🛡️ SentinelGrid — AI-Powered Compound-Risk Detection

A RAG-based compound-risk detection system for chemical process plants.

SentinelGrid demonstrates how Retrieval-Augmented Generation (RAG) can detect dangerous situations where every individual sensor reading stays within normal range, but the combination of factors creates critical risk that traditional threshold-based alarms miss entirely.

🏗️ Architecture

Reactor Simulator → Windowing (3-tick) → Chunking (<60 words)
                                              ↓
                              ┌── ChromaDB: top-3 historical matches
                              ├── ChromaDB: top-1 SOP snippet
                              └── Groq LLM: risk scoring
                                    ↓ (if risk > 70%)
                              Groq 70B: plain-language explanation
                                    ↓
                              Streamlit Dashboard + Human-in-the-Loop

🔑 Key Innovation: Scenario #10

In Scenario #10, no single alarm fires:

• Temperature: 352°C (normal: 340-370°C) ✅
• Pressure: 10.1 bar (normal: 8-12 bar) ✅
• Methane: 3200 ppm (alarm: 5000 ppm) ✅
• Vibration: 5.5 mm/s (alarm: 10 mm/s) ✅

But the compound risk is critical because:

• Maintenance is active with worker present in zone
• Ventilation is OFF → methane slowly accumulating
• Vibration trending upward → equipment stress
• All factors together = ~93% compound risk score

🚀 Quick Start

Local Development

# 1. Install dependencies
pip install -r requirements.txt

# 2. Set your Groq API key
cp .env.example .env
# Edit .env and add your GROQ_API_KEY from console.groq.com

# 3. Build the knowledge base (one-time)
python -m sentinelgrid.knowledge_base.build_kb

# 4. Run the dashboard
streamlit run sentinelgrid/app.py

Hugging Face Spaces Deployment

1. Create a new Space → SDK: Streamlit, Hardware: free CPU basic
2. Push this repo (app.py path: sentinelgrid/app.py)
3. Add GROQ_API_KEY in Space settings → Repository secrets
4. The pre-built ChromaDB in chroma_db/ is committed with the repo

🧰 Tech Stack (All Free-Tier)

Component	Technology	Cost
Language	Python 3.11	Free
Simulator	NumPy	Free
Embeddings	sentence-transformers (all-MiniLM-L6-v2)	Free (local CPU)
Vector DB	ChromaDB (embedded, persistent)	Free
LLM Scoring	Groq API — llama-3.1-8b-instant	Free tier
LLM Explanation	Groq API — llama-3.3-70b-versatile	Free tier (only for risk > 70%)
Dashboard	Streamlit	Free
Deployment	Hugging Face Spaces	Free CPU tier

🔒 Token Minimization

• Window text: <60 words
• Retrieved context: max 3 historical (60 words each) + 1 SOP (~100 words)
• Total prompt body: <450 words
• 8b model for routine scoring; 70b only for high-risk escalation
• In-memory cache prevents duplicate Groq calls for similar windows
• System prompt identical across calls for Groq prompt caching

📁 Project Structure

sentinelgrid/
├── app.py                    # Streamlit dashboard
├── simulator/
│   ├── reactor_physics.py    # Physics equations, state updates
│   └── scenarios.py          # Named scenarios incl. Scenario #10
├── pipeline/
│   ├── windowing.py          # 3-tick non-overlapping windows
│   ├── labeling.py           # Rule-based ground-truth labeler (offline)
│   ├── chunking.py           # Window → text chunk + metadata
│   └── embed_store.py        # sentence-transformers + ChromaDB
├── knowledge_base/
│   ├── build_kb.py           # Embeds SOPs + historical data
│   └── sop_docs/             # Safety procedure documents
├── reasoning/
│   ├── groq_client.py        # Groq API wrapper with retry
│   ├── prompt_templates.py   # Token-frugal prompt templates
│   └── risk_agent.py         # RAG orchestration agent
├── chroma_db/                # Pre-built ChromaDB (committed)
├── requirements.txt
├── .env.example
└── README.md

🧑‍⚖️ Human-in-the-Loop

SentinelGrid never auto-executes safety actions. When compound risk is detected:

1. Recommended actions are displayed (evacuate, reduce feed, alert supervisor)
2. Operator must manually acknowledge each action
3. The system logs acknowledgments but cannot override human decisions

---

Built for ET Hackathon 2026