AgenticRAG-Survey (1,625⭐) maps the evolving landscape of agentic retrieval-augmented generation, offering a taxonomy to help engineers pick the right architecture for their RAG pipelines.
Explore genai-llm-ml-case-studies, a curated repo of 500+ production GenAI and LLM system design case studies from 130+ companies, organized by architecture, industry, and use case.
Supavec is a self-hostable RAG platform in TypeScript that cuts OpenAI embedding costs by 65% via batch processing, boosts recall by 12 points with chunk tuning, and achieves 210ms P95 latency through hybrid filtering.
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.
Dot bundles local LLM inference, Retrieval Augmented Generation, and Text-To-Speech into a single offline Electron app, enabling document QA without cloud dependencies.
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.
RAGFlow is an open-source Python RAG engine combining deep document parsing, configurable pipelines, agentic workflows, and sandboxed code execution for LLM context management.
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.
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.
Explore over 200 pre-built n8n workflow templates integrating vector databases, embedding models, and LLMs for rapid RAG workflow prototyping and deployment without coding.
Supermemory replaces traditional RAG stacks with a unified AI memory layer, offering fast, hybrid memory retrieval and automatic fact extraction in ~50ms. Here’s how it works and how to try it.
Alibaba’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.
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.
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.
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.
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.
WhyHow Knowledge Graph Studio builds RAG-native knowledge graphs using MongoDB and OpenAI embeddings, offering flexible triple-based graph construction for AI workflows.
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.
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.
