8
n8n 中文网amn8n.com

使用Jotform、Supabase上的RAG、Together AI和Gemini构建知识库聊天机器人

中级

这是一个自动化工作流，包含 15 个节点。主要使用 Code, Supabase, Aggregate, HttpRequest, JotFormTrigger 等节点。 使用Jotform、Supabase上的RAG、Together AI和Gemini构建知识库聊天机器人

前置要求
  • •Supabase URL 和 API Key
  • •可能需要目标 API 的认证凭证
  • •Google Gemini API Key

使用的节点 (15)

Code
Supabase
Aggregate
StickyNote
HttpRequest
JotFormTrigger
Agent
ExtractFromFile
ChatTrigger
LmChatGoogleGemini

分类

-
工作流预览
可视化展示节点连接关系，支持缩放和平移
React Flow
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
  "meta": {
    "instanceId": "93f396852104089b8670e7494b0f3668b420464668ae4a8c1d6b4b5799f8e3ef",
    "templateCredsSetupCompleted": true
  },
  "nodes": [
    {
      "id": "1c57da69-7af2-47c8-8bc2-92e49449bd81",
      "name": "分块处理",
      "type": "n8n-nodes-base.code",
      "position": [
        2192,
        -496
      ],
      "parameters": {
        "jsCode": "const text = $input.first().json.text;\nconst chunkSize = 1000;\n\nlet chunks = [];\nfor (let i = 0; i < text.length; i += chunkSize) {\n  chunks.push({\n    json: { chunk: text.slice(i, i + chunkSize) }\n  });\n}\n\nreturn chunks;\n\n"
      },
      "typeVersion": 2
    },
    {
      "id": "d5ed1aaf-6089-4731-980d-b5c356b22403",
      "name": "嵌入上传文档",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        2416,
        -496
      ],
      "parameters": {
        "url": "https://api.together.xyz/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "sendHeaders": true,
        "authentication": "genericCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "model",
              "value": "BAAI/bge-large-en-v1.5"
            },
            {
              "name": "input",
              "value": "={{ $json.chunk }}"
            }
          ]
        },
        "genericAuthType": "httpBearerAuth",
        "headerParameters": {
          "parameters": [
            {
              "name": "Content-Type",
              "value": "application/json"
            }
          ]
        }
      },
      "credentials": {
        "httpBearerAuth": {
          "id": "ePx2TlbqIiRjDGfW",
          "name": "Together API"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "0b1c609f-e335-4541-8dae-e3517ec4bb63",
      "name": "将嵌入保存到数据库",
      "type": "n8n-nodes-base.supabase",
      "position": [
        2624,
        -496
      ],
      "parameters": {
        "tableId": "RAG",
        "fieldsUi": {
          "fieldValues": [
            {
              "fieldId": "chunk",
              "fieldValue": "={{ $('Splitting into Chunks').item.json.chunk }}"
            },
            {
              "fieldId": "embeddings",
              "fieldValue": "={{ JSON.stringify($json.data[0].embedding) }}"
            }
          ]
        }
      },
      "credentials": {
        "supabaseApi": {
          "id": "sNLLVD1n1FkMp81B",
          "name": "abhi.vaar"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "3a39d174-434e-4c81-921c-8a354fad5ebe",
      "name": "聚合",
      "type": "n8n-nodes-base.aggregate",
      "position": [
        2064,
        64
      ],
      "parameters": {
        "options": {},
        "fieldsToAggregate": {
          "fieldToAggregate": [
            {
              "fieldToAggregate": "chunk"
            }
          ]
        }
      },
      "typeVersion": 1
    },
    {
      "id": "4ce2ab5b-bb1e-46ce-9dd8-2cfdee5510a2",
      "name": "搜索嵌入",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1840,
        64
      ],
      "parameters": {
        "url": "https://enter-your-supabase-host/rest/v1/rpc/matchembeddings1",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "authentication": "predefinedCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "=query_embedding",
              "value": "={{ $json.data[0].embedding }}"
            },
            {
              "name": "match_count",
              "value": "5"
            }
          ]
        },
        "nodeCredentialType": "supabaseApi"
      },
      "credentials": {
        "supabaseApi": {
          "id": "sNLLVD1n1FkMp81B",
          "name": "abhi.vaar"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "76c8df3f-cf64-4848-b077-d04e9de88d12",
      "name": "嵌入用户消息",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1616,
        64
      ],
      "parameters": {
        "url": "https://api.together.xyz/v1/embeddings",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "authentication": "genericCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "model",
              "value": "BAAI/bge-large-en-v1.5"
            },
            {
              "name": "input",
              "value": "={{ $json.chatInput }}"
            }
          ]
        },
        "genericAuthType": "httpBearerAuth"
      },
      "credentials": {
        "httpBearerAuth": {
          "id": "ePx2TlbqIiRjDGfW",
          "name": "Together API"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "d8dba80c-597e-470b-852b-6d53363238bc",
      "name": "Google Gemini 聊天模型",
      "type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
      "position": [
        2272,
        288
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "googlePalmApi": {
          "id": "qsaK3VMNWQDWLweQ",
          "name": "Google Gemini(PaLM) Api account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "f74c0006-15e0-4f48-8c02-b0b765154c5b",
      "name": "AI Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        2272,
        64
      ],
      "parameters": {
        "text": "=You are a helpful and professional customer support agent. Use the following context to answer the user's question. \n\nHandle greetings without the need of the context...\n\nContext:\n{{ $json.chunk }}\n\nUser's message:\n{{ $('When chat message received').item.json.chatInput }}\n\nFormat your reply in WhatsApp style:\n- Use _italics_ for emphasis\n- Use *bold* for key points\n- Use • for bullet lists (no markdown dashes or hashes)\n- Keep responses short, clear, and conversational, like real WhatsApp support\n- Avoid markdown headers or code blocks\n\nGive a clear, accurate, and friendly response based only on the context.  \nIf the answer cannot be found in the context, reply: _\"I don't know based on the provided information.\"_\n",
        "options": {},
        "promptType": "define"
      },
      "typeVersion": 2.2
    },
    {
      "id": "81c63733-c5c8-4a4d-b634-e3d93d9bb1c6",
      "name": "从PDF文件提取文本",
      "type": "n8n-nodes-base.extractFromFile",
      "position": [
        2000,
        -496
      ],
      "parameters": {
        "options": {},
        "operation": "pdf"
      },
      "typeVersion": 1
    },
    {
      "id": "490c541e-fae8-4965-9840-9e13d562acdd",
      "name": "当收到聊天消息时",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        1392,
        64
      ],
      "webhookId": "2032c492-7d92-4d79-b545-5e0b9807253f",
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.3
    },
    {
      "id": "8add4f5e-d2f8-4ea8-a6e1-6d4912d60393",
      "name": "便签",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1296,
        -768
      ],
      "parameters": {
        "width": 1584,
        "height": 512,
        "content": "### 第1部分：为AI提供知识（\"图书管理员\"部分）"
      },
      "typeVersion": 1
    },
    {
      "id": "d764c67f-cca8-476e-8d63-78d2733f6b64",
      "name": "便签1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        1296,
        -208
      ],
      "parameters": {
        "width": 1600,
        "height": 656,
        "content": "---"
      },
      "typeVersion": 1
    },
    {
      "id": "d1f68d16-6baa-4420-8606-dbc7ca5791c7",
      "name": "JotForm 触发器",
      "type": "n8n-nodes-base.jotFormTrigger",
      "position": [
        1376,
        -496
      ],
      "webhookId": "52c8e2e7-7277-4dfd-8336-c3857f945102",
      "parameters": {
        "form": "252862840518058",
        "onlyAnswers": false
      },
      "credentials": {
        "jotFormApi": {
          "id": "4612J1BsqtC505ac",
          "name": "secondary"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "8f035b6b-c3c0-449a-acb4-0c359c309e32",
      "name": "获取新知识库",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1584,
        -496
      ],
      "parameters": {
        "url": "=https://api.jotform.com/submission/{{ $json.submissionID }}?apiKey=enter-your-jotfomr-api",
        "options": {}
      },
      "typeVersion": 4.2
    },
    {
      "id": "b826edc5-d97f-498c-bea1-b3f3d1430635",
      "name": "获取上传的知识库文件链接",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        1792,
        -496
      ],
      "parameters": {
        "url": "={{ $json.content.answers['6'].answer[0] }}",
        "options": {
          "response": {
            "response": {
              "responseFormat": "file"
            }
          }
        },
        "sendHeaders": true,
        "headerParameters": {
          "parameters": [
            {
              "name": "APIKEY",
              "value": "enter-your-jotfomr-api"
            }
          ]
        }
      },
      "typeVersion": 4.2
    }
  ],
  "pinData": {},
  "connections": {
    "AI Agent": {
      "main": [
        []
      ]
    },
    "Aggregate": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "JotForm Trigger": {
      "main": [
        [
          {
            "node": "Grab New knowledgebase",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Search Embeddings": {
      "main": [
        [
          {
            "node": "Aggregate",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embend User Message": {
      "main": [
        [
          {
            "node": "Search Embeddings",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Splitting into Chunks": {
      "main": [
        [
          {
            "node": "Embedding Uploaded document",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Grab New knowledgebase": {
      "main": [
        [
          {
            "node": "Grab the uploaded knowledgebase file link",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Extract Text from PDF File": {
      "main": [
        [
          {
            "node": "Splitting into Chunks",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When chat message received": {
      "main": [
        [
          {
            "node": "Embend User Message",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embedding Uploaded document": {
      "main": [
        [
          {
            "node": "Save the embedding in DB",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Grab the uploaded knowledgebase file link": {
      "main": [
        [
          {
            "node": "Extract Text from PDF File",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  }
}
常见问题

如何使用这个工作流？

复制上方的 JSON 配置代码，在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」，粘贴配置后根据需要修改凭证设置即可。

这个工作流适合什么场景？

中级

需要付费吗？

本工作流完全免费，您可以直接导入使用。但请注意，工作流中使用的第三方服务（如 OpenAI API）可能需要您自行付费。

相关工作流推荐

使用RAG、Gemini、Supabase和Google Docs构建基于知识的WhatsApp助手
使用RAG、Gemini、Supabase和Google Docs构建基于知识的WhatsApp助手
If
Code
Supabase
+9
15 节点iamvaar
内容创作
AI驱动的NDA审核与即时警报系统 - JotForm、Gemini、Telegram
基于JotForm、Gemini和Telegram的AI驱动NDA审核与即时警报系统
Telegram
Http Request
Jot Form Trigger
+4
13 节点iamvaar
使用Supabase + TogetherAI + Openrouter的RAG聊天机器人
使用Supabase + TogetherAI + Openrouter的RAG聊天机器人
Code
Supabase
Aggregate
+7
13 节点iamvaar
内部知识库
在可视化参考库中探索n8n节点
在可视化参考库中探索n8n节点
If
Ftp
Set
+93
113 节点I versus AI
其他
上下文混合RAG AI文案
Google Drive到Supabase上下文向量数据库同步用于RAG应用
If
Set
Code
+25
76 节点Michael Taleb
AI RAG 检索增强
使用Gemini AI自动化缺陷报告：Jotform到GitHub并发送Telegram提醒
使用Gemini AI自动化缺陷报告：Jotform到GitHub并发送Telegram提醒
Code
Telegram
Github Tool
+6
10 节点iamvaar
工作流信息
难度等级
中级
节点数量15
分类-
节点类型10
难度说明

适合有一定经验的用户，包含 6-15 个节点的中等复杂度工作流

作者
iamvaar

iamvaar

@iamvaar
外部链接
在 n8n.io 查看 →

分享此工作流