# templates

name: Turn BBC News Articles into Podcasts using Hugging Face and Google Gemini
author_name: Onur
author_username: onurpolat05
categories: []
created_at: 2025-02-22T07:58:58.336Z
updated_at: 2025-02-22T07:58:58.336Z
url: https://n8n.io/workflows/2972
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  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 n8n instance.
  Basic understanding of n8n workflows (no coding required).
  API credentials for Gemini and a Hugging Face account with an access token.

  What problem does it solve?

  This workflow eliminates the manual effort involved in creating podcasts from news articles. It automates the entire process, from fetching and filtering news to generating the final audio file.

  What are the benefits?

  Time-saving:** Create podcasts in minutes, not hours.
  Easy to use:** No coding or technical skills required.
  Customizable:** Adapt the workflow to your specific needs and preferences.
  Cost-effective:** Leverage free or low-cost services like Gemini and Hugging Face.

  How does it work?

  The workflow fetches news articles from the BBC website.
  It filters articles based on their suitability for a podcast.
  It extracts the full content of the selected articles.
  It uses Gemini LLM to create a podcast script.
  It converts the script to speech using Hugging Face's text-to-speech model.
  The final podcast audio is ready for use.

  Nodes in the Workflow

  Fetch BBC News Page: Retrieves the main BBC News page.
  News Classifier: Categorizes news articles using Gemini LLM.
  Fetch BBC News Detail: Extracts detailed content from suitable articles.
  Basic Podcast LLM Chain: Generates a podcast script using Gemini LLM.
  HTTP Request: Converts the script to speech using Hugging Face.

  Add Story

  I'm excited to share this workflow with the n8n community and help content creators and students easily produce engaging podcasts!

  Additional Tips

  Explore the n8n documentation and community resources for more advanced customization options.
  Experiment with different filtering criteria and LLM prompts to achieve your desired podcast style.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.html","n8n-nodes-base.html","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.html","n8n-nodes-base.filter","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.textClassifier","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.limit","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
  [encoded data, 6312 characters]

metadata_json:
  {"categories":["content-creation","media-generation","automation","integration","news-aggregation"],"complexity":"medium","use_cases":["Convert news articles into podcast episodes","Repurpose written content as audio for accessibility","Quickly generate audio summaries for students or researchers","Automate content pipeline for podcasters or news curators"],"estimated_setup_minutes":30,"required_services":["n8n instance","Google Gemini (LLM) API credentials","Hugging Face account + access token (TTS model)","Access to BBC News (public website)"],"key_features":["Fetches and parses BBC News pages","Filters and classifies articles via Gemini LLM","Extracts full article content","Generates podcast-style scripts with Gemini","Converts scripts to speech using Hugging Face TTS via HTTP request node"],"target_audience":["Content creators","Podcasters","Students and educators creating audio content for projects or assignments`,`Non-technical users who want no-code automation"]}


name: Bitrix24 Task Form Widget Application Workflow with Webhook Integration
author_name: Ferenc Erb
author_username: fefehun
categories: []
created_at: 2025-02-22T08:44:44.327Z
updated_at: 2025-02-22T08:44:44.327Z
url: https://n8n.io/workflows/2974
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Use Case
  Extend Bitrix24 tasks with custom widgets that display relevant task information and enable seamless interaction through a custom tab interface.

  What This Workflow Does
  Processes incoming webhook requests from Bitrix24 task interfaces
  Handles authentication and secure token validation
  Manages application installation and placement registration
  Displays task data in a custom formatted view
  Stores and retrieves configuration settings persistently
  Provides user-friendly HTML interfaces for task information

  Setup Instructions
  Configure Bitrix24 webhook endpoints for the task widget
  Set up authentication credentials in your Bitrix24 account
  Install the application and register the task view tab placement
  Customize the task data display format as needed
  Deploy and test the application functionality within Bitrix24 tasks

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.respondToWebhook","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.readWriteFile","n8n-nodes-base.set","n8n-nodes-base.convertToFile","n8n-nodes-base.readWriteFile","n8n-nodes-base.if","n8n-nodes-base.respondToWebhook","n8n-nodes-base.merge","n8n-nodes-base.extractFromFile","n8n-nodes-base.merge"]

workflow_json_compressed:
  [encoded data, 5916 characters]

metadata_json:
  {"categories":["integration","automation","CRM"],"complexity":"complex","use_cases":["Add a custom task widget/tab inside Bitrix24 to display and interact with task data","Process and respond to Bitrix24 webhook events for task interfaces","Handle app installation and placement registration within Bitrix24","Persist and retrieve configuration or token data for the widget","Render user-friendly HTML views for tasks inside Bitrix24"],"estimated_setup_minutes":45,"required_services":["Bitrix24 account with app credentials (app installation/placement access)","Public HTTPS endpoint for n8n webhooks (or tunneling tool like ngrok)","n8n instance with file-access (or other persistent storage)","Optional: external storage/API if you prefer not to use local file system"],"key_features":["Receive and process Bitrix24 task webhooks","Authenticate and validate tokens/requests from Bitrix24","Manage app installation and register task view placements","Custom HTML task view rendering","Persistent configuration via read/write file nodes or storage nodes"],"target_audience":["Developers building Bitrix24 extensions","CRM administrators customizing Bitrix24 task UI","System integrators automating CRM workflows"]}


name: Build Your Own Counseling Chatbot on LINE to Support Mental Health Conversations
author_name: lin@davoy.tech
author_username: linlinmhee
categories: []
created_at: 2025-02-22T09:35:59.969Z
updated_at: 2025-02-22T09:35:59.969Z
url: https://n8n.io/workflows/2975
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:31
description:
  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 low-cost counseling services to underserved communities.

  How this work?
  Line Webhook to receive new message
  Send loading animation in Line
  Check if the input is text or not
  Send the text as prompt in chat model (GPT 4o)
  Reply the message to user (you'll need  'edit field' to format it before reply)

  Pre-Requisites
  You have access to the LINE Developers Console.
  An Azure OpenAI account with necessary credentials.

  Set-up
  To receive messages from LINE, configure your webhook:
  Set up a webhook in  LINE Developer Console.
  Copy the Webhook URL from the Line Chatbot node and paste it into the LINE Console.
  Ensure to remove any 'test' part when moving to production.
  The loading animation reassures users that the system is processing their request.
  Authorize using header authorization
  Message Handling
  Use the Check Message Type IsText? node to verify if the incoming message is text.
  If the message type is text, proceed with ChatGPT processing; otherwise, send a reply indicating non-text inputs are not supported.
  AI Agent Configuration
  Define the system message within the AI Agent node to guide the conversation based on desired interaction principles.
  Connect the Azure OpenAI Chat Model to the AI Agent.
  Formatting Responses
  Ensure responses are properly formatted before sending them back to the user.
  Reply Message
  Use the ReplyMessage - Line node to send the formatted response.
  Ensure proper header authorization using Bearer tokens.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set"]

workflow_json_compressed:
  [encoded data, 6020 characters]

metadata_json:
  {"categories":["integration","chatbot","mental health","automation"],"complexity":"medium","use_cases":["24/7 empathetic counseling chatbot on LINE","Automated mental health triage and resources","Extending therapist services outside sessions","Nonprofit/educational mental-health outreach","Proof-of-concept for AI-powered messaging agents"],"estimated_setup_minutes":45,"required_services":["LINE Developers Console (LINE webhook & messaging API)","Azure OpenAI (GPT-4 / GPT-4o access and credentials)","n8n instance or similar workflow host with public HTTPS endpoint"],"key_features":["LINE webhook integration to receive incoming messages","Message-type checking (text vs non-text) and branching","Loading animation to acknowledge user input","AI Agent node with configurable system prompt","Azure OpenAI chat model (GPT-4/GPT-4o) for responses generation"],"target_audience":["Developers integrating AI chatbots into LINE","Counselors & therapists expanding digital support","Businesses/organizations offering mental-health tools to users"]}


name: Automatically Create YouTube Metadata with AI
author_name: Amjid Ali
author_username: amjid
categories: []
created_at: 2025-02-22T14:11:44.009Z
updated_at: 2025-02-22T14:11:44.009Z
url: https://n8n.io/workflows/2976
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:31
description:
  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 a designated Google Docs file.

  AI-Powered Metadata Generation
  The AI agent generates the video title, description, tags, hashtags, and call-to-action elements.

  Metadata Formatting and Update
  The generated metadata is structured and directly updated on YouTube.

  Confirmation
  A success message is displayed upon completion of the update process.

  Setup and Configuration

  Deploying the Workflow
  Deploy the workflow in n8n and ensure all integrations are properly set up.

  Configuring Integrations
  Google Docs:** Configure credentials to retrieve affiliate and promotional links.
  OpenAI (GPT-4):** Set up credentials for AI-powered metadata generation.
  YouTube API:** Enter your API credentials to enable automatic video updates.

  User Input Requirements
  Provide a valid YouTube video link and its corresponding transcript. Optionally, include focus keywords to further enhance metadata accuracy.

  Ideal For

  YouTube Content Creators:** Automate video descriptions and boost SEO.
  Digital Marketers:** Enhance content for improved search rankings and audience engagement.
  Affiliate Marketers:** Simplify the insertion of promotional and affiliate links.
  AI & Automation Enthusiasts:** Explore the integration of AI into automated workflows.

  Additional Resources

  For further guidance, refer to the tutorial video on this workflow. More courses and resources are available on the SyncBricks website. For support or inquiries, contact Amjid Ali at info@syncbricks.com. You can also support this work via PayPal donations and subscribe for additional AI and automation workflows.

  Watch the Tutorial:** YouTube Video on This Workflow
  More Courses & Resources:**
    SyncBricks LMS
    Full Course on ERPNext & AI Automation
  Connect:**
    Email: info@syncbricks.com
    Website: SyncBricks
    YouTube: SyncBricks Channel
    LinkedIn: Amjid Ali
  Support & Subscribe:**
    Donate via PayPal
    Subscribe for More AI & Automation Workflows

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.googleDocsTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.youTube","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.form","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4968 characters]

metadata_json:
  {"categories":["automation","content-creation","marketing","AI integration","video-production"],"complexity":"medium","use_cases":["Generate SEO-optimized YouTube titles, descriptions, tags and hashtags","Automate insertion of affiliate/promotional links into video descriptions","Streamline metadata updates for published YouTube videos","Customize metadata using AI prompts for niche audiences"],"estimated_setup_minutes":30,"required_services":["Google Docs (for link retrieval)","OpenAI GPT-4 (AI metadata generation)","YouTube Data API (video updates)"],"key_features":["Automated metadata generation from transcripts using GPT-4","SEO and engagement optimization (keyword-rich titles/descriptions/tags)","Retrieves affiliate/promotional links from Google Docs","Directly updates YouTube video details via API","Customizable AI prompt for niche tailoring (prompt editing)"],"target_audience":["YouTube content creators","Digital marketers","Affiliate marketers/content monetizers」「AI & automation enthusiasts"]}


name: Line Chatbot Handling AI Responses with Groq and Llama3
author_name: Sirisak Chantanate
author_username: openmymai
categories: []
created_at: 2025-02-22T17:00:37.407Z
updated_at: 2025-02-22T17:00:37.407Z
url: https://n8n.io/workflows/2977
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Workflow overview:
  This workflow is designed for dynamic and intelligent conversational capabilities. It incorporates Meta's llama3.3-versatile model for personal assistant. There are no issues when sending simple text to the LINE reply API, so in this workflow you can see how to handle large and complex text sending from AI chat without any errors.

  Workflow description:
  User uses Line Messaging API to send message to the chatbot, create line business ID from here: Line Business
  Set the message from Step 1 to the proper value
  Send the message to process at Groq using API key that we have created from Groq
  Send the reply message from AI Agent back to Line Messaging API account

  Key Features:

  Utilizes Meta's llama 3.3 model for robust conversational capabilities
  Handles large and complex text interactions with ease, ensuring reliable connections to LINE Messaging API
  Demonstrates effective strategies for processing and responding to large and complex text inputs from AI chat

  To use this template, you need to be on n8n version 1.79.0 or later.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["integration","automation","conversational AI"],"complexity":"medium","use_cases":["LINE-based chatbot / virtual assistant","Customer support and messaging automation","Handling and replying to large/complex AI-generated responses","Prototyping AI conversational flows using Llama 3.3"],"estimated_setup_minutes":20,"required_services":["LINE Messaging API (Line Business account / Channel access token and secret)","Groq API (API key and access to Meta Llama 3.3 model via Groq)","n8n version 1.79.0 or later"],"key_features":["Integrates LINE Messaging API webhooks and reply API","Uses Groq-hosted Meta Llama 3.3 model for AI responses","Handles large and complex AI-generated text safely when sending to LINE","Demonstrates message preparation and HTTP request handling in n8n","Minimal node set (HTTP/Webhooks, set, stickyNote) for clarity"],"target_audience":["Developers","Chatbot builders / conversational AI engineers","Product managers evaluating LINE integrations with LLMs"]}


name: Analyze Reddit Posts with AI to Identify Business Opportunities
author_name: Alex Huang
author_username: tao
categories: []
created_at: 2025-02-22T17:43:37.472Z
updated_at: 2025-02-22T17:43:37.472Z
url: https://n8n.io/workflows/2978
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  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 automatic Slack alerts for urgent opportunities
     Generate draft business plans using AI Document Writer

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.sentimentAnalysis","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.chainSummarization","n8n-nodes-base.merge","n8n-nodes-base.googleSheets","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.reddit","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4908 characters]

metadata_json:
  {"categories":["automation","integration","AI/ML","market research","data processing"],"complexity":"medium","use_cases":["Automated market research","Discover business ideas from Reddit","Trend monitoring and alerting","Filtering and prioritizing user pain points","Generating scored opportunity reports for decisions','Conducting sentiment analysis on community discussions"],"estimated_setup_minutes":20,"required_services":["Reddit (API/credentials)","Google Sheets (Google account)","OpenAI (GPT-4)"],"key_features":["Automated collection of trending Reddit discussions","GPT-4 analysis to surface viable business opportunities","Smart filters to exclude low-value content","Sentiment analysis to identify unmet customer needs","Opportunity scoring and prioritization using custom criteria','Export structured, scored reports to Google Sheets','Configurable target subreddits and scoring thresholds','Optional integrations: Slack alerts and AI-generated draft business plans"],"target_audience":["Entrepreneurs","Startup founders","Product managers','Market researchers','Growth teams','Business analysts"]}


name: Bulk File Upload to Google Drive with Folder Management
author_name: Julian Kaiser
author_username: jksr
categories: []
created_at: 2025-02-22T18:31:11.835Z
updated_at: 2025-02-22T18:31:11.835Z
url: https://n8n.io/workflows/2979
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:31
description:
  🗂️ Bulk File Upload to Google Drive with Folder Management

  How it works
  User submits files and target folder name via form
  Workflow checks if folder exists in Drive
  Creates folder if needed or uses existing one
  Processes and uploads all files maintaining structure

  Set up steps (Est. 10-15 mins)
  Set up Google Drive credentials in n8n
  Replace parent folder ID in search query with your Drive folder ID
  Configure form node with:
     Multiple file upload field
     Folder name text field
  Test workflow with sample files

  💡 Detailed configuration steps and patterns are documented in sticky notes within the workflow.

  Perfect for:
  Bulk file organization
  Automated Drive folder management
  File upload automation
  Maintaining consistent file structures

nodes_used:
  ["n8n-nodes-base.formTrigger","n8n-nodes-base.set","n8n-nodes-base.googleDrive","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["integration","file management","automation","cloud storage"],"complexity":"medium","use_cases":["Bulk file organization and upload to Google Drive","Automated Drive folder creation and management","Form-driven file submissions and processing","Maintaining consistent folder/file structures during batch uploads"],"estimated_setup_minutes":12,"required_services":["Google Drive (Google account / Drive API access)"],"key_features":["Checks if target folder exists and creates it if needed","Processes and uploads multiple files in bulk","Maintains original file structure during upload","Integrates with a form node for user submissions","Configurable logic via code and sticky notes for customization"],"target_audience":["Developers","IT / Operations teams","Content managers and creators\",\"Marketing teams\",\"Small business owners"]}


name: Nightly Discord Channel Cleanup
author_name: Viktor
author_username: qxuken
categories: []
created_at: 2025-02-22T20:09:12.911Z
updated_at: 2025-02-22T20:09:12.911Z
url: https://n8n.io/workflows/2980
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Nightly Discord Channel Cleanup
  This workflow runs every day at 9:00 p.m. and:
  Retrieves all Discord channels using your provided credentials.
  Pauses briefly to respect Discord API rate limits.
  Loops through each channel and fetches messages.
  Filters out messages older than seven days.
  Deletes those older messages, again pausing to stay within deletion rate limits.

  By setting up this workflow on a schedule, you can automatically keep Discord channels tidy and compliant with retention policies.
  👨‍🎤 Setup
  Add your Discord credentials
  Change the server in each Discord node to the correct one
  Click the Test Workflow button
  Activate the workflow to run on a schedule

nodes_used:
  ["n8n-nodes-base.splitInBatches","n8n-nodes-base.splitInBatches","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.discord","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.discord","n8n-nodes-base.discord","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","moderation","community management","integration"],"complexity":"medium","use_cases":["Automatically delete messages older than a retention period","Keep Discord channels tidy and within retention/compliance policies","Automate routine community moderation/cleanup","Periodic removal of stale content across multiple channels"],"estimated_setup_minutes":10,"required_services":["Discord (bot or user credentials with appropriate permissions - Read Message History, Manage Messages/Delete Messages)","n8n instance (cloud or self-hosted) with internet access"],"key_features":["Scheduled daily run (9:00 PM) to perform cleanup","Fetches all channels for a specified server/guild","Batch processing with pauses to respect Discord API rate limits","Filters messages older than seven days","Deletes filtered messages automatically across channels"],"target_audience":["Discord server administrators","Community moderators","DevOps/Automation engineers responsible for chat retention policies"]}


name: ✍️🌄 Your First Wordpress + AI Content Creator - Quick Start
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-23T01:20:13.550Z
updated_at: 2025-02-23T01:20:13.550Z
url: https://n8n.io/workflows/2981
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  ✍️🌄 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 connection
  Configure OpenAI API access
  Set up Google Drive integration
  Add Telegram bot credentials for notifications

  Customize Content Parameters ⚙️
  Adjust reading level prompts as needed
  Modify image generation settings
  Set WordPress post parameters

  Test and Deploy 🚀
  Run a test with a sample topic
  Verify all reading level versions
  Check WordPress draft creation
  Confirm notification system


  This workflow is perfect for content creators who need to maintain a consistent blog presence while catering to different audience reading levels. It's especially useful for educational content, news sites, or any platform that needs to communicate complex topics to diverse audiences.

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleDrive","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.wordpress","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.markdown","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8396 characters]

metadata_json:
  {"categories":["automation","content creation","AI","integration","CMS"],"complexity":"medium","use_cases":["Automated blog post generation","Creating multi-reading-level content (Grade 2, 5, 9)","Educational content adaptation","Generating and uploading featured images","Backing up drafts to Google Drive and sending notifications"],"estimated_setup_minutes":45,"required_services":["WordPress (REST API access)","OpenAI (or compatible LLM API)","Google Drive","Telegram (bot for notifications)","Pollinations.ai (image generation)"],"key_features":["AI-generated structured HTML blog posts","Automatic rewrites for multiple reading levels","Creates WordPress draft with Grade 9 version","Generates and uploads featured images","Saves draft backups to Google Drive automatically"],"target_audience":["Content creators","Bloggers","Educators and instructional designers"]}


name: 🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-23T01:59:29.690Z
updated_at: 2025-02-23T01:59:29.690Z
url: https://n8n.io/workflows/2982
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 19:51:23
description:
  🤖 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 Key to the 'Delete Qdrant Points by File ID' node

  Configure Document Sources:
     Set Google Drive folder ID
     Define Qdrant collection name
     Set up document processing parameters

  Test and Deploy:
     Verify document processing
     Test chat functionality
     Confirm vector store operations
     Check notification system


  This workflow is ideal for organizations needing to create intelligent chatbots that can access and understand large document repositories while maintaining context and providing accurate responses through RAG technology.

nodes_used:
  ["@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterTokenSplitter","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.extractFromFile","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.code","n8n-nodes-base.set","n8n-nodes-base.summarize","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDocs","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 10536 characters]

metadata_json:
  {"categories":["automation","integration","AI/ML","knowledge management"],"complexity":"complex","use_cases":["Enterprise knowledge-base chatbot","Internal document assistant for employees","Customer support & ticket augmentation","Research/document retrieval assistant","Compliance and audit document lookup"],"estimated_setup_minutes":90,"required_services":["Google Drive","Google Docs","Google Gemini (AI)","Qdrant (vector DB)","Telegram (bot for notifications)","OpenAI API (embeddings / delete operations)"],"key_features":["RAG-powered conversational interface","Document ingestion, splitting and vectorization","Metadata extraction for enhanced search","Qdrant vector storage and retrieval","Google Gemini for response generation (LM) and OpenAI embeddings support optionally used for vectors/ops during deletion node setup)"],"target_audience":["developers","data engineers","AI/ML engineers building retrieval systems or chatbots`,`knowledge managers and documentation teams`,`customer support and product teams"]}


name: ✨😃Automated Workflow Backups to Google Drive
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-23T04:57:19.609Z
updated_at: 2025-02-23T04:57:19.609Z
url: https://n8n.io/workflows/2983
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  ✨😃 Automated Workflow Backups to Google Drive

  This workflow automates the process of backing up your n8n workflows to Google Drive daily. It creates timestamped folders, saves workflows as JSON files, and manages old backups by retaining only the most recent seven days of data. Notifications are sent via Telegram to keep you informed of the backup status.

  How It Works

  Backup Creation Process 🗂️
  Triggering Backups**: The workflow starts with either a manual trigger or a scheduled trigger that runs daily.
  Folder Creation**: Creates a new folder in Google Drive with a timestamped name (e.g., n8n-Workflow-Backups-YYYY-MM-DD).
  Workflow Retrieval**: Fetches all workflows from your n8n instance.
  File Conversion**: Converts each workflow into a JSON file for storage.
  File Upload**: Saves the JSON files into the newly created Google Drive folder.

  Backup Management 🔄
  Folder Search**: Searches for existing backup folders in Google Drive with names matching n8n-Workflow-Backups.
  Retention Policy**: Identifies folders older than seven days using a custom JavaScript function and deletes them permanently to free up space.

  Notifications 📲
  Telegram Alerts**: Sends a message via Telegram once the backup process is complete, including the folder name and a link to access it in Google Drive.

  Setup Steps

  API Configuration 🔑
  Google Drive Integration:
     Set up Google Drive OAuth2 credentials in n8n.
     Specify the root folder or desired location for backups.
  n8n API Access:
     Configure n8n API credentials to allow fetching workflows.
  Telegram Notifications:
     Add your Telegram bot credentials and chat ID for notification delivery.

  Workflow Customization ⚙️
  Define the schedule for automatic backups (e.g., daily at midnight).
  Adjust the retention period if you need more or fewer days of backups.
  Customize the Telegram message format as needed.

  Testing & Deployment 🚀
  Run the workflow manually to verify folder creation and file uploads.
  Check that old folders are deleted correctly after seven days.
  Confirm Telegram notifications are sent with accurate details.

  Use Case Scenarios
  This workflow is perfect for teams or individuals who want to ensure their n8n workflows are securely backed up and organized. It is especially useful for:
  Protecting against accidental data loss.
  Automating routine administrative tasks.


  By combining automated backups, retention management, and real-time notifications, this workflow ensures your n8n workflows are always safe and accessible!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.set","n8n-nodes-base.n8n","n8n-nodes-base.limit","n8n-nodes-base.convertToFile","n8n-nodes-base.googleDrive","n8n-nodes-base.noOp","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5084 characters]

metadata_json:
  {"categories":["automation","backup","integration","cloud storage","notifications"],"complexity":"medium","use_cases":["Automated daily backups of n8n workflows","Disaster recovery and version preservation","Automated retention cleanup of old backups","Real-time backup status notifications"],"estimated_setup_minutes":20,"required_services":["Google Drive (OAuth2)","n8n API access","Telegram Bot API"],"key_features":["Scheduled (daily) backup trigger with manual run option","Creates timestamped folders in Google Drive","Exports workflows as JSON files and uploads them","Retention policy to delete backups older than 7 days","Telegram notifications with folder link and status"],"target_audience":["n8n users","DevOps / SREs","Automation engineers / platform owners\",\"Small teams managing n8n instances"]}


name: AI-Powered Chatbot Workflow with MySQL Database Integration
author_name: Gegenfeld
author_username: gegenfeld
categories: []
created_at: 2025-02-23T06:09:53.667Z
updated_at: 2025-02-23T06:09:53.667Z
url: https://n8n.io/workflows/2985
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:31
description:
  AI-Powered Chatbot Workflow with MySQL Integration

  This guide shows you how to deploy a chatbot that lets you query your database using natural language. You will build a system that accepts chat messages, retains conversation history, constructs dynamic SQL queries, and returns responses generated by an AI model. By following these instructions, you will have a working solution that integrates n8n’s AI Agent capabilities with MySQL.

  Prerequisites

  Before you begin, ensure that you have the following:

  An active n8n instance (self-hosted or cloud) running version 1.50.0 or later.
  Valid MySQL credentials configured in n8n.
  API credentials for the Groq Chat Model (or your preferred AI language model).
  Basic familiarity with SQL and n8n node concepts such as chat triggers and memory buffers.
  Access to the n8n Docs on AI Agents for further reference.

  Workflow Setup

  1. Chat Interface & Trigger

  When Chat Message Received**  
    This node listens for incoming chat messages via a webhook. When a message arrives, it triggers the workflow immediately.

  2. Conversation Memory

  Chat History**  
    This memory buffer node stores the last 10 interactions. It supplies conversation context to the AI Agent, ensuring that responses consider previous messages.

  3. AI Agent Core

  AI Agent (Tools Agent)**  
    The AI Agent node orchestrates the conversation by receiving the chat input and conversation history. It dynamically generates SQL queries based on your requests and coordinates calls to external tools (such as MySQL nodes).

  4. Database Interactions

  MySQL Node**  
    This node executes the SQL query generated by the AI Agent. You reference the query using an expression (e.g., {{$node["AI Agent"].json.sql_query}}), allowing the agent’s output to control data retrieval.

  MySQL Schema Node**  
    This node retrieves a list of base tables from your MySQL database (excluding system schemas). The agent uses this information to understand the available tables.

  MySQL Definition Node**  
    This node fetches detailed metadata (such as column names, data types, and relationships) for a specific table. The table and schema names are supplied dynamically by the AI Agent.

  5. Language Model Processing

  Groq Chat Model**  
    This node connects to the Groq Chat API to generate text completions. It processes the combined input (chat message, context, and data fetched from MySQL) and produces the final response.

  6. Guidance & Customization

  Sticky Notes**  
    These nodes provide guidance on:
    Switching the chat model if you wish to use another provider (e.g., OpenAI or Anthropic).
    Adjusting the maximum token count per interaction.
    Customizing the SQL queries and the context window size.
    
  They help you modify the workflow to suit your environment and requirements.

  Workflow Connections

  The Chat Trigger passes the incoming message to the AI Agent.
  The Chat History node supplies conversation context to the AI Agent.
  The AI Agent calls the MySQL nodes as external tools, generating and sending dynamic SQL queries.
  The Groq Chat Model processes the consolidated input from the agent and outputs the natural language response delivered to the user.

  Testing the Workflow

  Send a chat message using the chat interface.
  Observe how the AI Agent processes the input and generates a corresponding SQL query.
  Verify that the MySQL nodes execute the query and return data.
  Confirm that the Groq Chat Model produces a coherent natural language response.
  Refer to the sticky notes for guidance if you need to fine-tune any node settings.

  Next Steps and References

  Customize Your AI Model**  
    Replace the Groq Chat Model with another language model (such as the OpenAI Chat Model) by updating the node credentials and configuration.

  Enhance Memory Settings**  
    Adjust the Chat History node’s context window to retain more or fewer messages based on your needs.

  Modify SQL Queries**  
    Update the SQL queries in the MySQL nodes to match your specific database schema and desired data.

  Further Reading**  
    Consult the n8n Docs on AI Agents for additional details and examples to expand your workflow’s capabilities.

  Set Up a Website Chatbot**
    Copy & Paste and replace the placeholders in the following code to embed the chatbot into your personal or company's website: View in CodePen 🡥

  By following these steps, you will deploy a robust AI chatbot workflow that integrates with your MySQL database, allowing you to query data using natural language.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.mySqlTool","n8n-nodes-base.mySqlTool","n8n-nodes-base.mySqlTool","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGroq","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","AI/chatbots","data processing"],"complexity":"medium","use_cases":["Query MySQL databases using natural language","Build an interactive chatbot that returns DB-driven answers","Quick data lookups and ad-hoc reporting for analysts","Internal knowledge base or support assistant backed by DB records"],"estimated_setup_minutes":30,"required_services":["n8n (self-hosted or cloud) v1.50.0+","MySQL database with valid credentials","Groq Chat API (or alternative LLM provider such as OpenAI / Anthropic)","Webhook / chat frontend to send/receive messages"],"key_features":["Natural language → dynamic SQL generation via AI Agent","Conversation memory (windowed history) to preserve context","MySQL schema and table metadata inspection for safe query construction","LLM-based response generation (Groq Chat Model or substitute)","Configurable token limits and model switching guidance"],"target_audience":["Developers implementing conversational DB interfaces","Data analysts who want natural-language access to data","Product owners building embedded site chatbots tied to DBs"]}


name: All-in-One Telegram/Baserow AI Assistant 🤖🧠 Voice/Photo/Save Notes/Long Term Mem
author_name: Rod
author_username: xxbean-sproutxx
categories: []
created_at: 2025-02-23T09:02:25.572Z
updated_at: 2025-02-23T09:02:25.572Z
url: https://n8n.io/workflows/2986
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  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 buffers.  
     Long-Term Memory: When a message contains personal or noteworthy information, the assistant uses a dedicated tool to save this data as a long-term memory in Baserow.  
     Note-Taking: For specific instructions or reminders, the assistant saves concise notes in a separate Baserow table.  
     The AI agent follows defined rules to decide which details are saved as memories and which are saved as notes.

  Response Generation  
     After processing the message and updating memory/notes as needed, the AI agent crafts a contextual and personalized response.  
     The response is sent back to the user via Telegram, ensuring smooth and natural conversation flow.

  🚀 Key Features

  Multimodal Input:**  
    Seamlessly handles voice, photo (with captions), and text messages.

  Long-Term Memory & Note-Taking:**  
    Uses a Baserow database to store personal details and notes, enhancing conversational context over time.

  AI-Driven Contextual Responses:**  
    Leverages an AI agent to generate personalized, context-aware replies based on current input and past interactions.

  User Security & Validation:**  
    Incorporates validation steps to verify the user's Telegram ID before processing, ensuring secure and personalized interactions.

  Easy Baserow Setup:**  
    Comes with a clear setup guide and sample configurations to quickly integrate Baserow for managing memories and notes.

  🔧 Setup Guide

  Telegram Bot Setup:  
     Create your bot via BotFather and obtain the Bot Token.  
     Configure the Telegram webhook in n8n with your bot's token and URL.

  Baserow Database Configuration:  
     Memory Table:  
       Create a workspace titled "Memories and Notes".  
       Set up a table (e.g., "Memory Table") with at least two fields:  
         Memory (long text)  
         Date Added (US date format with time)  
     Notes Table:  
       Duplicate the Memory Table and rename it to "Notes Table".  
       Change the first field's name from "Memory" to "Notes".

  n8n Workflow Import & Configuration:  
     Import the workflow JSON into your n8n instance.  
     Update credentials for Telegram, Baserow, OpenAI, and PostgreSQL (for memory buffering) as needed.
     Adjust node settings if you need to customize AI agent prompts or memory management rules.

  Testing & Deployment:  
     Test your bot by sending various message types (text, voice, photo) to confirm that the workflow processes them correctly, updates Baserow, and returns the appropriate response.  
     Monitor logs to ensure that memory and note entries are correctly stored and retrieved.

  ✨ Example Interactions

  Voice Message Processing:**  
    User sends a voice note requesting a reminder.  
    Bot Response: "Thanks for your message! I've noted your reminder and saved it for future reference."

  Photo with Caption:**  
    User sends a photo with the caption "Save this recipe for dinner ideas."  
    Bot Response: "Got it! I've saved this recipe along with the caption for you."

  Text Message for Memory Saving:**  
    User: "I love hiking on weekends."  
    Bot Response: "Noted! I’ll remember your interest in hiking."

  Retrieving Information:**  
    User asks: "What notes do I have?"  
    Bot Response: "Here are your latest notes: [list of saved notes]."

  🛠️ Resources & Next Steps

  Telegram Bot Configuration:** Telegram BotFather Guide  
  n8n Documentation:** n8n Docs  
  Community Forums:** Join discussions and share your customizations!

  This workflow not only streamlines message processing but also empowers users with a personal AI assistant that remembers details over time. Customize the rules and responses further to fit your unique requirements and enjoy a more engaging, intelligent conversation experience on Telegram!

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.convertToFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.merge","n8n-nodes-base.telegram","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.memoryPostgresChat","n8n-nodes-base.baserowTool","n8n-nodes-base.baserowTool","n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.baserow","n8n-nodes-base.baserow","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","conversational AI","personal productivity","data storage"],"complexity":"complex","use_cases":["Personal AI assistant for Telegram","Long-term memory and note-taking","Multimodal message processing (voice/photo/text)","Automatic transcription and image analysis","Context-aware replies and reminders"],"estimated_setup_minutes":45,"required_services":["Telegram Bot API (BotFather)","Baserow (database for memories & notes)","OpenAI (GPT-4o-mini for agent & transcription)","PostgreSQL (conversation memory buffer)","n8n (workflow host/webhook endpoint)"],"key_features":["Handles voice, photo (with captions), and text messages","AI transcription for voice messages","AI image analysis for photos","Long-term memory storage in Baserow","Separate notes table for concise reminders/instructions"],"target_audience":["Developers/automation builders","Power users who want a personal assistant","Marketers and creators who save content/ideas to recall later"]}


name: Personal Portfolio CV Rag Chatbot - with Conversation Store and Email Summary
author_name: Sean Lon
author_username: seanlon
categories: []
created_at: 2025-02-23T09:02:59.165Z
updated_at: 2025-02-23T09:02:59.165Z
url: https://n8n.io/workflows/2987
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  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 frontend/backend interface to call the chat API (refer to the notes for details) .

  [optional] Use any frontend/backend interface to call the update chat history API (refer to the notes for details).

  3.Tracking Chat:

  Get daily automatic summaries of chat conversations.Format email conversations report as you like.

  You are ready to go!

nodes_used:
  ["@n8n/n8n-nodes-langchain.embeddingsGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.respondToWebhook","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.toolVectorStore","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.webhook","n8n-nodes-base.nocoDb","n8n-nodes-base.respondToWebhook","n8n-nodes-base.nocoDb","n8n-nodes-base.code","n8n-nodes-base.html","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["chatbot","knowledge management","integration","automation","data processing"],"complexity":"complex","use_cases":["Interactive personal portfolio / CV chatbot","RAG (retrieval-augmented generation) from uploaded resumes/CVs","Storing and tracking chat conversations for analytics or auditing","Daily email summaries / reporting of chat interactions","Embedding and vector database pipeline for QA over personal documents"],"estimated_setup_minutes":60,"required_services":["Google Drive (file upload trigger)","Google Gemini API (embeddings and chat LM)","Pinecone (vector store)","NocoDB (conversation storage / reporting)","Email provider or SMTP (for daily summaries)","n8n instance (to run workflow + webhooks)"],"key_features":["Automatic ingestion of CV/resume from Google Drive into a vector DB","Embeddings generation and RAG pipeline using Google Gemini + Pinecone","Chat API and chat-history API endpoints via HTTP/Webhooks","Conversation storage and tracking in NocoDB","Scheduled daily email summaries of conversations (automated reporting)"],"target_audience":["Developers building personal portfolio chatbots","Job-seekers wanting an interactive CV","Engineers implementing RAG workflows and conversation stores"]}


name: Get Daily Exercise Plan with Flex Message via LINE
author_name: lin@davoy.tech
author_username: linlinmhee
categories: []
created_at: 2025-02-23T10:17:56.432Z
updated_at: 2025-02-23T10:17:56.432Z
url: https://n8n.io/workflows/2988
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  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 Google Sheet structured as follows:

  PoseName : The name of the yoga pose.
  uri : The image URL representing the pose.
  url : A clickable link directing users to more information about the pose.

  Sample Data Layout
  Supine Angle
  https://example.com/SupineAngle-tn146.png
  https://example.com/pose/SupineAngle
  Warrior II
  https://example.com/WarriorII-tn146.png
  https://example.com/pose/WarriorII

  *Note : Ensure that you update the Google Sheet with your own data. Refer to this sample sheet for reference. *

  Scheduled Trigger
  The workflow is triggered daily at 21:30 (9:30 PM) Bangkok Time (Asia/Bangkok) . This ensures timely delivery of reminders to users, keeping them engaged with their yoga practice.

  Workflow Process
  Data Retrieval
  Node: Get PoseName
  Fetches yoga pose details from the specified range in the Google Sheet.
  Content Generation
  Node: WritePosesToday
  Utilizes Azure OpenAI to craft user-friendly text, complete with emojis and clear instructions.
  Node: RewritePosesToday
  Formats the AI-generated text specifically for Line messaging, ensuring compatibility and visual appeal.
  JSON Formatting
  Node: WriteJSONflex
  Generates JSON structures required for Line’s Flex Messages, enabling carousel displays of yoga pose images and links.
  Node: Fix JSON
  Ensures all JSON outputs are correctly formatted before being sent via Line.
  Message Delivery
  Node: Line Push with Flex Bubble
  Sends the final message, including both text and Flex Message carousels, directly to users via Line Push Messages.
  Logging Interactions
  Nodes: YogaLog & YogaLog2
  Logs each interaction back into Google Sheets to track which poses were sent and how often they appear, refining future recommendations.

  Setup Prerequisites
  Google Sheets Account : Set up a Google Sheet with the required structure and populate it with your yoga pose data.
  Line Developer Account : Create a Line channel to obtain necessary credentials for sending push messages.
  Azure OpenAI Account : Configure access to Azure OpenAI services for generating and formatting content.

  Intended Audience
  This workflow is ideal for:
  Yoga Instructors : Seeking to engage students with daily pose suggestions.
  Fitness Enthusiasts : Looking to maintain consistency in their yoga practice.
  Content Creators : Interested in automating personalized and visually appealing content distribution.
   

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheets","n8n-nodes-base.splitOut","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","@n8n/n8n-nodes-langchain.lmChatAzureOpenAi","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","notifications","content-generation","scheduling"],"complexity":"medium","use_cases":["Send daily yoga pose reminders","Deliver visually rich messages via LINE Flex Messages","Personalize content using AI-generated copy","Log interactions to refine future recommendations","Drive user engagement and retention"],"estimated_setup_minutes":45,"required_services":["n8n","Google Sheets","LINE Messaging API (Line channel)","Azure OpenAI (via Azure)"],"key_features":["Automated scheduled delivery (daily at 21:30 Asia/Bangkok)","AI-driven text generation and rewriting for friendly tone and emojis","Generates and validates JSON for LINE Flex Message carousels","Pulls pose data (name, image URL, link) from Google Sheets","Logs interactions back to Google Sheets for tracking and recommendations"],"target_audience":["Yoga instructors","Fitness enthusiasts","Content creators and community managers of wellness brands」「Developers / automation builders familiar with n8n"]}


name: Generate Text Images from the Free DummyJSON API Using the HTTP Request Node
author_name: Akram Kadri
author_username: akramkadri
nodes_used: ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.set"]
categories: []
created_at: 2025-02-23T22:19:30.985Z
updated_at: 2025-02-23T22:19:30.985Z
url: https://n8n.io/workflows/2990
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?

  This workflow template is ideal for marketers, designers, content creators, and developers who need to generate custom text-based images dynamically. Whether you want to create social media graphics, placeholder images, or text-based LinkedIn carousels, this workflow provides a simple, no-code solution using an API that requires no authentication.

  What problem does this workflow solve?

  Creating text-based images often requires design software or complex integrations with graphic tools. This workflow eliminates that hassle by allowing users to generate images with custom text, font styles, colors, and background colors using a simple HTTP request. It’s perfect for automating image generation without relying on external tools or manual effort.

  What this workflow does

  This workflow leverages an HTTP request to a free API that generates text-based images dynamically. Here's what it enables you to do:

  Define custom image text
  Set image dimensions (width x height)
  Choose a background color and text color using hex codes
  Select a font family and font size
  Specify the image format (PNG, JPG, or WebP)

  The generated image can be used immediately, making it ideal for automating content creation workflows.

  Setup

  Open the workflow in n8n.
  Modify the Set node to define your preferred image properties:
  text: The message displayed on the image.
  size: Image dimensions (e.g., 500x300 pixels).
  backgroundColor: Hex color code for the background.
  textColor: Hex color code for the text.
  fontFamily: Select from available font options (e.g., Pacifico, Ubuntu).
  fontSize: Define the text size.
  type: Choose the image format (PNG, JPG, or WebP).

  Execute the workflow to generate an image.
  The HTTP request returns the generated image, ready for use.

  How to customize this workflow

  1.     Adjust the Set node values to match your desired design.
  2.     Use dynamic data for text, allowing personalized images based on user input.
  3.     Automate image delivery by adding email or social media posting nodes.
  4.     Integrate this workflow into larger automation sequences, such as content marketing pipelines.

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metadata_json:
  {"categories":["automation","content-creation","image-processing","integration"],"complexity":"simple","use_cases":["Generate social media graphics automatically","Create placeholder images for designs or prototypes","Produce text-based images for LinkedIn carousels or posts","Personalized image generation (e.g., user-specific banners)","Automate image creation in content pipelines or marketing funnels"],"estimated_setup_minutes":5,"required_services":["DummyJSON free text-image HTTP API (no authentication)","n8n instance (with HTTP Request / Webhooks node)"],"key_features":["Generate images with custom text via a simple HTTP request","Configure image dimensions, background color, text color","Select font family and font size","Choose output format (PNG, JPG, WebP)","Supports dynamic text input for personalization or automation"],"target_audience":["marketers","designers","content creators / social media managers"]}


name: Automate Figma Versioning and Jira Updates with n8n Webhook Integration
author_name: omid dev
author_username: omiddev
categories: []
created_at: 2025-02-24T10:06:38.772Z
updated_at: 2025-02-24T10:06:38.772Z
url: https://n8n.io/workflows/2991
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  How It Works:
  This n8n template automates the process of tracking design changes in Figma and updating relevant Jira issues. The template is triggered when a new version is created in Figma via a custom plugin. Once the version is committed, the plugin sends the design details to an n8n workflow using a webhook.

  The workflow then performs the following actions:
  Fetches the Jira issue based on the provided issue link from Figma.
  Adds the design changes as a comment to the Jira issue.
  Updates the status of the Jira issue based on the provided task status (e.g., "In Progress", "Done").
  This streamlines the workflow, reducing the need for manual updates and ensuring that both the design team and developers have the latest design changes and task statuses in sync.

  How to Use It:
  Set up the Figma Plugin:

  Install the Figma Commit Plugin from GitHub.
  In the plugin, fill out the version name, design link, Jira issue link, and the task status.
  Commit the changes in Figma, which will trigger the webhook.

  Set Up the n8n Workflow:
  Import this template into your n8n instance.
  Connect the Figma Trigger node to capture version updates from Figma.
  Configure the Jira nodes to retrieve the issue and update the status/comment based on the data sent from the plugin.

  Automate:
  Once the version is committed in Figma, the workflow will automatically update the Jira issue and keep both your Figma design and Jira tasks in sync!
  By integrating Figma, Jira, and n8n through this template, you’ll eliminate manual steps, making collaboration between design and development teams more efficient.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.jira","n8n-nodes-base.jira","n8n-nodes-base.figmaTrigger"]

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metadata_json:
  {"categories":["integration","automation","collaboration"],"complexity":"medium","use_cases":["Automatically sync Figma version commits to Jira issues","Add design change comments to Jira","Update Jira issue status from design workflow","Reduce manual handoff between design and development teams"],"estimated_setup_minutes":20,"required_services":["Figma (plugin/API)","Jira (Cloud/Server API with credentials)","n8n instance (webhook endpoint)","Figma Commit Plugin (from GitHub)","Public webhook accessibility (or tunneling like ngrok if self‑hosted)"],"key_features":["Webhook trigger on Figma version commit","Fetch Jira issue by link","Add design details as a Jira comment","Update Jira issue status based on sent task status","Keeps design and dev tasks in sync automatically"],"target_audience":["Designers","Developers","Product managers','DesignOps','n8n users/administrators"]}


name: Split Test Different Agent Prompts with Supabase and OpenAI
author_name: Chris Carr
author_username: chriscarr
categories: []
created_at: 2025-02-24T10:35:55.283Z
updated_at: 2025-02-24T10:35:55.283Z
url: https://n8n.io/workflows/2992
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:31
description:
  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 LLM settings such as temperature
  Add a method to measure the efficacy of the two alternative prompts

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.supabase","n8n-nodes-base.if","n8n-nodes-base.supabase","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryPostgresChat","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","experimentation","AI/ML"],"complexity":"medium","use_cases":["A/B (split) testing LLM prompts in chat applications","Comparing prompt variants and LLM settings in production","Routing chat sessions to consistent prompt variants","Collecting session-level assignments for later analysis"],"estimated_setup_minutes":20,"required_services":["Supabase","OpenAI","PostgreSQL","n8n"],"key_features":["Randomly assigns each chat session to baseline or alternative prompt","Persists session→prompt mapping in Supabase for session consistency","Generates responses via OpenAI using the assigned prompt","Easy to modify baseline/alternative prompts and extend to test other LLM settings (e.g., temperature)","Uses PostgreSQL-backed memory for chat session tracking"],"target_audience":["Developers","ML engineers","AI/ML researchers and data scientists testing prompts in production scenarios`,`Product managers evaluating UX/response quality"]}


name: Copy Viral Reels with Gemini AI
author_name: Mark Shcherbakov
author_username: lowcodingdev
categories: []
created_at: 2025-02-24T10:38:34.868Z
updated_at: 2025-02-24T10:38:34.868Z
url: https://n8n.io/workflows/2993
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  Video Guide

  I prepared a detailed guide that shows the whole process of building an AI tool to analyze Instagram Reels using n8n.



  Youtube Link

  Who is this for?
  This workflow is ideal for social media analysts, digital marketers, and content creators who want to leverage data-driven insights from their Instagram Reels. It's particularly useful for those looking to automate the analysis of video performance to inform strategy and content creation.

  What problem does this workflow solve?
  Analyzing video performance on Instagram can be tedious and time-consuming, requiring multiple steps and data extraction. This workflow automates the process of fetching, analyzing, and recording insights from Instagram Reels, making it simpler for users to track engagement metrics without manual intervention.

  What this workflow does
  This workflow integrates several services to analyze Instagram Reels, allowing users to:
  Automatically fetch recent Reels from specified creators.
  Analyze the most-watched videos for insights.
  Store and manage data in Airtable for easy access and reporting.

  Initial Trigger: The process begins with a manual trigger that can later be modified for scheduled automation.
  Data Retrieval: It connects to Airtable to fetch a list of creators and their respective Instagram Reels.
  Video Analysis: It handles the fetching, downloading, and uploading of videos for analysis using an external service, simplifying performance tracking through a structured query process.
  Record Management: It saves relevant metrics and insights into Airtable, ensuring that users can access and organize their video analytics effectively.

  Setup

  Create accounts:
     Set up Airtable, Edify, n8n, and Gemini accounts.

  Prepare triggers and modules:
     Replace credentials in each node accordingly.

  Configure data flow:
     Ensure modules are set to fetch and analyze the correct data fields as outlined in the guide.

  Test the workflow:
     Run the scenario manually to confirm that data is fetched and analyzed correctly.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.sort","n8n-nodes-base.limit","n8n-nodes-base.set","n8n-nodes-base.splitInBatches","n8n-nodes-base.executeWorkflow","n8n-nodes-base.httpRequest","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.airtable","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","social media analytics"],"complexity":"complex","use_cases":["Automated Instagram Reels analytics","Content performance monitoring and reporting","Data-driven content strategy optimization","Influencer / creator monitoring"],"estimated_setup_minutes":90,"required_services":["n8n","Airtable","Gemini (Google Gemini AI)","Edify or other video-analysis service","Instagram API or video source (scraper/tool)","Storage for video files (optional)"],"key_features":["Automatically fetch recent Reels from specified creators","Analyze most-watched videos using AI (Gemini)","Download/upload videos for analysis and batch processing","Store and manage insights and metrics in Airtable","Manual trigger with option to schedule automation later (schedule node)"],"target_audience":["Social media analysts","Digital marketers","Content creators and managers\",\"Growth teams"]}


name: Automated AI image tagging and writing the keywords into the image file
author_name: Friedemann Schuetz
author_username: freddy-schuetz
categories: []
created_at: 2025-02-24T13:01:18.466Z
updated_at: 2025-02-24T13:01:18.466Z
url: https://n8n.io/workflows/2995
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  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

nodes_used:
  ["n8n-nodes-base.extractFromFile","n8n-nodes-base.convertToFile","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.code","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.merge"]

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metadata_json:
  {"categories":["automation","integration","image processing","data enrichment","AI"],"complexity":"medium","use_cases":["Automatically tag and organize photos in Google Drive","Enrich digital asset metadata for DAM systems","Improve image search and SEO by embedding keywords","Batch metadata updates for marketing and content teams","Add accessibility and descriptive keywords to image files"],"estimated_setup_minutes":20,"required_services":["Google Drive (OAuth access to target folder)","AI API (OpenAI, Anthropic, Google, Ollama, or similar)"],"key_features":["Trigger on new files added to a specific Google Drive folder","Download image and convert content to Base64","Analyze image content using an AI model to generate keywords","Merge generated metadata and write keywords into image file metadata (dc:subject)","Convert modified data back to a file and update the original in Drive"],"target_audience":["photographers","digital asset managers","content and marketing teams"]}


name: Automated AI image tagging and writing keywords into image (via community node)
author_name: Friedemann Schuetz
author_username: freddy-schuetz
categories: []
created_at: 2025-02-24T13:51:57.036Z
updated_at: 2025-02-24T13:51:57.036Z
url: https://n8n.io/workflows/2997
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  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

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.merge","n8n-nodes-exif-data.exifData","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","data processing","digital asset management"],"complexity":"medium","use_cases":["Automatic image tagging and metadata enrichment","Organizing and searching image libraries","Improving image SEO via keywords","Automated DAM (digital asset management) workflows","Batch processing new uploads in Google Drive"],"estimated_setup_minutes":30,"required_services":["Self-hosted n8n instance","n8n-nodes-exif-data (Community Node)","Google Drive API / Google account access","AI API access (OpenAI, Anthropic, Google PaLM, Ollama, etc.)"],"key_features":["Trigger on new Google Drive files","Download image and analyze content with AI","Merge generated keywords into image metadata (dc:subject/keywords)","Write/replace EXIF metadata and create updated image file","Update original file in Google Drive automatically"],"target_audience":["Developers automating media workflows","Photographers and creative teams","Content/marketing teams improving image SEO and discoverability"]}


name: 🐶 AI Agent for PetShop Appointments (Agente de IA para agendamentos de PetShop)
author_name: Bruno Dias
author_username: brunodias
categories: []
created_at: 2025-02-24T14:39:43.912Z
updated_at: 2025-02-24T14:39:43.912Z
url: https://n8n.io/workflows/2999
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:31
description:
  🐶🤖 AI Agent for Pet Shops – Automate Customer Service & Bookings! 🐾💡
  Transform Your Pet Shop with AI-Powered Automation! 🚀
  Enhance customer experience and optimize operations with this n8n AI Agent designed for pet shops. 📲🐾 Automate client interactions, appointment scheduling, and service recommendations—saving time and increasing revenue!

  🔹 Key Features:
  ✅ Instant WhatsApp responses – AI-powered chatbot handles customer inquiries. 💬
  ✅ Automated appointment scheduling – Clients can book services hassle-free. 📅✂️
  ✅ Personalized reminders – Reduce no-shows with automated notifications. 📢🐾
  ✅ Customer data & service history management – Track interactions effortlessly. 📊📁
  ✅ Product & service recommendations – Improve sales with smart suggestions. 🎁🐶

  📌 How It Works
  1️⃣ The workflow captures customer inquiries via WhatsApp.
  2️⃣ AI processes requests, provides information, and offers booking options.
  3️⃣ Clients can schedule grooming, vet visits, or other services in seconds.
  4️⃣ Automated reminders ensure appointments are remembered.
  5️⃣ Customer data is stored for better service personalization.

  ⚙️ Setup & Customization
  🔧 Connect your WhatsApp API (evolution) for instant messaging.
  🔧 Integrate with Google Calendar for appointment booking.
  🔧 Customize reminders, services, and pricing rules to fit your business.

  💡 Reduce manual work, improve customer satisfaction, and scale your pet shop with AI automation!

  🐶🤖 [PT-BR] Agente de IA para Pet Shops – Atendimento e Agendamentos Automatizados! 🐾💡
  Transforme Seu Pet Shop com Automação Inteligente! 🚀
  Otimize o atendimento ao cliente e agilize processos com este Agente de IA para n8n. 📲🐾 Automatize interações, agendamentos e recomendações de serviços—economizando tempo e aumentando as vendas!

  🔹 Principais Funcionalidades:
  ✅ Atendimento automático no WhatsApp – IA responde clientes instantaneamente. 💬
  ✅ Agendamento de serviços automatizado – Clientes marcam banho, tosa ou consultas facilmente. 📅✂️
  ✅ Lembretes personalizados – Reduza faltas com notificações automáticas. 📢🐾
  ✅ Gestão de clientes e histórico de serviços – Controle dados de forma eficiente. 📊📁
  ✅ Sugestão de produtos e serviços – Venda mais com recomendações inteligentes. 🎁🐶

  📌 Como Funciona
  1️⃣ O fluxo recebe perguntas dos clientes via WhatsApp.
  2️⃣ A IA processa os pedidos e fornece opções de agendamento.
  3️⃣ O cliente escolhe o serviço desejado e agenda em segundos.
  4️⃣ Lembretes automáticos garantem que os clientes não esqueçam os horários.
  5️⃣ O histórico do cliente é salvo para oferecer um atendimento mais personalizado.

  ⚙️ Configuração e Personalização
  🔧 Conecte sua API do WhatsApp (evolution) para interação automática.
  🔧 Integre ao Google Calendar para gerenciar agendamentos.
  🔧 Personalize valores, serviços e regras de envio de lembretes conforme sua necessidade.

  💡 Automatize processos, melhore a experiência do cliente e escale seu pet shop com IA! 🚀

nodes_used:
  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metadata_json:
  {"categories":["automation","customer service","scheduling","AI/ML","integration"],"complexity":"complex","use_cases":["Automated WhatsApp customer support for pet shops","Online appointment booking for grooming, vet visits and services","Automated personalized reminders to reduce no-shows","Customer data and service history management (light CRM)","AI-driven product and service recommendations / upselling"],"estimated_setup_minutes":120,"required_services":["WhatsApp API (evolution)","Google Calendar","LLM provider (e.g., OpenAI)","Database (e.g., Supabase/Postgres)","Redis (caching/session storage)","n8n"],"key_features":["Instant AI-powered WhatsApp responses and conversational booking","Automated appointment scheduling and calendar integration","Personalized automated reminders/notifications","Customer profile and service history storage","AI recommendations for products and services based on history/queries"],"target_audience":["Pet shop owners and managers","Small business operators (groomers, clinics, salons)","Automation/operations teams implementing customer-facing bots in n8n"]}


name: Dynamically Run SuiteQL Queries in NetSuite via HTTP Webhook in n8n
author_name: DataAnts
author_username: dataants
nodes_used: ["n8n-nodes-base.manualTrigger","n8n-nodes-netsuite.netsuite","n8n-nodes-base.webhook"]
categories: []
created_at: 2025-02-24T18:28:27.222Z
updated_at: 2025-02-24T18:28:27.222Z
url: https://n8n.io/workflows/3002
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Dynamically Run SuiteQL Queries in NetSuite via HTTP Webhook in n8n

  &gt; Important: This template uses a NetSuite community node, so it only works on self-hosted n8n. Cloud-based n8n instances currently do not support community nodes.  

  Summary

  This workflow template allows you to dynamically run SuiteQL queries in NetSuite by sending an HTTP request to an n8n Webhook node. Once triggered, the workflow uses token-based authentication to execute your SuiteQL query and returns the results as JSON. This makes it easy to integrate real-time NetSuite data into dashboards, reporting tools, or other applications.

  Who Is This For?

  Developers & Integrators**: Easily embed NetSuite data retrieval into custom apps or internal tools.  
  Enterprises & Consultants**: Integrate dynamic reporting or data enrichment from NetSuite without manual exports.  
  System Administrators**: Automate routine queries and reduce manual intervention.

  Use Cases & Benefits

  1. Dynamic Data Access
  Send any SuiteQL query on demand instead of hardcoding queries or manually running reports.

  2. Seamless Integration
  Quickly pull NetSuite data into front-end systems (like Excel dashboards, custom web apps, or internal tools) by calling the webhook endpoint.

  3. Simplified Reporting
  Automate data extraction and formatting, reducing the need for manual exports and improving efficiency.

  How It Works

  Trigger:  
     An HTTP request to the webhook node initiates the workflow.  

  Input Processing:  
     The workflow reads the SuiteQL query from the incoming request parameter (suiteql).  

  Query Execution:  
     The NetSuite node uses your token-based authentication credentials to run the SuiteQL query.  

  Response:  
     Results are returned as JSON in the HTTP response, ready for further processing or immediate consumption.

  Prerequisites & Setup

  NetSuite Community Node  
     This workflow requires the NetSuite community node. Make sure your self-hosted n8n instance supports community nodes.

  NetSuite Token-Based Authentication  
     Enable TBA in NetSuite. Obtain the required consumer key, consumer secret, token ID, and token secret.

  n8n Webhook  
     Copy the auto-generated webhook URL (e.g. http://&lt;your-n8n-domain&gt;/webhook/unique-id) from the Webhook node.

  Usage  
     Send an HTTP GET or POST request to the webhook with your SuiteQL query. For example:  
            curl "http://&lt;your-n8n-domain&gt;/webhook/unique-id?suiteql=SELECT%20*%20FROM%20account%20LIMIT%2010"
          The workflow will execute the query and return JSON data.

  Customization

  Change the Query**:  
    Simply adjust the suiteql parameter in your HTTP request to run different SuiteQL statements.

  Data Transformation**:  
    Insert nodes (e.g., Function, Set, or Format) to modify or reformat the data before returning it.

  Extend Integration**:  
    Chain additional nodes to push the retrieved data to other services (Google Sheets, Slack, custom dashboards, etc.).

  Additional Notes

  Remember that this template is only compatible with self-hosted n8n because it uses a community node. - 
  [netsuite community node](https://www.npmjs.com/package/n8n-nodes-netsuite
  )
  If you have questions, suggestions, or need support, contact us at support@dataants.org.

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metadata_json:
  {"categories":["integration","automation","data processing","reporting"],"complexity":"medium","use_cases":["Run ad-hoc SuiteQL queries on demand via HTTP","Expose NetSuite data to dashboards and custom apps","Automate periodic or on-demand reporting and exports","Data enrichment and integration with other systems"],"estimated_setup_minutes":45,"required_services":["NetSuite with Token-Based Authentication (TBA)","Self-hosted n8n instance with community nodes enabled","n8n NetSuite community node (n8n-nodes-netsuite)","Publicly reachable webhook endpoint (or accessible client to call webhook)"],"key_features":["Execute dynamic SuiteQL queries supplied via webhook parameter","Token-based authentication to NetSuite","Returns query results as JSON in the HTTP response","Supports GET and POST webhook triggers","Easily extendable with transformation or integration nodes"],"target_audience":["Developers & Integrators","Enterprises & Consultants","System Administrators"]}


name: Monitor Favorite YouTube Channels Through RSS feeds and Receive Notifications
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-24T21:02:39.062Z
updated_at: 2025-02-24T21:02:39.062Z
url: https://n8n.io/workflows/3003
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  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 YouTube channel IDs through form input
  Configure default channel list
  Set notification preferences
  Adjust monitoring schedule


  This workflow is perfect for content creators, marketers, or anyone wanting to stay updated with their favorite YouTube channels through automated, professionally formatted notifications delivered via email and Telegram.

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workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","content monitoring","notifications"],"complexity":"complex","use_cases":["Monitor favorite YouTube channels for new uploads","Send immediate Telegram alerts with thumbnails and links","Deliver individual or digest email notifications","Content curation and competitor/channel tracking","Generate summarized or enhanced content using AI"],"estimated_setup_minutes":45,"required_services":["YouTube Data API","Gmail (or SMTP email provider)","Telegram Bot API (bot token + chat ID)","OpenAI API (for content processing)"],"key_features":["Creates RSS feeds per YouTube channel and monitors for new videos","Filters/labels recent videos within configurable window (default 3 days)","Fetches detailed video data via YouTube API","Sends Telegram notifications with thumbnails and links","Sends either individual emails per video or a single digest email (responsive HTML) with previews and links」「Supports adding channel IDs via form input and default channel list configuration」「Configurable monitoring schedule and notification preferences"],"target_audience":["Content creators","Marketers and social media managers","Community managers and curators who track channels regularly (competitive/market monitoring)」「Developers or automation engineers setting up notification workflows"]}


name: 🚀 TikTok Video Automation Tool ✨ – Highly Optimized with OpenAI & Replicate
author_name: Jonas Busch
author_username: jonasbusch
categories: []
created_at: 2025-02-24T22:44:59.697Z
updated_at: 2025-02-24T22:44:59.697Z
url: https://n8n.io/workflows/3004
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  🚀 TikTok Video Automation Tool ✨ (Frequent Updates) 
  Create viral TikTok videos effortlessly — no editing skills required!

  Who is this for? 🎯  
  ✅ Content Creators: Pump out engaging short videos in minutes.  
  ✅ Marketing Agencies: Deliver high-quality client content — fast.
  ✅ Business Owners: Promote your brand with attention-grabbing TikToks.  

  What problem does this solve? 🛠️  
  Short-form video content is king, but creating it takes time, skill, and effort. This tool automates the entire process, from scriptwriting to video production, ensuring SEO-optimized, high-quality content without any manual editing.  

  How it works 🌟  
  1️⃣ Enter your video idea and choose where to receive the final video (TikTok upload or link via WhatsApp, Gmail, etc.).  
  2️⃣ AI crafts a high-engagement script with SEO optimization.  
  3️⃣ Voiceover is generated with ultra-realistic AI narration.  
  4️⃣ Relevant visuals are selected to perfectly match the script.  
  5️⃣ Your TikTok video is assembled and either directly uploaded to TikTok or delivered via a shareable link.  

  Quick & Easy Setup ⚙️ (5-10 min)  
  🔹 Connect required APIs (most have free plans).  
  🔹 Follow the step-by-step setup (video tutorial included).  
  🔹 Start generating professional TikTok videos instantly!  

  Required APIs 🔗  
  Content & Voiceover:** OpenAI (Paid), ElevenLabs (Free)
  Media Processing:** Cloudinary (Free), Replicate (Paid)
  Video Assembly:** 0codekit (Free), Creatomate (Free)

  Optional Integrations 🔗  
  Messaging & Sharing:** WhatsApp, Telegram, Gmail, Outlook  
  Direct Upload:** TikTok  

  Customization 🎨  
  Adjust script styles & voiceover preferences.  
  Modify visuals to align with your brand.  
  Optimize video length and format.  

  🚀 Start automating your TikTok content today and grow your audience on autopilot!

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metadata_json:
  {"categories":["automation","media production","social media","ai-generated content","integration"],"complexity":"complex","use_cases":["Automated TikTok/short-video production from idea to finished video","Scale content creation for creators and agencies","Repurpose written content into short-form videos","Deliver videos via messaging/email or direct upload to TikTok","A/B test scripts and voices for engagement optimization"],"estimated_setup_minutes":10,"required_services":["OpenAI","ElevenLabs","Cloudinary","Replicate","0codekit","Creatomate","TikTok (optional for direct upload)","WhatsApp/Telegram/Gmail/Outlook (optional for delivery)"],"key_features":["AI-driven scriptwriting with SEO/high-engagement optimization","Ultra-realistic AI voiceover generation","Automated visual selection and media processing","Automated video assembly and formatting for TikTok","Multiple delivery options: direct upload or shareable link via messaging/email"],"target_audience":["Content creators","Marketing agencies","Business owners and brands promoting on social media"]}


name: ✨🔪 Advanced AI Powered Document Parsing & Text Extraction with Llama Parse
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-25T00:38:08.693Z
updated_at: 2025-02-25T00:38:08.693Z
url: https://n8n.io/workflows/3005
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  Description

  This workflow automates document processing using LlamaParse to extract and analyze text from various file formats. It intelligently processes documents, extracts structured data, and delivers actionable insights through multiple channels.

  How It Works

  Document Ingestion & Processing 📄
  Monitors Gmail for incoming attachments or accepts documents via webhook
  Validates file formats against supported LlamaParse extensions
  Uploads documents to LlamaParse for advanced text extraction
  Stores original documents in Google Drive for reference

  Intelligent Document Analysis 🧠
  Automatically classifies document types (invoices, reports, etc.)
  Extracts structured data using customized AI prompts
  Generates comprehensive document summaries with key insights
  Converts unstructured text into organized JSON data

  Invoice Processing Automation 💼
  Extracts critical invoice details (dates, amounts, line items)
  Organizes financial data into structured formats
  Calculates tax breakdowns, subtotals, and payment information
  Maintains detailed records for accounting purposes

  Multi-Channel Delivery 📱
  Saves extracted data to Google Sheets for tracking and analysis
  Sends concise summaries via Telegram for immediate review
  Creates searchable document archives in Google Drive
  Updates spreadsheets with structured financial information

  Setup Steps

  Configure API Credentials 🔑
  Set up LlamaParse API connection
  Configure Gmail OAuth for email monitoring
  Set up Google Drive and Sheets integrations
  Add Telegram bot credentials for notifications

  Customize AI Processing ⚙️
  Adjust document classification parameters
  Modify extraction templates for specific document types
  Fine-tune summary generation prompts
  Customize invoice data extraction schema

  Test and Deploy 🚀
  Test with sample documents of various formats
  Verify data extraction accuracy
  Confirm notification delivery
  Monitor processing pipeline performance

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name: YouTube Shorts Automation - The Game-Changer in Scroll-Stopping Short Clips
author_name: Matt F.
author_username: lemolex
categories: []
created_at: 2025-02-25T01:36:09.427Z
updated_at: 2025-02-25T01:36:09.427Z
url: https://n8n.io/workflows/3007
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Automatically Create and Post YouTube Shorts from Podcasts and Other Videos Using AI (Simplified).

  Transform podcasts and other videos into captivating, fully optimized YouTube Shorts with this all-in-one automation solution—designed for content creators who repurpose engaging clips. By leveraging advanced YouTube analytics, this template identifies the most compelling moments from your source material and automatically crafts them into scroll-stopping shorts. With intelligent editing, auto-generated titles and descriptions, and customizable scheduling, your clips become instantly post-ready, helping you expand your reach while saving hours on manual editing.

  Key Features

  Analytics-Driven Highlight Extraction:**  
    Automatically analyzes engagement metrics to select the best moments from podcasts or other creators' videos, ensuring each clip resonates with your audience.

  AI-Powered Editing:**  
    Applies professional-grade editing—adding captions, effects, transitions, and more—to create visually stunning, high-impact shorts.

  Auto-Generated Metadata:**  
    Seamlessly creates dynamic titles and descriptions, fully optimizing your clips for immediate upload.

  Customizable Scheduling:**  
    Enables you to set upload intervals that align with your strategy, ensuring a steady stream of content on your channel.

  Seamless YouTube Integration:**  
    Directly connects with YouTube’s API, streamlining the process so your channel remains active and engaging with minimal effort.

  Designed specifically for content creators repurposing YouTube videos—and requiring only a Sipkes Studio account (it's Free) for full functionality—this simplified automation template streamlines the conversion of long-form content into bite-sized, shareable clips. Elevate your content strategy, maximize audience engagement, and reclaim valuable time with a solution built to drive your channel's growth.

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metadata_json:
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name: Extract Thai Bank Slip Data from LINE using SpaceOCR and Save to Google Sheets
author_name: Jaruphat J.
author_username: jaruphatj
categories: []
created_at: 2025-02-25T03:44:14.911Z
updated_at: 2025-02-25T03:44:14.911Z
url: https://n8n.io/workflows/3008
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?
  This workflow is ideal for businesses, accountants, and finance teams who receive bank slip images via LINE and want to automate the extraction of transaction details. It eliminates manual data entry and speeds up financial tracking.

  What problem does this workflow solve?
  Many businesses receive bank transfer slips via LINE from customers, but manually recording transaction details into spreadsheets is time-consuming and error-prone. This workflow automates the entire process, extracting structured data from the bank slips and storing it in Google Sheets for seamless record-keeping.

  What this workflow does:
  Receives bank slip images from LINE BOT
  Extracts transaction details (sender, receiver, amount, transaction ID) using SpaceOCR
  Automatically logs extracted data into Google Sheets
  Works with Standard Bank Slips & PromptPay transactions
  Eliminates manual data entry and reduces errors

  Setup Instructions:
  1. Prerequisites
  A LINE BOT with Messaging API enabled
  A SpaceOCR API Key (Get from https://spaceocr.com/)
  A Google Sheets account to store extracted data
  An n8n instance running (Cloud or Self-hosted)

  2. Setup Google Sheets
  Create a Google Sheet with the following structure:

  A (Date)	B (Time)	C (Sender)	D (Receiver)	E (Bank Name)	F (Amount)	G (Transaction ID)

  Ensure your Google Sheets API is enabled and connected to n8n.

  For an example of the required format, check this Google Sheets template: Google Sheets Template

  3. Configure n8n Workflow
  1. Webhook Node (Receives bank slip from LINE BOT)

  Set method:* Set Path:* 
  2. HTTP Request (Download Image from LINE Message)
  Retrieves image URL from the LINE message payload

  3. SpaceOCR Node (Extract Text from Bank Slip)
  Input:* API Key:* #### 4. Google Sheets Node (Save Transaction Data)
  Select your Google Sheet
  Map extracted data (sender, receiver, amount, etc.) to the respective columns

  4. Deploy & Test
  Activate the workflow in n8n
  Set Webhook URL in LINE Developer Console
  Send a test bank slip image to the LINE BOT
  Check Google Sheets for extracted transaction data

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  {"categories":["automation","integration","data extraction","finance"],"complexity":"medium","use_cases":["Automated capture of bank transfer slips received via LINE","Automatic population of transaction records in Google Sheets","Expense tracking and reconciliation","Reducing manual data-entry errors for payment records"],"estimated_setup_minutes":45,"required_services":["LINE Messaging API (LINE BOT)","SpaceOCR API key (https://spaceocr.com)","Google Sheets / Google Drive (Google Sheets API enabled)","n8n instance (cloud or self-hosted)"],"key_features":["Receive bank slip images from LINE webhook","Download image from LINE message payload","Perform OCR with SpaceOCR to extract transaction details","Parse fields: date, time, sender, receiver, bank name, amount, transaction ID","Automatically append structured rows into Google Sheets"],"target_audience":["Businesses receiving payments via LINE","Accountants and finance teams","Small business owners and operations staff automating bookkeeping tasks\",\"Automation engineers / n8n users"]}


name: 🧠 *NEW* Claude 3.7 Extended Thinking AI Agent 🤖 – Unlock Ultimate Intelligence
author_name: Jonas Busch
author_username: jonasbusch
categories: []
created_at: 2025-02-25T10:48:11.690Z
updated_at: 2025-02-25T10:48:11.690Z
url: https://n8n.io/workflows/3009
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  🧠 NEW Claude 3.7 Extended Thinking AI Agent 🤖 – Unlock Ultimate Intelligence

  Supercharge Claude 3.7 with full customization & deeper reasoning!  

  Who is this for? 🎯  
  ✅ AI Enthusiasts & Researchers: Push Claude’s intelligence to new heights.  
  ✅ Professionals & Analysts: Get in-depth, high-quality insights.  
  ✅ Developers & Power Users: Unlock settings not available on the official Claude site.  

  What makes this different? 🚀  
  Even Claude Pro limits your control—this tool breaks those barriers! Adjust thinking tokens to supercharge extended reasoning, fine-tune every setting, and get smarter, more strategic responses that outperform the default experience.  

  How it works 🌟  
  1️⃣ Customize Claude 3.7’s settings (beyond what’s possible on the official site).  
  2️⃣ Increase thinking tokens to drastically improve deep reasoning.  
  3️⃣ Chat with Claude at peak performance for more insightful answers.  

  Quick Setup ⚙️ (1-3 min)  
  🔹 Connect the Claude API.  
  🔹 Adjust settings for ultimate AI performance.  
  🔹 Start getting deeper, smarter responses instantly!  

  Required API 🔗  
  Claude 3.7 API (Paid)**  

  Why use this tool? 💡  
  Unlock full customization** & go beyond Claude’s default limits.  
  Enhance extended thinking** for more powerful reasoning.  
  Optimize response depth, quality & accuracy.**  

  👉 Take Claude 3.7 to the next level—start customizing now!

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metadata_json:
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name: 📄✨ Easy WordPress Content Creation from PDF Docs + Human in the Loop Gmail
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-25T15:45:40.461Z
updated_at: 2025-02-25T15:45:40.461Z
url: https://n8n.io/workflows/3010
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-30 08:33:37
description:
  📄✨ Easy WordPress Content Creation from PDF Docs + Human in the Loop Gmail

  This n8n workflow automates the process of transforming PDF documents into engaging, SEO-friendly WordPress blog posts. It incorporates AI-powered text analysis, automatic image generation, and a human review step to ensure quality before publishing.

  🚀 How It Works

  🗂️ PDF Upload & Text Extraction  
  Users upload a PDF document through a form trigger.  
  The workflow extracts text from the uploaded file, ensuring compatibility with supported formats.

  🤖 AI-Powered Blog Post Generation  
  The extracted text is analyzed by an AI model (GPT-based) to create a structured blog post.  
  The AI generates:  
    A captivating SEO-friendly title.  
    Well-formatted HTML content, including an introduction, chapters with subheadings, and a conclusion.

  🎨 Image Creation & Integration  
  An image is generated using Pollinations.ai based on the blog post title.  
  The vibrant image is uploaded to WordPress and set as the featured image for the post.

  📝 WordPress Draft Creation  
  A draft blog post is created on WordPress with the AI-generated title, content, and featured image.  

  ✅ Human-in-the-Loop Approval  
  The draft content is sent via Gmail to a reviewer for manual approval.  
  If approved, the post is published on WordPress. If not, an error message is sent for troubleshooting.

  📢 Multi-Channel Notifications  
  Once published, notifications are sent via Gmail and Telegram to relevant stakeholders.  

  🔧 Setup Steps

  🔑 Configure API Credentials  
  Set up API connections for:  
     OpenAI (for AI content generation).  
     WordPress (for post creation and media uploads).  
     Gmail (for sending approval emails).  
     Telegram (for notifications).
     imgbb (for saving blog image).

  ⚙️ Customize Workflow Parameters  
  Adjust the AI prompt to match your desired blog structure and tone.  
  Modify the image generation parameters to align with your branding needs.

  🧪 Test & Deploy  
  Test the workflow with sample PDFs to ensure:  
     Accurate text extraction.  
     Proper formatting of generated content.  
     Seamless approval and publishing processes.  


  This workflow streamlines content creation while maintaining quality control through human oversight, making it an ideal solution for efficient blog management! 🎉

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name: 🌐 Confluence Page AI Chatbot Workflow
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-25T16:29:19.644Z
updated_at: 2025-02-25T16:29:19.644Z
url: https://n8n.io/workflows/3012
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  🌐 Confluence Page AI Chatbot Workflow

  This n8n workflow template enables users to interact with an AI-powered chatbot designed to retrieve, process, and analyze content from Confluence pages. By leveraging Confluence's REST API and an AI agent, the workflow facilitates seamless communication and contextual insights based on Confluence page data.

  🌟 How the Workflow Works

  🔗 Input Chat Message
  The workflow begins when a user sends a chat message containing a query or request for information about a specific Confluence page.

  📄 Data Retrieval
  The workflow uses the Confluence REST API to fetch page details by ID, including its body in the desired format (e.g., storage, view).
  The retrieved HTML content is converted into Markdown for easier processing.

  🤖 AI Agent Interaction
  An AI-powered agent processes the Markdown content and provides dynamic responses to user queries. The agent is context-aware, ensuring accurate and relevant answers based on the Confluence page's content.

  💬 Dynamic Responses
  Users can interact with the chatbot to:
    Summarize the page's content.
    Extract specific details or sections.
    Clarify complex information.
    Analyze key points or insights.

  🚀 Use Cases

  📚 Knowledge Management**: Quickly access and analyze information stored in Confluence without manually searching through pages.
  📊 Team Collaboration**: Facilitate discussions by summarizing or explaining page content during team chats.
  🔍 Research and Documentation**: Extract critical insights from large documentation repositories for efficient decision-making.
  ♿ Accessibility**: Provide an alternative way to interact with Confluence content for users who prefer conversational interfaces.

  🛠️ Resources for Getting Started

  Confluence API Setup:
     Generate an API token for authentication via Atlassian's account management portal.
     Refer to Confluence's REST API documentation for endpoint details and usage instructions.

  n8n Installation:
     Install n8n locally or on a server using the official installation guide.

  AI Agent Configuration:
     Set up OpenAI or other supported language models for natural language processing.

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name: 🔄 Workflow Repos8r: Github Version Control User Interface for n8n Workflows
author_name: RealSimple Solutions
author_username: joeperes
categories: []
created_at: 2025-02-25T20:42:06.051Z
updated_at: 2025-02-25T20:42:06.051Z
url: https://n8n.io/workflows/3014
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  🔥 n8n Members Sale – n8n Community Members Get ideoGener8r for Just $10! (Reg. $15)
  Use Coupon Code: FeelinTheFlowgramming
  (Valid for n8n community members)

  💪 How it works
  Seamlessly track, manage, and version-control your n8n workflows with an intuitive Git-style system. Whether you're making updates or creating new workflows, this tool ensures structured commits, detailed change tracking, and seamless GitHub integration—all within a Matrix-inspired UI.

  🎯 Who is this for?

  Perfect for:

  n8n Developers & Automation Engineers** – Maintain workflow history and prevent accidental overwrites.
  Teams Collaborating on Automation** – Track and commit changes with structured version control.
  DevOps & IT Professionals** – Streamline deployment across multiple n8n environments.

  🚀 Key Features

  Version Control & Workflow Management

  Commit changes when editing existing workflows
  Create & commit new workflows from scratch
  Detect modifications with deep node comparison
  Access repo with direct links from changes window
  Workflow JSON Browser Caching **to avoid large loads on n8n"

  Core Features

  Workflow Management
  Workflow Selection**: Easy selection of n8n workflows and GitHub workflows from dropdown menus
  Smart Caching**: Client-side caching of workflows for faster loading (1-week cache duration)
  Cache Control**: Manual cache clearing via hard refresh (Cmd+Shift+R)
  Matrix-Style UI**: Terminal-inspired interface with glowing effects and animations

  GitHub Integration
  Push to GitHub**: Direct pushing of n8n workflows to GitHub repositories
  Commit Control**: Automated commit message generation with workflow details
  Branch Management**: Automatic branch creation and management
  Pull from GitHub**: Future feature for pulling workflows from GitHub (Coming Soon)

  Workflow Comparison
  Side-by-Side Comparison**: Compare n8n workflows with their GitHub counterparts
  Change Detection**: Automatic detection and highlighting of workflow changes
  Diff Visualization**: Clear visualization of additions, deletions, and modifications
  JSON Validation**: Ensures workflow JSON integrity before operations

  User Experience
  System Notifications**: Matrix-themed toast notifications for important alerts
    30-second duration with manual close option
    Context-aware messages (e.g., cache refresh hints)
    Glowing effects matching system console aesthetics
  Loading Animations**: Matrix-style loading indicators during operations
  Error Handling**: Clear error messages and recovery suggestions
  Responsive Design**: Adapts to different screen sizes

  Security & Performance
  Local Storage**: Efficient client-side storage for workflow data
  Header Authentication**: Secure API communication with authentication tokens
  Performance Optimization**: Smart caching to reduce server load
  Data Validation**: Input validation and sanitization

  Technical Features

  Code Organization
  Modular Structure**: Well-organized HTML, CSS, and JavaScript
  Component Separation**: Clear separation of concerns
  CSS Variables**: Consistent styling with CSS custom properties
  Event Handling**: Robust event listeners and handlers

  API Integration
  n8n Integration**: Direct communication with n8n workflow API
  GitHub API**: Seamless integration with GitHub repositories
  RESTful Endpoints**: Clean API design for workflow operations
  Error Handling**: Comprehensive error handling and user feedback

  Development Features
  Debug Mode**: Console logging for development
  Code Comments**: Well-documented code sections
  CSS Animations**: Smooth transitions and effects
  Browser Compatibility**: Works across modern browsers

  Future Enhancements
  Pull workflows from GitHub repositories
  Enhanced diff visualization
  Additional GitHub integration features
  Extended caching options
  More customization options for notifications
  Advanced workflow comparison tools

  GitHub Integration

  Push workflows directly to GitHub
  Commit new workflows directly to GitHub
  Auto-generate structured commit messages
  Pull workflows from GitHub into n8n

  Change Detection

  Identifies node additions, deletions, and property modifications
  Compares connections, settings, and configurations
  Real-time visualization** of detected changes

  Sleek UI for Effortless Control

  Matrix-style interface** for a futuristic feel
  Clear prompts to prevent accidental overwrites
  Interactive workflow commit & sync options

  🔧 Setup & Usage

  Generate your n8n API key
  Set up GitHub repository & access tokens
  Create Generic Basic Auth credentials
  Create Generic Header Auth credentials
  Set the workflow variables
  Deploy & start tracking your workflow versions

  📚 Use Cases

  🔹 Workflow Development – Ensure clean versioning and commit history.  
  🔹 Team Collaboration – Review and track modifications before deployment.  
  🔹 Audit & Compliance – Maintain an organized change log.

  🙌 Built for the n8n Community

  Created with ❤️ to bring reliable version control to the n8n community.

nodes_used:
  ["n8n-nodes-base.n8n","n8n-nodes-base.respondToWebhook","n8n-nodes-base.html","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.github","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.github","n8n-nodes-base.set","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.n8n","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.switch","n8n-nodes-base.set","n8n-nodes-base.n8n","n8n-nodes-base.github","n8n-nodes-base.n8n","n8n-nodes-base.github","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","developer tools","version control"],"complexity":"complex","use_cases":["Workflow versioning and history tracking","Team collaboration and code review for n8n workflows","Audit and compliance change logging","Safe deployment and rollback of automation","Syncing n8n workflows with GitHub repositories"],"estimated_setup_minutes":30,"required_services":["n8n instance (self-hosted or cloud) with API access","GitHub (repository + access token)","Web frontend or hosting to run the UI (browser-based)","Authentication credentials (Generic Basic/Header auth)"],"key_features":["Push workflows to GitHub with automated commit messages and branch management","Deep node-level change detection and side-by-side diff visualization","JSON validation and workflow integrity checks before operations","Client-side smart caching (1-week) and manual cache control","Matrix-style UI with notifications, loading animations, and responsive design\",\"Local storage for performance and header-based API authentication"],"target_audience":["n8n developers & automation engineers","Teams collaborating on automation","DevOps & IT professionals managing deployments and environments"]}


name: Invoices from Gmail to Drive and Google Sheets
author_name: Juan Carlos Cavero Gracia
author_username: carlosgracia
categories: []
created_at: 2025-02-25T21:34:30.197Z
updated_at: 2025-02-25T21:34:30.197Z
url: https://n8n.io/workflows/3016
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Attachments Gmail to Drive and Google Sheets

  Description
  Automatically process invoice emails by saving attachments to Google Drive and extracting key invoice data to Google Sheets using AI. This workflow monitors your Gmail for unread emails with attachments, saves PDFs to a specified Google Drive folder, and uses OpenAI's GPT-4o to extract invoice details (date, description, amount) into a structured spreadsheet.

  Use cases
  Invoice Management**: Automatically organize and track invoices received via email
  Financial Record Keeping**: Maintain a structured database of all invoice information
  Document Organization**: Keep digital copies of invoices organized in Google Drive
  Automated Data Entry**: Eliminate manual data entry for invoice processing

  Resources
  Gmail account
  Google Drive account
  Google Sheets account
  OpenAI API key

  Setup instructions

  Prerequisites
  Active Gmail, Google Drive, and Google Sheets accounts
  OpenAI API key (GPT-4o model access)
  n8n instance with credentials manager

  Steps
  Gmail and Google Drive Setup:
     Connect your Gmail account in n8n credentials
     Connect your Google Drive account with appropriate permissions
     Create a destination folder in Google Drive for invoice storage

  Google Sheets Setup:
     Connect your Google Sheets account
     Create a spreadsheet with columns: Invoice date, Invoice Description, Total price, and Fichero
     Copy your spreadsheet ID for configuration

  OpenAI Setup:
     Add your OpenAI API key to n8n credentials

  Configure Email Filter:
     Update the email filter node to match your specific sender requirements

  Benefits
  Time Saving**: Eliminates manual downloading, filing, and data entry
  Accuracy**: AI-powered data extraction reduces human error
  Organization**: Consistent file naming and storage structure
  Searchability**: Creates a searchable database of all invoice information
  Automation**: Runs every minute to process new emails as they arrive

  Related templates
  Email Parser to CRM
  Document Processing Workflow
  Financial Data Automation

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.gmailTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.gmail","n8n-nodes-base.extractFromFile","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.if"]

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metadata_json:
  {"categories":["automation","document processing","finance","data extraction","AI integration"],"complexity":"medium","use_cases":["Invoice management and organization","Financial record keeping and bookkeeping","Automated data entry from emailed invoices","Storing and indexing invoice PDFs in Google Drive","Creating a searchable invoice spreadsheet for reporting"],"estimated_setup_minutes":30,"required_services":["Gmail (Google account)","Google Drive","Google Sheets","OpenAI (GPT-4o/API key)","n8n (self-hosted or cloud instance)"],"key_features":["Monitors Gmail for unread emails with attachments","Saves invoice PDFs to a specified Google Drive folder","Uses GPT-4o to extract structured invoice fields (date, description, amount)","Populates a Google Sheets spreadsheet with extracted invoice data and file link","Configurable email filters and runs on a frequent schedule (every minute)"],"target_audience":["Accountants and bookkeepers","Small business owners","Finance and operations teams (AP/AR workflows)"]}


name: Automated Content Generation & Publishing - Wordpress
author_name: Sunny
author_username: xicpoywriter
categories: []
created_at: 2025-02-26T05:00:48.559Z
updated_at: 2025-02-26T05:00:48.559Z
url: https://n8n.io/workflows/3018
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Workflow Description: Automated Content Publishing for WordPress
  This n8n workflow automates the entire process of content generation, image selection, and scheduled publishing to a self-hosted WordPress website. It is designed for bloggers, marketers, and businesses who want to streamline their content creation and posting workflow.

  🌟 Features
  ✅ AI-Powered Content Generation  
  Uses ChatGPT to generate engaging, market-ready blog articles  
  Dynamically incorporates high-search volume keywords  

  ✅ Automated Image Selection  
  Searches for relevant stock images from Pexels  
  Embeds images directly into posts  
  (Optional)* Supports *Featured Image from URL (FIFU) plugin** for WordPress  

  ✅ Scheduled & Randomized Posting  
  Automatically schedules posts at predefined intervals  
  Supports randomized delay (0-6 hours) for natural publishing  

  ✅ WordPress API Integration  
  Uses WordPress REST API to directly publish posts  
  Configures featured images, categories, and metadata  
  Supports SEO-friendly meta fields  

  ✅ Flexible & Customizable  
  Works with any WordPress website (self-hosted)  
  Can be modified for other CMS platforms  

  🔧 How It Works
  1️⃣ Trigger & Scheduling  
     Automatically runs at preset times or on-demand  
     Supports cron-like scheduling  

  2️⃣ AI Content Generation  
     Uses a well-crafted prompt to generate high-quality blog posts  
     Extracts relevant keywords for both SEO and image selection  

  3️⃣ Image Fetching from Pexels  
     Searches and retrieves high-quality images  
     Embeds image credits and ensures proper formatting  

  4️⃣ WordPress API Integration  
     Sends post title, content, image, and metadata via HTTP Request  
     Can include custom fields, categories, and tags  

  5️⃣ Randomized Delay Before Publishing  
     Ensures natural posting behavior  
     Avoids bulk publishing issues  

  📌 Requirements
  Self-hosted WordPress website* with *REST API enabled**  
  FIFU Plugin* (optional) for *external featured images**  
  n8n Self-Hosted or Cloud Instance**  

  🚀 Who Is This For?
  ✅ Bloggers who want to automate content publishing  
  ✅ Marketing teams looking to scale content production  
  ✅ Business owners who want to boost online presence  
  ✅ SEO professionals who need consistent, optimized content  

  💡 Ready to Automate?
  👉 Click here to get this workflow! (Replace with Purchase URL)

nodes_used:
  ["n8n-nodes-base.wordpress","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.manualTrigger","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.openAi"]

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metadata_json:
  {"categories":["automation","content_creation","CMS_integration","marketing"],"complexity":"medium","use_cases":["Automated blog post generation and publishing","Scheduled and randomized content posting","SEO-optimized content production at scale","Automatic image selection and embedding","Content pipeline integration with spreadsheets or other sources"],"estimated_setup_minutes":60,"required_services":["Self-hosted WordPress with REST API enabled","OpenAI (ChatGPT) or compatible AI API","Pexels API (for stock images)","n8n (self-hosted or cloud instance)","Google Sheets (optional, for content/input storage)","FIFU WordPress plugin (optional, for external featured images)"],"key_features":["AI-powered article generation with keyword injection","Automated stock image search and embedding (Pexels)","Direct publishing via WordPress REST API with featured image support","Scheduled runs with optional randomized delay to mimic natural posting","Configurable metadata, categories, tags, and SEO fields"],"target_audience":["Bloggers","Content marketers","SEO professionals/agencies"]}


name: AI Linux system administrator for managing Linux VPS instance
author_name: Hostinger
author_username: hostinger
categories: []
created_at: 2025-02-26T08:41:17.448Z
updated_at: 2025-02-26T08:41:17.448Z
url: https://n8n.io/workflows/3020
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:31
description:
  This n8n workflow template is designed for developers, system administrators, and IT professionals who manage Linux VPS environments. It leverages an AI chatbot powered by the OpenAI model to interpret and execute SSH commands on a Linux VPS directly from chat messages. The workflow triggers when a specific chat message is received, which is then processed by the AI SysAdmin ReAct Agent to execute predefined SSH commands securely.

  How It Works
  Chat Trigger: The workflow starts when a chat message is received via a supported platform (like Slack, Telegram, etc.).
  AI Processing: The message is passed to the AI SysAdmin ReAct Agent, which uses an embedded OpenAI model to interpret the command and map it to a corresponding SSH action.
  Command Execution: The interpreted command is securely executed on the target Linux VPS using SSH, with login credentials managed through a secure method embedded within the workflow.

  Setup Instructions
  Import the Workflow: Download and import the workflow into your n8n instance.
  Configure Chat Integration: Set up the chat trigger node by connecting it to your preferred chat platform and configuring the trigger conditions.
  Set SSH Credentials: Securely input your SSH credentials in the designated SSH login credentials node.
  Deploy and Test: Deploy the workflow and perform tests to ensure that commands are executed correctly and securely on your VPS.

  Embrace the future of VPS management with our AI-driven SysAdmin for Linux VPS template. This innovative solution transforms how system administrators interact with and manage their servers, offering a streamlined, secure, and efficient method to handle routine tasks through simple chat commands. With the power of AI at your fingertips, enhance your operational efficiency, reduce response times, and manage your Linux environments more effectively. Get started today to experience a smarter way to manage your systems directly through your chat tool.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","system administration","devops","chatops"],"complexity":"medium","use_cases":["Execute shell commands on a Linux VPS via chat","Remote server management and maintenance","Automating routine sysadmin tasks through chat triggers","Incident response and quick diagnostics from messaging platforms","On-demand deployments or remediation actions executed over SSH"],"estimated_setup_minutes":30,"required_services":["n8n instance","OpenAI (or compatible embedded OpenAI model)","Chat platform (e.g., Slack, Telegram) integrated with n8n","Linux VPS with SSH access","Secure credential storage for SSH keys/passwords (recommended)"],"key_features":["Chat-triggered workflow to start SSH actions","AI SysAdmin ReAct Agent to interpret natural-language commands","Automated mapping of chat inputs to SSH commands","Secure SSH credential usage within the workflow","Supports testing and deployment inside n8n"],"target_audience":["developers","system administrators","DevOps engineers', 'SREs"]}


name: Get GitHub Issue Updates and Send Notifications to Telegram
author_name: Prakash
author_username: prakashbask
categories: []
created_at: 2025-02-26T09:43:30.005Z
updated_at: 2025-02-26T09:43:30.005Z
url: https://n8n.io/workflows/3021
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?  
  This workflow is ideal for:  
  Developers** who want to stay updated on issues without constantly checking GitHub.
  Managers** tracking issue progress in a Telegram group.   
   DevOps teams that need automated notification alerts for new or updated issues.

  What problem does this workflow solve?  
  Keeping track of GitHub issues manually can be tedious. Teams often miss critical updates because notifications are buried in emails or dashboards. This workflow automates the process by fetching new or open GitHub issues and instantly sending notifications to a specified Telegram chat.  

  What this workflow does  
  This workflow connects GitHub and Telegram to provide real-time issue notifications:  
  Fetch GitHub Issues – Retrieves new or open issues from a selected GitHub repository.  
  Format the Issue Details – Extracts key information like issue title, number, status, and URL.  
  Send to Telegram – Posts the formatted issue details to a Telegram group or private chat.  

  Setup Guide  

  Prerequisites  
  Before setting up the workflow, ensure you have:  
  GitHub Personal Access Token**: Required to fetch issue details. Generate it under Developer Settings with repo or public_repo permissions.  
  Telegram Bot Token**: Create a bot via BotFather on Telegram and obtain the token.  
  Telegram Chat ID**: Find the chat ID where the bot should send messages using this method.  

  Step-by-Step Setup  

  Set Up GitHub Node  
     Authenticate using your GitHub token.  
     Choose the repository you want to track.  
     Configure filters (e.g., fetch only open issues).  

  Format Issue Details  
     Extract key details like title, issue number, assignee, and status.  
     Customize the message structure for better readability.  

  Send Message to Telegram  
     Add the Telegram node and enter your bot token.  
     Use the Chat ID to define the recipient.  
     Format the message to include issue details and links.  

  Schedule the Workflow (Optional)  
     Use the Cron node to run this workflow periodically (e.g., every hour).  

  How to Customize This Workflow  
  Filter Issues by Labels**: Modify the GitHub node to fetch only issues with specific labels.  
  Include Additional Fields**: Add issue comments, priority, or assignee details in the message.  
  Send Alerts Based on Priority**: Use conditional logic to send high-priority issues to a different chat.  
  Trigger on Issue Events**: Instead of fetching periodically, use GitHub webhooks (if permitted in the repo) to trigger the workflow on issue creation or updates.  

  Why Use This Workflow?  
  Automates GitHub issue tracking** without manually checking repositories.  
  Instant notifications in Telegram** ensure quick response times.  
  Fully customizable** to fit different team workflows.  

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.filter","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.github"]

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metadata_json:
  {"categories":["integration","automation","notifications","monitoring","collaboration"],"complexity":"medium","use_cases":["Real-time GitHub issue notifications in Telegram","Periodic issue summaries and tracking","Alerting teams about new or updated/high-priority issues","Routing notifications to different chats based on labels or priority","Reducing missed issue updates for distributed teams"],"estimated_setup_minutes":20,"required_services":["GitHub (Personal Access Token)","Telegram Bot API (Bot token and target Chat ID)","(Optional) Publicly reachable n8n endpoint or GitHub Webhooks if using event-driven triggers"],"key_features":["Fetch new or open GitHub issues from a repo","Format and extract issue details (title, number, assignee, status, URL)","Send formatted messages to a Telegram chat or group","Schedule periodic checks with a Cron node","Filter issues by labels or other criteria and apply conditional routing (e.g., high-priority alerts)"],"target_audience":["Developers","Engineering managers","DevOps teams/operators」「Project managers/team leads"]}


name: 🧠 Empower Your AI Chatbot with Long-Term Memory and Dynamic Tool Routing
author_name: Joseph LePage
author_username: joe
categories: []
created_at: 2025-02-27T00:45:40.068Z
updated_at: 2025-02-27T00:45:40.068Z
url: https://n8n.io/workflows/3025
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Empower Your AI Chatbot with Long-Term Memory and Dynamic Tool Routing

  This n8n workflow equips your AI agent with long-term memory and a dynamic tools router, enabling it to provide intelligent, context-aware responses while managing tasks across multiple tools. By combining persistent memory and modular task routing, this workflow makes your AI smarter, more efficient, and highly adaptable.

  👥 Who Is This For?

  AI Developers & Automation Enthusiasts: Integrate advanced AI features like long-term memory and task routing without coding expertise.  
  Businesses & Teams: Automate tasks while maintaining personalized, context-aware interactions.  
  Customer Support Teams: Improve user experience with chatbots that remember past interactions.  
  Marketers & Content Creators: Streamline communication across platforms like Gmail and Telegram.  
  AI Researchers: Experiment with persistent memory and multi-tool integration.

  🚀 What Problem Does This Solve?

  This workflow simplifies the creation of intelligent AI systems that retain memory, manage tasks dynamically, and automate notifications across tools like Gmail and Telegram—saving time and improving efficiency.

  🛠️ What This Workflow Does

  Save & Retrieve Memories**: Uses Google Docs for long-term storage to recall past interactions or user preferences.  
  Dynamic Task Routing**: Routes tasks to the right tools (e.g., saving/retrieving memories or sending notifications).  
  AI-Powered Context Understanding**: Combines OpenAI GPT-based short-term memory with long-term memory for smarter responses.  
  Multi-Channel Notifications**: Sends updates via Gmail or Telegram.

  🔧 Setup

  API Credentials:
     Connect to OpenAI (AI processing), Google Docs (memory storage), Gmail/Telegram (notifications).  
  Customize Parameters:
     Adjust the AI agent's system message for your use case.
     Define task-routing rules in the tools router node.
  Test & Deploy:
     Verify memory saving/retrieval, task routing, and notification delivery.

  💡 How to Customize

  Modify the system message in the OpenAI node to tailor your agent’s behavior.
  Add or adjust routing rules for additional tools.
  Update notification settings to match your communication preferences.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.googleDocs","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.googleDocs","n8n-nodes-base.telegram","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDocs","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDocs","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6908 characters]

metadata_json:
  {"categories":["automation","integration","AI/chatbot","notifications","customer-support"],"complexity":"complex","use_cases":["Context-aware conversational agents that remember past interactions","Customer support chatbots with long-term memory","Automated notifications and alerts via Gmail or Telegram","Multi-tool task routing and orchestration","Personalized assistants for teams, marketing, or content workflows"],"estimated_setup_minutes":45,"required_services":["OpenAI (GPT) for AI processing","Google Docs for long-term memory storage","Gmail (optional) for email notifications","Telegram (optional) for chat notifications","n8n (workflow host)"],"key_features":["Persistent long-term memory storage and retrieval","Short-term/contextual memory via OpenAI","Dynamic tools router to dispatch tasks to appropriate nodes","Multi-channel notification support (Gmail, Telegram)","Customizable system message and routing rules for behavior tuning"],"target_audience":["AI developers","Automation enthusiasts","Businesses and teams building conversational agents or automations"]}


name: Run Apache Airflow DAG and Retrieve XCom Value
author_name: Antonio Cheong
author_username: windoac
categories: []
created_at: 2025-02-27T06:42:48.457Z
updated_at: 2025-02-27T06:42:48.457Z
url: https://n8n.io/workflows/3026
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Run Apache Airflow DAG and Retrieve XCom Value

  What this workflow does

  This workflow integrates the Apache Airflow API DAGRun and XCom. It enables n8n to trigger Airflow DAGs and retrieve the execution results.

  Preparation:

  Update Airflow API Link Prefix

     Navigate to the airflow-api node.
     Update the prefix of the Airflow API link in the format: http(s)://ip:port.
     Example: https://airflow.example.com

  Configure Authentication

     Go to the Airflow: dag_run node.
     Update the Basic Auth credentials with your Airflow username and password.
     Repeat this step for Airflow: dag_run - state and Airflow: dag_run - get result nodes.

     Security Note: Using Basic Authentication requires storing credentials in plaintext. If possible, consider using API Keys or Tokens for enhanced security.

     An example is setting Airflow's API Authentication to basic\_auth. Choose other authentication methods if needed.
     Ensure the user account has the following permissions: can create on DAG Runs, can read on DAG Runs, can read on XComs, can edit on DAGs, and can read on DAGs.

  How to Use:

  To execute this workflow, use the Execute Sub-workflow node with the following input parameters:

  dag\_id**: The DAG ID (name) in Airflow that you want to trigger.
  task\_id**: The Task ID (name) from which you want to retrieve the XCom return\_value.
  conf**: Input data for the Airflow DAG run.
  wait**: Delay (in seconds) between each Airflow: dag_run - state check.
  wait\_time**: The maximum time (in seconds) to wait for Airflow: dag_run - state before returning an error.

  Output:

  The workflow returns the XCom result from Airflow: dag_run - get result.
  The XCom return_value is stored in the value field.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stopAndError","n8n-nodes-base.if","n8n-nodes-base.stopAndError","n8n-nodes-base.httpRequest","n8n-nodes-base.switch","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.set"]

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metadata_json:
  {"categories":["integration","automation","orchestration","data pipelines"],"complexity":"medium","use_cases":["Trigger Airflow DAGs from n8n","Retrieve XCom return_value from a specific task","Pass conf payloads into DAG runs","Monitor DAG run state and wait for completion","Integrate Airflow results into downstream n8n workflows"],"estimated_setup_minutes":15,"required_services":["Apache Airflow (REST API enabled)","n8n instance","Authentication credentials for Airflow (Basic Auth, API key or token)"],"key_features":["Start an Airflow DAG run via API","Poll DAG run state with configurable interval and timeout","Fetch XCom return_value for a specific task","Configurable conf payload for DAG execution","Built-in error handling and timeout reporting"],"target_audience":["developers","data engineers","DevOps engineers / SREs"]}


name: Generate AI Prompts with Google Gemini and store them in Airtable
author_name: Zacharia Kimotho
author_username: imperolq
categories: []
created_at: 2025-02-27T09:18:24.480Z
updated_at: 2025-02-27T09:18:24.480Z
url: https://n8n.io/workflows/3027
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow is designed to generate prompts for AI agents and store them in Airtable. 


  It starts by receiving a chat message, processes it to create a structured prompt, categorizes the prompt, and finally stores it in Airtable.

  2. Setup Instructions

  Prerequisites
  AI model eg Gemini, openAI etc**
  Airtable base and table or other storage tool**

  Step-by-Step Guide

  Clone the Workflow
  Copy the provided workflow JSON and import it into your n8n instance.

  Configure Credentials
  Set up the Google Gemini(PaLM) API account credentials.
  Set up the Airtable Personal Access Token account credentials.

  Map Airtable Base and Table
  Create a copy of the Prompt Library in Airtable.
  Map the Airtable base and table in the Airtable node.

  Customize Prompt Template
  Edit the 'Create prompt' node to customize the prompt template as needed.

  Configuration Options
  Prompt Template:** Customize the prompt template in the 'Create prompt' node to fit your specific use case.
  Airtable Mapping:** Ensure the Airtable base and table are correctly mapped in the Airtable node.

  4. Running and Troubleshooting

  Running the Workflow
  Trigger the Workflow: Send a chat message to trigger the workflow.
  Monitor Execution: Use the n8n interface to monitor the workflow execution.
  Check Completion: Verify that the prompt is stored in Airtable and check the chat interface for the result.

  Troubleshooting Tips
  API Issues:** Ensure that the APIs and Airtable credentials are correctly configured.
  Data Mapping:** Verify that the Airtable base and table are correctly mapped.
  Prompt Template:** Check the prompt template for any errors or inconsistencies.

  Use Case Examples

  This workflow is particularly useful in scenarios where you want to automate the generation and management of AI agent prompts. 

  Here are some examples:

  Rapid Prototyping of AI Agents: 

  Quickly generate and test different prompts for AI agents in various applications.

  Content Creation:** Generate prompts for AI models that create blog posts, articles, or social media content.
  Customer Service Automation:** Develop prompts for AI-powered chatbots to handle customer inquiries and support requests.
  Educational Tools:** Create prompts for AI tutors or learning assistants.

  Industries/Professionals:

  Software Development:** Developers building AI-powered applications.
  Marketing:** Marketers automating content creation and social media management.
  Customer Service:** Customer service managers implementing AI-driven chatbots.

  Education:** Educators creating AI-based learning tools.

  Practical Value:

  Time Savings:** Automates the prompt generation process, saving significant time and effort.

  Improved Prompt Quality:** Leverages Google Gemini and structured prompt engineering principles to generate more effective prompts.

  Centralized Prompt Management:** Stores prompts in Airtable for easy access, organization, and reuse.

  4. Running and Troubleshooting

  Running the Workflow:**
  Activate the workflow in n8n.
  Send a chat message to the webhook URL configured in the "When chat message received" node.
  Monitor the workflow execution in the n8n editor.
  Monitoring Execution:**
  Check the execution log in n8n to see the data flowing through each node and identify any errors.

  Checking for Successful Completion:**
  Verify that a new record is created in your Airtable base with the generated prompt, name, and category.

  Confirm that the "Return results" node sends back confirmation of the prompt in the chat interface.

  Troubleshooting Tips:**
  Error:** 400: Bad Request in the Google Gemini nodes:

  Cause:** Invalid API key or insufficient permissions.
  Solution:** Double-check your Google Gemini API key and ensure that the API is enabled for your project.
  Error:** Airtable node fails to create a record:
  Cause:** Invalid Airtable credentials, incorrect Base ID or Table ID, or mismatched column names.
  Solution:** Verify your Airtable API key, Base ID, Table ID, and column names. Ensure that the data types in n8n match the data types in your Airtable columns.

  Follow me on Linkedin for more 

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.outputParserAutofixing","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.set","n8n-nodes-base.airtable","@n8n/n8n-nodes-langchain.chainLlm"]

workflow_json_compressed:
  [encoded data, 4928 characters]

metadata_json:
  {"categories":["automation","AI/ML","integration","data management"],"complexity":"medium","use_cases":["Rapid prototyping of AI agents","Centralized prompt library management","Content creation (blogs, social media)","Customer service chatbot prompt generation","Educational AI tutor prompt creation"],"estimated_setup_minutes":20,"required_services":["Google Gemini (PaLM) API credentials","Airtable (base and table) with Personal Access Token","n8n instance (with webhook access)","Optional: other AI model credentials (e.g., OpenAI)"],"key_features":["Generate structured prompts from chat messages","Categorize prompts automatically","Store prompts and metadata in Airtable","Customizable prompt template in 'Create prompt' node","Returns confirmation back to chat trigger/endpoint','Monitoring and troubleshooting guidance"],"target_audience":["Developers building AI-powered apps","Marketers automating content creation","Customer service managers implementing chatbots」「Educators creating AI-based learning tools"]}


name: Generate & Upload an Audio Summary of a WordPress (or Woocommerce) Article
author_name: phil
author_username: phil
categories: []
created_at: 2025-02-27T10:20:19.852Z
updated_at: 2025-02-27T10:20:19.852Z
url: https://n8n.io/workflows/3028
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow automates the process of summarizing or transcribing a WordPress article, converting the text into speech using Eleven Labs API, and uploading the resulting MP3 file back to WordPress.

  How It Works	
  Trigger – The workflow starts manually when the user clicks “Test Workflow”.
  Retrieve Article – It fetches a WordPress article based on a given post ID.
  Summarize or Transcribe – An LLM (GPT-4o-mini) generates either:
  	•	A summary of the article, or
  	•	A full transcription, depending on the chosen prompt.
  Generate Speech – The processed text (summary or transcription) is converted into an MP3 audio file using Eleven Labs API.
  Upload MP3 to WordPress – The generated MP3 file is uploaded to WordPress.
  Update WordPress Post – The article is updated with an embedded audio player, allowing users to listen to the summary or transcription.

  Set Up Steps
  	WordPress API Credentials
  	•	Configure your WordPress API credentials in n8n.
  	Eleven Labs API Key
  	•	Obtain an API Key from Eleven Labs and configure it in n8n.
  	Choose Between Summary or Transcription
  	•	Modify the AI prompt to either generate a summary or keep the full transcription.
  	Test the Workflow
  	•	Run the workflow and ensure the MP3 file is correctly generated and uploaded.

  💡 Customization Options
  	•	Modify the AI prompt to switch between a summary and a transcription.
  	•	Change the voice model in Eleven Labs for different speech styles.
  	•	Adjust output format to higher/lower quality MP3.

  🚀 This automation improves content accessibility and engagement by allowing users to listen to a summarized or full version of the article.

  Phil | Inforeole

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.wordpress","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wordpress","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.set"]

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metadata_json:
  {"categories":["automation","content","integration","accessibility"],"complexity":"medium","use_cases":["Create audio summaries of blog posts for accessibility","Repurpose articles into audio for podcasts or social channels","Provide audio transcriptions for SEO and user engagement","Automate creation and upload of audio files to WordPress/WooCommerce products"],"estimated_setup_minutes":20,"required_services":["WordPress API (site with REST access)","LLM API (e.g., OpenAI GPT-4o-mini or compatible)","Eleven Labs Text-to-Speech API"],"key_features":["Fetch WordPress post by ID","Generate summary or full transcription via LLM","Convert text to MP3 using Eleven Labs","Upload MP3 to WordPress media library","Update post with embedded audio player link or shortcode (attach audio to post)"],"target_audience":["content creators","website administrators","marketers and editors involved in repurposing content for audio consumption`,`developers and automation engineers integrating TTS into CMS workflows`,`accessibility specialists"]}


name: Real Estate Daily Deals Automation with Zillow API, Google Sheets and Gmail
author_name: T Zero
author_username: tzero
categories: []
created_at: 2025-02-27T19:18:09.189Z
updated_at: 2025-02-27T19:18:09.189Z
url: https://n8n.io/workflows/3030
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Daily Real Estate Deal Finder Automation


  This automation is aimed to send you daily deals via email every morning at 9AM in real estate markets you are interested in with strict search criteria you provide. It uses ZillowAPI to get up to date listings and RentZestimates. From there it calculates a host of investing metrics such as your Down PMT, Cash on Cash ROI, Monthly Cash Flow, Monthly Maintenance and Vacancy Loss.

  Prerequisites
  N8N account
  Google account with OAuth setup here's a video for help: https://youtu.be/LTuy83t_Rt4?si=0XdpxM7G48gtFDe6
  Google Sheets API enabled
  RapidAPI account with Zillow API credentials 
  Blank Google Sheet created with specific columns

  Step 1: Create a New Workflow
  Create a new workflow in N8N
  Name it something meaningful like "Daily Real Estate Deal Finder"
  Credentials you will need: Google OAuth credentials (here's a video for help: https://www.youtube.com/watch?v=LTuy83t_Rt4&t=22s) Google sheets API enabled, RapidAPI Zillow credentials

  Step 2: Configure Search Parameters in Set Parameters Node
  Define your real estate search criteria as key-value pairs: Example location: "Austin, TX" min_bed: 2 min_bath: 2, min_price: 250000, max_price: 400000, propertyType: "Single Family= True"

  Step 3: Update Google Sheet
  Create a new Google Sheets
  Create the following columns Address, Price, Rent Zestimate, Cash onCash RoI, Monthly CashFlow and Down Pmt
  Make sure your google sheets node in N8N is mapping to the correct columns and the correct sheet

  Troubleshooting Tips
  If Zillow API fails, check your API credentials and request limits
  For calculation errors, verify your formulas in the Code node
  If Google Sheets node fails, ensure proper column mapping
  Always test with a small data set before running in production
  Happy Investing please let me know if you have any questions or trouble

  This workflow will now automatically search for real estate deals matching your criteria, calculate investment metrics, update your tracking spreadsheet, and email you a summary each morning. Here is the entire step by step tutorial to set this up: https://www.youtube.com/watch?v=OSeLeKc375Y&t=6s

nodes_used:
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metadata_json:
  {"categories":["automation","integration","real estate","data processing","notifications"],"complexity":"medium","use_cases":["Daily property deal discovery and alerts","Automated investment metric calculations (ROI, cash flow, down payment)","Centralizing listings into a Google Sheet for tracking","Emailing daily summaries of matching listings","Filtering/property search automation based on custom criteria"],"estimated_setup_minutes":45,"required_services":["n8n account","RapidAPI (Zillow API credentials)","Google account with OAuth (Google Sheets & Gmail access)","Google Sheets API enabled"],"key_features":["Scheduled daily search (runs at 9AM)","Zillow API integration to fetch listings and RentZestimates","Customizable search parameters (location, beds, baths, price range, property type)","Automated investment calculations (Down PMT, Cash-on-Cash ROI, Monthly Cash Flow, maintenance/vacancy loss)","Writes results to a Google Sheet with predefined columns and mapping validation tips"],"target_audience":["Real estate investors","Property analysts","Real estate agents looking for deals/alerts"]}


name: CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage
author_name: Angel Menendez
author_username: djangelic
categories: []
created_at: 2025-02-28T06:21:55.097Z
updated_at: 2025-02-28T06:21:55.097Z
url: https://n8n.io/workflows/3031
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  Workflow Description

  Who is this for?
  This workflow is designed for sales and revenue teams using Gong and Salesforce to track and analyze sales calls. It helps automate the extraction, filtering, and preprocessing of Gong call data for further AI analysis.

  What problem is this solving?
  Sales teams often generate large amounts of call data, but not all calls are relevant for deeper analysis. This workflow filters calls based on predefined criteria, extracts relevant metadata, and formats the data before passing it to an AI processing pipeline.

  What this workflow does
  Triggers on new Gong calls synced to Salesforce** every hour.
  Filters calls based on opportunity stage** (Discovery or Meeting Booked).
  Retrieves Gong call details** via API.
  Formats call data into a structured JSON object** for AI processing.
  Passes the structured data to a Gong Call Preprocessor workflow** for further insights.

  Setup
  Ensure that you have connected Salesforce and Gong APIs with valid credentials.
  Modify the Salesforce query in Get all custom Salesforce Gong Objects to match your organization’s requirements.
  Set the schedule trigger interval in the Run Hourly node if needed.
  Connect this workflow to an AI processing workflow to analyze call transcripts.

  Workflow Templates:
  CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage
  CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization
  CallForge - 03 - Gong Transcript Processor and Salesforce Enricher
  CallForge - 04 - AI Workflow for Gong.io Sales Calls
  CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync
  CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI
  CallForge - 07 - AI Marketing Data Processing with Gong & Notion
  CallForge - 08 - AI Product Insights from Sales Calls with Notion

  How to customize
  Change filtering logic: Adjust the **opportunity stage filter (Check if Opportunity Stage is Meeting Booked or Discovery) to match your sales process.
  Modify data formatting**: Add or remove fields in the Format call into correct JSON Object node to customize the output.
  Adjust trigger frequency**: Change the Run Hourly node to run at a different interval if required.

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metadata_json:
  {"categories":["integration","automation","data processing","sales intelligence"],"complexity":"medium","use_cases":["Filter Gong calls synced to Salesforce by opportunity stage","Preprocess and format call data for AI analysis","Automate scheduled ingestion of sales call metadata","Enrich Salesforce records with call-derived insights via downstream workflows"],"estimated_setup_minutes":20,"required_services":["Gong API","Salesforce API","AI processing workflow / Gong Call Preprocessor (optional downstream)"],"key_features":["Hourly schedule trigger to fetch new Gong calls synced to Salesforce","Filter calls by Opportunity Stage (Discovery or Meeting Booked)","Retrieve full Gong call details via API","Format call data into a structured JSON object for AI processing","Execute downstream workflow for further preprocessing or analysis"],"target_audience":["Sales operations teams","Revenue analysts","Sales engineers / integration developers"]}


name: CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization
author_name: Angel Menendez
author_username: djangelic
categories: []
created_at: 2025-02-28T06:32:14.341Z
updated_at: 2025-02-28T06:32:14.341Z
url: https://n8n.io/workflows/3032
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:32
description:
  CallForge - AI Gong Sales Call Processor  
  Streamline your sales call analysis with CallForge, an automated workflow that extracts, enriches, and refines Gong.io call data for AI-driven insights.

  Who is This For?  
  This workflow is designed for:  
  ✅ Sales teams looking to automate sales call insights.  
  ✅ Revenue operations (RevOps) professionals optimizing call data processing.  
  ✅ Businesses using Gong.io to analyze and enhance sales call transcripts.  

  What Problem Does This Workflow Solve?  
  Manually analyzing sales calls is time-consuming and prone to inconsistencies. While Gong provides raw call data, interpreting these conversations and improving AI-generated summaries can be challenging.  

  With CallForge, you can:  
  ✔️ Automate transcript extraction from Gong.io.  
  ✔️ Enhance AI insights by adding product and competitor data.  
  ✔️ Reduce errors from AI-generated summaries by correcting mispronunciations.  
  ✔️ Eliminate duplicate calls to prevent redundant processing.  

  What This Workflow Does  

  1. Extracts Gong Call Data  
  Retrieves call recordings, metadata, meeting links, and duration from Gong.  

  2. Removes Duplicate Entries  
  Queries Notion** to ensure that already processed calls are not duplicated.  

  3. Enriches Call Data  
  Fetches integration details** from Google Sheets.  
  Retrieves competitor insights** from Notion.  
  Merges data** to provide AI with a more comprehensive context.  

  4. Prepares AI-Friendly Transcripts  
  Cleans up transcripts** for structured AI processing.  
  Reduces prompt complexity** for more accurate OpenAI outputs.  

  5. Sends Processed Data to an AI Call Processor  
  Delivers the cleaned and enriched transcript** to an AI-powered workflow for generating structured call summaries.  

  How to Set Up This Workflow  

  1. Connect Your APIs  
  🔹 Gong API Access – Set up your Gong API credentials in n8n.  
  🔹 Google Sheets Credentials – Provide API access for retrieving integration data.  
  🔹 Notion API Setup – Connect Notion to fetch competitor insights and store processed data.  
  🔹 AI Processing Workflow – Ensure an OpenAI-powered workflow is in place for structured summaries.  

  CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage
  CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization
  CallForge - 03 - Gong Transcript Processor and Salesforce Enricher
  CallForge - 04 - AI Workflow for Gong.io Sales Calls
  CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync
  CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI
  CallForge - 07 - AI Marketing Data Processing with Gong & Notion
  CallForge - 08 - AI Product Insights from Sales Calls with Notion

  2. Customize to Fit Your Needs  
  💡 Modify Data Sources – Update connections if using a different CRM, database, or analytics tool.  
  💡 Adjust AI Processing Logic – Optimize transcript formatting based on your preferred AI model.  
  💡 Expand Data Enrichment – Integrate CRM data, industry benchmarks, or other insights.  

  Why Use CallForge?  
  By automating Gong call processing, CallForge empowers sales teams to:  
  📈 Gain valuable AI-driven insights from calls.  
  ⚡ Speed up decision-making with cleaner, structured data.  
  🛠 Improve sales strategies based on enriched, accurate transcripts.  

  🚀 Start automating your Gong call analysis today!

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metadata_json:
  {"categories":["automation","integration","data processing","sales enablement","AI summarization"],"complexity":"medium","use_cases":["Automated extraction and enrichment of Gong call transcripts","Deduplication of processed calls to avoid redundant work","Preparing and cleaning transcripts for AI-driven summaries","Augmenting call data with product and competitor context from Sheets/Notion","Feeding enriched call data to an OpenAI (or other) AI workflow for structured insights"],"estimated_setup_minutes":45,"required_services":["Gong API","Google Sheets API","Notion API","OpenAI (or other AI/LLM service)","n8n (workflow runner)"],"key_features":["Retrieves recordings, metadata and meeting links from Gong","Checks Notion to prevent duplicate processing","Fetches integration and enrichment data from Google Sheets","Pulls competitor insights from Notion and merges context","Cleans and formats transcripts for AI-friendly prompts to reduce errors (e.g., mispronunciations)"],"target_audience":["Sales teams","Revenue Operations (RevOps)","Sales Ops / Enablement professionals implementing call analytics workflows」「Data analysts and AI engineers configuring call summarization pipelines"]}


