<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Rag on Noureddine RAMDI</title><link>https://ramdi.fr/tags/rag/</link><description>Recent content in Rag 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/rag/index.xml" rel="self" type="application/rss+xml"/><item><title>ai-interview-codex: iterative AI system design and interview prep with real-world benchmarks</title><link>https://ramdi.fr/github-stars/ai-interview-codex-iterative-ai-system-design-and-interview-prep-with-real-world-benchmarks/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/ai-interview-codex-iterative-ai-system-design-and-interview-prep-with-real-world-benchmarks/</guid><description>ai-interview-codex offers a practical AI interview prep guide featuring iterative system design for Agentic AI and RAG, with benchmarks and production insights for ML, LLM, and system design roles.</description></item><item><title>Dot: an offline Electron desktop app for local LLM inference and document QA</title><link>https://ramdi.fr/github-stars/dot-an-offline-electron-desktop-app-for-local-llm-inference-and-document-qa/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/dot-an-offline-electron-desktop-app-for-local-llm-inference-and-document-qa/</guid><description>Dot bundles local LLM inference, Retrieval Augmented Generation, and Text-To-Speech into a single offline Electron app, enabling document QA without cloud dependencies.</description></item><item><title>Ultimate AI Engineer Roadmap 2026: A comprehensive curriculum for aspiring AI engineers</title><link>https://ramdi.fr/github-stars/ultimate-ai-engineer-roadmap-2026-a-comprehensive-curriculum-for-aspiring-ai-engineers/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/ultimate-ai-engineer-roadmap-2026-a-comprehensive-curriculum-for-aspiring-ai-engineers/</guid><description>Explore a detailed 17-phase AI engineering roadmap for 2026, focusing on multi-LLM orchestration, RAG, AI agents, and production-ready skills with 51 hands-on projects.</description></item><item><title>RAGFlow: a modular, agentic retrieval-augmented generation engine with deep document understanding</title><link>https://ramdi.fr/github-stars/ragflow-a-modular-agentic-retrieval-augmented-generation-engine-with-deep-document-understanding/</link><pubDate>Wed, 06 May 2026 18:58:37 +0000</pubDate><guid>https://ramdi.fr/github-stars/ragflow-a-modular-agentic-retrieval-augmented-generation-engine-with-deep-document-understanding/</guid><description>RAGFlow is an open-source Python RAG engine combining deep document parsing, configurable pipelines, agentic workflows, and sandboxed code execution for LLM context management.</description></item><item><title>Langchain-Chatchat: A model-agnostic orchestration layer for Chinese-language RAG and Agents</title><link>https://ramdi.fr/github-stars/langchain-chatchat-a-model-agnostic-orchestration-layer-for-chinese-language-rag-and-agents/</link><pubDate>Tue, 05 May 2026 22:24:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/langchain-chatchat-a-model-agnostic-orchestration-layer-for-chinese-language-rag-and-agents/</guid><description>Langchain-Chatchat offers a flexible, offline-capable orchestration layer for multiple Chinese LLMs and RAG approaches, enabling seamless model swaps across frameworks without code changes.</description></item><item><title>Quivr: A Python framework for flexible retrieval-augmented generation pipelines</title><link>https://ramdi.fr/github-stars/quivr-a-python-framework-for-flexible-retrieval-augmented-generation-pipelines/</link><pubDate>Tue, 05 May 2026 22:24:55 +0000</pubDate><guid>https://ramdi.fr/github-stars/quivr-a-python-framework-for-flexible-retrieval-augmented-generation-pipelines/</guid><description>Quivr is a Python framework offering an opinionated, pluggable retrieval-augmented generation pipeline with multi-LLM support and YAML-defined workflows for flexible knowledge retrieval.</description></item><item><title>Building production-ready RAG workflows with n8n using free JSON templates</title><link>https://ramdi.fr/github-stars/building-production-ready-rag-workflows-with-n8n-using-free-json-templates/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-production-ready-rag-workflows-with-n8n-using-free-json-templates/</guid><description>Explore over 200 pre-built n8n workflow templates integrating vector databases, embedding models, and LLMs for rapid RAG workflow prototyping and deployment without coding.</description></item><item><title>Supermemory: a unified memory and context engine for AI applications</title><link>https://ramdi.fr/github-stars/supermemory-a-unified-memory-and-context-engine-for-ai-applications/</link><pubDate>Tue, 05 May 2026 13:37:39 +0000</pubDate><guid>https://ramdi.fr/github-stars/supermemory-a-unified-memory-and-context-engine-for-ai-applications/</guid><description>Supermemory replaces traditional RAG stacks with a unified AI memory layer, offering fast, hybrid memory retrieval and automatic fact extraction in ~50ms. Here&amp;rsquo;s how it works and how to try it.</description></item><item><title>Inside Alibaba’s VRAG: Multimodal Retrieval-Augmented Generation with Dynamic Reasoning Graphs</title><link>https://ramdi.fr/github-stars/inside-alibabas-vrag-multimodal-retrieval-augmented-generation-with-dynamic-reasoning-graphs/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-alibabas-vrag-multimodal-retrieval-augmented-generation-with-dynamic-reasoning-graphs/</guid><description>Alibaba&amp;rsquo;s VRAG models reasoning as a dynamic DAG with multimodal memory and RL-based fine-grained credit assignment, supporting text, image, and video retrieval in a unified framework.</description></item><item><title>Mapping the LLM agent landscape with the awesome-llm-agents curated catalog</title><link>https://ramdi.fr/github-stars/mapping-the-llm-agent-landscape-with-the-awesome-llm-agents-curated-catalog/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/mapping-the-llm-agent-landscape-with-the-awesome-llm-agents-curated-catalog/</guid><description>A curated catalog of 20+ LLM agent frameworks and tools organized by agent type and capabilities. Understand architectural differences and trade-offs in LLM agent design.</description></item><item><title>Automating bank statement processing with YOLOv8, OCR, and LLMs for personal finance analysis</title><link>https://ramdi.fr/github-stars/automating-bank-statement-processing-with-yolov8-ocr-and-llms-for-personal-finance-analysis/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/automating-bank-statement-processing-with-yolov8-ocr-and-llms-for-personal-finance-analysis/</guid><description>Explore how a hybrid pipeline using YOLOv8 layout detection, OCR, and LLMs automates messy bank statement PDFs for personal finance analysis with RAG and AI agents.</description></item><item><title>Blinko: an open-source, privacy-first AI note-taking app with RAG-powered local search</title><link>https://ramdi.fr/github-stars/blinko-an-open-source-privacy-first-ai-note-taking-app-with-rag-powered-local-search/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/blinko-an-open-source-privacy-first-ai-note-taking-app-with-rag-powered-local-search/</guid><description>Blinko is a self-hosted AI note-taking app using RAG for natural language search over local Markdown notes. Cross-platform, privacy-first, deployable via Docker one-liner.</description></item><item><title>RESTai: a multi-project AIaaS platform with agentic browser automation and visual AI pipelines</title><link>https://ramdi.fr/github-stars/restai-a-multi-project-aiaas-platform-with-agentic-browser-automation-and-visual-ai-pipelines/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/restai-a-multi-project-aiaas-platform-with-agentic-browser-automation-and-visual-ai-pipelines/</guid><description>RESTai exposes multi-project AI capabilities via a unified REST API, featuring an agentic browser with Dockerized Playwright, knowledge graph RAG, and a visual Blockly pipeline builder.</description></item><item><title>WhyHow Knowledge Graph Studio: building RAG-native knowledge graphs with MongoDB and OpenAI</title><link>https://ramdi.fr/github-stars/whyhow-knowledge-graph-studio-building-rag-native-knowledge-graphs-with-mongodb-and-openai/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/whyhow-knowledge-graph-studio-building-rag-native-knowledge-graphs-with-mongodb-and-openai/</guid><description>WhyHow Knowledge Graph Studio builds RAG-native knowledge graphs using MongoDB and OpenAI embeddings, offering flexible triple-based graph construction for AI workflows.</description></item><item><title>Building a production-ready second brain with agentic RAG and LLMOps</title><link>https://ramdi.fr/github-stars/building-a-production-ready-second-brain-with-agentic-rag-and-llmops/</link><pubDate>Sun, 03 May 2026 08:12:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/building-a-production-ready-second-brain-with-agentic-rag-and-llmops/</guid><description>Explore an open-source course that teaches building a production-grade AI assistant using advanced retrieval-augmented generation, agent orchestration, fine-tuning, and LLMOps practices.</description></item><item><title>Inside AI Engineering Hub: a hands-on collection of production-ready AI projects</title><link>https://ramdi.fr/github-stars/inside-ai-engineering-hub-a-hands-on-collection-of-production-ready-ai-projects/</link><pubDate>Sun, 26 Apr 2026 17:51:11 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-ai-engineering-hub-a-hands-on-collection-of-production-ready-ai-projects/</guid><description>AI Engineering Hub offers 90+ production-ready AI projects spanning LLMs, RAG, AI agents, and MCP, organized by difficulty and real-world use cases.</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><item><title>Awesome LLM Apps: a practical collection of runnable AI agent and RAG templates</title><link>https://ramdi.fr/github-stars/awesome-llm-apps-a-practical-collection-of-runnable-ai-agent-and-rag-templates/</link><pubDate>Fri, 24 Apr 2026 18:26:13 +0000</pubDate><guid>https://ramdi.fr/github-stars/awesome-llm-apps-a-practical-collection-of-runnable-ai-agent-and-rag-templates/</guid><description>Awesome LLM Apps offers 100+ runnable AI agent and RAG templates for quick LLM app development. It supports multiple providers and advanced multi-agent patterns with minimal setup.</description></item></channel></rss>