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RACE Management Console Documentation

The RACE Management Console is an advanced industrial data monitoring and AI-driven analysis platform leveraging the Rule-Action-Cognition-Events (RACE) framework with enhanced multi-provider AI integration and intelligent routing capabilities.

Documentation Structure

• RACE MES Introduction - Executive presentation and business value overview
• System Architecture - Technical architecture and component design
• API Reference - Complete API endpoints documentation
• User Guide - Comprehensive user manual
• Installation Guide - Setup and deployment instructions
• Developer Guide - Development and customization guide
• Configuration Reference - Configuration options and settings
• Troubleshooting - Common issues and solutions

Quick Start

1. Configuration: Set up CONNECT Data Services API credentials
2. Asset Discovery: Discover and register monitored assets and streams
3. Rule Templates: Create rule templates for different equipment types
4. Template Instances: Deploy template instances to specific plant equipment
5. AI Providers: Configure AI providers for autonomous investigation
6. Monitoring: Real-time monitoring and event management

Key Features

Rule-Action-Cognition-Events (RACE) Framework

• Rule Engine: ISA-95 compliant rule creation with template-instance architecture
• Action Engine: Automated workflow execution based on rule triggers
• Cognition Engine: AI-powered autonomous investigation of MES operations
• Events Engine: Comprehensive event lifecycle management with real-time visualization

Multi-Provider AI Integration

• OpenAI GPT Models: Support for GPT-4, GPT-4-turbo with function calling
• Anthropic Claude: Claude Sonnet models with advanced reasoning
• Google Gemini: Gemini Pro models with multimodal capabilities
• Azure OpenAI: Enterprise-grade AI integration

Advanced Features

• Function Calling: Autonomous MES context data retrieval
• Context Filtering: User-selectable context types (Events, Rules, Assets, Streams, Plant Model)
• Real-time Monitoring: Background monitoring engine with 30-second intervals
• Event Visualization: Timeline-based event wall with grouping and filtering
• Template System: Reusable rule templates with placeholder-based configuration

System Requirements

• Backend: Python 3.11+, Flask, SQLAlchemy, PostgreSQL
• Frontend: Bootstrap 5, Vanilla JavaScript, Chart.js, Feather Icons
• External APIs: AVEVA CONNECT Data Services
• AI Providers: OpenAI, Anthropic, Google AI, Azure OpenAI (optional)

Support

For technical support and documentation updates, refer to the individual documentation files in this directory.