Hi,
I really like the new feature that integrates LLM into the enrichment analysis.
However, I found that when running the following:
> interpret(enrichment$up$KEGG, task = "interpretation", model = "glm-4.7")
Interpreting cluster: Default
## Interpretation Result
### Cluster: Default
### 1. Overview
Warning message:
In value[[3L]](cond) :
Failed to parse JSON response from LLM. Returning raw text. Error: parse error: premature EOF
(right here) ------^
Here, enrichment$up$KEGG is an enrichResult object, and the previous version (glm-4) works fine:

So I guess the issue might be related to changes in the output format of the new glm version.
In addition, I noticed that we have to deploy the “fanyi” API to run the function:
> interpret(result$up$KEGG, task = "interpretation")
Interpreting cluster: Default
Error in value[[3L]](cond) :
Failed to call fanyi::chat_request. Error: API key for deepseek is missing.
Even though I don’t need translation, it’s a bit tedious to check the API documentation and manually call set_translate_option.
It might be better to add an option to disable fanyi when not needed.
Thanks again for the great work!
Best,
Peng
Hi,
I really like the new feature that integrates LLM into the enrichment analysis.
However, I found that when running the following:
Here, enrichment$up$KEGG is an enrichResult object, and the previous version (glm-4) works fine:

So I guess the issue might be related to changes in the output format of the new glm version.
In addition, I noticed that we have to deploy the “fanyi” API to run the function:
Even though I don’t need translation, it’s a bit tedious to check the API documentation and manually call set_translate_option.
It might be better to add an option to disable fanyi when not needed.
Thanks again for the great work!
Best,
Peng