Chatbot RAG básico

Name: Chatbot RAG básico
Rating: 4.5 (10 reviews)
Author: JustinLee

Intermedio

Este es unSupport, Building Blocks, AIflujo de automatización del dominio deautomatización que contiene 14 nodos.Utiliza principalmente nodos como ManualTrigger, ReadWriteFile, LmChatGroq, ChatTrigger, ChainRetrievalQa, combinando tecnología de inteligencia artificial para lograr automatización inteligente. Chat básico RAG

Requisitos previos

•Clave de API de servicio de IA (como OpenAI, Anthropic, etc.)

Nodos utilizados (14)

DocumentDefaultDataLoader

TextSplitterRecursiveCharacterTextSplitter

Categoría

Soporte

Bloques de construcción

Inteligencia Artificial

Vista previa del flujo de trabajo

Visualización de las conexiones entre nodos, con soporte para zoom y panorámica

Recursive Character Text Splitter

Default Data Loader

Question and Answer Cadena

Almacén de vectores Retriever

Al hacer clic 'Test Workflow' button

Al hacer clic 'Chat' button below

Read/Write Files from Disk

In-Memory Almacén de vectores1

In-Memory Almacén de vectores

Incrustaciones Cohere

Groq Chat Model

Incrustaciones Cohere1

React Flow

Exportar flujo de trabajo

Copie la siguiente configuración JSON en n8n para importar y usar este flujo de trabajo

{
  "nodes": [
    {
      "id": "3bc2f88b-c14e-4ee5-84ce-dc16a54aa12b",
      "name": "Recursive Character Text Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
      "position": [
        -580,
        320
      ],
      "parameters": {
        "options": {
          "splitCode": "markdown"
        },
        "chunkOverlap": 50
      },
      "typeVersion": 1
    },
    {
      "id": "6bd91468-17db-4918-a232-87fb295a30c2",
      "name": "Nota Adhesiva",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1240,
        -140
      ],
      "parameters": {
        "color": 7,
        "width": 978.0454109366399,
        "height": 806.6556079800943,
        "content": "### Load data into database\nFetch file from Google Drive, split it into chunks and insert into Pinecone index"
      },
      "typeVersion": 1
    },
    {
      "id": "3af4e8e9-0503-470e-b449-4551191fb405",
      "name": "Nota Adhesiva1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        0,
        -160
      ],
      "parameters": {
        "color": 7,
        "width": 795.4336844920119,
        "height": 849.4411596574598,
        "content": "### Chat with database\nEmbed the incoming chat message and use it retrieve relevant chunks from the vector store. These are passed to the model to formulate an answer "
      },
      "typeVersion": 1
    },
    {
      "id": "6f94ec58-4fca-40ee-a1a0-012998093589",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        -580,
        200
      ],
      "parameters": {
        "options": {},
        "dataType": "binary"
      },
      "typeVersion": 1
    },
    {
      "id": "3e145342-458d-4222-a707-9fee78e91c4d",
      "name": "Question and Answer Cadena",
      "type": "@n8n/n8n-nodes-langchain.chainRetrievalQa",
      "position": [
        60,
        -20
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.2
    },
    {
      "id": "7f2b288a-a002-4cd3-93c0-b2a0e491699c",
      "name": "Almacén de vectores Retriever",
      "type": "@n8n/n8n-nodes-langchain.retrieverVectorStore",
      "position": [
        240,
        200
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "ca930ba7-b45d-47d8-9f36-9db3a25ee77a",
      "name": "Al hacer clic 'Test Workflow' button",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -1420,
        -20
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "90782052-5df2-4f1e-84fc-c47095a81852",
      "name": "Al hacer clic 'Chat' button below",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        -140,
        -20
      ],
      "webhookId": "066b342b-f2b6-401e-b560-12f5d23b6103",
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "712dc9d3-af2d-4436-9315-78f66f748b91",
      "name": "Read/Write Files from Disk",
      "type": "n8n-nodes-base.readWriteFile",
      "position": [
        -1200,
        -20
      ],
      "parameters": {
        "options": {},
        "fileSelector": "/tmp/external_data/news.txt"
      },
      "typeVersion": 1,
      "alwaysOutputData": true
    },
    {
      "id": "1cd768c1-fcc0-480a-8b33-fbe714788b32",
      "name": "In-Memory Almacén de vectores1",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
      "position": [
        240,
        380
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "2393e667-7e4f-4392-9a7e-b2b4d74d46e8",
      "name": "In-Memory Almacén de vectores",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreInMemory",
      "position": [
        -980,
        -20
      ],
      "parameters": {
        "mode": "insert",
        "clearStore": true
      },
      "typeVersion": 1
    },
    {
      "id": "e53f51f3-04f3-46ef-aebd-e0b32b415101",
      "name": "Incrustaciones Cohere",
      "type": "@n8n/n8n-nodes-langchain.embeddingsCohere",
      "position": [
        -940,
        300
      ],
      "parameters": {
        "modelName": "embed-multilingual-v3.0"
      },
      "credentials": {
        "cohereApi": {
          "id": "rXh87ikYuJfDKuCk",
          "name": "CohereApi account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "cf1333b6-b69b-4ff1-bfc3-d3d579585efb",
      "name": "Groq Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatGroq",
      "notes": "使用繁體中文",
      "position": [
        100,
        220
      ],
      "parameters": {
        "model": "llama-3.3-70b-versatile",
        "options": {}
      },
      "credentials": {
        "groqApi": {
          "id": "dznjL979E8j0L4Zc",
          "name": "Groq account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "e49cfb2e-5eca-4b43-973d-4bf7285b5d94",
      "name": "Incrustaciones Cohere1",
      "type": "@n8n/n8n-nodes-langchain.embeddingsCohere",
      "position": [
        340,
        560
      ],
      "parameters": {
        "modelName": "embed-multilingual-v3.0"
      },
      "credentials": {
        "cohereApi": {
          "id": "rXh87ikYuJfDKuCk",
          "name": "CohereApi account"
        }
      },
      "typeVersion": 1
    }
  ],
  "connections": {
    "cf1333b6-b69b-4ff1-bfc3-d3d579585efb": {
      "ai_languageModel": [
        [
          {
            "node": "Question and Answer Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings Cohere": {
      "ai_embedding": [
        [
          {
            "node": "In-Memory Vector Store",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings Cohere1": {
      "ai_embedding": [
        [
          {
            "node": "In-Memory Vector Store1",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "6f94ec58-4fca-40ee-a1a0-012998093589": {
      "ai_document": [
        [
          {
            "node": "In-Memory Vector Store",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Vector Store Retriever": {
      "ai_retriever": [
        [
          {
            "node": "Question and Answer Chain",
            "type": "ai_retriever",
            "index": 0
          }
        ]
      ]
    },
    "In-Memory Vector Store1": {
      "ai_vectorStore": [
        [
          {
            "node": "Vector Store Retriever",
            "type": "ai_vectorStore",
            "index": 0
          }
        ]
      ]
    },
    "712dc9d3-af2d-4436-9315-78f66f748b91": {
      "main": [
        [
          {
            "node": "In-Memory Vector Store",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "3bc2f88b-c14e-4ee5-84ce-dc16a54aa12b": {
      "ai_textSplitter": [
        [
          {
            "node": "6f94ec58-4fca-40ee-a1a0-012998093589",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "When clicking 'Chat' button below": {
      "main": [
        [
          {
            "node": "Question and Answer Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When clicking 'Test Workflow' button": {
      "main": [
        [
          {
            "node": "712dc9d3-af2d-4436-9315-78f66f748b91",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}

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?

Intermedio - Soporte, Bloques de construcción, 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.