A comprehensive interview preparation guide covering all major RAG (Retrieval-Augmented Generation) architectures. 50 questions across 10 types, from Naive RAG to Agentic, Graph, Self-RAG, and beyond. Includes difficulty tags, detailed answers, a cheatsheet, and a decision tree.

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.

Self-Reflective Question Answering for Biomedical Reasoning

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.

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

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

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.

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

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

Implements SELF-RAG (Asai et al. 2023) — LLM decides when to retrieve, evaluates IS_REL/IS_SUP/IS_USE reflection tokens, and self-corrects responses.

Advanced RAG Implementations

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

Production adapters and pipelines for PortfolioCore. Vector stores (pgvector, Qdrant), graph stores (Neo4j), embedders (OpenAI), Broadway pipelines, advanced RAG (Self-RAG, CRAG, GraphRAG, Agentic), multi-graph federation, and observability.

https://files.rochiey.dev/s/APqtCyBpZXiwTHZ

A Streamlit-based Self-RAG-inspired multi-document evidence QA assistant with retrieval, answer generation, and structured critique.

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.

Hallucination-free AI medical assistant using Self-RAG verification on Llama-2-7B

Self-RAG (Self-Reflective Retrieval-Augmented Generation) implementation in Java using Google ADK

podcast chatbot using the ell llm framework uses self RAG with memory

This project is built using Python and the Flask web framework, providing a user-friendly web interface for interacting with the RAG system. The core logic, including document processing, embedding generation, retrieval strategies (Self-RAG and Agentic RAG), and integration with the Gemini API, is organized within the utils directory.