A complete collection of RAG interview questions, answers (505 questions & 41 RAG types), system design scenarios, architecture patterns, and production-ready concepts.

Training code for advanced RAG techniques - Adaptive-RAG, Corrective RAG, RQ-RAG, Self-RAG, Agentic RAG, and ReZero. Reproduces paper methodologies to fine-tune LLMs via SFT and GRPO for adaptive retrieval, corrective evaluation, query refinement, self-reflection, and agentic search behaviors.

生产级 3GPP 5G 规范 RAG Agent：自然语言提问，回答带段落级原文引用 + 严格 grounding，覆盖 Rel-18/19 全部 TS。

Evidence-synthesis RAG assistant for TCM practitioners — hybrid vector + knowledge graph retrieval over 17 classical texts, with query classification, self-critique verification, and blind A/B arena evaluation.

Self-Reflective Question Answering for Biomedical Reasoning. GRPO fine-tuning via QLoRA & Unsloth with rewards for correctness, relevance, groundness, utility & XML structure. Structured think → answer → self-reflection with context grading, relevance assessment & groundness evaluation. DeepEval LLM-as-a-Judge (GEval, Faithfulness, Relevancy).

Learn Retrieval-Augmented Generation (RAG) from scratch by manually building chunking, embeddings, retrieval, reranking, answerability, local generation, Graph-RAG, and Self-RAG.

Production-ready Retrieval-Augmented Generation (RAG) system with hybrid retrieval, Self-RAG agent workflows, cross-encoder reranking, and comprehensive benchmarking.

Backend Of STELLA that run SELF Retrieval-Augmented Generation [Senior Project]

AutoDocThinker is a production-ready Agentic RAG system that ingests PDFs, DOCX, URLs, and raw text into a Hybrid Search index (ChromaDB + BM25 + RRF + CrossEncoder), then answers natural language queries through four selectable LangGraph workflows — Naive, Advanced, CRAG, and Self-RAG.

Agentic RAG Multi-Agent Exam Tutor — LangGraph multi-agent system for Marine Structures | DeepSeek V4 Pro | BGE-M3 | ChromaDB | Self-RAG | FastAPI

Advanced RAG with hybrid search, query classification, answer fusion, and self-correction

A modular Self-Reflective RAG framework with built-in critique system. Features 3 adaptive critics ([Retrieve], [ISSUP], [ISCOMP]) for on-demand retrieval, factual verification, and completeness checking. Works with any document source with full reasoning trace visibility.

Prometheus is an open-source, multi-agent AI research engine that uses Corrective RAG (CRAG), hybrid retrieval, and Neo4j graph-based contradiction detection to autonomously synthesize complex biomedical literature.

Self-RAG chatbot with LangGraph that retrieves from internal PDFs, verifies grounding (IsSUP), checks usefulness (IsUSE), and iteratively rewrites queries to improve answer quality.

A hybrid Retrieval-Augmented Generation (RAG) system

Advanced RAG using langgraph which uses websearch functionality to produce relevant documents.

Agentic RAG with self-reflection, query decomposition, iterative retrieval and hallucination detection — CRAG + Self-RAG + Corrective RAG in production

Advanced RAG Implementations

Advanced RAG Q&A for PDFs. Delivers structured, educational answers with diagrams & follow-ups via Streamlit. Powered by LangGraph, featuring hybrid retrieval, cross-encoder reranking, and Self-RAG verification using Groq Llama 3.3 70B & local Ollama embeddings. Includes persistent chat & semantic search.