Smart break recommendation system using Google Calendar, weather data, and GPT-4 to Slack
Who is this for This workflow is perfect for busy professionals, consultants, and anyone who frequently travels between meetings. If you want to make the most of your free time between appointments and discover great nearby spots without manual searching, this template is for you. What it does This workflow automatically monitors your Google Calendar and identifies gaps between appointments. When it detects sufficient free time (configurable, default 30+ minutes), it calculates travel time to your next destination, checks the weather, and uses AI to recommend the top 3 spots to visit during your break. Recommendations are weather-aware: indoor spots like cafés in malls or stations for rainy days, and outdoor terraces or open-air venues for nice weather. How it works
Schedule Trigger - Runs every 30 minutes to check your calendar Fetch Data - Gets your next calendar event and user preferences from Notion Calculate Gap Time - Determines available free time by subtracting travel time (via Google Maps) from time until your next appointment Weather Check - Gets current weather at your destination using OpenWeatherMap Smart Routing - Routes to indoor or outdoor spot search based on weather conditions AI Recommendations - GPT-4.1-mini analyzes spots and generates personalized top 3 recommendations Slack Notification - Sends a friendly message with recommendations to your Slack channel
Set up steps
Configure API Keys - Add your Google Maps, Google Places, and OpenWeatherMap API keys in the "Set Configuration" node Connect Google Calendar - Set up OAuth connection and select your calendar Set up Notion - Create a database for user preferences and add the database ID Connect Slack - Set up OAuth and specify your notification channel Connect OpenAI - Add your OpenAI API credentials Customize - Adjust currentLocation and minGapTimeMinutes to your needs
Requirements
Google Cloud account with Maps and Places APIs enabled OpenWeatherMap API key (free tier available) Notion account with a preferences database Slack workspace with bot permissions OpenAI API key
How to customize
Change trigger frequency: Modify the Schedule Trigger interval Adjust minimum gap time: Change minGapTimeMinutes in the configuration node Modify search radius: Edit the radius parameter in the Places API calls (default: 1000m) Customize spot types: Modify the type and keyword parameters in the HTTP Request nodes Change AI model: Switch to a different OpenAI model in the AI node Localize language: Update the AI prompt to generate responses in your preferred language
Smart Break Recommendation System using Google Calendar, Weather Data, and GPT-4 to Slack
This n8n workflow automates the process of generating personalized break recommendations based on your Google Calendar events, local weather conditions, and intelligent suggestions from GPT-4, delivering them directly to your Slack channel. It aims to promote well-being and productivity by suggesting optimal times and activities for breaks.
What it does
- Triggers on Schedule: The workflow starts on a predefined schedule (e.g., daily) to check for upcoming events.
- Fetches Google Calendar Events: It retrieves your upcoming events from a specified Google Calendar.
- Filters for Busy Periods: It identifies periods in your calendar where you have scheduled events, indicating busy work times.
- Retrieves Local Weather: It fetches current weather data for a specified location using OpenWeatherMap.
- Prepares Data for GPT-4: It combines the calendar event data and weather information into a structured prompt for GPT-4.
- Generates Break Recommendations with GPT-4: It sends the prepared data to GPT-4 (via the OpenAI node) to generate smart break recommendations, considering factors like event density, weather, and general well-being advice.
- Formats Recommendations: The GPT-4 output is then processed and formatted into a clear, readable message.
- Sends to Slack: The final break recommendations are posted as a message to a designated Slack channel.
Prerequisites/Requirements
- n8n Instance: A running n8n instance.
- Google Calendar Account: Configured with credentials in n8n to access your calendar events.
- OpenWeatherMap API Key: An API key for OpenWeatherMap to fetch weather data.
- OpenAI API Key: An API key for OpenAI (specifically for GPT-4 access).
- Slack Account: Configured with credentials in n8n to post messages to a channel.
Setup/Usage
- Import the Workflow: Import the provided JSON into your n8n instance.
- Configure Credentials:
- Google Calendar Node: Set up your Google Calendar OAuth2 credentials.
- OpenWeatherMap Node: Enter your OpenWeatherMap API key.
- OpenAI Node: Enter your OpenAI API key.
- Slack Node: Set up your Slack OAuth2 credentials.
- Customize Nodes:
- Schedule Trigger: Adjust the schedule to your preferred frequency (e.g., daily at a specific time).
- Google Calendar Node: Specify the calendar ID you want to monitor.
- OpenWeatherMap Node: Enter the city and country for weather data.
- Code Node: Review and adjust the JavaScript logic if you need to modify how data is prepared for GPT-4 or how recommendations are parsed.
- OpenAI Node: You might want to fine-tune the prompt to GPT-4 to get more specific types of recommendations.
- Slack Node: Specify the Slack channel where you want to receive the break recommendations.
- Activate the Workflow: Once configured, activate the workflow to start receiving smart break recommendations.
Related Templates
Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax
Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions
Automate Dutch Public Procurement Data Collection with TenderNed
TenderNed Public Procurement What This Workflow Does This workflow automates the collection of public procurement data from TenderNed (the official Dutch tender platform). It: Fetches the latest tender publications from the TenderNed API Retrieves detailed information in both XML and JSON formats for each tender Parses and extracts key information like organization names, titles, descriptions, and reference numbers Filters results based on your custom criteria Stores the data in a database for easy querying and analysis Setup Instructions This template comes with sticky notes providing step-by-step instructions in Dutch and various query options you can customize. Prerequisites TenderNed API Access - Register at TenderNed for API credentials Configuration Steps Set up TenderNed credentials: Add HTTP Basic Auth credentials with your TenderNed API username and password Apply these credentials to the three HTTP Request nodes: "Tenderned Publicaties" "Haal XML Details" "Haal JSON Details" Customize filters: Modify the "Filter op ..." node to match your specific requirements Examples: specific organizations, contract values, regions, etc. How It Works Step 1: Trigger The workflow can be triggered either manually for testing or automatically on a daily schedule. Step 2: Fetch Publications Makes an API call to TenderNed to retrieve a list of recent publications (up to 100 per request). Step 3: Process & Split Extracts the tender array from the response and splits it into individual items for processing. Step 4: Fetch Details For each tender, the workflow makes two parallel API calls: XML endpoint - Retrieves the complete tender documentation in XML format JSON endpoint - Fetches metadata including reference numbers and keywords Step 5: Parse & Merge Parses the XML data and merges it with the JSON metadata and batch information into a single data structure. Step 6: Extract Fields Maps the raw API data to clean, structured fields including: Publication ID and date Organization name Tender title and description Reference numbers (kenmerk, TED number) Step 7: Filter Applies your custom filter criteria to focus on relevant tenders only. Step 8: Store Inserts the processed data into your database for storage and future analysis. Customization Tips Modify API Parameters In the "Tenderned Publicaties" node, you can adjust: offset: Starting position for pagination size: Number of results per request (max 100) Add query parameters for date ranges, status filters, etc. Add More Fields Extend the "Splits Alle Velden" node to extract additional fields from the XML/JSON data, such as: Contract value estimates Deadline dates CPV codes (procurement classification) Contact information Integrate Notifications Add a Slack, Email, or Discord node after the filter to get notified about new matching tenders. Incremental Updates Modify the workflow to only fetch new tenders by: Storing the last execution timestamp Adding date filters to the API query Only processing publications newer than the last run Troubleshooting No data returned? Verify your TenderNed API credentials are correct Check that you have setup youre filter proper Need help setting this up or interested in a complete tender analysis solution? Get in touch 🔗 LinkedIn – Wessel Bulte