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Version: 2.0.0

Natural Language Weather App

This simple web application allows you to check the current weather or forecast for a location using natural language queries (e.g., "Forecast for Tokyo", "Is it raining in Seattle?").

It leverages the Gaia Language Model (via an OpenAI compatible endpoint) to understand your request and the Nubila Weather API to fetch the actual weather data.

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The complete source code and detailed instructions for setting up and running this example can be found in the Gaia Cookbook repository.

Features​

  • Get current weather or forecasts using plain English.
  • Uses Gaia LLM to interpret the location and desired information (current/forecast) from your query.
  • Fetches detailed weather data from the Nubila API.
  • Displays the LLM's interpretation (location, coordinates, request type).
  • Illustrates the concept of an LLM "tool call" by showing which function and arguments the LLM conceptually decided to use.
  • Provides clickable example prompts for quick use.
  • Simple, clean UI built with vanilla JavaScript, Node.js, and CSS.

How it Works​

  1. User Query: You enter a query like "What's the weather like in Berlin?" into the web interface.
  2. Backend Request: The query is sent from your browser to the Node.js backend server.
  3. LLM Analysis (Gaia): The backend sends your query to the Gaia API. Gaia analyzes it to:
    • Identify the location (e.g., "Berlin").
    • Determine approximate geographical coordinates (latitude and longitude).
    • Understand if you want the 'current' weather or a 'forecast'.
  4. API Call (Nubila): The backend uses the coordinates and the request type ('current' or 'forecast') identified by Gaia to make a request to the appropriate Nubila Weather API endpoint.
  5. Weather Data: The Nubila API responds with the requested weather data.
  6. Frontend Display: The backend sends both Gaia's analysis and Nubila's weather data back to your browser. The frontend then displays:
    • How Gaia interpreted your request.
    • A simulation of the "tool call" Gaia would make.
    • The formatted current weather or forecast details.

Prerequisites​

  • Node.js and npm: Download and install from nodejs.org.
  • Nubila API Key: You need an API key from Nubila Weather API. Sign up or log in here to obtain one.

Setup & Installation​

  1. Clone the repository (or download the files):

    git clone <repository-url>
    cd <repository-folder-name>

    (Replace <repository-url> and <repository-folder-name> accordingly)

  2. Install dependencies:

    npm install

    This installs Express, node-fetch, dotenv, and cors.

Configuration​

  1. Create .env file: In the root directory of the project, create a file named .env.

  2. Add API Key and Settings: Open the .env file and add the following lines, replacing YOUR_NUBILA_API_KEY_HERE with your actual Nubila API key:

    NUBILA_API_KEY=YOUR_NUBILA_API_KEY_HERE
    GAIA_API_ENDPOINT=https://llama70b.gaia.domains/v1/chat/completions
    GAIA_API_KEY=your-gaia-api-key
    PORT=3000
    • NUBILA_API_KEY: Your secret key for the Nubila API.
    • GAIA_API_ENDPOINT: The endpoint for the Gaia LLM.
    • GAIA_API_KEY: Get your Gaia API key by following this tutorial: https://docs.gaianet.ai/getting-started/authentication
    • PORT: The port the local server will run on (default is 3000).

  3. Important: The .env file contains sensitive information (your API key). Ensure it is listed in your .gitignore file (it should be by default if you cloned) so you don't accidentally commit it to version control.

Running the Application​

  1. Start the server:

    node server.js

  2. Open the app: Open your web browser and navigate to: http://localhost:3000 (or http://localhost:YOUR_PORT if you changed the PORT in .env).

  3. Enter your weather query or click one of the suggestion buttons!

Technology Stack​

  • Backend: Node.js, Express.js
  • Frontend: Vanilla JavaScript (ES6+), HTML5, CSS3
  • APIs:
    • Gaia API (via OpenAI compatible endpoint) for Natural Language Understanding
    • Nubila Weather API for weather data
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The complete source code and detailed instructions for setting up and running this example can be found in the Gaia Cookbook repository.