Agentic RAG

Cohere’s Open Source 35B Model Surpasses Mixtral in RAG and Tool Capabilities

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Cohere's Open Source 35B Model Surpasses Mixtral in RAG and Tool Capabilities

https://txt.cohere.com/command-r/ https://huggingface.co/CohereForAI/c4ai-command-r-v01 1. RAG Performance On multiple datasets, it far exceeds the Mixtral MoE model. By using their own embeddings and reranking, it significantly outperforms open-source models. 2. Tool Capabilities The tool capabilities are slightly better than Mixtral and significantly outperform GPT-3.5. 3. Multilingual Capabilities Supports English, French, Spanish, Italian, German, Brazilian Portuguese, Japanese, Korean, … Read more

Cohere: Toolkit for Developing RAG Applications

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Cohere: Toolkit for Developing RAG Applications

Project Introduction Cohere is an open-source toolkit for developing RAG applications, which can be deployed to Microsoft Azure with one click or run locally. Building and Running Locally Clone the repository and run make setup Configure the model according to the instructions – AWS Sagemaker, Azure, or the Cohere platform. This can also be accomplished … Read more

LlamaIndex Practical Application – QueryEngine – Retriever

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LlamaIndex Practical Application - QueryEngine - Retriever

1. Overview The retriever is a part of the query engine, responsible for obtaining the most relevant context based on user queries (or chat messages). It can be built on existing indexes but can also be defined independently. It serves as a key building block for query engines (and chat engines) to retrieve relevant context. … Read more

Advanced RAG – Composable Retrieval with LlamaIndex

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Advanced RAG - Composable Retrieval with LlamaIndex

LlamaIndex is a simple and flexible data framework that connects custom data sources with large language models. LlamaIndex provides comprehensive support for RAG. Advanced RAG (Retrieval-Augmented Generation) techniques can be modeled using a composable hierarchical abstraction. The retrieved text can be linked to the following elements: Retriever Text Pipeline Query Engine The retrieval of RAG … Read more

RAG: From Theory to LlamaIndex Practice (Detailed Version)

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RAG: From Theory to LlamaIndex Practice (Detailed Version)

Abstract Large language models (LLMs) have demonstrated impressive capabilities. However, this does not mean they are error-free; anyone who has experienced ChatGPT’s “hallucinations” can attest to that. Retrieval Augmented Generation (RAG) is a framework designed to make LLMs more reliable by extracting relevant, up-to-date data directly related to user queries. In this article, I analyze … Read more

How LlamaIndex Performs Retrieval Augmented Generation (RAG)

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How LlamaIndex Performs Retrieval Augmented Generation (RAG)

The full name of RAG is Retrieval Augmented Generation, which means “retrieval enhanced generation”. LLMs are trained on a vast amount of data, but this training data does not include your data. RAG solves this problem by adding your data to the data that the LLM already has access to. In RAG, your data is … Read more

Implementing RAG Queries in LlamaIndex Agent

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Implementing RAG Queries in LlamaIndex Agent

Implementing RAG Queries in LlamaIndex Agent Overview This article explains how to integrate a RAG query engine into an Agent, enabling the Agent to utilize external knowledge bases for data queries, thus enhancing its capabilities. This approach is useful in many scenarios, for instance: often we need to query or compute a specific metric first, … Read more

LlamaIndex and RAG Evaluation Tools Overview

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LlamaIndex and RAG Evaluation Tools Overview

LlamaIndex is an LLM (Large Language Model) application development framework that many developers prefer to use for developing RAG (Retrieval-Augmented Generation) applications. During the development of RAG applications, we often need to evaluate relevant data to better adjust and optimize the applications. With the development of RAG technology, more excellent evaluation tools have emerged, which … Read more

Understanding the LlamaIndex Development Framework

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Understanding the LlamaIndex Development Framework

▼Recently, there have been many live broadcasts,make an appointment to ensure you gain something. Today:《LlamaIndex Architecture Design and Application Case Practice》 —1— Analysis of the LlamaIndex Development Framework LlamaIndex is a data development framework that provides applications based on LLM to acquire, build, and access private or domain-specific data. It establishes a bridge between natural … Read more

Amazon Bedrock Innovations in RAG Applications

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Amazon Bedrock Innovations in RAG Applications

Introduction to Amazon Bedrock Amazon Bedrock is an advanced generative artificial intelligence (AI) platform launched by Amazon Web Services (AWS) aimed at helping businesses easily build, train, and deploy large-scale generative AI models. By integrating various pre-trained language models, Amazon Bedrock provides users with flexible and scalable AI solutions that support natural language processing, text … Read more