10 related articles
TutorialsGuide 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.

A deep dive into LangChain's four core modules: LangChain components, LangGraph orchestration, Deep Agents, and LangSmith. Build your first Agent from scratch.

An in-depth look at LangChain's core value: the three limitations of LLMs, unified model interfaces, modular architecture, configuring the DeepSeek API, and understanding the SystemMessage/HumanMessage/AIMessage/ToolMessage system to build a foundation for Agent development.

Starting from the three limitations of LLMs, this guide systematically explains LangChain's core positioning, environment setup, API key prep, model init, and the message system. Learn init_chat_model and AIMessage/HumanMessage/SystemMessage.

Master LangChain from scratch: the three limitations of LLMs, init_chat_model unified interface config, the Message type system, and the path from LLM calls to Agent development.

A beginner's guide to the LangChain open-source framework: explaining how to use the init_chat_model unified interface, tips for disabling DeepSeek's thinking mode, and core essentials of Agent development.

Deep dive into LangGraph's core positioning, its relationship with LangChain, practical code comparisons of Chain vs Graph, understanding Agent essentials, and multi-agent orchestration design.
TutorialsA detailed comparison of LangChain's two model invocation approaches, focusing on init_chat_model unified interface usage and tips for avoiding DeepSeek V4 Pro Thinking Mode pitfalls in Agent scenarios.
TutorialsBuild an AI research assistant with Python, LangChain, and Consensus MCP. Eliminate LLM hallucinations in academic citations using structured outputs and real-time literature retrieval.
TutorialsLearn 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.