Text embeddings for RAG and search - Python, Ollama, OpenAI-compatible APIs:
https://www.glukhov.org/rag/embeddings/
#Embeddings #RAG #Python #Ollama #LLM #SelfHosting #VectorDatabase
Text embeddings for RAG and search - Python, Ollama, OpenAI-compatible APIs

Learn what text embeddings are, how they power RAG and semantic search, and how to call embedding APIs from Python using Ollama or an OpenAI-compatible server (for example llama.cpp). Includes persistence, retrieval, and links to chunking, vector stores, and reranking on this site.

Rost Glukhov | Personal site and technical blog

Databases for #AI: Should you use a vector #database? ๐Ÿค”

This article compares #opensource projects competing to handle modern #AI workloads, including #machinelearning and #LLMs. Discover which databases best meet todayโ€™s AI challenges: https://lpi.org/636x

(Disclaimer: This post contains an AI-generated image.)

#AndyOram #AI #vectordatabase #machinelearning #LLMs #SQL #opensource #hybridsearch #generativeAI #MariaDB #MongoDB #Milvus #Qdrant #Weaviate #Vespa #ChromaDB #LanceDB

Chat with Your Documents: A Practical Guide to RAG Using the New Laravel AI SDK

Have you ever wished you could just ask your documents a question and get an answer? That's exactly what RAG (Retrieval-Augmented Generation) lets you do. It's the technique behind those AI chatbots...

Tighten
Building Software That Welcomes Everyone - Marc HaunschildPimp My Solr Search - Chatting With the New Solr Vector Database - Olivier DobberkauHow to expose a...#TYPO3 #TYPO3campVenlo #WebCampVenlo #wcv #softwaredevelopment #cms #php #opensource #solr #vectordatabase #developer #figma
Friday - Building Software - Solr Vector Db - developer experience - Figma - Web Camp Venlo 2026
Friday - Building Software - Solr Vector Db - developer experience - Figma - Web Camp Venlo 2026

YouTube

Your RAGโ€™s Secret Backdoor: Leaking Data Through Vector Databases
This article exposes a vulnerability in Retrieval-Augmented Generation (RAG) systems, where misconfigured vector databases can lead to sensitive data leakage. By improperly securing these databases, attackers can gain access to internal documents such as HR policies and top-secret product roadmaps. The RAG system works by storing document chunks as embeddings in a special-purpose vector database and querying it to provide context for the LLM. The focus on securing the LLM while neglecting the vector database leaves it vulnerable to data exfiltration. The attacker can exploit weak access controls and clever retrieval attacks to gain access to sensitive data. Key lesson: Secure vector databases to prevent data breaches caused by RAG system vulnerabilities. #BugBounty #ArtificialIntelligence #DataLeak #Infosec #VectorDatabase

https://infosecwriteups.com/your-rags-secret-backdoor-leaking-data-through-vector-databases-c33755a5abbe?source=rss------bug_bounty-5

Your RAGโ€™s Secret Backdoor: Leaking Data Through Vector Databases ๐Ÿ’€

Why the โ€œsecureโ€ LLM is a lie if your vector DB is a sieve. A practical, no-BS guide for security pros on the new AI frontline.

Medium

[zvec - ์ดˆ๊ฒฝ๋Ÿ‰ยท์ดˆ๊ณ ์† ์ธํ”„๋กœ์„ธ์Šค ๋ฒกํ„ฐ DB

Zvec๋Š” ์ดˆ๊ฒฝ๋Ÿ‰ยท์ดˆ๊ณ ์† ์ธํ”„๋กœ์„ธ์Šค ๋ฒกํ„ฐ DB๋กœ, Alibaba์˜ Proxima ์—”์ง„ ๊ธฐ๋ฐ˜์œผ๋กœ ๊ตฌ์ถ•๋˜์–ด ๋Œ€๊ทœ๋ชจ ์œ ์‚ฌ๋„ ๊ฒ€์ƒ‰์„ ์ตœ์†Œ ์„ค์ •์œผ๋กœ ์ˆ˜ํ–‰ํ•˜๋„๋ก ์„ค๊ณ„๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๋ฐ€์ง‘ ๋ฐ ํฌ์†Œ ๋ฒกํ„ฐ๋ฅผ ๋ชจ๋‘ ์ง€์›ํ•˜๋ฉฐ, ํ•˜์ด๋ธŒ๋ฆฌ๋“œ ๊ฒ€์ƒ‰ ๊ธฐ๋Šฅ์„ ํ†ตํ•ด ์˜๋ฏธ์  ์œ ์‚ฌ๋„์™€ ๊ตฌ์กฐ์  ํ•„ํ„ฐ๋ง์„ ๊ฒฐํ•ฉํ•œ ์ •๋ฐ€ ๊ฒ€์ƒ‰์„ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. C++ ๊ธฐ๋ฐ˜ ํ•ต์‹ฌ ์—”์ง„๊ณผ SWIGยทPython ๋ฐ”์ธ๋”ฉ ๊ตฌ์กฐ๋กœ ๊ตฌ์„ฑ๋˜์–ด ๊ณ ์„ฑ๋Šฅ ์—ฐ์‚ฐ๊ณผ ๋‹ค์–‘ํ•œ ์–ธ์–ด ํ†ตํ•ฉ์„ ์ง€์›ํ•˜๋ฉฐ, Apache-2.0 ๋ผ์ด์„ ์Šค๋กœ ์ œ๊ณต๋ฉ๋‹ˆ๋‹ค.

https://news.hada.io/topic?id=27147

#vectordatabase #algorithms #machinelearning #opensource #search

zvec - ์ดˆ๊ฒฝ๋Ÿ‰ยท์ดˆ๊ณ ์† ์ธํ”„๋กœ์„ธ์Šค ๋ฒกํ„ฐ DB

<ul> <li> <strong>์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ๋‚ด์—์„œ ์ง์ ‘ ์ž„๋ฒ ๋“œ</strong> ๊ฐ€๋Šฅํ•œ <strong>๋ฒกํ„ฐDB</strong>๋กœ, ๋Œ€๊ทœ๋ชจ <strong>์œ ์‚ฌ๋„ ๊ฒ€์ƒ‰</strong>์„ ์ตœ์†Œ ...

GeekNews
Vector Data in .NET - Building Blocks for AI Part 2 - .NET Blog

Explore the power of Vector Data in .NET AI for enhancing semantic searches and intelligent applications.

.NET Blog

Did you know? Our pgedge-vectorizer tool (on GitHub: https://github.com/pgEdge/pgedge-vectorizer) automatically chunks text content and generates vector embeddings with the help of background workers.

OpenAI, Voyage AI, and Ollama are supported as embedding providers, and a simple SQL interface allows you to enable vectorization on any table. (Thereโ€™s even built-in views and functions for monitoring queue status.)

#github #opensource #semanticsearch #vector #vectordatabase #openai #ollama #voyageai

GitHub - pgEdge/pgedge-vectorizer: A PostgreSQL extension to create chunk tables for existing text data, and populate them with embeddings using your favourite LLM.

A PostgreSQL extension to create chunk tables for existing text data, and populate them with embeddings using your favourite LLM. - pgEdge/pgedge-vectorizer

GitHub
Retrieval-Augmented Generation (RAG) Tutorial: Architecture, Implementation, and Production Guide:
https://www.glukhov.org/rag/
#AI #LLM #RAG #Embeddings #Reranking #VectorDatabase
Retrieval-Augmented Generation (RAG) Tutorial: Architecture, Implementation, and Production Guide

Step-by-step RAG tutorial: build retrieval-augmented generation systems with vector databases, hybrid search, reranking, and web search. Architecture, implementation, and production best practices.

Rost Glukhov | Personal site and technical blog
Zvec by Alibaba is a lightweight, lightning-fast, in-process vector database. Beats any other vector db out there. https://zvec.org/en/ #VectorDatabase