Langgraph

Building a production-ready conversational agent with LangGraph that combines short-term memory (checkpointing), long-term memory (conversation summarization), and real-world tool access (weather, web search). The final project that assembles all building blocks from NB01 to NB05.

A complete hands-on guide to LangGraph's core building blocks: StateGraph and custom graphs, state reducers with add_messages, checkpointing with InMemorySaver, human-in-the-loop with interrupt and Command, and dependency injection in tools with ToolRuntime (state, context, store).

How to extend LLM capabilities with Tools and Agents. Three progressive levels: defining tools with @tool, understanding the manual ReAct loop with bind_tools and ToolMessage, and automating everything with create_react_agent from LangGraph. Covers sequential vs parallel tool calls, stateless LLM behavior, and how agents manage conversation history automatically.