Free AI image generator - n8n automation workflow with Gemini/ChatGPT
This n8n template demonstrates how to use AI to generate custom images from scratch - fully automated, prompt-driven, and ready to deploy at scale. Use cases are many: You can use it for marketing visuals, character art, digital posters, storyboards, or even daily image generation for your personal purposes. How It Works The flow is triggered by a chat message in N8N or via Telegram. The default image size is 1080 x 1920 pixels. To use a different size, update the values in the “Fields - Set Values” node before triggering the workflow. The input is parsed into a clean, structured prompt using a multi-step transformation process. Our AI Agent sends the final prompt to Google Gemini’s image model for generation (you can also integrate with OpenAI or other chat models). The raw image data created by the AI Agent will be run through a number of codes to make sure it's feasible for your preview if needed and downloading. Then, we use an HTTP node to fetch the result so you can preview the image. You can send it back to the chat message in N8N or Telegram, or save it locally to your disk. How To Use Download the workflow package. Import the package into your N8N interface. Set up the credentials in the following nodes for tool access and usability: "Telegram Trigger"; "AI Agent - Create Image From Prompt"; "Telegram Response" or "Save Image To Disk" (based on your wish). Activate the "Telegram Response" OR "Save Image To Disk" node to specify where you want to save your image later. Open the chat interface (via N8N or Telegram). Type your image prompt or detailed descriptions and send. Wait for the process to run and finish in a few seconds. Check the result in your desired saving location. Requirements Google Gemini account with image generation access. Telegram bot access and chat setup (optional). Connection to local storage (optional). How To Customize We’re setting the default image size to 1080 x 1920 pixels and the default image model to "flux". You can customize both of these values in the “Fields – Set Values” node. Supported image model options include: "flux", "kontext", "turbo", and "gptimage". In the “AI Agent – Create Image From Prompt” node, you can also change the AI chat model. By default, it uses Google Gemini, but you can easily replace it with OpenAI ChatGPT, Microsoft AI Copilot, or any other compatible provider. Need Help? Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle
By Agent CircleAI agent for project management and meetings with Airtable and Fireflies
Video Guide I prepared a comprehensive guide detailing how to create a Smart Agent that automates meeting task management by analyzing transcripts, generating tasks in Airtable, and scheduling follow-ups when necessary. [](https://www.youtube.com/watch?v=0TyX7G00x3A) Youtube Link Who is this for? This workflow is ideal for project managers, team leaders, and business owners looking to enhance productivity during meetings. It is particularly helpful for those who need to convert discussions into actionable items swiftly and effectively. What problem does this workflow solve? Managing action items from meetings can often lead to missed tasks and poor follow-up. This automation alleviates that issue by automatically generating tasks from meeting transcripts, keeping everyone informed about their responsibilities and streamlining communication. What this workflow does The workflow leverages n8n to create a Smart Agent that listens for completed meeting transcripts, processes them using AI, and generates tasks in Airtable. Key functionalities include: Capturing completed meeting events through webhooks. Extracting relevant meeting details such as transcripts and participants using API calls. Generating structured tasks from meeting discussions and sending notifications to clients. Webhook Integration: Listens for meeting completion events to trigger subsequent actions. API Requests for Data: Pulls necessary details like transcripts and participant information from Fireflies. Task and Notification Generation: Automatically creates tasks in Airtable and notifies clients of their responsibilities. Setup N8N Workflow Configure the Webhook: Set up a webhook to capture meeting completion events and integrate it with Fireflies. Retrieve Meeting Content: Use GraphQL API requests to extract meeting details and transcripts, ensuring appropriate authentication through Bearer tokens. AI Processing Setup: Define system messages for AI tasks and configure connections to the AI chat model (e.g., OpenAI's GPT) to process transcripts. Task Creation Logic: Create structured tasks based on AI output, ensuring necessary details are captured and records are created in Airtable. Client Notifications: Use an email node to notify clients about their tasks, ensuring communications are client-specific. Scheduling Follow-Up Calls: Set up Google Calendar events if follow-up meetings are required, populating details from the original meeting context.
By Mark ShcherbakovGenerate & schedule social posts with Gemini/OpenAI for X and LinkedIn
💼 LinkedIn Content Machine – AI-Powered Post Generator & Scheduler for X and LinkedIn How it works: This end-to-end workflow automates your personal or brand content strategy by: 🧠 Using Google Gemini or OpenAI to generate engaging LinkedIn/X content from a title or trending posts. 🗓️ Posting directly to LinkedIn and X (formerly Twitter). 📊 Pulling high-performing LinkedIn posts to inspire new ideas. ✍️ Saving AI-generated drafts to Google Sheets for review. 🔔 Notifying your team on Slack when drafts are ready. Steps to set up: Add your API keys for Google Gemini or OpenAI. Set up your LinkedIn, X (Twitter), Google Sheets, and Slack credentials. Customize prompt logic or post filters if needed. Schedule the idea generation module or trigger it manually. Start generating and posting consistent, high-quality content with zero manual effort!
By NurseflowFetch dynamic prompts from GitHub and auto-populate n8n expressions in prompt
Who Is This For? This workflow is designed for AI engineers, automation specialists, and content creators who need a scalable system to dynamically manage prompts stored in GitHub. It eliminates manual updates, enforces required variable checks, and ensures that AI interactions always receive fully processed prompts. --- 🚀 What Problem Does This Solve? Manually managing AI prompts can be inefficient and error-prone. This workflow: ✅ Fetches dynamic prompts from GitHub ✅ Auto-populates placeholders with values from the setVars node ✅ Ensures all required variables are present before execution ✅ Processes the formatted prompt through an AI agent --- 🛠 How This Workflow Works This workflow consists of three key branches, ensuring smooth prompt retrieval, variable validation, and AI processing. --- 1️⃣ Retrieve the Prompt from GitHub (HTTP Request → Extract from File → SetPrompt) The workflow starts manually or via an external trigger. It fetches a text-based prompt stored in a GitHub repository. The Extract from File Node retrieves the content from the GitHub file. The SetPrompt Node stores the prompt, making it accessible for processing. 📌 Note: The prompt must contain n8n expression format variables (e.g., {{ $json.company }}) so they can be dynamically replaced. --- 2️⃣ Extract & Auto-Populate Variables (Check All Prompt Vars → Replace Variables) A Code Node scans the prompt for placeholders in the n8n expression format ({{ $json.variableName }}). The workflow compares required variables against the setVars node: ✅ If all variables are present, it proceeds to variable replacement. ❌ If any variables are missing, the workflow stops and returns an error listing them. The Replace Variables Node replaces all placeholders with values from setVars. 📌 Example of a properly formatted GitHub prompt: Hello {{ $json.company }}, your product {{ $json.features }} launches on {{ $json.launch_date }}. This ensures seamless replacement when processed in n8n. --- 3️⃣ AI Processing & Output (AI Agent → Prompt Output) The Set Completed Prompt Node stores the final, processed prompt. The AI Agent Node (Ollama Chat Model) processes the prompt. The Prompt Output Node returns the fully formatted response. 📌 Optional: Modify this to use OpenAI, Claude, or other AI models. --- ⚠️ Error Handling: Missing Variables If a required variable is missing, the workflow stops execution and provides an error message: ⚠️ Missing Required Variables: ["launch_date"] This ensures no incomplete prompts are sent to AI agents. --- ✅ Example Use Case 📜 GitHub Prompt File (Using n8n Expressions) Hello {{ $json.company }}, your product {{ $json.features }} launches on {{ $json.launch_date }}. 🔹 Variables in setVars Node json { "company": "PropTechPro", "features": "AI-powered Property Management", "launch_date": "March 15, 2025" } ✅ Successful Output Hello PropTechPro, your product AI-powered Property Management launches on March 15, 2025. 🚨 Error Output (If Missing launch_date) ⚠️ Missing Required Variables: ["launch_date"] --- 🔧 Setup Instructions 1️⃣ Connect Your GitHub Repository Store your prompt in a public or private GitHub repo. The workflow will fetch the raw file using the GitHub API. 2️⃣ Configure the SetVars Node Define the required variables in the SetVars Node. Make sure the variable names match those used in the prompt. 3️⃣ Test & Run Click Test Workflow to execute. If variables are missing, it will show an error. If everything is correct, it will output the fully formatted prompt. --- ⚡ How to Customize This Workflow 💡 Need CRM or Database Integration? Connect the setVars node to an Airtable, Google Sheets, or HubSpot API to pull variables dynamically. 💡 Want to Modify the AI Model? Replace the Ollama Chat Model with OpenAI, Claude, or a custom LLM endpoint. --- 📌 Why Use This Workflow? ✅ No Manual Updates Required – Fetches prompts dynamically from GitHub. ✅ Prevents Broken Prompts – Ensures required variables exist before execution. ✅ Works for Any Use Case – Handles AI chat prompts, marketing messages, and chatbot scripts. ✅ Compatible with All n8n Deployments – Works on Cloud, Self-Hosted, and Desktop versions.
By RealSimple SolutionsCreate an automated customer support assistant with GPT-4o and GoHighLevel SMS
📌 AI Agent via GoHighLevel SMS with Website-Based Knowledgebase This n8n workflow enables an AI agent to interact with users through GoHighLevel SMS, leveraging a knowledgebase dynamically built by scraping the company's website. --- ❓ Problem It Solves Traditional customer support systems often require manual data entry and lack real-time updates from the company's website. This workflow automates the process by: Scraping the company's website at set intervals to update the knowledgebase. Integrating with GoHighLevel SMS to provide users with timely and accurate information. Utilizing AI to interpret user queries and fetch relevant information from the updated knowledgebase. --- 🧰 Pre-requisites Before deploying this workflow, ensure you have: An active n8n instance (self-hosted or cloud). A valid OpenAI API key (or any compatible AI model). A Bright Data account with Web Unlocker setup. A GoHighLevel SMS LeadConnector account. A GoHighLevel Marketplace App configured with the necessary scopes. Installed n8n-nodes-brightdata community node for Bright Data integration (if self-hosted). --- ⚙️ Setup Instructions Install the Bright Data Community Node in n8n For self-hosted n8n instances: Navigate to Settings → Community Nodes. Click on Install. In the search bar, enter n8n-nodes-brightdata. Select the node from the list and click Install. Docs: https://docs.n8n.io/integrations/community-nodes/installation/gui-install Configure Bright Data Credentials Obtain your API key from Bright Data. In n8n, go to Credentials → New, select HTTP Request. Set authentication to Header Auth. In Name, enter Authorization. In Value, enter Bearer <yourapikeyfromBright_Data>. Save the credentials. Configure OpenAI Credentials Add your OpenAI API key to the relevant nodes. If you want to use a different model, replace all OpenAI nodes accordingly. Set Up GoHighLevel Integration a. Create a GoHighLevel Marketplace App Go to https://marketplace.gohighlevel.com Click My Apps → Create App Set Distribution Type to Sub-Account Add the following scopes: locations.readonly contacts.readonly contacts.write opportunities.readonly opportunities.write users.readonly conversations/message.readonly conversations/message.write Add your n8n OAuth Redirect URL as a redirect URI in the app settings. Save and copy the Client ID and Client Secret. b. Configure GoHighLevel Credentials in n8n Go to Credentials → New Choose OAuth2 API Input: Client ID Client Secret Authorization URL: https://auth.gohighlevel.com/oauth/authorize Access Token URL: https://auth.gohighlevel.com/oauth/token Scopes: locations.readonly contacts.readonly contacts.write opportunities.readonly opportunities.write users.readonly conversations/message.readonly conversations/message.write Save and authenticate to complete setup. Docs: https://docs.n8n.io/integrations/builtin/credentials/highlevel --- 🔄 Workflow Functionality (Summary) Scheduled Scraping: Scrapes website at user-defined intervals. Edit Fields node: User defines the homepage or site to scrape. Bright Data Node (self-hosted) OR HTTP Node (cloud users) used to perform scraping. Knowledgebase Update: The scraped content is stored or indexed. GoHighLevel SMS: Incoming user queries are received through SMS. AI Processing: AI matches queries to relevant content. Response Delivery: AI-generated answers are sent back via SMS. --- 🧩 Use Cases Customer Support Automation: Provide instant, accurate responses. Lead Qualification: Automatically answer potential customer inquiries. Internal Knowledge Distribution: Keep staff updated via SMS based on website info. --- 🛠️ Customization Scraping URLs: Adjust targets in the Edit Fields node. Model Swap: Replace OpenAI nodes to use a different LLM. Format Response: Customize output to match your tone or brand. Other Channels: Expand to include chat apps or email responses. Vector Databases: It is advisable to store the data into a third-party vector database services like Pinecone, Supabase, etc. Chat Memory Node: This workflow is using Redis as a chat memory but you can use N8N built-in chat memory. --- ✅ Summary This n8n workflow combines Bright Data’s scraping tools and GoHighLevel’s SMS interface with AI query handling to deliver a real-time, conversational support experience. Ideal for businesses that want to turn their website into a live knowledge source via SMS, this agent keeps itself updated, smart, and customer-ready.
By Cyril Nicko GasparGenerate 360° virtual try-on videos for clothing with Kling API (unofficial)
What's the workflow used for？ Leverage this Kling API (unofficial) provided by PiAPI workflow to streamline virtual try-on video creation. This tool is designed for e-commerce platforms, fashion brands, content creators and content influencers. By uploading model and clothing images and linking PiAPI account, users can swiftly generate a realistic video of the model sporting the outfit with a 360° turn, offering an immersive viewing experience. Step-by-step Instruction For basic settings of virtual try-on, check API doc to get best practice. Fill in your X-API-Key of your PiAPI account in Preset Parameters node. Upload the model photo and provide target clothing image urls. Click Test Workflow to generate virtual try-on image. Get the video output in the final node. Param Settings If you want to change into a dress, input the modelinput URL and the dressinput URL in the parameters. If you want to change into separates, input modelinput URL, upperinput URL and lower_input URL in Preset Parameters. Use Case Input images： Output Video <video src="https://static.piapi.ai/n8n-instruction/virtual-try-on/example1.mp4" controls /> The output demonstrates that the model is wearing the clothing from the specified image and showcases a rotating runway-style view. This workflow enables you to efficiently test garment-on-model presentation effects while reducing business model validation costs to a certain extent.
By PiAPICreate a complete HR department with OpenAI O3 and GPT-4.1-mini multi-agent system
CHRO Agent with HR Team Description Complete AI-powered HR department with a Chief Human Resources Officer (CHRO) agent orchestrating specialized HR team members for comprehensive people operations. Overview This n8n workflow creates a comprehensive human resources department using AI agents. The CHRO agent analyzes HR requests and delegates tasks to specialized agents for recruitment, policy development, training, performance management, employee engagement, and compensation analysis. Features Strategic CHRO agent using OpenAI O3 for complex HR decision-making Six specialized HR agents powered by GPT-4.1-mini for efficient execution Complete HR lifecycle coverage from hiring to retention Automated policy creation and compliance documentation Performance review and goal-setting systems Employee engagement and culture initiatives Compensation analysis and benchmarking Team Structure CHRO Agent: Strategic HR oversight and task delegation (O3 model) Recruiter Agent: Job descriptions, candidate screening, interview questions HR Policy Writer: Employee handbooks, policies, compliance documentation Training & Development Specialist: Onboarding programs, learning materials Performance Review Specialist: Reviews, feedback templates, goal setting Employee Engagement Specialist: Culture initiatives, team building, communications Compensation & Benefits Analyst: Salary benchmarking, benefits packages How to Use Import the workflow into your n8n instance Configure OpenAI API credentials for all chat models Deploy the webhook for chat interactions Send HR requests via chat (e.g., "Create a complete onboarding program for software engineers") The CHRO will analyze and delegate to appropriate specialists Receive comprehensive HR deliverables Use Cases Complete Hiring Process: Job postings → Screening → Interviews → Offers Policy Development: Employee handbooks, compliance documentation Onboarding Programs: 30-60-90 day plans with training materials Performance Management: Review cycles, feedback systems, development plans Culture & Engagement: Surveys, team building activities, recognition programs Compensation Strategy: Market analysis, pay equity reviews, benefits design Requirements n8n instance with LangChain nodes OpenAI API access (O3 for CHRO, GPT-4.1-mini for specialists) Webhook capability for chat interactions Optional: Integration with HRIS systems Cost Optimization O3 model used only for strategic CHRO decisions GPT-4.1-mini provides 90% cost reduction for specialist tasks Parallel processing enables simultaneous agent execution Template library reduces redundant content generation Integration Options Connect to HRIS systems (Workday, BambooHR, etc.) Integrate with applicant tracking systems Link to performance management platforms Export to document management systems Contact & Resources Website: nofluff.online YouTube: @YaronBeen LinkedIn: Yaron Been Tags HRTech PeopleOperations TalentAcquisition EmployeeExperience HRAutomation AIRecruitment PerformanceManagement CompensationBenefits OnboardingAutomation CultureTech n8n OpenAI MultiAgentSystem FutureOfWork HRTransformation
By Yaron BeenTraining feedback automation with Usertask and Airtable
Who is this template for? This workflow template is designed for teams involved in training management and feedback analysis. It is particularly useful for: HR Departments: Automating the collection and response to training feedback. Training Managers: Streamlining the process of handling feedback and ensuring timely follow-up. Corporate Trainers: Receiving direct feedback and taking actions to improve training sessions. This workflow offers a comprehensive solution for automating feedback management, ensuring timely responses, and improving the quality of training programs. --- How it works This workflow operates with an Airtable trigger but can be easily adapted to work with other triggers like webhooks from external applications. Once feedback data is captured, the workflow evaluates the feedback and directs it to the appropriate channel for action. Tasks are created in Usertask based on the feedback rating, and notifications are sent to relevant parties. Here’s a brief overview of this n8n workflow template: Airtable Trigger: Captures new or updated feedback entries from Airtable. Switch Node: Evaluates the feedback rating and directs the workflow based on the rating. Webhook: Retrieves the result of a Usertask task. Task Creation: Creates tasks in Usertask for poor feedback. Creates follow-up tasks for fair to good feedback. Documents positive feedback and posts recognition on LinkedIn for very good to excellent ratings. Notifications: Sends email notifications to responsible parties for urgent actions. Sends congratulatory emails and posts on LinkedIn for positive feedback. --- To summarize Flexible Integration: This workflow can be triggered by various methods like Airtable updates or webhooks from other applications. Automated Task Management: It creates tasks in Usertask based on feedback ratings to ensure timely follow-up. Multichannel Notifications: Sends notifications via email and LinkedIn to keep stakeholders informed and recognize successes. Comprehensive Feedback Handling: Automates the evaluation and response to training feedback, improving efficiency and response time. --- Instructions: Set Up Airtable: Create a table in Airtable to capture training feedback. Configure n8n: Set up the Airtable trigger in n8n to capture new or updated feedback entries. Set Up Usertask: Configure the Usertask nodes in n8n to create and manage tasks based on feedback ratings. Configure Email and LinkedIn Nodes: Set up the email and LinkedIn nodes to send notifications and post updates. Test the Workflow: Run tests to ensure the workflow captures feedback, creates tasks, and sends notifications correctly. --- Video : https://youtu.be/U14MhTcpqeY Remember, this template was created in n8n v1.38.2.
By NonoCodeSmart message batching AI-powered Facebook Messenger chatbot
🤖 Facebook Messenger Smart Chatbot - Smart Batch, Format & History with n8n Data Table v3 Version 2026 - Adaptable to n8n v1.113+ and v2.x by Nguyen Thieu Toan (Jay Nguyen) --- 📖 Overview A production-ready, enterprise-grade chatbot solution for Facebook Messenger built entirely in n8n. Features intelligent message batching, session-aware conversation tracking, multi-page support, and natural AI-powered responses. Perfect for: 💼 Customer support automation 🛒 E-commerce product inquiries 📅 Appointment scheduling & consultation booking 🎓 Educational assistants & training 🤝 Lead qualification & sales automation Requirements: n8n v1.113.0+, Facebook App with Messenger, Google Gemini API key (or compatible LLM) 🔗 Complementary Workflow Facebook Messenger Chatbot – Smart Human Takeover, Auto Pause & Context-Aware Adds intelligent human agent detection and automatic AI pause. When a human joins, AI pauses for configurable duration, then resumes automatically. Why combine? Smart Batch (v3): Multi-message batching, spam reduction Human Takeover: AI pauses for humans, smooth collaboration 👉 Access workflow --- ⚡ What's New in Version 3 Major Upgrades | Feature | Impact | |---------|--------| | 🏢 Multi-Page Support | Manage multiple pages within one workflow | | ⏱️ Flexible Timing | Adjustable wait times instead of fixed delays | | 🔒 Improved Detection | More reliable identification of system vs. user messages | | 📦 Smart Delivery | Sequential message handling to avoid overload | | 🧹 Automatic Cleanup | Removes outdated records to keep storage efficient | | 📊 Better Context | Clear separation of past vs. current sessions | | 🔄 Ordered Updates | Ensures actions run in the right sequence | | 📝 Simplified Naming | Clearer labels for easier understanding | Architecture Comparison: Previous version had fixed timing, parallel updates, no multi-page handling, and no cleanup. New version introduces flexibility, sequential processing, and scalability for real-world use. --- 🎯 Key Features 🔄 Smart Batching: Groups consecutive messages within configurable window (default 7s) 🧠 Session-Aware Context: Distinguishes old vs. current sessions for temporal awareness 📋 Full History: Stores complete chat logs with both user and page responses 👀 Natural UX: "Seen" marker and "Typing..." indicator for human-like feel 🎯 AI Integration: Extensible prompts for domain-specific consulting (Gemini, Groq, or any LLM) 🌐 Multi-Language: Handles Vietnamese (anh/chị/em) with customizable settings 🏢 Multi-Page Ready: Single workflow serves multiple Facebook Pages simultaneously Technical Highlights: Idempotent processing, timezone-aware timestamps (Asia/HoChiMinh), Facebook API v24.0 compatible, sequential delivery with rate limiting protection, auto cleanup (keeps last 15 rows) --- 🏗️ How It Works 🔄 General Flow Reception & Validation → Batching & Storage → Context Aggregation ↓ ↓ ↓ Identify input Store for later use Combine with history Filter duplicates Apply short delay Build conversation context ↓ AI Processing → Delivery & Cleanup ↓ ↓ Generate response Format & send Add signals Maintain records Ensure continuity Clean old data --- 🛠️ Setup Guide Step 1: Facebook App Create app, add Messenger, set webhook, get token, subscribe page Step 2: Data Table Prepare tables for messages batching Step 3: Workflow Import template, set context, link tables, connect AI Step 4: Test Activate workflow, send test messages, verify pause/resume --- 👤 About the Author Nguyen Thieu Toan (Nguyễn Thiệu Toàn / Jay Nguyen) AI Automation Specialist | n8n Workflow Expert | Business Optimization Consultant Services: AI Automation Solutions, n8n Workflow Development, Custom Chatbot Implementation, Training Programs Contact: 🌐 nguyenthieutoan.com 📘 Facebook 💼 LinkedIn 🐦 X (Twitter) 📺 YouTube 📧 me@nguyenthieutoan.com GenStaff Company: genstaff.net | contact@genstaff.net --- 📄 License After purchase, use in commercial/personal projects. No redistribution or resale. Keep author attribution when sharing. --- Last Updated: December 18, 2025 | Version: 3.0 | n8n Compatibility: v1.123.0+ and v2.0.0+ | Facebook API: v24.0 --- Ready to transform your Facebook Messenger into an intelligent AI assistant? Import this workflow and start automating today! 🚀
By Nguyễn Thiệu Toàn (Jay Nguyen)Sum or aggregate a column of spreadsheet or table data
This workflow shows how to sum multiple items of data, like you would in Excel or Airtable when summing up the total of a column. It uses a Function node with some javascript to perform the aggregation of numeric data. The first node is simply mock data to avoid needing a credential to run the workflow. The second node actually performs the summation - the javascript has various comments in case you need to edit the JS. For example, to sum multiple items of data. Below is an example of the type of data this workflow can sum - so anything that is in a tabular form (Airtable, GSHeets, Postgres etc).
By Max TkaczGenerate biblical character vlogs with GPT-4o and Veo3 AI video generator
🧠 How It Works This intelligent workflow turns ancient stories and legendary characters into modern-style vlog ideas — then automatically builds cinematic prompts ready to generate short videos using Veo3. Think: “What if biblical figures had GoPros?” — funny, emotional, and visually stunning AI-made videos. --- 🔄 Workflow Steps ✨ 1. Concept Generator (AI Node 1) The first AI agent creates a video concept inspired by a biblical or mythological theme. It structures output as JSON with: 🎬 caption – Short, emotional or humorous line with emojis & hashtags 💭 concept – A short summary of the story or moment captured on camera 🌄 setting – Visual and mood details (lighting, style, colors) 📋 status – Stage label like “draft” or “to produce” Example Output: json { "caption": "POV: Moses trying to record a vlog mid–Red Sea split 🌊📹 faithvibes holyshorts", "concept": "Moses looks straight into the camera, trying to act calm while walls of water rise dramatically beside him.", "setting": "Vast sea corridor glowing in blue light, reflections dancing on wet sand, robes fluttering in the wind.", "status": "to produce" } --- 🎬 2. Cinematic Prompt Builder (AI Node 2) This agent converts the concept and setting into a Veo3-ready cinematic prompt that guides realistic video generation. Each output includes: Scene layout & description 🌅 Character framing & expression 🎭 Camera movement (pan, orbit, dolly-in, etc.) 🎥 Lighting style & atmosphere 💡 Textural realism (dust, wind, shadows, fabrics) Example Output: > A robed man stands between two towering walls of water, facing the camera as waves shimmer in the light. The handheld camera slowly pushes forward, capturing ripples and wind-blown fabric. His tone is confident yet tense. The atmosphere feels surreal — reflections glisten and mist drifts through golden rays. --- ☁️ 3. Send to Veo3 API The cinematic description is sent directly to the Veo3 video generation API to create the visual clip. POST Request https://queue.fal.run/fal-ai/veo3 Header → Authorization: Key YOURAPIKEY Body → { "prompt": "{{ $json.output }}" } The API responds with a request_id to track progress. --- ⏳ 4. Track Video Progress Monitor generation status and retrieve your final clip details. GET Request https://queue.fal.run/fal-ai/veo3/requests/{{ $json.request_id }} Header → Authorization: Key YOURAPIKEY When complete, the Veo3 model delivers your AI-generated short film. --- ⚙️ Setup Guide Connect APIs • Create a Veo3 (fal.run) account • Copy your API key → Add it under Header Auth: Authorization: Key YOUR_API_KEY Customize Prompts • Change the core question in Node 1 to explore other themes — e.g., “Greek myths,” “ancient warriors,” or “historic leaders.” • Refine the camera and lighting tone in Node 2 for different cinematic vibes (gritty, vintage, surreal). Run & Validate • Trigger manually to test flow • Check JSON output → must include caption, concept, setting, status • Ensure Veo3 receives your cinematic prompt correctly Automate & Expand • Add a Scheduler to generate new ideas daily or weekly • Send results to Google Sheets, Notion, or Discord for creative collaboration --- 🚀 Ideal For • 🎬 Creators & Filmmakers → Quickly generate cinematic ideas & AI-shot scripts • 🙏 Faith-Based Artists → Reimagine ancient lessons with modern storytelling • 💡 Creative Studios → Automate short video ideation for campaigns • 🧠 Educators & Animators → Visualize history or mythology through creative AI prompts ---
By NiteshPost unassigned Zendesk tickets to Slack
> This has been updated to support the Query feature added to the Zendesk node in 0.144.0 This workflow will post all New and Open tickets without an agent assigned to a Slack channel on a schedule. The function node is used in this example to merge multiple inputs into one output message which is then used as the Slack message. The output in Slack will be similar to the below message, The "TICKET_ID" will be a link to the ticket. > Unassigned Tickets TICKETID [STATUS] - TICKETSUBJECT Usage Update the Cron schedule, The default value is 16:30 daily. Update the Credentials in the Zendesk nodes Update the Credentials and Channel in the Slack Node Grab a coffee and enjoy! Zendesk Query In the Zendesk node we are using the query assignee:none status<pending this returns all New and Open tickets with no assignee allowing us to remove the extra nodes.
By Jonathan Bennetts