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.

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

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.

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

Indian Classical Music Practicing application

Retrieval-Augmented Generation (RAG) system for extracting information from legal documents such as NDAs, contracts, and privacy policies. Includes preprocessing, EDA, vector search using ChromaDB, and evaluation with ROUGE, BLEU, and RAGAS metrics.

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.

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