May 05, 2026
LLMs are great at prose, but they are often terrible at outputting consistent, parsable code. Instructor is a tiny library that forces an LLM to follow your schema, ensuring that the model’s output perfectly maps to your Python objects.
By using Pydantic, Instructor allows you to define exactly what the LLM should return. If the LLM generates bad output, the library automatically handles the retries, providing the model with feedback so it can correct its mistake. This is essential for building production apps that depend on AI-generated data.
With Instructor, you can extract entities from raw text, classify complex intents, and generate multi-step actions as structured objects, making the integration between AI reasoning and your application code seamless and robust.