Insertar y recuperar documentos

Avanzado

Este es unAIflujo de automatización del dominio deautomatización que contiene 25 nodos.Utiliza principalmente nodos como Set, Code, Html, Limit, SplitOut, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Construir un sistema de preguntas y respuestas RAG con citas usando los Essays de Paul, Milvus y OpenAI

Requisitos previos
  • Pueden requerirse credenciales de autenticación para la API de destino
  • Clave de API de OpenAI
Vista previa del flujo de trabajo
Visualización de las conexiones entre nodos, con soporte para zoom y panorámica
Exportar flujo de trabajo
Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo
{
  "id": "Hjyv9FkH5Oh6Yxw4",
  "meta": {
    "instanceId": "2c4c1e23e7b067270c08aab616bada21d0c384d16f212b23cf1143c6baa09219"
  },
  "name": "Insert and retrieve documents",
  "tags": [
    {
      "id": "msnDWKHQmwMDxWQH",
      "name": "Milvus",
      "createdAt": "2025-04-16T12:48:14.539Z",
      "updatedAt": "2025-04-16T12:48:14.539Z"
    },
    {
      "id": "tnCpo8hq8uKrdASK",
      "name": "AI",
      "createdAt": "2025-04-16T12:47:57.976Z",
      "updatedAt": "2025-04-16T12:47:57.976Z"
    }
  ],
  "nodes": [
    {
      "id": "52044ccd-4e0d-4353-b612-cf8db1b55331",
      "name": "Al hacer clic en \"Ejecutar Flujo de Trabajo\"",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
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      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "b6993775-d21b-4ae8-a59c-43aef2b7002b",
      "name": "Obtener Lista de Ensayos",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -220,
        -100
      ],
      "parameters": {
        "url": "http://www.paulgraham.com/articles.html",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "cbaeb236-5c93-4b34-a06b-ff0e5de8525f",
      "name": "Extraer nombres de ensayos",
      "type": "n8n-nodes-base.html",
      "position": [
        -20,
        -100
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "essay",
              "attribute": "href",
              "cssSelector": "table table a",
              "returnArray": true,
              "returnValue": "attribute"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "d92b6692-4a02-4519-b113-8a9172c71de9",
      "name": "Dividir en elementos",
      "type": "n8n-nodes-base.splitOut",
      "position": [
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      "parameters": {
        "options": {},
        "fieldToSplitOut": "essay"
      },
      "typeVersion": 1
    },
    {
      "id": "d16ba71b-10fc-454f-8bfc-a6826280a4e7",
      "name": "Obtener textos de ensayos",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        580,
        -100
      ],
      "parameters": {
        "url": "=http://www.paulgraham.com/{{ $json.essay }}",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "c4fa74ea-6af5-410c-bf5c-9d8d3decf31b",
      "name": "Limitar a los primeros 3",
      "type": "n8n-nodes-base.limit",
      "position": [
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        -100
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      "parameters": {
        "maxItems": 3
      },
      "typeVersion": 1
    },
    {
      "id": "3da8495b-62df-475d-b99d-e0f3c64266e3",
      "name": "Extraer Solo Texto",
      "type": "n8n-nodes-base.html",
      "position": [
        900,
        -100
      ],
      "parameters": {
        "options": {},
        "operation": "extractHtmlContent",
        "extractionValues": {
          "values": [
            {
              "key": "data",
              "cssSelector": "body",
              "skipSelectors": "img,nav"
            }
          ]
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "4a9b5d5d-fc94-40b7-af0c-13d992bc1eb9",
      "name": "Nota Adhesiva3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -300,
        -220
      ],
      "parameters": {
        "width": 1071.752021563343,
        "height": 285.66037735849045,
        "content": "## Scrape latest Paul Graham essays"
      },
      "typeVersion": 1
    },
    {
      "id": "b8a7a288-186f-4444-b0de-33ed90009c0a",
      "name": "Nota Adhesiva5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        820,
        -220
      ],
      "parameters": {
        "width": 625,
        "height": 607,
        "content": "## Load into Milvus vector store"
      },
      "typeVersion": 1
    },
    {
      "id": "c9e7b166-cc65-47e2-a437-9c00017b492a",
      "name": "Divisor de Texto Recursivo por Caracteres1",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        1240,
        240
      ],
      "parameters": {
        "options": {},
        "chunkSize": 6000
      },
      "typeVersion": 1
    },
    {
      "id": "e1a75f27-7c8c-4d0d-9b0f-33fe9ec96fc6",
      "name": "Generar respuesta",
      "type": "n8n-nodes-base.set",
      "position": [
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      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "11396286-0378-4c3a-86e1-c9ef51afbfc7",
              "name": "text",
              "type": "string",
              "value": "={{ $json.answer }} {{ $if(!$json.citations.isEmpty(), \"\\n\" + $json.citations.join(\"\"), '') }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "8b3497ad-5bc8-44b3-bdf4-3a028fe265ce",
      "name": "Componer citas",
      "type": "n8n-nodes-base.set",
      "position": [
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      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "ace6185e-8b3d-4f89-ae36-dfe0c391a0a9",
              "name": "citations",
              "type": "array",
              "value": "={{ $json.citations.map(i => '[' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata.file_name + ', lines ' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata['loc.lines.from'] + '-' + $('Get top chunks matching query').all()[$json.citations].json.document.metadata['loc.lines.to'] + ']') }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
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      "name": "Responder la consulta basado en fragmentos",
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "position": [
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      ],
      "parameters": {
        "text": "={{ $json.context }}\n\nQuestion: {{ $('When chat message received').first().json.chatInput }}\nHelpful Answer:",
        "options": {
          "systemPromptTemplate": "=Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer. Important: In your response, also include the the indexes of the chunks you used to generate the answer."
        },
        "schemaType": "manual",
        "inputSchema": "{\n  \"type\": \"object\",\n  \"required\": [\"answer\", \"citations\"],\n  \"properties\": {\n    \"answer\": {\n      \"type\": \"string\"\n    },\n    \"citations\": {\n      \"type\": \"array\",\n      \"items\": {\n        \"type\": \"number\"\n      }\n    }\n  }\n}"
      },
      "typeVersion": 1
    },
    {
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      "name": "Preparar fragmentos",
      "type": "n8n-nodes-base.code",
      "position": [
        480,
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      "parameters": {
        "jsCode": "let out = \"\"\nfor (const i in $input.all()) {\n  let itemText = \"--- CHUNK \" + i + \" ---\\n\"\n  itemText += $input.all()[i].json.document.pageContent + \"\\n\"\n  itemText += \"\\n\"\n  out += itemText\n}\n\nreturn {\n  'context': out\n};"
      },
      "typeVersion": 2
    },
    {
      "id": "379837f2-4f96-43ff-8e87-722cbe6d652f",
      "name": "Establecer máximo de fragmentos a enviar al modelo",
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      "parameters": {
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              "value": 4
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        "includeOtherFields": true
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      "name": "Embeddings OpenAI2",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
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      "parameters": {
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        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "hH2PTDH4fbS7fdPv",
          "name": "OpenAi account"
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      "typeVersion": 1.2
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    {
      "id": "efb030f4-445b-4ba0-b5c9-95e4e5893664",
      "name": "Cuando se recibe un mensaje de chat",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
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      "webhookId": "cd2703a7-f912-46fe-8787-3fb83ea116ab",
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    {
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      "name": "Nota Adhesiva1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -380,
        440
      ],
      "parameters": {
        "color": 7,
        "width": 1594,
        "height": 529,
        "content": ""
      },
      "typeVersion": 1
    },
    {
      "id": "2e27f3d8-e8a2-4647-80dd-f2643b224cb5",
      "name": "Almacén Vectorial Milvus en recuperación",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreMilvus",
      "position": [
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      ],
      "parameters": {
        "mode": "load",
        "topK": 2,
        "prompt": "answer the question",
        "milvusCollection": {
          "__rl": true,
          "mode": "list",
          "value": "my_collection",
          "cachedResultName": "my_collection"
        }
      },
      "credentials": {
        "milvusApi": {
          "id": "8tMHHoLiWXIAXa7S",
          "name": "Milvus account"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "a3cf7e0e-f681-4880-9ccf-5c42d5457c0f",
      "name": "Almacén Vectorial Milvus",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreMilvus",
      "position": [
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        -100
      ],
      "parameters": {
        "mode": "insert",
        "options": {
          "clearCollection": true
        },
        "milvusCollection": {
          "__rl": true,
          "mode": "list",
          "value": "my_collection",
          "cachedResultName": "my_collection"
        }
      },
      "credentials": {
        "milvusApi": {
          "id": "8tMHHoLiWXIAXa7S",
          "name": "Milvus account"
        }
      },
      "typeVersion": 1.1
    },
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      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "parameters": {
        "width": 280,
        "height": 180,
        "content": "## Step 1\n1. Set up a Milvus server based on [this guide](https://milvus.io/docs/install_standalone-docker-compose.md). And then create a collection named `my_collection`.\n2. Click this workflow to load scrape and load Paul Graham essays to Milvus collection.\n"
      },
      "typeVersion": 1
    },
    {
      "id": "18f42da4-42ea-4eb0-9c43-ef8bd31ab7ff",
      "name": "Nota Adhesiva2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -680,
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      ],
      "parameters": {
        "height": 120,
        "content": "## Step 2\nChat and get citations in response"
      },
      "typeVersion": 1
    },
    {
      "id": "0af427ed-d901-4192-9fdc-986a63fd585b",
      "name": "Embeddings OpenAI",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
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      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "hH2PTDH4fbS7fdPv",
          "name": "OpenAi account"
        }
      },
      "typeVersion": 1.2
    },
    {
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      "name": "Cargador de Datos Predeterminado",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        1160,
        120
      ],
      "parameters": {
        "options": {},
        "jsonData": "={{ $('Extract Text Only').item.json.data }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "b49eb3ae-82cb-4d87-8f22-0789b3a14d83",
      "name": "Modelo de Chat OpenAI",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
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      ],
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "options": {}
      },
      "credentials": {
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          "name": "OpenAi account"
        }
      },
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  ],
  "active": false,
  "pinData": {},
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    "executionOrder": "v1"
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Preguntas frecuentes

¿Cómo usar este flujo de trabajo?

Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.

¿En qué escenarios es adecuado este flujo de trabajo?

Avanzado - Inteligencia Artificial

¿Es de pago?

Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.

Información del flujo de trabajo
Nivel de dificultad
Avanzado
Número de nodos25
Categoría1
Tipos de nodos15
Descripción de la dificultad

Adecuado para usuarios avanzados, flujos de trabajo complejos con 16+ nodos

Autor
Cheney Zhang

Cheney Zhang

@zc277584121

Algorithm engineer at Zilliz, dedicating to the application of vector databases in the AI ecosystem.

Enlaces externos
Ver en n8n.io

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Categorías

Categorías: 34