Autonomous Research Notifier Agent

A Flask-based web application that provides an AI-powered assistant capable of managing scheduled jobs. The assistant can create, delete, and monitor scheduled tasks through a natural language interface.

Features

• 🤖 AI-powered assistant using Gemini 1.5 Flash
• 📅 Job scheduling system with support for various time intervals
• 🔒 Secure login system
• 💬 Natural language interface for job management
• 📊 Real-time job execution monitoring

Prerequisites

• Python 3.8 or higher
• pip (Python package installer)
• A Google Cloud API key for Gemini AI

Installation

1. Clone the repository:

git clone https://github.com/yourusername/autonomous-research-notifier-agent.git
cd autonomous-research-notifier-agent

2. Create and activate a virtual environment (recommended):

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

3. Install the required packages:

pip install -r requirements.txt

4. Set up environment variables: Create a .env file in the project root with the following variables:

USERNAME=your_username
PASSWORD=your_password
GOOGLE_API_KEY=your_google_api_key

Running the Application

Local Development

1. Start the Flask application:

python app.py

2. Open your browser and navigate to http://localhost:5000

Production Deployment

The application is configured to run on Heroku using the following Procfile:

web: flask run --host=0.0.0.0 --port=$PORT

Usage

1. Log in using your credentials
2. Navigate to the chat interface
3. Use natural language to interact with the assistant. Examples:
   • "Create a job that runs every 5 minutes"
   • "Show me all scheduled jobs"
   • "Delete job with ID abc123"

Job Scheduling

The application supports the following time units:

• seconds
• minutes
• hours
• days
• weeks

Project Structure

autonomous-research-notifier-agent/
├── app.py              # Main Flask application
├── agent.py           # AI agent implementation
├── jobs.py            # Job management system
├── templates/         # HTML templates
│   ├── login.html
│   └── chat.html
├── static/           # Static files (CSS, JS)
├── requirements.txt  # Python dependencies
└── Procfile         # Heroku deployment configuration

Development

Adding New Features

1. The AI agent's capabilities are defined in agent.py using the @agent.tool decorator
2. Job management logic is handled in jobs.py
3. Web interface is managed in app.py and the templates directory

Testing

To test the application locally:

1. Start the Flask server
2. Create a test job with a short interval
3. Monitor the console for job execution messages

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Flask web framework
• Google Gemini AI
• Schedule library for job management