 and some commercial model interfaces do not support stable tool calling functionality. The existing solution involves fine-tuning LLMs%2C which results in significant time and computational resource consumption. This paper proposes a method that enables LLMs to achieve stable tool calling capabilities using only prompt engineering and some ingenious code design. We conducted experiments on multiple LLMs that lack tool calling capabilities across various tool calling tasks%2C achieving a success rate of 100%25.?resize=650,400 "Achieving Tool Calling Functionality In LLMs Using Only Prompt Engineering Without Fine-Tuning ...")
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Spring AI Tutorial : 09 - Extend LLMs Capabilities using Tool Calling
Spring AI Tutorial : 09 - Extend LLMs Capabilities using Tool Calling
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 and some commercial model interfaces do not support stable tool calling functionality. The existing solution involves fine-tuning LLMs%2C which results in significant time and computational resource consumption. This paper proposes a method that enables LLMs to achieve stable tool calling capabilities using only prompt engineering and some ingenious code design. We conducted experiments on multiple LLMs that lack tool calling capabilities across various tool calling tasks%2C achieving a success rate of 100%25.?resize=91,91 "Achieving Tool Calling Functionality In LLMs Using Only Prompt Engineering Without Fine-Tuning ...")
![[Hands-on] Tool Calling In LLMs - By Avi Chawla](https://i0.wp.com/substackcdn.com/image/fetch/w_1200,h_600,c_fill,f_jpg,q_auto:good,fl_progressive:steep,g_auto/substack-post-media.s3.amazonaws.com/public/images/bb134d6c-2898-40fa-8563-e9db25c0b18c_2276x884.jpeg?resize=91,91 "[Hands-on] Tool Calling In LLMs - By Avi Chawla")
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