🔬 Summarize PDF documents in Telegram with Groq AI

⚡ 62 views · 🔬 Document Extraction & Analysis

Description

How It Works

Telegram Trigger → Sub-Workflow (Separate Text/Files) → IF (Is PDF?)
├── True: Extract PDF → Set Text → Code (Clean) → Done!
└── False: NoOp (Ignore)

• 9 nodes: Lightweight, efficient (no loops).
• Key Steps:
  1. Triggers on Telegram messages - downloads files.
  2. Sub-workflow splits text/files. (Optional but recommended)
  3. IF node checks MIME type/extension for PDFs.
  4. Extracts text via “Extract From File” node.
  5. AI writes summary.
  6. Responds to user.

Setup Instructions

IMPORTANT : Requiring an n8n instance to be configured with public/production webhook !

Recommendation: Ngrok or Cloudflare Tunnel

1. Add the Telegram credential
   • Go to Credentials → New Credential → Telegram API.
   • Paste your Bot Token.
2. Configure the Trigger
   • Open the Telegram Trigger node.
   • Ensure Trigger On contains Message.
   • Enable Download under Additional Fields so file payloads are attached to the node output.
3. (Optional) Enable the sub‑workflow Automate Telegram Message Processing - Separate Text and Files 💬📁
   • 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.
4. Deploy the workflow and activate it.
5. 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.

Nodes Used

• Telegram Trigger: Listens for incoming messages and downloads attachments.
• Execute Workflow: Calls a sub-workflow to separate text and file data (recommended for reliable file handling).
• If: Checks MIME type to ensure the file is a PDF.
• Extract From File: Converts the PDF binary into text.
• Set: Assignments to organize the text data.
• Code: Cleans the text (removes excess newlines) to prepare it for the LLM.
• Basic LLM Chain: Orchestrates the AI prompt and processing.
• AI Chat Model: The specific LLM provider used for high-speed inference.
• Telegram: Sends the final summary back to the user.

Output Example

The bot will reply with a message formatted like this: > Title: Q3 Financial Report > Type: Financial Report > Exec Summary: Revenue increased by 15% due to new product lines… > Key Insights: > • Growth in APAC region. > • Reduced operational costs by 5%.

🙏 Thank You for Trying This Workflow!

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🔗 Nodes Used

Telegram, Telegram Trigger, Basic LLM Chain, Extract from File, Groq Chat Model

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup