HTTP Request and Redis integration

This n8n template uses a Telegram chatbot to conduct a Product Satisfaction Survey and fetches questions and stores answers in a Google sheet. It augments an AI Agent to ask follow-up questions to engage the user and uncover more insights in their responses. This template is intended to demonstrate how you'd realistically approach a workflow where there is structured conversation (static questions) but you still want to include an free-form element (follow-up questions) which can only be accomplished via AI. Check out an example Survey results: https://docs.google.com/spreadsheets/d/e/2PACX-1vQWcREg75CzbZd8loVI12s-DzSTj3NE_02cOCpAh7umj0urazzYCfzPpYvvh7jqICWZteDTALzBO46i/pubhtml?gid=0&single=true How it works A chat session is started with the user who needs to enter the bot command "/next" to start the survey. Once started, the template pulls in questions from a google sheet to ask the user. Questions are asked in sequence from left column to right column. When the user answers the question, a text classifier node is used to determine if a follow-up question could be asked. If so, a mini conversation is initiated by the AI agent to get more details. If not, the survey proceeds to the next question. All answers and mini-conversations are recorded in the Google Sheet under the respective question. When all questions are answered, the template will stop the survey and give the user a chance to restart. How to use You'll need to setup a Telegram bot (see docs) Create a google sheet with an ID column. Populate the rest of the columns with your survey questions (see sample) Ensure you have a Redis instance to capture state. Either self-host or sign-up to Upstash for a free account. Update the "Set Variable" node with your google sheet ID and survey title. Share your bot to allow others to participate in your survey. Requirements Telegram for Chatbot Google Sheets for Survey questions and answers Redis for State Management and Chat Memory Community+ license and above for Execution data node - you can remove this node if you don't have this licence. Customising this workflow Not using Telegram? This template technically works with other chat apps such as Whatsapp, wechat and even n8n's hosted chat! This state management pattern can also be applied to other use-cases and scenarios. Try it for other types of surveys!

🔧 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

🤖Multi-Agent AI WhatsApp Bot for Service Businesses Transform your salon/service business with this streamlined WhatsApp automation system featuring Claude integration, zero-setup database management, and intelligent conversation handling. How it works Claude MCP Integration** - Direct connection to Claude Sonnet 4 via Model Context Protocol Streamlined 2-Agent System** - Booking Agent and Admin Agent (simplified from 5 for better reliability) GPT-5 Mini Primary** with Gemini 2.5 Flash backup for cost-effective processing Multi-Media Support** - Handles text, voice (Whisper transcription), images, and PDFs with cost extraction Smart Acknowledgments** - "One moment...", "Let me check availability..." during processing Rate Limiting & Spam Protection** - Configurable limits (default: 100 msg/hour) with professional UX Zero-Setup Database Management Autonomous Airtable Creation** - Bot creates all necessary tables automatically Complete CRUD Operations** - Create, edit, delete services and settings via WhatsApp Dynamic Business Configuration** - Modify hours, pricing, services conversationally Friend Booking Support** - "Book for my friend Sarah" functionality Set up steps WhatsApp Business API** setup (detailed instructions included) Airtable Base ID** extraction (store in Redis or hardcode - recommended) Google Calendar** integration for scheduling Redis** for caching, rate limiting, and conversation memory MCP Server** deployment for Claude integration Whatsapp** for notifications Key Features Booking Limit Control** - Default 6 appointments per customer (configurable in workflow) Service Name Matching** - GPT-5 Nano workflow for cost-optimized service recognition 24-Hour Advance Reminders** - Automatic WhatsApp reminders sent at 8 PM Conversation Memory** maintains context across interactions Error Resilience** with backup models and graceful failure handling Perfect for salons, spas, clinics, consulting services, or any appointment-based business. Complete business setup happens through conversational commands - no manual database configuration required.

AI YouTube Playlist & Video Analyst Chatbot This n8n workflow transforms entire YouTube playlists or single videos into interactive knowledge bases you can chat with. Ask questions and get summaries without needing to watch hours of content. 🌟 How it Works 🔗 Provide a Link: Start by giving the workflow a URL for a YouTube playlist or a single video. 📄 Content Retrieval: The workflow automatically fetches the video details and transcripts for the provided link. For playlists, it can process multiple videos at once (you might be asked how many). 🧠 AI Processing: Google's Gemini AI reads through the transcripts, understands the content, and creates summaries. 💾 Storage & Context: The processed information and summaries are stored in a vector database (Qdrant), making them ready for conversation. Context is managed using Redis, remembering the current video/playlist you're discussing. 💬 Chat & Ask: Now, you can ask the AI agent questions about the playlist or video content! Because context is maintained, you can ask follow-up questions (like "expand on point X") without needing to provide the URL again. 🛠️ Requirements Community Node:** This workflow uses the youtubeTranscripter community node to fetch video transcripts. You'll need to install it in your n8n environment. Installation: npm install n8n-nodes-youtube-transcription-dmr Important: Community nodes require a self-hosted n8n instance. Redis:** A Redis instance is required for managing conversation context and status between interactions. Credentials:** You will need API credentials configured in your n8n instance for: Google Gemini (AI Models) Qdrant (Vector Store) Redis (Context Store) 🤖 AI Agent Capabilities Engage with the AI agent to explore the video content. Since the agent remembers the context of your conversation, you can ask detailed follow-up questions naturally: Get a quick summary of a single video or an entire playlist. Ask for key takeaways or main topics discussed. Query for specific information mentioned in the videos. Ask the agent to elaborate on a specific point previously mentioned. Understand complex subjects without watching the full duration. 🚀 Use Cases 📊 Content Analysis:** Quickly understand the themes and key points across a playlist or long video. 📚 Research & Learning:** Extract insights from educational series or tutorials efficiently. ✍️ Content Creation:** Easily repurpose video transcript information into blog posts, notes, or social media content. ⏱️ Save Time:** Get the essence of video content when you're short on time. ♿ Accessibility:** Offers a text-based way to interact with and understand video content. ✨ Sample Prompts Please analyze this playlist and tell me the main topics covered: [YouTube Playlist URL] Summarize the first 5 videos in this playlist: [YouTube Playlist URL] (Follow-up) Tell me more about the main point in video 3. What are the key points discussed in this video? [YouTube Video URL] (Follow-up) Expand on the second key point you mentioned. Does the video at [YouTube Video URL] mention [specific topic]?

AI-Powered WhatsApp Assistant for Restaurant & Delivery – Automate Orders, Calculate Delivery Fees & Enhance Customer Service with n8n 📌 Optimize your restaurant's delivery process with AI-powered automation! This n8n workflow enables an intelligent WhatsApp assistant for restaurants, burger joints, and delivery businesses. The AI chatbot efficiently handles orders, calculates delivery fees based on distance, manages customer interactions, and seamlessly integrates with your CRM and database for streamlined operations. ⚠️ Important Notice: This template is only compatible with self-hosted n8n instances as it uses community nodes. Ensure secure credential management when configuring APIs. 🔹 Key Features ✅ AI-Powered Order Processing – Automatically receive and confirm orders via WhatsApp. ✅ Real-Time Distance Calculation – Determines the delivery distance and calculates the fee dynamically. ✅ Automated Customer Interaction – Engages customers with intelligent conversation and order updates. ✅ WhatsApp Integration – Processes messages, saves customer details, and retrieves past interactions. ✅ Secure Customer Data Storage – Saves order history, customer preferences, and location details in a database. ✅ Seamless CRM & POS System Integration – Sync orders and customer data with your existing platforms. 📌 How It Works 1️⃣ A customer sends a message via WhatsApp to start an order. 2️⃣ The AI assistant guides them through the menu, recommends items, and confirms their choices. 3️⃣ The system retrieves and saves customer details (name, phone number, and address). 4️⃣ The AI calculates the delivery distance and applies the appropriate delivery fee. 5️⃣ The order details are saved and forwarded to the restaurant’s system for preparation. 6️⃣ The assistant keeps the customer updated about the order status. ⚙️ Setup & Customization 🔧 Webhook for WhatsApp – Capture and process customer messages automatically. 🔧 OpenAI-Powered AI Assistant – Configure conversation flows for natural and engaging interactions. 🔧 Delivery Fee Calculation – Set your delivery price per kilometer and adjust base rates. 🔧 Database & CRM Integration – Store customer details, order history, and location data. 🔧 Customizable Order Flow – Adapt the workflow for different restaurant models. 🔧 Secure Credential Management – Store API keys safely to prevent unauthorized access. 💡 Requirements: This template is recommended for users with basic knowledge of n8n. If you need custom development or setup assistance, contact us via WhatsApp: +55 17 99155-7874. 🚀 Automate order processing, reduce manual tasks, and improve customer satisfaction with AI-powered WhatsApp automation! Assistente de WhatsApp com IA para Restaurantes & Delivery – Automatize Pedidos, Calcule Taxas de Entrega e Melhore o Atendimento ao Cliente com n8n 📌 Otimize o processo de entrega do seu restaurante com automação baseada em IA! Este fluxo para n8n permite criar um atendente virtual inteligente no WhatsApp, ideal para hamburguerias, restaurantes e serviços de delivery. O chatbot baseado em IA recebe pedidos, calcula a taxa de entrega com base na distância, interage com os clientes e integra-se ao seu CRM para operações mais eficientes. ⚠️ Aviso Importante: Este template é compatível apenas com instâncias auto-hospedadas do n8n, pois utiliza nós da comunidade. Certifique-se de gerenciar credenciais de forma segura ao configurar APIs. 🔹 Principais Funcionalidades ✅ Processamento Inteligente de Pedidos – Recebe e confirma pedidos automaticamente via WhatsApp. ✅ Cálculo Dinâmico da Taxa de Entrega – Mede a distância e aplica a taxa correta automaticamente. ✅ Atendimento Automatizado ao Cliente – Interage com clientes de forma natural e profissional. ✅ Integração com WhatsApp – Captura mensagens, armazena dados e recupera histórico de pedidos. ✅ Armazenamento Seguro de Dados do Cliente – Salva pedidos, preferências e endereços de entrega. ✅ Sincronização com CRM e Sistema de PDV – Conecta-se ao seu sistema de gestão para um fluxo contínuo. 📌 Como Funciona 1️⃣ O cliente envia uma mensagem via WhatsApp para iniciar um pedido. 2️⃣ O assistente de IA apresenta o menu, sugere itens e confirma a escolha do cliente. 3️⃣ O sistema captura e salva os dados do cliente (nome, telefone e endereço). 4️⃣ A IA calcula a distância de entrega e aplica a taxa de acordo com a localização. 5️⃣ Os detalhes do pedido são registrados e enviados para a cozinha. 6️⃣ O assistente atualiza o cliente sobre o status do pedido. ⚙️ Configuração e Personalização 🔧 Webhook para WhatsApp – Configuração para capturar e processar pedidos automaticamente. 🔧 Assistente de IA com OpenAI – Configuração de fluxos conversacionais naturais e envolventes. 🔧 Cálculo de Taxa de Entrega – Definição de valores por quilômetro e ajustes de tarifas base. 🔧 Banco de Dados & CRM – Armazena dados de clientes, histórico de pedidos e localização. 🔧 Fluxo de Pedidos Personalizável – Adapte para diferentes tipos de restaurantes e serviços de delivery. 🔧 Gerenciamento Seguro de Credenciais – Proteja suas chaves de API contra acessos não autorizados. 💡 Requisitos: Este template é recomendado para usuários que já possuem conhecimentos básicos em n8n. Se precisar de personalização ou suporte para instalação, entre em contato pelo WhatsApp: +55 17 99155-7874. 🚀 Automatize o processamento de pedidos, reduza tarefas manuais e melhore a satisfação dos clientes com um WhatsApp automatizado e inteligente!

🐶🤖 AI Agent for Pet Shops – Automate Customer Service & Bookings! 🐾💡 Transform Your Pet Shop with AI-Powered Automation! 🚀 Enhance customer experience and optimize operations with this n8n AI Agent designed for pet shops. 📲🐾 Automate client interactions, appointment scheduling, and service recommendations—saving time and increasing revenue! 🔹 Key Features: ✅ Instant WhatsApp responses – AI-powered chatbot handles customer inquiries. 💬 ✅ Automated appointment scheduling – Clients can book services hassle-free. 📅✂️ ✅ Personalized reminders – Reduce no-shows with automated notifications. 📢🐾 ✅ Customer data & service history management – Track interactions effortlessly. 📊📁 ✅ Product & service recommendations – Improve sales with smart suggestions. 🎁🐶 📌 How It Works 1️⃣ The workflow captures customer inquiries via WhatsApp. 2️⃣ AI processes requests, provides information, and offers booking options. 3️⃣ Clients can schedule grooming, vet visits, or other services in seconds. 4️⃣ Automated reminders ensure appointments are remembered. 5️⃣ Customer data is stored for better service personalization. ⚙️ Setup & Customization 🔧 Connect your WhatsApp API (evolution) for instant messaging. 🔧 Integrate with Google Calendar for appointment booking. 🔧 Customize reminders, services, and pricing rules to fit your business. 💡 Reduce manual work, improve customer satisfaction, and scale your pet shop with AI automation! 🐶🤖 [PT-BR] Agente de IA para Pet Shops – Atendimento e Agendamentos Automatizados! 🐾💡 Transforme Seu Pet Shop com Automação Inteligente! 🚀 Otimize o atendimento ao cliente e agilize processos com este Agente de IA para n8n. 📲🐾 Automatize interações, agendamentos e recomendações de serviços—economizando tempo e aumentando as vendas! 🔹 Principais Funcionalidades: ✅ Atendimento automático no WhatsApp – IA responde clientes instantaneamente. 💬 ✅ Agendamento de serviços automatizado – Clientes marcam banho, tosa ou consultas facilmente. 📅✂️ ✅ Lembretes personalizados – Reduza faltas com notificações automáticas. 📢🐾 ✅ Gestão de clientes e histórico de serviços – Controle dados de forma eficiente. 📊📁 ✅ Sugestão de produtos e serviços – Venda mais com recomendações inteligentes. 🎁🐶 📌 Como Funciona 1️⃣ O fluxo recebe perguntas dos clientes via WhatsApp. 2️⃣ A IA processa os pedidos e fornece opções de agendamento. 3️⃣ O cliente escolhe o serviço desejado e agenda em segundos. 4️⃣ Lembretes automáticos garantem que os clientes não esqueçam os horários. 5️⃣ O histórico do cliente é salvo para oferecer um atendimento mais personalizado. ⚙️ Configuração e Personalização 🔧 Conecte sua API do WhatsApp (evolution) para interação automática. 🔧 Integre ao Google Calendar para gerenciar agendamentos. 🔧 Personalize valores, serviços e regras de envio de lembretes conforme sua necessidade. 💡 Automatize processos, melhore a experiência do cliente e escale seu pet shop com IA! 🚀

Purpose This solution enables you to manage all your Notion and Todoist tasks from different workspaces as well as your calendar events in a single place. All tasks can be managed in Todoist and additionally Fantastical can be used to manage scheduled tasks & events all together. Demo & Explanation How it works The realtime sync consists of two workflows, both triggered by a registered webhook from either Notion or Todoist To avoid overwrites by lately arriving webhook calls, every time the current task is retrieved from both sides. Redis is used to prevent from endless loops, since an update in one system triggers another webhook call again. Using the ID of the task, the trigger is being locked down for 15 seconds. Depending on the detected changes, the other side is updated accordingly. Generally Notion is treaded as the main source. Using an "Obsolete" Status, it is guaranteed, that tasks never get deleted entirely by accident. The Todoist ID is stored in the Notion task, so they stay linked together An additional full sync workflow daily fixes inconsistencies, if any of them occurred, since webhooks cannot be trusted entirely. Since Todoist requires a more complex setup, a tiny workflow helps with activating the webhook. Another tiny workflow helps generating a global config, which is used by all workflows for mapping purposes. Mapping (Notion >> Todoist) Name: Task Name Priority: Priority (1: do first, 2: urgent, 3: important, 4: unset) Due: Date Status: Section (Done: completed, Obsolete: deleted) <page_link>: Description (read-only) Todoist ID: <task_id> Current limitations Changes on the same task cannot be made simultaneously in both systems within a 15-20 second time frame Subtasks are not linked automatically to their parent yet Recurring tasks are not supported yet Tasks names do not support URL’s yet Compatibility n8n v2.5.0 and above Updates This templated has been updated to work with the new "combined" Todoist API (v1). The general flow works exactly the same as before. Only the setup of the Todoist Webhook might look a tiny bit different then shown in the setup video, so please also have a look at the yellow sticky notes. Prerequisites Notion A database must already exist (get a basic template here) with the following properties (case matters!): Text: "Name" Status: "Status", containing at least the options "Backlog", "In progress", "Done", "Obsolete" Select: "Priority", containing the options "do first", "urgent", "important" Date: "Due" Checkbox: "Focus" Text: "Todoist ID" Todoist A project must already exist with the same sections like defined as Status in Notion (except Done and Obsolete) Redis Create a Free Redis Cloud instance or self-host Setup The setup involves quite a lot of steps, yet many of them can be automated for business internal purposes. Just follow the video or do the following steps: Setup credentials for Notion (access token), Todoist (access token) and Redis - you can also create empty credentials and populate these later during further setup Clone this workflow by clicking the "Use workflow" button and then choosing your n8n instance - otherwise you need to map the credentials of many nodes. Follow the instructions described within the bundle of sticky notes on the top left of the workflow How to use You can apply changes (create, update, delete) to tasks both in Notion and Todoist which then get synced over within a couple of seconds (this is handled by the differential realtime sync) The daily running full sync, resolves possible discrepancies in Todoist and sends a summary via email, if anything needed to be updated. In case that contains an unintended change, you can jump to the Task from the email directly to fix it manually.

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.

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.

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

Build a WhatsApp AI shopping bot with virtual try-on using Gemini 📌 Overview This workflow fully automates your T-shirt store's WhatsApp shopping experience using GPT for intent detection, MongoDB Atlas for vector-based product search, Redis for session management, and Google Gemini for AI-powered virtual try-on. It automatically handles customer messages, finds relevant products, processes orders, and generates realistic try-on images — all inside WhatsApp, with no app or website required. Customers can search for T-shirts, place orders, and virtually try on items in a single conversation. Redis ensures fast product caching and session tracking. MongoDB Atlas stores the product catalog and orders. Google Sheets logs every order automatically. Gemini generates realistic try-on images from customer selfies. This workflow eliminates manual order handling, improves customer experience, and gives store owners full visibility into orders and product searches. ⚙️ How it works This workflow runs automatically when a customer sends a WhatsApp message. 🔍 Product search 💬 Receives the customer message via WhatsApp Business API 🧠 GPT classifies the intent as product search, recommendation, or general query ⚡ Checks Redis cache for existing results (TTL: 1 hour) 🔎 On a cache miss, runs MongoDB Atlas vector search using OpenAI embeddings 🛍️ Sends matching products as interactive WhatsApp cards with Order Now and Virtual Try-On buttons 🛒 Order flow 👆 Triggered when the customer taps the Order Now button 📦 AI agent fetches product details from MongoDB 🗃️ Creates a new order document in MongoDB 📊 Logs the order to Google Sheets automatically ✅ Sends an order confirmation message to the customer via WhatsApp 👗 Virtual try-on flow 👆 Triggered when the customer taps the Virtual Try-On button 💾 Stores the product ID in Redis (TTL: 10 minutes) 📸 Prompts the customer to send a clear front-facing selfie 🔍 Gemini validates that exactly one real person is in the photo 🖼️ Merges the product image and selfie and generates a realistic try-on image 📩 Sends the try-on result back to the customer via WhatsApp 🗑️ Clears the Redis context after delivery 🛠 Setup steps Import this workflow into n8n Connect your WhatsApp Business Cloud API credentials Connect your OpenAI API credentials (for embeddings and GPT model) Connect your Google Gemini API credentials Connect your MongoDB Atlas credentials and create a vector index named ShopingBot on the product collection Connect your Redis credentials Connect your Google Drive service account credentials Connect your Google Sheets service account credentials Import your product catalog with embeddings into the MongoDB product collection Activate the workflow The workflow will run automatically when customers send WhatsApp messages. 🚀 Features 🧠 AI-powered shopping 🤖 Automatically classifies customer intent using GPT 🔎 Semantic product search using OpenAI embeddings and MongoDB Atlas vector search ⚡ Redis caching for ultra-fast repeated search results (TTL: 1 hour) 💬 Interactive WhatsApp product cards with Order Now and Virtual Try-On buttons 🔄 Sliding window session memory (last 20 messages per user) 🛒 Order management 📦 Fully automated order creation saved to MongoDB 📊 Automatic order logging to Google Sheets 🤖 AI agent handles the complete order flow without manual input ✅ Instant order confirmation sent to the customer via WhatsApp 👗 Virtual try-on ✨ AI-powered try-on image generation using Google Gemini 📷 Selfie validation ensures exactly one real person is in the photo 🖼️ Product and selfie images resized and merged before generation 📩 Try-on result delivered directly in the WhatsApp conversation 🗑️ Redis TTL automatically clears try-on context after delivery 🔐 Security and reliability 🛡️ Advanced message validation with spam and XSS protection ❌ Unsupported message types rejected with friendly error messages 🔁 Retry logic on critical HTTP request nodes 📦 Modular workflow architecture for easy customisation and scaling 📋 Requirements You need the following accounts and credentials: 🔧 n8n 📱 WhatsApp Business Cloud API 🤖 OpenAI API (embeddings and GPT model) ✨ Google Gemini API 🍃 MongoDB Atlas (with vector index named ShoppingBot on the product collection) ⚡ Redis server 📁 Google Drive (service account) 📊 Google Sheets (service account) 🎯 Benefits 🚀 Fully automated WhatsApp shopping experience 🙌 No manual order handling required 👗 Customers can try on products before buying ⚡ Fast product search with Redis caching 📊 All orders automatically tracked in Google Sheets 💼 Reduces support workload for store owners 🕐 Works 24/7 without human intervention 👨‍💻 Author BytezTech Pvt Ltd

🔄 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

Purpose This solution enables you to manage all your Notion and Todoist tasks from different workspaces as well as your calendar events in a single place. This is 2 way sync with partial support for recurring How it works The realtime sync consists of two workflows, both triggered by a registered webhook from either Notion or Todoist. To avoid overwrites by lately arriving webhook calls, every time the current task is retrieved from both sides. Redis is used to prevent from endless loops, since an update in one system triggers another webhook call again. Using the ID of the task, the trigger is being locked down for 80 seconds. Depending on the detected changes, the other side is updated accordingly .Generally Notion is treaded as the main source. Using an "Obsolete" Status, it is guaranteed, that tasks never get deleted entirely by accident. The Todoist ID is stored in the Notion task, so they stay linked together An additional full sync workflow daily fixes inconsistencies, if any of them occurred, since webhooks cannot be trusted entirely. Since Todoist requires a more complex setup, a tiny workflow helps with activating the webhook. Another tiny workflow helps generating a global config, which is used by all workflows for mapping purposes. Mapping (Notion >> Todoist) Name: Task Name Priority: Priority (1: do first, 2: urgent, 3: important, 4: unset) Due: Date Status: Section (Done: completed, Obsolete: deleted) <page_link>: Description (read-only) Todoist ID: <task_id> Current limitations Changes on the same task cannot be made simultaneously in both systems within a 15-20 second time frame. Subtasks are not linked automatically to their parent yet. Tasks names do not support URL’s yet. Credentials Follow the video: Setup credentials for Notion (access token), Todoist (access token) and Redis. Todoist Follow this video to get Todoist to obtain API Token. Todoist Credentials.mp4 Notion Follow this video to get Notion Integration Secret. Redis Follow this video to get Redis Setup The setup involves quite a lot of steps, yet many of them can be automated for business internal purposes. Just follow the video or do the following steps: Setup credentials for Notion (access token), Todoist (access token) and Redis - you can also create empty credentials and populate these later during further setup Clone this workflow by clicking the "Use workflow" button and then choosing your n8n instance - otherwise you need to map the credentials of many nodes. Follow the instructions described within the bundle of sticky notes on the top left of the workflow How to use You can apply changes (create, update, delete) to tasks both in Notion and Todoist which then get synced over within a couple of seconds (this is handled by the differential realtime sync) The daily running full sync, resolves possible discrepancies in Todoist. This workflow incorporates ideas and techniques inspired by Mario (https://n8n.io/creators/octionic/) whose expertise with specific nodes helped shape parts of this automation. Significant enhancements and customizations have been made to deliver a unique and improved solution.

Purpose This solution enables you to manage all your Notion and Todoist tasks from different workspaces as well as your calendar events in a single place. This is 2 way sync with partial support for recurring How it works The realtime sync consists of two workflows, both triggered by a registered webhook from either Notion or Todoist. To avoid overwrites by lately arriving webhook calls, every time the current task is retrieved from both sides. Redis is used to prevent from endless loops, since an update in one system triggers another webhook call again. Using the ID of the task, the trigger is being locked down for 80 seconds. Depending on the detected changes, the other side is updated accordingly .Generally Notion is treaded as the main source. Using an "Obsolete" Status, it is guaranteed, that tasks never get deleted entirely by accident. The Todoist ID is stored in the Notion task, so they stay linked together An additional full sync workflow daily fixes inconsistencies, if any of them occurred, since webhooks cannot be trusted entirely. Since Todoist requires a more complex setup, a tiny workflow helps with activating the webhook. Another tiny workflow helps generating a global config, which is used by all workflows for mapping purposes. Mapping (Notion >> Todoist) Name: Task Name Priority: Priority (1: do first, 2: urgent, 3: important, 4: unset) Due: Date Status: Section (Done: completed, Obsolete: deleted) <page_link>: Description (read-only) Todoist ID: <task_id> Current limitations Changes on the same task cannot be made simultaneously in both systems within a 15-20 second time frame. Subtasks are not linked automatically to their parent yet. Tasks names do not support URL’s yet. Credentials Follow the video: Setup credentials for Notion (access token), Todoist (access token) and Redis. Todoist Follow this video to get Todoist to obtain API Token. Todoist Credentials.mp4 Notion Follow this video to get Notion Integration Secret. Redis Follow this video to get Redis Setup The setup involves quite a lot of steps, yet many of them can be automated for business internal purposes. Just follow the video or do the following steps: Setup credentials for Notion (access token), Todoist (access token) and Redis - you can also create empty credentials and populate these later during further setup Clone this workflow by clicking the "Use workflow" button and then choosing your n8n instance - otherwise you need to map the credentials of many nodes. Follow the instructions described within the bundle of sticky notes on the top left of the workflow How to use You can apply changes (create, update, delete) to tasks both in Notion and Todoist which then get synced over within a couple of seconds (this is handled by the differential realtime sync) The daily running full sync, resolves possible discrepancies in Todoist. This workflow incorporates ideas and techniques inspired by Mario (https://n8n.io/creators/octionic/) whose expertise with specific nodes helped shape parts of this automation. Significant enhancements and customizations have been made to deliver a unique and improved solution.

Purpose This solution enables you to manage all your Notion and Todoist tasks from different workspaces as well as your calendar events in a single place. This is 2 way sync with partial support for recurring How it works The realtime sync consists of two workflows, both triggered by a registered webhook from either Notion or Todoist. To avoid overwrites by lately arriving webhook calls, every time the current task is retrieved from both sides. Redis is used to prevent from endless loops, since an update in one system triggers another webhook call again. Using the ID of the task, the trigger is being locked down for 80 seconds. Depending on the detected changes, the other side is updated accordingly .Generally Notion is treaded as the main source. Using an "Obsolete" Status, it is guaranteed, that tasks never get deleted entirely by accident. The Todoist ID is stored in the Notion task, so they stay linked together An additional full sync workflow daily fixes inconsistencies, if any of them occurred, since webhooks cannot be trusted entirely. Since Todoist requires a more complex setup, a tiny workflow helps with activating the webhook. Another tiny workflow helps generating a global config, which is used by all workflows for mapping purposes. Mapping (Notion >> Todoist) Name: Task Name Priority: Priority (1: do first, 2: urgent, 3: important, 4: unset) Due: Date Status: Section (Done: completed, Obsolete: deleted) <page_link>: Description (read-only) Todoist ID: <task_id> Current limitations Changes on the same task cannot be made simultaneously in both systems within a 15-20 second time frame. Subtasks are not linked automatically to their parent yet. Tasks names do not support URL’s yet. Credentials Follow the video: Setup credentials for Notion (access token), Todoist (access token) and Redis. Todoist Follow this video to get Todoist to obtain API Token. Todoist Credentials.mp4 Notion Follow this video to get Notion Integration Secret. Redis Follow this video to get Redis Setup The setup involves quite a lot of steps, yet many of them can be automated for business internal purposes. Just follow the video or do the following steps: Setup credentials for Notion (access token), Todoist (access token) and Redis - you can also create empty credentials and populate these later during further setup Clone this workflow by clicking the "Use workflow" button and then choosing your n8n instance - otherwise you need to map the credentials of many nodes. Follow the instructions described within the bundle of sticky notes on the top left of the workflow How to use You can apply changes (create, update, delete) to tasks both in Notion and Todoist which then get synced over within a couple of seconds (this is handled by the differential realtime sync) The daily running full sync, resolves possible discrepancies in Todoist. This workflow incorporates ideas and techniques inspired by Mario (https://n8n.io/creators/octionic/) whose expertise with specific nodes helped shape parts of this automation. Significant enhancements and customizations have been made to deliver a unique and improved solution.

How it Works This workflow transforms natural language queries into research reports through a five-stage AI pipeline. When triggered via webhook (typically from Google Sheets using the companion google-apps-script.js (GitHub gist), it first checks Redis cache for instant results. For new queries, GPT-4o breaks complex questions into focused sub-queries, optimizes them for search, then uses Bright Data's MCP Tool to find the top 5 credible sources (official sites, news, financial reports). URLs are scraped in parallel, bypassing bot detection. GPT-4o extracts structured data from each source: answers, facts, entities, sentiment, quotes, and dates. GPT-4o-mini validates source credibility and filters unreliable content. Valid results aggregate into a final summary with confidence scores, key insights, and extended analysis. Results cache for 1 hour and output via webhook, Slack, email, and DataTable—all in 30-90 seconds with 60 requests/minute rate limiting. Who is this for? Research teams needing automated multi-source intelligence Content creators and journalists requiring fact-checked information Due diligence professionals conducting competitive intelligence Google Sheets power users wanting AI research in spreadsheets Teams managing large research volumes needing caching and rate limiting Setup Steps Setup time: 30-45 minutes Requirements: Bright Data account (Web Scraping API + MCP token) OpenAI API key (GPT-4o and GPT-4o-mini access) Redis instance Slack workspace (optional) SMTP email provider (optional) Google account (optional for Sheets integration) Core Setup: Get Bright Data Web Scraping API token and MCP token Get OpenAI API key Set up Redis instance Configure critical nodes: Webhook Entry: Add Header Auth token Bright Data MCP Tool: Add MCP endpoint with token Parallel Web Scraping: Add Bright Data API credentials Redis Nodes: Add connection credentials All GPT Nodes: Add OpenAI API key (5 nodes) Slack/Email: Add credentials if using Google Sheets Integration: Create Google Sheet Open Extensions → Apps Script Paste the companion google-apps-script.js code Update webhook URL and auth token Save and authorize Test: {"prompt": "What is the population of Tokyo?", "source": "Test", "language": "English"} Customization Guidance Source Count:** Change from 5 to 3-10 URLs per query Cache Duration:** Adjust from 1 hour to 24 hours for stable info Rate Limits:** Modify 60/minute based on usage needs Character Limits:** Adjust 400-char main answer to 200-1000 AI Models:** Swap GPT-4o for Claude or use GPT-4o-mini for all stages Geographic Targeting:** Add more regions beyond us/il Output Channels:** Add Notion, Airtable, Discord, Teams Temperature:** Lower (0.1-0.2) for facts, higher (0.4-0.6) for analysis Once configured, this workflow handles all web research, from fact-checking to complex analysis—delivering validated intelligence in seconds with automatic caching. Built by Daniel Shashko Connect on LinkedIn

This workflow automatically replies to new comments on your Instagram posts using smart AI. It checks your recent posts, finds unread comments, and skips spam or duplicates. The AI reads the post and comments to create a friendly, natural reply with emojis. It posts the reply instantly and logs everything so you can track engagement. Perfect for busy creators — stays active 24/7 without you lifting a finger! What It Monitors Recent Instagram Posts**: Fetches the latest posts based on your account activity. New Comments**: Detects unreplied comments in real time. Reply Eligibility**: Filters spam, duplicates, and already replied comments. AI-Generated Responses**: Creates personalized, engaging replies using post context. Features Runs on a schedule trigger (High traffic: 2–3 min | Medium: 5 min | Low: 10+ min). Fetches recent posts and their comments via Instagram Graph API. Context-aware AI replies** using post caption + comment content. Spam & duplicate filtering** to avoid unwanted or repeated replies. Tone-friendly & emoji-rich** responses for higher engagement. Logs every reply** with metadata (post ID, comment ID, timestamp). Workflow Steps | Node Name | Description | |---------|-----------| | Schedule Trigger | Triggers workflow based on traffic level (2–10 min intervals). | | Get Recent Posts | Fetches recent posts using Instagram Graph API. Returns post IDs needed to fetch comments. | | Split Posts | Splits batch of posts into individual items for parallel processing. | | Get Comments | For each post, retrieves comments with content, username, timestamp, like count. | | Split Comments | Splits comments into individual items for granular processing. | | Add Post Context | Combines comment + original post caption to generate relevant replies. | | Check if Replied | Checks if AI has already replied to this comment (prevents duplicate replies). | | Not Replied Yet? | Routes only unreplied comments forward. | | Spam Filter | Filters out spam using: • Spam keywords • Empty/one-word comments • Excessive emojis • Known spam patterns | | Should Reply? | Final logic gate: • If reply key exists → Skip • If spam → Skip • Else → Proceed | | Generate AI Reply | Uses OpenAI (or compatible LLM): • Input: Post caption + comment • Tone: Friendly & engaging • Max tokens: 150 • Temperature: 0.8 (creative) | | Post Reply | Posts AI-generated reply via Instagram API: • Method: POST • Body: message parameter • TTL: 30 days | | Mark As Replied | Updates internal tracking to prevent duplicate replies. | | Log Reply | Logs full reply details: • Post ID • Comment ID • Username • Reply text • Timestamp • Used for analytics & reporting | How to Use Copy the JSON configuration of the workflow. Import it into your n8n workspace. Configure Instagram Graph API credentials (Business/Creator Account required). Set up OpenAI API key in the Generate AI Reply node. Activate the workflow. Monitor replies in Instagram and execution logs in n8n. > The bot will only reply once per comment, skip spam, and use full post context for natural responses. Requirements n8n** account and self-hosted or cloud instance. Instagram Business or Creator Account** with Graph API access. Facebook App** with pages_read_engagement, pages_manage_comments permissions. OpenAI API key** (or compatible LLM endpoint). Valid access token with long-lived permissions. Customizing this Workflow Change Schedule Trigger interval based on post frequency (e.g., every 1 min for viral accounts). Update Spam Filter keywords list for brand-specific spam patterns. Modify Generate AI Reply prompt to match your brand voice (e.g., formal, humorous, Gen-Z). Adjust Temperature (0.5 = consistent, 1.0 = creative) and Max Tokens. Replace OpenAI with Claude, Gemini, or local LLM via HTTP request. Add approval step (manual review) before posting replies. Export logs to Google Sheets, Airtable, or database for analytics. Explore More AI Workflows: https://www.oneclickitsolution.com/contact-us/

👥 Who's it for This workflow is perfect for businesses or individuals who want to automate WhatsApp conversations 💬 with an intelligent AI chatbot that can handle text, voice notes 🎵, and images 🖼️. No advanced coding required! 🤖 What it does It automatically receives WhatsApp messages through WasenderAPI, intelligently buffers consecutive messages to avoid fragmented responses, processes multimedia content (transcribing audio and analyzing images with AI), and responds naturally using GPT-4o mini with conversation memory. All while protecting your WhatsApp account from being banned. ⚙️ How it works 📱 Webhook Trigger – Receives new messages from WasenderAPI 🗃️ Redis Buffer System – Groups consecutive messages intelligently (7-second window) 🔀 Content Classifier – Routes messages by type (text, audio, or image) 🎵 Audio Processing – Decrypts and transcribes voice notes using OpenAI Whisper 🖼️ Image Analysis – Decrypts and analyzes images with GPT-4O Vision 🧠 AI Agent (GPT-4o mini) – Generates intelligent responses with 10-message memory ⏱️ Anti-Ban Wait – 6-second delay to simulate human typing 📤 Message Sender – Delivers response back to WhatsApp user 📋 Requirements WasenderAPI account with connected WhatsApp number : https://wasenderapi.com/ Redis database (free tier works fine) OpenAI API key with access to GPT-4o mini and Whisper n8n's AI Agent, LangChain, and Redis nodes 🛠️ How to set up Create your WasenderAPI account and connect a WhatsApp number Set up a free Redis database and get connection credentials Configure OpenAI API key in n8n credentials Replace the WasenderAPI Bearer token in "Get the audio", "Get the photo", and "Send Message to User" nodes Change the Manual Trigger to a Webhook and configure it in WasenderAPI Customize the AI Agent prompt to match your business needs Adjust wait times if needed (default: 6 seconds for responses, 7 seconds for buffer) Save and activate the workflow ✅ 🎨 How to customize Modify the AI Agent prompt to change bot personality and instructions Adjust buffer wait time (7 seconds) for faster/slower message grouping Change response delay (6 seconds) based on your use case , its recomendable 30 seconds. Add more content types (documents, videos) by extending the Switch Type node Configure conversation memory window (default: 10 messages)

Automating WhatsApp replies in Go High Level with Redis and Anthropic Description Integrates GHL + Wazzap with Redis and an AI Agent using ClientInfo to process messages, generate accurate replies, and send them via a custom field trigger. Who’s it for This workflow is for businesses using GoHighLevel (GHL), including the Wazzap plugin for WhatsApp, who want to automate inbound SMS/WhatsApp replies with AI. It’s ideal for teams that need accurate, data-driven responses from a predefined ClientInfo source and want to send them back to customers without paying for extra inbound automations. How it works / What it does Receive message in n8n via Webhook from GHL (Customer Replied (SMS) automation). WhatsApp messages arrive the same way using the Wazzap plugin. Filter message type: If audio → skip processing and send fallback asking for text. If text → sanitize by fixing escaped quotes, escaping line breaks/carriage returns/tabs, and removing invalid fields. Buffer messages in Redis to group multiple messages sent in a short window. Run AI Agent using the ClientInfo tool to answer only with accurate service/branch data. Sanitize AI output before sending back. Update GHL contact custom field (IA_answer) with the AI’s response. Send SMS reply automatically via GHL’s outbound automation triggered by the updated custom field. How to set up In GHL, create: Inbound automation: Trigger on Customer Replied (SMS) → Send to your n8n Webhook. Outbound automation: Trigger when IA_answer is updated → Send SMS to the contact. Create a custom field named IA_answer. Connect Wazzap in GHL to handle WhatsApp messages. Configure Redis in n8n (host, port, DB index, password). Add your AI model credentials (Anthropic, OpenAI, etc.) in n8n. (Optional) Set up the Google Drive Excel Merge sub-workflow to enrich ClientInfo with external data. Requirements GoHighLevel sub-account API key**. Anthropic (Claude)** API key or another supported LLM provider. Redis database** for temporary message storage. GHL automations: one for inbound messages to n8n, one for outbound replies when **IA\_answer is updated. GHL custom field: **IA\_answer to store and trigger replies. Wazzap plugin** in GHL for WhatsApp message handling. How to customize the workflow Add more context or business-specific data to the AI Agent prompt so replies match your brand tone and policies. Expand the ClientInfo dataset with additional services, branches, or product details. Adjust the Redis wait time to control how long the workflow buffers messages before replying.

VEXA: AI-Powered Meeting Intelligence I'll be honest, I built this because I was getting lazy in meetings and missing key details. I started with a simple VEXA integration for transcripts, then added AI to pull out summaries and tasks. But that just solved part of the problem. The real breakthrough came when we integrated Mem0, creating a persistent memory of every conversation. Now, you can stop taking notes and actually focus on the person you're talking to, knowing a system is tracking everything that matters. This is the playbook for how we built it. How It Works This isn't just one workflow; it's a two-part system designed to manage the entire meeting lifecycle from start to finish. Bot Management: It starts when you flick a switch in your CRM (Baserow). A command deploys or removes an AI bot from Google Meet. No fluff—it's there when you need it, gone when you don't. The workflow uses a quick "digital sticky note" in Redis to remember who the meeting is with and instantly updates the status in your Baserow table. AI Analysis & Memory: Once the meeting ends, VEXA sends the transcript over. Using the client ID (thank god for redis) , we feed the conversation to an AI model (OpenAI). It doesn't just summarize; it extracts actionable next steps and potential risks. All this structured data is then logged into a memory layer (Mem0), creating a permanent, searchable record of every client conversation. Setup Steps: Your Action Plan This is designed for rapid deployment. Here's what you do: Register Webhook: Run the manual trigger in the workflow once. This sends your n8n webhook URL to VEXA, telling it where to dump transcripts after a call. Connect Your CRM: Copy the vexa-start webhook URL from n8n. Paste it into your Baserow automation so it triggers when you set the "Send Bot" field to Start_Bot. Integrate Your Tools: Plug your VEXA, Mem0, Redis, and OpenAI API credentials into n8n. Use the Baserow Template: I've created a free Baserow template to act as your control panel. Grab it here: https://baserow.io/public/grid/t5kYjovKEHjNix2-6Rijk99y4SDeyQY4rmQISciC14w. It has all the fields you need to command the bot. Requirements An active n8n instance or cloud account. Accounts for VEXA.ai, Mem0.ai, Baserow, and OpenAI. A Redis database . Your Baserow table must have these fields: Meeting Link, Bot Name, Send Bot, and Status. Next Steps: Getting More ROI This workflow is the foundation. The real value comes from what you build on top of it. Automate Follow-ups:** Use the AI-identified next steps to automatically trigger follow-up emails or create tasks in your project management tool. Create a Unified Client Memory:** Connect your email and other communication platforms. Use Mem0 to parse and store every engagement, building a complete, holistic view of every client relationship. Build a Headless CRM:** Combine these workflows to build a fully AI-powered system that handles everything from lead capture to client management without any manual data entry. Copy the workflow and stop taking notes

Description Automates the forwarding of messages from WhatsApp (via Evolution API) to Chatwoot, enabling seamless integration between external WhatsApp users and internal Chatwoot agents. It supports both text and media messages, ensuring that customer conversations are centralized and accessible for support teams. What Problem Does This Solve? Managing conversations across multiple platforms can lead to fragmented support and lost context. This subworkflow bridges the gap between WhatsApp and Chatwoot, automatically forwarding messages received via the Evolution API to a Chatwoot inbox. It simplifies communication flow, centralizes conversations, and enhances the support team's productivity. Features Support for plain text messages Support for media messages: images, videos, documents, and audio Automatic media upload to Chatwoot with proper attachment rendering Automatic contact association using WhatsApp number and Chatwoot API Designed to work with Evolution API webhooks or any message source Prerequisites Before using this automate, make sure you have: Evolution API credentials with incoming message webhook configured A Chatwoot instance with access token and API endpoint An existing Chatwoot inbox (preferably API channel) A configured HTTP Request node in n8n for Chatwoot API calls Suggested Usage This subworkflow should be attached to a parent workflow that receives WhatsApp messages via the Evolution API webhook. Ideal for: Centralized customer service operations WhatsApp-to-CRM/chat routing Hybrid automation workflows where human agents need to reply from Chatwoot It ensures that all incoming WhatsApp messages are properly converted and forwarded to Chatwoot, preserving message content and structure.

Description 'Elena AI' is a powerful n8n workflow that transforms your automation platform into a full-fledged, multi-agent AI hub. 🤖✨ By combining Redis state management with specialized “tool” sub-workflows, you can build contextual, scalable, and highly personalized conversational automations for WhatsApp, Telegram, email, and more. 🔥 Key Features Unified Ingestion** 📥 • Webhook trigger for text, audio, image, or document messages • Automatic extraction of remoteJid, user ID, and payload metadata Stateful Context** 🔄 • Redis push/get queue to preserve conversation history • Seamless handling of follow-ups and multi-turn dialogs Dynamic Routing** 🔀 • Smart Switch logic directs messages to the right agent workflow • Agents available: 🗓️ Malu: Google Calendar scheduling & reminders 💰 Maria: Expense logging & budget tracking in Baserow 👥 Mafalda: Contact CRUD operations in Baserow 📸 Marcela: Audio transcription & image analysis ✉️ Martina: Gmail send/receive & template replies Bite-Sized Responses** ✂️ • Splits long AI replies into line-by-line messages • Loop node controls rate & order for best UX Flexible Output** 📤 • HTTP Request node to deliver text, media, or files • Customize headers, payloads, and endpoints 🎯 Use Cases AI-powered customer support bots Automated lead qualification & follow-up Intelligent scheduling & reminders Expense approval workflows Multimedia content analysis & response 📋 Requirements n8n ≥ 1.0* with Webhook, *Redis, SplitInBatches, HTTP Request & Workflow nodes Redis** server (connection credentials in n8n) Service accounts / API keys for: Google Calendar (OAuth2) Baserow (API token) Gmail (OAuth2) Messaging API endpoint (HTTP) Environment variables set in n8n: REDIS_HOST, REDIS_PORT, REDIS_PASSWORD GOOGLE_CLIENT_ID, GOOGLE_CLIENT_SECRET BASEROW_API_TOKEN GMAIL_CLIENT_ID, GMAIL_CLIENT_SECRET MSG_API_URL, MSG_API_KEY 🚀 Quick Start Import the ElenaAI.json into n8n. Configure credentials and environment variables under Settings → Credentials. Link sub-workflows (Malu, Maria, Mafalda, Marcela, Martina) by updating their Workflow IDs in the main node. Test via Execute node or send a sample webhook payload. Deploy by exposing the Webhook endpoint to your messaging platform. Unlock seamless, AI-driven conversations across any channel—get MavenBot 2.0 running in minutes! 🚀

This Workflow does a HTTPs request to ConnectWise Manage through their REST API. It will pull all tickets in the "New" status or whichever status you like, and notify your dispatch team/personnel whenever a new ticket comes in using Microsoft Teams. Video Explanation https://youtu.be/yaSVCybSWbM

This Template gives the ability to monitor all uplinks for your Meraki Dashboard and then alert your team in a method you prefer. This example is a Teams notification to our Dispatch Channel Setup will probably take around 30 minutes to 1h provided with the Template. Most time intensive steps are getting a Meraki API key which I go over and setting up the Teams node which n8n has good documentation for. Tutorial & explanation https://www.youtube.com/watch?v=JvaN0dNwRNU