 'OpenAI timed out waiting for response'
})];
}
else {
return [2 /*return*/, responseP];
}
return [2 /*return*/];
}
});
});
};
Object.defineProperty(ChatGPTAPI.prototype, "apiKey", {
get: function () {
return this._apiKey;
},
set: function (apiKey) {
this._apiKey = apiKey;
},
enumerable: false,
configurable: true
});
Object.defineProperty(ChatGPTAPI.prototype, "apiOrg", {
get: function () {
return this._apiOrg;
},
set: function (apiOrg) {
this._apiOrg = apiOrg;
},
enumerable: false,
configurable: true
});
ChatGPTAPI.prototype._buildMessages = function (text, role, opts) {
return __awaiter(this, void 0, void 0, function () {
var _a, systemMessage, parentMessageId, userLabel, assistantLabel, maxNumTokens, messages, systemMessageOffset, nextMessages, numTokens, prompt_1, nextNumTokensEstimate, isValidPrompt, parentMessage, parentMessageRole, maxTokens;
return __generator(this, function (_b) {
switch (_b.label) {
case 0:
_a = opts.systemMessage, systemMessage = _a === void 0 ? this._systemMessage : _a;
parentMessageId = opts.parentMessageId;
userLabel = USER_LABEL_DEFAULT;
assistantLabel = ASSISTANT_LABEL_DEFAULT;
maxNumTokens = this._maxModelTokens - this._maxResponseTokens;
messages = [];
if (systemMessage) {
messages.push({
role: 'system',
content: systemMessage
});
}
systemMessageOffset = messages.length;
nextMessages = text
? messages.concat([
{
role: role,
content: text,
name: opts.name
}
])
: messages;
numTokens = 0;
_b.label = 1;
case 1:
prompt_1 = nextMessages
.reduce(function (prompt, message) {
switch (message.role) {
case 'system':
return prompt.concat(["Instructions:\n".concat(message.content)]);
case 'user':
return prompt.concat(["".concat(userLabel, ":\n").concat(message.content)]);
case 'function':
return prompt.concat(["Function:\n".concat(message.content)]);
default:
return message.content ? prompt.concat(["".concat(assistantLabel, ":\n").concat(message.content)]) : prompt;
}
}, [])
.join('\n\n');
return [4 /*yield*/, this._getTokenCount(prompt_1)];
case 2:
nextNumTokensEstimate = _b.sent();
isValidPrompt = nextNumTokensEstimate <= maxNumTokens;
if (prompt_1 && !isValidPrompt) {
return [3 /*break*/, 5];
}
messages = nextMessages;
numTokens = nextNumTokensEstimate;
if (!isValidPrompt) {
return [3 /*break*/, 5];
}
if (!parentMessageId) {
return [3 /*break*/, 5];
}
return [4 /*yield*/, this._getMessageById(parentMessageId)];
case 3:
parentMessage = _b.sent();
if (!parentMessage) {
return [3 /*break*/, 5];
}
parentMessageRole = parentMessage.role || 'user';
nextMessages = nextMessages.slice(0, systemMessageOffset).concat(__spreadArray([
{
role: parentMessageRole,
content: parentMessage.text,
name: parentMessage.name,
function_call: parentMessage.functionCall ? parentMessage.functionCall : undefined,
}
], nextMessages.slice(systemMessageOffset), true));
parentMessageId = parentMessage.parentMessageId;
_b.label = 4;
case 4:
if (true) return [3 /*break*/, 1];
_b.label = 5;
case 5:
maxTokens = Math.max(1, Math.min(this._maxModelTokens - numTokens, this._maxResponseTokens));
return [2 /*return*/, { messages: messages, maxTokens: maxTokens, numTokens: numTokens }];
}
});
});
};
ChatGPTAPI.prototype._getTokenCount = function (text) {
return __awaiter(this, void 0, void 0, function () {
return __generator(this, function (_a) {
// TODO: use a better fix in the tokenizer
text = text.replace(/<\|endoftext\|>/g, '');
return [2 /*return*/, tokenizer.encode(text).length];
});
});
};
ChatGPTAPI.prototype._defaultGetMessageById = function (id) {
return __awaiter(this, void 0, void 0, function () {
var res;
return __generator(this, function (_a) {
switch (_a.label) {
case 0: return [4 /*yield*/, this._messageStore.get(id)];
case 1:
res = _a.sent();
return [2 /*return*/, res];
}
});
});
};
ChatGPTAPI.prototype._defaultUpsertMessage = function (message) {
return __awaiter(this, void 0, void 0, function () {
return __generator(this, function (_a) {
switch (_a.label) {
case 0: return [4 /*yield*/, this._messageStore.set(message.id, message)];
case 1:
_a.sent();
return [2 /*return*/];
}
});
});
};
return ChatGPTAPI;
}());
export { ChatGPTAPI };

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import Keyv from 'keyv'
import pTimeout from 'p-timeout'
import QuickLRU from 'quick-lru'
import { v4 as uuidv4 } from 'uuid'
import * as tokenizer from './tokenizer'
import * as types from './types'
import globalFetch from 'node-fetch'
import { fetchSSE } from './fetch-sse'
import {Role} from "./types";
const CHATGPT_MODEL = 'gpt-3.5-turbo-0613'
const USER_LABEL_DEFAULT = 'User'
const ASSISTANT_LABEL_DEFAULT = 'ChatGPT'
export class ChatGPTAPI {
protected _apiKey: string
protected _apiBaseUrl: string
protected _apiOrg?: string
protected _debug: boolean
protected _systemMessage: string
protected _completionParams: Omit<
types.openai.CreateChatCompletionRequest,
'messages' | 'n'
>
protected _maxModelTokens: number
protected _maxResponseTokens: number
protected _fetch: types.FetchFn
protected _getMessageById: types.GetMessageByIdFunction
protected _upsertMessage: types.UpsertMessageFunction
protected _messageStore: Keyv<types.ChatMessage>
/**
* Creates a new client wrapper around OpenAI's chat completion API, mimicing the official ChatGPT webapp's functionality as closely as possible.
*
* @param apiKey - OpenAI API key (required).
* @param apiOrg - Optional OpenAI API organization (optional).
* @param apiBaseUrl - Optional override for the OpenAI API base URL.
* @param debug - Optional enables logging debugging info to stdout.
* @param completionParams - Param overrides to send to the [OpenAI chat completion API](https://platform.openai.com/docs/api-reference/chat/create). Options like `temperature` and `presence_penalty` can be tweaked to change the personality of the assistant.
* @param maxModelTokens - Optional override for the maximum number of tokens allowed by the model's context. Defaults to 4096.
* @param maxResponseTokens - Optional override for the minimum number of tokens allowed for the model's response. Defaults to 1000.
* @param messageStore - Optional [Keyv](https://github.com/jaredwray/keyv) store to persist chat messages to. If not provided, messages will be lost when the process exits.
* @param getMessageById - Optional function to retrieve a message by its ID. If not provided, the default implementation will be used (using an in-memory `messageStore`).
* @param upsertMessage - Optional function to insert or update a message. If not provided, the default implementation will be used (using an in-memory `messageStore`).
* @param fetch - Optional override for the `fetch` implementation to use. Defaults to the global `fetch` function.
*/
constructor(opts: types.ChatGPTAPIOptions) {
const {
apiKey,
apiOrg,
apiBaseUrl = 'https://api.openai.com/v1',
debug = false,
messageStore,
completionParams,
systemMessage,
maxModelTokens = 4000,
maxResponseTokens = 1000,
getMessageById,
upsertMessage,
fetch = globalFetch
} = opts
this._apiKey = apiKey
this._apiOrg = apiOrg
this._apiBaseUrl = apiBaseUrl
this._debug = !!debug
this._fetch = fetch
this._completionParams = {
model: CHATGPT_MODEL,
temperature: 0.8,
top_p: 1.0,
presence_penalty: 1.0,
...completionParams
}
this._systemMessage = systemMessage
if (this._systemMessage === undefined) {
const currentDate = new Date().toISOString().split('T')[0]
this._systemMessage = `You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.\nKnowledge cutoff: 2021-09-01\nCurrent date: ${currentDate}`
}
this._maxModelTokens = maxModelTokens
this._maxResponseTokens = maxResponseTokens
this._getMessageById = getMessageById ?? this._defaultGetMessageById
this._upsertMessage = upsertMessage ?? this._defaultUpsertMessage
if (messageStore) {
this._messageStore = messageStore
} else {
this._messageStore = new Keyv<types.ChatMessage, any>({
store: new QuickLRU<string, types.ChatMessage>({ maxSize: 10000 })
})
}
if (!this._apiKey) {
throw new Error('OpenAI missing required apiKey')
}
if (!this._fetch) {
throw new Error('Invalid environment; fetch is not defined')
}
if (typeof this._fetch !== 'function') {
throw new Error('Invalid "fetch" is not a function')
}
}
/**
* Sends a message to the OpenAI chat completions endpoint, waits for the response
* to resolve, and returns the response.
*
* If you want your response to have historical context, you must provide a valid `parentMessageId`.
*
* If you want to receive a stream of partial responses, use `opts.onProgress`.
*
* Set `debug: true` in the `ChatGPTAPI` constructor to log more info on the full prompt sent to the OpenAI chat completions API. You can override the `systemMessage` in `opts` to customize the assistant's instructions.
*
* @param message - The prompt message to send
* @param opts.parentMessageId - Optional ID of the previous message in the conversation (defaults to `undefined`)
* @param opts.conversationId - Optional ID of the conversation (defaults to `undefined`)
* @param opts.messageId - Optional ID of the message to send (defaults to a random UUID)
* @param opts.systemMessage - Optional override for the chat "system message" which acts as instructions to the model (defaults to the ChatGPT system message)
* @param opts.timeoutMs - Optional timeout in milliseconds (defaults to no timeout)
* @param opts.onProgress - Optional callback which will be invoked every time the partial response is updated
* @param opts.abortSignal - Optional callback used to abort the underlying `fetch` call using an [AbortController](https://developer.mozilla.org/en-US/docs/Web/API/AbortController)
* @param completionParams - Optional overrides to send to the [OpenAI chat completion API](https://platform.openai.com/docs/api-reference/chat/create). Options like `temperature` and `presence_penalty` can be tweaked to change the personality of the assistant.
*
* @returns The response from ChatGPT
*/
async sendMessage(
text: string,
opts: types.SendMessageOptions = {},
role: Role = 'user',
): Promise<types.ChatMessage> {
const {
parentMessageId,
messageId = uuidv4(),
timeoutMs,
onProgress,
stream = onProgress ? true : false,
completionParams,
conversationId
} = opts
let { abortSignal } = opts
let abortController: AbortController = null
if (timeoutMs && !abortSignal) {
abortController = new AbortController()
abortSignal = abortController.signal
}
const message: types.ChatMessage = {
role,
id: messageId,
conversationId,
parentMessageId,
text,
name: opts.name
}
const latestQuestion = message
const { messages, maxTokens, numTokens } = await this._buildMessages(
text,
role,
opts
)
const result: types.ChatMessage = {
role: 'assistant',
id: uuidv4(),
conversationId,
parentMessageId: messageId,
text: undefined,
functionCall: undefined
}
const responseP = new Promise<types.ChatMessage>(
async (resolve, reject) => {
const url = `${this._apiBaseUrl}/chat/completions`
const headers = {
'Content-Type': 'application/json',
Authorization: `Bearer ${this._apiKey}`
}
const body = {
max_tokens: maxTokens,
...this._completionParams,
...completionParams,
messages,
stream
}
// Support multiple organizations
// See https://platform.openai.com/docs/api-reference/authentication
if (this._apiOrg) {
headers['OpenAI-Organization'] = this._apiOrg
}
if (this._debug) {
console.log(`sendMessage (${numTokens} tokens)`, body)
}
if (stream) {
fetchSSE(
url,
{
method: 'POST',
headers,
body: JSON.stringify(body),
signal: abortSignal,
onMessage: (data: string) => {
if (data === '[DONE]') {
result.text = result.text.trim()
return resolve(result)
}
try {
const response: types.openai.CreateChatCompletionDeltaResponse =
JSON.parse(data)
if (response.id) {
result.id = response.id
}
if (response.choices?.length) {
const delta = response.choices[0].delta
if (delta.function_call) {
if (delta.function_call.name) {
result.functionCall = {
name: delta.function_call.name,
arguments: delta.function_call.arguments
}
} else {
result.functionCall.arguments = result.functionCall.arguments || '' + delta.function_call.arguments
}
} else {
result.delta = delta.content
if (delta?.content) result.text += delta.content
}
if (delta.role) {
result.role = delta.role
}
result.detail = response
onProgress?.(result)
}
} catch (err) {
console.warn('OpenAI stream SEE event unexpected error', err)
return reject(err)
}
}
},
this._fetch
).catch(reject)
} else {
try {
const res = await this._fetch(url, {
method: 'POST',
headers,
body: JSON.stringify(body),
signal: abortSignal
})
if (!res.ok) {
const reason = await res.text()
const msg = `OpenAI error ${
res.status || res.statusText
}: ${reason}`
const error = new types.ChatGPTError(msg, { cause: res })
error.statusCode = res.status
error.statusText = res.statusText
return reject(error)
}
const response: types.openai.CreateChatCompletionResponse =
await res.json()
if (this._debug) {
console.log(response)
}
if (response?.id) {
result.id = response.id
}
if (response?.choices?.length) {
const message = response.choices[0].message
if (message.content) {
result.text = message.content
} else if (message.function_call) {
result.functionCall = message.function_call
}
if (message.role) {
result.role = message.role
}
} else {
const res = response as any
return reject(
new Error(
`OpenAI error: ${
res?.detail?.message || res?.detail || 'unknown'
}`
)
)
}
result.detail = response
return resolve(result)
} catch (err) {
return reject(err)
}
}
}
).then(async (message) => {
if (message.detail && !message.detail.usage) {
try {
const promptTokens = numTokens
const completionTokens = await this._getTokenCount(message.text)
message.detail.usage = {
prompt_tokens: promptTokens,
completion_tokens: completionTokens,
total_tokens: promptTokens + completionTokens,
estimated: true
}
} catch (err) {
// TODO: this should really never happen, but if it does,
// we should handle notify the user gracefully
}
}
return Promise.all([
this._upsertMessage(latestQuestion),
this._upsertMessage(message)
]).then(() => message)
})
if (timeoutMs) {
if (abortController) {
// This will be called when a timeout occurs in order for us to forcibly
// ensure that the underlying HTTP request is aborted.
;(responseP as any).cancel = () => {
abortController.abort()
}
}
return pTimeout(responseP, {
milliseconds: timeoutMs,
message: 'OpenAI timed out waiting for response'
})
} else {
return responseP
}
}
get apiKey(): string {
return this._apiKey
}
set apiKey(apiKey: string) {
this._apiKey = apiKey
}
get apiOrg(): string {
return this._apiOrg
}
set apiOrg(apiOrg: string) {
this._apiOrg = apiOrg
}
protected async _buildMessages(text: string, role: Role, opts: types.SendMessageOptions) {
const { systemMessage = this._systemMessage } = opts
let { parentMessageId } = opts
const userLabel = USER_LABEL_DEFAULT
const assistantLabel = ASSISTANT_LABEL_DEFAULT
const maxNumTokens = this._maxModelTokens - this._maxResponseTokens
let messages: types.openai.ChatCompletionRequestMessage[] = []
if (systemMessage) {
messages.push({
role: 'system',
content: systemMessage
})
}
const systemMessageOffset = messages.length
let nextMessages = text
? messages.concat([
{
role,
content: text,
name: opts.name
}
])
: messages
let numTokens = 0
do {
const prompt = nextMessages
.reduce((prompt, message) => {
switch (message.role) {
case 'system':
return prompt.concat([`Instructions:\n${message.content}`])
case 'user':
return prompt.concat([`${userLabel}:\n${message.content}`])
case 'function':
return prompt.concat([`Function:\n${message.content}`])
default:
return message.content ? prompt.concat([`${assistantLabel}:\n${message.content}`]) : prompt
}
}, [] as string[])
.join('\n\n')
const nextNumTokensEstimate = await this._getTokenCount(prompt)
const isValidPrompt = nextNumTokensEstimate <= maxNumTokens
if (prompt && !isValidPrompt) {
break
}
messages = nextMessages
numTokens = nextNumTokensEstimate
if (!isValidPrompt) {
break
}
if (!parentMessageId) {
break
}
const parentMessage = await this._getMessageById(parentMessageId)
if (!parentMessage) {
break
}
const parentMessageRole = parentMessage.role || 'user'
nextMessages = nextMessages.slice(0, systemMessageOffset).concat([
{
role: parentMessageRole,
content: parentMessage.text,
name: parentMessage.name,
function_call: parentMessage.functionCall ? parentMessage.functionCall : undefined
},
...nextMessages.slice(systemMessageOffset)
])
parentMessageId = parentMessage.parentMessageId
} while (true)
// Use up to 4096 tokens (prompt + response), but try to leave 1000 tokens
// for the response.
const maxTokens = Math.max(
1,
Math.min(this._maxModelTokens - numTokens, this._maxResponseTokens)
)
return { messages, maxTokens, numTokens }
}
protected async _getTokenCount(text: string) {
// TODO: use a better fix in the tokenizer
text = text.replace(/<\|endoftext\|>/g, '')
return tokenizer.encode(text).length
}
protected async _defaultGetMessageById(
id: string
): Promise<types.ChatMessage> {
const res = await this._messageStore.get(id)
return res
}
protected async _defaultUpsertMessage(
message: types.ChatMessage
): Promise<void> {
await this._messageStore.set(message.id, message)
}
}

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var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
return new (P || (P = Promise))(function (resolve, reject) {
function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
step((generator = generator.apply(thisArg, _arguments || [])).next());
});
};
var __generator = (this && this.__generator) || function (thisArg, body) {
var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g;
return g = { next: verb(0), "throw": verb(1), "return": verb(2) }, typeof Symbol === "function" && (g[Symbol.iterator] = function() { return this; }), g;
function verb(n) { return function (v) { return step([n, v]); }; }
function step(op) {
if (f) throw new TypeError("Generator is already executing.");
while (g && (g = 0, op[0] && (_ = 0)), _) try {
if (f = 1, y && (t = op[0] & 2 ? y["return"] : op[0] ? y["throw"] || ((t = y["return"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;
if (y = 0, t) op = [op[0] & 2, t.value];
switch (op[0]) {
case 0: case 1: t = op; break;
case 4: _.label++; return { value: op[1], done: false };
case 5: _.label++; y = op[1]; op = [0]; continue;
case 7: op = _.ops.pop(); _.trys.pop(); continue;
default:
if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }
if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }
if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }
if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }
if (t[2]) _.ops.pop();
_.trys.pop(); continue;
}
op = body.call(thisArg, _);
} catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }
if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };
}
};
var __rest = (this && this.__rest) || function (s, e) {
var t = {};
for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
t[p] = s[p];
if (s != null && typeof Object.getOwnPropertySymbols === "function")
for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
t[p[i]] = s[p[i]];
}
return t;
};
var __asyncValues = (this && this.__asyncValues) || function (o) {
if (!Symbol.asyncIterator) throw new TypeError("Symbol.asyncIterator is not defined.");
var m = o[Symbol.asyncIterator], i;
return m ? m.call(o) : (o = typeof __values === "function" ? __values(o) : o[Symbol.iterator](), i = {}, verb("next"), verb("throw"), verb("return"), i[Symbol.asyncIterator] = function () { return this; }, i);
function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }
function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }
};
import { createParser } from 'eventsource-parser';
import * as types from './types.js';
import fetch from 'node-fetch';
import { streamAsyncIterable } from './stream-async-iterable.js';
export function fetchSSE(url, options, fetchFn) {
var _a, e_1, _b, _c;
if (fetchFn === void 0) { fetchFn = fetch; }
return __awaiter(this, void 0, void 0, function () {
var onMessage, onError, fetchOptions, res, reason, err_1, msg, error, parser, feed, body_1, _d, _e, _f, chunk, str, e_1_1;
return __generator(this, function (_g) {
switch (_g.label) {
case 0:
onMessage = options.onMessage, onError = options.onError, fetchOptions = __rest(options, ["onMessage", "onError"]);
return [4 /*yield*/, fetchFn(url, fetchOptions)];
case 1:
res = _g.sent();
if (!!res.ok) return [3 /*break*/, 6];
reason = void 0;
_g.label = 2;
case 2:
_g.trys.push([2, 4, , 5]);
return [4 /*yield*/, res.text()];
case 3:
reason = _g.sent();
return [3 /*break*/, 5];
case 4:
err_1 = _g.sent();
reason = res.statusText;
return [3 /*break*/, 5];
case 5:
msg = "ChatGPT error ".concat(res.status, ": ").concat(reason);
error = new types.ChatGPTError(msg, { cause: res });
error.statusCode = res.status;
error.statusText = res.statusText;
throw error;
case 6:
parser = createParser(function (event) {
if (event.type === 'event') {
onMessage(event.data);
}
});
feed = function (chunk) {
var _a;
var response = null;
try {
response = JSON.parse(chunk);
}
catch (_b) {
// ignore
}
if (((_a = response === null || response === void 0 ? void 0 : response.detail) === null || _a === void 0 ? void 0 : _a.type) === 'invalid_request_error') {
var msg = "ChatGPT error ".concat(response.detail.message, ": ").concat(response.detail.code, " (").concat(response.detail.type, ")");
var error = new types.ChatGPTError(msg, { cause: response });
error.statusCode = response.detail.code;
error.statusText = response.detail.message;
if (onError) {
onError(error);
}
else {
console.error(error);
}
// don't feed to the event parser
return;
}
parser.feed(chunk);
};
if (!!res.body.getReader) return [3 /*break*/, 7];
body_1 = res.body;
if (!body_1.on || !body_1.read) {
throw new types.ChatGPTError('unsupported "fetch" implementation');
}
body_1.on('readable', function () {
var chunk;
while (null !== (chunk = body_1.read())) {
feed(chunk.toString());
}
});
return [3 /*break*/, 18];
case 7:
_g.trys.push([7, 12, 13, 18]);
_d = true, _e = __asyncValues(streamAsyncIterable(res.body));
_g.label = 8;
case 8: return [4 /*yield*/, _e.next()];
case 9:
if (!(_f = _g.sent(), _a = _f.done, !_a)) return [3 /*break*/, 11];
_c = _f.value;
_d = false;
chunk = _c;
str = new TextDecoder().decode(chunk);
feed(str);
_g.label = 10;
case 10:
_d = true;
return [3 /*break*/, 8];
case 11: return [3 /*break*/, 18];
case 12:
e_1_1 = _g.sent();
e_1 = { error: e_1_1 };
return [3 /*break*/, 18];
case 13:
_g.trys.push([13, , 16, 17]);
if (!(!_d && !_a && (_b = _e.return))) return [3 /*break*/, 15];
return [4 /*yield*/, _b.call(_e)];
case 14:
_g.sent();
_g.label = 15;
case 15: return [3 /*break*/, 17];
case 16:
if (e_1) throw e_1.error;
return [7 /*endfinally*/];
case 17: return [7 /*endfinally*/];
case 18: return [2 /*return*/];
}
});
});
}

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import { createParser } from 'eventsource-parser'
import * as types from './types'
import { fetch as nodefetch } from 'node-fetch'
import { streamAsyncIterable } from './stream-async-iterable'
export async function fetchSSE(
url: string,
options: Parameters<typeof fetch>[1] & {
onMessage: (data: string) => void
onError?: (error: any) => void
},
fetch: types.FetchFn = nodefetch
) {
const { onMessage, onError, ...fetchOptions } = options
const res = await fetch(url, fetchOptions)
if (!res.ok) {
let reason: string
try {
reason = await res.text()
} catch (err) {
reason = res.statusText
}
const msg = `ChatGPT error ${res.status}: ${reason}`
const error = new types.ChatGPTError(msg, { cause: res })
error.statusCode = res.status
error.statusText = res.statusText
throw error
}
const parser = createParser((event) => {
if (event.type === 'event') {
onMessage(event.data)
}
})
// handle special response errors
const feed = (chunk: string) => {
let response = null
try {
response = JSON.parse(chunk)
} catch {
// ignore
}
if (response?.detail?.type === 'invalid_request_error') {
const msg = `ChatGPT error ${response.detail.message}: ${response.detail.code} (${response.detail.type})`
const error = new types.ChatGPTError(msg, { cause: response })
error.statusCode = response.detail.code
error.statusText = response.detail.message
if (onError) {
onError(error)
} else {
console.error(error)
}
// don't feed to the event parser
return
}
parser.feed(chunk)
}
if (!res.body.getReader) {
// Vercel polyfills `fetch` with `node-fetch`, which doesn't conform to
// web standards, so this is a workaround...
const body: NodeJS.ReadableStream = res.body as any
if (!body.on || !body.read) {
throw new types.ChatGPTError('unsupported "fetch" implementation')
}
body.on('readable', () => {
let chunk: string | Buffer
while (null !== (chunk = body.read())) {
feed(chunk.toString())
}
})
} else {
for await (const chunk of streamAsyncIterable(res.body)) {
const str = new TextDecoder().decode(chunk)
feed(str)
}
}
}

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export async function * streamAsyncIterable (stream) {
const reader = stream.getReader()
try {
while (true) {
const { done, value } = await reader.read()
if (done) {
return
}
yield value
}
} finally {
reader.releaseLock()
}
}

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import { getEncoding } from 'js-tiktoken';
// TODO: make this configurable
var tokenizer = getEncoding('cl100k_base');
export function encode(input) {
return new Uint32Array(tokenizer.encode(input));
}

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import { getEncoding } from 'js-tiktoken'
// TODO: make this configurable
const tokenizer = getEncoding('cl100k_base')
export function encode(input: string): Uint32Array {
return new Uint32Array(tokenizer.encode(input))
}

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{
"compilerOptions": {
"module": "es2020"
}
}

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var __extends = (this && this.__extends) || (function () {
var extendStatics = function (d, b) {
extendStatics = Object.setPrototypeOf ||
({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||
function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };
return extendStatics(d, b);
};
return function (d, b) {
if (typeof b !== "function" && b !== null)
throw new TypeError("Class extends value " + String(b) + " is not a constructor or null");
extendStatics(d, b);
function __() { this.constructor = d; }
d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());
};
})();
var ChatGPTError = /** @class */ (function (_super) {
__extends(ChatGPTError, _super);
function ChatGPTError() {
return _super !== null && _super.apply(this, arguments) || this;
}
return ChatGPTError;
}(Error));
export { ChatGPTError };
export var openai;
(function (openai) {
})(openai || (openai = {}));

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import Keyv from 'keyv'
export type Role = 'user' | 'assistant' | 'system' | 'function'
export type FetchFn = typeof fetch
export type ChatGPTAPIOptions = {
apiKey: string
/** @defaultValue `'https://api.openai.com'` **/
apiBaseUrl?: string
apiOrg?: string
/** @defaultValue `false` **/
debug?: boolean
completionParams?: Partial<
Omit<openai.CreateChatCompletionRequest, 'messages' | 'n' | 'stream'>
>
systemMessage?: string
/** @defaultValue `4096` **/
maxModelTokens?: number
/** @defaultValue `1000` **/
maxResponseTokens?: number
messageStore?: Keyv
getMessageById?: GetMessageByIdFunction
upsertMessage?: UpsertMessageFunction
fetch?: FetchFn
}
export type SendMessageOptions = {
/**
* function role name
*/
name?: string
parentMessageId?: string
conversationId?: string
messageId?: string
stream?: boolean
systemMessage?: string
timeoutMs?: number
onProgress?: (partialResponse: ChatMessage) => void
abortSignal?: AbortSignal
completionParams?: Partial<
Omit<openai.CreateChatCompletionRequest, 'messages' | 'n' | 'stream'>
>
}
export type MessageActionType = 'next' | 'variant'
export type SendMessageBrowserOptions = {
conversationId?: string
parentMessageId?: string
messageId?: string
action?: MessageActionType
timeoutMs?: number
onProgress?: (partialResponse: ChatMessage) => void
abortSignal?: AbortSignal
}
export interface ChatMessage {
id: string
text: string
role: Role
name?: string
delta?: string
detail?:
| openai.CreateChatCompletionResponse
| CreateChatCompletionStreamResponse
// relevant for both ChatGPTAPI and ChatGPTUnofficialProxyAPI
parentMessageId?: string
// only relevant for ChatGPTUnofficialProxyAPI (optional for ChatGPTAPI)
conversationId?: string
functionCall?: openai.FunctionCall
}
export class ChatGPTError extends Error {
statusCode?: number
statusText?: string
isFinal?: boolean
accountId?: string
}
/** Returns a chat message from a store by it's ID (or null if not found). */
export type GetMessageByIdFunction = (id: string) => Promise<ChatMessage>
/** Upserts a chat message to a store. */
export type UpsertMessageFunction = (message: ChatMessage) => Promise<void>
export interface CreateChatCompletionStreamResponse
extends openai.CreateChatCompletionDeltaResponse {
usage: CreateCompletionStreamResponseUsage
}
export interface CreateCompletionStreamResponseUsage
extends openai.CreateCompletionResponseUsage {
estimated: true
}
/**
* https://chat.openapi.com/backend-api/conversation
*/
export type ConversationJSONBody = {
/**
* The action to take
*/
action: string
/**
* The ID of the conversation
*/
conversation_id?: string
/**
* Prompts to provide
*/
messages: Prompt[]
/**
* The model to use
*/
model: string
/**
* The parent message ID
*/
parent_message_id: string
}
export type Prompt = {
/**
* The content of the prompt
*/
content: PromptContent
/**
* The ID of the prompt
*/
id: string
/**
* The role played in the prompt
*/
role: Role
}
export type ContentType = 'text'
export type PromptContent = {
/**
* The content type of the prompt
*/
content_type: ContentType
/**
* The parts to the prompt
*/
parts: string[]
}
export type ConversationResponseEvent = {
message?: Message
conversation_id?: string
error?: string | null
}
export type Message = {
id: string
content: MessageContent
role: Role
user: string | null
create_time: string | null
update_time: string | null
end_turn: null
weight: number
recipient: string
metadata: MessageMetadata
}
export type MessageContent = {
content_type: string
parts: string[]
}
export type MessageMetadata = any
export namespace openai {
export interface CreateChatCompletionDeltaResponse {
id: string
object: 'chat.completion.chunk'
created: number
model: string
choices: [
{
delta: {
role: Role
content?: string,
function_call?: {name: string, arguments: string}
}
index: number
finish_reason: string | null
}
]
}
/**
*
* @export
* @interface ChatCompletionRequestMessage
*/
export interface ChatCompletionRequestMessage {
/**
* The role of the author of this message.
* @type {string}
* @memberof ChatCompletionRequestMessage
*/
role: ChatCompletionRequestMessageRoleEnum
/**
* The contents of the message
* @type {string}
* @memberof ChatCompletionRequestMessage
*/
content: string
/**
* The name of the user in a multi-user chat
* @type {string}
* @memberof ChatCompletionRequestMessage
*/
name?: string
function_call?: FunctionCall
}
export interface FunctionCall {
name: string
arguments: string
}
export declare const ChatCompletionRequestMessageRoleEnum: {
readonly System: 'system'
readonly User: 'user'
readonly Assistant: 'assistant'
readonly Function: 'function'
}
export declare type ChatCompletionRequestMessageRoleEnum =
(typeof ChatCompletionRequestMessageRoleEnum)[keyof typeof ChatCompletionRequestMessageRoleEnum]
/**
*
* @export
* @interface ChatCompletionResponseMessage
*/
export interface ChatCompletionResponseMessage {
/**
* The role of the author of this message.
* @type {string}
* @memberof ChatCompletionResponseMessage
*/
role: ChatCompletionResponseMessageRoleEnum
/**
* The contents of the message
* @type {string}
* @memberof ChatCompletionResponseMessage
*/
content: string
function_call: FunctionCall
}
export declare const ChatCompletionResponseMessageRoleEnum: {
readonly System: 'system'
readonly User: 'user'
readonly Assistant: 'assistant'
}
export declare type ChatCompletionResponseMessageRoleEnum =
(typeof ChatCompletionResponseMessageRoleEnum)[keyof typeof ChatCompletionResponseMessageRoleEnum]
/**
*
* @export
* @interface CreateChatCompletionRequest
*/
export interface CreateChatCompletionRequest {
/**
* ID of the model to use. Currently, only `gpt-3.5-turbo` and `gpt-3.5-turbo-0301` are supported.
* @type {string}
* @memberof CreateChatCompletionRequest
*/
model: string
/**
* The messages to generate chat completions for, in the [chat format](/docs/guides/chat/introduction).
* @type {Array<ChatCompletionRequestMessage>}
* @memberof CreateChatCompletionRequest
*/
messages: Array<ChatCompletionRequestMessage>
/**
* 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.
* @type {number}
* @memberof CreateChatCompletionRequest
*/
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.
* @type {number}
* @memberof CreateChatCompletionRequest
*/
top_p?: number | null
/**
* How many chat completion choices to generate for each input message.
* @type {number}
* @memberof CreateChatCompletionRequest
*/
n?: number | 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.
* @type {boolean}
* @memberof CreateChatCompletionRequest
*/
stream?: boolean | null
/**
*
* @type {CreateChatCompletionRequestStop}
* @memberof CreateChatCompletionRequest
*/
stop?: CreateChatCompletionRequestStop
/**
* The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens).
* @type {number}
* @memberof CreateChatCompletionRequest
*/
max_tokens?: number
/**
* 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)
* @type {number}
* @memberof CreateChatCompletionRequest
*/
presence_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)
* @type {number}
* @memberof CreateChatCompletionRequest
*/
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 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.
* @type {object}
* @memberof CreateChatCompletionRequest
*/
logit_bias?: object | 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).
* @type {string}
* @memberof CreateChatCompletionRequest
*/
user?: string
functions?: Function[]
}
export interface Function {
name: string
description: string
parameters: FunctionParameters
}
export interface FunctionParameters {
type: string
properties: Record<string, Record<string, any>>
required: string[]
}
/**
* @type CreateChatCompletionRequestStop
* Up to 4 sequences where the API will stop generating further tokens.
* @export
*/
export declare type CreateChatCompletionRequestStop = Array<string> | string
/**
*
* @export
* @interface CreateChatCompletionResponse
*/
export interface CreateChatCompletionResponse {
/**
*
* @type {string}
* @memberof CreateChatCompletionResponse
*/
id: string
/**
*
* @type {string}
* @memberof CreateChatCompletionResponse
*/
object: string
/**
*
* @type {number}
* @memberof CreateChatCompletionResponse
*/
created: number
/**
*
* @type {string}
* @memberof CreateChatCompletionResponse
*/
model: string
/**
*
* @type {Array<CreateChatCompletionResponseChoicesInner>}
* @memberof CreateChatCompletionResponse
*/
choices: Array<CreateChatCompletionResponseChoicesInner>
/**
*
* @type {CreateCompletionResponseUsage}
* @memberof CreateChatCompletionResponse
*/
usage?: CreateCompletionResponseUsage
}
/**
*
* @export
* @interface CreateChatCompletionResponseChoicesInner
*/
export interface CreateChatCompletionResponseChoicesInner {
/**
*
* @type {number}
* @memberof CreateChatCompletionResponseChoicesInner
*/
index?: number
/**
*
* @type {ChatCompletionResponseMessage}
* @memberof CreateChatCompletionResponseChoicesInner
*/
message?: ChatCompletionResponseMessage
/**
*
* @type {string}
* @memberof CreateChatCompletionResponseChoicesInner
*/
finish_reason?: string
}
/**
*
* @export
* @interface CreateCompletionResponseUsage
*/
export interface CreateCompletionResponseUsage {
/**
*
* @type {number}
* @memberof CreateCompletionResponseUsage
*/
prompt_tokens: number
/**
*
* @type {number}
* @memberof CreateCompletionResponseUsage
*/
completion_tokens: number
/**
*
* @type {number}
* @memberof CreateCompletionResponseUsage
*/
total_tokens: number
}
}