🗨️ Real-Time WebSocket Chat with .NET 9 (Clean Architecture + Razor Pages)

A real-time, extensible chat application built using .NET 9, leveraging Clean Architecture, Razor Pages with MVC pattern, and WebSocket for real-time communication.

This project showcases scalable backend design and now includes Docker support, along with future integration plans for AI/ML agents, JWT, RSA encryption, SignalR, and unit tests.

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🚀 Features

• ✅ Real-time public and private chat using WebSockets
• ✅ Clean Architecture (Domain, Application, Infrastructure, UI)
• ✅ Built on .NET 9, Razor Pages, MVC pattern
• ✅ Client registration via /ws?clientId=xyz
• ✅ Message routing: public or private via @clientId
• 🐳 Docker support for easy deployment

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🤖 AI/ML Agent (Planned)

A built-in AI agent (e.g., @Bot) will:

• Automatically respond to specific queries (@Bot what is the weather?)
• Use local ML models or external LLM APIs
• Handle NLP and intent detection
• Integrate with external APIs (e.g., weather, time, definitions)
• Future extensibility to RAG or LangChain-style LLM agents

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📦 Tech Stack

Area	Technology
Backend	ASP.NET Core 9
Architecture	Clean Architecture
Frontend View	Razor Pages (MVC Pattern)
Deployment	Docker
Real-Time Comm	WebSocket (SignalR Planned)
Authentication	JWT (Planned)
Encryption	RSA (Planned)
AI/ML Agent	ML.NET / Python APIs / LangChain (Planned)
Data Storage	SQL Server / PostgreSQL (Planned)
Testing	xUnit / NUnit (Planned)

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📁 Project Structure

ChatApp/
├── Chat.API/               # Presentation Layer (Razor Pages)
├── Chat.Application/       # Application Layer (Use Cases, Interfaces)
├── Chat.Domain/            # Domain Layer (Entities, Models)
├── Chat.Infrastructure/    # Infrastructure (WebSockets, DB, External APIs)
│   └── AI/                # AI Agent logic (Planned)
├── Chat.Tests/             # Unit Tests (Planned)
└── Dockerfile              # Docker Support

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🔧 Planned Improvements

Priority	Feature	Description
🐳 P1	Dockerization	Containerize the app for easy deployment (Done)
🔐 P2	RSA Encryption	End-to-end encrypted messaging
🔐 P2	JWT Authentication	Secure client identity and session
🤖 P2	AI/ML Agent	Add @Bot that replies with smart responses
🧠 P3	Dynamic Client Tracking	Show online/offline clients dynamically
🗃️ P4	Persist Messages to DB	Store chat history in SQL DB
🧪 P5	Unit Tests	Test business logic, WebSocket handler, etc.
🔄 P6	SignalR Migration	Replace or extend WebSocket with SignalR framework

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▶️ Getting Started

Prerequisites

• .NET 9 SDK
• Visual Studio 2022 / VS Code
• (Optional) Docker
• (Optional) Python or ML.NET environment for AI agent

Option 1: Run with Docker (Recommended)

docker build -t chatapp-api -f src/ChatApp.API/Dockerfile .
docker run -d -p 5000:8080 --name chatapp-api chatapp-api

Then visit: https://localhost:8080/ or whatever port you mapped.

Option 2: Run Locally with .NET

dotnet run --project src/ChatApp.API/ChatApp.API.csproj

Then visit: https://localhost:7016/

💡 License This project is licensed under the MIT License.

🛠️ Contributing

Welcome contributions!

• Fork the repo
• Create your feature branch
• Submit a PR

You can help with:

• AI agent development
• Frontend UI
• WebSocket/SignalR scalability
• Security improvements
• Writing tests

👨‍💻 Author Faojul Ahsan Senior .NET Backend Developer 🔗 faojulahsan.com

📣 Acknowledgments This project is part of a long-term vision to build modular, scalable, and ethical software — including secure real-time apps and AI-powered assistants.