This article provides a complete, practical walkthrough of the Telegram Splitout Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Automating YouTube Video Analysis with AI: How to Summarize and Chat via Telegram Using n8n & GPT-4o-mini
   
   Meta Description:
   Learn how an n8n workflow integrates Telegram, YouTube, GPT-4o-mini, and Google Docs to summarize YouTube videos and allow users to interactively ask AI questions about the content—all in real time.
   
   Keywords:
   n8n workflow, YouTube transcript summary, GPT-4o-mini Telegram integration, OpenAI GPT-4o-mini, automate YouTube summaries, Telegram AI chatbot, Google Docs integration, YouTube video analysis, AI video summarizer, intelligent video assistant
   
   Third-party APIs/Services Used:
   
   - Telegram Bot API
   - OpenAI API (GPT-4o-mini)
   - YouTube Transcription via n8n community node (youtubeTranscripter)
   - Google Docs API
   - Langchain (integrated via n8n community nodes and tools)
   
   —
   
   Article:
   
   Revolutionizing Video Consumption: Summarize and Interact with YouTube Content via Telegram and GPT-4o-mini
   
   With the explosive growth of video content across the internet, staying on top of the latest information and tutorials can feel overwhelming. But what if you could instantly get a structured summary of a YouTube video and ask questions about its content—all through a chat interface like Telegram?
   
   A new n8n workflow aims to make this a reality by combining the power of AI, natural language processing, and automation. This no-code/low-code workflow lets you:
   
   - Automatically extract a YouTube video transcript
   - Generate structured summaries using OpenAI's GPT-4o-mini
   - Save and update transcripts on Google Docs
   - Interact with the video’s content via Telegram-based AI chat
   
   Here’s a deep dive into how this powerful automation works and the technologies that make it tick.
   
   ⚙️ Step-by-Step Overview of the Workflow
   
   1. 📨 Input a YouTube Video URL
   The workflow accepts a YouTube video URL via two input methods:
   - A Telegram message using the Telegram Bot API
   - A webhook trigger that can be integrated with external tools or an iOS Shortcut
   
   These triggers initiate the chain reaction of actions that follow.
   
   2. 🔍 Extract the Video ID
   Straightforward Python code is used in an internal n8n code node to parse out the video ID from the URL, which is needed to request the video transcript.
   
   3. 📄 Fetch the YouTube Transcript
   Using the community-built youtubeTranscripter node, the video’s subtitles or auto-generated transcript is retrieved by video ID. This eliminates the need for scraping or manual labor.
   
   4. 🧩 Split and Format the Transcript
   To handle large transcripts efficiently, the workflow:
   - Splits the transcript into smaller segments
   - Concatenates the parts into one long, clean string suitable for AI processing
   
   5. 🧠 Generate an AI-Powered Summary (via GPT-4o-mini)
   The full transcript is then submitted to an OpenAI GPT-4o-mini model with a rich prompt:
   - General Summary (concise, one-paragraph overview)
   - Key Moments (outlined event or topic bullet points)
   - Instructions (if applicable, shown as step-by-step)
   - Markdown/HTML formatting restrictions for Telegram compatibility
   
   This ensures a human-readable, skimmable overview—perfect for those who don't have time to watch lengthy videos.
   
   6. 🗨️ Send the Summary to Telegram
   The summary message, carefully formatted for Telegram (using HTML instead of unsupported markdown features like nested lists), is sent directly back to the user's Telegram chat. The original YouTube link is also included for easy reference.
   
   7. 📝 Save Transcript to Google Docs
   If you’d like to interact more deeply with the video content later, the cleaned transcript is written to a Google Docs document, helping maintain context and persistent storage.
   
   8. 🤖 Interactive AI Chat Experience
   The workflow doesn't stop at just summaries. A Telegram-based chat interface allows users to ask follow-up questions about the video.
   
   When a question is asked, the workflow:
   - Loads the saved Google Docs transcript
   - Uses GPT-4o-mini to process the user question
   - Leverages Langchain memory and tool nodes to ensure the AI respects the source information and context
   - Delivers the intelligent response back via Telegram
   
   This turns a YouTube video into a queryable knowledge base.
   
   💡 Use Case Highlights
   - Students can summarize lengthy university lectures on YouTube.
   - Professionals can extract action steps from how-to videos.
   - Curious viewers can ask clarifying questions without watching entire videos.
   - Educators and developers can provide scalable, NLP-driven assistance using publicly available content.
   
   🔗 APIs and Tools Working Behind the Scenes
   
   This workflow is made possible through deep integration of the following third-party APIs and services:
   
   - Telegram Bot API: Used for chatbot input/output and alerting
   - OpenAI API: Provides the GPT-4o-mini model for summarizing and responding to questions
   - YouTube Transcription (via community-built node): Pulls transcripts from YouTube videos
   - Google Docs API: Reads and writes transcript data for persistent memory
   - Langchain: Manages AI tool integration, memory buffers, and agent logic to guide AI responses
   
   📚 A Smart Framework for Smarter Viewing
   
   This project showcases how accessible no-code automation tools like n8n can empower users to transform mundane tasks into intelligent experiences. With cognitive heavy lifting handled by LLMs like GPT-4o-mini, and orchestration by n8n, this workflow brings sophisticated AI-powered interactivity into everyday tools like Telegram and Google Docs.
   
   Combine that with real-time triggers and a structured user interface, and you’ve got a prototype for the future of consuming and interacting with video content.
   
   —  
   Want to implement this system for yourself or your organization? All you need is an n8n server, API credentials for OpenAI, Telegram, and Google, and a basic understanding of how to design workflows using prebuilt nodes. The possibilities are limitless.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.