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 ShcherbakovEnrich property inventory survey with image recognition and AI agent
This n8n workflow assists property managers and surveyors by reducing the time and effort it takes to complete property inventory surveys. In such surveys, articles and goods within a property may need to be captured and reported as a matter of record. This can take a sizable amount of time if the property or number of items is big enough. Our solution is to delegate this task to a capable AI Agent who can identify and fill out the details of each item automatically. How it works An AirTable Base is used to capture just the image of an item within the property Our workflow monitoring this AirTable Base sends the photo to an AI image recognition model to describe the item for purpose of identification. Our AI agent uses this description and the help of Google's reverse image search in an attempt to find an online product page for the item. If found, the product page is scraped for the item's specifications which are then used to fill out the rest of the details of the item in our Airtable. Requirements Airtable for capturing photos and product information OpenAI account to for image recognition service and AI for agent SerpAPI account for google reverse image search. Firecrawl.dev account for webspacing. Customising this workflow Try building an internal inventory database to query and integrate into the workflow. This could save on costs by avoiding fetching new each time for common items.
By Jimleuk🎦🚀 YouTube video comment analysis agent
🎦🚀 YouTube Video Comment Analysis Agent This n8n workflow is designed to help YouTube creators analyze video details and comments to generate a comprehensive and actionable report. The workflow provides insights into video performance, audience engagement, and viewer feedback, helping creators identify trends, interests, and opportunities for future content creation. --- ✨ Key Features Video Performance Analysis: Extracts metrics like views, likes, and comments to evaluate the video's success. Comment Sentiment Analysis: Determines the tone of comments (positive, neutral, or negative) to understand audience sentiment. Recurring Themes Detection: Identifies common topics or questions in comments to highlight viewer interests. Engagement Drivers: Pinpoints what aspects of the video resonated most with viewers. Actionable Recommendations: Offers strategies for creating follow-up content or improving future videos. Keyword Suggestions: Extracts frequently mentioned terms for better discoverability on YouTube. Collaboration Opportunities: Suggests potential partnerships based on viewer feedback or related channels. --- 🛠️ How to Use Set Up Workflow Variables: Add your GOOGLEAPIKEY and the VIDEO_ID of the YouTube video you want to analyze in the "Workflow Variables" node. Ensure your Google API key has access to the YouTube Data API. Run the Workflow: Trigger the workflow manually or through another workflow using the "Execute Workflow Trigger" node. The workflow will fetch video details and comments using pagination to ensure all data is captured. Generate Insights: The workflow processes video details and comments to create a detailed report with actionable insights. Outputs include sentiment analysis, engagement drivers, content opportunities, and audience profiling. View or Share Results: The report is converted into Markdown and can be emailed via Gmail or saved to Google Drive as a document. --- 🌟 Value from This Workflow Gain a deeper understanding of your audience's preferences and feedback. Identify trends and engagement drivers to replicate success in future videos. Discover new content opportunities based on viewer questions and suggestions. Improve discoverability by leveraging keyword suggestions extracted from comments. Build stronger connections with your audience by addressing their needs effectively.
By Joseph LePageSend RSS feed data to webhook
Filters articles based on keywords, checks against MongoDB for unique links, then sends results to different webhooks
By daveGenerate & 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 SolutionsClone viral TikTok & Instagram reels with Apify and Gemini 2.5 Pro
Reverse engineer short-form videos from Instagram and TikTok using Gemini AI Who's it for Content creators, AI video enthusiasts, and digital marketers who want to analyze successful short-form videos and understand their production techniques. Perfect for anyone looking to reverse-engineer viral content or create detailed prompts for AI video generation tools like Google Veo or Sora. How it works This automation takes any Instagram Reel or TikTok URL and performs a forensic analysis of the video content. The workflow downloads the video, converts it to base64, and uses Google's Gemini 2.5 Pro vision API to generate an extremely detailed "Generative Manifest" - a comprehensive prompt that could be used to recreate the video with AI tools. The analysis includes: Visual medium identification (film stock, camera sensor, lens characteristics) Color grading and lighting breakdown Shot-by-shot deconstruction with precise timing Camera movement and framing details Subject description and action choreography Environmental and atmospheric details How to set up Configure API credentials: Add your Apify API key for video scraping Set up Google Gemini API authentication Set up Slack integration (optional): Configure Slack OAuth for result sharing Update the channel ID where results should be posted Access the form: The workflow creates a web form where you can input video URLs Form accepts both Instagram Reel and TikTok URLs Requirements Apify account with API access for video scraping Google Cloud account with Gemini API enabled Slack workspace (optional, for sharing results) Videos must be publicly accessible (no private accounts) How to customize the workflow Modify the analysis prompt: Edit the "setbaseprompt" node to adjust the depth and focus of the video analysis Add different platforms: Extend the switch node to handle other video platforms Integrate with other tools: Replace Slack with email, Discord, or other notification systems
By Lucas WalterCreate 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 BeenScrape TikTok profile & transcript with Dumpling AI and save to Google Sheets
Who is this for? This workflow is built for marketers, researchers, and content analysts who need to monitor TikTok content, analyze user data, or track trends across influencers. It's useful for agencies that manage creators or want to keep an organized record of profile performance and video content for reporting or outreach. --- What problem is this workflow solving? Instead of manually checking TikTok profiles or watching videos to understand performance or content, this workflow automates everything. It extracts both profile statistics and full video transcripts, then logs them in Google Sheets for easy access, filtering, and segmentation. --- What this workflow does The automation watches for new TikTok video URLs added to a Google Sheet. When a new row is detected: It extracts the username from the URL. Sends the username to Dumpling AI to get full profile data (followers, likes, videos). Sends the video URL to Dumpling AI to extract the full transcript. Appends all this information back into the same sheet. Everything happens automatically after a new URL is added to the sheet. --- Setup Google Sheets Trigger Connect your Google account and select the spreadsheet where TikTok links will be added. The workflow will trigger on each new row. Example sheet column: USERNAME Video Extract Username This Set node uses RegEx to extract the username (handle) from the TikTok video URL. No need to change anything unless TikTok URL formatting changes. Dumpling AI Profile Scraper Go to Dumpling AI Sign in and retrieve your API key Create an agent using the get-tiktok-profile endpoint Paste your API key into the httpHeaderAuth field in n8n Dumpling AI Transcript Scraper Also uses Dumpling AI Make sure the endpoint get-tiktok-transcript is enabled in your Dumpling account Connect using the same API key Save to Google Sheets The final node appends data back to your original Google Sheet Required columns: USERNAME Video, Username, Follower count, Following Count, heart count, Video Count, Transcript --- How to customize this workflow to your needs Add a filter node to only save profiles with a minimum follower count Add sentiment analysis for the transcript using OpenAI Connect Airtable or Notion instead of Google Sheets Use GPT to summarize or classify transcripts for research --- ⚠️ Notes Requires a Dumpling AI account and API key Make sure Google Sheets API is connected and has the correct permissions TikTok usernames must start with @ for RegEx to work ---
By Yang