Unverified50% confidenceFactExact time
The requirements that tool-call support places on inference engines include an interrupt-resume generation process, structured output constraints (such as forcing the output of valid JSON), and state management for multi-turn tool-call chains.
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50%
Confidence
Long-term
Relevance
9/24/2026
First Seen
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Related Claims
UnverifiedThe core idea of the Tool Use protocol is to completely decouple decision-making from execution: the model is only responsible for reasoning and planning and outputting JSON, while actual file reading/writing and command execution are handled by the local runtime.73% similarUnverifiedThe actual execution of a tool call requires a runtime environment to parse the JSON, locate the corresponding function and execute it, and finally feed the result back to the large model.70% similarUnverified自定义工具（Custom Tool）可以将重复流程封装起来实现一键复用，绕过重复推理70% similarUnverifiedDify's workflow engine supports orchestrating complex logic such as LLM calls, tool execution, conditional branching, and loop iteration via a visual DAG approach.68% similarUnverified建议在工具链中保留官方API作为备用通道，并为关键任务配置错误重试与降级策略68% similar
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