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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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.

Details

Category

Coding

Use Cases

Output enforcementSchema validationReliable generation

Works Best With

claude-sonnet-4-20250514gpt-4o
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