Azure-Samples/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.
> - ☁️ Scenarios use .NET and Aspire, with a stable .NET 10 baseline and an isolated .NET 11 RC2 scenario for experimental Blazor AI components. See the dependency baseline below for compatibility exceptions.
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## Features
This project framework provides the following features:
Modern .NET application architecture with 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. | 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, 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, 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. | 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 an Aspire multi-service eCommerce app to Azure App Service, using SQLite for data and integrating AI search. | Azure App Service, Aspire, OpenAI, SQLite |
| 10 - A2A Network | Demonstrates advanced agent-to-agent (A2A) communication and orchestration patterns in Aspire, including multi-agent collaboration and reasoning. | Aspire, Multi-Agent Systems, A2A Protocol |