langchain-architecture

Build sophisticated LLM applications with LangChain 1.x and LangGraph for agents, memory, and tool integration. 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: - LangGraph provides the standard agent framework with StateGraph for explicit state management, durable execution, human-in-the-loop inspection, and checkpointing across sessions - Supports ReAct agents, plan-and-execute workflows, multi-agent supervision, and structured tool invocation with Pydantic schemas - Memory systems include ConversationBufferMemory, ConversationSummaryMemory, VectorStoreRetrieverMemory, and persistent PostgreSQL checkpointers for production deployments - Integrates with LangSmith for request logging, token tracking, latency monitoring, and trace visualization; includes custom callback handlers for fine-grained observability - Document processing pipeline covers loading, chunking, embedding, and retrieval; supports RAG patterns with vector stores like Pinecone and Chroma - Building autonomous AI agents with tool access -...