Building your first WhatsApp chatbot
This n8n template builds a simple WhatsApp chabot acting as a Sales Agent. The Agent is backed by a product catalog vector store to better answer user's questions. This template is intended to help introduce n8n users interested in building with WhatsApp. How it works This template is in 2 parts: creating the product catalog vector store and building the WhatsApp AI chatbot. A product brochure is imported via HTTP request node and its text contents extracted. The text contents are then uploaded to the in-memory vector store to build a knowledgebase for the chatbot. A WhatsApp trigger is used to capture messages from customers where non-text messages are filtered out. The customer's message is sent to the AI Agent which queries the product catalogue using the vector store tool. The Agent's response is sent back to the user via the WhatsApp node. How to use Once you've setup and configured your WhatsApp account and credentials First, populate the vector store by clicking the "Test Workflow" button. Next, activate the workflow to enable the WhatsApp chatbot. Message your designated WhatsApp number and you should receive a message from the AI sales agent. Tweak datasource and behaviour as required. Requirements WhatsApp Business Account OpenAI for LLM Customising this workflow Upgrade the vector store to Qdrant for persistance and production use-cases. Handle different WhatsApp message types for a more rich and engaging experience for customers.
By Jimleuk🎓 Learn JSON basics with an interactive step-by-step tutorial for beginners
How it works This workflow is an interactive, hands-on tutorial designed to teach you the absolute basics of JSON (JavaScript Object Notation) and, more importantly, how to use it within n8n. It's perfect for beginners who are new to automation and data structures. The tutorial is structured as a series of simple steps. Each node introduces a new, fundamental concept of JSON: Key/Value Pairs: The basic building block of all JSON. Data Types: It then walks you through the most common data types one by one: String (text) Number (integers and decimals) Boolean (true or false) Null (representing "nothing") Array (an ordered list of items) Object (a collection of key/value pairs) Using JSON with Expressions: The most important step! It shows you how to dynamically pull data from a previous node into a new one using n8n's expressions ({{ }}). Final Exam: A final node puts everything together, building a complete JSON object by referencing data from all the previous steps. Each node has a detailed sticky note explaining the concept in simple terms. Set up steps Setup time: 0 minutes! This is a tutorial workflow, so there is no setup required. Simply click the "Execute Workflow" button to run it. Follow the instructions in the main sticky note: click on each node in order, from top to bottom. For each node, observe the output in the right-hand panel and read the sticky note next to it to understand what you're seeing. By the end, you'll have a solid understanding of what JSON is and how to work with it in your own n8n workflows.
By Lucas PeyrinRespond to WhatsApp messages with AI like a pro!
This n8n template demonstrates the beginnings of building your own n8n-powered WhatsApp chatbot! Under the hood, utilise n8n's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case! How it works Incoming WhatsApp Trigger provides a way to get messages into the workflow. The message received is extracted and sent through 1 of 4 branches for processing. Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video. The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries. Finally, the response message is sent back to the WhatsApp user using the WhatsApp node. How to use Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages. Good to know: Large media files may negatively impact workflow performance. Requirements WhatsApp Buisness account Google Gemini for LLM. Gemini is used specifically because it can accept audio and video files whereas at time of writing, many other providers like OpenAI's GPT, do not. Customising this workflow For performance reasons, consider detecting large audio and video before sending to the LLM. Pre-processing such files may allow your agent to perform better. Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!
By JimleukCustomer support WhatsApp bot with Google Docs knowledge base and Gemini AI
Document-Aware WhatsApp AI Bot for Customer Support Google Docs-Powered WhatsApp Support Agent 24/7 WhatsApp AI Assistant with Live Knowledge from Google Docs 📝Description Template Smart WhatsApp AI Assistant Using Google Docs Help customers instantly on WhatsApp using a smart AI assistant that reads your company’s internal knowledge from a Google Doc in real time. Built for clubs, restaurants, agencies, or any business where clients ask questions based on a policy, FAQ, or services document. ⚙️ How it works Users send free-form questions to your WhatsApp Business number (e.g. “What are the gym rules?” or “Are you open today?”) The bot automatically reads your company’s internal Google Doc (policy, schedule, etc.) It merges the document content with today’s date and the user’s question to craft a custom AI prompt The AI (Gemini or ChatGPT) then replies back on WhatsApp using natural, helpful language All conversations are logged to Google Sheets for reporting or audit > 💡Bonus: The AI even understands dates inside the document and compares them to today’s date — e.g. if your document says “Closed May 25 for 30 days,” it will say “We're currently closed until June 24. 🧰 Set up steps Connect your WhatsApp Cloud API account (Meta) Add your Google account and grant access to the Doc containing your company info Choose your AI model (ChatGPT/OpenAI or Gemini) Paste your document ID into the Google Docs node Connect your WhatsApp webhook to Meta (only takes 5 minutes) Done — start receiving and answering customer questions! > 📄 Works best with free-tier OpenAI/Gemini, Google Docs, and Meta's Cloud API (no phone required). Everything is modular, extensible, and low-code. 🔄 Customization Tips Change the Google Doc anytime to update answers — no retraining needed Add your logo and business name in the AI agent’s “System Prompt” Add fallback routes like “Escalate to human” if the bot can't help Clone for multiple brands by duplicating the workflow and swapping in new docs 🤝 Need Help Setting It Up? If you'd like help connecting your WhatsApp Business API, setting up Google Docs access, or customizing this AI assistant for your business or clients… 📩 I offer setup, branding, and customization services: WhatsApp Cloud API setup & verification Google OAuth & Doc structure guidance AI model configuration (OpenAI / Gemini) Branding & prompt tone customization Logging, reporting, and escalation logic Just send a message via: Email: tharwat.elsayed2000@gmail.com WhatsApp: +20 106 180 3236
By Tharwat Mohamed✨🩷Automated social media content publishing factory + system prompt composition
Social Media Content Publishing Factory for Streamlined Content Creation Across Platforms Who is this for? This workflow is designed for content creators, social media managers, and marketing teams who need to efficiently create and publish content across multiple social media platforms. It's perfect for businesses looking to maintain a consistent presence across X (Twitter), Instagram, Facebook, LinkedIn, Threads, and YouTube Shorts without spending hours crafting platform-specific content manually. What problem is this workflow solving? Creating tailored content for different social media platforms is time-consuming and requires understanding each platform's unique requirements and audience expectations. This workflow solves the challenge of: Maintaining consistent messaging across platforms while respecting platform-specific formats Generating optimized content that follows best practices for each platform Creating accompanying visuals without graphic design skills Streamlining the approval process before publishing Reducing the time spent on repetitive content creation tasks What this workflow does This automated content factory takes your content idea and transforms it into platform-optimized posts for all major social media channels. The workflow: Accepts your content idea or topic through a chat interface Leverages AI to generate tailored content for each platform (X/Twitter, Instagram, Facebook, LinkedIn, Threads, YouTube Shorts) Creates appropriate images using AI image generation Sends content for approval via email before publishing Publishes approved content to selected platforms Maintains chat memory to improve future content generation Setup Connect your social media platform credentials (X/Twitter, Instagram, Facebook, LinkedIn) Set up your email account for the approval process Configure your OpenAI API key for AI content generation Update the image generation service credentials (Pollinations.ai is used by default) Customize the system prompts and schemas in the Google Docs nodes with your brand voice and content requirements How to customize this workflow to your needs Modify the system prompts in the Google Docs nodes to match your brand voice and content strategy Adjust the social media schemas to include specific fields relevant to your content Update the approval process to include additional stakeholders if needed Add or remove social media platforms based on your marketing strategy Customize the image generation prompts to better match your visual branding Integrate with your existing content calendar or CRM systems This workflow eliminates the need to manually craft different versions of the same content for each platform, saving hours of work while ensuring your social media presence remains consistent and optimized for maximum engagement.
By Joseph LePageRead in an Excel spreadsheet file
How to take the path of a local Excel file and read its contents into n8n.
By Tien DeWorking with Excel spreadsheet files (xls & xlsx)
This workflow will help guide you through obtaining a spreadsheet file, reading it, making a change then saving it to local or cloud storage.
By n8n TeamA very simple "Human in the Loop" email response system using AI and IMAP
Functionality This workflow automates the handling of incoming emails by summarizing their content, generating appropriate responses, and validating the responses through a "Human-in-the-Loop" system. It integrates with IMAP email services (e.g., Gmail, Outlook) and uses AI models to streamline the email response process. The workflow ensures that all AI-generated responses are reviewed by a human before being sent, maintaining a high level of professionalism and accuracy. This approach is particularly useful for businesses that receive a high volume of emails and need to respond quickly while ensuring quality control. --- How It Works Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new messages. When a new email arrives, it triggers the workflow. Email Preprocessing: The Markdown node converts the email's HTML content into plain text for easier processing by the AI models. Email Summarization: The Email Summarization Chain node uses an AI model (OpenAI) to generate a concise summary of the email. The summary is limited to 100 words and is written in a professional tone. Email Response Generation: The Write email node uses an AI model (OpenAI) to draft a professional response to the email. The response is based on the email content and is limited to 100 words. Human-in-the-Loop Approval: The Set Email text node prepares the drafted response for approval. The Approve Email node sends the drafted response to a human approver (e.g., an internal email address) for review. The email includes: The original message. The AI-generated response. The Approved? node checks if the response has been approved by the human reviewer. If approved, the workflow proceeds to send the response; otherwise, it stops. Sending the Response: The Send Email node sends the approved response back to the original sender. --- Key Features Automated Email Summarization: Summarizes incoming emails to provide a quick overview of the content. AI-Powered Response Generation: Drafts professional responses to emails using AI. Human-in-the-Loop Approval: Ensures all AI-generated responses are reviewed and approved by a human before being sent. IMAP Integration: Works with IMAP email services like Gmail and Outlook. Efficient Email Management: Reduces the time and effort required to handle incoming emails while maintaining high-quality responses. This workflow is ideal for businesses looking to automate their email response process while maintaining control over the quality of outgoing communications. It leverages AI to handle repetitive tasks and ensures that all responses are reviewed by a human, providing a balance between automation and human oversight. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By DavideSearch LinkedIn companies, score with AI and add them to Google Sheet CRM
Search LinkedIn companies, Score with AI and add them to Google Sheet CRM Setup Video: https://youtube.com/watch?v=m904RNxtF0w&t Who is this for? This template is ideal for sales teams, business development professionals, and marketers looking to build a targeted prospect database with automatic qualification. Perfect for agencies, consultants, and B2B companies wanting to identify and prioritize the most promising potential clients. What problem does this workflow solve? Manually researching companies on LinkedIn, evaluating their fit for your services, and tracking them in your CRM is time-consuming and subjective. This automation streamlines lead generation by automatically finding, scoring, and importing qualified prospects into your database. What this workflow does This workflow automatically searches for companies on LinkedIn based on your criteria, retrieves detailed information about each company, filters them based on quality indicators, uses AI to score how well they match your ideal customer profile, and adds them to your Google Sheet CRM while preventing duplicates. Setup Create a Ghost Genius API account and get your API key Configure HTTP Request nodes with Header Auth credentials Create a copy of the provided Google Sheet template Set up your Google Sheet and OpenAI credentials following n8n documentation Customize the "Set Variables" node to match your target audience and scoring criteria How to customize this workflow Modify search parameters to target different industries, locations, or company sizes Adjust the follower count threshold based on your qualification criteria Customize the AI scoring system to align with your specific product or service offering Add notification nodes to alert you when high-scoring companies are identified
By MatthieuBuild custom workflows automatically with GPT-4o, RAG, and web search
🚀 What the “Agent Builder” template does Need to turn a one-line chat request into a fully-wired n8n workflow template—complete with AI agents, RAG, and web-search super-powers—without lifting a finger? That’s exactly what Agent Builder automates: Listens to any incoming chat message (via the Chat Trigger). Spins up an AI architect that analyses the request, searches the web, reads n8n docs from a Pinecone vector store, and designs the smallest possible set of nodes. Auto-generates a ready-to-import JSON template and hands it back as a downloadable file—plus all the supporting assets (embeddings, vector store etc.) so the next prompt is even smarter. Think of it as your personal “workflow chef”: you shout the order, it shops for ingredients, cooks, plates, and serves the meal. All you do is eat. --- 🤗 Who will love this? No-code builders / power users who don’t want to wrestle with AI node wiring. Agencies & consultants delivering lots of bespoke automations. Internal platform teams who need a “workflow self-service portal” for non-technical colleagues. --- 🧩 How it’s wired | Sub-process | What happens inside | Key nodes | | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------- | | Web Crawler (optional) | Firecrawl scrapes docs.n8n.io (or any URL you drop in) and streams raw markdown back. | Set URL → HTTP Request (Extract) → Wait & Retry | | RAG Trainer | Splits the scraped docs, embeds them with OpenAI, and upserts vectors into Pinecone. | Recursive Text Splitter → Embeddings OpenAI → Train Pinecone | | Agent Builder | The star of the show – orchestrates GPT-4o (via OpenRouter), SerpAPI web-search, your Pinecone index and a Structured Output Parser to produce → validate → prettify the final n8n template. | Chat Trigger → AI Agent → OpenAI (validator) → Code (extract) → Convert to JSON file | Every arrow in the drawn workflow is pre-connected, so the generated template always passes n8n’s import check. --- 🛠️ Getting set up (5 quick creds) | Service | Credential type | | --------------------------------------------------- | ---------------------------------------------------------- | | OpenAI / Azure OpenAI – embeddings & validation | OpenAI API | | Pinecone – vector store | Pinecone API | | OpenRouter – GPT-4o LLM | OpenRouter API Key | | SerpAPI – web search | SerpAPI Key | | Firecrawl (only if you plan to crawl) | Generic Header Auth → Authorization: Bearer YOUR_KEY | Each node already expects those creds; just create them once, select in the dropdown, hit Activate. --- 🏃♀️ What a typical run looks like User says: “Build me a workflow that monitors our support inbox, summarises new tickets with GPT and posts to Slack.” Chat Trigger captures the message. AI Agent: queries Pinecone for relevant n8n docs, fires a SerpAPI search for “n8n gmail trigger example”, sketches an architecture (Gmail Trigger → GPT Model → Slack). The agent returns JSON ➜ OpenAI node double-checks field names, connections, type versions. A tiny JS Code node slices the JSON out of the chat blob and saves it as template.json ready for download. You download, import, and… done. --- ✏️ Customising Switch the LLM – plug in Claude 3, Gemini 1.5, or a local model; just swap the OpenRouter Chat Model* node. Point the RAG at your own docs – change the crawl URL or feed PDFs via the Default Data Loader*. Hard-code preferred nodes – edit the “User node preferences” in the system message so the agent always chooses Notion* for databases, etc. --- 🥡 Take-away notes It's a prototype feel free to experiment with it to improve its capabilities. Have fun building!
By FranzAdvanced AI demo (presented at AI Developers #14 meetup)
This workflow was presented at the AI Developers meet up in San Fransico on 24 July, 2024. AI workflows Categorize incoming Gmail emails and assign custom Gmail labels. This example uses the Text Classifier node, simplifying this usecase. Ingest a PDF into a Pinecone vector store and chat with it (RAG example) AI Agent example showcasing the HTTP Request tool. We teach the agent how to check availability on a Google Calendar and book an appointment.
By Max TkaczAutomate blog content creation with OpenAI, Google Sheets & email approval flow
Who is this for? This workflow is perfect for: Digital marketers who need to scale SEO-optimized content production Bloggers and content creators who want to maintain consistent publishing schedules Small business owners who need regular blog content but lack writing resources What problem is this workflow solving? Creating high-quality, SEO-optimized blog content consistently is time-consuming and resource-intensive. This workflow solves that by: Automating the content generation process from topic to final draft Ensuring quality control through human-in-the-loop approval Managing topic queues and preventing duplicate content creation Streamlining the revision process based on human feedback Organizing and archiving all generated content for future reference What this workflow does From topics stored in Google Sheets, this workflow: Automatically retrieves pending topics from your Google Sheets tracking document Generates SEO-optimized blog posts (800-1200 words) using OpenAI GPT-4 with structured prompts Sends content for human approval via email with custom approval forms Handles revision requests by incorporating feedback while maintaining SEO best practices Updates topic status to prevent duplicate processing Add approved generated content in Google Sheets for easy access and management Routes workflow based on approval decisions (approve, revise, or cancel) Setup Copy the Google Sheet template here: 👉 Automate Blog Content Creation – Google Sheet Template Connect Google Sheets with your topic tracking document (requires "Topic List" and "Generated Content" sheets) Add your OpenAI API key to the AI agent nodes for content generation Configure Gmail for the approval notification system Set up your topic list in Google Sheets with "Topic" and "Status" columns Customize the schedule trigger to run at your preferred intervals Update email recipient in the approval node to your email address Test with a sample topic marked as "Pending" in your Google Sheet How to customize this workflow to your needs Adjust content length: modify the word count requirements in the AI agent prompts Change writing style: customize the copywriter prompts for different tones (formal, casual, technical) Add multiple reviewers: extend the approval system to include additional stakeholders Integrate with CMS: add nodes to automatically publish approved content to WordPress, Webflow, or other platforms Include keyword research: add Ahrefs or SEMrush nodes to incorporate keyword data Add image generation: integrate DALL-E or Midjourney for automatic featured image creation Customize approval criteria: modify the approval form to include specific feedback categories Add content scoring: integrate readability checkers or SEO analysis tools before approval Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy Christi