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Master Contextual Retrieval and enriched chunk logic with OpenAI and Azure AI Search. Use Prompt Caching in Microsoft Foundry to optimize RAG costs and speed.
Learn effective chunking strategies for RAG with C#, including Fixed-Size, Semantic, Hierarchical Parent-Child and more, shown in a real C# example.
HyDE for RAG explained: a practical guide to boosting retrieval accuracy with hypothetical answers and advanced search methods (Azure AI Search + Foundry).
Learn how Multi-Query Retrieval for RAG uses query rewrites and Azure AI Search to improve accuracy and boost retrieval quality.
Semantic Ranking in Azure AI Search explained with cross‑encoders that boost RAG accuracy and improve retrieval relevance.
Learn how to implement Hybrid Search in RAG using C#. Combine BM25 precision with Vector semantics in Azure AI Search for better retrieval.
Learn how to build a Naive RAG system using C# and Microsoft Foundry. Ground LLMs in private markdown data for accurate FAQ bots.
Learn Image Verbalization via LLM to bridge the gap between pixels and text. Master C# vector search by turning images into searchable descriptions.
Multimodal Embeddings with Azure Vision enable powerful text‑image search. Check how this approach can enhance your app’s retrieval capabilities!
