Combining Prompts with Chains

LangChain's true power emerges when you combine individual components into sequences or graphs that perform complex tasks. These sequences are known as Chains, acting as the orchestrator that links together various steps, such as fetching data, formatting input, interacting with a language model, and processing its output. Understanding how prompt templates integrate into these Chains is fundamental to building sophisticated LLM applications.

At its core, a Chain represents a series of operations that take input and produce output. A simple Chain might involve just a prompt template and an LLM. More complex Chains can include multiple LLMs, data transformers, retrieval systems, and other utilities, all working in concert.