langchain-architecture

Master modern LangChain 1.x and LangGraph for building sophisticated LLM applications with agents, state management, memory, and tool integration. LangGraph is the standard for building agents in 2026. It provides: Key Features: Agent Patterns: LangGraph uses TypedDict for explicit state: Modern memory implementations: Loading, transforming, and storing documents: Components: LangSmith is the standard for observability: - Building autonomous AI agents with tool access - Implementing complex multi-step LLM workflows - Managing conversation memory and state - Integrating LLMs with external data sources and APIs - Creating modular, reusable LLM application components - Implementing document processing pipelines - Building production-grade LLM applications - StateGraph : Explicit state management with typed state - Durable Execution : Agents persist through failures - Human-in-the-Loop : Inspect and modify state at any point - Memory : Short-term and long-term memory across sessions - Checkpointing : Save and resume agent state - ReAct : Reasoning + Acting with create_react_agent - Plan-and-Execute : Separate planning and execution nodes - Multi-Agent : Supervisor routing between specialized agents - Tool-Calling : Structured tool invocation with Pydantic schemas - ConversationBufferMemory : Stores all messages (short conversations) - ConversationSummaryMemory : Summarizes older...