A small demonstration C# project for testing graphify-dotnet knowledge graph extraction.

This sample demonstrates common architectural patterns that create interesting knowledge graphs:

• Repository Pattern: Generic IRepository<T> interface with concrete UserRepository implementation
• Service Layer: UserService orchestrates business logic and calls the repository
• Dependency Injection: ServiceCollectionExtensions provides DI registration methods
• Entity Model: Simple User entity with validation logic

src/
├── IRepository.cs              # Generic repository interface
├── User.cs                     # User entity model
├── UserRepository.cs           # In-memory repository implementation
├── UserService.cs              # Service layer with business logic
└── ServiceCollectionExtensions.cs  # DI configuration

From the repository root, run:

dotnet run --project src/Graphify.Cli/Graphify.Cli.csproj run samples/mini-library

This will:

1. Detect all .cs files in the sample
2. Extract entities, methods, and relationships using AST parsing
3. Build a knowledge graph showing the repository pattern structure
4. Generate multiple export formats (JSON, HTML, report, etc.)

The knowledge graph should reveal:

• Interfaces: IRepository<T>
• Classes: User, UserRepository, UserService, ServiceCollectionExtensions
• Relationships:
  • UserRepository implements IRepository<User>
  • UserService depends on IRepository<User>
  • ServiceCollectionExtensions registers both repository and service
  • Method calls between service and repository
• Communities: Likely 2-3 communities (data layer, service layer, infrastructure)

1. Interface/Implementation: Abstract repository contract with concrete implementation
2. Generic Constraints: IRepository<T> where T : class
3. Dependency Injection: Constructor injection in UserService
4. Extension Methods: Fluent API for service registration
5. Async/Await: Task-based async patterns throughout

This is a realistic mini-codebase that mimics production patterns while being small enough to analyze quickly.