Update README.md

README.md

@@ -11,6 +11,7 @@ license: mit
 ---
 
 # ProMonitor 🌖
+
 A Gradio-based web interface for monitoring and managing system resources on an HP Z440 workstation, designed for cybersecurity and system performance monitoring. ProMonitor interacts with a FastAPI backend (running at http://localhost:8000 by default) to provide real-time metrics, historical data, resource limit management, process control, and emergency stop functionality.
 	•	Title: ProMonitor
 	•	Emoji: 🌖
@@ -18,7 +19,7 @@ A Gradio-based web interface for monitoring and managing system resources on an
 	•	SDK: Gradio (version 5.35.0)
 	•	App File: app.py
 	•	License: MIT
-Features
+## Features
 ProMonitor offers a comprehensive interface for system monitoring and management, with a focus on security and usability:
 	•	Dashboard: Displays real-time system metrics (CPU, memory, GPU, disk usage) and health status (Healthy, Degraded, Unhealthy) with a refreshable view.
 	•	History: Visualizes historical CPU, memory, and GPU usage over a user-specified time range (1–1440 minutes) using tables and line charts.
@@ -27,11 +28,11 @@ ProMonitor offers a comprehensive interface for system monitoring and management
 	•	Processes: Lists top CPU- and memory-intensive processes, with options to kill, suspend, or resume processes (secured with API key).
 	•	System Info: Provides static system information (platform, CPU, memory, disk, GPU) in a structured format.
 	•	Emergency Stop: Enables termination of high-memory processes with confirmation and API key authentication.
-Prerequisites
+## Prerequisites
 	•	Python: 3.10+ (as specified in .hf_space.yml)
 	•	FastAPI Backend: The backend (app/main.py) must be running and accessible (default: http://localhost:8000).
 	•	Dependencies: Listed in requirements.txt (see Installation).
-Installation
+## Installation
 	1	Clone the Repository:
git clone https://huggingface.co/spaces//ProMonitor
 	2	cd ProMonitor
 	3	
@@ -51,7 +52,7 @@ Installation
 	10	
If the backend is hosted elsewhere, update API_BASE_URL in .env.
 	11	Run the UI: Launch the Gradio app:
python app.py
 	12	
The UI will be available at http://localhost:7860.
-Usage
+# Usage
 	1	Access the UI: Open http://localhost:7860 in a web browser to access the ProMonitor interface.
 	2	Navigate Tabs:
 	◦	Dashboard: View real-time metrics and health status. Click “Refresh Metrics” to update.
@@ -64,8 +65,8 @@ Usage
 	3	Secure Actions:
 	◦	For process actions and emergency stop, provide the API key in the respective input fields.
 	◦	Ensure the backend validates the API key to prevent unauthorized access.
-Deployment on Hugging Face Spaces
-ProMonitor is configured for deployment on Hugging Face Spaces with the following setup:
+## Deployment on Hugging Face Spaces
+### ProMonitor is configured for deployment on Hugging Face Spaces with the following setup:
 	1	Push to Hugging Face Spaces:
 	◦	Create a new Space on Hugging Face: https://huggingface.co/new
 	◦	Select “Gradio” as the SDK and configure it as a public or private Space.
@@ -83,7 +84,7 @@ ProMonitor is configured for deployment on Hugging Face Spaces with the followin
 	◦	The FastAPI backend must be hosted separately (e.g., on another Hugging Face Space, AWS, or a local server with tunneling via ngrok).
 	◦	Update API_BASE_URL in Spaces secrets to point to the backend.
 	◦	Ensure the backend implements API key authentication for endpoints like /processes/action and /emergency/stop.
-Security Considerations
+## Security Considerations
 	•	API Key Authentication:
 	◦	The backend (app/main.py) must validate the Authorization header (e.g., Bearer ).
 	◦	Update the backend to include middleware for API key verification:
from fastapi import Depends, HTTPException, Security
@@ -104,7 +105,7 @@ Security Considerations
 	•	Rate Limiting:
 	◦	Implement rate limiting in the Gradio UI (e.g., using the ratelimit library) to prevent overwhelming the backend.
 	◦	Consider adding rate limiting to the FastAPI backend using slowapi.
-Testing
+## Testing
 To ensure the UI works correctly, test it locally before deploying:
 	1	Install Testing Dependencies:
pip install pytest pytest-httpx pytest-asyncio
 	2	
@@ -138,7 +139,7 @@ To ensure the UI works correctly, test it locally before deploying:
 	◦	Start the FastAPI backend: uvicorn app.main:app --host 0.0.0.0 --port 8000
 	◦	Run the Gradio UI: python app.py
 	◦	Verify all tabs and functionality in the browser.
-Troubleshooting
+## Troubleshooting
 	•	Backend Unreachable:
 	◦	Ensure the FastAPI backend is running and accessible at API_BASE_URL.
 	◦	Check network connectivity and firewall settings.
@@ -150,17 +151,17 @@ Troubleshooting
 	◦	Review ui.log for error messages.
 	◦	Ensure gradio==5.35.0 is installed correctly.
 	◦	Check Hugging Face Spaces logs for deployment issues.
-Contributing
-Contributions are welcome! To contribute:
+## Contributing
+### Contributions are welcome! To contribute:
 	1	Fork the repository.
 	2	Create a feature branch: git checkout -b feature/your-feature.
 	3	Commit changes: git commit -m "Add your feature".
 	4	Push to the branch: git push origin feature/your-feature.
 	5	Open a pull request on the Hugging Face Space repository.
 Please include tests and follow PEP 8 guidelines.
-License
+## License
 This project is licensed under the MIT License. See the LICENSE file for details.
-Acknowledgments
+## Acknowledgments
 	•	Built with Gradio for the UI and FastAPI for the backend.
 	•	Designed for cybersecurity and system performance monitoring on HP Z440 workstations.
 	•	Hosted on Hugging Face Spaces.