FAQ
This document was translated from Chinese by AI and has not yet been reviewed.
Common Error Codes
4xx (Client Error Status Codes): Generally, these indicate issues like incorrect request syntax, authentication failure, or authorization failure, preventing the request from being completed.
5xx (Server Error Status Codes): Generally, these indicate server-side errors, such as server downtime or request processing timeouts.
400
Request body format error, etc.
Check the error content returned in the conversation or view the error message in the console and follow the prompts.
401
Authentication failed: model not supported or server account banned, etc.
Contact or check the status of the corresponding service provider's account.
403
Request operation unauthorized
Perform corresponding operations based on the error message returned in the conversation or the error message prompt in the console.
404
Requested resource not found
Check the request path, etc.
422
Request format is correct, but semantically incorrect
The server can parse such errors but cannot process them. Common in JSON semantic errors (e.g., null values; expecting a string but receiving a number or boolean, etc.).
429
Request rate limit reached
Request rate (TPM or RPM) limit reached, wait a moment before trying again.
500
Internal server error, unable to complete request
If it persists, contact the upstream service provider.
501
Server does not support the requested functionality, unable to complete request
502
As a gateway or proxy, the server received an invalid response from an upstream server while attempting to fulfill the request.
503
The server is currently unable to handle the client's request due to overload or system maintenance. The length of the delay may be included in the server's Retry-After header.
504
The server, acting as a gateway or proxy, did not receive a timely response from the upstream server.
How to View Console Errors
After clicking the Cherry Studio client window, press the shortcut key Ctrl + Shift + I (Mac: Command + Option + I).
In the popped-up console window, click
Network→ click to view the lastcompletionsmarked with a red×at ② (when encountering errors in conversation, translation, model connectivity checks, etc.) orgenerations(when encountering errors in drawing) → clickResponseto view the complete returned content (area ④ in the figure).
If you cannot determine the cause of the error, please send a screenshot of this interface to the Official Communication Group for assistance.

This inspection method can be used not only to obtain error messages during conversations but also during model testing, knowledge base addition, drawing, etc. In any case, you need to open the debug window first and then perform the request operation to get the request information.
Formulas not rendered / Formula rendering errors
If formulas are not rendered and instead display as formula code, check if the formulas have delimiters.
Delimiter usage
Inline formulas
Use a single dollar sign:
$formula$Or use
\(and\), e.g.:\(formula\)Block formulas
Use double dollar signs:
$$formula$$Or use
\[formula\]Example:
$$\sum_{i=1}^n x_i$$
Formula rendering errors/garbled text often occur when formulas contain Chinese content; try switching the formula engine to KateX.
Failed to create knowledge base / Failed to get embedding dimensions
Model status unavailable
Confirm whether the service provider supports the model or whether the model service status is normal for the service provider.
Used a non-embedding model
Model cannot recognize images / Unable to upload or select images
First, you need to confirm whether the model supports image recognition. Cherry Studio categorizes popular models; those with an eye icon after the model name support image recognition.
Image recognition models support image file uploads. If the model's functionality is not correctly matched, you can find the model in the corresponding service provider's model list, click the settings button after its name, and check the image option.
Specific model information can be found and reviewed with the corresponding service provider. Similar to embedding models, models that do not support vision do not need to have image functionality forcibly enabled, and checking the image option will have no effect.
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