* docs: add ai documentation * docker: update docker files for ai/regular versions, lint * feat: add initial /ask command * Delete docker-compose.yml * docker: ignore ollama folder in builds * fix: add emojis to help commands, capitalize, add ai commands to help menu * feat: add better logging, thought handling improvements * bug fixes, better logging and seperation of ai, update docs for ai * clean, remove prompt and user info from logs, more docs edits * system prompt change (plaintext only), parse out /think * clean up, axios tweaks * cleanup, logging of ratelimit --------- Co-authored-by: Aidan <aidan@p0ntus.com>
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Lucas Gabriel
GitHub
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13 changed files with 733 additions and 35 deletions
287
src/commands/ai.ts
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287
src/commands/ai.ts
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// AI.TS
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// by ihatenodejs/Aidan
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//
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// -----------------------------------------------------------------------
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//
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// This is free and unencumbered software released into the public domain.
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//
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// Anyone is free to copy, modify, publish, use, compile, sell, or
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// distribute this software, either in source code form or as a compiled
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// binary, for any purpose, commercial or non-commercial, and by any
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// means.
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//
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// In jurisdictions that recognize copyright laws, the author or authors
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// of this software dedicate any and all copyright interest in the
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// software to the public domain. We make this dedication for the benefit
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// of the public at large and to the detriment of our heirs and
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// successors. We intend this dedication to be an overt act of
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// relinquishment in perpetuity of all present and future rights to this
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// software under copyright law.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
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// MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
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// IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
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// OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
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// ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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//
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// For more information, please refer to <https://unlicense.org/>
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import { isOnSpamWatch } from "../spamwatch/spamwatch"
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import spamwatchMiddlewareModule from "../spamwatch/Middleware"
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import { Telegraf, Context } from "telegraf"
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import type { Message } from "telegraf/types"
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import { replyToMessageId } from "../utils/reply-to-message-id"
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import { getStrings } from "../plugins/checklang"
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import { languageCode } from "../utils/language-code"
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import axios from "axios"
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import { rateLimiter } from "../utils/rate-limiter"
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import { logger } from "../utils/log"
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const spamwatchMiddleware = spamwatchMiddlewareModule(isOnSpamWatch)
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export const flash_model = "gemma3:4b"
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export const thinking_model = "deepseek-r1:1.5b"
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type TextContext = Context & { message: Message.TextMessage }
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export function sanitizeForJson(text: string): string {
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return text
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.replace(/\\/g, '\\\\')
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.replace(/"/g, '\\"')
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.replace(/\n/g, '\\n')
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.replace(/\r/g, '\\r')
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.replace(/\t/g, '\\t')
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}
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export async function preChecks() {
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const envs = [
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"ollamaApi",
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]
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for (const env of envs) {
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if (!process.env[env]) {
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console.error(`[✨ AI | !] ❌ ${env} not set!`)
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return false
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}
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}
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console.log("[✨ AI] Pre-checks passed\n")
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return true
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}
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async function getResponse(prompt: string, ctx: TextContext, replyGenerating: Message, model: string) {
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const Strings = getStrings(languageCode(ctx))
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if (!ctx.chat) {
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return {
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success: false,
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error: Strings.unexpectedErr.replace("{error}", "No chat found"),
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}
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}
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try {
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const aiResponse = await axios.post(
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`${process.env.ollamaApi}/api/generate`,
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{
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model,
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prompt,
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stream: true,
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},
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{
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responseType: "stream",
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}
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)
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let fullResponse = ""
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let thoughts = ""
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let lastUpdate = Date.now()
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const stream = aiResponse.data
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for await (const chunk of stream) {
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const lines = chunk.toString().split('\n')
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for (const line of lines) {
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if (!line.trim()) continue
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let ln
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try {
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ln = JSON.parse(line)
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} catch (e) {
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console.error("[✨ AI | !] Error parsing chunk:", e)
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continue
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}
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if (model === thinking_model) {
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if (ln.response.includes('<think>')) {
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const thinkMatch = ln.response.match(/<think>([\s\S]*?)<\/think>/)
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if (thinkMatch && thinkMatch[1].trim().length > 0) {
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logger.logThinking(ctx.chat.id, replyGenerating.message_id, true)
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} else if (!thinkMatch) {
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logger.logThinking(ctx.chat.id, replyGenerating.message_id, true)
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}
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} else if (ln.response.includes('</think>')) {
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logger.logThinking(ctx.chat.id, replyGenerating.message_id, false)
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}
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}
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const now = Date.now()
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if (ln.response) {
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if (model === thinking_model) {
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let patchedThoughts = ln.response
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const thinkTagRx = /<think>([\s\S]*?)<\/think>/g
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patchedThoughts = patchedThoughts.replace(thinkTagRx, (match, p1) => p1.trim().length > 0 ? '`Thinking...`' + p1 + '`Finished thinking`' : '')
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patchedThoughts = patchedThoughts.replace(/<think>/g, '`Thinking...`')
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patchedThoughts = patchedThoughts.replace(/<\/think>/g, '`Finished thinking`')
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thoughts += patchedThoughts
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fullResponse += patchedThoughts
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} else {
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fullResponse += ln.response
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}
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if (now - lastUpdate >= 1000) {
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await rateLimiter.editMessageWithRetry(
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ctx,
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ctx.chat.id,
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replyGenerating.message_id,
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thoughts,
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{ parse_mode: 'Markdown' }
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)
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lastUpdate = now
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}
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}
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}
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}
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return {
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success: true,
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response: fullResponse,
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}
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} catch (error: any) {
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let shouldPullModel = false
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if (error.response) {
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const errData = error.response.data?.error
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const errStatus = error.response.status
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if (errData && (errData.includes(`model '${model}' not found`) || errStatus === 404)) {
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shouldPullModel = true
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} else {
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console.error("[✨ AI | !] Error zone 1:", errData)
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return { success: false, error: errData }
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}
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} else if (error.request) {
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console.error("[✨ AI | !] No response received:", error.request)
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return { success: false, error: "No response received from server" }
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} else {
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console.error("[✨ AI | !] Error zone 3:", error.message)
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return { success: false, error: error.message }
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}
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if (shouldPullModel) {
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ctx.telegram.editMessageText(ctx.chat.id, replyGenerating.message_id, undefined, `🔄 Pulling ${model} from ollama...\n\nThis may take a few minutes...`)
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console.log(`[✨ AI | i] Pulling ${model} from ollama...`)
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try {
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await axios.post(
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`${process.env.ollamaApi}/api/pull`,
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{
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model,
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stream: false,
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timeout: process.env.ollamaApiTimeout || 10000,
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}
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)
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} catch (e: any) {
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if (e.response) {
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console.error("[✨ AI | !] Something went wrong:", e.response.data?.error)
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return {
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success: false,
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error: `❌ Something went wrong while pulling ${model}, please try your command again!`,
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}
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} else if (e.request) {
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console.error("[✨ AI | !] No response received while pulling:", e.request)
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return {
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success: false,
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error: `❌ No response received while pulling ${model}, please try again!`,
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}
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} else {
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console.error("[✨ AI | !] Error while pulling:", e.message)
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return {
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success: false,
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error: `❌ Error while pulling ${model}: ${e.message}`,
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}
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}
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}
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console.log(`[✨ AI | i] ${model} pulled successfully`)
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return {
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success: true,
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response: `✅ Pulled ${model} successfully, please retry the command.`,
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}
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}
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}
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}
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export default (bot: Telegraf<Context>) => {
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const botName = bot.botInfo?.first_name && bot.botInfo?.last_name ? `${bot.botInfo.first_name} ${bot.botInfo.last_name}` : "Kowalski"
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bot.command(["ask", "think"], spamwatchMiddleware, async (ctx) => {
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if (!ctx.message || !('text' in ctx.message)) return
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const isAsk = ctx.message.text.startsWith("/ask")
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const model = isAsk ? flash_model : thinking_model
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const textCtx = ctx as TextContext
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const reply_to_message_id = replyToMessageId(textCtx)
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const Strings = getStrings(languageCode(textCtx))
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const message = textCtx.message.text
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const author = ("@" + ctx.from?.username) || ctx.from?.first_name
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logger.logCmdStart(author, model === flash_model ? "ask" : "think")
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if (!process.env.ollamaApi) {
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await ctx.reply(Strings.aiDisabled, {
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parse_mode: 'Markdown',
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...({ reply_to_message_id })
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})
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return
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}
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const replyGenerating = await ctx.reply(Strings.askGenerating.replace("{model}", model), {
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parse_mode: 'Markdown',
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...({ reply_to_message_id })
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})
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const fixedMsg = message.replace(/\/(ask|think) /, "")
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if (fixedMsg.length < 1) {
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await ctx.reply(Strings.askNoMessage, {
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parse_mode: 'Markdown',
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...({ reply_to_message_id })
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})
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return
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}
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logger.logPrompt(fixedMsg)
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const prompt = sanitizeForJson(
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`You are a plaintext-only, helpful assistant called ${botName}.
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Current Date/Time (UTC): ${new Date().toLocaleString()}
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---
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Respond to the user's message:
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${fixedMsg}`)
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const aiResponse = await getResponse(prompt, textCtx, replyGenerating, model)
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if (!aiResponse) return
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if (!ctx.chat) return
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if (aiResponse.success && aiResponse.response) {
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await rateLimiter.editMessageWithRetry(
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ctx,
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ctx.chat.id,
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replyGenerating.message_id,
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aiResponse.response,
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{ parse_mode: 'Markdown' }
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)
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return
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}
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const error = Strings.unexpectedErr.replace("{error}", aiResponse.error)
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await rateLimiter.editMessageWithRetry(
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ctx,
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ctx.chat.id,
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replyGenerating.message_id,
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error,
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{ parse_mode: 'Markdown' }
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)
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})
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}
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