# LangChain LangChain is an open-source orchestration framework for building applications with [[Large Language Models (LLMs)]]. Available in both Python and JavaScript, it provides tools and APIs to simplify building LLM-driven applications like chatbots, [[AI Agents]], and [[Retrieval-Augmented Generation (RAG)]] systems. The framework serves as a generic interface for nearly any LLM, providing a centralized development environment to build applications and integrate them with external data sources and software workflows. ## Key Features - **Modular architecture**: Chain together interoperable components - **Model agnostic**: Connect to [[OpenAI]], [[Anthropic]], Google, and other providers - **Tool integration**: Built-in support for external tools and APIs - **Memory systems**: Short-term and long-term conversation memory - **Retrieval mechanisms**: Document loaders, text splitters, and [[Vector Store|Vector Stores]] - **Prompt templates**: Reusable, parameterized prompts ## Core Components LangChain's ecosystem includes several libraries: | Component | Purpose | |-----------|---------| | LangChain-core | Fundamental abstractions for chat models | | Integration packages | Provider-specific integrations (OpenAI, Anthropic, etc.) | | Chains | Sequential processing pipelines | | Agents | Autonomous decision-making components | | Retrievers | Document retrieval mechanisms | ## Architecture LangChain applications typically follow patterns: - **Chains**: Linear sequences of operations (input → process → output) - **[[AI Agents]]**: Dynamic decision-making with tool selection - **[[RAG Pipelines]]**: Retrieve context → Augment prompt → Generate response ## Limitations - Steep learning curve due to layered abstractions - Overhead may be excessive for simple applications - Rapid API changes between versions ## References - https://www.langchain.com/ - https://docs.langchain.com/ - https://github.com/langchain-ai/langchain ## Related - [[LangGraph]] - [[AI Agents]] - [[Large Language Models (LLMs)]] - [[Mastra AI]] - [[Directed Acyclic Graphs (DAG)]] - [[Python]] - [[TypeScript]] - [[Retrieval-Augmented Generation (RAG)]] - [[Vector Store]] - [[RAG Pipelines]]