langchain-langgraph-best-practices

What problem does it solve?

Python best-practice guide for building robust LangChain Core, LangChain, LangGraph, and DeepAgents integrations. It helps engineers design and implement durable, multi-layer agent systems with correct patterns, middleware sequencing, and tool delegation.

Core Features & Use Cases

• Guidance on layer selection across LangChain Core, LangChain, LangGraph, and DeepAgents.
• Patterns for agent creation, memory management, streaming, interrupts, and sub-agent delegation.
• Use cases for designing agent workflows, guardrails, and durable execution in real-world projects.

Quick Start

Run a quick reference to establish a robust LangGraph workflow by following the guidelines for graph design, middleware ordering, and memory strategies.