Exploring key components of LangChain
Chains, agents, memory, and tools enable the creation of sophisticated LLM applications that go beyond basic API calls to a single LLM. In the following dedicated subsections on these key concepts, we’ll consider how they enable the development of capable systems by combining language models with external data and services.
We won’t dive into implementation patterns in this chapter; however, we will discuss in more detail what some of these components are good for. By the end, you should have the level of understanding that’s required to architect systems with LangChain. Let’s start with chains!
What are chains?
Chains are a critical concept in LangChain for composing modular components into reusable pipelines. For example, developers can put together multiple LLM calls and other components in a sequence to create complex applications for things like chatbot-like social interactions, data extraction, and...
