Update README.md

README.md

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 # 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: 🌖
-	•	Color Scheme: Red to Blue
-	•	SDK: Gradio (version 5.35.0)
-	•	App File: app.py
-	•	License: MIT
 ## 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.
-	•	Resource Limits: Allows setting and viewing CPU, memory, and GPU power limits, with validation and feedback.
-	•	Alerts: Shows active system alerts with severity levels (critical, warning) in a clear, color-coded table.
-	•	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.
+- 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.
+- Resource Limits: Allows setting and viewing CPU, memory, and GPU power limits, with validation and feedback.
+- Alerts: Shows active system alerts with severity levels (critical, warning) in a clear, color-coded table.
+- 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
-	•	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).
+- 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
 	1	Clone the Repository:
git clone https://huggingface.co/spaces//ProMonitor
 	2	cd ProMonitor
@@ -41,6 +36,7 @@ ProMonitor offers a comprehensive interface for system monitoring and management
 	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.
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 # Usage
 	1	Access the UI: Open http://localhost:7860 in a web browser to access the ProMonitor interface.
 	2	Navigate Tabs:
@@ -54,6 +50,7 @@ ProMonitor offers a comprehensive interface for system monitoring and management
 	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.
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 ## Deployment on Hugging Face Spaces
 ### ProMonitor is configured for deployment on Hugging Face Spaces with the following setup:
 	1	Push to Hugging Face Spaces:
@@ -73,6 +70,7 @@ ProMonitor offers a comprehensive interface for system monitoring and management
 	◦	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.
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 ## Security Considerations
 	•	API Key Authentication:
 	◦	The backend (app/main.py) must validate the Authorization header (e.g., Bearer ).
@@ -94,6 +92,7 @@ ProMonitor offers a comprehensive interface for system monitoring and management
 	•	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.
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 ## Testing
 To ensure the UI works correctly, test it locally before deploying:
 	1	Install Testing Dependencies:
pip install pytest pytest-httpx pytest-asyncio
@@ -128,18 +127,20 @@ 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.
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 ## Troubleshooting
-	•	Backend Unreachable:
-	◦	Ensure the FastAPI backend is running and accessible at API_BASE_URL.
-	◦	Check network connectivity and firewall settings.
-	◦	Use a tunneling service like ngrok for local testing: ngrok http 8000.
-	•	API Key Errors:
-	◦	Verify the API_KEY matches the backend’s expected value.
-	◦	Check backend logs for authentication errors.
-	•	Gradio UI Issues:
-	◦	Review ui.log for error messages.
-	◦	Ensure gradio==5.35.0 is installed correctly.
-	◦	Check Hugging Face Spaces logs for deployment issues.
+- Backend Unreachable:
+- Ensure the FastAPI backend is running and accessible at API_BASE_URL.
+- Check network connectivity and firewall settings.
+- Use a tunneling service like ngrok for local testing: ngrok http 8000.
+- API Key Errors:
+- Verify the API_KEY matches the backend’s expected value.
+- Check backend logs for authentication errors.
+- Gradio UI Issues:
+- 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:
 	1	Fork the repository.
@@ -148,10 +149,12 @@ To ensure the UI works correctly, test it locally before deploying:
 	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.
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 ## License
 This project is licensed under the MIT License. See the LICENSE file for details.
+
 ## 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.
+- 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.