What This Automation Does
This workflow gets user chat requests for weather information in a city and timeframe.
It fetches the city location then gets a weather forecast.
The final result is a clear weather report for the user.
The goal is to save time and avoid errors in finding weather data manually.
How This Workflow Works (Input → Process → Output)
Input
- User sends chat message asking for weather in a city and time period.
Processing Steps
- Chat Trigger: Detects the chat input.
- OpenAI Chat Model: Understands the query and plans next actions.
- Chat Memory Buffer: Keeps track of chat history for follow-up messages.
- Agent Node: Controls which API calls happen next.
- Geolocation Tool: Requests city latitude and longitude from Open-Meteo geocoding API.
- Weather Forecast Tool: Gets weather forecast data from Open-Meteo API using the geolocation.
Output
User receives detailed weather forecast report for selected days and city.
Who Should Use This Workflow
This workflow fits people who need quick, reliable weather info for different places.
It’s good for event planners, travelers, or anyone checking weather regularly.
Users with little time for manual search will save many hours.
Tools and Services Used
- n8n Platform: Runs the automation workflow.
- OpenAI API: Understands chat input and manages API calls.
- Open-Meteo Geocoding API: Finds city coordinates.
- Open-Meteo Weather Forecast API: Provides temperature and precipitation forecast data.
Beginner Step-By-Step: Using This Workflow in n8n Production
Step 1: Import Workflow
- Download the workflow file using the Download button on this page.
- Open the n8n editor where you want to use this workflow.
- Choose Import from File and upload the downloaded workflow JSON.
Step 2: Configure Credentials
- Enter your OpenAI API Key in the OpenAI Chat Model node’s credential settings.
- Make sure the HTTP Request nodes for geolocation and weather have correct URLs (usually no change needed).
- If needed, update IDs, emails, channels, folders, or tables if the workflow connects to other services (not in this basic workflow).
Step 3: Test the Workflow
- Run the workflow once manually to check if it returns weather data correctly.
- You can test sending messages like: Weather Forecast for the Next 7 Days in São Paulo.
Step 4: Activate for Production
- Switch the workflow to active in n8n.
- Connect your chat user interface or API to the Webhook URL from the chat trigger node for live use.
If you want full control or better performance, consider self-host n8n on your own server.
Customization Ideas
- Change forecast days count in the weather tool to get shorter or longer reports.
- Add extra weather info like wind speed or humidity by updating API query parameters.
- Switch the OpenAI model to GPT-3.5-turbo for lower cost or other models as needed.
- Add more API tools to include other data sources, then update the AI agent workflow.
Inputs and Outputs Explained
- Input: User chat message with city name and desired forecast length.
- Output: Weather forecast summary showing temperature max and precipitation for requested days.
Common Failures and Fixes
- OpenAI 401 Unauthorized — Check API key in OpenAI Chat Model node and update if expired.
- No Weather Data Returned — Confirm latitude and longitude map correctly from geolocation response to weather API query.
- Chat Lost Previous Messages — Make sure Chat Memory Buffer node is connected and active.
- Webhook Not Responding — Verify workflow is active and network can reach webhook URL.
Summary of What You Get
✓ Quick and easy weather info by just chatting.
✓ Automatically finds location and fetches accurate forecasts.
✓ Saves time by avoiding manual web searches.
→ A weather assistant ready inside your n8n setup.
Deployment Guide
After importing and testing, turn your workflow on in n8n.
Connect frontend chat with the webhook URL from the When chat message received node.
Watch execution logs to ensure smooth runs.
Optionally, add notifications or logging nodes for better production monitoring.