When we use large language model (LLM) chatbots as end users, they usually come back to us with an unstructured natural language answer. When building GenAI applications that are more than chatbots, it can be useful to ask the LLM for a structured answer in JSON, YAML or other formats, and then parse and use that response in the application. However, as LLMs are nondeterministic, they might not always do what we ask them to do. Instructor is a library that can be used to help us request structured output from LLMs. You can define the intended output structure and configure retries if the LLM doesn't return the structure you asked for. As the best end user experience for working with LLMs is often to stream the results to them instead of waiting for the full response, Instructor also takes care of parsing partial structures from a stream.
