Building RAG and Agentic Applications with Haystack 2.0, RAGAS and LangGraph 1.0 published by Packt

RAG using LlamaIndex：Computer Network Q&A System powered by LlamaIndex | 基于 LlamaIndex 框架的计算机网络智能问答系统 - HyDE+混合检索 + vLLM 推理+Ragas评估

🔰 A Comprehensive RAG repository covering basic vanilla RAG techniques, advanced retrieval methods, hybrid search fusion approaches, hands-on reranking techniques with code + explanation 📚✨

A curated collection of papers, frameworks, tools, and resources on Retrieval-Augmented Generation (RAG). Maintained for students of the Text Mining and Data Visualization course as a starting point for thesis research.

🤖 The RAG application retrieves data from Notion

LangGraph-orchestrated RAG multi-agent pipeline that routes queries to specialized agents. Modular design for ingestion, routing and evaluation.

Advanced RAG system with enhanced retrieval and error-handling capabilities. Implemented totally locally with open-source tools — LangGraph, Qdrant, Llama.cpp server, Qwen3-0.6B-UD-Q8_K_XL.gguf and MLflow server for observability.

This project integrates LangFlow as a backend API with a Streamlit frontend for a chatbot interface. It also includes RAGAS evaluation for measuring the performance of RAG (Retrieval-Augmented Generation) pipelines.

RAG Evaluation Pipeline (RAGAS)

An enterprise-grade, full-stack AI travel planner which provides data-driven itineraries for Lucknow, India and showcases production-ready architecture, combining a FastAPI backend with a Streamlit frontend. It leverages an advanced agentic RAG system, context-aware responses by integrating a local knowledge base with live, external APIs.

A LangChain-based Retrieval-Augmented Generation (RAG) chatbot for medical data. Integrates with Gemini/Grok AI to deliver accurate, context-aware answers in healthcare and biomedical domains.

Streamlit, LangChain, OpenAI, FAISS, Ollama, ChromaDB, Llama 3.1 for PDF RAG Chat Interaction

A realtime Concierge Agent made using Pipecat and LanGraph with COT reasoning.

Indian Classical Music Practicing application

An enterprise-grade contextual RAG chatbot with ZenML pipelines, CrewAI agents, Ollama models, and OpenWebUI — designed for intelligent, local, and explainable document querying.

A practical guide for building and evaluating an end-to-end Retrieval Augmented Generation (RAG) system with memory and more!

Contextual RAG Chatbot with LlamaIndex, Ollama & PGVector

This project presents an end-to-end multimodal framework integrating tumor detection, TNM staging, and guideline-based treatment recommendations for lung cancer. The system unifies computer vision models with Retrieval-Augmented Generation (RAG) using modern LLMs.