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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- ➡️ Get your own copy by Forking this repo and find it next in your own repositories.
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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
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-4o-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 |
- .NET 9
- Docker Desktop or Podman
- Azure Developer CLI (azd) (for Azure deployment)
- Git
-
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
azdenvironment name (like "eShopLite"), select a subscription from your Azure account, and select a location where the necessary models, like gpt-4o-mini and ADA-002 are available, a sample region can be "eastus2".
- Navigate to a specific scenario folder (e.g.,
scenarios/01-SemanticSearch/) - Follow the README instructions in that scenario folder
- Run the solution using
dotnet runin the appropriate host project folder
To run the demo, follow these steps:
- Navigate to the specific scenario folder
- Follow the "Run the solution" instructions in that scenario's README
- Access the application via the URLs provided in the console output
This is the eShopLite Aplication running, performing a Keyword Search:
This is the eShopLite Aplication running, performing a Semantic Search:
This is the eShopLite Application running the Realtime Audio feature:
This is the eShopLite Application using the DeepSeek-R1 Reasoning Model:
The Aspire Dashboard to check the running services:
The Azure Resource Group with all the deployed services:
