AI Automation
923 Ergebnisse — ausschließlich quellenverknüpfte n8n-Referenzen
WMonitor Favorite YouTube Channels Through RSS feeds and Receive Notifications
This workflow creates an automated system for monitoring and receiving notifications about new videos from your favorite YouTube channels through RSS feeds, with customizable email and Telegram notifications. 🌟 Key Features 📡 RSS Feed Management Accepts custom YouTube channel IDs or uses default channels Automatically creates RSS feeds for each YouTube channel Monitors channels for new video uploads Labels and filters recent videos within a 3-day window (change this as required) 📨 Multi-Channel Notification System Sends Telegram notifications with video thumbnails and links Delivers customized email notifications in two formats: Individual emails for each new video Single digest email containing all new videos ⚙️ Content Processing Fetches detailed video information using YouTube API Creates responsive HTML email templates with video previews Includes video thumbnails, titles, descriptions, and direct links Maintains professional formatting across different email clients 🛠️ Setup Requirements 🔑 API Configuration YouTube Data API credentials Gmail account for sending notifications Telegram bot token and chat ID OpenAI API key for content processing 📋 Channel Management Add You
Automated AI image tagging and writing keywords into image (via community node)
Welcome to my Automated Image Metadata Tagging Workflow! DISCLAIMER: This workflow only works with self-hosted n8n instances! You have to install the n8n-nodes-exif-data Community Node! This workflow automatically analyzes the image content with the help of AI and writes it directly back into the image file as keywords. (https://n8n.io/workflows/2995).** This workflow has the following steps: Google Drive trigger (scan for new files added in a specific folder) Download the added image file Analyse the content of the image Merge Metadata and image file Write the Keywords into the Metadata (dc:subject/keywords) and create new image file Update the original file in the Google Drive folder The following accesses are required for the workflow: You have to install the n8n-nodes-exif-data Community Node** Google Drive: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) You can contact me via LinkedIn, if you have any questions: https://www.linkedin.com/in/friedemann-schuetz
Automated AI image tagging and writing the keywords into the image file
Welcome to my Automated Image Metadata Tagging Workflow! This workflow automatically analyzes the image content with the help of AI and writes it directly back into the image file as keywords. This workflow has the following sequence: Google Drive trigger (scan for new files added in a specific folder) Download the added image file Analyse the content of the image and extract the file as Base64 code Merge Metadata and Base64 Code Code Node to write the Keywords into the Metadata (dc:subject) Convert to file and update the original file in the Google Drive folder The following accesses are required for the workflow: Google Drive: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) You can contact me via LinkedIn, if you have any questions: https://www.linkedin.com/in/friedemann-schuetz
Split Test Different Agent Prompts with Supabase and OpenAI
Split Test Agent Prompts with Supabase and OpenAI Use Case Oftentimes, it's useful to test different settings for a large language model in production against various metrics. Split testing is a good method for doing this. What it Does This workflow randomly assigns chat sessions to one of two prompts, the baseline and the alternative. The agent will use the same prompt for all interactions in that chat session. How it Works When messages arrive, a table containing information regarding session ID and which prompt to use is checked to see if the chat already exists If it does not, the session ID is added to the table and a prompt is randomly assigned These values are then used to generate a response Setup Create a table in Supabase called split_test_sessions. It needs to have the following columns: session_id (text) and show_alternative (bool) Add your Supabase, OpenAI, and PostgreSQL credentials Modify the Define Path Values node to set the baseline and alternative prompt values. Activate the workflow and test by sending messages through n8n's inbuilt chat Experiment with different chat sessions to test see both prompts in action Next Steps Modify the workflow to test different LL
BGet Daily Exercise Plan with Flex Message via LINE
The YogiAI workflow automates sending daily yoga pose reminders and related information via Line Push Messages . This automation leverages data from a Google Sheets database containing yoga pose details such as names, image URLs, and links to ensure users receive personalized and engaging content every day. Purpose Provide users with daily yoga pose suggestions tailored to their practice. Deliver visually appealing and informative content through Line's Flex Messages, including images and clickable links. Log user interactions and preferences back into Google Sheets to refine future recommendations. Key Features Automated Daily Reminders : Sends a curated list of yoga poses at a scheduled time (21:30 Bangkok time). Dynamic Content Generation : Uses AI to rewrite and format messages in a user-friendly manner, complete with emojis and clear instructions. Integration with Google Sheets : Pulls data from a predefined Google Sheet and logs interactions for continuous improvement. Customizable Messaging : Ensures JSON outputs are properly formatted for Line’s Flex Message API, allowing for interactive and visually rich content. Data Source Google Sheets Structure The workflow relies on a
Personal Portfolio CV Rag Chatbot - with Conversation Store and Email Summary
Personal Portfolio CV Rag Chatbot - with Conversation Store and Email Summary Target Audience This template is perfect for: Individuals looking to create a working professional and interactive personal portfolio chatbot. Developers interested in integrating RAG Chatbot functionality with conversation storage. 1. Description Create a stunning Personal Portfolio CV with integrated RAG Chatbot capabilities, including conversation storage and daily email summaries. 2.Features: Training: Setup Ingestion stage Upload your CV to Google Drive and let the Drive trigger updates to read your resume cv and convert it into your vector database (RAG purpose). Modify any parts as needed. Chat & Track: Use any frontend/backend interface to call the chat API and chat history API. Reporting Daily Chat Conversations: Receive daily automatic summaries of chat conversations. Data stored via NocoDB. 3.Setup Guide: Step-by-Step Instructions: Ensure all credentials are ready. Follow the notes provided. Ingestion: Upload your CV to Google Drive. The Drive triggers RAG update in your vector database. You can change the folder name, files and indexname of the vector database accordingly. Chat: Use any fronte
All-in-One Telegram/Baserow AI Assistant 🤖🧠 Voice/Photo/Save Notes/Long Term Mem
Telegram Personal Assistant with Long-Term Memory & Note-Taking This n8n workflow transforms your Telegram bot into a powerful personal assistant that handles voice, photo, and text messages. The assistant uses AI to interpret messages, save important details as long-term memories or notes in a Baserow database, and recall information for future interactions. 🌟 How It Works Message Reception & Routing Telegram Integration: The workflow is triggered by incoming messages on your Telegram bot. Dynamic Routing: A switch node inspects the message to determine whether it's voice, text, or photo (with captions) and routes it for the appropriate processing. Content Processing Voice Messages: Audio files are retrieved and sent to an AI transcription node to convert spoken words into text. Text Messages: Text is directly captured and prepared for analysis. Photos: If an image is received, the bot fetches the file (and caption, if provided) and uses an AI-powered image analysis node to extract relevant details. AI-Powered Agent & Memory Management The core AI agent (powered by GPT-4o-mini) processes the incoming message along with any previous conversation history stored in PostgreSQL memory
🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant
🤖 AI-Powered RAG Chatbot with Google Drive Integration This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI. How It Works Document Processing & Storage 📚 Retrieves documents from a specified Google Drive folder Processes and splits documents into manageable chunks Extracts metadata using AI for enhanced search capabilities Stores document vectors in Qdrant for efficient retrieval Intelligent Chat Interface 💬 Provides a conversational interface powered by Google Gemini Uses RAG to retrieve relevant context from stored documents Maintains chat history in Google Docs for reference Delivers accurate, context-aware responses Vector Store Management 🗄️ Features secure delete operations with human verification Includes Telegram notifications for important operations Maintains data integrity with proper version control Supports batch processing of documents Setup Steps Configure API Credentials: Set up Google Drive & Docs access Configure Gemini AI API Set up Qdrant vector store connection Add Telegram bot for notifications Add OpenAI Api Ke
W✍️🌄 Your First Wordpress + AI Content Creator - Quick Start
✍️🌄 WordPress + AI Content Creator This workflow automates the creation and publishing of multi-reading-level content for WordPress blogs. It leverages AI to generate optimized articles, automatically creates featured images, and provides versions of the content at different reading levels (Grade 2, 5, and 9). How It Works Content Generation & Processing 🎯 Starts with a manual trigger and a user-defined blog topic Uses AI to create a structured blog post with proper HTML formatting Separates and validates the title and content components Saves a draft version to Google Drive for backup Multi-Reading Level Versions 📚 Automatically rewrites the content for different reading levels: Grade 9: Sophisticated language with appropriate metaphors Grade 5: Simplified with light humor and age-appropriate examples Grade 2: Basic language with simple metaphors and child-friendly explanations WordPress Integration 🌐 Creates a draft post in WordPress with the Grade 9 version Generates a relevant featured image using Pollinations.ai Automatically uploads and sets the featured image Sends success/error notifications via Telegram Setup Steps Configure API Credentials 🔑 Set up WordPress API conn
Analyze Reddit Posts with AI to Identify Business Opportunities
Use case Manually monitoring Reddit for viable business ideas is time-consuming and inconsistent. This workflow automatically analyzes trending Reddit discussions using AI to surface high-potential opportunities, filter irrelevant content, and generate actionable insights - saving entrepreneurs 10+ hours weekly in market research. What this workflow does This AI-powered workflow automatically collects trending Reddit discussions, analyzes posts for viable business opportunities using GPT-4, applies smart filters to exclude low-value content, and generates scored opportunity reports with market insights. It identifies unmet customer needs through sentiment analysis, prioritizes high-potential ideas using custom criteria, and outputs structured data to Google Sheets for actionable decision-making. Setup Add Reddit,Google and OpenAI credentials Configure target subreddits in Subreddit node Test workflow by testing workflow Review generated opportunity report in Google Sheets How to adjust this template Change data sources**: Replace Reddit trigger with Twitter/X or Hacker News API Modify criteria**: Adjust scoring thresholds in Opportunity Calculator node Add integrations**: Create au
Automatically Create YouTube Metadata with AI
This n8n workflow automates YouTube video metadata generation using AI. It extracts video transcripts, analyzes content, and produces optimized titles, descriptions, tags, hashtags, and call-to-action elements. Additionally, the workflow integrates affiliate and promotional links to enhance overall video performance. Key Features Automated Metadata Generation Utilizes an AI agent integrated with OpenAI GPT-4 to generate engaging metadata based on the provided video transcript. SEO and Engagement Optimization Creates keyword-rich, well-structured content that boosts search engine visibility and audience engagement. Affiliate and Promotional Integration Retrieves pre-set promotional and affiliate links using a Google Docs integration. Direct YouTube Update Automatically updates video details on YouTube via the YouTube API. Customization Allows you to modify the AI prompt to tailor metadata for your specific niche. Workflow Breakdown User Submission Users supply the YouTube video link, transcript, and optionally, focus keywords. Video ID Extraction The workflow converts the YouTube URL into a video ID to streamline automation. Link Retrieval Affiliate and course links are fetched from
WBuild Your Own Counseling Chatbot on LINE to Support Mental Health Conversations
Are you looking to create a counseling chatbot that provides emotional support and mental health guidance through the LINE messaging platform ? This guide will walk you through connecting LINE with powerful AI language models like GPT-4 to build a chatbot that supports users in navigating their emotions, offering 24/7 conversational therapy and accessible mental health resources . By leveraging LINE's webhook integration and Azure OpenAI , this template allows you to design a chatbot that is both empathetic and efficient, ensuring users receive timely and professional responses. Whether you're a developer, counselor, or business owner, this guide will help you create a customizable counseling chatbot tailored to your audience's needs. Who Is This Template For? Developers who want to integrate AI-powered chatbots into the LINE platform for mental health applications. Counselors & Therapists looking to expand their reach and provide automated emotional support to clients outside of traditional sessions. Businesses & Organizations focused on improving mental health accessibility and offering innovative solutions to their users. Educators & Nonprofits seeking tools to provide free or l
WTurn BBC News Articles into Podcasts using Hugging Face and Google Gemini
Turn BBC News Articles into Podcasts using Hugging Face and Google Gemini Effortlessly transform BBC news articles into engaging podcasts with this automated n8n workflow. Who is this for? This template is perfect for: Content creators** who want to quickly produce podcasts from current events. Students** looking for an efficient way to create audio content for projects or assignments. Individuals** interested in generating their own podcasts without technical expertise. Setup Information Install n8n: If you haven't already, download and install n8n from n8n.io. Import the Workflow: Copy the JSON code for this workflow and import it into your n8n instance. Configure Credentials: Gemini API: Set up your Gemini API credentials in the workflow's LLM nodes. Hugging Face Token: Obtain an access token from Hugging Face and add it to the HTTP Request node for the text-to-speech model. Customize (Optional): Filtering Criteria: Adjust the News Classifier node to fine-tune the selection of news articles based on your preferences. Output Options: Modify the workflow to save the generated audio file to a cloud storage service or publish it to a podcast hosting platform. Prerequisites An active
🎦🚀 YouTube Video Comment Analysis Agent
🎦🚀 YouTube Video Comment Analysis Agent This n8n workflow is designed to help YouTube creators analyze video details and comments to generate a comprehensive and actionable report. The workflow provides insights into video performance, audience engagement, and viewer feedback, helping creators identify trends, interests, and opportunities for future content creation. ✨ Key Features Video Performance Analysis: Extracts metrics like views, likes, and comments to evaluate the video's success. Comment Sentiment Analysis: Determines the tone of comments (positive, neutral, or negative) to understand audience sentiment. Recurring Themes Detection: Identifies common topics or questions in comments to highlight viewer interests. Engagement Drivers: Pinpoints what aspects of the video resonated most with viewers. Actionable Recommendations: Offers strategies for creating follow-up content or improving future videos. Keyword Suggestions: Extracts frequently mentioned terms for better discoverability on YouTube. Collaboration Opportunities: Suggests potential partnerships based on viewer feedback or related channels. 🛠️ How to Use Set Up Workflow Variables: Add your GOOGLE_API_KEY and the
Free YouTube Video Analyzer with AI-Powered Summaries & Email Alerts
This workflow is designed to analyze YouTube videos by extracting their transcripts, summarizing the content using AI models, and sending the analysis via email. This workflow is ideal for content creators, marketers, or anyone who needs to quickly analyze and summarize YouTube videos for research, content planning, or educational purposes. How It Works: Trigger: The workflow starts with a manual trigger, allowing you to test it by clicking "Test workflow." You can also set a YouTube video URL manually or dynamically. YouTube Video ID Extraction: The workflow extracts the YouTube video ID from the provided URL using a custom JavaScript function. This ID is necessary for fetching the transcript. Transcript Generation: The video ID is sent via an HTTP request to generate the transcript. You need to replace APIKEY with a free API key from the service. Transcript Validation: The workflow checks if a transcript exists for the video. If a transcript is available, it proceeds; otherwise, it stops. Full Text Extraction: If a transcript exists, the workflow combines all transcript segments into a single text variable for further analysis. AI-Powered Analysis: The full transcript is passed t
CW⚡📽️ Ultimate AI-Powered Chatbot for YouTube Summarization & Analysis
🎥 YouTube Video AI Agent Workflow This n8n workflow template allows you to interact with an AI agent that extracts details and the transcript of a YouTube video using a provided video ID. Once the details and transcript are retrieved, you can chat with the AI agent to explore or analyze the video's content in a conversational and insightful manner. 🌟 How the Workflow Works 🔗 Input Video ID: The user provides a YouTube video ID as input to the workflow. 📄 Data Retrieval: The workflow fetches essential details about the video (e.g., title, description, upload date) and retrieves its transcript using YouTube's Data API and additional tools for transcript extraction. 🤖 AI Agent Interaction: The extracted details and transcript are processed by an AI-powered agent. Users can then ask questions or engage in a conversation with the agent about the video's content, such as: Summarizing the transcript. Analyzing key points. Clarifying specific sections. 💬 Dynamic Responses: The AI agent uses natural language processing (NLP) to generate contextual and accurate responses based on the video data, ensuring a smooth and intuitive interaction. 🚀 Use Cases 📊 Content Analysis**: Quickly an
#️⃣Nostr #damus AI Powered Reporting + Gmail + Telegram
The n8n Nostr Community Node is a tool that integrates Nostr functionality into n8n workflows, allowing users to interact with the Nostr protocol seamlessly. It provides both read and write capabilities and can be used for various automation tasks. Disclaimer This node is ideal for self-hosted n8n setups, as ++community nodes are not supported on n8n cloud++. It opens up exciting possibilities for integrating workflows with the decentralized Nostr protocol. n8n Community Node for Nostr n8n-nodes-nostrobots Features Write Operations**: Send notes and events (kind1) to the Nostr network. Read Operations**: Fetch events based on criteria such as event ID, public key, hashtags, mentions, or search terms. Utility Functions**: Convert events into different formats like naddr or nevent and handle key transformations between bech32 and hex formats. Trigger Events**: Monitor the Nostr network for specific mentions or events and trigger workflows automatically. Use Cases Automating note posting without exposing private keys. Setting up notifications for mentions or specific events. Creating bots or AI assistants that respond to mentions on Nostr. Installation Install n8n on your system. Add
Fetch Keyword From Google Sheet and Classify Them Using AI
Who is this template for This template is for marketers, SEO specialists, or content managers who need to analyze keywords to identify which ones contain references to a specific area or topic, in this case – IT software, services, tools, or apps. Use case Automating the process of scanning a large list of keywords to determine if they reference known IT products or services (like ServiceNow, Salesforce, etc.), and updating a Google Sheet with this classification. This helps in categorizing keywords for targeted SEO campaigns, content creation, or market analysis. How this workflow works Fetches keyword data from a Google Sheet Processes keywords in batches to prevent rate limiting Uses an AI agent (OpenAI) to analyze each keyword and determine if it contains a reference to an IT service/software Updates the original Google Sheet with the results in a "Service?" column Continues processing until all keywords are analyzed Set up steps Connect your Google Sheets account credentials Set the Google Sheet document ID (currently using "Copy of Sheet1 1") Configure the OpenAI API credentials for the AI agent Adjust the batch size (currently 6) if needed based on your API rate limits Ensur
S🌐🪛 AI Agent Chatbot with Jina.ai Webpage Scraper
The 🌐🤖 AI Agent Chatbot with Jina.ai Webpage Scraper workflow is a powerful automation designed to integrate real-time web scraping capabilities into an AI-driven chatbot. Here's how it works and why it's important: How It Works 💬 Chat Trigger: The workflow begins when a user sends a chat message, triggering the "When chat message received" node. 🧠 AI Agent Processing: The input is passed to the "Jina.ai Web Scraping Agent," which uses advanced AI logic to interpret the user’s query and determine the information needed. 🌐 Web Scraping: The agent utilizes the "HTTP Request" node to scrape real-time data from a user-provided URL, enabling the chatbot to fetch and analyze live website content. 🗂️ Memory Management: The "Window Buffer Memory" node ensures context retention by storing and managing conversational history, allowing for seamless interactions. 🤖 Language Model Integration: The scraped data is processed using the "gpt-4o-mini" language model, which generates clear, accurate, and contextually relevant responses for the user. Why It's Cool ⏱️ Real-Time Information Retrieval**: This workflow empowers users to access up-to-date web content directly through a chatbot, elim
🤖🧑💻 AI Agent for Top n8n Creators Leaderboard Reporting
This n8n workflow is designed to automate the aggregation, processing, and reporting of community statistics related to n8n creators and workflows. Its primary purpose is to generate insightful reports that highlight top contributors, popular workflows, and key trends within the n8n ecosystem. Here's how it works and why it's important: How It Works Data Retrieval: The workflow fetches JSON data files from a GitHub repository containing statistics about creators and workflows. It uses HTTP requests to access these files dynamically based on pre-defined global variables. Data Processing: The data is parsed into separate streams for creators and workflows. It processes the data to identify key metrics such as unique weekly and monthly inserters/visitors. Ranking and Filtering: The workflow sorts creators by their weekly inserts and workflows by their popularity. It selects the top 10 creators and top 50 workflows for detailed analysis. Report Generation: Using AI tools like GPT-4 or Google Gemini, the workflow generates a Markdown report summarizing trends, contributors, and workflow statistics. The report includes tables with detailed metrics (e.g., unique visitors, inserters) and i
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🔥📈🤖 AI Agent for n8n Creators Leaderboard - Find Popular Workflows
n8n Creators Leaderboard Workflow Why Use This Workflow? The n8n Creators Leaderboard Workflow is a powerful tool for analyzing and presenting detailed statistics about workflow creators and their contributions within the n8n community. It provides users with actionable insights into popular workflows, community trends, and top contributors, all while automating the process of data retrieval and report generation. Benefits Discover Popular Workflows**: Identify workflows with the most unique visitors and inserters (weekly and monthly). Understand Community Trends**: Gain insights into what workflows are resonating with the community. Recognize Top Contributors**: Highlight impactful creators to foster collaboration and inspiration. Save Time with Automation**: Automates data fetching, processing, and reporting for efficiency. Use Cases For Workflow Creators**: Track performance metrics of your workflows to optimize them for better engagement. For Community Managers**: Identify trends and recognize top contributors to improve community resources. For New Users**: Explore popular workflows as inspiration for building your own automations. How It Works This workflow aggregates data fr
SChat with your event schedule from Google Sheets in Telegram
What it is Chat with your event schedule from Google Sheets in Telegram: "When is the next meetup?" "How many events are there next month?" "Who presented most often?" "Which future meetups have no presenters yet?" This workflow lets you chat with a telegram bot about past, present and future events that are scheduled in a Google Spreadsheet. (Info: This proof-of-concept was created as a demo for a hackathon of an AI & Developer Meetup in Da Nang (Vietnam) that uses a telegram group to organize) Who it is for If you want an easy way for your audience to get information about your events, you can us this workflow for the same purpose, or easily adapt it to your needs and different use-cases where you want to query smaller amounts of tabular data in natural language. How it works Upon getting triggered by a chat message to a telegram bot, the schedule of meetups is retrieved from Google Spreadsheets, converted into a markdown table syntax and fed into the system prompt of an LLM (we're using OpenRouter in this example), whose output is posted back as answer into the same telegram chat. Setup steps TO REVIEWING IN ACTION As the reviewer of this workflow, you can temporarily use it via
SAI Agent with Ollama for current weather and wiki
This workflow template demonstrates how to create an AI-powered agent that provides users with current weather information and Wikipedia summaries. By integrating n8n with Ollama's local Large Language Models (LLMs), this template offers a seamless and privacy-conscious solution for real-time data retrieval and summarization. Who is this for? Developers and Enthusiasts: Individuals interested in building AI-driven workflows without relying on external APIs. Privacy-Conscious Users: Those who prefer processing data locally to maintain control over their information. Educators and Students: Learners seeking hands-on experience with AI integrations and workflow automation. What problem does this workflow solve? Accessing up-to-date weather information and concise Wikipedia summaries typically requires multiple API calls to external services, which can raise privacy concerns and incur costs. This workflow addresses these issues by utilizing Ollama's self-hosted LLMs within n8n, enabling users to retrieve and process information locally. What this workflow does: User Input Capture: Begins with a chat interface where users can input queries. AI Processing: The input is sent to an AI Agen
BCWHacker News Job Listing Scraper and Parser
This automated workflow scrapes and processes the monthly "Who is Hiring" thread from Hacker News, transforming raw job listings into structured data for analysis or integration with other systems. Perfect for job seekers, recruiters, or anyone looking to monitor tech job market trends. How it works Automatically fetches the latest "Who is Hiring" thread from Hacker News Extracts and cleans relevant job posting data using the HN API Splits and processes individual job listings into structured format Parses key information like location, role, requirements, and company details Outputs clean, structured data ready for analysis or export Set up steps Configure API access to [Hacker News](https://github.com/HackerNews/API ) (no authentication required) Follow the steps to get your cURL command from https://hn.algolia.com/ Set up desired output format (JSON structured data or custom format) Optional: Configure additional parsing rules for specific job listing information Optional: Set up integration with preferred storage or analysis tools The workflow transforms unstructured job listings into clean, structured data following this pattern: Input: Raw HN thread comments Process: Extract,