BestHub
search
Sign in
Topic

RAG

Collection size
167 articles
Page 3 of 9
JD Tech
JD Tech
Oct 31, 2024 · Artificial Intelligence

Design and Implementation of the Logistics Intelligent Robot “Yunli XiaoZhi” Powered by Large Language Models

The article details the development of Yunli XiaoZhi, an AI‑driven logistics chatbot that combines knowledge‑base Q&A, data‑analysis, proactive alerts and report‑pushing to streamline SOP access, reduce manual query effort, and improve operational efficiency for operators, carriers and drivers.

AI chatbotRAGVector Database
0 likes · 22 min read
Design and Implementation of the Logistics Intelligent Robot “Yunli XiaoZhi” Powered by Large Language Models
JD Tech
JD Tech
Jul 10, 2024 · Artificial Intelligence

Implementing Retrieval‑Augmented Generation (RAG) with LangChain4j in Java

This article provides a step‑by‑step guide for Java engineers on building a Retrieval‑Augmented Generation (RAG) application using the LangChain4j framework, covering RAG fundamentals, environment setup, Maven integration, document loading, splitting, embedding with OpenAI, vector store management with Chroma, and prompt‑based LLM interaction.

JavaLLMLangChain4j
0 likes · 35 min read
Implementing Retrieval‑Augmented Generation (RAG) with LangChain4j in Java
JD Tech
JD Tech
Jun 28, 2024 · Artificial Intelligence

An Overview of Large Language Models: History, Fundamentals, Prompt Engineering, Retrieval‑Augmented Generation, Agents, and Multimodal AI

This article provides a comprehensive introduction to large language models, covering their historical development, core architecture, training process, prompt engineering techniques, Retrieval‑Augmented Generation, agent frameworks, multimodal capabilities, safety challenges, and future research directions.

AI SafetyAI agentsDeep Learning
0 likes · 22 min read
An Overview of Large Language Models: History, Fundamentals, Prompt Engineering, Retrieval‑Augmented Generation, Agents, and Multimodal AI
JD Tech Talk
JD Tech Talk
Sep 30, 2024 · Artificial Intelligence

Yunli XiaoZhi: An AI‑Powered Intelligent Assistant for Knowledge Q&A and Data Analysis in Logistics Operations

The document describes the design, implementation, and operational results of Yunli XiaoZhi, an AI‑driven portable knowledge‑base and data‑analysis chatbot that consolidates SOPs, manuals, and real‑time information for logistics staff, using LangChain‑based RAG, vector databases, and large‑model prompting to improve query efficiency, proactive alerts, and reporting across multiple user groups.

AIChatbotRAG
0 likes · 19 min read
Yunli XiaoZhi: An AI‑Powered Intelligent Assistant for Knowledge Q&A and Data Analysis in Logistics Operations
JD Tech Talk
JD Tech Talk
Oct 8, 2024 · Artificial Intelligence

Building a Retrieval‑Augmented Generation (RAG) System with Rust and Qdrant

This article explains how to construct a Retrieval‑Augmented Generation pipeline in Rust, covering knowledge‑base creation with Qdrant, model loading and embedding using the candle library, data ingestion, and integration of a Rust‑based inference service based on mistral.rs, while also discussing resource usage and common pitfalls.

AILLMQdrant
0 likes · 16 min read
Building a Retrieval‑Augmented Generation (RAG) System with Rust and Qdrant
58 Tech
58 Tech
Aug 7, 2024 · Artificial Intelligence

Bridging Compute and Applications: 58.com AI Lab’s Large‑Model Platform and AI Agent Solutions

In this article, 58.com AI Lab senior director Zhan Kunlin explains how the company built a multi‑layer AI platform, created a vertical large‑language model called LingXi, and developed an AI Agent system with RAG capabilities to accelerate practical AI applications across various business scenarios.

AI PlatformAI agentsRAG
0 likes · 10 min read
Bridging Compute and Applications: 58.com AI Lab’s Large‑Model Platform and AI Agent Solutions
Cognitive Technology Team
Cognitive Technology Team
Mar 4, 2025 · Artificial Intelligence

Deep Searcher: An Open‑Source Agentic RAG Framework for Enterprise‑Level Search and Knowledge Retrieval

The article introduces Deep Searcher, an open‑source Agentic Retrieval‑Augmented Generation system that combines large language models, Milvus vector databases, and multi‑step reasoning to deliver enterprise‑grade search, reporting, and complex query capabilities, and compares its performance against traditional RAG and Graph RAG approaches.

LLMOpen SourceRAG
0 likes · 18 min read
Deep Searcher: An Open‑Source Agentic RAG Framework for Enterprise‑Level Search and Knowledge Retrieval
Cognitive Technology Team
Cognitive Technology Team
Feb 28, 2025 · Artificial Intelligence

Comparative Study of Traditional RAG, GraphRAG, and DeepSearcher for Knowledge Retrieval and Generation

This article examines why Retrieval‑Augmented Generation (RAG) is needed, compares traditional RAG, GraphRAG, and the DeepSearcher framework across architecture, data organization, retrieval mechanisms, result generation, efficiency and accuracy, and provides step‑by‑step implementation guides and experimental results using vector and graph databases.

DeepSearcherGraphRAGRAG
0 likes · 20 min read
Comparative Study of Traditional RAG, GraphRAG, and DeepSearcher for Knowledge Retrieval and Generation
AntData
AntData
Oct 16, 2024 · Artificial Intelligence

Building a Data Assistant Application with DB‑GPT V0.6.0

This tutorial walks through the end‑to‑end process of creating a data‑assistant application using DB‑GPT V0.6.0, covering prerequisite deployment, knowledge‑base construction, sub‑agent creation, RAG‑based QA, AWEL workflow installation, intent‑recognition knowledge base, and unified multi‑agent orchestration.

AIDB-GPTData Assistant
0 likes · 12 min read
Building a Data Assistant Application with DB‑GPT V0.6.0
AntData
AntData
Sep 26, 2024 · Artificial Intelligence

DB-GPT: Open-Source AI-Native Data Application Development Framework

DB‑GPT is an open‑source AI‑native data‑application framework that provides multi‑model management, Text‑to‑SQL optimization, RAG, multi‑agent collaboration, and intelligent workflow orchestration, enabling developers to build scalable large‑model database applications, with proven enterprise adoption, community growth, and academic publications.

AIData EngineeringOpen Source
0 likes · 6 min read
DB-GPT: Open-Source AI-Native Data Application Development Framework
AntTech
AntTech
Jul 2, 2024 · Artificial Intelligence

Design and Implementation of a Generalized Retrieval‑Augmented Generation (RAG) Framework with Graph RAG Support

This article surveys Retrieval‑Augmented Generation (RAG), analyzes the limitations of traditional vector‑based RAG, introduces Graph RAG that leverages knowledge graphs for more reliable context, proposes a universal RAG architecture compatible with vector, graph and full‑text indexes, and details its open‑source implementation, code components, testing, and future research directions.

AIEngineeringGraphRAGKnowledgeGraph
0 likes · 26 min read
Design and Implementation of a Generalized Retrieval‑Augmented Generation (RAG) Framework with Graph RAG Support
Zhihu Tech Column
Zhihu Tech Column
Dec 9, 2024 · Artificial Intelligence

Large Model Application Engineering: ZhiLight Inference Framework and Zhihu Direct Answer System

The article details Zhihu's technical salon on large‑model engineering, covering the RAG‑based Zhihu Direct Answer system, the open‑source ZhiLight inference framework, prompt engineering, agent research, and future plans for integrating AI into product and community workflows.

AI EngineeringAgentInference Framework
0 likes · 8 min read
Large Model Application Engineering: ZhiLight Inference Framework and Zhihu Direct Answer System
Zhihu Tech Column
Zhihu Tech Column
Jan 17, 2025 · Artificial Intelligence

Zhihu Direct Answer: Product Overview and Technical Practices

This article summarizes the key technical insights from Zhihu Direct Answer, an AI-powered search product, covering its product overview, RAG framework, query understanding, retrieval strategies, chunking, reranking, generation techniques, evaluation methods, and engineering optimizations for cost and performance.

AI SearchChunkingEngineering Optimization
0 likes · 13 min read
Zhihu Direct Answer: Product Overview and Technical Practices
Aikesheng Open Source Community
Aikesheng Open Source Community
Nov 12, 2024 · Artificial Intelligence

ChatDBA: An AI‑Powered Database Fault Diagnosis Assistant Using Large Language Models

ChatDBA is a conversational AI system built by Shanghai Aikesheng that employs large language models and Retrieval‑Augmented Generation to help database administrators diagnose faults, learn domain knowledge, and generate or optimize SQL, with a redesigned architecture that addresses early‑stage shortcomings and outlines future enhancements.

ChatDBADatabase AIFault Diagnosis
0 likes · 10 min read
ChatDBA: An AI‑Powered Database Fault Diagnosis Assistant Using Large Language Models
Aikesheng Open Source Community
Aikesheng Open Source Community
Nov 11, 2024 · Databases

ChatDBA: An AI‑Powered Intelligent Assistant for Database Fault Diagnosis and Management

ChatDBA is an AI‑driven conversational system developed by Shanghai Aikesheng that assists DBAs with fault diagnosis, knowledge learning, SQL generation and optimization by leveraging large language models, RAG architecture, and advanced retrieval and document‑processing techniques.

ChatDBADatabase AIFault Diagnosis
0 likes · 10 min read
ChatDBA: An AI‑Powered Intelligent Assistant for Database Fault Diagnosis and Management
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Feb 22, 2025 · Artificial Intelligence

Deploying DeepSeek Locally with Ollama, Building Personal and Organizational Knowledge Bases, and Integrating with Spring AI

This guide explains how to locally deploy the DeepSeek large‑language model using Ollama on Windows, macOS, and Linux, configure model storage and CORS, build personal and enterprise RAG knowledge bases with AnythingLLM and Open WebUI, and integrate the model into a Spring AI application via Docker and Docker‑Compose.

ContainerizationDeepSeekDocker
0 likes · 16 min read
Deploying DeepSeek Locally with Ollama, Building Personal and Organizational Knowledge Bases, and Integrating with Spring AI
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Apr 11, 2024 · Artificial Intelligence

AI Hackathon Journey: Building the "Novel Jump" Bot on Coze Platform

This article recounts the author's participation in a Shenzhen AI Hackathon, detailing the development of an interactive novel‑character chatbot using the Coze platform, describing the workflow design, technical challenges, model choices, knowledge‑base construction, and the final demo and award outcomes.

AIChatbotCoze
0 likes · 12 min read
AI Hackathon Journey: Building the "Novel Jump" Bot on Coze Platform
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Apr 8, 2024 · Artificial Intelligence

PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal Retrievers

The article introduces PreFLMR, an open‑source, general‑purpose pre‑trained multimodal retriever that leverages fine‑grained late‑interaction to boost retrieval‑augmented generation for knowledge‑intensive visual tasks, describes its M2KR benchmark, training stages, and strong experimental results across multiple tasks.

AIFLMRRAG
0 likes · 11 min read
PreFLMR: Scaling Up Fine-Grained Late-Interaction Multi-modal Retrievers
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Feb 25, 2024 · Artificial Intelligence

Pinecone Vector Database and Embedding Model Summary from DeepLearning.AI’s AI Course

This article reviews the author’s hands‑on experience with Pinecone’s serverless vector database, various embedding and generation models such as all‑MiniLM‑L6‑v2, text‑embedding‑ada‑002, clip‑ViT‑B‑32, and GPT‑3.5‑turbo‑instruct, and demonstrates how they are applied to semantic search, RAG, recommendation, hybrid, and facial similarity tasks using Python code examples.

AIEmbedding ModelsPinecone
0 likes · 9 min read
Pinecone Vector Database and Embedding Model Summary from DeepLearning.AI’s AI Course