Import Research Papers From Telegram to Zotero with AI Abstract Summaries

The workflow JSON

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{
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  "meta": {
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  "name": "Automatically Import Research Papers using DOI URL from Telegram to Zotero",
  "tags": [],
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        "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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      "position": [
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        "url": "=https://api.datacite.org/dois/{{ $('Code').item.json.doi }}",
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      "onError": "continueRegularOutput",
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        "url": "=https://api.crossref.org/works/{{ $('Code').item.json.doi }}",
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        "url": "=https://api.unpaywall.org/v2/{{ $('Code').item.json.doi }}?email=your-email@example.com",
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        "jsCode": "// Code4 \u2014 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(\\?|$)/i.test(loc.url || '')) return loc.url;\n  }\n  return null;\n}\n\n// Priority: Crossref \u2192 Unpaywall \u2192 DataCite \u2192 arXiv fallback (from DOI)\nlet pdfUrl = fromCrossref(crossrefBody);\nif (!pdfUrl) pdfUrl = fromUnpay(unpayBody);\nif (!pdfUrl) pdfUrl = fromDataCite(dataciteAttr);\nif (!pdfUrl && /^10\\.48550\\/arxiv\\./i.test(doi || '')) {\n  const arxivId = doi.replace(/^10\\.48550\\/arxiv\\./i, '');\n  pdfUrl = `https://arxiv.org/pdf/${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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        "method": "POST",
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        "method": "POST",
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      "parameters": {
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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## \u2728 Key Features  \n- **Telegram Integration** \u2013 Send a DOI link via Telegram bot to trigger the workflow.  \n- **DOI Parsing** \u2013 Automatically detects and extracts DOI or arXiv identifiers from user messages.  \n- **Metadata Fetching** \u2013 Retrieves bibliographic information from **Crossref**, **DataCite**, and **Unpaywall**.  \n- **Smart PDF Finder** \u2013 Locates the best available PDF (publisher link, open access, or arXiv).  \n- **Zotero Integration** \u2013 Creates a Zotero parent item with complete metadata and attaches the PDF link when available.  \n- **Abstract Summarization** \u2013 Uses a basic LLM chain to generate a short and clear summary of the abstract.  \n- **Telegram Feedback** \u2013 Sends the title, URL, and abstract summary back to the user in Telegram.  \n\n\n## \ud83d\udd11 Required Credentials  \n- **Telegram API** \u2013 To connect the workflow with your Telegram bot.  \n- **Zotero API Key** \u2013 To create and update items in your Zotero library.  \n- **OpenRouter API Key** \u2013 To enable the LLM for generating abstract summaries.  \n- *(Optional)* Email for **Unpaywall API** requests (recommended for stable access).  \n\n## \ud83d\udca1 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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      "position": [
        2600,
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      "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\u20133 sentences), highlight the main contribution or finding, and avoid technical jargon if possible.  "
            }
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    {
      "id": "aa28ca2d-8590-431f-b01f-c80494be010c",
      "name": "Send a text message",
      "type": "n8n-nodes-base.telegram",
      "position": [
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      ],
      "parameters": {
        "text": "=\ud83d\udcc4 Research Paper Summary\nTitle: {{ $('HTTP Request9').item.json.successful['0'].data.title }}\nURL:  {{ $('HTTP Request1').item.json.successful['0'].data.url }}\n\n\ud83d\udcdd Summary:\n{{ $json.text }}\n",
        "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
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          "appendAttribution": false
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      "position": [
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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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    {
      "id": "cc9533ee-5edc-4573-9dfa-1cca98a3c854",
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      "position": [
        820,
        -500
      ],
      "parameters": {
        "color": 4,
        "width": 600,
        "height": 940,
        "content": "- **Crossref API Request** \u2013 Fetch bibliographic data from Crossref using the provided DOI.  \n- **DataCite API Request** \u2013 Retrieve additional metadata and attributes from DataCite.  \n- **Unpaywall API Request** \u2013 Check open-access availability and possible full-text links.  \n- **Structured Data Storage** \u2013 Save API responses into separate fields (`crossref`, `datacite`, `unpay`) for merging and downstream processing.  \n"
      },
      "typeVersion": 1
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      "position": [
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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"
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      "name": "Send a text message1",
      "type": "n8n-nodes-base.telegram",
      "position": [
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      "parameters": {
        "text": "=PDF not found",
        "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
        "additionalFields": {
          "appendAttribution": false
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      "parameters": {
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        "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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      "position": [
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      "parameters": {
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        "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"
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          {
            "node": "If3",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Merge": {
      "main": [
        [
          {
            "node": "Code4",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Edit Fields": {
      "main": [
        [
          {
            "node": "HTTP Request",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Edit Fields1": {
      "main": [
        [
          {
            "node": "Merge",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Edit Fields2": {
      "main": [
        [
          {
            "node": "Merge",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "Edit Fields3": {
      "main": [
        [
          {
            "node": "Merge",
            "type": "main",
            "index": 2
          }
        ]
      ]
    },
    "HTTP Request": {
      "main": [
        [
          {
            "node": "HTTP Request3",
            "type": "main",
            "index": 0
          },
          {
            "node": "HTTP Request2",
            "type": "main",
            "index": 0
          },
          {
            "node": "HTTP Request4",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "HTTP Request1": {
      "main": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "HTTP Request2": {
      "main": [
        [
          {
            "node": "Edit Fields2",
            "type": "main",
            "index": 0
          }
        ],
        []
      ]
    },
    "HTTP Request3": {
      "main": [
        [
          {
            "node": "Edit Fields1",
            "type": "main",
            "index": 0
          }
        ],
        []
      ]
    },
    "HTTP Request4": {
      "main": [
        [
          {
            "node": "Edit Fields3",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "HTTP Request9": {
      "main": [
        [
          {
            "node": "HTTP Request1",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Basic LLM Chain": {
      "main": [
        [
          {
            "node": "Send a text message",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Telegram Trigger": {
      "main": [
        [
          {
            "node": "Code",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenRouter Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}

About this workflow

This 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…

Source: https://n8n.io/workflows/7676/ — original creator credit. Request a take-down →

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