# templates

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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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, 40660 characters]

metadata_json:
  {"categories":["automation","integration","field reporting","data collection"],"complexity":"complex","use_cases":["Send daily task lists to field workers via Telegram","Collect photo reports and status replies from field staff","Log photos, statuses and timestamps into Google Sheets","Maintain report history and track task completion","Eliminate paper reporting and streamline back-office updates"],"estimated_setup_minutes":20,"required_services":["n8n","Telegram (create bot via BotFather)","Google Sheets (Google account)","Google Drive"],"key_features":["Dispatch daily tasks to workers via Telegram","Receive and auto-save photo reports and text replies","Write entries (photos, status, timestamps) to a Google Sheet","Track task completion and maintain historical reports","Preconfigured task templates and sticky-note setup instructions in workflow"],"target_audience":["Construction project managers","Field/site supervisors and workers","Engineering and consulting firms implementing site reporting automations','Operations teams responsible for daily reporting"]}


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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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]

metadata_json:
  {"categories":["automation","integration","data processing","HR/recruiting","AI-powered screening"],"complexity":"medium","use_cases":["Bulk resume parsing and shortlisting","Job description to candidate fit scoring","Automated candidate communication (email/Slack)","Maintaining auditable evaluation logs in Sheets","Integrating ATS or job boards via webhooks"],"estimated_setup_minutes":45,"required_services":["n8n (self‑hosted or cloud)","OpenAI GPT‑4 API (or alternative LLM)","Google Drive","Google Sheets","Slack (bot/token)","SendGrid or SMTP (optional for emails)"],"key_features":["Bulk upload of CVs to Google Drive","GPT‑4 parsing to extract structured candidate profiles","Retrieve and parse JD from Sheets/Drive","Generate fit score, strengths, gaps, and recommendation","Append structured results to evaluation Google Sheet (audit trail)」「Optional Slack notifications to hiring team and email triggers to candidates」「Configurable fit threshold and message templates」「Supports swapping LLM providers and webhook/ATS integration"],"target_audience":["HR / Talent Acquisition teams","Recruiters","Hiring managers coordinating candidate evaluation workflows」「HR operations / automation engineers"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
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"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","personal finance"],"complexity":"medium","use_cases":["Automated expense tracking from receipt photos via OCR","Manual income/expense entry through Telegram text commands","Populating and maintaining a Google Sheets financial ledger","Customizing parsing logic to handle different receipt formats","Receiving instant confirmations of logged transactions in Telegram"],"estimated_setup_minutes":15,"required_services":["n8n (self-hosted or cloud)","Telegram Bot API (Telegram bot token)","OCR.space API (free API key)","Google Sheets (Google account and Sheet ID)"],"key_features":["OCR-based extraction of amount, date, and description from receipt photos","Telegram bot interface for photo and text command input","Automatic appending of parsed transactions to Google Sheets","Fallback/manual entry via simple text commands","Customizable parsing logic via a Function node for different receipt formats"],"target_audience":["Individuals tracking personal finances","Automation enthusiasts and n8n users","Freelancers or small-business owners who log expenses manually or via receipts"]}


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 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
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"]

workflow_json_compressed:
  [encoded data, 10308 characters]

metadata_json:
  {"categories":["automation","integration","IT support","AI-assisted support","ticketing"],"complexity":"complex","use_cases":["Automatically convert incoming support emails into Jira issues","AI-assisted triage and suggested resolutions for IT requests","Notify IT teams via Slack when new tickets are created","Prevent duplicate ticket creation from repeated emails","Optional automated acknowledgements to requesters via email"],"estimated_setup_minutes":60,"required_services":["Gmail (API access)","OpenAI (GPT-4 or GPT-3.5 API)","Jira (project with create/comment permissions)","Slack (webhook or OAuth)","SendGrid (optional, for requester email acknowledgements)","n8n instance with required credentials configured"],"key_features":["Gmail trigger + full email fetch and deduplication","LLM-powered reader agent to extract structured request fields","Creates main Jira issue from extracted data","LLM-powered advisor agent that generates suggested resolutions","Posts AI suggestions as Jira comments and notifies Slack channel(s))"],"target_audience":["lean IT teams","helpdesk managers","office managers and business operators handling support requests"]}


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 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
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:
  [encoded data, 4568 characters]

metadata_json:
  {"categories":["automation","lead generation","integration","monitoring"],"complexity":"medium","use_cases":["Automated prospecting from Reddit","Lead enrichment and qualification","Market/customer discovery","Daily lead digest for outreach teams","Monitoring niche communities for opportunities"],"estimated_setup_minutes":45,"required_services":["Reddit API","OpenAI (GPT-4 / Chat API)","Supabase","Google Sheets (Google API)","Gmail (Google API)","n8n instance"],"key_features":["Targeted subreddit keyword search","AI-powered relevance scoring (yes/no)","Duplicate filtering via Supabase","Content quality filters (body text, upvotes)","Save qualified leads to Google Sheets with metadata (URL, subreddit, timestamp)"],"target_audience":["SDRs / Sales teams","Growth marketers","Founders / Product teams doing customer discovery"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
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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metadata_json:
  {"categories":["automation","social media","integration"],"complexity":"complex","use_cases":["Automated Instagram engagement (auto-liking)","Hashtag discovery and targeting","Hands-free account activity scheduling","Duplicate prevention for engagements","Rate-limited, multi-session cookie rotation"],"estimated_setup_minutes":30,"required_services":["Phantombuster (Growth plan with API access)","OpenAI API (GPT-4o)","Microsoft 365 SharePoint (OAuth2)","Instagram account(s) with session cookies","n8n (v1.33+)"],"key_features":["Scheduled trigger (every 2 hours) to launch jobs","Rotating Instagram session-cookie selection (time-sliced)","GPT-4o generates realistic/targeted hashtags","Phantombuster scrapes recent hashtag posts (ENV_MAX_POSTS_PER_HASHTAG)","Random post selection with duplicate check (SharePoint CSV) before liking','Builds/uploads instagram_posts_to_like.csv to SharePoint and launches Auto-like Agent','Appends liked post URLs to instagram_posts_already_liked.csv to avoid repeats','Throttling/wait nodes to limit likes (~12 per profile/day) and configurable ENV variables"],"target_audience":["Social media managers","Brands and marketing teams","Growth hackers and community managers\",\"Digital marketing agencies\",\"Automation engineers/implementers"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
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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metadata_json:
  {"categories":["social media automation","integration","growth hacking","data processing","scheduling"],"complexity":"complex","use_cases":["Automatically follow relevant Instagram profiles to grow audience","Scale outreach using seed profile lists","Process CSV seed lists from SharePoint and act on followers","Enforce rate limits to stay within platform limits","Adapt workflow to scrape hashtags or other profile sources"],"estimated_setup_minutes":30,"required_services":["Phantombuster API (Growth plan with API access)","Microsoft 365 SharePoint tenant","Instagram session cookies (session-cookie file)","n8n >= 1.33","Optional: OpenAI API (if using AI nodes)"],"key_features":["Hourly scheduled trigger with configurable minute slice","Rotating Instagram session-cookie selection (time-slice logic)","Downloads seed profile CSV from SharePoint","Phantombuster Follower Collector agent to fetch followers","Autofollow agent to follow selected profiles with ENV-controlled limits (ENV_PROFILES_TO_PROCESS, ENV_AMOUNT_FOLLOWERS_PER_PROFILE)"],"target_audience":["Community managers","Growth hackers","Brands and social media teams looking to scale Instagram growth safely under rate limits\",\"Automation/ops engineers integrating Phantombuster and SharePoint"]}


name: Generate Tailored Interview Questions with GPT-4 Based on CV, JD, and Round
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-01T08:29:51.767Z
updated_at: 2025-08-01T08:29:51.767Z
url: https://n8n.io/workflows/6767
scraped_at: 2025-09-29 22:37:33
metadata_generated_at: 2025-09-30 08:33:37
description:
  🤖 Smart Interview Assistant: Tailored Questions Based on CV, JD, and Round
  Watch the demo video below:

  📌 Who’s it for
  This workflow is designed for:
  Recruiters* and *Talent Acquisition Specialists** who want to automate candidate interview prep.
  Hiring Managers** conducting multiple interviews and needing personalized question sets.
  Technical Interviewers** who want to save time and be well-prepared with relevant questions.

  ⚙️ How it works / What it does
  The Smart Interview Assistant automates the interview preparation process in a few clicks:

  Accepts:
     Multiple resumes (PDFs)
     Selected job role
     Chosen interview round
  Extracts structured data from:
     The candidate’s CV
     The corresponding Job Description (JD)
  Uses GPT-4 to analyze:
     Candidate profile
     Role requirements
     Interview round context
  Generates:
     Tailored interview questions
     Expected answers
     A summarized interview prep report
  Sends the report directly to the hiring team via email (SMTP)

  📁 Google Drive Structure

  📂 Root Folder
  ├── 📁 jd/                          # Stores all job descriptions in PDF format
  │   ├── Backend_Engineer.pdf
  │   ├── Azure_DevOps_Lead.pdf
  │   └── ...
  └── 📄 Positions (Google Sheet)    # Maps Job Role ↔ JD File Link

  📝 Sample Mapping Sheet:  
  Positions Sheet

  Columns:
  Job Role
  Job Description File URL (pointing to PDF in jd/ folder)

  🛠️ How to Set Up

  Step 1: Configure API Integrations
  ✅ Connect your OpenAI GPT-4 API Key
  ✅ Enable Google Cloud APIs:
    Google Sheets API (to read job roles)
    Google Drive API (to access CV and JD files)
  ✅ Set up SMTP credentials (for email delivery)

  Step 2: Prepare Google Drive & Mapping Sheet

  Create a root folder on Google Drive  
  Inside the root folder:
     Create a folder named /jd/ and upload all job descriptions (PDFs)  
  Create a Google Sheet named Positions with the following format:

  | Job Role                     | Job Description File URL                   |
  |-----------------------------|--------------------------------------------|
  | Azure DevOps Engineer        | https://drive.google.com/xxx/jd1.pdf       |
  | Full-Stack Developer (.NET)  | https://drive.google.com/xxx/jd2.pdf       |

  Step 3: Build the Application Form

  Use any form tool (e.g., Typeform, Tally, or custom HTML) that collects:
  📎 Resume file (PDF)
  🧾 Job Role (dropdown)
  🔄 Interview Round (dropdown)

  Step 4: Resume & JD Extraction

  🔍 Use Extract from PDF to parse the resume content
  📄 Retrieve the JD link from the Positions sheet based on the selected Job Role
  🔗 Use Download file to pull the PDF for processing

  Step 5: Analyze with GPT-4

  Run both Resume and JD through a Profile Analyzer Agent (GPT-4 with JSON output)
  Merge results
  Add manual input or mapping for the Interview Round metadata

  Step 6: Generate Interview Report

  Use a second GPT-4 agent (e.g., HR Expert Agent) to:
    Generate 6–8 tailored interview questions
    Include expected answers and rationale

  Step 7: Deliver Final Report

  Format the content as:
    📄 PDF (optional)
    📨 Email body
  Send the report to the recruiter, hiring manager, or interviewer via SMTP

  ✅ Requirements

  🔑 OpenAI GPT-4 API Key
  📁 Google Drive (for resume and JD storage)
  📊 Google Sheet (job role mapping)
  📬 SMTP credentials (host, username, password)
  🧰 n8n self-hosted or cloud instance with:
    PDF Parser
    Google Sheets node
    HTTP Download node
    Email node

  ✏️ How to Customize the Workflow

  | Part                        | Customization Options                                      |
  |----------------------------|-------------------------------------------------------------|
  | Form UI                | Modify the design, dropdown options, or input validations   |
  | Job Description Source | Replace Google Sheet with Notion, Airtable, or database     |
  | Interview Metadata     | Add job level, region, or language preference               |
  | AI Prompt Tuning       | Adjust prompt phrasing or temperature in GPT nodes          |
  | Report Format          | Generate PDF instead of email body using PDF node           |
  | Delivery Method        | Add internal HR portal webhook or generate downloadable link |

nodes_used:
  ["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/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.code","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","recruitment","hr","ai-assistant","productivity"],"complexity":"medium","use_cases":["Generate tailored interview questions from candidate CV and job description","Automate interview preparation for different interview rounds (screening, technical, final)","Standardize interviewer question sets across hiring teams","Save time for recruiters and hiring managers by producing role- and round-specific prompts","Store and log generated questions to spreadsheets or Google Drive"],"estimated_setup_minutes":30,"required_services":["OpenAI GPT-4 (or compatible AI/ML provider)","Google Drive","Google Sheets / Spreadsheets node (n8n)","File parsing (CV/JD) - extractFromFile capability (PDF/DOCX)"],"key_features":["Parses CV and job description to extract relevant skills and experience","Considers interview round to tailor question difficulty and focus","Generates structured, role-specific interview questions via GPT-4","Outputs and formats results for spreadsheets or Google Drive storage","Includes form/input node to capture job/round parameters and merge data sources"],"target_audience":["Recruiters","Talent acquisition specialists","Hiring managers conducting multiple interviews rapidly and consistently」「Technical interviewers seeking focused, role-specific questions"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
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.

nodes_used:
  ["n8n-nodes-base.wait","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.wait","n8n-nodes-base.phantombuster","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.microsoftSharePoint","n8n-nodes-base.phantombuster","n8n-nodes-base.phantombuster","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.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-nodes-base.microsoftSharePoint","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","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:
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metadata_json:
  {"categories":["automation","social media","integration"],"complexity":"complex","use_cases":["Automated engagement (auto-comments)","Hashtag-based post discovery and targeting","Scaling social growth and outreach","Maintaining deduplicated interaction logs"],"estimated_setup_minutes":30,"required_services":["n8n v1.33+","Phantombuster (Growth plan with API access)","OpenAI account (GPT-4o)","Microsoft 365 SharePoint tenant (OAuth2)","Instagram session cookies (one per line)"],"key_features":["Scheduled trigger (every 2 hours)","Rotating Instagram session-cookie selection","Generate realistic hashtags with GPT-4o","Scrape recent posts by hashtag via Phantombuster","Pick random post and create ≤150-char comment with GPT-4o in chosen language"],"target_audience":["Social-media teams","Influencers","Growth marketers/agencies"]}


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 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
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"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","accounting","data processing"],"complexity":"medium","use_cases":["Automate sales entry from Google Sheets to QuickBooks Online","Auto-create customer records when missing","Generate Sales Receipts linked to customers","Eliminate manual data entry for bookkeeping","Sync spreadsheet-based order capture with accounting"],"estimated_setup_minutes":20,"required_services":["n8n instance","Google Sheets (Google account)","QuickBooks Online account","QuickBooks Developer credentials (API)","At least one Product/Service item in QuickBooks"],"key_features":["Triggers on new Google Sheet row","Searches QuickBooks for existing customer by DisplayName","Conditional branch to create customer if not found","Creates Sales Receipt for existing or newly created customer","Requires mapping of Product/Service ID for receipt line items"],"target_audience":["small business owners","bookkeepers and accountants","operations teams handling orders/invoices people who manage spreadsheets and accounting integrations, automation engineers"]}


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 19:10:59
metadata_generated_at: 2025-09-30 08:33:37
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:
  [encoded data, 4632 characters]

metadata_json:
  {"categories":["automation","integration","chatbots","ai/ml","data processing"],"complexity":"complex","use_cases":["WhatsApp-based knowledge assistant for FAQs","Customer support and ticket triage over WhatsApp","Internal company document Q&A (policies, SOPs, onboarding)","Semantic search + conversational retrieval (RAG) over documents"],"estimated_setup_minutes":45,"required_services":["n8n","WhatsApp Business API (or provider like Twilio)","Supabase (vector store/Postgres + vector extension)","OpenAI API (for embeddings)","Google Gemini 2.5 Flash (Vertex AI or Gemini endpoint)","Public webhook endpoint / hosting (or ngrok during testing)"],"key_features":["WhatsApp inbound/outbound messaging integration","Retrieval-Augmented Generation (RAG) using Supabase vector store","OpenAI embeddings for semantic document search","Gemini 2.5 Flash for high-quality LLM replies","Document loader and vector upsert for knowledge ingestion workflow nodes included in template (documentDefaultDataLoader, vectorStoreSupabase nodes, etc.)"],"target_audience":["developers","no-code/low-code builders","customer support teams, knowledge managers"]}


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 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
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"]

workflow_json_compressed:
  [encoded data, 5652 characters]

metadata_json:
  {"categories":["automation","integration","developer workflow","project management"],"complexity":"medium","use_cases":["Automatically create GitHub pull requests from commit messages","Update JIRA issue status from commit commands","Keep code changes and project tracking in sync","Enforce commit-driven workflow transitions"],"estimated_setup_minutes":20,"required_services":["n8n instance","GitHub (repo with webhook permission)","JIRA Cloud (API access)"],"key_features":["GitHub push webhook trigger","Parses commit messages for JIRA key, base branch, and action commands","Conditional auto PR creation","Conditional JIRA issue transition (e.g., Done/In Review)","Configurable JIRA transition and GitHub credentials"],"target_audience":["Developers","DevOps engineers","Engineering managers/project leads"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
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

nodes_used:
  ["n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.merge","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","@gotohuman/n8n-nodes-gotohuman.gotoHuman","n8n-nodes-base.filter","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","social media","content creation","marketing automation"],"complexity":"medium","use_cases":["Automated LinkedIn post generation","AI-assisted caption writing","Human-in-the-loop content approval","Scheduled social publishing","Content workflow orchestration"],"estimated_setup_minutes":45,"required_services":["n8n instance","Google Sheets (OAuth2)","OpenAI (GPT-4 API key)","GoToHuman (review template & API key)","Blotato (API key & Account ID)"],"key_features":["Selects today's topic from Google Sheets","Generates emoji-rich LinkedIn captions with GPT-4","Sends captions for human approval via GoToHuman","Automatically publishes approved posts to LinkedIn via Blotato","Saves generated captions back to the sheet for tracking and auditability"],"target_audience":["Creators","Marketers","Agencies and social media teams」「Automation engineers and ops teams"]}


name: AI-Powered CV Extractor: Google Drive to Sheet with GPT-4 + Slack for Recruiters
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T05:56:38.102Z
updated_at: 2025-08-02T05:56:38.102Z
url: https://n8n.io/workflows/6835
scraped_at: 2025-09-29 22:37:33
metadata_generated_at: 2025-09-30 08:33:37
description:
  CV Extractor: Google Drive to Sheet + Slack Update for Recruiters
  Watch the demo video below:

  &gt; This workflow automatically processes resumes (PDFs) uploaded or updated in a Google Drive folder. It extracts and structures the candidate’s information using AI, then updates or inserts the data into a Google Sheet, acting as a central talent database. Finally, it notifies the hiring team via Slack with a summary. Perfect for HR and TA teams, this automation eliminates the repetitive task of manually copying candidate details from CVs into spreadsheets, saving hours of admin work every week and keeping your hiring pipeline clean, fast, and up to date.
  👤 Who’s it for
  This workflow is designed for:
  Recruiters* and *HR coordinators** who manage candidate profiles via Google Drive.
  Talent Acquisition teams** who want to automate CV parsing, enrichment, and database updating.
  Companies or hiring agencies** using spreadsheets for candidate tracking and CRM-like HR ops.
  ⚙️ How it works / What it does
  This smart and fully automated workflow:
  Monitors a Google Drive folder for any uploaded or updated resumes (PDFs).
  Downloads and extracts resume content using PDF parsing.
  Sends the raw text to GPT-4, which returns a structured profile (name, title, experience, skills, etc.).
  Verifies the profile and transforms it into a clean, row-based format.
  Upserts the candidate profile into a Google Sheet (insert or update by email).
  Notifies the hiring team in Slack or email that a profile was added or updated.

  This is a no-touch pipeline to keep your candidate data clean, current, and centralized.
  🛠️ How to set up
  Step 1: Prepare your Google Drive folder
  Create a folder like /SmartHR/cv/
  Upload sample resumes in .pdf format

  Step 2: Create your Google Sheet
  Columns to include: Email, FullName, JobTitle, Phone, Location, Experience, Education, Skills, etc.
  Optional: Add conditional formatting to highlight updates

  Step 3: Connect the n8n workflow
  Use the Google Drive Trigger:
    fileCreated → new profile uploaded
    fileUpdated → existing profile modified
  Use Google Drive (Download file) to fetch the resume
  Use Extract From PDF to get raw content

  Step 4: Configure GPT-4 node
  Use the structured system prompt to extract profile information
  Use json parser node to ensure safe formatting for next steps

  Step 5: Transform & Save
  Use a Function node to map fields to Google Sheet columns
  Use Append or update row (based on email as unique key)
  Optionally send Slack or email message to notify hiring team

  ✅ Requirements

  🔑 OpenAI GPT-4 API key
  🟩 n8n Cloud or Self-hosted with:
    Google Drive integration
    Google Sheets integration
    Email/Slack credentials (optional)
  📄 Resume files in readable PDF format
  📊 Google Sheet prepared with relevant headers

  ✏️ How to customize the workflow

  | Part                        | Customization Options                                                                 |
  |----------------------------|----------------------------------------------------------------------------------------|
  | GPT Prompt             | Tune for different job levels or fields (e.g., engineers vs marketers)                |
  | Field Mapping          | Update transform node to include other profile fields (LinkedIn, portfolio, etc.)     |
  | Notification           | Switch to Microsoft Teams, Telegram, or email alerts instead of Slack                 |
  | Data Store             | Replace Google Sheet with Airtable, Notion, or database system                        |
  | Trigger Source         | Trigger from email attachments or webhook instead of Google Drive if needed           |
  | Output Format          | Generate PDF profile cards or summary documents using HTML → PDF node                 |

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

workflow_json_compressed:
  [encoded data, 8220 characters]

metadata_json:
  {"categories":["automation","recruitment","human resources","ai-integration","data-integration"],"complexity":"medium","use_cases":["Automated resume ingestion from Google Drive","AI extraction and structuring of candidate data","Maintaining a central candidate database in Google Sheets","Notifying hiring teams via Slack with candidate summaries","Reducing manual CV screening and data entry"],"estimated_setup_minutes":30,"required_services":["Google Drive","Google Sheets","OpenAI (GPT-4) or other AI/ML provider","Slack"],"key_features":["Watches a Google Drive folder for new/updated PDF resumes","Extracts structured candidate information using GPT-4","Parses AI output into a consistent schema (outputParserStructured)","Updates or inserts rows in a Google Sheet talent database","Sends Slack notifications to hiring team with candidate summary and link to CV/file"],"target_audience":["Recruiters","Talent acquisition teams","HR operations (TA ops) professionals in SMBs and enterprises looking to automate hiring workflows"]}


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 19:11:00
metadata_generated_at: 2025-09-30 08:33:37
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.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.filter","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","data extraction","integration","AI/ML"],"complexity":"medium","use_cases":["Extract contact details from business card photos","Automate contact entry into Google Sheets","Collect contacts at events or trade shows","Help recruiters and sales teams capture leads without manual typing"],"estimated_setup_minutes":20,"required_services":["OpenAI (GPT4o) or compatible AI API","Google Sheets (Google account & Sheets API access)","Google Drive (for storing uploaded images)"],"key_features":["Image-to-structured-contact extraction using GPT4o","Form-based photo upload and Google Drive storage","Structured output parsing to map fields (name, phone, email, company, title, notes)","Automatic write/update of contacts into Google Sheets","Filter and code nodes for validation/formatting of extracted data"],"target_audience":["Sales & Business Development teams","Recruiters & Talent Acquisition specialists","Event teams collecting business cards or leads collection staffers/volunteers instead of manual entry\",\"Administrative staff managing contact databases"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:34
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!

nodes_used:
  ["n8n-nodes-base.gmail","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.httpRequestTool","n8n-nodes-base.gmail","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","content_aggregation","summarization","email/newsletter"],"complexity":"medium","use_cases":["Weekly industry briefings for film journalists","Automated newsletters for entertainment bloggers","Personal weekly movie updates for enthusiasts","PR/media monitoring for studios and publicists","Programming/promotions teams tracking releases and box office"],"estimated_setup_minutes":20,"required_services":["Tavily API","Google Gemini API (Google Cloud)","Gmail (OAuth2 for sending emails)"],"key_features":["Scheduled weekly trigger (configurable)","Four Tavily real-time searches: releases, last week box office, industry news, must-watch in theatres","Google Gemini summarization into Gmail-friendly HTML with emojis and bullets","Email delivery via Gmail node","Configurable Tavily queries (genres, filters) and schedule in n8n; optional swap to OpenAI models"],"target_audience":["Film journalists","Entertainment bloggers","Movie enthusiasts and consumers of film news"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.memoryPostgresChat","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.noOp","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.splitOut","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","devops","ai-assistant"],"complexity":"medium","use_cases":["Interactive chat-based DNS management (list/create/update/delete records)","Automating DNS changes from CI/CD or deployment pipelines","Delegating routine DNS operations to an AI assistant","Persisting and auditing chat-driven DNS actions (optional Postgres)","Integrating DNS management into larger infrastructure workflows"],"estimated_setup_minutes":30,"required_services":["Cloudflare API token/key","LLM provider (e.g., OpenAI API) or OpenAPI-compatible provider","n8n instance","(Optional) Postgres database for chat history"],"key_features":["AI chat agent with prompt-driven getter/setter for DNS records","Tool sub-workflow (cf_tool) that maps actions to Cloudflare API endpoints","Create, read, update, delete DNS records via Cloudflare API","Optional chat history persistence in Postgres","Switching/routing logic and webhook/HTTP nodes for integration into pipelines"],"target_audience":["DevOps engineers","Site Reliability Engineers (SREs)","Developers managing infrastructure or DNS records','Automation/Infrastructure engineers"]}


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 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
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.

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

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metadata_json:
  {"categories":["automation","media generation","AI/ML","content creation","integration"],"complexity":"medium","use_cases":["Generate short animated human videos from a single image and audio","Create personalized video messages (marketing or onboarding)","Produce social media clips and ads","Rapid prototyping of character animation for games/apps","E-learning or explainer video generation"],"estimated_setup_minutes":15,"required_services":["Replicate API (Bytedance/omni-human model)","n8n (self‑hosted or cloud)","Publicly accessible hosting for input image and audio (CDN / storage)","Optional: Slack, Gmail, Google Drive or other delivery integrations for distribution"],"key_features":["Accepts image + audio inputs to initiate video generation","Secure storage/use of Replicate API key in workflow","Creates prediction request to Replicate and polls status until completion","Wait/retry loop to avoid API spamming","Parses and returns structured JSON including video_url, status, metrics, timestamps, and model info (bytedance/omni-human)"],"target_audience":["Developers and automation engineers","Content creators and marketers","Product teams and indie game developers prototyping characters or cutscenes\",\"E‑learning creators and agencies"]}


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 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
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.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.compression","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["data processing","integration","automation","developer tools"],"complexity":"medium","use_cases":["Batch-encode multiple binary files to Base64 for API uploads","Convert files inside a ZIP to Base64 for integrations","Preprocess multiple attachments before sending to a service","Automate file-format transformations in workflows"],"estimated_setup_minutes":15,"required_services":["n8n instance","HTTP/HTTPS file host (e.g., public URL, S3, file server)","Target API that accepts Base64-encoded file payloads (optional for end-to-end testing)"],"key_features":["Downloads a ZIP or binary file via HTTP","Unzips archive to extract multiple binary files","Uses a Code node to convert each binary file to a Base64 string","Produces per-file Base64 outputs suitable for API requests","Easy to customize output format and file paths"],"target_audience":["Developers","Integration engineers","Automation specialists / DevOps engineers who build workflows that upload files to APIs"]}


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 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
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

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

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metadata_json:
  {"categories":["automation","AI/ML integration","audio processing"],"complexity":"medium","use_cases":["Generate synthetic audio/voiceovers from reference audio","Content creation for podcasts, videos, ads","Prototype audio features in apps (TTS/voice conversion)","Automated delivery/storage of generated audio"],"estimated_setup_minutes":10,"required_services":["Replicate API (notdaniel/voxtral-small-24b-2507)","Optional: cloud storage or CDN for hosting audio (S3, GCS)"],"key_features":["Secure API key authentication","Create prediction request to Replicate with configurable parameters (e.g., max_new_tokens)","Polling loop to wait for asynchronous prediction completion","Extraction and structuring of final output (status, output, metrics, timestamps, audio_url)","Manual trigger to run workflow on demand"],"target_audience":["Developers integrating audio generation APIs","Audio engineers/producers prototyping AI-generated audio","Content creators and marketers generating voiceovers or podcast assets"]}


name: Automated Trip Expense Claim Form With OpenAI Agent & Google Drive
author_name: Trung Tran
author_username: trungtran
categories: []
created_at: 2025-08-02T15:21:04.891Z
updated_at: 2025-08-02T15:21:04.891Z
url: https://n8n.io/workflows/6896
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  🧾 Automated Trip Expense Claim Form With OpenAI Agent & Google Drive
  Watch the demo video below:

  &gt; This workflow is designed for employees who need to submit expense claims for business trips. It automates the process of extracting data from receipts/invoices, logging it to a Google Sheet, and notifying the finance team via email.
  👤 Who’s it for
  Ideal users:
  Employees submitting business trip expense claims
  HR or Admins reviewing travel-related reimbursements
  Finance teams responsible for processing claims

  ⚙️ How it works / What it does

  Employee submits a form with trip information (name, department, purpose, dates) and uploads one or more receipts/invoices (PDF).
  Uploaded files are saved to Google Drive for record-keeping.
  Each PDF is passed to a DocClaim Assistant agent, which uses GPT-4o and a structured parser to extract structured invoice data.
  The data is transformed and formatted into a standard JSON structure.
  Two parallel paths are followed:
     Invoice records are appended to a Google Sheet for centralized tracking.
     A detailed HTML email summarizing the trip and expenses is generated and sent to the finance department for claim processing.

  🛠 How to set up

  Create a form to capture:
     Employee Name
     Department
     Trip Purpose
     From Date / To Date
     Receipt/Invoice File Upload (multiple PDFs)

  Configure file upload node to store files in a specific Google Drive folder.

  Set up DocClaim Agent using:
     GPT-4o or any LLM with document analysis capability
     Output parser for standardizing extracted receipt data (e.g., vendor, total, tax, date)

  Transform extracted data into a structured claim record (Code Node).

  Path 1: Save records to a Google Sheet (one row per expense).

  Path 2:
     Format the employee + claim data into a dynamic HTML email
     Use Send Email node to notify the finance department (e.g., finance@yourcompany.com)

  ✅ Requirements

  n8n running with access to:
    Google Drive API (for file uploads)
    Google Sheets API (for logging expenses)
    Email node (SMTP or Gmail for sending)
  GPT-4o or equivalent LLM with document parsing ability
  PDF invoices with clear formatting
  Shared Google Sheet for claim tracking
  Optional: Shared inbox for finance team

  🧩 How to customize the workflow

  Add approval steps**: route the email to a manager before finance
  Attach original PDFs**: include uploaded files in the email as attachments
  Localize for other languages**: adapt form labels, email content, or parser prompts
  Sync to ERP or accounting system**: replace Google Sheet with QuickBooks, Xero, etc.
  Set limits/validation**: enforce max claim per trip or required fields before submission
  Auto-tag expenses**: add categories (e.g., travel, accommodation) for better reporting

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.formTrigger","n8n-nodes-base.code","n8n-nodes-base.googleDrive","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.extractFromFile","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.googleSheets","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.emailSend","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi"]

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metadata_json:
  {"categories":["automation","document processing","finance","integration"],"complexity":"medium","use_cases":["Automate trip expense claims submission","Extract structured data from PDF receipts/invoices using LLM","Centralize expense records in Google Sheets","Notify finance via formatted HTML email","Pre-process claims for ERP/accounting sync"],"estimated_setup_minutes":45,"required_services":["n8n instance","Google Drive API","Google Sheets API","Email service (SMTP or Gmail)","LLM provider with document parsing (e.g., OpenAI GPT-4o)"],"key_features":["Form-based submission with multi-file PDF upload","Save uploaded receipts to Google Drive","LLM agent (DocClaim) extracts structured invoice data","Transform and standardize extracted data to JSON","Append expense rows to Google Sheet (central tracking) in parallel with email path\",\"Generate dynamic HTML email summarizing trip and expenses\",\"Send notification to finance team; optional attachments and approval routing"],"target_audience":["Employees submitting travel expenses","HR / Admins handling travel reimbursements","Finance teams processing claims and reconciliations\",\"IT/automation engineers implementing workflow integrations"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:32
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.

nodes_used:
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metadata_json:
  {"categories":["automation","finance","AI-assisted workflows","integration"],"complexity":"complex","use_cases":["Automated budgeting and forecasting","Cash flow modeling and treasury management","Financial reporting and KPI tracking","Accounting, tax prep and compliance checks","Investment analysis and risk assessments','Internal audit automation"],"estimated_setup_minutes":60,"required_services":["n8n instance","OpenAI API (O3 model for CFO + GPT-4.1-mini for specialist agents)","Optional: accounting/ERP systems (QuickBooks, Xero, NetSuite) or bank APIs for live financial data"],"key_features":["CFO (O3) orchestration + strategy delegation","Multiple specialist agents (GPT-4.1-mini) running in parallel","Think tool for brainstorming/refinement","Automated compilation of forecasts, reports and audit notes","Cost-optimized model usage and easy role scaling"],"target_audience":["CFOs and finance leaders","FP&A teams and financial analysts","Accounting firms and shared-services teams for automation pilots\",\"Startup founders and finance ops managers"]}


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 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
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.

nodes_used:
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metadata_json:
  {"categories":["automation","integration","data processing","AI/ML","revenue operations"],"complexity":"complex","use_cases":["Pipeline optimization and conversion improvement","Multi-touch revenue attribution and ROI analysis","Revenue forecasting and scenario planning","CRM automation and sales operations optimization","Pricing & packaging strategy development and testing','Revenue intelligence and KPI monitoring"],"estimated_setup_minutes":90,"required_services":["OpenAI (O3 for CRO + GPT-4.1-mini for specialists)","n8n","CRM (e.g., Salesforce, HubSpot) - optional","BI/dashboarding tools (e.g., Looker, Tableau, Power BI) - optional","Communication channels (Slack, Email) - optional","Data sources (databases, Google Sheets, CSVs) - optional"],"key_features":["CRO-led orchestration with advanced O3 reasoning","Specialist multi-agent architecture using GPT-4.1-mini","Parallel processing of domain-specific analyses","Feedback loop: agents report back to CRO for final synthesis","Outputs: pipeline health, attribution models, forecasts, pricing recommendations, ops improvements, BI-ready reports and dashboards integration options"],"target_audience":["Chief Revenue Officers / RevOps leaders","Revenue operations and sales operations teams","Growth marketers and analysts','Founders and executives seeking data-driven revenue strategy"]}


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 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
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:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.agentTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","SEO","content creation","analytics"],"complexity":"complex","use_cases":["End-to-end SEO campaign planning","Keyword research and clustering","Automated SEO content generation (blogs, landing pages)","Technical SEO audits and schema recommendations","Link building strategy and outreach planning\",\"Local SEO optimization and GMB setup"],"estimated_setup_minutes":45,"required_services":["n8n","OpenAI (O3 model + GPT-4.1-mini)","Website CMS (e.g., WordPress)","Google Analytics","Google Search Console","Google Business Profile (GMB) — for local SEO","SMTP/email provider (for outreach)","Optional SEO tools (Ahrefs, SEMrush, Moz)"],"key_features":["Director agent (O3) for strategy & orchestration","Multiple specialist agents (GPT-4.1-mini) for task execution","Parallel execution of specialists","Keyword research, clustering and competitor analysis","Automated SEO content creation (optimized posts/pages)"],"target_audience":["SEO agencies","Digital marketers","Content teams and writers implementing large-scale SEO content workflows」「Technical SEOs and consultants looking to automate audits and fixes"]}


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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
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 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
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 19:11:01
metadata_generated_at: 2025-09-30 08:33:37
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 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
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 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
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

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.slack","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.emailSend","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.slack","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","contract management","notifications","vendor management"],"complexity":"medium","use_cases":["Automated tracking of expiring vendor contracts","Slack-based reminders and approval workflows","Automated vendor outreach email generation","Distinguishing auto-renew vs manual renewals","Logging and audit trail for renewal actions"],"estimated_setup_minutes":45,"required_services":["Google Sheets API (or alternate data source)","Slack API","OpenAI API (GPT-4.1 mini)","Email service (Gmail/SMTP)","n8n (self‑hosted or cloud)"],"key_features":["Daily scheduler to scan contracts","Filter contracts by notice period and end date","Branching logic for auto-renew vs manual renewals","Slack notifications and send‑and‑wait approval flow","OpenAI-generated personalized Slack messages and HTML vendor emails」「Email sending to vendors to initiate renewals"],"target_audience":["Finance teams","Procurement teams","Vendor managers / contract owners」「Operations / administrative staff responsible for vendor relationships"]}


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 19:10:59
metadata_generated_at: 2025-09-14 21:18:33
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. 

nodes_used:
  ["n8n-nodes-base.microsoftOutlookTrigger","n8n-nodes-base.filter","n8n-nodes-base.splitOut","n8n-nodes-base.microsoftOneDrive","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.microsoftOneDrive"]

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metadata_json:
  {"categories":["automation","integration","file management","productivity"],"complexity":"medium","use_cases":["Automatically save email attachments to cloud storage","Organize attachments into per-email folders named by subject and timestamp","Automate intake of client submissions, invoices, receipts, or reports","Improve document traceability and reduce manual filing"],"estimated_setup_minutes":15,"required_services":["Microsoft Outlook (Office 365) account"],"key_features":["Monitors Outlook inbox for new emails","Filters to process only messages with binary attachments","Retrieves full message and downloads attachments","Creates OneDrive folders dynamically using email subject + timestamp","Splits and processes each attachment individually before upload to OneDrive"],"target_audience":["business users","office administrators","accountants/finance teams handling invoices and receipts on email intake"]}


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 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
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.

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

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metadata_json:
  {"categories":["automation","AI/ML integration","content generation"],"complexity":"medium","use_cases":["On-demand AI content generation from prompts","Integrating model outputs into apps/dashboards/notifications","Automating long-running model jobs with polling","Testing and iterating prompts with reproducible seeds"],"estimated_setup_minutes":15,"required_services":["Replicate API (moicarmonas/2ndmoises_generator model)","n8n"],"key_features":["Manual trigger for on-demand runs","Secure API key storage via Set node","Start prediction request to Replicate","Extract Prediction ID and status via code node","Automated polling with Wait + HTTP nodes until completion','Conditional routing (If node) to loop or proceed"],"target_audience":["Developers","Automation engineers","Data scientists/ML engineers experimenting with models','Content creators/marketers who use AI-generated outputs"]}


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 19:11:01
metadata_generated_at: 2025-09-14 21:18:33
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!

nodes_used:
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metadata_json:
  {"categories":["automation","backup","integration","devops"],"complexity":"medium","use_cases":["Scheduled backup of n8n workflows to a secondary instance","Versioned workflow archiving for audit and rollback","Rolling retention of workflow versions","Centralized tracking of backup runs and counts in Notion","Migration or cloning of workflows between n8n instances"],"estimated_setup_minutes":30,"required_services":["n8n (source instance with API access / API key)","n8n (destination instance with API access / API key)","Notion (database and API integration for tracking)"],"key_features":["Copies workflows from a source n8n instance to a destination via n8n API","Prefixes copied workflow names with date (YYYY_MM_DD_) to keep multiple versions","Records execution date and number of workflows processed in Notion","Configurable rolling retention (delete older dated sets) via date subtraction node","Supports test runs via limit node and configurable retention window"],"target_audience":["n8n users and administrators","Automation engineers","SREs / DevOps teams managing n8n instances"]}


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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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

nodes_used:
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metadata_json:
  {"categories":["automation","integration","notifications","productivity"],"complexity":"simple","use_cases":["Daily meeting/event summaries","Automated schedule reminders via Telegram","Keeping remote workers/teams informed of daily agenda","Reducing missed meetings and manual checking of calendar","Personal productivity / morning briefing"],"estimated_setup_minutes":10,"required_services":["Google Calendar (Google account)","Telegram account","n8n instance"],"key_features":["Daily scheduled trigger (7:00 AM)","Fetches events from Google Calendar for the day","Conditional handling when there are no events","Formats a human-readable summary of events","Sends summary messages via Telegram bot/user chat entry point (no-event message supported)"],"target_audience":["individuals who use Google Calendar","professionals and managers","remote workers and team leads who need daily briefings on schedule details (meetings, events)"]}


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 19:11:02
metadata_generated_at: 2025-09-14 21:18:34
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 19:11:00
metadata_generated_at: 2025-09-14 21:18:33
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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metadata_json:
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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 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
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! ✨

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.if","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, 5076 characters]

metadata_json:
  {"categories":["automation","integration","AI/ML","content generation"],"complexity":"medium","use_cases":["On-demand AI text generation (marketing copy, blog drafts, product descriptions)","Automated content pipelines feeding Sheets/Notion/CRM/Slack","Prototyping prompts and model parameters (temperature, max_tokens, top_k, top_p)","Batch or repeated generation using polling for async model jobs"],"estimated_setup_minutes":10,"required_services":["n8n (self-hosted or cloud)","Replicate API (access to ibm-granite/granite-3.3-8b-instruct model)","Optional: Google Sheets, Notion, Slack, Email or other destination apps for output"],"key_features":["Manual trigger for ad-hoc testing","Secure storage of Replicate API key in a Set node (no hardcoding)","Creates asynchronous prediction job via Replicate API","Polling loop (Wait + If) to check job status until completion","Processing node to extract structured JSON output, metrics, and timestamps for downstream use"],"target_audience":["No-code builders using n8n","Content creators and marketers","Product managers and growth teams automating copy generation workflows, and analysts integrating AI outputs into apps and databases"]}


