eShopLite

eShopLite is a set of reference .NET applications implementing an eCommerce site with features like Semantic Search, Model Context Protocol (MCP), Reasoning models, vector databases, and more.

☁️ All scenarios in this repository use the latest version of .NET and leverage .NET Aspire to orchestrate the entire solution.

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Features

This project framework provides the following features:

Modern .NET application architecture with .NET Aspire
Various search capabilities (keyword search, semantic search)
Integration with multiple AI models (GPT-4o, DeepSeek-R1, etc.)
Vector database implementations (In Memory, Azure AI Search, Chroma DB and others)
Real-time audio capabilities
Model Context Protocol (MCP) server and client implementation

eShopLite Scenarios

The project includes several scenarios demonstrating different capabilities:

Scenario	Description	Key Technologies
01 - Semantic Search	A reference .NET application implementing an eCommerce site with Search features using Keyword Search and Semantic Search.	.NET Aspire, OpenAI GPT-4.1-mini, In-memory Vector DB
02 - Azure AI Search	Implements an eCommerce site with Keyword Search using SQL queries and Semantic Search with Vector Database and Azure AI Search.	Azure AI Search, OpenAI Embeddings, SQL Server
03 - Realtime Audio	Extends the eCommerce site with advanced search features and real-time audio capabilities powered by the GPT-4o Realtime Audio API.	GPT-4o Realtime Audio API, Audio in Blazor, .NET Aspire
04 - Chroma DB	Implements semantic search functionality using Chroma DB, an open-source database designed for AI applications.	Chroma DB, OpenAI Embeddings, .NET SDK
05 - DeepSeek-R1	Demonstrates integration of the DeepSeek-R1 model for enhanced semantic understanding and search capabilities.	DeepSeek-R1, .NET Aspire, Vector Embeddings
06 - Model Context Protocol (MCP)	Implements the Model Context Protocol (MCP) for advanced AI interactions with MCP Servers and MCP Clients.	Model Context Protocol, Function Calling, SSE Events
07 - Agents Concurrent	Demonstrates concurrent agent orchestration and advanced AI agent collaboration patterns.	.NET Aspire, Multi-Agent Systems, Orchestration
08 - SQL Server 2025	Demonstrates the use of vector search and vector indexes in the SQL Database Engine	SQL Server 2025, Vector Search, Vector Indexes
09 - Azure App Service	Shows how to deploy a .NET Aspire multi-service eCommerce app to Azure App Service, using SQLite for data and integrating AI search.	Azure App Service, .NET Aspire, OpenAI, SQLite
10 - A2A Network	Demonstrates advanced agent-to-agent (A2A) communication and orchestration patterns in .NET Aspire, including multi-agent collaboration and reasoning.	.NET Aspire, Multi-Agent Systems, A2A Protocol
11 - GitHub Models	Local-first AI development using GitHub Models during local runs, with automatic switch to Azure OpenAI when deployed.	.NET Aspire, GitHub Models, Azure OpenAI
12 - Azure Functions	Optional Azure Functions façade for semantic search and an alternate deployment boundary for vector search.	Azure Functions, .NET Aspire, Azure OpenAI

Getting Started

Prerequisites

.NET 9
Docker Desktop or Podman
Azure Developer CLI (azd) (for Azure deployment)
Git

Installation

Clone the repository:

git clone https://github.com/Azure-Samples/eShopLite.git

Navigate to the scenario directory of interest:
```
cd eShopLite/scenarios/[scenario-folder]
```
Login to Azure:
```
azd auth login
```
Provision and deploy all the resources:
```
azd up
```
It will prompt you to provide an azd environment name (like "eShopLite"), select a subscription from your Azure account, and select a location where the necessary models, like gpt-4.1-mini and ADA-002 are available, a sample region can be "eastus2".