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使用Gemini和Supabase从Google Drive文档创建RAG向量数据库

高级

这是一个Document Extraction, AI RAG领域的自动化工作流，包含 16 个节点。主要使用 Code, Postgres, GoogleDrive, SplitInBatches, ExecuteWorkflowTrigger 等节点。 通过Gemini和Supabase从Google Drive文档创建RAG向量数据库

前置要求
  • •PostgreSQL 数据库连接信息
  • •Google Drive API 凭证
  • •Supabase URL 和 API Key

使用的节点 (16)

Code
Postgres
StickyNote
GoogleDrive
SplitInBatches
ExecuteWorkflowTrigger
VectorStoreSupabase
EmbeddingsGoogleGemini
DocumentDefaultDataLoader

分类

文档提取
AI RAG 检索增强
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": "a243f35537ecbb3a29ba49c4cf2200720075b362bcc7d02523f79748238bcfd6"
  },
  "nodes": [
    {
      "id": "97927b62-d8b9-4c98-b3d1-160c81c524e5",
      "name": "Embeddings Google Gemini4",
      "type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
      "position": [
        208,
        320
      ],
      "parameters": {},
      "credentials": {
        "googlePalmApi": {
          "id": "VCZQfcHNj0rHxcNf",
          "name": "GEMINI_API_KUDDUS"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "a9afa4ed-5e53-423c-9521-a79b17dbdde1",
      "name": "Default Data Loader2",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        384,
        304
      ],
      "parameters": {
        "options": {},
        "dataType": "binary"
      },
      "typeVersion": 1.1
    },
    {
      "id": "478d1053-af37-451e-9baf-7708f43653fa",
      "name": "执行 SQL 查询",
      "type": "n8n-nodes-base.postgres",
      "position": [
        -624,
        48
      ],
      "parameters": {
        "query": "DROP TABLE IF EXISTS documents CASCADE;\n\nCREATE EXTENSION IF NOT EXISTS vector;\n\nCREATE TABLE IF NOT EXISTS documents (\n  id bigserial PRIMARY KEY,\n  content text,\n  metadata jsonb,\n  embedding vector(768)\n);\n\nCREATE OR REPLACE FUNCTION match_documents(\n  query_embedding vector(768),\n  match_count int DEFAULT NULL,\n  filter jsonb DEFAULT '{}'::jsonb\n)\nRETURNS TABLE (\n  id bigint,\n  content text,\n  metadata jsonb,\n  similarity double precision\n)\nLANGUAGE sql\nAS $$\n  SELECT\n    d.id,\n    d.content,\n    d.metadata,\n    1 - (d.embedding <=> query_embedding) AS similarity\n  FROM documents d\n  WHERE (filter = '{}'::jsonb OR d.metadata @> filter)\n  ORDER BY d.embedding <=> query_embedding\n  LIMIT match_count;\n$$;\n",
        "options": {},
        "operation": "executeQuery"
      },
      "credentials": {
        "postgres": {
          "id": "KbYSAyR6T3ljhFKn",
          "name": "Postgres account"
        }
      },
      "typeVersion": 2.6
    },
    {
      "id": "7e4395b7-b822-41b6-aac3-0d4c2e3a749b",
      "name": "JavaScript 代码",
      "type": "n8n-nodes-base.code",
      "position": [
        -848,
        48
      ],
      "parameters": {
        "jsCode": "// Get the Drive_Folder_link from the workflow input\nconst driveUrl = $input.first().json.Drive_Folder_link;\n\n// Extract Google Drive folder/file ID from URL\nfunction getDriveId(url) {\n  const folderMatch = url.match(/\\/folders\\/([a-zA-Z0-9_-]+)/);\n  const fileMatch = url.match(/\\/file\\/d\\/([a-zA-Z0-9_-]+)/);\n  return folderMatch ? folderMatch[1] : (fileMatch ? fileMatch[1] : null);\n}\n\n// Process input items\nreturn items.map(item => {\n  const chatInput = item.json.chatInput || driveUrl || '';\n  const driveId = getDriveId(chatInput);\n\n  return {\n    json: {\n      originalInput: chatInput,\n      folderId: driveId,\n      driveId: driveId\n    }\n  };\n});\n"
      },
      "typeVersion": 2
    },
    {
      "id": "3a4041d1-25ac-4ab4-974e-a5460c9a8ffa",
      "name": "当由另一个工作流执行时",
      "type": "n8n-nodes-base.executeWorkflowTrigger",
      "position": [
        -1056,
        48
      ],
      "parameters": {
        "inputSource": "jsonExample",
        "jsonExample": "{\n  \"Drive_Folder_link\": \"https://drive.google.com/drive/folders/example\"\n}"
      },
      "typeVersion": 1.1
    },
    {
      "id": "92141102-016e-4e8a-b69f-f09d0522924d",
      "name": "便签1",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1504,
        -128
      ],
      "parameters": {
        "color": 5,
        "width": 368,
        "height": 512,
        "content": "# 📁 从 Google Drive 到 Supabase 向量存储的学习 RAG 工作流"
      },
      "typeVersion": 1
    },
    {
      "id": "6960ace8-fd01-4f9e-acfc-05185a0b197f",
      "name": "便签",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1104,
        208
      ],
      "parameters": {
        "width": 176,
        "height": 128,
        "content": "**触发器节点** - 当从另一个 n8n 工作流调用时启动工作流。接受 Drive 文件夹 URL 作为输入。"
      },
      "typeVersion": 1
    },
    {
      "id": "2befa4d1-ded3-4eeb-93ec-acdc9a9e22fb",
      "name": "便签 2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -864,
        208
      ],
      "parameters": {
        "width": 150,
        "height": 128,
        "content": "**提取文件夹 ID** - 使用正则表达式解析 Google Drive URL 以提取文件夹/文件 ID 用于 API 调用。"
      },
      "typeVersion": 1
    },
    {
      "id": "e71b4968-43de-477f-9de6-474cd471c405",
      "name": "便签 3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -656,
        208
      ],
      "parameters": {
        "width": 176,
        "content": "**初始化数据库** - 使用 pgvector 扩展创建 Supabase 向量表和 match_documents 搜索函数。⚠️ 会删除现有表！"
      },
      "typeVersion": 1
    },
    {
      "id": "4ac27951-096f-44ba-8e66-be73b3c0d380",
      "name": "遍历项目",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        -192,
        48
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 3
    },
    {
      "id": "d556d5eb-6216-4e39-bf8f-07a948fcbb0d",
      "name": "搜索文件和文件夹",
      "type": "n8n-nodes-base.googleDrive",
      "position": [
        -416,
        48
      ],
      "parameters": {
        "filter": {
          "folderId": {
            "__rl": true,
            "mode": "id",
            "value": "={{ $('Code in JavaScript').item.json.folderId }}"
          }
        },
        "options": {},
        "resource": "fileFolder"
      },
      "credentials": {
        "googleDriveOAuth2Api": {
          "id": "CVN95k3ctbjWs60e",
          "name": "Google_Drive_gaming"
        }
      },
      "typeVersion": 3
    },
    {
      "id": "db2f57b6-1aa9-4926-a211-7362d5d4533e",
      "name": "插入到 Supabase 向量存储",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
      "position": [
        256,
        48
      ],
      "parameters": {
        "mode": "insert",
        "options": {
          "queryName": "match_documents"
        },
        "tableName": {
          "__rl": true,
          "mode": "list",
          "value": "documents",
          "cachedResultName": "documents"
        }
      },
      "credentials": {
        "supabaseApi": {
          "id": "OweRv8RLSfhKJyfg",
          "name": "Supabase account"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "09addf62-6c1a-4af4-a5d5-6b2323f64886",
      "name": "下载文件",
      "type": "n8n-nodes-base.googleDrive",
      "position": [
        48,
        64
      ],
      "parameters": {
        "fileId": {
          "__rl": true,
          "mode": "id",
          "value": "={{ $json.id }}"
        },
        "options": {
          "googleFileConversion": {
            "conversion": {
              "docsToFormat": "text/plain"
            }
          }
        },
        "operation": "download"
      },
      "credentials": {
        "googleDriveOAuth2Api": {
          "id": "CVN95k3ctbjWs60e",
          "name": "Google_Drive_gaming"
        }
      },
      "typeVersion": 3
    },
    {
      "id": "0c929411-a2d2-49ff-ab92-09aeece9d892",
      "name": "便签 4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -432,
        224
      ],
      "parameters": {
        "width": 176,
        "height": 128,
        "content": "**列出 Drive 文件** - 使用提取的文件夹 ID 从指定的 Google Drive 文件夹检索所有文件。"
      },
      "typeVersion": 1
    },
    {
      "id": "b2b6df82-5145-4719-b3bc-a5501e31ed08",
      "name": "便签 5",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        16,
        -112
      ],
      "parameters": {
        "width": 150,
        "content": "**列出 Drive 文件** - 使用提取的文件夹 ID 从指定的 Google Drive 文件夹检索所有文件。"
      },
      "typeVersion": 1
    },
    {
      "id": "0d6c2252-f11a-4a12-978c-b121c68c8663",
      "name": "便签6",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        240,
        -208
      ],
      "parameters": {
        "color": 7,
        "height": 240,
        "content": "**存储嵌入** - 通过 Gemini 生成 768 维向量并将文档插入 Supabase 用于语义搜索。"
      },
      "typeVersion": 1
    }
  ],
  "pinData": {},
  "connections": {
    "Download File": {
      "main": [
        [
          {
            "node": "Insert into Supabase Vectorstore",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Loop Over Items": {
      "main": [
        [],
        [
          {
            "node": "Download File",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Code in JavaScript": {
      "main": [
        [
          {
            "node": "Execute a SQL query",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Execute a SQL query": {
      "main": [
        [
          {
            "node": "Search files and folders",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Default Data Loader2": {
      "ai_document": [
        [
          {
            "node": "Insert into Supabase Vectorstore",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "Search files and folders": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Embeddings Google Gemini4": {
      "ai_embedding": [
        [
          {
            "node": "Insert into Supabase Vectorstore",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "Insert into Supabase Vectorstore": {
      "main": [
        [
          {
            "node": "Loop Over Items",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "When Executed by Another Workflow": {
      "main": [
        [
          {
            "node": "Code in JavaScript",
            "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？

高级 - 文档提取, AI RAG 检索增强

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。

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工作流信息
难度等级
高级
节点数量16
分类2
节点类型9
难度说明

适合高级用户，包含 16+ 个节点的复杂工作流

作者
Mantaka Mahir

Mantaka Mahir

@mantakamahir

Al Automation Expert || Al Agents || n8n || Python || LangChain || Helping businesses scale revenue and reduce costs with Al driven automation .

外部链接
在 n8n.io 查看 →

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