langgraph-sitnova

What problem does it solve?

This skill provides a blueprint for building SITNOVA, an intelligent access control system that replaces human security guards with an AI operator. It solves the challenge of automating complex, real-time decision-making for vehicle and visitor access using LangGraph's stateful capabilities.

Core Features & Use Cases

• Stateful AI Operator: Manage complex, multi-step interactions for gate access using LangGraph's StateGraph.
• Real-time OCR Integration: Automatically identify vehicles by license plate and visitors by ID card (cédula) using integrated OCR tools.
• Conditional Routing & Authorization: Implement dynamic decision flows for pre-authorized access, resident approval, and denial based on configurable protocols.
• Use Case: Deploy an autonomous virtual porter for a residential condominium that can detect vehicles, read license plates, verify authorization, contact residents via WhatsApp for visitor approval, and control gate opening, all while logging every event for audit.

Quick Start

To implement the SITNOVA LangGraph skill, first define your OperatorState TypedDict. Then, create tools for check_authorized_vehicle, capture_plate_ocr, open_gate, and log_access_event. Assemble your StateGraph with nodes like greeting_node, validate_visitor_node, and open_gate_node, adding conditional edges to manage the flow.