📌 Overview
📌 Overview This workflow allows users to send any newspaper or article link to a Telegram bot. The workflow then: Validates the URL Scrapes the webpage (title, description, full text, images, OG metadata) Processes it using a Vision-Language Model (VLM) Generates structured summaries & highlights Downloads images (if available) Sends a formatted report + document back to Telegram Stores the summary in a vector database Allows users to chat with the article using semantic search Perfect for: ✔ News researchers ✔ Students ✔ Journalists ✔ Telegram-based AI assistants ✔ Automated media monitoring 🧠 What the Workflow Does 1. Telegram Trigger Listens for messages from the user. Detects if the message contains a valid link. 2. URL Scraper A custom n8n Code node fetches the webpage and extracts: Meta description paragraph text All image sources Open Graph metadata (og:title, og:image) Returns everything as structured JSON. 3. VLM Run – Highlighter A Vision-Language Model analyzes the scraped content and outputs: { "news_summary": { "headline": "", "source_url": "", "published_date": "", "key_points": "", "summary": "", "extracted_images_url": "" } } 4. Image Validation & Download Checks if image URLs are valid. Downloads them (if any). Sends them to Telegram as documents. 5. Summary File Generation Converts VLM output into a .txt report. Sends the report back to the user. 6. Vector Store + Q&A Agent Converts the summary into embeddings. Stores the vector in an in-memory store. Provides the user with a chat interface: Ask anything about the newspaper article. The AI agent retrieves information using the vector store. 📤 Outputs You receive: ✔ Telegram message summary ✔ Downloadable summary .txt file ✔ Extracted images (if available) ✔ Chat-based Q&A agent to explore the newspaper details 🚀 Use Cases News summarization bots Media intelligence agents Educational news explorers Topic-based daily digest creators. An n8n automation workflow template by Mehedi Ahamed.
Mehedi Ahamed
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