Workflow Templates

Complete MCP server exposing all Pushbullet Tool operations to AI agents. Zero configuration needed - all 4 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Pushbullet Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Pushbullet Tool tool with full error handling 📋 Available Operations (4 total) Every possible Pushbullet Tool operation is included: 🔧 Push (4 operations) • Create a push • Delete a push • Get many pushes • Update a push 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Pushbullet Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Pushbullet Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Learn n8n: Interactive Lesson 1 This interactive tutorial teaches you how to build in n8n from scratch, using a live walkthrough with real-time examples. Rather than static documentation, this guided workflow explains key n8n concepts while you execute each step. It is ideal for developers new to n8n but experienced with programming, JSON, and APIs. Requirements An active n8n instance (cloud or self-hosted) Basic programming experience (JavaScript or TypeScript, JSON, and APIs) Web browser with console access (for log inspection) What This Workflow Covers Triggers, Form nodes, and data flow How n8n executes nodes one step at a time How data moves between nodes (variables, context, side effects) Merge, Split, Aggregate, and Loop patterns Code nodes in single vs multiple execution modes Debugging using Logs and console output Step-by-Step Setup Manual Setup Before starting, create your n8n account and optionally enable dark mode. A video link is included with suggested background material. Form-Based Progression The tutorial uses Form Trigger and Form nodes as interactive checkpoints. You will execute the workflow, follow the browser prompts, and observe what happens in the visual editor. Live Code and Flow Examples Key concepts like branching, merging, and data references are shown in action. Sticky notes in the workflow explain what to look for and how things work. Execution Behavior You will see how multiple items affect execution count, and how to control it using options like Execute Once, batching, and aggregation. Debugging with Logs Toward the end, the workflow encourages you to inspect inputs and outputs of each node, and use console.log() inside Code nodes to understand the data being passed around. How to Use This Workflow This workflow is meant to be a long-term reference. If you get stuck building in n8n, return to it. Each section focuses on a core concept such as how data flows, how execution counts behave, or how to merge parallel branches. You can copy and paste working examples from this tutorial directly into your own workflows to solve common problems. This is not just a lesson. It's a toolbox.

This workflow automates the generation of AI-enhanced, contextualized images using FLUX Kontext, based on prompts stored in a Google Sheet. The generated images are then saved to Google Drive, and their URLs are written back to the spreadsheet for easy access. Example Image: Prompt: The girl is lying on the bed and sleeping Result: Perfect for E-commerce and Social Media This workflow is especially useful for e-commerce businesses: Generate product images with dynamic backgrounds based on the use-case or season. Create contextual marketing visuals for ads, newsletters, or product pages. Scale visual content creation without the need for manual design work. How It Works Trigger**: The workflow can be started manually (via "Test workflow") or scheduled at regular intervals (e.g., every 5 minutes) using the "Schedule Trigger" node. Data Fetch**: The "Get new image" node retrieves a row from a Google Sheet where the "RESULT" column is empty. It extracts the prompt, image URL, output format, and aspect ratio for processing. Image Generation**: The "Create Image" node sends a request to the FLUX Kontext API (fal.run) with the provided parameters to generate a new AI-contextualized image. Status Check**: The workflow waits 60 seconds ("Wait 60 sec." node) before checking the status of the image generation request via the "Get status" node. If the status is "COMPLETED," it proceeds; otherwise, it loops back to wait. Result Handling**: Once completed, the "Get Image Url" node fetches the generated image URL, which is then downloaded ("Get Image File"), uploaded to Google Drive ("Upload Image"), and the Google Sheet is updated with the result ("Update result"). Set Up Steps To configure this workflow, follow these steps: Google Sheet Setup: Create a Google Sheet with columns for PROMPT, IMAGE URL, ASPECT RATIO, OUTPUT FORMAT, and RESULT (leave this empty). Link the sheet in the "Get new image" and "Update result" nodes. API Key Configuration: Sign up at fal.ai to obtain an API key. In the "Create Image" node, set the Header Auth with: Name: Authorization Value: Key YOURAPIKEY Google Drive Setup: Specify the target folder ID in the "Upload Image" node where generated images will be saved. Schedule Trigger (Optional): Adjust the "Schedule Trigger" node to run the workflow at desired intervals (e.g., every 5 minutes). Test Execution: Run the workflow manually via the "Test workflow" node to verify all steps function correctly. Once configured, the workflow will automatically process pending prompts, generate images, and update the Google Sheet with results. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This n8n workflow is designed to work on the local network and assists with reconciling downloaded bank statements with internal tenant records to quickly highlight any issues with payments such as missed or late payments or those of incorrect amounts. This assistant can then generate a report to quick flag attention to ensure remedial action is taken. How it works The workflow monitors a local network drive to watch for new bank statements that are added. This bank statement is then imported into the n8n workflow, its contents extracted and sent to the AI Agent. The AI Agent analyses the line items to identify the dates and any incoming payments from tenants. The AI agent then uses an locally-hosted Excel ("XLSX") spreadsheet to get both tenant records and property records. From this data, it can determine for each active tenant when payment is due, the amount and the tenancy duration. Comparing to the bank statement, the AI Agent can now report on where tenants have missed their payments, made late payments or are paying the incorrect amounts. The final report is generated and logged in the same XLSX for a human to check and action. Requirements A self-hosted version of n8n is required. OpenAI account for the AI model Customising this workflow If you organisation has a Slack or Teams account, consider sending reports to a channel for increased productivity. Email may be a good choice too. Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/1YRKjfakpInm23F_g8AHupKPBN-fphWgK/view?usp=sharing

Overview This comprehensive n8n workflow provides a sophisticated solution for dynamically selecting and using AI models while maintaining GDPR compliance. It leverages Requesty's European-based AI routing service to ensure data privacy and automatically updates available model options based on real-time API availability. Choose Your Integration Approach Before diving into the setup, it's crucial to understand that this workflow offers two completely independent AI integration approaches: Approach 1: Dynamic HTTP Request Workflow (Advanced) Complete infrastructure with dynamic model selection What it includes: Automatic model discovery from Requesty's API Dynamic dropdown updates in web forms Model selection persistence in Google Sheets Complex workflow orchestration with multiple phases Full control over API parameters and response handling Best for: Teams needing multiple AI models for different tasks Organizations requiring model usage auditing Users who want maximum flexibility and control Advanced n8n users comfortable with complex workflows Setup complexity: High (requires multiple components and configurations) Approach 2: Standalone AI Agent (Simple) Plug-and-play solution without complexity What it includes: Direct use of n8n's native OpenAI Chat Model node Simple configuration: just set base URL to https://router.requesty.ai/v1 Immediate GDPR compliance through European infrastructure No model discovery or selection infrastructure needed Best for: Users wanting quick GDPR-compliant AI integration Single-model use cases Simple chat interfaces Users preferring minimal configuration Setup complexity: Low (5-minute setup) Quick Start: Approach 2 (Simple AI Agent) If you want to get started quickly with GDPR-compliant AI, follow these steps: Step 1: Register with Requesty Visit https://www.requesty.ai Complete the registration process Choose "OpenAI-compatible" integration Note your API endpoint: https://router.requesty.ai/v1 Create an API key (name it "n8n Integration") Step 2: Configure n8n Add a new OpenAI credential in n8n Set the base URL to: https://router.requesty.ai/v1 Enter your Requesty API key Add an OpenAI Chat Model node to your workflow Select your Requesty credential Step 3: Test Your AI agent is now ready and GDPR-compliant! All requests will be routed through Requesty's European infrastructure. Advanced Setup: Approach 1 (Dynamic HTTP Workflow) For users who need dynamic model selection and advanced features, follow this comprehensive setup: Prerequisites n8n instance (self-hosted or cloud) Requesty API credentials Google Sheets integration Basic understanding of n8n workflows Phase 1: Requesty Account Setup 1.1 Registration Process Navigate to https://www.requesty.ai Sign up with your email address Complete the welcome process 1.2 Integration Configuration Choose Integration Type: Select "OpenAI-compatible" Note API Endpoint: https://router.requesty.ai/v1 Create API Key: Provide a descriptive name (e.g., "n8n Dynamic Workflow") Click "Create API Key" Important: Save this key securely - you'll need it for n8n configuration Phase 2: Google Sheets Preparation 2.1 Create Storage Sheet Create a new Google Sheet named "AI Model Selections" Add the following column: A1: "Selected Model" Note the Google Sheet ID from the URL 2.2 Configure Google Sheets API Enable Google Sheets API in Google Cloud Console Create service account credentials Share your sheet with the service account email Download the credentials JSON file Phase 3: n8n Workflow Configuration 3.1 Import Workflow Download the workflow JSON file Import into your n8n instance Review all nodes and connections 3.2 Configure Credentials Requesty API Credentials: Go to n8n Credentials section Create new HTTP Request credential Set authentication type to "Header Auth" Header name: "Authorization" Header value: "Bearer YOUR_REQUESTY_API_KEY" Google Sheets Credentials: Create new Google Sheets credential Upload your service account JSON file Test the connection Google Sheets Nodes: Update sheet ID in all Google Sheets nodes Verify column mappings match your sheet structure Phase 4: Troubleshooting Guide Common Issues and Solutions Models Not Loading: Verify Requesty API credentials Check network connectivity and API endpoint URL Selection Not Persisting: Verify Google Sheets credentials and write permissions Check sheet ID configuration Chat Not Responding: Verify selected model availability Check API request formatting and response processing Debug Procedures Enable debug mode and detailed logging Check node outputs and data flow Validate API calls with external tools Review n8n execution logs Conclusion The choice between approaches depends on your specific requirements: Simple AI Agent**: Perfect for straightforward AI integration with minimal setup Dynamic HTTP Workflow**: Ideal for complex requirements with multiple models and advanced features

✍️🌄 WordPress + AI Content Creator This workflow automates the creation and publishing of multi-reading-level content for WordPress blogs. It leverages AI to generate optimized articles, automatically creates featured images, and provides versions of the content at different reading levels (Grade 2, 5, and 9). How It Works Content Generation & Processing 🎯 Starts with a manual trigger and a user-defined blog topic Uses AI to create a structured blog post with proper HTML formatting Separates and validates the title and content components Saves a draft version to Google Drive for backup Multi-Reading Level Versions 📚 Automatically rewrites the content for different reading levels: Grade 9: Sophisticated language with appropriate metaphors Grade 5: Simplified with light humor and age-appropriate examples Grade 2: Basic language with simple metaphors and child-friendly explanations WordPress Integration 🌐 Creates a draft post in WordPress with the Grade 9 version Generates a relevant featured image using Pollinations.ai Automatically uploads and sets the featured image Sends success/error notifications via Telegram Setup Steps Configure API Credentials 🔑 Set up WordPress API connection Configure OpenAI API access Set up Google Drive integration Add Telegram bot credentials for notifications Customize Content Parameters ⚙️ Adjust reading level prompts as needed Modify image generation settings Set WordPress post parameters Test and Deploy 🚀 Run a test with a sample topic Verify all reading level versions Check WordPress draft creation Confirm notification system This workflow is perfect for content creators who need to maintain a consistent blog presence while catering to different audience reading levels. It's especially useful for educational content, news sites, or any platform that needs to communicate complex topics to diverse audiences.

How it works This template takes a YouTube video ID and identifies potentially engaging moments based on the intensity of specific timestamps 👇 Ideal for vloggers and YouTube content creators, it serves as a foundation for various automations to streamline content calendars or highlight popular moments in your videos. You can leverage it for: Automatic processes to analyze YouTube videos and create sizzle reels or clips for social media, particularly effective for microcontent strategies like those endorsed by Gary Vee. Instant alerts via Slack, Telegram, Email, or WhatsApp when significant moments occur in your videos. Utilizing transcripts of these moments with AI to refine content ideas or brainstorm chatbots in your editorial workflow. Example response from the Workflow-as-an-API A GET request to {your instance URL}/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy returns 👇 The workflow generates multiple moments; the screenshot above shows a truncated version. Not all videos contain timestamp intensity data, the workflow handles this case as well 👇 How to use Import the template into your n8n workspace or self-hosted instance, then activate the workflow. Open the Webhook trigger node and copy the Production URL. In a web browser or any tool capable of consuming HTTP Requests (e.g., native code, Bubble app, n8n workflow, another automation tool, Postman, etc.), pass along the URL parameter ?ytID={youtube video ID} when invoking the API endpoint. Your URL should resemble something like https://acme.app.n8n.cloud/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy. Keep in mind This workflow relies on an unofficial YouTube API graciously hosted for free by the folks at lemnoslife.com. It's not recommended for high-volume production usecases.

Use case LLMs have provided a lot of value for several use cases. Especially some OpenAI models are proving to be quite valuable. However, it's sometimes not super accessible to chat with these models. This workflow enables you to chate directly with OpenAI's GPT-3.5 via Telegram. How it works A simple telegram bot that connects to your botfather bot to give AI responses, using OpenAI's GPT 3.5 model, to a user's messages with emojis. What to do Add your telegram API key and your OpenAI api key and have fun!

Automating LinkedIn Connection Requests Use Case Automatically sending LinkedIn connection requests to prospects can significantly streamline your outreach process. This automation ensures you only send requests to users you're not already connected with, and can optionally include a personalized message. What This Automation Does This automation sends a LinkedIn connection request using the following input parameters: linked_url**: The LinkedIn profile URL of the person you want to connect with. airtop_profile**: The name of your Airtop Profile authenticated on LinkedIn. message* *(optional): The note you want to include with your connection request. How It Works Starts an Airtop browser session using your authenticated profile. Opens the target LinkedIn profile in a new browser window. Detects if you're already connected or if a connection request is pending. If the "Connect" button is available: If no message is provided, clicks "Connect" and sends the request without a note. If a message is provided, clicks "Add a note", types the message, and sends the request. Terminates the browser session. Setup Requirements Airtop API Key — free to generate. An Airtop Profile logged in to LinkedIn (requires one-time authentication). Next Steps Pair with People Enrichment**: Use with the LinkedIn Profile Finder to generate URLs before sending requests. CRM Integration**: Log connection attempts and responses in your CRM. Campaign Sequencing**: Combine with message follow-up automations for a complete outreach flow. Read more about automating Linkedin Connection Requests

Complete AI Graphic Design Suite with OpenAI, Replicate & Google Drive Categories: AI Agents, Design Automation, Business Tools This workflow creates a complete AI-powered graphic design system that replaces expensive designers with intelligent automation. Featuring a conversational AI agent that orchestrates 5 specialized design tools, this suite can generate logos, style guides, gradients, and revisions on demand. Built by someone who's scaled automation agencies to $72K/month, this system demonstrates how AI agents can deliver real business value beyond simple chatbots. Benefits Complete Design Automation** - Generate logos, style guides, gradients, and revisions through natural conversation Conversational AI Interface** - Chat-based interaction makes design accessible to non-designers Professional Quality Output** - Uses advanced AI models and proven templates for consistent results Instant Delivery** - Generate designs in seconds vs. days of traditional design processes Scalable Business Tool** - Deploy for clients, embed on websites, or use internally Cost-Effective Solution** - Replace $82K/year designers with $30/month automation How It Works AI Agent Orchestration: Central conversational AI that understands design requests in natural language Automatically selects the right tool based on user needs and context Maintains conversation memory for iterative design improvements Provides professional, helpful responses with design expertise Logo Generation System: Creates professional logos using OpenAI's advanced image generation Supports various styles: minimalistic, corporate, creative, and industry-specific Automatically uploads to Google Drive with shareable links Perfect for startups, rebranding projects, and client work Style Guide Creation: Generates comprehensive brand guidelines using template-based approach Includes color palettes, typography, logo usage, and brand elements Uses AI to customize templates with client-specific information Delivers presentation-ready style guides for professional use Gradient Background Generator: Creates beautiful background gradients for websites and marketing materials Uses proven design templates with AI-powered customization Generates multiple variations and color combinations Perfect for landing pages, social media, and brand materials Design Editor & Revision System: Intelligently revises existing designs based on feedback Handles both Google Drive files and external image URLs Maintains design consistency while implementing requested changes Supports iterative improvements and client feedback cycles Advanced Upscaling Integration: Uses Replicate API to enhance image quality up to 4x resolution Professional print-quality output for all generated designs Seamlessly integrates with all design generation tools Perfect for high-resolution marketing materials and presentations Required Setup Configuration OpenAI API Setup: Connect your OpenAI API for: GPT-4 conversation handling and design guidance DALL-E (4o) image generation for all design tools Intelligent prompt processing and tool selection Google Drive Integration: Create template files for style guides and examples Set up OAuth credentials for file management Configure sharing permissions for client access Organize folders for different design categories Replicate API Configuration: Set up account for image upscaling capabilities Replace <your-replicate-api-key-here> with actual API key Configure upscaling factors (2x or 4x options) AI Agent System Message: Configure the agent with business context: You are a helpful, intelligent design assistant. You generate high-quality designs using the provided tools (generate logo, generate style guide, and generate gradient background). Then you can also upscale them, and finally, you can revise them. When you receive an image from a tool, wrap it in nice looking Markdown (atx) format and present it to the user. The only things you can generate are logos, style guides, and gradient backgrounds. Make sure to clarify which (as well as any additional information needed) so the prompt you send to the image model is optimal. If you are asked to adjust or revise an image, ask the user to define their changes as explicitly as possible. Chat Integration Options: Embedded website chat widget for client-facing design services Direct chat interface for internal team use Hosted chat endpoint for external integrations Business Use Cases Design Agencies** - Offer automated design services with instant delivery and unlimited revisions Marketing Teams** - Generate brand assets, social media graphics, and campaign materials on demand Startups** - Create professional branding without expensive design budgets Consultants** - Provide design services as value-added offerings to clients Web Developers** - Offer integrated design services alongside development projects E-commerce Businesses** - Generate product graphics, banners, and promotional materials Revenue Potential This system transforms design service economics: Replace $82K/year designers** with $30/month automation costs Instant delivery advantage** - complete designs in minutes vs. days Unlimited revisions** without additional designer time costs Premium service offering** - charge $1,500-5,000 per client implementation Scalable white-label solution** for agencies and consultants 24/7 availability** for time-sensitive client requests Difficulty Level: Intermediate Estimated Build Time: 2-3 hours Monthly Operating Cost: ~$30 (OpenAI + Replicate APIs) Watch My Complete Build Process Want to see exactly how I built this entire AI design system from scratch? I walk through the complete development process, including AI agent setup, tool integration, and the business strategy behind replacing expensive designers with intelligent automation. 🎥 Watch My Live Build: "This AI Agent Replaces an $82k/yr Graphic Designer (N8N)" This comprehensive tutorial shows the real development approach - including agent design patterns, tool orchestration, and the exact prompting strategies that deliver professional-quality results. Set Up Steps Core AI Agent Configuration: Set up chat trigger with embedded and hosted options Configure OpenAI chat model with design-focused system prompts Add memory buffer for conversation context and design iterations Design Tool Integration: Configure all 5 specialized design workflows as callable tools Set up proper data flow between agent and design generators Test tool selection logic with various design requests Template and Asset Management: Upload design templates to Google Drive for style guide generation Configure file sharing permissions for client access Set up organized folder structure for different design types Quality Control Setup: Test complete design workflows from request to delivery Validate AI output quality across all design categories Optimize prompts and templates based on actual usage patterns Client Integration Options: Embed chat widget on client websites for design services Set up hosted endpoints for external system integration Configure branding and messaging for client-facing interactions Advanced Extensions Scale the system with additional capabilities: Industry-Specific Templates** - Customize design styles for different verticals Brand Consistency Engine** - Maintain design standards across all generated assets Client Portal Integration** - Automated design delivery with approval workflows Multi-Language Support** - Generate designs with international text and cultural considerations Advanced Analytics** - Track design performance and client satisfaction metrics Print Production Tools** - Generate print-ready files with proper color profiles and dimensions Why This System Works The competitive advantage lies in intelligent automation combined with professional quality: Natural conversation interface** eliminates design tool complexity Template-based generation** ensures consistent, professional results Instant iteration capability** allows real-time design improvements Cost advantage** enables competitive pricing while maintaining margins 24/7 availability** provides service levels impossible with human designers Scalable delivery** handles multiple clients simultaneously without quality degradation Check Out My Channel For more advanced AI automation systems that generate real business results, explore my YouTube channel where I share the exact strategies used to build successful automation agencies and scale to $72K+ monthly revenue.

This workflow is a modification of the previous template on how to create an SQL agent with LangChain and SQLite. The key difference – the agent has access only to the database schema, not to the actual data. To achieve this, SQL queries are made outside the AI Agent node, and the results are never passed back to the agent. This approach allows the agent to generate SQL queries based on the structure of tables and their relationships, without having to access the actual data. This makes the process more secure and efficient, especially in cases where data confidentiality is crucial. 🚀 Setup To get started with this workflow, you’ll need to set up a free MySQL server and import your database (check Step 1 and 2 in this tutorial). Of course, you can switch MySQL to another SQL database such as PostgreSQL, the principle remains the same. The key is to download the schema once and save it locally to avoid repeated remote connections. Run the top part of the workflow once to download and store the MySQL chinook database schema file on the server. With this approach, we avoid the need to repeatedly connect to a remote db4free database and fetch the schema every time. As a result, we reach greater processing speed and efficiency. 🗣️ Chat with your data Start a chat: send a message in the chat window. The workflow loads the locally saved MySQL database schema, without having the ability to touch the actual data. The file contains the full structure of your MySQL database for analysis. The Langchain AI Agent receives the schema, your input and begins to work. The AI Agent generates SQL queries and brief comments based solely on the schema and the user’s message. An IF node checks whether the AI Agent has generated a query. When: Yes: the AI Agent passes the SQL query to the next MySQL node for execution. No: You get a direct answer from the Agent without further action. The workflow formats the results of the SQL query, ensuring they are convenient to read and easy to understand. Once formatted, you get both the Agent answer and the query result in the chat window. 🌟 Example queries Try these sample queries to see the schema-driven AI Agent in action: Would you please list me all customers from Germany? What are the music genres in the database? What tables are available in the database? Please describe the relationships between tables. - In this example, the AI Agent does not need to create the SQL query. And if you prefer to keep the data private, you can manually execute the generated SQL query in your own environment using any database client or tool you trust 🗄️ 💭 The AI Agent memory node does not store the actual data as we run SQL-queries outside the agent. It contains the database schema, user questions and the initial Agent reply. Actual SQL query results are passed to the chat window, but the values are not stored in the Agent memory.

Avoid Asking Redundant Questions with Dynamically Generated Forms using OpenAI Target Audience This workflow has been built for those who require a form to capture as much data as possible as well as the answers to predefined questions, whilst optimising the user experience by avoiding asking redundant questions. Use Case When creating a form to capture information, it can be useful to give the user an opportunity to input a long answer to a large, open-ended question. We then want to drill down to answer specific questions that we require the answer to. When doing this, we don't want to ask duplicate questions. This particular scenario imagines an AI consultancy capturing leads. What it Does This workflow requires users to input basic information and then answer an open ended question. The specific questions on the next page will only be those that weren't answered in the open-ended question. How it Works The open-ended question (and relevant basic information) is analysed by an LLM to determine which specific questions have not been answered. Chain-of-thought reasoning is utilised and the output structure is specified with the Structured Output Parser. Those questions that have already been answered are filtered out nodes. The remaining items are then used to generate the last page of the form. Once the user has filled in the final page of the form, they are shown a form completion page. Setup Add your OpenAI credentials Go to the Get Basic Information node and click Test Step Complete the form to test the generic use case Modify the prompt in Analyse Response to fit your use case Next Steps Add additional nodes to send an email to the form owner Add a subsequent LLM call to analyse the form response - those that are qualified should be given the opportunity to book an appointment