Telegram AI chatbot
The workflow starts by listening for messages from Telegram users. The message is then processed, and based on its content, different actions are taken. If it's a regular chat message, the workflow generates a response using the OpenAI API and sends it back to the user. If it's a command to create an image, the workflow generates an image using the OpenAI API and sends the image to the user. If the command is unsupported, an error message is sent. Throughout the workflow, there are additional nodes for displaying notes and simulating typing actions.
By EduardGenerate & auto-post AI videos to social media with Veo3 and Blotato
Automate video creation with Veo3 and auto-post to Instagram, TikTok via Blotato Who is this for? This template is ideal for content creators, social media managers, YouTubers, and digital marketers who want to generate high-quality videos daily using AI and distribute them effortlessly across multiple platforms. It’s perfect for anyone who wants to scale short-form content creation without video editing tools. What problem is this workflow solving? Creating and distributing consistent video content requires: Generating ideas Writing scripts and prompts Rendering videos Manually posting to platforms This workflow automates all of that. It transforms one prompt into a professional AI-generated video and publishes it automatically — saving time and increasing reach. What this workflow does Triggers daily to generate a new idea with OpenAI (or your custom prompt). Creates a video prompt formatted specifically for Google Veo3. Generates a cinematic video using the Veo3 API. Logs the video data into a Google Sheet. Retrieves the final video URL once Veo3 finishes rendering. Uploads the video to Blotato for publishing. Auto-posts the video to Instagram, TikTok, YouTube, Facebook, LinkedIn, Threads, Twitter (X), Pinterest, and Bluesky. Setup Add your OpenAI API key to the GPT-4.1 nodes. Connect your Veo3 API credentials in the video generation node. Link your Google Sheets account and use a sheet with columns: Prompt, Video URL, Status. Connect your Blotato API key and set your platform IDs in the Assign Social Media IDs node. Adjust the Schedule Trigger to your desired posting frequency. How to customize this workflow to your needs Edit the AI prompt to align with your niche (fitness, finance, education, etc.). Add your own branding overlays using JSON2Video or similar tools. Change platform selection by enabling/disabling specific HTTP Request nodes. Add a Telegram step to preview the video before auto-posting. Track performance by adding metrics columns in Google Sheets. 📄 Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
By Dr. Firas🤖 Build an interactive AI agent with chat interface and multiple tools
How it works This template is a complete, hands-on tutorial that lets you build and interact with your very first AI Agent. Think of an AI Agent as a standard AI chatbot with superpowers. The agent doesn't just talk; it can use tools to perform actions and find information in real-time. This workflow is designed to show you exactly how that works. The Chat Interface (Chat Trigger): This is your window to the agent. It's a fully styled, public-facing chat window where you can have a conversation. The Brain (AI Agent Node): This is the core of the operation. It takes your message, understands your intent, and intelligently decides which "superpower" (or tool) it needs to use to answer your request. The agent's personality and instructions are defined in its extensive system prompt. The Tools (Tool Nodes): These are the agent's superpowers. We've included a variety of useful and fun tools to showcase its capabilities: Get a random joke. Search Wikipedia for a summary of any topic. Calculate a future date. Generate a secure password. Calculate a monthly loan payment. Fetch the latest articles from the n8n blog. The Memory (Memory Node): This gives the agent a short-term memory, allowing it to remember the last few messages in your conversation for better context. When you send a message, the agent's brain analyzes it, picks the right tool for the job, executes it, and then formulates a helpful response based on the tool's output. Set up steps Setup time: ~3 minutes This template is nearly ready to go out of the box. You just need to provide the AI's "brain." Configure Credentials: This workflow requires an API key for an AI model. Make sure you have credentials set up in your n8n instance for either Google AI (Gemini) or OpenAI. Choose Your AI Brain (LLM): By default, the workflow uses the Google Gemini node. If you have Google AI credentials, you're all set! If you prefer to use OpenAI, simply disable the Gemini node and enable the OpenAI node. You only need one active LLM node. Make sure it is connected to the Agent parent node. Explore the Tools: Take a moment to look at the different tool nodes connected to the Your First AI Agent node. This is where the agent gets its abilities! You can add, remove, or modify these to create your own custom agent. Activate and Test! Activate the workflow. Open the public URL for the Example Chat Window node (you can copy it from the node's panel). Start chatting! Try asking it things like: "Tell me a joke." "What is n8n?" "Generate a 16-character password for me." "What are the latest posts on the n8n blog?" "What is the monthly payment for a $300,000 loan at 5% interest over 30 years?"
By Lucas PeyrinExport CSV file to JSON
This workflow exports a local CSV file to a JSON file.
By LorenaSmart email assistant: automate customer support with AI & Supabase
Intelligent Email Support System with Vector Database Overview This n8n workflow automates email support using AI and vector database technology to provide smart, context-aware responses. It seamlessly integrates email automation and document management, ensuring efficient customer support. 📌 System Components ✉️ Email Support System Email Monitoring & Classification Gmail trigger node monitoring inbox AI-powered email classification Intelligent routing (support vs non-support inquiries) AI Response Generation LangChain agent for response automation OpenAI integration for NLP-driven replies Vector-based knowledge retrieval Automated draft creation in Gmail Vector Database System Supabase vector store for document management OpenAI embeddings for vector conversion Fast and efficient similarity search 📂 Document Management System Google Drive Integration Monitors specific folders for new/updated files Automatic document processing Supports various file formats Document Processing Pipeline Auto file download & text extraction Smart text chunking for better indexing Embedding generation via OpenAI Storage in Supabase vector database 🔄 Workflow Processes 📧 Email Support Flow Monitor Gmail inbox for new emails AI classification of incoming messages Route support emails to AI response generator Perform vector similarity search for knowledge retrieval Generate personalized AI-driven response Create email drafts in Gmail 📁 Document Management Flow Monitor Google Drive for new/updated files Auto-download and process documents Clean up outdated vector entries for updated files Extract and split document text efficiently Generate OpenAI embeddings Store processed data in Supabase vector DB ⚙️ Setup Instructions 1️⃣ Prerequisites Supabase account & project OpenAI API key Gmail account with OAuth2 setup Google Drive API access n8n installation 2️⃣ Supabase Database Setup sql -- Create the vector extension create extension if not exists vector; -- Create the documents table create table documents ( id bigserial primary key, content text, metadata jsonb, embedding vector(1536) ); -- Create an index for similarity search create index on documents using ivfflat (embedding vectorcosineops) with (lists = 100); 3️⃣ Google Drive Setup Create & configure two monitored folders: RAG folder for new documents documents Assign correct folder permissions Add folder IDs to the workflow 4️⃣ Document Processing Configuration Set up triggers for file creation and file updates Configure text extraction: Define chunk size & overlap settings Set document metadata processing 🔍 Maintenance & Optimization 📌 Regular Tasks Monitor system performance Update the knowledge base regularly Review AI response quality Optimize vector search parameters Clean up outdated document embeddings ✅ Best Practices Document Organization Maintain structured folders & naming conventions Keep knowledge base content updated System Optimization Track AI classification accuracy Tune response times & chunk sizes Perform regular database maintenance 🛠️ Troubleshooting Email Issues Verify Gmail API credentials Check AI service uptime Monitor classification performance Document Processing Issues Ensure correct file permissions Validate extraction & embedding processes Debug vector database insertions
By Badr🗲 Creating a Secure Webhook - MUST HAVE
How it works This workflow demonstrates a fundamental pattern for securing a webhook by requiring an API key. It acts as a gatekeeper, checking for a valid key in the request header before allowing the request to proceed. Incoming Request: The Secured Webhook node receives an incoming POST request. It expects an API key to be sent in the x-api-key header. API Key Verification: The Check API Key node takes the key from the incoming request's header. It then makes an internal HTTP request to a second* webhook (Get API Key) which acts as a mock database. This second webhook retrieves a list of registered API keys (from the Registered API Keys node) and filters it to find a match for the key that was provided. Conditional Response: If a match is found, the API Key Identified node routes the execution to the "success" path, returning a 200 OK response with the identified user's ID. If no match is found, it routes to the "unauthorized" path, returning a 401 Unauthorized error. This pattern separates the public-facing endpoint from the data source, which is a good security practice. Set up steps Setup time: ~2 minutes This workflow is designed to be a self-contained example. Set up Credentials: This workflow uses "Header Auth" for its internal communication. Go to Credentials and create a new Header Auth credential. You can use any name and value (e.g., Name: X-N8N-Auth, Value: my-secret-password). Select this credential in all four webhook/HTTP Request nodes. Add Your API Keys: Open the Registered API Keys node. This is your mock database. Edit the array to include the userid and apikey pairs you want to authorize. Activate the workflow. Test it: Use the Test Secure Webhook node to send a request. Try it with a valid key from your list to see the success response. Change the x-api-key header to an invalid key to see the 401 Unauthorized error. For Production: Replace the mock database part of this workflow (the Get API Key webhook and Registered API Keys node) with a real database node like Supabase, Postgres, or Baserow to look up keys.
By Lucas PeyrinSend WhatsApp bulk messages from Google Sheets
WhatsApp Bulk Message Broadcast via Google Sheets (n8n Workflow) Use Case This workflow enables automated bulk WhatsApp message broadcasting using the WhatsApp Business Cloud API. It pulls recipient and message data from a Google Sheet, sends templated messages (optionally with image headers), and updates the sheet with the message status. It is ideal for marketing teams, support agents, and businesses handling high-volume outreach. --- Who Is This For? Businesses conducting WhatsApp marketing or outreach campaigns Customer support or notification teams Administrators seeking an automated, no-code message distribution system using Google Sheets --- What This Workflow Does Triggers automatically every minute to scan for pending messages Fetches unsent entries from a Google Sheet Limits the number of messages processed per execution to comply with API usage guidelines Sanitizes WhatsApp numbers for proper formatting Sends messages using a pre-approved WhatsApp template (text and optional image) Marks the row as "Sent" in the sheet upon successful delivery --- Workflow Breakdown (Node by Node) Trigger Every 5 Minutes Initiates the workflow every minute using a scheduled trigger to continuously monitor pending rows. Fetch All Pending Queries for Messaging Reads rows from a Google Sheet where the Status column is empty, indicating they haven’t been processed yet. Limit Restricts processing to 2 rows per execution to manage API throughput. Loop Over Items Uses SplitInBatches to iterate through each row individually. Clean WhatsApp Number A code node that strips non-numeric characters from the WhatsApp No field, ensuring the format is valid for the API. Send Message to 300 Phone No Sends a WhatsApp message using the WhatsApp Cloud API and a pre-approved template. Template includes: An image from the Image URL column (as header, optional) Dynamic variables for the recipient's Name and Message fields Template variables must be pre-defined and approved in the Meta Developer Portal, such as {{1}}, {{2}}. Change State of Rows in Sent1 Updates the Status column to Sent for each successfully processed row using the row number as a reference. --- Google Sheet Format Structure your Google Sheet as shown below: | WhatsApp No | Name | Message | Image URL | Status | |--------------|------------|---------------------------|---------------------|--------| | +8801XXXXXXX | John Doe | Hello, your order shipped | https://.../img.jpg | | Leave the Status column empty for rows that need to be processed. --- Requirements WhatsApp Business Cloud API access via Meta for Developers A properly structured Google Sheet as described above Active OAuth2 credentials configured in n8n for: googleSheetsOAuth2Api whatsAppApi --- Customization Options Update the Limit node to control how many rows are processed in each run Adjust the trigger schedule (e.g., change to every 5 minutes) Replace the message template ID with your own custom-approved one from Meta Add error-handling logic (e.g., IF or Try/Catch nodes) to log failures or set Status = Failed --- Sample Sheet Template View Sample Google Sheet --- Workflow Highlights Automated execution every 1 minute Reads and processes only pending records Verifies WhatsApp numbers and delivers templated messages Updates Google Sheet after each attempt --- Support & Community Need help setting up or customizing the workflow? WhatsApp: Contact Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: Visit SpaGreen Creative
By SpaGreen CreativeGmail to vector embeddings with PGVector and Ollama
Gmail to Vector Embeddings with PGVector and Ollama Who is this for? Everyone! Did you dream of asking an AI "what hotel did I stay in for holidays last summer?" or "what were my marks last semester like?". Dream no more, as vector similarity searches and this workflow are the foundations to make it possible (as long as the information appears in your e-mails 😅). 100% local This workflow is designed to use locally-hosted open source. Ollama as LLM provider, nomic-embed-text as the embeddings model, and pgvector as the vector database engine, on top of Postgres. But.. how?! Firstly, specify the date you created your Gmail account on, then manually run the workflow in order to bulk read all your e-mail in monthly batches. Your database is now populated! Now it's the task for other workflows to query the vector database. Activate the workflow so that new e-mail is continuously added by the Gmail Trigger upon receiving it. Structured AND Vectorized This workflow stores your e-mail activity in two ways: In a structured table In a vector embeddings table And the information in both of them can be correlated by Gmail's messages id, which is stored in the vectors table as metadata property emails_metadata.id. That way consumers can benefit from both worlds! ✨ Vector similarity searches enable semantic searches, while structured queries can retrieve more factual data like the message id, its date or who it came from. Other useful templates My template Chat with Your Email History using Telegram, Mistral and Pgvector for RAG is a ready-made solution to consume this workflow. You may also pair this workflow with my other template to Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL and you'll enable RAG workflows that use both structured and vectorized databases. Customizations I suppose the e-mail provider could be changed, but then you'd have to identify an alternative id field. Message-ID would be a more standard option. There are a few opinionated choices as to what metadata to store, but those shouldn't need adjustments.
By Alfonso CorrettiYouTube trends finding agent
Who this is for This workflow is for content creators, digital marketers, or YouTube strategists who want to automatically discover trending videos in their niche, analyze engagement metrics, and get data-driven insights for their content strategy — all from one simple form submission. What this workflow does This workflow starts every time someone submits the YouTube Trends Finder Form. It then: Searches YouTube videos based on your topic and specified time range using the YouTube Data API. Fetches detailed analytics (views, likes, comments, engagement rates) for each video found. Calculates engagement rates and filters out low-performing content (below 2% engagement). Applies smart filters to exclude videos with less than 1000 views, content outside your timeframe, and hashtag-heavy titles. Removes duplicate videos to ensure clean data. Creates a Google Spreadsheet with all trending video data organized by performance metrics. Delivers the results via a completion form with a direct link to your analytics report. Setup To set this workflow up: Form Trigger – Customize the "YouTube Trends Finder" form fields if needed (Topic Name, Last How Many Days). YouTube Data API – Add your YouTube OAuth2 credentials and API key in the respective nodes. Google Sheets – Connect your Google Sheets account for automatic report generation. Engagement Filters – Adjust the 2% engagement rate threshold based on your quality standards. View Filters – Modify the minimum view count (currently 1000+) in the filter conditions. Regional Settings – Update the region code (currently "US") to target specific geographic markets. How to customize this workflow to your needs Change the engagement rate threshold to be more or less strict based on your niche requirements. Add additional filters like video duration, subscriber count, or specific keywords to refine results. Modify the Google Sheets structure to include extra metrics like "Channel Name", "Video Duration", or "Trending Score". Switch to different output formats like CSV export or direct email reports instead of Google Sheets.
By Rakin JakariaCreate AI news video content ideas for social media with Perplexity & OpenAI
--- AI Latest News Content Script Writer Overview This workflow automates the daily generation of viral short-form video content ideas tailored for founders and business leaders. It scrapes fresh AI-related news and trends from various topics, synthesizes the information, and then uses AI to craft complete content packages—including video scripts, captivating captions, and punchy text overlays. All generated content is saved to a Google Sheet, ready for your review and use. Use Case This workflow is perfect for: Founders & Entrepreneurs: Consistently produce engaging content to build authority and attract inbound leads without a dedicated content team. AI Thought Leaders: Stay on top of the latest AI news and effortlessly create shareable insights. Content Marketing Teams: Automate the ideation and initial drafting phases for short-form video strategies. Agencies: Offer a unique AI-powered content generation service to your clients. --- How It Works Scheduled Daily Trigger: The workflow runs automatically every day at 6 AM IST, ensuring you always have fresh content ideas to start your day. AI-Powered News Gathering: It uses Perplexity AI to fetch the latest, most interesting, and relevant stories across three key AI topics: Topic 1: General AI News Topic 2: AI Market and Industry Trends Topic 3: AI Business Automation Organize and Combine Content: The information from each topic is organized, and then all content and their respective citations are combined into a single, comprehensive input. Personalize "About Me": Crucially, a configurable "About me" node allows you to define the personal brand of the founder (e.g., Name, Niche, Business Name, Business Type). This context is fed to the AI to ensure generated content aligns perfectly with your persona and business objectives. Generate Content Packages: Leveraging OpenAI (acting as "CreatorAI"), the workflow takes the combined news and your "About me" information to: Identify a Unique Angle: Finds a distinct, engaging angle from the input that aligns with key content pillars (e.g., AI solving business pain points, future of work with AI). Craft Video Scripts: Generates concise video scripts (under 700 characters) with powerful hooks, mini-narratives (problem → AI solution → impact), and a focus on tangible business benefits. It subtly references your business as a thought leader, not a direct pitch. Write Captions: Creates friendly, expert-toned captions with engaging hooks, more context, a clear call to action (e.g., "Comment 'Workflow' for more"), and relevant hashtags. Design Text Overlays: Produces short, punchy text overlays (3-7 words, ALL CAPS or Title Case) perfect for video thumbnails or initial screens. Save to Google Sheet: Each generated content package (Text Overlay, Video Script, Caption) is appended as a new row in your designated Google Sheet ("Content Idea" sheet within "Video Automation (Vansh)"). Notify User: Finally, you'll receive an email notification confirming that new content ideas have been generated and saved to your Google Sheet. --- How to Set It Up To set up this AI Viral Content Generator, follow these steps: API Keys & Credentials: Perplexity AI API Key: Obtain your API key from Perplexity AI and replace the Bearer token in the "Topic 1", "Topic 2", and "Topic 3" HTTP Request nodes. OpenAI API Key: Connect your OpenAI API key in n8n and link it to the "Content Generation" node. Google Sheets Account: Ensure your Google Sheets OAuth2 API credentials are set up and connected to the "Save Data" node. Gmail Account: Connect your Gmail OAuth2 credentials to the "Notify user" node. Google Sheet Setup: Copy the Google Sheet Template provided. This template has predefined columns for "Text Overlay", "Video Script", "Caption", "Approval", and "Published". Update the documentId in the "Save Data" Google Sheets node with the ID of your copied template*. Personalize "About me": Open the "About me" node. Fill in your Name, Niche, Business Name, Business Type, Website, and detailed Key Services & Products. This is crucial for the AI to generate relevant and personalized content. Configure Notification Email: In the "Notify user" node, update the sendTo field with your email address where you want to receive notifications. Set Schedule: The "Schedule Trigger" is set to run daily at 6 AM IST. You can adjust the time to your preference. Activate and Monitor: Activate the workflow. It will now automatically generate content ideas daily. Check your Google Sheet regularly to review the new content, mark it for approval, and track its publication status. This workflow is your secret weapon for consistently creating engaging, AI-driven short-form video content!
By Gain FLow AIBuild a text & image responding Telegram bot with Google Gemini 2.5 Flash
Telegram AI Bot Workflow An intelligent Telegram bot powered by Google Gemini AI that provides smart responses to both text messages and images. Features Multi-Modal Input: Handles both text messages and image uploads AI-Powered Responses: Uses Google Gemini 2.5 Flash for intelligent reply generation Image Analysis: Automatically analyzes uploaded images and responds with descriptions Conversation Memory: Maintains context across 20 messages per conversation Formatted Output: Delivers well-structured, Telegram-friendly responses How It Works User sends a message (text or image) to the Telegram bot Workflow routes the input based on message type Images are downloaded and analyzed using Gemini Vision AI AI agent processes the input with conversation context Formatted response is sent back to the user instantly Requirements Telegram Bot Token (from @BotFather) Google Gemini API Key n8n instance with webhook capability Perfect for building interactive AI assistants, customer support bots, or educational tools on Telegram.
By Ahmed SherifPublish a post to a publication on Medium
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By Harshil Agrawal