by Tiartyos
Voice Cloning Workflow - Zyphra Zonos API Who is this for? This workflow is designed for developers, content creators, and businesses looking to automate high-quality voice synthesis using AI voice cloning technology. What problem does this solve? It automates the process of generating natural-sounding speech from text using a sample voice file, eliminating the need for manual voice recording and providing consistent voice output for applications like audiobooks, virtual assistants, or content localization. What this workflow does The workflow receives text and voice cloning parameters via webhook, reads a sample voice file from your storage, sends the data to Zyphra's Zonos API for voice synthesis, and saves the generated audio file to your specified output location. Prerequisites You'll need: API key from Zyphra (obtain from https://playground.zyphra.com/settings/api-keys) Account registration at https://playground.zyphra.com Sample voice file stored on accessible disk/cloud storage n8n instance running with webhook capabilities Setup Configure your Zyphra API key in the "Call Zyphra Clone API" node under Header Parameters (Name: X-API-Key, Value: your-api-key) Ensure your sample voice files are accessible at the paths you'll specify Test the webhook endpoint is accessible Supported Audio Formats The API supports multiple output formats through the mime_type parameter: WebM** (default) - audio/webm Ogg** - audio/ogg WAV** - audio/wav MP3** - audio/mp3 or audio/mpeg MP4/AAC** - audio/mp4 or audio/aac Usage Example Endpoint: POST http://localhost:5678/webhook-test/voice-clone Headers: Content-Type: application/json Request Body: { "text": "Hello there! This voice sounds just like the sample!", "speaking_rate": 18, "sample_voice_path": "/data/output/sampleVoice.wav", "output_path": "/data/output/", "language_iso_code": "en-us", "mime_type": "audio/wav", "model": "zonos-v0.1-transformer", "emotion": { "happiness": 0.8, "neutral": 0.3, "sadness": 0.05, "disgust": 0.05, "fear": 0.05, "surprise": 0.05, "anger": 0.05, "other": 0.5 } } Parameters Required Parameters text**: Text to synthesize into speech sample_voice_path**: Path to your voice sample file output_path**: Directory where generated audio will be saved Optional Parameters (with defaults) speaking_rate**: 15 - Speech speed language_iso_code**: "en-us" - Language code mime_type**: "audio/wav" - Output audio format model**: "zonos-v0.1-transformer" - AI model to use emotion**: Object with emotion levels (0-1 scale)
by Sagar
This template streamlines your AI Avatar Video Automation workflow by connecting Google sheets for Voice Text & AI Avatar Video Link storage, using HTTP Nodes for connecting Heygen API & AI Avatar/Voice Id for automated Video generation. Pre-requisites Before setting up this workflow, ensure you have: A Google account with access to Google Sheets A Heygen Account with API access in account's settings. n8n.io account with workflow access Setup Instructions Configure Data Source Create a Google Sheet with the following columns: Script/Voice Text & Final AI Avatar Video Link. Connect Google Sheet Add your Google sheet credentials in the “Google Sheet” node Specify the folder path where your columns are stored. Configure the node to retrieve files based on filenames from your Google Sheet Set Up HTTP Node with Heygen API Credentials Configure the node to generate AI Video based on Script/Voice Text. Configure HTTP Node 2 Connect Heygen API Credentials Set up the API node to Get the AI Avatar Video Link. then finally setup Google sheet node again to get & upload the final AI Avatar video link in the column "the Final AI Avatar Video Link" Workflow Automation Setup Configure the scheduler node to run at your preferred frequency Set up error handling to notify you of any posting failures Execution Instructions After completing all connections, test the workflow. Monitor the execution in the n8n dashboard to ensure proper functioning View the “Executions” tab to track successful and troubleshoot any errors. This template saves hours of manual AI Avatar video Creation Process. use this without the daily manual effort. Details Nodes used in workflow Manual Trigger Node Google Sheet Node 1 HTTP Node 1 HTTP Node 2 Google Sheets Node 2
by David Ashby
Complete MCP server exposing 2 CarbonDoomsDay API operations to AI agents. ⚡ 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 Credentials Add CarbonDoomsDay credentials 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 This workflow converts the CarbonDoomsDay API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.carbondoomsday.com/api • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Co2 (2 endpoints) • GET /co2/: Get CO2 Measurement by Date • GET /co2/{date}/: CO2 measurements from the Mauna Loa observatory. This data is made available through the good work of the people at the Mauna Loa observatory. Their release notes say: These data are made freely available to the public and the scientific community in the belief that their wide dissemination will lead to greater understanding and new scientific insights. We currently scrape the following sources: [co2_mlo_weekly.csv] [co2_mlo_surface-insitu_1_ccgg_DailyData.txt] [weekly_mlo.csv] We have daily CO2 measurements as far back as 1958. Learn about using pagination via [the 3rd party documentation]. [co2_mlo_weekly.csv]: https://www.esrl.noaa.gov/gmd/webdata/ccgg/trends/co2_mlo_weekly.csv [co2_mlo_surface-insitu_1_ccgg_DailyData.txt]: ftp://aftp.cmdl.noaa.gov/data/trace_gases/co2/in-situ/surface/mlo/co2_mlo_surface-insitu_1_ccgg_DailyData.txt [weekly_mlo.csv]: http://scrippsco2.ucsd.edu/sites/default/files/data/in_situ_co2/weekly_mlo.csv [the 3rd party documentation]: http://www.django-rest-framework.org/api-guide/pagination/#pagenumberpagination 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native CarbonDoomsDay API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.
by Mutasem
How it works This workflow adds a priority to each Todoist item in your inbox, based on a list of projects that you add in the workflow. Setup Add your Todoist credentials Add your OpenAI credentials Set your project names and add priority
by Joseph LePage
✨😃 Automated Workflow Backups to Google Drive This workflow automates the process of backing up your n8n workflows to Google Drive daily. It creates timestamped folders, saves workflows as JSON files, and manages old backups by retaining only the most recent seven days of data. Notifications are sent via Telegram to keep you informed of the backup status. How It Works Backup Creation Process 🗂️ Triggering Backups**: The workflow starts with either a manual trigger or a scheduled trigger that runs daily. Folder Creation**: Creates a new folder in Google Drive with a timestamped name (e.g., n8n-Workflow-Backups-YYYY-MM-DD). Workflow Retrieval**: Fetches all workflows from your n8n instance. File Conversion**: Converts each workflow into a JSON file for storage. File Upload**: Saves the JSON files into the newly created Google Drive folder. Backup Management 🔄 Folder Search**: Searches for existing backup folders in Google Drive with names matching n8n-Workflow-Backups. Retention Policy**: Identifies folders older than seven days using a custom JavaScript function and deletes them permanently to free up space. Notifications 📲 Telegram Alerts**: Sends a message via Telegram once the backup process is complete, including the folder name and a link to access it in Google Drive. Setup Steps API Configuration 🔑 Google Drive Integration: Set up Google Drive OAuth2 credentials in n8n. Specify the root folder or desired location for backups. n8n API Access: Configure n8n API credentials to allow fetching workflows. Telegram Notifications: Add your Telegram bot credentials and chat ID for notification delivery. Workflow Customization ⚙️ Define the schedule for automatic backups (e.g., daily at midnight). Adjust the retention period if you need more or fewer days of backups. Customize the Telegram message format as needed. Testing & Deployment 🚀 Run the workflow manually to verify folder creation and file uploads. Check that old folders are deleted correctly after seven days. Confirm Telegram notifications are sent with accurate details. Use Case Scenarios This workflow is perfect for teams or individuals who want to ensure their n8n workflows are securely backed up and organized. It is especially useful for: Protecting against accidental data loss. Automating routine administrative tasks. By combining automated backups, retention management, and real-time notifications, this workflow ensures your n8n workflows are always safe and accessible!
by InfyOm Technologies
✅ What problem does this workflow solve? Tired of the back-and-forth involved in scheduling meetings? This workflow lets you offer a seamless, voice-based appointment booking experience. It automatically checks your Cal.com availability and either books a meeting or helps the caller choose another time—powered by ElevenLabs for a human-like voice interaction. ⚙️ What does this workflow do? Receives an inbound voice call (e.g., from a website or IVR system). Uses ElevenLabs to drive the voice interaction with natural, AI-generated speech. Checks real-time availability from your Cal.com calendar. Books a meeting if a slot is available. If not, asks the user to suggest a new time and checks availability again. Confirms the appointment with a verbal response and optional email or SMS. 🔧 Setup 🧠 ElevenLabs Custom Tools Setup Add two tools in Custom Tools in ElevenLabs with the following details. Name: bookSlot Description: Use this tool when the user confirms their slot and appointment. When you have the proper name and email of theirs. POST: {n8n_webhook_url} Name: checkAvailableSlot Description: Use this slot to check Available slots in our calendar. POST: {n8n_webhook_url} 🗣 ElevenLabs Prompt Configuration First Message: Thanks for calling InfyOm Technologies. How can I help you? Use the following System Prompt: 1. Personality You are a clear, helpful, and respectful assistant focused solely on booking appointments for clients. Identity**: A virtual appointment scheduler. Core Traits**: Polite, efficient, conversational, respectful. Role**: Guide users through choosing a time, checking availability, and finalizing the booking. 2. Tone Your tone is polite, professional, and engaging—friendly enough to feel human, but focused enough to stay on task. Use conversational cues like “Okay,” “Got it,” “Sounds good,” etc. Maintain a warm but efficient pace. Speak clearly and respectfully at all times. Ensure the conversation is on both topics. 3. Goal Your task is to book an appointment for the client. Step-by-step Conversation Flow Greeting & Purpose Greet politely and state the purpose. Example: “Hi! I’m here to help you book an appointment.” Request Preferred Time Ask: “Can you please tell me your preferred time slot for the appointment?” Understand the user's date, and if it is not clear, then ask for the full date with month and year. Check Availability Use the checkAvailableSlot tool with the user’s preferred time. If the slot is available: Confirm with the user: “That slot is available. Should I go ahead and book it for you?” If the user agrees, → Use bookSlot. If the slot is not available: Say: “It looks like that time isn’t available... Would you like to look for the same time on the next day?” Handle Next-Day Option If the user agrees, check availability for the same time on the next day using checkAvailableSlot. If available, → confirm and use bookSlot. If not, → politely inform and ask for a different time. Close the Call Confirm the booking if done. Example: “Great! Your appointment is booked. Thank you and have a wonderful day!” 4. Guardrails Do not** discuss anything unrelated to appointment booking. If the user asks for something outside your scope: Say: “I’m only here to help with appointment bookings. For other questions, please contact our support team.” Never speculate about unavailable data or functions. Never ask for a date format from the User, like Say date in Day Month and Year format. If you can't understand the user's date, then say Please speak the full date. 5. Tools You can use the following tools to help book appointments: checkAvailableSlot: Use this to check if the user’s requested time is open. bookSlot: Use this to confirm the appointment after the user agrees. End call Always says Thanks for reaching out to us. Have a nice day. 📅 Cal.com API Setup Go to cal.com and generate an API Key. Create new Cal API credentials in n8n. Set this API Key in the credentials. 🧠 How it Works ☎️ 1. Incoming Call An inbound call is received by the system, and the user begins the conversation with your voice AI agent. 🧏 2. Voice Interaction via ElevenLabs The caller is greeted and asked for their preferred appointment time. All conversations are powered by natural AI speech from ElevenLabs. 🗓 3. Availability Check (Cal.com) The requested time is validated against your Cal.com availability: ✅ If available, the appointment is booked instantly. ❌ If unavailable, the agent informs the caller and asks for another time. 🔁 4. Retry Loop (If Slot Unavailable) If the initial slot is unavailable: The agent asks for a new preferred time. The process repeats until a valid slot is found or a fallback message is delivered. ✅ 5. Appointment Confirmation Once booked, the AI confirms the appointment verbally. You may also configure it to send: 📧 Email confirmations 📱 SMS reminders (optional) 👤 Who can use it? This is perfect for: 🧑⚕️ Clinics or Therapists 🧑💼 Consultants & Coaches 🏢 Sales Teams 🧠 AI-first SaaS Tools If your business relies on scheduled meetings and you'd like to automate bookings using a conversational voice experience, this is your go-to no-code solution.
by Ficky
Build a Redis-Powered CRUD App with HTML Frontend This workflow demonstrates how to use n8n to build a complete, self-contained CRUD (Create, Read, Update, Delete) application without relying on any external server or hosting. It not only acts as the backend, handling all CRUD operations through Webhook endpoints, but also serves a fully functional HTML Single Page Application (SPA) directly via a webhook response. Redis is used as a lightweight data store, providing fast and simple key-value storage with auto-incremented IDs. Because both the frontend (HTML app) and backend (API endpoints) are managed entirely within a single n8n workflow, you can quickly prototype or deploy small tools without additional infrastructure. This approach is ideal for: Rapidly creating no-code or low-code applications Running fully browser-based tools served directly from n8n Teaching or demonstrating n8n + Redis integration in a single workflow Features Add new item with auto-incremented ID Edit existing item Delete specific item Reset all data (clear storage and reset autoincrement id) Single HTML frontend for demonstration (no framework required) Setup Instructions 1. Prerequisites Before importing and running the workflow, make sure you have: A running n8n instance (self-hosted or cloud) A running Redis server (local or remote) 2. API Path Setup For the REST API, use a consistent path. For example, if you choose items as the path: 2a. Get All Items** Method: GET Endpoint: items 2b. Add Item** Method: POST Endpoint: items 2c. Edit Item** Method: PUT Endpoint: items 2d. Delete Item** Method: DELETE Endpoint: items 2e. Reset Items** Method: POST Endpoint: items-reset 3. Configure the API URL Set the API URL in the SET API URL node. Use your n8n webhook URL, for example: https://yourn8n.com/webhook/items 4. Run the HTML App Once everything is set: Open the webhook URL for the HTML app in a browser. The CRUD interface will load and connect to the API endpoints automatically. You can now add, edit, delete, or reset items directly from the web interface. Workflows 1. Render the HTML CRUD App This webhook serves a self-contained HTML Single Page Application (SPA) for basic CRUD operations. The HTML content is returned directly in the webhook response. This setup is ideal for lightweight, browser-based tools without external hosting. How to Use Open the webhook URL in a browser The CRUD interface will load and connect to the data source via API calls Before using, make sure to edit the api_url in the SET API URL node to match your webhook endpoint 2a. REST API: Get All Items This webhook handles retrieving all saved items from Redis. Each item is returned with its corresponding ID and associated data (e.g., name). This endpoint is used by the HTML CRUD App to display the full list of items. Method**: GET Function**: Fetches all items stored in Redis and returns them as a JSON array 2b. REST API: Add Item This webhook handles the Add Item functionality. This endpoint is typically called by the HTML CRUD App when adding a new item. Method**: POST Request Body**: { "name": "item name" } Function**: Generates an auto-incremented ID using Redis and saves the data under that ID 2c. REST API: Edit Item This webhook handles updating an existing item in Redis. Method**: PUT Request Body**: { "id": 1, "name": "Updated Item Name" } Function**: Finds the item by the given id and updates its data in Redis 2d. REST API: Delete Item This webhook handles deleting a specific item from Redis. Method**: DELETE Request Body**: { "id": 1 } Function**: Removes the item with the given id from Redis 2e. REST API: Reset Items This webhook handles resetting all data in the application. Method**: POST Function**: Deletes all stored items from Redis Resets the auto-increment ID by deleting the data in Redis
by Mal Chia
Who’s it for This workflow is perfect for HR teams, recruiters, or hiring managers who collect applicant information via a web form and want to automatically forward both candidate details and attached resumes into a dedicated Telegram channel or group. It streamlines manual email checks, speeding up review and collaboration. How it works On form submission: A Form Trigger node captures all applicant fields (name, age, WhatsApp number, education, desired role, availability date, expected salary, resume file, and additional comments). Date & Time: Formats the “fastest start date” into a human-readable string. Edit Fields: A Set node renames and reshapes incoming JSON into clear key/value pairs. If Have Resume: An If node routes submissions with an attached resume to one branch (sending both info and document) and submissions without a resume to a simpler info-only branch. Merge: Combines branches so both message types terminate in a single unified flow. Send a Resume & Send a Info: Two Telegram nodes post Markdown-formatted messages (and the PDF resume when available) to your specified Telegram chat. How to set up Install and enable the n8n-nodes-base.formTrigger and n8n-nodes-base.telegram community nodes (preview). Copy this JSON into your n8n instance (Workflow → Import from clipboard). Create environment variables for credentials: TELEGRAM_BOT_TOKEN TELEGRAM_CHAT_ID In each Telegram node, reference these variables instead of hard-coding ({{$env.TELEGRAM_BOT_TOKEN}}, {{$env.TELEGRAM_CHAT_ID}}). Requirements n8n version ≥ 0.200.0 Community nodes: Form Trigger, Telegram A Telegram bot with chat permissions A hosted form endpoint or embedded form at path /mmc-newjob How to customize the workflow Form fields: Edit the **Form Trigger node’s formFields.values to add or remove fields. Telegram formatting: Tweak captions under **Send a Resume and Send a Info to adjust the MarkdownV2 styling. Conditional logic: Modify the **If Have Resume node to branch on other criteria (e.g., education level). Styling: Update the customCss section in **Form Trigger to match your brand’s look. Good to know Community nodes may be in preview; test thoroughly before production. Webhook URLs change when you rename the workflow—revisit your form’s embed or webhook settings after renaming. Consider adding an Error Trigger node to capture failures and notify your team.
by InfraNodus
This template can be used to find the content gaps in PDF documents using the InfraNodus knowledge graph / GraphRAG text representation and then generate ideas / questions / AI prompts that bridge those gaps based on optimizing the knowledge graph's structure. Simply upload several PDF files (research papers, corporate or market reports, etc) and generate an idea in seconds. The template is useful for: generating ideas / questions for research generating content ideas based on competitors' discourse finding blind spots in any discourse and generating ideas that address them. avoiding the generic bias of LLM models and focusing on what's important in your particular context What are Content Gaps and Knowledge Graphs? Knowledge graphs represent any text as a network: the main concepts are the nodes, their co-occurrences are the connections between them. Based on this representation, we build a graph and apply network science metrics to rank the most important nodes (concepts) that serve as the crossroads of meaning and also the main topical clusters that they connect. Naturally, some of the clusters will be disconnected and will have gaps between them. These are the topics (groups of concepts) that exist in this context (the documents you uploaded) but that are not very well connected. Addressing those gaps can help you see which groups of concepts you could connect with your own ideas. This is exactly what InfraNodus does: builds the structure, finds the gaps, then uses the built-in AI to generate research questions and ideas that bridge those gaps. How it works 1) Step 1: First, you upload your PDF files using an online web form, which you can run from n8n or even make publicly available. 2) Steps 2-4: The documents are processed using the Code and PDF to Text nodes to extract plain text from them. 3) Step 5: This text is then sent to the InfraNodus GraphRAG node that creates a knowledge graph, identifies structural gaps in this graph, and then uses built-in AI to generate ideas or research questions / prompts (if you use the InfraNodus question module instead). 4) Step 6: The ideas are then shown to the user in the same web form. Optionally, you can hook this template to your own workflow and send the idea / question generated to your own AI model / agent for further processing. If you'd like to sync this workflow to PDF files in a Google Drive folder, you can copy our Google Drive PDF processing workflow for n8n. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key. Add this key into the InfraNodus GraphRAG HTTP node(s) you use in this workflow. You do not need any OpenAI keys for this to work. Optionally, you can change the settings in the Step 4 of this workflow and enforce it to always use the biggest gap it identifies. Requirements An InfraNodus account and API key Note: OpenAI key is not required. You will have direct access to the InfraNodus AI with the API key. Customizing this workflow You can use this same workflow with a Telegram bot or Slack (to be notified of the summaries and ideas). You can also hook up automated social media content creation workflows in the end of this template, so you can generate posts that are relevant (covering the important topics in your niche) but also novel (because they connect them in a new way). Check out our n8n templates for ideas at https://n8n.io/creators/infranodus/ Also check the full tutorial with a conceptual explanation at https://support.noduslabs.com/hc/en-us/articles/20454382597916-Beat-Your-Competition-Target-Their-Content-Gaps-with-this-n8n-Automation-Workflow Also check out the video introduction to InfraNodus to better understand how knowledge graphs and content gaps work: For support and help with this workflow, please, contact us at https://support.noduslabs.com
by David Olusola
🎯 JavaScript Master Class - Interactive Code Tutorial 📚 How It Works This tutorial is designed as a self-paced learning experience where you explore working JavaScript code examples. Unlike traditional tutorials, you learn by examining real implementations and understanding how they work. 🔍 The Learning Method: Execute first - See the workflow in action Open each node - This is where the real learning happens! Study the code - Read JavaScript implementations and comments Understand the flow - See how data transforms between nodes Experiment - Modify code to test your understanding 🎮 The "Game" Concept: It's not a real game - it's a gamified learning experience Uses RPG elements (XP, levels, achievements) to make learning engaging Simulates progression through 3 difficulty levels Main learning happens when you open nodes and read the code!** 🚀 Setup Steps Step 1: Import the Template Copy the JSON template provided Open your n8n instance Create a new workflow Press Ctrl+A (or Cmd+A on Mac) to select all Press Ctrl+V (or Cmd+V) to paste the JSON Click "Save" and name it: JavaScript Master Class - Interactive Tutorial Step 2: Execute the Workflow Click "Test workflow" or "Execute workflow" Watch it run through all nodes automatically See the final results and progression simulation Step 3: Start Learning (The Important Part!) Now the real learning begins - you must open each node manually: 🔍 For Each Code Node: Double-click the node to open it Read the JavaScript code carefully Study the comments - they explain key concepts Understand the logic - how input becomes output Note the techniques used in each challenge 📖 For Each Sticky Note: Read the explanations and context Understand the learning objectives Note the skills being taught 🎯 Learning Path Level 1: Data Warrior (Beginner) 📂 Open Node: 🎲 Level 1: Data Warrior Focus:** Data deduplication using filter() and findIndex() Key Skills:** Array methods, duplicate detection What to Study:** How the deduplication algorithm works Level 2: API Ninja (Intermediate) 📂 Open Node: ⚔️ Level 2: API Ninja Focus:** Data transformation and validation Key Skills:** String manipulation, validation logic, error handling What to Study:** How to clean and validate messy API data Level 3: Automation Master (Advanced) 📂 Open Node: 🏆 Final Boss: Automation Master Focus:** Complex workflow processing Key Skills:** Task orchestration, priority sorting, error handling What to Study:** How to build robust automation systems 💡 Learning Tips 🔍 Active Exploration: Don't just run it** - open every single node! Read all comments** - they contain key insights Compare approaches** - see how complexity increases Try modifications** - change values and see what happens 📝 Study Techniques: Take notes** on patterns you see Copy interesting code** snippets for reference Try to explain** each function to yourself Test your understanding** by modifying the code 🧪 Experimentation: Change filter conditions** in Level 1 Modify validation rules** in Level 2 Adjust workflow logic** in Level 3 Break something** and fix it - great for learning! ⚠️ Important Notes 🎮 "Game" Reality Check: This is NOT an interactive game where you make choices It's a code tutorial with game-like progression themes The "game" runs automatically when executed Real learning happens when you manually open and study each node** 📚 Educational Value: Primary learning:** Understanding JavaScript implementations Secondary learning:** n8n workflow patterns Bonus learning:** Problem-solving approaches 🔧 Technical Requirements: Working n8n instance Basic JavaScript knowledge helpful but not required Willingness to explore and experiment 🎯 Success Metrics You'll know you're learning when you can: ✅ Explain how each deduplication algorithm works ✅ Identify the validation patterns used ✅ Understand the workflow orchestration logic ✅ Modify the code to handle different scenarios ✅ Apply these patterns to your own projects 🤔 Next Steps After completing this tutorial: Apply the patterns to your own workflows Experiment with variations Build something using these techniques Share your learnings with the community Remember: The magic happens when you open each node and study the code! 🔍
by InfraNodus
This template can be used to generate research ideas from PDF scientific papers based on the content gaps found in text using the InfraNodus knowledge graph GraphRAG knowledge graph representation. Simply upload several PDF files (research papers, corporate or market reports, etc) and the template will generate a research question, which will then be sent as an AI prompt to the InfraNodus GraphRAG system that will extract the answer from the documents. As a result, you find the gap in a collection of research papers and bridge it in a few seconds . The template is useful for: advancing scientific research generating AI prompts that drive research further finding the right questions to ask to bridge blind spots in a research field avoiding the generic bias of LLM models and focusing on what's important in your particular context Using Content Gaps for Generating Research Questions Knowledge graphs represent any text as a network: the main concepts are the nodes, their co-occurrences are the connections between them. Based on this representation, we build a graph and apply network science metrics to rank the most important nodes (concepts) that serve as the crossroads of meaning and also the main topical clusters that they connect. Naturally, some of the clusters will be disconnected and will have gaps between them. These are the topics (groups of concepts) that exist in this context (the documents you uploaded) but that are not very well connected. Addressing those gaps can help you see which groups of concepts you could connect with your own ideas. This is exactly what InfraNodus does: builds the structure, finds the gaps, then uses the built-in AI to generate research questions that bridge those gaps. How it works 1) Step 1: First, you upload your PDF files using an online web form, which you can run from n8n or even make publicly available. 2) Steps 2-4: The documents are processed using the Code and PDF to Text nodes to extract plain text from them. 3) Step 5: This text is then sent to the InfraNodus GraphRAG node that creates a knowledge graph, identifies structural gaps in this graph, and then uses built-in AI to research questions, which are then used as AI prompts. 4) Step 6: The research questino is sent to the InfraNodus GraphRAG system that represents the PDF documents you submitted as a knowledge graph and then uses the research question generated to come up with an answer based on the content you uploaded. 4) Step 7: The ideas are then shown to the user in the same web form. Optionally, you can derive the answers from a different set of papers, so the question is generated from one batch, but the answer is generated from another. If you'd like to sync this workflow to PDF files in a Google Drive folder, you can copy our Google Drive PDF processing workflow for n8n. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account Get the API key at https://infranodus.com/api-access and create a Bearer authorization key. Add this key into the InfraNodus GraphRAG HTTP node(s) you use in this workflow. You do not need any OpenAI keys for this to work. Optionally, you can change the settings in the Step 4 of this workflow and enforce it to always use the biggest gap it identifies. Requirements An InfraNodus account and API key Note: OpenAI key is not required. You will have direct access to the InfraNodus AI with the API key. Customizing this workflow You can use this same workflow with a Telegram bot or Slack (to be notified of the summaries and ideas). You can also hook up automated social media content creation workflows in the end of this template, so you can generate posts that are relevant (covering the important topics in your niche) but also novel (because they connect them in a new way). Check out our n8n templates for ideas at https://n8n.io/creators/infranodus/ Also check the full tutorial with a conceptual explanation at https://support.noduslabs.com/hc/en-us/articles/20454382597916-Beat-Your-Competition-Target-Their-Content-Gaps-with-this-n8n-Automation-Workflow Also check out the video introduction to InfraNodus to better understand how knowledge graphs and content gaps work: For support and help with this workflow, please, contact us at https://support.noduslabs.com
by Zach @BrightWayAI
Who's it for Content creators, researchers, educators, and digital marketers who need to discover high-quality YouTube training videos on specific topics. Perfect for building curated learning resource lists, competitive research, or content inspiration. What it does This workflow automatically searches YouTube using multiple search queries, filters for quality content, scores videos by relevance, and exports the top results to Google Sheets. It processes hundreds of videos and delivers only the most valuable educational content ranked by custom relevance criteria. The workflow searches for videos using 10 different AI automation-related queries (easily customizable), filters out low-quality content like shorts and clickbait, then ranks results based on title keywords, view counts, and engagement metrics. How it works Multi-query search: Searches YouTube with an array of related queries to get comprehensive coverage Content filtering: Removes shorts, spam, and low-quality videos using regex patterns Quality assessment: Filters videos based on view count, likes, and publication date Relevance scoring: Assigns scores based on title keywords and engagement metrics Result ranking: Sorts videos by relevance score and limits to top 50 results Export to Sheets: Delivers clean, organized data to Google Sheets with all metadata Requirements YouTube Data API v3 credentials from Google Cloud Console Google Sheets credentials for n8n workspace A Google Sheets document to receive the results How to set up Enable YouTube Data API v3 in your Google Cloud Console Add YouTube OAuth2 credentials to your n8n workspace Add Google Sheets credentials to your n8n workspace Create a Google Sheet and update the Google Sheets node with your document ID Customize search queries in the "Set Query" node for your topic Adjust filtering criteria in the Filter nodes based on your quality requirements How to customize the workflow Search topics: Modify the query array in the "Set Query" node to research any topic: [ "Python tutorial", "JavaScript course", "React beginner guide", // Add your queries here ] Quality thresholds: Adjust minimum views, likes, and date ranges in the "Filter for Quality" node Relevance scoring: Customize keyword weightings in the "Relevance Score" node to match your priorities Result limits: Change the number of final results in the "Limit" node (default: 50) Output format: Modify the "Set Fields" node to include additional YouTube metadata like duration, thumbnails, or category information The workflow is designed to be easily adaptable for any research topic while maintaining high content quality standards.