{
  "name": "DBBot Unified (Ingest + RAG)",
  "nodes": [
    {
      "parameters": {
        "httpMethod": "POST",
        "path": "tg-inbox",
        "options": {}
      },
      "type": "n8n-nodes-base.webhook",
      "typeVersion": 2.1,
      "position": [
        -640,
        -120
      ],
      "id": "31d39bff-4f9a-4645-94b2-b38d4ebf0bf0",
      "name": "Webhook TG Inbox",
      "webhookId": "dbbot-tg-inbox-webhook"
    },
    {
      "parameters": {
        "jsCode": "const body = $input.item.json.body || {};\nconst meta = body.metadata || {};\nconst rawText = (body.text || '').trim();\n\nif (!rawText) {\n  return { json: { skip: true, reason: 'empty_text' } };\n}\n\nconst authorLabel = meta.author_label || meta.sender_name || 'Unknown';\nconst authorId = meta.sender_id || meta.author?.id || '0';\nconst repliedTo = meta.replied_to_author_label ? ` (в ответ ${meta.replied_to_author_label})` : '';\n\nreturn {\n  json: {\n    skip: false,\n    text: `Автор ${authorLabel} (ID: ${authorId})${repliedTo}: ${rawText}`,\n    metadata: {\n      ...meta,\n      original_text: rawText,\n      source: meta.source || 'telegram_group',\n      processed_at: new Date().toISOString()\n    }\n  }\n};"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        -416,
        -120
      ],
      "id": "a9347d4b-fad0-4fb8-a23c-bcad6d2f3186",
      "name": "Normalize Telegram Payload"
    },
    {
      "parameters": {
        "conditions": {
          "boolean": [
            {
              "value1": "={{ $json.skip }}",
              "value2": true
            }
          ]
        },
        "options": {}
      },
      "type": "n8n-nodes-base.if",
      "typeVersion": 2,
      "position": [
        -192,
        -120
      ],
      "id": "de52e6d1-98be-4c24-bc03-d90d7fa80b93",
      "name": "Skip Empty Text"
    },
    {
      "parameters": {
        "mode": "insert",
        "qdrantCollection": {
          "__rl": true,
          "value": "telegram_kb",
          "mode": "list",
          "cachedResultName": "telegram_kb"
        },
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "typeVersion": 1.3,
      "position": [
        288,
        -120
      ],
      "id": "2444f3f3-d57d-45fa-b80e-e40f73f0c70f",
      "name": "Qdrant Insert",
      "retryOnFail": true,
      "maxTries": 5,
      "waitBetweenTries": 5000
    },
    {
      "parameters": {
        "jsCode": "const WINDOW_MS = 5 * 60 * 1000;\nconst MAX_MESSAGES = 3;\nconst MIN_MESSAGES_TO_FLUSH = 1;\n\nfunction aggregateBuffer(buffer) {\n  const lines = buffer.messages.map((m) => {\n    const repliedTo = m.replyTo ? ` -> ${m.replyTo}` : '';\n    return `[${m.date}] ${m.author}${repliedTo}: ${m.text}`;\n  });\n\n  return {\n    skip: false,\n    text: [\n      `Контекст диалога (${buffer.messages.length} сообщений, участники: ${buffer.participants.join(', ')})`,\n      ...lines,\n    ].join('\\n'),\n    metadata: {\n      ...buffer.lastMeta,\n      context_id: buffer.contextId,\n      context_message_count: buffer.messages.length,\n      context_start_date: new Date(buffer.startTs).toISOString(),\n      context_end_date: new Date(buffer.lastTs).toISOString(),\n      context_participants: buffer.participants,\n      context_mode: 'thread_time_window_5m_fast_flush'\n    }\n  };\n}\n\nconst staticData = $getWorkflowStaticData('global');\nstaticData.contextBuffers = staticData.contextBuffers || {};\n\nconst meta = $json.metadata || {};\nconst rawText = (meta.original_text || '').trim();\nif (!rawText) {\n  return { json: { skip: true, reason: 'empty_original_text' } };\n}\n\nconst nowTs = meta.date ? new Date(meta.date).getTime() : Date.now();\nconst safeTs = Number.isNaN(nowTs) ? Date.now() : nowTs;\nconst chatId = String(meta.chat_id || meta.group_id || 'unknown_chat');\nconst threadId = String(meta.thread_id || meta.reply_to_message_id || meta.message_id || 'single');\nconst contextId = `${chatId}:${threadId}`;\n\nlet buffer = staticData.contextBuffers[contextId];\n\nif (buffer && safeTs - buffer.lastTs > WINDOW_MS) {\n  const staleBuffer = buffer;\n  buffer = null;\n\n  const author = meta.author_label || meta.sender_name || 'Unknown';\n  staticData.contextBuffers[contextId] = {\n    contextId,\n    startTs: safeTs,\n    lastTs: safeTs,\n    participants: [author],\n    lastMeta: meta,\n    messages: [\n      {\n        date: meta.date || new Date(safeTs).toISOString(),\n        author,\n        replyTo: meta.replied_to_author_label || '',\n        text: rawText\n      }\n    ]\n  };\n\n  if (staleBuffer.messages.length >= MIN_MESSAGES_TO_FLUSH) {\n    return { json: aggregateBuffer(staleBuffer) };\n  }\n\n  return { json: { skip: true, reason: 'buffer_reset_on_timeout', context_id: contextId } };\n}\n\nif (!buffer) {\n  buffer = {\n    contextId,\n    startTs: safeTs,\n    lastTs: safeTs,\n    participants: [],\n    lastMeta: meta,\n    messages: []\n  };\n}\n\nconst author = meta.author_label || meta.sender_name || 'Unknown';\nif (!buffer.participants.includes(author)) {\n  buffer.participants.push(author);\n}\n\nbuffer.messages.push({\n  date: meta.date || new Date(safeTs).toISOString(),\n  author,\n  replyTo: meta.replied_to_author_label || '',\n  text: rawText\n});\nbuffer.lastMeta = meta;\nbuffer.lastTs = safeTs;\n\nconst shouldFlush =\n  buffer.messages.length >= MAX_MESSAGES ||\n  buffer.lastTs - buffer.startTs >= WINDOW_MS;\n\nif (!shouldFlush) {\n  staticData.contextBuffers[contextId] = buffer;\n  return {\n    json: {\n      skip: true,\n      reason: 'buffering',\n      context_id: contextId,\n      buffered_messages: buffer.messages.length\n    }\n  };\n}\n\ndelete staticData.contextBuffers[contextId];\nreturn { json: aggregateBuffer(buffer) };"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        32,
        -120
      ],
      "id": "b3866944-b7ca-4505-b89e-a5f3d331f43d",
      "name": "Build Context Block"
    },
    {
      "parameters": {
        "conditions": {
          "boolean": [
            {
              "value1": "={{ $json.skip }}",
              "value2": true
            }
          ]
        },
        "options": {}
      },
      "type": "n8n-nodes-base.if",
      "typeVersion": 2,
      "position": [
        160,
        -120
      ],
      "id": "a343f1ca-2423-43e7-9b8d-ce4f48f1e5ff",
      "name": "Skip Buffered Context"
    },
    {
      "parameters": {
        "jsonMode": "expressionData",
        "jsonData": "={{ $json.text }}",
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "typeVersion": 1.1,
      "position": [
        288,
        56
      ],
      "id": "3de4bfe4-bd8a-4f36-a9ec-8955f2f26f83",
      "name": "Document Loader"
    },
    {
      "parameters": {
        "model": "qwen3-embedding:8b"
      },
      "type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
      "typeVersion": 1,
      "position": [
        96,
        56
      ],
      "id": "5f48d9eb-ec81-4a00-b2fa-ec6a1fc2f009",
      "name": "Embeddings For Insert",
      "retryOnFail": true,
      "maxTries": 5,
      "waitBetweenTries": 5000
    },
    {
      "parameters": {
        "updates": [
          "message"
        ],
        "additionalFields": {}
      },
      "type": "n8n-nodes-base.telegramTrigger",
      "typeVersion": 1.2,
      "position": [
        -640,
        288
      ],
      "id": "163fbd89-644c-4858-a2ce-8c572a2d3593",
      "name": "Telegram Trigger",
      "retryOnFail": true,
      "maxTries": 5,
      "waitBetweenTries": 5000
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "=Ответь на вопрос пользователя, используя данные из Qdrant Vector Store: {{ $json.message.text }}",
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3.1,
      "position": [
        -384,
        288
      ],
      "id": "e67a8860-3c52-407e-8fd7-1f481e3c5019",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "model": "qwen3:30b-a3b",
        "options": {
          "temperature": 0
        }
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatOllama",
      "typeVersion": 1,
      "position": [
        -352,
        496
      ],
      "id": "3c7db13e-1be9-4f2f-ab26-a613db89ea71",
      "name": "Ollama Chat Model",
      "retryOnFail": true,
      "maxTries": 5,
      "waitBetweenTries": 5000
    },
    {
      "parameters": {
        "mode": "retrieve-as-tool",
        "toolDescription": "Всегда используй этот инструмент для ответа: в нем релевантные документы из базы знаний.",
        "qdrantCollection": {
          "__rl": true,
          "value": "telegram_kb",
          "mode": "list",
          "cachedResultName": "telegram_kb"
        },
        "includeDocumentMetadata": true,
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "typeVersion": 1.3,
      "position": [
        -128,
        528
      ],
      "id": "2f204e2e-58e7-4514-9f3c-3e23949f8520",
      "name": "Qdrant Retrieve Tool",
      "retryOnFail": true,
      "maxTries": 5,
      "waitBetweenTries": 5000
    },
    {
      "parameters": {
        "model": "qwen3-embedding:8b"
      },
      "type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
      "typeVersion": 1,
      "position": [
        -128,
        704
      ],
      "id": "e5d5f376-bb95-4a16-ab11-e5e3e7d74524",
      "name": "Embeddings For Retrieve",
      "retryOnFail": true,
      "maxTries": 5,
      "waitBetweenTries": 5000
    },
    {
      "parameters": {
        "jsCode": "let rawText = $input.item.json.text || $input.item.json.response || $input.item.json.output || '';\nlet cleanText = rawText.replace(/<think>[\\s\\S]*?<\\/think>/g, '').trim();\n\nif (!cleanText) {\n  cleanText = 'Не смог сформировать ответ. Попробуйте переформулировать вопрос.';\n}\n\nreturn {\n  json: {\n    clean_response: cleanText\n  }\n};"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        -128,
        288
      ],
      "id": "81f5d5e9-3f13-4d43-b8e2-7112e2ca63e4",
      "name": "Clean Agent Output"
    },
    {
      "parameters": {
        "chatId": "={{ $('Telegram Trigger').item.json.message.from.id }}",
        "text": "={{ $json.clean_response }}",
        "additionalFields": {
          "appendAttribution": false
        }
      },
      "type": "n8n-nodes-base.telegram",
      "typeVersion": 1.2,
      "position": [
        96,
        288
      ],
      "id": "e8476b38-8344-4aaf-828e-5da8344b79d2",
      "name": "Send Telegram Reply",
      "retryOnFail": true,
      "maxTries": 5,
      "waitBetweenTries": 5000
    }
  ],
  "pinData": {},
  "connections": {
    "Webhook TG Inbox": {
      "main": [
        [
          {
            "node": "Normalize Telegram Payload",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Normalize Telegram Payload": {
      "main": [
        [
          {
            "node": "Skip Empty Text",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Skip Empty Text": {
      "main": [
        [],
        [
          {
            "node": "Build Context Block",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Build Context Block": {
      "main": [
        [
          {
            "node": "Skip Buffered Context",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Skip Buffered Context": {
      "main": [
        [],
        [
          {
            "node": "Qdrant Insert",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings For Insert": {
      "ai_embedding": [
        [
          {
            "node": "Qdrant Insert",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Document Loader": {
      "ai_document": [
        [
          {
            "node": "Qdrant Insert",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Telegram Trigger": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Ollama Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Qdrant Retrieve Tool": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings For Retrieve": {
      "ai_embedding": [
        [
          {
            "node": "Qdrant Retrieve Tool",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "AI Agent": {
      "main": [
        [
          {
            "node": "Clean Agent Output",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Clean Agent Output": {
      "main": [
        [
          {
            "node": "Send Telegram Reply",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false,
  "settings": {
    "executionOrder": "v1",
    "availableInMCP": false
  },
  "tags": []
}