I am thinking about how to help you Agent ReAct

[Gum97]

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Dify version

1.10.1

Cloud or Self Hosted

Self Hosted (Source)

Steps to reproduce

Steps to reproduce
create a workflow app
add agent node, with react strategy , Gemini 2.5 pro
add tavily search and extract tools
write system and user prompt
run this app
✔️ Expected Behavior
agent works fine, use tavily tools, return Final Answer.

✔️ Expected Behavior

agent works fine, use tavily tools, return Final Answer.

❌ Actual Behavior

After testing, React agent often experiences a lack of output after more than 3 iterations, resulting in the program returning "I am thinking about how to help you", or only having thought output without action_input, action_name, etc., which means there is no Final Answer output.

[dosubot]

This is a known issue with the ReAct agent in Dify, especially when using models like Gemini 2.5 Pro and tools such as Tavily. The agent often stalls after several iterations, outputting only "I am thinking about how to help you" or incomplete responses without a Final Answer. The root cause is usually that the LLM output is not in the exact JSON format the agent expects (i.e., {"action": "Final Answer", "action_input": "..."}), or the output parser fails to extract a valid action from the model's response. This can be due to model quirks, prompt formatting, or edge cases in the output parser logic. When this happens, the agent loop doesn't proceed and stalls without producing a final answer example.

Troubleshooting steps:

• Make your system prompt very explicit about the required output format, instructing the model to always output the action and action_input fields in JSON.
• Check your agent configuration, especially the Maximum Iterations and Output Variables settings.
• Review backend logs for JSON parsing errors or "Invalid input value" messages when the agent stalls example.
• Try switching to a different LLM (e.g., GPT-4 or deepseek-v3) or use Function Calling mode if you need stricter output formatting—some models are more reliable at producing valid JSON example.
• If you are using a workflow as a tool, be aware of known issues with variable passing between agent and workflow contexts, which can also cause stalling example.

Recent versions of Dify have included fixes and refactors to agent iteration and output handling, so upgrading may help if feasible example.

If you need deeper debugging, capture and share the relevant logs or the exact LLM output when the agent stalls—look for malformed or incomplete JSON, or missing action fields.

To reply, just mention @dosu.

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[crazywoola]

So what's you plan?

[paul0728]

same problem here.
@crazywoola
Found and fixed the cause of the React strategy inference interruption. This issue was likely caused by a failure during the middle of inference, which resulted in the expected output format not being detected in the final check.

[crazywoola]

same problem here. @crazywoola Found and fixed the cause of the React strategy inference interruption. This issue was likely caused by a failure during the middle of inference, which resulted in the expected output format not being detected in the final check.

Do you mean this PR langgenius/dify-official-plugins#2154 ?

[paul0728]

same problem here. @crazywoola Found and fixed the cause of the React strategy inference interruption. This issue was likely caused by a failure during the middle of inference, which resulted in the expected output format not being detected in the final check.

Do you mean this PR langgenius/dify-official-plugins#2154 ?

Not quite. That PR fixes the issue where the agent node tool response was being duplicated (a problem shared by both the React and function-calling strategies). This issue, however, is specific to the React strategy: the reasoning process unexpectedly stops halfway (with no visible errors in the logs), and the final response is simply “I am thinking about how to help you.” I’ve already confirmed that this is not caused by exceeding the token limit.

[Pandaaaa906]

it's cause by LLM doesn't obey the prompt exactly, respond a wrong format to the plugin that can't handle

i made a quickfix for this situation in another plugin, it will retry it until exceed max_iteration_steps
https://github.com/Pandaaaa906/dify-plugin-agent-mcp_sse/tree/fix-retry-llm-false-format
cant put an end to the problem, but better than nothing, right?

besides, modifying the LLM's parameters might help(TopP TopK ...)