YAML Inputs to LLMs

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Pragmatic AI Labs

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Published on January 27, 2025 7:16:41 PM ● Video Link: https://www.youtube.com/watch?v=1m2G0MaBInA

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Natural Language vs Deterministic Interfaces for LLMs
Key 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 processingProposed 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 practicesConclusion


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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