Document Q&A chatbot with Gemini AI and Supabase vector search for Telegram

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        "group": "[\"transform\"]",
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          "name": "Code"
        },
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            "name": "Development"
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            "name": "Core Nodes"
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        ]
      },
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        "id": 1119,
        "icon": "fa:robot",
        "name": "@n8n/n8n-nodes-langchain.agent",
        "codex": {
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              "Chat",
              "Conversational",
              "Plan and Execute",
              "ReAct",
              "Tools"
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              ]
            },
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              "Langchain"
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            "subcategories": {
              "AI": [
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                "Root Nodes"
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            }
          }
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        "group": "[\"transform\"]",
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          "color": "#404040"
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        "displayName": "AI Agent",
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            "name": "AI"
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            "id": 26,
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        "icon": "fa:database",
        "name": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
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                }
              ]
            },
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              "Langchain"
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            "subcategories": {
              "AI": [
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              ],
              "Memory": [
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          }
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        "displayName": "Simple Memory",
        "typeVersion": 1,
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        "icon": "fa:grip-lines-vertical",
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            "subcategories": {
              "AI": [
                "Text Splitters"
              ]
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          "type": "icon"
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            "name": "AI"
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            "id": 26,
            "name": "Langchain"
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        ]
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        "icon": "file:supabase.svg",
        "name": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
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              "Langchain"
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                "Root Nodes"
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              ],
              "Vector Stores": [
                "Other Vector Stores"
              ]
            }
          }
        },
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          "name": "Supabase Vector Store"
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              "Spreadsheet",
              "Excel",
              "xls",
              "xlsx",
              "ods",
              "tabular",
              "decode",
              "decoding",
              "Move Binary Data",
              "Binary",
              "File",
              "PDF",
              "JSON",
              "HTML",
              "ICS",
              "iCal",
              "txt",
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              "RTF",
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            "subcategories": {
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                "Data Transformation"
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        "group": "[\"input\"]",
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        "displayName": "Extract from File",
        "typeVersion": 1,
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        ]
      },
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        "icon": "file:aggregate.svg",
        "name": "n8n-nodes-base.aggregate",
        "codex": {
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            "alias": [
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              "Combine",
              "Flatten",
              "Transform",
              "Array",
              "List",
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            "details": "",
            "resources": {
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              "primaryDocumentation": [
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            },
            "categories": [
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
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              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Aggregate"
        },
        "iconData": {
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        "displayName": "Aggregate",
        "typeVersion": 1,
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        ]
      },
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        "id": 1239,
        "icon": "file:splitOut.svg",
        "name": "n8n-nodes-base.splitOut",
        "codex": {
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              "Split",
              "Nested",
              "Transform",
              "Array",
              "List",
              "Item"
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            "details": "",
            "resources": {
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              "primaryDocumentation": [
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                  "url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.splitout/"
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            "categories": [
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            "nodeVersion": "1.0",
            "codexVersion": "1.0",
            "subcategories": {
              "Core Nodes": [
                "Data Transformation"
              ]
            }
          }
        },
        "group": "[\"transform\"]",
        "defaults": {
          "name": "Split Out"
        },
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