Summary
LLMs produce convincing language but have significant limitations in terms of reasoning, knowledge, and access to tools. The LangChain framework simplifies the building of sophisticated applications powered by LLMs that can mitigate these shortcomings. It provides developers with modular, reusable building blocks like chains for composing pipelines and agents for goal-oriented interactions. These building blocks fit together as LLM apps that come with extended capabilities.
As we saw in this chapter, chains allow sequencing calls to LLMs, databases, APIs, and more to accomplish multi-step workflows. Agents leverage chains to take actions based on observations for managing dynamic applications. Memory persists information across executions to maintain state. Together, these concepts enable developers to overcome the limitations of individual LLMs by integrating external data, actions, and context. In other words, LangChain reduces complex orchestration into customizable...
