by Jorge Martínez
Automate tweet engagement on X (formerly Twitter) Description Automate professional engagement on X (formerly Twitter) by searching for, filtering, liking, and replying to tweets that match your key topics. This workflow enables you to engage consistently and efficiently with relevant conversations, using your defined professional role and the power of GPT for filtering and replies. Save time and maintain high-quality interactions, while staying focused on your business or personal brand interests. How it Works Rotating Topic Selection The workflow selects one search term from your list on each run, using a rotating index based on the date. Search Tweets & Extract Essentials Searches X (formerly Twitter) for tweets matching the chosen topic, then extracts only the tweet id and text for further processing. GPT‑Based Filtering with Role Context Filters tweets based on your role and strict criteria, removing non-English tweets, memes, spam, Grok-generated content, political posts, internships, and more. Engagement Loop For every filtered tweet, the workflow likes the post, generates a professional, concise reply with GPT (matching language and context), and posts the reply. Wait nodes ensure compliance with Twitter’s API rate limits (can be adjusted for paid API tiers). Requirements X (Twitter) API credentials (for searching, liking, and replying to tweets) OpenAI API key (for GPT-based steps) Setup Steps Obtain your X (Twitter) API credentials. Obtain your OpenAI API key. Configure the schedule in the trigger node to your desired frequency (e.g., every 3 days or daily). Set your list of topics and professional role in the variables node. How to Customize the Workflow (Optional) Adjust prompts** in the GPT nodes to fine-tune filtering and reply style. Upgrade your Twitter API plan** to increase request limits and search for more tweets per run. Change tweet processing logic:** For high-volume engagement (e.g., analyzing 100+ tweets per run), consider switching to a per-tweet loop for advanced filtering and response handling. This workflow enables scalable, professional, and targeted engagement on X (formerly Twitter), fully customizable to your audience and objectives.
by WeWeb
This n8n template helps you build a full AI-powered LinkedIn content generator with just a few clicks. Paired with the free WeWeb UI template, it becomes a ready-to-use web app where users can: Add their own OpenAI API key Customize the prompt and define 6 content topics Edit the AI-generated topics Choose when to generate LinkedIn posts, complete with hashtags and an optional image Who This Is For Perfect for marketers, indie hackers, and solopreneurs who want to build their personal brand on LinkedIn while staying in control of what gets posted. 🧠 What Makes This Different Unlike most AI agents, you stay fully in control: You define the tone and focus via the prompt. You choose which topics to keep or modify. You decide when to generate a post. You can build on top of this and create your own SaaS product. It’s also modular and extendable—hook it up to your backend, add user login, or feed AI improvements based on user input. ⚙️ How It Works Triggering Events: The app includes 3 pre-configured triggers, ready to be hooked into your WeWeb frontend. Just update the webhook URLs after duplicating the n8n workflow. Topic Generation: A call is made to OpenAI (GPT-4) to generate topic ideas based on your prompt. Post Creation: Once topics are approved or edited, GPT-4 writes full posts with suggested hashtags. Image Generation (Optional): If enabled, a DALL·E call generates a relevant image. Everything Stays Local: All data and images are handled locally, no cloud storage setup needed. 🧪 Requirements & Setup No fancy infrastructure required. Here’s what helps you get started: Free WeWeb account** (recommended) to use the frontend UI template OpenAI account** with API access (for GPT-4 and DALL·E) n8n account** (self-hosted or cloud) to run the backend workflow The template is completely free to use. Since each user adds their own OpenAI API key, you don't need to worry about usage costs or rate limits on your end. 🔧 Want to Go Further? This setup is beginner-friendly, but developers can: Add user accounts Save post history Feed user feedback back into the prompt logic Launch their own branded version as a SaaS
by David Roberts
This workflow allows you to ask questions about the data in a Google Sheet over a chat interface. It uses n8n's built-in chat, but could be modified to work with Slack, Teams, WhatsApp, etc. Behind the scenes, the workflow uses GPT4, so you'll need to have an OpenAI API key that supports it. How it works The workflow uses an AI agent with custom tools that call a sub-workflow. That sub-workflow reads the Google Sheet and returns information from it. Because models have a context window (and therefore a maximum number of characters they can accept), we can't pass the whole Google Sheet to GPT - at least not for big sheets. So we provide three ways of querying less data, that can be used in combination to answer questions. Those three functions are: List all the columns in the sheet Get all values of a single column Get all values of a single row Note that to use this template, you need to be on n8n version 1.19.4 or later.
by Davide
This workflow allows users to generate AI videos using Google Veo3, save them to Google Drive, generate optimized YouTube titles with GPT-4o, and automatically upload them to YouTube with Upload-Post. The entire process is triggered from a Google Sheet that acts as the central interface for input and output. IT automates video creation, uploading, and tracking, ensuring seamless integration between Google Sheets, Google Drive, Google Veo3, and YouTube. Benefits of this Workflow 💡 No Code Interface**: Trigger and control the video production pipeline from a simple Google Sheet. ⚙️ Full Automation**: Once set up, the entire video generation and publishing process runs hands-free. 🧠 AI-Powered Creativity**: Generates engaging YouTube titles using GPT-4o. Leverages advanced generative video AI from Google Veo3. 📁 Cloud Storage & Backup**: Stores all generated videos on Google Drive for safekeeping. 📈 YouTube Ready**: Automatically uploads to YouTube with correct metadata, saving time and boosting visibility. 🧪 Scalable**: Designed to process multiple video prompts by looping through new entries in Google Sheets. 🔒 API-First**: Utilizes secure API-based communication for all services. How It Works Trigger: The workflow can be started manually ("When clicking ‘Test workflow’") or scheduled ("Schedule Trigger") to run at regular intervals (e.g., every 5 minutes). Fetch Data: The "Get new video" node retrieves unfilled video requests from a Google Sheet (rows where the "VIDEO" column is empty). Video Creation: The "Set data" node formats the prompt and duration from the Google Sheet. The "Create Video" node sends a request to the Fal.run API (Google Veo3) to generate a video based on the prompt. Status Check: The "Wait 60 sec." node pauses execution for 60 seconds. The "Get status" node checks the video generation status. If the status is "COMPLETED," the workflow proceeds; otherwise, it waits again. Video Processing: The "Get Url Video" node fetches the video URL. The "Generate title" node uses OpenAI (GPT-4.1) to create an SEO-optimized YouTube title. The "Get File Video" node downloads the video file. Upload & Update: The "Upload Video" node saves the video to Google Drive. The "HTTP Request" node uploads the video to YouTube via the Upload-Post API. The "Update Youtube URL" and "Update result" nodes update the Google Sheet with the video URL and YouTube link. Set Up Steps Google Sheet Setup: Create a Google Sheet with columns: PROMPT, DURATION, VIDEO, and YOUTUBE_URL. Share the Sheet link in the "Get new video" node. API Keys: Obtain a Fal.run API key (for Veo3) and set it in the "Create Video" node (Header: Authorization: Key YOURAPIKEY). Get an Upload-Post API key (for YouTube uploads) and configure the "HTTP Request" node (Header: Authorization: Apikey YOUR_API_KEY). YouTube Upload Configuration: Replace YOUR_USERNAME in the "HTTP Request" node with your Upload-Post profile name. Schedule Trigger: Configure the "Schedule Trigger" node to run periodically (e.g., every 5 minutes). Need help customizing? Contact me for consulting and support or add me on Linkedin.
by Michael Muenzer
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Generates relevant keywords and questions from a a customer profile. Keyword data is enriched from ahref and everything is stored in a Google Sheet. This is great for market and customer research. Understanding search intent for a well defined audience and gives relevant actionable data in a fraction of time that manual research takes. How it works We'll define a customer profile in the 'Data' node We use an OpenAI LLM to fetch relevant search intent as keywords and questions We use an SEO MCP server to fetch keyword data from ahref free tooling The fetched data is stored in the Google sheet Set up steps Copy Google Sheet template and add it in all Google Sheet nodes Make sure that n8n has read & write permissions for your Google sheet. Add your list of domains in the first column in the Google sheet Add MCP credentials for seo-mcp Add OpenAI API credentials
by Mario
Purpose This workflow enables you to listen to your recent favorites in very hight quality offline without sacrificing all of your storage. How it works This workflow automatically creates a playlist in Spotify named "Downloads" which periodically gets updated so it always contains only a defined amount of the latest liked songs. This enables only the Downloads playlist to set for automatic downloading and thus free up space on the device. Setup The workflow is ready to go. Just select your Spotify credentials and activate the workflow. In Spotify just enable automatic downloads on the automatically created Downloads folder after the first workflow run. Current limitations This setup currently supports a maximum of 50 songs in the Downloads Playlist. This is due to the paylod limits defined by Spotify encountered in the Get liked songs node. Implementing batching would solve the issue.
by Arunava
This n8n workflow automates replying to Google Play Store reviews using AI. It analyzes each review’s sentiment and tone and posts a human-like response — saving time for indie devs, founders, and PMs managing multiple apps. 💡 Use Cases Respond to reviews at scale without sounding robotic Prioritize negative sentiment feedback Maintain consistent tone and support messaging Free up time for teams to focus on product instead of ops 🧠 How it works Uses the Play Store API to fetch new app reviews Filters out reviews that have already been replied to Analyzes sentiment using OpenAI GPT-4o Passes sentiment and review context to an AI Agent node that crafts a reply Replies are posted to Play Store via Google API (Optional) Logs the reply to Slack for visibility 🛠️ Setup Instructions (Sticky notes included in the workflow) 1. HTTPS Node Replace the package name with your app’s package ID Add Google Service Account credentials → Create from Google Cloud Console with access to Play Console → Add to n8n Credential Manager 2. OpenAI Node Add your OpenAI API key → GPT-4o or GPT-4o mini supported → Customize model or instructions if needed 3. AI Agent Node Modify prompt to reflect your app name, tone, and feature set → E.g. polite, witty, casual, support-friendly, etc. → You can add reply conditions or logic for different types of reviews 4. Slack Node (Optional) Configure Slack Webhook or OAuth credentials if you want reply logs → Otherwise, delete the node to simplify the workflow ⚡ Requirements Google Play Developer Console access Google Cloud Project with service account OpenAI account (GPT-4o or mini) (Optional) Slack workspace & app for logging 🙌 Don’t want to set this up yourself? I’ll do it for you. Just drop me an email: imarunavadas@gmail.com Let’s automate the boring stuff so you can focus on growth. 🚀
by MRJ
:car: Business Value Proposition Accelerates ISO 26262 compliance for automotive/industrial systems by automating safety analysis while maintaining rigorous audit standards. :gear: How It Works graph TD A[Engineer uploadssystem description] --> B(LLM identifies hazards) B --> C(LLM scores risks per ISO 26262) C --> D(Generates mitigation strategies) D --> E(Produces audit-ready reports) :chart_with_upwards_trend: Key Benefits Time 50-70% faster than manual HAZOP/FMEA sessions Instant report generation vs. weeks of documentation Risk Mitigation Pre-validated templates reduce human error Auto-generated traceability simplifies audits :warning: Governance Controls Human-in-the-loop: All LLM outputs require engineer sign-off Version tracking: Full history of modifications Audit mode: Export all decision rationales :computer: Technical Requirements Runs on existing n8n instances Docker deployment (<1hr setup) Integrates with JAMA/DOORS (optional) :wrench: Setup and Usage Prerequisites Docker (Install Guide) Docker Compose (Install Guide) n8n instance (Free Self-Hosted or Cloud - Paid) OpenAI API key (Get Key) Enterprise-ready deployment: When supported by IT infrastructure teams, this solution transforms into a scalable AI safety assistant, providing real-time HARA guidance akin to engineering Co-pilot tools. :arrow_down: Installation and :play_or_pause_button: Running the Workflow For installation procedures and usage of workflow, refer the repository :warning: Validation & Limitations AI-Assisted Analysis Considerations | Advantage | Mitigation Strategy | Implementation Example | |-----------|---------------------|------------------------| | Rapid hazard identification | Human validation layer | Manual review nodes in workflow | | Consistent S/E/C scoring | Rule-based validation | ASIL-D → Redundancy check | | Edge case coverage | Cross-reference with historical data | Integration with incident databases | Critical Validation Steps AI Output Review node in n8n Example: (by code) { "type": "function", "parameters": { "functionCode": "if ($input.item.json.ASIL === 'D' && !$input.item.json.redundancy) throw new Error('ASIL D requires redundancy');" } } Version Control Prompt versions tied to ISO standard editions (e.g., ISO26262:2018-v1.2) Git-tracked changes to ai_models/training_data/ Audit trails Providing a log structure for audit trails Log structure /logs/ └── YYYY-MM-DD/ ├── hazards_approved.log └── hazards_rejected.log
by Yaron Been
This workflow provides automated access to the Ibm Granite Granite Speech 3.3 8B AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for text generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete text generation process using the Ibm Granite Granite Speech 3.3 8B model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: Granite-speech-3.3-8b is a compact and efficient speech-language model, specifically designed for automatic speech recognition (ASR) and automatic speech translation (AST). Key Capabilities Advanced text generation and processing** Natural language understanding and generation** Intelligent text manipulation and analysis** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Ibm Granite/granite-speech-3.3-8b AI model Ibm Granite Granite Speech 3.3 8B**: The core AI model for text generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Text Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Writing**: Generate articles, blogs, and marketing copy Code Generation**: Assist with programming and code documentation Text Analysis**: Process and analyze large volumes of text data Automated Communication**: Generate responses and communication templates Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #textgeneration #nlp #aiwriting #textai #contentgeneration #aitext #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation
by Yaron Been
This workflow provides automated access to the Lucataco Seed X Ppo AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for text generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete text generation process using the Lucataco Seed X Ppo model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: Seed-X-PPO-7B by ByteDance-Seed, a powerful series of open-source multilingual translation language models Key Capabilities Advanced text generation and processing** Natural language understanding and generation** Intelligent text manipulation and analysis** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Lucataco/seed-x-ppo AI model Lucataco Seed X Ppo**: The core AI model for text generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Text Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Writing**: Generate articles, blogs, and marketing copy Code Generation**: Assist with programming and code documentation Text Analysis**: Process and analyze large volumes of text data Automated Communication**: Generate responses and communication templates Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #textgeneration #nlp #aiwriting #textai #contentgeneration #aitext #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation
by Yaron Been
This workflow provides automated access to the Zsxkib Canary Qwen 2.5B AI model through the Replicate API. It saves you time by eliminating the need to manually interact with AI models and provides a seamless integration for text generation tasks within your n8n automation workflows. Overview This workflow automatically handles the complete text generation process using the Zsxkib Canary Qwen 2.5B model. It manages API authentication, parameter configuration, request processing, and result retrieval with built-in error handling and retry logic for reliable automation. Model Description: 🎤The best open-source speech-to-text model as of Jul 2025, transcribing audio with record 5.63% WER and enabling AI tasks like summarization directly from speech✨ Key Capabilities Advanced text generation and processing** Natural language understanding and generation** Intelligent text manipulation and analysis** Tools Used n8n**: The automation platform that orchestrates the workflow Replicate API**: Access to the Zsxkib/canary-qwen-2.5b AI model Zsxkib Canary Qwen 2.5B**: The core AI model for text generation Built-in Error Handling**: Automatic retry logic and comprehensive error management How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Replicate API: Add your Replicate API token to the 'Set API Token' node Customize Parameters: Adjust the model parameters in the 'Set Text Parameters' node Test the Workflow: Run the workflow with your desired inputs Integrate: Connect this workflow to your existing automation pipelines Use Cases Content Writing**: Generate articles, blogs, and marketing copy Code Generation**: Assist with programming and code documentation Text Analysis**: Process and analyze large volumes of text data Automated Communication**: Generate responses and communication templates Connect with Me Website**: https://www.nofluff.online YouTube**: https://www.youtube.com/@YaronBeen/videos LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Get Replicate API**: https://replicate.com (Sign up to access powerful AI models) #n8n #automation #ai #replicate #aiautomation #workflow #nocode #textgeneration #nlp #aiwriting #textai #contentgeneration #aitext #machinelearning #artificialintelligence #aitools #automation #digitalart #contentcreation #productivity #innovation
by David Roberts
LangChain is a framework for building AI functionality that users large language models. By leveraging the functionality of LangChain, you can write even more powerful workflows. This workflow shows how you can write LangChain code within n8n, including importing LangChain modules. The workflow itself produces a summary of a YouTube video, when given the video's ID. Note that to use this template, you need to be on n8n version 1.19.4 or later.