Unverified50% confidenceFactExact time
Implementing task chaining typically relies on two types of technical support: large language models with tool-calling capabilities (such as GPT or Claude series supporting Function Calling) and multimodal models.
1
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50%
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Long-term
Relevance
9/14/2026
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Unverified现代大语言模型如GPT-4、Claude通过特定系统提示和结构化输出，能够自主决定调用外部工具，本质上是模型生成结构化JSON指令由运行时框架解析执行79% similarVerifiedGPT-4 and Claude are large language models that can understand context, generate structured outputs, and execute multi-step reasoning76% similarUnverifiedLarge language models have undergone a qualitative leap in instruction-following and long-range reasoning, evolving from the GPT-3 era—which required carefully designed few-shot examples—to today, where simply providing goals and constraints is sufficient for the model to autonomously fill in execution details.76% similarUnverifiedClaude uses the tool_use format defined by Anthropic, the GPT series uses OpenAI's function_calling protocol, and there is no unified industry standard for tool calling in large language models.76% similarVerifiedGPT-5.5 supports hierarchical model pairing, allowing users to flexibly select different model tiers based on task complexity.74% similar
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