🤖 SysWatch — AI Powered System Intelligence

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📌 Overview

SysWatch is an intelligent real-time monitoring system that combines:

• ⚡ Live system monitoring
• 🧠 AI-powered advisory insights
• 📈 Trend analysis
• 🚨 Smart anomaly detection
• 🔍 Software issue detection
• 💬 RAG-based AI assistant

Instead of only displaying CPU/RAM numbers, SysWatch explains:

What is happening, why it is happening, and what to do next.

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✨ Core Features

Feature	Description
📊 Real-Time Dashboard	Live CPU, RAM, Disk, Network monitoring
🚨 Smart Alerts	Detects warnings and critical state transitions
🧠 AI Advisor	Generates human-readable optimization suggestions
📈 Historical Analysis	Tracks metrics over time using CSV storage
🔍 Software Detection	Detects memory leaks, thread explosions, suspicious processes
💬 AI Chat	RAG-powered contextual assistant using system history
⚡ Fast APIs	Flask backend with optimized routes and caching
🧪 Evaluation Framework	Precision, Recall, F1, Latency benchmarking

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🧠 Architecture

sys_watcher/
│
├── app.py                  # Flask backend and APIs
├── snapshot.py             # System metrics collection
├── advisor.py              # AI advisory engine
├── software_detector.py    # Software issue detection
├── storage.py              # CSV storage utilities
├── monitor.py              # Terminal monitoring mode
│
├── templates/
│   └── index.html          # Frontend dashboard
│
├── evaluation/
│   ├── evaluate.py         # Evaluation framework
│   └── test_cases.json     # Ground truth cases
│
├── metrics.csv
├── anomalies.csv
├── .env
└── README.md

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🌐 API Endpoints

Endpoint	Purpose
/api/metrics	Live CPU/RAM/Disk metrics
/api/processes	Top RAM-consuming processes
/api/network	Network statistics
/api/history	Historical CSV data
/api/anomalies	Logged anomaly events
/api/advisor	AI-generated system advice
/api/chat	RAG-based AI assistant

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📊 Evaluation Metrics

SysWatch includes an evaluation framework for measuring:

• ✅ Precision
• ✅ Recall
• ✅ F1 Score
• ✅ Latency
• ✅ Advisor relevance

📈 Latest Results

Precision : 1.0000
Recall    : 1.0000
F1 Score  : 1.0000

Average Latency : 269ms
Advisor Relevance : 0.56

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🛠️ Tech Stack

Layer	Technology
Backend	Flask + Python
Monitoring	psutil
AI	Groq + Llama 3.1
Frontend	HTML/CSS/JavaScript
Visualization	Chart.js
Terminal UI	Rich
Storage	CSV

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🔍 Detection Capabilities

🔴 Critical CPU spikes
🟡 High RAM consumption
🔴 Disk nearing full capacity
🟡 Memory leak suspects
🔴 Handle leaks
🟡 Thread explosions
🔴 Suspicious process locations

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🔐 Security

• ✅ Runs locally
• ✅ Environment variables protected via .env
• ✅ No telemetry
• ✅ Read-only monitoring
• ✅ Sensitive files excluded using .gitignore

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🗺️ Future Improvements

• Predictive crash analysis
• Email/desktop notifications
• Docker deployment
• Multi-machine monitoring
• PDF system reports
• ML-based anomaly prediction

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👩‍💻 Author

Ramya Dattaraj Joshi

Software Engineer • AI Systems Enthusiast

Built as part of advanced system intelligence and GenAI experimentation.

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⭐ If you found SysWatch interesting, consider starring the repository.