# templates

name: Smart Sales Support Chatbot with GPT-4o and Google Sheets
author_name: Babish Shrestha
author_username: bbz
categories: []
created_at: 2025-04-04T09:13:57.734Z
updated_at: 2025-04-04T09:13:57.734Z
url: https://n8n.io/workflows/3433
scraped_at: 2025-12-24 13:02:42
description:
  Who is this tempate for?
  This workflow powers a simple yet effective customer and sales support chatbot for your webshop. It's perfect for solopreneurs who want to automate customer interactions without relying on expensive or complex support tools.

  How it works?
  The chatbot listens to user requests—such as checking product availability—and automatically handles the following

  Fetches product information from a Google Sheet
  Answers customer queries
  Places an order
  Updates the stock after a successful purchase

  Everything runs through a single Google Sheet used for both stock tracking and order management.

  Setup Instructions

  Before you begin, connect your Google Sheets credentials by following this guide: This will be used to connect all the tools to Google Sheets
  👉 Setup Google sheets credentials

  Get Stock

  	Open "Get Stock" tool node and select the Google sheet credentials you created. 
  	Choose the correct google sheet document and sheet name and you are done.
  Place order
  	
  	Go to your "Place Order" tool node and select the Google sheet credentials you have created. 
  	Choose the correct google sheet document and sheet name.

  Update Stock
  	- Open your "Update Stock" tool node and select the Google sheet credentials you have created. 
  	Choose the correct google sheet document and sheet name.
  	In "Mapping Column Mode" section select map each column manually.
  	In "Column to match on" select the column with a unique identifier (e.g., Product ID) to match stock items.
  	In values to update section, add only the column(s) that need to be updated—usually the stock count.
  AI Agent node 
  	Adjust the prompt according to your use case and customize what you need. 

  Google Sheet Template
  Stock sheet

  |Case ID|Phone Model|Case Name|Case Type|Image URL|Quantity Avaialble|Initital Inventory|Sold|
  |-|-|-|-|-|-|-|-|
  |1023|Iphone 14 pro|Black Leather|Magsafe|https://example.com/url|90|100|10

  Order sheet

  |Case ID|Phone Model|Case Name|Name|Phone Number|Address|
  |-|-|-|-|-|-|
  |1023|Black Leather |Iphone 14 pro|Fernando Torres|9998898888|Paris, France

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheetsTool"]

workflow_json_compressed:
  [encoded data, 4752 characters]


name: Get Qualified Leads in One Click from Apollo to Airtable
author_name: Not Another Marketer
author_username: notanothermarketer
categories: []
created_at: 2025-04-04T11:10:06.804Z
updated_at: 2025-04-04T11:10:06.804Z
url: https://n8n.io/workflows/3435
scraped_at: 2025-12-24 13:02:42
description:
  You Don’t Need More Tools. You Just Need the Right Leads.
  Why spend $1,000s on lead gen when your perfect leads are already waiting in Apollo? You’ve already filtered the ideal prospects. You know who they are, where they work, and what they do.

  Now imagine turning that list into enriched, ready-to-contact leads—without paying pricey Apollo's recurring subscription (spoiler: you will pay only 0.60$ per 500 leads).

  From Filter to Outreach-Ready in Seconds
  With the Lead Generation System, you just drop your Apollo search URL.

  The workflow does the rest:
  ✅ Scrapes all matching contacts from your Apollo filter
  ✅ Enriches and organizes the data (names, roles, emails, LinkedIns, companies, etc.)
  ✅ Delivers the final lead list to Airtable—or your CRM of choice

  No more manual exports. 
  No CSV mess. 
  No VA needed.
  Just qualified leads, cleaned and ready to go.

  Perfect For
  Founders doing DIY outbound
  Growth marketers scaling cold email
  Agencies running lead-gen for clients
  Anyone tired of paying too much for messy, outdated lists

  Setup Guide
  I built a step-by-step guide to setup this workflow in 5 to 10 minutes, available here: https://notanothermarketer.gitbook.io/home/templates/lead-generation

  This template is free. Enjoy!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.if"]

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name: Send links from Telegram Channel to Hoarder and Readeck
author_name: Sherlockes
author_username: sherlockes
categories: []
created_at: 2025-04-04T11:19:47.480Z
updated_at: 2025-04-04T11:19:47.480Z
url: https://n8n.io/workflows/3436
scraped_at: 2025-12-24 13:02:47
description:
  What this template is made for:
  I have a personal Telegram channel and a bot inside it where I save interesting links that I want to save or read later. The idea is that n8n will take care of reading the new links added to this channel and send them, through the corresponding API, to the Hoarder and Readeck installations.

  How it works
  Since my server where n8n runs is not always on, a "Schedule Trigger" will be responsible for checking every so often if there is any new content in the Telegram channel where I store the links. This request is made through "http request" and the Telegram API.
  Next, a code block is responsible for filtering out everything that is not a hyperlink.
  At this point, the flow splits into two so that parallel and similar processes are performed for Hoarder and Readeck.
  The corresponding API is accessed to get a list of all the links saved in the corresponding service.
  A code block is responsible for filtering the list of hyperlinks previously obtained from Telegram so that only those that are not already saved in the service continue.
  Finally, another "Http Request" node is responsible for using the service API to save the link in the corresponding service.

  Configuration instructions
  The template makes use of the environment variables that I have declared in the n8n "docker-compose.yml" file through an external ".env" file. These are the variables I use:
  Telegram Bot Token Sherlink
  TG_SHERLINK_BOT_TOKEN=XXXXXXXX:XXXXXXXXXXXXXXXX
  Id Telegram Channel Sherlink
  TG_SHERLINK_ID=-XXXXXXXXXXXXX
  Readeck server
  READECK_SERVER=http://readeck.midomain.com
  READECK_API_KEY=xxxxxxxxxxxxx
  Hoarder server
  HOARDER_SERVER=http://hoarder.midomain.com
  HOARDER_API_KEY=xxxxxxxxxxxxxx

  Created in 1.85.4 n8n version

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.httpRequest"]

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name: Automatically Create Cinematic Quote Videos with AI and Upload to YouTube
author_name: Jaruphat J.
author_username: jaruphatj
categories: []
created_at: 2025-04-05T01:03:46.035Z
updated_at: 2025-04-05T01:03:46.035Z
url: https://n8n.io/workflows/3438
scraped_at: 2025-12-24 13:02:44
description:
  ⚠️ Important Disclaimer:
  This template is only compatible with a self-hosted n8n instance using a community node.
  Who is this for?
  This workflow is ideal for digital content creators, marketers, social media managers, and automation enthusiasts who want to produce fully automated vertical video content featuring inspirational or motivational quotes. Specifically tailored for Thai language, it effectively demonstrates integration of AI-generated imagery, video, ambient sound, and visually appealing quote overlays.

  What problem is this workflow solving?
  Manually creating high-quality, vertically formatted quote videos is often repetitive, time-consuming, and involves multiple tedious steps like selecting suitable visuals, editing audio tracks, and correctly overlaying text. Additionally, manual uploading to platforms like YouTube and maintaining accurate content records are prone to errors and inefficiencies.

  What this workflow does:
  Fetches a quote, author, and scenic background description from a Google Sheet.
  Automatically generates a vertical background image using the Flux AI (txt2img) API.
  Transforms the AI-generated image into a subtly animated cinematic vertical video using the Kling video-generation API.
  Generates an immersive, ambient background sound using ElevenLabs’ sound generation API.
  Dynamically overlays the selected Thai-language quote and author text onto the generated video using FFmpeg, ensuring visually appealing typography (e.g., Kanit font).
  Automatically uploads the final video to YouTube.
  Updates the resulting YouTube video URL back to the Google Sheet, keeping your content records current and well-organized.

  Setup
  Requirements:
  This workflow requires a self-hosted n8n instance, as the execution of FFmpeg commands is not supported on n8n Cloud. Ensure FFmpeg is installed on your self-hosted environment.

  API keys and accounts setup for Flux, Kling, ElevenLabs, Google Sheets, Google Drive, and YouTube.

  Google Sheets Setup:
  Your Google Sheet must include these columns:
  Index**	Unique identifier for each quote
  Quote (Thai)**	Quote text in Thai language (or your chosen language)
  Pen Name (Thai)**	Author or pen name of the quote's creator
  Background (EN)**	Short English description of the scene (e.g., "sunrise over mountains")
  Prompt (EN)**	Detailed English prompt describing the image/video scene (e.g., "peaceful sunrise with misty mountains")
  Background Image**	URL of AI-generated image (updated automatically)
  Background Video**	URL of generated video (updated automatically)
  Music Background**	URL of generated ambient audio (updated automatically)
  Video Status**	YouTube URL (updated automatically after upload)
  A ready-to-use Google Sheets template is provided [here (provide your actual link)].

  To help you get started quickly, you can use this template spreadsheet.
  Next steps:
  Authenticate Google Sheets, Google Drive, YouTube API, Flux AI, Kling API, and ElevenLabs API within n8n.
  Ensure FFmpeg supports fonts compatible with your chosen language (for Thai, "Kanit" font is recommended).
  Prepare your Google Sheets with desired quotes, authors, and image/video prompts.
  How to customize this workflow to your needs:
  Fonts:** Adjust font type, size, color, and positioning within the provided FFmpeg commands in the workflow’s code nodes. Verify that selected fonts properly support your target language.
  Media Customization:** Customize the scene descriptions in your Google Sheet to change image/video backgrounds automatically generated by AI.
  Quote Management:** Easily manage, add, or update quotes and associated details directly via Google Sheets without workflow modifications.
  Audio Ambiance:** Customize or adjust the ambient sound prompt for ElevenLabs within the workflow’s HTTP Request node to match your video's desired mood.

  Benefits of using AI-generated content and localized fonts:
  Leveraging AI-generated visual and audio elements along with localized fonts greatly enhances audience engagement by creating visually appealing, professional-quality content tailored specifically for your target audience. This automated workflow drastically reduces production time and manual effort, enabling rapid, consistent content creation optimized for platforms such as YouTube Shorts, Instagram Reels, and TikTok.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","n8n-nodes-base.readWriteFile","n8n-nodes-base.httpRequest","n8n-nodes-base.readWriteFile","n8n-nodes-base.code","n8n-nodes-base.executeCommand","n8n-nodes-base.httpRequest","n8n-nodes-base.readWriteFile","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 7928 characters]


name: Validate Seatable Webhooks with HMAC SHA256 Authentication
author_name: Vitali
author_username: vquie
categories: []
created_at: 2025-04-05T09:40:14.968Z
updated_at: 2025-04-05T09:40:14.968Z
url: https://n8n.io/workflows/3439
scraped_at: 2025-12-24 13:02:46
description:
  📌 Validate Seatable Webhooks with HMAC SHA256 Authentication

  This mini workflow is designed to securely validate incoming Seatable webhooks using HMAC SHA256 signature verification.

  🔐 What it does:
  Listens for incoming Seatable webhook requests.
  Calculates a SHA256 HMAC hash of the raw request body using your shared secret.
  Compares the computed hash with the x-seatable-signature header (after removing the sha256= prefix).
  If the hashes match: responds with 200 OK and forwards the request to subsequent nodes.
  If the hashes don’t match: responds with 403 Forbidden.

  ⚠️ Important Notes:
  This workflow is provided as a template and is not intended to work standalone. Please duplicate it and integrate it with your custom logic at the "Add nodes for processing" node.

  Configuration steps:
  Set your secret key in the “Calculate sha256” crypto node (replace the placeholder).
  Adjust the webhook path to suit your environment (or set it to "manual" for testing).
  Connect your actual logic after the verification step.

nodes_used:
  ["n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.crypto","n8n-nodes-base.webhook","n8n-nodes-base.noOp","n8n-nodes-base.if","n8n-nodes-base.stickyNote"]

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name: Track LLM Token Costs per Customer Using the Langchain Code Node
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-05T10:50:28.430Z
updated_at: 2025-04-05T10:50:28.430Z
url: https://n8n.io/workflows/3440
scraped_at: 2025-12-24 13:02:46
description:
  Note: This template only works for self-hosted n8n.

  This n8n template demonstrates how to use the Langchain code node to track token usage and cost for every LLM call.

  This is useful if your templates handle multiple clients or customers and you need a cheap and easy way to capture how much of your AI credits they are using.

  How it works
  In our mock AI service, we're offering a data conversion API to convert Resume PDFs into JSON documents.
  A form trigger is used to allow for PDF upload and the file is parsed using the Extract from File node.
  An Edit Fields node is used to capture additional variables to send to our log.
  Next, we use the Information Extractor node to organise the Resume data into the given JSON schema.
  The LLM subnode attached to the Information Extractor is a custom one we've built using the Langchain Code node.
  With our custom LLM subnode, we're able to capture the usage metadata using lifecycle hooks.
  We've also attached a Google Sheet tool to our LLM subnode, allowing us to send our usage metadata to a google sheet.
  Finally, we demonstrate how you can aggregate from the google sheet to understand how much AI tokens/costs your clients are liable for.


  Check out the example Client Usage Log - https://docs.google.com/spreadsheets/d/1AR5mrxz2S6PjAKVM0edNG-YVEc6zKL7aUxHxVcffnlw/edit?usp=sharing

  How to use
  SELF-HOSTED N8N ONLY** - the Langchain Code node is only available in the self-hosted version of n8n. It is not available in n8n cloud.
  The LLM subnode can only be attached to non-"AI agent" nodes; Basic LLM node, Information Extractor, Question & Answer Chain, Sentiment Analysis, Summarization Chain and Text Classifier.

  Requirements
  Self-hosted version of n8n 
  OpenAI for LLM
  Google Sheets to store usage metadata

  Customising this template
  Bring the custom LLM subnode into your own templates! In many cases, it can be a drop-in replacement for the regular OpenAI subnode.
  Not using Google Sheets? Try other databases or a HTTP call to pipe into your CRM.

nodes_used:
  ["n8n-nodes-base.googleSheetsTool","n8n-nodes-base.set","n8n-nodes-base.formTrigger","@n8n/n8n-nodes-langchain.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.form","n8n-nodes-base.filter","n8n-nodes-base.googleSheets","n8n-nodes-base.summarize","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.informationExtractor"]

workflow_json_compressed:
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name: Generate Conversational Twitter/X Threads with GPT-4o AI
author_name: joseph
author_username: josephn8n
categories: []
created_at: 2025-04-05T17:33:45.203Z
updated_at: 2025-04-05T17:33:45.203Z
url: https://n8n.io/workflows/3441
scraped_at: 2025-12-24 13:02:46
description:
  🧵 Generate Conversational Twitter/X Threads with GPT-4o AI (n8n Workflow)
  This workflow uses OpenAI (GPT-4o) and Twitter/X to automatically generate and publish engaging, conversational threads in response to a trigger (e.g., from a chatbot or form).

  🚀 What Does It Do?
  Listens for an incoming message (e.g., via webhook or another n8n input).
  Uses GPT-4o to craft a narrative-style Twitter thread in a personal, friendly tone.
  Publishes the first tweet, then automatically posts each following tweet as a reply—building a full thread.

  🛠️ What Do You Need to Configure?
  Before using this template, make sure to set up the following credentials:

  OpenAI
  Add your OpenAI API key in the OpenAI Chat Model node. This is used to generate the thread content.

  Twitter/X
  Add your Twitter OAuth2 credentials to the First Tweet and Thread Reply nodes. This allows the workflow to publish tweets on your behalf.

  ✨ Who Is This For?
  This template is perfect for:
  Content creators who want to share ideas regularly
  Personal brands looking to grow their presence
  Social media managers automating thread creation

  🔧 How to Customize It
  You can easily adjust the tone, structure, or length of the threads by modifying the system prompt in the OpenAI node.

  For example:
  To create threads with humor, change the prompt to “Write in a witty and humorous tone.”
  To tailor it for marketing, prompt it with “Write a persuasive product-focused Twitter thread.”

  You can also integrate this workflow with:
  Telegram bots
  Web forms (e.g., Typeform, Tally)
  CRM tools or newsletter platforms


  📋 Sample Output
  Prompt sent to the workflow:
  “Tips for growing on Twitter in 2025”

  Generated thread:

  ++Tweet 1:++
  Thinking of growing your presence on Twitter/X in 2024? Here's a thread with the most effective strategies that actually work 🧵

  ++Reply 1:++
  Engage, don’t broadcast
  Twitter is a conversation platform. Reply to others, quote-tweet, and start discussions instead of just posting links.

  ++Reply 2:++
  Consistency beats virality
  Tweeting regularly builds trust and visibility. You don't need to go viral — just show up.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.twitterTool","n8n-nodes-base.twitterTool","@n8n/n8n-nodes-langchain.agent"]

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name: Fully Automated AI Video Generation & Multi-Platform Publishing
author_name: Juan Carlos Cavero Gracia
author_username: carlosgracia
categories: []
created_at: 2025-04-05T18:28:46.255Z
updated_at: 2025-04-05T18:28:46.255Z
url: https://n8n.io/workflows/3442
scraped_at: 2025-12-24 13:02:41
description:
  Description

  This comprehensive n8n automation template orchestrates a complete end-to-end workflow for generating engaging short-form Point-of-View (POV) style videos using multiple AI services and automatically publishing them across major social media platforms. It takes ideas from a Google Sheet and transforms them into finished videos with captions, voiceovers, and platform-specific descriptions, ready for distribution.

  Who Is This For?

  Content Creators & Agencies:** Mass-produce unique short-form video content for various clients or channels with minimal manual effort.
  Digital Marketers:** Automate video content pipelines to boost online presence and engagement across multiple platforms simultaneously.
  Social Media Managers:** Schedule and distribute consistent video content efficiently without juggling multiple tools and manual uploads.
  Businesses:** Leverage AI to create branded video content for marketing, reducing production time and costs.

  What Problem Does This Workflow Solve?

  Creating and distributing high-quality short-form video content consistently across multiple social networks is incredibly time-consuming and resource-intensive. This workflow tackles these challenges by:

  Automating Idea-to-Video Pipeline:** Generates video concepts, image prompts, scripts, images, video clips, and voiceovers using AI.
  Streamlining Video Assembly:** Automatically combines generated assets into a final video using a template.
  Generating Platform-Optimized Descriptions:** Creates relevant descriptions for posts by transcribing the final video audio.
  Automating Multi-Platform Publishing:** Uploads the final video and description to TikTok, Instagram, YouTube, Facebook, and LinkedIn simultaneously.
  Reducing Manual Workload:** Drastically cuts down the time and effort required for video production and distribution.
  Centralized Tracking:** Updates a Google Sheet with results, costs, and status for easy monitoring.

  How It Works

  Trigger & Input: Runs on a daily schedule (configurable) and fetches new video ideas from a designated Google Sheet.
  AI Content Generation:
      Uses OpenAI to generate video captions and image prompts based on the idea.
      Uses PiAPI (Flux) to generate images from prompts.
      Uses PiAPI (Kling) to generate video clips from the images (Image-to-Video).
      Uses OpenAI to generate a voiceover script based on the captions.
      Uses ElevenLabs to generate voiceover audio from the script and uploads it to Google Drive.
  Video Assembly: Combines the generated video clips, captions, and voiceover audio using a Creatomate template to render the final video.
  Description Generation: Uploads the final video to Google Drive, extracts the audio using OpenAI (Whisper), and generates a social media description using OpenAI (GPT).
  Multi-Platform Distribution: Uses upload-post.com to upload the final video and generated description to TikTok, Instagram, YouTube, Facebook, and LinkedIn.
  Tracking & Notification: Updates the original Google Sheet row with output details (video link, costs, tokens used) and sends a completion notification via Discord.

  Setup

  Accounts & API Keys: Obtain accounts and generate API keys/credentials for:
      n8n
      Google Cloud Platform (for Google Sheets & Google Drive APIs + OAuth Credentials)
      OpenAI
      PiAPI
      ElevenLabs
      Creatomate
      upload-post.com
      Discord (Webhook URL)
  Google Sheet: Make a copy of the provided Google Sheet Template and connect it in the Load Google Sheet node.
  Creatomate Template: Set up a video template in Creatomate (use the provided JSON source code as a base) and note its Template ID.
  Configure Nodes:
      Enter all API Keys/Credentials in the Set API Keys node and other relevant credential sections (Google nodes, upload-post nodes, etc.).
      Configure Google Drive nodes (Folder IDs, Permissions).
      Configure the upload-post.com nodes with your user identifier and necessary platform details (e.g., Facebook Page ID).
      Customize AI prompts within the OpenAI nodes (Generate Video Captions, Generate Image Prompts, Generate Script, Generate Description...) if desired.
      Set the Discord Webhook URL in the Notify me on Discord node.
  Enable Google APIs: Ensure Google Drive API and Google Sheets API are enabled in your Google Cloud Project.

  Requirements

  Accounts:** n8n, Google (Sheets, Drive, Cloud Platform), OpenAI, PiAPI, ElevenLabs, Creatomate, The social media api Upload-Post, Discord.
  API Keys & Credentials:** API Keys for OpenAI, PiAPI, ElevenLabs, Creatomate, upload-post.com. Google Cloud OAuth 2.0 Credentials. Discord Webhook URL.
  Templates:** A configured Google Sheet based on the template, a configured Creatomate video template.
  (Potentially) Paid Plans:** Some services (OpenAI, PiAPI, Creatomate, upload-post.com) may require paid plans depending on usage volume after free trials/credits are exhausted.

  Use this template to build a powerful, automated video content factory, scaling your production and distribution efforts across the social media landscape.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.stickyNote","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.discord","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.readBinaryFile","n8n-nodes-base.writeBinaryFile"]

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name: Scrape business leads from Google Maps using OpenAI and Google Sheets
author_name: Dr. Firas
author_username: drfiras
categories: []
created_at: 2025-04-05T19:50:44.805Z
updated_at: 2025-04-05T19:50:44.805Z
url: https://n8n.io/workflows/3443
scraped_at: 2025-12-24 13:02:41
description:
  Google Maps Data Extraction Workflow for Lead Generation

  This workflow is ideal for sales teams, marketers, entrepreneurs, and researchers looking to efficiently gather detailed business information from Google Maps for:

  Lead generation  
  Market analysis  
  Competitive research

  Who Is This Workflow For?

  Sales professionals** aiming to build targeted contact lists  
  Marketers** looking for localized business data  
  Researchers** needing organized, comprehensive business information  

  Problem This Workflow Solves

  Manually gathering business contact details from Google Maps is:

  Tedious  
  Error-prone  
  Time-consuming  

  This workflow automates data extraction to increase efficiency, accuracy, and productivity.

  What This Workflow Does

  Automates extraction of business data (name, address, phone, email, website) from Google Maps  
  Crawls and extracts additional website content  
  Integrates OpenAI to enhance data processing  
  Stores structured results in Google Sheets for easy access and analysis  
  Uses Google Search API to fill in missing information  

  Setup

  Import the provided n8n workflow JSON into your n8n instance.  
  Set your OpenAI and Google Sheets API credentials.  
  Provide your Google Maps Scraper and Website Content Crawler API keys.  
  Ensure SerpAPI is configured to enhance data completeness.  

  Customizing This Workflow to Your Needs

  Adjust scraping parameters:
    Location  
    Business category  
    Country code  
  Customize Google Sheets output format to fit your current data structure  
  Integrate additional AI processing steps or APIs for richer data enrichment  

  Final Notes

  This structured approach ensures:

  Accurate and compliant data extraction** from Google Maps  
  Streamlined lead generation  
  Actionable and well-organized data ready for business use  

  📄 Documentation: Notion Guide

  Demo Video

  🎥 Watch the full tutorial here: YouTube Demo

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolSerpApi","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote"]

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name: Redis Locking for Concurrent Task Handling
author_name: Geoffrey Saxena
author_username: geffy
categories: []
created_at: 2025-04-06T08:12:44.136Z
updated_at: 2025-04-06T08:12:44.136Z
url: https://n8n.io/workflows/3444
scraped_at: 2025-12-24 13:02:46
description:
  👤 Who is this for?

  This workflow is great for n8n users who want to prevent duplicate or overlapping workflow runs. If you're a developer, DevOps engineer, or automation enthusiast managing tasks like database updates, syncing tools, or hitting rate-limited APIs, this one’s for you.

  🧩 What problem does this solve?

  In the real world, automations can get triggered at the same time—whether that’s because of multiple webhook calls, overlapping schedules, or retries. And when two workflows try to do the same thing at once (like updating a record or syncing data), it can cause conflicts, data corruption, or wasted API calls.

  This workflow helps avoid that problem by using Redis as a lock system, so only one instance runs at a time. Think of it like putting up a “🚧 Workflow in Progress” sign while your logic is running.

  ⚙️ What this workflow does

  When the workflow starts, it tries to set a Redis key as a lock with a short expiry.
  If the lock is free:
     Your main business logic runs.
     Once it's done, the lock is cleared.
  If the lock is already taken (i.e., another run is in progress):
     The workflow will wait and retry a few times.
  If a duplicate request shows up while one is already being processed:
     It skips that duplicate to avoid unnecessary work.

  You can customize both the timeout and retry logic to match your needs.

  🛠️ Setup guide

  To use this template:

  You’ll need access to a Redis instance (either self-hosted or managed like Upstash, Redis Cloud, etc).
  Set up your Redis credentials in the n8n Redis node.
  Swap out the webhook node with your actual trigger or logic.
  Adjust the lock timeout to match how long your task typically takes.

  &gt; 💡 Bonus Tip: Use this pattern wherever you need idempotency or want to avoid duplicate processing.

  🧪 Example use case

  Let’s say you have a workflow that syncs ClickUp tickets to Google Sheets. It runs daily at 9 AM and updates tickets, adds notes, and makes sure nothing is missed.

  But what if two runs start at the same time? Or someone triggers a manual sync while the scheduled one is still working?

  By wrapping that whole sync inside this Redis locking template, you can make sure it only runs one at a time, saving your APIs (and your sanity).

nodes_used:
  ["n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.webhook","n8n-nodes-base.code","n8n-nodes-base.redis","n8n-nodes-base.redis","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.redis","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Convert n8n tags into folders and move workflows
author_name: Zacharia Kimotho
author_username: imperolq
categories: []
created_at: 2025-04-06T08:40:16.391Z
updated_at: 2025-04-06T08:40:16.391Z
url: https://n8n.io/workflows/3445
scraped_at: 2025-12-24 13:02:47
description:
  N8n recently introduced folders and it has been a big improvement on workflow management on top of the tags.

  This means the current workflows need to be moved manually to the folders. 

  The simplest idea to try is to convert the current tags into folders and move all the current workflows within the respective tags into the folders

  This assumes the tag name will be used as the folder name.

  To Note

  For workflows that use more than 1 tag, the workflow will be assigned the last tag that runs as the folder. 

  How does it work
  I took the liberty of simplifying the setup of this workflow that will be needed on your part and also be beginner-friendly 

  Copy and paste this workflow into your n8n canvas. You must have existing workflows and tags before you can run this
  Set your n8n login details on the node set Credentials with the n8n URL, username, and password.
  Setup your n8n API credentials on the n8n node get workflows
  Run the workflow. This opens up a form where you can select the number of tags to move and click on submit
  The workflow responds with the successful number of workflows that were imported 


  Read more about the template

  Built by Zacharia Kimotho - Imperol

nodes_used:
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name: Daily Newsletter Service using Excel, Outlook and AI
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-06T14:53:44.596Z
updated_at: 2025-04-06T14:53:44.596Z
url: https://n8n.io/workflows/3446
scraped_at: 2025-12-24 13:02:42
description:
  This n8n template builds a newsletter ("daily digest") delivery service which pulls and summarises the latest n8n.io template in select categories defined by subscribers.

  It's scheduled to run once a day and sends the newsletter directly to subscriber via a nicely formatted email. If you've had trouble keeping up with the latest and greatest templates beign published daily, this workflow can save you a lot of time!

  How it works
  A scheduled trigger pulls a list of subscribers (email and category preferences) from an Excel workbook.
  We work out unique categories amongst all subscribers and only fetch the latest n8n website templates from these categories to save on resources and optimise the number of API calls we make.
  The fetched templates are summarised via AI to produce a short description which is more suitable for our email format.
  For each subscriber, we filter and collect only the templates relevant to their category preferences (as defined in the Excel) and ensure that duplicate templates or those which have been "seen before" are omitted.
  A HTML node is then used to generate the email newsletter. HTML emails are the perfect format since we can add links back to the template.
  Finally, we use the Outlook node to send the email digest to the subscriber.

  How to use
  Populate your Excel sheet with 3 columns: name, email and categories. Categories is a comma-delimited list of categories which match the n8n template website. The available categories are AI, SecOps, Sales, IT Ops, Marketing, Engineering, DevOps, Building Blocks, Design, Finance, HR, Other, Product and Support.
  To subscribe a new user, simply add their email to the Excel sheet with at least one category.
  To unsubscribe a user, remove them from the sheet.
  If you're not interested in paid templates, you may want to filter them out after fetching.

  Requirements
  Microsoft Excel for subscriber list
  Microsoft Outlook for delivering emails
  OpenAI for AI-generated descriptions

  Customising the workflow
  Use AI to summarise the week's trend of templates types and use-cases
  This template can be the basis for other similar newsletters - just pull in a list of things from anywhere!

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.microsoftExcel","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.splitInBatches","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.removeDuplicates","n8n-nodes-base.splitOut","n8n-nodes-base.aggregate","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.html","n8n-nodes-base.set","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.set","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.splitInBatches","n8n-nodes-base.stickyNote"]

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name: Manage Calendar Events with Slack Using OpenAI-Powered Outlook Assistant
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-06T18:35:30.751Z
updated_at: 2025-04-06T18:35:30.751Z
url: https://n8n.io/workflows/3449
scraped_at: 2025-12-24 13:02:46
description:
  This n8n template demonstrates how easy it is to build an Outlook Calendar Assistant powered by an AI agent equipped with Tools.

  For teams using Outlook Calendar and Slack who need easier calendar management, this workflow can be a great first step to introducing powerful AI tools into your daily activities.

  How it works
  A Slack Trigger node is configured to catch "bot mentions" events in a designated channel.
  The message is parsed using the Edit fields node to extract only the required attributes of the event.
  An AI Agent equipped with Outlook Calendar Tools enables question and answer capability for the organisation's shared calendars and events.
  The AI agent's response is sent back to Slack as a reply to the user's query.

  How to use
  The workflow is triggered via @mention-ing the bot followed by the query. eg. "@bot how many meetings does Paul have to attend to this week?"
  To start listening to real mentions, you must activate the workflow and set it to production mode. You must use the production webhook URL for the event subscription.

  Some sample queries to try
  "What's included in the product team's sprint demo this week?"
  "Who's booked room 7 for this Thursday?"
  "When is Jim & Nik's sales meeting with Microsoft?"

  Requirements
  Slack for Chat and Trigger.
    To get connected to Slack, see the official n8n docs for Slack Credentials.
  Outlook for Agent Tools
    To get connected to Outlook, see the official n8n docs for Outlook Credentials.

  Customising this workflow
  Not using Slack? This template can be modified to work with Teams but requires a little more configuration.
  Agents can have any number of tools but an overloaded agent is prone to confusion! If this happens, try splitting into multiple agents serving separate needs.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftOutlookTool","n8n-nodes-base.microsoftOutlookTool","n8n-nodes-base.microsoftOutlookTool","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.slack","n8n-nodes-base.respondToWebhook","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Auto-Generate YouTube Chapters with Gemini AI & YouTube Data API v3
author_name: irfan saeed
author_username: irfansaeed
categories: []
created_at: 2025-04-06T18:49:17.804Z
updated_at: 2025-04-06T18:49:17.804Z
url: https://n8n.io/workflows/3450
scraped_at: 2025-12-24 13:02:44
description:
  Auto-Generate YouTube Chapters with AI-Powered Transcript Analysis  
  Overview  
  This workflow uses YouTube Data API v3  and Google Gemini 1.5 Flash AI  to automatically generate timestamped chapters for videos by analyzing SRT captions. It enhances viewer navigation, improves SEO , and saves creators time by automating manual tasks.  

  Prerequisites  
  YouTube API Setup  
  Create a Google Cloud Project  
     Go to the Google Cloud Console.  
     Click Select a project &gt; New Project and name it (e.g., "YouTube Chapters Automation") .  

  Enable YouTube Data API v3  
     Navigate to APIs & Services &gt; Library.  
     Search for "YouTube Data API v3" and click Enable .  

  Configure OAuth Consent Screen  
     Go to APIs & Services &gt; OAuth consent screen.  
     Select External (public) or Internal (testing), then add required details (app name, support email) .  

  Generate OAuth 2.0 Credentials  
     Under Credentials, click Create Credentials &gt; OAuth client ID.  
     Choose Web app, then download the JSON key file .  

  Add Credentials to n8n  
  Other Requirements  
  Google Gemini API**: Configure access for the gemini-1.5-flash-8b-exp-0924 model by getting the api key.  
  Workflow Steps  
  Set Video ID  
     Input the target video ID (e.g., r1wqsrW2vmE) using the Set Video ID node.  

  Fetch Video Metadata  
     Use the YouTube API node to retrieve the video’s title, category, and existing description .  

  Download SRT Captions  
     Get Caption ID: Call https://www.googleapis.com/youtube/v3/captions to fetch the caption track ID .  
     Download Transcript: Use the ID to retrieve SRT data via https://www.googleapis.com/youtube/v3/captions/{{ID}}?tfmt=srt .  

  Analyze Transcript with Gemini AI  
     Process the SRT file with Google Gemini AI to identify chapters using a prompt like:  
            "Classify this transcript into timestamped chapters (e.g., 00:00 - Introduction)."  
          Validate output with a structured parser (e.g., Structured Captions node) .  

  Update Video Description  
     Append chapters to the description using the YouTube API’s videos.update method .  

  Value Proposition  
  Viewer Experience**: Chapters improve navigation and reduce drop-off rates .  
  SEO Benefits**: Structured descriptions enhance search visibility .  
  Time Savings**: Eliminates manual chapter creation .  

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name: 🔊 Browser Recording Audio Transcribing and AI Analysis with Deepgram and GPT-4o
author_name: RealSimple Solutions
author_username: joeperes
categories: []
created_at: 2025-04-07T00:41:41.162Z
updated_at: 2025-04-07T00:41:41.162Z
url: https://n8n.io/workflows/3451
scraped_at: 2025-12-24 13:02:46
description:
  Overview

  Transcript Evalu8r V2 is a robust browser-based transcript analysis tool powered by Deepgram’s speech-to-text API and built into an n8n workflow template. This release introduces full in-browser audio recording, device selection, and playback functionality, allowing users to capture and analyze conversations without leaving their browser.

  Designed for researchers, support teams, podcasters, legal professionals, and analysts, Transcript Evalu8r simplifies how you extract value from voice data using intuitive tools, AI-powered insights, and seamless automation.

  ✅ What’s New in V2

  |  |  |
  |:--|:--|
  |### 🔴 Record in Browser Users can now record audio directly in the browser with one click. Record meetings, calls, or voice notes instantly—no external software required. | ### 🎧 Select Audio Input Devices Users can choose from connected input devices (e.g., internal mic, USB mic, headset) before recording, ensuring maximum control and audio quality.|

  ▶️ Listen to Recording in Browser  
  Once a recording is complete, users can immediately play back the audio in-browser to review before submitting for transcription—ensuring content is clear and relevant.

  How It Works

  Record or upload an audio file
  **Audio recording is uploaded to Google Drive
  Audio file is sent to Deepgram for transcribing and AI analysis
  Audio File is moved to completed folder
  JSON transcript is saved to Google Drive
  Google Doc of AI analysis, summary, key points, action items, and full transctip is created
  Use the Web UI to Explore:
     Speaker Names
     Transcript
     Key points & tasks
     Sentiment chart
     Topic and intent lists with time stamps
  Download or export transcript and insights
  Add Additional automations or continue workflow (e.g., send to Notion, Slack, Google Sheets, todoist)

  Key Features

  🔹 Transcript Processing & Uploads
  Upload or record audio directly in your browser
  Track progress of file uploads in real-time
  View, select, or download transcripts in Google Docs, JSON, and other formats

  🔹 Interactive Transcript Viewer
  Full transcript display with timestamps, speaker IDs, and auto-scroll
  Clickable word-level navigation for pinpointing dialogue
  Real speaker labeling (not just "Speaker 1")

  🔹 AI-Powered Analysis
  Sentiment visualization** over time, per speaker
  Topic and intent extraction** with confidence scores
  Speaker contribution insights**, interruptions, and common word frequency

  🔹 Insight Summaries Google Doc
  AI-generated summary, key points, and action items
  Speaker-specific task suggestions and idea highlights

  🔹 UI Enhancements
  Collapsible sections for focused analysis
  Light and dark mode support
  Responsive design across desktop, tablet, and mobile

  Use Cases

  ✅ Interview & podcast summarization  
  ✅ Customer support QA monitoring  
  ✅ Legal or compliance transcription logging  
  ✅ Market research and trend analysis  
  ✅ Internal meeting follow-up automation  

  Requirements

  n8n instance** (self-hosted or cloud)
  Deepgram API Key** (for audio transcription)
  Supported browser with mic permissions enabled

  Why Choose Transcript Evalu8r V2?

  🚀 Instantly record and transcribe within your browser  
  🧠 Extract sentiment, insights, and intent automatically  
  📈 Visualize speaker tone and engagement  
  🎧 Choose audio input for cleaner recordings  
  🔗 Connect with your favorite tools using n8n’s integrations  

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleDocs","n8n-nodes-base.html","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.webhook","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.respondToWebhook","n8n-nodes-base.gmail","n8n-nodes-base.convertToFile","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDocs","n8n-nodes-base.googleDrive","n8n-nodes-base.merge","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.merge","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","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.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.code"]

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name: Monitor GitHub Releases with Gemini AI Chinese Translation & Slack Notifications
author_name: tbphp
author_username: tbphp
categories: []
created_at: 2025-04-07T03:07:49.414Z
updated_at: 2025-04-07T03:07:49.414Z
url: https://n8n.io/workflows/3452
scraped_at: 2025-12-24 13:02:46
description:
  Overview

  This n8n template monitors specified GitHub repositories. When a new release is published, it automatically fetches the information, uses AI (Google Gemini by default) to summarize and translate it into Chinese, and sends a formatted notification to a designated Slack channel.

  Core Features:

  Automated Monitoring**: Checks for updates on a predefined schedule.
  Intelligent Processing**: Uses AI to extract key information and translate.
  Error Handling**: Sends an error notification if fetching RSS for a single repository fails, without affecting others.
  Duplicate Prevention**: Remembers the last processed release ID using Redis to ensure only new content is pushed.

  Prerequisites

  Slack**: Configure your Slack app credentials in n8n.
  Redis**: Have an available Redis service and configure its credentials in n8n.
  AI Provider (Gemini)**: Configure credentials for Google Gemini (or your chosen AI model) in n8n.

  Configuration Instructions

  After importing the template, you need to modify the following key nodes:

  Cron Trigger:
      Adjust the Rule setting to change the update check frequency (default is 0 */10 9-23 * * *, checking every 10 minutes between 9 AM and 11 PM daily).
  GitHub Config (Repository List - Code Node):
      Edit the JavaScript array within this node's code area.
      Modify or add the repositories you want to follow. Each repository object needs a name (custom display name) and github (format: owner/repo).
      Example:
                  {
            "name": "n8n", // Custom display name
            "github": "n8n-io/n8n" // GitHub path
          },
          {
            "name": "LobeChat",
            "github": "lobehub/lobe-chat"
          }
          // ... add more repositories
          Redis and Redis2 (Redis Connection):
      Select your configured Redis credentials in both nodes.
  Gemini (AI Model):
      Select your configured Google Gemini credentials.
      (Optional) Replace with a different supported AI model node and select its credentials.
  Information Extractor (AI Processing & Translation):
      Main Configuration: Review the System Prompt. By default, it asks the AI to extract information and translate it into Chinese. Modify this prompt if you need a different language or summary style.
  Send Message and Send Error (Slack Notifications):
      Select your configured Slack credentials in both Slack nodes.
      Set the target Channel ID for notifications.

  Workflow Overview

  Start: Cron Trigger initiates the workflow on schedule.
  Load Config: GitHub Config provides the list of repositories to monitor.
  Loop: The Loop node iterates through each repository.
  Fetch & Check:
      The RSS node attempts to fetch the repository's releases feed.
      If No Error checks for success:
          Failure: Send Error posts an error to Slack, skips this repository.
          Success: Continues.
  Check for New Release:
      The Redis node retrieves the last recorded Release ID for this repository.
      The If New node compares the latest Release ID with the recorded ID:
          Different IDs (New Release): Proceeds to processing.
          Same ID (Already Processed): Skips this repository.
  Process & Notify (Only for New Releases):
      Information Extractor (with Gemini) extracts, summarizes, and translates the content.
      The Code node formats the information into Slack Block Kit.
      Send Message sends the formatted message to Slack.
      The Redis2 node stores the current Release ID in Redis.
  End: The workflow finishes after processing all repositories.

  Conclusion

  Once configured, this template automates GitHub release monitoring, uses AI to distill key information, and delivers it efficiently to your Slack workspace.

nodes_used:
  ["n8n-nodes-base.limit","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.slack","n8n-nodes-base.if","n8n-nodes-base.dateTime","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.slack","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","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.redis","n8n-nodes-base.code","n8n-nodes-base.rssFeedRead","n8n-nodes-base.redis"]

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name: Automated Weekly Project Cost Reports with MySQL and Outlook HTML Emails
author_name: Amjid Ali
author_username: amjid
categories: []
created_at: 2025-04-07T05:56:27.085Z
updated_at: 2025-04-07T05:56:27.085Z
url: https://n8n.io/workflows/3453
scraped_at: 2025-12-24 13:02:45
description:
  Automated Weekly Project Cost Reports with MySQL and Outlook HTML Emails

  🧠 Use Case

  Need to keep your finance or operations team updated on missing project costs?  
  This practical automated report workflow does the job without AI — and saves hours weekly.

  Runs on a weekly schedule
  Queries your MySQL database for projects missing cost data
  Filters by budgeted_project_cost IS NULL
  Generates a clean HTML email report
  Sends it through Microsoft Outlook to relevant teams

  🚀 How It Works

  Schedule Trigger – Runs every Monday at 8 AM
  MySQL Node – Connects and runs SQL to fetch project data missing budgeted_project_cost
  Switch Node – Routes logic based on cost_center (e.g., Retail, Service, Projects)
  Outlook Nodes – Sends formatted HTML emails; each node handles a specific group
  Dynamic Content – Inject values using mustache tags like {{ $json.project_name }}

  🔧 Setup Instructions

  MySQL Setup:
     Ensure the MySQL node is connected using a valid credential set:
       Hostname/IP
       Port (default: 3306)
       Database name
       Username with SELECT permissions
       Password
     Query Example:
            SELECT project_name, cost_center FROM tabProject 
       WHERE status = 'Open' AND project_type = 'External' AND budgeted_project_cost IS NULL;
       
  Outlook Configuration:
     Connect your Microsoft Outlook node using OAuth2 credentials.
     Rename each Outlook node clearly (e.g., Send Email - Retail, Send Email - Service).

  Switch Node:
     Modify cost center values as needed to match your organization (e.g., 'Retail', 'Service', 'Projects').

  HTML Email Formatting:
     Customize the HTML message body using inline styles and mustache syntax.
     Sample:
            Missing Budgeted Cost Report
       
         Project: {{ $json.project_name }}
         Cost Center: {{ $json.cost_center }}
       
       
  Recipients:
     Replace amjid@amjidali.com with the actual email addresses of the concerned teams.

  📘 Read More

  👉 Why Simple Workflows Work  

  📺 Demo & Tutorial

  🎥 Watch the video walkthrough:  
  https://youtube.com/@syncbricks

  👤 About the Creator

  Amjid Ali  
  🌐 amjidali.com  
  📘 n8n Book  
  🎓 Learn n8n

  &gt; “Start simple, scale smart. Even basic workflows like this can save your team hours!” — Amjid Ali

nodes_used:
  ["n8n-nodes-base.mySql","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.switch","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.microsoftOutlook"]

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name: Auto-Generate and Post Social Media Content to Bluesky using Groq LLM
author_name: Mehdi
author_username: mlstudio
categories: []
created_at: 2025-04-07T09:14:47.000Z
updated_at: 2025-04-07T09:14:47.000Z
url: https://n8n.io/workflows/3455
scraped_at: 2025-12-24 13:02:46
description:
  Automatically Generate Content and Post to Bluesky with LLM Workflow

  Unlock the power of automation with the Automatically Generate Content and Post to Bluesky with LLM Workflow, an n8n-powered solution that uses Large Language Model (LLM) APIs to create engaging content and seamlessly posts it to Bluesky. Say goodbye to manual content creation and posting—streamline your social media presence in minutes!

  How It Works
  This workflow harnesses an LLM API (like Openai or your preferred model) to generate tailored content based on your input prompts. Once the content is created, it’s formatted to fit Bluesky’s requirements (e.g., under 300 characters), authenticated via the Bluesky API, and posted automatically. Built-in checks ensure error-free execution, making your content strategy seamless and efficient.

  Set Up Steps (10-15 Minutes)
  Authenticate Bluesky: Add your Bluesky API credentials (username and app password in your Bluesky settings).
  Configure LLM API: Connect your chosen LLM API (e.g., Groq) with your API key.
  Set Prompt: Define a system prompt in the LLM node (e.g., “Write a witty Bluesky post about AI automation”).
  Test Workflow: Run it manually to verify content generation and posting.
  Schedule (Optional): Set a cron node to automate posts (e.g., daily at 9 AM).

  Total setup time: 10-15 minutes, depending on familiarity with n8n.

  Features
  LLM-Powered Content**: Generate unique, high-quality posts using any LLM API.
  Bluesky Automation**: Posts directly to Bluesky with proper formatting and authentication.
  Character Limit Safety**: Ensures posts stay under 300 characters with built-in validation.
  Error Handling**: Stops execution on errors to prevent unwanted posts.
  Customizable Scheduling**: Post instantly or schedule content at your preferred intervals.
  Scalable Design**: Easily adapt for multiple platforms or content types.

  Perfect for Creators Who Want To
  Save time by automating content creation and posting.
  Maintain a consistent Bluesky presence without manual effort.
  Experiment with AI-generated content tailored to their brand.
  Focus on strategy and engagement rather than repetitive tasks.

  Suggested Enhancements
  Multi-Platform Support**: Extend the workflow to post to Twitter, Mastodon, or LinkedIn simultaneously.
  Content Variety**: Add nodes to generate images (e.g., via DALL-E) alongside text for richer posts.
  Analytics Integration**: Track post performance with a Bluesky API feedback loop.
  Dynamic Prompts**: Incorporate trending topics or keywords from the web for timely content.
  Approval Step**: Add a manual review node before posting for extra control.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatGroq","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.stopAndError","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.stickyNote"]

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name: Automated Discord Chatbot for chat Interaction in channel using Gemini 2.0 Flash
author_name: JPres
author_username: stardawnai
categories: []
created_at: 2025-04-07T09:39:02.177Z
updated_at: 2025-04-07T09:39:02.177Z
url: https://n8n.io/workflows/3456
scraped_at: 2025-12-24 13:02:46
description:
  A Discord bot that responds to mentions by sending messages to n8n workflows and returning the responses. Connects Discord conversations with custom automations, APIs, and AI services through n8n.

  Full guide on: https://github.com/JimPresting/AI-Discord-Bot/blob/main/README.md 

  Discord Bot Summary

  Overview
  The Discord bot listens for mentions, forwards questions to an n8n workflow, processes responses, and replies in Discord.
  This workflow is intended for all Discord users who want to offer AI interactions with their respective channels.

  What do you need?
  You need a Discord account as well as a Google Cloud Project

  Key Features

  1. Listens for Mentions
  The bot monitors Discord channels for messages that mention it.
  Optional Configuration**: Can be set to respond only in a specific channel.

  2. Forwards Questions to n8n
  When a user mentions the bot and asks a question:
    The bot extracts the question.
    Sends the question, along with channel and user information, to an n8n webhook URL.

  3. Processes Data in n8n
  The n8n workflow receives the question and can:
    Interact with AI services (e.g., generating responses).
    Access databases or external APIs.
    Perform custom logic.
  n8n formats the response and sends it back to the bot.

  4. Replies to Discord with n8n's Response
  The bot receives the response from n8n.
  It replies to the user's message in the Discord channel with the answer.
  Long Responses**: Handles responses exceeding Discord's 2000-character limit by chunking them into multiple messages.

  5. Error Handling
  Includes error handling for:
    Issues with n8n communication.
    Response formatting problems.
  Manages cases where:
    No question is asked.
    An invalid response is received from n8n.

  6. Typing Indicator
  While waiting for n8n's response, the bot sends a "typing..." indicator to the Discord channel.

  7. Status Update
  For lengthy n8n processes, the bot sends a message to the Discord channel to inform the user that it is still processing their request.

  Step-by-Step Setup Guide as per Github Instructions


  Key Takeaways

  You’ll configure an n8n webhook to receive Discord messages, process them with your workflow, and respond.  
  You’ll set up a Discord application and bot, grant the right permissions/intents, and invite it to your server.  
  You’ll prepare your server environment (Node.js), scaffold the project, and wire up environment variables.  
  You’ll implement message‐chunking, “typing…” indicators, and robust error handling in your bot code.  
  You’ll deploy with PM2 for persistence and know how to test and troubleshoot common issues.

  1. n8n: Create & Expose Your Webhook

  New Workflow  
     Log into your n8n instance.  
     Click Create Workflow (➕), name it e.g. Discord Bot Handler.  

  Webhook Trigger  
     Add a node (➕) → search Webhook.  
     Set:  
       Authentication: None (or your choice)  
       HTTP Method: POST  
       Path: e.g. /discord-bot  
     Click Execute Node to activate.

  Copy Webhook URL  
     After execution, copy the Production Webhook URL.  
     You’ll paste this into your bot’s .env.  

  Build Your Logic  
     Chain additional nodes (AI, database lookups, etc.) as required.

  Format the JSON Response  
     Insert a Function node before the end:  
            return {
         json: { answer: "Your processed reply" }
       };
       
  Respond to Webhook  
     Add Respond to Webhook as the final node.  
     Point it at your Function node’s output (with the answer field).

  Activate  
     Toggle Active in the top‐right and Save.

  2. Discord Developer Portal: App & Bot

  New Application  
     Visit the Discord Developer Portal.  
     Click New Application, name it.  
     Go to Bot → Add Bot.

  Enable Intents & Permissions  
     Under Privileged Gateway Intents, toggle Message Content Intent.  
     Under Bot Permissions, check:  
       Read Messages/View Channels  
       Send Messages  
       Read Message History  

  Grab Your Token  
     In Bot → click Copy (or Reset Token).  
     Store it securely.

  Invite Link (OAuth2 URL)  
     Go to OAuth2 → URL Generator.  
     Select scopes: bot, applications.commands.  
     Under Bot Permissions, select the same permissions as above.  
     Copy the generated URL, open it in your browser, and invite your bot.

  3. Server Prep: Node.js & Project Setup

  Install Node.js v20.x  
        sudo apt purge nodejs npm
     sudo apt autoremove
     curl -fsSL https://deb.nodesource.com/setup_20.x | sudo -E bash -
     sudo apt install -y nodejs
     node -v    # Expect v20.x.x
     npm -v     # Expect 10.x.x
     
  Project Folder  
        mkdir discord-bot
     cd discord-bot
     
  Initialize & Dependencies  
        npm init -y
     npm install discord.js axios dotenv
  4. Bot Code & Configuration

  Environment Variables  
     Create .env:  
            nano .env
          Populate:  
            DISCORD_BOT_TOKEN=your_bot_token
       N8N_WEBHOOK_URL=https://your-n8n-instance.com/webhook/discord-bot
  Optional: restrict to one channel
  TARGET_CHANNEL_ID=123456789012345678
       
  Bot Script  
     Create index.js:  
            nano index.js
          Implement:  
       Import dotenv, discord.js, axios.  
       Set up client with MessageContent intent.  
       On messageCreate:  
         Ignore bots or non‐mentions.  
         (Optional) Filter by channel ID.  
         Extract and validate the user’s question.  
         Send “typing…” every 5 s; after 20 s send a status update if still processing.  
         POST to your n8n webhook with question, channelId, userId, userName.  
         Parse various response shapes to find answer.  
         If answer.length ≤ 2000, message.reply(answer).  
         Else, split into ~1900‑char chunks at sentence/paragraph breaks and send sequentially.  
         On errors, clear intervals, log details, and reply with an error message.

  Login  
        client.login(process.env.DISCORD_BOT_TOKEN);
  5. Deployment: Keep It Alive with PM2

  Install PM2  
        npm install -g pm2
     
  Start & Monitor  
        pm2 start index.js --name discord-bot
     pm2 status
     pm2 logs discord-bot
     
  Auto‐Start on Boot  
        pm2 startup
  Follow the printed command (e.g. sudo env PATH=$PATH:/usr/bin pm2 startup systemd -u your_user --hp /home/your_user)
     pm2 save
  6. Test & Troubleshoot

  Functional Test  
     In your Discord server:  
            @YourBot What’s the weather like?
          Expect a reply from your n8n workflow.

  Common Pitfalls  
     No reply → check pm2 logs discord-bot.  
     Intent Errors → verify Message Content Intent in Portal.  
     Webhook failures → ensure workflow is active and URL is correct.  
     Formatting issues → confirm your Function node returns json.answer.

  Inspect Raw Data  
     Search your logs for Complete response from n8n: to debug payload shapes.

  `

nodes_used:
  ["n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.respondToWebhook","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent"]

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name: Classify Emails & Extract Structured Data from Job Applications with GPT-4o
author_name: Sleak
author_username: sleak
categories: []
created_at: 2025-04-07T10:57:05.716Z
updated_at: 2025-04-07T10:57:05.716Z
url: https://n8n.io/workflows/3457
scraped_at: 2025-12-24 13:02:47
description:
  Who is this template for?
  This workflow template is designed for business owners and HR professionals to automatically detect and structure unstructured job applications received through email. Additionally, other email categories can be added, each with it's own workflow.

  How it works
  Every time a new email is received, an OpenAI model classifies it into a predefined category by analyzing the plain text of the email and the extracted content from the attachment.
  If the email is classified as a job application, an OpenAI model uses the email’s plain text and extracted attachment content to populate predefined fields such as age and study.
  A relevant additional step would be to directly push the applicant and their structured job application into a CRM or ATS like Hubspot or Recruitee.

  Set up steps
  Configure your IMAP credentials to connect your email account. Use this n8n documentation page for quickstart guides for common email providers.
  Connect your OpenAI account in the 'Classify email' node.
  	And add or remove any category for classification in this node. Make sure the description is clear and concise.

  	
  Connect your OpenAI account in the 'Extract variables - email & attachment' node.
  	And add or remove any predefined fields that should be populated for job applications in this node. Make sure the description is clear and concise.

  	

nodes_used:
  ["n8n-nodes-base.emailReadImap","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.textClassifier","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.noOp"]

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name: Adaptive RAG Strategy with Query Classification & Retrieval (Gemini & Qdrant)
author_name: dmr
author_username: dmr
categories: []
created_at: 2025-04-07T15:43:47.541Z
updated_at: 2025-04-07T15:43:47.541Z
url: https://n8n.io/workflows/3459
scraped_at: 2025-12-24 13:02:43
description:
  This n8n workflow implements a version of the Adaptive Retrieval-Augmented Generation (RAG) framework. It recognizes that the best way to retrieve information often depends on the type of question asked. Instead of a one-size-fits-all approach, this workflow adapts its strategy based on the user's query intent.

  🌟 How it Works

  Receive Query: Takes a user query as input (along with context like a chat session ID and Vector Store collection ID if used as sub-workflow).
  Classify Query: First, the workflow classifies the query into a predefined category. This template uses four examples:
      Factual: For specific facts.
      Analytical: For deeper explanations or comparisons.
      Opinion: For subjective viewpoints.
      Contextual: For questions relying on specific background.
  Select & Adapt Strategy: Based on the classification, it selects a corresponding strategy to prepare for information retrieval. The example strategies aim to:
      Factual: Refine the query for precision.
      Analytical: Break the query into sub-questions for broad coverage.
      Opinion: Identify different viewpoints to look for.
      Contextual: Incorporate implied or user-specific context.
  Retrieve Info: Uses the output of the selected strategy to search the specified knowledge base (Qdrant vector store - change as needed) for relevant documents.
  Generate Response: Constructs a response using the retrieved documents, guided by a prompt tailored to the original query type.

  By adapting the retrieval strategy, this workflow aims to provide more relevant results tailored to the user's intent.

  ⚙️ Usage & Flexibility

  Sub-Workflow:** Designed to be called from other n8n workflows, passing user_query, chat_memory_key, and vector_store_id as inputs.
  Chat Testing:** Can also be triggered directly via the n8n Chat interface for easy testing and interaction.
  Customizable Framework:** The query categories (Factual, Analytical, etc.) and the associated retrieval strategies are examples. You can modify or replace them entirely to fit your specific domain or requirements.

  🛠️ Requirements

  Credentials:** You will need API credentials configured in your n8n instance for:
      Google Gemini (AI Models)
      Qdrant (Vector Store)

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.embeddingsGoogleGemini","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.summarize","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: 🎨 AI Design Team - Generate and Review AI Images with Ideogram and OpenAI
author_name: RealSimple Solutions
author_username: joeperes
categories: []
created_at: 2025-04-07T17:05:15.082Z
updated_at: 2025-04-07T17:05:15.082Z
url: https://n8n.io/workflows/3460
scraped_at: 2025-12-24 13:02:42
description:
  🎨 AI Graphic Design Team - Generate and Review AI Images with Ideogram and OpenAI

  Description

  Who is this for?
  This workflow is perfect for graphic designers, creative agencies, marketing teams, or freelancers who regularly use AI-generated images in their projects. It's specifically beneficial for teams that want to automate the generation, review, and management of AI-created graphics efficiently.

  What problem does this workflow solve?
  Design teams often face time-consuming manual reviews and inconsistent quality checks for AI-generated images. This workflow addresses these challenges by automating image generation and introducing a systematic, AI-driven vetting process. This ensures only high-quality, relevant images reach your team's assets, saving valuable time and enhancing workflow efficiency.

  What this workflow does
  AI Image Generation:** Integrates Ideogram via HTTP Request to automatically create AI-generated images based on creative briefs.
  Automated Image Review:** Uses OpenAI to automatically evaluate and approve images, ensuring they meet your predefined quality standards.
  Efficient Asset Management:** Automatically creates structured Google Drive folders and compiles key metadata (including creation dates, prompts, and image links) into a CSV file and Google Sheet.
  Immediate Email Notifications:** Delivers a setup confirmation and provides easy access to Google Drive folders and assets via automated email notifications.
  Final Approved Images:** Outputs vetted, ready-to-use images for your creative projects, removing the burden of manual reviews.

  Setup
  Initial Email Configuration
     Update your email details in both the "Setup Gmail" node and the "Gmail" notification node.
     Run the initial setup workflow to automatically create the Google Drive folders "Graphic_Design_Team" and "Image_Generations," and upload your CSV file (n8n-Graphic_Design_Team.csv).

  Review Email & Set Up Google Sheets
     Check your inbox for an automated email containing folder IDs and direct links.
     Create and set up a Google Sheet by importing the provided CSV data from your email.

  Update Workflow Nodes
     Select your newly created Google Sheet in both Google Sheets nodes.
     Update your Creative Brief node with the Google Drive folder IDs provided in the email.

  Run Workflow for AI Image Generation & Review
     Execute the workflow. Your generated images will be automatically vetted, organized, and ready for creative use.

  How to Customize This Workflow
  Tailor Image Generation Prompts:** Adjust prompts and settings in the Ideogram HTTP Request node to better fit your project's creative requirements.
  Set Quality Standards:** Modify the criteria used by the OpenAI node to reflect your specific standards and preferences for image approval.
  Customize Asset Organization:** Adapt Google Drive folder structures, CSV headers, or Google Sheets integrations to match your team's organizational preferences.

  Dependencies & Requirements
  Nodes Used:**
    HTTP Request (Ideogram API integration)
    OpenAI (Image review and quality assessment)
    Gmail (Automated notifications)
    Google Drive (File and asset management)
    Google Sheets (Metadata organization)

  Credentials:**
    Ensure Gmail, Google Drive, Google Sheets, and OpenAI credentials are properly configured in your n8n account. No custom or community nodes are needed.

  Final Outcome
  Upon completion, your workflow efficiently provides vetted, high-quality AI-generated images, organized in Google Drive and accessible via easy-to-use metadata in Google Sheets, drastically reducing manual intervention and accelerating your creative processes.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.googleDrive","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleDrive","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.gmail","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.manualTrigger","n8n-nodes-base.convertToFile","n8n-nodes-base.set","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: RSS Feed Reader that saves the feeds of the last 3 days in Google Sheets
author_name: Holger
author_username: capa
categories: []
created_at: 2025-04-07T21:16:17.406Z
updated_at: 2025-04-07T21:16:17.406Z
url: https://n8n.io/workflows/3463
scraped_at: 2025-12-24 13:02:45
description:
  ++How it Works:++
  This RSS reader retrieves links from a Google Sheets file and goes through each link to retrieve the messages that are younger than 3 days, then saves them in a second Google Sheets file and then deletes all older entries in the second Google Sheets file!

  The retrieval can take a while due to the Google API block prevention, depending on the number of news feeds that were retrieved!==*

  Detailed Description is in the sticky Notes from the Workflow!*

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.markdown","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.rssFeedRead","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.wait","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.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets"]

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name: Organize Email Attachments into Google Drive Folders by Company with Gmail & Sheets
author_name: Ventsislav Minev
author_username: vminev
categories: []
created_at: 2025-04-07T21:57:04.743Z
updated_at: 2025-04-07T21:57:04.743Z
url: https://n8n.io/workflows/3464
scraped_at: 2025-12-24 13:02:44
description:
  Automated Email Attachment Organizer
  Automatically process labeled emails with attachments into organized Google Drive folders

  Who Is This For?
  Teams or Individuals** needing to:
    Automatically sort invoices, receipts, and files.
    Organize client documents by date.
    Verify sender emails against a whitelist.
    Timestamp files to avoid duplicate names.

  What Does This Workflow Solve?
  🕒 Manual Email Sorting: Saves time by automating the organization of email attachments.
  📂 Disorganized Cloud Storage: Ensures attachments are neatly stored in Google Drive folders.
  📧 Unverified Sender Issues: Filters and validates emails using a whitelist.
  🔄 Duplicate Filenames: Uses timestamps to ensure every file name is unique.

  Setup Guide

  1. Pre-Requisites
  Whitelist Sheet**: Make a copy of the Example Whitelist Sheet
  Gmail Filter**: Create a filter in Gmail to label emails with attachments.
    
  To Create a Gmail Filter:
  Open your Gmail Inbox.
  Click the search bar and select "Show search options".
  Enter your criteria (e.g., type has:attachment).
  Click "Create filter".
  Choose "Apply the label: Custom_Label" and save.

  2. Credentials Setup
  Make sure your n8n instance is connected with:
  Gmail Account**: (via OAuth2)
  Google Drive Account**: (via OAuth2)
  Google Sheets** (via OAuth2)

  3. Configure Your n8n Workflow Nodes

  1. Trigger and Email Retrieval
  Gmail Trigger**: Setup check interval and filters for emails (i.e. emails labeled with Custom_Label)

  2. Whitelist settings
  Lookup in Sheets**: Searches for a row with the sender email. Configure this node to point to your whitelist spreadsheet containing two columnds:
  |email|company|

  3. File storage location
  Confirue parent folder to create sub-folders and store files into in the Create Company Folder node Parent Folder dropdown

  Final Steps
  Test Your Workflow: Run the workflow to verify emails are processed and files are uploaded correctly.

  Happy Automating!

nodes_used:
  ["n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.if","n8n-nodes-base.gmailTrigger","n8n-nodes-base.gmail","n8n-nodes-base.function","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive"]

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name: Capture Website Screenshots with Bright Data Web Unlocker and Save to Disk
author_name: Ranjan Dailata
author_username: ranjancse
categories: []
created_at: 2025-04-08T00:03:05.827Z
updated_at: 2025-04-08T00:03:05.827Z
url: https://n8n.io/workflows/3465
scraped_at: 2025-12-24 13:02:46
description:
  Who is this for?
  The Capture Website Screenshots with Bright Data Web Unlocker and Save to Disk workflow is built for automation professionals and developers who need reliable, high-quality screenshots from any website even those protected by anti-bot technologies. 

  It is ideal for:

  Compliance Teams - Capturing visual records of web content for legal or audit purposes.

  Product Managers - Tracking visual changes across competitor landing pages.

  Digital Marketers - Archiving campaign pages and offer variations.

  Developers and QA Teams - Validating UI deployments or rendering issues.

  Growth Hackers and Scrapers - Who need to bypass bot protection and capture visual snapshots of restricted content.

  What problem is this workflow solving?
  Websites today are highly protected with anti-bot tools like Cloudflare, bot detection scripts, and geo-restrictions. These protections often break traditional screenshot tools or prevent headless browsers from accessing content.

  This workflow solves the following problems:

  Bypasses anti-bot defenses using Bright Data Web Unlocker.

  Automatically captures screenshots without manual browser steps.

  Stores images locally for easy access or reporting.

  Operates headlessly and at scale, perfect for automations or scheduled jobs.

  What this workflow does
  Sets the target URL, file name, and Bright Data zone name using the Set URL, Filename and Bright Data Zone node.
  Sends an HTTP POST request to Bright Data Web Unlocker API to capture a screenshot.
  Saves the screenshot image (.png) to a specified disk location using the Write a file to disk node.

  Pre-conditions

  You need to have a Bright Data account and do the necessary setup as mentioned in the "Setup" section below.

  Setup
  Sign up at Bright Data.
  Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.
  In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication).

  The Value field should be set with the
  Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token.
  Ensure the URL, file name, and Bright Data zone name are correctly set in the Set URL, Filename and Bright Data Zone node.
  Set the desired local path in the Write a file to disk node to save the screenshot.

  How to customize this workflow to your needs
  Change the target URL: Modify the value in the **Set URL, Filename and Bright Data Zone node to capture different websites.
  Set dynamic filenames**: Use expressions in n8n to generate filenames based on date/time or URL.
  Specify custom save paths: Adjust the path in the **Write a file to disk node to store screenshots in your preferred directory.
  Enhance with notifications**: Add additional nodes to send alerts or log activity after each screenshot is taken.
  Integrate with external systems**: Send screenshots to cloud storage (e.g: AWS S3, Google Drive) or link into monitoring/reporting tools.

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

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name: Gumroad Clientbell: Auto-Log Sales, Ping Telegram, & Thank via Email
author_name: Velebit from Innovatio
author_username: innovatio
categories: []
created_at: 2025-04-08T06:37:56.846Z
updated_at: 2025-04-08T06:37:56.846Z
url: https://n8n.io/workflows/3469
scraped_at: 2025-12-24 13:02:46
description:
  Who is this for?  
  This template is perfect for Gumroad creators, solopreneurs, digital product sellers, and freelancers who want to track and thank customers automatically — without spending time on manual work.

  What problem does this solve?  
  Every sale is a moment to build trust. But manually checking your inbox for new orders, logging clients, and remembering to send a thank-you note? It’s time-consuming and inconsistent.

  This workflow handles it all:  
  From sale → to sheet → to ping → to personalized “thank you” — all fully automated.

  What this workflow does:  
  ✅ Triggers on each new sale on Gumroad  
  📋 Extracts buyer details, amount paid, and product purchased  
  📈 Logs the sale to a Google Sheet for tracking  
  📲 Sends a Telegram approval message to notify you  
  💌 (Optional) Sends a Gmail thank-you email to the buyer  
  🔁 Keeps your workflow organized with color-coded notes and sample data

  ⚙️ Setup Instructions:

  Create Gumroad API and connect the trigger node  
  Authenticate with Google Sheets to store each client  
  Connect your Telegram bot for real-time alerts  
  (Optional) Setup Gmail API for sending thank-you emails  
  Customize the email copy & sheet headers (e.g. % cut, timestamps)

  🗒 Color-coded workflow notes:

  To make customization smooth, the workflow includes a color-coded sticky note system:

  🟩 Green Notes – Main building blocks (trigger, logging, ping, email)  
  🟦 Blue Notes – Setup guidance and editable fields (e.g. your email or brand name)  
  🟨 Yellow Notes – Optional upgrades (e.g. swap Gmail, use AI email generator, change to WhatsApp)

  Each step has comments or hints to make your setup easy — whether you're new to n8n or a seasoned automator.

  🔧 How to customize this workflow?

  🎯 Swap Gmail with Outlook, SMTP, or Mailgun  
  🤖 Use AI (e.g. OpenAI or Claude) to draft personalized emails dynamically  
  📞 Replace Telegram with WhatsApp, Discord, or Slack  
  🗃️ Log to Airtable or Notion instead of Google Sheets  
  🧠 Add approval logic or advanced tagging in Gmail

  🧾 Licensing & Support

  This template is built by Velebit from Innovatio. External links (Gumroad store or support email) are included in the notes for optional help and upgrades.

  A separate license applies to the paid version on Gumroad, which includes additional modules and commercial use rights.

  📩 Support & customization: velebit@innovatio.design

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.gumroadTrigger","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.noOp","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.airtable","n8n-nodes-base.hubspot","n8n-nodes-base.notion","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.twilio","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.emailSend","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent"]

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name: Automate WordPress Contact Form (CF7) Responses and Classification with Gemini
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-04-08T09:34:12.687Z
updated_at: 2025-04-08T09:34:12.687Z
url: https://n8n.io/workflows/3472
scraped_at: 2025-12-24 13:02:45
description:
  This workflow optimizes the management of inquiries received through a contact form (Contact Form 7 - CF7 Plugin) on a WordPress site, automating the process of classification, response drafting, and data storage.

  This workflow is particularly useful for businesses that receive multiple daily inquiries and want to improve their efficiency in managing customer communications. 

  Benefits:  
  ✅ Automation & Speed – Reduces the time needed to handle inquiries manually.  
  ✅ Better Email Management – Ensures every message receives a timely and accurate response.  
  ✅ Customization – The generated draft can be edited before sending, maintaining a personal touch.  
  ✅ Inquiry History – Storing data in Google Sheets allows for easy tracking of customer interactions.  
  ✅ Easy Integration – Works seamlessly with Contact Form 7 without complex configurations. 

  How It Works  
  Form Submission Handling: The workflow starts with a WordPress form submission captured via a webhook. The form data (first name, last name, email, phone, and message) is extracted and structured using the "Set Fields" node.  
  Message Classification: The submitted message is classified into predefined categories (e.g., "Product Info," "Order Info," or "Other") using the "Message Classifier" node, powered by Google Gemini.  
  Automated Email Drafting: Based on the classification, the workflow generates a professional email draft using one of three "Email Writer" nodes (for Product, Order, or Other requests). Each node uses Google Gemini to craft a personalized response with a structured format (subject and body).  
  Email Draft Creation: The drafted email is sent as a Gmail draft to the appropriate department, including the original form data for context.  
  Data Logging: All submissions, along with their classifications and email drafts, are logged in a Google Sheets spreadsheet for record-keeping and further action.  

  Set Up Steps  
  Install WordPress Plugin: Install the "CF7 to Webhook" plugin on WordPress and configure it to send form submissions to the n8n webhook URL.  
  Configure Webhook in n8n: Set up the "From Wordpress" webhook node in n8n to receive POST requests from the WordPress form.  
  Google Gemini Integration: Ensure the Google Gemini nodes are properly authenticated with the correct API credentials.  
  Gmail and Google Sheets Setup: Authenticate the Gmail and Google Sheets nodes with the appropriate OAuth2 credentials and specify the target spreadsheet and sheet name.  
  Customize Classification Categories: Adjust the categories in the "Message Classifier" node to match your business needs.  
  Test the Workflow: Trigger a test form submission to verify the workflow processes data correctly, classifies the message, generates an email draft, and logs the data.  

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.textClassifier","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Scalable Multi-Agent Chat Using @mentions
author_name: Jon Doran
author_username: jondoran
categories: []
created_at: 2025-04-08T12:49:14.252Z
updated_at: 2025-04-08T12:49:14.252Z
url: https://n8n.io/workflows/3473
scraped_at: 2025-12-24 13:02:42
description:
  Summary

  Engage multiple, uniquely configured AI agents (using different models via OpenRouter) in a single conversation. Trigger specific agents with @mentions or let them all respond. Easily scalable by editing simple JSON settings.

  Overview

  This workflow is for users who want to experiment with or utilize multiple AI agents with distinct personalities, instructions, and underlying models within a single chat interface, without complex setup. It solves the problem of managing and interacting with diverse AI assistants simultaneously for tasks like brainstorming, comparative analysis, or role-playing scenarios.

  It enables dynamic conversations with multiple AI assistants simultaneously within a single chat interface. You can:

  Define multiple unique AI agents.
  Configure each agent with its own name, system instructions, and LLM model (via OpenRouter).
  Interact with specific agents using @AgentName mentions.
  Have all agents respond (in random order) if no specific agents are mentioned.
  Maintain conversation history across multiple turns.

  It's designed for flexibility and scalability, allowing you to easily add or modify agents without complex workflow restructuring.

  Key Features

  Multi-Agent Interaction:** Chat with several distinct AI personalities at once.
  Individual Agent Configuration:** Customize name, system prompt, and LLM for each agent.
  OpenRouter Integration:** Access a wide variety of LLMs compatible with OpenRouter.
  Mention-Based Triggering:** Direct messages to specific agents using @AgentName.
  All-Agent Fallback:** Engages all defined agents randomly if no mentions are used.
  Scalable Setup:** Agent configuration is centralized in a single Code node (as JSON).
  Conversation Memory:** Remembers previous interactions within the session.

  How to Set Up

  Configure Settings (Code Nodes):
      Open the Define Global Settings Code node: Edit the JSON to set user details (name, location, notes) and add any system message instructions that all agents should follow.
      Open the Define Agent Settings Code node: Edit the JSON to define your agents. Add or remove agent objects as needed. For each agent, specify:
          "name": The unique name for the agent (used for @mentions).
          "model": The OpenRouter model identifier (e.g., "openai/gpt-4o", "anthropic/claude-3.7-sonnet").
          "systemMessage": Specific instructions or persona for this agent.
  Add OpenRouter Credentials:
      Locate the AI Agent node.
      Click the OpenRouter Chat Model node connected below it via the Language Model input.
      In the 'Credential for OpenRouter API' field, select or create your OpenRouter API credentials.

  How to Use

  Start a conversation using the Chat Trigger input.
  To address specific agents, include @AgentName in your message. Agents will respond sequentially in the order they are mentioned.
      Example: "@Gemma @Claude, please continue the count: 1" will trigger Gemma first, followed by Claude.
  If your message contains no @mentions, all agents defined in Define Agent Settings will respond in a randomized order.
      Example: "What are your thoughts on the future of AI?" will trigger Chad, Claude, and Gemma (based on your default settings) in a random sequence.
  The workflow will collect responses from all triggered agents and return them as a single, formatted message.

  How It Works (Technical Details)

  Settings Nodes: Define Global Settings and Define Agent Settings load your configurations.
  Mention Extraction: The Extract mentions Code node parses the user's input (chatInput) from the When chat message received trigger. It looks for @AgentName patterns matching the names defined in Define Agent Settings.
  Agent Selection:
      If mentions are found, it creates a list of the corresponding agent configurations in the order they were mentioned.
      If no mentions are found, it creates a list of all defined agent configurations and shuffles them randomly.
  Looping: The Loop Over Items node iterates through the selected agent list.
  Dynamic Agent Execution: Inside the loop:
      An If node (First loop?) checks if it's the first agent responding. If yes (true path -&gt; Set user message as input), it passes the original user message to the Agent. If no (false path -&gt; Set last Assistant message as input), it passes the previous agent's formatted output (lastAssistantMessage) to the next agent, creating a sequential chain.
      The AI Agent node receives the input message. Its System Message and the Model in the connected OpenRouter Chat Model node are dynamically populated using expressions referencing the current agent's data from the loop ({{ $('Loop Over Items').item.json.* }}).
      The Simple Memory node provides conversation history to the AI Agent.
      The agent's response is formatted (e.g., AgentName:\n\nResponse) in the Set lastAssistantMessage node.
  Response Aggregation: After the loop finishes, the Combine and format responses Code node gathers all the lastAssistantMessage outputs and joins them into a single text block, separated by horizontal rules (---), ready to be sent back to the user.

  Benefits

  Scalability & Flexibility:** Instead of complex branching logic, adding, removing, or modifying agents only requires editing simple JSON in the Define Agent Settings node, making setup and maintenance significantly easier, especially for those managing multiple assistants.
  Model Choice:** Use the best model for each agent's specific task or persona via OpenRouter.
  Centralized Configuration:** Keeps agent setup tidy and manageable.

  Limitations

  Sequential Responses:** Agents respond one after another based on mention order (or randomly), not in parallel.
  No Direct Agent-to-Agent Interaction (within a turn):* Agents cannot directly call or reply to each other *during the processing of a single user message. Agent B sees Agent A's response only because the workflow passes it as input in the next loop iteration.
  Delayed Output:* The user receives the combined response only *after all triggered agents have completed their generation.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter"]

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name: Track Daily PG&E Energy Costs with Airtop and Email Notifications
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T16:20:15.016Z
updated_at: 2025-04-08T16:20:15.016Z
url: https://n8n.io/workflows/3474
scraped_at: 2025-12-24 13:02:47
description:
  About The Airtop Automation

  Are you tired of being shocked by unexpectedly high energy bills? With this automation using Airtop and n8n, you can take control of your daily energy costs and ensure you’re always informed.

  How to monitor your daily energy consumption

  With this automation, we’ll walk you through setting up an automation that retrieves your PG&E (Pacific Gas and Electric) energy usage data, calculates costs, and emails you the details—all without manual effort.

  What You’ll Need
  To get started, make sure you have the following:

  A free Airtop API Key
  PG&E Account Credentials - with minor adaptations, this will also work with other providers
  An Email Address - To receive the energy cost updates

  Estimated setup time: 5 minutes

  Understanding the Process

  This automation works by:
   
  Logging into your PG&E account using your credentials
  Navigating to your energy usage data
  Extracting relevant details about energy consumption and costs
  Emailing the daily summary directly to your inbox

  The automation is straightforward and ensures you have real-time insights into your energy usage, empowering you to adjust your habits and save money.

  Setting Up Your Automation
  We’ve created a step-by-step guide to help you set up this workflow. Here’s how:

  Insert Your Credentials:

  In the tools section, add your PG&E login details as variables
  In Airtop, add your Airtop API Key
  Configure your email address to receive the updates

  Run the Automation:

  Start the scenario, and watch as the automation retrieves your energy data and sends you a detailed email summary.

  Customization Options

  While the default setup works seamlessly, you can tweak it to suit your needs:

  Data Storage: Store energy usage data in a database for long-term tracking and analysis
  Visualization: Plot graphs of your energy usage trends over time for better insights
  Notifications: Change the automation to only send alerts on high usage instead of a daily email

  Real-World Applications

  This automation isn’t just about monitoring energy usage and taking control. Here are some practical applications:

  Daily Energy Management: Receive updates every morning and adjust your energy consumption based on costs
  Smart Home Integration: Use the data to automate appliances during off-peak hours
  Budgeting: Track energy expenses over weeks or months to plan your budget more effectively

  Happy automating!

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.airtop","n8n-nodes-base.set","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.wait","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.gmail","n8n-nodes-base.airtop","n8n-nodes-base.stickyNote"]

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name: LinkedIn Company ICP Scoring Automation with Airtop & Google Sheets
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T16:51:03.186Z
updated_at: 2025-04-08T16:51:03.186Z
url: https://n8n.io/workflows/3475
scraped_at: 2025-12-24 13:02:47
description:
  About The ICP Company Scoring Automation

  Sorting through lists of potential leads manually to determine who's truly worth your sales team's time isn't just tedious, it's incredibly inefficient. Without proper qualification, your team might spend hours pursuing prospects who aren't the right fit for your product, while ideal customers slip through the cracks.

  How to Automate Identifying Your Ideal Customers

  With this automation, you'll learn how to automatically score and prioritize leads using data extracted directly from LinkedIn profiles via Airtop's integration with n8n. By the end, you'll have a fully automated workflow that analyzes prospects and calculates an Ideal Customer Profile (ICP) score, helping your sales team focus on high-potential opportunities.

  What You'll Need

  A free Airtop API key
  A copy of this Google Sheets

  Understanding the Process

  This automation transforms how you qualify and prioritize leads by extracting real-time, accurate information directly from LinkedIn profiles. Unlike static databases that quickly become outdated, this workflow taps into the most current professional information available.

  The workflow in this template:

  Uses Airtop to extract comprehensive LinkedIn profile data
  Analyzes the data to calculate an ICP score based on AI interest, technical depth, and seniority
  Updates your Google Sheet with the enriched data and the ICP Company score

  Company ICP Scoring Workflow

  Our company-focused workflow analyzes company LinkedIn profiles with a comprehensive set of criteria:

   Company Identity Extraction
   Company Scale Assessment
   Business Classification
   Technical Sophistication Assessment
   Investment Profile

  To then calculate the ICP Scoring, it will focus on:

  AI Implementation Level: Low-5 pts, Medium-10 pts, High-25 pts
  Technical Sophistication: Basic-5 pts, Intermediate-15 pts, Advanced-25 pts, Expert-35 pts
  Employee Count: 0-9 employees-5 pts, 10-150 employees-25 pts, 150+ employees-30 pts
  Automation Agency Status: True-20 pts, False-0 pts
  Geography: US/Europe Based-10 pts, Other-0 pts

  Setting Up Your Automation

  We've created ready-to-use templates for both person and company ICP scoring. Here's how to get started:

  Configure your connections

  Connect your Google Sheets account
  Add your Airtop API key (obtain from the Airtop dashboard)

  Set up your Google Sheet

  Ensure your Google Sheet has the necessary columns for input data and result fields
  Ensure that columns Linkedin_URL_Company and ICP_Score_Company exist at least

  Configure the Airtop module

  Set up the Airtop module to use the appropriate LinkedIn extraction prompt
  Use our provided prompt that extracts company profile data

  Customization Options

  While our templates work out of the box, you might want to customize them for your specific needs:

  Modify the ICP scoring criteria: Adjust the point values or add additional criteria specific to your business
  Add notification triggers: Set up Slack or email notifications for high-value leads that exceed a certain ICP threshold
  Implement batch processing: Modify the workflow to process leads in batches to optimize performance
  Add conditional logic: Create different scoring models for different industries or product lines
  Integrate with your CRM: Integrate this automation with your preferred CRM to get the details added automatically for you

  Real-World Applications

  Here's how businesses are using this automation:

  AI Sales Platform: A B2B AI company could implement this workflow to process their trade show lead list of contacts. Within hours, they can identify the top 50 prospects based on ICP score.

  SaaS Analytics Tool: A SaaS company could implement LinkedIn enrichment to identify which companies fit best. The automation processes weekly leads and categorizes them into high, medium, and low priority tiers, allowing their sales team to focus on the most promising opportunities first.

  Best Practices

  To get the most out of this automation:

  Review and refine your ICP criteria quarterly: What constitutes an ideal customer may evolve as your product and market develop
  Create tiered follow-up processes: Develop different outreach strategies based on ICP score ranges
  Perform regular data validation: Periodically check the accuracy of the automated scoring against your actual sales results

  What's Next?

  Now that you've automated your ICP scoring with LinkedIn data, you might be interested in:

  Setting up automated outreach sequences based on ICP score thresholds
  Creating custom reporting dashboards to track conversion rates by ICP segment
  Expanding your scoring model to include additional data sources
  Implementing lead assignment automation based on ICP scores


  Happy automating!

nodes_used:
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name: LinkedIn Person ICP Scoring Automation with Airtop & Google Sheets
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T17:21:04.457Z
updated_at: 2025-04-08T17:21:04.457Z
url: https://n8n.io/workflows/3476
scraped_at: 2025-12-24 13:02:46
description:
  About The ICP Person Scoring Automation

  Sorting through lists of potential leads manually to determine who's truly worth your sales team's time isn't just tedious, it's incredibly inefficient. Without proper qualification, your team might spend hours pursuing prospects who aren't the right fit for your product, while ideal customers slip through the cracks.

  How to Automate Identifying Your Ideal Customers

  With this automation, you'll learn how to automatically score and prioritize leads using data extracted directly from LinkedIn profiles via Airtop's built-in integration with n8n. By the end, you'll have a fully automated workflow that analyzes prospects and calculates an Ideal Customer Profile (ICP) score, helping your sales team focus on high-potential opportunities.

  What You'll Need

  A free Airtop API key
  A copy of this Google Sheets

  Understanding the Process

  This automation transforms how you qualify and prioritize leads by extracting real-time, accurate information directly from LinkedIn profiles. Unlike static databases that quickly become outdated, this workflow taps into the most current professional information available.

  The workflow in this template:

  Uses Airtop to extract comprehensive LinkedIn profile data
  Analyzes the data to calculate an ICP score based on AI interest, technical depth, and seniority
  Updates your Google Sheet with the enriched data and the ICP score

  Person ICP Scoring Workflow

  Our person-focused workflow evaluates individual LinkedIn profiles to determine how well they match your ideal customer profile by:

  Extracting data for each individual
  Analyzing  their profile to determine seniority and technical depth

  The system then automatically calculates an ICP score based on the following criteria:

  AI Interest: beginner-5 pts, intermediate-10 pts, advanced-25 pts, expert-35 pts
  Technical Depth: basic-5 pts, intermediate-15 pts, advanced-25 pts, expert-35 pts
  Seniority Level: junior-5 pts, mid-level-15 pts, senior-25 pts, executive-30 pts

  Setting Up Your Automation

  Here's how to get started:

  Configure your connections

  Connect your Google Sheets account
  Add your Airtop API key (obtain from the Airtop dashboard)

  Set up your Google Sheet

  Ensure your Google Sheet has the necessary columns for input data and result fields
  Ensure that columns Linkedin_URL_Person and ICP_Score_Person exist at least

  Configure the Airtop module

  Set up the Airtop module to use the appropriate LinkedIn extraction prompt
  Use our provided prompt that extracts individual profile data

  Customization Options

  While our templates work out of the box, you might want to customize them for your specific needs:

  Modify the ICP scoring criteria: Adjust the point values or add additional criteria specific to your business
  Add notification triggers: Set up Slack or email notifications for high-value leads that exceed a certain ICP threshold
  Implement batch processing: Modify the workflow to process leads in batches to optimize performance
  Add conditional logic: Create different scoring models for different industries or product lines
  Integrate with your CRM: Integrate this automation with your preferred CRM to get the details added automatically for you

  Real-World Applications

  Here's how businesses are using this automation:

  AI Sales Platform: A B2B AI company could implement this workflow to process their trade show lead list of contacts. Within hours, they can identify the top 50 prospects based on ICP score.

  SaaS Analytics Tool: A SaaS company could implement LinkedIn enrichment to identify which companies fit best. The automation processes weekly leads and categorizes them into high, medium, and low priority tiers, allowing their sales team to focus on the most promising opportunities first.

  Best Practices

  To get the most out of this automation:

  Review and refine your ICP criteria quarterly: What constitutes an ideal customer may evolve as your product and market develop
  Create tiered follow-up processes: Develop different outreach strategies based on ICP score ranges
  Perform regular data validation: Periodically check the accuracy of the automated scoring against your actual sales results

  What's Next?

  Now that you've automated your ICP scoring with LinkedIn data, you might be interested in:

  Setting up automated outreach sequences based on ICP score thresholds
  Creating custom reporting dashboards to track conversion rates by ICP segment
  Expanding your scoring model to include additional data sources
  Implementing lead assignment automation based on ICP scores


  Happy automating!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.airtop","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets"]

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name: Automated LinkedIn Profile Discovery with Airtop and Google Search
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T17:36:04.378Z
updated_at: 2025-04-08T17:36:04.378Z
url: https://n8n.io/workflows/3477
scraped_at: 2025-12-24 13:02:41
description:
  About The LinkedIn Profile Discovery Automation

  Are you tired of manually searching for LinkedIn profiles or paying expensive data providers for often outdated information? If you spend countless hours trying to find accurate LinkedIn URLs for your prospects or candidates, this automation will change your workflow forever. Just give this workflow the information you have about a contact, and it will automatically augment it with a LinkedIn profile.

  How to find a LinkedIn Profile Link

  In this guide, you'll learn how to automate LinkedIn profile link discovery using Airtop's built-in node in n8n. Using this automation, you'll have a fully automated workflow that saves you hours of manual searching while providing accurate, validated LinkedIn URLs.

  What You'll Need

  A free Airtop API key
  A Google Workspace account. If you have a Gmail account, you’re all set
  Estimated setup time: 10 minutes

  Understanding the Process

  This automation leverages the power of intelligent search algorithms combined with LinkedIn validation to ensure accuracy. Here's how it works:

  Takes your input data (name, company, etc.) and constructs intelligent search queries
  Utilizes Google search to identify potential LinkedIn profile URLs
  Validates the discovered URLs directly against LinkedIn to ensure accuracy
  Returns confirmed, accurate LinkedIn profile URLs

  Setting Up Your Automation

  Getting started with this automation is straightforward:

  Prepare Your Google Sheet

  Create a new Google Sheet with columns for input data (name, company, domain, etc.)
  Add columns for the output LinkedIn URL and validation status (see this example)

  Configure the Automation

  Connect your Google Workspace account to n8n if you haven't already
  Add your Airtop API credentials
  (Optionally) Configure your Airtop Profile and sign-in to LinkedIn in order to validate profile URL's

  Run Your First Test

  Add a few test entries to your Google Sheet
  Run the workflow
  Check the results in your output columns

  Customization Options

  While the default setup uses Google Sheets, this automation is highly flexible:

  Webhook Integration**: Perfect for integrating with tools like Clay, Instantly, or your custom applications
  Alternatives**: Replace Google Sheets with Airtable, Notion, or any other tools you already use for more robust database capabilities
  Custom Output Formatting**: Modify the output structure to match your existing systems
  Batch Processing**: Configure for bulk processing of multiple profiles

  Real-World Applications

  This automation has the potential to transform how we organizations handle profile enrichment.

  Recruiting Firm Success Story

  With this automation, a recruiting firm could save hundreds of dollars a month in data enrichment fees, achieve better accuracy, and eliminate subscription costs. They would also be able to process thousands of profiles weekly with near-perfect accuracy.

  Sales Team Integration

  A B2B sales team could integrate this automation with their CRM, automatically enriching new leads with validated LinkedIn profiles and saving their SDRs hours per week on manual research.

  Best Practices

  To maximize the accuracy of your results:

  Always include company information (domain or company name) with your search queries
  Use full names rather than nicknames or initials when possible
  Consider including location data for more accurate results with common names
  Implement rate limiting to respect LinkedIn's usage guidelines
  Keep your input data clean and standardized for best results
  Use the integrated proxy to navigate more effectively through Google and LinkedIn

  What's Next?

  Now that you've automated LinkedIn profile discovery, consider exploring related automations:

  Automated lead scoring based on LinkedIn profile data
  Email finder automation using validated LinkedIn profiles
  Integration with your CRM for automated contact enrichment

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.airtop","n8n-nodes-base.code","n8n-nodes-base.googleSheets"]

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name: Automate Instagram Posts with Google Drive, AI Captions & Facebook API
author_name: Sagar
author_username: sagarmasand9
categories: []
created_at: 2025-04-08T17:43:28.144Z
updated_at: 2025-04-08T17:43:28.144Z
url: https://n8n.io/workflows/3478
scraped_at: 2025-12-24 13:02:42
description:
  This template streamlines your Instagram content posting workflow by connecting Google Drive for image storage, using OpenAI for AI-generated captions, and leveraging Facebook Graph API for automated publishing.

  Pre-requisites
  Before setting up this workflow, ensure you have:

  A Google account with access to Google Drive

  An OpenAI API key for AI caption generation

  A Facebook Developer account with Instagram Graph API access

  An Instagram Business or Creator account connected to a Facebook Page

  n8n.io account with workflow access

  Setup Instructions
  Configure Data Source
  Create a Google Sheet with the following columns:

   Name: Filename of your image in Google Drive

  Caption: Optional custom caption (leave empty for AI-generated captions)

  URL: your Video Reel or Image in Google Drive

  Connect Google Drive
  Add your Google Drive credentials in the "Google Drive" node

  Specify the folder path where your Instagram image/Video are stored

  Configure the node to retrieve image files based on filenames from your Google Sheet

  Set Up OpenAI Integration
  Add your OpenAI API key to the credentials

  Configure the OpenAI node to generate engaging captions based on image content

  Adjust temperature and model parameters for desired creativity level

  Configure Facebook Graph API
  Connect your Facebook account with Instagram access

  Set up the Facebook Graph API node to post to your Instagram Business/Creator account

  Ensure proper image formatting (1:1, 4:5, or 16:9 aspect ratios supported by Instagram)

  Workflow Automation Setup
  Configure the scheduler node to run at your preferred frequency

  Set up error handling to notify you of any posting failures

  Add conditional nodes to use either custom or AI-generated captions

  Execution Instructions
  After completing all connections, test the workflow with a single image

  Monitor the execution in the n8n dashboard to ensure proper functioning

  View the "Executions" tab to track successful posts and troubleshoot any errors

  Adjust posting frequency and scheduling as needed

  This template saves hours of manual Instagram posting work while maintaining an authentic presence. Perfect for social media managers, content creators, and businesses looking to maintain consistent Instagram activity without the daily manual effort.

  The workflow handles image retrieval, caption generation or customization, proper Instagram API formatting, scheduled posting, and execution tracking - all in one automated solution.

nodes_used:
  ["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.facebookGraphApi","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.googleSheets","n8n-nodes-base.facebookGraphApi"]

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name: Build Lists of Profiles from Any Platform using Airtop and Google Sheets
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T17:50:38.487Z
updated_at: 2025-04-08T17:50:38.487Z
url: https://n8n.io/workflows/3479
scraped_at: 2025-12-24 13:02:45
description:
  About The List Building Automation

  This automation will guide you on how to automate list building using Airtop. You’ll have a streamlined workflow that can reduce your research time by up to 90% while improving the accuracy of your target lists.

  How to automate list building

  It can be challenging to spend too much time on tasks like compiling lists of potential investors, customers, job candidates, industry influencers, or key decision-makers. Verifying contact details often requires significant effort, whether building an outreach list, tracking thought leaders, or researching potential customers. Not anymore. With Airtop's List Building Automation, turn hours of tedious research into clean, reliable and accurate lists, built in just minutes. 

  Check this out:

  What You'll Need

  A free Airtop API Key
  Target audience parameters (persona and which network. i.e. "AI Influencers on LinkedIn)
  Make a copy of this template to start

  Understanding the Process

  This automation leverages Airtop's advanced data processing capabilities powered by AI to scan multiple unstructured sources and compile accurate, targeted lists based on your specific requirements. The magic lies in its ability to understand context and verify information across different platforms.

  This workflow:
   Handles multi-source data collection and consolidation
   Manages automatic verification of social profiles and domains
   Automates the filtering and ranking of results based on relevance

  Setting Up Your Automation

  Enter your search criteria in the "Parameters" node:
      Who: Your target audience (e.g., "Angel investors in Europe," "Top AI influencers")
      Where: The platform or domain to focus on (e.g., "LinkedIn," "TikTok") 
  Configure your Airtop API Key
      Create one for free at the Airtop Portal
   In the last node, select the spreadsheet that you copied earlier
   Run the workflow

  Customization Options

  While our template works out of the box, you might want to customize it for your specific needs:

  Add custom filtering criteria for more targeted results
  Implement automatic data enrichment from additional sources
  Set up automatic exports to your preferred CRM or database

  Real-World Applications

  Here's how businesses can use this automation:

  A VC firm could use this automation to build a comprehensive EU angel investors database. What previously required their analysts to work 15 hours per week now runs automatically in the background, providing fresh leads daily.

  A PR agency could automate its influencer discovery process across multiple platforms, reducing its research time from 10 hours to 30 minutes per client while increasing the relevance of its outreach lists.

  Best Practices

  To get the most out of this automation:

  Start with specific, well-defined parameters to ensure relevant results
  Regularly update your parameters to keep your lists fresh and relevant
  Combine multiple runs with different parameters for comprehensive coverage

  What's Next?

  Now that you've automated your list building, you might be interested in:

  Setting up automated outreach sequences
  Creating dynamic lead scoring systems
  Implementing automatic list updating and maintenance

  Happy automating!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.code","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.set"]

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name: Get notified when your competitors change their pricing with Airtop and Slack
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T18:06:13.231Z
updated_at: 2025-04-08T18:06:13.231Z
url: https://n8n.io/workflows/3480
scraped_at: 2025-12-24 13:02:45
description:
  About the Automation

  Staying on top of competitor pricing changes can be a full-time job. Manual price tracking is time-consuming and prone to errors, especially when dealing with complex pricing structures and multiple subscription tiers. Paid competitor price monitoring tools like Competera, Visualping and Fluxguard can be expensive. What if you could automate this process and get instant alerts when competitors adjust their pricing?

  How to easily monitor competitor pricing

  With this automation, you'll learn how to set up automated price monitoring system using Airtop's built-in node in n8n. By the end, your system will automatically track competitor pricing changes and notify you of any modifications.

  What You'll Need

  A free Airtop API Key
  Google Sheets account with a copy of this sheet
  URLs of competitors' pricing pages

  Understanding the Process

  This automation continuously monitors competitor pricing pages and compares them against your baseline data. The workflow:

  Tracks all different pricing plans (monthly, yearly, etc.).
  Monitors feature changes across different tiers.
  Detects and logs pricing structure modifications.
  Alerts you via Slack when changes are detected

  Setting Up Your Automation

  We've created a ready-to-use blueprint for seamless price monitoring. Here's how to get started:

  Connect your Google Sheets
  Set up your Airtop API connection
  Define update frequency

  Customization Options

  Enhance the basic template with these popular modifications:

  Add other notification channels (Email, Telegram, etc.).
  Include feature comparison tracking.
  Set up threshold-based alerts for significant price changes
  Track historical pricing trends

  Real-World Applications

  Case Study 1: A B2B SaaS company can use this automation to track competitors' pricing changes. When they identify a market-wide pricing shift, they can adjust their strategy proactively within minutes.

  Case Study 2: An online Ecommerce retailer automates monitoring of 100+ competitor products, maintaining optimal pricing positions and increasing profit margins.

  Best Practices

  To ensure accurate tracking:

  Include detailed baseline data for each pricing tier
  Specify both monthly and annual pricing clearly
  List all features included in each plan
  Update your baseline data whenever you verify changes
  Include any promotional pricing or special offers
  Document currency and regional variations if applicable

  Example Structure in Google Sheets:

  Competitor: Acme Tools
  Basic Plan:
  Monthly: $29
  Annual: $290 ($24.17/mo)
  Features: 5 users, 10GB storage, basic support
  Pro Plan:
  Monthly: $79
  Annual: $790 ($65.83/mo)
  Features: 20 users, 50GB storage, priority support

  What's Next?

  After setting up your price monitoring automation, consider the following:

  Creating automated competitive analysis reports
  Setting up market trend analysis
  Implementing automatic pricing recommendations
  Expanding monitoring to feature changes

  Happy monitoring!

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.airtop","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.googleSheets","n8n-nodes-base.slack","n8n-nodes-base.filter"]

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name: Automate Product Hunt Discovery with Airtop and Slack
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T18:16:07.546Z
updated_at: 2025-04-08T18:16:07.546Z
url: https://n8n.io/workflows/3481
scraped_at: 2025-12-24 13:02:46
description:
  About The Product Hunt Automation

  Staying up-to-date with specific topics and launches on Product Hunt can be time-consuming. Manually checking the site multiple times a day interrupts your workflow and risks missing important launches. What if you could automatically get relevant launches delivered to your Slack workspace?

  How to Monitor Product Hunt

  In this guide, you'll learn how to create a Product Hunt monitoring system using Airtop's built-in node in n8n. This automation will scan Product Hunt for your chosen topics and deliver the most relevant launches directly to Slack.

  What You'll Need

  A free Airtop API key
  A Slack workspace with permissions to add incoming webhooks
  Estimated setup time: 5 minutes

  Understanding the Process

  The Monitor Product Hunt automation uses Airtop's cloud browser capabilities to access Product Hunt and extract launch information. Here's what happens:

  Airtop visits Product Hunt and navigates the page
  It searches for and extracts up to 5 launches related to your chosen topic
  The information is formatted and sent to your specified Slack channel

  This process can run on your preferred schedule, ensuring you never miss relevant launches.

  Setting Up Your Automation

  We've created a ready-to-use template that handles all the complex parts. Here's how to get started:

  Connect your Airtop account by adding the API key you created
  Connect your Slack account
  Set your prompt in the Airtop node. For this example, we’ve set it to be “Extract up to 5 launches related to AI products”
  Choose your preferred monitoring schedule.

  Customization Options

  While our template works immediately, you might want to customize it for your specific needs:

  Adjust the prompt and the maximum number of launches to monitor
  Customize the Slack message format
  Change the monitoring frequency
  Add filters for particular keywords or companies

  Real-World Applications

  Here's how teams can use this automation:

  A startup's engineering team could track trends in other product’s tech stack, helping them stay informed about potential issues and improvements.

  A product manager can track launches of competitor products, enabling them to gather valuable market insights and user feedback directly from the tech community on that launch.

  Best Practices

  To get the most out of this automation:

  Choose Specific Search Terms**: For more relevant results, instead of broad terms like "AI," use specific phrases like "machine learning for healthcare"
  Optimize Scheduling**: When setting the monitoring frequency, consider your team's workflow. Running the scenario every 4 hours during working hours often provides a good balance between staying updated and avoiding notification fatigue.
  Set Up Error Handling**: Enable n8n's error output to alert you if the automation encounters any issues with accessing Product Hunt or sending messages to Slack.
  Regular Topic Review**: Schedule a monthly review of your monitored topics to ensure they're still relevant to your needs and adjust as necessary.

  What's Next?

  Now that you've set up your Product Hunt monitor automation, you might be interested in:

  Creating a similar monitor for other tech websites
  Setting up automated content curation for your team's newsletter
  Building a competitive intelligence dashboard using web monitoring

  Happy Automating!

nodes_used:
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name: Post on X using Airtop and automate content pipelines
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T18:21:21.478Z
updated_at: 2025-04-08T18:21:21.478Z
url: https://n8n.io/workflows/3482
scraped_at: 2025-12-24 13:02:46
description:
  About The Post to X Automation

  Seamlessly automate posting to X using Airtop and Make.

  How to Automate Posting to X with Airtop

  Consistently engaging your audience on X (formerly Twitter) can be a challenge, particularly when done manually. Developers and automation engineers often struggle with repetitive tasks like scheduling tweets, maintaining consistent posting cycles, and integrating content from various sources or AI-generated feeds. Manually managing content updates increases fatigue, human error, and decreases scalability.

  This n8n automation, powered by Airtop, simplifies automated content publishing onto X. Whether you're sharing daily updates, integrating dynamically generated AI content, or streamlining your marketing content pipeline, Airtop’s automation helps eliminate manual labor and reduces potential execution errors.

  Who is this Automation for?

  Social Media Managers scheduling recurring or automated posts on X
  Content Marketers integrating AI-generated content into their publishing process
  Developers implementing automated social media pipelines
  Automation Engineers minimizing errors and manual posting efforts

  Key Benefits

  Real-time, authenticated API postings via X
  Reliable structured workflows minimize manual errors
  Seamless integration with AI content pipelines

  Use Cases

  Automatically publish scheduled daily content updates
  Seamlessly post AI-generated insights, news summaries or industry updates
  Distribute alerts and event announcements reliably at set intervals
  Maintain active audience engagement by automating regular, high-frequency posts

  How the Post to X Automation Works

  This Airtop automation works by using your Airtop Profile signed-in into X via Airtop. Once authenticated securely with your X credentials, n8n handles the structured data flow, which can come from manual inputs, AI-generated sources, databases, or RSS feeds. Airtop then securely publishes the posts, providing reliable scheduled updates directly on X, removing manual oversight and streamlining your social media workflows.

  What You’ll Need

  An Airtop API key
  Your X (Twitter) account
  An Airtop Profile signed into X

  Setting Up the Automation

  Connect your Airtop account using your free Airtop API key
  Create an Airtop Profile and connect it to your X account
  Activate and schedule your scenario to automate regular posting

  Customize the Automation

  Customize your posting workflow extensively using Airtop's built-in node in n8n:

  Integrate diverse sources like RSS feeds and AI tools to dynamically customize automated posts
  Schedule precise posting intervals or diversify times for maximum audience engagement
  Set conditional logic to automate content posting based on predefined triggers and events
  Utilize Airtop’s structured data flows to manage categories, hashtags, or mentions in your posts

  Automation Best Practices

  Consistently update security credentials for uninterrupted access
  Clearly structure your workflow to simplify troubleshooting and logic updates
  Monitor posting frequency to ensure optimal audience reach and engagement
  Regularly review content sources to maintain quality control of automated postings

  Happy Automating!

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name: Sell a Used Car with an AI Agent in Airtop
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-08T18:51:40.903Z
updated_at: 2025-04-08T18:51:40.903Z
url: https://n8n.io/workflows/3483
scraped_at: 2025-12-24 13:02:46
description:
  How to Sell Your Used Car Easily with Airtop

  Selling a used car traditionally involves tedious manual steps: listing your vehicle online, filling repetitive forms, answering buyer inquiries, and comparing multiple offers—often leading to lost time, inaccuracies, and missed opportunities. Dealers' platforms and marketplace websites can introduce additional friction, occasionally requiring manual interactions and delivering inconsistent offers.

  The Sell a Used Car Agent powered by Airtop and n8n eliminates this friction by automating the selling process. Simply input your car's details once, and the automation quickly navigates through popular used car marketplaces like Carvana, CarMax, and others, efficiently fetching competitive buying offers. Leveraging Airtop’s powerful real-browser automation capabilities, this setup interacts smoothly with the forms and queries specific to each sales platform, eliminating error-prone manual entries and tedious repetition.

  This Airtop automation employs sophisticated data extraction features, including structured JSON output, ensuring accurate, formatted data ready for immediate review.

  Say goodbye to cumbersome listing processes, and hello to streamlined, effortless car selling.

  Who is this Automation for?

   Automation engineers streamlining marketplace interactions
   Developers building user-friendly car selling apps
   Technical teams optimizing inventory resale processes
   Dealership IT departments automating valuation systems

  Key Benefits

  No-code automation setup using Make
  Saves significant time with instant multi-platform offers
  Real browser sessions ensuring reliable site interactions
  Structured JSON output simplifying data integration

  Use Cases

  Car dealership teams quickly pricing used vehicles
  Individuals efficiently comparing offers from online dealers
  Developers building consumer-friendly automated car resale apps
  Technical consultants streamlining used car valuation processes

  How this Airtop Automation Works

  When started, Airtop opens automated, real browser sessions to intelligently fill out required car details on leading resale marketplaces (e.g., Carvana and CarMax). It captures instantly generated vehicle offers, structures them into clean JSON output, and returns organized buying proposals. All of this is accomplished without manual intervention.

  What You’ll Need

  A free Airtop API key
  Basic details describing your vehicle (make, model, condition, mileage)

  Setting up the workflow

  Create a new Airtop connection with your API key:



  Enter the information about the car you are selling into the "Variables" node. For example:

  &gt; VIN: 1FTRF17253NB81140
  Mileage: 221081
  Zip code: 01952
  Condition: Perfect, no interior or exterior damages, all tires are inflated, have 2 keys, working battery, has an attached catalytic converter, Airbags not deployed, No flood or fire damage.
  Ownership: full clean title with no debt answer yes to all other questions

  Run the workflow
  Customize the Automation

  Add or remove marketplaces based on regional availability or preference
  Extend JSON outputs to your internal inventory or sales systems
  Schedule regular automation runs to track market pricing trends
  Integrate additional valuation platforms for broader market coverage

  Automation Best Practices

  Regularly review marketplace URLs to maintain accuracy and consistency
  Verify structured data to ensure consistent JSON outputs
  Maintain clearly documented Make scenarios for easy debugging
  Periodically update your car's condition description for accurate pricing


  Happy Automating!

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name: 🧠 Build AI Agents with Think-Plan-Act Architecture Using Llama-4 Reasoning
author_name: Lucas Dias
author_username: devreis
categories: []
created_at: 2025-04-08T21:26:21.801Z
updated_at: 2025-04-08T21:26:21.801Z
url: https://n8n.io/workflows/3489
scraped_at: 2025-12-24 13:02:46
description:
  🧠 A plug-and-play n8n workflow that adds LLM-powered reasoning, planning, and action to your automations — with prompts, schemas, and full agent logic included.

  Ever wish your n8n flows could think before they act?

  Now they can. Say hello to the ultimate agent-based upgrade:

  "Think → Plan → Act" – fully automated. Fully intelligent.⚡

  🧩 What Is This?
  This product is a ready-to-use AI-powered workflow template for n8n, featuring a smart “Thinking Agent” that:

  🧠 Analyzes tasks
  📋 Generates a step-by-step plan
  🛠️ Executes actions intelligently
  🧾 Returns structured JSON outputs for your next steps

  Inspired by the Hugging Face agent architecture, this template gives your automations a brain before they press the red button. 🔴✅

  A clean 2-step process:
  THINK mode → Generates structured reasoning (goal, subgoals, tools, assumptions)
  ACT mode → Executes subgoals step-by-step using tools and AI.

  🧬 What's Inside?
  This isn’t just a flow — it’s a framework. You get:
  🔹 Modular Agent Loop
  🔹 A demonstration workflow

  📝 Requirements
  🔹 OpenRouter API Key (or any other provider like OpenAI, groq...)

  🔹 Built-in Parsers
  🧾 Structured JSON parser for reliable outputs
  🪄 Natural language and unstructured parsing fallback

  🛠️ Plug in your own goals, tools, and OpenRouter keys

  📦 Includes a demo (e.g., “get the weather”) to get started fast

  💡 Why You'll Love It
  ✅ Plug & Play – Drop into any existing n8n flow
  ✅ Tool-Aware Reasoning – Plans include which tool to use and why
  ✅ Composable – Build workflows like agents: Reason → Plan → Execute
  ✅ Customizable by anyone – Even your intern can tweak the prompts

  ⚙️ Agent customization
  🔹 Feel free to customize the agent settings by changing the Config node. Here's the default configuration:

  const config = {
    THINK: {
      CONTEXT: ``, // Add the necessary context to the AI.
      CONSTRAINTS: [Rule 1, Rule 2], // here are the rules that your AI should follow
      TOOLS: [
        {
          tool: "",
          description: "",
        },
      ], // add here the list of the tools that the AI will call in your backend or workflow.
    },
  };

  return {
    json: {
      config: config,
      input: $input.last().json,
    },
  };
  After updating the configuration file, you will see the AI reasoning for your input. Feel free to connect with any other node creating smart tasks!

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name: Automated LinkedIn Lead Generation, Scoring & Communication with AI-Agent
author_name: Andrey
author_username: kulia
categories: []
created_at: 2025-04-08T23:40:26.853Z
updated_at: 2025-04-08T23:40:26.853Z
url: https://n8n.io/workflows/3490
scraped_at: 2025-12-24 13:02:43
description:
  ⚠️ DISCLAIMER: This workflow uses the AnySite LinkedIn community node, which is only available on self-hosted n8n instances. It will not work on n8n.cloud.

  Overview

  This workflow automates the entire LinkedIn lead generation process from finding prospects that match your Ideal Customer Profile (ICP) to sending personalized messages. It uses AI to analyze lead data, score potential clients, and prioritize your outreach efforts.

  Key Features

  AI-Driven Lead Generation**: Convert ICP descriptions into LinkedIn search parameters
  Comprehensive Data Enrichment**: Analyze company websites, LinkedIn posts, and news
  Intelligent Lead Scoring**: Prioritize leads based on AI analysis of intent signals
  Automated Outreach**: Connect with prospects and send personalized messages

  Requirements

  Self-hosted n8n instance with the  AnySite LinkedIn community node installed
  OpenAI API access (for GPT-4o)
  Google Sheets access
  AnySite API key (available at anysite.io)
  LinkedIn account

  Setup Instructions

  1. Install Required Nodes

  Ensure the AnySite LinkedIn community node is installed on your n8n instance
  Command: npm install n8n-nodes-hdw
  (or use this instruction)

  2. Configure Credentials

  OpenAI**: Add your OpenAI API key
  Google Sheets**: Set up Google account access
  AnySite LinkedIn**: Configure your API key from AnySite.io

  3. Set Up Google Sheet

  Create a new Google Sheet with the following columns (or copy template):
    Name, URN, URL, Headline, Location, Current company, Industry, etc.
    The workflow will populate these columns automatically

  4. Customize Your ICP

  Use chat to provide the AI Agent with your Ideal Customer Profile
  Example: "Target marketing directors at SaaS companies with 50-200 employees"

  5. Adjust Scoring Criteria

  Modify the lead scoring prompt in the "Company Score Analysis" node to match your specific product/service
  Tune the evaluation criteria based on your unique business needs

  6. Configure Message Templates

  Update the AnySite LinkedIn Send Message node with your custom message

  How It Works

  ICP Translation: AI converts your ICP description into LinkedIn search parameters
  Lead Discovery: Workflow searches LinkedIn using these parameters
  Data Collection: Results are saved to Google Sheets
  Enrichment: System collects additional data about each lead:
     Company website analysis
     Lead's LinkedIn posts
     Company's LinkedIn posts
     Recent company news
  Intent Analysis: AI analyzes all data to identify buying signals
  Lead Scoring: Leads are scored on a 1-10 scale based on likelihood of interest
  Connection Requests: Top-scoring leads receive connection requests
  Follow-Up: When connections are accepted, automated messages are sent

  Customization

  Search Parameters**: Adjust the AI Agent prompt to refine your target audience
  Scoring Criteria**: Modify scoring prompts to highlight indicators relevant to your product
  Message Content**: Update message templates for personalized outreach
  Schedule**: Configure when connection requests and messages are sent

  Rate Limits & Best Practices

  LinkedIn has connection request limits (approximately 100-200 per week)
  The workflow includes safeguards to avoid exceeding these limits
  Consider spacing your outreach for better response rates

  Note: Always use automation tools responsibly and in accordance with LinkedIn's terms of service.

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","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-hdw.hdwLinkedin","n8n-nodes-hdw.hdwLinkedin","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-hdw.hdwLinkedin","n8n-nodes-base.aggregate","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.aggregate","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.aggregate","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-hdw.hdwLinkedin","n8n-nodes-hdw.hdwLinkedin","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","n8n-nodes-hdw.hdwWebParserTool","n8n-nodes-hdw.hdwWebParserTool","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.sort","n8n-nodes-base.if","n8n-nodes-base.limit","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.splitInBatches","n8n-nodes-hdw.hdwLinkedinManagement","n8n-nodes-base.scheduleTrigger","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.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-hdw.hdwLinkedinManagement","n8n-nodes-hdw.hdwLinkedinManagement","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.merge"]

workflow_json_compressed:
  [encoded data, 24272 characters]


name: Monitor SSL Certificate Expiry with Google Sheets and Multi-Channel Alert
author_name: Jesse Davids
author_username: cultrix
categories: []
created_at: 2025-04-09T07:25:10.177Z
updated_at: 2025-04-09T07:25:10.177Z
url: https://n8n.io/workflows/3493
scraped_at: 2025-12-24 13:02:45
description:
  SSL Expiry Alert System

  Who is this for?
  This workflow is ideal for administrators or IT professionals responsible for monitoring SSL certificates of multiple websites to ensure they do not expire unexpectedly.

  Problem
  SSL certificates play a crucial role in ensuring secure communication over the internet. However, if not monitored closely, they can expire, leading to potential security risks and service disruption. This workflow helps in proactively monitoring SSL certificate expiry dates.

  Functionality
  Pulls URLs to monitor from a Google Sheet.
  Checks SSL certificates using SSL-Checker.io.
  Updates Google Sheet with SSL details such as expiry date and certificate status.
  Sends email alerts for SSL certificates nearing expiry (&lt;30 days) or invalid certificates.

  Setup
  Clone the provided Google Sheet and update the Google Sheet URL in the "URLs to Monitor" node.
  Set up Google Sheets and Gmail credentials in n8n.
  Configure the Discourse Trigger for weekly monitoring.
  Customize email/telegram/ntfy alert settings as needed.

  Customization
  Modify the frequency of monitoring by adjusting the trigger interval in the "Weekly Trigger" node.
  Customize email content and recipients in the "Send Alert Email" node.
  Extend functionality by adding additional checks or actions based on SSL certificate status.

  Note
  Ensure proper authentication and authorization for accessing Google Sheets, SSL-Checker.io, and Gmail accounts within the workflow.

nodes_used:
  ["n8n-nodes-base.googleSheets","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-base.gmail","n8n-nodes-ntfy.Ntfy","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5360 characters]


name: Loading JSON via FTP to Qdrant Vector Database Embedding Pipeline
author_name: Ghaith Alsirawan
author_username: gsirawan
categories: []
created_at: 2025-04-09T07:42:31.732Z
updated_at: 2025-04-09T07:42:31.732Z
url: https://n8n.io/workflows/3495
scraped_at: 2025-12-24 13:02:46
description:
  🧠 This workflow is designed for one purpose only, to bulk-upload structured JSON articles from an FTP server into a Qdrant vector database for use in LLM-powered semantic search, RAG systems, or AI assistants.

  The JSON files are pre-cleaned and contain metadata and rich text chunks, ready for vectorization. This workflow handles
  Downloading from FTP
  Parsing & splitting
  Embedding with OpenAI-embedding
  Storing in Qdrant for future querying

  JSON structure format for blog articles
  {
    "id": "article_001",
    "title": "reseguider",
    "language": "sv",
    "tags": ["london", "resa", "info"],
    "source": "alltomlondon.se",
    "url": "https://...",
    "embedded_at": "2025-04-08T15:27:00Z",
    "chunks": [
      {
        "chunk_id": "article_001_01",
        "section_title": "Introduktion",
        "text": "Välkommen till London..."
      },
      ...
    ]
  }

  🧰 Benefits
  ✅ Automated Vector Loading
  Handles FTP → JSON → Qdrant in a hands-free pipeline.

  ✅ Clean Embedding Input
  Supports pre-validated chunks with metadata: titles, tags, language, and article ID.

  ✅ AI-Ready Format
  Perfect for Retrieval-Augmented Generation (RAG), semantic search, or assistant memory.

  ✅ Flexible Architecture
  Modular and swappable: FTP can be replaced with GDrive/Notion/S3, and embeddings can switch to local models like Ollama.

  ✅ Community Friendly
  This template helps others adopt best practices for vector DB feeding and LLM integration.

nodes_used:
  ["@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.ftp","n8n-nodes-base.splitInBatches","n8n-nodes-base.ftp","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Enhance AI Prompts with GPT-4o-mini and Telegram Delivery
author_name: Jesse Davids
author_username: cultrix
categories: []
created_at: 2025-04-09T07:54:42.486Z
updated_at: 2025-04-09T07:54:42.486Z
url: https://n8n.io/workflows/3496
scraped_at: 2025-12-24 13:02:46
description:
  Workflow Documentation

  Description:
  This workflow is designed to optimize prompts by enhancing user inputs for clarity and specificity using AI. The workflow takes a user-provided prompt as input and uses a Natural Language Processing (NLP) model to refine and improve the prompt. The optimized prompt is then sent back to the user, ready for use in further workflows or processes.

  Setup:
  This workflow is suitable for users who want to improve their prompts for better communication and understanding in their workflows.
  The workflow utilizes an AI Agent powered by an OpenAI Chat Model to enhance user prompts.

  Expected Outcomes:
  Users can provide vague or imprecise prompts as input to the workflow.
  The AI Agent will refine and optimize the prompt, adding clarity and specific details.
  The optimized prompt will be delivered back to the user via Telegram or can be input for the next nodes.

  Extra Information:
  A. A Telegram node is used to deliver the optimized prompt back to the user.
  B. Ensure you have the necessary credentials set up for Telegram and OpenAI accounts.
  C. Customize the workflow's settings, such as the AI model used for prompt optimization, to suit your requirements.
  D. Activate the workflow once all configurations are set to start optimizing prompts efficiently.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Conversing with Data: Transforming Text into SQL Queries and Visual Curves
author_name: hippolyte-hu
author_username: hippolyte-hu
categories: []
created_at: 2025-04-09T10:47:20.113Z
updated_at: 2025-04-09T10:47:20.113Z
url: https://n8n.io/workflows/3497
scraped_at: 2025-12-24 13:02:44
description:
  Conversational Data Retrieval and Visualization Workflow

  This workflow enables users to interact with a PostgreSQL database using natural language. It translates text inputs into SQL queries, retrieves the corresponding data, and generates visualizations using QuickChart, facilitating seamless data analysis without manual query writing.

  Table of Contents

  Pre-conditions and Requirements
  Database Schema Setup
  Step-by-Step Workflow Explanation
  Customization Guide

  Pre-conditions and Requirements

  1. API Keys and Services Required

  To operate this workflow, access to the following services is necessary:

  DeepSeek API**: For converting natural language into SQL queries.
    API Key: Obtain from your DeepSeek account.
  QuickChart**: For generating data visualizations.
    Service URL: https://quickchart.io/chart

  2. n8n Instance Setup

  n8n Installation**: Install and run n8n using the Official Guide.
  Credential Configuration**:
    DeepSeek API: Set up DeepSeek credentials in n8n by adding your API key.
    PostgreSQL Database:
      Local Database Access: If your PostgreSQL database is hosted locally and needs to be accessed over the internet (e.g., by n8n running on a different machine or in the cloud), you can expose it using ngrok:
        Install ngrok: Download and install ngrok from ngrok.com.
        Start ngrok Tunnel: Run the command ngrok tcp 5432 to expose your local PostgreSQL server.
           This will provide a forwarding address like tcp://0.tcp.ngrok.io:12345 that can be used to connect to your local database remotely.
        Update n8n Credentials: In n8n, configure the PostgreSQL node to use the ngrok forwarding address, ensuring remote access to your local database.

  Database Schema Setup

  Before initiating the workflow, ensure that the database schema is extracted and saved:

  Extract Schema: Retrieve the database schema, including table names and column details.
  Save Schema: Store the extracted schema in a JSON file for reference during query generation.

  Step-by-Step Workflow Explanation

  User Input Handling
     The workflow begins by receiving a natural language query from the user.

  Schema Retrieval
     Loads the previously saved database schema from the JSON file.

  AI-Based SQL Generation
     Combines the user's query with the database schema.
     Utilizes the DeepSeek API to translate the natural language query into a SQL statement.

  SQL Query Execution
     Executes the generated SQL query against the PostgreSQL database.
     Retrieves the data corresponding to the query.

  Data Visualization
     Formats the retrieved data into a structure compatible with QuickChart.
     Sends the data to QuickChart to generate a visual representation.
       Example: To create a bar chart, construct a URL with the chart configuration:
                https://quickchart.io/chart?c={type:'bar',data:{labels:['Label1','Label2'],datasets:[{label:'Dataset1',data:[10,20]}]}}
                This URL returns an image of the chart.

  Response Delivery
     Presents the generated visualizations and data insights to the user.

  Customization Guide

  Modifying the AI Model

  Alternative AI Services**: Replace DeepSeek with other AI models by adjusting the API call configurations in the workflow.

  Changing Visualization Services

  Visualization Tools**: Swap QuickChart with other visualization services by modifying the data processing and visualization steps.

  Expanding Database Support

  Additional Databases**: Adapt the workflow to support other databases (e.g., MySQL, MongoDB) by configuring the respective database credentials and query execution nodes.

  This workflow streamlines the process of data retrieval and visualization, allowing users to interact with their database using natural language, thereby enhancing accessibility and efficiency in data analysis.

nodes_used:
  ["@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.readWriteFile","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.readWriteFile","n8n-nodes-base.set","n8n-nodes-base.if","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.merge","n8n-nodes-base.postgres","n8n-nodes-base.convertToFile","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Build an IT Support Assistant Chatbot Leveraging Existing Support Portal
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-09T11:53:49.647Z
updated_at: 2025-04-09T11:53:49.647Z
url: https://n8n.io/workflows/3498
scraped_at: 2025-12-24 13:02:43
description:
  This n8n template demonstrates how you can leverage existing support site search to power your Support Chatbots and agents.

  Building a support chatbot need not be complicated! If building and indexing vector stores or duplicating data isn't necessarily your thing, an alternative implementation of the RAG approach is to leverage existing knowledge-bases such as support portals. In this way, document management and maintenance of your support agent is significantly reduced.

  Disclaimer: This template example uses AcuityScheduling's help center website but is not associated, supported nor endorsed by the company.

  How it works
  A simple AI agent is connected with chat trigger to receive user queries.
  The AI agent is instructed to fetch information from the knowledge-base via the attached custom workflow tool (aka "knowledgebase tool").
  There is no step to replicate the entire support articles database into a vector store. You may choose not too because of time, cost and maintainence involved.
  Instead, the tool leverages the existing support portal's search API to retrieve knowledge-base articles.
  Finally, the search results are formatted before sending an aggregated response back to the agent.

  How to use?
  Customise the subworkflow to work with your own support portal API and format accordingly.
  Try the following queries
    How do I connect my icloud to acuityScheduling?
    How do I download past invoices for my Acuity account?

  Requirements
  OpenAI for LLM.
  If your organisation's APIs require authorisation, you may need to add custom credentials as necessary.

  Customising this workflow
  Add additional tools to reach other parts of your internal knowledgebase.
  Not using OpenAI? Feel free to swap but ensure the LLM has tools/function calling support.

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger"]

workflow_json_compressed:
  [encoded data, 5900 characters]


name: AI-powered Student Assistant for Course Information via Twilio SMS
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-09T15:37:15.063Z
updated_at: 2025-04-09T15:37:15.063Z
url: https://n8n.io/workflows/3499
scraped_at: 2025-12-24 13:02:45
description:
  This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS.

  Given the right access to data, AI Agents are capable of planning and performing relatively complex research tasks to get their answers. In this example, the agent must first understand the database schema, retrieve lists of values before generating it's own query to search over the database.

  Checkout the example database here - https://airtable.com/appO5xvP1aUBYKyJ7/shr8jSFDaghubDOrw

  How it works
  A Twilio trigger gives us the ability to receive SMS input into our workflow via webhook.
  The message is then directed to our AI agent who is instructed to assist the user and use the course database as reference. The database is an Airtable base.
  The agent autonomously figures out which tool it needs to use and generates it's own "filter_by_formula" query to search over the available courses.
  On successful search results, the Agent can then use this information to answer the user's query.
  The Agent's output is logged in a second sheet of the Airtable base. We can use this later for analysis and lead gen.
  Finally, the response is sent back to the user through SMS using Twilio.

  How to use
  Ensure your Twilio number is set to forward messages to this workflow's webhook URL.
  Configure and update the course database as required. If you're not interested in courses, you can swap this out for inventory, deliveries or any other data relevant to your business.
  Ask questions like:
    "Can you help me find suitable courses to fill my Wednesday mornings?"
    "Which courses are being instructed by profession Lee?"
    "I'm interested in creative arts. What courses are available which could be relevant to me?"

  Requirements
  Twilio for SMS receiving and sending
  OpenAI for LLM and Agent
  Airtable for Course Database

  Customising this workflow
  Add additional tools and expand the range of queries the agent is able to answer or assist with.
  Not using Airtable? This technique also works with SQL databases like PostgreSQL.

nodes_used:
  ["n8n-nodes-base.twilioTrigger","n8n-nodes-base.airtableTool","n8n-nodes-base.airtableTool","n8n-nodes-base.set","n8n-nodes-base.twilio","n8n-nodes-base.airtable","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.airtableTool","n8n-nodes-base.airtableTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote"]

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  [encoded data, 4756 characters]


