Datalab.to APIを使用してPDF、DOC、画像をMarkdownに変換

中級

これはDocument Extraction, Multimodal AI分野の自動化ワークフローで、11個のノードを含みます。主にSet, Wait, Switch, FormTrigger, HttpRequestなどのノードを使用。 PDF、DOC、画像をMarkdownに変換するにはDatalab.to APIを使用する

前提条件
  • ターゲットAPIの認証情報が必要な場合あり
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
  "meta": {
    "instanceId": "b3c467df4053d13fe31cc98f3c66fa1d16300ba750506bfd019a0913cec71ea3"
  },
  "nodes": [
    {
      "id": "c302f8e5-6bed-4b64-8d52-33eaa5fce86a",
      "name": "フォーム送信時",
      "type": "n8n-nodes-base.formTrigger",
      "position": [
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        48
      ],
      "webhookId": "a857ad3f-4b4d-4574-b503-809a95b1fbbf",
      "parameters": {
        "options": {},
        "formTitle": "upload file",
        "formFields": {
          "values": [
            {
              "fieldType": "file",
              "fieldLabel": "file",
              "multipleFiles": false,
              "requiredField": true
            }
          ]
        }
      },
      "typeVersion": 2.2
    },
    {
      "id": "3cc12307-f5da-476a-811a-79920f20abf7",
      "name": "Markdown取得",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        336,
        48
      ],
      "parameters": {
        "url": "={{ $json.request_check_url }}",
        "options": {},
        "authentication": "genericCredentialType",
        "genericAuthType": "httpHeaderAuth"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "7Wx4MGEDgCG0D7fT",
          "name": "datalab.io"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "ec9e9703-fb38-4ba5-97f6-a73bee7c47f7",
      "name": "Datalab API に送信",
      "type": "n8n-nodes-base.httpRequest",
      "position": [
        -112,
        48
      ],
      "parameters": {
        "url": "https://www.datalab.to/api/v1/marker",
        "method": "POST",
        "options": {},
        "sendBody": true,
        "contentType": "multipart-form-data",
        "authentication": "genericCredentialType",
        "bodyParameters": {
          "parameters": [
            {
              "name": "max_pages",
              "value": "4"
            },
            {
              "name": "use_llm",
              "value": "true"
            },
            {
              "name": "output_format",
              "value": "markdown"
            },
            {
              "name": "file",
              "parameterType": "formBinaryData",
              "inputDataFieldName": "file"
            }
          ]
        },
        "genericAuthType": "httpHeaderAuth"
      },
      "credentials": {
        "httpHeaderAuth": {
          "id": "7Wx4MGEDgCG0D7fT",
          "name": "datalab.io"
        }
      },
      "typeVersion": 4.2
    },
    {
      "id": "542793bf-05c1-4c6c-b0e0-b087669f966c",
      "name": "フィールド設定",
      "type": "n8n-nodes-base.set",
      "position": [
        560,
        48
      ],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "20280dbd-8188-4f5e-8e4e-74621d65d40a",
              "name": "markdown",
              "type": "string",
              "value": "={{ $json.markdown }}"
            }
          ]
        }
      },
      "typeVersion": 3.4
    },
    {
      "id": "cb900de1-e4b1-488f-8a12-9946bb8466f6",
      "name": "待機",
      "type": "n8n-nodes-base.wait",
      "position": [
        112,
        48
      ],
      "webhookId": "7b49cf9b-9859-4361-a8b8-2407d114d418",
      "parameters": {
        "amount": 10
      },
      "typeVersion": 1.1
    },
    {
      "id": "9fcdcaab-2041-4411-8ec1-10edfe29f1d6",
      "name": "付箋13",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -1424,
        -32
      ],
      "parameters": {
        "width": 972,
        "height": 564,
        "content": "![](https://res.cloudinary.com/dd6vlwblr/image/upload/v1756196495/Convert_PDF_DOC_IMAGES_to_1_sfdzu1.png)"
      },
      "typeVersion": 1
    },
    {
      "id": "32550fd8-2570-4e42-b249-8d53288da00a",
      "name": "付箋",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        -416,
        -32
      ],
      "parameters": {
        "width": 1200,
        "height": 272,
        "content": "## Convert Files to Markdown for LLM with Datalab.to"
      },
      "typeVersion": 1
    },
    {
      "id": "f968189c-83c4-436c-91c6-dc0313ee4256",
      "name": "付箋2",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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        272
      ],
      "parameters": {
        "width": 1200,
        "height": 256,
        "content": "## Guide\nThis simple automation enables you to convert .doc, .pdf, .png, .jpg, and .webp files to markdown using datalab.to API. This is useful for llm workflows for ai processing. \n\nSetup \n- Sign up to datalab.to to get your api key. Get the free $5 credits by entering your payment method.\n- Set up a Generic Header with name \"X-API-Key\" and api key as the value. \n- Thats it you are good to go.\n\nLearn more on tweaking the body payload here; [api reference](https://www.datalab.to/redoc#operation/marker_api_v1_marker_post)"
      },
      "typeVersion": 1
    },
    {
      "id": "883e4090-cb4f-4de6-bfc4-4c5c7ce85728",
      "name": "付箋3",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
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        -32
      ],
      "parameters": {
        "color": 6,
        "width": 400,
        "height": 416,
        "content": "## Polling Confirmation Node\n\nYou can add this node after \"Get Markdown\" node to confirm if the get request worked or the doc is still being processed. If the outcome is \"*success*\" then proceed, if \"*failed*\" then plug that route to the wait node, to try again. You can also add more outcomes of this node to cover api call fails. If you are processing **larger files**, increase the wait time."
      },
      "typeVersion": 1
    },
    {
      "id": "4f0c8ae8-e92e-419f-a609-d426db8321d8",
      "name": "分岐",
      "type": "n8n-nodes-base.switch",
      "disabled": true,
      "position": [
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                  "caseSensitive": true,
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                    "leftValue": "={{ $json.status }}",
                    "rightValue": "complete"
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              "renameOutput": true
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                    "operator": {
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      "typeVersion": 3.2
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    {
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      "type": "n8n-nodes-base.stickyNote",
      "position": [
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      ],
      "parameters": {
        "color": 4,
        "width": 400,
        "height": 128,
        "content": "## Wanna work with me?\n**Email**: joseph@uppfy.com\n**X/Twitter**: [@juppfy](https://x.com/juppfy)"
      },
      "typeVersion": 1
    }
  ],
  "pinData": {},
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}
よくある質問

このワークフローの使い方は?

上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。

このワークフローはどんな場面に適していますか?

中級 - 文書抽出, マルチモーダルAI

有料ですか?

このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス(OpenAI APIなど)は別途料金が発生する場合があります。

ワークフロー情報
難易度
中級
ノード数11
カテゴリー2
ノードタイプ6
難易度説明

経験者向け、6-15ノードの中程度の複雑さのワークフロー

作成者
Joseph

Joseph

@mjomba

Automation expert specializing in building smart, scalable workflows using tools like n8n, Make, and Airtable. I help businesses save time, reduce manual work, and grow faster with tailored automation solutions. Feel free to reach out at joseph@uppfy.com to discuss your project. I am also on x.com/juppfy

外部リンク
n8n.ioで表示

このワークフローを共有

カテゴリー

カテゴリー: 34