Templates by RealSimple Solutions
🎨 AI design team - generate and review AI images with Ideogram and OpenAI
🎨 AI Graphic Design Team - Generate and Review AI Images with Ideogram and OpenAI Description Who is this for? This workflow is perfect for graphic designers, creative agencies, marketing teams, or freelancers who regularly use AI-generated images in their projects. It's specifically beneficial for teams that want to automate the generation, review, and management of AI-created graphics efficiently. What problem does this workflow solve? Design teams often face time-consuming manual reviews and inconsistent quality checks for AI-generated images. This workflow addresses these challenges by automating image generation and introducing a systematic, AI-driven vetting process. This ensures only high-quality, relevant images reach your team's assets, saving valuable time and enhancing workflow efficiency. What this workflow does AI Image Generation: Integrates Ideogram via HTTP Request to automatically create AI-generated images based on creative briefs. Automated Image Review: Uses OpenAI to automatically evaluate and approve images, ensuring they meet your predefined quality standards. Efficient Asset Management: Automatically creates structured Google Drive folders and compiles key metadata (including creation dates, prompts, and image links) into a CSV file and Google Sheet. Immediate Email Notifications: Delivers a setup confirmation and provides easy access to Google Drive folders and assets via automated email notifications. Final Approved Images: Outputs vetted, ready-to-use images for your creative projects, removing the burden of manual reviews. --- Setup --- Initial Email Configuration Update your email details in both the "Setup Gmail" node and the "Gmail" notification node. Run the initial setup workflow to automatically create the Google Drive folders "GraphicDesignTeam" and "ImageGenerations," and upload your CSV file (n8n-GraphicDesign_Team.csv). Review Email & Set Up Google Sheets Check your inbox for an automated email containing folder IDs and direct links. Create and set up a Google Sheet by importing the provided CSV data from your email. Update Workflow Nodes Select your newly created Google Sheet in both Google Sheets nodes. Update your Creative Brief node with the Google Drive folder IDs provided in the email. Run Workflow for AI Image Generation & Review Execute the workflow. Your generated images will be automatically vetted, organized, and ready for creative use. How to Customize This Workflow Tailor Image Generation Prompts: Adjust prompts and settings in the Ideogram HTTP Request node to better fit your project's creative requirements. Set Quality Standards: Modify the criteria used by the OpenAI node to reflect your specific standards and preferences for image approval. Customize Asset Organization: Adapt Google Drive folder structures, CSV headers, or Google Sheets integrations to match your team's organizational preferences. Dependencies & Requirements Nodes Used: HTTP Request (Ideogram API integration) OpenAI (Image review and quality assessment) Gmail (Automated notifications) Google Drive (File and asset management) Google Sheets (Metadata organization) Credentials: Ensure Gmail, Google Drive, Google Sheets, and OpenAI credentials are properly configured in your n8n account. No custom or community nodes are needed. Final Outcome Upon completion, your workflow efficiently provides vetted, high-quality AI-generated images, organized in Google Drive and accessible via easy-to-use metadata in Google Sheets, drastically reducing manual intervention and accelerating your creative processes.
By RealSimple SolutionsFetch 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 Solutions🥇 Token Estim8r -sub workflow to track AI model token usage and cost with JinaAI
Save Your Tokens from Evil King Browser > Image Generated with ideoGener8r n8n workflow template --- 🔍 Estimate token usage and AI model cost from any workflow in n8n 🙋♂️ Who is this for? This workflow is ideal for AI engineers, automation specialists, and business analysts who use OpenAI, Anthropic, or other token-based large language models (LLMs) in their n8n workflows and want to track their usage and accuratley estimate associated costs. Whether you're prototyping workflows or deploying in production, this tool gives you insight into how many tokens you're using and what that translates to in actual dollars. 😌 What problem is this workflow solving? n8n users running AI-based workflows often struggle to track how many tokens were used per execution and how much those tokens cost. Without visibility into usage, it’s easy to lose track of API spending. This workflow solves that problem by: Logging token counts and costs to Google Sheets Supporting prompt and completion token counts Providing live pricing (optional, via Jina AI API) ⚙️ What this workflow does This template allows you to analyze the token usage and cost of any workflow in n8n. It uses an Execute Workflow node to call the Token Estim8r utility, which: Estimates prompt and completion tokens Retrieves model pricing (either statically or live via Jina API) Calculates the total cost Logs the data to a connected Google Sheet with timestamp and model info 🛠️ Setup Instructions Create Google Sheet: Copy and paste the CSV template below into a .csv file and upload to Google Sheets: timestamp, Total Tokens, Prompt Tokens, Completion Tokens, Models Used, Tools Used, Total Cost, Json Array Set up pricing (optional): In the Get AI Pricing node, add your Jina API Auth Header if you want live pricing. Select the correct Google Sheet: Ensure your workflow is pointing to the imported sheet. Attach to your target workflow: Add an Execute Workflow node to the end of your target workflow. Point to this Token Estim8r: Choose this template as the executed workflow and send {{ $execution.id }} as the input. Run and view results: Trigger the target workflow and see your token usage and cost data populate in the sheet. --- 🔧 How to customize this workflow to your needs Change the logging destination: Instead of Google Sheets, connect to Airtable, Notion, or a database. Support multiple models: Extend the price-mapping logic to cover your own model providers. Add Slack alerts: Send a notification if a workflow exceeds a token or cost threshold. Aggregate costs: Create a weekly summary workflow that totals cost by workflow or model. --- > This utility workflow works across all n8n deployment types and uses only built-in nodes.
By RealSimple Solutions✨ ideoGener8r – complete Ideogram AI image generator UI with Google integration
--- ideoGener8r – Self-Hosted Ideogram AI Interface in n8n 🔥 March Sale – n8n Community Members Get ideoGener8r for Just $27! (Reg. $47) Use Coupon Code: ILoven8n (Valid until 3/31/2025 for n8n community members) --- ideoGener8r is an n8n template that sets up a self-contained, front-end interface for Ideogram AI image generation. It offers a complete workflow to generate, upscale, remix, and store images—entirely on your self-hosted n8n instance. --- Key Benefits & Limited-Time Offer Fully Self-Hosted: Avoid monthly fees and keep your data private. All-in-One: Generate, remix, and upscale images without third-party tools. Streamlined Automation: Integrates directly with Google Sheets & Drive. Sale: Save $20 – Get ideoGener8r for just $27 with coupon code ILoven8n (valid until 3/31/2025). --- Requirements & Overview Ideogram AI API Key Sign up at Ideogram AI and create an API key. Google Sheets & Drive A Google Sheet for storing metadata. A Google Drive folder for saving generated images. n8n Auth Credentials Basic Auth for the login webhook. Header Auth (Bearer token) for the generation/remix webhooks. With ideoGener8r, you can instantly create a private user interface—within n8n—to produce AI images on demand, trigger image generation through webhooks, and automatically log data to Google Sheets. --- Required Google Sheet Columns Your Google Sheet must contain (at minimum) the following columns for proper logging: Cheeck Setup note in workflow for csv template --- Step-by-Step Setup Instructions Import the Template Download the JSON file you received upon purchase. In your n8n instance, go to Workflows → Import, then upload the JSON file. Configure Ideogram API In n8n, create an HTTP Header Auth credential. For the “Authorization” header, use Bearer YOURIDEOGRAMAPI_KEY. Attach this credential to the Ideogram-related nodes (e.g., IDEOGRAM Image generator, ideogram Upscale). Google Sheets Setup Copy or create a Google Sheet with the columns listed above. In the template, locate the Google Sheets “Append” nodes. Select the correct Sheet, tab, and map each column accordingly. Google Drive Folder Create a Drive folder to store images (sharing permissions are up to you). In the Google Drive nodes, enter the folder ID to save new images there. Basic Auth for Login Open the Login Webhook-ideoGener8r node. Set it to use Basic Auth and create credentials for a username/password. This will secure the login route (e.g., /ideogener8r-login). Bearer Token for Generation & History Open the “Generation Webhook” (e.g., /ideogen) and “History Webhook” (e.g., /ideogener8r-history). Set them to Header Auth and use Authorization: Bearer <YOURSECRETTOKEN>. Any requests to these endpoints must include that token in the header. Publish & Test Activate or publish your workflow. Go to /ideogener8r-login, enter your Basic Auth credentials, and test by generating images. Verify that images appear in your Google Drive folder, and the metadata is logged in the Google Sheet. --- Ideogram API Details Endpoint: The template uses Ideogram’s /generate, /upscale, and /remix endpoints. Headers: You must provide your API key as a Bearer token in the request header. Rate Limits: Check your Ideogram AI account for any usage or rate-limiting policies. --- More info at ideoGener8r.com
By RealSimple Solutions🧠 Flowatch 👁️ analyze and diagnose n8n workflow errors via OpenAI and email
🧠 Analyze and Diagnose n8n Workflow Errors Automatically via OpenAI and Email > ⚠️ This template is available on ☁️ Cloud & 🖥️ self-hosted n8n instances with the OpenAI node enabled. --- 👤 Who is this for? This workflow is designed for n8n developers, automation engineers, and DevOps teams who want to automatically capture and analyze workflow errors, and receive professional HTML-styled diagnostics directly in their inbox. --- 💥 What problem does this solve? Manually troubleshooting failed workflows in n8n can be time-consuming. This template streamlines error detection by: Capturing workflow failures using the Error Trigger node Diagnosing root causes with the help of OpenAI Sending a fully-formatted, human-readable HTML error report via email Including practical resolutions and next-step suggestions This helps you or your team resolve issues faster and avoid repeated manual debugging. --- ⚙️ What this workflow does ⚡ Triggers on any n8n workflow error 📦 Extracts relevant error metadata including node, execution ID, and timestamps 🧠 Sends error content to OpenAI for analysis and recommendations 💌 Generates an HTML email report with inline styles and clear formatting 📥 Emails the result to a system administrator or support email --- 🛠️ Setup Install the OpenAI node in your self-hosted n8n instance. Add your OpenAI API Key securely in credentials. Configure the SMTP Email node with your email credentials. Adjust the Error Trigger to monitor specific workflows or all workflows. Set your preferred admin or dev email address in the final node. --- 🔧 How to customize this workflow to your needs 🧩 Use a [Set node] to define your variables, such as: Default admin email Workflow filter (optional) ✍️ Customize the prompt sent to OpenAI if you want deeper or more specific analysis 🎨 Modify the email HTML styles to match your brand or internal format 💾 Add additional logging (e.g., to Airtable, Google Sheets, or Notion) for long-term error tracking --- 📌 Sticky Note Title: Automated Error Reporter with AI-Powered Diagnosis Description: Captures any n8n error, sends it to OpenAI, and emails a beautiful HTML report to the administrator with steps to resolve the issue. Requires OpenAI credentials and SMTP configured.
By RealSimple Solutions🔊 Browser recording audio transcribing and AI analysis with Deepgram and GPT-4o
Overview Transcript Evalu8r V2 is a robust browser-based transcript analysis tool powered by Deepgram’s speech-to-text API and built into an n8n workflow template. This release introduces full in-browser audio recording, device selection, and playback functionality, allowing users to capture and analyze conversations without leaving their browser. Designed for researchers, support teams, podcasters, legal professionals, and analysts, Transcript Evalu8r simplifies how you extract value from voice data using intuitive tools, AI-powered insights, and seamless automation. --- ✅ What’s New in V2 | | | |:--|:--| |🔴 Record in Browser <br>Users can now record audio directly in the browser with one click. Record meetings, calls, or voice notes instantly—no external software required. | 🎧 Select Audio Input Devices <br>Users can choose from connected input devices (e.g., internal mic, USB mic, headset) before recording, ensuring maximum control and audio quality.| ▶️ Listen to Recording in Browser Once a recording is complete, users can immediately play back the audio in-browser to review before submitting for transcription—ensuring content is clear and relevant. --- How It Works Record or upload an audio file Audio recording is uploaded to Google Drive Audio file is sent to Deepgram for transcribing and AI analysis Audio File is moved to completed folder JSON transcript is saved to Google Drive Google Doc of AI analysis, summary, key points, action items, and full transctip is created Use the Web UI to Explore: Speaker Names Transcript Key points & tasks Sentiment chart Topic and intent lists with time stamps Download or export transcript and insights Add Additional automations or continue workflow (e.g., send to Notion, Slack, Google Sheets, todoist) --- --- Key Features 🔹 Transcript Processing & Uploads Upload or record audio directly in your browser Track progress of file uploads in real-time View, select, or download transcripts in Google Docs, JSON, and other formats 🔹 Interactive Transcript Viewer Full transcript display with timestamps, speaker IDs, and auto-scroll Clickable word-level navigation for pinpointing dialogue Real speaker labeling (not just "Speaker 1") 🔹 AI-Powered Analysis Sentiment visualization over time, per speaker Topic and intent extraction with confidence scores Speaker contribution insights, interruptions, and common word frequency 🔹 Insight Summaries Google Doc AI-generated summary, key points, and action items Speaker-specific task suggestions and idea highlights 🔹 UI Enhancements Collapsible sections for focused analysis Light and dark mode support Responsive design across desktop, tablet, and mobile --- Use Cases ✅ Interview & podcast summarization ✅ Customer support QA monitoring ✅ Legal or compliance transcription logging ✅ Market research and trend analysis ✅ Internal meeting follow-up automation --- Requirements n8n instance (self-hosted or cloud) Deepgram API Key (for audio transcription) Supported browser with mic permissions enabled --- Why Choose Transcript Evalu8r V2? 🚀 Instantly record and transcribe within your browser 🧠 Extract sentiment, insights, and intent automatically 📈 Visualize speaker tone and engagement 🎧 Choose audio input for cleaner recordings 🔗 Connect with your favorite tools using n8n’s integrations
By RealSimple Solutions📊 Token Estim8r UI – visualize token usage analytics dashboard in n8n
📊 Visualize all your AI Token Usage analytics Dashboard using a single n8n Workflow --- Artwork Generated with ✨ ideoGener8r n8n workflow template --- Token Estim8r UI is the premium version of our token tracking solution for n8n users who want real-time insight into AI model usage and exact cost per execution — all in a beautifully designed analytics dashboard. We've done the work with over 4000 lines of code for you to simply add a pre-configured HTTP Request node to the end of any workflow you want to track, and Token Estim8r UI will handle the rest: collecting data, analyzing token usage, calculating model costs, and feeding everything into a clean UI with charts, graphs, and summaries. --- 🖼️ What the Dashboard Looks Like --- 🙋♂️ Who is this for? This workflow is perfect for: AI engineers Automation specialists Business analysts Teams using OpenAI, Anthropic, Claude, or any token-based LLM If you’re managing API budgets or optimizing prompt performance, this tool provides immediate visibility into where tokens (and money) are going. --- 😌 What problem does this solve? n8n makes it easy to build powerful workflows — but it doesn’t natively track OpenAI token usage or cost. Without that visibility, it’s impossible to: Know what each automation is costing Spot inefficiencies in prompt construction Track cost trends over time Token Estim8r UI solves that with zero manual logging. --- ⚙️ What this workflow does Fetches detailed execution logs from n8n Extracts prompt/completion token usage per model/tool Optionally retrieves live pricing or use preset pricing as of 4/2025 Calculates total cost per run Sends data to a backend for aggregation Displays a full-featured analytics dashboard with: Total tokens, cost, and usage trends Most used models/tools Workflow-model correlations Cost breakdowns and comparisons Workflow usage over time Auto-complete workflow search with filtering by ID or name Filter by date or workflow (single or all workflows) Built in image server Sortable & searchable data table of filtered results with: Prompt & completion token breakdown Cost calculations Workflow name + direct link to the workflow Link to exact execution in n8n --- 🛠️ How Setup Works Import the Token Estim8r UI workflow into your n8n instance Deploy the included dashboard (React/Next.js app, hosted or self-hosted) Configure Google Sheets or your preferred backend (e.g., Supabase, Airtable) Copy the prebuilt HTTP Request node into the end of any n8n workflow Run your workflow — data is captured, aggregated and stored automatically in Google Sheets 🎉 --- 🔄 What Makes This Better than the simple version? The simple version logs to Google Sheets only. This premium UI version adds: Full analytics dashboard Cost aggregation across all workflows Graphs, filters, and model/tool comparisons --- 🔧 Customization Ideas Switch backend to Supabase or Firebase Add alerts via Slack when costs exceed thresholds Build weekly token cost summaries Track model performance across teams Add filters by user/session/timeframe --- 🧠 Why Users Love It "Token Estim8r UI is exactly what I needed to take control of my AI costs inside n8n. It’s plug and play — and the dashboard makes optimization easy." – Beta user, AI Ops Lead 😐 If you're serious about building with AI in n8n, Token Estim8r UI gives you the visibility to scale confidently. 🚀
By RealSimple SolutionsConvert POML to AI-Ready Prompts & Chat Messages with Zero Dependencies
POML → Prompt/Messages (No-Deps) What this does Turns POML markup into either a single Markdown prompt or chat-style messages\[] — using a zero-dependency n8n Code node. It supports variable substitution (via context), basic components (headings, lists, code, images, tables, line breaks), and optional schema-driven validation using componentSpec + attributeSpec. Credits Created by Real Simple Solutions as an n8n template friendly POML compiler (no dependencies) for full POML feature parity. View more of our templates here Who’s it for Teams who author prompts in POML and want a template-safe way to turn them into either a single Markdown prompt or chat-style messages—without installing external modules. Works on n8n Cloud and self-hosted. What it does This workflow converts POML into: prompt (Markdown) for single-shot models, or messages[] (system|user|assistant) for chat APIs when speakerMode is true. It supports variable substitution via a context object ({{dot.path}}), lists, headings, code blocks, images (incl. base64 → data: URL), tables from JSON (records/columns), and basic message components. How it works Set (Specs & Context): Provide componentSpec (allowed attrs per tag), attributeSpec (typing/coercion), and optional context. Code (POML → Prompt/Messages): A zero-dependency compiler parses the POML and emits prompt or messages[]. > Add a yellow Sticky Note that includes this description and any setup links. Use additional neutral sticky notes to explain each step. How to set up Import the template. Open the first Set node and paste your componentSpec, attributeSpec, and context (examples included). In the Code node, choose: speakerMode: true to get messages[], or false for a single prompt. listStyle: dash | star | plus | decimal | latin. Run → inspect prompt/messages in the output. Requirements No credentials or community nodes. Works without external libraries (template-compliant). How to customize Add message tags (<system-msg>, <user-msg>, <ai-msg>) in your POML when using speakerMode: true. Extend componentSpec/attributeSpec to validate or coerce additional tags/attributes. Preformat arrays in context (e.g., bulleted, csv) for display, or add a small Set node to build them on the fly. Rename nodes and keep all user-editable fields grouped in the first Set node. Security & best practices Never hardcode API keys in nodes. Remove any personal IDs before publishing. Keep your Sticky Note(s) up to date and instructional.
By RealSimple Solutions