YAML Inputs to LLMs

Natural Language vs Deterministic Interfaces for LLMsKey Points

Natural language interfaces for LLMs are powerful but can be problematic for software engineering and automation

Benefits of natural language:

• Flexible input handling
• Accessible to non-technical users
• Works well for casual text manipulation tasks

Challenges with natural language:

• Lacks deterministic behavior needed for automation
• Difficult to express complex logic
• Results can vary with slight prompt changes
• Not ideal for command-line tools or batch processing

Proposed Solution: YAML-Based Interface

• YAML offers advantages as an LLM interface:
  • Structured key-value format
  • Human-readable like Python dictionaries
  • Can be linted and validated
  • Enables unit testing and fuzz testing
  • Used widely in build systems (e.g., Amazon CodeBuild)

Implementation Suggestions

• Create directories of YAML-formatted prompts
• Build prompt templates with defined sections
• Run validation and tests for deterministic behavior
• Consider using with local LLMs (Ollama, Rust Candle, etc.)
• Apply software engineering best practices

Conclusion

Moving from natural language to YAML-structured prompts could improve determinism and reliability when using LLMs for automation and software engineering tasks.

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