This project is designed with a modern, scalable architecture leveraging multiple technologies for different components:
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.NET API
- Serves as the main backend for core business logic and data management.
- Handles authentication, authorization, and main application workflows.
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FastAPI (Python)
- Dedicated to utility endpoints and AI/ML services.
- Provides fast, asynchronous APIs for machine learning inference and data processing.
- Angular
- Single Page Application (SPA) for user interface.
- Communicates with backend APIs via RESTful endpoints.
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CDN Server (C#/.net)
- Delivers static assets (images, scripts, styles) efficiently.
- Built with .NET for performance and integration.
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Redis Cache
- Used for caching frequently accessed data.
- Improves response times and reduces load on databases.
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Qdrant (Vector Database)
- Stores and searches vector embeddings for AI/ML features.
- Enables semantic search and recommendation functionalities.
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PostgreSQL
- Main relational database for persistent storage.
- Stores user data, application state, and transactional records.
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Docker
- Services and components will be containerized if they do not natively support deployment on Linux environments. This ensures compatibility and consistent deployment where needed.
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Vercel
- The Angular frontend will be deployed and hosted on Vercel for fast, global delivery and easy CI/CD integration.