#RAG LangChain

1044 related articles

Jul 23, 2026·3 min

LangChain v1.3 Hands-On Tutorial: Deep Dive into Agents, RAG, and Local Model Deployment

Deep dive into LangChain v1.3: compare LangChain, LangGraph, and DeepAgent paradigms, explore RAG pipelines, multi-agent systems, and local LLM deployment for enterprise AI apps.

Jul 14, 2026·3 min

LangChain Practical Guide: From RAG Applications to Intelligent Agent Development

A comprehensive guide to LangChain: core concepts, RAG applications, Agent development, version selection (0.3/1.0), and career opportunities for Java/Python developers entering LLM development.

Jul 13, 2026·2 min

LangChain in Practice: Building the ChatDoc Document Chat Application with RAG

An in-depth explanation of RAG (Retrieval-Augmented Generation) principles, with a hands-on guide to loading PDF, Word, and other document formats in LangChain to build a complete ChatDoc Q&A app.

Jul 13, 2026·3 min

LangChain V1.3 Hands-On Tutorial: A Complete Breakdown of RAG, Multi-Agents, and Engineering Mindset

An in-depth look at LangChain V1.3's core philosophy: from RAG to multi-agent workflows. Master LangGraph, Chain, and DeepAgent, learn token control and Human-in-the-loop, and become a true master of AI app development.

Jun 13, 2026·3 min

LangChain Beginner's Guide: From Environment Setup to RAG — A Complete Hands-On Walkthrough

A systematic guide to LangChain covering environment setup, model invocation, Prompt Templates, Output Parsers, LCEL chain expressions, and hands-on RAG implementation for beginners.

Jun 13, 2026·4 min

LangChain4j in Practice: A Complete Tutorial for Building a RAG Medical Q&A System

A complete tutorial on building a RAG medical Q&A system with LangChain4j, covering Ollama local deployment, Redis vector DB, document vectorization, and Cursor AI-assisted development.

LangChain Agent Development Tutorial: RAG and Agent Hands-On Learning Path

Tutorials

May 22, 2026·1 min

LangChain Agent Development Tutorial: RAG and Agent Hands-On Learning Path

A systematic learning path for LangChain Agent development covering RAG, autonomous Agent decision-making, and tool calling—from zero to production-ready projects.

Agentic RAG in Practice: Architecture Deep Dive and LangChain Implementation Guide

Tutorials

May 13, 2026·4 min

Agentic RAG in Practice: Architecture Deep Dive and LangChain Implementation Guide

Compare traditional RAG vs Agentic RAG architectures, explore planning, tool use, and multi-step iteration capabilities, with full LangChain/LangGraph ReAct Agent code and ChatBoss project examples.

Tutorials

May 13, 2026·3 min

Agentic RAG in Practice: Architecture Deep Dive and LangChain Implementation

Deep dive into Agentic RAG vs traditional RAG, covering planning, tool calling, and multi-step iteration capabilities with complete LangChain and LangGraph code implementation.

Aug 1, 2026·3 min

Ollama + Qwen-Agent: Building a Local Private AI Assistant — From Deployment to Security Best Practices

A complete guide to building a local private AI assistant with Ollama and Qwen-Agent. Covers RAG knowledge integration, voice interaction, and permission isolation for a secure local AI Agent architecture.

Aug 1, 2026·2 min

AI Agents Running a Real Company: Experiment Results and Capability Boundary Analysis

What happens when AI agents are tasked with running a real company? This analysis examines agent performance, critical shortcomings, and practical enterprise deployment advice.

Aug 1, 2026·2 min

AI Frontier Technology Accelerating: Decoding Industry Signals and Future Trends

Decoding signals like "frontiermogging" to analyze upcoming AI frontier model leaps, Agent automation deployment, and developer ecosystem expansion trends.

Aug 1, 2026·5 min

Have AI Doomers Actually Used AI? A Developer Exposes the Gap Between Hype and Reality

AI Doomers warn AI will destroy humanity, but have they actually built AI apps? A developer's sharp critique reveals the vast gap between AI demos and real engineering practice.

Jul 31, 2026·4 min

Tiling Window Management: A New Interaction Paradigm for Multi-Agent Conversations

Exploring tiling window management for multi-agent AI conversations: how it solves parallel monitoring and observability challenges, real-world limitations, and the evolution from chat boxes to control consoles.

Jul 31, 2026·3 min

TraceLLM: An Open-Source LLM Observability Platform Built on OpenTelemetry

TraceLLM is an open-source observability platform for production AI apps, built on OpenTelemetry, offering Prompt tracing, Token monitoring, latency analysis, and full distributed tracing.

Jul 31, 2026·3 min

What Kind of GUI Do AI Agents Need? The Evolution from Chat Boxes to Task Consoles

Exploring GUI design for AI Agents: why chat boxes fall short, and how ideal agent interfaces need task visualization, human-in-the-loop intervention, state presentation, and multi-agent orchestration.

Jul 30, 2026·3 min

Claude Opus 5 Plays Pokémon: A 12-Hour AI Experiment in Multi-Agent Loop Architecture

Deep analysis of Claude Opus 5 playing Pokémon for 12 hours via multi-agent loop architecture, exploring Agent design patterns, long-horizon planning, and AI Agent trends.

Jul 30, 2026·3 min

Claude Opus 5 Plays Pokémon: Analyzing a 12-Hour AI Experiment Under Multi-Agent Loop Architecture

In-depth analysis of Claude Opus 5's 12-hour Pokémon gameplay through multi-agent loop architecture, exploring multi-Agent design, long-horizon planning, and AI Agent trends.

Jul 30, 2026·2 min

GPT-5.6 Released: Redefining the Price-Performance Boundary of AI Models

OpenAI releases GPT-5.6, targeting the price-performance frontier. Analysis of how architectural optimization and inference efficiency reduce costs, and how LLM competition shifts from capability to cost efficiency.

Jul 30, 2026·3 min

Jina v3 Matryoshka Embeddings in Practice: Cut Vector Storage Costs by 75%

Use Jina v3 Matryoshka embeddings to truncate 1024-dim vectors to 256-dim, cutting Pinecone storage costs by 75% while maintaining retrieval quality with task-specific LoRA adapters and circuit breakers.