Llm Agents

This skill provides comprehensive guidance for building sophisticated LLM applications using LangChain 1.x and LangGraph. It covers agent orchestration with StateGraph, RAG implementations, multi-agent systems, memory management patterns, and production deployment best practices including LangSmith observability integration.

A comprehensive reference guide for the Langroid multi-agent LLM framework. Provides design patterns and code examples for agent configuration, stateful tool handlers, task control with done_sequences, batch processing, MCP tool integration, and quiet mode output control.