Retrieval-Augmented Generation (RAG) is a powerful approach in natural language processing that combines the benefits of information retrieval and text generation. In this article, we will explore six different types of RAG, each offering unique capabilities to improve the quality and accuracy of generated content.
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Multi-Stage Vector Querying Using Matryoshka Representation Learning (MRL) in Qdrant
Data retrieval is a crucial component in creating an efficient Retrieval Augmented Generation (RAG) application. The effectiveness of data retrieval directly impacts the performance, accuracy, and reliability of the application.
There are various methods of data retrieval from vector databases. Some of the most efficient ones are:
- Self-Query Retrieval
- Multi-Stage Query
- Auto-Merging Retrieval
- Hybrid Retrieval
In this article, we will explore Multi-Stage Query for data retrieval using Matryoshka Representation Learning (MRL) to increase the efficiency of fetching data from the database.
(more…)How to Perform Full-fledged RAG for Any Website Using Firecrawl and Korvus
We are excited to present a detailed guide on using the power of RAG (Retrieval Augmented Generation) from Korvus in combination with Firecrawl. This combination allows you to quickly and easily set up a generation system with enhanced search capabilities using data from any website. Our approach demonstrates how to combine efficient web scraping, data processing, and modern machine learning methods in one elegant solution.
(more…)Simple RAG with LlamaIndex, Qdrant & GPT-4o Mini: A Step-by-Step Guide for Beginners
Retrieval-Augmented Generation (RAG) applications are gaining significant attention in the AI world. But why?
(more…)AI Technologies: RAG Chatbots vs Agent AI – Which Is More Effective?
In the rapidly evolving world of artificial intelligence (AI), new technologies continually emerge, revolutionizing our interaction with machines. Two such technologies – RAG chatbots and Agent AI – have recently garnered significant attention. Let’s delve into what they are and which might be more effective for various tasks.
(more…)Building Enterprise AI Applications with Multi-Agent RAG Systems (MARS)
In the rapidly evolving world of artificial intelligence, the emergence of advanced Retrieval-Augmented Generation (RAG) and Multi-Agent Software Engineering (MASE) has opened new horizons for enterprise AI applications. Let’s explore how these technologies converge to create a powerful tool for businesses.
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