Agentic RAG

Advanced RAG: Enhancing Queries with LlamaIndex for Superior Search

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Advanced RAG: Enhancing Queries with LlamaIndex for Superior Search

Originally from Akash Mathur’s Blog Abstract: In the field of information retrieval, Retrieval-Augmented Generation (RAG) models signify a paradigm shift, empowering large language models (LLMs) to generate responses that are rich in context and accurate. However, unlocking the full potential of RAG often transcends the limitations of its default query-retrieve-generate framework. This article delves into … Read more

LlamaIndex Surpasses RAG for Complex Decision Making

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LlamaIndex Surpasses RAG for Complex Decision Making

The popular AI orchestration frameworkLlamaIndex has introduced the Agent Document Workflow (ADW), a new architecture that the company claims surpasses the Retrieval-Augmented Generation (RAG) process and enhances the efficiency of agents. As orchestration frameworks continue to improve, this approach provides organizations with options to enhance agent decision-making capabilities. LlamaIndex states that ADW can assist agents … Read more

Quick Start Guide to LlamaIndex RAG CLI

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Quick Start Guide to LlamaIndex RAG CLI

Click 01 Magician Society Follow the official account, and never get lost in AI learning LlamaIndex is a simple and flexible data framework for connecting custom data sources with large language models. RAG is the process of optimizing LLM outputs by referencing knowledge bases outside of their training data sources before generating responses. RAG extends … Read more

Building a Q&A Bot with Local Knowledge Base Using LlamaIndex and Qwen1.5

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Building a Q&A Bot with Local Knowledge Base Using LlamaIndex and Qwen1.5

01 Introduction What is RAG LLMs can produce misleading “hallucinations”, depend on information that may be outdated, and are inefficient when handling specific knowledge, lacking deep insights in specialized fields, while also having some deficiencies in reasoning capabilities. It is against this backdrop that Retrieval-Augmented Generation (RAG) technology has emerged, becoming a significant trend in … Read more

Cohere AI Model Tool for High-Quality Text Generation

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Cohere AI Model Tool for High-Quality Text Generation

AI Model Tool Payment channels available in over 200 countries and regions, please choose! Cohere is a large language model platform focused on building top-notch AI products, primarily aimed at enterprise users and developers, especially those in need of efficient, flexible, and secure language AI solutions for B-end clients. Below is a detailed introduction to … Read more

Getting Started with Mistral: An Introduction

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Getting Started with Mistral: An Introduction

Getting Started with Mistral: An Introduction The open-source Mixtral 8x7B model launched by Mistral adopts a “Mixture of Experts” (MoE) architecture. Unlike traditional Transformers, the MoE model incorporates multiple expert feedforward networks (this model has 8), and during inference, a gating network is responsible for selecting two experts to work. This setup allows MoE to … Read more

Improving RAG with Llama3 and Ollama

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Improving RAG with Llama3 and Ollama

In this article, we will learn how to leverage Llama-3 to implement an advanced RAG with a fully local infrastructure.This article provides a firsthand guide for the first day of implementing advanced RAG. ◆Introduction: In this article, we will create an advanced RAG that will answer user queries based on research papers provided as input … Read more

Enhancement Techniques for Large Model Retrieval (RAG)

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Enhancement Techniques for Large Model Retrieval (RAG)

Click the bottom “Read Original” to browse the detailed content of “CCF Digital Focus” Issue 48 Editor’s Note Large language models (LLMs) still face many challenges when dealing with domain-specific or knowledge-intensive tasks, such as generating hallucinations, outdated knowledge, and opaque, untraceable reasoning processes. Retrieval-Augmented Generation (RAG) technology has emerged to address these issues. RAG … Read more

LangGraph Empowers RAG Research Agents to Tackle Complex Queries!

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LangGraph Empowers RAG Research Agents to Tackle Complex Queries!

This article introduces a practical project that uses LangGraph to develop a RAG research multi-agent tool. This tool is designed to solve complex problems that require multiple sources and iterative steps to arrive at a final answer. It employs hybrid search and Cohere reordering steps to retrieve documents, and also includes a self-correction mechanism, including … Read more