Orchestrate LLM applications with LCEL chains, LangGraph agents, and RAG pipelines.
npx skills add https://github.com/magnus919/agent-skills --skill langchain-magnus919
Please help me install this Agent Skill. Skill: langchain Source: https://github.com/magnus919/agent-skills/tree/main/langchain Command: npx skills add https://github.com/magnus919/agent-skills --skill langchain-magnus919
This skill addresses the complexity of orchestrating LLM applications by providing a standardized, modular framework for building chains, agents, and RAG pipelines that are observable and production-ready.
Use the langchain skill to initialize a basic LCEL chain that prompts a model to answer a specific question.
High-intent search queries and answers about installing and using this skill.
Build production-ready LLM apps with LangChain by orchestrating modular components through LCEL chain composition, LangGraph agent creation, and RAG pipeline implementation for enterprise-grade AI scenarios.
Create tool-using agents with LangGraph by leveraging its runtime for state management, streaming event handling, and persistent memory, enabling complex multi-step reasoning workflows.
Implement a RAG pipeline using LCEL composition to connect retrieval components with language models, enabling applications like customer support bots to retrieve documentation and use external tools.
Integrate LangSmith tracing to achieve production observability, allowing you to debug agent behavior, monitor latency, and evaluate LLM performance in real-time.
LangChain supports streaming event handling through LangServe and FastAPI integration, allowing you to deploy modular LCEL chains and LangGraph agents as production-ready APIs.
Use LCEL composition to build complex LLM workflows with the pipe operator, resulting in clean, readable, and modular code that supports framework-neutral evaluation and standardized integration.
bobmatnycBuild and orchestrate LLM-powered applications with LangChain.
manutejOrchestrate LangChain chains, agents, memory, and RAG patterns.
JNZader-VaultBuild LLM chains, agents, and RAG systems with LangChain and LangGraph.
hoodiniBuild end-to-end LLM applications with LangChain and LangGraph.
