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Implementing Self-Correction with LLM Validator - Instructor

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Learn how to use llm_validator for self-healing in NLP applications and improve response accuracy with validation errors.

Self-Correction with llm_validator ¶ Introduction ¶ This guide demonstrates how to use llm_validator for implementing self-healing. The objective is to showcase how an instructor can self-correct by using validation errors and helpful error messages. from pydantic import BaseModel import instructor # Apply the patch to the OpenAI client # enables response_model keyword client = instructor . from_provider ( "openai/gpt-4.1-mini" ) class QuestionAnswer ( BaseModel ): question : str answer : str question = "What is the meaning of life?" context = "The according to the devil the meaning

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