# templates

name: Automate Video Content Posting to Multiple Social Platforms with Postiz
author_name: Aitor | 1Node
author_username: aitoralonso
categories: []
created_at: 2025-07-29T16:01:19.131Z
updated_at: 2025-07-29T16:01:19.131Z
url: https://n8n.io/workflows/6653
scraped_at: 2025-09-14 11:38:21
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  This workflow automates the distribution and scheduling of video content across multiple social platforms (TikTok, YouTube, Facebook, Instagram, Threads) through Postiz. Videos are collected from Google Drive, approved manually, and scheduled via the Postiz community node. 

  🧾 Requirements

  Google Drive** account with access to the folder that will watch for new items uploaded.
  videos in mp4 format ready to be shared or, alternatively you can connect a community node from Cloud Convert to convert the format before uploading into Postiz.
  Postiz account with integrations for TikTok, YouTube, Facebook, Instagram, and Threads
  🔗 Useful Links

  Postiz Docs
  Postiz Community Node

  🔄 Workflow Steps

  Trigger: Google Drive File Added
     Watches your selected Google Drive folder for new file uploads.

  Download File
     Downloads the detected video from Drive.

  Upload to Postiz
     Video is uploaded to Postiz to prepare for social scheduling.

  Set Fields
     Manual setting of social options 

  Extract Datetime (AI)
     Uses OpenAI to find/predict intended publish date & time, as the datetime format  is required to schedule on Postiz

  Get Social Integrations
     Fetches a list of user’s connected platforms from Postiz.

  Split and Filter Integrations
     Splits the process per platform (TikTok, YouTube, Facebook, Instagram, Threads).

  Schedule Post
     For each enabled platform, schedules the video with chosen options.

  🙋‍♂️ Need Help?

  Connect with 1 Node

nodes_used:
  ["n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.informationExtractor","n8n-nodes-base.stickyNote","n8n-nodes-postiz.postiz","n8n-nodes-base.httpRequest","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-postiz.postiz","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter"]

workflow_json_compressed:
  [encoded data, 6172 characters]


name: Manage Construction Projects with Tasks, Photo Reports, Telegram & Google Sheets
author_name: Artem Boiko
author_username: datadrivenconstruction
categories: []
created_at: 2025-07-30T06:10:11.318Z
updated_at: 2025-07-30T06:10:11.318Z
url: https://n8n.io/workflows/6675
scraped_at: 2025-09-14 11:38:21
description:
  How it works
  This template helps project managers collect task updates and photo reports from field workers via Telegram and stores everything in a Google Sheet. It enables daily project reporting without paper or back-office overhead.

  High-level flow:

  Workers receive daily tasks via Telegram

  They respond with photo reports

  Bot auto-saves replies (photos + status) to a Google Sheet

  The system tracks task completion, adds timestamps, and maintains report history

  Set up steps
  🕒 Estimated setup time: 15–30 min
  You’ll need:

  A Telegram bot (via BotFather)

  A connected Google Sheet (with specific column headers)

  A set of preconfigured tasks

  👉 Detailed setup instructions and required table structure are documented in sticky notes inside the workflow.

  Consulting and Training
  We work with leading construction, engineering, consulting agencies and technology firms around the world to help them implement open data principles, automate CAD/BIM processing and build robust ETL pipelines.

  If you would like to test this solution with your own data, or are interested in adapting the workflow to real project tasks, feel free to contact us.


  Docs & Issues:  
    Full Readme on GitHub

nodes_used:
  ["n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.cron","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.googleSheets","n8n-nodes-base.cron","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.noOp","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegramTrigger","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleDrive","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 40656 characters]


name: Bulk Resume Screening & JD Matching with GPT-4 for HR Teams
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-07-30T08:07:01.612Z
updated_at: 2025-07-30T08:07:01.612Z
url: https://n8n.io/workflows/6680
scraped_at: 2025-09-14 11:38:21
description:
  TalentFlow AI – Bulk Resume Screening with JD Matching

  Automatically extract, evaluate, and shortlist multiple resumes against a selected job description using GPT-4. This smart, scalable n8n workflow helps HR/TA teams streamline hiring decisions while keeping results structured, auditable, and easy to share.

  👤 Who’s it for

  This workflow is designed for:
  HR or Talent Acquisition (TA) teams handling multiple candidates per role
  Recruiters who want AI-assisted resume screening to save time and reduce bias
  Organizations that want to automatically log evaluations and keep stakeholders updated in real-time via Slack or Sheets

  ⚙️ How it works / What it does

  HR/TA uploads multiple candidate resumes and selects a job role
  Each resume is:
     Uploaded to Google Drive
     Parsed with GPT-4 to extract structured profile data
  The job description for the selected role is:
     Retrieved from Google Sheets
     Downloaded from Drive and parsed
  The profile + JD are sent to an AI agent to generate:
     Fit score
     Strengths & gaps
     Final recommendation
  Results are:
     Appended to the evaluation tracking sheet
     Optionally shared with the hiring team on Slack
     Used to trigger emails to qualified or unqualified candidates

  🛠️ How to set up

  Clone or import the workflow into your n8n instance
  Connect your integrations:
     Google Sheets (positions & evaluation form)
     Google Drive (CV & JD folders)
     OpenAI API (GPT-4)
     Slack (for notifications)
     (Optional) SendGrid or SMTP for email notifications
  Update Google Sheets structure:
     Positions sheet: maps Job Role → JD file link
     Evaluation form: stores evaluation results
  Prepare Drive folders:
     /cv folder for uploaded resumes
     /jd folder for job description PDFs

  📋 Requirements

  ✅ n8n (hosted or self-hosted)
  ✅ OpenAI GPT-4 account (used in Profile & JD evaluator agents)
  ✅ Google Drive + Google Sheets access
  ✅ Slack workspace + bot token
  (Optional) SendGrid or email credentials for candidate follow-up

  🎨 How to customize the workflow

  Change the fit score threshold in the Candidate qualified? node
  Edit Slack message content/formatting to match your company tone
  Add additional candidate metadata to Sheets or Slack messages
  Use a webhook trigger to integrate with your ATS or job board
  Swap GPT-4 with Claude or Gemini if you prefer other AI services
  Expand to include multi-position batch screening logic

  Happy Hiring! 🚀  
  Automated with love using n8n

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDrive","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.sendGrid","n8n-nodes-base.slack","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.filter"]

workflow_json_compressed:
  [encoded data, 11836 characters]


name: Track Expenses from Receipt Photos with Telegram & Google Sheets using OCR.space
author_name: Candra Reza
author_username: candrareza
categories: []
created_at: 2025-07-30T09:02:35.042Z
updated_at: 2025-07-30T09:02:35.042Z
url: https://n8n.io/workflows/6686
scraped_at: 2025-09-14 11:38:20
description:
  Hello automation enthusiasts! 👋

  Want to automatically track your expenses from receipts without hefty OCR service costs? I've got you covered!

  I've updated my Personal Finance Tracking Chatbot template to incorporate a free OCR service (OCR.space). This powerful n8n workflow lets you effortlessly log your expenses by sending a picture of your receipt to your Telegram bot. The OCR will extract key details like amount, date, and description, which are then neatly saved into your Google Sheets!

  Why use this template?
  📸 Free OCR-Powered Expense Tracking: Simply send a photo of your receipt to your Telegram bot and let OCR.space do the heavy lifting – without breaking the bank!
  📊 Automated Google Sheets Entry: Extracted data is seamlessly appended to your Google Sheet for easy financial overview.
  💰 Manual Entry Still Available: Easily record incomes and expenses via text commands for transactions without receipts.
  🤖 Instant Telegram Confirmations: Get immediate feedback on successful recordings, whether manual or OCR-processed.
  ✨ Customizable Parsing: The included Function node allows you to refine the data extraction logic to perfectly match your receipt formats.

  What Do You Need?
  An n8n account (self-hosted or cloud)
  Your own Telegram Bot (free and easy to create!)
  A free API Key from OCR.space.
  A Google account and an empty Google Spreadsheet for your financial data.
  A Google Spreadsheet with "Income" and "Expenses" sheets (with columns like Date, Description, Amount, Category, Type, Source).

  Who Is This For?
  This template is perfect for anyone who wants to gain more control over their personal finances in an efficient and hassle-free way. No more complex apps, just use your personal chatbot!

  How to Use It?
  Get Your Free OCR.space API Key: Visit ocr.space/OCRAPI and sign up for a free key.
  Import this JSON template into your n8n instance.
  Configure Credentials: Set your Telegram Bot Token, Google Sheet ID, and OCR.space API Key as environment variables in n8n.
  Activate the workflow.
  Start tracking your finances by sending text commands (e.g., income salary 5000, expense coffee 15 food) or just snapping a photo of your receipt to your Telegram bot!

  Let's simplify your financial management with automation! Feel free to try it out and modify it to suit your needs. If you have any questions, leave a comment below!

nodes_used:
  ["n8n-nodes-base.telegramBot","n8n-nodes-base.if","n8n-nodes-base.telegramBot","n8n-nodes-base.httpRequest","n8n-nodes-base.telegramBot"]

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name: Automate IT Support: Convert Emails to Jira Tickets with AI Resolution
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-07-31T10:19:09.456Z
updated_at: 2025-07-31T10:19:09.456Z
url: https://n8n.io/workflows/6735
scraped_at: 2025-09-14 11:38:22
description:
  SmartSupport Flow: Auto-Handle IT Requests from Email to JIRA with Slack notification
  Watch the demo video below:

  Who’s it for
  &gt; This workflow is built for lean IT teams, office managers, and business operators who receive support requests via email and want to automate ticket creation, smart AI resolution advice, and seamless communication with both users and internal teams, all without lifting a finger.  
  If your team is tired of manually triaging inbox requests, this AI-powered flow will transform your support handling process.

  How it works / What it does

  Trigger on New Email: Uses Gmail Trigger to detect new support request emails.
  Fetch Email Content: Retrieves the full message body and metadata.
  Check for Duplication: Skips processing if the email has already been handled (based on READ/UNREAD label).
  Mark as Read: Updates Gmail to mark the email as processed.
  Extract Structured Request: Uses the Support Request Reader Agent powered by OpenAI to extract:
     Request title
     Request description
     Requested by
     Department
     Category and priority
  Create Jira Ticket: A main issue is created in Jira using the structured request.
  Generate AI-Based Solution: Invokes the IT Support Advisor Agent to propose resolution(s).
  Post Comment to Jira: Adds the suggested solution(s) to the issue as a comment.
  Notify IT Team: Sends the ticket and context to a Slack channel for visibility and action.
  (Optional) Send Email to Requester: Currently deactivated. Can be enabled to acknowledge receipt.

  How to set up

  Gmail Integration
     Connect Gmail in the “Gmail Trigger” and “Get Email Content” nodes.
  OpenAI Configuration
     Use OpenAI API credentials in both the Reader and Advisor agent models.
  Jira Integration
     Authenticate your Jira account.
     Set project key and issue fields in the “Create Main Issue” node.
  Slack Notification
     Configure Slack connection and select a target channel.
  Set up Jira, Slack, Email
     Set your company Jira based URL, IT Support slack channel and IT Support email in the Edit Fields (Set) node 
  (Optional) Email Acknowledgment
     Provide SendGrid credentials and email template in the “Send email to requester” node if re-enabled.

  Requirements

  Gmail API access with appropriate permissions  
  OpenAI account with API access (for GPT-4 or GPT-3.5)  
  Jira instance with project and permission to create/comment on issues  
  Slack workspace and Webhook or OAuth setup  
  n8n instance running with all above integrations configured

  How to customize the workflow

  Enhance Email Deduplication**: Adjust the deduplication logic to use message-id, threadId, or custom headers.
  Expand Reader Agent**: Configure the LLM to extract more details such as asset tags, urgency levels, or locations.
  Tailor Advisor Agent**: Adjust prompt to generate multiple solutions, troubleshooting guides, or internal references.
  Routing by Department**: Add logic to forward requests to different teams based on the request category or department.
  Enable Email Acknowledgment**: Activate and customize the email notification step to inform requesters that their issue is being handled.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.filter","n8n-nodes-base.slack","n8n-nodes-base.sendGrid","n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.jira","n8n-nodes-base.gmail","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.jira","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Reddit Lead Finder: Automated Prospecting with GPT-4, Supabase and Gmail Alerts
author_name: BluePro
author_username: bluepro
categories: []
created_at: 2025-08-01T01:36:19.492Z
updated_at: 2025-08-01T01:36:19.492Z
url: https://n8n.io/workflows/6756
scraped_at: 2025-09-14 11:38:21
description:
  This workflow monitors targeted subreddits for potential sales leads using Reddit’s API, AI content analysis, Supabase, and Google Sheets.

  It is built specifically to discover posts from Reddit users who may benefit from a particular product or service. It can be easily customized for any market.

  🔍 Features

  Targeted Subreddit Monitoring:**  
    Searches multiple niche subreddits like smallbusiness, startup, sweatystartup, etc., using relevant keywords.

  AI-Powered Relevance Scoring:**  
    Uses OpenAI GPT to analyze each post and determine if it’s written by someone who might benefit from your product, returning a simple “yes” or “no.”

  Duplicate Lead Filtering with Supabase:**  
    Ensures you don’t email the same lead more than once by storing already-processed Reddit post IDs in a Supabase table.

  Content Filtering:**  
    Filters out posts with no body text or no upvotes to ensure only high-quality content is processed.

  Lead Storage in Google Sheets:**  
    Saves qualified leads into a connected Google Sheet with key data (URL, post content, subreddit, and timestamp).

  Email Digest Alerts:**  
    Compiles relevant leads and sends a daily digest of matched posts to your team’s inbox for review or outreach.

  Manual or Scheduled Trigger:**  
    Can be manually triggered or automatically scheduled (via the built-in Schedule Trigger node).

  ⚙️ Tech Stack

  Reddit API** – For post discovery  
  OpenAI Chat Model** – For AI-based relevance filtering  
  Supabase** – For lead de-duplication  
  Google Sheets** – For storing lead details  
  Gmail API** – For sending email alerts

  🔧 Customization Tips

  Adjust Audience**: Modify the subreddits and keywords in the initial Code node to match your market.
  Change the AI Prompt**: Customize the prompt in the “Analysis Content by AI” node to describe your product or service.
  Search Comments Instead**: To monitor comments instead of posts, change type=link to type=comment in the Reddit Search node.
  Change Email Recipients**: Edit the Gmail node to direct leads to a different email address or format.

nodes_used:
  ["n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.reddit","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.gmail","n8n-nodes-base.splitInBatches","n8n-nodes-base.supabase","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.supabase","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.scheduleTrigger"]

workflow_json_compressed:
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name: Scheduled Instagram Auto-Liker with Phantombuster, GPT-4o & Cookie Rotation
author_name: plemeo
author_username: plemeo
categories: []
created_at: 2025-08-01T08:20:52.647Z
updated_at: 2025-08-01T08:20:52.647Z
url: https://n8n.io/workflows/6765
scraped_at: 2025-09-14 11:38:20
description:
  Who’s it for  
  Social-media managers and brands that want to keep their Instagram
  accounts active by automatically liking fresh posts under selected
  hashtags—hands-free and rate-limited.

  How it works / What it does  
  Schedule Trigger runs every 2 hours at a specified minute.  
  Select Cookie chooses a rotating Instagram session-cookie
     (time-slice logic).  
  Generate Random Hashtag (GPT-4o) outputs a realistic AI/BPA
     hashtag.  
  Instagram Hashtag Agent (Phantombuster) scrapes up to
     ENV_MAX_POSTS_PER_HASHTAG recent posts.  
  Get Random Post selects one; duplicate checker ensures it
     hasn’t been liked before (SharePoint CSV).  
  Builds instagram_posts_to_like.csv, uploads to SharePoint, then
     launches the Auto-like Agent which likes the post.  
  Post URL is appended to instagram_posts_already_liked.csv to avoid
     duplicates.  
  Wait nodes throttle launches to ~12 likes per profile daily.

  How to set up  
  Add credentials: Phantombuster API, SharePoint OAuth2, OpenAI API
     key.  
  In SharePoint › “Phantombuster” folder create:  
     • instagram_session_cookies.txt – one cookie per line.  
     • instagram_posts_already_liked.csv with header postUrl.  
  Adjust Set ENV Variables to change max posts per scrape.  
  Activate the workflow; it will like one post every 2 hours.

  Requirements  
  n8n 1.33 +  
  Phantombuster Growth plan (API access)  
  OpenAI account
  Microsoft 365 SharePoint tenant

  How to customize  
  Target a different niche: edit hashtag prompt in Generate Random Hashtag.  
  Like more posts: raise ENV_MAX_POSTS_PER_HASHTAG,
    numberOfPostsPerLaunch, or schedule frequency.  
  Replace SharePoint with Drive/Dropbox by swapping storage nodes.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.wait","n8n-nodes-base.phantombuster","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.extractFromFile","n8n-nodes-base.convertToFile","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Auto-follow Instagram profiles via Phantombuster and SharePoint
author_name: plemeo
author_username: plemeo
categories: []
created_at: 2025-08-01T08:26:18.753Z
updated_at: 2025-08-01T08:26:18.753Z
url: https://n8n.io/workflows/6766
scraped_at: 2025-09-14 11:38:20
description:
  Who’s it for  
  Community managers, growth hackers, and brands that want to grow their
  Instagram audience by automatically following new, relevant profiles—
  while respecting daily limits.

  How it works / What it does  
  Schedule Trigger runs hourly at a specified minute.  
  Select Cookie chooses a rotating Instagram session-cookie (time-slice logic).  
  Get List of Accounts downloads a CSV of seed profiles from SharePoint.  
  Follower Collector Agent (Phantombuster) fetches each seed
     profile’s followers (limit set by ENV_AMOUNT_FOLLOWERS_PER_PROFILE).  
  Autofollow Agent follows up to ENV_PROFILES_TO_PROCESS of those
     followers per launch.  
  Wait nodes pause between Phantombuster calls and poll until each
     run is complete.  
  Rate-limit configuration keeps follows between 1 and 40 per hour.

  How to set up  
  Add credentials: Phantombuster API, SharePoint OAuth2, (optional) OpenAI API key if you later add AI.  
  In SharePoint › “Phantombuster” folder add:  
     • instagram_session_cookies.txt – one cookie per line.  
     • accounts_to_follow.csv – header profileUrl, one seed profile per line.  
  Update Set ENV Variables to control profiles/launch and followers/profile.  
  Adjust schedule frequency or Wait durations to meet your plan limits.  
  Activate the workflow; it will follow new profiles every hour.

  Requirements  
  n8n 1.33 +  
  Phantombuster Growth plan (API access)  
  Microsoft 365 SharePoint tenant

  How to customize  
  Scrape hashtags instead of followers: replace the Follower Collector
    agent with a Hashtag‐to‐Profiles agent.  
  Increase speed: raise ENV_PROFILES_TO_PROCESS and cron frequency
    (ensure you stay within Instagram limits).  
  Swap SharePoint for Drive/Dropbox by replacing storage nodes.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.phantombuster","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Auto-comment on Instagram posts with GPT-4o, Phantombuster, and SharePoint
author_name: plemeo
author_username: plemeo
categories: []
created_at: 2025-08-01T08:32:37.238Z
updated_at: 2025-08-01T08:32:37.238Z
url: https://n8n.io/workflows/6768
scraped_at: 2025-09-14 11:38:20
description:
  Who’s it for  
  Social-media teams and influencers who want to grow engagement by
  automatically posting short, relevant comments on new Instagram posts
  under rotating hashtags—while staying under platform limits.

  How it works / What it does  
  Schedule Trigger fires every 2 h at a specified minute.  
  Select Cookie chooses a rotating Instagram session-cookie by
     time slice.  
  Generate Random Hashtag (GPT-4o) outputs a realistic AI/BPA tag.  
  Hashtag Agent (Phantombuster) scrapes up to
     ENV_MAX_POSTS_PER_HASHTAG recent posts.  
  Get Random Post picks one; Create Comment (GPT-4o) crafts a
     ≤150-character reply in the chosen language.  
  Builds instagram_post_to_comment.csv, uploads to SharePoint, then
     launches the Auto-comment Agent which posts the reply.  
  Post URL is logged to instagram_posts_already_commented.csv
     to avoid duplicates.  
  Wait nodes throttle launches to ≈80 comments/day.

  How to set up  
  Add credentials: Phantombuster API, SharePoint OAuth2, OpenAI API key.  
  In SharePoint › “Phantombuster” folder create:  
     • instagram_session_cookies.txt – one cookie per line.  
     • instagram_posts_already_commented.csv with header postUrl.  
  Edit Set ENV Variables to set default language, prompt, and max
     posts per scrape.  
  Activate the workflow; it will comment every 2 h.

  Requirements  
  n8n 1.33 +  
  Phantombuster Growth plan (API access)  
  OpenAI account (GPT-4o)  
  Microsoft 365 SharePoint tenant

  How to customize  
  Change tone/length: tweak prompt in Create Comment.  
  Comment more often: raise ENV_MAX_POSTS_PER_HASHTAG,
    adjust cron, and agent limits.  
  Swap SharePoint for Drive/Dropbox by replacing storage nodes.

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name: Automate QuickBooks Customers & Sales Receipts Generation from a Google Sheet
author_name: Intuz
author_username: intuz
categories: []
created_at: 2025-08-01T08:59:09.867Z
updated_at: 2025-08-01T08:59:09.867Z
url: https://n8n.io/workflows/6770
scraped_at: 2025-09-14 11:38:21
description:
  This n8n template from Intuz provides a complete and automated solution to streamline your sales and accounting process.

  Simply add new transaction details to a designated Google Sheet, and this workflow takes over. Using specific status keywords in a column to trigger the process, it automatically creates new customer profiles and generates sales receipts in QuickBooks. This creates a complete, end-to-end system from a simple spreadsheet entry to a formal accounting record, eliminating manual data entry.

  How it works

  This workflow streamlines the process of recording sales from a Google Sheet into QuickBooks Online, intelligently handling both new and existing customers.

  1. Trigger on New Row: The workflow starts automatically whenever a new row is added to your specified Google Sheet.

  2. Check for Existing Customer: It takes the customer's name from the new row and searches your QuickBooks account to see if a customer with that DisplayName already exists.

  3. Conditional Logic (IF Node): Based on the search result, the workflow splits into two paths:

  If Customer Exists (True Path): The workflow proceeds directly to create a Sales Receipt, linking it to the existing customer's ID found in the search.
  If Customer Does Not Exist (False Path): The workflow first creates a new customer in QuickBooks using the name and email from the sheet. It then uses the ID of this newly created customer to generate the corresponding Sales Receipt.

  How to Use: Quick Start Guide

  Prepare your Google Sheet: Make sure you have a Google Sheet with clear headers for your sales data. The template is configured for the following columns: CustomerName, Email, Amount, and Quantity.

  Import the Template: Click the "Use Template" button to import the workflow into your n8n instance.

  Configure Google Sheet Node: 
  Enter the Spreadsheet ID from your Google Sheet's URL.
  Enter the Sheet Name where your sales data is located (e.g., Sheet1).

  Configure the QuickBooks Nodes: 
  Select your QuickBooks Online credential or create a new one for the "Search for Customer", "Create Receipt for EXISTING Customer", "Create New Customer", and "Create Receipt for NEW Customer" nodes.
  Important: In both "Create Receipt" nodes, you must provide a valid Product/Service ID from your QuickBooks account. Find this in the node parameters under Line &gt; Sales Item Line Detail &gt; Item Ref &gt; Value.

  Activate the Workflow: Save your changes and activate the workflow. Now, every new row you add to the Google Sheet will automatically create the necessary records in QuickBooks.
  Key Requirements to Use Template
  An active n8n instance.
  A Google account with a prepared Google Sheet.
  A QuickBooks Online account.
  A QuickBooks Developer account to obtain the API credentials needed to connect to n8n.
  At least one Product or Service item set up in your QuickBooks account to be referenced in the sales receipts.
  Connect with us

  Website: https://www.intuz.com/services
  Email: getstarted@intuz.com
  LinkedIn: https://www.linkedin.com/company/intuz
  Get Started: https://n8n.partnerlinks.io/intuz

  For Custom Worflow Automation
  Click here- Get Started

nodes_used:
  ["n8n-nodes-base.googleSheetsTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.quickbooks","n8n-nodes-base.quickbooks","n8n-nodes-base.stickyNote","n8n-nodes-base.quickbooks"]

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name: WhatsApp RAG Chatbot with Supabase, Gemini 2.5 Flash, and OpenAI Embeddings
author_name: Manav Desai
author_username: manavdesai17
categories: []
created_at: 2025-08-01T09:17:50.511Z
updated_at: 2025-08-01T09:17:50.511Z
url: https://n8n.io/workflows/6771
scraped_at: 2025-09-14 11:38:20
description:
  WhatsApp RAG Chatbot with Supabase, Gemini 2.5 Flash, and OpenAI Embeddings

  This n8n template demonstrates how to build a WhatsApp-based AI chatbot that answers user questions using document retrieval (RAG) powered by Supabase for storage, OpenAI embeddings for semantic search, and Gemini 2.5 Flash LLM for generating high-quality responses.

  Use cases are many: Turn your WhatsApp into a knowledge assistant for FAQs, customer support, or internal company documents — all without coding.

  Good to know

  The workflow uses OpenAI embeddings for both document embeddings and query embeddings, ensuring accurate semantic search.  
  Gemini 2.5 Flash LLM** is used to generate user-friendly answers from the retrieved context.  
  Messages are processed in real-time and sent back directly to WhatsApp.  
  Workflow is modular — you can split document ingestion and query handling for large-scale setups.  
  Supabase and WhatsApp API credentials must be configured before running.  

  How it works

  Trigger: A new WhatsApp message triggers the workflow via webhook.  
  Message Check: Determines if the message is a query or a document upload.  
  Document Handling:  
     Fetch file URL from WhatsApp.  
     Convert binary to text.  
     Generate embeddings with OpenAI and store them in Supabase.  
  Query Handling:  
     Generate query embeddings with OpenAI.  
     Retrieve relevant context from Supabase.  
     Pass context to Gemini 2.5 Flash LLM to compose a response.  
  Response: Send the answer back to the user on WhatsApp.  

  Optional: Add Gmail node to forward chat logs or daily summaries.

  How to use

  Configure WhatsApp Business API webhook for incoming messages.  
  Add your Supabase and OpenAI credentials in n8n’s credentials manager.  
  Upload documents via WhatsApp to populate the Supabase vector store.  
  Ask queries — the bot retrieves context and answers using Gemini 2.5 Flash.

  Requirements

  WhatsApp Business API** (or Twilio WhatsApp Sandbox)  
  Supabase account** (vector storage for embeddings)  
  OpenAI API key** (for generating embeddings)  
  Gemini API access** (for LLM responses)  

  Customising this workflow

  Swap WhatsApp with Telegram, Slack, or email for different chat channels.  
  Extend ingestion to other sources like Google Drive or Notion.  
  Adjust the number of retrieved documents or prompt style in Gemini for tone control.  
  Add a Gmail output node to send logs or alerts automatically.  

nodes_used:
  ["@n8n/n8n-nodes-langchain.vectorStoreSupabase","n8n-nodes-base.whatsAppTrigger","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStoreSupabase","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.whatsApp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.whatsApp","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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name: Automate GitHub PRs & JIRA Updates from Git Commit Commands-Single Repo
author_name: Intuz
author_username: intuz
categories: []
created_at: 2025-08-01T10:22:39.160Z
updated_at: 2025-08-01T10:22:39.160Z
url: https://n8n.io/workflows/6773
scraped_at: 2025-09-14 11:38:21
description:
  This n8n template from Intuz delivers a complete and automated solution to streamline your development workflow for a single repository.

  By embedding specific keywords and a JIRA issue ID within your git commit commands, this workflow automatically creates a Pull Request in GitHub and simultaneously updates the corresponding JIRA ticket. This provides a complete, seamless integration that eliminates manual steps and keeps your project management perfectly in sync with your codebase.

  How it works

  This workflow acts as a powerful bridge between your Git repository and your project management tools, driven entirely by the structure of your commit messages.

  GitHub Webhook Trigger: 
  The workflow starts when a developer pushes a new commit to a specified repository in GitHub.

  Parse Commit Message: A Code node extracts key information from the commit message:

  The JIRA Issue Key (e.g., FF-1196).
  The base branch for the PR (e.g., development).
  Action commands like [auto-pr] and [taskcompleted].

  Conditional PR Creation: An IF node checks if the [auto-pr] command is present.

  If yes, it uses the GitHub node to automatically create a pull request from the developer's branch to the specified base branch.
  If no, this step is skipped, allowing for multiple commits before a PR is made.

  Conditional JIRA Update: Another IF node checks for the [taskcompleted] command.

  If yes, it uses the JIRA node to transition the corresponding issue to your "Done" status (e.g., "Task Completed" or "In Review").
  If no, the JIRA issue remains in its current state, perfect for work-in-progress commits.

  How to Use: Quick Start Guide

  Click the "Use Template" button to import this workflow into your n8n instance.

  Configure the GitHub Trigger:
  Open the "GitHub Push Trigger" node. It will display a unique Webhook URL. Copy this URL.
  In your GitHub repository, go to Settings &gt; Webhooks &gt; Add webhook.
  Paste the URL into the Payload URL field.
  Set the Content type to application/json.
  Under "Which events would you like to trigger this webhook?", select Just the push event.
  Click Add webhook.

  Connect Your Accounts:
  GitHub: Select your GitHub API credential in the "Create Pull Request" node.
  JIRA : Select your JIRA API credential in the "Update JIRA Issue Status" node.

  Customize the JIRA Transition (Important):
  Open the "Update JIRA Issue Status" node.
  In the Transition parameter, you need to set the specific status you want to move the issue to (e.g., 'Done', 'Completed', 'In Review'). You can use the ID or the exact name of the transition from your JIRA  project's workflow.

  Activate the Workflow: Save your changes and activate the workflow. You're ready to automate!

  Example Commit Message:
  git commit -m "FF-1196 Implement OAuth login [auto-pr,development,taskcompleted]"

  Key Requirements to Use Template

  An active n8n instance.
  A GitHub account with repository admin permissions to create webhooks.
  A JIRA Cloud account with permissions to update issues.
  Developers who can follow the specified git commit message format.

  Connect with us

  Website: https://www.intuz.com/services
  Email: getstarted@intuz.com
  LinkedIn: https://www.linkedin.com/company/intuz
  Get Started: https://n8n.partnerlinks.io/intuz

  For Custom Worflow Automation
  Click here- Get Started

nodes_used:
  ["n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.githubTrigger","n8n-nodes-base.stopAndError","n8n-nodes-base.stopAndError","n8n-nodes-base.if","n8n-nodes-base.jira","n8n-nodes-base.jira","n8n-nodes-base.if","n8n-nodes-base.jira","n8n-nodes-base.if","n8n-nodes-base.jira","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: AI-Generated LinkedIn Posts with Human Approval using GPT-4, GoToHuman & Blotato
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-02T00:04:14.003Z
updated_at: 2025-08-02T00:04:14.003Z
url: https://n8n.io/workflows/6827
scraped_at: 2025-09-14 11:38:20
description:
  This workflow is designed for creators, marketers, and agencies who want to automate content publishing while keeping quality control through human review. It integrates four powerful tools — Google Sheets, OpenAI, GoToHuman, and Blotato — to deliver a seamless AI-assisted, human-approved, auto-publishing system for LinkedIn.

  ⚙️ What This Workflow Does

  📅 Pulls Today’s Topic from Google Sheets  
     You store ideas in a spreadsheet with a date column.  
     The workflow runs daily (or manually) and selects the row matching today’s date.

  🧠 Generates a Caption with OpenAI  
     The selected idea is passed to GPT-4 via an AI Agent node.  
     OpenAI returns a short, emoji-rich LinkedIn caption (1–2 sentences).  
     The result is saved back to the sheet.

  👤 Sends the Caption for Human Review via GoToHuman  
     A human reviewer sees the AI-generated caption.  
     They approve or reject it using a GoToHuman review template.  
     Only approved captions move forward.

  🚀 Publishes the Approved Caption to LinkedIn via Blotato  
     The caption is posted to a LinkedIn account via Blotato's API.  
     No additional input is required — it's fully automated after approval.

  🔧 Setup Requirements

  ✅ Google Sheets
  Create or copy the provided sample sheet.
  Connect your Google Sheets account in n8n using OAuth2.

  ✅ OpenAI
  Create an API key at platform.openai.com.
  Add it to n8n as an OpenAI credential.

  ✅ GoToHuman
  Create an account and a Review Template at gotohuman.com.
  Add your API credential in n8n and use your reviewTemplateId in the node.

  ✅ Blotato
  Create an account at blotato.com.
  Get your API key and Account ID.
  Insert them into the HTTP Request node that publishes the LinkedIn post.

  🧪 Testing the Workflow

  Use the Manual Trigger node for step-by-step debugging.  
  Review nodes like AI Agent, Ask Human for Approval, and Post to LinkedIn to verify output.  
  Once confirmed, activate the schedule for fully hands-free publishing.

  👋 Built By

  Robert Breen  
  Founder of Ynteractive — Automation, AI, and Data Strategy

  🌐 Website: https://ynteractive.com  
  📧 Email: robert@ynteractive.com  
  🔗 LinkedIn: https://www.linkedin.com/in/robert-breen-29429625/  
  📺 YouTube: YnteractiveTraining

  🏷 Tags

  linkedin openai gotohuman social automation ai content approval workflow google sheets blotato marketing automation

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workflow_json_compressed:
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name: Extract Contacts from Business Cards to Google Sheets With GPT4o
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T06:44:32.114Z
updated_at: 2025-08-02T06:44:32.114Z
url: https://n8n.io/workflows/6840
scraped_at: 2025-09-14 11:38:21
description:
  📄 Auto Extract Contacts from Business Cards to Sheet With GPT4o

  &gt; This smart workflow extracts names, phone numbers, emails, and more from uploaded name card photos using AI, then logs them neatly into your Google Sheet. No typing. No mess. Just upload and go.

  👤 Who’s it for

  Sales & Business Development Teams  
  Recruiters & Talent Acquisition Specialists  
  Event Teams collecting business cards  
  Admins who manage contact databases manually  

  ⚙️ How it works / What it does

  This workflow automates the extraction of contact details from uploaded name card (business card) images and stores them in a structured Google Sheet for easy tracking and follow-up.

  Workflow Steps:
  User uploads one or more name card images through a web form.
  The uploaded files are saved to a Google Drive folder for archiving.
  A smart AI agent (with OCR and GPT capabilities) scans each image and extracts relevant contact data into structured JSON format.
  Data is transformed, cleaned (e.g., removing + from phone numbers), and filtered.
  Valid contacts are appended to a Google Sheet for central tracking and future use.

  🛠 How to set up

  Create a Form  
     Allow file upload (JPG/PNG format).
     Label it as “Name Card Uploader” with a clear description.

  Upload to Google Drive  
     Use the Google Drive node to store uploaded images.

  Configure Smart Agent  
     Use GPT-4o or similar model with OCR capability.
     Apply a structured output parser to extract contact fields like name, phone, email, company, etc.

  Transform Data  
     Use the Code node to clean and structure contact info.
     Strip out unwanted characters from phone numbers (e.g., +).

  Filter Invalid Records  
     Remove entries with no meaningful contact data.

  Append to Google Sheets  
     Use the Google Sheets node with "Append Sheet Row".
     Map fields to columns like Name, Phone, Email, etc.

  ✅ Requirements

  n8n workflow environment  
  Google Drive integration (for file storage)  
  Google Sheets integration (for storing contacts)  
  GPT-4o or any image-capable LLM  
  Clear name card images (PNG/JPG, readable text)  
  (Optional) Slack/email integration for notifications

  🧩 How to customize the workflow

  CRM Sync**: Connect to platforms like HubSpot, Salesforce, or Zoho.  
  Validation Logic**: Ensure records contain key fields like name or email before writing.  
  Uploader Info**: Attach submitter metadata to each contact record.  
  Language Adaptation**: Adjust extracted field labels/output to target your preferred language.  
  Batch Upload**: Handle multiple cards in a single image or multiple uploads in one go.

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name: Automate weekly Hollywood film briefing via Tavily and Gemini
author_name: Manav Desai
author_username: manavdesai17
categories: []
created_at: 2025-08-02T08:23:11.194Z
updated_at: 2025-08-02T08:23:11.194Z
url: https://n8n.io/workflows/6841
scraped_at: 2025-09-14 11:38:19
description:
  This n8n template demonstrates how to build a weekly Hollywood film industry briefing using Tavily for real-time search and Google Gemini for summarization. It sends a concise, emoji‑styled email with movie releases, box office results, industry news, and must‑watch recommendations every week automatically.

  Use cases: Great for film journalists, entertainment bloggers, or movie enthusiasts who want automated weekly updates without manually checking multiple sources.

  Good to know

  Free to use: Tavily provides **1,000 API credits per month on their free plan (no credit card required), so this workflow can run at zero cost.
  Real-time data**: Tavily’s search API is optimized for up-to-date information — perfect for weekly movie releases and box office stats.
  Google Gemini is used for summarization, and you only need basic API access (no paid tier required).

  How it works

  Trigger**: Scheduled every Thursday morning (configurable).
  Search**: Four Tavily API calls gather:

    Movies releasing this week
    Last week’s box office results
    Hollywood industry news
    Must‑watch movies currently in theatres
  Summarization**: Google Gemini turns this into Gmail‑friendly HTML with emojis and bullet points.
  Email**: The formatted newsletter is sent via Gmail node.

  How to use

  Configure Tavily API and Gmail OAuth2 credentials in n8n’s credential manager.
  (Optional) Edit Tavily queries to focus on specific genres or add filters.
  Adjust the schedule trigger to any day/time you prefer.

  Requirements

  Tavily API account (free plan – 1,000 monthly requests)
  Google Gemini API key for summarization
  Gmail account (OAuth2 credentials for sending emails)

  Want insane output quality?

  You can swap Gemini for OpenAI’s ChatGPT models:

  GPT‑3.5 Turbo** – \~\$0.002/run (crazy cheap)
  GPT‑4o** – \~\$0.009/run (latte price)
  GPT‑4.5** – \~\$0.15/run (god‑mode quality)

  This upgrade gives you cleaner, richer, “did‑a‑human‑write‑this?” vibes — perfect for journalist‑grade Hollywood briefings. Just note: OpenAI API requires a \$5 minimum credit to activate usage.

  Example Output (ChatGPT version)

  Subject: Daily Hollywood Film Industry Briefing – August 3, 2025

  Good morning,
  Here's your daily Hollywood film briefing for August 3, 2025:

  🎬 Releases

  The Bad Guys 2 – Released Friday, August 1, 2025
  The Naked Gun – Released Friday, August 1, 2025

  These are the confirmed new wide theatrical Hollywood releases this week (Monday through Sunday of current week). No additional new Hollywood theatrical releases found for this week.

  📊 Box Office

  Highest‑grossing Hollywood films of 2025 (worldwide):

  Ne Zha 2 – approx. \$1.90 billion (non‑Hollywood Chinese animated film leads)
  Lilo & Stitch – approx. \$1.02 billion
  A Minecraft Movie – approx. \$955 million
  Jurassic World Rebirth – approx. \$731 million
  How to Train Your Dragon – approx. \$610 million

  Last week’s box office performance (Monday–Sunday):

  The Fantastic Four: First Steps – domestic debut \\$118 M; global \\$218 M, Marvel’s biggest opening of 2025
  Superman – added \~\$94 M worldwide last week, passing \$500 M global total
  Jurassic World Rebirth – up \\$70 M worldwide last week, despite \40 % drop week‑on‑week
  F1: The Movie – up \~\$48 M last week internationally/domestically growth visible
  Lilo & Stitch – added \~\$10 M worldwide last week, slower tail but still billion‑plus gross

  Highlights & trends:
  Fantastic Four’s strong debut reboots Marvel success, signaling resumed audience interest; Superman continues to hold strong; Jurassic World Rebirth remains durable after holiday surge; surge in box office recovery noted across key titles. Overall box office up \~12–15 % year‑on‑year.

  📰 Industry Buzz

  Christopher Nolan has signed to direct a massive \$250 million adaptation of Homer’s The Odyssey, starring Matt Damon and Tom Holland, with Imax pre‑sales at 95 % capacity across major locations.
  Marvel has relaunched the Fantastic Four franchise successfully with First Steps; positive CinemaScore and strong visuals marking a fresh start.
  DC’s Superman continues strong with over \$500 M global, solidifying DC’s summer comeback.
  Universal’s Jurassic World Rebirth continues strong overseas, especially in China, contributing to \$318 M global in opening holiday weekend.
  Warner Bros.–Discovery stock surges (\~30 %) amid box office rebound, with Disney, IMAX and Cinemark also seeing robust growth in 2025.
  Ne Zha 2 becomes highest‑grossing animated and non‑Hollywood film ever, crossing \$2 billion globally—though not Hollywood, its impact on global trends is notable.
  Mission: Impossible – The Final Reckoning quietly solidifies strong global numbers (\~\$562 M) and continues reliable franchise performance.

  🎥 Must‑Watch in Theatres (Surat, India)

  The Fantastic Four: First Steps** – Currently showing in English/Hindi/Tamil/Telugu in Surat cinemas; hyped globally, strong visuals, action‑heavy, best experienced in IMAX or premium formats if available in Surat multiplexes. Runs this week.
  F1: The Movie** – Available in Surat in multiple languages, strong reviews praising adrenaline‑fuelled direction and visuals and growing fan hype; ideal in standard or Dolby formats for immersive sound and speed feel.
  Jurassic World Rebirth** – Still playing in Surat, popular with family audiences; grand visuals and dinosaur action well‑suited to IMAX or large format screens.

  That’s all for today’s briefing. Have a great theatrical weekend ahead!

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name: Manage Cloudflare DNS Records with AI-powered Chat Assistant
author_name: KPendic
author_username: kres
categories: []
created_at: 2025-08-02T10:45:57.207Z
updated_at: 2025-08-02T10:45:57.207Z
url: https://n8n.io/workflows/6844
scraped_at: 2025-09-14 11:38:20
description:
  This n8n flow demos basic dev-ops operation task, dns records management. 

  AI agent with light and basic prompt functions like getter and setter for DNS records. 

  In this special case, we are managing remote dns server, via API calls - that are handled on CloudFlare platform side.

  Use-cases for this flow can be standalone, or you can chain it in your pipe-line to get powerful infrastructure flows for your needs.

  How it works

  we created basic agent and gave it a prompt to know about one tool: cf_tool - sub-routine (to itself flow - or it can be separate dedicated one)
  prompt have defined arguments that are needed for passing them when calling agent, for each action specifically
  tool it self have basic if switch that is - based of a action call - calling specific CloudFlare API endpoint (and pass down the args from the tool)

  Requirements

  For storing and processing of data in this flow you will need:

  CloudFlare.com API key/token - for retrieving your data (https://dash.cloudflare.com/?to=/:account/api-tokens)
  OpenAPI credentials (or any other LLM provider) saved - for agent chat
  (Optional) PostGres table for chat history saving

  Official CloudFlare api Documentation

  For full details and specifications please use API documentation from: https://developers.cloudflare.com/api/

  Linkedin post

  Let me know if you found this flow usefull on my Linkedin post &gt; here.

  tags: #cloudflare, #dns, #domain

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name: Generate Animated Human Videos from Images & Audio with Bytedance Omni Human
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T12:19:24.841Z
updated_at: 2025-08-02T12:19:24.841Z
url: https://n8n.io/workflows/6876
scraped_at: 2025-09-14 11:38:22
description:
  Generate Animated Human Videos from Images & Audio with Bytedance Omni Human

  Built with n8n + Replicate

  This workflow takes an image + audio, sends them to Bytedance’s omni-human model, waits for processing, and returns a generated video.

  ⚡ Section 1: Start & Authenticate

  ▶️ On clicking ‘execute’** → Manual trigger to start the workflow.
  🔑 Set API Key** → Stores your Replicate API key so future requests are authorized.

  Benefit: Secures your API credentials in one place for easy re-use.

  🛠️ Section 2: Send Video Generation Request

  📡 Create Prediction** → Makes a POST request to Replicate with:

    image: input image URL
    audio: input audio URL
    Model version: 7ec44f5140c7338b3496cbf99ee8ea391a4bc18ff5d1677a146dfc936a91f65b

  Benefit: Combines visual and audio inputs to start AI-powered video generation.

  🔍 Section 3: Track the Prediction

  📦 Extract Prediction ID** → Saves predictionId, status, and predictionUrl for polling.
  ⏳ Wait** → Pauses 2 seconds between status checks (to avoid spamming the API).
  🔁 Check Prediction Status** → Queries Replicate using the stored prediction URL.
  ✅ Check If Complete** → Branches:

    If status = succeeded → move forward.
    Else → loop back to Wait until completion.

  Benefit: Ensures workflow patiently waits for the video instead of timing out.

  📽️ Section 4: Process & Return Results

  📦 Process Result** → Cleans the API response, returning:

    status
    video_url (generated video)
    metrics
    created_at & completed_at
    model: bytedance/omni-human

  Benefit: Gives you a neat, structured output with the generated video link ready to use.

  📊 Workflow Overview

  | Section             | Purpose                     | Key Nodes                                     | Benefit                          |
  | ------------------- | --------------------------- | --------------------------------------------- | -------------------------------- |
  | ⚡ Start & Auth      | Initialize & secure API key | Manual Trigger, Set API Key                   | Keeps credentials safe           |
  | 🛠️ Send Request    | Start video generation      | Create Prediction                             | Submits image+audio to Replicate |
  | 🔍 Track Prediction | Poll status until done      | Extract Prediction ID, Wait, Check Status, If | Reliable async handling          |
  | 📽️ Process Result  | Format output               | Process Result                                | Easy access to final video link  |

  ✅ Final Benefits

  🎬 Turns static image + audio into full AI-generated video.
  🔑 API key stored securely in workflow.
  🔄 Handles async generation with auto-polling.
  📤 Outputs clean JSON with direct video link.
  🧩 Modular — you can connect results to Slack, Gmail, or Google Drive for auto-sharing.

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name: Convert Multiple Files to Base64 with JavaScript Code
author_name: Viktor Klepikovskyi
author_username: vklepikovskyi
categories: []
created_at: 2025-08-02T12:39:55.614Z
updated_at: 2025-08-02T12:39:55.614Z
url: https://n8n.io/workflows/6885
scraped_at: 2025-09-14 11:38:22
description:
  Base64 Encode Multiple Binary Files with a Code Node
  This template demonstrates how to handle multiple binary files in n8n by using a Code node to convert them into a Base64 encoded string. It's particularly useful when an API requires file uploads in this format and the standard 'Extract From File' node is not sufficient for batch processing. The workflow starts by downloading a ZIP file, unzipping it to get multiple binary files, and then uses a Code node with custom JavaScript to encode each file individually.
  Instructions
  Download and import this template into your n8n instance.
  Run the workflow once to see how it downloads, unzips, and then encodes multiple files.
  Modify the 'HTTP Request' node to download your own binary file or a ZIP file containing multiple files.
  Update the 'Code' node if you need to adjust the output format or file paths.
  Use the output of the 'Code' node in a subsequent node, such as another 'HTTP Request' to send the Base64-encoded files to your desired API.

  A link to the full blog post is available here.

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name: Generate High-Quality Audio with Voxtral Small 24B 2507
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T14:22:43.454Z
updated_at: 2025-08-02T14:22:43.454Z
url: https://n8n.io/workflows/6890
scraped_at: 2025-09-14 11:38:22
description:
  Generate High-Quality Audio with Voxtral Small 24B 2507

  This workflow integrates the notdaniel/voxtral-small-24b-2507 model from Replicate to generate audio content from provided inputs. It handles API authentication, creates predictions, polls until completion, and outputs the final generated audio file.

  ⚡ Section 1: Trigger & Authentication

  🔘 On clicking 'execute'** → Manually starts the workflow.
  🔑 Set API Key** → Stores your Replicate API key to authenticate requests.

  Benefit: Securely connects your workflow to Replicate’s API and ensures only authorized requests are made.

  🎛️ Section 2: Create Prediction

  🌐 Create Prediction** → Sends a request to Replicate’s API with parameters like:

    audio: Input audio file (e.g., a reference sample).
    max\_new\_tokens: Maximum number of tokens to generate (controls audio length/complexity).

  Benefit: Starts the audio generation process with configurable input and settings.

  ⏳ Section 3: Polling & Status Tracking

  🆔 Extract Prediction ID** → Captures the unique prediction ID and endpoint for polling.
  ⏱️ Wait** → Pauses for 2 seconds before re-checking.
  📡 Check Prediction Status** → Polls Replicate’s API to see if the audio generation is done.
  ✅ Check If Complete** →

    If finished: moves forward to process results.
    If not: loops back to wait and check again.

  Benefit: Efficiently manages asynchronous audio generation, ensuring the workflow only proceeds when results are ready.

  🎧 Section 4: Process Result

  📝 Process Result** → Extracts and structures final output data:

    status (success or failure)
    output (raw response)
    metrics (generation statistics)
    timestamps (created and completed times)
    audio\_url (final generated audio link)

  Benefit: Provides a clean, structured output that can be used in follow-up automations (e.g., sending audio to users, storing in a database, or sharing via email).

  📊 Workflow Overview

  | Section                     | Purpose                         | Key Nodes                                                               | Benefit                          |
  | --------------------------- | ------------------------------- | ----------------------------------------------------------------------- | -------------------------------- |
  | ⚡ Trigger & Authentication  | Start workflow & authenticate   | Manual Trigger, Set API Key                                             | Secure execution                 |
  | 🎛️ Create Prediction       | Submit audio generation request | Create Prediction                                                       | Start model processing           |
  | ⏳ Polling & Status Tracking | Monitor prediction progress     | Extract Prediction ID, Wait, Check Prediction Status, Check If Complete | Ensures reliable completion      |
  | 🎧 Process Result           | Format and deliver output       | Process Result                                                          | Clean audio result ready for use |

  ✅ Final Benefits

  🔒 Secure authentication with Replicate
  🎛️ Flexible audio generation using voxtral-small-24b-2507
  ⏳ Reliable polling until results are ready
  🎧 Clean and structured audio output

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name: Automate Financial Operations with O3 CFO & GPT-4.1-mini Finance Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:00:37.200Z
updated_at: 2025-08-02T18:00:37.200Z
url: https://n8n.io/workflows/6906
scraped_at: 2025-09-14 11:38:20
description:
  Automate Financial Operations with O3 CFO & GPT-4.1-mini Finance Team

  This workflow builds a virtual finance department inside n8n. At the center is a CFO Agent (O3 model) who acts like a strategic leader. When a financial request comes in, the CFO interprets it, decides the strategy, and delegates to the specialist agents (each powered by GPT-4.1-mini for cost efficiency).

  🟢 Section 1 – Entry & Leadership

  Nodes:

  💬 When chat message received → Entry point for user financial requests.
  💼 CFO Agent (O3) → Acts as the Chief Financial Officer. Interprets the request, decides the approach, and delegates tasks.
  💡 Think Tool → Helps the CFO brainstorm and refine financial strategies.
  🧠 OpenAI Chat Model CFO (O3) → High-level reasoning engine for strategic leadership.

  ✅ Beginner view: Think of this as your finance CEO’s desk — requests land here, the CFO figures out what needs to be done, and the right specialists are assigned.

  📊 Section 2 – Specialist Finance Agents

  Each specialist is powered by GPT-4.1-mini (fast + cost-effective).

  📈 Financial Planning Analyst → Builds budgets, forecasts, and financial models.
  📚 Accounting Specialist → Handles bookkeeping, tax prep, and compliance.
  🏦 Treasury & Cash Management Specialist → Manages liquidity, banking, and cash flow.
  📊 Financial Analyst → Runs KPI tracking, performance metrics, variance analysis.
  💼 Investment & Risk Analyst → Performs investment evaluations, capital allocation, and risk management.
  🔍 Internal Audit & Controls Specialist → Checks compliance, internal controls, and audits.

  ✅ Beginner view: This section is your finance department — every role you’d find in a real company, automated by AI.

  📋 Section 3 – Flow of Execution

  User sends a request (e.g., “Create a financial forecast for Q1 2026”).
  CFO Agent (O3) interprets it → “We need planning, analysis, and treasury.”
  Delegates tasks to the relevant specialists.
  Specialists process in parallel, generating plans, numbers, and insights.
  CFO Agent compiles and returns a comprehensive financial report.

  ✅ Beginner view: The CFO is the conductor, and the specialists are the musicians. Together, they produce the financial “symphony.”

  📊 Summary Table

  | Section                | Key Roles                                               | Model             | Purpose             | Beginner Benefit                       |
  | ---------------------- | ------------------------------------------------------- | ----------------- | ------------------- | -------------------------------------- |
  | 🟢 Entry & Leadership  | CFO Agent, Think Tool                                   | O3                | Strategic direction | Acts like a real CFO                   |
  | 📊 Finance Specialists | FP Analyst, Accounting, Treasury, FA, Investment, Audit | GPT-4.1-mini      | Specialized tasks   | Each agent = finance department role   |
  | 📋 Execution Flow      | All connected                                           | O3 + GPT-4.1-mini | Collaboration       | Output = complete financial management |

  🌟 Why This Workflow Rocks

  Full finance department in n8n**
  Strategic + execution separation** → O3 for CFO, GPT-4.1-mini for team
  Cost-optimized** → Heavy lifting done by mini models
  Scalable** → Easily add more finance roles (tax, payroll, compliance, etc.)
  Practical outputs** → Reports, budgets, risk analyses, audit notes

  👉 Example Use Case:
  “Generate a Q1 financial forecast with cash flow analysis and risk report.”

  CFO reviews request.
  Financial Planning Analyst → Budget + Forecast.
  Treasury Specialist → Cash flow modeling.
  Investment Analyst → Risk review.
  Audit Specialist → Compliance check.
  CFO delivers a packaged financial report back to you.

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name: Revenue Growth Strategy with CRO-led Multi-Agent Team using O3 & GPT-4.1-mini
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:02.218Z
updated_at: 2025-08-02T18:01:02.218Z
url: https://n8n.io/workflows/6907
scraped_at: 2025-09-14 11:38:21
description:
  Revenue Growth Strategy with CRO-led Multi-Agent Team using O3 & GPT-4.1-mini

  🔥 Powered by OpenAI O3 & GPT-4.1-mini Multi-Agent System
  \#RevOps #n8nWorkflows #AIRevenue #OpenAI #GrowthHacking

  ⚡ Section 1: Start & Orchestrator

  💬 Chat Trigger* → Listens for revenue-related requests (e.g., *“Optimize our sales funnel”).
  🤖 CRO Agent (O3)* → Acts as the *Chief Revenue Officer**.

    Thinks strategically with the Think Node.
    Decides which specialist agents to call.
  🧠 OpenAI O3 Model** → Provides advanced reasoning for CRO decisions.

  Benefit: Central orchestration ensures every request gets a strategic, executive-level response before delegation.

  🛠️ Section 2: Specialist Agents

  Each specialist agent uses GPT-4.1-mini for fast, cost-effective execution.
  They receive the CRO’s instructions and return insights.

  📈 Sales Pipeline Analyst

     Funnel optimization, conversion tracking, bottleneck fixes.
     Outputs: Pipeline health, drop-off points, recommendations.

  🎯 Revenue Attribution Specialist

     Multi-touch attribution, ROI analysis, campaign efficiency.
     Outputs: Attribution models, marketing ROI.

  📊 Revenue Forecasting Analyst

     Predictive modeling, scenario planning, growth projections.
     Outputs: Forecast reports, “what-if” scenarios.

  ⚙️ Revenue Operations Manager

     CRM optimization, territory planning, sales automation.
     Outputs: Process improvements, efficiency boosts.

  💰 Pricing & Packaging Strategist

     Competitive pricing analysis, packaging strategy, revenue optimization.
     Outputs: Price models, package recommendations.

  🧠 Revenue Intelligence Analyst

     BI dashboards, performance tracking, KPI insights.
     Outputs: Reports with actionable intelligence.

  Benefit: Breaks complex revenue problems into specialized tasks handled by domain experts.

  🔄 Section 3: Feedback & Integration

  Each agent → sends results back to CRO Agent.
  CRO Agent → compiles a comprehensive revenue strategy.
  Can integrate with CRM, BI dashboards, or Slack/Email for delivery.

  Benefit: Clear, actionable insights delivered in one place — like having a virtual RevOps team on demand.

  📊 Workflow Overview

  | Section                 | Key Nodes                           | Purpose                                           | Benefit                              |
  | ----------------------- | ----------------------------------- | ------------------------------------------------- | ------------------------------------ |
  | ⚡ Start & Orchestration | Chat Trigger, CRO Agent, O3 Model   | Capture request & assign to CRO                   | Centralized leadership               |
  | 🛠️ Specialists         | 6 Agent Nodes + GPT-4.1-mini models | Analyze pipeline, pricing, ops, attribution, etc. | Specialized, cost-efficient insights |
  | 🔄 Feedback Loop        | CRO Agent aggregation               | Compiles strategy from multiple agents            | Unified, data-driven revenue plan    |

  💡 Use Cases

  Pipeline Optimization** → Identify bottlenecks, improve conversions.
  Attribution Modeling** → Know exactly where revenue comes from.
  Revenue Forecasting** → Plan growth scenarios and projections.
  Ops Excellence** → Automate CRM, streamline sales ops.
  Pricing Strategy** → Compete smarter with optimized pricing models.
  Revenue Intelligence** → Ongoing tracking and performance monitoring.

  💸 Cost Optimization

  O3 only for CRO decisions** → Strategic layer.
  GPT-4.1-mini for specialists** → Low-cost execution (\~90% cheaper).
  Parallel processing** → All agents can run simultaneously.

  ✅ Final Result: A virtual AI-powered RevOps team that turns any revenue-related question into a comprehensive growth strategy — instantly.

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name: Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:26.784Z
updated_at: 2025-08-02T18:01:26.784Z
url: https://n8n.io/workflows/6908
scraped_at: 2025-09-14 11:38:22
description:
  Comprehensive SEO Strategy with O3 Director & GPT-4 Specialist Team

  Trigger

     When chat message received → User submits an SEO request (e.g., “Help me rank for project management software”).
     The message goes straight to the SEO Director Agent.

  SEO Director Agent (O3)

     Acts like the head of SEO strategy.
     Uses the Think node to plan and decide which specialists to call.
     Delegates tasks to relevant agents.

  Specialist Agents (GPT-4.1-mini)

     Each agent has its own OpenAI model connection for lightweight cost-efficient execution.
     Tasks include:

       Keyword Research Specialist → Keyword discovery, clustering, competitor analysis.
       SEO Content Writer → Generates optimized blog posts, landing pages, etc.
       Technical SEO Specialist → Site audit, schema markup, crawling fixes.
       Link Building Strategist → Backlink strategies, outreach campaign ideas.
       Local SEO Specialist → Local citations, GMB optimization, geo-content.
       Analytics Specialist → Reports, performance insights, ranking metrics.

  Feedback Loop

     Each agent sends results back to the SEO Director.
     Director compiles insights into a comprehensive SEO campaign plan.

  ✅ Why This Setup Works Well

  O3 Model for Director** → Handles reasoning-heavy orchestration (strategy, delegation).
  GPT-4.1-mini for Specialists** → Cheap, fast, task-specific execution.
  Parallel Execution** → All specialists can run at the same time.
  Scalable & Modular** → You can add/remove agents depending on campaign needs.
  Sticky Notes** → Already document the workflow (great for onboarding & sharing).

nodes_used:
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name: Multi-Agent Cold Email Campaign Generator with O3 Director & GPT-4.1 Specialists
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:01:52.773Z
updated_at: 2025-08-02T18:01:52.773Z
url: https://n8n.io/workflows/6909
scraped_at: 2025-09-14 11:38:21
description:
  Multi-Agent Cold Email Campaign Generator with O3 Director & GPT-4.1 Specialists

  🌍 Overview

  This workflow simulates a virtual sales & marketing team where each AI agent has a role:

  A Director Agent (O3) who manages strategy.
  Multiple Specialist Agents (GPT-4.1-mini) for research, writing, personalization, deliverability, sequencing, and analytics.
  Everything is triggered automatically when a new chat message request comes in.

  🟢 Section 1: Entry & Director

  🔗 Nodes:
  1️⃣ When chat message received (Trigger)
  💬 Starts the workflow when a new request arrives (e.g., “Create a cold email campaign for SaaS CTOs”).

  2️⃣ Outreach Director Agent (O3 model)
  🎯 The “manager” agent. Decides what kind of campaign is needed and assigns tasks.

  3️⃣ Think (Planning Node)
  🧠 Helps the Director structure thoughts before delegating.

  💡 Why useful?

  Director uses O3 (strong reasoning model) only where strategy is needed → reduces cost.
  Provides a single point of control to coordinate all other agents.

  🔵 Section 2: Specialist Agents

  Each is powered by GPT-4.1-mini (cheaper + faster).

  🔍 Prospect Research Specialist → researches target companies, roles, pain points.
  ✍️ Cold Email Copywriter → drafts subject lines, hooks, and persuasive body copy.
  🎯 Personalization Specialist → inserts custom variables for each recipient.
  📅 Email Sequence Strategist → designs follow-ups, timing, nurture flows.
  📬 Email Deliverability Expert → ensures emails land in inbox, not spam.
  📊 Outreach Analytics Specialist → tracks performance, runs A/B tests, optimizes campaigns.

  💡 Why useful?

  Each agent is a specialist → just like a real marketing team.
  Parallel execution** in n8n means faster results.
  Modular → you can remove or add more specialists.

  🟣 Section 3: Execution Flow

  Request comes in via chat trigger
  Director (O3) interprets and delegates → calls specialists as tools
  Specialists generate their pieces (research → copy → personalization → sequence → deliverability → analytics)
  Director integrates results into a cohesive cold email campaign

  🟡 Section 4: Documentation & Notes

  There are two Sticky Notes inside the workflow:

  Header Note** → Support info + tutorials (YouTube & LinkedIn by Yaron Been)
  Main Note** → Full documentation (overview, use cases, cost optimization, tags)

  📊 Final Overview

  | Section        | What Happens             | Why It’s Useful             |
  | -------------- | ------------------------ | --------------------------- |
  | 🟢 Director    | Trigger + O3 strategy    | Ensures smart coordination  |
  | 🔵 Specialists | GPT-4.1-mini agents      | Faster, cheaper execution   |
  | 🟣 Flow        | Delegation + Integration | Automated campaign building |
  | 🟡 Docs        | Sticky Notes             | In-workflow guide for users |

  🚀 Benefits

  ✅ AI-powered cold email team without hiring humans
  ✅ Cost-optimized (O3 only for strategy, GPT-4.1-mini for tasks → \~90% cheaper)
  ✅ End-to-end coverage (research → writing → personalization → sequencing → analytics)
  ✅ Scalable: can run multiple campaigns in parallel
  ✅ Customizable: swap models, add tools, or expand team

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name: Create Multi-Channel Content with O3 Director & GPT-4 Specialist Agents
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:02:16.967Z
updated_at: 2025-08-02T18:02:16.967Z
url: https://n8n.io/workflows/6910
scraped_at: 2025-09-14 11:38:22
description:
  Create Multi-Channel Content with O3 Director & GPT-4 Specialist Agents

  This n8n workflow creates a complete AI-powered content department. It starts when a chat request is received, then a Content Director Agent (powered by OpenAI O3) analyzes the request and delegates tasks to specialized agents (blogs, social, video, email, website, strategy). Each agent is powered by GPT-4.1-mini, keeping costs low and quality high.

  ✅ 📩 Section 1: Trigger & Director Setup

  ⚙️ Nodes

  1️⃣ When Chat Message Received

  What it does:** Starts the workflow whenever a user sends a content request.
  Why it’s useful:** Allows real-time or on-demand content creation from chat inputs.

  2️⃣ Content Director Agent (O3)

  What it does:** Analyzes user request, defines the best content mix, and delegates tasks to specialist agents.
  Why it’s useful:** Keeps your brand voice consistent and ensures all channels align to a unified content strategy.

  💡 Beginner Benefit

  ✅ Single entry point → just type your content idea once
  ✅ AI Director coordinates everything for you
  ✅ No need to manage multiple tools

  ✅ 👥 Section 2: Specialist Content Agents

  Each request gets routed to one (or several) of these agents, depending on the strategy.

  3️⃣ Blog Content Writer

  Long-form articles, editorials, and thought leadership pieces.

  4️⃣ Social Media Content Creator

  Social posts, captions, hashtags, and community content.

  5️⃣ Video Script Writer

  YouTube scripts, explainer videos, and video marketing content.

  6️⃣ Email Newsletter Writer

  Campaigns, nurture sequences, and newsletter copy.

  7️⃣ Website Copy Specialist

  Landing pages, product descriptions, and conversion-focused web copy.

  8️⃣ Content Strategist & Planner
  Editorial calendars, campaign planning, and audience strategy.

  💡 Beginner Benefit

  ✅ Each agent is an expert in its field
  ✅ Powered by GPT-4.1-mini → faster and cheaper
  ✅ Parallel execution → all content types can be generated at once

  ✅ 🧠 Section 3: Language Models & Execution Flow

  O3 Model → Content Director**

    Handles analysis, strategy, and delegation.

  GPT-4.1-mini → All Specialists**

    Powers blog, social, video, email, website, and strategy agents.

  Think Node**

    Helps the Content Director organize reasoning before delegating tasks.

  💡 Beginner Benefit

  ✅ AI Director (O3) = smart leadership
  ✅ Specialists (GPT-4.1-mini) = cost-efficient execution
  ✅ Built-in reasoning = better, more aligned campaigns

  📊 Workflow Overview

  | Section                     | What Happens                                                    | Key Benefit                |
  | --------------------------- | --------------------------------------------------------------- | -------------------------- |
  | 📩 Trigger & Director Setup | Workflow starts from chat → Content Director interprets request | Centralized control        |
  | 👥 Specialist Agents        | Each AI agent produces tailored content                         | Multi-channel coverage     |
  | 🧠 Models & Flow            | O3 for Director, GPT-4.1-mini for specialists                   | Cost-efficient + strategic |

  📌 How You Benefit Overall

  ✅ One input → full content campaign
  ✅ Consistent brand voice across all platforms
  ✅ Cost-effective (O3 only for strategy, GPT-4.1-mini for bulk work)
  ✅ Ready-to-publish content in minutes

  ✨ You’ve basically built an AI marketing department inside n8n — no extra staff required! 🚀

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name: Creative Design Agency Simulation with OpenAI O3 and GPT-4.1-mini Multi-Agent
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:03:54.373Z
updated_at: 2025-08-02T18:03:54.373Z
url: https://n8n.io/workflows/6914
scraped_at: 2025-09-14 11:38:21
description:
  Creative Design Agency Simulation with OpenAI O3 and GPT-4.1-mini Multi-Agent Team

  This n8n workflow simulates a full-service creative agency powered by AI. At the center is a Creative Director Agent (O3 model) who takes client requests, plans the creative direction, and delegates work to a specialized design team. Each specialist runs on GPT-4.1-mini, keeping execution fast and cost-efficient.

  🟢 Section 1 – Entry & Strategic Leadership

  Nodes:

  💬 When chat message received → Entry point, listens for design briefs.
  🎨 Creative Director Agent (O3) → The “agency head” who interprets requirements and decides which specialists to involve.
  💡 Think Tool → Helps the Director brainstorm, evaluate alternatives, and refine direction.
  🧠 OpenAI Chat Model Director (O3) → Strategic reasoning engine for the Director.

  ✅ Benefit for beginners: Think of this as the project manager’s desk — you submit a design request, and the Director figures out how to make it happen.

  ✍️ Section 2 – Core Creative Specialists

  Nodes:

  🖼️ Graphic Designer → Logos, visual identity, print, packaging.
  📱 UI/UX Designer → Wireframes, prototypes, interaction design.
  🎯 Brand Strategist → Market positioning, brand guidelines, competitive research.
  📝 Creative Copywriter → Taglines, messaging, campaign copy.

  Each agent is powered by GPT-4.1-mini.

  ✅ Benefit for beginners: This section is your creative studio team — they craft visuals, design user experiences, and write compelling words.

  🚀 Section 3 – Extended Design & Motion Team

  Nodes:

  🎬 Motion Graphics Designer → Animations, promo videos, explainer graphics.
  🌐 Web Designer → Websites, responsive layouts, accessibility improvements.
  🖌️ OpenAI Chat Model Agents (GPT-4.1-mini) → Back each specialist with creative power.

  ✅ Benefit for beginners: This section brings motion and web into the mix, ensuring your creative package isn’t static — it moves, animates, and lives online.

  📊 Summary Table

  | Section             | Key Roles                         | Model        | Purpose               | Beginner Benefit                      |
  | ------------------- | --------------------------------- | ------------ | --------------------- | ------------------------------------- |
  | 🟢 Entry & Strategy | Chat Trigger, Director, Think     | O3           | Leadership & planning | Turns briefs into action plans        |
  | ✍️ Core Creatives   | Graphic, UI/UX, Brand, Copywriter | GPT-4.1-mini | Design & content      | Produces visuals, UX, and words       |
  | 🚀 Extended Team    | Motion Graphics, Web              | GPT-4.1-mini | Motion & web design   | Animates, builds, and scales projects |

  🌟 Why This Workflow Rocks

  Complete agency in a box** → Strategy + Design + Motion + Web + Copy
  Smart leadership** → Director (O3) only used for high-level thinking
  Cost-effective execution** → GPT-4.1-mini runs most tasks
  Parallel creativity** → Specialists work simultaneously
  Scalable** → Adaptable to any design or branding request

  👉 Example: Send a message like “Design a brand identity for a sustainable clothing startup”.
  Within minutes, your AI agency produces:

  A logo & color scheme 🎨
  A UX prototype 📱
  A brand positioning doc 🎯
  Animated ad ideas 🎬
  Website mockups 🌐
  A tagline & ad copy ✍️

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name: Amplify Social Media Presence with O3 and GPT-4 Multi-Agent Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:04:18.274Z
updated_at: 2025-08-02T18:04:18.274Z
url: https://n8n.io/workflows/6915
scraped_at: 2025-09-14 11:38:21
description:
  Amplify Social Media Presence with O3 and GPT-4 Multi-Agent Team

  🌍 Overview

  This n8n workflow acts like a virtual social media department. A Social Media Director Agent coordinates multiple specialized AI agents (Instagram, Twitter/X, Facebook, TikTok, YouTube, and Analytics). Each agent creates or analyzes content for its platform, powered by OpenAI models.

  The result? A fully automated, cross-platform social media strategy—from content creation to performance tracking.

  🟢 Section 1: Trigger & Director Setup

  🔗 Nodes:

  When chat message received (Trigger)** → Starts the workflow whenever you send a request (e.g., “Plan a TikTok campaign for my product launch”).
  Social Media Director Agent* (connected to *OpenAI O3 model**) → Acts as the strategist.
  Think Tool** → Helps the Director “reason” before delegating.

  💡 Beginner takeaway:
  This section makes your workflow interactive. You send a request → the Director decides the best approach → then it assigns tasks.

  📈 Advantage:
  Instead of manually planning content per platform, you only send one command, and the AI Director handles the strategy.

  🟦 Section 2: Specialized Social Media Agents

  🔗 Nodes (each paired with GPT-4.1-mini):

  📸 Instagram Content Creator → Visual storytelling, Reels, Hashtags
  🐦 Twitter/X Strategist → Viral tweets, trends, engagement
  👥 Facebook Community Manager → Audience growth, ads, group engagement
  🎵 TikTok Video Creator → Short-form video, viral trends
  🎬 YouTube Content Planner → Long-form strategy, SEO, thumbnails
  📊 Analytics Specialist → Performance insights, cross-platform reporting

  💡 Beginner takeaway:
  Each platform has its own AI expert. They receive the Director’s strategy and produce tailored content for their platform.

  📈 Advantage:
  Instead of one-size-fits-all posts, you get optimized content per platform—increasing reach and engagement.

  🟣 Section 3: Models & Connections

  🔗 Nodes:

  OpenAI Chat Models** (O3 + multiple GPT-4.1-mini models)
  Each model is connected to its respective agent.

  💡 Beginner takeaway:
  Think of these as the “brains” behind each specialist. The Director uses O3 for advanced reasoning, while the specialists use GPT-4.1-mini (cheaper, faster) for content generation.

  📈 Advantage:
  This keeps costs low while maintaining quality output.

  📊 Final Overview Table

  | Section               | Nodes                                                    | Purpose                                | Benefit                        |
  | --------------------- | -------------------------------------------------------- | -------------------------------------- | ------------------------------ |
  | 🟢 Trigger & Director | Chat Trigger, Director, Think Tool                       | Capture requests & plan strategy       | One command → full social plan |
  | 🟦 Specialists        | Instagram, Twitter, Facebook, TikTok, YouTube, Analytics | Platform-specific content              | Optimized posts per platform   |
  | 🟣 Models             | O3 + GPT-4.1-mini                                        | Provide reasoning & content generation | High-quality, cost-efficient   |

  🚀 Why This Workflow is Powerful

  Multi-platform coverage**: All major platforms handled in one flow
  Human-like strategy**: Director agent makes real marketing decisions
  Scalable & fast**: Generate a full campaign in minutes
  Cost-effective**: O3 only for strategy, GPT-4.1-mini for bulk content
  Beginner-friendly**: Just type your request → get full campaign output

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name: Create Viral LinkedIn Content with O3 & GPT-4.1-mini Multi-Agent Team
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-02T18:04:42.673Z
updated_at: 2025-08-02T18:04:42.673Z
url: https://n8n.io/workflows/6916
scraped_at: 2025-09-14 11:38:21
description:
  Create Viral LinkedIn Content with O3 & GPT-4.1-mini Multi-Agent Team

  This n8n workflow is a multi-agent LinkedIn content factory.
  At its heart is the Content Director Agent (O3 model), who acts as the project manager. It listens for LinkedIn chat messages, analyzes them, and coordinates a team of AI specialists (all powered by GPT-4.1-mini) to produce viral, engaging, and optimized LinkedIn content.

  🟢 Section 1 – Workflow Entry & Strategy Layer

  Nodes:

  🔔 When chat message received → Captures LinkedIn requests (your idea, draft, or prompt).
  🧠 Content Director Agent (O3) → Acts as the leader, deciding how the content should be structured and which specialists to call.
  💡 Think Node → Helps the Director brainstorm and evaluate possible approaches before delegating.
  🤖 OpenAI Chat Model Director (O3) → The Director’s brain, providing strategic-level thinking.

  ✅ Beginner-friendly benefit: This section is like the “command center.” Any LinkedIn content request starts here and gets transformed into a clear, strategic plan before moving to specialists.

  ✍️ Section 2 – Content Creation Specialists

  Nodes:

  ✍️ LinkedIn Copywriter → Creates viral hooks, compelling posts, and platform-friendly messaging.
  🎓 Domain Expert → Ensures technical accuracy and industry authority in the post.
  📝 Proofreader & Editor → Polishes content for grammar, tone, and style.

  Each agent connects to its own GPT-4.1-mini model for cost-efficient, specialized output.

  ✅ Beginner-friendly benefit: This section is like your content writing team—from drafting, to adding expertise, to polishing for professional LinkedIn standards.

  🚀 Section 3 – Engagement & Optimization Specialists

  Nodes:

  🚀 Engagement Strategist → Crafts hashtags, posting times, and audience growth strategies.
  🎨 Visual Content Strategist → Designs carousels, infographics, and visual ideas.
  📊 Content Performance Analyst → Tracks analytics, measures performance, and suggests improvements.

  Each of these also relies on GPT-4.1-mini, keeping cost low while delivering specialized insights.

  ✅ Beginner-friendly benefit: This section is like your growth & marketing team—they ensure your content doesn’t just look good but also performs well and reaches the right audience.

  📊 Summary Table

  | Section                      | Key Nodes                              | Role                 | Beginner Benefit                        |
  | ---------------------------- | -------------------------------------- | -------------------- | --------------------------------------- |
  | 🟢 Entry & Strategy          | Trigger, Director, Think, O3 Model     | Strategy & planning  | Turns your idea into a clear strategy   |
  | ✍️ Content Creation          | Copywriter, Domain Expert, Proofreader | Writing & refinement | Produces expert-level, polished content |
  | 🚀 Engagement & Optimization | Engagement, Visuals, Analytics         | Growth & performance | Maximizes reach, visuals, and results   |

  🌟 Why This Workflow Rocks

  All-in-one content team** → Strategy + Writing + Optimization
  Low cost** → O3 only for strategy, GPT-4.1-mini for specialists
  Parallel agents** → Work simultaneously for faster results
  Scalable** → Reusable for any LinkedIn content need

  👉 Even a beginner can use this workflow: just send a LinkedIn content idea (e.g., “Write a post on AI in finance”), and your AI team handles the rest—writing, polishing, visuals, and engagement tactics.

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name: Automate Vendor Contract Renewals & Reminders with GPT-4.1 mini, Slack & Gmail
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-03T13:24:37.325Z
updated_at: 2025-08-03T13:24:37.325Z
url: https://n8n.io/workflows/6935
scraped_at: 2025-09-14 11:38:22
description:
  📝 Smart Vendor Contract Renewal & Reminder Workflow With GPT 4.1 mini
  Watch the demo video below:

  Never miss a vendor renewal again!
  This smart workflow automatically tracks expiring contracts, reminds your finance team via Slack, and helps initiate renewal with vendors through email — all with built-in approval and logging. Perfect for managing both auto-renew and manual contracts.
  📌 Who’s it for
  This workflow is designed for Finance and Procurement teams responsible for managing vendor/service contracts. It ensures timely notifications for expiring contracts and automates the initiation of renewal conversations with vendors.

  ⚙️ How it works / What it does

  ⏰ Daily Trigger
     Runs every day at 6:00 AM using a scheduler.

  📄 Retrieve Contract List
     Reads vendor contract data from a Google Sheet (or any data source).
     Filters for contracts nearing their end date, using a Notice Period (days) field.

  🔀 Branch Based on Renewal Type
     Auto-Renew Contracts:
       Compose a Slack message summarizing the auto-renewal.
       Notify the finance contact via Slack.

     Manual Renewal Contracts:
       Use an OpenAI-powered agent to generate a meaningful Slack message.
       Send message and wait for approval from the finance contact (e.g., within 8 hours).
       Upon approval, generate a formal HTML email to the vendor.
       Send the email to initiate the contract extension process.

  📊 (Optional) Logging
     Can be extended to log all actions (Slack messages, emails, approvals) to Google Sheets or other databases.

  🛠️ How to set up

  Prepare your Google Sheet
     Include the following fields:
       Vendor Name, Vendor Email, Service Type, Contract Start Date, Contract End Date, Notice Period (days), Renewal Type, Finance Contact, Contact Email, Slack ID, Contract Value, Notes.
       Sample: https://docs.google.com/spreadsheets/d/1zdDgKyL0sY54By57Yz4dNokQC_oIbVxcCKeWJ6PADBM/edit?usp=sharing

  Configure Integrations
     🟢 Google Sheets API: To read contract data.
     🔵 Slack API: To notify and wait for approval.
     🧠 OpenAI API (GPT-4): To generate personalized reminders.
     ✉️ Email (SMTP/Gmail): To send emails to vendors.

  Set the Daily Scheduler
     Use a Cron node to trigger the workflow at 6:00 AM daily.

  ✅ Requirements

  | Component                        | Required |
  |----------------------------------|----------|
  | Google Sheets API                | ✅       |
  | Slack API                        | ✅       |
  | OpenAI API (GPT-4)               | ✅       |
  | Email (SMTP/Gmail)               | ✅       |
  | n8n (Self-hosted or Cloud)       | ✅       |
  | Contract Sheet with proper schema| ✅       |

  🧩 How to customize the workflow
  Adjust Reminder Period**: Modify the logic in the Find Expiring Vendors node (based on Contract End Date and Notice Period).
  Change Message Tone or Format**: Customize the OpenAI agent's prompt or switch from plain text to branded HTML email.
  Add Logging or Tracking: Add a node to append logs to a **Google Sheet, Notion, or database.
  Replace Data Source: Swap out Google Sheets for **Airtable, PostgreSQL, or other CRM/database systems.
  Adjust Wait/Approval Duration**: Modify the sendAndWait Slack node timeout (e.g., from 8 hours to 2 hours).

  📦 Optional Extensions
  🧾 Add PDF contract preview via Drive link
  🧠 Use GPT to summarize renewal terms
  🛠 Auto-create Jira task for contract review

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name: Automatically Save & Organize Outlook Email Attachments in OneDrive Folders
author_name: Michael Gullo
author_username: mgullo
categories: []
created_at: 2025-08-03T16:05:57.477Z
updated_at: 2025-08-03T16:05:57.477Z
url: https://n8n.io/workflows/6938
scraped_at: 2025-09-14 11:38:20
description:
  Outlook to OneDrive
  This workflow automates the process of saving binary attachments from Outlook emails into newly created folders in OneDrive. It's ideal for users who regularly receive files and need them organized into separate folders without manual intervention. Each folder is automatically named based on the email subject and the current timestamp, allowing all attachments from that email to be stored inside the corresponding folder. This is particularly useful for streamlining document workflows, improving file traceability, and reducing the time spent on repetitive tasks like organizing client submissions, invoices, or internal reports.

  The configuration and setup of the workflow can be customized to meet the business or personal needs of the user. Its purpose is to automatically process binary attachments from Outlook emails and upload them to dynamically created folders in OneDrive.

  Overview
  Microsoft Outlook Trigger – Monitors your inbox for new emails.
  Filter – Ensures only emails with binary attachments proceed.
  Get Outlook Message – Retrieves the full email and downloads attachments.
  Create Folder – Makes a new folder in OneDrive based on the email subject and time.
  Split Out – Extracts each binary attachment.
  Merge– Combines folder and file data before upload.
  Upload File OneDrive – Uploads each binary file into the new folder.

  Need Help? Have Questions?
  For consulting and support, or if you have questions, please feel free to connect with me on LinkedIn or via email. 

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name: Enhance Your Workflow with 2Ndmoises_Generator AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-03T17:02:44.280Z
updated_at: 2025-08-03T17:02:44.280Z
url: https://n8n.io/workflows/6943
scraped_at: 2025-09-14 11:38:22
description:
  Enhance Your Workflow with 2Ndmoises_Generator AI

  This n8n workflow integrates with Replicate’s moicarmonas/2ndmoises_generator model to generate custom outputs based on your prompt. It handles authentication, triggers the prediction, monitors progress, and processes the final result automatically.

  📌 Section 1: Trigger & Authentication

  ⚡ On Clicking ‘Execute’ (Manual Trigger)

  Purpose: Start the workflow manually whenever you want to run it.
  Benefit: Great for testing or running on-demand without needing automation.

  🔑 Set API Key (Set Node)

  Purpose: Stores your Replicate API key in the workflow.
  How it works: Adds your API key as a variable that other nodes can reference.
  Benefit: Keeps credentials secure and reusable.

  📌 Section 2: Sending the AI Request

  📤 Create Prediction (HTTP Request Node)

  Purpose: Sends a request to the Replicate API to start generating output with the model.
  Input Parameters:

    prompt (text you provide)
    seed (for reproducibility)
    width / height / lora\_scale (generation settings)
  Benefit: Allows full customization of the AI’s generation process.

  🆔 Extract Prediction ID (Code Node)

  Purpose: Pulls out the Prediction ID and status from the API response.
  Why important: The ID is required to check the job’s progress later.
  Benefit: Automates polling without manual tracking.

  📌 Section 3: Polling & Waiting

  ⏳ Wait (Wait Node)

  Purpose: Adds a short pause (2 seconds) between checks.
  Benefit: Prevents hitting the API too quickly and avoids errors.

  🔄 Check Prediction Status (HTTP Request Node)

  Purpose: Calls Replicate again to ask if the prediction is finished.
  Benefit: Automates progress monitoring without manual refresh.

  ✅ Check If Complete (If Node)

  Purpose: Decides whether the model has finished generating.
  Paths:

    True → Move on to processing the result.
    False → Go back to Wait and recheck.
  Benefit: Ensures the workflow loops until a final output is ready.

  📌 Section 4: Handling the Result

  📦 Process Result (Code Node)

  Purpose: Cleans up the final API response and extracts:

    Status
    Output (generated result)
    Metrics
    Timestamps (created\_at / completed\_at)
    Model info
  Benefit: Provides a structured, ready-to-use output for other workflows or integrations.

  📊 Workflow Overview Table

  | Section           | Node Name               | Purpose                      |
  | ----------------- | ----------------------- | ---------------------------- |
  | 1. Trigger & Auth | On Clicking ‘Execute’   | Starts the workflow manually |
  |                   | Set API Key             | Stores API credentials       |
  | 2. AI Request     | Create Prediction       | Sends request to Replicate   |
  |                   | Extract Prediction ID   | Gets prediction ID + status  |
  | 3. Polling        | Wait                    | Adds delay before recheck    |
  |                   | Check Prediction Status | Monitors progress            |
  |                   | Check If Complete       | Routes based on completion   |
  | 4. Result         | Process Result          | Extracts and cleans output   |
  | Notes             | Sticky Note             | Explains setup + model info  |

  🎯 Key Benefits

  🔐 Secure authentication using Set node for API key storage.
  🤖 Hands-free generation — just provide a prompt, the workflow handles everything else.
  🔄 Automated polling ensures you always get the final result without manual checking.
  📦 Clean structured output ready for downstream use in apps, dashboards, or notifications.

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name: Backup n8n Workflows with Versioning and Notion Tracking
author_name: Stéphane Heckel
author_username: stephaneheckel
categories: []
created_at: 2025-08-03T17:52:26.644Z
updated_at: 2025-08-03T17:52:26.644Z
url: https://n8n.io/workflows/6947
scraped_at: 2025-09-14 11:38:21
description:
  Copy n8n workflows to a slave n8n repository

  Inspired by Alex Kim's workflow, this version adds the ability to keep multiple versions of the same workflow on the destination instance. Each copied workflow’s name is prefixed with the date (YYYY_MM_DD_), enabling simple version tracking. Process details and workflow counts are recorded centrally in Notion.

  How it works

  Workflows from the source n8n instance are copied to the destination using the n8n API node.
  On the destination, each workflow name is prefixed with the current date (e.g., 2025_08_03_PDF Summarizer), so you can keep multiple daily versions.
  The workflow tracks and saves:
      The date of execution.
      Number of workflows processed.
      Both details are recorded in Notion.

  Rolling retention policy example:

  Day 1:** Workflows are saved with 2025_08_03_ prefix.
  Day 2:** New set saved with 2025_08_04_.
  Day 3:** Day 1’s set is deleted, new set saved as 2025_08_05_.
  To keep more days, adjust the “Subtract From Date” node.

  How to use

  Create a Notion database with one page and three fields:
      sequence: Should contain "prefix".
      Value: Today's date as YYYY_MM_DD_.
      Comment: Number of saved workflows.

  Configure the Notion node:
      Enter your Notion credentials.
      Link to the created database/page.

  Update the "Subtract From Date" node:
      Set how many days’ versions you want to keep (default: 2 days).
      Set the limit to 1 in the "Limit" node for testing.
  Input credentials for both source and destination n8n instances.

  Requirements

  Notion** for tracking execution date and workflow count.
  n8n API Keys* for both source and destination instances. Ensure you have the necessary *API permissions** (read, create, delete workflows)
  n8n version** this workflow was tested on 1.103.2 (Ubuntu)

  Need Help?

  Comment this post or contact me on LinkedIn
  Ask in the Forum!

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name: Daily Calendar Summary Notifications via Telegram from Google Calendar
author_name: Yassin Zehar
author_username: yassinzehar
categories: []
created_at: 2025-08-03T18:33:22.621Z
updated_at: 2025-08-03T18:33:22.621Z
url: https://n8n.io/workflows/6952
scraped_at: 2025-09-14 11:38:21
description:
  Context:
  This workflow automatically sends you a daily message on Telegram summarizing all your meetings and events for the day, straight from your Google Calendar.

  For who ? 
  Perfect for anyone who:
  Uses Google Calendar to manage their schedule.
  Wants Telegram reminders for daily events.
  Loves automation and productivity tools.

  Requirements:
  Telegram.
  Google account.
  Google Calendar.

  Steps:


  🗒️ Use the sticky notes in the n8n canvas to:
  Add your Telegram and Google credentials.
  Execute and test the workflow.
  Check if you receive your daily summary on Telegram.

  You'll get this:

  Tutorial video:
  Watch the Youtube Tutorial video

  How does it work?
  ⏰ The trigger runs every day at 7AM.
  📅 Your Google Calendar is checked.
  🔢 If there are events or meetings, a number &gt; 0 is returned. Otherwise, it's 0.
  📝 A text message is generated with a summary of all your events, including all relevant details.
  ❌ If no events are found, a "no event" message is sent.

  About me :
  I'm Yassin, IT Project Manager, Agile & Data specialist. Scaling tech products with data-driven project management.
  📬 Feel free to connect with me on Linkedin

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name: Automate Your Magento 2 Weekly Sales & Performance Reports
author_name: Kanaka Kishore Kandregula
author_username: kmyprojects
categories: []
created_at: 2025-08-03T22:56:21.791Z
updated_at: 2025-08-03T22:56:21.791Z
url: https://n8n.io/workflows/6953
scraped_at: 2025-09-14 11:38:22
description:
  Automatically fetches last week’s Magento 2 orders, summarises sales and product performance, logs the data to Google Sheets, and emails a polished report — all without logging into admin or buying extra modules. 

  Perfect for store owners and agencies.

  ✅ What This Workflow Does:
  This workflow automatically fetches the last 7 days of orders from your Magento 2 store, summarizes key metrics (orders, revenue, products sold), groups product performance data, generates a Google Sheet with two tabs (Weekly Summary & Product Breakdown), and emails the report to your team in a modern dashboard-style HTML format — all without ever logging into Magento admin.

  🔧 Modules Used:
  🕒 Schedule Trigger
  ⚙️ Code (JavaScript)
  🌐 HTTP Request
  📊 Google Sheets
  ✉️ Gmail (HTML Email with custom design)

  💼 Use Cases:
  E-commerce store managers who want weekly sales snapshots without logging into Magento 2.
  Agencies managing multiple Magento clients and reporting to them weekly.
  Business owners who want automated insights without paying for extra reporting modules.
  Marketing or growth teams that need product-wise performance regularly in Google Sheets.

  🔒 Credentials Required:
  Magento 2 API (Bearer Token)
  Google Sheets OAuth2
  Gmail OAuth2 (for sending HTML email reports)

  📂 Category:
  E-commerce / Magento 2 / Reporting / Automation

  ✨ Why This Saves Hours:
  This workflow replaces manual Magento report exports, repetitive data cleanup, and weekly email formatting. Store managers often waste 1–2 hours/week collecting data — now it takes 0 minutes. Just set it and forget it.
  You don’t need to buy reporting extensions, log into the admin, or manually touch a spreadsheet again.

  🤝 Need a Custom Workflow?
  If you need this tailored for your own workflow, store, or client —
  📩 Let’s connect. I build custom, high-performance n8n automations for e-commerce, growth, and reporting.

  Contact: Author

  👤 Author
  Kanaka Kishore Kandregula
  Certified Magento 2 Developer
  https://gravatar.com/kmyprojects
  https://www.linkedin.com/in/kanakakishore

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name: Generate Videos from Images with Wan 2.2 I2V A14B AI Model
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-04T14:24:22.279Z
updated_at: 2025-08-04T14:24:22.279Z
url: https://n8n.io/workflows/6966
scraped_at: 2025-09-14 11:38:21
description:
  Generate Videos from Images with Wan 2.2 I2V A14B AI Model

  🌍 Overview

  This workflow connects n8n with Replicate’s Wan-Video model to generate video content from an image + prompt.
  It handles:

  🔑 API authentication
  📤 Sending a generation request
  ⏳ Polling until completion
  📥 Returning a downloadable video link

  🟢 Section 1: Start & Authentication

  🔗 Nodes:
  1️⃣ On clicking 'execute' (Manual Trigger)
  ▶️ Starts the workflow manually when you click Execute Workflow.

  2️⃣ Set API Key
  🔑 Stores your Replicate API Key securely inside n8n.

  Value: YOUR_REPLICATE_API_KEY

  💡 Beginner Benefit:
  ✅ No need to hardcode API keys in every request
  ✅ Easy to swap keys for different accounts

  🔵 Section 2: Send Video Generation Request

  🔗 Nodes:
  3️⃣ Create Prediction (HTTP Request)
  📤 Sends a request to Replicate API → /v1/predictions

  Model: wan-video/wan-2.2-i2v-a14b
  Input Parameters:

    📝 prompt → your text description
    🖼️ image → input video/image URL
    🎲 seed → reproducibility
    🎞️ num_frames → 81 frames
    ⏩ sample_shift → 5
    ⚙️ sample_steps → 30
    🎬 frames_per_second → 16

  4️⃣ Extract Prediction ID (Code)
  🆔 Pulls out the prediction ID + status from Replicate’s response.
  This ID is needed for polling until the video finishes generating.

  💡 Beginner Benefit:
  ✅ Automates the API call to generate video
  ✅ Extracts ID → avoids manual copy-paste

  🟣 Section 3: Polling & Status Check

  🔗 Nodes:
  5️⃣ Wait (2 sec)
  ⏳ Adds a short delay before checking progress.

  Prevents API spam

  6️⃣ Check Prediction Status (HTTP Request)
  🔄 Calls Replicate API → /v1/predictions/{id}

  Checks whether the video is still processing or finished

  7️⃣ Check If Complete (IF Node)
  ❓ Compares status → succeeded or not

  ✅ If complete → goes to Process Result
  ❌ If not → loops back to Wait and tries again

  💡 Beginner Benefit:
  ✅ Automatic re-checking → you don’t need to refresh manually
  ✅ Works until result is ready

  🟡 Section 4: Process Final Result

  🔗 Nodes:
  8️⃣ Process Result (Code)
  📥 Once complete, extracts:

  ✅ Status
  🎞️ Output video URL
  📊 Generation metrics
  ⏱️ Timestamps (created\_at, completed\_at)
  🧩 Model used

  Final output = direct video URL you can download/share 🎥

  📊 Final Overview

  | Section   | What Happens                   | Why It’s Useful                   |
  | --------- | ------------------------------ | --------------------------------- |
  | 🟢 Auth   | Manual Trigger + API Key       | Secure, easy start                |
  | 🔵 Send   | Create Prediction + Extract ID | Kicks off video generation        |
  | 🟣 Poll   | Wait + Check Status + IF       | Auto-checks progress until done   |
  | 🟡 Result | Process Result                 | Gives final video link + metadata |

  🚀 Why This Workflow Rocks

  🎥 Video from Image + Prompt → AI-powered video generation in minutes
  🔄 Fully automated → from request to final video, no manual checks
  🔑 Secure → API keys handled safely
  ⚙️ Customizable → tweak frames, FPS, prompt, seed

  ✨ With this workflow, you’ve got a personal AI video generator inside n8n — all you need to do is provide a prompt + input image/video, and you’ll get a fresh AI video link back.

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name: Generate Custom Text Content with IBM Granite 3.3 8B Instruct AI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-04T14:25:22.747Z
updated_at: 2025-08-04T14:25:22.747Z
url: https://n8n.io/workflows/6968
scraped_at: 2025-09-14 11:38:23
description:
  Generate Custom Text Content with IBM Granite 3.3 8B Instruct AI

  This workflow connects to Replicate’s API and uses the ibm-granite/granite-3.3-8b-instruct model to generate text.

  ✅ 🔵 SECTION 1: Trigger & Setup

  ⚙️ Nodes

  1️⃣ On clicking 'execute'

  What it does:* Starts the workflow manually when you hit *Execute.
  Why it’s useful:** Perfect for testing text generation on-demand.

  2️⃣ Set API Key

  What it does:* Stores your *Replicate API key** securely.
  Why it’s useful:** You don’t hardcode credentials into HTTP nodes — just set them once here.
  Beginner tip:** Replace YOUR_REPLICATE_API_KEY with your actual API key.

  💡 Beginner Benefit

  ✅ No coding needed to handle authentication.
  ✅ You can reuse the same setup for other Replicate models.

  ✅ 🤖 SECTION 2: Model Request & Polling

  ⚙️ Nodes

  3️⃣ Create Prediction (HTTP Request)

  What it does:* Sends a *POST request** to Replicate’s API to start a text generation job.
  Parameters include:** temperature, max_tokens, top_k, top_p.
  Why it’s useful:** Controls how creative or focused the AI text output will be.

  4️⃣ Extract Prediction ID (Code)

  What it does:* Pulls the *prediction ID** and builds a URL for checking status.
  Why it’s useful:** Replicate jobs run asynchronously, so you need the ID to track progress.

  5️⃣ Wait

  What it does:* Pauses for *2 seconds** before checking the prediction again.
  Why it’s useful:** Prevents spamming the API with too many requests.

  6️⃣ Check Prediction Status (HTTP Request)

  What it does:* Polls the Replicate API for the *current status** (e.g., starting, processing, succeeded).
  Why it’s useful:** Lets you loop until the AI finishes generating text.

  7️⃣ Check If Complete (IF Condition)

  What it does:* If the status is *succeeded, it goes to “Process Result.” Otherwise, it loops back to **Wait and retries.
  Why it’s useful:** Creates an automated polling loop without writing complex code.

  💡 Beginner Benefit

  ✅ No need to manually refresh or check job status.
  ✅ Workflow keeps retrying until text is ready.
  ✅ Smart looping built-in with Wait + If Condition.

  ✅ 🟢 SECTION 3: Process & Output

  ⚙️ Nodes

  8️⃣ Process Result (Code)

  What it does:* Collects the final *AI output**, status, metrics, and timestamps.
  Adds info like:**

    ✅ output → Generated text
    ✅ model → ibm-granite/granite-3.3-8b-instruct
    ✅ metrics → Performance data
  Why it’s useful:** Gives you a neat, structured JSON result that’s easy to send to Sheets, Notion, or any app.

  💡 Beginner Benefit

  ✅ Ready-to-use text output.
  ✅ Easy integration with any database or CRM.
  ✅ Transparent metrics (when it started, when it finished, etc.).

  ✅✅✅ ✨ FULL FLOW OVERVIEW

  | Section                        | What happens                                                                 |
  | ------------------------------ | ---------------------------------------------------------------------------- |
  | ⚡ Trigger & Setup          | Start workflow + set Replicate API key.                                      |
  | 🤖 Model Request & Polling | Send request → get Prediction ID → loop until job completes.                 |
  | 🟢 Process & Output        | Extract clean AI-generated text + metadata for storage or further workflows. |

  📌 How You Benefit Overall

  ✅ No coding needed — just configure your API key.
  ✅ Reliable polling — the workflow waits until results are ready.
  ✅ Flexible — you can extend output to Google Sheets, Slack, Notion, or email.
  ✅ Beginner-friendly — clean separation of input, process, and output.

  ✨ With this workflow, you’ve turned Replicate’s IBM Granite LLM into a no-code text generator — running entirely inside n8n! ✨

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name: Track Expenses from Telegram to Google Sheets with GPT-4.1 Mini
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-04T14:53:50.938Z
updated_at: 2025-08-04T14:53:50.938Z
url: https://n8n.io/workflows/6970
scraped_at: 2025-09-14 11:38:21
description:
  📒 Telegram Expense Tracker to Google Sheets with GPT-4.1
  .jpg)
  &gt; A lightweight automation that lets users log daily expenses via a Telegram bot and instantly saves them into Google Sheets—perfect for anyone looking to manage spending on the go with AI-powered structure and ease.
  👤 Who’s it for
  This workflow is for anyone who wants to log their daily expenses by simply chatting with a Telegram bot. Ideal for:
  Individuals who want a quick way to track spending
  Freelancers who log receipts and purchases on the go
  Teams or small business owners who want lightweight expense capture

  ⚙️ How it works / What it does
  User sends a text message on Telegram describing an expense  
     (e.g., “Bought coffee for 50k at Highlands”)

  Message format is validated
     If the message is text, it proceeds to GPT-4.1 Mini for processing.
     If it's not text (e.g. image or file), the bot sends a fallback message.

  OpenAI GPT-4.1 Mini parses the message and returns:
     relevant: true/false
     expense_record: structured fields (date, amount, currency, category, description, source)
     message: a friendly confirmation or fallback

  If valid:
     The bot replies with a fun acknowledgment
     The data is saved to a connected Google Sheet

  If invalid:
     A fallback message is sent to encourage proper input

  🛠️ How to set up

  1. Telegram Bot Setup
  Create a bot using BotFather on Telegram
  Copy the bot token and paste it into the Telegram Trigger node

  2. Google Sheet Setup
  Create a Google Sheet with these columns:
      Date | Amount | Currency | Category | Description | SourceMessage
    Share the sheet with your n8n service account email

  3. OpenAI Configuration
  Connect the OpenAI Chat Model node using your OpenAI API key
  Use GPT-4.1 Mini as the model
  Apply a system prompt that extracts structured JSON with:
    relevant, expense_record, and message

  4. Add Parser
  Use the Structured Output Parser node to safely parse the JSON response

  5. Conditional Logic Nodes
  Is text message?  
     Checks if the message is in text format  
  Supported scenario?  
     Checks if relevant = true in the LLM response

  6. Final Actions
  If relevant**:  
     Send confirmation via Telegram  
     Append row to Google Sheet  
  If not relevant**:  
     Send fallback message via Telegram

  ✅ Requirements
  Telegram bot token
  OpenAI GPT-4.1 Mini API access
  n8n instance (self-hosted or cloud)
  Google Sheet with access granted to n8n
  Basic understanding of n8n node configuration

  🧩 How to customize the workflow

  | Feature                         | How to Customize                                                  |
  |----------------------------------|-------------------------------------------------------------------|
  | Add multi-currency support       | Update system prompt to detect and extract different currencies  |
  | Add more categories              | Modify the list of categories in the system prompt               |
  | Track multiple users             | Add username or chat ID column to the Google Sheet           |
  | Trigger alerts                   | Add Slack, Email, or Telegram alerts for specific expense types  |
  | Weekly summaries                 | Use a cron node + Google Sheet query + Telegram message          |
  | Visual dashboards                | Connect the sheet to Looker Studio or Google Data Studio         |

  Built with 💬 Telegram + 🧠 GPT-4.1 Mini + 📊 Google Sheets + ⚡ n8n

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 7836 characters]


name: Website Contact Form to Slack with Optional Email Confirmation
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-04T23:17:08.377Z
updated_at: 2025-08-04T23:17:08.377Z
url: https://n8n.io/workflows/6987
scraped_at: 2025-09-14 11:38:22
description:
  This n8n workflow sends a real-time Slack notification when a user submits a contact form on your website. It also optionally sends a confirmation email via either Outlook or Gmail.

  You can embed the form directly into your website and route all submissions to your preferred Slack channel for quick follow-up.

  ✅ Key Features

  🌐 Website Form Trigger**: A no-code form that can be embedded directly on your website.
  ⚡ Slack Integration**: Instantly posts lead details to a designated Slack channel.
  📧 Email Follow-Up (Optional)**: Sends a thank-you email to the user via either Gmail or Microsoft Outlook.
  🔗 Easy to Connect**: Requires minimal setup with OAuth for Slack and email APIs.

  🧰 What You'll Need

  Slack Bot Token & Permissions**
  Gmail or Outlook account (optional)**
  n8n instance (cloud or self-hosted)**

  🛠️ Step-by-Step Setup

  1️⃣ Embed Contact Form on Website
  Node**: Form Submission on Website
  What it does**: Captures user inputs — Name, Email, and Phone.
  How to use**:
    Grab the public webhook URL from this node.
    Embed it as a form action on your website (HTML form or no-code builder).
  API**: None required. Webhook-based.

  2️⃣ Send to Slack
  Node**: Slack
  What it does**: Posts a message to your Slack #leads channel with submission details.
  Message format**:
      You have a form submission with these details.
    Name: {{ Name }}
    Email: {{ Email }}
    Phone: {{ Phone }}
    API**: Slack Bot Token (OAuth2)

  3️⃣ Optional: Send Confirmation Email
  Node**: Send Email - Gmail
    Sends email using Gmail API.
  Node**: Send Email - Outlook
    Sends email using Microsoft Outlook API.
  Message**:
      Hi {{ Name }},

    Thank you for reaching out on our website. We'll be in touch soon!
    API**: Gmail or Microsoft Outlook OAuth2

  👤 Created By
  Robert Breen  
  Automation Consultant | AI Workflow Designer | n8n Expert  
  📧 rbreen@ynteractive.com  
  🌐 ynteractive.com  
  🔗 LinkedIn

  🏷️ Tags
  slack lead alerts website form n8n email automation real-time notification lead generation form trigger webhook

nodes_used:
  ["n8n-nodes-base.slack","n8n-nodes-base.formTrigger","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote"]

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name: Daily Ad Spend Monitoring with Google Sheets and Slack Threshold Alerts
author_name: Robert Breen
author_username: rbreen
categories: []
created_at: 2025-08-05T00:44:26.418Z
updated_at: 2025-08-05T00:44:26.418Z
url: https://n8n.io/workflows/6990
scraped_at: 2025-09-14 11:38:22
description:
  This n8n workflow checks daily ad spend totals from a Google Sheet and sends a Slack alert if spend exceeds $100. It can be scheduled to run automatically or manually triggered for testing. This is perfect for marketing teams who want to monitor budget spikes in near real-time.

  ✅ Key Features

  📥 Google Sheets Integration**: Pulls raw spend data from a shared spreadsheet.
  📆 Scheduled or Manual Execution**: Can run daily on a schedule or manually for testing.
  📈 Aggregates Spend**: Summarizes daily totals from raw data.
  🧠 Logic Check**: Alerts only when spend exceeds a certain threshold.
  🔔 Slack Alerts**: Sends instant notification to a specified channel.

  🧰 What You'll Need

  Google Cloud Project** with Sheets API enabled
  OAuth2 Credential** for Google Sheets
  Slack Bot Token** with permission to post to your workspace
  Your Google Sheet link and tab name**

  📎 Copy this Sample Google Sheet to Use:  
  Marketing Data Sheet - Copy Me

  🔧 Step-by-Step Setup

  1️⃣ Schedule or Manual Trigger
  Node**: Schedule Workflow or Test Workflow
  Purpose**: Either run daily via a cron-like rule or manually trigger the flow.

  2️⃣ Get Google Sheet Data
  Node**: Get Data
  What it does**: Fetches all rows from your connected sheet.
  Setup**:
    Go to Google Cloud Console
    Create a new project
    Enable Google Sheets API
    Create OAuth2 credentials for a desktop or web application
    Connect your Google account in n8n via OAuth2
    Grant access to the sheet you want to read (ensure it's shared with your OAuth email)
    Use the copied sheet's link when connecting in n8n

  3️⃣ Summarize Spend by Day
  Node**: Sum spend by Day
  What it does**: Groups the dataset by Date and sums the Spend ($) column
  Requirements**:
    Your sheet must have a header row with Date and Spend ($) as columns

  4️⃣ Sort by Most Recent Date
  Node**: Sort Dates Descending
  What it does**: Sorts all entries by the Date field so that the most recent day is first
  Custom JavaScript**:
  const items = $input.all();
  items.sort((a, b) =&gt; new Date(b.json.Date) - new Date(a.json.Date));
  return items;

  5️⃣ Select Top Result
  Node**: Keep only Last Day
  What it does**: Captures the top row (most recent day) for evaluation
  Fields**: Sets only Date and sum_Spend_($) to keep things clean

  6️⃣ Check Spend Threshold
  Node**: Check if Spend over $100
  What it does**: Uses an IF node to compare sum_Spend_($) against a 100 threshold
  Logic**:
  sum_Spend_($) &gt; 100

  7️⃣ Send Slack Notification
  Node**: Send Slack Message
  What it does**: Sends a message to a Slack channel if the threshold is exceeded
  Setup**:
    Go to Slack API
    Create a new app
    Enable chat:write and channels:read scopes under OAuth & Permissions
    Install the app to your workspace
    Copy the OAuth Token into your Slack credentials in n8n
    Select your target channel from the dropdown (must be public or the bot must be invited)
  Message**:
      The spend for the most recent day is over $100
  8️⃣ No Action if Under Budget
  Node**: Do Nothing. Under 100
  Purpose**: This path simply ends the flow with no action if spend is below the threshold

  👤 Created By
  Robert Breen  
  Automation Consultant | AI Workflow Designer | n8n Expert  
  📧 rbreen@ynteractive.com  
  🌐 ynteractive.com  
  🔗 LinkedIn

  🏷️ Tags
  slack marketing automation budget alert daily schedule google sheets threshold logic n8n spend tracking data summarization

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.summarize","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.slack","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Scrape Google Maps by area & Generate Outreach Messages for Lead Generation
author_name: Solomon
author_username: solomon
categories: []
created_at: 2025-08-05T06:05:50.841Z
updated_at: 2025-08-05T06:05:50.841Z
url: https://n8n.io/workflows/6993
scraped_at: 2025-09-14 11:38:20
description:
  This n8n workflow automates lead extraction from Google Maps, enriches data with AI, and stores results for cold outreach.

  It uses the Bright Data community node and Bright Data MCP for scraping and AI message generation.

  How it works

  Form Submission
      
      User provides Google Maps starting location, keyword and country.
      
  Bright Data Scraping
      
      Bright Data community node triggers a Maps scraping job, monitors progress, and downloads results.
      
  AI Message Generation
      
      Uses Bright Data MCP with LLMs to create a personalized cold call script and talking points for each lead.
      
  Database Storage
      
      Enriched leads and scripts are upserted to Supabase.
  How to use

  Set up all the credentials, create your Postgres table and submit the form. The rest happens automatically.

  Requirements

  LLM account (OpenAI, Gemini…) for API usage.
  Bright Data account for API and MCP usage.
  Supabase account (or other Postgres database) to store information.

nodes_used:
  ["n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.noOp","n8n-nodes-base.formTrigger","n8n-nodes-base.merge","n8n-nodes-base.postgres","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.mcpClientTool","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.limit","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","@brightdata/n8n-nodes-brightdata.brightData","@brightdata/n8n-nodes-brightdata.brightData","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.splitInBatches","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.postgres","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

workflow_json_compressed:
  [encoded data, 10852 characters]


name: AI Orchestrator: dynamically Selects Models Based on Input Type
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-08-05T10:21:49.772Z
updated_at: 2025-08-05T10:21:49.772Z
url: https://n8n.io/workflows/7004
scraped_at: 2025-09-14 11:38:20
description:
  This workflow is designed to intelligently route user queries to the most suitable large language model (LLM) based on the type of request received in a chat environment. It uses structured classification and model selection to optimize both performance and cost-efficiency in AI-driven conversations.

  It dynamically routes requests to specialized AI models based on content type, optimizing response quality and efficiency.

  Benefits

  Smart Model Routing**: Reduces costs by using lighter models for general tasks and reserving heavier models for complex needs.
  Scalability**: Easily expandable by adding more request types or LLMs.
  Maintainability**: Clear logic separation between classification, model routing, and execution.
  Personalization**: Can be integrated with session IDs for per-user memory, enabling personalized conversations.
  Speed Optimization**: Fast models like GPT-4.1 mini or Gemini Flash are chosen for tasks where speed is a priority.
  How It Works
  Input Handling:  
     The workflow starts with the "When chat message received" node, which triggers the process when a chat message is received. The input includes the chat message (chatInput) and a session ID (sessionId).

  Request Classification:  
     The "Request Type" node uses an OpenAI model (gpt-4.1-mini) to classify the incoming request into one of four categories:  
       general: For general queries.  
       reasoning: For reasoning-based questions.  
       coding: For code-related requests.  
       search: For queries requiring search tools.  
     The classification is structured using the "Structured Output Parser" node, which enforces a consistent output format.

  Model Selection:  
     The "Model Selector" node routes the request to one of four AI models based on the classification:  
       Opus 4 (Claude 4 Sonnet): Used for coding requests.  
       Gemini Thinking Pro: Used for reasoning requests.  
       GPT 4.1 mini: Used for general requests.  
       Perplexity: Used for search (Google-related) requests.  

  AI Processing:  
     The selected model processes the request via the "AI Agent" node, which includes intermediate steps for complex tasks.  
     The "Simple Memory" node retains session context using the provided sessionId, enabling multi-turn conversations.  

  Output:  
     The final response is generated by the chosen model and returned to the user.  

  Set Up Steps
  Configure Trigger:  
     Ensure the "When chat message received" node is set up with the correct webhook ID to receive chat inputs.  

  Define Classification Logic:  
     Adjust the prompt in the "Request Type" node to refine classification accuracy.  
     Verify the output schema in the "Structured Output Parser" node matches expected categories (general, reasoning, coding, search).  

  Connect AI Models:  
     Link each model node (Opus 4, Gemini Thinking Pro, GPT 4.1 mini, Perplexity) to the "Model Selector" node.  
     Ensure credentials (API keys) for each model are correctly configured in their respective nodes.  

  Set Up Memory:  
     Configure the "Simple Memory" node to use the sessionId from the input for context retention.  

  Test Workflow:  
     Send test inputs to verify classification and model routing.  
     Check intermediate outputs (e.g., request_type) to ensure correct model selection.  

  Activate Workflow:  
     Toggle the workflow to "Active" in n8n after testing.  

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

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.modelSelector","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatAnthropic","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote"]

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name: Automate WhatsApp Sales with DeepSeek AI, Google Sheets and Gmail Notifications
author_name: Ahmed Saadawi
author_username: ahmedsaadawi
categories: []
created_at: 2025-08-05T10:24:36.993Z
updated_at: 2025-08-05T10:24:36.993Z
url: https://n8n.io/workflows/7005
scraped_at: 2025-09-14 11:38:22
description:
  Turn WhatsApp Into a 24/7 AI Sales Assistant — n8n + DeepSeek + Sheets + Gmail

  ⚠️ Self-Hosted n8n Only

  Description

  Turn your WhatsApp channel into a smart sales assistant! This workflow listens for inbound customer messages, looks up product data in Google Sheets, uses a DeepSeek Chat Model to answer in Saudi dialect, collects purchase details, and notifies your service rep only when the customer is ready to buy.

  🔧 How to Install Community Nodes

  Go to Settings → Community Nodes
  Click Install Node, then add:

  n8n-nodes-evolution-api

  Restart n8n if prompted.

  🔄 What This Workflow Does

  Webhook Listener
     Captures inbound WhatsApp messages (MESSAGES_UPSERT via Evolution API).
  Filters
     Ignores outbound (fromMe) and group (@g.us) messages.
  Data Extraction
     Pulls the customer’s message and phone number.
  AI Response
     Uses the DeepSeek Chat Model node to answer from your Google Sheets product list, greeting with “هلا وغلا” and speaking in Saudi dialect.
  Purchase Flow
     Prompts for name, phone, and delivery/pickup date.
  Notify Sales
     Sends an email via Gmail only when the customer requests to purchase.
  Context Memory
     (Optional) Stores conversation history in Postgres for coherent multi-turn chats.

  📸 Visual Preview

  🧩 Workflow 

  🛠️ Setup Instructions

  Evolution API Webhook

     In Evolution API dashboard → Events → Webhook
     Enable only MESSAGES\_UPSERT
     Set Webhook URL to:
       https://your-n8n-domain/webhook/whatsAppListen

  Google Sheets

     Create a spreadsheet (“You Conmanay Name Items”) with your product data [Item name, Item Model, Item Description, Item Components, Item Price, Item Availability, ...]
     Connect your Google Sheets credentials in n8n

  DeepSeek Chat Model

     Configure your DeepSeek API credentials in the DeepSeek Chat Model node
     Ensure the system prompt matches your company’s tone and data columns

  Gmail Notifications

     Add Gmail OAuth2 credentials to the Send a message in Gmail node
     Customize subject and email template if needed

  Postgres Memory (Optional)

     Connect a Postgres instance in the Postgres Chat Memory node for session context

  👥 Who Is This For?

  E-commerce teams** automating first-touch customer replies
  Sales reps** needing AI-driven chat support on WhatsApp
  Businesses** using WhatsApp as a primary customer channel

  🔐 Credentials Required

  Evolution API (webhook only)
  Google Sheets API
  DeepSeek API
  Gmail OAuth2
  Postgres (optional, for memory)

  🏷 Tags

  whatsapp bot, deepseek, google sheets, evolution api, gmail, postgres memory, ecommerce, sales automation, n8n template, no-code, ai, agent, ai agent

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.gmailTool","n8n-nodes-base.googleSheetsTool","@n8n/n8n-nodes-langchain.lmChatDeepSeek","n8n-nodes-base.if","n8n-nodes-base.noOp","n8n-nodes-evolution-api.evolutionApi","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.memoryPostgresChat"]

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name: Automate SEO Analysis for Multiple Domains with Ahrefs and Google Sheets
author_name: Michael Muenzer
author_username: michaelmuenzer
categories: []
created_at: 2025-08-05T13:29:03.226Z
updated_at: 2025-08-05T13:29:03.226Z
url: https://n8n.io/workflows/7010
scraped_at: 2025-09-14 11:38:20
description:
  This workflow contains community nodes that are only compatible with the self-hosted version of n8n.

  Fetch SEO and traffic information from ahref for a list of domains in a Google Sheet. This is great for marketing research and SEO workflow optimizations and saves tons of time.

  How it works
  We'll import domains from the Google sheet
  We use an SEO MCP server to fetch data from ahref free tooling
  The fetched data is stored in the Google sheet

  Set up steps
  Copy Google Sheet template and add it in all Google Sheet nodes
  Make sure that n8n has read & write permissions for your Google sheet.
  Add your list of domains in the first column in the Google sheet
  Add MCP credentials for seo-mcp

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-mcp.mcpClient","n8n-nodes-mcp.mcpClient","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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name: Generate Images from Text with IBM Granite Vision 3.3 2B AI Model
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-08-05T14:23:41.808Z
updated_at: 2025-08-05T14:23:41.808Z
url: https://n8n.io/workflows/7012
scraped_at: 2025-09-14 11:38:21
description:
  Generate Images from Text with IBM Granite Vision 3.3 2B AI Model

  🌍 Overview

  This workflow uses the ibm-granite/granite-vision-3.3-2b model (hosted on Replicate) to generate AI images. It starts manually, sends a request to the Replicate API, waits for the result, and finally outputs the generated image link.

  Think of it as your AI art assistant — you click once, and it handles the full request/response cycle for image generation.

  🟢 Section 1: Trigger & API Setup

  🔗 Nodes:

  Manual Trigger* → Starts when you click *Execute.
  Set API Key** → Stores your Replicate API Key safely in the workflow.

  💡 Beginner takeaway:
  This section is like turning the key in the ignition. You start the workflow, and it loads your credentials so you can talk to Replicate’s API.

  📈 Advantage:
  Keeps your API key stored inside the workflow instead of hard-coding it everywhere.

  🟦 Section 2: Create Prediction

  🔗 Nodes:

  HTTP Request (Create Prediction)** → Sends a request to Replicate with the chosen model (granite-vision-3.3-2b) and input parameters (seed, temperature, max\_tokens, etc.).

  💡 Beginner takeaway:
  This is where the workflow actually asks the AI model to generate an image.

  📈 Advantage:
  You can tweak parameters like creativity (temperature) or randomness (seed) to control results.

  🟣 Section 3: Polling & Status Check

  🔗 Nodes:

  Extract Prediction ID (Code)** → Saves the unique job ID.
  Wait (2s)** → Pauses before checking status.
  Check Prediction Status (HTTP Request)** → Calls Replicate to see if the image is ready.
  If Condition (Check If Complete)** →

    ✅ If status = succeeded → move to result
    🔄 Else → go back to Wait and check again

  💡 Beginner takeaway:
  Since image generation takes a few seconds, this section keeps asking the AI “are you done yet?” until the image is ready.

  📈 Advantage:
  No need to guess — the workflow waits automatically and retries until success.

  🔵 Section 4: Process Result

  🔗 Nodes:

  Process Result (Code)** → Extracts the final data:

    ✅ Status
    ✅ Output image URL
    ✅ Metrics (time taken, etc.)
    ✅ Model info

  💡 Beginner takeaway:
  This section collects the finished image link and prepares it neatly for you.

  📈 Advantage:
  You get structured output that you can save, display, or use in another workflow (like auto-sending images to Slack or saving to Google Drive).

  📊 Final Overview Table

  | Section              | Nodes                              | Purpose                     | Benefit                     |
  | -------------------- | ---------------------------------- | --------------------------- | --------------------------- |
  | 🟢 Trigger & Setup   | Manual Trigger, Set API Key        | Start + load credentials    | Secure API key management   |
  | 🟦 Create Prediction | HTTP Request                       | Ask AI to generate image    | Control creativity & output |
  | 🟣 Polling           | Extract ID, Wait, Check Status, If | Repeatedly check job status | Auto-wait until done        |
  | 🔵 Process Result    | Process Result                     | Extract image + details     | Get clean output for reuse  |

  🚀 Why This Workflow is Useful

  Automates full API cycle** → From request to final image URL
  Handles delays automatically** → Keeps checking until your image is ready
  Customizable parameters** → Adjust creativity, randomness, and token limits
  Reusable** → Connect it to email, Slack, Notion, or storage for instant sharing
  Beginner-friendly* → Just plug in your API key and hit *Execute

nodes_used:
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workflow_json_compressed:
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name: Send a voice note on Telegram to generate a professional email with ChatGPT
author_name: Baptiste Fort
author_username: baptistefort
categories: []
created_at: 2025-08-06T08:30:25.992Z
updated_at: 2025-08-06T08:30:25.992Z
url: https://n8n.io/workflows/7041
scraped_at: 2025-09-14 11:38:21
description:
  Telegram Voice Message → Automatic Email



  Imagine: What if you could turn a simple Telegram voice message into a professional email—without typing, copying, pasting, or even opening Gmail?

  This workflow does it all for you: just record a voice note, and it will transcribe, format, and write a clean HTML email, then send it to the right person—all by itself.

  Prerequisites

  Create a Telegram bot** (via BotFather) and get the token.
  Have an OpenAI account** (API key for Whisper and GPT-4).
  Set up a Gmail account with OAuth2.**
  Import the JSON template** into your automation platform.

  🧩 Detailed Flow Architecture

  1. Telegram Trigger



  Node: Telegram Trigger  
  This node listens to all Message events received by the specified bot (e.g., “BOT OFFICIEL BAPTISTE”).  
  Whenever a user sends a voice message, the trigger fires automatically.

  &gt; ⚠️ Only one Telegram trigger per bot is possible (API limitation).

  Key parameter:  
  Trigger On: Message

  2. Wait

  Node: Wait  
  Used to buffer or smooth out calls to avoid collisions if you receive several voice messages in a row.

  3. Retrieve the Audio File



  Node: Get a file  
  Type:** Telegram (resource: file)
  Parameter:**  
    fileId = {{$json"message"["file_id"]}}  
  This node fetches the voice file from Telegram received in step 1

  4. Automatic Transcription (Whisper)



  Node: Transcribe a recording  
  Resource:** audio  
  Operation:** transcribe  
  API Key:** Your OpenAI account  
  The audio file is sent to OpenAI Whisper: the output is clean, accurate text ready to be processed.

  5. Optional Wait (Wait1)

  Node: Wait1  
  Same purpose as step 2: useful if you want to buffer or add a delay to absorb processing time.

  6. Structured Email Generation (GPT-4 + Output Parser)

  Node: AI Agent  
  This is the core of the flow:

  The transcribed text is sent to GPT-4 (or GPT-4.1-mini here, via OpenAI Chat Model)
  Prompt used:**

          You are an assistant specialized in writing professional emails.

      Based on the text below, you must: {{ $json.text }}

      Detect if there is a recipient's email address in the text (or something similar like "send to fort.baptiste.pro")
         If it’s not a complete address, complete it by assuming it ends with @gmail.com.
      Understand the user's intent (resignation, refusal, application, excuse, request, etc.)
      Generate a relevant and concise email subject, faithful to the content
      Write a professional message, structured in HTML:
         With a polite tone, adapted to the situation
         Formatted with HTML tags (`, `, etc.)
         No spelling mistakes in French
         My first name is jeremy and if the text says he is not happy, specify the wish to resign

  ⚠️ You must always return your answer in the following strict JSON format, with no extra text:
      
          {
        "email": "adresse@gmail.com",
        "subject": "Objet de l’email",
        "body": "Contenu HTML de l’email"
      }
      
  Everything is strictly validated and formatted with the Structured Output Parser node.

  7. Automatic Email Sending (Gmail)

  Node: Send a message  
  To:** {{$json.output.email}}
  Subject:** {{$json.output.subject}}
  HTML Body:** {{$json.output.body}}  
  This node takes the JSON structure returned by the AI and sends the email via Gmail, to the right recipient, with the correct subject and full HTML formatting.

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