InnoTrack System

InnoTrack is a comprehensive, full-stack application designed as a graduation project. The system consists of three main components: a modern web frontend, a robust backend API, and an AI-powered microservice for advanced analytics and natural language processing.

Project Structure

The repository is organized into three main directories, each representing a core component of the system:

• InnoTrack Frontend: The user interface built with Next.js and React.
• InnoTrack backend: The core API and business logic built with .NET.
• InnoTrack AI: The AI microservice providing machine learning and NLP capabilities.

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1. Frontend (InnoTrack Frontend)

A modern, responsive web application built to provide a seamless user experience. It leverages real-time communication and beautiful UI components.

Tech Stack:

• Framework: Next.js 16+ & React 19
• Styling: Tailwind CSS v4
• UI Components: Shadcn UI, Radix UI, Framer Motion
• Real-time: Microsoft SignalR
• Data Visualization: Recharts
• Icons & Markdown: Lucide React, React Markdown, remark-gfm

To get started with the frontend, navigate to the InnoTrack Frontend directory and check its README.md.

2. Backend (InnoTrack backend)

A robust, scalable backend system following Clean Architecture principles (Domain, Application, Infrastructure, API).

Tech Stack:

• Framework: .NET (C#)
• Architecture: Clean Architecture
• Containerization: Docker & Docker Compose
• Features: Entity Framework Core (assumed), RESTful API, Real-time Hubs.

To run the backend, navigate to the InnoTrack backend directory. You can use the provided .slnx solution file or run it via Docker Compose.

3. AI Service (InnoTrack AI)

A specialized Python microservice providing machine learning, embeddings, and generative AI capabilities to the main application.

Tech Stack:

• API Framework: FastAPI & Uvicorn
• Machine Learning: PyTorch, Scikit-learn, SciPy
• NLP & Embeddings: Transformers, Sentence-Transformers, KeyBERT, YAKE
• Vector Search: FAISS
• Generative AI: Google GenAI
• Data Processing: Pandas, NumPy, PyArrow
• Database: SQLAlchemy, PyODBC

To start the AI service, navigate to the InnoTrack AI directory, install the requirements, and run the FastAPI server.

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Getting Started

To run the full system locally, you will need to set up each component.

1. Backend: Navigate to InnoTrack backend, configure your .env (using .env.example as a reference), and start the API (via Visual Studio, .NET CLI, or Docker Compose).
2. AI Service: Navigate to InnoTrack AI, create a virtual environment, install requirements.txt, and run start.sh or the Uvicorn server.
3. Frontend: Navigate to InnoTrack Frontend, run npm install, and then npm run dev to start the development server.

(Note: Please refer to the individual README.md files in each subdirectory for more specific setup instructions, environment variables, and scripts.)