Redis and Telegram integration

🔧 Setup Guide - Hiring Bot Workflow 📋 Prerequisites Before importing this workflow, make sure you have: ✅ n8n Instance (cloud or self-hosted) ✅ Telegram Bot Token (from @BotFather) ✅ OpenAI API Key (with GPT-4 Vision access) ✅ Gmail Account (with OAuth setup) ✅ Google Drive (to store your resume) ✅ Redis Instance (free tier available at Redis Cloud) 🚀 Step-by-Step Setup 1️⃣ Upload Your Resume to OpenAI First, you need to upload your resume to OpenAI's Files API: Upload your resume to OpenAI curl https://api.openai.com/v1/files \ -H "Authorization: Bearer YOUR_OPENAI_API_KEY" \ -F purpose="assistants" \ -F file="@/path/to/your/resume.pdf" Important: Save the file_id from the response (looks like file-xxxxxxxxxxxxx) Alternative: Use OpenAI Playground or Python: from openai import OpenAI client = OpenAI(api_key="YOUR_API_KEY") with open("resume.pdf", "rb") as file: response = client.files.create(file=file, purpose="assistants") print(f"File ID: {response.id}") 2️⃣ Upload Your Resume to Google Drive Go to Google Drive Upload your resume PDF Right-click → "Get link" → Copy the file ID from URL URL format: https://drive.google.com/file/d/FILE_ID_HERE/view Example ID: 1h79U8IFtI2dp_OBtnyhdGaarWpKb9qq9 3️⃣ Create a Telegram Bot Open Telegram and message @BotFather Send /newbot Choose a name and username Save the Bot Token (looks like 123456789:ABCdefGHIjklMNOpqrsTUVwxyz) (Optional) Set bot commands: /start - Start the bot /help - Get help 4️⃣ Set Up Redis Option A: Redis Cloud (Recommended - Free) Go to Redis Cloud Create a free account Create a database Note: Host, Port, Password Option B: Local Redis Docker docker run -d -p 6379:6379 redis:latest Or via package manager sudo apt-get install redis-server 5️⃣ Import the Workflow to n8n Open n8n Click "+" → "Import from File" Select Hiring_Bot_Anonymized.json Workflow will import with placeholder values 6️⃣ Configure Credentials A. Telegram Bot Credentials In n8n, go to Credentials → Create New Select "Telegram API" Enter your Bot Token from Step 3 Test & Save B. OpenAI API Credentials Go to Credentials → Create New Select "OpenAI API" Enter your OpenAI API Key Test & Save C. Redis Credentials Go to Credentials → Create New Select "Redis" Enter: Host: Your Redis host Port: 6379 (default) Password: Your Redis password Test & Save D. Gmail Credentials Go to Credentials → Create New Select "Gmail OAuth2 API" Follow OAuth setup flow Authorize n8n to access Gmail Test & Save E. Google Drive Credentials Go to Credentials → Create New Select "Google Drive OAuth2 API" Follow OAuth setup flow Authorize n8n to access Drive Test & Save 7️⃣ Update Node Values A. Update OpenAI File ID in "PayloadForReply" Node Double-click the "PayloadForReply" node Find this line in the code: const resumeFileId = "YOUR_OPENAI_FILE_ID_HERE"; Replace with your actual OpenAI file ID from Step 1: const resumeFileId = "file-xxxxxxxxxxxxx"; Save the node B. Update Google Drive File ID (Both "Download Resume" Nodes) There are TWO nodes that need updating: Node 1: "Download Resume" Double-click the node In the "File ID" field, click "Expression" Replace YOUR_GOOGLE_DRIVE_FILE_ID with your actual ID Update "Cached Result Name" to your resume filename Save Node 2: "Download Resume1" (same process) Double-click the node Update File ID Update filename Save 8️⃣ Assign Credentials to Nodes After importing, you need to assign your credentials to each node: Nodes that need credentials: | Node Name | Credential Type | |-----------|----------------| | Telegram Trigger | Telegram API | | Generating Reply | OpenAI API | | Store AI Reply | Redis | | GetValues | Redis | | Download Resume | Google Drive OAuth2 | | Download Resume1 | Google Drive OAuth2 | | Schedule Email | Gmail OAuth2 | | SendConfirmation | Telegram API | | Send a message | Telegram API | | Edit a text message | Telegram API | | Send a text message | Telegram API | | Send a chat action | Telegram API | How to assign: Click on each node In the "Credentials" section, select your saved credential Save the node 🧪 Testing the Workflow 1️⃣ Activate the Workflow Click the "Active" toggle in the top-right Workflow should now be listening for Telegram messages 2️⃣ Test with a Job Post Find a job post online (LinkedIn, Indeed, etc.) Take a screenshot Send it to your Telegram bot Bot should respond with: "Analyzing job post..." (typing indicator) Full email draft with confirmation button 3️⃣ Test Email Sending Click "Send The Email" button Check Gmail to verify email was sent Check if resume was attached 🐛 Troubleshooting Issue: "No binary image found" Solution:** Make sure you're sending an image file, not a document Issue: "Invalid resume file_id" Solution:** Check OpenAI file_id format (starts with file-) Verify file was uploaded successfully Make sure you updated the code in PayloadForReply node Issue: "Failed to parse model JSON" Solution:** Check OpenAI API quota/limits Verify model name is correct (gpt-5.2) Check if image is readable Issue: Gmail not sending Solution:** Re-authenticate Gmail OAuth Check Gmail permissions Verify "attachments" field is set to "Resume" Issue: Redis connection failed Solution:** Test Redis connection in credentials Check firewall rules Verify host/port/password Issue: Telegram webhook not working Solution:** Deactivate and reactivate workflow Check Telegram bot token is valid Make sure bot is not blocked 🔐 Security Best Practices Never share your credentials - Keep API keys private Use environment variables in n8n for sensitive data Set up Redis password - Don't use default settings Limit OAuth scopes - Only grant necessary permissions Rotate API keys regularly Monitor usage - Check for unexpected API calls 🎨 Customization Ideas Change AI Model In the PayloadForReply node, update: const MODEL = "gpt-5.2"; // Change to gpt-4, claude-3-opus, etc. Adjust Email Length Modify the system prompt: // From: Email body: ~120–180 words unless INSIGHTS specify otherwise. // To: Email body: ~100–150 words for concise applications. Add More Languages Update language detection logic in the system prompt to support more languages. Custom Job Filtering Edit the system prompt to target specific roles: // From: Only pick ONE job offer to process — the one most clearly related to Data roles // To: Only pick ONE job offer to process — the one most clearly related to [YOUR FIELD] Add Follow-up Reminders Add a "Wait" node after email sends to schedule a reminder after 7 days. 📊 Workflow Structure Telegram Input ↓ Switch (Route by type) ↓ ├─ New Job Post │ ↓ │ Send Chat Action (typing...) │ ↓ │ PayloadForReply (Build AI request) │ ↓ │ Generating Reply (Call OpenAI) │ ↓ │ FormatAiReply (Parse JSON) │ ↓ │ Store AI Reply (Redis cache) │ ↓ │ SendConfirmation (Show preview) │ └─ Callback (User clicked "Send") ↓ GetValues (Fetch from Redis) ↓ Format Response ↓ Download Resume (from Drive) ↓ ├─ Path A: Immediate Send │ ↓ │ Send Confirmation Message │ ↓ │ Edit Message (update status) │ └─ Path B: Scheduled Send ↓ Wait (10 seconds) ↓ Download Resume Again ↓ Schedule Email (Gmail) ↓ Send Success Message 💡 Tips for Best Results High-Quality Resume: Upload a well-formatted PDF resume Clear Screenshots: Take clear, readable job post screenshots Use Captions: Add instructions via Telegram captions Example: "make it more casual" Example: "send to [email protected]" Review Before Sending: Always read the draft before clicking send Update Resume Regularly: Keep your Google Drive resume current Test First: Try with a few test jobs before mass applying 🆘 Need Help? 📚 n8n Documentation 💬 n8n Community Forum 📺 n8n YouTube Channel 🤖 OpenAI Documentation 📱 Telegram Bot API Docs 📝 Checklist Use this checklist to verify your setup: [ ] OpenAI resume file uploaded (got file_id) [ ] Google Drive resume uploaded (got file ID) [ ] Telegram bot created (got bot token) [ ] Redis instance created (got credentials) [ ] All n8n credentials created and tested [ ] PayloadForReply node updated with OpenAI file_id [ ] Both Download Resume nodes updated with Drive file_id [ ] All nodes have credentials assigned [ ] Workflow activated [ ] Test message sent successfully [ ] Test email received successfully 🎉 You're all set! Start applying to jobs in 10 seconds! Made with ❤️ and n8n

Automatically capture, categorize, and log expenses from receipts, PDFs, voice notes, or text — powered by AI and integrated with Telegram and Google Sheets. 🧑‍💼 Who is this for? Small business owners, freelancers, digital nomads, and finance professionals who want to eliminate manual expense tracking and automate financial data entry through chat, AI, and cloud tools. ❓ What problem is this workflow solving? Manually managing receipts and tracking expenses across various formats (paper, PDF, or voice) is time-consuming and error-prone. This workflow automates that entire process—OCR, categorization, validation, and reporting—so your finances stay organized with zero manual effort. 📦 What You Get ✅ Complete Smart_Money_Manager.json n8n workflow 📄 API credential setup guide 📈 Google Sheets sample template 🛠️ AI prompt customization examples 🧪 Troubleshooting & error handling logic 📺 Bonus video tutorial (if provided) 💬 Telegram support from the developer ⚙️ What this workflow does 🎯 Triggers Runs on Telegram message (text, image, voice note, PDF) Smart inline menu to select income or expense tracking 🧠 Processing Auto-detects content type (photo, PDF, voice note, or text) Transcribes voice using OpenAI Whisper Extracts data from images using Google Vision OCR Parses PDFs via LlamaIndex Uses OpenAI GPT-4 for intelligent expense categorization and validation Categorizes by income/expense, with subcategories like Food, Transport, etc. Parses currency and performs logic validation on totals 📊 Logging Automatically appends categorized transaction data into Google Sheets Adds details like date, merchant, item list, payment method, etc. Saves both income and expenses with conditional Google Sheet routing 💬 Notifications Sends detailed transaction summaries via Telegram Warns users of errors or invalid inputs with friendly retry guidance Voice-command friendly for hands-free logging 🔧 How to customize this workflow to your needs 🧾 Add custom expense types — edit categorization prompts in the GPT node 🌎 Enable multi-language or multi-currency support by modifying AI prompts 🗂️ Route to different Google Sheets by user ID, business unit, or project 📣 Expand to other platforms — Add Slack or email notifications 🔍 Enhance validation with stricter logic for budgets, tax codes, or policy rules 🚀 Setup Instructions Requirements: n8n instance (Cloud or self-hosted)** (Cloud or self-hosted) Telegram Bot API credentials Google Cloud (Vision API) OpenAI API key LlamaIndex API key Google Sheets API Redis (optional, for session memory) Step-by-step: Import workflow.json into your n8n instance Configure credentials for all services: Telegram, OpenAI, Google, Redis Set up your Google Sheets with defined columns Modify AI prompts (optional) for categories and business rules Test by sending a receipt photo, PDF invoice, or voice note to your bot Monitor output in Google Sheets and Telegram summaries 🧩 Nodes Used Telegram Trigger + Chat Node** (bot interaction and input selection) Switch/IF nodes** (content-type routing and condition checking) OpenAI Whisper & GPT-4** (voice transcription and categorization) Google Vision OCR** (receipt image processing) LlamaIndex PDF API** (PDF parsing and extraction) Google Sheets Append** (expense logging and formatting) Redis** (session and state tracking) Custom JS nodes** (data transformation and formatting) Made by: Khaisa Studio Tag: youtube, summarizer, telegram, openai Category: AI Automation, Video Tools Need a custom? Contact Me 💸 Take control of your finances with zero manual work. Let Smart Money Manager handle the receipts, so you can focus on growing your business.

How It Works Telegram bot listens for messages and uses chat ID as the unique user identifier. Checks Google Sheets for existing users; registers new users if not found. Caches active sessions in Redis for fast lookup and login-state handling. Stores and retrieves user data (UserID, Name, Telegram Chat ID) in Google Sheets. Can be triggered by other n8n workflows to fetch or update user/session data. Setup Steps Obtain Telegram Bot token, Google Sheets “Users” sheet with API credentials, and a Redis instance. Import the n8n workflow and configure Redis, Telegram Bot, and Google Sheets credentials. Expect 30–45 minutes to complete workflow import, Redis setup, and API wiring. Refer to sticky notes inside the workflow for exact field mappings and node configurations.

Workflow Name: 💬 Demo Call Back Template was created in n8n v1.90.2 Skill Level: High Categories: n8n, Chatbot Stacks Execute Sub-workflow Trigger node Chat Trigger node Redis node Postgres node Telegram node HTTP Request node If node, Code node, Edit Fields (Set) Prerequisite Execute Sub-workflow Trigger: your own node MiniMax Account (https://www.minimax.io/) Production Features Scaling Design* for n8n Queue mode* in production environment Optional Provider Data from external Database with Caching Mechanism. Optional AI Clone Voice Message response via MiniMax API with Multi-Languages support. Optional Backup Chat Log to Database, so you can use in APP/API building. Testing Flow** with or without dependance on other workflow. Multi Chatbot** (This is a demo for Telegram, you can add WhatsApp, Line, etc) Error Management** What this workflow does? This is a n8n Telegram Output Workflow. It will receive message from other Sub-workflow then output to Telegram for Message, or Replay Message and extra Voice Message. How it works The Flow Trigger node will wait for the message from other Sub-workflow. When message is received, it will first check for the matching Provider from the PostgreSQL database. Then determine if it is a Voice message to Text message. OPTIONAL. For voice message, use the MiniMax API to generate a voice message, then send it to Telegram. Finally, send the text to Telegram. Set up instructions Pull and Set up the required SQL from our Github repository. Create you Redis credentials, refer to n8n integration documentation for more information. Select your Credentials in Provider Cache and Save Provider Cache. Create you Postgres credentials, refer to n8n integration documentation for more information. Select your Credentials in Load Member Data, Create Chat Log Input, and Create Chat Log Output. Create you Telegram credentials, refer to n8n integration documentation for more information. Select your Credentials in Telegram Voice Output, Telegram Reply Output, and Telegram Output. AI Clone Voice setup instructions (Optional) You can clone any voice with MiniMax Go to https://www.minimax.io/ and create a MiniMax account Setup the Database with the required variables found in the MiniMax TTS node That’s it How to adjust it to your needs By default, this template will use the sys_provider table provider information, you could change it for your own design. The demo use MiniMax API for AI voice cloning, you could implement any other AI your choice. The Backup Chat Log will backup all chat conversion line by line. You can use it for you own APP/API development.

Workflow Name: 🤙 Telegram Call In Template was created in n8n v1.90.2 Skill Level: High Categories: n8n, Chatbot Stacks Chat Trigger node Telegram Trigger node Redis node Postgres node Execute Sub-workflow If node, Code node, Edit Fields (Set), Extract From File Prerequisite Community nodes: n8n-nodes-google-speech Sub-workflow: Demo Call Back Sub-workflow: Demo Call Center Production Features Scaling Design* for n8n Queue mode* in production environment Optional Member Data from external Database with Caching Mechanism. Optional Voice Message to Text Message via Google STT API with Multi-Languages support. Testing Flow** with or without dependance on other workflow. Error Management** What this workflow does? This is a n8n Telegram Call In Workflow. It will wait for message from Telegram bot and sent to the Call Center to process. How it works The Telegram Trigger node will wait for the message from the Telegram bot. When message is received, it will first check for the matching Member from the PostgreSQL database. Then determine if it is a Text message or Voice message. For voice message, use the Google Speech to Text API to transcript it into text. Finally, pass the text to the next flow, i.e. the Call Center. Set up instructions n8n-nodes-google-speech Pull and Set up the required SQL from our Github repository. Go User > Settings > Community nodes, install n8n-nodes-google-speech node Follow https://www.npmjs.com/package/n8n-nodes-google-speech Setup the Google STT node Create you Telegram credentials, refer to n8n integration documentation for more information. Select your Credentials in Telegram Trigger Create you Redis credentials, refer to n8n integration documentation for more information. Select your Credentials in Member Cache and Save Member Cache. Create you Postgres credentials, refer to n8n integration documentation for more information. Select your Credentials in Load Member Data. FOR TEST ONLY. Enable the Telegram Test Output for testing from the Test Input. Remember to activate this workflow for incoming message. How to adjust it to your needs By default, this template will use the sys_member table for member information, you could change it for your own design. The demo implementation does not include failed member loading situation, you should implement based on your needs, e.g. if is_active is not true, do… You can replace the sub-workflow Demo Call Back and Demo Call Center to another flow as needs.

A robust n8n workflow designed to enhance Telegram bot functionality for user management and broadcasting. It facilitates automatic support ticket creation, efficient user data storage in Redis, and a sophisticated system for message forwarding and broadcasting. How It Works Telegram Bot Setup: Initiate the workflow with a Telegram bot configured for handling different chat types (private, supergroup, channel). User Data Management: Formats and updates user data, storing it in a Redis database for efficient retrieval and management. Support Ticket Creation: Automatically generates chat tickets for user messages and saves the corresponding topic IDs in Redis. Message Forwarding: Forwards new messages to the appropriate chat thread, or creates a new thread if none exists. Support Forum Management: Handles messages within a support forum, differentiating between various chat types and user statuses. Broadcasting System: Implements a broadcasting mechanism that sends channel posts to all previous bot users, with a system to filter out blocked users. Blocked User Management: Identifies and manages blocked users, preventing them from receiving broadcasted messages. Versatile Channel Handling: Ensures that messages from verified channels are properly managed and broadcasted to relevant users. Set Up Steps Estimated Time**: Around 30 minutes. Requirements**: A Telegram bot, a Redis database, and Telegram group/channel IDs are necessary. Configuration**: Input the Telegram bot token and relevant group/channel IDs. Configure message handling and user data processing according to your needs. Detailed Instructions**: Sticky notes within the workflow provide extensive setup information and guidance. Live Demo Workflow Bot: Telegram Bot Link (Click here) Support Group: Telegram Group Link (Click here) Broadcasting Channel: Telegram Channel Link (Click here) Keywords: n8n workflow, Telegram bot, chat ticket system, Redis database, message broadcasting, user data management, support forum automation

🔄 AI Video Polling Engine - Long-Running Job Handler for Veo, Sora & Seedance The async backbone that makes AI video generation production-ready ⚡🎬 🎥 See It In Action 🔗 Full Demo: youtu.be/OI_oJ_2F1O0 ⚠️ Must Read First This is a companion workflow for the main AI Shorts Generator: 🔗 Main Workflow: AI Shorts Reactor This workflow handles the "waiting game" so your main bot stays fast and responsive. Think of it as the backstage crew that handles the heavy lifting while your main workflow performs on stage. 🤔 The Problem This Solves Without This Workflow: User sends message ↓ Bot calls AI API ↓ ⏳ Bot waits 2-5 minutes... (BLOCKED) ↓ ❌ Timeout errors ❌ Execution limits exceeded ❌ Users think bot is broken ❌ Can't handle multiple requests With This Workflow: User sends message ↓ Bot calls AI API ↓ ✅ Bot responds instantly: "Video generating..." ↓ 🔄 This webhook polls in background ↓ ⚡ Main bot handles other users ↓ ✅ Video ready → Auto-sends to user Result: Your bot feels instant, scales infinitely, and never times out 🚀 🔁 What This Workflow Does This is a dedicated polling webhook that acts as the async job handler for AI video generation. It's the invisible worker that: 1️⃣ Receives the Job POST /webhook/poll-video { "sessionId": "user_123", "taskId": "veo_abc456", "model": "veo3", "attempt": 1 } 2️⃣ Responds Instantly 200 OK - "Polling started" (Main workflow never waits!) 3️⃣ Polls in Background Wait 60s → Check status → Repeat ⏱️ Waits 1 minute between checks (API-friendly) 🔄 Polls up to 15 times (~15 minutes max) 🎯 Supports Veo, Sora, and Seedance APIs 4️⃣ Detects Completion Handles multiple API response formats: // Veo format { status: "completed", videoUrl: "https://..." } // Market format (Sora/Seedance) { job: { status: "success", result: { url: "..." } } } // Legacy format { data: { video_url: "..." } } (No matter how the API responds, this workflow figures it out) 5️⃣ Delivers the Video Once ready: 📥 Downloads video from AI provider ☁️ Uploads to your S3 storage 💾 Restores user session from Redis 📱 Sends Telegram preview with buttons 🔄 Enables video extension (Veo only) 📊 Logs metadata for analytics ⚙️ Technical Architecture The Flow: Main Workflow Polling Webhook │ │ ├──[Trigger AI Job]──────────┤ │ "Task ID: abc123" │ │ │ ├──[Return Instantly] │ │ "Generating..." │ │ │ ├──[Handle New User] │ │ ├──[Wait 60s] │ │ │ ├──[Check Status] │ │ "Processing..." │ │ │ ├──[Wait 60s] │ │ │ ├──[Check Status] │ │ "Completed!" │ │ │ ├──[Download Video] │ │ │ ├──[Upload to S3] │ │ │ └──[Send to User] │ │ └──────────────────────────────────┘ "Your video is ready!" 🚀 Key Features ⚡ Non-Blocking Architecture Main workflow never waits Handle unlimited concurrent jobs Each user gets instant responses 🔄 Intelligent Polling Respects API rate limits (60s intervals) Auto-retries on transient failures Graceful timeout handling (15 attempts max) 🎯 Multi-Provider Support Handles different API formats: Veo** - record-info endpoint Sora** - Market job status Seedance** - Market job status 🛡️ Robust Error Handling ✅ Missing video URL → Retry with fallback parsers ✅ API timeout → Continue polling ✅ Invalid response → Parse alternative formats ✅ Max attempts reached → Notify user gracefully 💾 Session Management Stores state in Redis Restores full context when video is ready Supports video extension workflows Maintains user preferences 📊 Production Features Detailed logging at each step Metadata tracking (generation time, model used, etc.) S3 storage integration Telegram notifications Analytics-ready data structure 🧩 Integration Points Works Seamlessly With: | Use Case | How It Helps | |----------|--------------| | 🤖 Telegram Bots | Keeps bot responsive during 2-5 min video generation | | 📺 YouTube Automation | Polls video, then triggers auto-publish | | 🎬 Multi-Video Pipelines | Handles 10+ videos simultaneously | | 🏢 Content Agencies | Production-grade reliability for clients | | 🧪 A/B Testing | Generate multiple variations without blocking | Required Components: ✅ Main workflow that triggers video generation ✅ Redis for session storage ✅ S3-compatible storage for videos ✅ KIE.ai API credentials ✅ Telegram Bot (for notifications) 📋 How to Use Step 1: Set Up Main Workflow Import and configure the AI Shorts Reactor Step 2: Import This Webhook Add this workflow to your n8n instance Step 3: Configure Credentials KIE.ai API key Redis connection S3 storage credentials Telegram bot token Step 4: Link Workflows In your main workflow, call this webhook: // After triggering AI video generation const response = await httpRequest({ method: 'POST', url: 'YOUR_WEBHOOK_URL/poll-video', body: { sessionId: sessionId, taskId: taskId, model: 'veo3', attempt: 1 } }); Step 5: Activate & Test Activate this polling webhook Trigger a video generation from main workflow Watch it poll in background and deliver results 🎯 Real-World Example Scenario: User generates 3 videos simultaneously Without This Workflow: User A: "Generate video" → Bot: ⏳ Processing... (BLOCKED 5 min) User B: "Generate video" → Bot: ❌ Timeout (main workflow still processing User A) User C: "Generate video" → Bot: ❌ Never receives request With This Workflow: User A: "Generate video" → Bot: ✅ "Generating! Check back in 3 min" → Polling webhook handles in background User B: "Generate video" → Bot: ✅ "Generating! Check back in 3 min" → Second polling instance starts User C: "Generate video" → Bot: ✅ "Generating! Check back in 3 min" → Third polling instance starts 3 minutes later--- User A: 📹 "Your video is ready!" [Preview] [Publish] User B: 📹 "Your video is ready!" [Preview] [Publish] User C: 📹 "Your video is ready!" [Preview] [Publish] All three users served simultaneously with zero blocking! 🚀 🔧 Customization Options Adjust Polling Frequency // Default: 60 seconds // For faster testing (use credits faster): const waitTime = 30; // seconds // For more API-friendly (slower updates): const waitTime = 90; // seconds Change Timeout Limits // Default: 15 attempts (15 minutes) const maxAttempts = 20; // Increase for longer videos Add More Providers Extend to support other AI video APIs: switch(model) { case 'veo3': // Existing Veo logic case 'runway': // Add Runway ML polling case 'pika': // Add Pika Labs polling } Custom Notifications Replace Telegram with: Discord webhooks Slack messages Email notifications SMS via Twilio Push notifications 📊 Monitoring & Analytics What Gets Logged: { "sessionId": "user_123", "taskId": "veo_abc456", "model": "veo3", "status": "completed", "attempts": 7, "totalTime": "6m 32s", "videoUrl": "s3://bucket/videos/abc456.mp4", "metadata": { "duration": 5.2, "resolution": "1080x1920", "fileSize": "4.7MB" } } Track Key Metrics: ⏱️ Average generation time per model 🔄 Polling attempts before completion ❌ Failure rate by provider 💰 Cost per video (API usage) 📈 Concurrent job capacity 🚨 Troubleshooting "Video never completes" ✅ Check KIE.ai API status ✅ Verify task ID is valid ✅ Increase maxAttempts if needed ✅ Check API response format hasn't changed "Polling stops after 1 attempt" ✅ Ensure webhook URL is correct ✅ Check n8n execution limits ✅ Verify Redis connection is stable "Video downloads but doesn't send" ✅ Check Telegram bot credentials ✅ Verify S3 upload succeeded ✅ Ensure Redis session exists ✅ Check Telegram chat ID is valid "Multiple videos get mixed up" ✅ Confirm sessionId is unique per user ✅ Check Redis key collisions ✅ Verify taskId is properly passed 🏗️ Architecture Benefits Why Separate This Logic? | Aspect | Monolithic Workflow | Separated Webhook | |--------|--------------------|--------------------| | ⚡ Response Time | 2-5 minutes | <1 second | | 🔄 Concurrency | 1 job at a time | Unlimited | | 💰 Execution Costs | High (long-running) | Low (short bursts) | | 🐛 Debugging | Hard (mixed concerns) | Easy (isolated logic) | | 📈 Scalability | Poor | Excellent | | 🔧 Maintenance | Complex | Simple | 🛠️ Requirements Services Needed: ✅ n8n Instance (cloud or self-hosted) ✅ KIE.ai API (Veo, Sora, Seedance access) ✅ Redis (session storage) ✅ S3-compatible Storage (videos) ✅ Telegram Bot (optional, for notifications) Skills Required: Basic n8n knowledge Understanding of webhooks Redis basics (key-value storage) S3 upload concepts Setup Time: ~15 minutes Technical Level: Intermediate 🏷️ Tags webhook polling async-jobs long-running-tasks ai-video veo sora seedance production-ready redis s3 telegram youtube-automation content-pipeline scalability microservices n8n-webhook job-queue background-worker 💡 Best Practices Do's ✅ Keep polling interval at 60s minimum (respect API limits) Always handle timeout scenarios Log generation metadata for analytics Use unique session IDs per user Clean up Redis after job completion Don'ts ❌ Don't poll faster than 30s (risk API bans) Don't store videos in Redis (use S3) Don't skip error handling Don't use this for real-time updates (<10s) Don't forget to activate the webhook 🌟 Success Stories After Implementing This Webhook: | Metric | Before | After | |--------|--------|-------| | ⚡ Bot response time | 2-5 min | <1 sec | | 🎬 Concurrent videos | 1 | 50+ | | ❌ Timeout errors | 30% | 0% | | 😊 User satisfaction | 6/10 | 9.5/10 | | 💰 Execution costs | $50/mo | $12/mo | 🔗 Related Workflows 🎬 Main: AI Shorts Reactor - The full video generation bot 📤 YouTube Auto-Publisher - Publish completed videos 🎨 Video Style Presets - Custom prompt templates 📊 Analytics Dashboard - Track all generations 📜 License MIT License - Free to use, modify, and distribute! ⚡ Make your AI video workflows production-ready. Let the webhook handle the waiting. ⚡ Created by Joe Venner | Built with ❤️ and n8n | Part of the AI Shorts Reactor ecosystem

Breaking News Aggregator with Telegram and Redis ⚠️ COMMUNITY TEMPLATE DISCLAIMER: This is a community-contributed template that uses ScrapeGraphAI (a community node). Please ensure you have the ScrapeGraphAI community node installed in your n8n instance before using this template. This workflow monitors selected government websites, regulatory bodies, and legal-news portals for new or amended regulations relevant to specific industries. It scrapes the latest headlines, compares them against previously recorded items in Redis, and pushes real-time compliance alerts to a Telegram channel or chat. Pre-conditions/Requirements Prerequisites n8n instance (self-hosted or cloud) ScrapeGraphAI community node installed Redis server accessible from n8n Telegram Bot created via BotFather (Optional) Cron node if you want fully automated scheduling instead of manual trigger Required Credentials ScrapeGraphAI API Key** – Enables ScrapeGraphAI scraping functionality Telegram Bot Token** – Allows n8n to send messages via your bot Redis Credentials** – Host, port, and (if set) password for your Redis instance Redis Setup Requirements | Key Name | Description | Example | |----------|-------------|---------| | latestRegIds | Redis Set used to store hashes/IDs of the most recent regulatory articles processed | latestRegIds | > Hint: Use a dedicated Redis DB (e.g., DB 1) to keep workflow data isolated from other applications. How it works This workflow monitors selected government websites, regulatory bodies, and legal-news portals for new or amended regulations relevant to specific industries. It scrapes the latest headlines, compares them against previously recorded items in Redis, and pushes real-time compliance alerts to a Telegram channel or chat. Key Steps: Manual Trigger / Cron**: Starts the workflow manually or on a set schedule (e.g., daily at 06:00 UTC). Code (Define Sources)**: Returns an array of URL objects pointing to regulatory pages to monitor. SplitInBatches**: Iterates through each source URL in manageable chunks. ScrapeGraphAI**: Extracts article titles, publication dates, and article URLs from each page. Merge (Combine Results)**: Consolidates scraped items into a single stream. If (Deduplication Check)**: Verifies whether each article ID already exists in Redis. Set (Format Message)**: Creates a human-readable Telegram message string. Telegram**: Sends the formatted compliance alert to your chosen chat/channel. Redis (Add New IDs)**: Stores the article ID so it is not sent again in the future. Sticky Note**: Provides inline documentation inside the workflow canvas. Set up steps Setup Time: 10-15 minutes Install community nodes: In n8n, go to Settings → Community Nodes and install n8n-nodes-scrapegraphai. Create credentials: a. Telegram → Credentials → Telegram API → paste your bot token. b. Redis → Credentials → Redis → fill host, port, password, DB. c. ScrapeGraphAI → Credentials → ScrapeGraphAI API → enter your key. Configure the “Define Sources” Code node: Replace the placeholder URLs with the regulatory pages you need to monitor. Update Telegram chat ID: Open any chat with your bot and use https://api.telegram.org/bot<token>/getUpdates to find the chat.id. Insert this value in the Telegram node. Adjust frequency: Replace the Manual Trigger with a Cron node (e.g., daily 06:00 UTC). Test the workflow: Execute once manually; confirm messages appear in Telegram and that Redis keys are created. Activate: Enable the workflow so it runs automatically according to your schedule. Node Descriptions Core Workflow Nodes: Manual Trigger** – Allows on-demand execution during development/testing. Code (Define Sources)** – Returns an array of page URLs and meta info to the workflow. SplitInBatches** – Prevents overloading websites by scraping in controlled groups. ScrapeGraphAI** – Performs the actual web scraping using an AI-assisted parser. Merge** – Merges data streams from multiple batches into one. If (Check Redis)** – Filters out already-processed articles using Redis SET membership. Set** – Shapes output into a user-friendly Telegram message. Telegram** – Delivers compliance alerts to stakeholders in real time. Redis** – Persists article IDs to avoid duplicate notifications. Sticky Note** – Contains usage tips directly on the canvas. Data Flow: Manual Trigger → Code (Define Sources) → SplitInBatches → ScrapeGraphAI ScrapeGraphAI → Merge → If (Check Redis) If (true) → Set → Telegram → Redis Customization Examples Change industries or keywords // Code node snippet return [ { url: "https://regulator.gov/energy-updates", industry: "Energy", keywords: ["renewable", "grid", "tariff"] }, { url: "https://financewatch.gov/financial-rules", industry: "Finance", keywords: ["AML", "KYC", "cryptocurrency"] } ]; Modify Telegram message formatting // Set node “Parameters → Value” items[0].json.message = 🛡️ ${$json.industry} Regulation Update\n\n${$json.title}\n${$json.date}\n${$json.url}; return items; Data Output Format The workflow outputs structured JSON data: { "title": "EU Proposes New ESG Disclosure Rules", "date": "2024-04-18", "url": "https://europa.eu/legal/eu-proposes-esg-disclosure", "industry": "Finance" } Troubleshooting Common Issues Empty scraped data – Verify CSS selectors/XPath in the ScrapeGraphAI node; website structure may have changed. Duplicate alerts – Ensure Redis credentials point to the same DB across nodes; otherwise IDs are not shared. Performance Tips Limit SplitInBatches to 2-3 URLs at a time if sites implement rate limiting. Use environment variables for credentials to simplify migration between stages. Pro Tips: Combine this workflow with n8n’s Error Trigger to log failures to Slack or email. Maintain a CSV of source URLs in Google Sheets and fetch it dynamically via the Google Sheets node. Pair with the Webhook node to let team members add new sources on the fly.