#LCEL
50 related articles
Tutorials·2 min
Getting Started with LangChain for Enterprise Development: Core Modules and Debugging Tools Explained
Detailed guide to LangChain core modules including prompt templates, output parsers, Chain invocation, LCEL expression language, and LangSmith tracing tools for LLM application development.
Read more →
Deep Dives·2 min
AI Agent Development Methodology: A Complete Guide from ReAct to Enterprise-Grade Tech Stack
A deep dive into AI Agent development methodology, from the ReAct theoretical framework to a four-layer enterprise tech stack covering model services, Agent types, LangChain, and production deployment.
Read more →
Tutorials·2 min
LangChain Unified Interface in Practice: Complete Guide from Model Invocation to Agent Development
A detailed guide to LangChain's unified interface, comparing model invocation methods, explaining LLM vs Agent differences, with complete Python walkthrough from setup to agent development.
Read more →
Tutorials·2 min
OpenClaw Agent Architecture in Practice: Skills System Deployment & LangChain Reproduction Guide
Deep dive into OpenClaw's industrial-grade Agent architecture with its three-layer design, pluggable Skills system, and memory management. Includes a step-by-step LangChain reproduction guide with an enterprise HR assistant example.
Read more →
Tutorials·2 min
LangChain 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.
Read more →
Tutorials·2 min
LangChain 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.
Read more →
Deep Dives·2 min
LangChain 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.
Read more →
Product Reviews·5 min
DeepClaude Open Source Analysis: DeepSeek + Claude Dual-Model Collaborative Code Generation
Deep dive into DeepClaude, a 2800+ Star open source project combining DeepSeek R1 reasoning with Claude 3.7 Sonnet code generation for superior AI output.
Read more →
Tutorials·3 min
LangGraph E-commerce AI Agent in Practice: From RAG Q&A to Automated Return Workflows
Deep dive into the E-commerce-Smart-Agent open-source framework built with LangGraph and FastAPI, covering RAG knowledge base Q&A, return workflow automation, and graph-based orchestration.
Read more →
Product Reviews·3 min
Micro-Agent: Fudan University's Open-Source Lightweight AI Agent Framework Built for Vertical Domains
Micro-Agent is a lightweight AI Agent framework open-sourced by Fudan University, focused on vertical domain applications. It offers streamlined architecture, low learning costs, and high customization flexibility compared to heavyweight frameworks like LangChain.
Read more →