Create AI generated videos 4x cheaper than veo3 with Google Sheets & Fal.AI
Turn Your Ideas into Videos—Right from Google Sheets! This workflow helps you make cool 5-second videos using Fal.AI and Kling 2.1, just by typing your idea into a Google Sheet. You can even choose if you want your video to have sound or not. It’s super easy—no tech skills needed! And the best? 4x Cheaper than Veo3 model with similar quality! Why use this? Just type your idea in a sheet—no fancy tools or uploads. Get a video link back in the same sheet. Works with or without sound—your choice! How does it work? You write your idea, pick the video shape, and say if you want sound (true or false) in the Google Sheet. n8n reads your idea and asks Fal.AI to make your video. When your video is ready, the link shows up in your sheet. What do you need? A Google account and Google Sheets connected with service account (check this link for reference) A copy of the following Google Spreadsheet: Spreadsheet to copy An OpenAI API key A Fal.AI account with some money in it That’s it! Just add your ideas and let the workflow make the videos for you. Have fun creating! If you have any questions, just contact me in X @maxrojasdelgado.
By Maximiliano Rojas-DelgadoAuto-respond to Gmail inquiries using OpenAI, Google Sheet & AI agent
Who is this for? This workflow is ideal for: Customer support teams looking to reduce manual response time SaaS companies that frequently receive product inquiries E-commerce stores with common customer questions about orders, shipping, and returns What problem is this workflow solving? Manually responding to repetitive customer emails is inefficient, prone to inconsistency, and time-consuming. This workflow solves the issue by: Automatically replying to real customer inquiries 24/7 Ensuring every response is consistent, friendly, and based on approved knowledge Preventing responses to non-inquiries like newsletters or confirmations Logging every interaction for traceability, analysis, and compliance What this workflow does This AI-powered Gmail auto-responder intelligently handles inbound emails with the following steps: Monitors your Gmail inbox for new incoming emails in real time Classifies each email as either an “Inquiry” or “Not Inquiry” using GPT-4 Gets context from a Google Sheets FAQ database The context will be used to determine the most accurate and helpful response Generates a professional reply only if it’s a valid inquiry (e.g., pricing, refund, product details) Builds a context-aware, helpful response using verified knowledge only Sends the reply to the original sender automatically Logs everything to a Google Sheet — original email, AI response, timestamp, and email address Example Use Case: An email comes in: "Hi, I want to know your pricing and refund policy." The workflow: Detects it’s an inquiry Finds the pricing and refund FAQs in your Google Sheet Sends back a professional response like: "Hi! Thanks for reaching out. Our pricing starts at \$99/month. Refunds can be requested within 30 days of purchase. Let us know if you have more questions!" Logs the interaction to your “Enquiry\_Log” tab Setup Copy the Google Sheet template here: 👉 Gmail Auto-Responder – Google Sheet Template This contains: A FAQ_Context tab (your knowledge base) An Enquiry_Log tab (interaction logs) Connect your Gmail account to the Gmail Trigger and Gmail Send nodes Add your OpenAI API key in the classification and response generator nodes Link the Google Sheet in both the FAQ lookup and logging nodes Test with a sample email — try asking a pricing and refund question to see the complete process in action How to customize this workflow to your needs Adjust tone or brand voice in the AI prompt for a more casual or formal reply Modify classification rules if your use case includes more custom logic Expand the FAQ database to include new questions and answers Add multilingual support by customizing the AI prompt to detect and respond in different languages Integrate CRM or ticketing systems (like HubSpot, Zendesk, or Notion) to log or escalate unanswered queries Contact me for consulting and support: 📧 billychartanto@gmail.com
By Billy ChristiGenerate text-to-video & image-to-video content with Seedance 1 Lite AI
Generate Text-to-Video & Image-to-Video Content with Seedance 1 Lite AI Built with n8n + Replicate This workflow takes a prompt (and optional seed), sends it to Bytedance’s seedance-1-lite 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 all requests are authorized. Benefit: Keeps your API credentials secure and reusable. --- 🛠️ Section 2: Send Video Generation Request 📡 Create Prediction → Makes a POST request to Replicate with: prompt: your text description of the video seed: (optional) controls randomness for reproducibility Model version: b6519549e375404f45af5ef2e4b01f651d4014f3b57d3270b430e0523bad9835 Benefit: Kickstarts AI video generation from just a simple text prompt. --- 🔍 Section 3: Track the Prediction 📦 Extract Prediction ID → Stores predictionId, status, and predictionUrl for polling. ⏳ Wait → Pauses 2 seconds between checks. 🔁 Check Prediction Status → Calls Replicate to see if the video is ready. ✅ Check If Complete → Branches: If status = succeeded → continue. Else → loop back to Wait until it’s finished. Benefit: Ensures the workflow patiently monitors progress without timing out. --- 📽️ Section 4: Process & Return Results 📦 Process Result → Outputs a clean response containing: status video_url (generated video) metrics createdat & completedat model: bytedance/seedance-1-lite Benefit: Gives you structured data and the direct video link, ready to share or store. --- 📊 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 prompt 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 🎬 Generate AI-powered videos directly from text prompts. 🔑 API key stored securely within workflow. 🔄 Handles asynchronous processing with automatic polling. 📤 Provides clean, ready-to-use JSON output including video URL. 🧩 Flexible — you can connect results to Slack, Google Drive, or YouTube for instant publishing. ---
By Yaron BeenPersonalized email mail merge with Google Sheets and Gmail
Who is it for This workflow is designed for anyone who wants to simplify email automation without leaving Google Sheets. You can also send out emails automatically, without even visiting Google Sheets. It’s especially useful for: Marketers sending bulk or personalized campaigns Recruiters managing outreach from candidate lists Small business owners who want automated follow-ups Anyone who wants to trigger emails directly from sheet updates, e.g. event updates. How it works The workflow connects Google Sheets with Gmail to let you send emails in either of two ways: Bulk emails (mail merge): Use data from your sheet to send an email to multiple email addresses, one by one. Triggered emails: Automatically send an email whenever specific values or conditions in your sheet are met. No need to manually copy, paste, or switch to Gmail, because the process is fully automated. How to set it up Copy this template into your personal n8n workspace: https://docs.google.com/spreadsheets/d/1fWgGOU0m2cQpah7foDiz1WqTRKjCbJJCLBGCvJlXc/edit?usp=sharing Connect your Google Sheets and Gmail accounts using this workflow in n8n. Select the spreadsheet and sheet you want to use. Customize the email nodes with your subject line, body text, and variables (e.g., names or links from your sheet). Test the workflow, then activate it to start sending emails automatically. For a step-by-step walkthrough, check out this video guide on YouTube: https://www.youtube.com/watch?v=XJQ0W3yWR-0 Requirements A Google Sheets account with your data organized in rows and columns A Gmail account for sending emails An active n8n account to run the workflow
By Ladies Build With AIDaily news aggregation with Perplexity AI & MongoDB storage
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Workflow: Daily News Aggregator & MongoDB Storage This workflow is designed to run seamlessly in the background, automating the full cycle of news aggregation, storage, and reporting with precision and reliability. Daily Trigger (Cron Node) The process kicks off every morning at 8:00 AM UTC. This scheduling ensures that fresh global news is captured consistently at the start of each day. Perplexity Node At the heart of the workflow, a Perplexity node queries the latest global news. The prompt specifies both the type of news and the JSON structure required, guaranteeing the output is ready for structured storage. The result is a clean feed of headlines, timestamps, sources, and URLs. Data Formatting (Code Node) Since Perplexity’s response is a string, the workflow includes a custom JavaScript function to clean and parse it into a valid JSON array. Each news item is then transformed into its own object, ready for iteration. MongoDB Insertion (Loop Node) Each news article is inserted into the daily_news collection in MongoDB. The workflow ensures that fields such as headline, timestamp, source, URL, and category are stored neatly, with additional metadata available for future filtering and analysis. Aggregation & Notification Prep (Code Node) Once all items are stored, the workflow aggregates the day’s results. This step prepares a digest of what was successfully processed, ensuring visibility into the pipeline’s performance. Email Notification (Gmail Node) Finally, a summary email is sent via Gmail. This message confirms the operation’s success and provides a quick snapshot of the news collected and stored that day. Workflow Flow Cron Trigger → Perplexity API → Format Data → MongoDB Insert → Aggregate Results → Send Email Notification This setup transforms what could be a manual, repetitive task into a streamlined daily routine. It not only guarantees timely and structured storage of news but also provides immediate confirmation, making it an elegant solution for automated information management.
By Samuel HerediaCreate fact-based articles from your knowledge sources with Super RAG and GPT-5
Move beyond generic AI-generated content and create articles that are high-quality, factually reliable, and aligned with your unique expertise. This template orchestrates a sophisticated "research-first" content creation process. Instead of simply asking an AI to write an article from scratch, it first uses an AI planner to break your topic down into logical sub-questions. It then queries a Super assistant—which you've connected to your own trusted knowledge sources like Notion, Google Drive, or PDFs—to build a comprehensive research brief. Only then is this fact-checked brief handed to a powerful AI writer to compose the final article, complete with source links. This is the ultimate workflow for scaling expert-level content creation. Who is this for? Content marketers & SEO specialists: Scale the creation of authoritative, expert-level blog posts that are grounded in factual, source-based information. Technical writers & subject matter experts: Transform your complex internal documentation into accessible public-facing articles, tutorials, and guides. Marketing agencies: Quickly generate high-quality, well-researched drafts for clients by connecting the workflow to their provided brand and product materials. What problem does this solve? Reduces AI "hallucinations": By grounding the entire writing process in your own trusted knowledge base, the AI generates content based on facts you provide, not on potentially incorrect information from its general training data. Ensures comprehensive topic coverage: The initial AI-powered "topic breakdown" step acts like an expert outliner, ensuring the final article is well-structured and covers all key sub-topics. Automates source citation: The workflow is designed to preserve and integrate source URLs from your knowledge base directly into the final article as hyperlinks, boosting credibility and saving you manual effort. Scales expert content creation: It effectively mimics the workflow of a human expert (outline, research, consolidate, write) but in an automated, scalable, and incredibly fast way. How it works This workflow follows a sophisticated, multi-step process to ensure the highest quality output: Decomposition: You provide an article title and guidelines via the built-in form. An initial AI call then acts as a "planner," breaking down the main topic into an array of 5-8 logical sub-questions. Fact-based research (RAG): The workflow loops through each of these sub-questions and queries your Super assistant. This assistant, which you have pre-configured and connected to your own knowledge sources (Notion pages, Google Drive folders, PDFs, etc.), finds the relevant information and source links for each point. Consolidation: All the retrieved question-and-answer pairs are compiled into a single, comprehensive research brief. Final article generation: This complete, fact-checked brief is handed to a final, powerful AI writer (e.g., GPT-5). Its instructions are clear: write a high-quality article using only the provided information and integrate the source links as hyperlinks where appropriate. Implementing the template Set up your Super assistant (Prerequisite): First, go to Super, create an assistant, connect it to your knowledge sources (Notion, Drive, etc.), and copy its Assistant ID and your API Token. Configure the workflow: Connect your AI provider (e.g., OpenAI) credentials to the two Language Model nodes (GPT 5 mini and GPT 5 chat). In the Query Super Assistant (HTTP Request) node, paste your Assistant ID in the body and add your Super API Token for authentication (we recommend using a Bearer Token credential). Activate the workflow: Toggle the workflow to "Active" and use the built-in form to generate your first fact-checked article! Taking it further Automate publishing: Connect the final Article result node to a Webflow or WordPress node to automatically create a draft post in your CMS. Generate content in bulk: Replace the Form Trigger with an Airtable or Google Sheet trigger to automatically generate a whole batch of articles from your content calendar. Customize the writing style: Tweak the system prompt in the final New content - Generate the AI output node to match your brand's specific tone of voice, add SEO keywords, or include specific calls-to-action.
By Guillaume DuvernayAI-powered Gmail assistant: send replies by analyzing thread ID with Sonnet 4.5
This workflow automates analyzing Gmail threads and drafting AI-powered replies with the new model Anthropic Sonnet 4.5. This workflow automates the process of analyzing incoming emails and generating context-aware draft replies by examining the entire email thread. --- Key Advantages ✅ Time-Saving – Automates repetitive email replies, reducing manual workload. ✅ Context-Aware Responses – Replies are generated using the entire email thread, not just the latest message. ✅ Smart Filtering – The classifier prevents unnecessary drafts for spam or promotional emails. ✅ Human-in-the-Loop – Drafts are created instead of being sent immediately, allowing manual review and corrections. ✅ Scalable & Flexible – Can be adapted to different accounts, reply styles, or workflows. ✅ Seamless Gmail Integration – Directly interacts with Gmail threads and drafts via OAuth. --- How it Works This workflow automates the process of analyzing incoming emails and generating context-aware draft replies by examining the entire email thread. Trigger & Initial Filtering: The workflow is automatically triggered every minute by the Gmail Trigger node, which detects new emails. For each new email, it immediately performs a crucial first step: it uses an AI Email Classifier to analyze the email snippet. The AI determines if the email is a legitimate message that warrants a reply (categorized as "ok") or if it's spam, a newsletter, or an advertisement. This prevents the system from generating replies for unwanted emails. Context Aggregation: If an email is classified as "ok," the workflow fetches the entire conversation thread from Gmail using the threadId. A Code Node then processes all the messages in the thread, structuring them into a consistent format that the AI can easily understand. AI-Powered Draft Generation: The structured conversation history is passed to the Replying email Agent with Sonnet 4.5. This agent, powered by a language model, analyzes the entire thread to understand the context and the latest inquiry. It then drafts a relevant and coherent HTML email reply. The system prompt instructs the AI not to invent information and to use placeholders for any missing details. Draft Creation: The final step takes the AI-generated reply and the original email's metadata (subject, recipient, threadId) and uses them to create a new draft email in Gmail. This draft is automatically placed in the correct email thread, ready for the user to review and send. --- Set up Steps To implement this automated email reply system, you need to configure the following: Configure Gmail & OpenAI Credentials: Ensure the following credentials are set up in your n8n instance: Gmail OAuth2 Credentials: The workflow uses the same Gmail account for the trigger, fetching threads, and creating drafts. Configure this in the "Gmail Trigger," "Get a thread," and "Create a draft" nodes. OpenAI API Credentials: Required for both the "Email Classifier". Provide your API key in the respective OpenAI Chat Model nodes. Anthropic API Credentials: Required for the main "Replying email Agent." Provide your API key in the respective Antrhopic Chat Model nodes. Review AI Classification & Prompting: Email Filtering: Check the categories in the Email Classifier node. The current setup marks only non-advertising, non-newsletter emails as "ok." You can modify these categories to fit your specific needs and reduce false positives. Reply Agent Instructions: Review the system message in the Replying email Agent. You can customize the AI's persona, tone, and instructions (e.g., making it more formal, or instructing it to sign with a specific name) to better align with your communication style. --- Need help customizing? Contact me for consulting and support or add me on Linkedin.
By DavideMonitor LinkedIn posts & create AI content digests with OpenAI and Airtable
Automatically monitor LinkedIn posts from your community members and create AI-powered content digests for efficient social media curation. This template is perfect for community managers, content creators, and social media teams who need to track LinkedIn activity from their network without spending hours manually checking profiles. It fetches recent posts, extracts key information, and creates digestible summaries using AI. Good to know API costs apply - LinkedIn API calls (~$0.01-0.05 per profile check) and OpenAI processing (~$0.001-0.01 per post) Rate limiting included - Built-in random delays prevent API throttling issues Flexible scheduling - Easy to switch from daily schedule to webhook triggers for real-time processing Requires API setup - Need RapidAPI access for LinkedIn data and OpenAI for content processing How it works Daily profile scanning - Automatically checks each LinkedIn profile in your Airtable for posts from yesterday Smart data extraction - Pulls post content, engagement metrics, author information, and timestamps AI-powered summarization - Creates 30-character previews of posts for quick content scanning Duplicate prevention - Checks existing records to avoid storing the same post multiple times Structured storage - Saves all processed data to Airtable with clean formatting and metadata Batch processing - Handles multiple profiles efficiently with proper error handling and delays How to use Set up Airtable base - Create tables for LinkedIn profiles and processed posts using the provided structure Configure API credentials - Add your RapidAPI LinkedIn access and OpenAI API key to n8n credentials Import LinkedIn profiles - Add community members' LinkedIn URLs and URNs to your profiles table Test the workflow - Run manually with a few profiles to ensure everything works correctly Activate schedule - Enable daily automation or switch to webhook triggers for real-time processing Requirements Airtable account - For storing profile lists and managing processed posts with proper field structure RapidAPI Professional Network Data API - Access to LinkedIn post data (requires subscription) OpenAI API account - For intelligent content summarization and preview generation LinkedIn profile URNs - Properly formatted LinkedIn profile identifiers for API calls Customising this workflow Change monitoring frequency - Switch from daily to hourly checks or use webhook triggers for real-time updates Expand data extraction - Add company information, hashtag analysis, or engagement trending Integrate notification systems - Add Slack, email, or Discord alerts for high-engagement posts Connect content tools - Link to Buffer, Hootsuite, or other social media management platforms for direct publishing Add filtering logic - Set up conditions to only process posts with minimum engagement thresholds Scale with multiple communities - Duplicate workflow for different LinkedIn communities or industry segments
By Anna BuiCreate & upload AI videos to YouTube with Kling 2.5 & auto-SEO
++What it is++ An automated workflow for creating Kling 2.5 videos and posting them to YouTube. The workflow is divided into three main phases: Create Kling 2.5 Video Wait for Video Processing Post to YouTube ++Create Kling 2.5 Video++ This phase handles the initial video creation based on user input. Type Prompt: A form trigger allows the user to input details for the video, including: Prompt: A simple scenario for the video. Video Style: (e.g., Dialogue, Monologue, Advertisement, Documentary) Aspect Ratio: (e.g., 16:9, 9:16, 1:1) Videography (AI Refinement): Refines the user’s prompt into a detailed “script-to-screen” format suitable for video generation. FAL.AI Request: The refined prompt is sent to the Fal.ai Kling 2.5 model via an HTTP request to generate the video. Store Data: Details of the video request, including the date requested, the refined prompt, and the request URL, are stored in a Google Sheet. ++Wait for Video Processing++ Wait 5 mins: The workflow pauses for 5 minutes. This waiting period is necessary as it typically takes 3–5 minutes for the video to be ready after the generation request. ++Post to YouTube++ This phase focuses on generating YouTube SEO details and uploading the video. YT Video SEO (AI Generation): An AI agent (using OpenRouter’s OpenAI GPT-5 Mini model) acts as a YouTube SEO specialist and viral content strategist. It generates the following details for the YouTube video: Video Title: A compelling title (less than 6 words). Video Description: A detailed description. Video Tags: Relevant tags to maximize discoverability. The AI agent is configured to follow guidelines for virality and YouTube’s tag limits. Structured Output: Parses the structured JSON output from the AI agent. Get Keywords: Extracts and formats the video tags into a comma-separated list suitable for YouTube. Fetch Video Credentials: Fetches the video URL and other credentials from Fal.ai. Download Video: Downloads the generated video file. Post on YouTube: The video is uploaded to YouTube using the generated title, description, and tags. ++Setup++ To run this workflow, you need to set up credentials in n8n for: OpenRouter: Generate API key from your OpenRouter account. (Tutorial) Google Sheets: Uses OAuth 2.0. Connect by authenticating your Google account. YouTube Data API: Configure credentials to allow posting videos to YouTube (Follow this section of another Tutorial).
By Ari Nakos