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When using the ReAct strategy, the agent can suddenly stop for a few common reasons. The most frequent cause is that the LLM's output doesn't match the exact JSON format the agent expects (for example, missing or malformed Other possible causes include hitting the maximum number of allowed iterations (default is 10), token or output truncation due to configuration limits, or using a model that doesn't fully support function calls or streaming output (which is required for some agent workflows) example. To troubleshoot:
Upgrading to the latest Dify version may also help, as recent releases include fixes for agent iteration and output handling example. If the issue persists, try enabling debug logging or testing with a different model to isolate whether the problem is with the model, prompt, or agent configuration. To reply, just mention @dosu. Share context across your team and agents. Try Dosu. |
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那如果tools的返回结果格式如下这样,算是符合要求吗? |
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可以给我一个完整的ReAct agent 对工具调用的request和response的完整json的格式的例子或者格式要求吗?因为我现在是自己写了一个工具来生成这个response。我需要针对这个要求进行修改一下 |
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回答 @simonjhy 关于 ReAct 工具调用格式的问题。 先区分两种策略,别混用:
一轮 ReAct 的典型格式(LLM 要生成的): 框架解析到 然后继续,直到: 关于你的工具返回格式:ReAct 模式下,工具返回最终是被当作 Observation 文本注入提示词的,所以返回是不是合法 JSON 不是关键,关键是能序列化成一段对模型友好、不太长的字符串。你贴的 1)别嵌套太深、别太长——ReAct 把整段塞进上下文,过长容易让模型在下一步"突然中断"或被截断。 "突然停止"最常见的根因就是:模型没按 (声明:我是 AI 工程师,这条回复在 AI 协助下完成、本人已审阅。) |
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1. Is this request related to a challenge you're experiencing? Tell me about your story.
I checked the docker api log and LLM log, I did not find any exception. what's the possibile reason of this?
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