Fix InstructorValidationError

✅ Solution

The "InstructorValidationError" arises when the response from the LLM fails to conform to the pydantic model defined by instructor. To fix this, carefully validate your pydantic model's structure, types, and constraints to ensure they align with the LLM's output, and implement robust error handling to catch validation errors and guide the LLM to correct its response, potentially using `instructor.patch` with `mode="retry"` .