Client-side retrieval firewall for RAG systems — blocks prompt injection and secret leaks, re-ranks stale or untrusted content, and keeps all data inside your environment.

Intuitive RAG system on top of LllamaIndex

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

This project aims to compare different Retrieval-Augmented Generation (RAG) frameworks in terms of speed and performance.

A simple AgenticAI RAG agent showcasing autonomous reasoning and decision-making by integrating thought, logic, and action in real-time tasks.

Stop indexing noise. Turn messy websites and PDFs into clean, structured data for RAG pipelines with semantic importance scoring and token optimization.

A RAG-powered customer support chatbot using LlamaIndex, Ollama, and Streamlit for efficient and accurate query responses.

Using MLflow to deploy your RAG pipeline, using LLamaIndex, Langchain and Ollama/HuggingfaceLLMs/Groq

Knowledge Graph (Graph RAG) from Turkish News with LlamaIndex

This repository contains my personal documentation and learning journey through the Hugging Face Agents Course. I'm documenting my progress, notes, and implementations as I work through the course materials.

Wikipedia Retrieval-Augmented Generation System with LlamaIndex and GPT-4o

🎸 Hands-on tutorial for building RAG applications with LlamaIndex

A Jupyter-native AI teaching assistant using agentic RAG, PDF retrieval, and notebook inspection.

Ever wished you could chat with your PDFs like they're your personal sidekicks? Now you can! This wild project lets you ask your documents questions and get real-time answers. Powered by LlamaIndex and Next.js, it's basically turning your files into chatty little helpers. Let's talk docs!

RAG Document Query System with LlamaIndex

Instantly access Anyparser's robust document processing and data extraction capabilities directly within your LlamaIndex workflows. Enhance your AI applications with superior content understanding and data quality.

Experimenting with different kinds of RAGs Systems

Miako solves real conversation challenges: Understands slang, Taglish, and Gen-Z terms naturally while maintaining production-grade performance. This production-ready open-source Compound AI System handles multiple users simultaneously with isolated sessions, all built for affordability and speed.

Utilizes the Nike_Catalog document for answering queries regarding price, category, etc

a template for multi-agent collaboration using chainlit, llamaindex, autogen