Workflow Templates

Workflow: Publish to Contentful with Rich Text Formatting ⚡ About the Creators This workflow was created by Varritech Technologies, an innovative agency that leverages AI to engineer, design, and deliver software development projects 500% faster than traditional agencies. Based in New York City, we specialize in custom software development, web applications, and digital transformation solutions. If you need assistance implementing this workflow or have questions about content management solutions, please reach out to our team. 🏗️ Architecture Overview This workflow takes a JSON article payload, splits its markdown content into logical chunks, converts each chunk into Contentful Rich Text JSON via an AI agent, merges the resulting rich text nodes back into a single document, formats the entire entry according to Contentful's field schema, and finally publishes it to Contentful. Trigger → Executes when called by another workflow Split by Headings → Breaks markdown into ##-delimited chunks Markdown → Rich Text → AI agent converts each chunk to Contentful Rich Text JSON Combine Rich Text Objects → Aggregates all chunk outputs into one document Format Entry → Wraps metadata and rich-text content into Contentful schema Publish Entry → HTTP POST to Contentful API 📦 Node-by-Node Breakdown flowchart LR A[When Executed by Another Workflow] --> B[Split by Headings] B --> C[Markdown to Contentful format] C --> D[Combine Rich Text Objects] D --> E[Merge1] E --> F[Format1] F --> G[Create newly formatted Contentful Entry] 1. When Executed by Another Workflow Type: Execute Workflow Trigger Input Example: title, slug, category.id, description, keywords, content, metaTitle, metaDescription, readingTime, difficulty Purpose: Receives the JSON payload from the upstream workflow. 2. Split by Headings Type: Code Logic: Splits input.content into an array of markdown chunks at each second-level heading (##). Emits one item per chunk with index, slug, title, and contentChunk. 3. Markdown to Contentful format Type: LangChain Agent (+ OpenAI Chat model) System Prompt: Defines rules for generating valid Contentful Rich Text JSON (must include nodeType, data:{}, content:[], etc.). Provides examples for paragraphs, headings, lists, links, and images. User Prompt: Here is the markdown content to convert: Purpose: Converts each markdown chunk into an array of rich-text nodes. 4. Combine Rich Text Objects Type: Code Logic: Parses and merges all content arrays returned by the AI agent into one combined content array under a document root. 5. Merge1 Type: Merge Purpose: Joins the original item (with metadata) and the combined rich-text document into a single data stream. 6. Format1 Type: Code Logic: Maps workflow data into the Contentful entry schema by setting each field (title, slug, category link, description, keywords, rich-text content, metaTitle, metaDescription, readingTime, difficulty) under the appropriate locale and structure required by Contentful. 7. Create newly formatted Contentful Entry Type: HTTP Request Method: POST URL: https://api.contentful.com/spaces Headers: Authorization: Bearer token for Contentful Management API Content-Type: application/vnd.contentful.management.v1+json X-Contentful-Version: entry version number X-Contentful-Content-Type: content type ID Body: The formatted fields object produced by the previous node Purpose: Publishes the new entry with rich-text content to Contentful. 🔍 Design Rationale & Best Practices Chunked Conversion Splitting by headings prevents AI context limits and keeps conversions modular. Strict Rich Text Schema Enforcing nodeType, data, and content structure avoids validation errors on Contentful. Two-Phase Merge Separating "combine AI outputs" and "format entry" keeps transformations clear and testable. Idempotent Publish Uses explicit versioning and content type headers to ensure correct entry creation.

The Agent Decisioner is a dynamic, AI-powered routing system that automatically selects the most appropriate large language model (LLM) to respond to a user's query based on the query’s content and purpose. This workflow ensures dynamic, optimized AI responses by intelligently routing queries to the best-suited model. Advantages 🔁 Automatic Model Routing:** Automatically selects the best model for the job, improving efficiency and relevance of responses. 🎯 Optimized Use of Resources:** Avoids overuse of expensive models like GPT-4 by routing simpler queries to lightweight models. 📚 Model-Aware Reasoning:** Uses detailed metadata about model capabilities (e.g., reasoning, coding, web search) for intelligent selection. 📥 Modular and Extendable:** Easy to integrate with other tools or expand by adding more models or custom decision logic. 👨‍💻 Ideal for RAG and Multi-Agent Systems:** Can serve as the brain behind more complex agent frameworks or Retrieval-Augmented Generation pipelines. How It Works Chat Trigger: The workflow starts when a user sends a message, triggering the Routing Agent. Model Selection: The AI Agent analyzes the query and selects the best-suited model from the available options (e.g., Claude 3.7 Sonnet for coding, Perplexity/Sonar for web searches, GPT-4o Mini for reasoning). Structured Output: The agent returns a JSON response with the user’s prompt and the chosen model. Execution: The selected model processes the query and generates a response, ensuring optimal performance for the task. Set Up Steps Configure Nodes: Chat Trigger: Set up the webhook to receive user messages. Routing Agent (AI Agent): Define the system message with model strengths and JSON output rules. OpenRouter Chat Model: Connect to OpenRouter for model access. Structured Output Parser: Ensure it validates the JSON response format (prompt + model). Execution Agent (AI Agent1): Configure it to forward the prompt to the selected model. Connect Nodes: Link the Chat Trigger to the Routing Agent. Connect the OpenRouter Chat Model and Output Parser to the Routing Agent. Route the parsed JSON to the Execution Agent, which uses the chosen model via OpenRouter Chat Model1. Credentials: Ensure OpenRouter API credentials are correctly set for both chat model nodes. Test & Deploy: Activate the workflow and test with sample queries to verify model selection logic. Adjust the routing rules if needed for better accuracy. Need help customizing? Contact me for consulting and support or add me on Linkedin.

🤖 Grok-4 Customer Support Agent with Document-Based Intelligence Template [RAG] This workflow creates a smart, AI-powered customer support agent using Grok-4 that can answer questions based on a preloaded Google Doc knowledge base. It listens for incoming customer queries via Telegram, then uses Grok-4’s language reasoning + memory features to generate helpful responses pulled directly from the doc. Watch the Step-by-Step Tutorial of this Workflow: https://www.youtube.com/watch?v=OXzsh-Ba-8Y&t=2s It’s perfect for solopreneurs, startups, or businesses that want to: Automate first-level support Build a Telegram-based knowledge agent Answer FAQs using internal docs (like manuals, policies, product details) 🔍 How It Works: Telegram Trigger – Listens for incoming messages from users Google Docs Tool – Retrieves a specified doc to serve as the knowledge base Grok-4 AI Agent – Uses xAI’s latest LLM with built-in memory and the document as a tool Memory Buffer – Keeps track of ongoing context in the conversation Telegram Reply – Sends the final response back to the customer 🧠 Tools & Integrations Used: xAI Grok-4 Model (via Langchain-compatible node) Google Docs Tool (as a reference knowledge base) Telegram Bot API (chat interface) n8n Agent Framework (for chaining memory, model, and tools) 💡 Use Cases: AI-powered FAQ assistant for your product Internal HR bot answering company policy questions Support assistant trained on onboarding documents or technical manuals Private support bot for VIP groups on Telegram

Get real-time cryptocurrency prices directly in Telegram! This workflow integrates CoinMarketCap API with Telegram, allowing users to request live crypto prices simply by sending a message to the bot. Ideal for crypto traders, analysts, and enthusiasts who need quick and easy access to market data. How It Works A Telegram bot listens for user input (e.g., "BTC" for Bitcoin). The workflow sends a request to the CoinMarketCap API to fetch the latest price. The response is processed using an AI-powered language model (GPT-4o-mini) for structured messaging. The workflow logs session data using a memory buffer for better response tracking. The latest price is sent back to the user via Telegram. Set Up Steps Create a Telegram Bot Use @BotFather on Telegram to create a bot and obtain an API token. Get a CoinMarketCap API Key Sign up at CoinMarketCap and retrieve your API key. Configure API Credentials in n8n Add the CoinMarketCap API key under HTTP Header Auth. Add your Telegram bot token under Telegram API credentials. Deploy and Test Send a message (e.g., "BTC") to your Telegram bot and receive live price updates instantly! Automate your crypto price tracking today with this powerful Telegram bot!

Tags*: Sustainability, Supply Chain, AI Agent, CO2 Emissions, Carbon Interface API, Logistics, Automation Context Hi! I’m Samir — a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting. I help logistics teams reduce their environmental footprint by combining AI automation and carbon estimation APIs. This workflow is part of our green logistics initiative, allowing businesses to track the CO₂ emissions of last-mile or regional shipments. > Automate carbon tracking for shipping operations with n8n! 📬 For business inquiries, feel free to connect with me on LinkedIn Who is this template for? This workflow is designed for logistics coordinators, transportation planners, or sustainability officers who want to estimate and record emissions for B2B shipments. Let’s imagine your carrier sends a shipment confirmation email after a pickup is scheduled: An AI Agent reads the email and extracts structured data: addresses, distance, cargo weight, and delivery time. The Carbon Interface API is then called to calculate CO₂ emissions based on weight and distance, and the results are stored in a Google Sheet. How does it work? This workflow automates the process of tracking CO₂ emissions for scheduled shipments: 📨 Gmail Trigger captures shipment confirmation emails 🧠 AI Agent parses the shipment info (pickup, delivery, weight, distance) 🚚 Carbon Interface API estimates CO₂ emissions 📊 Google Sheets is used to store shipment metadata and carbon results Steps: 💌 Trigger on new shipment confirmation email 🧠 Extract structured shipment info with AI Agent 📋 Store metadata in Google Sheets ⚙️ Call Carbon Interface API with weight and distance 📥 Append estimated CO₂ emissions to the shipment row What do I need to get started? You’ll need: A Gmail account to receive shipment confirmation emails A Google Sheet to track shipment data and CO₂ A free Carbon Interface API key OpenAI access for using the AI Agent parser A few sample emails from your logistics provider to test Next Steps 🗒️ Use the sticky notes in the n8n canvas to: Add your Gmail and Carbon Interface credentials Try with a sample shipment confirmation email Check your Google Sheet to verify emissions and timestamps This template was built using n8n v1.93.0 Submitted: June 7, 2025

Gmail Daily Summary Scheduler - Template Description Never miss important emails again! This intelligent automation runs every morning at 8 AM to analyze your Gmail inbox from the past 24 hours and delivers a comprehensive summary powered by Google Gemini AI. 🚀 What it does: Automatically triggers daily at 8 AM (customizable) Fetches Gmail emails from the last 24 hours AI analyzes all emails to identify themes and key updates Highlights priority emails with reasons why they're important Delivers structured output in consistent JSON format 💡 Perfect for: Busy professionals managing high email volumes Team leads who need quick inbox overviews Anyone wanting to prioritize email responses efficiently Remote workers staying on top of communications 🎯 Key Features: Smart filtering - Only processes emails from the last 24 hours AI-powered analysis - Uses Google Gemini for intelligent summaries Priority detection - Identifies urgent, time-sensitive emails Consistent output - Structured JSON with summary and highlights Fully automated - Set it and forget it 📋 Sample Output: Summary: "Today's emails covered 3 project updates, 2 meeting requests, and 1 urgent client issue requiring immediate attention." Important Emails: Subject: "Project Deadline Extension Request" | Sender: client@company.com | Reason: Client requesting timeline change for major deliverable due this week Subject: "Tomorrow's Board Meeting Moved" | Sender: assistant@office.com | Reason: Last-minute schedule change requiring immediate calendar adjustment 🛠 Prerequisites: Gmail account with API access Google Gemini API credentials Basic n8n knowledge for credential setup ⚙️ Easy to Customize: Change schedule time (default: 8 AM daily) Adjust time window (default: 24 hours) Modify AI analysis focus Add email filters by sender, subject, etc. Extend with notifications (Slack, email, etc.) 🔒 Privacy Note: This workflow processes email content through Google Gemini API. Ensure compliance with your organization's data policies. Save hours of manual email sorting every week! Import this template and start getting intelligent email summaries delivered automatically every morning.

⚠️ Disclaimer This workflow uses a community node: npm install n8n-nodes-supadata Please make sure to install this before running the workflow. 🔎 Who is this for? This workflow is for anyone who wants quick summaries of YouTube videos, such as researchers, students, analysts, or busy professionals. Just send a video link via Telegram and receive a structured summary in seconds—no need to watch the entire video. 🧠 What problem is this workflow solving? Watching long videos to extract key information is time-consuming. This automation solves that by instantly: Fetching the full transcript of the video Summarizing the content with AI Sending a clean summary directly to Telegram for quick reading It’s a fast and reliable way to stay informed without the overwhelm. ⚙️ What this workflow does 💬 Telegram Trigger Start by sending a YouTube link to your Telegram bot. 🎙️ Get Transcript (Supadata) Uses Supadata API to retrieve the full video transcript. 🧠 Summarize with OpenAI GPT-4o Processes the transcript using a structured prompt to extract: Main theme of the video Target audience Key insights and tips Problems discussed and solutions mentioned Notable quotes or highlights 📨 Send to Telegram The final summary is formatted and sent back to your Telegram chat, ready for reading or saving. 🛠️ Requirements n8n instance (Cloud or self-hosted)** Supadata API Key OpenAI API Key Telegram Bot Token ✅ Output Example The Telegram summary includes: 🎯 Title and topic 💡 Key learnings 🛠️ Tips or insights 🚨 Issues raised and solutions 📝 Quotes or highlights Just send a link, and get the core message—fast. Perfect for learning on the go. 🧠📲 Made by: Khaisa Studio Tag: youtube, summarizer, telegram, openai Category: AI Automation, Video Tools Need a custom? contact me on LinkedIn or Web

Description This workflow creates an automated video content pipeline that generates creative TikTok-style videos using AI. It combines OpenAI's GPT-4o-mini for idea generation with Sisif.ai's text-to-video AI technology to produce engaging short-form content automatically. Perfect for: Content creators, social media managers, marketing teams, and anyone who wants to maintain a consistent flow of AI-generated video content without manual intervention. Prerequisites Sisif.ai Account**: Sign up at sisif.ai and get your API token from sisif.ai/api/ OpenAI Account**: Get your API key from OpenAI platform n8n Instance**: Self-hosted or cloud instance How it Works The workflow operates on a scheduled cycle, generating fresh video content every 6 hours: 🤖 AI Idea Generation: OpenAI's GPT-4o-mini acts as a creative video strategist, generating unique, trend-aware video concepts optimized for TikTok and social media 🎬 Video Creation: Sisif.ai transforms each creative prompt into a high-quality 5-second video in 360x640 resolution ⏱️ Smart Monitoring: The workflow intelligently monitors video generation progress, waiting for completion before proceeding 📊 Data Processing: Final video data is structured and prepared for further use or storage Key Features ⚡ Fully Automated Runs every 6 hours without manual intervention Generates 4 unique videos daily (28 videos per week) Self-monitoring with automatic retry logic 🎯 Optimized for Social Media TikTok-perfect 360x640 resolution 5-second duration for maximum engagement Trend-aware content generation Action-packed, visual storytelling 🔧 Smart Architecture Simple HTTP requests for reliable operation Bearer token authentication for secure API access Automatic status checking and waiting logic Error handling and retry mechanisms

📧 Morning Mail Summary Ai Agent Simplify your mornings with this automated email summary workflow in n8n, designed for teams and individuals who want a quick, actionable snapshot of their inbox—every day, at a glance. 📌 Features Fully Automated**: Triggers daily at 8 AM IST Targeted Extraction**: Fetches messages from specific senders with dynamic date filtering Structured Data Aggregation**: Pulls key fields (sender, recipients, snippet) AI-Powered Summarization**: Uses LangChain + OpenRouter to generate: Insightful summaries Highlighted issues Assigned action items Memory-Enhanced Context**: Maintains continuity across days Stylish HTML Email Output**: Responsive design with: Summary section Action items Branded footer Team-Ready Sharing**: Auto-distributes to team with CC support 🛠️ How It Works Trigger: Daily schedule in n8n Fetch: Retrieves last 24h emails from target sender Organize: Aggregates email metadata Summarize: AI agent produces structured report: Key updates Critical issues Actionable tasks Send: Emails digest to team 🎯 Ideal For Project managers needing stakeholder briefings Customer success teams tracking communications Leadership staying informed efficiently Anyone streamlining email review 📦 Included Resources Complete n8n workflow JSON (6 nodes) Prompt template for structured summarization (Summary, Issues, Actions, Follow‑Ups). -Styled HTML email template, with responsive design and branding sections. 🆓 Get Started Import JSON into n8n Configure: Gmail / OpenRouter credentials Recipient lists Custom prompts Modify freely for your use case ⭐ Benefits ⏳ Time saved: Skip inbox digging 🔍 Focus: See only what matters ✨ Clarity: Structured tasks & deadlines 🔄 Consistency: Daily alignment for teams

🎥 YouTube Video Summarizer for Social Media Turn any YouTube video into a short, structured summary using AI — perfect for content creators, marketers, or social media managers. 🔧 What We Built We created a no-code automation in n8n that: Accepts a YouTube Video ID via a form Fetches the video transcript using an external API Summarizes the transcript using AI (Google Gemini) Automatically saves the summary to Google Docs for team use 🧩 Flow Overview | Step | Description | |------|-------------| | ✅ Form Trigger | User submits a YouTube video ID using an n8n form | | 🔁 Set Node | Maps the YouTube video ID for use in the API request | | 🌐 HTTP Request (External API) | Calls the YouTube Transcriptor AI API via RapidAPI to fetch transcript | | 🧹 Formatter (Code Node) | Joins transcript lines into a readable text block | | 🧠 AI Agent + Google Gemini (via Langchain) | Summarizes the full transcript into bullet points and tone | | 🧽 Optimizer (Code Node) | Extracts just the summary from the AI response | | 📝 Google Docs Node | Appends the clean summary to a shared Google Doc | 🌍 Real-World Problem Solved ❌ The Challenge Creators and marketers waste hours watching full videos just to extract the key points. Manual summarization is inconsistent, repetitive, and delays content planning. ✅ Our Solution ⏱️ Reduces time spent watching videos 🧠 AI-powered summaries keep tone consistent and structured 📄 Auto-sync with Google Docs makes summaries instantly available for teams 🔥 Bonus: This uses the YouTube Transcriptor AI API, so no need to manually scrape captions or use browser extensions. 🚀 Ideal Use Cases Repurpose YouTube content into Instagram Reels, LinkedIn posts, or blog content Build a video summary library for your editorial team Quickly extract talking points from podcast episodes 🛠️ Tech Stack n8n** – workflow automation engine YouTube Transcriptor AI API** – via RapidAPI Google Gemini (via Langchain)** – AI summarization Google Docs** – stores the final summary JavaScript nodes** – custom text parsing & formatting 💡 Want to customize it? Add Slack, Airtable, Notion, or Tweet auto-posting to expand the flow. Create your free n8n account and set up the workflow in just a few minutes using the link below: 👉 Start Automating with n8n Save time, stay consistent, and grow your LinkedIn presence effortlessly!

This workflow integrates LINE BOT, AI Agent (GPT), Google Sheets, and Google Drive to enable users to search for file URLs using natural language. The AI Agent extracts the filename from the message, searches for the file in Google Sheets, and returns the corresponding Google Drive URL via LINE BOT. Supports natural language queries (e.g., "Find file 1.pdf for me") AI-powered filename extraction Google Sheets Lookup for file URLs Auto-response via LINE BOT How to Use This Template 1. Download & Import Copy and save the Template Code as a .json file. Go to n8n Editor → Click Import → Upload the file. 2. Update Required Fields Replace YOUR_GOOGLE_SHEET_ID with your actual Google Sheet ID. Replace YOUR_LINE_ACCESS_TOKEN with your LINE BOT Channel Access Token. 3. Activate & Test Click Execute Workflow to test manually. Set Webhook URL in LINE Developer Console. Features of This Template Supports Natural Language Queries (e.g., “Find file 1.pdf for me”) AI-powered filename extraction using OpenAI (GPT-4/3.5) Real-time file lookup in Google Sheets Automatic LINE BOT Response Fully Automated Workflow

SEO-Optimized Description: Streamline your interview scheduling process with this intelligent n8n automation template powered by Google Calendar, Google Sheets, and GPT-4. This workflow reads candidate information from a spreadsheet, automatically schedules interviews in Google Calendar, and sends personalized interview invitation emails—all without manual input. What This Template Does: 📋 Monitors a Google Sheet for new candidate entries every minute 🕒 Auto-selects the next available interview slot (Mon/Wed/Fri at 3 PM) 📅 Creates a calendar invite in your Google Calendar ✍️ Uses GPT-4 to generate personalized emails based on candidate data 📧 Sends the email invite with the interview link via Gmail Built-in logic ensures: Candidates never get same-day interviews AI-generated emails are concise, polite, and professionally formatted Scheduling remains conflict-free and easy to manage Requirements: Google Calendar API credentials Google Sheets with candidate info (Name, Email, Background) Gmail account with OAuth2 Azure OpenAI API (GPT-4o recommended) Perfect For: Startups, HR teams, and recruiters looking to automate interview scheduling, eliminate back-and-forth emails, and deliver a professional candidate experience—all with zero hassle.