Workflow Templates

Automated Invoice Collection & Data Extraction Using Vision API and LLM This workflow automates the process of collecting uploaded invoices, extracting text using Google Vision API, and processing the extracted text with an LLM to produce structured data containing key transaction details such as date, voucher number, transaction detail, vendor, and transaction value. The final data is saved to Google Sheets and a notification is sent to Telegram in real time. ✨ Key Features Invoice Upload Form** Users can upload invoice images through a provided form. Google Drive Integration** Files are stored in a specified Google Drive folder with a shareable preview link. OCR via Google Vision API** Converts invoice images to text using TEXT_DETECTION. Data Structuring via LLM** Uses LLM model to parse and structure data. Structured Output Parser** Ensures consistent output with required columns. Data Cleaning** Cleans and formats numeric values without currency symbols. Google Sheets Sync** Appends or updates transaction data in Google Sheets (matched by file ID). Template: Google Sheets Telegram Notification** Sends a transaction summary directly to a Telegram chat/group. 🔐 Required Credentials Google Vision API Key** → for OCR processing. OpenRouter API Key** → to access the Gemini Flash LLM. Google Drive OAuth2** → to upload and download invoice files. Google Sheets OAuth2** → to write or update spreadsheet data. Telegram Bot Token** → to send notifications to Telegram. Telegram Chat ID** → target chat/group for notifications. 🎁 Benefits Fully automated** from invoice upload to structured reporting. Time-saving** by eliminating manual transaction data entry. Real-time integration** with Google Sheets for reporting and auditing. Instant notifications** via Telegram for quick transaction monitoring. Duplicate prevention** using file ID as a matching key. Flexible** for accounting, finance, or administrative teams.

Description Who's it for: Content creators, marketers, and businesses who publish on both YouTube and blog platforms. What it does: Monitors your YouTube channel for new videos and automatically creates SEO-optimized blog posts using AI, then publishes to WordPress or Webflow. How it works: RSS Feed Trigger polls YouTube videos (every X amount of time) Extracts video metadata (title, description, thumbnail) YouTube node extracts full description for extra context Uses OpenAI (you can choose any model) to generate 600-800 word blog post Publishes to WordPress AND/OR Webflow with error handling Sends notifications to Telegram if publishing fails Requirements: YouTube channel ID (avoid tutorial channels for better results) OpenAI API key (or similar) WordPress OR Webflow credentials Telegram bot (optional, for error notifications) Setup steps: Replace YOUR_CHANNEL_ID in RSS Feed Trigger Add OpenAI credentials in AI generation node Configure WordPress and/or Webflow credentials Add Telegram bot for error notifications (optional). If you choose to set up Telegram, you need to input your channel ID. Test with manual execution first Customization: Modify AI prompt for different content styles Adjust polling frequency (30-60 minutes recommended) Add more CMS platforms Add content verification (is content larger than 600 characters? if not, improve)

🧠 Automated Resume & Cover Letter Generator This project is an automation workflow that generates a personalized resume and cover letter for each job listing. 🚀 Features Automated Resume Crafting Generates an HTML resume from your data. Hosts it live on GitHub Pages. Converts it to PDF using Gotenberg and saves it to Google Drive. Automated Cover Letter Generation Uses an LLM to create a tailored cover letter for each job listing. Simple Input Database Agent Stores your experience in an n8n Data Table with the following fields: role, summary, task, skills, tools, industry. The main agent pulls this data using RAG (Retrieval-Augmented Generation) to personalize the outputs. One-Time GitHub Setup Initializes a blank GitHub repository to host HTML files online, allowing Gotenberg to access and convert them. 🧩 Tech Stack Gotenberg** – Converts HTML to PDF GitHub Pages** – Hosts live HTML files n8n** – Handles data tables and workflow automation LLM (OpenAI / Cohere / etc.)** – Generates cover letters Google Drive** – Stores the final PDFs ⚙️ Installation & Setup 1. Create a GitHub Repository This repo will host your HTML resume through GitHub Pages. 2. Set the Webhook URL In the notify-n8n.yml file, replace: role | summary | task | skills | tools | industry 3. Create the n8n Data Table Add the following columns: role | summary | task | skills | tools | industry 4. Create a Google Spreadsheet Add these columns: company | cover_letter | resume 5. Install Gotenberg Follow the installation instructions on the Gotenberg GitHub repository: https://github.com/thecodingmachine/gotenberg 6. Customize the HTML Template Modify the HTML resume to your liking. You can use an LLM to locate and edit specific sections. 7. Add Authentication and Link Your GitHub Repo Ensure your workflow has permission to push updates to your GitHub Pages branch. 8. Run the Workflow Once everything is connected, trigger the workflow to automatically generate and save personalized resumes and cover letters. 📝 How to Use Copy and paste the job listing description into the Telegram bot. Wait for the "Done" notification before submitting another job. Do not use the bot again until the notification appears. The process usually takes a few minutes to complete. ✅ Notes This workflow is designed to save time and personalize your job applications efficiently. By combining n8n automation, LLMs, and open-source tools like Gotenberg, you can maintain full control over your data while generating high-quality resumes and cover letters for every job opportunity.

Rename Workflow Nodes with AI for Clarity This workflow automates the tedious process of renaming nodes in your n8n workflows. Instead of manually editing each node, it uses an AI language model to analyze its function and assign a concise, descriptive new name. This ensures your workflows are clean, readable, and easy to maintain. Who's it for? This template is perfect for n8n developers and power users who build complex workflows. If you often find yourself struggling to understand the purpose of different nodes at a glance or spend too much time manually renaming them for documentation, this tool will save you significant time and effort. How it works / What it does The workflow operates in a simple, automated sequence: Configure Suffix: A "Set" node at the beginning allows you to easily define the suffix that will be appended to the new workflow's name (e.g., "- new node names"). Fetch Workflow: It then fetches the JSON data of a specified n8n workflow using its ID. AI-Powered Renaming: The workflow's JSON is sent to an AI model (like Google Gemini or Anthropic Claude), which has been prompted to act as an n8n expert. The AI analyzes the type and parameters of each node to understand its function. Generate New Names: Based on this analysis, the AI proposes new, meaningful names and returns them in a structured JSON format. Update and Recreate: A Code Node processes these suggestions, updates all node names, and correctly rebuilds the connections and expressions. Create & Activate New Workflow: Finally, it creates a new workflow with the updated name, deactivates the original to avoid confusion, and activates the new version.

YouTube Chapter Auto-Description with AI This n8n template automatically adds structured timestamp chapters to your latest YouTube video’s description using your RSS feed, SupaData for transcript extraction, and an AI tool for chapter generation. Ideal for creators who want every video to include chapter markers without doing it manually. Good to Know SupaData extracts full transcripts from YouTube videos via URL. The AI chapter generator converts long transcripts into formatted timestamps with short titles. This workflow edits the existing video description and appends the chapters to the bottom. How It Works The RSS Feed Trigger detects new uploads from your YouTube channel. The workflow checks Airtable to prevent duplicate processing. Transcript is fetched using SupaData API. The total video duration is extracted from the transcript. AI is prompted to generate well-formatted chapter timestamps. The existing description is fetched from YouTube. The chapters are appended and pushed back via the YouTube API. How to Use Start with the Manual Trigger to test the setup. Replace it with the RSS Trigger once you're ready for automation. Chapters are added only if the video hasn't been processed before. Requirements YouTube OAuth2** credentials in n8n SupaData API Key** Airtable account** (for optional deduplication logic) Customizing This Workflow Change the chapter format, or instruct the AI to use emojis, bold titles, or include sections like "sponsor" or "Q&A". Replace the RSS Trigger with a webhook if using a different publishing process.

How it works Input your proposal basics - Manually enter the core details and key points for your proposal Dual AI processing - OpenAI expands your inputs into a comprehensive draft, then Claude refines it for clarity and readability Automated document output - The workflow copies your Google Doc template, replaces all variables with the AI-generated content, and delivers your finished proposal Set up steps Estimated time: 10-15 minutes Create an OpenRouter account - Sign up at OpenRouter to get API access for Claude Set up your Google Doc template - Create a template document with placeholder variables (variable names are listed in the 'Update proposal' node) Configure API credentials - Add your OpenAI and OpenRouter API keys to the workflow Connect Google Drive - Authenticate your Google account to enable document creation 💡 Detailed configuration instructions and variable naming conventions can be found in the sticky notes within the workflow. `

AI Workflow Description and Template Generator This workflow automates the creation of professional documentation and template-ready sticky notes for any n8n workflow using AI. How it works Receives an n8n workflow JSON file via Telegram Validates the input file type and extracts workflow data Scrubs sensitive information and analyzes workflow structure Uses Google Gemini AI to generate comprehensive documentation Assembles a complete template with main workflow sticky note and logical section stickies Sends back the documented workflow file, usage checklist, and setup guide via Telegram Setup Configure Telegram Trigger credentials for receiving files Configure Telegram API credentials for sending messages Configure Google Gemini Chat Model (Google PaLM API) credentials Customization Adjust the prompt in the "AI Template Generator" node to modify documentation style, detail level, or specific requirements for your use case.

Generate GitHub Release Notes with AI Automatically generate GitHub release notes using AI. This workflow compares your latest two GitHub releases, summarises the changes, and produces a clean, ready-to-paste changelog entry. It’s ideal for automating GitHub Releases, versioning workflows, and keeping your documentation or CHANGELOG.md up to date without manual editing. What this workflow does Listens for newly published GitHub Releases. Fetches and compares the latest two GitHub release versions. Uses an AI Chat Model to summarise changes and generate structured release notes. Outputs clean, reusable release note content for GitHub, documentation, or CI/CD pipelines. How it works GitHub Trigger detects a new published release. Release detail nodes extract the latest tag, body, and repository metadata. Comparison logic fetches the previous release and prepares a diff. Chat Model nodes (via OpenRouter) generate both a summary and a final, formatted release note. Requirements / Connections GitHub OAuth credential configured in n8n. OpenRouter API key connected to the Chat Model nodes. Setup instructions Import the template. Select your GitHub OAuth connection in all GitHub nodes. Add your OpenRouter credential to the Chat Model nodes. (Optional) Adjust the AI prompts to customise tone or formatting. Output The workflow produces: A concise summary of differences between the last two GitHub releases. A polished AI-generated GitHub release note ready to publish. Customisation ideas Push generated notes directly into a CHANGELOG.md or documentation repo. Send release summaries to Slack or Teams. Include commit messages, PR titles, or labels for deeper analysis.

🧥 Virtual Try-On Image & Video Generation (VLM Run) 📌 Overview This n8n workflow enables a Virtual Try-On experience where users upload a dress image and the system: Combines it with a fashion model image Generates a realistic try-on image Generates a fashion walking video Automatically shares results via: Telegram Discord YouTube 🚀 Use Cases Virtual fashion try-on AI fashion marketing Clothing e-commerce previews Social media fashion automation Influencer & brand demo pipelines ✨ Key Features 🖼️ Image-based virtual try-on (model wearing the dress) 🎥 AI-generated fashion video 🔗 Multi-platform publishing (Telegram, Discord, YouTube) 🧩 Modular, extensible workflow design 🧠 Workflow Architecture 🟨 Input Dress Image** – Uploaded by user (Form Trigger) Model Image** – Downloaded from predefined URL Prompt** – Auto-constructed inside workflow 🟦 Output 🖼️ Try-On Image 🎥 Fashion Walk Video 📤 Shared to: Telegram (image/video) Discord (image) YouTube (video upload) 🔐 Required Credentials You must configure the following credentials in n8n: | Service | Credential Type | | -------- | ------------------ | | VLM Run | VLM Run API | | Telegram | Telegram Bot API | | Discord | Discord OAuth2 | | YouTube | YouTube OAuth2 | ⚠️ Community Node Warning > Important: This workflow uses a Community Node > @vlm-run/n8n-nodes-vlmrun What this means: This node is NOT installed by default in n8n You must manually install it before using the workflow 📦 Installation Run the following command in your n8n environment: npm install @vlm-run/n8n-nodes-vlmrun Then restart n8n. 📖 Community Nodes Documentation: https://docs.n8n.io/integrations/community-nodes/

Shopify AI Automation Image-to-Product CSV Bulk Upload Automation This Shopify AI automation is an advanced n8n-powered workflow that converts raw product images into a Shopify-ready product CSV. It uses AI image analysis, Google Drive, Google Sheets, and Shopify APIs to fully automate product onboarding — from images to structured ecommerce data. Built for scalable ecommerce automation, this workflow is especially effective for image-first catalogs such as jewelry, fashion, and accessories. 🚀 Features 🖼️ AI Image Analysis — Analyzes product images one by one for higher accuracy and lower risk 🧠 Automatic Category Detection — Identifies main product category (e.g. Jewelry), easily customizable for any niche ✍️ AI Product Content Generation — Creates product names, descriptions (HTML), tags, and attributes 📄 Google Sheets Orchestration — Structures data and outputs a clean Shopify-compatible CSV 🛍️ Shopify Asset Upload — Uploads images to Shopify and retrieves CDN URLs 🧩 Workflow Preparation Before running the workflow: Upload all product images to Google Drive Name images using the format: <SKU><ColorCode> Example: 12345GR Place all images inside a folder named:<Brand Name> Root folder name : pending Example : Google_Drive/pending/Manish Collection/All Images Each image represents one product variant. ⚙️ How It Works The workflow follows a 6-step automation pipeline designed for reliability and scalability. Notes : You may connect all these step to make it fully automatic or shecdule it according to your suitable time. 🔄 Step-by-Step Process Step 1: Fetch Images from Google Drive Scans the pending/<brand_name> folder Fetches all images Extracts SKU and color code Stores references in Google Sheets Step 2: AI Image Analysis (One-by-One) Images are analyzed individually Slower than batch processing, but far more reliable Reduces hallucinations and incorrect attributes Ideal for production-grade Shopify automation. Step 3: Main Category Identification AI determines the primary product category (example: Jewelry) Prompts can be modified for any ecommerce niche Step 4: Conditional Product Content Generation Based on category: Product titles are generated Descriptions are written in Shopify-ready HTML Tags and attributes are created This replaces repetitive work typically handled via Shopify Flow or manual data entry. Step 5: Shopify Image Upload Images are uploaded to Shopify assets Shopify returns CDN URLs URLs are mapped back to product data Step 6: Shopify CSV Generation All enriched data is compiled into a new Google Sheet Output matches Shopify’s product import CSV format File is ready for bulk upload 🛠️ n8n Nodes Used Trigger Node (Manual / Schedule) Google Drive Node Google Sheets Node AI Agent Node (Image Analysis + Content) Switch Node (Category-based logic) Code Node (Formatting & CSV structure) Shopify Node / HTTP Node 🔐 Credentials Required Before running the workflow, configure the following credentials in n8n: Shopify Access Token** — For asset uploads and API calls AI Provider API Key** — For image analysis and content generation Google Drive OAuth** — To access product images Google Sheets OAuth** — To store and export data 👤 Ideal For This workflow is ideal for: Shopify store owners handling bulk product uploads Ecommerce teams managing image-heavy catalogs Agencies building scalable Shopify automation systems Anyone exploring how to automate Shopify product onboarding 💬 Extensibility This workflow is modular and easy to extend. You can add: Multi-language product descriptions Pricing and margin automation Shopify marketing automation triggers Shopify Flow integrations after product import Marketplace exports (Google Shopping, Meta, Amazon) 🔑 Keywords shopify ai shopify flow shopify marketing automation shopify automation ecommerce automation how to automate shopify 📌 Notes No AI fine-tuning required No fragile prompt chaining Designed for accuracy over speed Safe for production ecommerce workflows 📞 Support If you’re looking to customize or extend this workflow, feel free to reach out or fork the project. Happy automating 🚀

This workflow is a simple yet brilliant automation designed to generate time-coded SRT subtitles starting directly from a video URL using ElevenLabs. With just a single video link, the workflow automatically extracts the audio, transcribes it using AI speech recognition, and converts the transcription into a properly formatted SRT subtitle file with accurate timestamps. This workflow automates the creation of SRT subtitle files for YouTube videos using AI speech recognition, eliminating the need for manual captioning and saving creators hours of work. It’s a fast, reliable, and fully automated solution, perfect for YouTube creators, video editors, and content producers who want to improve accessibility, engagement, and SEO with minimal effort. With just one input (a video link), the workflow: Downloads the video Automatically transcribes the audio using AI speech-to-text Intelligently splits the transcription into readable subtitle segments Generates a perfectly formatted SRT file with accurate timestamps Uploads the final subtitle file to Google Drive, ready to use It’s a lightweight, no-friction workflow that turns a raw video into professional subtitles in a fully automated way. Key Advantages 1. ✅ Extremely Simple, Yet Powerful This workflow proves that automation doesn’t need to be complex to be effective. A minimal number of nodes delivers a complete end-to-end subtitle generation process. 2. ✅ Automatic Time-Based SRT Generation Subtitles are not just plain text: they are properly time-aligned, making them immediately compatible with YouTube, video editors, and media players. 3. ✅ Smart Subtitle Splitting The workflow intelligently splits text based on punctuation and length, producing subtitles that are: Easy to read Well-paced Aligned with natural speech flow 4. ✅ Perfect for Video Creators This workflow is ideal for: YouTube creators** Content marketers Educators Podcasters Social video producers It dramatically reduces the time needed to add subtitles, improving: Accessibility Engagement SEO and watch time 5. ✅ Fully Automatable & Scalable Once set up, it can be reused endlessly: One video or hundreds Manual trigger or automated pipelines Easy to extend with translations, publishing, or notifications This workflow automates the creation of SRT subtitle files from YouTube videos using AI speech recognition. The process begins when the workflow is manually triggered, requiring a YouTube video URL as input. The system first fetches the video content via HTTP request, then sends the audio to ElevenLabs for transcription. The AI returns timestamped text segments which are intelligently split into readable subtitle chunks based on punctuation and length constraints. These segments are formatted into standard SRT (SubRip) format with precise timing, converted to a binary file, and finally uploaded to a specified Google Drive folder as a ready-to-use subtitle file. Set up Steps Configure Video Source: In the "Set Video Url" node, replace the placeholder value with a valid YouTube video URL or set up a method to dynamically provide URLs API Credentials Setup: Configure ElevenLabs API credentials in the "Transcribe audio or video" node with your API key Set up Google Drive OAuth2 credentials in the "Upload file" node with appropriate folder permissions Customize Output: Adjust the SRT generation parameters in the "From Elevenlabs to Srt" node if different subtitle formatting is needed Destination Folder: Verify the Google Drive folder ID in the upload node points to your desired destination Execution: Trigger the workflow manually and provide a video URL when prompted to generate and upload subtitles 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Generate professional sales proposals from a simple form—AI writes the content, you deliver the document. Fill out client details, pain points, and pricing, and this workflow creates a polished proposal with calculated ROI metrics, executive summary, solution strategy, and team bios. How It Works Sales rep submits a form with client name, industry, pain points, and pricing Code node calculates ROI, net savings, and break-even period Gemini AI generates proposal content: executive summary, key challenges, solution strategy, team bios, and call to action Copies your Google Doc template and replaces all placeholders with generated content Final proposal is ready in Google Drive Setup Import the workflow JSON Create a Google Doc template with placeholders: {{client_name}}, {{executive_summary}}, {{key_challenges}} {{solution_strategy}}, {{team_bios}}, {{next_steps}} {{formatted_roi}}, {{formatted_net_savings}}, {{formatted_break_even}} {{formatted_solution_cost}}, {{date}} Add credentials: Google Drive → OAuth2 Google Docs → OAuth2 Google Gemini → API key from aistudio.google.com Configure "Copy proposal template" node → Point to your template document Customize the AI → Edit system message in "Generate proposal content" to match your tone Test → Submit the form and check the generated proposal Activate