Assistant Telegram intelligent

• •Informations de connexion à la base de données PostgreSQL
• •Token Bot Telegram
• •Clé API Google Gemini

{
  "meta": {
    "instanceId": "50be75eaab016244f302e16f06394e6613d664bfc61e8cd41452474a0de6a3ee",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "fccc9f50-71fa-4e25-9b15-8fd540ddc2fa",
      "name": "Sélecteur de Modèle",
      "type": "@n8n/n8n-nodes-langchain.modelSelector",
      "position": [
        800,
        1536
      ],
      "parameters": {
        "rules": {
          "rule": [
            {
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "976d83bb-7e9e-4aab-9722-25a9e238164f",
                    "operator": {
                      "type": "number",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $json.output.difficulty }}",
                    "rightValue": 1
                  }
                ]
              }
            },
            {
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "1e68688d-73fe-47c1-9b35-a1e226220bcd",
                    "operator": {
                      "type": "number",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $json.output.difficulty }}",
                    "rightValue": 2
                  }
                ]
              },
              "modelIndex": 2
            },
            {
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "61d58197-db59-4cd7-bc41-bbeaf5e7b069",
                    "operator": {
                      "type": "number",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $json.output.difficulty }}",
                    "rightValue": 3
                  }
                ]
              },
              "modelIndex": 3
            }
          ]
        },
        "numberInputs": 3
      },
      "typeVersion": 1
    },
    {
      "id": "cf5b2ea0-78c5-47bf-a3c1-4c59c9a32f76",
      "name": "Analyseur de Sortie Structurée",
      "type": "@n8n/n8n-nodes-langchain.outputParserStructured",
      "position": [
        336,
        1504
      ],
      "parameters": {
        "schemaType": "manual",
        "inputSchema": "{\n  \"type\": \"object\",\n  \"properties\": {\n    \"difficulty\": {\n      \"type\": \"integer\",\n      \"enum\": [1, 2, 3]\n    },\n    \"context\": {\n      \"type\": \"string\"\n    }\n  },\n  \"required\": [\"difficulty\", \"context\"]\n}\n"
      },
      "typeVersion": 1.3
    },
    {
      "id": "3a60caa7-eb1a-4bbd-88fc-55d7a3ffae29",
      "name": "Gemini 2.5 Flash Lite",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        720,
        1728
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.5-flash-lite"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "to92mdfNe3L6sBae",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "412d35ed-cd49-4d20-b425-2f556ef175b1",
      "name": "Gemini 2.5 Flash",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        880,
        1728
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "googlePalmApi": {
          "id": "to92mdfNe3L6sBae",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "2cc40e2c-a2be-435e-8540-9235efc41e08",
      "name": "Gemini 2.5 Pro",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        1024,
        1728
      ],
      "parameters": {
        "options": {},
        "modelName": "models/gemini-2.5-pro"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "to92mdfNe3L6sBae",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "35f56404-6998-4952-a7f3-8716712bf96a",
      "name": "Obtenir la Mémoire de Chat",
      "type": "n8n-nodes-base.postgres",
      "onError": "continueRegularOutput",
      "position": [
        -256,
        1328
      ],
      "parameters": {
        "limit": 25,
        "table": {
          "__rl": true,
          "mode": "list",
          "value": "chat_memory",
          "cachedResultName": "chat_memory"
        },
        "schema": {
          "__rl": true,
          "mode": "list",
          "value": "public"
        },
        "options": {},
        "operation": "select"
      },
      "credentials": {
        "postgres": {
          "id": "eQR2NFRag48wov9g",
          "name": "Postgres account"
        }
      },
      "typeVersion": 2.6,
      "alwaysOutputData": true
    },
    {
      "id": "5e6058bc-a3b8-4827-954e-85e3a000a986",
      "name": "MarkdownV2",
      "type": "n8n-nodes-base.code",
      "position": [
        1136,
        1264
      ],
      "parameters": {
        "jsCode": "/**\n * MarkdownV2-safe formatter + auto-chunker for Telegram (n8n Code node)\n * --------------------------------------------------------------------\n * - Allows: *bold*, _italic_, ||spoiler||, [label](url)\n * - Escapes everything else for Telegram MarkdownV2\n * - Validates/normalizes URLs\n * - Converts \"# Heading\" lines to bold titles\n * - Splits long messages into <= 4096-char chunks (uses a 4000-char budget)\n * - Outputs one item per chunk so the Telegram node sends all parts\n *\n * Recommended: Run this node in \"Run Once for All Items\".\n */\n\nconst MAX_TELEGRAM = 4096;\nconst SAFE_BUDGET = 4000; // small margin to avoid edge overflows\n\n// ============ MarkdownV2 helpers ============\nfunction escapeMarkdownV2(text) {\n  if (!text) return '';\n  return String(text).replace(/([\\\\_*[\\]()~`>#+\\-=|{}.!])/g, '\\\\$1');\n}\n\nfunction escapeForUrl(url) {\n  return String(url).replace(/[)\\\\]/g, '\\\\$&');\n}\n\nfunction normalizeAndValidateUrl(url) {\n  let raw = String(url || '').trim();\n  try {\n    const u = new URL(raw);\n    return u.toString();\n  } catch {}\n  // Try https:// for bare domains\n  const domainLike = /^[a-z0-9.-]+\\.[a-z]{2,}([/:?#].*)?$/i.test(raw);\n  if (domainLike) {\n    try {\n      const u2 = new URL('https://' + raw);\n      return u2.toString();\n    } catch {}\n  }\n  return null;\n}\n\nfunction normalizeHeadings(text) {\n  // Turn \"# Title\" → \"*Title*\"\n  return text.replace(/^(#{1,6})\\s+(.*)$/gm, (m, hashes, title) => `*${title.trim()}*`);\n}\n\nfunction normalizeCommonMd(text) {\n  return String(text)\n    .replace(/\\*\\*([\\s\\S]*?)\\*\\*/g, '*$1*') // **bold** → *bold*\n    .replace(/__([\\s\\S]*?)__/g, '_$1_');    // __italic__ → _italic_\n}\n\n/**\n * Convert incoming text to Telegram-safe MarkdownV2.\n */\nfunction processMarkdownV2Safe(inputText) {\n  if (!inputText) return '';\n\n  let text = normalizeCommonMd(String(inputText));\n  text = normalizeHeadings(text);\n\n  const placeholders = { links: [], bolds: [], italics: [], spoilers: [] };\n\n  // Links: keep safe via placeholders during escaping\n  text = text.replace(/\\[([^\\]\\n]+)\\]\\(([^)]+)\\)/g, (m, label, url) => {\n    const normalizedUrl = normalizeAndValidateUrl(url);\n    if (!normalizedUrl) return escapeMarkdownV2(label);\n    const idx = placeholders.links.length;\n    const ph = `⟬L${idx}⟭`;\n    const safeLabel = escapeMarkdownV2(label);\n    const safeUrl = escapeForUrl(normalizedUrl);\n    placeholders.links.push(`[${safeLabel}](${safeUrl})`);\n    return ph;\n  });\n\n  // Bold\n  text = text.replace(/\\*([\\s\\S]+?)\\*/g, (m, inner) => {\n    const idx = placeholders.bolds.length;\n    const ph = `⟬B${idx}⟭`;\n    placeholders.bolds.push(`*${escapeMarkdownV2(inner)}*`);\n    return ph;\n  });\n\n  // Italic\n  text = text.replace(/_([\\s\\S]+?)_/g, (m, inner) => {\n    const idx = placeholders.italics.length;\n    const ph = `⟬I${idx}⟭`;\n    placeholders.italics.push(`_${escapeMarkdownV2(inner)}_`);\n    return ph;\n  });\n\n  // Spoilers\n  text = text.replace(/\\|\\|([\\s\\S]+?)\\|\\|/g, (m, inner) => {\n    const idx = placeholders.spoilers.length;\n    const ph = `⟬S${idx}⟭`;\n    placeholders.spoilers.push(`||${escapeMarkdownV2(inner)}||`);\n    return ph;\n  });\n\n  // Escape everything else\n  text = escapeMarkdownV2(text);\n\n  // Restore placeholders\n  placeholders.links.forEach((md, i) => { text = text.replace(`⟬L${i}⟭`, md); });\n  placeholders.bolds.forEach((md, i) => { text = text.replace(`⟬B${i}⟭`, md); });\n  placeholders.italics.forEach((md, i) => { text = text.replace(`⟬I${i}⟭`, md); });\n  placeholders.spoilers.forEach((md, i) => { text = text.replace(`⟬S${i}⟭`, md); });\n\n  return text;\n}\n\n// ============ Chunking helpers ============\n/**\n * Split text into Telegram-safe chunks <= maxLen.\n * Prefers paragraph boundaries, then sentence boundaries, then words.\n * Falls back to hard cuts only when unavoidable (e.g., extremely long URL).\n */\nfunction chunkForTelegram(text, maxLen = SAFE_BUDGET) {\n  if (!text || text.length <= maxLen) return [text || ''];\n\n  const parts = [];\n  let buffer = '';\n\n  const flush = () => {\n    if (buffer) {\n      parts.push(buffer);\n      buffer = '';\n    }\n  };\n\n  // 1) Paragraph-level packing\n  const paragraphs = text.split(/\\n{2,}/);\n  for (const pRaw of paragraphs) {\n    const p = pRaw; // keep paragraph as-is\n    const candidate = buffer ? buffer + '\\n\\n' + p : p;\n    if (candidate.length <= maxLen) {\n      buffer = candidate;\n      continue;\n    }\n    if (p.length <= maxLen) {\n      flush();\n      buffer = p;\n      continue;\n    }\n\n    // 2) Sentence-level packing (paragraph is still too big)\n    flush();\n    const sentences = p.split(/(?<=[.!?…])\\s+(?=[^\\s])/u);\n    let sBuf = '';\n    for (const s of sentences) {\n      const sCandidate = sBuf ? sBuf + ' ' + s : s;\n      if (sCandidate.length <= maxLen) {\n        sBuf = sCandidate;\n        continue;\n      }\n      if (s.length <= maxLen) {\n        if (sBuf) parts.push(sBuf);\n        sBuf = s;\n        continue;\n      }\n\n      // 3) Word-level packing (sentence is still too big)\n      if (sBuf) { parts.push(sBuf); sBuf = ''; }\n      let wBuf = '';\n      const words = s.split(/\\s+/);\n      for (const w of words) {\n        const wCandidate = wBuf ? wBuf + ' ' + w : w;\n        if (wCandidate.length <= maxLen) {\n          wBuf = wCandidate;\n          continue;\n        }\n        if (w.length <= maxLen) {\n          if (wBuf) parts.push(wBuf);\n          wBuf = w;\n          continue;\n        }\n        // 4) Hard split (extremely long token, e.g., massive URL)\n        if (wBuf) { parts.push(wBuf); wBuf = ''; }\n        const re = new RegExp(`.{1,${maxLen}}`, 'g');\n        const hardPieces = w.match(re) || [];\n        parts.push(...hardPieces);\n      }\n      if (wBuf) parts.push(wBuf);\n    }\n    if (sBuf) parts.push(sBuf);\n  }\n  if (buffer) parts.push(buffer);\n\n  // Final safety pass: trim chunks that might still exceed MAX_TELEGRAM\n  return parts.flatMap(part => {\n    if (part.length <= MAX_TELEGRAM) return [part];\n    const re = new RegExp(`.{1,${SAFE_BUDGET}}`, 'g');\n    return part.match(re) || [];\n  });\n}\n\n// ============ Main ============\nconst inputItems = $input.all();\nconst out = [];\n\nfor (const item of inputItems) {\n  const j = item.json || {};\n  const raw =\n    j.message ?? j.output ?? j.text ?? j.content ?? '';\n\n  const formatted = processMarkdownV2Safe(raw);\n  const chunks = chunkForTelegram(formatted, SAFE_BUDGET);\n\n  chunks.forEach((chunk, idx) => {\n    out.push({\n      json: {\n        ...j,\n        message: chunk,\n        message_part_index: idx + 1,\n        message_parts_total: chunks.length,\n      },\n      binary: item.binary,\n    });\n  });\n}\n\nreturn out;\n"
      },
      "typeVersion": 2
    },
    {
      "id": "6ce0f61c-03d1-4bef-827f-ac3c80f48939",
      "name": "Envoyer un message texte",
      "type": "n8n-nodes-base.telegram",
      "position": [
        1312,
        1264
      ],
      "webhookId": "1ad49e91-7894-4fb1-ba93-73ba3ec4e666",
      "parameters": {
        "text": "={{ $json.message }}",
        "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
        "additionalFields": {
          "parse_mode": "MarkdownV2",
          "appendAttribution": false
        }
      },
      "credentials": {
        "telegramApi": {
          "id": "rzhkYoexl5hHvqnv",
          "name": "Telegram account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "662e6beb-7498-42c2-ba0c-6530c100bf97",
      "name": "Corriger le type MIME",
      "type": "n8n-nodes-base.code",
      "position": [
        -1184,
        1328
      ],
      "parameters": {
        "jsCode": "// --- Mapa Extendido de Tipos MIME ---\n// Una lista completa para cubrir la mayoría de los formatos de archivo comunes.\nconst mimeMap = {\n  // --- Formatos de Documentos ---\n  'pdf': 'application/pdf',\n  'txt': 'text/plain',\n  'rtf': 'application/rtf',\n  'csv': 'text/csv',\n  'html': 'text/html',\n  'htm': 'text/html',\n  'json': 'application/json',\n  'xml': 'application/xml', // 'text/xml' también es válido pero 'application/xml' es más común\n  'yaml': 'application/x-yaml',\n  'yml': 'application/x-yaml',\n\n  // --- Formatos de Microsoft Office ---\n  'doc': 'application/msword',\n  'docx': 'application/vnd.openxmlformats-officedocument.wordprocessingml.document',\n  'xls': 'application/vnd.ms-excel',\n  'xlsx': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet',\n  'ppt': 'application/vnd.ms-powerpoint',\n  'pptx': 'application/vnd.openxmlformats-officedocument.presentationml.presentation',\n  'pub': 'application/vnd.ms-publisher',\n\n  // --- Formatos de OpenOffice / LibreOffice ---\n  'odt': 'application/vnd.oasis.opendocument.text',\n  'ods': 'application/vnd.oasis.opendocument.spreadsheet',\n  'odp': 'application/vnd.oasis.opendocument.presentation',\n  'odg': 'application/vnd.oasis.opendocument.graphics',\n\n  // --- Formatos de Apple iWork ---\n  'pages': 'application/vnd.apple.pages',\n  'numbers': 'application/vnd.apple.numbers',\n  'key': 'application/vnd.apple.keynote',\n\n  // --- Formatos de Imagen ---\n  'png': 'image/png',\n  'jpg': 'image/jpeg',\n  'jpeg': 'image/jpeg',\n  'gif': 'image/gif',\n  'webp': 'image/webp',\n  'svg': 'image/svg+xml',\n  'bmp': 'image/bmp',\n  'ico': 'image/vnd.microsoft.icon',\n  'tif': 'image/tiff',\n  'tiff': 'image/tiff',\n  'heic': 'image/heic',\n  'heif': 'image/heif',\n\n  // --- Formatos de Audio ---\n  'mp3': 'audio/mpeg',\n  'wav': 'audio/wav',\n  'oga': 'audio/ogg',\n  'ogg': 'audio/ogg',\n  'flac': 'audio/flac',\n  'm4a': 'audio/mp4',\n  'aac': 'audio/aac',\n  'opus': 'audio/opus',\n  'wma': 'audio/x-ms-wma',\n  'mid': 'audio/midi',\n  'midi': 'audio/midi',\n\n  // --- Formatos de Video ---\n  'mp4': 'video/mp4',\n  'mov': 'video/quicktime',\n  'webm': 'video/webm',\n  'mpeg': 'video/mpeg',\n  'mpg': 'video/mpeg',\n  'avi': 'video/x-msvideo',\n  'wmv': 'video/x-ms-wmv',\n  'flv': 'video/x-flv',\n  'mkv': 'video/x-matroska',\n\n  // --- Formatos de Archivos y Compresión ---\n  'zip': 'application/zip',\n  'rar': 'application/vnd.rar',\n  '7z': 'application/x-7z-compressed',\n  'tar': 'application/x-tar',\n  'gz': 'application/gzip',\n  'bz2': 'application/x-bzip2',\n\n  // --- Otros Formatos ---\n  'epub': 'application/epub+zip',\n  'ics': 'text/calendar',\n  'vcf': 'text/vcard',\n  'js': 'text/javascript',\n  'css': 'text/css',\n  'sh': 'application/x-sh',\n  'py': 'text/x-python',\n};\n\n// --- Lógica de Procesamiento (sin cambios) ---\n\n// Obtenemos todos los items que llegan al nodo\nconst items = $input.all();\n\n// Iteramos sobre cada item para procesarlo\nfor (const item of items) {\n  // Verificamos que el item tenga datos binarios para procesar\n  if (item.binary && item.binary['data']) {\n    // Obtenemos el nombre del archivo de forma segura\n    const fileName = item.binary['data'].fileName || '';\n    if (!fileName) {\n      continue; // Si no hay nombre de archivo, pasamos al siguiente item\n    }\n\n    // Extraemos la extensión del archivo de forma robusta\n    const extension = fileName.slice((fileName.lastIndexOf(\".\") - 1 >>> 0) + 2).toLowerCase();\n\n    // Buscamos la extensión en nuestro mapa\n    const newMimeType = mimeMap[extension];\n\n    // Si encontramos una coincidencia en el mapa, actualizamos el mimeType\n    if (newMimeType) {\n      if(item.binary['data'].mimeType !== newMimeType) {\n        console.log(`Cambiando mimeType para '${fileName}' de '${item.binary['data'].mimeType}' a '${newMimeType}'.`);\n        item.binary['data'].mimeType = newMimeType;\n      }\n    }\n  }\n}\n\n// Devolvemos todos los items, modificados o no\nreturn items;"
      },
      "typeVersion": 2
    },
    {
      "id": "07281d83-6c94-4952-819e-288a4435da24",
      "name": "En train d'écrire…",
      "type": "n8n-nodes-base.telegram",
      "position": [
        -1744,
        1184
      ],
      "webhookId": "b768e407-5f22-4b80-a8a9-2d255b9bf815",
      "parameters": {
        "chatId": "={{ $json.message.chat.id }}",
        "operation": "sendChatAction"
      },
      "credentials": {
        "telegramApi": {
          "id": "rzhkYoexl5hHvqnv",
          "name": "Telegram account"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "e211d4af-9ebd-4524-84ef-934349b6b155",
      "name": "obtenir_message (message Audio/Video)",
      "type": "n8n-nodes-base.set",
      "position": [
        -848,
        1328
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "d8935452-fe20-469d-a68d-1aad056cb8dd",
              "name": "message",
              "type": "string",
              "value": "=Voice message description:{{ $json.candidates?.[0]?.content?.parts?.[0]?.text || $json.content?.parts?.[0]?.text }}"
            },
            {
              "id": "93f1bba1-1180-404a-93ca-c34cf1d1b7ac",
              "name": "chat_id",
              "type": "string",
              "value": "={{ $('Telegram Trigger').item.json.message.chat.id }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "9c28c37b-1d37-4f23-90a3-872f5e3870a7",
      "name": "Analyser le message vocal",
      "type": "@n8n/n8n-nodes-langchain.googleGemini",
      "position": [
        -1024,
        1328
      ],
      "parameters": {
        "text": "What's in this audio message from telegram user?",
        "modelId": {
          "__rl": true,
          "mode": "list",
          "value": "models/gemini-2.5-pro",
          "cachedResultName": "models/gemini-2.5-pro"
        },
        "options": {},
        "resource": "audio",
        "inputType": "binary",
        "operation": "analyze"
      },
      "credentials": {
        "googlePalmApi": {
          "id": "to92mdfNe3L6sBae",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "ea646e8c-e6d0-47ea-8743-45eade4c1c4d",
      "name": "obtenir_message (texte)",
      "type": "n8n-nodes-base.set",
      "position": [
        -1184,
        1152
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "801ec600-22ad-4a94-a2b4-ae72eb271df0",
              "name": "message",
              "type": "string",
              "value": "={{ $('Telegram Trigger').item.json.message.text }}"
            },
            {
              "id": "263071fb-bcdf-42b0-bb46-71b75fa0bf2a",
              "name": "chat_id",
              "type": "string",
              "value": "={{ $('Telegram Trigger').item.json.message.chat.id }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "1ca88076-5c56-4561-bb8a-fdf1db080d2a",
      "name": "Routeur de Message d'Entrée1",
      "type": "n8n-nodes-base.switch",
      "position": [
        -1600,
        1312
      ],
      "parameters": {
        "rules": {
          "values": [
            {
              "outputKey": "Text",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "fcb767ee-565e-4b56-a54e-6f97f739fc24",
                    "operator": {
                      "type": "string",
                      "operation": "exists",
                      "singleValue": true
                    },
                    "leftValue": "={{ $('Telegram Trigger').item.json.message.text }}",
                    "rightValue": ""
                  }
                ]
              },
              "renameOutput": true
            },
            {
              "outputKey": "Voice Message",
              "conditions": {
                "options": {
                  "version": 2,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "c1016c40-f8f2-4e08-8ec8-5cdb88f5c87a",
                    "operator": {
                      "type": "object",
                      "operation": "exists",
                      "singleValue": true
                    },
                    "leftValue": "={{ $('Telegram Trigger').item.json.message.voice }}",
                    "rightValue": ""
                  }
                ]
              },
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        "text": "=Chat Memory: {{ $('Aggregate').item.json.message.join('\\n') }}\n\nUser Request: {{ $('Normalize input').item.json.message }}",
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        "content": "## ⚙️ Database Initialization (Chat Memory Table)\n\n**Purpose:**  \nThis section is responsible for creating and preparing the `chat_memory` table in PostgreSQL. It ensures that chat interactions are stored persistently for later use in context management, summarization, and categorization.\n"
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        "content": "## 🔵 Input Handling (Telegram Trigger & Preprocessing)\n\n### Purpose:\nThis section receives and processes incoming messages from Telegram. It detects whether the input is text, voice, or unsupported media.\n\n### Key Steps:\n\n*   **Telegram Trigger** – Listens for new updates (messages from users).\n*   **Input Message Router** – Classifies whether the input is:\n    *   Text message\n    *   Voice message\n    *   Unsupported media → redirects to an error handler\n*   **Voice Handling** – If it’s a voice message:\n    *   Downloads the file\n    *   Normalizes MIME type\n    *   Sends it to speech-to-text analysis\n    *   Extracts the text message from audio\n*   **Error Handling** – If the input is not supported, an error message is returned.\n\n### Optional Extension:\nFor multimodal and media group support (multiple files, images, videos), you can extend this section with the following template: https://n8n.io/workflows/7455-process-multiple-media-files-in-telegram-with-gemini-ai-and-postgresql-database/"
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        "content": "## 🔴 Chat Memory Retrieval & Context Optimization\n\n### Purpose:\nThis section retrieves past interactions from the database, aggregates them into a single string, and summarizes them before passing them to the agent.\n\n### Key Steps:\n\n*   **Normalize Input** – Standardizes the message before processing.\n*   **Get Chat Memory** – Queries PostgreSQL for previous messages linked to the `session_id`.\n*   **Aggregate** – Combines past interactions into one text block.\n*   **Summarize & Categorize** – Uses Google Gemini 2.5 Flash Lite (low-cost, low-latency) to:\n    *   Summarize the chat history.\n    *   Extract relevant context.\n    *   Categorize the difficulty level of the task.\n\n### Why Summarization First?\n\n*   Only relevant and important context is passed to the agent.\n*   Reduces token usage, speeding up responses and lowering costs.\n*   Prevents irrelevant history from cluttering the model’s attention.\n\n### Advantages:\n\n*   Saves processing time and cost by using a lightweight summarization model.\n*   Produces more accurate and focused responses.\n*   Optimizes memory queries by reducing data size passed downstream."
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        "content": "## 🟣 Agent Processing & Response Delivery\n\n### Purpose:\nThis section routes the request to the appropriate Gemini model depending on task difficulty, generates the final response, and sends it back to Telegram. It also updates the chat memory.\n\n### Key Steps:\n\n*   **Agent Node** – Receives:\n    *   User request\n    *   Relevant summarized context\n    *   Difficulty level\n*   **Model Selector** – Dynamically chooses the model:\n    *   **Difficulty 1** → Gemini 2.5 Flash Lite (fastest & cheapest)\n    *   **Difficulty 2** → Gemini 2.5 Flash\n    *   **Difficulty 3** → Gemini 2.5 Pro (advanced reasoning)\n*   **Markdown Formatting** – Converts model output into Telegram-compatible Markdown V2.\n*   **Send Message** – Sends the response back to Telegram.\n*   **Update Chat Memory** – Inserts a single row containing both the user and agent message.\n\n### Why single-row storage for user & agent?\n\n*   Since the message is sent to Telegram first and then the memory is updated, this saves an average of 0.3 seconds in response time.\n*   Reduces the number of queries (`Get Chat Memory` fetches fewer rows).\n*   Updates are faster since both messages are stored at once.\n*   Optimizes resource usage while maintaining full conversational context.\n\n### Advantages:\n\n*   Cost-optimized model usage (only advanced models used when strictly necessary).\n*   Faster response times by minimizing context size and database operations.\n"
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        "content": "## ✅ Key Benefits of This Architecture\n\n### Cost Efficiency\n\n*   Uses cheaper LLMs for summarization and simple queries.\n*   Reserves expensive models only for complex tasks.\n\n### Performance Optimization\n\n*   Reduced token consumption through summarization.\n*   Faster memory queries due to single-row storage.\n\n### Flexibility & Scalability\n\n*   Easy integration of multimodal inputs (images, audio, video).\n*   Modular structure allows replacing/upgrading models or database logic.\n\n### User Experience\n\n*   Quick Telegram responses.\n*   Consistent memory of past interactions without overwhelming the LLM."
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        "content": "## Acknowledgment\n\nA special thank you to Davide for the inspiration behind this template.  \nHis work on the [**AI Orchestrator that dynamically selects models based on input type**](https://n8n.io/workflows/7004-ai-orchestrator-dynamically-selects-models-based-on-input-type/) served as a foundational guide for this architecture.\n"
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        "content": "## 💡 Need Assistance?\n\nIf you’d like help customizing or extending this workflow, feel free to reach out:  \n\n📧 Email: [johnsilva11031@gmail.com](mailto:johnsilva11031@gmail.com)  \n🔗 LinkedIn: [John Alejandro Silva Rodríguez](https://www.linkedin.com/in/john-alejandro-silva-rodriguez-48093526b/)\n"
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