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E-Mail-Verlauf-RAG

Experte

Dies ist ein Internal Wiki, AI RAG-Bereich Automatisierungsworkflow mit 23 Nodes. Hauptsächlich werden Code, Gmail, GmailTrigger, ManualTrigger, SplitInBatches und andere Nodes verwendet. E-Mail-Wissensdatenbank mit Gmail, OpenAI und Qdrant-Vektordatenbank erstellen

Voraussetzungen
  • •Google-Konto + Gmail API-Anmeldedaten
  • •OpenAI API Key
  • •Qdrant-Serververbindungsdaten

Verwendete Nodes (23)

Code
Gmail
StickyNote
GmailTrigger
ManualTrigger
SplitInBatches
Agent
ChatTrigger
LmChatOpenAi
EmbeddingsOpenAi
VectorStoreQdrant
MemoryBufferWindow
DocumentDefaultDataLoader
TextSplitterCharacterTextSplitter

Kategorie

Internes Wiki
KI RAG
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
React Flow
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "id": "7QhxjMbqHv5tk9wM",
  "meta": {
    "instanceId": "b50483b2122f6dc268662b45507d575d939570ea8e1e086601ebb3b6273c1cfd",
    "templateCredsSetupCompleted": true
  },
  "name": "Email History RAG",
  "tags": [
    {
      "id": "PNmVCFjr9sq0xind",
      "name": "RAG",
      "createdAt": "2025-07-12T09:30:51.202Z",
      "updatedAt": "2025-07-12T09:30:51.202Z"
    }
  ],
  "nodes": [
    {
      "id": "dec780ab-9e05-4305-ba52-8a92dfc266e7",
      "name": "OpenAI Chat Model",
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "position": [
        -7040,
        800
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "K8T7HIhpd7gMJG20",
          "name": "OpenAi account - Remap"
        }
      },
      "typeVersion": 1
    },
    {
      "id": "13f21017-5470-4e0e-8d13-aea6d98c4918",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -7440,
        448
      ],
      "parameters": {
        "width": 1162,
        "height": 796,
        "content": "# RAG AI Agent\n"
      },
      "typeVersion": 1
    },
    {
      "id": "b6615316-94c0-4091-b6e3-8cdf64cb0902",
      "name": "When clicking ‘Test workflow’",
      "type": "n8n-nodes-base.manualTrigger",
      "position": [
        -6048,
        1472
      ],
      "parameters": {},
      "typeVersion": 1
    },
    {
      "id": "349336cd-9373-4553-aa13-9cf6a427a0c6",
      "name": "RAG Agent",
      "type": "@n8n/n8n-nodes-langchain.agent",
      "position": [
        -6944,
        576
      ],
      "parameters": {
        "options": {
          "systemMessage": "=You are a helpful assistant that will get data from RAG and send a good response to user.\n\nToday date is this if user ask for dated or latest data: {{ $now }}\n\nSo add date when send query to vector database because I am already setting the date field in embedding."
        }
      },
      "typeVersion": 1.7
    },
    {
      "id": "82da160a-a572-4cdf-a260-f7a0c51a30fa",
      "name": "Gmail Trigger1",
      "type": "n8n-nodes-base.gmailTrigger",
      "position": [
        -6064,
        672
      ],
      "parameters": {
        "filters": {},
        "pollTimes": {
          "item": [
            {
              "mode": "everyMinute"
            }
          ]
        }
      },
      "credentials": {
        "gmailOAuth2": {
          "id": "ufYEel3Kf0MiIlZB",
          "name": "Gmail account - chzainali6363@gmail.com"
        }
      },
      "typeVersion": 1.2
    },
    {
      "id": "954a8ea4-9e00-43b9-9fe2-6d717b6dccd7",
      "name": "Get Mail Data1",
      "type": "n8n-nodes-base.gmail",
      "position": [
        -5840,
        672
      ],
      "webhookId": "[REDACTED_WEBHOOK_ID]",
      "parameters": {
        "simple": false,
        "options": {},
        "messageId": "={{ $json.id }}",
        "operation": "get"
      },
      "credentials": {
        "gmailOAuth2": {
          "id": "ufYEel3Kf0MiIlZB",
          "name": "Gmail account - chzainali6363@gmail.com"
        }
      },
      "typeVersion": 2.1
    },
    {
      "id": "16acb16b-8d56-425a-b484-fa4ffc3f5616",
      "name": "Embeddings OpenAI5",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        -5680,
        912
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "K8T7HIhpd7gMJG20",
          "name": "OpenAi account - Remap"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "73a26bce-0df2-4755-8175-8a0e367f7418",
      "name": "Enhanced Default Data Loader3",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        -5424,
        880
      ],
      "parameters": {
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "=data_source",
                "value": "=gmail"
              },
              {
                "name": "=created_at",
                "value": "={{ $json.date }}"
              }
            ]
          }
        },
        "jsonData": "=Email details:\nDate: {{ $json.headers.date }}\n\nFrom Email: {{ $json.from.value[0].address }}\nFrom Name:  {{ $json.from.value[0].name }}\n\nTo Email: {{ $json.to.value[0].address }}\n\nEmail Subject:\n{{ $json.subject }}\n\nEmail body:\n{{ $json.text }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "262344fa-8b26-4665-b0ff-e1354e6d84eb",
      "name": "Sticky Note4",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -6128,
        448
      ],
      "parameters": {
        "color": 4,
        "width": 1200,
        "height": 788,
        "content": "# Watch Trigger (Email) - New Email\n## Get new Email -> Extract the text -> Add to Vector Store"
      },
      "typeVersion": 1
    },
    {
      "id": "c70f74e1-75ab-4ce3-9c84-f92ff1d7a762",
      "name": "Character Text Splitter",
      "type": "@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter",
      "position": [
        -5344,
        1056
      ],
      "parameters": {
        "separator": "Email details:"
      },
      "typeVersion": 1
    },
    {
      "id": "f01ccf0e-caf4-44f1-a385-a6eb2b063551",
      "name": "Code",
      "type": "n8n-nodes-base.code",
      "position": [
        -5616,
        1472
      ],
      "parameters": {
        "jsCode": "const emails = $input.all().map((item) => item.json);\n\nconst extractedData = emails.map((email) => {\n  // Remove line breaks and excessive spaces from body\n  const cleanBody = email.text\n    ?.replace(/(\\r\\n|\\n|\\r)/gm, ' ')  // Replace newlines with space\n    ?.replace(/\\s+/g, ' ')           // Collapse multiple spaces\n    ?.trim();                        // Remove leading/trailing space\n\n  return {\n    to: email.to?.value?.[0]?.address || '',\n    from: email.from?.value?.[0]?.address || '',\n    fromName: email.from?.value?.[0]?.name || '',\n    date: email.date || '',\n    subject: email.subject || '',\n    body: cleanBody || '',\n    emailId: email.id || '',\n  };\n});\n\nreturn extractedData;\n"
      },
      "typeVersion": 2
    },
    {
      "id": "69d042bf-b75a-414e-a2e2-a62632e6aef2",
      "name": "Embeddings OpenAI11",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        -5280,
        1712
      ],
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "5200b258-2c96-4d38-9c92-b5353ada6957",
      "name": "Default Data Loader",
      "type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
      "position": [
        -5104,
        1696
      ],
      "parameters": {
        "options": {
          "metadata": {
            "metadataValues": [
              {
                "name": "created_at",
                "value": "={{ $json.date }}"
              },
              {
                "name": "data_source",
                "value": "gmail"
              }
            ]
          }
        },
        "jsonData": "=Email details:\nDate: {{ $json.date }}\n\nFrom Email: {{ $json.from }}\nFrom Name:  {{ $json.fromName }}\n\nTo Email: {{ $json.to }}\n\nEmail Subject:\n{{ $json.subject }}\n\nEmail body:\n{{ $json.body }}",
        "jsonMode": "expressionData"
      },
      "typeVersion": 1
    },
    {
      "id": "cd126bb7-60a6-450b-b31c-cfd9517e9441",
      "name": "Sticky Note11",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -6128,
        1328
      ],
      "parameters": {
        "width": 1596,
        "height": 740,
        "content": "# Get All Emails -> Store embedding in vector db\n"
      },
      "typeVersion": 1
    },
    {
      "id": "19fe59c6-6576-453a-8098-97e47c72c033",
      "name": "batch emails",
      "type": "n8n-nodes-base.splitInBatches",
      "position": [
        -5424,
        1472
      ],
      "parameters": {
        "options": {},
        "batchSize": 50
      },
      "typeVersion": 3
    },
    {
      "id": "512bb68a-94d7-4e0f-ab51-265f19d670bd",
      "name": "Character Text Splitter1",
      "type": "@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter",
      "position": [
        -5024,
        1888
      ],
      "parameters": {
        "separator": "Email details:"
      },
      "typeVersion": 1
    },
    {
      "id": "051c026e-0fd7-4182-a388-0ccd6e0c085e",
      "name": "Embeddings OpenAI3",
      "type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
      "position": [
        -6784,
        1072
      ],
      "parameters": {
        "options": {}
      },
      "credentials": {
        "openAiApi": {
          "id": "K8T7HIhpd7gMJG20",
          "name": "OpenAi account - Remap"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "d7481948-2972-42e9-b2ef-900c55bc6465",
      "name": "Qdrant Email Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        -6736,
        896
      ],
      "parameters": {
        "mode": "retrieve-as-tool",
        "options": {},
        "toolName": "emails_vector_search",
        "toolDescription": "=Call this tool to perform a vector embeddings search in my e-mail database. For time-specific queries:\n1. ALWAYS include the time frame in your query (e.g., \"interviews scheduled after April 27, 2025\" or \"interviews for next week April 28-May 4, 2025\")\n2. For future events, explicitly mention \"future\" or \"upcoming\" in your query",
        "qdrantCollection": {
          "__rl": true,
          "mode": "list",
          "value": "emails_history",
          "cachedResultName": "emails_history"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "7cecd74a-bde6-4fcf-8622-81620c63b20f",
      "name": "Qdrant Vector Store",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        -5568,
        672
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "qdrantCollection": {
          "__rl": true,
          "mode": "list",
          "value": "emails_history",
          "cachedResultName": "emails_history"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "1e6d26d8-60e3-4128-82b4-a5e61d83cff1",
      "name": "Qdrant Vector Store1",
      "type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
      "position": [
        -5104,
        1456
      ],
      "parameters": {
        "mode": "insert",
        "options": {},
        "qdrantCollection": {
          "__rl": true,
          "mode": "list",
          "value": "emails_history",
          "cachedResultName": "emails_history"
        }
      },
      "typeVersion": 1.1
    },
    {
      "id": "8b9845c3-a9e6-47a1-ae0e-8e66a15b5812",
      "name": "When chat message received",
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "position": [
        -7248,
        576
      ],
      "webhookId": "61ffbc2d-0469-49ab-8541-694f021112e6",
      "parameters": {
        "options": {}
      },
      "typeVersion": 1.1
    },
    {
      "id": "2c320869-b169-4961-a8fd-5403c7a1366e",
      "name": "Simple Memory",
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "position": [
        -6864,
        800
      ],
      "parameters": {},
      "typeVersion": 1.3
    },
    {
      "id": "6735edda-91ff-4872-8c13-bec68a8af925",
      "name": "Get many messages",
      "type": "n8n-nodes-base.gmail",
      "position": [
        -5824,
        1472
      ],
      "webhookId": "778c704a-a717-45e1-adc7-f15a6426c415",
      "parameters": {
        "simple": false,
        "filters": {},
        "options": {},
        "operation": "getAll",
        "returnAll": true
      },
      "credentials": {
        "gmailOAuth2": {
          "id": "ufYEel3Kf0MiIlZB",
          "name": "Gmail account - chzainali6363@gmail.com"
        }
      },
      "typeVersion": 2.1
    }
  ],
  "active": false,
  "pinData": {},
  "settings": {
    "executionOrder": "v1"
  },
  "versionId": "a81f41c7-8a71-483c-82bb-ff45081649cf",
  "connections": {
    "f01ccf0e-caf4-44f1-a385-a6eb2b063551": {
      "main": [
        [
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            "node": "19fe59c6-6576-453a-8098-97e47c72c033",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "349336cd-9373-4553-aa13-9cf6a427a0c6": {
      "main": [
        []
      ]
    },
    "19fe59c6-6576-453a-8098-97e47c72c033": {
      "main": [
        [],
        [
          {
            "node": "1e6d26d8-60e3-4128-82b4-a5e61d83cff1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "2c320869-b169-4961-a8fd-5403c7a1366e": {
      "ai_memory": [
        [
          {
            "node": "349336cd-9373-4553-aa13-9cf6a427a0c6",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "954a8ea4-9e00-43b9-9fe2-6d717b6dccd7": {
      "main": [
        [
          {
            "node": "7cecd74a-bde6-4fcf-8622-81620c63b20f",
            "type": "main",
            "index": 0
          }
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    },
    "82da160a-a572-4cdf-a260-f7a0c51a30fa": {
      "main": [
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          }
        ]
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    },
    "dec780ab-9e05-4305-ba52-8a92dfc266e7": {
      "ai_languageModel": [
        [
          {
            "node": "349336cd-9373-4553-aa13-9cf6a427a0c6",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "051c026e-0fd7-4182-a388-0ccd6e0c085e": {
      "ai_embedding": [
        [
          {
            "node": "d7481948-2972-42e9-b2ef-900c55bc6465",
            "type": "ai_embedding",
            "index": 0
          }
        ]
      ]
    },
    "16acb16b-8d56-425a-b484-fa4ffc3f5616": {
      "ai_embedding": [
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            "type": "ai_embedding",
            "index": 0
          }
        ]
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    },
    "5200b258-2c96-4d38-9c92-b5353ada6957": {
      "ai_document": [
        [
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            "node": "1e6d26d8-60e3-4128-82b4-a5e61d83cff1",
            "type": "ai_document",
            "index": 0
          }
        ]
      ]
    },
    "69d042bf-b75a-414e-a2e2-a62632e6aef2": {
      "ai_embedding": [
        [
          {
            "node": "1e6d26d8-60e3-4128-82b4-a5e61d83cff1",
            "type": "ai_embedding",
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    },
    "1e6d26d8-60e3-4128-82b4-a5e61d83cff1": {
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    },
    "c70f74e1-75ab-4ce3-9c84-f92ff1d7a762": {
      "ai_textSplitter": [
        [
          {
            "node": "73a26bce-0df2-4755-8175-8a0e367f7418",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
      ]
    },
    "512bb68a-94d7-4e0f-ab51-265f19d670bd": {
      "ai_textSplitter": [
        [
          {
            "node": "5200b258-2c96-4d38-9c92-b5353ada6957",
            "type": "ai_textSplitter",
            "index": 0
          }
        ]
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    },
    "d7481948-2972-42e9-b2ef-900c55bc6465": {
      "ai_tool": [
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            "type": "ai_tool",
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    },
    "8b9845c3-a9e6-47a1-ae0e-8e66a15b5812": {
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    "73a26bce-0df2-4755-8175-8a0e367f7418": {
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            "type": "ai_document",
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          }
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    },
    "b6615316-94c0-4091-b6e3-8cdf64cb0902": {
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            "type": "main",
            "index": 0
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    }
  }
}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Experte - Internes Wiki, KI RAG

Ist es kostenpflichtig?

Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

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Autor
Zain Ali

Zain Ali

@zain104

Software Engineer with over 3+ years of experience in full-stack development.

Externe Links
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Kategorien: 34