{"workflow":{"id":11451,"name":"Summarize PDF documents in Telegram with Groq AI","views":104,"recentViews":0,"totalViews":104,"createdAt":"2025-12-03T06:05:15.950Z","description":"### How It Works\n```\nTelegram Trigger → Sub-Workflow (Separate Text/Files) → IF (Is PDF?)\n├── True: Extract PDF → Set Text → Code (Clean) → Done!\n└── False: NoOp (Ignore)\n```\n- **9 nodes**: Lightweight, efficient (no loops).\n- **Key Steps**:\n  1. Triggers on Telegram messages - downloads files.\n  2. Sub-workflow splits text/files. *(Optional but recommended)*\n  3. IF node checks MIME type/extension for PDFs.\n  4. Extracts text via **\"Extract From File\"** node.\n  5. AI writes summary.\n  6. Responds to user.\n---\n## Setup Instructions\n***IMPORTANT*** : Requiring an n8n instance to be configured with public/production webhook !\n\n**Recommendation:** Ngrok or Cloudflare Tunnel\n\n1. **Add the Telegram credential**\n   - Go to **Credentials → New Credential → Telegram API**.\n   - Paste your Bot Token.\n2. **Configure the Trigger**\n   - Open the **Telegram Trigger** node.\n   - Ensure `Trigger On` contains `Message`.\n   - Enable **Download** under *Additional Fields* so file payloads are attached to the node output.\n3. (Optional) **Enable the sub‑workflow** [Automate Telegram Message Processing - Separate Text and Files 💬📁](https://n8n.io/workflows/9254-automate-telegram-message-processing-separate-text-and-files/)\n   - If you need both message text and attachments, enable the **Automate Telegram Message Processing – Separate Text and Files** node and import the referenced workflow into your workspace.\n4. **Deploy** the workflow and activate it.\n5. **Testing** Send a message with a PDF attachment to your Telegram bot. There will be a response from the chat that summarizes the PDF content.\n\n## Nodes Used\n* **Telegram Trigger**: Listens for incoming messages and downloads attachments.\n* **Execute Workflow**: Calls a sub-workflow to separate text and file data (recommended for reliable file handling).\n* **If**: Checks MIME type to ensure the file is a PDF.\n* **Extract From File**: Converts the PDF binary into text.\n* **Set**: Assignments to organize the text data.\n* **Code**: Cleans the text (removes excess newlines) to prepare it for the LLM.\n* **Basic LLM Chain**: Orchestrates the AI prompt and processing.\n* **AI Chat Model**: The specific LLM provider used for high-speed inference.\n* **Telegram**: Sends the final summary back to the user.\n\n## Output Example\nThe bot will reply with a message formatted like this:\n> **Title:** Q3 Financial Report\n> **Type:** Financial Report\n> **Exec Summary:** Revenue increased by 15% due to new product lines...\n> **Key Insights:**\n> • Growth in APAC region.\n> • Reduced operational costs by 5%.\n\n---\n## 🙏 Thank You for Trying This Workflow!\nYour time and trust mean a lot! I truly appreciate you using this template.\n### Your feedback shapes future updates:\n- 💡 Suggestions for improvement\n- 🆕 Ideas for new features  \n- 📝 Requests for other automation workflows\n#### Please share your thoughts! Every idea helps shape the next update.\n---\n### 🙋‍♂️ Join & Follow For More Free Templates!\n- #### Discord Community: [We Work Together](https://discord.gg/RFuTXZ4n)\nGet help, share builds, collaborate!\nDaily tips, tutorials, and updates\n### Thank you again for being part of this journey! 🚀\n### Together, we automate better! 🤖✨","workflow":{"meta":{"instanceId":"cd9bb7894b11bab249a60976239056d06e4831b51d7348f6790a85241c21fc56","templateCredsSetupCompleted":true},"nodes":[{"id":"0cd3a6d7-6e8e-43d6-975d-18549c8e6e9d","name":"Get PDF Data","type":"n8n-nodes-base.set","position":[352,-176],"parameters":{"options":{},"assignments":{"assignments":[{"id":"cab388e8-37e9-4a98-b663-680bb6f4b8b2","name":"text","type":"string","value":"={{ $json.text }}"}]}},"typeVersion":3.4},{"id":"282fc6aa-c906-4191-a8dd-59357ee2a6e3","name":"Extract PDF Data","type":"n8n-nodes-base.extractFromFile","position":[160,-176],"parameters":{"options":{},"operation":"pdf"},"typeVersion":1},{"id":"ac1f29c1-98b2-4170-ae50-1e6738b41931","name":"Data Parser & Cleaner","type":"n8n-nodes-base.code","position":[544,-176],"parameters":{"jsCode":"/**\n * This function removes all newline characters (\"\\n\") from a given string.\n * In the context of your n8n workflow, you can use this in a \"Code\" node\n * to clean up the PDF text content before passing it to the AI Agent.\n *\n * @param {string} text The input string that may contain newline characters.\n * @returns {string} The processed string with all newline characters removed.\n */\nfunction removeNewlines(text) {\n  if (typeof text !== 'string') {\n    // Return an empty string or handle the error as appropriate for your workflow\n    console.error(\"Input must be a string.\");\n    return \"\";\n  }\n  // The .replace() method with a regular expression /g ensures all occurrences are replaced.\n  return text.replace(/\\n/g, ' ');\n}\n\n// Example usage based on the text you provided:\n// In your n8n \"Code\" node, you would get the input from the previous node.\n// For example: const a_variable_from_another_node = \"your text here\";\nconst inputText = $input.first().json.text;\nconst cleanedText = removeNewlines(inputText);\nconsole.log(\"Original Text:\");\nconsole.log(inputText);\nconsole.log(\"\\\\n------------------\\\\n\");\nconsole.log(\"Cleaned Text:\");\nconsole.log(cleanedText);\n\n// To use this in n8n, you'd typically return the result like this:\nreturn { cleanedText: cleanedText };\n"},"typeVersion":2},{"id":"c10225ce-b103-481a-b775-0c88c2a44d34","name":"Is PDF File","type":"n8n-nodes-base.if","position":[-112,-272],"parameters":{"options":{},"conditions":{"options":{"version":2,"leftValue":"","caseSensitive":true,"typeValidation":"strict"},"combinator":"and","conditions":[{"id":"776994e7-59b0-49d3-8d86-4bb342574a41","operator":{"type":"boolean","operation":"true","singleValue":true},"leftValue":"={{ $('Telegram Trigger').item.json.message.document.mime_type === 'application/pdf'}}","rightValue":""}]}},"typeVersion":2.2},{"id":"cc27f96f-2167-4c01-be32-a2dbf4abc764","name":"No Operation, do nothing","type":"n8n-nodes-base.noOp","position":[-112,-48],"parameters":{},"typeVersion":1},{"id":"224456cf-cb49-4870-aa50-792d874dd9ce","name":"Sticky Note","type":"n8n-nodes-base.stickyNote","position":[-352,-352],"parameters":{"width":432,"height":464,"content":"## Receive and Filter"},"typeVersion":1},{"id":"8ff09bd8-8e1f-4bca-b3a9-178ba9aab036","name":"Sticky Note1","type":"n8n-nodes-base.stickyNote","position":[112,-288],"parameters":{"width":592,"height":288,"content":"## Extract and Clean\nConverts binary PDF data into clean, plain text."},"typeVersion":1},{"id":"04b4da9f-1c3e-40db-b762-fabe7ee1563c","name":"Sticky Note3","type":"n8n-nodes-base.stickyNote","position":[736,-320],"parameters":{"width":304,"height":400,"content":"## Summarizing\nGenerates a structured summary using AI"},"typeVersion":1},{"id":"62d113e0-d279-4c28-a91f-8707d6ec99ef","name":"Basic LLM Chain","type":"@n8n/n8n-nodes-langchain.chainLlm","position":[784,-224],"parameters":{"text":"={{$json.cleanedText}}","batching":{},"messages":{"messageValues":[{"message":"### ROLE & PERSONA You are an Expert Research Analyst and Senior Technical Communicator. Your goal is to synthesize complex documents into high-value, actionable insights. You possess deep knowledge across business, technology, and academic domains. Your tone is professional, objective, and concise.\n\n### TASK You will receive the text content of a PDF file. Your objective is to analyze the content and generate a structured summary optimized for a Telegram messaging interface.\n\n### ANALYSIS RULES\n1.  **Identify the Core Value:** Determine the primary argument, result, or purpose of the document immediately.\n2.  **Filter Noise:** Ignore introductory fluff, legal disclaimers, or generic pleasantries. Focus on facts, data, and conclusions.\n3.  **Think Step-by-Step:** Before generating the output, internalize the logical flow of the document to ensure the summary follows a coherent narrative.\n4.  **Accuracy:** Strictly adhere to the provided text. Do not hallucinate or invent outside information.\n\n### OUTPUT FORMAT (TELEGRAM OPTIMIZED) You must output the summary using the following Markdown structure exactly. Do not use Markdown features that Telegram does not support (like tables).\n**Title:** [Insert Document Title/Subject]\n**Type:** [e.g., Financial Report, Academic Paper, Legal Contract]\n\n**Exec Summary** [A 1-2 sentence high-level overview of what this document is and why it matters.]\n\n**Key Insights**\n• [Insight 1: Strong fact or data point]\n• [Insight 2: Critical finding or argument]\n• [Insight 3: Critical finding or argument] \n\n**Actionable Takeaways**\n• [What should the reader do with this info?]\n• [Implication or next step]\n\n**Rating:** [1-10 Relevance Score based on content density]"}]},"promptType":"define"},"typeVersion":1.7},{"id":"9d5f909e-7f1c-4884-a21f-c581eee92c36","name":"Telegram Trigger","type":"n8n-nodes-base.telegramTrigger","position":[-288,-272],"webhookId":"b2b661ae-5a43-40c5-a59f-845d6de421db","parameters":{"updates":["message"],"additionalFields":{"download":true}},"credentials":{"telegramApi":{"id":"KDZRFnPXPuAVravz","name":"Template"}},"typeVersion":1.2},{"id":"db7fc6d0-da27-44ff-93b4-6675191cadd3","name":"Groq Chat Model","type":"@n8n/n8n-nodes-langchain.lmChatGroq","position":[848,-64],"parameters":{"model":"openai/gpt-oss-20b","options":{}},"credentials":{"groqApi":{"id":"UXGlRuvH2Jz11Ely","name":"Template"}},"typeVersion":1},{"id":"c56853a9-ae32-4242-be49-5fe97d66c0e7","name":"Send a text message","type":"n8n-nodes-base.telegram","position":[1152,-160],"webhookId":"481164fa-3b19-4315-8125-dc67cdd960a8","parameters":{"text":"={{ $json.text }}","chatId":"={{ $('Is PDF File').item.json.message.chat.id }}","additionalFields":{}},"credentials":{"telegramApi":{"id":"KDZRFnPXPuAVravz","name":"Template"}},"typeVersion":1.2},{"id":"bb869178-6ea3-481e-b14b-3716abb12e9f","name":"Sticky Note4","type":"n8n-nodes-base.stickyNote","position":[1072,-256],"parameters":{"width":256,"height":272,"content":"## Response\nSends the insight back to the user."},"typeVersion":1},{"id":"9f6fb78d-7d8b-4cc4-8432-ffb74c49b616","name":"Sticky Note2","type":"n8n-nodes-base.stickyNote","position":[-400,-432],"parameters":{"color":7,"width":1776,"height":976,"content":"## AI-Powered Document Summarization With Telegram ⌯⌲"},"typeVersion":1},{"id":"68d198ca-58bb-43a6-b2bd-47891785a00c","name":"Sticky Note5","type":"n8n-nodes-base.stickyNote","position":[-352,176],"parameters":{"color":5,"width":832,"height":336,"content":"## How it works\nThis workflow turns your Telegram bot into a personal document analyst. When you upload a PDF file to the chat, n8n automatically intercepts the document and extracts and cleans the raw text to ensure high-quality results. This data is then passed to a Large Language Model (LLM). The LLM acts as an expert analyst, reviewing the content and generating a structured summary with key insights and actionable takeaways. Finally, the summary is formatted and sent back to you in the Telegram chat.\n\n## Setup steps\n- Telegram: create a new bot using @BotFather on Telegram. Copy the HTTP API Token and add it to the credentials in the Telegram Trigger and Telegram nodes.\n- Groq AI: Get a free API key from the Groq Cloud console. Add this key to the credentials in the Groq Chat Model node.\n- Activate: Save the workflow and toggle the \"Active\" switch to on.\n- Test: Open your bot in Telegram and upload a PDF file to receive your summary."},"typeVersion":1},{"id":"4a38d3e9-02fe-45b6-b801-b273991f2833","name":"Sticky Note6","type":"n8n-nodes-base.stickyNote","position":[544,176],"parameters":{"width":784,"height":336,"content":"## Quick Demo\n- Open your bot on Telegram.\n- Drag and drop a financial report or academic paper (PDF) into the chat.\n- Wait 5-10 seconds.\n- Receive a formatted \"Executive Summary\" with bulleted insights.\n\n## Perfect For\n- Summarizing long contracts or legal docs.\n- Quickly reviewing academic papers on the go.\n- Extracting action items from meeting minutes or reports."},"typeVersion":1}],"pinData":{},"connections":{"Is PDF File":{"main":[[{"node":"Extract PDF Data","type":"main","index":0}],[{"node":"No Operation, do nothing","type":"main","index":0}]]},"Get PDF Data":{"main":[[{"node":"Data Parser & Cleaner","type":"main","index":0}]]},"Basic LLM Chain":{"main":[[{"node":"Send a text message","type":"main","index":0}]]},"Groq Chat Model":{"ai_languageModel":[[{"node":"Basic LLM Chain","type":"ai_languageModel","index":0}]]},"Extract PDF Data":{"main":[[{"node":"Get PDF Data","type":"main","index":0}]]},"Telegram Trigger":{"main":[[{"node":"Is PDF File","type":"main","index":0}]]},"Data Parser & Cleaner":{"main":[[{"node":"Basic LLM Chain","type":"main","index":0}]]}}},"lastUpdatedBy":1,"workflowInfo":{"nodeCount":16,"nodeTypes":{"n8n-nodes-base.if":{"count":1},"n8n-nodes-base.set":{"count":1},"n8n-nodes-base.code":{"count":1},"n8n-nodes-base.noOp":{"count":1},"n8n-nodes-base.telegram":{"count":1},"n8n-nodes-base.stickyNote":{"count":7},"n8n-nodes-base.extractFromFile":{"count":1},"n8n-nodes-base.telegramTrigger":{"count":1},"@n8n/n8n-nodes-langchain.chainLlm":{"count":1},"@n8n/n8n-nodes-langchain.lmChatGroq":{"count":1}}},"status":"published","readyToDemo":null,"user":{"name":"EoCi - Mr.Eo","username":"eocimreo","bio":"","verified":true,"links":[""],"avatar":"https://gravatar.com/avatar/6b339bea5116c0f71dfc3abae11ffc31d51395d2437ce34d5f2a107b7b8abfdf?r=pg&d=retro&size=200"},"nodes":[{"id":20,"icon":"fa:map-signs","name":"n8n-nodes-base.if","codex":{"data":{"alias":["Router","Filter","Condition","Logic","Boolean","Branch"],"details":"The IF node can be used to implement binary conditional logic in your workflow. 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