Unverified60% confidenceFactExact time
Three technical approaches exist in the structured output domain: server-side native support represented by OpenAI Function Calling/Structured Outputs, prompt programming solutions represented by Microsoft Guidance and LMQL, and pure sampling-layer constraint solutions represented by Outlines.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
7/22/2026
First Seen
Valid until: 10/20/2026
Sources
Related Claims
VerifiedOpenAI's Function Calling and Anthropic's Tool Use convert the unstructured output of LLMs into structured data that can be reliably parsed by programs.79% similarUnverifiedOpenAI's function calling/tool use mechanism is a hard constraint; the model inference engine directly constrains the valid set of output tokens during the decoding phase, thereby guaranteeing format compliance at the protocol level.75% similarUnverifiedMicrosoft's Semantic Kernel and OpenAI's Function Calling mechanism contain an Orchestration Layer design pattern similar to the Coze Engine.74% similarUnverifiedDify supports integration with multiple LLMs, including OpenAI, Anthropic, and domestic Chinese large models, and has built-in node types such as variable management, conditional branching, HTTP requests, and code execution.74% similar
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