BestHub
Sign in
Tag

agent

1 views collected around this technical thread.

Tencent Technical Engineering
Tencent Technical Engineering
Jun 9, 2025 · Artificial Intelligence

Is Model Context Protocol (MCP) the Future of AI Tool Integration? A Critical Review

This article critically examines the rise of Model Context Protocol (MCP) in AI, explaining its purpose as a unified tool‑calling standard, detailing its architecture, comparing it with traditional function calls, and evaluating the technical and market challenges that limit its universal applicability.

AI ecosystemAI tool integrationFunction Call
0 likes · 21 min read
Is Model Context Protocol (MCP) the Future of AI Tool Integration? A Critical Review
Didi Tech
Didi Tech
Jun 5, 2025 · Artificial Intelligence

Unlocking Modern AI Application Architecture: From RAG to Agents and MCP

This article surveys the evolution of AI applications, explains large language model fundamentals, outlines architectural challenges, and introduces three core patterns—Retrieval‑Augmented Generation (RAG), autonomous Agents, and Model Context Protocol (MCP)—while providing practical LangChain code snippets and integration guidance.

AILLMLangChain
0 likes · 28 min read
Unlocking Modern AI Application Architecture: From RAG to Agents and MCP
Tencent Technical Engineering
Tencent Technical Engineering
May 28, 2025 · Artificial Intelligence

A Beginner-friendly Overview of LLMs, Transformers, Prompts, Function Calling, MCP and Agents

This article provides a concise, easy-to-understand introduction to large language models, the transformer architecture, prompt engineering, temperature settings, function calling, the Model Context Protocol (MCP), agent communication (A2A), and future AI programming trends, using simple analogies and illustrative examples.

AIFunction CallingLLM
0 likes · 11 min read
A Beginner-friendly Overview of LLMs, Transformers, Prompts, Function Calling, MCP and Agents
Efficient Ops
Efficient Ops
May 26, 2025 · Artificial Intelligence

How AI Agents Are Revolutionizing AIOps: Boosting Automation and Efficiency

This article explains how AI agents enhance large‑model capabilities for AIOps, detailing single‑agent use cases like knowledge retrieval, tool guidance, and fault diagnosis, as well as multi‑agent collaborations, required skills, and future prospects for autonomous operations.

AIAIOpsagent
0 likes · 7 min read
How AI Agents Are Revolutionizing AIOps: Boosting Automation and Efficiency
Nightwalker Tech
Nightwalker Tech
Apr 17, 2025 · Artificial Intelligence

LangGraph Explained: Advanced AI Workflow Framework and Hands‑On Guide

This article introduces LangGraph, the next‑generation framework built on LangChain for constructing complex, stateful AI applications, compares it with LangChain, showcases real‑world deployments, and provides a step‑by‑step Python tutorial for building a smart customer‑service chatbot with looped reasoning, tool integration, and human‑in‑the‑loop support.

AI WorkflowChatbotLangChain
0 likes · 20 min read
LangGraph Explained: Advanced AI Workflow Framework and Hands‑On Guide
Rare Earth Juejin Tech Community
Rare Earth Juejin Tech Community
Apr 16, 2025 · Backend Development

Building a Web MCP Client and Server with CopilotKit, LangChain, and Next.js

This article walks through the overall design, implementation, and troubleshooting of a web‑based MCP client and server using CopilotKit, LangChain, Next.js, and related TypeScript libraries, covering setup, core code, environment configuration, and deployment steps.

ClientCopilotKitLangChain
0 likes · 18 min read
Building a Web MCP Client and Server with CopilotKit, LangChain, and Next.js
JD Tech Talk
JD Tech Talk
Feb 18, 2025 · Artificial Intelligence

Agent Applications in Advertising at JD.com: Technical Implementation and Platform Architecture

This article explores how JD.com's advertising team leverages Agent technology to enhance advertising operations through AI-driven automation, covering technical implementations like RAG, Function Call capabilities, and platform architecture for scalable AI solutions.

AI PlatformArtificial IntelligenceFunction Call
0 likes · 23 min read
Agent Applications in Advertising at JD.com: Technical Implementation and Platform Architecture
JD Retail Technology
JD Retail Technology
Feb 18, 2025 · Artificial Intelligence

Engineering Practices of JD Advertising Agent: JDZunTong Intelligent Assistant

JD’s advertising R&D team created the JDZunTong Intelligent Assistant by engineering a modular Agent platform that combines advanced Retrieval‑Augmented Generation (RAG 1.0 → 2.0) and Function‑Call capabilities, a visual designer, custom tool registration, and a native Python workflow engine to deliver intelligent customer service, data queries, and ad creation for merchants.

AIFunction CallJD Advertising
0 likes · 18 min read
Engineering Practices of JD Advertising Agent: JDZunTong Intelligent Assistant
FunTester
FunTester
Jan 21, 2025 · Operations

Byteman Extensions: Custom Helper Classes, Agent Transformation, and ECA Rule Engine

The article explains how Byteman's rule engine can be extended with custom helper classes, describes its Java agent‑based bytecode transformation process, dynamic rule retransformation, and details the underlying ECA rule engine's parsing, type checking, and execution mechanisms.

BytemanJava instrumentationagent
0 likes · 11 min read
Byteman Extensions: Custom Helper Classes, Agent Transformation, and ECA Rule Engine
DataFunSummit
DataFunSummit
Jan 7, 2025 · Artificial Intelligence

Tencent OlaChat: Intelligent Data Analysis Platform – Research, Architecture, and Capabilities

This article presents the Tencent PCG OlaChat team's research and practice in intelligent data analysis, covering the DIKW model, evolution of BI platforms, the impact of large language models, challenges of third‑generation data products, detailed product features, agent architecture, system design, and related academic publications.

Intelligent BILLMTencent
0 likes · 19 min read
Tencent OlaChat: Intelligent Data Analysis Platform – Research, Architecture, and Capabilities
DataFunSummit
DataFunSummit
Jan 1, 2025 · Artificial Intelligence

Challenges and Evaluation Strategies for LLM Agents in 2024

The article outlines the rapid progress of LLM agents in 2024 while highlighting key difficulties in planning capabilities, evaluation methods, dataset generation, and metric design, and suggests practical combinations and product‑level enhancements to improve efficiency, accuracy, and usability.

AILLMagent
0 likes · 3 min read
Challenges and Evaluation Strategies for LLM Agents in 2024
DevOps
DevOps
Dec 23, 2024 · Artificial Intelligence

Understanding AIGC Agents: Definition, Core Features, Underlying Logic, and Commercial Applications

This article explains what AIGC agents are, outlines their four main characteristics, describes the underlying transformer‑based architecture, dual‑stage learning, probabilistic generation and feedback optimization, and explores their current and future commercial use cases across content creation, knowledge bases, customer service, internal operations, and product design.

AIGCArtificial IntelligenceBusiness Applications
0 likes · 14 min read
Understanding AIGC Agents: Definition, Core Features, Underlying Logic, and Commercial Applications
DataFunSummit
DataFunSummit
Dec 22, 2024 · Artificial Intelligence

From Concept to Deployment: The Evolution of 1688’s AI Purchasing Assistant “Yuanbao”

This article chronicles the development of 1688’s AI buyer assistant “Yuanbao”, detailing why an e‑commerce AI assistant is needed, its functional design, MVP constraints, the shift to a data‑driven 2.0 version, future prospects, and a Q&A, providing practical insights for AI product rollout in B‑to‑C platforms.

AILLMagent
0 likes · 24 min read
From Concept to Deployment: The Evolution of 1688’s AI Purchasing Assistant “Yuanbao”
DataFunTalk
DataFunTalk
Dec 10, 2024 · Artificial Intelligence

Tencent Large Language Model Applications: RAG, GraphRAG, and Agent Technologies

This article explores Tencent's large language model deployments across various business scenarios, detailing the principles and practical implementations of Retrieval‑Augmented Generation (RAG), GraphRAG for role‑playing, and Agent technologies, while also covering model fine‑tuning, knowledge‑base construction, and evaluation methods.

AI applicationsGraphRAGRAG
0 likes · 15 min read
Tencent Large Language Model Applications: RAG, GraphRAG, and Agent Technologies
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 EngineeringInference FrameworkRAG
0 likes · 8 min read
Large Model Application Engineering: ZhiLight Inference Framework and Zhihu Direct Answer System
37 Interactive Technology Team
37 Interactive Technology Team
Nov 4, 2024 · Artificial Intelligence

Developing RAG and Agent Applications with LangChain: A Case Study of an AI Assistant for Activity Components

The article outlines a step‑by‑step methodology for creating Retrieval‑Augmented Generation and custom Agent applications with LangChain, illustrated by an AI assistant for activity components that evolves from a rapid Dify prototype to a LangChain‑based RAG system and finally a hand‑crafted ReAct‑style agent, detailing LCEL chain composition, vector‑search integration, model performance trade‑offs, and a unified routing layer.

AI AssistantCloud-nativeLLM
0 likes · 6 min read
Developing RAG and Agent Applications with LangChain: A Case Study of an AI Assistant for Activity Components
DataFunSummit
DataFunSummit
Oct 24, 2024 · Big Data

Bilibili’s Large Language Model‑Based Intelligent Assistant for the Big Data Platform: Architecture, Principles, and Deployment

This article details Bilibili’s implementation of a large‑language‑model‑driven intelligent assistant for its massive big‑data platform, covering background, problem analysis, architectural design, knowledge‑base construction, precision and recall challenges, deployment across offline and real‑time Spark/Flink diagnostics, and future outlooks.

RAGSparkagent
0 likes · 23 min read
Bilibili’s Large Language Model‑Based Intelligent Assistant for the Big Data Platform: Architecture, Principles, and Deployment
DataFunSummit
DataFunSummit
Oct 18, 2024 · Artificial Intelligence

Building Efficient RAG Applications with a Small Team: Insights from PingCAP AI Lab

This article details how PingCAP's three‑person AI Lab leveraged Retrieval‑Augmented Generation (RAG) techniques—including basic RAG, fine‑tuned embeddings, re‑ranking, graph RAG, and agent‑based RAG—to create scalable, multilingual document‑question answering services while addressing large‑scale documentation challenges, model limitations, and user feedback loops.

Fine-tuningLLMRAG
0 likes · 14 min read
Building Efficient RAG Applications with a Small Team: Insights from PingCAP AI Lab
DevOps
DevOps
Jul 21, 2024 · Artificial Intelligence

LLM Fundamentals, Applications, Prompt Engineering, RAG, and Agentic Workflows

This article provides a comprehensive overview of large language models (LLMs), covering their basic concepts, relationship with NLP, development history, parameter scaling, offline deployment, practical applications, prompt‑engineering frameworks, retrieval‑augmented generation, LangChain integration, agents, workflow orchestration, and future directions toward multimodal AI and AGI.

AI applicationsArtificial IntelligenceLLM
0 likes · 36 min read
LLM Fundamentals, Applications, Prompt Engineering, RAG, and Agentic Workflows