CogniwareIMS - AI-Powered Inventory Management System

OPEA Intel License Docker

Overview

CogniwareIMS is a production-ready, AI-powered Inventory Management System built on the OPEA (Open Platform for Enterprise AI) framework, specifically optimized for Intel Xeon processors. It demonstrates enterprise-grade integration of multiple GenAI microservices for intelligent inventory operations.

Built with CogniDREAM Code Generation Platform, a Cogniware AI engine for creating production-ready agentic platforms.

Key Features

  • 🤖 AI-Powered Queries: Natural language inventory search using RAG (Retrieval-Augmented Generation)

  • 📊 DBQnA Agent: Convert natural language to SQL for database queries

  • 📝 Document Summarization: Automatic report generation and analysis

  • 🔄 Continuous Learning: Add new knowledge and retrain models in real-time

  • 📤 Multi-Format Upload: Upload CSV, XLSX, PDF, DOCX files directly to knowledge base

  • 💬 Interactive Agent: Context-aware conversational AI for inventory management

  • 📈 Real-time Analytics: Dynamic graphs, forecasting, and performance metrics

  • 🐳 Fully Dockerized: One-command deployment with Docker Compose

  • ⚡ Intel Optimized: Leverages Intel Xeon CPU capabilities for maximum performance

Quick Start

Prerequisites

  • Docker 24.0+ and Docker Compose 2.0+

  • 16GB RAM minimum (32GB recommended)

  • 50GB free disk space

  • HuggingFace API token (for model downloads)

Step 1: Set Environment Variables

export HUGGINGFACEHUB_API_TOKEN=your_token_here

Step 2: Download Sample Data

./scripts/download-data.sh

Step 3: Deploy with Docker Compose

cd docker_compose/intel/cpu/xeon
docker compose up -d

Step 4: Access the Application

  • Frontend: http://localhost:3000

  • Backend API: http://localhost:8000

  • API Documentation: http://localhost:8000/docs

Testing

Run the end-to-end test:

cd tests
export HUGGINGFACEHUB_API_TOKEN=your_token_here
./test_compose_on_xeon.sh

Architecture

This system uses the OPEA megaservice pattern to orchestrate multiple microservices:

  • LLM Microservice: Text generation (Intel/neural-chat-7b-v3-3)

  • Embedding Microservice: Text vectorization (BAAI/bge-base-en-v1.5)

  • Retriever Microservice: Vector search with Redis

  • Reranking Microservice: Improve retrieval quality (BAAI/bge-reranker-base)

  • DataPrep Microservice: Document ingestion and processing

Documentation

License

Apache 2.0 - See LICENSE file for details.

Support

For issues and questions, please open an issue in the OPEA GenAIExamples repository.