agent node can not use tools because error occurs
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Dify version
1.0.0 and 1.0.1
Cloud or Self Hosted
Self Hosted (Docker)
Steps to reproduce
when i try to create a simple agent node, the same error always occurs:
✔️ Expected Behavior
invoke tools successfully
❌ Actual Behavior
Failed to transform agent message: PluginInvokeError: {"args":{},"error_type":"ValidationError","message":"1 validation error for ReActParams\nmodel.entity\n Input should be a valid dictionary or instance of AIModelEntity [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.8/v/model_type"}
I found similar discussions that might be relevant to your issue:
-
Agent node in workflow run status fails. - This discussion is currently unsolved and might provide insights into similar issues with agent nodes [1].
-
Error reported when running an agent in a workflow. - Another unsolved discussion that could be related to the error you're encountering [2].
For the specific validation error you're facing with the FunctionCallingParams\model.entity, switching from the qwen2.5-72b-instruct model to the Deepseek model might resolve the issue. This change has been suggested to prevent validation errors while maintaining the same workflow configuration [3].
To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
I found similar discussions that might be relevant to your issue:
- Agent node in workflow run status fails. - This discussion is currently unsolved and might provide insights into similar issues with agent nodes [1].
- Error reported when running an agent in a workflow. - Another unsolved discussion that could be related to the error you're encountering [2].
For the specific validation error you're facing with the
FunctionCallingParams\model.entity, switching from theqwen2.5-72b-instructmodel to theDeepseekmodel might resolve the issue. This change has been suggested to prevent validation errors while maintaining the same workflow configuration [3].To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
@dosu deepseek v3 also have this problem, no matter i use any llm model, this error always occurs
The validation error you're encountering with FunctionCallingParams\model.entity suggests that the input should be a valid dictionary or an instance of AIModelEntity. This issue can occur if the model configuration is not compatible with the expected input type. To resolve this, ensure that the model is correctly configured as an AIModelEntity. You can follow these steps to configure it properly:
-
Define the Model Identifier: Set the
modelfield with a string that identifies the model, such asgpt-3.5-turbo. -
Specify the Model Type: Choose the appropriate
model_typefrom the available options likellm,text-embedding, etc. -
Configure Model Properties: Set the
model_propertiesobject with relevant properties based on the model type. -
Ensure Compatibility: Verify that the model you are using is compatible with the workflow configuration and does not trigger validation errors.
If the issue persists across different models, it might be worth checking if there are any specific configuration settings or updates required for the models you are using.
To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
I got the same error when creating an agent node in chatflow with model gemma-2, provider openai compatible.
got same error too, any updates for this issue?
Could you please provider your agent plugin's version? Maybe update the plugin's version could solve the issue
when i update dify to 1.1.3, this error no longer exists
when i update dify to 1.1.3, this error no longer exists
Could you please show me the plugin's version, you could update the plugin's version and try it again if it's possible.