DR_AIJSONA - Enterprise JSON Analytics Engine

A high-performance, security-first RAG (Retrieval-Augmented Generation) engine designed to analyze complex JSON datasets while enforcing strict data access policies. Optimized for ERP integrations and VPS deployment.

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🔐 Advanced Security Features (v2.2.0)

• PBAC (Policy-Based Access Control)
  Restricts AI knowledge based on user roles (Admin, Manager, Staff, etc.)

• JWT Authentication
  Integrates with external ERP tokens for role-based identity

• Role-Isolated Vector DBs
  Separate FAISS indexes per role to prevent data leakage

• Dynamic Chain Construction
  AI pipeline adapts dynamically based on user permissions

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🛠️ Microservices Architecture

User Query + JWT
        ↓
   [Nginx Proxy]
        ↓
[FastAPI Engine (PBAC Layer)]
        ↓
 Check Role Index
        ↓
 [Role-Specific FAISS]
        ↓
 [Re-Ranker (Flashrank)]
        ↓
 [Ollama Local LLM]

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📂 Project Structure

DR_AIJSONA/
├── data/                 # Raw JSON files
├── schemas/              # JSON schema definitions
├── policy.json           # PBAC rules
├── faiss_indexes/        # Role-based vector DBs
├── src/
│   ├── main.py           # API + security middleware
│   ├── brain.py          # Multi-role RAG logic
│   ├── loader.py         # Policy-aware loader
│   └── __init__.py
├── Dockerfile
└── docker-compose.yml

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🚀 Deployment Guide

1. Environment Configuration

Update your environment:

JWT_SECRET=your_erp_jwt_signing_key
OLLAMA_BASE_URL=http://10.73.7.198:11434

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2. Multi-Role Indexing

curl -X POST http://localhost:8000/retrain

• Reads policy.json
• Builds isolated FAISS indexes per role

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📡 API Endpoints

🔹 Secure Ask AI

Endpoint: /ask
Method: POST

Headers:

Authorization: Bearer <JWT_TOKEN>

Request:

{
  "question": "What is the total revenue for this quarter?"
}

👉 Response is filtered based on role permissions.

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🔹 Role Re-indexing

Endpoint: /retrain
Method: POST

• Rebuilds all role-based indexes
• Required after data/policy updates

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🐳 Volume Mapping & Persistence

Host Path	Container Path	Purpose
./data	/app/data	Raw datasets
./policy.json	/app/policy.json	Access rules
./faiss_indexes	/app/faiss_indexes	Secure vector DB
./cache_data	/app/cache_data	Performance cache

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🧠 Performance Metrics

Scenario	Logic	Response Time
Cached Answer	Exact match	< 10ms
Semantic Match	Vector similarity	< 150ms
Full RAG Cycle	PBAC + LLM	1.5s – 3s

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🛡️ Security Model

• Zero Cloud Leakage: Fully local inference via Ollama
• Memory Isolation: Role-based FAISS separation
• Strict Access Control: Policy-driven data visibility

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⚙️ ERP Integration Highlights

• Uses existing ERP JWT authentication
• Maps roles directly to AI access layers
• Enables secure “Ask Your Data” feature

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📄 License

MIT License

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🤝 Contributing

Contributions and improvements are welcome!

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👨‍💻 Maintainer

Danuja Dilanka
Optimized for Enterprise ERP Systems