Project Title: LinuxAI Operations Assistant
Team Name: Tech nuggets
| Member | Responsibility |
|---|---|
| Roshan Patel | AI Agent + LLM + Tool Calling |
| Safwan Shaik | Linux System Integration |
| Nitheesh S | React/Electron UI + Dashboard |
| Sreekuttan S | Filesystem + Processes + Services + Testing |
| Vipul Raj Shah | Backend + Security + APIs + ML Engineer |
Integration of AI capabilities in the OS ecosystem(Linux Based) Submission Page
AI-Powered Linux Operations Assistant Using Natural Language Queries Develop an AI assistant that allows users to interact with Linux using natural language instead of complex commands. It should diagnose system issues, search files and documents, and provide easy-to-understand solutions and recommended Linux commands.
Our solution is an AI-powered Linux Operations Assistant that acts as an intelligent natural-language layer between the user and the Linux operating system. Users can simply ask questions such as “Why is my system slow?”, “Find large files,” or “Why isn’t my web server running?” and the AI will understand the intent, inspect system resources, processes, files, services, logs, and network status, diagnose the underlying problem, recommend the appropriate Linux commands or actions, and—after permission—safely execute and verify them. Unlike a basic AI command generator, our system combines AI reasoning, direct Linux OS integration, intelligent file/document search, autonomous troubleshooting, explainable recommendations, and a safety-controlled execution layer, making Linux more accessible, intelligent, and user-friendly.
Setup .env file in the root directory
GEMINI_API_KEY=
If you using Window then kindly run the Docker.
For backend, we use Ubuntu Container as linux
docker-compose up --build
For the frontend , in new terminal
cd frontend
npm run dev
Now, Visit http://localhost:5173
Deployed App: https://ssm-hackathon-wine.vercel.app/
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flowchart TD
A[User] --> B[LinuxAI Desktop Application]
B --> C[React UI]
C --> D[Local FastAPI Backend]
D --> E[AI Agent]
E --> F{Intent Detection}
F --> G[System Tools]
F --> H[Filesystem Tools]
F --> I[Process Tools]
F --> J[Service Tools]
F --> K[Network Tools]
G --> L[Linux OS]
H --> L
I --> L
J --> L
K --> L
L --> M[Real-Time System Data]
M --> N[Tool Result]
N --> O[Verification Layer]
O --> P[Natural Language Response]
P --> C
sequenceDiagram
participant U as User
participant UI as LinuxAI UI
participant API as Local Backend
participant AI as AI Agent
participant T as System Tool
participant OS as Linux OS
participant V as Verification
U->>UI: "Why is my system slow?"
UI->>API: User request
API->>AI: Analyze intent
AI->>AI: Select required tools
AI->>T: Get CPU/RAM/Process data
T->>OS: Inspect system
OS-->>T: Real system data
T-->>AI: Tool results
AI->>V: Verify data
V-->>AI: Verified
AI->>API: Generate explanation
API-->>UI: Natural language response
UI-->>U: System diagnosis
flowchart LR
OS[Linux Kernel]
OS --> CPU[/proc + psutil/]
OS --> MEM[/proc/meminfo/]
OS --> DISK[Filesystem APIs]
OS --> PROC[/proc processes/]
OS --> NET[Network APIs]
OS --> SYS[systemd]
CPU --> MON[System Monitor]
MEM --> MON
DISK --> MON
PROC --> MON
NET --> MON
SYS --> MON
MON --> WS[WebSocket / API]
WS --> UI[LinuxAI Dashboard]