Understanding LangChain LLM Output Parser
The large Language Model, or LLM, has revolutionized how people work. By helping users generate the answer from a text prompt, LLM can do many things, such as answering questions, summarizing, planning events, and more.
However, there are times when the output from LLM is not up to our standard. For example, the text generated could be thoroughly wrong and need further direction. This is where the LLM Output Parser could help.
By standardizing the output result with LangChain Output Parser, we can have some control over the output. So, how does it work? Let’s get into it.
Preparation
In this article, we would rely on the LangChain packages, so we need to install them in the environment.