Implement reliable structured output enforcement for LLM responses. ## Required Output Schema {{output_schema}} ## LLM Provider {{llm_provider}} ## Reliability Requirements {{reliability_requirements}} Implement enforcement strategies: ```python class StructuredOutputEnforcer: def __init__(self, schema: dict): self.schema = schema def enforce_via_prompt(self, base_prompt: str) -> str: """Add schema instructions to prompt""" pass def enforce_via_constrained_decoding(self, model: str) -> DecodingConfig: """Configure constrained decoding""" pass def validate_and_repair(self, response: str) -> ValidatedOutput: """Validate output, repair if needed""" pass ``` Approaches to implement: - JSON mode / function calling - Grammar-based decoding - Retry with error feedback - LLM-based repair Include reliability metrics and fallback chains.
Structured Output Enforcer
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Implement reliable structured output enforcement using prompt engineering, constrained decoding, validation, and LLM-based repair strategies.
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Output enforcementSchema validationReliable generation
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claude-sonnet-4-20250514gpt-4o
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