Categoría: RAG

Implementing Embeddings via ONNX with Semantic Kernel for Local RAG Solutions in .NET

Flowchart diagram showing a RAG pipeline: a user sends a request to a .NET API, which performs embedding generation (highlighted with a large magnifying glass), then queries a vector database, and finally uses Phi-3 LLM to generate the response.

Introduction In our previous article "Building a RAG API with .NET, Semantic Kernel, Phi-3 and Qdrant", we focused on setting up a local Retrieval-Augmented Generation (RAG) API with minimal dependencies on external services. One key piece of that architecture, which we only briefly touched upon, is the embedding service. In this follow-up, we'll dive deeper … Sigue leyendo Implementing Embeddings via ONNX with Semantic Kernel for Local RAG Solutions in .NET →

🚀 Building a RAG API with .NET, Semantic Kernel, Phi-3, and Qdrant: Enrich Your E-commerce Experience

Basic flow of a RAG

Learn how to build a powerful RAG (Retrieval-Augmented Generation) API using .NET, Microsoft Semantic Kernel, Phi-3, and Qdrant. Combine your private e-commerce data with LLMs to create smarter, grounded responses. Simple and easy step-by-step! Introduction In previous articles we explored the power of Phi-3 for image analysis and automating e-commerce product descriptions. Now, let's take … Sigue leyendo 🚀 Building a RAG API with .NET, Semantic Kernel, Phi-3, and Qdrant: Enrich Your E-commerce Experience →