<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Vector-Search on Noureddine RAMDI</title><link>https://ramdi.fr/tags/vector-search/</link><description>Recent content in Vector-Search on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/vector-search/index.xml" rel="self" type="application/rss+xml"/><item><title>SmartScan Android: on-device AI for offline media search and clustering</title><link>https://ramdi.fr/github-stars/smartscan-android-on-device-ai-for-offline-media-search-and-clustering/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/smartscan-android-on-device-ai-for-offline-media-search-and-clustering/</guid><description>SmartScan Android runs vector similarity search and clustering entirely on-device using ONNX Runtime, enabling offline private text and reverse-image search over local media.</description></item><item><title>XCDocs: Local Apple Developer Documentation Search via Xcode's Vector Database</title><link>https://ramdi.fr/github-stars/xcdocs-local-apple-developer-documentation-search-via-xcode-s-vector-database/</link><pubDate>Mon, 04 May 2026 10:23:03 +0000</pubDate><guid>https://ramdi.fr/github-stars/xcdocs-local-apple-developer-documentation-search-via-xcode-s-vector-database/</guid><description>XCDocs exposes Apple&amp;rsquo;s developer docs as a local searchable resource using Xcode&amp;rsquo;s vector database, enabling zero-maintenance, high-quality search for Swift devs and AI agents on macOS.</description></item><item><title>Building private AI workflows with the n8n self-hosted AI starter kit</title><link>https://ramdi.fr/github-stars/building-private-ai-workflows-with-the-n8n-self-hosted-ai-starter-kit/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-private-ai-workflows-with-the-n8n-self-hosted-ai-starter-kit/</guid><description>Spin up a private AI agent stack in under 5 minutes with n8n&amp;rsquo;s self-hosted AI starter kit. Combines local LLMs, automation, and vector search for secure AI workflows.</description></item><item><title>pdftochat: a cloud-integrated PDF-to-chat system with hybrid vector search</title><link>https://ramdi.fr/github-stars/pdftochat-a-cloud-integrated-pdf-to-chat-system-with-hybrid-vector-search/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/pdftochat-a-cloud-integrated-pdf-to-chat-system-with-hybrid-vector-search/</guid><description>pdftochat is a TypeScript-based PDF-to-chat app leveraging Chroma Cloud for hybrid vector search and Together.ai for LLMs, integrating multiple cloud services for scalable document Q&amp;amp;A.</description></item><item><title>GrafeoDB: a high-performance Rust graph database supporting six query languages with a unified execution model</title><link>https://ramdi.fr/github-stars/grafeodb-a-high-performance-rust-graph-database-supporting-six-query-languages-with-a-unified-execution-model/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/grafeodb-a-high-performance-rust-graph-database-supporting-six-query-languages-with-a-unified-execution-model/</guid><description>GrafeoDB is a Rust-native graph database supporting LPG and RDF with six query languages. Its modular translator compiles all queries into a unified plan and delivers top-tier performance in benchmarks.</description></item><item><title>Pathway LLM App: unified pipelines for scalable retrieval-augmented generation and AI search</title><link>https://ramdi.fr/github-stars/pathway-llm-app-unified-pipelines-for-scalable-retrieval-augmented-generation-and-ai-search/</link><pubDate>Sun, 26 Apr 2026 09:31:26 +0000</pubDate><guid>https://ramdi.fr/github-stars/pathway-llm-app-unified-pipelines-for-scalable-retrieval-augmented-generation-and-ai-search/</guid><description>Pathway LLM App provides integrated pipelines for scalable RAG and AI search, combining vector and full-text indexing with real-time sync for Gen AI apps at scale.</description></item></channel></rss>