Plantilla de n8n para agente local de IA RAG

• •Punto final de HTTP Webhook (n8n generará automáticamente)
• •Información de conexión de la base de datos PostgreSQL
• •Clave de API de OpenAI

{
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  "meta": {
    "instanceId": "8cf060ebda3ec45b5ebb6a30779eaf0c03dfba83865feab3f32adb31b82caa08"
  },
  "name": "n8n Local AI Agentic RAG Template",
  "tags": [],
  "nodes": [
    {
      "id": "397d00eb-8034-49e5-a8f6-0a0fd9b97d5b",
      "name": "Cargador de Datos Predeterminado",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        3312,
        1280
      ],
      "parameters": {
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "=file_id",
                "value": "={{ $('Set File ID').first().json.file_id }}"
              },
              {
                "name": "file_title",
                "value": "={{ $('Set File ID').first().json.file_title }}"
              }
            ]
          }
        },
        "jsonData": "={{ $json.data || $json.text || $json.concatenated_data }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "e57065a2-9087-48e9-839e-d9c5c5fb477f",
      "name": "Nota Adhesiva",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        2304,
        144
      ],
      "parameters": {
        "color": 4,
        "width": 583.4552380860637,
        "height": 528.85546469693,
        "content": "## Agent Tools for RAG"
      },
      "typeVersion": 1
    },
    {
      "id": "f7efaf27-78fb-4429-beba-74ffcc700342",
      "name": "Nota Adhesiva1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        560,
        688
      ],
      "parameters": {
        "color": 5,
        "width": 3073,
        "height": 867,
        "content": "## Tool to Add a Google Drive File to Vector DB"
      },
      "typeVersion": 1
    },
    {
      "id": "a137d00b-fb01-408c-9963-645e2beb44d9",
      "name": "Extraer Texto del Documento",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        2512,
        1280
      ],
      "parameters": {
        "options": {},
        "operation": "text"
      },
      "typeVersion": 1,
      "alwaysOutputData": true
    },
    {
      "id": "1aec304d-7264-4e65-8654-cb9294c96c82",
      "name": "Memoria de Chat Postgres",
      "type": "@n8n/n8n-nodes-langchain.memoryPostgresChat",
      "position": [
        1712,
        512
      ],
      "parameters": {},
      "notesInFlow": false,
      "typeVersion": 1
    },
    {
      "id": "9c407f2b-4f6a-46d6-a607-225c1c628ae5",
      "name": "Establecer ID de Archivo",
      "type": "n8n-nodes-base.set",
      "position": [
        992,
        960
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "10646eae-ae46-4327-a4dc-9987c2d76173",
              "name": "file_id",
              "type": "string",
              "value": "={{ $json.path }}"
            },
            {
              "id": "f4536df5-d0b1-4392-bf17-b8137fb31a44",
              "name": "file_type",
              "type": "string",
              "value": "={{ $json.path.split(/[\\\\/]/).pop().split('.').pop(); }}"
            },
            {
              "id": "77d782de-169d-4a46-8a8e-a3831c04d90f",
              "name": "file_title",
              "type": "string",
              "value": "={{ $json.path.split(/[\\\\/]/).pop().split('.').slice(0, -1).join('.'); }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "bc93aa94-10ec-4670-99f4-3bcec36be1ce",
      "name": "Nota Adhesiva2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1264,
        208
      ],
      "parameters": {
        "width": 1035.6381264595484,
        "height": 464.8027193303974,
        "content": "## RAG AI Agent with Chat Interface"
      },
      "typeVersion": 1
    },
    {
      "id": "8ccc451e-2fac-49b0-8700-085476add599",
      "name": "Responder a Webhook",
      "type": "n8n-nodes-base.respondToWebhook",
      "position": [
        2128,
        288
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "55abb8ac-7988-430a-ae41-5155471228a2",
      "name": "Editar Campos",
      "type": "n8n-nodes-base.set",
      "position": [
        1568,
        288
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "9a9a245e-f1a1-4282-bb02-a81ffe629f0f",
              "name": "chatInput",
              "type": "string",
              "value": "={{ $json?.chatInput || $json.body.chatInput }}"
            },
            {
              "id": "b80831d8-c653-4203-8706-adedfdb98f77",
              "name": "sessionId",
              "type": "string",
              "value": "={{ $json?.sessionId || $json.body.sessionId}}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "78b3fd17-23e9-4693-b782-918a5a8e5aed",
      "name": "Cuando se recibe mensaje de chat",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        1312,
        288
      ],
      "webhookId": "e104e40e-6134-4825-a6f0-8a646d882662",
      "parameters": {
        "public": true,
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "06e362d1-d20c-407a-a75a-ed175c07439d",
      "name": "Webhook",
      "type": "n8n-nodes-base.webhook",
      "position": [
        1312,
        480
      ],
      "webhookId": "bf4dd093-bb02-472c-9454-7ab9af97bd1d",
      "parameters": {
        "path": "bf4dd093-bb02-472c-9454-7ab9af97bd1d",
        "options": {},
        "httpMethod": "POST",
        "responseMode": "responseNode"
      },
      "typeVersion": 2
    },
    {
      "id": "e8ba5c17-3426-4d76-b69b-ff91dff7958f",
      "name": "Extraer Texto de PDF",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        2512,
        720
      ],
      "parameters": {
        "options": {},
        "operation": "pdf"
      },
      "typeVersion": 1
    },
    {
      "id": "b40eb123-d7fc-4799-b248-4b9516aee49e",
      "name": "Agregar",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        2544,
        912
      ],
      "parameters": {
        "options": {},
        "aggregate": "aggregateAllItemData"
      },
      "typeVersion": 1
    },
    {
      "id": "0e3755e8-9532-447f-9137-f65d542c247e",
      "name": "Resumir",
      "type": "n8n-nodes-base.summarize",
      "position": [
        2752,
        992
      ],
      "parameters": {
        "options": {},
        "fieldsToSummarize": {
          "values": [
            {
              "field": "data",
              "aggregation": "concatenate"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "b185f2be-06bf-4a14-8d58-4b411a709f18",
      "name": "Agente IA RAG",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        1792,
        288
      ],
      "parameters": {
        "text": "={{ $json.chatInput }}",
        "options": {
          "systemMessage": "You are a personal assistant who helps answer questions from a corpus of documents. The documents are either text based (Txt, docs, extracted PDFs, etc.) or tabular data (CSVs or Excel documents).\n\nYou are given tools to perform RAG in the 'documents' table, look up the documents available in your knowledge base in the 'document_metadata' table, extract all the text from a given document, and query the tabular files with SQL in the 'document_rows' table.\n\nAlways start by performing RAG unless the users asks you to check a document or the question requires a SQL query for tabular data (fetching a sum, finding a max, something a RAG lookup would be unreliable for). If RAG doesn't help, then look at the documents that are available to you, find a few that you think would contain the answer, and then analyze those.\n\nAlways tell the user if you didn't find the answer. Don't make something up just to please them."
        },
        "promptType": "define"
      },
      "typeVersion": 1.6
    },
    {
      "id": "2ee45951-3553-49b7-9f79-3cef3d065e8a",
      "name": "Switch",
      "type": "n8n-nodes-base.switch",
      "position": [
        1840,
        944
      ],
      "parameters": {
        "rules": {
          "values": [
            {
              "conditions": {
                "options": {
                  "version": 1,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "operator": {
                      "type": "string",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $('Set File ID').item.json.file_type }}",
                    "rightValue": "pdf"
                  }
                ]
              }
            },
            {
              "conditions": {
                "options": {
                  "version": 1,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "2ae7faa7-a936-4621-a680-60c512163034",
                    "operator": {
                      "name": "filter.operator.equals",
                      "type": "string",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $('Set File ID').item.json.file_type }}",
                    "rightValue": "xlsx"
                  }
                ]
              }
            },
            {
              "conditions": {
                "options": {
                  "version": 1,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "fc193b06-363b-4699-a97d-e5a850138b0e",
                    "operator": {
                      "name": "filter.operator.equals",
                      "type": "string",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $('Set File ID').item.json.file_type }}",
                    "rightValue": "=csv"
                  }
                ]
              }
            },
            {
              "conditions": {
                "options": {
                  "version": 1,
                  "leftValue": "",
                  "caseSensitive": true,
                  "typeValidation": "strict"
                },
                "combinator": "and",
                "conditions": [
                  {
                    "id": "b69f5605-0179-4b02-9a32-e34bb085f82d",
                    "operator": {
                      "name": "filter.operator.equals",
                      "type": "string",
                      "operation": "equals"
                    },
                    "leftValue": "={{ $('Set File ID').item.json.file_type }}",
                    "rightValue": "txt"
                  }
                ]
              }
            }
          ]
        },
        "options": {
          "fallbackOutput": 3
        }
      },
      "typeVersion": 3
    },
    {
      "id": "20bf7dde-e073-4288-a9d6-34df3973b5c3",
      "name": "Extraer de Excel",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        2320,
        912
      ],
      "parameters": {
        "options": {},
        "operation": "xlsx"
      },
      "typeVersion": 1
    },
    {
      "id": "f1840995-3f1c-4f4e-9d78-bc9225ecbe2b",
      "name": "Establecer Esquema",
      "type": "n8n-nodes-base.set",
      "position": [
        3184,
        848
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "f422e2e0-381c-46ea-8f38-3f58c501d8b9",
              "name": "schema",
              "type": "string",
              "value": "={{ $('Extract from Excel').isExecuted ? $('Extract from Excel').first().json.keys().toJsonString() : $('Extract from CSV').first().json.keys().toJsonString() }}"
            },
            {
              "id": "bb07c71e-5b60-4795-864c-cc3845b6bc46",
              "name": "data",
              "type": "string",
              "value": "={{ $json.concatenated_data }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "b79ceb0b-f370-4ffb-9953-14b411acb5d9",
      "name": "Extraer de CSV",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        2320,
        1088
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1
    },
    {
      "id": "7067874e-4123-4a6c-a94d-89e4d1878309",
      "name": "Nota Adhesiva3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        560,
        368
      ],
      "parameters": {
        "color": 3,
        "width": 680,
        "height": 300,
        "content": "## Run Each Node Once to Set Up Database Tables"
      },
      "typeVersion": 1
    },
    {
      "id": "130c53e8-d507-4b6f-b1cf-f79dbc571c46",
      "name": "Crear Tabla de Metadatos de Documentos",
      "type": "n8n-nodes-base.postgres",
      "position": [
        688,
        464
      ],
      "parameters": {
        "query": "CREATE TABLE document_metadata (\n    id TEXT PRIMARY KEY,\n    title TEXT,\n    created_at TIMESTAMP DEFAULT NOW(),\n    schema TEXT\n);",
        "options": {},
        "operation": "executeQuery"
      },
      "typeVersion": 2.5
    },
    {
      "id": "421d2123-b68a-4c51-a482-db5bdffd3f76",
      "name": "Crear Tabla de Filas de Documentos (para Datos Tabulares)",
      "type": "n8n-nodes-base.postgres",
      "position": [
        992,
        464
      ],
      "parameters": {
        "query": "CREATE TABLE document_rows (\n    id SERIAL PRIMARY KEY,\n    dataset_id TEXT REFERENCES document_metadata(id),\n    row_data JSONB  -- Store the actual row data\n);",
        "options": {},
        "operation": "executeQuery"
      },
      "typeVersion": 2.5
    },
    {
      "id": "55ff6535-bedb-479f-b3da-eb45e1127e77",
      "name": "Listar Documentos",
      "type": "n8n-nodes-base.postgresTool",
      "position": [
        1840,
        512
      ],
      "parameters": {
        "table": {
          "__rl": true,
          "mode": "list",
          "value": "document_metadata",
          "cachedResultName": "document_metadata"
        },
        "schema": {
          "__rl": true,
          "mode": "list",
          "value": "public"
        },
        "options": {},
        "operation": "select",
        "returnAll": true,
        "descriptionType": "manual",
        "toolDescription": "Use this tool to fetch all available documents, including the table schema if the file is a CSV or Excel file."
      },
      "typeVersion": 2.5
    },
    {
      "id": "ffcb630b-5119-4ff6-b85a-d77eeb8d5713",
      "name": "Obtener Contenido de Archivo",
      "type": "n8n-nodes-base.postgresTool",
      "position": [
        1984,
        512
      ],
      "parameters": {
        "query": "SELECT \n    string_agg(text, ' ') as document_text\nFROM documents_pg\n  WHERE metadata->>'file_id' = $1\nGROUP BY metadata->>'file_id';",
        "options": {
          "queryReplacement": "={{ $fromAI('file_id') }}"
        },
        "operation": "executeQuery",
        "descriptionType": "manual",
        "toolDescription": "Given a file ID, fetches the text from the document."
      },
      "typeVersion": 2.5
    },
    {
      "id": "f504b2f4-ffb5-4ef7-ba93-753151b77d9e",
      "name": "Consultar Filas de Documentos",
      "type": "n8n-nodes-base.postgresTool",
      "position": [
        2144,
        512
      ],
      "parameters": {
        "query": "{{ $fromAI('sql_query') }}",
        "options": {},
        "operation": "executeQuery",
        "descriptionType": "manual",
        "toolDescription": "Run a SQL query - use this to query from the document_rows table once you know the file ID (which is the file path) you are querying. dataset_id is the file_id (file path) and you are always using the row_data for filtering, which is a jsonb field that has all the keys from the file schema given in the document_metadata table.\n\nExample query:\n\nSELECT AVG((row_data->>'revenue')::numeric)\nFROM document_rows\nWHERE dataset_id = '/data/shared/document.csv';\n\nExample query 2:\n\nSELECT \n    row_data->>'category' as category,\n    SUM((row_data->>'sales')::numeric) as total_sales\nFROM dataset_rows\nWHERE dataset_id = '/data/shared/document2.csv'\nGROUP BY row_data->>'category';"
      },
      "typeVersion": 2.5
    },
    {
      "id": "4abe03ca-297c-4509-b0db-7bed4338a158",
      "name": "Iterar sobre Elementos",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        800,
        800
      ],
      "parameters": {
        "options": {
          "reset": false
        }
      },
      "typeVersion": 3
    },
    {
      "id": "e382d750-85ba-492d-9d3e-eb839af0bfc1",
      "name": "Insertar Metadatos de Documento",
      "type": "n8n-nodes-base.postgres",
      "position": [
        1488,
        832
      ],
      "parameters": {
        "table": {
          "__rl": true,
          "mode": "list",
          "value": "document_metadata",
          "cachedResultName": "document_metadata"
        },
        "schema": {
          "__rl": true,
          "mode": "list",
          "value": "public"
        },
        "columns": {
          "value": {
            "id": "={{ $('Set File ID').item.json.file_id }}",
            "title": "={{ $('Set File ID').item.json.file_title }}"
          },
          "schema": [
            {
              "id": "id",
              "type": "string",
              "display": true,
              "removed": false,
              "required": true,
              "displayName": "id",
              "defaultMatch": true,
              "canBeUsedToMatch": true
            },
            {
              "id": "title",
              "type": "string",
              "display": true,
              "required": false,
              "displayName": "title",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            },
            {
              "id": "url",
              "type": "string",
              "display": true,
              "removed": true,
              "required": false,
              "displayName": "url",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            },
            {
              "id": "created_at",
              "type": "dateTime",
              "display": true,
              "required": false,
              "displayName": "created_at",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            },
            {
              "id": "schema",
              "type": "string",
              "display": true,
              "removed": true,
              "required": false,
              "displayName": "schema",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "id"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "upsert"
      },
      "executeOnce": true,
      "typeVersion": 2.5
    },
    {
      "id": "bbf6f704-b4a2-4ff2-ac09-27626526b35f",
      "name": "Insertar Filas de Tabla",
      "type": "n8n-nodes-base.postgres",
      "position": [
        2544,
        1088
      ],
      "parameters": {
        "table": {
          "__rl": true,
          "mode": "list",
          "value": "document_rows",
          "cachedResultName": "document_rows"
        },
        "schema": {
          "__rl": true,
          "mode": "list",
          "value": "public"
        },
        "columns": {
          "value": {
            "row_data": "={{ $json.toJsonString().replaceAll(/'/g, \"''\") }}",
            "dataset_id": "={{ $('Set File ID').item.json.file_id }}"
          },
          "schema": [
            {
              "id": "id",
              "type": "number",
              "display": true,
              "removed": true,
              "required": false,
              "displayName": "id",
              "defaultMatch": true,
              "canBeUsedToMatch": true
            },
            {
              "id": "dataset_id",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "dataset_id",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            },
            {
              "id": "row_data",
              "type": "object",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "row_data",
              "defaultMatch": false,
              "canBeUsedToMatch": true
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "id"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {}
      },
      "typeVersion": 2.5
    },
    {
      "id": "3265a7df-dd40-421e-b1fb-53293a7460f8",
      "name": "Actualizar Esquema para Metadatos de Documentos",
      "type": "n8n-nodes-base.postgres",
      "position": [
        3408,
        848
      ],
      "parameters": {
        "table": {
          "__rl": true,
          "mode": "list",
          "value": "document_metadata",
          "cachedResultName": "document_metadata"
        },
        "schema": {
          "__rl": true,
          "mode": "list",
          "value": "public"
        },
        "columns": {
          "value": {
            "id": "={{ $('Set File ID').item.json.file_id }}",
            "schema": "={{ $json.schema }}"
          },
          "schema": [
            {
              "id": "id",
              "type": "string",
              "display": true,
              "removed": false,
              "required": true,
              "displayName": "id",
              "defaultMatch": true,
              "canBeUsedToMatch": true
            },
            {
              "id": "title",
              "type": "string",
              "display": true,
              "removed": true,
              "required": false,
              "displayName": "title",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            },
            {
              "id": "url",
              "type": "string",
              "display": true,
              "removed": true,
              "required": false,
              "displayName": "url",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            },
            {
              "id": "created_at",
              "type": "dateTime",
              "display": true,
              "required": false,
              "displayName": "created_at",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            },
            {
              "id": "schema",
              "type": "string",
              "display": true,
              "removed": false,
              "required": false,
              "displayName": "schema",
              "defaultMatch": false,
              "canBeUsedToMatch": false
            }
          ],
          "mappingMode": "defineBelow",
          "matchingColumns": [
            "id"
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {},
        "operation": "upsert"
      },
      "typeVersion": 2.5
    },
    {
      "id": "53f9f045-bb08-4b22-a11e-dfd2c964b687",
      "name": "Nota Adhesiva9",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        0,
        0
      ],
      "parameters": {
        "color": 6,
        "width": 540,
        "height": 1320,
        "content": "## 🚀 n8n Local AI Agentic RAG Template\n\n**Author:** [Jadai kongolo](https://my.jadaikongolo.tech)\n\n## What is this?\nThis template provides an entirely local implementation of an **Agentic RAG (Retrieval Augmented Generation)** system in n8n that can be extended easily for your specific use case and knowledge base. Unlike standard RAG which only performs simple lookups, this agent can reason about your knowledge base, self-improve retrieval, and dynamically switch between different tools based on the specific question. \n\n## Why Agentic RAG?\nStandard RAG has significant limitations:\n- Poor analysis of numerical/tabular data\n- Missing context due to document chunking\n- Inability to connect information across documents\n- No dynamic tool selection based on question type\n\n## What makes this template powerful:\n- **Intelligent tool selection**: Switches between RAG lookups, SQL queries, or full document retrieval based on the question\n- **Complete document context**: Accesses entire documents when needed instead of just chunks\n- **Accurate numerical analysis**: Uses SQL for precise calculations on spreadsheet/tabular data\n- **Cross-document insights**: Connects information across your entire knowledge base\n- **Multi-file processing**: Handles multiple documents in a single workflow loop\n- **Efficient storage**: Uses JSONB in Supabase to store tabular data without creating new tables for each CSV\n\n## Getting Started\n1. Run the table creation nodes first to set up your database tables in Supabase\n2. Upload your documents to the folder on your computer that is mounted to /data/shared in the n8n container. This folder by default is the \"shared\" folder in the local AI package.\n3. The agent will process them automatically (chunking text, storing tabular data in Supabase)\n4. Start asking questions that leverage the agent's multiple reasoning approaches\n\n## Customization\nThis template provides a solid foundation that you can extend by:\n- Tuning the system prompt for your specific use case\n- Adding document metadata like summaries\n- Implementing more advanced RAG techniques\n- Optimizing for larger knowledge bases\n\n---\n\nThe non-local (\"cloud\") version of this Agentic RAG agent can be [found here](https://kongolo.gumroad.com/l/anxwv)."
      },
      "typeVersion": 1
    },
    {
      "id": "cdee87fe-e154-47ab-9330-32dee5c213d3",
      "name": "Disparador de Archivo Local",
      "type": "n8n-nodes-base.localFileTrigger",
      "position": [
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        800
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      "parameters": {
        "path": "/data/shared",
        "events": [
          "add",
          "change"
        ],
        "options": {
          "usePolling": true,
          "followSymlinks": true
        },
        "triggerOn": "folder"
      },
      "typeVersion": 1
    },
    {
      "id": "67311475-7928-4ddc-957a-79817c98d26d",
      "name": "Leer/Escribir Archivos del Disco",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        1648,
        960
      ],
      "parameters": {
        "options": {
          "dataPropertyName": "=data"
        },
        "fileSelector": "={{ $('Set File ID').item.json.file_id }}"
      },
      "typeVersion": 1
    },
    {
      "id": "366e800a-9bd7-4822-a11c-f555800bbba6",
      "name": "Embeddings Ollama",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
      "position": [
        3072,
        1280
      ],
      "parameters": {
        "model": "nomic-embed-text:latest"
      },
      "typeVersion": 1
    },
    {
      "id": "be37cfb9-ea40-4244-87d7-b562be315573",
      "name": "Embeddings Ollama1",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOllama",
      "position": [
        2560,
        480
      ],
      "parameters": {
        "model": "nomic-embed-text:latest"
      },
      "typeVersion": 1
    },
    {
      "id": "1306b972-2b24-4c62-846e-f1c5b3d0482c",
      "name": "Divisor de Texto Recursivo por Caracteres",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        3200,
        1408
      ],
      "parameters": {
        "options": {},
        "chunkSize": 400
      },
      "typeVersion": 1
    },
    {
      "id": "677ad468-8118-4f8f-9a47-f5429cdc7582",
      "name": "Ollama (Cambiar URL Base)",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        1568,
        512
      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "qwen2.5:14b-8k",
          "cachedResultName": "qwen2.5:14b-8k"
        },
        "options": {}
      },
      "typeVersion": 1.2
    },
    {
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      "name": "Nota Adhesiva4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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        "width": 540,
        "height": 200,
        "content": "## NOTE\n\nThe Ollama chat model node doesn't work with the RAG nodes - known issue with n8n.\n\nSo for now, we are using the OpenAI chat model but changing the base URL to Ollama when creating the credentials (i.e. http://ollama:11434/v1). The API key can be set to whatever, it isn't used for local LLMs."
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      "type": "n8n-nodes-base.postgres",
      "position": [
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      ],
      "parameters": {
        "query": "DO $$\nBEGIN\n    IF EXISTS (SELECT 1 FROM information_schema.tables WHERE table_name = 'documents_pg') THEN\n        EXECUTE 'DELETE FROM documents_pg WHERE metadata->>''file_id'' LIKE ''%' || $1 || '%''';\n    END IF;\nEND\n$$;",
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      "name": "Eliminar Registros Antiguos de Datos",
      "type": "n8n-nodes-base.postgres",
      "position": [
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      ],
      "parameters": {
        "query": "DELETE FROM document_rows\nWHERE dataset_id LIKE '%' || $1 || '%';",
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      "name": "Almacén Postgres PGVector",
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      "position": [
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      ],
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        "mode": "insert",
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        "tableName": "documents_pg"
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        "toolName": "documents",
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