feat(openai): add chat streaming and model commands
- add /openai (/chatgpt) chat command using OpenAI Responses API (streaming + incremental edits) - add /openAIListModels, /openAIGetModel, /openAISetModel - introduce base Command class and migrate non-chat commands to it - wire OpenAI client + env vars (OPENAI_API_KEY, OPENAI_MODEL) - bump deps (@google/genai, systeminformation, @types/node) and add openai
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@@ -0,0 +1,160 @@
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import {Message} from "typescript-telegram-bot-api";
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import {MessageStore} from "../common/message-store";
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import {
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collectReplyChainText,
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escapeMarkdownV2Text,
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logError,
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replyToMessage,
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startIntervalEditor
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} from "../util/utils";
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import {Environment} from "../common/environment";
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import {bot, openAi} from "../index";
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import {Requirements} from "../base/requirements";
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import {Requirement} from "../base/requirement";
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import {ChatCommand} from "../base/chat-command";
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export class OpenAIChat extends ChatCommand {
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command = ["openai", "chatgpt"];
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argsMode = "required" as const;
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requirements = Requirements.Build(Requirement.BOT_CREATOR);
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async execute(msg: Message, match?: RegExpExecArray): Promise<void> {
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console.log("OpenAI Chat: ", match);
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return this.executeOpenAI(msg, match?.[3]);
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}
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async executeOpenAI(msg: Message, text: string): Promise<void> {
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if (!text || text.trim().length === 0) return;
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const chatId = msg.chat.id;
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const storedMsg = await MessageStore.get(chatId, msg.message_id);
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const messageParts = await collectReplyChainText(storedMsg);
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console.log("MESSAGE PARTS", messageParts);
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const chatMessages = messageParts.map(part => {
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const content = [];
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content.push({
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type: "input_text",
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text: (Environment.USE_NAMES_IN_PROMPT && !part.bot ? `MESSAGE FROM USER "${part.name}":\n` : "") + part.content,
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});
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// TODO: 03/02/2026, Danil Nikolaev: upload file then add here
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// for (const image of part.images) {
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// content.push({
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// type: "image_url",
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// imageUrl: "data:image/jpeg;base64," + image
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// });
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// }
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return {
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role: part.bot ? "assistant" : "user",
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content: content,
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type: "message",
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};
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});
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chatMessages.reverse();
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chatMessages.unshift({
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role: "system",
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content: [{type: "input_text", text: Environment.SYSTEM_PROMPT}],
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type: "message"
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});
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let waitMessage: Message;
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const startTime = Date.now();
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try {
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waitMessage = await bot.sendMessage({
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chat_id: chatId,
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text: Environment.waitText,
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reply_parameters: {
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chat_id: chatId,
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message_id: msg.message_id
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}
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});
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const stream = await openAi.responses.create({
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model: Environment.OPENAI_MODEL,
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// eslint-disable-next-line @typescript-eslint/no-explicit-any
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input: chatMessages as any,
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stream: true
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});
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let currentText = "";
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let shouldBreak = false;
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const editor = startIntervalEditor({
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intervalMs: 4500,
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getText: () => currentText,
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editFn: async (text) => {
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await bot.editMessageText(
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{
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chat_id: chatId,
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message_id: waitMessage.message_id,
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text: escapeMarkdownV2Text(text),
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parse_mode: "Markdown"
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}
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).catch(logError);
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console.log("editMessageText", text);
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waitMessage.reply_to_message = msg;
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waitMessage.text = text;
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await MessageStore.put(waitMessage);
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},
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onStop: async () => {
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}
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});
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await editor.tick();
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try {
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for await (const chunk of stream) {
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console.log("chunk", chunk);
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if (chunk.type === "response.output_text.delta") {
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const text = chunk.delta;
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currentText += text;
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if (currentText.length > 4096) {
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currentText = currentText.slice(0, 4093) + "...";
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shouldBreak = true;
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}
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console.log("messageText", currentText);
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console.log("length", currentText.length);
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if (shouldBreak) {
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console.log("break", true);
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break;
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}
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}
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}
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} finally {
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await editor.tick();
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await editor.stop();
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if (!shouldBreak) {
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console.log("ended", true);
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}
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const diff = Math.abs(Date.now() - startTime) / 1000.0;
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console.log("time", diff);
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waitMessage.reply_to_message = msg;
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waitMessage.text = currentText;
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await MessageStore.put(waitMessage);
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await replyToMessage({message: waitMessage, text: `⏱️ ${diff}s`});
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}
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} catch (error) {
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logError(error);
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await replyToMessage({
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message: waitMessage,
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text: `Произошла ошибка!\n${error.toString()}`
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}).catch(logError);
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}
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}
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}
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