Integrating AI with Open-Meteo API for Enhanced Weather Forecasting

For Open-Meteo API, this workflow automates weather forecasting by integrating AI to fetch geolocation and forecast data. Users can input a city name to receive accurate weather predictions for the next several days, aiding in travel planning and decision-making. The manual trigger allows for interactive use, making it ideal for workshops and demonstrations.

7/8/2025
12 nodes
Medium
manualmediumlangchainsticky noteadvancedapiintegration
Categories:
Manual TriggeredMedium Workflow
Integrations:
LangChainSticky Note

Target Audience

This workflow is tailored for:
- Developers looking to integrate AI with weather APIs for applications.
- Data Scientists who need reliable weather forecasts for analysis.
- Travel Planners wanting to provide weather insights for trip planning.
- Educators seeking a practical example of AI integration in workshops.
- Businesses in the tourism or logistics sectors requiring accurate weather data to optimize operations.

Problem Solved

This workflow addresses the challenge of obtaining accurate and timely weather forecasts by:
- Automating the process of fetching geographic coordinates and weather data.
- Integrating AI capabilities to streamline user interactions and make intelligent decisions about which API to call based on user input.
- Enhancing the user experience by allowing natural language queries for weather information.

Workflow Steps

  • Trigger: The workflow begins when a chat message is received, prompting the user to request weather information for a specific city.
    2. AI Processing: The message is processed by the OpenAI Chat Model, which understands the user's request.
    3. Geolocation Request: The workflow sends a request to the Open-Meteo Geocoding API to obtain the geographic coordinates (latitude and longitude) of the requested city.
    4. Weather Forecast Request: Once the coordinates are retrieved, another request is made to the Open-Meteo Forecast API to get the weather forecast for the next specified number of days.
    5. Response Delivery: The weather information is compiled and sent back to the user in the chat interface, providing them with the forecast details they requested.

    • Customization Guide

    To customize and adapt this workflow:
    - Change the API Endpoints: Modify the URL parameters in the HTTP request nodes if you wish to use different APIs or endpoints.
    - Adjust the Forecast Parameters: Edit the parameters for the weather forecast request to include different data points (like humidity or wind speed) as needed.
    - Modify User Prompts: Update the initial messages in the chat trigger to guide users on how to interact with the chatbot effectively.
    - Integrate Additional Tools: Add more nodes to the workflow for additional functionalities, such as saving user queries or integrating with other data sources for enriched responses.