#LangChain
161 related articles
TutorialsLangChain Unified Interface in Practice: init_chat_model Usage & DeepSeek Troubleshooting Guide
Guide to LangChain's init_chat_model unified interface vs model classes, with DeepSeek V4 Pro thinking mode fix, multi-provider switching tips, and AI Agent integration practices.
TutorialsHow Frontend Engineers Can Systematically Build AI Agent Architecture Skills
How frontend engineers can move beyond API calls to build production AI systems — covering streaming output, BFF layers, RAG pipelines, and Agent orchestration with LangChain.js/LangGraph.js.
TutorialsLangChain 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.
TutorialsLangChain Beginner's Guide: A Complete Guide to LLM and Agent Development
A deep dive into LangChain framework essentials, clarifying the key differences between LLMs and Agents, covering Agent development, DeepAgent advanced topics, and learning paths.
TutorialsBuilding an AI Research Assistant with Python + LangChain: Eliminating Academic Hallucinations via MCP
Build an AI research assistant with Python, LangChain, and Consensus MCP. Eliminate LLM hallucinations in academic citations using structured outputs and real-time literature retrieval.
TutorialsLangChain Conversational Memory in Practice: Principles and Latest Implementation of Four Memory Types
Deep dive into four conversational memory types in LangChain 0.3: Buffer, Window, Summary, and Summary Buffer. Covers RunnableWithMessageHistory implementation with selection guidelines.
TutorialsLangChain Prompt Templates Explained: A Practical Guide to Few-Shot and Chain-of-Thought
A deep dive into LangChain prompt templates covering ChatPromptTemplate basics, Few-Shot prompting, and Chain-of-Thought techniques with RAG examples to build high-quality prompt pipelines.
TutorialsLangChain v0.3 Agent Tutorial: Complete Guide to Tool Definition, Building, and Execution
Complete guide to building AI Agents in LangChain v0.3, covering @tool decorator, Agent Executor, parallel tool calls, Google Search integration, and ReAct framework with code examples.
TutorialsLangChain Agent Executor Architecture: Building a ReAct Agent from Scratch
Deep dive into LangChain Agent Executor internals, covering the ReAct reasoning-action-observation loop, tool choice strategies, and building a custom Agent Executor from scratch.
TutorialsLangChain LCEL Expression Language Deep Dive: Pipe Operator, RunnableLambda, and Parallel Execution in Practice
Deep dive into LangChain LCEL core concepts: pipe operator internals, RunnableLambda function wrapping, RunnableParallel retrieval, and RunnablePassThrough with complete code examples and RAG practice.
TutorialsLangChain AI Agent in Practice: Complete Tutorial on Streaming Output + Parallel Tool Calling
Learn how to build a production-grade AI Agent chat app with LangChain and FastAPI, covering streaming tokens, asyncio parallel tool calling, SerpAPI async conversion, and structured output.
TutorialsLangChain Streaming Output & Async in Practice: Complete Implementation for Agent Scenarios
Deep dive into LangChain streaming output and async implementation, covering astream usage, custom AsyncQueueCallbackHandler, and Agent streaming executor architecture for production AI apps.
TutorialsLangChain 1.2 Agent Memory Mechanisms: A Practical Guide to Short-term and Long-term Memory
Learn how LangChain 1.2 Agent memory works. Code demos show why default Agents lack memory, plus practical guides to short-term and long-term memory mechanisms for building conversational AI Agents.
Deep DivesHow to Add Deep Research Skills to AI Agent Frameworks: NVIDIA's Skill-Based Architecture Explained
Explore NVIDIA's Deep Research Skill approach for embedding deep research capabilities as skill modules into AI Agent frameworks like Claude Code and LangChain, enabling goal decomposition, multi-source retrieval, and knowledge synthesis.
TutorialsLangGraph 1.0.5 Tutorial: Master AI Agent Orchestration & Multi-Agent Systems in Six Lessons
Complete guide to LangGraph 1.0.5 tutorial series covering durable execution, memory management, Human in the Loop, streaming, time travel, and multi-agent collaboration.
Deep DivesLangChain Core Architecture Explained: A Practical Guide to Its Five Key Modules
Deep dive into LangChain's five core modules: Model I/O, Data Connection & Retrieval, Chains, Agents, and Memory. Learn RAG workflows, Agent decision-making, and practical AI app development.
TutorialsLangGraph Multi-Agent in Practice: Building a Medical Agent System from Scratch
A deep dive into LangGraph multi-agent architecture for healthcare, covering LangChain, RAG, and MCP integration, from requirements analysis to Agent orchestration.
Product Reviews2025 Comparison of Six Major Agent Development Frameworks: AutoGen/LangChain/LangGraph Selection Guide
In-depth comparison of six AI Agent frameworks—AutoGen, LangChain, LangGraph, Google ADK, OpenAI Agents, AgentScope—covering architecture, ecosystem maturity, and practical selection advice.
TutorialsLangChain 1.3 Event Stream in Practice: Real-Time Agent Monitoring from 4 Perspectives
Master LangChain 1.3 Event Stream V3 with 4 monitoring perspectives: run.messages, tool_cause, and more for real-time Agent debugging, streaming output, tool tracking, and token cost control.
Tutorials2025 LLM Career Transition Roadmap: A Three-Phase Plan from Foundations → Frameworks → Real-World Projects
A systematic 2025 LLM career transition roadmap covering Python, Transformers, LangChain, LlamaIndex, RAG, Agent development, and fine-tuning across three phases achievable in 2-3 months.