by David Olusola
This workflow analyzes images submitted via a form using OpenAI Vision, then delivers the analysis result directly to your Telegram chat. ✅ Use case examples: • Users submit screenshots for instant AI interpretation • Automated document or receipt analysis with Telegram delivery • Quick OCR or image classification workflows ⸻ ⚙️ Setup Guide Form Submission Trigger • Connect your form app (e.g. Typeform, Tally, or n8n’s own webhook form) to the On form submission trigger node. • Ensure it sends the image file or URL as input. OpenAI Vision Analysis • In the OpenAI node, select Analyze Image operation. • Provide your OpenAI API key and configure the prompt to instruct the model on what to analyze (e.g. “Describe this receipt in detail”). Set Telegram Chat ID • Use this manual node to input your Telegram Chat ID for delivery. • Alternatively, automate this with a database lookup or user session if building for multiple users. Telegram Delivery Node • Connect your Telegram Bot to n8n using your bot token. • Set up the sendMessage operation, using the analysis result from the previous node as the message text. Testing • Click Execute workflow. • Submit an image via your form and confirm it delivers to your Telegram as expected.
by Vitali
Template Description This n8n workflow template allows you to create a masked email address using the Fastmail API, triggered by a webhook. This is especially useful for generating disposable email addresses for privacy-conscious users or for testing purposes. Workflow Details: Webhook Trigger: The workflow is initiated by sending a POST request to a specific webhook. You can include state and description in your request body to customize the masked email's state and description. Session Retrieval: The workflow makes an HTTP request to the Fastmail API to retrieve session information. It uses this data to authenticate further requests. Create Masked Email: Using the retrieved session data, the workflow sends a POST request to Fastmail's JMAP API to create a masked email. It uses the provided state and description from the webhook payload. Prepare Output: Once the masked email is successfully created, the workflow extracts the email address and attaches the description for further processing. Respond to Webhook: Finally, the workflow responds to the original POST request with the newly created masked email and its description. Requirements: Fastmail API Access**: You will need valid API credentials for Fastmail configured with HTTP Header Authentication. Authorization Setup**: Optionally set up authorization if your webhook is exposed to the internet to prevent misuse. Custom Webhook Request**: Use a tool like curl or create a shortcut on macOS/iOS to send the POST request to the webhook with the necessary JSON payload, like so: curl -X POST -H 'Content-Type: application/json' https://your-n8n-instance/webhook/87f9abd1-2c9b-4d1f-8c7f-2261f4698c3c -d '{"state": "pending", "description": "my mega fancy masked email"}' This template simplifies the process of integrating masked email functionality into your projects or workflows and can be extended for various use cases. Feel free to use the companion shortcut I've also created. Please update the authorization header in the shortcut if needed. https://www.icloud.com/shortcuts/ac249b50eab34c04acd9fb522f9f7068
by Angel Menendez
Enhance Query Resolution with the Knowledge Base Tool! Our KB Tool - Confluence KB is crafted to seamlessly integrate into the IT Ops AI SlackBot Workflow, enhancing the IT support process by enabling sophisticated search and response capabilities via Slack. Workflow Functionality: Receive Queries**: Directly accepts user queries from the main workflow, initiating a dynamic search process. AI-Powered Query Transformation**: Utilizes OpenAI's models or local ai to refine user queries into searchable keywords that are most likely to retrieve relevant information from the Knowledge Base. Confluence Integration**: Executes searches within Confluence using the refined keywords to find the most applicable articles and information. Deliver Accurate Responses**: Gathers essential details from the Confluence results, including article titles, links, and summaries, preparing them to be sent back to the parent workflow for final user response. To view a demo video of this workflow in action, click here. Quick Setup Guide: Ensure correct configurations are set for OpenAI and Confluence API integrations. Customize query transformation logic as per your specific Knowledge Base structure to improve search accuracy. Need Help? Dive into our Documentation or get support from the Community Forum! Deploy this tool to provide precise and informative responses, significantly boosting the efficiency and reliability of your IT support workflow.
by shepard
Overview This workflow leverages the LangChain code node to implement a fully customizable conversational agent. Ideal for users who need granular control over their agent's prompts while reducing unnecessary token consumption from reserved tool-calling functionality (compared to n8n's built-in Conversation Agent). Setup Instructions Configure Gemini Credentials: Set up your Google Gemini API key (Get API key here if needed). Alternatively, you may use other AI provider nodes. Interaction Methods: Test directly in the workflow editor using the "Chat" button Activate the workflow and access the chat interface via the URL provided by the When Chat Message Received node Customization Options Interface Settings: Configure chat UI elements (e.g., title) in the When Chat Message Received node Prompt Engineering: Define agent personality and conversation structure in the Construct & Execute LLM Prompt node's template variable ⚠️ Template must preserve {chat_history} and {input} placeholders for proper LangChain operation Model Selection: Swap language models through the language model input field in Construct & Execute LLM Prompt Memory Control: Adjust conversation history length in the Store Conversation History node Requirements: ⚠️ This workflow uses the LangChain Code node, which only works on self-hosted n8n. (Refer to LangChain Code node docs)
by Aji Prakoso
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow provides a complete, ready-to-use template for a Retrieval-Augmented Generation (RAG) system. It allows you to build a powerful AI chatbot that can answer questions based on the content of PDF documents you provide, using a modern and powerful stack for optimal performance. Good to know Costs:** This workflow uses paid services (OpenAI, Pinecone, Cohere). Costs will be incurred based on your usage. Please review the pricing pages for each service to understand the potential expenses. Video Tutorial (Bahasa Indonesia):** For a step-by-step guide on how this workflow functions, you can watch the accompanying video tutorial here: N8N Tutorial: Membangun Chatbot RAG dengan Pinecone, OpenAI, & Cohere How it works This workflow operates in two distinct stages: 1. Data Ingestion & Indexing: It begins when a .pdf file is uploaded via the n8n Form Trigger. The Default Data Loader node processes the PDF, and the Recursive Character Text Splitter breaks down the content into smaller, manageable chunks. The Embeddings OpenAI node converts these text chunks into vector embeddings (numerical representations). Finally, the Pinecone Vector Store node takes these embeddings and stores (upserts) them into your specified Pinecone index, creating a searchable knowledge base. 2. Conversational AI Agent: A user sends a message through the Chat Trigger. The AI Agent receives the message and uses its VectorDB tool to search the Pinecone index for relevant information. The Reranker Cohere node refines these search results, ensuring only the most relevant context is selected. The user's original question and the refined context are sent to the OpenAI Chat Model (gpt-4.1), which generates a helpful, context-aware answer. The Simple Memory node maintains conversation history, allowing for natural, multi-turn dialogues. How to use Using this workflow is a two-step process: Populate the Knowledge Base: First, you need to add documents. Trigger the workflow by using the Form Trigger and uploading a PDF file. Wait for the execution to complete. You can do this for multiple documents. Start Chatting: Once your data has been ingested, open the Chat Trigger's interface and start asking questions related to the content of your uploaded documents. The Form Trigger is just an example. Feel free to replace it with other triggers, such as a node that watches a Google Drive or Dropbox folder for new files. Requirements To run this workflow, you will need active accounts and API keys for the following services. OpenAI Account & API Key:** Function: Powers text embedding and the final chat generation. Required for the Embeddings OpenAI and OpenAI Chat Model nodes. Pinecone Account & API Key:** Function: Used to store and retrieve your vector knowledge base. Required for the Pinecone Vector Store and VectorDB nodes. You also need to provide your Pinecone Environment. Cohere Account & API Key:** Function: Improves the accuracy of your chatbot by re-ranking search results for relevance. Required for the Reranker Cohere node. Customising this workflow This template is a great starting point. Here are a few ways you can customize it: Change the AI Personality:* Edit the *System Message** in the AI Agent node to change the bot's behavior, tone, or instructions. Use Different Models:** You can easily swap the OpenAI model for another one (e.g., gpt-3.5-turbo for lower costs) in the OpenAI Chat Model node. Adjust Retrieval:** In the VectorDB tool node, you can modify the Top K parameter to retrieve more or fewer document chunks to use as context. Automate Ingestion:** Replace the manual Form Trigger with an automated one, like a node that triggers whenever a new file is added to a specific cloud storage folder.
by Kunsh
A streamlined AI-powered tool that extracts actionable technical insights from HackerOne security reports for advanced bug bounty hunters. How It Works Send any HackerOne report URL (e.g., https://hackerone.com/reports/123456) to the chat interface. The AI agent will: Fetch the report JSON automatically Analyze for unique techniques, payloads, and root causes Extract reusable insights in a structured format Summarize with practical pentesting value Setup Requirements Google Gemini API credentials configured Chat interface deployed and accessible HackerOne report URLs Output Format Summary: One-liner impact statement Techniques: Payloads, code snippets, exploitation steps Pro Tips: Reusable insights for future hunts Perfect for rapid triage and building your personal exploit knowledge base.
by Yaron Been
Automated system for monitoring and analyzing competitor activities, funding rounds, and market movements using CrunchBase data. 🚀 What It Does Tracks competitor funding rounds Monitors leadership changes Analyzes investment patterns Identifies new market entries Tracks product launches 🎯 Perfect For Startup founders Business strategists Market analysts Investment professionals Corporate development ⚙️ Key Benefits ✅ Competitive intelligence ✅ Early warning system ✅ Market trend analysis ✅ Strategic insights ✅ Time-saving automation 🔧 What You Need CrunchBase API access n8n instance Google Sheets (for data storage) Notification preferences 📊 Tracking Metrics Funding amounts and rounds Investor networks Hiring trends Market expansion Product updates 🛠️ Setup & Support Quick Setup Start tracking in 20 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Gain a competitive edge with automated tracking and analysis of your competitors' activities and strategies.
by Mirajul Mohin
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automatically transform your video uploads into AI-powered summaries with key topic extraction and instant team notifications. What this workflow does Monitors Google Drive for new video uploads Downloads and processes videos using VLM Run AI Generates intelligent summaries with key topics extracted Posts results to Slack for immediate team access Setup Prerequisites: Google Drive account, VLM Run API credentials, Slack workspace, self-hosted n8n. You need to install VLM Run community node Quick Setup: Configure Google Drive OAuth2 and create video upload folder Add VLM Run API credentials Set up Slack integration for notifications Update folder/channel IDs in workflow nodes Test and activate Perfect for Meeting recordings and training videos Webinar summaries and educational content Content analysis and team collaboration Any video content requiring quick insights Key Benefits Asynchronous processing** handles large files without timeouts Multi-format support** for MP4, AVI, MOV, WebM, MKV Instant team updates** via Slack notifications Saves hours** of manual video review time How to customize Extend by adding: Video categorization and tagging Integration with project management tools Email notifications alongside Slack Searchable video databases with summaries This workflow transforms lengthy videos into actionable insights, making your content instantly accessible and shareable with your team.
by Mohan Gopal
Overview This release introduces a Voice-Enabled Tour Recommendation System that leverages n8n, ElevenLabs Voice Agent, OpenAI GPT-4o, and Pinecone Vector DB to deliver personalized travel itineraries based on spoken input. Users speak their preferences to the ElevenLabs voice agent, which then triggers an n8n workflow that returns a tailored tour plan. Features Voice interaction with AI-powered travel agent via ElevenLabs Uses ChatGPT-4o for contextual understanding and generation Dynamic query handling with vector-based search using Pinecone Fast response generation using n8n webhook Modular agent memory and role design for scalable enhancement Pre-requisites n8n account with workflow creation access ElevenLabs account with agent and webhook setup OpenAI API key (GPT-4o access) Pinecone account for vector database A list of vectorized tour packages using this n8n embedder (https://creators.n8n.io/workflows/5085) Setup Instructions Step 1: Configure the Voice Agent Webhook in ElevenLabs Use POST method Webhook URL: https://... Breakdown voice input into: Destination Type of tour Number of days Number of passengers Step 2: Set Up the AI Agent Prompt in ElevenLabs Use a conversational style with summaries, clarifying questions, and affirmations. Example Prompt: “You use a natural speech style and periodically summarize... Your goal is to help callers create a personalized tour plan.” Step 3: Select LLM LLM: GPT-4o Mini Memory window: Up to 5 contexts Step 4: Integrate Tools Use Custom Tool: n8n ID: tool_xxxxxx Tool Description: “Generates travel plan once the details are collected” Step 5: Build n8n Workflow Trigger: Webhook (POST) Process user input: Tour Recommendation AI Agent Use OpenAI Chat Model (GPT-4o) for reasoning Query Pinecone Vector Store using Tour Builder Q&A node Respond with structured Itinerary Plan via webhook response How to use: Execute the n8n workflow (the webhook waits for the voice trigger from elevenlabs) Start the Elevenlabs Voice Agent Request for a tour plan to any destination giving the details of your tour preferences. Wait for the Voice Agent to respond back with tour package suggestions after fetching the tour details from the n8n workflow. Close the conversation. | Area | Improvement | | ------------------ | ----------------------------------------------------- | | 🔉 Voice UX | Natural-sounding travel agent using ElevenLabs | | 💡 Personalization | ChatGPT-4o adapts based on travel style & preferences | | 📚 Knowledge Base | Pinecone-powered vector retrieval of real tour data | | 🔁 Reusability | Modular workflow with reusable embedding tools | | ⚙️ System Design | Separation of memory, logic, and data layers | Who is this for? Travel Agencies & DMCs Offer ultra-personalized packages based on customer queries. Let AI do the matching. Tour Package Aggregators Auto-curate and send matching packages from your catalog — no manual searching needed. Content & Marketing Teams Craft customized tour recommendations for email campaigns and newsletters. Tech-enabled Travel Startups Embed this intelligence in your workflows, CRMs, or chatbots to delight customers.
by Mike Russell
Automated YouTube Video Promotion Workflow Automate the promotion of new YouTube videos on X (formerly Twitter) with minimal effort. This workflow is perfect for content creators, marketers, and social media managers who want to keep their audience updated with fresh content consistently. How it works This workflow triggers every 30 minutes to check for new YouTube videos from a specified channel. If a new video is found, it utilizes OpenAI's ChatGPT to craft an engaging, promotional message for X. Finally, the workflow posts the generated message to Twitter, ensuring your latest content is shared with your audience promptly. Set up steps Schedule the workflow to run at your desired frequency. Connect to your YouTube account and set up the node to fetch new videos based on your Channel ID. Integrate with OpenAI to generate promotional messages using GPT-3.5 turbo. Link to your X account and set up the node to post the generated content. Please note, you'll need API keys and credentials for YouTube, OpenAI, and X. Check out this quick video tutorial to make the setup process a breeze. Additional Tips Customize the workflow to match your branding and messaging tone. Test each step to ensure your workflow runs smoothly before going live.
by Mike Russell
Boost engagement on your Discord server by automatically sharing new YouTube videos along with AI generated summaries of their content. This workflow is ideal for content creators and community managers looking to provide value and spark interest through summarized content, making it easier for community members to decide if a video is of interest to them. Watch this video tutorial to learn more about the template. How it works RSS Feed Trigger**: Monitors your YouTube channel for new uploads using the RSS feed. Video Captions Retrieval**: Fetches video captions using the YouTube API to get detailed content data. AI Summary Generation**: Uses an AI model to generate concise summaries from the video captions, highlighting key points. Discord Notification**: Posts video announcements along with their AI generated summaries to a specified Discord channel using a webhook. Set up steps Configure YouTube RSS Feed: Set up the RSS feed node to detect new video uploads. Add your YouTube channel ID to the URL in the first node: https://www.youtube.com/feeds/videos.xml?channel_id=YOUR_CHANNEL_ID. Connect OpenAI Account: To enable AI summary generation, connect your OpenAI account in n8n. Set Up Discord Webhook: Create a webhook in your Discord server and configure it in the Discord node. Design the Message: Format the Discord message as you like to include the video title, link, and the AI generated summary. Example This template empowers you to maintain a highly engaging Discord community, ensuring members receive not only regular updates but also valuable insights into each video's content without needing to watch immediately.
by Fan Luo
Auto-Share YouTube Videos with AI-Generated Posts to Facebook, X and Notify in Discord This n8n template demonstrates how to use a LLM like DeepSeek to generate a post and share to Facebook page and X automatically whenever a new video is published to a YouTube channel. How it works We first define RSS with a polling schedule to pull YouTube videos from a specified channel Prompt AI agent to generate a post with proper url and hash tags based on the video metadata Then automatically create a new post in Facebook and X via their APIs Post a new message in Discord channel via Webhook How to use Simply setup a RSS polling trigger to automatically trigger the workflow Requirements Facebook API setup, see step by step tutorials X v2 API setup, see step by step tutorials Discord channel webhook, see step by step tutorials Need Help? Contact me via My Blog or ask in the Forum! Happy Hacking!