TelegramのDOI URL経由で研究論文をZoteroに自動インポートする
上級
これはAI Summarization, Multimodal AI分野の自動化ワークフローで、25個のノードを含みます。主にIf, Set, Code, Merge, Telegramなどのノードを使用。 Telegramから研究論文をZoteroにインポート（AI要約付）
前提条件
- •Telegram Bot Token
- •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
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"meta": {
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"templateCredsSetupCompleted": true
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"name": "Automatically Import Research Papers using DOI URL from Telegram to Zotero",
"tags": [],
"nodes": [
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"name": "Telegram トリガー",
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"type": "n8n-nodes-base.code",
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"parameters": {
"jsCode": "// Node: Code (Parse DOI)\nconst txt = $json.message?.text?.trim() || \"\";\n\nfunction extractDOI(s) {\n // 1) doi.org/...\n let m = s.match(/doi\\.org\\/(10\\.\\d{4,9}\\/\\S+)/i);\n if (m) return m[1].replace(/[)\\].,;]*$/, \"\");\n // 2) raw DOI\n m = s.match(/(10\\.\\d{4,9}\\/\\S+)/i);\n if (m) return m[1].replace(/[)\\].,;]*$/, \"\");\n // 3) arXiv link\n m = s.match(/arxiv\\.org\\/abs\\/([\\w\\-.]+)/i);\n if (m) return `10.48550/arXiv.${m[1]}`;\n return null;\n}\n\nconst doi = extractDOI(txt);\nif (!doi) {\n return [{ error: true, message: \"DOI not found. Please send a DOI or arXiv/doi.org link.\" }];\n}\n\nreturn [{ doi }];\n"
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"onError": "continueRegularOutput",
"position": [
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"parameters": {
"url": "=https://api.datacite.org/dois/{{ $('Code').item.json.doi }}",
"options": {}
},
"typeVersion": 4.2
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{
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"parameters": {
"url": "=https://api.crossref.org/works/{{ $('Code').item.json.doi }}",
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"position": [
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"url": "=https://api.unpaywall.org/v2/{{ $('Code').item.json.doi }}?email=your-email@example.com",
"options": {}
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"url": "=https://api.zotero.org/keys/{{ $json['Zotero API Key'] }}",
"options": {},
"sendHeaders": true,
"headerParameters": {
"parameters": [
{
"name": "Zotero-API-Key",
"value": "={{ $json['Zotero API Key'] }}"
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{
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"jsCode": "// Code4 — Build Zotero parent metadata + pick best PDF URL\n// Input from Merge: $json.crossref, $json.datacite, $json.unpay, and $json.doi\n\nconst doi = $json.doi;\n\n// Unwrap API results if not error\nconst crossrefBody = ($json.crossref && !$json.crossref.error) ? $json.crossref.message : null;\nconst dataciteAttr = ($json.datacite && !$json.datacite.error) ? $json.datacite.data?.attributes : null;\nconst unpayBody = ($json.unpay && !$json.unpay.error) ? $json.unpay : null;\n\nconst pick = (...vals) => vals.find(v => {\n if (v === undefined || v === null) return false;\n if (typeof v === 'string') return v.trim().length > 0;\n return true;\n}) ?? null;\n\n/* ---------- PDF pickers ---------- */\nfunction fromCrossref(m) {\n if (!m) return null;\n const links = m.link || [];\n for (const l of links) {\n const ct = (l['content-type'] || '').toLowerCase();\n const url = l.URL || '';\n if (ct.includes('pdf') || /\\.pdf(\\?|$)/i.test(url)) return url;\n }\n return null;\n}\n\nfunction fromDataCite(attr) {\n if (!attr) return null;\n // try identifiers -> arXiv\n const ids = attr.identifiers || [];\n const arxiv = ids.find(i => /arxiv/i.test(i.identifierType || ''))?.identifier;\n if (arxiv) {\n const id = String(arxiv).replace(/^arXiv:/i,'');\n return `https://arxiv.org/pdf/${id}.pdf`;\n }\n return null;\n}\n\nfunction fromUnpay(u) {\n if (!u) return null;\n if (u.best_oa_location?.url_for_pdf) return u.best_oa_location.url_for_pdf;\n if (/\\.pdf(\\?|$)/i.test(u.best_oa_location?.url || '')) return u.best_oa_location.url;\n for (const loc of (u.oa_locations || [])) {\n if (loc.url_for_pdf) return loc.url_for_pdf;\n if (/\\.pdf(\\?|$)/i.test(loc.url || '')) return loc.url;\n }\n return null;\n}\n\n// Priority: Crossref → Unpaywall → DataCite → arXiv fallback (from DOI)\nlet pdfUrl = fromCrossref(crossrefBody);\nif (!pdfUrl) pdfUrl = fromUnpay(unpayBody);\nif (!pdfUrl) pdfUrl = fromDataCite(dataciteAttr);\nif (!pdfUrl && /^10\\.48550\\/arxiv\\./i.test(doi || '')) {\n const arxivId = doi.replace(/^10\\.48550\\/arxiv\\./i, '');\n pdfUrl = `https://arxiv.org/pdf/${arxivId}.pdf`;\n}\n\n/* ---------- Parent metadata (Zotero item) ---------- */\n// Title\nconst title = pick(\n crossrefBody?.title?.[0],\n dataciteAttr?.titles?.[0]?.title,\n doi\n);\n\n// Date (YYYY, YYYY-MM, or YYYY-MM-DD)\nconst issued = crossrefBody?.issued?.['date-parts']?.[0] || [];\nconst dateStr = issued.length\n ? issued.join('-')\n : pick(\n dataciteAttr?.published,\n dataciteAttr?.publishedOnline,\n dataciteAttr?.publishedPrint,\n dataciteAttr?.created\n ) || \"\";\n\n// Journal / container\nconst publicationTitle = pick(\n crossrefBody?.['container-title']?.[0],\n dataciteAttr?.container?.title\n) || \"\";\n\n// Landing page (not PDF)\nconst landingFromCR = crossrefBody?.URL;\nconst landingFromUP = unpayBody?.best_oa_location?.url || unpayBody?.oa_locations?.[0]?.url;\nconst landingFromDC = dataciteAttr?.url;\nconst url = pick(landingFromCR, landingFromUP, landingFromDC) || \"\";\n\n// Abstract\nlet abstractNote = \"\";\nif (Array.isArray(dataciteAttr?.descriptions) && dataciteAttr.descriptions.length) {\n const absExact = dataciteAttr.descriptions.find(d => /abstract/i.test(d.descriptionType || ''));\n abstractNote = pick(absExact?.description, dataciteAttr.descriptions[0]?.description) || \"\";\n}\n\n// Creators\nlet creators = [];\nif (Array.isArray(crossrefBody?.author)) {\n creators = crossrefBody.author.map(a => ({\n creatorType: \"author\",\n firstName: a.given || \"\",\n lastName: a.family || (a.name || \"\")\n }));\n} else if (Array.isArray(dataciteAttr?.creators)) {\n creators = dataciteAttr.creators.map(c => ({\n creatorType: \"author\",\n firstName: c.givenName || \"\",\n lastName: c.familyName || (c.name || \"\")\n }));\n}\n\n// Tags\nconst tags = [];\nif (Array.isArray(crossrefBody?.subject)) {\n for (const s of crossrefBody.subject.slice(0, 5)) tags.push({ tag: String(s) });\n}\ntags.push({ tag: \"from-telegram\" });\n\n// Item type heuristic\nconst itemType = publicationTitle ? \"journalArticle\" : \"preprint\";\n\n// Build meta object for POST /items (parent)\nconst meta = {\n itemType,\n title,\n DOI: doi || \"\",\n url,\n date: dateStr,\n publicationTitle,\n abstractNote,\n creators,\n tags\n};\n\n// Unified output for next step:\n// - meta: used for \"Zotero - Create Parent\"\n// - pdfUrl + hasPdf: for IF & attachment creation (linked_url)\nreturn [{\n doi,\n title,\n meta,\n pdfUrl,\n hasPdf: Boolean(pdfUrl)\n}];\n"
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"leftValue": "={{ $json.hasPdf }}",
"rightValue": ""
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"parameters": {
"url": "=https://api.zotero.org/users/{{ $('HTTP Request').item.json.userID }}/items",
"method": "POST",
"options": {},
"jsonBody": "={{ [ $('Code4').item.json.meta ] }}",
"sendBody": true,
"sendHeaders": true,
"specifyBody": "json",
"headerParameters": {
"parameters": [
{
"name": "ZOTERO-API-KEY",
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"content": "# Automatically Import Research Papers using DOI URL from Telegram to Zotero\n\nThis workflow allows you to automatically import research papers into your Zotero library by simply sending a DOI link through Telegram. It fetches metadata from reliable sources such as Crossref, DataCite, and Unpaywall, enriches the bibliographic details, attaches the best available full-text PDF when possible, and generates a concise summary of the abstract using an LLM before sending it back to Telegram. \n\n## ✨ Key Features \n- **Telegram Integration** – Send a DOI link via Telegram bot to trigger the workflow. \n- **DOI Parsing** – Automatically detects and extracts DOI or arXiv identifiers from user messages. \n- **Metadata Fetching** – Retrieves bibliographic information from **Crossref**, **DataCite**, and **Unpaywall**. \n- **Smart PDF Finder** – Locates the best available PDF (publisher link, open access, or arXiv). \n- **Zotero Integration** – Creates a Zotero parent item with complete metadata and attaches the PDF link when available. \n- **Abstract Summarization** – Uses a basic LLM chain to generate a short and clear summary of the abstract. \n- **Telegram Feedback** – Sends the title, URL, and abstract summary back to the user in Telegram. \n\n\n## 🔑 Required Credentials \n- **Telegram API** – To connect the workflow with your Telegram bot. \n- **Zotero API Key** – To create and update items in your Zotero library. \n- **OpenRouter API Key** – To enable the LLM for generating abstract summaries. \n- *(Optional)* Email for **Unpaywall API** requests (recommended for stable access). \n\n## 💡 Benefits \n- Save time by automating manual research paper imports. \n- Ensure high-quality metadata by combining multiple sources (Crossref, DataCite, Unpaywall). \n- Get instant summaries of abstracts directly in Telegram for quick understanding. \n- Keep your Zotero library organized with accurate titles, abstracts, authors, and tags. \n- Quickly attach available full-text PDFs without manual searching. \n- Improve your academic workflow by managing references and summaries directly from Telegram. \n"
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"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
2600,
0
],
"parameters": {
"text": "=Summarize the following abstract: \n\n{{ $('HTTP Request9').item.json.successful['0'].data.abstractNote }}",
"batching": {},
"messages": {
"messageValues": [
{
"message": "=You are an assistant that summarizes academic paper abstracts. Your task is to generate a short and clear summary of the abstract in plain English. Keep the summary concise (2–3 sentences), highlight the main contribution or finding, and avoid technical jargon if possible. "
}
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"position": [
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"options": {}
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{
"id": "aa28ca2d-8590-431f-b01f-c80494be010c",
"name": "Send a text message",
"type": "n8n-nodes-base.telegram",
"position": [
2940,
0
],
"webhookId": "0cb93924-6255-48e4-815f-ef2ecd0a8099",
"parameters": {
"text": "=📄 Research Paper Summary\nTitle: {{ $('HTTP Request9').item.json.successful['0'].data.title }}\nURL: {{ $('HTTP Request1').item.json.successful['0'].data.url }}\n\n📝 Summary:\n{{ $json.text }}\n",
"chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
"additionalFields": {
"appendAttribution": false
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"type": "n8n-nodes-base.stickyNote",
"position": [
-20,
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],
"parameters": {
"color": 2,
"width": 780,
"height": 380,
"content": "- Start the workflow when a user sends a message to your Telegram bot. \n- Automatically extract DOI or arXiv identifiers from the message text. \n- Store the Zotero API Key for subsequent steps (e.g., creating or updating Zotero items). \n- Sends a simple HTTP request to the Zotero API to validate and fetch information associated with your Zotero API Key. It is useful as a first step to ensure that your credentials are correctly set up before running more advanced Zotero automations."
},
"typeVersion": 1
},
{
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"name": "付箋2",
"type": "n8n-nodes-base.stickyNote",
"position": [
820,
-500
],
"parameters": {
"color": 4,
"width": 600,
"height": 940,
"content": "- **Crossref API Request** – Fetch bibliographic data from Crossref using the provided DOI. \n- **DataCite API Request** – Retrieve additional metadata and attributes from DataCite. \n- **Unpaywall API Request** – Check open-access availability and possible full-text links. \n- **Structured Data Storage** – Save API responses into separate fields (`crossref`, `datacite`, `unpay`) for merging and downstream processing. \n"
},
"typeVersion": 1
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"position": [
1460,
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"parameters": {
"color": 5,
"width": 360,
"height": 440,
"content": "- Combine metadata from Crossref, DataCite, and Unpaywall into a single object. \n- Prioritize PDF links from Crossref, fallback to Unpaywall, DataCite, or arXiv. \n- Generate a Zotero-ready object including title, DOI, date, publication title, abstract, authors, and tags. \n- Identify whether the resource is a journal article or preprint. \n"
},
"typeVersion": 1
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{
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"name": "Send a text message1",
"type": "n8n-nodes-base.telegram",
"position": [
2160,
200
],
"webhookId": "0cb93924-6255-48e4-815f-ef2ecd0a8099",
"parameters": {
"text": "=PDF not found",
"chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
"additionalFields": {
"appendAttribution": false
}
},
"typeVersion": 1.2
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"position": [
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],
"parameters": {
"color": 6,
"width": 640,
"height": 600,
"content": "- Uses an IF node to check whether a PDF URL is available. \n- Creates a new Zotero item with complete metadata. \n- Automatically attaches the full-text PDF to the Zotero item if available. \n- Alerts the user in Telegram when no PDF could be found. \n"
},
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"type": "n8n-nodes-base.stickyNote",
"position": [
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"parameters": {
"width": 600,
"height": 600,
"content": "- Uses a basic LLM chain to summarize paper abstracts. \n- Delivers the paper title, URL, and generated summary back to the user in a formatted message. \n"
},
"typeVersion": 1
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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？
上級 - AI要約, 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。
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ワークフロー情報
難易度
上級
ノード数25
カテゴリー2
ノードタイプ10
作成者
Budi SJ
@budisjI’m a Product Designer who also works as an Automation Developer. With a background in product design and systems thinking, I build user-centered workflows. My focus is on helping teams and businesses work more productively through impactful automation systems.
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