This project aims to compare different Retrieval-Augmented Generation (RAG) frameworks in terms of speed and performance.
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Updated
Jul 28, 2024 - Python
This project aims to compare different Retrieval-Augmented Generation (RAG) frameworks in terms of speed and performance.
Intuitive RAG system on top of LllamaIndex
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.
A simple AgenticAI RAG agent showcasing autonomous reasoning and decision-making by integrating thought, logic, and action in real-time tasks.
A RAG-powered customer support chatbot using LlamaIndex, Ollama, and Streamlit for efficient and accurate query responses.
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.
YouTube RAG Research Agent
Development of a AI chatbot (a desktop pet) with persistent & organic cognitive and memory system
🎸 Hands-on tutorial for building RAG applications with LlamaIndex
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!
Using MLflow to deploy your RAG pipeline, using LLamaIndex, Langchain and Ollama/HuggingfaceLLMs/Groq
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
a template for multi-agent collaboration using chainlit, llamaindex, autogen
Utilizes the Nike_Catalog document for answering queries regarding price, category, etc
This project implements a modular and customizable Retrieval-Augmented Generation (RAG) pipeline, designed to enable question-answering and context-aware response generation using external document knowledge.
Wikipedia Retrieval-Augmented Generation System with LlamaIndex and GPT-4o
Llama index demo project
RAG with Apache Airflow, LlamaIndex, and Qdrant
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