AI Real-time Weather Alert Chat Application

This innovative solution combining real-time weather monitoring with AI-powered interactions. This application uses Streamlit for the frontend, Python and NATS for the backend, and integrates OpenAI's GPT model for decision making, setting alerts and intelligent responses. Read more on this article:

https://learn.glassflow.dev/blog/usecases/revolutionizing-real-time-alerts-with-ai-nats-and-streamlit

Installation

Before you begin, ensure you have Python and Docker installed on your system. This project requires Python 3.6 or later.

Clone the Repository

First, clone the repository to your local machine:

git clone https://github.com/glassflow/example-real-time-ai-alerts.git
cd example-real-time-ai-alerts

Set Up Python Environment

It's recommended to use a virtual environment for Python projects. Create and activate one using:

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

Install Python Dependencies

Install the required Python packages:

pip install -r requirements.txt

Set Up NATS Server with Docker

Ensure Docker is running on your machine. Then, start the NATS server using Docker Compose:

docker compose up -d

Configuration

Environment Variables

Create a .env file in the root directory of the project and add your OpenAI and Weather API keys:

OPENAI_API_KEY=your_openai_api_key
WEATHER_API_KEY=your_weather_api_key

Replace your_openai_api_key and your_weather_api_key with your actual API keys.Before running the application, ensure that the environment variables are set. If you're using a virtual environment, you can load them manually:

Running the Application

Start the Backend

Run the backend server with:

python backend.py

Start the Streamlit Frontend

In a new terminal, launch the Streamlit application:

streamlit run frontend.py

Testing the Application

1. Interact with the Chat: Open the Streamlit app in your web browser and try sending messages or asking questions.
2. Set Weather Alerts: Use the interface to set custom weather alerts and see how the application responds.
3. Monitor NATS Server: Optionally, you can monitor the NATS server at http://localhost:8222.

Shutting Down

To stop the application:

1. Close the Streamlit app.

2. Terminate the backend script (Ctrl+C in the terminal).

3. Stop the NATS server with Docker Compose:

   docker compose down

Contributing

Contributions to this project are welcome! Please fork the repository and submit a pull request with your changes.