To debug a model that outputs invalid JSON for natural language to code conversion by enforcing strict schema validation, applying syntax correction, using structured prompting, and implementing automatic error handling.
Here is the code snippet you can refer to:
In the above code we are using the following key points:
- Strict Schema Validation: Ensures JSON correctness before execution.
- Structured Prompting: Instructs the model to maintain proper JSON formatting.
- Zero-Temperature Setting: Reduces randomness for better structured outputs.
- Error Handling & Auto-Correction: Detects and fixes invalid JSON issues.
- Controlled Token Limit (max_tokens): Prevents incomplete JSON generation.
Hence, fixing invalid JSON outputs in natural language-to-code conversion requires schema enforcement, structured model prompting, syntax validation, and error handling to ensure well-formed and executable JSON responses.