LangGraph #16: Before Tools in LangGraph | Annotated, Sequence & Reducers Explained

Before using tools in LangGraph, you need to understand the state system. In LangGraph Class 16, this video explains the most important concepts required before building tools with LLMs. We deep-dive into Annotated state, Sequence, add_messages, and reducers in Python, which control how data and messages flow across your LangGraph nodes. You’ll clearly understand: What Annotated state is and why LangGraph uses it How Sequence manages message ordering How add_messages updates conversation state What reducers are and how LangGraph merges state Why these concepts are required before tool calling This lesson is a direct prerequisite for the next class, where we: Build custom tools in LangGraph Attach tools to an LLM Learn how LangGraph automatically calls tools If you’re learning LangGraph, AI agents, or LLM tool calling in Python, this video is essential before moving forward. Next Video: LangGraph Tools Explained – Create, Attach & Call Tools Course: LangGraph from Beginner to Advanced Language: Python Subscribe to follow the complete LangGraph course series Github: https://github.com/Alihamza-786/LangGraph #LangGraph #LangGraphTools #LangGraphPython #LLMTools #AIagents #PythonAI #LangChain #LLMDevelopment #ToolCalling #AIWorkflows #AgenticAI #OpenAI #PythonProgramming #MachineLearning #GenerativeAI