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Model Misinterprets Input as Empty Array in Dify with Azure OpenAI GPT-5 #576
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Originally created by @Atopoz on GitHub (Aug 21, 2025).
Self Checks
Dify version
1.6.0
Plugin version
Azure OpenAI 0.0.27
Cloud or Self Hosted
Self Hosted (Docker)
Description
I am experiencing an issue with the Azure OpenAI GPT-5 model when using it within the Dify platform. The model incorrectly interprets valid input as an empty array, leading to unexpected responses.
Steps to Reproduce:
Expected Behavior:
The model should process the input correctly and return a relevant response.
Actual Behavior:
The model treats the input as including an empty array and returns a response about empty array.
✔️ Error log
No response
@dosubot[bot] commented on GitHub (Aug 21, 2025):
Hi @Atopoz! I'm Dosu and I’m helping the dify-official-plugins team.
This issue is likely caused by how Dify and the Azure OpenAI plugin map and serialize input for GPT-5 models. Recent updates to the plugin and model configuration changed how parameters and input arrays are handled, especially for models starting with "gpt-5"—for example, mapping
max_tokenstomax_completion_tokensand updating the way messages are constructed and sent to the Azure OpenAI endpoint [PR #1444], [PR #1454], [PR #1461].Dify expects the plugin to transform the model's response into its internal schema, specifically populating the
message.contentfield. If the input mapping or response parsing is incorrect, the frontend may show empty output or reference an empty array, even if the model received valid input [issue #1323], [issue #1303].Troubleshooting steps:
messagesarray should contain your user prompt, not be empty).sys.queryandsys.filesare populated and not defaulting to empty arrays.If the issue persists, it may be due to a regression or a subtle bug in the input mapping logic for GPT-5 models. Reviewing the plugin's recent changes and the mapping utilities in the provider code may help pinpoint where empty arrays are introduced [PR #1461].
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@crazywoola commented on GitHub (Aug 24, 2025):
If you don't want the LLM to process files, you can remove that from user's query.
You can not expect LLM to return things you want for sure.
@Atopoz commented on GitHub (Aug 24, 2025):
Thanks, I solved this problem by removing the
filesvariable from the memory box. However, other models didn't encounter this problem, so it might be a bug.