HRAG – Hybrid RAG on €116/month of Hetzner, officially benchmarked
Self-hosted hybrid RAG on a €116/month cluster — Postgres, BM25, vectors, a reranker, and a public benchmark score for every claim.
HRAG – Hybrid RAG on €116/month of Hetzner, officially benchmarked launched on August 19, 2026 with 8 votes, #1,241 of 23,274 launches that month and more than 75% of that year's launches.
What it does
actual screenshots of the live thing… the 512K-document playground, streamed answers, citations you can open. no mockups — mockups would have been easier. pg_textsearch gives real IDF ranking with Block-Max WAND: 88ms over 2 million chunks, where plain tsquery took 7.5 seconds. Vector and lexical arms fuse with a measured 0.3 vector weight — equal weighting scored worse than turning one arm off. A fourth service reads query and chunk together and reorders the window. Worth +3.9 on the public benchmark… and 16 seconds of latency on 2 vCPUs, which is why it ships as a checkbox and not a default. Both numbers are published. Empty retrieval refuses without calling the model. On the benchmark's…from hrag.app
Does a similar job
all alternatives →
FastGraphRAG – Better RAG using good old PageRank2024 · github.com · ▲457Hey there HN! We’re Antonio, Luca, and Yuhang, and we’re excited to introduce Fast GraphRAG, an open-source RAG approach that leverages knowledge graphs and the 25 years old PageRank for better information retrieval and reasoning. Building a good RAG pipeline these days takes a lot of manual optimizations. Most engineers intuitively start from naive RAG: throw everything in a vector database and hope that semantic search is powerful enough. This can work for use cases where accuracy isn’t too important and hallucinations are tolerable, but it doesn’t work for more difficult queries that…
Ragas – Open-source library for evaluating RAG pipelines2024 · github.com · ▲121Ragas is an open-source library for evaluating and testing RAG and other LLM applications. Github: https://docs.ragas.io/en/stable/, docs: https://docs.ragas.io/. Ragas provides you with different sets of metrics and methods like synthetic test data generation to help you evaluate your RAG applications. Ragas started off by scratching our own itch for evaluating our RAG chatbots last year. Problems Ragas can solve - How do you choose the best components for your RAG, such as the retriever, reranker, and LLM? - How do you formulate a test dataset…
R2R – Open-source framework for production-grade RAG2024 · github.com · ▲167Hello HN, I'm Owen from SciPhi (https://www.sciphi.ai/), a startup working on simplifying˛Retrieval-Augmented Generation (RAG). Today we’re excited to share R2R (https://github.com/SciPhi-AI/R2R), an open-source framework that makes it simpler to develop and deploy production-grade RAG systems. Just a quick reminder: RAG helps Large Language Models (LLMs) use current information and specific knowledge. For example, it allows a programming assistant to use your latest documents to answer questions. The idea is to gather all the relevant information…
PostgreSQL performance and cost across 23 EC2 instance typesJul 2026 · postgres.saneengineer.com · ▲97Hey! I'm Andrei. I got frustrated by how people tend to build overcomplicated backend systems, being "motivated" by big tech case studies and popular books. So, I started exploring lean architecture, and building my digital garden of ideas, approaches and data that align with this direction. Here I want to present one of the tools – Sizing tool for PostgreSQL. I've benchmarked PostgreSQL on different EC2 instances and disks, with different initial data sets to see performance that these instances can give you. And I've built a tool to visualize this data, which I welcome you to explore. So,…
RAGBuilder – Hyperparameter tuning on various RAG parameters2024 · github.com · ▲17A RAG has several moving parts: data ingestion, retrieval, re-ranking, generation etc.. Each part comes with numerous options. If we consider a toy example, where you could choose from: 5 different chunking methods, 5 different chunk sizes, 5 different embedding models, 5 different retrievers, 5 different re-rankers/ compressors 5 different prompts 5 different LLMs That’s 78,125 distinct RAG configurations! If you could try evaluating each one in just 5 mins, that’d still take 271 days of non-stop trial-and-error effort! In short, it’s kinda impossible to find your optimal RAG setup…
IgnitionRAGApr 2026 · ignitionrag.com · ▲83Multimodal RAG platform, from POC to production in minutes
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 22d ago · stillwet.art
FastRouter.ai▲364Route requests to the right LLM for cost, latency & quality
AI · 23d ago · fastrouter.ai
Source: Show HN post ↗
Launched alongside, August 2026
the whole month →- TL
Life & fun · Aug 2026 · louisabraham.github.io
Clipto MCP▲655Hey HN, We recently built Clipto. It’s a tool that lets you search over terabytes of video, audio, and images on your computer, without relying on the cloud. Motivation: we probably all had this similar experience, we know a moment exists in a video or audio, but finding it takes hours scrubbing the timeline. You can send all the media to process in the cloud, but it’s slow, expensive and raises privacy concerns. So we decided to build our own on-device media search engine. How it works (high level): 1. We ingest video, audio, image; normalize formats via ffmpeg; run content analysis to…
Work · Aug 2026 · clipto.com
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
Astute▲606Automate your B2B brand going viral, with new media creators
AI · Aug 2026 · company-app.joinastute.com