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ABAditya Biranjeadityabiranje210.hashnode.devJul 23 · 27 min read

Designing the Ingestion Layer of a Production RAG System

Most RAG postmortems point at retrieval. Wrong chunks come back, the reranker doesn't help, the LLM hallucinates around a gap in context. Almost none of it is a retrieval bug. By the time a query hits

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TSTina Sharmatheaicartographer.hashnode.devJul 7 · 28 min read

How to Use Semantic Caching with Qdrant to Optimize Token Costs in Customer Support

Most people remember the story because it was funny. Someone asked McDonald’s AI-powered drive-through assistant to write Python code instead of ordering food. The internet laughed. Engineers noticed

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JCJim Chundevalelaccidentalcomplexity.hashnode.devJul 5 · 19 min read

Part 3: Open WebUI, a One-Sided Load Balancer, and a Bug Hiding One Field Deep

Two Birds, One Qdrant With the core database built and my own homelab knowledge ingested, I had a second idea. Open WebUI, the chat front end I already run for my Hailo and Gemma models, has its own b

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JCJim Chundevalelaccidentalcomplexity.hashnode.devJul 4 · 8 min read

Part 2: Herding Files Across Five Pis, Dodging Junk, & Teaching Qdrant What Matters

The Plan Was Simple Qdrant was running. I had a collection. All I needed to do was feed it something. My homelab "knowledge" was scattered across five different Pis: config files here, Modelfiles ther

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JCJim Chundevalelaccidentalcomplexity.hashnode.devJul 3 · 9 min read

Part 1: RAID, Rust, and a Very Stubborn Memory Allocator

The Idea I’ve had a local AI stack running for a while now: Hermes on WhatsApp, Gemma 4 on CPU, two Hailo AI HAT+ boards handling NPU inference, and Open WebUI tying most of it together. It was good a

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CDCoding Dropletscodingdroplets.comJun 26 · 9 min read

Choosing a Vector Store for .NET AI Apps: sqlite-vec vs SQL Server 2025 vs Qdrant - Enterprise Decision Guide

Every .NET team building a Retrieval-Augmented Generation (RAG) feature or semantic search endpoint hits the same question early: which vector store should we use? The answer shapes infrastructure cos

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SSsatyam sahuthebuildersnotebook.hashnode.devJun 23 · 30 min read

Building an Offline “Life Memorizer” with Gemini 2.0 & Qdrant Edge

Originally published on Medium. Reposted here for the Hashnode community. Consider this. You are trying to find where you left an item, like your wallet or keys, inside your own house. You know you s

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MPMohana Priya Rmona23.hashnode.devJun 22 · 2 min read

Why I chose Qdrant over ChromaDB in my RAG System

When I started building Nexus — my multi-source RAG system — one of the first real decisions I had to make was picking a vector database. It sounds like a small choice. It isn't. First, why do you eve

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LSLakhan Samaniblog.authorizer.devJun 16 · 11 min read

Your AI assistant can leak files people aren't allowed to see — here's how to fix it

TL;DR Vector search ignores your permission model: an engineer can ask your RAG assistant about board-level financials and get them, because semantically close = retrieved, and a restricted chunk in

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TSThirumurthi Sthirumurthi.hashnode.devJun 1 · 9 min read

RAG system in Spring AI and Langflow using Qdrant Vector Storage

The motivation of the article is use AI with my financial statements as context and ask questions around those. In order to build everything locally had to use RAG approach. The statements in this cas

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Trending tags this week

Designing the Ingestion Layer of a Production RAG System

How to Use Semantic Caching with Qdrant to Optimize Token Costs in Customer Support

Part 3: Open WebUI, a One-Sided Load Balancer, and a Bug Hiding One Field Deep

Part 2: Herding Files Across Five Pis, Dodging Junk, & Teaching Qdrant What Matters

Part 1: RAID, Rust, and a Very Stubborn Memory Allocator

Choosing a Vector Store for .NET AI Apps: sqlite-vec vs SQL Server 2025 vs Qdrant - Enterprise Decision Guide

Building an Offline “Life Memorizer” with Gemini 2.0 & Qdrant Edge

Why I chose Qdrant over ChromaDB in my RAG System

Your AI assistant can leak files people aren't allowed to see — here's how to fix it

RAG system in Spring AI and Langflow using Qdrant Vector Storage