Workflow Templates

🤖 Create a Telegram Bot with Mistral AI and Conversation Memory A sophisticated Telegram bot that provides AI-powered responses with conversation memory. This template demonstrates how to integrate any AI API service with Telegram, making it easy to swap between different AI providers like OpenAI, Anthropic, Google AI, or any other API-based AI model. 🔧 How it works The workflow creates an intelligent Telegram bot that: 💬 Maintains conversation history for each user 🧠 Provides contextual AI responses using any AI API service 📱 Handles different message types and commands 🔄 Manages chat sessions with clear functionality 🔌 Easily adaptable to any AI provider (OpenAI, Anthropic, Google AI, etc.) ⚙️ Set up steps 📋 Prerequisites 🤖 Telegram Bot Token (from @BotFather) 🔑 AI API Key (from any AI service provider) 🚀 n8n instance with webhook capability 🛠️ Configuration Steps 🤖 Create Telegram Bot Message @BotFather on Telegram Create new bot with /newbot command Save the bot token for credentials setup 🧠 Choose Your AI Provider OpenAI: Get API key from OpenAI platform Anthropic: Sign up for Claude API access Google AI: Get Gemini API key NVIDIA: Access LLaMA models Hugging Face: Use inference API Any other AI API service 🔐 Set up Credentials in n8n Add Telegram API credentials with your bot token Add Bearer Auth/API Key credentials for your chosen AI service Test both connections 🚀 Deploy Workflow Import the workflow JSON Customize the AI API call (see customization section) Activate the workflow Set webhook URL in Telegram bot settings ✨ Features 🚀 Core Functionality 📨 Smart Message Routing**: Automatically categorizes incoming messages (commands, text, non-text) 🧠 Conversation Memory**: Maintains chat history for each user (last 10 messages) 🤖 AI-Powered Responses**: Integrates with any AI API service for intelligent replies ⚡ Command Support**: Built-in /start and /clear commands 📱 Message Types Handled 💬 Text Messages**: Processed through AI model with context 🔧 Commands**: Special handling for bot commands ❌ Non-text Messages**: Polite error message for unsupported content 💾 Memory Management 👤 User-specific chat history storage 🔄 Automatic history trimming (keeps last 10 messages) 🌐 Global state management across workflow executions 🤖 Bot Commands /start 🎯 - Welcome message with bot introduction /clear 🗑️ - Clears conversation history for fresh start Regular text 💬 - Processed by AI with conversation context 🔧 Technical Details 🏗️ Workflow Structure 📡 Telegram Trigger - Receives all incoming messages 🔀 Message Filtering - Routes messages based on type/content 💾 History Management - Maintains conversation context 🧠 AI Processing - Generates intelligent responses 📤 Response Delivery - Sends formatted replies back to user 🤖 AI API Integration (Customizable) Current Example (NVIDIA): Model: mistralai/mistral-nemotron Temperature: 0.6 (balanced creativity) Max tokens: 4096 Response limit: Under 200 words 🔄 Easy to Replace with Any AI Service: OpenAI Example: { "model": "gpt-4", "messages": [...], "temperature": 0.7, "max_tokens": 1000 } Anthropic Claude Example: { "model": "claude-3-sonnet-20240229", "messages": [...], "max_tokens": 1000 } Google Gemini Example: { "contents": [...], "generationConfig": { "temperature": 0.7, "maxOutputTokens": 1000 } } 🛡️ Error Handling ❌ Non-text message detection and appropriate responses 🔧 API failure handling ⚠️ Invalid command processing 🎨 Customization Options 🤖 AI Provider Switching To use a different AI service, modify the "NVIDIA LLaMA Chat Model" node: 📝 Change the URL in HTTP Request node 🔧 Update the request body format in "Prepare API Request" node 🔐 Update authentication method if needed 📊 Adjust response parsing in "Save AI Response to History" node 🧠 AI Behavior 📝 Modify system prompt in "Prepare API Request" node 🌡️ Adjust temperature and response parameters 📏 Change response length limits 🎯 Customize model-specific parameters 💾 Memory Settings 📊 Adjust history length (currently 10 messages) 👤 Modify user identification logic 🗄️ Customize data persistence approach 🎭 Bot Personality 🎉 Update welcome message content ⚠️ Customize error messages and responses ➕ Add new command handlers 💡 Use Cases 🎧 Customer Support**: Automated first-line support with context awareness 📚 Educational Assistant**: Homework help and learning support 👥 Personal AI Companion**: General conversation and assistance 💼 Business Assistant**: FAQ handling and information retrieval 🔬 AI API Testing**: Perfect template for testing different AI services 🚀 Prototype Development**: Quick AI chatbot prototyping 📝 Notes 🌐 Requires active n8n instance for webhook handling 💰 AI API usage may have rate limits and costs (varies by provider) 💾 Bot memory persists across workflow restarts 👥 Supports multiple concurrent users with separate histories 🔄 Template is provider-agnostic - easily switch between AI services 🛠️ Perfect starting point for any AI-powered Telegram bot project 🔧 Popular AI Services You Can Use | Provider | Model Examples | API Endpoint Style | |----------|---------------|-------------------| | 🟢 OpenAI | GPT-4, GPT-3.5 | https://api.openai.com/v1/chat/completions | | 🔵 Anthropic | Claude 3 Opus, Sonnet | https://api.anthropic.com/v1/messages | | 🔴 Google | Gemini Pro, Gemini Flash | https://generativelanguage.googleapis.com/v1beta/models/ | | 🟡 NVIDIA | LLaMA, Mistral | https://integrate.api.nvidia.com/v1/chat/completions | | 🟠 Hugging Face | Various OSS models | https://api-inference.huggingface.co/models/ | | 🟣 Cohere | Command, Generate | https://api.cohere.ai/v1/generate | Simply replace the HTTP Request node configuration to switch providers!

Update Hubspot engagement by parsing inbox mail with AI

by PollupAI

Who is this for? This workflow is designed for Customer Success Managers (CSM), sales, support, or marketing teams using HubSpot CRM who want to automate customer engagement tracking when new emails arrive. It’s ideal for businesses looking to streamline CRM updates without manual data entry. Problem Solved / Use Case Manually logging email interactions in HubSpot is time-consuming. This workflow automatically parses incoming emails, checks if the sender exists in HubSpot, and either: Creates a new contact + logs the email as an engagement (if the sender is new). Logs the email as an engagement for an existing contact. What This Workflow Does Triggers when a new email arrives in a connected IMAP inbox. Parses the email using AI (OpenAI) to extract structured data. Searches HubSpot for the sender’s email address. Updates HubSpot: Creates a contact (if missing) and logs the email as an engagement. Or logs the engagement for an existing contact. Setup Configure Email Account: Replace the default IMAP node with your email provider HubSpot Credentials: Add your HubSpot API key in the HubSpot nodes. OpenAI Integration: Ensure your OpenAI API key is set for email parsing. Customization Tips Improve AI Prompt**: Modify the OpenAI prompt to extract specific email data (e.g., customer intent). Add Filters**: Exclude auto-replies or spam by adding a filter node. Extend Functionality**: Use the parsed data to trigger follow-up tasks (e.g., Slack alerts, tickets). Need Help? Contact thomas@pollup.net for workflow modifications or help. Discover my other workflows here

⚙️Business Automation

4 nodes868 views

Multi-User Telegram Bot to Summarize & Repurpose YouTube Videos with GPT-4o

by Aashiq

👤 Who’s it for This workflow is for content creators, marketers, educators, or anyone who wants to instantly summarize YouTube videos and repurpose them into different formats (LinkedIn post, tweet, etc.) via a simple Telegram chatbot. ⚙️ How it works This n8n automation listens for messages in Telegram. If the message contains a YouTube link, it: Extracts the video ID Fetches the video transcript using RapidAPI Cleans the transcript of any special characters Sends it to OpenAI to generate a summary If the message is not a link, it simply acts as an AI chatbot using OpenAI with memory support. ✅ Supports follow-up prompts like: “Make it shorter” “Turn this into a LinkedIn post” “Create a tweet thread” 🧑‍🤝‍🧑 Multi-User Support This Telegram bot supports multiple users simultaneously. It tracks memory and context separately for each user using Telegram's unique chat_id. ✅ Each user gets personalized AI replies ✅ Follow-up commands work per user ✅ No interference between users 🛠️ Requirements A Telegram bot token (get via @BotFather) An OpenAI API Key (from https://platform.openai.com/account/api-keys) A RapidAPI Key and Host (typically youtube-transcript3.p.rapidapi.com) > 🚨 API keys must be added manually — they are not included in the template. 🧩 How to Set It Up Configure the Telegram Trigger node with your bot token. In the HTTP Request node, set: X-RapidAPI-Key: your RapidAPI key X-RapidAPI-Host: your RapidAPI host URL Add your OpenAI API credentials to the AI Agent node. Use the provided sticky notes for guidance inside the workflow itself. 🎛️ How to Customize Modify AI prompt behavior in the AI Agent node Change the text formatting in the Code node Use a different transcript API if preferred Add commands like make it into a blog post, summarize in bullet points, etc. 📌 Notes All nodes are renamed to reflect their function API credentials are removed for security Includes colored boxes and sticky notes to guide the user Compatible with n8n cloud and self-hosted setups

🤖AI & Machine Learning

6 nodes112 views

Verify & enrich form leads with Hunter and Clearbit then add them to Pipedrive

by Niklas Hatje

Use case When collecting leads via an online form, you often need to manually add those new leads into your Pipedrive CRM. This not only takes a lot of time but is also error-prone. This workflow automates this tedious work for you. What this workflow does The workflow is triggered each time a form is submitted in n8n. It validates the email address using Hunter.io. If the email is valid, the workflow checks for an existing person with that email in Pipedrive. If no existing person is found, it utilizes Clearbit to enrich the person's information. It then verifies if the person's organization already exists in Pipedrive, creating a new organization if necessary. The workflow then registers the person in Pipedrive. Lastly, it creates a lead in Pipedrive using information from the person and organization. Setup This workflow is very quick to set up. Add your Hunter.io, Clearbit and Pipedrive credentials Click the test workflow button Activate the workflow and use the form trigger production URL to collect your leads in a smart way How to adjust it to your needs Exchange the n8n form trigger with your form of choice (Typeform, Google Forms, SurveyMonkey...) Add a filter criteria to only add new leads if they match certain requirements Remove the email check with Hunter.io if you don't own this tool and expect new form submission to have a correct email anyways Add ways to handle invalid emails or existing Persons

beginner

3 nodes1190 views

Automatically Classify and Label Gmail Emails with Google Gemini AI

by Jakkrapat Ampring

Description Quickly organize your inbox with AI! This simple workflow automatically classifies incoming emails into different categories — like High Priority, Work Related, or Promotions — and applies Gmail labels accordingly. Setup takes less than 2 minutes, and it runs 24/7, helping you stay focused on what matters most without manual sorting. Tools/Services Needed Gmail: To trigger the workflow and label emails. Google Gemini (or any LLM Model): To intelligently classify email content. How It Works Gmail Trigger: Detects every new incoming email. Text Classifier Node: Classifies the email content into predefined categories. Google Gemini Chat Model: Provides the AI-powered understanding behind the classification. Conditional Labeling: If the email is High Priority, label it accordingly. If it’s Work Related (e.g., internal emails), apply the work label. If it’s a Promotion, sort it into the promotions label. Gmail Labeling: Automatically adds the correct label to the email. Setup Instructions Connect your Gmail account to n8n. Connect your Google Gemini (or other LLM) credentials. Customize the categories and labels if needed. Activate the workflow — and that's it! Notes You can easily add more categories (like "Finance," "Newsletters," etc.) by adjusting the classification prompt. Works best with a clean and minimal set of categories to avoid overlap. Can be adapted to work with any other large language model (OpenAI, Claude, etc.) if preferred.

5 nodes4476 views

AI-Powered Automated Outreach with Scheduling, Gemini, Gmail & Google Sheets

by Sarfaraz Muhammad Sajib

AI-Powered Automated Outreach Scheduling with Gemini, Gmail & Google Sheets Automate your lead generation and outreach process seamlessly using AI, Gmail, and Google Sheets—all within n8n. No complicated setup—just import, activate, and start reaching prospects with personalized messages generated by Google Gemini’s AI model. Quick Setup Import the Workflow Download and import the provided workflow into your n8n instance. Connect Your Accounts Authenticate your Google Sheets account. Connect your Gmail account for sending emails. Prepare the Spreadsheet Use this template to set up your leads and tracking sheet. Configure the Gemini API Obtain your Gemini API key. Here Add it to the Gemini API credentials within n8n. Set Scheduling Preferences Customize the Schedule Trigger node to control when the workflow runs. Edit Email Prompts Update the initial and follow-up email prompts to match your outreach tone and goals. Set Rate Limits Configure the rate limiting settings to comply with Gmail sending limits and avoid spam filters. Activate the Workflow Enable the workflow to begin automated outreach to your leads. Track and Manage Leads Monitor responses and update lead statuses directly in your Google Sheet. How It Works Schedule Trigger:** Automatically starts outreach based on your defined schedule Google Sheets Integration:** Fetches leads and updates their status after outreach Email Validation:** Checks if lead emails are valid before sending Website Scraper:** Gathers info from lead websites to personalize messages Google Gemini AI:** Generates tailored cold outreach messages optimized for high response Gmail Node:** Sends personalized emails directly from your Gmail account Core Features Pull leads automatically from Google Sheets Validate emails to avoid bounces Scrape lead websites for custom messaging context Generate AI-crafted outreach emails with dynamic personalization Send emails on schedule without manual intervention Update lead status to track outreach progress AI Integration Uses Google Gemini AI to create professional, friendly, and engaging outreach emails Dynamic prompt templates tailored to each lead’s company and website content Structured JSON output to easily map subject, greeting, and body content 💡 Usage Examples B2B cold outreach campaigns with personalized emails Automated follow-ups based on lead engagement Lead nurturing with context-aware messaging Sales prospecting workflows integrated into your CRM ✨ Benefits Save hours by automating personalized outreach Increase response rates with AI-optimized messaging Keep lead data organized and updated in Google Sheets Fully scalable and customizable n8n workflow Minimal setup, ready to run out-of-the-box

6 nodes104 views

Facebook Token Retrieval & Management

by L Hùng

Pre-Conditions A Facebook Developer account with an active app. Basic understanding of n8n workflows. Access to a database (optional, for storing tokens). Setup Webhook Activation: Configure the Webhook to receive user requests and process input data. Ensure the Webhook URL is correctly set in your Facebook App settings. Short-Lived Token Retrieval: Use Facebook OAuth to fetch a short-lived token from the authorization code. Long-Lived Token Conversion: Convert the short-lived token into a long-lived token (valid for ~60 days). Page Token Retrieval: Follow the provided instructions to retrieve Page Tokens for posting on managed Facebook Pages. Customizable Scopes: Edit the correctScopes array to include or exclude permissions as needed. Optional Database Storage: Extend the workflow to save tokens to a database instead of displaying them on-screen. Step-by-Step Instructions: Detailed guidance is provided via sticky notes for activating the app, configuring Webhook, and editing parameters like fb_redirect_uri, app_id, and app_secret. Who the Template is For Developers**: Integrating Facebook APIs into their applications. Social Media Managers**: Automating posting and engagement on Facebook Pages. n8n Users**: Looking for a ready-to-use workflow for Facebook Token management. Primary Use Automates Facebook Token retrieval and management. Supports posting to Facebook Pages via Page Tokens. Easily customizable and extendable for specific requirements.

beginner

2 nodes1144 views

Perform SEO Keyword Research & Insights with Ahrefs API and Gemini 1.5 Flash

by Joseph

This n8n workflow automates SEO keyword research by querying the Ahrefs API for keyword data and related keyword insights. The enriched data is then processed by an AI agent to format a response and provide valuable SEO recommendations. Perfect for SEO specialists, content marketers, digital agencies, and anyone looking to gain valuable insights into keyword opportunities to boost their rankings. ⚙️ How This Workflow Works This workflow guides you through the entire SEO keyword research process, from entering the initial keyword to receiving detailed insights and related keyword suggestions. 1. 🗣️ User Input (Keyword Query) The user enters a keyword they want to research. This input is captured by the Chat Input Node, ready for analysis. 2. 🤖 AI Agent (Input Verification) The AI Agent reviews the keyword input for any grammatical errors or extra commentary. If necessary, it cleans the input to ensure a seamless query to the API. 3. 🔑 Ahrefs API (Keyword Data Retrieval) The cleaned keyword is sent to the Ahrefs Keyword Tool API. This retrieves a detailed report including metrics like search volume, keyword difficulty, and CPC. 4. 💡 Related Keywords Extraction (Using JavaScript Function) The workflow uses a JavaScript function to extract main keyword data and 10 related keywords data from the Ahrefs response. You can tweak the script to adjust the number of related keywords or the level of detail you want. 5. 🧠 AI Agent (Text Formatting) The aggregated data, including both the main keyword and related keywords, is sent to an AI agent. The AI agent formats the data into a concise, readable format that can be shared with the user. 6. 📨 Final Response The formatted text is delivered to the user with keyword insights, recommendations, and related keyword suggestions. ✅ Smart Retry & Error Handling Each subworkflow includes a fail-safe mechanism to ensure: ✅ Proper error handling for any issues with the API request. 🕒 Failed API requests are retried after a customizable period (e.g., 2 hours or 1 day). 💬 User input validation prevents any incorrect or malformed queries from being processed. 📋 Ahrefs API Setup To use this workflow, you’ll need to set up your Ahrefs API credentials: 🔑 Ahrefs API Sign up for an Ahrefs account and get your key here: Ahrefs Keyword Tool API Once signed up, you'll receive an API key, which you’ll use in the x-rapidapi-key header in n8n. Ensure you check the Ahrefs Keyword Tool API documentation for more details on available parameters. 📥 How to Import This Workflow Copy the json code. Open your n8n instance. Open a new workflow. Paste anywhere inside the workflow. Voila. 🛠️ Customization Options Adjust the number of related keywords extracted (default is 10). Customize the AI agent response formatting or add specific recommendations for users. Modify the JavaScript function to extract different metrics from the Ahrefs API. 🧪 Use Case Example Trying to optimize your blog post around a specific keyword? Query a broad keyword, like “SEO tips”. Get related keyword data and search volume insights. Use the AI agent to provide keyword recommendations and additional topics to target. 💥 Boost your content strategy with fresh keywords and relevant search data!

🤖AI & Machine Learning

5 nodes4510 views

Connect Retell Voice Agents to Custom Functions

by Agent Studio

Overview This workflow allows you to trigger custom logic in n8n directly from Retell's Voice Agent using Custom Functions. It captures a POST webhook from Retell every time a Voice Agent reaches a Custom Function node. You can plug in any logic—call an external API, book a meeting, update a CRM, or even return a dynamic response back to the agent. Who is it for For builders using Retell who want to extend Voice Agent functionality with real-time custom workflows or AI-generated responses. Prerequisites Have a Retell AI Account A Retell agent with a Custom Function node in its conversation flow (see template below) Set your n8n webhook URL in the Custom Function configuration (see "How to use it" below) (Optional) Familiarity with Retell's Custom Function docs Start a conversation with the agent (text or voice) Retell Agent Example To get you started, we've prepared a Retell Agent ready to be imported, that includes the call to this template. Import the agent to your Retell workspace (top-right button on your agent's page) You will need to modify the function URL in order to call your own instance. This template is a simple hotel agent that calls the custom function to confirm a booking, passing basic formatted data. How it works Retell sends a webhook to n8n whenever a Custom Function is triggered during a call (or test chat). The webhook includes: Full call context (transcript, call ID, etc.) Parameters defined in the Retell function node You can process this data and return a response string back to the Voice Agent in real-time. How to use it Copy the webhook URL (e.g. https://your-instance.app.n8n.cloud/webhook/hotel-retell-template) Modify the Retell Custom Function webhook URL (see template description for screenshots) Edit the function Modify the URL Modify the logic in the Set node or replace it with your own custom flow Deploy and test: Retell will hit your n8n workflow during the conversation Extension Ideas Call a third-party API to fetch data (e.g. hotel availability, CRM records) Use an LLM node to generate dynamic responses Trigger a parallel automation (Slack message, calendar invite, etc.) 👉 Reach out to us if you're interested in analyzing your Retell Agent conversations.

🧹 Archive (delete) duplicate items from a Notion database

by Lucía Maio Brioso

🧑‍💼 Who is this for? If you’re using Notion to manage a database (like saving links, tasks, notes, or anything really), and it’s starting to get messy with duplicate entries, this workflow is for you. It’s especially useful if you want to keep things tidy without doing any manual cleanup. 🧠 What problem is this workflow solving? Notion doesn’t have a built-in way to find or remove duplicates, so you either clean them up manually 😩 or just let them pile up. This workflow automatically finds entries that share the same property (like a URL or title) and archives the extra copies, keeping just one. ⚙️ What this workflow does Pulls all pages from a Notion database. Identifies duplicates based on a property you choose. Archives the duplicate pages (which is like soft-deleting them). Keeps one version of each duplicate group. It includes two optional triggers: Run it every day ⏰ Or trigger it automatically when a new page is added to the database ⚡ 🛠️ Setup Connect your Notion account in n8n. Select your database in the Notion nodes. In the “Format items properly” node, replace "SET YOUR PROPERTY HERE" with a reference to the property you want to use for detecting duplicates. I recommend using the n8n property drag-and-drop feature. Enable whichever trigger you prefer — or both. And that’s it. It runs on its own after that. 🧩 How to customize this workflow to your needs Use a different property for detecting duplicates by updating the Set node. Want to tag duplicates instead of archiving them? Just replace the last Notion node with an update operation. Adjust the schedule to run it hourly, weekly, or whenever suits your setup.

⚙️Business Automation

beginner

2 nodes601 views

Business Lead Generation with Apify Web Scraping and Google Sheets Storage

by Jordan Lee