Document Processing Pipelines: From Raw Files to Vector-Ready Chunks

Introduction: Document processing is the foundation of any RAG (Retrieval-Augmented Generation) system. Before you can search and retrieve relevant information, you need to extract text from various file formats, split it into meaningful chunks, and generate embeddings for vector search. The quality of your document processing pipeline directly impacts retrieval accuracy and ultimately the quality […]

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LLM Response Streaming: Building Real-Time AI Experiences

Introduction: Streaming LLM responses transforms the user experience from waiting for complete responses to seeing text appear in real-time, dramatically improving perceived latency. Instead of staring at a loading spinner for 5-10 seconds, users see the first tokens within milliseconds and can start reading while generation continues. But implementing streaming properly involves more than just […]

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Query Understanding and Intent Detection: Building Smarter AI Interfaces

Introduction: Query understanding is the critical first step in building intelligent AI systems that respond appropriately to user requests. Before your system can retrieve relevant documents, call the right tools, or generate helpful responses, it needs to understand what the user actually wants. This involves intent classification (is this a question, command, or conversation?), entity […]

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Hybrid Search Implementation: Combining Vector and Keyword Retrieval

Introduction: Hybrid search combines the best of both worlds: the semantic understanding of vector search with the precision of keyword matching. Pure vector search excels at finding conceptually similar content but can miss exact matches; pure keyword search finds exact terms but misses semantic relationships. Hybrid search fuses these approaches, using vector similarity for semantic […]

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LLM Fallback Strategies: Building Reliable AI Applications

Introduction: LLM APIs fail. Rate limits hit, services go down, models return errors, and responses sometimes don’t meet quality thresholds. Building reliable AI applications requires robust fallback strategies that gracefully handle these failures without degrading user experience. A well-designed fallback system tries alternative models, implements retry logic with exponential backoff, caches successful responses, and provides […]

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Windows Azure SDK for .NET–Version 2.0 (for Visual Studio 2010 SP1/2012)

Latest version of Windows Azure SDK for .NET – Version 2.0 released by Microsoft. DOWNLOAD: Windows Azure SDK for .NET 2.0 (Offline Installer) Recommended: Instead of manually downloading the files from above link, it is recommended you use the automated one-click install provided by the Web Platform Installer x64 or x86. Click on the appropriate […]

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