Workflow Templates

Disclaimer The Execute Command node is only supported on self-hosted (local) instances of n8n. Introduction KOKORO TTS - Kokoro TTS is a compact yet powerful text-to-speech model, currently available on Hugging Face and GitHub. Despite its modest size—trained on less than 100 hours of audio—it delivers impressive results, consistently topping the TTS leaderboard on Hugging Face. Unlike larger systems, Kokoro TTS offers the advantage of running locally, even on devices without GPUs, making it accessible for a wide range of users. Who will benefit from this integration? This will be useful for video bloggers, TikTokers, and it will also enable the creation of a free voice chat bot. Currently, TTS models are mostly paid, but this integration will allow for fully free voice generation. The possibilities are limited only by your imagination. Note Unfortunately, we can't interact with the KOKORO API via browser URL (GET/POST), but we can run a Python script through n8n and pass any variables to it. In the tutorial, the D drive is used, but you can rewrite this for any paths, including the C drive. Step 1 You need to have Python installed. link Also, download and extract the portable version of KOKORO from GitHub. Create a file named voicegen.py with the following code in the KOKORO folder: (C:\KOKORO). As you can see, the output path is: (D:\output.mp3). import sys import shutil from gradio_client import Client Set UTF-8 encoding for stdout sys.stdout.reconfigure(encoding='utf-8') Get arguments from command line text = sys.argv[1] # First argument: input text voice = sys.argv[2] # Second argument: voice speed = float(sys.argv[3]) # Third argument: speed (converted to float) print(f"Received text: {text}") print(f"Voice: {voice}") print(f"Speed: {speed}") Connect to local Gradio server client = Client("http://localhost:7860/") Generate speech using the API result = client.predict( text=text, voice=voice, speed=speed, api_name="/generate_speech" ) Define output path output_path = r"D:\output.mp3" Move the generated file shutil.move(result[1], output_path) Print output path print(output_path) Step 2 Go to n8n and create the following workflow. Step 3 Edit Field Module. { "voice": "af_sarah", "text": "Hello world!" } Step 4 We’ll need an Execute Command module with the command: python C:\KOKORO\voicegen.py “{{ $json.text }}” “{{ $json.voice }}” 1 Step 5 The script is already working, but to listen to it, you can connect a Binary module with the path to the generated MP3 file D:/output.mp3 Step 6 Click “Text workflow” and enjoy the result. There are more voices and accents than in ChatGPT, plus it’s free. P.S. If you want, there is a detailed tutorial on my blog.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🎬 Seedance Video Marketing AI Agent Description: This AI-powered marketing automation workflow takes a user prompt, researches trending topics, generates a compelling short-form video prompt, and sends it to the Seedance API via Wavespeed to create a ready-to-use video ad — all from a single Telegram message. Built for marketers, founders, and content creators who want to turn trend-based ideas into visual video content without touching a video editor. For the step-by-step video tutorial guide on how to build this workflow, check out: https://youtu.be/2oZ5NhosKgo 🤖 How It Works: 📲 Telegram Trigger  Kick off the workflow by messaging a short prompt (e.g., “Create a 5-second IG ad for my new perfume”) via Telegram. 📈 Trend Research with Perplexity AI (Sonar Pro)  An AI agent scans the latest 14-day trends and selects the top marketing angle based on the product/niche input. 🧠 Video Prompt Engineer (ChatGPT)  Crafts a concise, visually rich video generation prompt — optimized for Seedance — based on the trend insight and product. 🎥 Video Generation (Wavespeed + Seedance API)  Sends the AI-generated prompt to Seedance via Wavespeed to generate a 5-second short-form video ad. 🔁 Status Loop & Response  The workflow checks if the video is ready. Once complete, it sends the final video output URL back to you in Telegram. 🔧 Tools Used: Telegram Trigger & Response Perplexity AI (Sonar Pro) OpenAI Seedance API (via Wavespeed) n8n HTTP Request, Wait, and Loop nodes 💡 Use Cases: Auto-generate TikTok/Instagram ads from current trends Scale creative content generation with zero design work Plug into your marketing chatbot or campaign assistant Use trends as visual inspiration for ad creatives If you like the build, check out my channel and consider subscribing: https://www.youtube.com/@Automatewithmarc

Ever wanted to just tell your 3d printer what to do remotely? This game changer let's you converse with OpenAI agents to manage OctoPrint connected 3d printers. Great for remote management and monitoring with easy to read responses. Query what jobs are available, Load a print job (upload workflow in development, will be released soon for community use), start the print job and request detailed reports on your printers performance as it runs. Chat > AI > OctoPrint API > Your 3d Printer ++Example 1:++ Human Input: "What print job is running?" AI Response: Current Print Job Details, Job Name: Stand v1.gcode File Size: 2,533,233 bytes Estimated Print Time: Approximately 6 hours 15 minutes (22536 seconds) Progress: Completion: 1.97%, Current Position in File: 49,940 bytes, Time Spent Printing: 2,611 seconds (~43.5 minutes), Time Remaining: Approximately 5 hours 34 minutes (20,123 seconds), Status, Current State: Printing." ++Example 2++ Human Input: "Is my 3d Printer ok?" AI Response: "Status: Printing, Operational: Yes, ++Temperature:++ Bed Temperature: Actual: 50°C, Target: 50°C, Nozzle (Tool 0) Temperature: Actual: 200°C, Target: 200°C, ++Connection Status:++ Connection State: Currently connected to the printer, Port: /dev/ttyUSB0, Baudrate: 115200, Summary, Your 3D printer is currently operational and printing without errors. The bed and nozzle temperatures are both at their target values."

An automated n8n workflow that analyzes stocks using RSI and MACD, summarizes insights with OpenAI, and sends a Slack-ready market update every hour. This workflow: Runs hourly from 6:30 AM to 2:30 PM PT, Mon–Fri Checks if the U.S. stock market is open using Alpaca’s /clock API Pulls daily stock bars for a list of tickers via Alpaca’s /v2/stocks/bars Calculates RSI and MACD using a Python code node Categorizes each stock as Buy / Hold / Sell Uses OpenAI Assistant to summarize the results in Slack markdown Sends the message to a specific Slack user or channel

Template to get your public IP address and push it to Namecheaps Dynamic DNS per subdomain. Open "yourdomain.com" Insert your domain and your Namecheap DDNS password Open "subdomains" Replaces and insert your subdomains Execute Workflow Have fun!

This n8n template demonstrates walks you through a fully automated process to generate faceless videos - from script creation to final download - using AI-generated voice, images, and smart video editing. Use cases are many: This tool is perfect for YouTube and Shorts creators who want to publish daily content without showing their face, TikTok and Reels marketers automating voice-over-driven videos, and solopreneurs scaling up their content without hiring a team. It’s also ideal for agencies producing batches of faceless video ads, automation enthusiasts building smart media workflows in n8n, and anyone who’s rich in ideas but tired of spending hours editing. How It Works Phase 1: Provide Topic Input A short topic and idea should be entered into the Idea part in Node Fields - Set Idea inside the workflow in n8n. Trigger the process manually by clicking Test Workflow or Execute Workflow. Phase 2: Script Generation Your idea is passed to Google Gemini's chat model. The model returns a concise, 60-second faceless video script. The script is then reformatted into a structured layout optimized for voice generation and visual synchronization. Phase 3: Audio Generation The formatted script is passed to ElevenLabs, which turns the text into a high-quality voiceover audio. The generated audio is uploaded to Google Drive and made publicly accessible. At the same time, the audio is sent to OpenAI Whisper via a POST request to generate a transcription of the voiceover. Phase 4: Timestamps Generation The tool merges the original script and the OpenAI Whisper-generated transcription. The merged data is passed to Google Gemini's chat model to generate image prompts with precise timestamps. The output is parsed and cleaned using a structured parser to ensure it's in ready-to-use JSON format for image generation. Phase 5: Images Generation The full list of timestamped prompts is is split into individual entries. Each prompt is sent to Leonardo's API that turns text descriptions into visuals. A delay of 30 seconds is added to give the image generation engine enough time to complete rendering. Once completed, the workflow retrieves all final images for the next stage. Phase 6: Images To Video Conversion All generated images are sent to Leonardo's API, which stitches them together based on the structured prompts and timing. A 5-minute wait allows time for rendering. After the wait, the workflow retrieves the generated small videos and makes them downloadable. Then, the tool aggregates all downloaded videos into a single unified structure, preparing them for the final editing. Phase 7: Video Editing and Downloading The raw video, along with timestamps or subtitles, is sent to Shotstack, a video editing tool that supports advanced edits. A delay of 1 minute allows Shotstack to process the edit. Then, the tool checks whether the edited video is finished by Shotstack and ready to be downloaded. Once completed, you can download the final polished video to your local storage for later use. How To Use Download the workflow package. Import the package into your n8n interface. Set up necessary credentials for tools access and usability: For Google Gemini access, please connect to its API in the following nodes: Node Google Gemini Chat Model 1 Node Google Gemini Chat Model 2 For Google Drive access, please ensure connection in the following nodes: Node Upload Audio to Drive Node Make Audio File Public For ElevenLabs access, please connect to its API in the following node: Node Generate Voice For OpenAI Whisper access, please connect to its API in the following node: Node Transcribe Audio with OpenAI Whisper For Leonardo access, please allow connection to its API in the following nodes: Node Generate Images Node Generate Videos/Scenes For Shortstack access, please connect to its API in the following nodes: Node Edit with Shotstack Node Render Final Video with Shotstack Input your video idea or short description as a string in Node Fields - Set Idea in n8n. Run the workflow by clicking Execute Workflow or Test Workflow. Wait the process to run and finish. View the result in Node Download Final Video and download it in your local storage for later use. Requirements Basic setup in Google Cloud Console (OAuth or API Key method enabled) with enabled access to Google Drive. Google Gemini API** access with permission to use chat-based large language models. ElevenLabs API** access for generating high-quality voiceovers from scripts. OpenAI Whisper API** access to transcribe voiceovers into clean text. Leonardo API** access for both image and video generation tasks. Shotstack API** access for editing and rendering the final video with enhanced visuals and timing. How To Customize You can input your requested video topic or description directly in Node Fields – Set Idea. By default, the script length is set to around 60 seconds in Node 60 Second Script Writer. You can easily change this in the prompt to create shorter or longer videos based on your needs. While the default setup uses Google Gemini for script and prompt generation, you can replace it with OpenAI ChatGPT, Claude, or any other compatible chat-based model you prefer. The voiceover is currently created using ElevenLabs, but you’re free to substitute it with other text-to-speech engines like Google Cloud Text-to-Speech, HeyGen, etc. We're using OpenAI Whisper to transcribe the voiceover into text. You can switch to alternatives such as AssemblyAI, Deepgram, or other compatible providers depending on your preference. This workflow uses Leonardo for both image and video generation. You can swap it out for other compatible providers based on availability or style preference. Video editing is handled by Shotstack by default. You can plug in alternatives like Runway, FFmpeg, or other API-based editors depending on your editing needs or desired effects. If you’d like this workflow customized to fit your tools and platforms availability, or if you’re looking to build a tailored AI Agent for your own business - please feel free to reach out to Agent Circle. We’re always here to support and help you to bring automation ideas to life. 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

🔮 Mystic Tarot Bot — AI-Powered iMessage Readings This magical n8n template turns your iMessage inbox into a soulful tarot reading experience powered by Blooio and AI. Users can send in questions or photos of their tarot spreads, and the bot replies like a mystical oracle — interpreting symbols, offering gentle insights, and guiding with poetic warmth. ✨ Ideal for solo reflection, spiritual creators, or client-based guidance services — no tech knowledge needed. 🌟 Use Cases Offer intuitive, emotionally resonant tarot readings via iMessage Support coaching, wellness, and metaphysical businesses with AI-enhanced readings Accept photos of real tarot card spreads or plain text questions Great for automating daily card pulls, client responses, or onboarding into spiritual flows 🧠 Good to Know Built using Blooio’s iMessage API — supports image attachments and conversational replies Includes visual recognition and symbolic interpretation of real tarot card photos Responses generated by OpenAI with a custom “Mystic Tarot Reader” persona Onboards users if they say “Hi” or request a virtual card draw Responds in poetic, spiritually attuned language — no markdown, no tech-speak ⚙️ How it Works Trigger: iMessage webhook via Blooio receives user message or image Check: Bot ignores self-sent messages to prevent loops Detect: If a photo is attached, it’s passed to AI for card recognition Interpret: The AI agent gives a heartfelt, symbolic interpretation Respond: A final, warm tarot reading is sent back through iMessage 📝 How to Use Set Up Blooio: Sign up at https://blooio.com Choose a Dedicated or Enterprise plan (image support required) Copy your API key from Settings → API Keys Paste it into the Send Message HTTP node as a Bearer token Customize the Experience: Adjust the prompt for a different tone or deck style Add journaling prompts, affirmations, or follow-ups Use other workflows to track users, create reading logs, or offer upsells Try It Out: Text your Blooio-connected number with: “Hi” → get onboarding “Draw a card for me” → get a virtual pull A tarot photo + question → get a full, soulful reading ✅ Requirements Blooio Account & API Token (Dedicated plan or higher for images) Optional: Tarot images, user questions, or both 🔧 Customizing This Workflow Add personalized spreads (e.g. past/present/future layouts) Send AI-generated visuals of the pulled cards Route readings into Notion, Airtable, or Google Sheets Expand to WhatsApp, web, or email with Blooio’s multichannel support 🃏 Let the cards speak. Let the messages flow.

Use case This workflow is designed for e-commerce brands and content teams who: Need to scale SEO content production without sacrificing quality Want to eliminate manual keyword filtering (saves 10+ hours/week) Aim to dominate niche search terms (e.g., "vegan leather crossbody bags") What this workflow does Automates the end-to-end process from keyword discovery to publish-ready articles: Keyword Harvesting: Pulls 1,000+ keywords/day from SEMrush/Ahrefs Smart Filtering:Blocks competitor brands (e.g., "Zara alternatives") Detects irrelevant demographics ("kids", "petite") AI Content Generation:Flags non-compliant colors (non-black/white terms) Multi-Channel Output: Formats content for blogs, product descriptions, and email campaigns setup Add Google,SEMrush and OpenAI credentials Set the rules excel of google drive Test workflow by testing workflow Review generated opportunity report in Google Sheets How to adjust this template Change scenario: Replace the rules and define different target

This n8n workflow template lets teams easily generate a custom AI chat assistant based on the schema of any Notion database. Simply provide the Notion database URL, and the workflow downloads the schema and creates a tailored AI assistant designed to interact with that specific database structure. Set Up Watch this quick set up video 👇 Key Features Instant Assistant Generation**: Enter a Notion database URL, and the workflow produces an AI assistant configured to the database schema. Advanced Querying**: The assistant performs flexible queries, filtering records by multiple fields (e.g., tags, names). It can also search inside Notion pages to pull relevant content from specific blocks. Schema Awareness**: Understands and interacts with various Notion column types like text, dates, and tags for accurate responses. Reference Links**: Each query returns direct links to the exact Notion pages that inform the assistant’s response, promoting transparency and easy access. Self-Validation**: The workflow has logic to check the generated assistant, and if any errors are detected, it reruns the agent to fix them. Ideal for Product Managers**: Easily access and query product data across Notion databases. Support Teams**: Quickly search through knowledge bases for precise information to enhance support accuracy. Operations Teams**: Streamline access to HR, finance, or logistics data for fast, efficient retrieval. Data Teams**: Automate large dataset queries across multiple properties and records. How It Works This AI assistant leverages two HTTP request tools—one for querying the Notion database and another for retrieving data within individual pages. It’s powered by the Anthropic LLM (or can be swapped for GPT-4) and always provides reference links for added transparency.

💬🗂️🤖 This workflow automates the translation of Google Slides presentations from any languages, while preserving the original formatting and slide structure. It leverages Google APIs, AI translation (Gemini/PaLM), and modular execution for high flexibility and accuracy. DISCLAIMER: texts are split by Google Slides APIs into small blocks, so the translation will not always be contextualized. Key Benefits ⚡ Time-Saving**: Automates a typically manual and error-prone task of translating slides. 🌍 AI-Powered Accuracy**: Uses Google Gemini to provide context-aware translations while respecting defined rules. 🔒 Safe & Non-Destructive**: The original presentation is never modified — a new copy is always created. 🎯 Precision**: Skips irrelevant text (e.g., emails, URLs, names) to avoid mistranslation. 🔁 Modular & Scalable**: Uses subworkflows and batching, ideal for presentations with many slides. 🎨 Layout Preservation**: Keeps the original design and formatting intact. How it Works Initialization: The workflow starts with a manual trigger ("When clicking ‘Execute workflow’"). Set the language to translate (IMPORTANT format ISO-639) It duplicates a specified Google Slides presentation ("Duplicate presentation") to create a new copy for translation, preserving the original. Slide Processing: The workflow retrieves slides from the copied presentation ("Get slides from a presentation") and processes them in batches ("Loop Over Items"). For each slide, text content is extracted ("Extract Text") using a custom JavaScript snippet, which identifies and collects text elements while retaining the slide's objectId. Translation: The extracted texts are passed to a LangChain agent ("Translation expert"), which translates the content from Italian to English. The agent follows strict guidelines (e.g., skipping URLs, brand names, etc.). The translated text is sent to the "Translate Google Slides" node, which replaces the original text in the presentation using the slide's objectId for targeting. Execution Flow: The workflow includes delays ("Wait 10 sec" and "Wait 3 sec") to manage API rate limits and ensure smooth execution. The process repeats for each batch of slides until all content is translated. Set Up Steps Prerequisites: Ensure access to the source Google Slides presentation (specified by fileId in "Duplicate presentation"). Set up Google OAuth2 credentials for Google Drive and Slides (nodes reference credentials like "Google Slides account"). Configure the Google Gemini (PaLM) API credentials for the translation agent. Configuration: Update the fileId in the "Duplicate presentation" node to point to your source presentation. Adjust the translation guidelines in the "Translation expert" node if needed (e.g., language pairs or exclusion rules). Modify batch sizes or wait times (e.g., "Wait 10 sec") based on API constraints. Execution: Run the workflow manually or trigger it via the "Execute Workflow" node from another workflow. Monitor progress in n8n’s execution log, as each slide is processed and translated sequentially. Output: The translated presentation is saved as a new file in Google Drive, with the filename including a timestamp (e.g., NAME_PRESENTATION_{lang}_{timestamp}). Note: The workflow is currently inactive ("active": false); enable it after configuration. Need help customizing? Contact me for consulting and support or add me on Linkedin.

PersonalNotesAssistant – Organize and Understand Your Thoughts with Local AI PersonalNotesAssistant is an offline-capable, AI-powered agent that helps you store, summarize, retrieve, and reflect on your personal notes and voice memos — all processed locally and sent via Telegram. Built to run efficiently on a Raspberry Pi 5, this agent supports a variety of note-taking styles and acts as your private memory extension. 🧠 What It Can Do Accept voice or text notes via Telegram Transcribe audio messages into clean, structured text (using Whisper) Automatically summarize or categorize notes with a local LLM Answer questions based on your past notes Retrieve relevant entries by topic, date, or keyword Help you journal or reflect by asking follow-up questions Work completely offline — no cloud or external APIs 🔧 How It Works Capture Notes via Telegram You send a voice message or text to your Telegram bot. The assistant supports both quick thoughts and long-form content. Transcription with Whisper (Local) If the input is a voice message, it is transcribed into text using Whisper running locally on your Raspberry Pi. AI Summarization & Tagging The transcribed or typed note is sent to LLaMA 3.2 via Ollama, which summarizes it, suggests tags, and stores it with metadata (e.g., timestamp, mood, theme). Storage & Retrieval Notes are stored in a local database (e.g., SQLite or JSON). You can later query the assistant with prompts like: “What did I say about stress last week?” “Summarize my ideas from this month.” “Show notes tagged with 'travel'.” Follow-Up & Reflection The agent can optionally engage with reflective prompts to help you deepen your thoughts or gain insight from what you’ve recorded. 💡 Use Cases Track personal growth, habits, or therapy progress Create voice memos while walking or commuting Maintain a structured journal without typing Use as a second brain to help you remember and revisit important thoughts 🔐 Privacy by Default Everything runs locally: No notes are uploaded to cloud platforms No audio is sent to third-party transcription services No LLM processing happens outside your device Ideal for privacy-minded users, psychologists, researchers, or digital minimalists who want AI assistance without surveillance. ⚙️ Technical Stack Raspberry Pi 5: Low-power edge device Whisper (local): For voice-to-text conversion Ollama + LLaMA 3.2: For summarization, classification, and retrieval Telegram Bot API: For input/output Custom Database (e.g., JSON/SQLite): For storing and querying notes 🧪 Real-Life Use This agent is actively used daily by the developer to log ideas, emotions, and plans. It has proven effective for lightweight journaling and context-aware memory assistance, even when offline.

This AI agent can access data provided by another n8n workflow. Since that workflow can be used to retrieve any data from any service, this template can be used give an agent access to any data. Note that to use this template, you need to be on n8n version 1.19.4 or later.