AI System Call Optimizer

A real-time system call monitoring and optimization tool using eBPF, Flask, and optional AI (Groq API) for performance analysis and smart recommendations.

📌 Features

• 🟢 Real-time monitoring with eBPF
• 📊 Execution time & resource metrics (CPU, memory, I/O)
• 📁 Categorization of syscalls: File I/O, Process, Memory, IPC, etc.
• 🤖 AI-generated optimization tips (Groq API)
• 🛠️ Rule-based fallback suggestions
• 🌐 Clean Flask web UI with auto-refresh
• 🔍 API endpoints for programmatic access

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⚙️ System Requirements

• Linux with eBPF support (Kernel ≥ 4.1)
• Python 3.6+
• BCC (BPF Compiler Collection)

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🛠️ Installation

1. Clone the Repository

git clone https://github.com/yourusername/ai-system-call-optimizer.git
cd ai-system-call-optimizer

2. Install Python Dependencies

pip install -r requirements.txt

🔸 Note: The bcc Python package requires BCC system packages. Install them first.

3. Install BCC System Package

On Ubuntu:

sudo apt-get install bpfcc-tools linux-headers-$(uname -r)

On Other Distros:

Refer to the official BCC installation guide.

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🚀 Usage

1. Set the Groq API Key (Optional)

To enable AI optimization:

export GROQ_API_KEY=your_api_key_here

2. Start the Flask Application

python app.py

3. Run on a Different Port (Optional)

export PORT=8080
python app.py

4. Open the Web Interface

Visit: http://localhost:5000 (The page auto-refreshes every 5 seconds.)

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🔌 API Endpoints

Endpoint	Description
/performance	Get live syscall performance data
/recommendations	Get AI-based or rule-based optimization suggestions
/categories	View syscall categories and groupings
/syscall/<syscall>	Get detailed metrics for a specific syscall

Example:

curl http://localhost:5000/syscall/write

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🛠️ Configuration

• Groq API Key: Set GROQ_API_KEY as an environment variable.
• Performance Threshold: Defined in AISystemCallOptimizer (default: 0.05s)
• Refresh Interval: Modify REFRESH_INTERVAL (default: 5 seconds)

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⚡ Performance Considerations

• eBPF overhead is minimal but can slightly impact very high-load systems.
• Groq API calls are async/lightweight and do not block real-time monitoring.

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🔒 Security

• Requires root to attach eBPF probes:

sudo python app.py

• Ensure the host system is secure. eBPF can access kernel-level metrics.

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🤝 Contributing

We love contributions! Here’s how to get started:

1. Fork the repo
2. Create a new branch (git checkout -b feature-name)
3. Commit your changes
4. Push to your branch (git push origin feature-name)
5. Open a Pull Request 🚀

You can also:

• Open Issues for bugs or feature suggestions
• Discuss ideas via GitHub Discussions

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📄 License

This project is licensed under the MIT License. See the LICENSE file for full details.

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📝 Additional Notes

• 📷 Screenshot Placeholder: Replace path/to/screenshot.png above with your image file or a hosted URL.
• 📦 requirements.txt:

Flask
groq
psutil
bcc
numpy
python-dotenv

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