Structured Outputs with LLMs: JSON Mode, Function Calling, and When to Use Each

The article discusses techniques for obtaining structured outputs from Large Language Models (LLMs), including JSON mode and function calling. It aims to provide guidance on choosing the right tool for reliable and readable responses. The article explores the use of JSON mode for structured data and function calling for more complex tasks. The practical implication for engineers building AI systems is to understand the strengths and limitations of each approach to select the most suitable method for their specific use case.

⚡ Key Takeaways

• JSON mode is used for structured data output
• Function calling is used for more complex tasks
• The choice between JSON mode and function calling depends on the specific use case

Understanding the strengths and limitations of JSON mode and function calling is crucial for engineers building AI systems that rely on LLMs, as it enables them to select the most suitable method for their specific use case. This knowledge can help improve the reliability and readability of LLM outputs.

✅ Practical Steps

1. Apply the concepts from this article to your own system design

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