langchain-patterns

What problem does it solve?

This Skill simplifies the development of complex AI applications by providing battle-tested patterns for using LangChain, LangGraph, and LiteLLM, ensuring efficient and reliable LLM integrations.

Core Features & Use Cases

• Chain Composition: Implement sequential and parallel execution of LLM calls using LCEL.
• Structured Output: Reliably extract data into Pydantic models, supporting both large and small models.
• Model Routing: Dynamically select LLM providers and models using LiteLLM, with fallback strategies.
• Stateful Workflows: Build multi-step conversational agents with LangGraph.
• Use Case: Develop a customer support chatbot that first identifies the user's intent, then queries a knowledge base, and finally generates a personalized response, all while handling potential model failures gracefully.

Quick Start

Use the langchain-patterns skill to create a chain that takes user input, summarizes it, and extracts keywords.