Creating different LangChain chains
In this section, we’ll explore how to create some of the various chains you can create in LangChain. Our aim is to guide you from basic chains to more advanced chains.
We’ll start with an example to introduce the basics of a simple chain. This will provide a foundation for understanding how chains work in LangChain. Next, we’ll learn how to create sequential chains, parallel chains, and finally, routing chains.
By the end of this section, you’ll have a clear understanding of how to create and utilize different LangChain chains and be equipped with the skills to apply these in your future LangChain projects. Let’s dive in.
Basic chain example
In this basic example, we’ll show the simplest chain with a prompt and LLM component, which forms the basis of many more complex implementations. In this example, we are using our model to translate text into any language:
prompt = ChatPromptTemplate.from_template...
